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European-Russian Centre for cooperation in the Arctic and Sub-Arctic environmental and climate research

Final Report Summary - EURUCAS (European-Russian Centre for cooperation in the Arctic and Sub-Arctic environmental and climate research)

Executive Summary:
EuRuCAS (European-Russian Centre for cooperation in the Arctic and Sub-Arctic environmental and climate research) Project aims on extension, consolidation and strengthening scientific cooperation between researchers from EU Member States and Associated Countries and Russia using Nansen International Environmental and Remote Sensing Centre (NIERSC), established in St. Petersburg by institutions from Norway, Germany and Russia, as a joint research facility. The selection of NIERSC for this goal was justified by solid expertise of its personnel in the Arctic and Sub-Arctic climate and environmental research, critical importance of this research for the European Union and Russia and a wide network established by NIERSC with Russian and foreign organizations. The project partners from EU Member States and Associated Countries are selected basing on their scientific expertise in these fields of research as well as their motivation to work with Russian scientists. The strengthening cooperation in the proposed research area between EU and Russia in the framework of EuRuCAS has been implemented through research visits of European scientists from project partner institutions for joint work at NIERSC with Russian scientists, new future joint projects initiated at the international workshops at NIERSC, summer school with the goal of involving the young generation of researches, and opening NIERSC institutional arrangements for new additional partners from EU Member States and Associated Countries. Joint research work at NIERSC was organised within on-going NIERSC projects and included such tasks as the Arctic and Sub-Arctic climate change, land and sea ice and snow, remote sensing of marine environment and polar atmosphere, marine ecosystems, land hydrology and permafrost dynamics and socioeconomic impact of climate change.

Project Context and Objectives:
Project concept:
EuRuCAS used the Nansen International Environmental and Remote Sensing Centre (NIERSC) in St. Petersburg, Russia, as the joint research facility to extend and consolidate scientific cooperation between researchers from EU Member States and Associated Countries with those from Russia.
The research area of EuRuCAS included study of climate and environmental changes in the Arctic and Sub-Arctic in the 21st century and their socio-economic impact. This research area is becoming increasingly important for Europe and Russia due to impact of climate change on the Arctic environment combined with increased demand for energy and other natural resources. Russia has huge natural resources stored in the shelf zone of the Arctic seas that will be exploited in the future. This will stimulate the growth in the economic activities in the high northern latitudes, especially in the oil, gas and mineral resources exploration and exploitation, transportation, fisheries and tourism. Climate change will further impact the Arctic environment with consequences for human beings and socio-economic activities; particularly they will simplify the economic activities in the Arctic and Sub-Arctic. Several examples can be mentioned here, such as: 1) reduction of the Arctic sea ice cover with impact on marine transportation, oil and gas extraction, ecosystems; 2) thawing of permafrost with impact on infrastructure; 3) increase of air temperature with impact on ecosystems, agriculture, fisheries. In turn, the growing human activity in high northern latitudes will enhance the impact of climate change, both positive and negative, on the environment, which can be manifested in many different ways. Therefore, extensive and multidisciplinary studies are needed to build up the comprehensive knowledge about the climate change and their impact on environment and society, particularly in high northern latitudes. This has a high priority for both Europe and Russia. From this point of view EU Member States and Associated Countries as well as Russia, where many institutions carry out research activity in this area, have high research potential to answer the emerging challenges in the Arctic and Sub-Arctic. However, this research activity, performed in European and Russian institutions, was not sufficiently coordinated.
EuRuCAS contributed to improving this situation by means of building strategic R&D partnerships between institutions in Europe and Russia for performing joint multidisciplinary research in the area of climate and environmental change in the Arctic and Sub-Arctic, including socio-economic impact. This has been done through the Nansen Centre, established in St. Petersburg in 1992 by Norwegian, Russian and German founders. It is envisaged that NIERSC might become the European-Russian Centre for cooperation in the Arctic and Sub-Arctic environmental and climate research and serve as a focal point for its further development. The further extending and enhancing cooperation will be attained by implementation of joint projects beyond EuRuCAS Project, both on-going and oncoming.
The activities within EuRuCAS Project included research visits of European scientists from project partner institutions to NIERSC for joint work with Russian scientists, international workshops aimed at the preparation of new future joint projects, and a summer school with the goal to sustain future long-term cooperation by means of involving the young generation of researches. In the framework of EuRuCAS Project NIERSC research facilities have been enhanced and its institutional arrangements have been opened for new additional partners from EU Member States and Associated Countries.

Overall objective:
To use and extend the Nansen International Environmental and Remote Sensing Centre (NIERSC), established in St. Petersburg, Russia, as a catalyst for structuring and strengthening European-Russian cooperation in the area of environmental and climate research in the Arctic and Sub-Arctic including socio-economic impact of global warming.

Specific objectives:
o To open NIERSC activities to additional researchers from EuRuCAS consortium (Austria, Finland, France, Germany, Norway, Sweden and UK) and new researchers from other EU Member States and Associated Countries.
o To enhance the research capacity of NIERSC with the aim of implementation of activities associated with future joint European-Russian projects and opening NIERSC institutional arrangements for additional partners from EU Member States and Associated Countries.
o To increase and extend scientific cooperation between researchers from the Member States/Associated Countries and Russia in the area of environmental and climate research through involvement of additional researches in the on-going projects at NIERSC and the preparation of new joint projects.
o To prepare new joint research projects between institutions in Russia and EU Member States/Associated Countries in the area of environmental and climate research in the Arctic and Sub-Arctic including socio-economic issues.
o To organize at NIERSC a series of workshops and seminars with the aim of preparation of new joint proposals in the EuRuCAS research area.
o To organize a Summer School on environmental and climate research topics with the aim to involve young generation of researchers into EU-Russia scientific cooperation.
o To prepare NIERSC institutional arrangements for involving new partners/research organizations from Member States/Associated Countries

Project context:
EuRuCAS was based on the selected scientific topics for cooperation in the area of environmental and climate research in the Arctic and Sub-Arctic including socio-economic impact. This selection was based on the expertise of the coordinating institution (NIERSC) and the relevance for Russia and Europe. Since Russian scientists have long tradition and high level of expertise in many Arctic research topics, it is very beneficial for EU and European scientists to build up strong cooperation with Russian institutions in environment and climate research at high northern latitudes. The project partners from EU Member States and Associated Countries were selected basing on their scientific expertise in these fields of research as well as their motivation to work with Russian scientists. EuRuCAS focused on the development of the cooperation between scientists from EU Member States and Associated Countries with scientists from Russian institutions. Thus, EuRuCAS opened up the research infrastructure at NIERSC for new researchers from European countries. The cooperation was first based on the existing projects at NIERSC, and subsequently on new projects established in the framework of EuRuCAS.
EuRuCAS was organized in seven Work Packages. Dr. Jürgen Sanders from the European Commission was the Project officer.
The overall management of the project has being implemented within WP1 by Project Coordinator Dr. Leonid Bobylev (NIERSC) and Deputy Coordinator Prof. Stein Sandven (NERSC).
WP2 was dealt with the strengthening and coordination of cooperation in selected research tasks. These tasks included: climate change in the Arctic and Sub-Arctic, ice and snow in the Arctic and Sub-Arctic, Arctic polar lows, marine and lake ecosystems in the Arctic and Sub-Arctic, permafrost dynamics and hydrological modelling and socio-economic impact of climate change in the Arctic and Sub-Arctic. Researchers from project partner institutions were staying in St. Petersburg and working at NIERS during several months each year. Their research activity was organized in the framework of on-going projects at NIERSC. Among them were: 1) “Monitoring and Assessing Regional Climate Change in High Latitudes and the Arctic (MONARCH-A)”, EU-FP7, 2010-2013; 2) “Monitoring Arctic Land and Sea Ice using Russian and European Satellites (MIRES)”, EU-FP7, 2011-2014; 3) “Sea Ice Downstream services for Arctic and Antarctic Users and Stakeholders” (SIDARUS), EU-FP7, 2011-2014; 4) Ships and Waves Reaching Polar Regions (SWARP), EU-FP7, 2014-2017; 5) MyOcean-2, EU-FP7, 2012-2015; 6) Knowledge Based Climate Mitigation Systems for a Low Carbon Economy (COMPLEX), EU-FP7, 2012-2016, and other.
Enhancement of NIERSC research infrastructure has been done through the implementation of WP3.
WP4 was aimed at the further enhancement of the coordinated scientific cooperation between researches from EU Member States, Associated Countries and Russia in the area of environmental and climate research in the Arctic and Sub-Arctic including socio-economic issues through preparation of new joint projects. To achieve this goal workshops devoted to preparation of new joint European-Russian projects have been held at NIERSC.
WP5 was devoted to organization of a summer school in St. Petersburg during the 3rd year of the project with participants from European countries and Russia. Future research recruitment is essential to make cooperation sustainable and, hence, involvement of postdocs and PhD-students in such cooperation is important. The summer school, together with workshops and generation of new projects was important mechanism to recruit young scientists to work in the considered research topics.
WP6 was dealt with preparing NIERSC institutional arrangements for their opening for new NIERSC partners from EU Member States/Associated Countries. Involving new partners in a joint research institute, like NIERSC, will secure long-term European-Russian cooperation.
Finally, WP7 was aimed at dissemination and exploitation of project results.

Project Results:
Enhancing research capacity of Nansen Centre:
When starting EuRuCAS Project, NIERSC had moderate research capacities, which were generally sufficient for implementation of ongoing research projects. However, for achieving ambitious goals of EuRuCAS, including successful activities of joint working groups, established at NIERSC from project partner researchers, implementation of new future joint projects, and opening NIERSC institutional arrangements for additional partners from EU Member States and Associated Countries, these capacities required significant enhancement.
This enhancement has been performed through:
o purchase of required hardware, software and other equipment
o organization of six new working places/environments for visiting researchers from the project participating institutions
o upgrade of current computer server and purchase and installation of two new powerful computer servers and four data storage systems
o installation of optical cable for high-speed INTERNET connection
o equipping conference hall
The undertaken measures provided for the perfect conditions for the efficient work of visiting scientists from EuRuCAS Consortium’s institutions at NIERSC and significantly enhanced NIERSC research capacity which is now sufficient for implementation of new future joint EU-Russia projects in the area of Arctic and Sub-Arctic research and opening NIERSC institutional arrangements for additional partners from EU Member States and Associated Countries.

Strengthening and coordination of EU-Russia cooperation in the Arctic and Sub-Arctic research:
Strengthening and coordination of cooperation between EU and Russia in the Arctic and Sub-Arctic research in the framework of EuRuCAS Project has been carried out through:
o opening NIERSC activities and institutional arrangements to researchers from EuRuCAS Consortium and other organisations from EU Member States and Associated Countries
o enhancement of NIERSC research facilities
o elaboration of joint research programme
o organisation and implementation of joint work of researchers from EuRuCAS Consortium institutions and Nansen Centre personnel at NIERSC within the NIERSC on-going projects
o organisation and implementation of visits of NIERSC researchers to partner institutions
o preparation and submission of new joint research proposals for securing continuation of cooperation far beyond EuRuCAS Project

Opening NIERSC activities and institutional arrangements to researchers from EuRuCAS Consortium and other EU organisations as well as enhancement of NIERSC research facilities formed the necessary environment for successful coordinated cooperation in the Arctic and Sub-Arctic research between Russian and EU institutions using NIERSC as a catalyst for strengthening such cooperation.
Research cooperation in the framework of EuRuCAS was organized around seven tasks:
1. Climate change in the Arctic and Sub-Arctic
2. Ice in the Arctic and Sub-Arctic
3. Polar lows in the Arctic
4. Arctic and Sub-Arctic marine and lake ecosystems
5. Large lakes in Scandinavia and European Russia within sub-Arctic zone
6. Permafrost dynamics and hydrological modelling
7. Socioeconomic impact of climate change in the Arctic and Sub-Arctic

Within these tasks, joint research topics and working groups were defined and established, and the joint research programme (Integrated Research Plan) was elaborated aimed on the consolidation of joint coordinated research in the area of Arctic and Sub-Arctic climate and environment changes and their socioeconomic consequences. Major scientific results of the implementation of this joint research programme are described below.
The joint research activity of scientists from EuRuCAS Consortium members was organised at NIERSC in St. Petersburg according to developed programme and within on-going NIERSC projects. Totally, EU scientists have worked for 3 356 days or about 112 months at NIERSC. The same time, NIERSC personnel also visited other partner institutions. NIERSC researchers have worked for totally 471 days or about 16 months at EU institutions, mostly at the Nansen Centre in Bergen, Norway, Finnish Meteorological Institute in Helsinki, Finland, Friedrich-Schiller University in Jena and Max-Plank Institute for Meteorology in Hamburg, Germany. This two-way exchange of researches significantly contributed to the achievement of the project objectives.
To ensure further cooperation between EU Member States, Associated Countries and Russia in the area of environmental and climate research in the Arctic and Sub-Arctic including socio-economic issues far beyond the end of EuRuCAS Project, a number of joint research proposals have been prepared and submitted to various funding agencies including EU FP7 and Horizon 2020 Programmes. The ideas and outlines of such proposals have been elaborated during the following six workshops held at NIERSC in St. Petersburg and in Moscow: First Workshop, 11-13 September 2012; Second Workshop, 5-6 November 2013; Third Workshop, 27-28 May 2015; Fourth Workshop on the impact of future global processes, including climatic, economic and legal developments, to the Russian and wider Arctic region, 9 April 2014; Fifth Workshop on climate policy modelling, 24-26 June 2015; and Sixth Workshop on modelling Green Growth options for Russia with the special attention to the Arctic and Sub-Arctic regions, 23 October 2015.
Totally, the project partners have prepared and submitted 16 joint research proposals, four of which were funded. Among the funded projects are one EU FP7 Project “Ships and Waves Reaching Polar Regions (SWARP)”, two Russian-Norwegian projects: “Climate variability and change in the Arctic (CLIMARC)” and “Development of sea ice monitoring and forecasting system to support safe operations and navigation in Arctic seas (SONARC)”, and one project funded by Russian Ministry of Education and Science (MON-SWARP) and supporting NIERSC activity in the framework of EU FP7 SWARP Project.
NIERSC is also invited and now involved into preparation of two new joint research proposals under Call 2016-2017 of EU Horizon 2020 Programme: 1) BG-9-2016 “Integrated Arctic Observing System” and BG-10-2016 "Impact of Arctic changes on the weather and climate of the Northern Hemisphere" with participation of several institutions from EuRuCAS Consortium and other EU and Russian institutions. Participation of NIERSC in these proposals as well as other optional proposals under EU Horizon 2020 Programme is ensured by establishing co-financing mechanism by the Russian Ministry of Education and Science to support involvement of Russian teams in H2020.
The major achievement of this activity on the strengthening and coordination of EU-Russia cooperation in the Arctic and Sub-Arctic research is establishing close ties between NIERSC and EuRuCAS project institutions with the mutual strong intent for continuation of future fruitful cooperation.

