Interpolative mapping of mean precipitation in the Baltic countries by using landscape characteristics

Maps of the long-term mean precipitation involving local landscape variables were generated for the Baltic countries, and the effectiveness of seven modelling methods was compared. The precipitation data were recorded in 245 meteorological stations in 1966–2005, and 51 location-related explanatory variables were used. The similarity-based reasoning in the Constud software system outperformed other methods according to the validation fit, except for spring. The multivariate adaptive regression splines (MARS) was another effective method on average. The inclusion of landscape variables, compared to reverse distance-weighted interpolation, highlights the effect of uplands, larger water bodies and forested areas. The long-term mean amount of precipitation, calculated as the station average, probably underestimates the real value for Estonia and overestimates it for Lithuania due to the uneven distribution of observation stations

Wintertime Greenhouse Gas Fluxes in Hemiboreal Drained Peatlands

Funding Information: Funding: This study was supported by the Estonian Research Council (IUT2-16 and PRG352); the EU through the European Regional Development Fund (Centre of Excellence EcolChange, Estonia) and by the Estonian State Forest Management Centre (projects LLOOM13056 “Carbon and nitrogen cycling in forests with altered water regime “, 2013–2016 and LLTOM17250 “Water level restoration in cut-away peatlands: development of integrated monitoring methods and monitoring”, 2017–2023).Peer reviewedPublisher PD

Characteristics of Temperature and Humidity Inversions and Low-Level Jets over Svalbard Fjords in Spring

Peer reviewe

Recent Change-Atmosphere

Non peer reviewe

Climate change in the Baltic Sea region : a summary

Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge of the effects of global warming on past and future changes in climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere. Based on the summaries of the recent knowledge gained in palaeo-, historical, and future regional climate research, we find that the main conclusions from earlier assessments still remain valid. However, new long-term, homogenous observational records, for example, for Scandinavian glacier inventories, sea-level-driven saltwater inflows, so-called Major Baltic Inflows, and phytoplankton species distribution, and new scenario simulations with improved models, for example, for glaciers, lake ice, and marine food web, have become available. In many cases, uncertainties can now be better estimated than before because more models were included in the ensembles, especially for the Baltic Sea. With the help of coupled models, feedbacks between several components of the Earth system have been studied, and multiple driver studies were performed, e.g. projections of the food web that include fisheries, eutrophication, and climate change. New datasets and projections have led to a revised understanding of changes in some variables such as salinity. Furthermore, it has become evident that natural variability, in particular for the ocean on multidecadal timescales, is greater than previously estimated, challenging our ability to detect observed and projected changes in climate. In this context, the first palaeoclimate simulations regionalised for the Baltic Sea region are instructive. Hence, estimated uncertainties for the projections of many variables increased. In addition to the well-known influence of the North Atlantic Oscillation, it was found that also other low-frequency modes of internal variability, such as the Atlantic Multidecadal Variability, have profound effects on the climate of the Baltic Sea region. Challenges were also identified, such as the systematic discrepancy between future cloudiness trends in global and regional models and the difficulty of confidently attributing large observed changes in marine ecosystems to climate change. Finally, we compare our results with other coastal sea assessments, such as the North Sea Region Climate Change Assessment (NOSCCA), and find that the effects of climate change on the Baltic Sea differ from those on the North Sea, since Baltic Sea oceanography and ecosystems are very different from other coastal seas such as the North Sea. While the North Sea dynamics are dominated by tides, the Baltic Sea is characterised by brackish water, a perennial vertical stratification in the southern subbasins, and a seasonal sea ice cover in the northern subbasins.Peer reviewe

Climate change scenarios for Estonia based on climate models from the IPCC Fourth Assessment Report

Climate change scenarios were created for Estonia by employing the SRES (= Special Report on Emission Scenarios) emission scenarios and general circulation model (GCM) outputs used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4) and presented at the IPCC Data Distribution Centre. Control simulations were explored for the estimation of the suitability of different GCMs to describe climatic conditions in Estonia. Comparing the modelled and observed monthly mean temperatures and precipitation during 1961–1990, better-quality GCM outputs were selected for further analysis. Climate change scenarios based on GCMs were created for Estonia for the period 2070–2099. The mean projected increase in air temperature was 3–4 K; it was slightly higher in winter than in summer. All models revealed some warming in all months. The projections of precipitation were more variable. The mean increase in annual precipitation was estimated to be mostly between 10% and 20%. An increase in precipitation was uniformly predicted for the cold season, while a variety of possible changes existed in summer. Some models projected even a decrease in precipitation in July, August and September