Mait Sepp

Large-scale synoptic types and their impact on European precipitation

Atmospheric circulation strongly modulates precipitation patterns throughout Europe. A selection of synoptic types was chosen to investigate the impact of circulation on the spatial distribution of precipitation within Europe and neighbouring regions (for 1951–2010). Applied were (1) the original and one automated version of the Grosswetterlagen classification, (2) the Vangengeim–Girs classification and (3) a dataset of the North Atlantic Oscillation (NAO). Daily values of the E-OBS gridded precipitation dataset were allocated to synoptic types, visualising precipitation anomalies (in percent) during winter (October–March) and summer (April–September) half years. Anomalies from average precipitation conditions (only) contain days connected to each of the investigated synoptic types. Distinct anomaly patterns become visible and are explained by the location of pressure systems. Patterns are spatially similar between both half years for Grosswetterlagen and Vangengeim–Girs classifications, while the NAO shows pronounced seasonal changes. Precipitation anomaly maps were applied to help explain observed changes in European precipitation amounts from 1981 to 2010, as compared to 1951–1980. Changes of precipitation amounts were related to frequency changes of synoptic types, predominantly during the winter half year. Here, increasing (decreasing) frequencies of synoptic types connected to westerly (easterly) inflow supported higher precipitation amounts in northern Europe and lower amounts in southern Europe.

Spatial response of two European atmospheric circulation classifications (data 1901–2010)

Air pressure field and circulation pattern frequencies were investigated to (1) locate and compare positions of the underlying pressure fields, (2) analyse the spatial dimension of affected areas, (3) create schematic maps of important circulation types and (4) compare the classification types in their response to the data. Two manual classifications were used, selected for the length of their time series and their applicability to a larger region: the Grosswetterlagen classification (GWLc) and the Vangengeim–Girs classification (VGc). Their time series were correlated with a global set of gridded monthly sea-level pressure data. Results show the different conceptual orientation of VGc (hemispheric) and GWLc (continental). The highest correlation values and the largest affected areas are visible in winter, where patterns frequently extended into northern Africa and western Asia. Schematic maps, illustrating the average location of main pressure centres, are provided for basic classes of both classifications. Re-arranging GWLc subtypes increases the classifications comparability with the VGc. Analysis of moving correlation coefficients reveals high fluctuations in the relation of both classifications over time.

Sea-Level Change and Flood Risks at Estonian Coastal Zone

This paper reviews Estonian relative sea level, land uplift and coastal floods data and provides sea-level scenarios and risk assessment of coastal flooding in urban areas for the twenty-first century. Considering the present post-glacial land uplift rates of Estonian coastal areas and the global ocean level rise projections, the long-existing trend of relative sea-level lowering may very probably be replaced by a relative sea-level rising trend during the twenty-first century. By the end of the twenty-first century we project the relative sea level to be c. 20 to 40 cm or c. 40 to 60 cm higher in the case of the International Panel for Climate Change Representative Concentration Pathways (RCP) 4.5 or RCP 8.5 scenario, respectively. The sea-level rise together with the increased storm frequency and decreased winter ice cover period will very probably increase the extent of floods during the twenty-first century. A significant coastal flooding risk affects four cities, Parnu, Kuressaare, Haapsalu and Tallinn and eight smaller towns. The largest coastal flooding in Estonia is recorded in Parnu, with the highest sea level 275 cm in 2005. Calculations show that due to the impact of predicted climate change and in the case of certain weather conditions, coastal floods in Parnu may affect areas up to 400 cm above the present sea level by the end of the twenty-first century. The scenarious of future flood limits are needed for sustainable planning of the coastal zone and for development of rescue strategies.There are already several land use and urban planning instruments and laws for climate adaptation, such as environmental impact assessment, risk assessment and restriction zones for construction in certain buffer and flood areas. Flooding risk measures consist of risk mapping and a national emergency plan. However, further integration of climate issues into existing laws, strategies and land use plans is essential to have a targeted approach in reducing the vulnerability of populated areas and strengthening the adaptive capacity of the urban system against climate change.

Landsat-8 TIRS Data for Assessing Urban Heat Island Effect and Its Impact on Human Health

Heat waves are reaching our cities more frequently nowadays, leading to the urban heat island (UHI) effect. Measured by the remotely sensed land surface temperature (LST), the effect is frequently called surface UHI (SUHI). In Estonia, the SUHI has been studied little and the LST method has not being used yet in studies of Estonian cities’ microclimate. The analysis clearly reveals that the effect of UHI in Estonian settlements is larger than ever assumed. Satellite images showed that Tallinn suffers from quite strong UHI effect. Landsat-8 thermal infrared sensor image from July 25, 2014 shows that for all settlements of densely populated Harju County, the temperature is higher than that in the surroundings by 3 °C–5 °C. To evaluate potential impact to the health of vulnerable groups of residents of Tallinn city, we applied an “exposure to risk—sensitivity—impact” method to evaluate the potential impact of the UHI effect on the health of vulnerable groups of residents of Tallinn city. Our analysis showed that the parts of Tallinn severely affected by heat are mostly the areas of apartment buildings with lower real estate prices. Thus, those areas have also a higher population density and more vulnerable people live there. Produced map of UHI impact can be successfully used for spatial planning measures for adaptation to climate change.