Facilitating involvement of younger generation of researchers into EU-Russia scientific cooperation and networking:
The long-term prospects of sustainability of European-Russian scientific cooperation, being fostered in the framework of EuRuCAS project, crucially depend on how actively the younger generation of researchers participates in knowledge transfer and preparation/implementation of joint research projects. To promote effective scientific communication between world-wide acknowledged scholars and leading experts from project partner institutions, on the one hand, and promising young scientists from various research domains (both from project partner institutions and beyond), on the other hand, an International Summer School has been organized and held by NIERSC on 29 June-5 July 2014 in Repino, St. Petersburg, Russian Federation.
The workshop theme was “Land Hydrology and Cryosphere of the Arctic and Northern Eurasia in the changing climate”. It gathered 52 participants including 27 students and young scientists and 25 lectures. The scientific programme encompassed 21 expert lectures and 26 presentations made by the young scientists. The poster session collected 17 student posters. Four thematic student groups were set up at the school: 1) Impact of climate change on the primary production dynamics in the Arctic Ocean; 2) Contradictory response of Arctic river hydrology to global climate change: process mechanisms and spatial patterns; 3) Ecology of Eurasian boreal and Arctic lakes: impact of climate change on seasonal hydrological and ecological cycle; and 4) Estimating uncertainties in the future CH4 fluxes in the permafrost region. These groups prepared summarizing presentations and the final summaries. The final scientific report, based on these summaries, is download to the project website (
Both the Summer School and the broad involvement of young scientists into joint research activity at NIERSC as well as into preparation of new joint research proposals under EuRuCAS Project made considerable contribution to facilitating involvement of younger generation of researchers into EU-Russia scientific cooperation and networking in the Arctic and Sub-Arctic climate and environmental research.

Opening institutional arrangements of Nansen Centre to new partners:
For maintaining the long-term research cooperation between European institutions and NIERSC far exceeding the project duration Nansen Centre’s institutional arrangements were opened to new partners from EU Member States and Associated Countries. The examination of Russian legislation on the Non-Governmental Organisations showed that the Associated Partnership was the most proper mechanism for joining of new partners to NIERSC. It is assumed that the Associated Partner and NIERSC develop close cooperation in research submitting joint proposals, implementing joint projects and supervising joint PhD-students. The Associated Partner has rights to participate in the General Meetings of Founders of NIERSC with the consultative vote. For the implementation of this decision the special Memorandum on the Associated Partnership has been elaborated.
As a result of this activity, six institutions signed Memorandum on Associated Partnership with NIERSC during the EuRuCAS Project: 1) Nansen Scientific Society, Bergen, Norway; 2) University of Helsinki, Finland; 3) Laboratory of Marine Security of DLR, Germany; 4) Finnish Meteorological Institute, Helsinki, Finland; 5) Stockholm University, Sweden; and 6) Global Climate Forum, Berlin, Germany.
The Nansen Centre authority is going to continue the involvement of new partners in its activity using the instrument of the Associated Partnership.

Main S&T results:

Climate change in the Arctic and Sub-Arctic:

Summary. The EuRuCAS research on the Arctic climate change has addressed two high-priority topics that need to be better understood. They are (a) Arctic sea ice decline, and (b) Arctic amplification of climate warming and its effect on mid-latitude weather and climate. A total of seven peer-reviewed papers are expected: one of them is published, three are submitted, and three are under preparation (see list at the end of this section). During the project, new collaborations have been generated both internationally and within Russia.

Participants. Leader: Timo Vihma (Finnish Meteorological Institute (FMI)); Co-Leaders: Ola M. Johannessen (Nansen Centre (NERSC), Bergen) and Leonid Bobylev (Nansen Centre (NIERSC), St. Petersburg); Contributors: Svyatoslav Tyuryakov (FMI), Svetlana Kuzmina, Natalia Gnatyuk, Elena Shalina (all-NIERSC), Valentin Meleshko (Voeikov Main Geophysical Observatory).

Introduction. The recent rapid decline of the Arctic sea ice cover belongs to the most dramatic signals of the climate change. The warming in the Arctic has been two to three times as fast as the global average. Several mechanisms contribute to this Arctic amplification of climate warming, but the relative importance of each of them is poorly known, as is also the regional and seasonal quantification of the Arctic amplification.
Another poorly known issue is the effects of Arctic sea ice decline on mid-latitude weather and climate. Simultaneously with the strongly warming Arctic, cooling trends in 2-m air temperature have prevailed over the large parts of the Northern Eurasia in winters since late 1980s, and during the latest ten years several mid-latitude regions have experienced several cold, snow-rich winters. Whether these events have been largely affected by the changes in the Arctic is under an intense scientific debate. There is also a need for future projections of atmospheric response to diminishing sea ice cover in the Arctic.

Arctic sea ice decline in the warming climate. The EuRuCAS research has addressed changes in sea ice cover in the Eurasian Arctic seas due to global warming on the basis of historical and satellite observations and climate model simulations (Bobylev et al, in preparation). The reduction and thinning of the Arctic sea ice during recent decades is one of the most important indicators of on-going global warming. The most significant decline is observed for the summer sea ice, which accelerated in the beginning of this century. Thus, in September 2012 sea ice extent (SIE) in the Arctic Ocean reached the new record minimum dropping down to 3.41 million km2. This extent was only half of the 1979-2000 average value. The reduction of sea ice, observed for the whole Arctic Ocean, occurs also in all its sectors. Thus, for the Eurasian seas 2012 was the year of the absolute September minima when sea ice extent for the Barents, Kara, Laptev, East-Siberian and Chukchi seas accounted for only 2%, 5.4%, 5.7%, 0.8% and 1.7% of its average for the period of satellite observations, respectively.
For the regional analysis of sea ice changes in the Arctic in the 20th and 21st centuries the unique observational dataset and ensemble of CMIP5 global climate models were used. The applied new dataset is the compilation of historical SIE dataset created by Zakharov (Zakharov, 2003) and SIE time series derived from satellite passive microwave measurements using NORSEX algorithm (Svendsen et al., 1983). This dataset provides monthly mean sea ice extent values for the period 1924-2014 for the Barents, Kara, Laptev, East-Siberian and Chukchi seas. It was used for estimation of SIE variability and trends in these seas for the said period.
The assessment of future changes in the ice cover in Eurasian Arctic seas in the 21st century, which has the crucial importance for the planning and developing industrial activity in the Arctic, was based on the CMIP5 climate model simulations. At the first step, an assessment was performed how well the current climate models reproduce observed regional changes of sea ice extent in the five Eurasian Arctic seas in the second half of the 20th century, especially in summer. It was shown that CMIP5 multi-model mean September SIE trend is more consistent with satellite observations than CMIP3 trend, but still underestimates the observed trend and overestimates SIE values over the past decades, i.e. sea ice decreases faster than projected by models. And, as in the case of CMIP3, the inter-model spread is considerable. Therefore, for getting more reliable projections of SIE in the Eurasian Arctic seas in the 21st century, at the second step, the selection of models from CMIP5 ensemble which best match SIE observations was performed. Selected models show trends for September SIE in the 21st century larger by 21% than the CMIP5 ensemble mean.
Results of simulations by selected models were compared with the extrapolation of the observed SIE. Analysis of model projections and extrapolation of observed data showed that the sea ice would be decreasing in all Eurasian Arctic seas with more rapid decline in Chukchi Sea, which to the middle of the 21st century might become ice-free in summer. Slower decrease is expected for Laptev and East-Siberian seas, where the sea ice extent will be about 0.2×106 km2 for Laptev Sea and 0.4×106 km2 for East-Siberian Sea up to the middle of the 21st century.
Based on the CMIP5 selected model projections of SIE in the Eurasia Arctic seas in the 21st century, the length of the navigation season on the Northern Sea Route (NSR) was estimated and the perspectives of NSR development in the 21st century were assessed for the moderate anthropogenic scenario RCP 4.5. Thus, it has been shown that the length of the navigation season at the NSR might increase to the end of this century by about a factor of two.

Arctic amplification and its links with mid-latitudes. In the EuRuCAS Task on the Arctic climate change, the most extensively studied topic was the Arctic Amplification of climate warming and its effects on mid-latitude weather and climate. In spite of intense past and present studies on these issues, there is still a considerable uncertainty on the mechanisms responsible for the Arctic Amplification and links between this amplification and weather and climate in mid-latitudes.
One of the studies, made in collaboration between NERSC and NIERSC, has been focused on the surface air temperature (SAT) variability and trends in the Arctic and on a new assessment of the Arctic Amplification (Johannessen et al., submitted). In this study, for a better observational assessment and understanding of Arctic Amplification, a thorough detailed analysis of surface air temperature variability and trends in the Arctic was made in the comparison with mid-latitudes and the entire Northern Hemisphere. The analysis was based on the advanced SAT dataset, NansenSAT (Kuzmina et al., 2008), and new Arctic climate regionalisation, created by means of a hierarchical cluster analysis, identifying six major natural regions in the Arctic that reflect peculiarities of SAT variability. It was shown, using a newly established Arctic Amplification Index, that the temperature amplification in the Arctic is characteristic feature not only for the on-going warming but also for the early 20th century warming (ETCW) and subsequent cooling. Moreover, the amplification appears to be substantially less during the on-going warming than in the ETCW, simply because the index values reflect the more pervasive nature of the present warming. Statistical comparison with climate indices for the warming and cooling periods, showed that the Atlantic Multidecadal Oscillation (AMO) is most significantly and consistently associated with the amplified warming-cooling in the Arctic on these time scales.
The second study on the Arctic Amplification, based on collaboration between FMI and NIERSC, addressed the role of the atmospheric boundary layer (ABL) in this phenomenon (Tyuryakov et al., in preparation). One of the many factors contributing to the Arctic Amplification is the shallow, stably-stratified ABL in the Arctic. Due to its shallowness, the Arctic ABL has a small heat capacity. Hence, a certain heat input causes a large increase in near-surface air temperature. The relationship between the ABL depth and air temperature trend and variability during the latest 35 years in the Arctic and mid-latitudes (north of 50oN) was studied applying the ERA-Interim reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) and CFSR reanalysis of the National Centre for Atmospheric Research. The results indicated that, averaged over the whole study area, the annual mean air temperature trend was largest in regions where the ABL height was smallest (correlation coefficient was −0.72). The relationship included, however, a lot of regional and seasonal variability. Thus, over the open ocean, the air temperature trends and variability are reduced by the large heat capacity of the ocean, and the ABL heat capacity plays a secondary role. In winter over sea areas with a large sea ice loss, such as the Kara Sea, the temperature increase has been strongest, although the ABL was not the shallowest. This is because the sea ice loss causes both an air temperature increase and deepening of the ABL.
The third EuRuCAS study on the Arctic Amplification addressed its potential impacts on the Polar Jet Stream and extreme weather events in mid-latitudes (Meleshko et al., submitted). Three years ago a hypothesis has been proposed (Francis and Vavrus, 2012) that the Arctic Amplification results in reduced zonal winds in mid-latitudes and further enhances the oscillation of planetary waves, favouring extreme weather in mid-latitudes. To test this hypothesis, the response of the atmosphere to the Arctic Amplification has been studied for a projected sea ice-free period during summer using an atmospheric model from a CMIP5 ensemble with prescribed surface boundary conditions. It was shown that when climate warmed, enhancement of northward heat transport provided the major contribution to decrease of the northward temperature gradient in the polar troposphere in cold seasons. The Arctic Amplification was not large enough to invoke increased oscillation of the planetary waves causing extreme weather in mid-latitudes as it was hypothesized earlier. However, the Arctic Amplification is important mechanism for transporting the heat out to the continents in the lower troposphere. Examined also was sub-seasonal variability of air temperature and geopotential heights during an ice-free period and it was found that their variability will decrease, which could cause more frequent occurrence of blocking in high- and mid-latitudes in the future including strengthening the polar vortex in winter.
The fourth EuRuCAS study related to the Arctic Amplification addressed the role of Arctic sea ice reduction in Eurasian wintertime cooling (Outten and Esau, 2015). Despite a general warming of the Northern Hemisphere in recent decades, a pattern of extremely cold winters has emerged as a robust feature in observations over the last few years over the northern continental Europe, Asia and North America.
In this study, a region of cooling over mid-latitude Eurasia is identified in the wintertime surface air temperatures of the ERA-Interim and NCEP/NCAR reanalyses. This Eurasian wintertime cooling is related to the decrease of sea ice concentrations in the Arctic. Singular Value Decomposition (SVD) is used to identify the temporal and spatial pattern of co-variability between the Arctic sea ice concentrations and mid-latitude Eurasian wintertime temperatures. For ERA-Interim, the primary mode explains approximately 59% of the co-variability between these two fields with a strong coupling correlation of R=0.68 (p ≤ 0.05). The study was extended by examining 20 CMIP5 models for the same pattern of co-variability. While wintertime cooling over Eurasia is found in only a few of the models, the majority do show the same pattern of co-variability between decreasing Arctic sea ice and wintertime Eurasian surface temperatures. This suggests that the Eurasian cooling may be a secondary response to the warming climate of the Arctic.
The fifth study related to Arctic Amplification addressed the atmospheric response to the autumn sea-ice free Arctic and its detectability (Suo et al., 2015). An Atmospheric General Circulation Model was applied with a large ensemble (300 members) to explore the responses of the autumn-winter atmosphere to the projected future sea-ice free Arctic in autumn. In addition, the detectability of the responses against the backdrop of the internal variability was studied. Three experiments were performed: the control experiment (CONT) forced by the model simulated present Arctic sea ice concentration and sea surface temperature (SST); the second one forced by the projected autumn Arctic sea ice-free and present SSTs (SENSICE); and the third experiment forced by the projected autumn Arctic sea ice-free and projected SSTs (SENS). The results showed that the disappearance of autumn Arctic sea ice could cause significant synchronous near-surface warming and precipitation increase over the region where the sea ice was removed. The autumn heat flux, surface air temperature and precipitation responses averaged over the sea ice reduction region increased 46%, 43% and 50% respectively in the SENS compared with SENSICE, which was consistent with the prescribed boundary setting: the surface temperature averaged over the sea ice reduction region was 48% higher in the SENS than in the SENSICE. The significant negative Arctic Oscillation response appeared in the troposphere during autumn and early winter but did not persist into January-February (JF) in these simulations. Instead, 500 hPa geopotential height (GH) response presented a wave train like pattern in JF, which was related to the slow downstream propagation of the planetary wave perturbations caused by the autumn Arctic sea ice-free from autumn to winter. The SAT increased over the northern Eurasia in JF in accordance with the atmosphere circulation changes. The comparison of the atmosphere responses with the atmosphere internal variability (AIV) showed that the responses of SAT and precipitation in the Arctic far exceeded the AIV in autumn and the response of the 500 hPa GH was comparable to the AIV in autumn, but none of the JF responses exceeded the AIV.
The sixth EuRuCAS study related to Arctic Amplification and its effects on mid-latitudes was made in collaboration between NIERSC and FMI (Gnatiuk et al., in preparation). The hemispheric-scale relationships between anomalies in the Earth surface temperature and 2-m air temperature were studied in order to characterize the atmospheric response to changes in surface forcing. The hemispherical approach allowed to quantitatively compare the impacts of Arctic forcing (mostly due to sea ice decline) and impacts of forcing originating from changes in surface temperature at lower latitudes. The temperature data were based on the ERA-Interim reanalysis, and the study has been based on linear regression analysis and neural networks clustering (Self-Organizing Maps). The temperature linkages have been analysed with focus on seasonal, lagged inter-seasonal, and lagged monthly relationships between Earth surface temperature and 2-m air temperature in Eastern Europe (including European parts of Russia).

