34 research outputs found

    A revised agricultural drought index in Lithuania

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    The objective of this study was to develop the best methodology for determining agricultural droughts in Lithuania. The currently used assessment methods do not always accurately reflect drought conditions in the country, especially in the first half of the growing season. For this purpose, the relevance of the currently used Hydrothermal Coefficient (HTC) and five drought indices widely used in other countries were reassessed. It was found that the methodologies applied in Lithuania and other countries are not completely suitable under current conditions. A new agricultural drought identification methodology using the Temperature–Precipitation Index (TPI) is proposed as a result of this study. Analysis of long-term changes (1961–2019) in reoccurrence of droughts was carried out. It was determined that the largest number of droughts in Lithuania was recorded in the last decade of the 20th century and in the first decade of the 21st century. Despite the fact that there is a positive tendency in reoccurrence of droughts, the changes are not statistically significant

    Temporal variation of extreme precipitation events in Lithuania**The study was supported by the Lithuanian State Science and Studies Foundation and by the BSR Interreg IVB Project ‘Climate Change: Impacts, Costs and Adaptation in the Baltic Sea Region (BaltCICA)’.

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    AbstractHeavy precipitation events in Lithuania for the period 1961–2008 were analysed. The spatial distribution and dynamics of precipitation extremes were investigated. Positive tendencies and in some cases statistically significant trends were determined for the whole of Lithuania.Atmospheric circulation processes were derived using Hess & Brezowski’s classification of macrocirculation forms. More than one third of heavy precipitation events (37%) were observed when the atmospheric circulation was zonal. The location of the central part of a cyclone (WZ weather condition subtype) over Lithuania is the most common synoptic situation (27%) during heavy precipitation events.Climatic projections according to outputs of the CCLM model are also presented in this research. The analysis shows that the recurrence of heavy precipitation events in the 21st century will increase significantly (by up to 22%) in Lithuania

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

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    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