在乌克兰气象站的降水测量中量化风引起的捕获量

V. Osypov, Andrii S. Bonchkovskyi, A. Oreshchenko, D. Oshurok, N. Osadcha
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Field experiments have shown that wind-induced undercatch reaches 14% for rain and 40% for snow for the Tretyakov wind-shielded gauge (Goodison et al., 1998).\n\nIn Ukraine, precipitation records omit wind-induced undercatch correction.\n\nThis study aims to calculate true precipitation values at Ukrainian weather stations, evaluate existing methodologies for precipitation measurements correction, and create the digital archive of corrected precipitation values based on sub-daily observations.\n\nMaterial and methods. We used four methods to quantify wind-related errors for the Tretyakov gauge with wind shield proposed by Golubev (Konovalov et al., 2000), Bryazgin (Aleksandrov et al., 2005), Norway meteorological institute (Forland et al., 1996), and Yang (Yang et al., 1995). Sub-daily records were requested from Central Geophysical Observatory named after Boris Sreznevsky covering 207 stations between 1976 and 2019; 187 stations had more than 20 years’ period.\n\nResults. 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引用次数: 2

摘要

文献概述。降水测量包括随机误差和系统误差。系统误差的增加顺序如下:蒸发损失、湿润损失和风引起的渔获不足(世界气象组织,2008年)。最后一种是由于降水计集热器下的气动阻塞(Baghapour et al. 2017;Sevruk & Nespor, 1994)。野外试验表明,在Tretyakov防风计中,雨和雪的风致捕获量分别为14%和40% (Goodison et al., 1998)。在乌克兰,降水记录忽略了风引起的渔下校正。本研究旨在计算乌克兰气象站的真实降水值,评估现有的降水测量校正方法,并基于次日观测创建校正降水值的数字档案。材料和方法。我们使用了四种方法来量化由Golubev (Konovalov等,2000)、Bryazgin (Aleksandrov等,2005)、挪威气象研究所(Forland等,1996)和Yang (Yang等,1995)提出的带有风罩的Tretyakov测量仪的风相关误差。以Boris Sreznevsky命名的中央地球物理观测站要求提供1976年至2019年期间207个站点的亚日记录;20年以上的气象站有187个。对于Tretyakov标准,根据校正方法的不同,每年由风引起的欠渔获量在5%到9.5%之间。固体降水的偏差最大,从17.7%到27.4%。气象站降水损失随年风速增大而增大(相关系数r = 0.89)。我们建议Golubev和Yang的方法在经常观测到暴风雪的站点更准确地估计由风引起的降水,我们建议使用Golubev的方法,因为它考虑了“假”降水。在有盖气象站,根据Golubev的方法,降水损失为0.2-4%,在光秃秃的山区或海边,降水损失达到13-19%。固体降水对风-雪损失的影响更为敏感,根据Golubev方法平均为17.3%,根据Yang方法平均为21%,而雨损失分别为2.6%和6.7%。所获得的校正降水数据库包括1976年至2019年乌克兰207个站点的次日和日记录。它可用于水文和气候学研究。
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Quantifying wind-induced undercatch in the precipitation measurements at Ukrainian weather stations
Literature overview. Precipitation measurements include random and systematic errors. Systematic errors increase in the following order: evaporation loss, wetting loss, and wind-induced undercatch (World Meteorological Organization, 2008). The last one occurs because of the aerodynamic blockage under the precipitation gauge collector (Baghapour et al. 2017; Sevruk & Nespor, 1994). Field experiments have shown that wind-induced undercatch reaches 14% for rain and 40% for snow for the Tretyakov wind-shielded gauge (Goodison et al., 1998). In Ukraine, precipitation records omit wind-induced undercatch correction. This study aims to calculate true precipitation values at Ukrainian weather stations, evaluate existing methodologies for precipitation measurements correction, and create the digital archive of corrected precipitation values based on sub-daily observations. Material and methods. We used four methods to quantify wind-related errors for the Tretyakov gauge with wind shield proposed by Golubev (Konovalov et al., 2000), Bryazgin (Aleksandrov et al., 2005), Norway meteorological institute (Forland et al., 1996), and Yang (Yang et al., 1995). Sub-daily records were requested from Central Geophysical Observatory named after Boris Sreznevsky covering 207 stations between 1976 and 2019; 187 stations had more than 20 years’ period. Results. For the Tretyakov gauge, annual wind-induced undercatch ranges from 5 to 9.5%, depending on correction methodology. The highest bias is observed for the solid precipitation – from 17.7 to 27.4%. The precipitation loss increases along with annual wind speed at the weather station (correlation coefficient r = 0.89). Conclusions. We suggest that Golubev’s and Yang’s methodologies estimate precipitation wind-induced undercatch more accurately at stations where blizzards are often observed, we recommended using the Golubev’s methodology because it takes into account “false” precipitations. The precipitation loss equals 0.2–4% according to the Golubev’s method at covered weather stations and reaches 13–19% at the bare mountain regions or seashore. Solid precipitation is more sensitive to the influence of wind – snow loss averages 17.3% according to the Golubev methodology or 21% according to the Yang methodology, while rain loss – 2.6% or 6.7%, respectively. The obtained database with corrected precipitation comprises sub-daily and daily records from 207 Ukrainian stations between 1976 and 2019. It could be used for hydrological and climatological research.
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