Recommendations and outlook. A need remains to better understand the importance of and interactions between the various processes contributing to the Arctic Amplification of climate warming. As the amplification depends, among others, on the local Earth surface properties and mixing in the lower atmosphere, further studies should also include a more regional focus. EuRuCAS research has reviled the importance of combined effects of the amplified greenhouse-gas induced warming and the variability related to the Atlantic Multi-decadal Oscillation. To better estimate the Arctic warming during the coming decades, there is a strong need to better understand the mechanisms controlling the Atlantic Multi-decadal Oscillation, with some hope for its predictability.
Despite of the very active recent research, understanding of effects of changes in the Arctic sea ice cover and terrestrial snow pack on mid-latitude weather and climate is still limited. As the effects are often episodic and regional, it remains a challenge to quantitatively distinguish the impact of Arctic forcing from the impact of forcing factors acting at lower latitudes. The atmospheric response to changes in sea ice and snow cover varies regionally within Eurasia. Future studies on the regional effects are needed, with focus on better understanding on large-scale dynamics of the atmosphere, which carries the effects of remote forcing factors to Eurasia.
During EuRuCAS, links have been built with several new collaborators in Russia and globally. The largest network where EuRuCAS activities will be continued in a multidisciplinary consortium is the Pan-Eurasian Experiment (PEEX), which includes partners from Russia, China, Finland, and several other European countries. Partners of EuRuCAS have contributed to the design of PEEX, which aims towards system understanding of the Arctic-boreal regions for constructing scenarios and assessments of the future development of the Northern Pan-Eurasian environments and societies (Lappalainen et al., 2015). The Arctic climate change has been discussed in PEEX workshops, where EuRuCAS partners and colleagues from the Institute of Geography of Russian Academy of Sciences have presented results on Arctic – mid-latitude linkages.
New international collaboration has also included an extension of Norwegian – Chinese project “Winter and spring climate change at mid- and high-latitudes of Eurasian continent and its future projections” to collaboration with NIERSC and FMI. A project workshop was organized in Helsinki on 26-27 August 2015. Possibilities to extend the collaboration in the following fields were discussed: coordinated model experiments on sea-ice decline, teleconnections in general, water cycle in changing climate, heat waves and health, and coupling of stratosphere and troposphere. Two Horizon-2020 proposals involving EuRuCAS partners from Russia, Norway, and Finland are under preparation.
As a continuation of EuRuCAS collaboration between NERSC, NIERSC, and FMI, work has been started to write a book entitled “Arctic Sea Ice: Past, Present and Future”.
The studies reported above would have not been possible without research collaboration between Russia and EU (with Norway as a member of EU research activities). Russian research infrastructure, resources and expertise are naturally play the central role in observationally based studies, such as PEEX (Lappalainen et al., 2014) and research on sea ice in Eurasian Arctic (Bobylev et al., in preparation). Further, the added value of collaboration with Russian scientists has made possible several studies on the Arctic Amplification and linkages between the Arctic and mid-latitudes (e.g. Meleshko et al., Tyuryakov et al., Gnatiuk et al.).

Francis, J.A. and S.J. Vavrus (2012). Evidence linking Arctic amplification to extreme weather in mid-latitudes. Geophys. Res. Lett., 39, L06801, doi:10.1029/2012GL051000.
Kuzmina, S., Johannessen, O.M. Bengtsson, L., Aniskina, O. and Bobylev, L. (2008). High northern latitude surface air temperature: comparison of existing data and creation of a new gridded data set 1900-2000. Tellus, 60A, 289-304.
Svendsen, E., K. Kloster, B. Farrelly, O.M. Johannessen, J.A. Johannessen, W.J. Campbell, P. Gloersen, D. Cavalieri and C. Mätzler (1983). Norwegian remote sensing experiment: Evaluation of the Nimbus 7 scanning multichannel microwave radiometer for sea ice research. Journal of Geophysical Research, vol. 88, 2781-2991.
Zakharov, V.F. (2003). Changes of the Arctic sea ice extent in XX century. Meteorologiya i Gidrologiya (Meteorology and Hydrology), 5, 75-86 (in Russian).

Scientific publications with acknowledgement to EuRuCAS:
Bobylev et al. (2016). Ice cover variability and trends in the Eurasian Arctic seas in the 20th and 21st centuries (in preparation).
Gnatyuk, N., T. Vihma, and L. Bobylev. (2016). Effects of Northern Hemisphere surface temperature anomalies on 2-m air temperature in Northern and Eastern Europe (in preparation).
Johannessen, O.M. S.I. Kuzmina, L.P. Bobylev, and M.W. Miles (2016). Surface air temperature variability and trends in the Arctic: new amplification assessment and regionalization (under review in Tellus).
Lappalainen, H.K. V.M Kerminen, T. Petäjä, T. Kurten, A. Baklanov, A. Shvidenko, J. Bäck, T. Vihma, P. Alekseychik, S. Arnold, M. Arshinov, E. Asmi, L. Bobylev, S. Chalov, N. Chubarova, Leeuw, A. Ding, S. Dobrolyubov, S. Dubtsov, E. Dyukarev, N. Elansky, K. Eleftheriadis, I. Ezau, N. Filatov, M. Flint, C. Fu, O. Glezer, A. Gliko, M. Heimann, B. Holtslag, U. Hõrrak, J. Janhunen, S. Juhola, L. Järvi, H. Järvinen, A. Kanukhina, L. Karlin, V. Kotlyakov, A-J. Kieloaho, A. Komarov, J. Kujansuu, I. Kukkonen, A. Laaksonen, T. Laurila, H. Lihavainen, A. Lisitzin, A. Mahura, A. Makshtas, E. Mareev, D. Matishov, G. Matishov, V. Melnikov, R. Nigmatulin, S. Noe, A. Ojala, M. Pihlatie, O. Popovicheva, J. Pumpanen, T. Regerand, I. Repina, A. Shcherbinin, M. Sipil1, D.A. Skorokhod, Spracklen, H. Su, D. Subetto, J. Sun, A. Terzhevik, Y. Timofeyev, Y. Troitskaya, V-P.Tynkkynen I. Vyacheslav, N. Zaytseva, J. Zhang, V. Vitale, Y. Viisanen, T. Vesala, P. Hari, H-C Hansson, G. Matvienko, N. Kasimov, H. Guo, V. Bondur, S. Zilitinkevich, and M. Kulmala. (2016). Pan-Eurasian Experiment (PEEX): System understanding of the Arctic-boreal regions for constructing scenarios and assessments of the future development of the Northern Pan-Eurasian environments and societies (submitted to Atmos. Chem. Phys.)
Meleshko, V.P. O.M. Johannessen, A.B. Baidin, T.V. Pavlova, and V.A. Govorkova. (2016). Arctic Amplification: Does it Impact the Polar Jet Stream and Extreme Weather? (submitted to Science).
Outten, S., and I. Esau (2015). Role of Sea Ice Reduction in Eurasian Wintertime Cooling. ICARPIII (International Conference on Arctic Research Planning) and ISAR-4 (International Symposium on Arctic Research), Toyama, Japan, 23-30 April, 2015.
Suo, L., Y. Gao, D. Guo, J. Liu, H. Wang, and O.M. Johannessen (2015). Atmospheric response to the autumn sea-ice free Arctic and its detectability. Clim. Dyn., DOI 10.1007/s00382-015-2689-8.
Tyuryakov, S., T. Vihma, and L. Bobylev (2016). Effects of boundary layer heat capacity on the Arctic Amplification of climate warming (in preparation).

Ice and snow in the Arctic and Sub-Arctic:

Summary. Ice is found in the Northern Hemisphere down to the latitude around 40°N, apart from low latitude high mountains, and plays a major role in the environment and climate. It became a natural EuRuCAS topic, which is closely linked to other topics included. The principal objective of this research was to obtain new understanding, develop remote sensing methods, and improve existing models of ice in the Arctic Ocean and neighbouring Eurasian land areas. The main research field was Arctic sea ice, from basic science of snow on sea ice to remote sensing of ice types and drift, glaciers flowing to sea, and icebergs. Additional work concerned the Baltic Sea and freezing boreal and tundra lakes. Ice conditions in these lakes are related to their ecology and also they serve as references to compare with nearby freezing marine coastal zones. A total of seven peer-reviewed papers are expected: one of them is published, three are submitted, and three are under preparation (see list at the end of this section).

Participants. Leaders: Matti Leppäranta (University of Helsinki (UH)) and Aleksey Sharov (Johanneum research (JR)); Co-Leader: Vladimir Volkov (NIERSC); Contributors: Henna-Reeta Hannula (FMI), Mengxi Zhai and Ioanna Merkouriadi (both – UH), Dmitry Nikolskiy, Ksenia Troshko and Zinaida Zaprudnova (all – JR), Elena Shalina, Natalia Zakhvatkina, Alexandra Mushta, Anna Vesman (all – NIERSC), Denis Demchev (Arctic and Antarctic Research Institute/NIERSC), R. Husson, Nicolas Longépé and V. Renault (all – CLS).

Sea ice classification using SAR images. Arctic sea ice classification and monitoring relies heavily on Synthetic Aperture Radars (SARs), since these sensors deliver high-resolution (40-50 m) images independent of sun and cloud cover. Within the EuRuCAS project, focus was put on developing robust, automatic sea ice classification methods for dual-polarisation SAR data (Radarsat-2 and Sentinel-1), that can provide useful results under varying sea ice types and open water.
Pre-processing of the raw SAR data (angular correction for HH polarisation and noise reduction for HV polarisation) were developed for both Radarsat-2 and Sentinel-1 and improved significantly the performance of image processing algorithms like feature analysis and segmentation.
An ice/water classification algorithm was developed for Radarsat-2 satellite using texture feature analysis and support vector machine (SVM). Seven texture features and 3rd and 4th statistical moments of brightness were calculated for a 'sliding' window (64x64 pixel) and served then as input for the SVM, which predicted whether the window contained sea ice or open water. SVM is a supervised learning method and the algorithm has been trained using 24 Radarsat-2 images displaying different ice/water types around Svalbard. Operational classification has been started in March 2012 and since then more than 2,700 Radarsat-2 images have been processed and results were published online ( Validation of this algorithm has been performed by comparison with manually drawn sea ice charts form the Norwegian Meteorological Institute, which showed that the achieved accuracy for the latest algorithm version was around 99 (Zakhvatkina et al., 2015).
Recently a new algorithm for Sentinel-1 has been developed, based on a combination of SVM and segmentation. Instead of classifying a 'sliding' window, this algorithm defines the ice or water class for each pre-defined segment. This improves the resolution from 1,600 m to 120 m. Using additional training images and including new classes, this algorithm can be adopted for detecting all types of sea surface coverage, which have distinct textural characteristics (e.g. leads, marginal ice zone). The new algorithm will be improved and its potential for detecting different types of ocean surface coverage in the Arctic will be exploited within the current and upcoming cooperation between NERSC, NIERSC and other EuRuCAS partners.

Sea ice drift. Ice drift is a very important parameter of the oceanographic regime. Data on sea-ice drift are necessary to ensure safety navigation and offshore operations in the Arctic and are also important for climate studies. Satellite remote sensing data provide an opportunity to obtain information about the ice drift not only at certain points, but also to build a maps of the drift fields for large areas – from separate regions of seas up to the entire ocean.
Cooperation in the studies of ice drift in the Arctic Ocean, as a part of the EuRuCAS project, was organised around two main directions: 1) development of methodologies for sea ice drift retrieval from SAR data with an emphasis on the new satellite Sentinel-1; and 2) analysis of ice drift fields variability on the various spatial-temporal scales: from meso-scale (especially important for study of Marginal Ice Zones (MIZ)), trough synoptic-scale (providing information for navigation and offshore activity), to large-scale (for analysis of climate variability in polar region).
The study used an expanded dataset of satellite images collected by partner organizations. For processing successive pairs of images and getting ice drift fields, both traditional methods (e.g. correlation method) and new methods jointly developed by partners were use. New methods were based on the Oriented FAST and Rotated BRIEF (ORB) algorithm and on the Histogram Oriented Gradients based descriptors. New approaches made it possible to perform calculations quickly and accurately, and were more robust in case of ice floes rotation. The validation showed a very good agreement with the "manual" analysis of SAR images. These algorithms can be used in operational mode for the practical use.
Combined analysis of long time series (up to 30-40 years) of large-scale sea ice drift fields and atmospheric circulation variations revealed links between them on the interannual and seasonal scales. Additionally, the important role of ice drift field structure changes in variations of the ice extent in the Arctic Ocean was identified. Satellite-derived data on sea ice drift have been used for the validation of regional ocean circulation models. For this purpose, a feature tracking algorithm was applied.

