Periodic Reporting for period 1 - STARGATE (reSilienT fARminG by Adaptive microclimaTe managEment)
Reporting period: 2019-10-01 to 2021-03-31
STARGATE develop’s a breakthrough, multiscale and holistic climate-smart agriculture methodology, capitalizing innovations in the field of microclimate and weather risk management and in the field of landscape design. It is based on Earth Observation, weather/climate intelligence and IoT technologies to support a more effective farm/parcel management and related options for adaptation to climatic changes, local and regional policy formulation leading to better landscape management, protection against climatic risks and implementation related to mitigation on microclimate changes. Public-Private Partnership is a living paradigm for STARGATE implementation. STARGATE implements the PPP model using the Living Lab approach, by connecting research organization, policy-making organization, ICT companies, farmers and other stakeholders to shape a Climate-Smart Agriculture (CSA) multi‐actor regional framework. Moreover, STARGATE study the benefits of applying agri‐environmental‐climate technical solutions to achieve sustainable agricultural development at the field and landscape level including livestock farming and agroforestry. This means to support farm management modernization and at the same time, this allows the understanding of the underlying ecological factors that shape the rural landscape. STARGATE is leveraging access to these data and climate-smart decisions tools to foster easy and affordable adoption by farm management and policymaking bodies.
During the 1st reporting period of the project, STARGATE focused and worked on:
1) The development of the STARGATE’s community through the engagement of the pilot stakeholders: A strong stakeholder community have been developed consisted of farmers, farmers associations, agronomists, water managers, public sector agencies, government, agri‐businesses, civil society organizations and researchers/experts.
2) The definition of the STARGATE pilot case studies through the active participation of the pilot stakeholders/users: 16 use cases have been identified covering different aspects of the crop and livestock production, as well as different agroclimatic zones and user segments.
3) The understanding of the services/user requirements for weather/climate information in the pilots, as well as on the needs and challenges on the adoption of climate-smart agriculture technologies from the pilots.
4) The understanding of pilot data requirements and defining the STARGATE data protocol collection: A detailed analysis of the use cases from a data management perspective that based on them the data collection protocols of the STARGATE data management platform is designed of.
5) The development of an atmospheric data assimilation system: A workflow chain for an atmospheric data assimilation system has been developed. Satellite and ground‐based observations are pre‐processed and ingested into the assimilation system to produce high-quality analysis fields. These are then the starting point of the forecasting model, which subsequently produces weather forecasts at high spatial resolutions. The coupled system of analysis/forecasts is deployed for two separate domain areas covering all pilot sites.
6) The development of a multimodel ensemble numerical weather prediction system: A multi‐model ensemble was created from the operational weather prediction models of METEOBLUE, AUTH and AGROAPPS. Both AUTH and AGROAPPS utilize the WRF modelling system but with different setup and parametrizations while METEOBLUE is operating the NMM/NEMS system. The medium-range forecasts, of up to 7 days are first brought to the same grid with the help of the MET software utilities and then combined into a multi‐model ensemble, monitored with the help of ensemble scores and statists against verifying observations.
7) The development of Sub-seasonal to seasonal climate predictions system: A Sub-seasonal to seasonal climate prediction system has been developed. Depending on the type of the variable, the observations and hindcast data a calibration methodology is applied and the predicted data are presented in a meaningful way of probabilities and anomalies that can guide the decision process chain of the agricultural sector on the desired time scales.
8) The development of a crop-specific risk analysis/monitoring/prediction method for the pilots based on historical climatic data: Several climate risk scenarios have been developed for each pilot use case based on extreme temperatures, precipitation, solar radiation, soil moisture, wind and crop type.
9) The development of Agroclimatic indicators for each pilot site: A number of 16 different agro-climatic indicators have been developed that try to take into account all the aspects of climate impact on the agricultural production of each pilot site.
10) The climatological analysis of past and future climate conditions of the pilot areas: A climatological analysis for each use case has been performed in order to identify climatic trends and assessing the impact of anthropogenic global warming in the pilot sites. The climatic analysis was referred to temperature, precipitation, relative humidity, evapotranspiration, solar radiation and wind.
11) The design of the Strategic and tactical climate-smart decision tools: A suite of Strategic and Tactical Decision Support Tools has been designed for STARGATE. These tools will be used to support policymakers, farmers and agricultural consultants to use agricultural inputs and energy more efficiently while reducing agricultural emissions and preserving the environment.
12) The development of a land/crop suitability methodology: A Land/Crop suitability methodology have been developed that will be used by STARGATE for efficient land-use planning and for crop variety selection to enhance the adaptability of the farming sector in the changing climate.
