Doctoral defence: Tanel Voormansik "Long-term datasets of dual-polarisation weather radar help detect and nowcast convective storms including extreme precipitation, lightning, and hail“

On 25 August at 13:15 Tanel Voormansik will defend his doctoral thesis „Long-term datasets of dual-polarisation weather radar help detect and nowcast convective storms including extreme precipitation, lightning, and hail“ for obtaining the degree of Doctor of Philosophy (in Environmental Technology).

Supervisors:
Associate Professor Piia Post, University of Tartu
Professor Dmitri Moisseev, University of Helsinki

Opponent:
PhD Hidde Leijnse, Royal Netherlands Meteorological Institute (Netherlands).

Summary

Precipitation related hazardous weather phenomena such as convective storms, extreme precipitation, lightning and hail are becoming more intense with global climate warming. Weather radars are particularly suitable to study these kind of phenomena because they allow observing large areas with high spatiotemporal resolution. Up to now these phenomena have been studied mainly with single polarisation weather radars. In this work long time series of up to 9 years of operational dual polarisation weather radar data have been used for the first time to study these phenomena. These kind of radars have many benefits over the legacy single polarisation radars such as more accurate precipitation estimation and hydrometeor classification. In Estonia there are very long datasets of at least 9 years of operational dual polarisation weather radar data available. It is shown in this thesis that by applying suitable filtering and calibration these data can be used for climatological purposes. Based on the convective storm definition provided in this work, the distribution of convective storms in Estonia from 2010-2019 is determined. It was found that during the summer period convective storm or lightning occurs nearly every other day in Estonia. Although the frequency of south or south-east airflow is low in Estonia, the probability of convective storms is the highest in case of these airflow directions. In order to calculate precipitation amounts a method using only radar data is developed that is superior to earlier methods. It combines horizontal reflectivity data in weak precipitation and polarimetric data in more intense precipitation. This combined method was the most accurate in finding yearly 1-hour accumulation maxima and for calculating short-term extreme precipitation return periods. It was also demonstrated that based on just 5 years of radar data it is possible to obtain extreme precipitation return periods which otherwise would require rain gauge dataset that is several times longer. The results of this thesis have great practical value, they help increase the detection accuracy of summertime hazardous weather phenomena and can form a basis for nowcast systems.