Iceberg detection based on SAR data. The monitoring of icebergs is important in order to address maritime security and navigation safety issues. As the icebergs transfer material and nutrients from land to sea, the evolution of their statistical geographic occurrence is also an important tracker for the evolution of Arctic and Antarctic environments.
SAR data are commonly used for maritime security applications and object detection. The study of climatology of iceberg occurrences on SAR images on a large scale requires anyway adapting generic object detection framework in order to accommodate the various kinds of signatures observed in the Arctic/Antarctic environments. The opportunity to use historical wave mode acquisition of European SAR missions was evaluated in order to derive global statistics. This specific kind of acquisition is dedicated to the observation of swell systems in open oceans by sparse observations on high-resolution small imagettes. Generic echo detection tools were adapted in order to make them compatible with Envisat/ASAR/Wave Modes products and to enable to generate first results of climatology of iceberg locations. The results were compared with results of iceberg detection based on anomalies of altimeter waveforms. This comparison highlighted the need to define a new detection approach, not based on the assumption of bright isolated echoes but enabling also to extract iceberg locations in more dense areas. Since the launch of Sentinel-1 A in April 2014 and the availability of its first wave mode acquisitions the tools are under adaptation to the specificities of this new type of product in terms of format, coverage and incidence angle. The results will be useful for improving the navigation safety in areas not routinely monitored by other remote sensing means. This is of typical interest for the navigation routes in South Atlantic, Pacific and Indian Oceans both for commercial vessels routes and round-the-world yacht races. A synergetic and coordinated use of various kinds of remote sensing instruments would be relevant for this purpose. For this purpose the products generated by the Sentinel-1/2/3 constellation will be of typical interest. An abstract on the detection of icebergs from Wave mode of Sentinel-1 has been submitted to the ESA Living Planet Symposium in May 2016 (Husson et al., 2015).

Ice on lakes and marine coasts. To a most part freezing lakes and marine coasts have a seasonal ice cover. Common characteristics are the vicinity of land areas and shallow depths, and as a consequence the mobility of ice is limited. Thermal growth of ice is less than about 2 m, while mechanically forced piling-up of ice blocks may reach thicknesses more than 10 m. Ice seasons are closely connected to climate in that freezing and breakup dates and maximum annual ice thickness are quite sensitive to atmospheric forcing. The present ice research problems are the annual cycle of ice thickness, stability of the ice cover, ice-driven erosion of the bottom and shoreline, ice forces on man-made structures, and ice climatology (Karetnikov et al, 2015; Leppäranta, 2015a; Leppäranta et al., 2015a).
In lakes fetches are more limited and the resulting erosion and forces are weaker. In EuRuCAS research a new thermodynamic ice model has been developed including the porosity of ice resulting from internal melting (Leppäranta, 2015b). This significantly improves the modelling of the melting season. Thermal remote sending of ice thickness in large lakes has been examined with MODIS data, and the method is applicable for smaller lakes when the horizontal image resolution allows (Leppäranta et al., 2015c). Also the influence of ice cover on circulation has been investigated showing the strong difference between wind-driven summer circulation and thermohaline winter circulation.
The coastal zone research has involved the Siberian shelf, where the landfast ice decays as a thermal-mechanical process (Yang et al., 2015). Due to melting, especially internal melting, the strength of ice decreases and the landfast ice is broken by winds and tides and drifts out (Peng et al., 2015). The mechanics is necessary to prevent multiyear landfast ice formation in the Arctic coast. The work was based on satellite remote sensing and mathematical modelling. Also a sea ice modelling chapter is in preparation for a new book about Arctic sea ice (Leppäranta et al., 2015b).
The achieved results will be useful to ice safety issues on lakes and coastal areas with on-ice traffic conditions depending on the ice thickness and strength. This is critical especially in the warming climate. Also improved lake ice models can be utilized in the development of the land – atmosphere coupling in weather and climate models. A realistic landfast ice sub-model would also be highly relevant to implement into existing sea ice models.

Snow cover. Most of the Arctic sea ice is covered with the snow almost all the year round. Snow cover plays an important role in the sea ice transformations and thus is important for thermodynamical processes description. Besides, information on snow depth is also very important for satellite altimeter estimates of the sea ice thickness.
Snow climatology based on the North Pole drifting station measurements is widely used and extensively discussed. IBM buoys data and recently available data from IceBridge flights are also in use by scientific community. In cooperation with NERSC, NIERSC scientists have been working on analysing data collected during aircraft landings of the Soviet Union's high-latitude airborne expeditions Sever. UH scientists were also studying results of measurements done at the meteorological stations located in the Russian Arctic. Sever expeditions measurements are different from data collected at drifting stations as aircraft landing sites covered mostly marginal seas and only partly the central Arctic where drifting stations operated on the multiyear ice. Meteorological stations are also located in the marginal part of the Arctic Ocean.
Sever expeditions were carried out in 1937, 1941, 1948-1952, and 1954-1993. The landings generally took place from mid-March to early May, when there was enough light to operate, but before summer melt made safe landings impossible. As to the ice types where the landings took place, they were quite different. The most thorough examination of the ice and snow characteristics was provided for the marginal seas.
There were several types of snow depth measurements obtained during landings: runway snow depth, snow depth on prevailing landing area ice, depth measured at mid-length of snow dunes extending out from ridges, depth of snow on hummocks, on both windward and lee sides, and height of sastrugi. The main goal of this study was to produce a reliable map of snow depth on the marginal sea ice in the end of winter season that could be used in ice thickness retrievals form satellite altimeter measurements. Therefore, the main attention was paid to the processing of snow depth measurements done on prevailing landing area ice. However data collected on hummocks, ridges and sastrugi were also analysed.
In the central Arctic snow depth observations were quite sparse and measured values were unexpectedly low (in most cases lower and in some cases much lower than in the widely used Warren climatology). In the marginal seas observations were densely packed making a good base for snow depth analysis. Basing on those observations a map of the average snow depth in the marginal seas has been produced. The highest values were observed in the East Siberian Sea and the lowest values – in the Barents and Kara seas.
These results can be used to improve snow on sea ice climatology especially in the marginal part of the Arctic Ocean and particularly in the Siberian Arctic seas.
Snow on ground is a vital component of the water cycle, as well as being critically important for the weather and climate due to its high albedo, its high thermal emissivity, and its thermal insulating properties. To predict and monitor the evolution of potential snowmelt, continuous observations of key parameters such as Snow Water Equivalent (SWE), Snow Depth (SD), and Snow Extent (SE) are required. While traditional snow pit and automatic weather station observations are important, remote sensing observations of snow using passive microwave radiometers are vital for global daily measurements of snow properties.
Continuous manual measurements of snow on ground are performed at Finnish Meteorological Institute’s Arctic Research Centre in Sodankylä, Finland. Regular measurements started in 1909 with SWE and SD, and snow pit observations have been made weekly since 2006. Field campaign Arctic Snow Microstructure Experiment (ASMEx) took place in Sodankylä during two winter seasons 2014-2015. The aim was to understand better microwave extinction in snow and develop models for passive microwave measurements. The experiment included radiometer observations of snow microwave emission with 18.7 21.0 and 37.5 GHz frequencies, and manual reference measurements of snow macro- and microstructure from homogenous snow slabs extracted from natural seasonal snowpack. Simulations of microwave emission were made with two snow emission models, a single layer Helsinki University of Technology (HUT) snow model and Microwave Emission Model for Layered Snowpacks (MEMLS). Simulations were compared to microwave observations. RMSE and bias were calculated; accuracy of the models depended on measurement setup and used frequency. This experiment provided an excellent framework for future research on the extinction of microwave radiation inside snow.
The large variability of the physical properties of Arctic snow cover forms a challenge for correct estimation of snow properties from the remote sensing data. For example, satellite measurements of hemispheric scale SWE are suffering from large uncertainties, although, assimilation of ground-based and space-borne information and algorithms specific for a land-cover type have proven to lower these remaining errors. The lack of extensive field ground data collected simultaneously with the RS data is often a limitation for further assessment and development of the RS algorithms to attain better snow cover information. A large collection of in situ snow data was collected in a support of ESA SnowSAR airborne acquisitions in Northern Finland during winter 2011-2012. This measurement collection has now been used to statistically analyse the snow property variation within and between different land-cover types in North boreal and tundra environments. The goal was to develop regionally and temporally the best possible knowledge of the snow property variation. This study is contributing to the work aiming for more reliable SWE retrieval methods as this kind of ground data analysis can be further utilized, for example, in studies researching the effects of land cover type and snow property variation on SAR backscatter signatures. In the future work now generated field information will be compared with simultaneously collected airborne and space-borne measurements of snow.

Glaciers. Arctic glaciers are among the most varied objects on the earth’s surface as a result of changes in global climate, fluctuations in the Arctic Oscillation, enhanced oceanic forcing, varying inflow of warmth and moisture, and sea ice concentration in the Arctic Basin. Tidewater glaciers terminating in the sea and producing icebergs are considered as especially dynamic and changeable types of land ice in the Arctic. In the EuRuCAS frameworks ERS, TanDEM-X and Sentinel-1A satellite SAR interferometric models calibrated with ICESat and CryoSat-2 altimetry data were successfully applied to mapping and quantifying glacier elevation changes and mass balance characteristics in climatically sensitive areas of the Eurasian Arctic. A new series of six full-value maps were generated in comparison with 60-year old reference elevation models, validated and added to the Online Atlas of Glacier Fluctuations in the Eurasian Arctic accessible at New map prototypes showing spatial distribution of ice balance characteristics in the heterogeneous field of gravity were generated and interpreted using long-term oceanographic data, precipitation records and GOCE gradiometry data. The regional assessment of the mapped changes showed that the Eurasian insular glaciation lost 1,005±20 km³ of its volume and 2,030±100 km² of its area in the period of 1950-2010. The most remarkable decay of tidewater glaciers was recorded in southern and eastern parts of Svalbard, Franz Josef Land and Severnaya Zemlya. But we also registered a dozen growing ice caps.
The Matusevich Ice Shelf in Severnaya Zemlya lost 123±2.5 km² or two thirds of its area and 9±0.3 km³ of its volume in the course of the past 5 years. According to our most conservative estimate, nearly 4.000 icebergs with the mean size of 200x100 m² escaped from the Matusevich Fjord in the period of 2009-2014. The largest iceberg was 3.5 km long and 1.1 km wide. We located and dated main surging and calving events in the study region. The potential causes and aftereffects of the ice shelf disintegration were determined and the sensitivity of its remnants to climatic forcing was assessed. The mean annual temperature of −9°C proved to be a valid climatic threshold for the ice-shelf viability in the Russian Arctic. We suggested that the integral estimation of calving regime in the high-latitudinal archipelagos of Svalbard, Franz Josef Land, Novaya and Severnaya Zemlya previously published by other investigators was out-of-date and must be revised. The research work was carried out in close collaboration with four young cartographers from Moscow thus contributing to the professional orientation and training of young Russian scientists.
An abstract has been submitted to the ESA Living Planet Symposium in May 2016 (Sharov and Nikolskiy, 2015).

Recommendations and outlook. EuRuCAS Arctic and Sub-Arctic ice research has achieved significant results. Sea ice classification has been performed operational for Radarsat-2 data with high accuracy. A new algorithm has been developed for Sentinel-1 and will be exploit in current and upcoming projects for discriminating and identifying different types of sea ice and sea surface characteristics, like leads and marginal ice zone. A new thermodynamic model with two-phase structure has been developed for lake ice, and the process of landfast decay has been examined in detail. The reported snow work was based on the historical data and new field experiments for calibration of remote sensing data and models. It adds a new knowledge to existing representation of the Arctic snow cover.
The following recommendations can be given for the future joint cooperative research:
o To progress research on conjugate climatic changes in sea ice and Arctic glaciers, and production and distribution of icebergs in conditions of present global warming.
o To implement physically based landfast ice model to Arctic Ocean sea ice models that is useful for improved short-term and climate predictions and shipping in the Northern Sea Route.
o To use the improved thermodynamic ice model for monitoring springtime ice cover and connect this to safety issues and warning systems in inhabited lake and coastal zone environments.
o To investigate the changes that have occurred in the snow in the EuRuCAS research area. Most recent studies connected with the snow on sea ice changes are based on the IceBridge data that do not cover the part of the Arctic Ocean adjoining the Russian coast. The main source of in-situ data will be meteorological station measurements.
o To revise the integral estimation of calving regime in the high-latitudinal archipelagos of Svalbard, Franz Josef Land, Novaya and Severnaya Zemlya previously published by other investigators.
During EuRuCAS, the Department of Physics, University of Helsinki has signed to become an Associated Partner of NIERSC. This allows the UH representative to be present at NIERSC meetings, and opens further possibilities to joint proposals, research and education of students, in all providing a firm basis for future collaboration.

Leppäranta, M. (2015a). Physics of lake ice. UNESCO EOLLS Encyclopedia (in press).

