Long-term datasets of dual-polarisation weather radar help detect and nowcast convective storms including extreme precipitation, lightning, and hail
Date
2023-07-05
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Abstract
Kliimasoojenemisega seoses muutuvad sagedasemaks ja tugevamaks ka konvektsiooniga kaasnevad ohtlikud ilmanähtused nagu tormid, paduvihmad, äike ja rahe. Selliste nähtuste uurimiseks on eriti sobilikud ilmaradarid, sest nendega saab jälgida õhus toimuvat suurel alal kõrge ajalise ja ruumilise lahutusega. Pikalt on kasutusel olnud horisontaalselt polariseeritud signaaliga ilmaradarid, kuid moodsad kaksikpolarimeetrilised radarid, kus lisandub ka vertikaalselt polariseeritud signaal, pakuvad mitmeid uusi võimalusi ohtlike ilmanähtuste tuvastamiseks, jälgimiseks ja ennustamiseks. Täpsemad on nii sajukoguste hindamine kui ka sademeliikide eristamine. Eestis on nüüdseks olemas 9-aastased ehk väga pikad operatiivsed kaksikpolarimeetrilise ilmaradari aegread. Töös näidatakse, et neid ridu sobivalt kalibreerides saab neid andmeid kasutada ka klimatoloogilistel eesmärkidel. Antud töös leitud konvektiivse tormi kriteeriumite põhjal analüüsitakse konvektiivsete tormide jaotumist Eestis aastatel 2010-2019. Selgus, et suveperioodil esineb pea ülepäeviti kas konvektiivne torm või äike kusagil Eestis. Ehkki kagu- või lõunavoolude sagedus on Eesti aladel väike, on nende esinedes konvektiivse tormi oht suurim. Luuakse sajukoguste arvutamiseks vaid radarandmetel põhinev eelnevaid metoodikaid ületav meetod, mis kombineerib madalate sajutugevuste korral horisontaalse peegelduvuse ja tugevama saju korral kaksikpolarimeetrilised andmed. Kombineeritud meetod oli kõige täpsem nii aastaste 1-tunni sajumaksimumide kui ka lühiajaliste ekstreemsademete korduvusperioodide arvutamiseks. Ühtlasi näidati, et vaid 5 aasta radariandmete põhjal on võimalik korrektselt leida tugevate sadude esinemise korduvusperioode, milleks tavametoodikaid kasutades oleks tarvis kordades pikemaid sademejaamade aegridu. Töö tulemustel on suur praktiline väärtus, need aitavad tõsta suviste ohtlike ilmastikunähtuste määramise täpsust ja saavad olla aluseks lühiennustuste koostamiseks.
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.
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.
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Keywords
weather radars, meteorological measurements, atmospheric phenomena, storms, thunder, precipitation, weather forecasts