A climatology of freezing precipitation over the Ukraine and Moldova 12th EMS Annual Meeting & 9th European Conference on Applied Climatology 10 – 14 September 2012 Łódź, Poland A climatology of freezing precipitation over the Ukraine and Moldova Khomenko Inna, Odessa State Environmental University, Ukraine

Location of the cites in the Ukraine and Moldova, for which freezing precipitation conditions are studied

Periods and number of surface observations at the respective airports

Location of the cites in the Ukraine, for which radiosounding data are available

Months in which FP occurs at the respective airports

monthly mean occurrence frequency Maximum and minimum monthly mean occurrence frequency 0,01 Apr 1,00 Dec 0,50 Mar 2,25 Dec 0,05 Nov 1,45 Dec 0,24 Mar 1,15 Jan 0,11 Mar 0,86 Feb 0,23 Nov 1,60 Dec 0,21 Mar 0,09 Mar 0,87 Dec 1,03 Dec 0,05 Apr 1,29 Jan 0,01 Apr 0,72 Jan 0,39 Mar 1,83 Jan

Spatial distribution of freezing drizzle cases (%) Both types of precipitation – freezing rain and freezing drizzle – are geographically distributed: for the central part a predominant type is the freezing rain (from 49 to 74 for Moldova, Kishinev). This result may be explained by influence of cyclonic activity in winter. For the other stations a predominant type is freezing drizzle: from 58 (Lviv) to 90 % (Dnepropetrovsk). The predominant type of freezing drizzle was induced by air-mass mechanism of FP formation.

Frequency (%) of surface temperature associated with FP

Spatial distributions (%) of wind direction associated with FP

Classical mechanism of the freezing precipitation formation

Classification of the FP cases

Summary: Freezing precipitation in the Ukraine represents a rare event, whose monthly maximum averaged occurrence frequency does not exceed a few percent. The low clouds, which produce FP, are mainly cold. The classical stratification of “warm nose” type, with warm layer within the cloud, occurs, on average, in about 14% of FP cases, while “all cold” stratification – in about 54% of the cases. This result is important from a practical point of view. The existing schemes for FP forecasting are based on revealing the warm layers in or below the lower clouds. It is evident now that this notion cannot be efficient in the situations typical for the Ukraine. Other approaches, in particular, probabilistic ones should be found. Investigations of FP conditions, using all of the available data, can provide useful indications for detection of areas with increased probability of FP.