Scientific publications with acknowledgement to EuRuCAS:
Husson, R., N. Longépé and V. Renault (2015). Iceberg detection in the Southern Ocean using Sentinel-1 wave mode acquisitions. Abstract submitted to ESA Living Planet Symposium, Prague, May 2016.
Karetnikov, S., M. Leppäranta, and A. Jokiniemi (2015). Time series over 100 years of the ice season in Lake Ladoga (in preparation).
Leppäranta, M. (2015b). A two-phase model for lake ice (in preparation).
Leppäranta, M., E. Lindgren and L. Arvola (2015a). Heat balance of supraglacial lakes in the western Dronning Maud Land. Annals of Glaciology (submitted).
Leppäranta, M., P. Uotila and V. Meleshko (2015b). Sea ice modelling. In O.M. Johannessen et al. (eds.), Sea ice in the Arctic: Past Present and Future. (in preparation).
Leppäranta, M., J.E. Lewis and A. Erm (2015c). Thermal remote sensing of ice thickness in Lake Peipsi. Abstract submitted to ESA Living Planet Symposium, Prague, May 2016.
Peng, L., M. Leppäranta, B. Cheng and Z. Li (2015). Influence of melt-pond depth and ice thickness on Arctic sea-ice albedo and light transmittance. Cold Regions Science and Technology (submitted).
Sharov A., and B. Nikolskiy (2015). Directional dynamics of Eurasian ice caps in anomalous gravity fields. Abstract submitted to ESA Living Planet Symposium, Prague, May 2016.
Sharov A. and D. Nikolskiy (2013) Satellite map series of long-term elevation changes on Eurasia’s northernmost ice caps. In: R. Lasaponara (Ed.), Proceedings of the 33rd EARSeL Symposium, Matera, Italy, 14 p.
Sharov A., D. Nikolskiy, K. Troshko, and Z. Zaprudnova (2015) Interferometric control for mapping and quantifying the 2012 breakup of Matusevich Ice Shelf, Severnaya Zemlya. Proceedings of the International Workshop FRINGE2015, ESRIN, Frascati, ESA SP731, 9 p.
Yang, Y., M. Leppäranta, Z. Li, B. Cheng, M. Zhai and D. Demchev (2015). Model simulations of the annual cycle of the landfast ice thickness in the East Siberian sea. Advances in Polar Sciences, 26(2), 168-178.
Zakhvatkina N., A. Korosov, S. Muckenhuber, and S. Sandven (2015). Ice edge and water automated detection on dual-polarized RADARSAT-2 images (in preparation).
Zhai, M., M. Leppäranta, B. Cheng, X. Cheng and F. Hui (2015). Remote sensing of sea ice thickness in the Arctic Ocean. International Journal of Remote Sensing, EARSeL 2015 Special Issue (submitted).

Polar lows in the Arctic:

Summary. The EuRuCAS research on this task has addressed high-priority topic – creating advanced climatology of polar lows in the Nordic and Barents seas. This work has been performed by NIERSC, IFREMER and Satellite Oceanography Laboratory at the Russian State Hydrometeorological University (SOLab RSHU) in St. Petersburg, Russia. One peer-reviewed paper has been published under EuRuCAS on this topic (see reference at the end of this section).

Participants. Leader: Leonid Bobylev (NIERSC); Co-Leaders: Elizaveta Zabolotskikh and Julia Smirnova (SOLab RSHU); Participants: Pavel Golubkin (SOLab RSHU), Bertrand Chapron (IFREMER).

Introduction. Polar lows are intense meso-scale maritime cyclones, characterized by short lifetime (several hours – one day), small sizes (<1,000 km) and surface wind speed ≥ 15 m s−1. These cyclones develop during wintertime in high latitudes over marine areas in both hemispheres, but in the Arctic they are most vigorous and dangerous. Polar lows possess by high destructive power and, therefore, present threats for ships, oil and gas platforms and coastal infrastructure in the Arctic and Sub-Arctic. The same time polar lows are much less studied than the tropical cyclones: the climatology of the occurrence and characteristics of polar lows is poorly known. In addition, polar lows continue to be a major challenge for operational forecasting in the Arctic. Due to small size of polar lows, their detection forms a part of the challenge. Therefore, additional, more reliable polar low climatological data are of a critical importance for both scientific and practical applications.

Creation of polar low climatology for the Nordic and Barents seas. There are several existing polar low climatologies, but most of them are based on modelling and reanalysis data, weather maps and partly on infrared imagery. However, polar lows are often not detected at the weather maps and are under-represented in the current reanalysis datasets. Therefore, the most informative polar low studies should base on the comprehensive joint analysis of different satellite data from various instruments. Among the satellite sensors, microwave radiometers have important advantages for detecting and tracking polar lows. This is independence on day and night time and clouds, and regularity and high temporal resolution in polar regions provided by past and present satellite radiometers.
For creating new polar low climatology for the Arctic in the framework of EuRuCAS Project new approach has been applied for detecting and tracking polar lows based on satellite passive microwave data (Bobylev et al., 2011). In this approach, satellite measurements using microwave radiometers such as SSM/I were used for retrieval fields of total water vapour (TWV) content in the atmosphere over the ocean open water, using algorithm described in (Bobylev et al., 2010). This algorithm was tuned for the Arctic conditions, leading to a higher accuracy (retrieval error 1.34 kg m−2) than the Wentz (1997) global operational algorithm (retrieval error 1.90 kg m−2). This is especially important since TWV content in polar lows can be just 2–3 kg m−2 higher than in surrounding areas. Consistent polar low detection thus becomes impossible if the retrieval error is close to these values (Smirnova et al., 2015).
Obtained TWV fields were further visually analyzed for the presence of polar low-like vortices, which manifested themselves as a cyclonic signatures having small horizontal extent and exceeding ambient level of the TWV content by at least 2 kg m−2. Then, the detected vortices were defined as polar lows only if sea surface wind speed exceeded 15 m s−1 as estimated using SSM/I wind products provided by Remote Sensing Systems ( Additionally, presence of cloud signature on infrared imagery was checked for each detected polar low using AVHRR quicklook images from the Dundee Satellite Receiving Station ( For all verified cases, the following polar low parameters were estimated: diameter, lifetime, distance traveled, translation speed, and maximum wind speed.
Based on this approach, new 14-year (1995-2008, September-April) climatology of polar lows for the Nordic (Norwegian, Greenland, Iceland) and Barents seas has been created (Smirnova et al., 2015). Totally 637 polar lows were detected above these seas over the considered period with average frequency 45.5 cyclones/year. A 14-year period is insufficient for trend estimation, however there is some tendency for increasing polar low number over this period. Overwhelming majority of polar lows in this climatology has diameter from 100 to 400 km and lifetime from 3 to 18 hours. Maximum of polar low occurrence is observed in the South-Western Barents Sea, North-Eastern Norwegian Sea and in the Greenland Sea South-West of Svalbard.

Recommendations and outlook. Considering polar lows, the highest priority is to improve the assimilation of various remote-sensing observations into numerical weather prediction models. Challenges remain also in the optimization of high-resolution ensemble prediction systems for polar lows and in better understanding of the effects of polar lows on ocean deep convection.

Bobylev, L.P. E.V. Zabolotskikh, L.M. Mitnik, and M.L. Mitnik (2010). Atmospheric water vapor and cloud liquid water retrieval over the Arctic Ocean using satellite passive microwave sensing. IEEE Trans. Geosci. Remote Sens., 48(1), 283-294, doi:10.1109/TGRS.2009.2028018.
Bobylev, L.P. E.V. Zabolotskikh, L.M. Mitnik, and M.L. Mitnik (2011). Arctic polar low detection and monitoring using atmospheric water vapor retrievals from satellite passive microwave data. IEEE Trans. Geosci. Remote Sens., 49(9), 3302-3310, doi:10.1109/TGRS.2011.2143720.
Wentz, F.J. (1997). A well-calibrated ocean algorithm for special sensor microwave/imager, J. Geophys. Res., 102(C4), 8703-8718, doi:10.1029/96JC01751.

Scientific publication with acknowledgement to EuRuCAS:
Smirnova, J.E. P.A. Golubkin, L.P. Bobylev, E.V. Zabolotskikh, and B. Chapron (2015). Polar low climatology over the Nordic and Barents seas based on satellite passive microwave data. Geophys. Res. Lett., 42, 5603-5609, doi:10.1002/2015GL063865.

Arctic and Sub-Arctic marine and lake ecosystems:

Summary. This task addresses two priority topics. They are: (1) remote quantification of primary productivity in the Baltic Sea; and (2) improved monitoring of water quality in Sub-Artic lakes. A total of six peer-reviewed papers are expected: five of them are submitted, and one is under preparation (see list at the end of this section).

Participants. Leaders: Susanna Kratzer (Stockholm University (SU)) and Dmitry Pozdnyakov (NIERSC); Co-Leader: Victor Podsechin (UH); Contributors: Evgeny Morozov (NIERSC); Selima Ben Mustapha (SU), Matti Leppäranta (UH).

Introduction. The increasing Arctic and Sub-Arctic warming is conductive to inevitable and possibly very significant environmental changes including those residing in marine and lacustrine environments at high latitudes in the Northern Hemisphere. Development of efficient tools based on innovative methodologies and their application to study of the above aquatic media is an urgent necessity to which this programme’s task is responding.

Primary productivity model for the Baltic Sea. The absence of an acknowledged pun-Baltic Sea model of primary productivity (PP) stems from two major impediments: a) significant complexity and heterogeneity of optical properties of the Baltic Sea (BS), and b) notable seasonal variations in the indigenous phytoplankton composition (Beltran-Abaunza et al., 2014). These specific features determined the course of considered topic implementation: identification of, firstly, a PP model and, secondly, a biohydrooptical algorithm for the retrieval of phytoplankton chlorophyll (CHL) that are most adequate for the Baltic Sea.
Following this pathway, four primary production models developed specifically for the Northern Atlantic – Marra et al., 2003; Behrenfeld and Falkowski, 1997; Behrenfeld et al., 2005, and Arrigo and van Dijken, 2011 (see also Pubi et al., 2008), have been tested for the conditions in the Baltic Sea. For this purpose a BS database of in-situ PP measurements was developed. In addition to PP values, it encompassed all presently available data from the Helsinki Commission (HELCOM) and the Swedish Meteorological and Hydrological Institute (SMHI) archives on surface and depth-distributed CHL, sea surface temperature (SST), and incident photosynthetically active solar radiation (EPAR). The database included 2,200 and 105 measurements of CHL and PP respectively for the period 2002-2012. The Behrenfeld and Falkowski (1997) model yielded the best results and became basic for further work. Among the tested for the BS CHL retrieval algorithms, viz. OC3 (NASA), GSM (NASA) (Maritorena et al., 2002), OC4 (NASA), OC2-modified (Darecki et al., 2005), BOREALI (Korosov et al., 2009), the OC3 algorithm gave better results. Two atmospheric correction techniques were comparatively exploited: MUMM (Ruddick et al., 2000) and NASA standard models. The MUMM technique permitted to attain better CHL retrievals. So, that the PP model and CHL retrieval algorithm most appropriate for the BS have been ascertained and further employed for restoring seasonal PP fields for the period 2002-2012.

Study of large lakes in Scandinavia within Sub-Arctic zone. Improvement of monitoring water quality in Sub-Artic lakes is described here on the basis of two case studies performed for lakes Vänern in Sweden and Vesijärvi in Finland.
Lake Vänern is characterized (Willén, 1984) by a significant spatial and temporal variability in both biogeochemical properties and external forcing (both of atmospheric and catchment origin). Since a few decades, it is under a significant anthropogenic pressure (Willén, 2001a, b).
To work out a procedure for efficient remote sensing of the lake, dedicated databases were compiled to accommodate MERIS data over the lake and in-situ supporting measurements (Katzer et al., 2008, 2009). MERIS data are reported as highly appropriate for these aims (Ohde et al., 2007; Philipson et al., 2014). The complete archive (2002-2011) of MERIS full resolution data from the 3rd reprocessing was processed using the Case-2 water processor developed by the Free University of Berlin (FUB algorithm) to obtain aerosol optical thickness (AOT), normalized water-leaving radiance (nLw) and water constituents. The nLw and AOT products were evaluated using AERONET-OC match-up data measured at station Pålgrunden in Lake Vänern.
Thus, based on the performed assessments it has been concluded that satellite data, in particular data gathered from MERIS with its high spatial resolution of 300 m, could be used to map the spatial and temporal variability of water quality parameters in Lake Vänern through quantitatively characterizing CHL, total suspended matter, turbidity, coloured dissolved organic matter, Abs420 and Secchi depth spatial and temporal distributions.
However, the initial evaluation against local monitoring data showed that the FUB algorithm does not work sufficiently well in the Lake Vänern. This is presumably because of the high CDOM values in Lake Vänern, which are usually around 1.0 m-1 in the open lake during the summer (Hommersom, 2012), but which strongly increase in the shallow coastal areas. The FUB, however, has only been trained for CDOM values of up to 1.0 m-1, and therefore does not cover the full range of CDOM concentrations in lake Vänern. But, it was found that retraining of the FUB algorithm with enhanced CDOM values and the corresponding values of all other optical properties allowed improving the accurate retrieval of all optical constituents directly from MERIS data. The evaluation against AERONET-OC data also showed that the atmospheric correction procedure inherent in the FUB processor does not return realistic reflectance spectra in the blue range and AOT values are generally overestimated. FUB is currently working on an improved atmospheric model.
Nevertheless, it has been shown in this study, that MERIS data still could be used to retrieve reliable in-water products after recalibration against local monitoring data using regression analysis. As the optical properties in Lake Vänern do not show very large ranges, data from three other Swedish lakes was included in the calibration data set in order to improve the predictive power of the regressions analysis. The results showed relatively good accuracy for optically complex waters (here we should compare to other optically complex water bodies). Furthermore, a significant improvement in the sampling frequency could be obtained for Lake Vänern by adding complementary satellite-based water quality products to the monitoring programme. Moreover, the use of satellite data allows deriving time series of distribution maps of optical constituents over the whole lake basin. Such detailed maps cannot be derived from in-situ monitoring data with such low spatial coverage and sampling frequency as the existing freshwater monitoring programmes.
Lake Vesijärvi, located in the vicinity of the city Lahti (Finland), has been under heavy anthropogenic influence since the middle of the last century. The total surface area of the lake is 108 km2, with a mean depth of 6 m, and a maximum depth of 42 m. After 1976, when the outlet of the sewage treatment plant in Kariniemi was redirected to Porvoojoki, the state of the lake was improved, but in the beginning of 2000 water quality was deteriorated again. As a result of continuing nutrients loading, intensive algal blooms were observed, leading to oxygen depletion in hypolimnion. Nevertheless, generally the ecological status of the lake is classified as satisfactory.
Lake Vesijärvi is used for fishing and has a high recreational value. A lot of experimental data were collected during many years of research, including hydrophysical, hydrochemical and hydrobiological data. For the Lake Vesijärvi case study, a coupled hydrodynamic and sediment transport model COHERENS (Luyten et al., 1999) was applied to study the dynamics of flow, thermal regime and transport of suspended sediments, and to determine the location of resuspension zones during stormy episodic events. The suspended sediment block describes sinking, resuspension to and from the fluff layer, advection and diffusion of single-fraction of suspended particulate matter. Simulated were depth-averaged currents, surface water temperature and suspended sediments concentrations at different time slices. Winds of South-Western direction prevail in Southern Finland. As a consequence the North-Eastern shallow coastal zones of Lake Vesijärvi are areas where erosion mainly takes place. It is also revealed that suspended particles are then transported by currents and settle in the deeper central basins of the lake.
A numerical experiment was performed also to calculate currents in winter conditions. These conditions differ drastically from the open water period in the lakes of the boreal and Sub-Arctic zones. Lakes are covered with ice during 4-5 months period, which prevents the momentum transfer from atmosphere to water. The COHERENS model does not have a module for ice growth and decay. To imitate the winter conditions in case of Lake Vesijärvi the surface air temperature was fixed and equalled 0°C, both wind components were equal to zero. Zero heat flux boundary condition was applied at the bottom. Initial water temperature was equal to 4°C. The model was integrated for two days period. For longer simulation periods the numerical instability was observed.

