The dataset consists of a collection of annual soil moisture (SM) anomalies during the vegetation growing season (GS) for the years 2000-2019 across EEA 38 area and the United Kingdom. The vegetation growing season is defined by EEA´s phenology data series "Vegetation growing season length 2000-2016" [https://www.eea.europa.eu/data-and-maps/data/annual-above-ground-vegetation-season]. The anomalies are calculated based on the European Commission's Joint Research Centre European Drought Observatory (EDO) Soil Moisture Index (SMI) with respect to the 1995–2019 base period. The yearly start and end of GS periods are dynamic and calculated according to the EEA Phenology Indicators. A positive anomaly indicates that the observed SM was wetter than the long-term SM average for the base period, while a negative anomaly indicates that the observed SM was drier than the reference value. Because SM anomalies are measured in units of standard deviation from the long-term SMI average, they can be used to compare annual deficits/surplus of SM between geographic regions.
EDO is one of the early warning and monitoring systems of the Copernicus Emergency Management Service. As the dataset builds on EDO's SMI, it therefore contains modified Copernicus Emergency Management Service information (2019).
Data Visualization
20 Dec 2020
Data Visualization
20 Dec 2020
Indicator Assessment
20 Dec 2020
Between 1980 and 2019, climate-related extremes caused economic losses totaling an estimated EUR 446 billion in the EEA member countries. Although analysing trends in economic losses is difficult, partly as a result of high variability from year to year, climate-related extremes are becoming more common and, without mitigating action, could result in even greater losses in the coming years. The EU adaptation strategy aims to build resilience and ensure that Europe is well prepared to manage the risks and adapt to the impacts of climate change, thus minimising economic losses and other harms.
Impacts of extreme weather and climate related events in the EEA member countries and the UK.
Indicator Assessment
11 Dec 2020
Global mean sea level (GMSL) has risen about 19 cm since 1900, at an accelerating rate. GMSL reached its highest value ever in 2019. Climate models project a GMSL rise during the 21st century that will likely be in the range of 0.29-0.59 m for a low emissions scenario and 0.61-1.10 m for a high one. GMSL projections that include the possibility of faster disintegration of the polar ice sheets predict a rise of up to 2.4 m in 2100 and up to 15 m in 2300. Most coastal regions in Europe have experienced an increase in sea level relative to land, except for the northern Baltic coast.
The left panel depicts the rise in global mean sea level from 1880 to 2019 based on two data sources.
The red line (DMW) shows the hybrid sea-level reconstruction of sea level anomalies during 1900–2015 (Dangendorf et al., 2019). The uncertainty interval around is shaded.
The dark blue line (CMEMS) shows the filtered sea level anomalies for the time period from 1993 to 2019 based on satellite observations (Ablain et al., 2017; WCRP Sea Level Budget Group, 2018).
All values are relative to the average level of the period 1993-2012, during which the two datasets overlap.
The right panel shows projections of global mean sea level until 2100 for three emissions scenarios based on the IPCC SROCC (Special Report on the Ocean and Cryosphere in a Changing Climate).
The arrows show the trend in relative sea level at selected European tide gauge stations since 1970 (in mm/year) based on data from the Permanent Service for Mean Sea Level (PSMSL).
The background colours show projections of European sea level change for 2081–2100 for RCP8.5 (in metres). Results are median values based on the values in the IPCC SROCC Table 4.4.
The figure shows the maximum extent of ice cover in the Baltic Sea in the winters over the period 1719/20-2019/20 (blue bars) and the 15 year moving average (red line). Source: Jouni Vainio, Finnish Meteorological Institute (updated from Seinä and Palosuo 1996; Seinä et al. 2001).
New technology and tools are opening up new possibilities for environmental monitoring and analysis. For
example, citizen science, satellite observations, big data and artificial intelligence present opportunities for
improving the timeliness, comparability, granularity and integration of data.
GIS Map Application
13 Feb 2020
These maps present a story about how Europe might be affected by key climate hazards such as droughts, floods, forest fires and sea level rise during the 21st century and beyond. These maps are based on different greenhouse gas emissions scenarios and climate models and have been published already in various EEA reports and indicators.
This layer provides information at 237 locations along the European coastline
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