This figure shows the greenhouse gas emission targets, trends as well as the EU Member States (EU-28 and after 2019 EU-27) MMR projections.
The maps show the long-term average soil moisture contents (left) and the trends in soil moisture values (right), aggregated by NUTS3 regions.
Soil moisture is equal to 0 when the soil is severely dry (wilting point) and equal to 1 when the soil moisture is above the field capacity. Low long-term average soil moisture values indicate areas where during the 2000-2019 period the soil moisture deficit was the biggest problem. Trends are expressed in standard deviation from the long term average. Negative trends indicate that soil moisture values show a decreasing tendency during the 2000-2019 period. Areas with lower soil moisture content together with decreasing tendency in the soil moisture are in risk of loosing their land functions of supplying ecosystem services.
See also:
https://www.eea.europa.eu/data-and-maps/data/data-viewers/soil-moisture and
Original dataset: https://edo.jrc.ec.europa.eu/documents/factsheets/factsheet_soilmoisture.pdf
Data Visualization
22 Mar 2021
Indicator Assessment
22 Mar 2021
Monitoring the pressure from soil moisture deficits can warn of potential impacts on plant development and soil health, supporting the assessment of drought-tolerant, resilient and vulnerable ecosystems. In 2000-2019, soil moisture in the growing season was several times below the long-term average in the EEA member countries plus the United Kingdom. The largest soil moisture deficits occurred in 2003, 2017 and 2019, affecting over 1.45 million km 2 in 2019. Soil moisture content was also low in 2012, 2015 and 2018, contributing to increasingly frequent and intense drought pressure.
Indicator Assessment
23 Feb 2021
Extreme sea levels have increased at most locations along the European coastline. Both observed and projected increases can be explained mainly by increases in mean local sea levels. However, extreme sea levels can be further increased by storm surges and tidal changes, particularly along the northern European coastline. In the absence of better coastal protection, the sea level rise projected for 2100 will increase the frequency of extreme coastal flooding events by a factor of 10 to more than 1 000 along most European coastlines, depending on the location and the emissions scenario.
The map show the trade flow of primary plastics between EU-28 and the most important trade partners for each category. Arrows outbound from EU-28 shows exported value and inbound show imported value.
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
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).
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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