Nordic Network for Baltic Sea Remote Sensing. EuRuCAS participant, Associate Prof. Susanne Kratzer, is the coordinator of the Nordic Network for Baltic Sea Remote Sensing (NordBaltRemS; 2012-2016). NordBaltRemS is a continuation of the previous Nordic Network for Aquatic Remote Sensing (NordAquaRemS, 2009-2011). NordBaltRemS has a clear focus on the Baltic Sea, but it also includes discussion of results from Nordic Lakes at its workshops. EuRuCAS Partners, Stockholm University, the University of Helsinki and NIERSC, are part of this Nordic Network. The involvement of NIERSC in this network together with some other EuRuCAS Partners serves to further strengthening and continuation of EU-Russia cooperation in the Arctic and Sub-Arctic research far beyond EuRuCAS.
The following events in collaboration with the EuRuCAS scientists were organized within NordBaltRemS:
o ECTS PhD training course “Remote sensing of sea ice in the Baltic Sea”, 4-9 March 2013, Tvärminne Zoological Station, Finland. Organizer: Prof. Matti Leppäranta, University of Helsinki.
o Special topic session on Baltic Sea Remote Sensing (topic 19) in the Baltic Sea Science Congress (BSSC), 29 August 2013, Klaipeda, Lithuania. Organizers: Prof. Inga Dailidiene, Prof. Matti Leppäranta and Associate Prof. Susanne Kratzer.
o NordBaltRemS workshop “Regional differences in optical properties of the Baltic Sea” during the BSSC, 30 Aug 2013, Klaipeda, Lithuania. Organizers: Prof. Inga Dailidiene and Associate Prof. Susanne Kratzer.
o PhD training course on sea-truthing and bio-optical modelling, 25-31 May 2014, Askö Laboratory, Sweden. Course organizer: Associated Professor Susanne Kratzer.
o Workshop on coastal waters during the EARSeL Symposium, 15-19 June 2015, Stockholm, Sweden. Organizer: Associated Professor Susanne Kratzer.

Arrigo, K.R. and van Dijken, G. L. (2011). Secular trends in Arctic Ocean net primary production, J. Geophys. Res.,116 (C09011), 1-15, Doi:10.1029/2011JC007151.
Behrenfeld, M., and P. Falkowski. (1997). Photosynthetic Rates Derived from Satellite-Based Chlorophyll Concentration. Limnology and Oceanography, 42 (1), 1-20.
Behrenfeld, M., E. Boss, D. Siegel, and D. Shea. (2005). Carbon-Based Ocean Productivity and Phytoplankton Physiology from Space. Global Biogeochemical Cycles, 19 (GB1006), 1–14. doi:10.1029/2004GB002299.
Beltran-Abaunza, J.M. Kratzer S. and Brockmann, C. (2014). Evaluation of MERIS products from Baltic Sea coastal waters rich in CDOM. Ocean Science, 10, 377-396.
Darecki, M., Kaczmarek, S. and Olszewskia, J. (2005). SeaWiFS ocean colour chlorophyll algorithms for the southern Baltic Sea. Int. J. Remote Sens., 26(2), 247-260.
Hommersom, A., Kratzer, S., Strömbeck, N., Philipson, P. (2012). Characterisation of the optical properties of Lake Vänern, Sweden, for improved water quality mapping by remote sensing. Extended abstract and poster at Ocean Optics, Glasgow, October 2012.
Korosov, A.A. Pozdnyakov, D.V. Folkestad, A., Pettersson, L.H. Sorensen, K., Shuchman, R. (2009). Semi-empirical algorithm for the retrieval of ecology-relevant water constituents in various aquatic environments. Algorithms, 2, 470-497, doi: 10.3390/a2010470.
Kratzer, S., Brockmann, C., and Moore, G. (2008). Using MERIS full resolution data (300 m spatial resolution) to monitor coastal waters– a case study from Himmerfjärden, a fjord-like bay in the north-western Baltic Sea. Remote Sensing of Environment, 112(5), 2284-2300.
Kratzer, S., and Tett, P. (2009). Using bio-optics to investigate the extent of coastal waters: A Swedish case study. Hydrobiologia, 629, 169-186.
Luyten, P.J. Jones, J.E. Proctor, R., Taylor, A., Tett, P., Wild-Allen, K. (1999). COHERENS. A Coupled Hydrodynamical-Ecological Model for Regional and Shelf Seas. User Documentation. MUMM Report, Management Unit of the Mathematical Models of the North Sea, 914 p.
Maritorena S., D.A. Siegel & A. Peterson. (2002). Optimization of a Semi-Analytical Ocean Color Model for Global Scale Applications. Applied Optics, 41(15), 2705-2714.
Marra, J., Ho, C. and Trees, C.C. (2003) An Alternative Algorithm for the Calculation of Primary Productivity from Remote Sensing Data, LDEO Technical Report LDEO-2003-1. National Aeronautics and Space Administration, Lamont-Doherty Earth Observatory of Columbia University.
Ohde, T., Siegel, H. and Gerth, M. (2007). Validation of MERIS Level-2 products in the Baltic Sea, the Namibian coastal area and the Atlantic Ocean. International Journal of Remote Sensing, 28 (3&4), 609-624.
Pabi, S., van Dijken, G.L. and Arrigo, K.R. (2008). Primary production in the Arctic Ocean, 1998-2006. J. Geophys. Res., 113, C08005, doi:10.1029/2007JC004578.
Philipson, P., Eriksson, K., Stelzer, K. (2014). MERIS data for monitoring of small and medium sized humic Swedish lakes. Proc. of IEEE/OES Baltic Symposium 2014, Tallinn, Estonia.
Ruddick, K.G. Ovidio, F., Rijkeboer M. (2000). Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters. Appl. Opt., 39(6), 897-912.
Willén, E. (1984). The large lakes of Sweden: Vänern, Vättern, Mälaren and Hjälmaren. In: Ecosystems of the world 23, Lakes and Reservoirs. Taub F.B. (editor).
Willén, E. (2001a). Four decades of research on the Swedish large lakes Mälaren, Hjälmaren, Vättern and Vänern: The significance of monitoring and remedial measures for a sustainable society. AMBIO: A Journal of the Human Environment, 30(8), 458-466.
Willén, E. (2001b). Phytoplankton and water quality characterization: experiences from the Swedish large lakes Mälaren, Hjälmaren, Vättern and Vänern. AMBIO: A Journal of the Human Environment, 30(8), 529-537.

Scientific publications with acknowledgment to EuRuCAS:
Podsechin, V., M. Leppäranta, Eu. Morozov, and D. Pozdnyakov. (2016). Modelling of flow, thermal regime and transport of suspended sediments in Lake Vesijärvi, Finland (in preparation).
Morozov, Eu., S. Kratzer, and G. Moore. (2016). Seasonal and spatial changes of the spectral diffuse attenuation coefficient in the NW Baltic proper. International Journal of Remote Sensing (submitted).
Morozov, Eu., S. Kratzer, and L. Pettersson. (2016). Using MODIS for retrieving primary productivity in the Baltic Sea: Algorithm validation using the HELCOM and SMHI database. International Journal of Remote Sensing (submitted).
Ben Mustapha, S., P. Philipso, S. Kratzer, N. Strömbeck. (2016). Monitoring water quality in Lake Vänern, Sweden, from space. Journal of Great Lakes Research (submitted).
Beltrán-Abaunza, J. M., Kratzer, S, and Höglander, H. (2016). Using the MERIS archive for the evaluation of spatial-temporal variability of water quality: the Himmerfjärden nitrogen experiment viewed from space. Remote Sensing Environment of Environment (submitted).
Kari E., Merkouriadi I., Kratzer S. and Leppäranta M. (2016). Spring development: a study on hydrography and water quality in Himmerfjärden estuary. Estuarine, Coastal and Shelf Sciences (submitted).

Permafrost dynamics and hydrological modelling:

The EuRuCAS research on the permafrost dynamics and hydrological modelling has covered three high-priority tasks:
o identification of vegetation changes that have recently occurred in the forest-tundra zone of Eurasia using satellite remote sensing
o understanding processes behind the changes related to the hydrological system, e.g. caused by disturbance like forest fires
o application of remote sensing in modelling for knowledge gain, parameter estimates and direct data assimilation
A total of ten peer-reviewed papers are expected: five are published, three are submitted and two are in preparation (see list at the end of this section).

Participants. Leader: Cristiane Schmullius (Friedrich-Schiller-University (FSU)); Co-Leader: Alla Yurova (NIERSC); Contributors: Shaun Quegan and Euripides Kantzas (both – University of Sheffield), Marcel Urban, Jonas Eberle and Maxim Chernetskiy (all – FSU), Lyudmila Lebedeva (NIERSC/Melnikov Permafrost Institute).

Introduction. Our current understanding of the climate system is limited and the uncertainly lies both in each its component and in the interaction between them. One scientific challenge has its origin in the nature of greenhouse gases that affect the Earth’s energy balance. Water vapour, carbon dioxide and methane molecules cycle continuously through living organisms and the products of their activity and decay. The complexity of the biosphere provides numerous possibilities for feedbacks between its components, biogeochemical cycles, biogeophysical parameters and climate. Reliable quantitative estimates of carbon cycling in the biosphere are needed to facilitate better prediction of climate system behaviour with increasing CO2 concentration (Tang et al., 2015). In addition, vegetation can affect the climate by altering radiative and heat balance, and therefore temperature regime of the atmosphere surface layer and soil, and water balance. Remote sensing is crucial source of information about the vegetation parameters. Concerning modelling, one category of the mathematical models that predict the state of the vegetation and soil is Dynamical Global Vegetation Models (DGVMs). Another group is watershed hydrological models that may be used to investigate propagation of the global scale climate signal into smaller scales and the feedbacks from those systems back to climate.

Detection of land surface changes in high northern latitudes using satellite remote sensing. Spatial-temporal mapping of surface changes with respect to albedo and land surface temperature has been performed. This study was conducted on the co-occurrence of temperature, precipitation, snow cover and vegetation greenness trends between 1981 and 2012 in the pan-Arctic region based on coarse resolution climate and remote sensing data. It has been shown that the vegetation greenness in the vegetation-growing period is characterized by a constant increase trend during the successive years.
Mapping tree properties using lidar data has been carried out. Terrestrial laser scanner (TLS) was successively used to retrieve leaf area index (LAI) due to the ability to capture structural information of canopies as 3D point cloud data (PCD). The new method was developed to produce semi-hemispherical 2D images based on PCD and operational software (Solarc7.0) was used to estimate LAI on the basis of those images. This new LAI estimation methods might be a nondestructive tool for spatially explicit calibration of LAI estimated by aerial or satellite remote sensing techniques.
Development of innovative methodology for trend analysis of different land surface parameters has been performed. High-resolution remote sensing data were utilized to map structural vegetation changes between 1973 and 2012 for a selected test region in the Northern Siberia (Urban et al., 2013, 2014; Eberle et al., 2015). An intensification of woody vegetation cover at the taiga-tundra transition area has been found. The observed co-occurrence of climatic and ecosystem changes is an example of the multi-scale feedbacks in the Arctic ecosystems.
In order to support future efforts in implementation of land data assimilation and trend analysis for various land surface parameters additional research was carried out. Its main aim was to develop a physically reliable automated approach for retrieving biophysical parameters derived from remote sensing data. This approach has to be able to fill gaps in time series of parameters and work over a wide variety of satellite sensors and observational/illumination conditions (Chernetskiy et. al. 2015a, Chernetskiy et. al. 2015b, Chernetskiy et. al. 2015c). To fulfill this aim, the Earth Observation Land Data Assimilation System (EO-LDAS) was used. As an example of a biophysical parameter, the Fraction of Photosynthetically Active Radiation (FAPAR) was chosen because of its importance as an Essential Climate Variable (ECV). Therefore a time series of FAPAR from the Multi-angle Imaging Spectro-Radiometer (MISR) data over a US FluxNet test site were retrieved (Chernetskiy et. al. 2015c). The retrieval used temporal regularization with 7 MISR cameras. Results were compared against 8 years of ground-based data and Joint Research Centre’s Two-stream Inversion Package (JRC-TIP) FAPAR products for 2001-2008.
It was confirmed that the EO-LDAS approach to temporal regularization could be used for consistent estimation of FAPAR without any in-situ information. This demonstrates that, at least for these particular sites, EO-LDAS is able to estimate absorbed fluxes relying only on multi-angular data information. Furthermore, since EO-LDAS generates results for each day of year, it is able to predict FAPAR between the dates of available satellite observations: this could be a new way for space product validation in absence of ground-based measurements.
The most interesting finding from trend analysis based on remote sensing data is a notable increase in land surface temperature and decrease in albedo over large areas of tundra-taiga transition zone in Western Siberia. Although the change probably stems from climate warming, the exact mechanism is still unclear. A working hypothesis is that it is related to the soil moisture/availability change, which may express itself in changes in the bryophyte (moss) cover and its properties.

