, 2011) In recent years extreme event analysis has generated gre

, 2011). In recent years extreme event analysis has generated greater scientific interest in the eastern Baltic (Jaagus, 2006, Tammets, 2007, Avotniece et al., 2010 and Kažys et al., 2011). Drought dynamics over the Baltic Sea region (Rimkus et al. 2012) and the Neman river basin (Rimkus et al. 2013), as well as drought analysis in Lithuania using SPI and HTC indices (Valiukas 2012), have been carried out. Also, the impact of atmospheric circulation on extreme precipitation (Rimkus et al. 2011) and snow cover variability (Rimkus et al. 2014) have been analysed using macro-circulation form classification. In this study we tried to discover the main atmospheric circulation patterns during dry periods

in Lithuania between 1961 and 2010. The subjective Hess and Brezowski macro-circulation form EPZ5676 cost classification (Werner & Gerstengarbe 2010) was used for identifying weather type. The main objective of our work was to characterise the atmospheric circulation during the development, persistence and attenuation phases of dry periods in Lithuania. The atmospheric circulation patterns during dry events were analysed using composite 500 hPa geopotential height field analysis. The clustering of NAO and AO indices prior to positive/negative phases were performed during dry periods. In addition, blocking episodes during drought phases were identified using the Tibaldi and Molteni

blocking Vincristine manufacturer index (TMI) (Tibaldi & Molteni 1990). Atmospheric Progesterone circulation patterns which led to dry periods and drought formation from 1961–2010 were analysed in this study. Droughts in Lithuania are identified using the Selianinov hydrothermal coefficient (HTC) (Selianinov 1928), when for 30 consecutive days the HTC is lower than

or equal to 0.5. Droughts were recorded in the entire territory of Lithuania four times (1992, 1994, 1996 and 2002) during this 50-year period. This aspect was analysed in the present study in order to determine the circulation conditions that led to the formation of drought and shorter dry periods when the HTC was less than or equal to 0.5 for 15 consecutive days. During these 50 years such dry periods were recorded 14 times in at least one third of the territory of Lithuania. The daily air temperature and precipitation data for the growing season (May–September) from 17 meteorological stations were used (Figure 1). The HTC for each day was calculated according to the following formula: HTC=∑p0.1∑t, where ∑p – total precipitation and ∑t – sum of mean air temperatures for 30 consecutive days. The interpretation of the HTCs is as follows: < 0.5 – severe drought; < 0.7 – medium drought; < 0.9 – weak drought; > 1 – sufficient moisture; > 1.5 – excessive moisture. One can start calculating HTC when the mean average air temperature is 10 °C. In Lithuania this transition is most often recorded at the beginning of May. During the investigation, therefore, calculations of HTC started on May 1.

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