13) The development of the multi-actor validation framework: STARGATE establishes the fundamental concepts and methods for setting up, implementing and monitoring the participatory process that will be carried out in all pilot areas during the whole project lifetime.
14) The effective dissemination and communication of the project results
1) The development of the STARGATE’s community through the engagement of the pilot stakeholders: A strong stakeholder community have been developed consisted of farmers, farmers associations, agronomists, water managers, public sector agencies, government, agri‐businesses, civil society organizations and researchers/experts.
2) The definition of the STARGATE pilot case studies through the active participation of the pilot stakeholders/users: 16 use cases have been identified covering different aspects of the crop and livestock production, as well as different agroclimatic zones and user segments.
3) The understanding of the services/user requirements for weather/climate information in the pilots, as well as on the needs and challenges on the adoption of climate-smart agriculture technologies from the pilots.
4) The understanding of pilot data requirements and defining the STARGATE data protocol collection: A detailed analysis of the use cases from a data management perspective that based on them the data collection protocols of the STARGATE data management platform is designed of.
5) The development of an atmospheric data assimilation system: A workflow chain for an atmospheric data assimilation system has been developed. Satellite and ground‐based observations are pre‐processed and ingested into the assimilation system to produce high-quality analysis fields. These are then the starting point of the forecasting model, which subsequently produces weather forecasts at high spatial resolutions. The coupled system of analysis/forecasts is deployed for two separate domain areas covering all pilot sites.
6) The development of a multimodel ensemble numerical weather prediction system: A multi‐model ensemble was created from the operational weather prediction models of METEOBLUE, AUTH and AGROAPPS. Both AUTH and AGROAPPS utilize the WRF modelling system but with different setup and parametrizations while METEOBLUE is operating the NMM/NEMS system. The medium-range forecasts, of up to 7 days are first brought to the same grid with the help of the MET software utilities and then combined into a multi‐model ensemble, monitored with the help of ensemble scores and statists against verifying observations.
7) The development of Sub-seasonal to seasonal climate predictions system: A Sub-seasonal to seasonal climate prediction system has been developed. Depending on the type of the variable, the observations and hindcast data a calibration methodology is applied and the predicted data are presented in a meaningful way of probabilities and anomalies that can guide the decision process chain of the agricultural sector on the desired time scales.
8) The development of a crop-specific risk analysis/monitoring/prediction method for the pilots based on historical climatic data: Several climate risk scenarios have been developed for each pilot use case based on extreme temperatures, precipitation, solar radiation, soil moisture, wind and crop type.
9) The development of Agroclimatic indicators for each pilot site: A number of 16 different agro-climatic indicators have been developed that try to take into account all the aspects of climate impact on the agricultural production of each pilot site.
10) The climatological analysis of past and future climate conditions of the pilot areas: A climatological analysis for each use case has been performed in order to identify climatic trends and assessing the impact of anthropogenic global warming in the pilot sites. The climatic analysis was referred to temperature, precipitation, relative humidity, evapotranspiration, solar radiation and wind.
11) The design of the Strategic and tactical climate-smart decision tools: A suite of Strategic and Tactical Decision Support Tools has been designed for STARGATE. These tools will be used to support policymakers, farmers and agricultural consultants to use agricultural inputs and energy more efficiently while reducing agricultural emissions and preserving the environment.
12) The development of a land/crop suitability methodology: A Land/Crop suitability methodology have been developed that will be used by STARGATE for efficient land-use planning and for crop variety selection to enhance the adaptability of the farming sector in the changing climate.
13) The development of the multi-actor validation framework: STARGATE establishes the fundamental concepts and methods for setting up, implementing and monitoring the participatory process that will be carried out in all pilot areas during the whole project lifetime.
14) The effective dissemination and communication of the project results
STARGATEs contribution beyond the state‐of‐the‐art in applied climatic data solutions is the implementation of analytics models to support local and regional policy formulation and implementation related to mitigation on microclimate changes. Once the policy development process expands the evidence base and data sources beyond the traditional approach, there will be a need for global data sets for comparative analysis including meteorological, climatic analysis, satellite data sources to improve decision-making processes. STARGATE will leverage access to these data and its climatic platform including developed model platforms to foster easy adoption by policy-making bodies. STARGATE provides innovative components for the visualization of big data with an emphasis on geospatial visualization and dynamic charting. Additionally, the project has been designed so that its results may be further developed in other projects, or adapted to broader contexts (i.e. agro‐food industry, climate adaptations, food security, precision farming, etc), providing opportunities for influencing policies in a wide range of issues, so that project results last longer and benefit more interested parties.