Modelling forest fires effect on runoff from small river basins in the permafrost region. The impact of fire on daily discharges from two mountainous basins located in the permafrost region of Eastern Siberia has been investigated (Semenova et al., 2014). There were basins of the Vitimkan (969 km2) and Vitim (18,200 km2) rivers, 78% and 49% of whose areas, respectively, were affected by fire in 2003. Hydrological and meteorological data analysis suggested that the Vitimkan River basin had a rapid and profound hydrological response to wildfire in 2003 expressed through an increased summer flow of 41% (133 mm). Conversely, the larger Vitim River basin showed no significant changes in discharges after the fire. The new set of model parameters implied intensification of soil thaw, reduction of infiltration rate and evapotranspiration, and increase of upper subsurface flow fraction in summer flood events following the fire.

Application of remotely sensed data in process based hydrological and ecosystem modeling. The Earth Observation products have been used for estimation of post-fire vegetation parameters and improvement of simulations of a Dynamic Vegetation Model by assimilating field snow data and data on burned area. The parameters of the process-based hydrological model Hydrograph were first estimated for pre-fire conditions. Runoff simulations conducted for continuous pre-fire periods over 1966-2002 for the Vitimkan and over 1970-2002 for the Vitim river basins on a daily time step showed satisfactory agreement with the observed flow series of both basins. Post-fire runoff simulations showed a notable discrepancy between the modelled and observed values. The set of dynamic parameters was developed based on data analysis and post-fire landscape changes as derived from a literature review for corresponding land-surface parameters.
Field data on snow water equivalent and snow density obtained from hydrological snow surveys over Russia (Krenke, 2004) have been used to assess the performance in capturing snow dynamics of 2 Earth Observational (EO) products, GlobSnow (Luojus et al., 2011), LEGOS SWE (Zakharova et al., 2011), 4 DVMs, CLM4CN (Lawrence et al, 2011), JULES (Best et al., 2011), LPJ-WM (Wania et al., 2009) and SDGVM (Woodward and Lomas, 2004) . This enabled to quantify the accuracy of the EO products, which dictates their usability, and to evaluate snow-related model processes in DVMs. Building on these results, an interface which assimilates field and EO snow data in DVMs in order to improve the accuracy of their simulations has been created. These findings were published in (Kantzas et al., 2014).
To improve the representation of the fire regime in DVMs, EO products of burned area (Giglio et al., 2013) and image analysis algorithms have been employed in order to create a database of individual fire events over the Arctic. These fires then have been assimilated in a DVM, which gave us a more pragmatic fire representation with realistic fire size distributions. A paper with these findings has been published (Kantzas et al., 2015).

Recommendations and outlook. The following recommendations might be given for the further research in considered area:
o For understanding carbon balance watershed scale modelling might be instrumental.
o Satellite observations on a finer spatial scale might be a good supplementary tool for watershed model development and exploitation.
o The role of water regime in DGVMs deserves further research.
o Better accounting for post-disturbance vegetation recovery (effect on evapotranspiration, soil processes) has to be made both in DGVMs and watershed hydrological models.
o The mechanisms of soil ice melting in the permafrost area deserve further modelling study.
o Water body dynamics and their long-term history should be studied for more regions based on remote sensing data to assess possible methane outgassing.
o Land data assimilation is a priority area in climate modeling.
o Improved representation of radiation and thermal conduction in DGVMs is needed if the effects of fire on the permafrost active layer are to be correctly estimated.
EuRuCAS partners involved in research on this task are planning to study the optional links and feedbacks between decreasing sea ice in the Arctic and the land surface processes in tundra and boreal zone.
One of the outcomes of EuRuCas collaboration is the strengthening research links between FSU, NIESRC, Permafrost Institute in Yakutsk and Moscow State University. The joint team is now producing competitive proposals on the subject of possible release of methane in permafrost areas including the modelling thermocarst lake greenhouse gas balance.

Best, M.J. Pryor, M., Clark, D.B. Rooney, G.G. Essery, R.L.H. Menard, C.B. Edwards, J.M. Hendry, M.A. Porson, A., Gedney, N., Mercado, L.M. Sitch, S., Blyth, E., Boucher, O., Cox, P.M. Grimmond, C.S.B. and Harding, R. . (2011). The Joint UK Land Environment Simulator (JULES), model description - Part 1: Energy and water fluxes. Geosci. Model. Dev., 4, 677-699.
Giglio, L., Randerson, J.T. and van der Werf, G.R. (2013). Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4), Journal of Geophysical Research. Biogeosciences, 118, 317-328.
Krenke, A. (2004). Former Soviet Union hydrological snow surveys. NSIDC, Boulder,CO.
Lawrence, D.M. Oleson, K.W. Flanner, M.G. Thornton, P.E. Swenson, S.C. Lawrence, P.J. Zeng, X.B. Yang, Z.L. Levis, S., Sakaguchi, K., Bonan, G.B. and Slater, A.G. (2011). Parameterization Improvements and Functional and Structural Advances in Version 4 of the Community Land Model. J. Adv. Model. Earth. Sys., 3.
Luojus, K., Pulliainen, J., Takala, M., Lemmetyinen, J., Derksen, C., Metsamaki, S., and Bojkov, B. (2011). Investigating Hemispherical Trends in Snow Accumulation Using Globsnow Snow Water Equivalent Data. Proceedings of 2011 IEEE International Geoscience and Remote Sensing Symposium (IGARRS), 3772-3774.
Walker, D.A. Raynolds, M.K. Daniëls, F.J. Einarsson, E., Elvebakk, A., Gould, W.A. ... & Moskalenko, N.G. (2005). The circumpolar Arctic vegetation map. Journal of Vegetation Science, 16(3), 267-282.
Wania, R., Ross, I., and Prentice, I.C. (2009). Integrating peatlands and permafrost into a dynamic global vegetation model: 1. Evaluation and sensitivity of physical land surface processes. Global Biogeochem. Cyc., 23.
Woodward, F.I. and Lomas, M.R. (2004). Vegetation dynamics - simulating responses to climatic change. Biol. Rev., 79, 643-670.
Zakharova, E.A. Kouraev, A.V. Biancamaria, S., Kolmakova, M.V. Mognard, N.M. Zemtsov, V.A. Kirpotin, S.N. and Decharme, B. (2011). Snow Cover and Spring Flood Flow in the Northern Part of Western Siberia (the Poluy, Nadym, Pur, and Taz Rivers). J. Hydrometeorol., 12, 1498-1511.

Scientific publications with acknowledgement to EuRuCAS:
Kantzas, E., Quegan, S., Lomas, M., & Zakharova, E. (2014). Evaluation of the snow regime in dynamic vegetation land surface models using field measurements. The Cryosphere, 8, 487-502.
Kantzas, E.P. Quegan, S., and Lomas, M. (2015). Improving the representation of fire disturbance in dynamic vegetation models by assimilating satellite data: a case study over the Arctic. Geosci. Model Dev., 8, 2597-2609.
Semenova, O., Lebedeva, L., Volkova, N., Korenev, I., Forkel, M., Eberle, J., & Urban, M. (2014). Detecting immediate wildfire impact on runoff in a poorly-gauged mountainous permafrost basin. Hydrological Sciences Journal, 141217125340005.
Urban, M., J. Eberle, C. Hüttich, C. Schmullius & M. Herold (2013). Comparison of satellite derived Land Surface Temperature and Air Temperature from meteorological station on pan-arctic scale. Remote Sensing, 5, 2348-2367.
Urban, M., M. Forkel, J. Eberle, C. Schmullius & M. Herold (2014). Pan-arctic climate and land cover trends derived from multi-variate and multi-scale analysis (1981-2012). Remote Sensing, Special Issue on Remote Sensing of Changing Northern High Latitude Ecosystems, 6, 3, 2296-2316.
Eberle, J., R. Adewoye, C. Hüttich & C. Schmullius (2015). From global observations to local information: The Earth Observation Monitor. Environmental Modelling & Software (submitted).
Tang, J., Poska, A., Yurova, A.Yu. Miller, P.A. Olin, S., G. Schurgers (2015). Modelling dissolved organic carbon export in a subarctic catchment using a dynamic ecosystem model (submitted to Geophysical Model Development).
Chernetskiy, M., Gobron, N., Gomez-Dans, J., Lewis, P., Schmullius, C. (2015a). Earth Observation Land Data Assimilation System (EO-LDAS) regularization constraints over Barrax site. Chapter in: H. Balzter, Ed., Earth Observation for Land and Emergency Monitoring: Innovative concepts for environmental monitoring from space. Wiley Publishing House (accepted).
Chernetskiy, M., Gobron, N., Gomez-Dans, J., Lewis, P., Schmullius, C. (2015b). Simulations of CHRIS/PROBA spectra with Earth Observation Land Data Assimilation System using MISR data. Advances in Space Research (in preparation).
Chernetskiy, M., Gobron, N., Morgan, O., Truckenbrodt, S., Gomez-Dans, J., Lewis, P., Schmullius, C. (2015c). EO-LDAS Temporal Regularization for estimation of FAPAR over an agriculture test site using MISR multiangular information. Remote Sensing (in preparation).

Socio-economic impact of climate change in the Arctic and Sub-Arctic:

Summary. The EU FP7 EuRuCAS activities related to the socioeconomic impacts of climate change in the Arctic and Sub-Arctic were performed along two main research lines: Research line 1 – Economic modelling; and Research line 2 – Risk management and risk governance. A total of five publications (four peer-reviewed papers and one paper in a conference proceedings volume) are expected: two of them are published, and three are under preparation (see list at the end of this section).

Participants. Leaders: Carlo Jaeger (Global Climate Forum (GCF)) and Dmitry Kovalevsky (NIERSC); Contributors: Klaus Hasselmann (Max Planck Institute for Meteorology (MPIM)/GCF), Armin Haas (GCF), Vilena Valeeva (GCF), Timo Vihma (FMI), Adriaan Perrels (FMI), Karoliina Pilli-Sihvola (FMI), Stein Sandven (NERSC), Lasse Pettersson (NERSC), Ola M. Johannessen (NERSC), Oldag Caspar (Germanwatch).

Introduction. The Arctic is experiencing significant socioeconomic transformations, driven by interacting forces of climate and environmental changes, developments in the global energy market, transport and technologies. Changes in the Arctic environment create risks for the local infrastructure, people’s health and livelihoods, and biodiversity. On the other hand, it is expected that environmental changes will create new opportunities for the socioeconomic development of the Arctic, facilitating exploitation of its natural resources, and shipping in the Arctic waters (AMSA, 2009). Increasing business activity in the Arctic in its turn is also connected with a number of risks and uncertainties: ecological risks, geological uncertainties, uncertainties regarding future climate conditions, energy market and relations among main Arctic states and actors.
To deal with these multiple interacting uncertainties, it is required to (i) develop comprehensive climate-environmental-economic-energy models to assess the dynamics of coupled socio-natural systems; and (ii) integrate knowledge from different fields of expertise. In this respect, international scientific cooperation as well as inclusion of stakeholders in developing options for risk governance and risk management is crucial. Stakeholders, as referred here, are those who affect or are affected by changes in the Arctic. Main stakeholder groups in this respect are: business actors (resource extraction companies, shipping companies, insurance companies etc), state agencies, NGOs, local communities. Engagement of stakeholders in the research is a time-consuming and many-stage process, which requires following steps: identification of stakeholders, making contacts, building trust, conducting interviews and workshops in order to reveal and analyze their perceptions, ideas and communicate science.

Research line 1: Economic modelling:
Innovative approaches to climate-economic modelling and their contribution to reframing the climate mitigation problem. The ultimate strategy for combatting the global climate change, as well as the Arctic regional climate change, is the development and implementation of efficient climate mitigation policies. The paper by Hasselmann et al. (2015) prepared within EU FP7 EuRuCAS and EU FP7 COMPLEX projects argues that innovative approaches to climate-economic modelling are urgently needed for comprehensive assessment of climate mitigation policies. Climate change can aggravate other contemporary societal and environmental problems, as is widely recognized; but actions to mitigate climate change can also contribute significantly to their resolution – an opportunity that has been widely overlooked. An economic model presented in (Hasselmann et al., 2015) (freely downloadable from the MADIAMS model family homepage maintained at the Global Climate Forum website ( and also described in detail in the Supplementary Information to the paper available online at Nature Geoscience website) is developed within an actor-based system dynamics approach to economic modelling (Hasselmann, 2013; Hasselmann and Kovalevsky, 2013) and assesses the potential efficiency of external green investment for the resolution of the Euro crisis.

Integrated Assessment modelling of global impacts of shrinking Arctic sea ice – the “Arctic feedback model”. It is well known that on-going global climate change is amplified in the Arctic region, and regional climate changes in the Arctic are projected to induce far-reaching economic impacts going well beyond high northern latitudes and affecting the global economy. With potentially easier access to its abundant hydrocarbon resources under projected conditions of shrinking sea ice, the Arctic may there be expected to substantially affect future global energy markets.
The dynamics of the coupled climate–socioeconomic system and its possible futures can be explored by Integrated Assessment Models (IAMs). To assess the potential impacts of shrinking Arctic sea ice on global energy markets, an actor-based system dynamics IAM is developed to explore the effects of exhaustibility of fossil fuel resources (in the Arctic and globally). The model includes a positive nonlinear feedback through which global warming and shrinking sea ice in the Arctic leads to intensification of the offshore extraction of hydrocarbons, thereby enhancing global warming even further (“the Arctic feedback”). One of the objectives of this modelling study is to explore the strength and the dynamic performance of this positive feedback, and the manner in which the feedback amplifies various uncertainties in the system under study. Modelling results presented in (Kovalevsky and Hasselmann, 2014; Kovalevsky et al., 2016a) suggest that “the Arctic feedback” is significant and should be included in other existing IAMs as well.
The same “Arctic feedback” has been also assessed in the framework of EU FP7 EuRuCAS within a mainstream economic modelling paradigm – a theory of exhaustible natural resources (Dasgupta and Heal, 1979). The model by Withagen (1994) was taken as the starting point, and the parameterization of Arctic sea ice sensitivity to global mean temperature change was adopted from (Winton, 2011). Overall, the results of assessment of “the Arctic feedback” obtained within the mainstream economic modelling approach (Kovalevsky, 2016) are qualitatively the same as within the innovative actor-based system dynamics modelling approach (see above).

