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A Palaeoreanalysis To Understand Decadal Climate Variability

Periodic Reporting for period 4 - PALAEO-RA (A Palaeoreanalysis To Understand Decadal Climate Variability)

Okres sprawozdawczy: 2023-04-01 do 2023-09-30

Climatic variations at decadal scales, such as phases of accelerated warming, weak monsoons, or widespread subtropical drought, have profound effects on society and the economy. Understanding such variations re-quires insights from the past. However, no data sets of past climate are available to study decadal variability of large-scale climate with state-of-the-art diagnostic methods. Previously available data sets were limited to statistical reconstructions of local or regional surface climate. The PALAEO-RA project produced the first ever comprehensive, 3-dimensional, physically consistent reconstruction of the global climate system at a monthly scale for the past six centuries. This palaeoreanalysis is based on combining information from early instrumental measurements, historical documents, and proxies (e.g. tree rings) with a large ensemble of climate model simulations. To achieve this novel combination, a completely new data assimilation system for palaeoclimatological data was developed. The product is a family of three data sets, termed ModE-RA (the full reanalsysis using the full model simulations and all observations), ModE-RAclim (a reanalysis based only on a model climatology but all observations) and ModE-Sim (the full model simulations without assimilating observations). Analysing all three allows disentangling the the role of observations and model in the full product. The data sets produced in this project allow studying past climatic variations in greater detail than before, providing a multi-variable, 3-dimensional view of past climatic anomalies and allowing to address dynamical causes behind climatic anomalies. We analysed decadal cold periods, decadal drought periods, variations in the Indian monsoons, and effects of volcanic eruptions. Theses analyses provide new insights into the processes governing decadal variability of weather and climate.
In the first project phase we compiled observations, i.e. early instrumental measurements, documentary climate data, and proxy time series. This work started with global inventories of such data, the compilation of already electronically available data, and then data rescue work for early instrumental data (focusing on data from the 18th and early 19th century) and for documentary data. The data sets were published separately. In order to use observations in an assimilation approach, forward models need to be developed that extract a documentary or proxy series form the model state. This work was also done in the first project phase. Simultaneously, the climate model simulations were set up. They required monthly sea-surface temperatures as a boundary condition. Such a data set was not available and therefore an esnemble of reconstructions was performed for the past millennium. Likewise, ensembles of other boundary conditions were generated (e.g. volcanic aerosols).
The atmospheric model ECHAM6 was set up and simulations were performed for the period 1420-2009, in different time slices. In addition to ca. 36 low-resolution simulations (2°x2°), we also performed 5 high-resolution simulations (1°x1°). Additional simulations were performed for each volcanic eruption, such that larger ensembles are available. The assimilation scheme was further developed. Novel features include, among others, a partitioning in three cycles (progressing from long to short observation series). This allows shorter time series to be debiased against the intermediate results after assimilating the long series. The product eventually was assimilated in three cycles. Another novelty is the observation feedback archive that contains all information in the observaiton space (the observations themselves with all metadata, all quality information background and analysis departures, etc.). Further reconstruction products were generated, e.g. one reconstruction based entirely on phenological observations. Within the project and in collaboration with other projects, several analyses of climate variability could be performed. Climate variability in the early 19th century was analysed and specifically the effects of the Tambora eruption in 1815. The project also analysed decadal changes in flood frequency in the 19th century as well as past internannual-to-decadal droughts in the USA and their relation to atmospheric circulation. Furthermore, we analysed the causes of climatic changes since the Little Ice Age, finding that several volcanic eruptions in a short period can have particularly long-lasting effects on the climate system.
All data sets are publisched in recognized repositories. An extended inventory of early instrumental data was published and the data (compiled as well as newly rescued) were published as H-CLIM data set. Similarly, for the documentary data an extensive inventory was published as well as the compiled and rescued data set DOCU-CLIM. The compiled observations extend the currently available data sets for climate reconstructions by a large amount. The model simulatoins (ModE-Sim) and reconstructions (ModE-RA and ModE-RAclim) are also published in repositories, as are various other usefuly data sets produced in the project (e.g. Bayesian reconstructions based entirely on phenological observations). The final reconstructions are accessible via a web-app (http://climeapp-modera.unibe.ch:3838/(odnośnik otworzy się w nowym oknie)) that allows statistical analyses online.
Some of the scientific analyses performed in this project triggered wide media attention. This concerns work on the volcanic origin of the last phase of the Little Ice Age in the early 19th century, work on decadal cold periods, and work on decadal variations on floods in Europe. Results were presented at conferences, and so far close to 75 publications have been written. We were involved in teaching several Summer Schools and developed an e-learning tool. We also published a popular science book (open access) on Alexander von Humboldt and the making of climate science.
The project went far beyond the state of the art in several respects. The inventory of early instrumental data is the first of its kind and will be useful for future efforts in climate reconstruction, but also a resource for historians. The data digitising effort was substantial. In this project alone 7155 station years were digitised. The same is true for the inventory of documentary data. Rather than a handful of series, we now have 621 documentary series (again, many were rescued in this project). The data assimilation scheme has several novel features, and the family of final data sets is far beyond the state of the art. The project also went beyond the state of the art in terms of analyses. A particular achievement was the publication of an analysis of the causes of climatic changes since the Little Ice Age, which caught media attention.
Cold season (Oct-May) land temperature anomalies 30-70°N since 1700 from phenological observations
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