Modelling the impacts of longer navigation periods and of investment in port infrastructure on transit Arctic shipping. A model world consisting of two big trading centers (“Europe” and “Asia”) connected through two alternative shipping routes (the Arctic route and the Suez route) is considered. Initially, the Arctic route is uncompetitive, and all traffic is through the Suez route. Investments can be made by relevant model actors in Arctic port infrastructure, in other navigation infrastructure/services (like weather forecasts), and also in construction of Polar class vessels. Exogenous increase of length of the Arctic navigation (projected by global climate models; see section of this report) and the above mentioned investments of model actors are both favorable to making the Arctic route competitive. The model is tailored to project plausible investment behavior of key economic actors under uncertain future regional climate change (Kovalevsky et al., 2016b).

Research line 2: Risk management and risk governance:

Sustainable modes of Arctic resource-driven transformations. Through the EuRuCAS project, researchers from the Global Climate Forum (GCF) and the Institute of Advanced Sustainability Studies (IASS, Germany) have had a unique opportunity to come to Russia and to build contacts with scientists from NIERSC, the Institute of World Economy and International Relations of the Russian Academy of Sciences (IMEMO RAN), the Higher School of Economics (HSE) etc.
Scientific cooperation has to a great extent been coupled to the SMART (Sustainable Modes of Arctic Resource-driven Transformation) research project ( which was developed at IASS in Potsdam, in which GCF is also involved. The SMART project gathers an interdisciplinary team of researchers from the social and natural sciences such as geography, law, economics, political science, atmospheric physics and chemistry. The overarching goal of the SMART project is to contribute to scientific understanding and informed, effective stakeholder participation in decision-making at multiple levels, thus enabling pathways to more sustainable development of the Arctic and beyond. SMART also specifically looks into the interdependencies and feedback loops between Arctic and non-Arctic systems and processes and aims to establish and strengthen so far missing stakeholder links from within and outside the Arctic. Given the fact that Russia is a very important Arctic player, engagement of Russian stakeholders is an essential but very challenging part of the SMART project. It would have been impossible to reach this goal without engaging with Russian partners through the EuRuCAS cooperation, which was a fantastic platform to interact with Russian researchers. Thanks to EuRuCAS, the SMART team had a great opportunity to come to Russia, meet Russian stakeholders, conduct interviews and organize stakeholder-engaging events.
Within the EuRuCAS framework, the workshop “Changes in the Russian Arctic and Global-Local Feedback Processes” took place in Moscow on 09 April 2014. The workshop was organized by GCF and IASS in cooperation with researchers from NIERSC and IMEMO RAN. Russian and European researchers from multiple natural and social science backgrounds as well as representatives from civil society, government and local Arctic organizations presented and discussed various issues in relation to the ongoing changes in the Russian Arctic. A special focus was put on the role of the climatic and ecological changes in a warming Arctic environment, energy markets and their role for resource development in the Arctic, and local effects and consequences of resource development. The workshop was very successful and was an important step in the development of collaboration between Russian and European researchers and stakeholders within the SMART project. Input from this stakeholder workshop helped to frame and design concrete research questions to be addressed in future IASS and GCF Arctic research. The workshop report is published on the EuRuCAS website (
In climate policy, computer modelling tools (like IAMs) play a big role. However, today, the most influential model families have got certain limitations and fail to meet all relevant requirements and expectations of policy makers and broad public. In particular, they make it hard and often impossible to identify green growth opportunities without which climate policy can hardly be effective.
The Climate Policy Modeling workshop was conducted by GCF at NIERSC on 24-26 June 2015. The goal of the workshop was to gather European and Russian scientists and explore possibilities to advance climate policy modelling. Workshop participants discussed strengths and weaknesses of neoliberal climate policy models, ways to transform them and how such progress can build on work performed by organizations and researchers involved in EuRuCAS.
Following the Climate Policy Modeling workshop, a next EuRuCAS workshop “Modelling Green Growth Options for Russia” was initiated and organized by the GCF at NIERSC on 23 October 2015. A group of Russian and German scientists and experts gathered together to elaborate a joint research proposal to be submitted by NIERSC, GCF, IASS, and Germanwatch to the German Ministry of the Environment in 2016. The research proposal will be focused on modelling green growth options for Russia and Germany with case studies that include options for development of renewable and ecotourism in the Arctic and sub-Arctic regions. Within the workshop, a teleconference with Prof. Dr. mult. K. Töpfer, former Federal Minister of the Environment in Germany and patron of the German-Russian Raw Materials Forum, was held to discuss the prospects for research cooperation on the planned proposal.

Analysis of stakeholder perspectives within adaptation actions for a changing Arctic. Vilena Valeeva (GCF) was invited by researchers of the Russian Academy of Science to participate in one of the research projects of the Arctic Council with the title “Adaptation Actions for a Changing Arctic (AACA)”. This invitation is one of the results of cooperation efforts conducted by the GCF within EuRuCAS. The goal of the AACA project is to understand the interactions of different drivers of Arctic change and to find optimal ways to adapt to them. Within this project, Vilena Valeeva participated in preparation of reports on Barents and Bering/Beaufort/Chukchi regions, by analyzing local implications of changes, stakeholder perspectives of changes as well as adaptation policies of Russian Arctic regions. The AACA reports will be published in 2017 and presented at the ministerial meeting of the Arctic Council.

Recommendations and outlook
o Further advancement of climate-economic modelling work would help policy makers to identify promising green growth options that existing model architectures have a hard time to represent.
o Improvement of risk governance with respect to business activities in such a vulnerable region like Arctic requires further international and transdisciplinary projects which will cover different aspects as sea ice trends, climate and weather influences, air pollution, local, regional and global economic, political and social developments.
o Further research on Arctic sustainability issues has to be conducted based on recommendations from stakeholders that were engaged in Arctic research during the EuRuCAS project.
o Studies of international cooperation in the Arctic are needed with special attention to how scientific cooperation and similarities/differences in understanding of the Arctic issues affect intergovernmental, business and cultural cooperation on circumpolar issues.


AMSA (2009). Arctic Marine Shipping Assessment 2009 Report. The Arctic Council.
Dasgupta, P.S. and G.M. Heal (1979). Economic Theory and Exhaustible Resources. Cambridge University Press.
Hasselmann, K. (2013). Detecting and responding to climate change. Tellus B, 65, 20088.
Hasselmann, K., and D.V. Kovalevsky (2013). Simulating animal spirits in actor-based environmental models. Environmental Modelling & Software, 44, 10-24.
Winton, M. (2011). Do climate models underestimate the sensitivity of Northern Hemisphere sea ice cover? Journal of Climate, 24, 3924-3934.
Withagen, C.A.A.M. (1994). Pollution and exhaustibility of fossil fuel resource. Resource and Energy Economics, 16(3), 235-242.

Scientific publications with acknowledgement to EuRuCAS:
Hasselmann, K., R. Cremades, T. Filatova, R. Hewitt, C. Jaeger, D. Kovalevsky, A. Voinov, and N. Winder (2015). Free-riders to forerunners. Nature Geoscience, 8, 895-898.
Kovalevsky, D.V. and K. Hasselmann, (2014). Integrated Assessment modelling of global impacts of shrinking Arctic sea ice. Proceedings of All-Russian conference with international participation “State of Arctic seas and territories under conditions of climate change”, 18-19 September 2014, Arkhangelsk, Russia, 79-80.
Kovalevsky, D.V. (2016). Shrinking Arctic sea ice and its impacts on global energy markets: an assessment from perspectives of the theory of exhaustible natural resources (in preparation).
Kovalevsky, D.V. K. Hasselmann, and L.H. Pettersson (2016a). Integrated Assessment modelling of impacts of shrinking Arctic sea ice on global energy markets (in preparation).
Kovalevsky, D.V. A. Perrels, K. Pilli-Sihvola, T. Vihma, S. Sandven, et al. (2016b). The impact of longer navigation periods and of investment in port infrastructure on transit Arctic shipping (in preparation).

Potential Impact:
The major, strategic, impact of EuRuCAS Project is on the strengthening and coordination of research cooperation between European Union including Member States and Associated Countries and Russia in the Arctic and Sub-Arctic climate and environmental research including socioeconomic consequences of Arctic warming, area, which is critically important for both sides. Many research topics related to climate and environment are global and regional in character and cannot be solved nationally or locally. During EuRuCAS Project the International Nansen Centre in St. Petersburg (NIERSC) became, in fact, the focal institution for this EU-Russia cooperation and its catalyst. By enhancement of its research infrastructure, opening its institutional arrangements to new partners from EU member States and Associated Countries, establishing solid research ties with EuRuCAS partners and initiating new joint research projects NIERSC secured the continuation of this role for the future. To support this statement, it may be mentioned that during the project six new Associated Partners joint to NIERSC, 16 joint proposals have been submitted under various calls and four of them have been funded. This present and future NIERSC’s role is also gained by wide network of leading Russian and European institutions established by the Nansen Centre. New co-financing mechanism established by the Russian Ministry for Education and Science for funding Russian teams participating in EU Horizon 2020 Programme opens excellent opportunities for Russian research institutions to be partners in and contributors to research within this programme in topics where Russians have significant expertise and can contribute to develop research excellence in Europe. And NIERSC is going to actively participate in EU H2020 Calls.
Thus, during EuRuCAS Project strategic R&D partnership has been established between institutions in Europe and Russia, contributing to building critical research mass needed to solve societal problems related to climate and environment changes in high northern latitudes.
EuRuCAS has stimulated development of socio-economic research addressing impact of climate change on environment and society in high northern latitudes. This research is important for solving major societal challenges in Europe as outlined in its 2020 Strategy (
European research institutions – partners in EuRuCAS, have transferred competence and expertise to NIERSC, and vice versa, contribution to an open and competitive research and free circulation of researchers.
During EuRuCAS, young scientists from Europe and Russia (NIERSC) have been given opportunity to work together at the NIERSC premises on its ongoing research projects and at partner institutions, as well as at the workshops and summer school. This has enabled development of joint long-term research plans and new projects with participation from Russian and European institutions.
Impact on EU’s Arctic research. EuRuCAS has established trough NIERSC the cooperation with Russian institutions, which can provide valuable contribution to EU’s Arctic research. The EU has strong interest in developing the Arctic natural resources, which are believed to host large amounts of oil, natural gas and other mineral resources. Most of the discovered resources are either on the territory, or within the exclusive economic zones of the Arctic states where the largest part belongs to Russia. Any exploration or exploitation activities would be carried out in accordance with the highest environmental standards of EU. This requires extensive knowledge about the status of the environment and its changes caused by global warming and human activities. It is not possible to build up this knowledge without strong involvement of Russian institutions. Research activities in the framework of EuRuCAS and achieved S&T results have already contributed to increasing knowledge about the status of the environment and its changes in the Arctic and Sub-Arctic. Moreover, due to further continuation of established cooperation within new, initiated during EuRuCAS, and future EU-Russia research projects the existing knowledge about the expected Arctic environment and climate changes will be widen.

EuRuCAS Consortium has been working actively on the disseminating information on the project and its results including scientific knowledge and findings. The dissemination activity has been aimed at providing the possibly largest coverage of scientific community, stakeholders, policy makers and public. This activity included:
Project logo. The EuRuCAS logo provided a good recognisability of the project and its identification by researchers and stakeholders.
Project website. The EuRuCAS website ( has been regularly updated. Its open part contains description of the project, pdf-copies of the project brochure, scientific and popular papers, presentations at the workshops, summer school and conferences etc.
Project brochure. The EuRuCAS brochure has been widely distributed at the workshops, summer school, international conferences and other events.
Presentations at the workshops and conferences. The EuRuCAS partners actively participated in a number of international conferences, symposia and workshops with the oral and poster presentations disseminating information on the project and its collaborative and scientific results for the wide audience of scientists, stakeholders and policy makers. These events included the most important gatherings such as the European Geosciences Union General Assembly, American Geophysical Union Fall Meeting, Arctic Science Summit Week and other.
Publication of scientific papers in the peer-reviewed journals. A number of scientific papers have been published in the peer-reviewed journals including Nature Geoscience and Geophysical Research Letters with the acknowledgements to EuRuCAS. In spite of the type of the project was as Supporting Actions, a number of important research results and finding have been achieved what has indicated the effectiveness of the established cooperation between NIERSC and other EuRuCAS partners.
Interviews and publication of popular articles. Several interviews have been given and popular papers have been published by the EuRuCAS Coordinator and participants including interview and paper by Leonid Bobylev “Russia, research and cooperation” in the “Pan European Networks: Science & Technology”, issue 4, September 2012.
The exploitation of EuRuCAS results is being performed now and will be performed in the future mostly in the frame of continuation of established during EuRuCAS project cooperation between NIERSC and other project partners as well as new involved institutions. This continued cooperation is secured by new joint research projects initiated and got funded within EuRuCAS and by opened NIERSC’s institutional arrangements to new partners.
Additional option for continuation of established cooperation is the Pan-Eurasian Experiment (PEEX) ( commenced in 2012. This is an extensive international programme for development of research infrastructure, research and education with the University of Helsinki, hosting the project office, NIERSC, Finnish Meteorological Institute and several other Russian, EU and Chinese participants. PEEX focuses on climate change with its consequences in the northern Eurasian boreal and tundra zone. Russian partners in addition to NIERSC include the Institute of Geography of Moscow State University, AEROCOSMOS, and the Institute of Atmospheric Optics of Siberian Branch of the Russian Academy of Science. PEEX programme aims to bridge with key organizations in the northern and Arctic regions such as the Arctic Council, Future Earth, IPCC, GEOSS, and Digital Earth.

List of Websites:

EuRuCAS public website address is
Coordinator: Dr. Leonid Bobylev, Nansen International Environmental and Remote Sensing Centre (NIERSC), 14th Line 7, VO, 199034 St. Petersburg,
Russian Federation.
Phone: +7 812 324 5101; E-mail: