The Heidke skill score (HSS) is used to quantitatively evaluate the simulations with different schemes:
HHS = 2(???? ? ????)/ (?? + ??)(?? + ??) + (?? + ??)(?? + ??) (9)
294 where the four elements a-d for HSS, representing the numbers of “hits”, “false alarms”, “misses” and “correct negatives”, respectively, are calculated from a contingency table
(Table 1). HHS can not only judge well-simulated events (both hits and correct negatives, element a and d) but also account for erroneous forecast (b and c) (Barnston, 1992). A higher HSS (0 ~ 1) represents better skill. As shown in Table 1, pt is the threshold value and is set to be 2 mm covering most of the observed and simulated precipitation area, ps and po are the values from simulations and observations,
respectively.
青藏高原混合相積云中液相云微物理過程的影響
https://www.atmos-chem-phys-discuss.net/acp-2019-1063/
在數(shù)值模擬中經(jīng)常發(fā)現(xiàn)對青藏高原降水的過度預(yù)測宰掉，這被認為與粗網(wǎng)格尺寸或不正確的大尺度強迫有關(guān)。除了證實模型網(wǎng)格大小的重要作用外，這項研究還表明，液相降水參數(shù)化是另一個關(guān)鍵原因，并且揭示了潛在的物理機制。
使用天氣研究和預(yù)報（WRF）模型模擬??典型的夏季高原降水事件串慰，方法是將液相微物理過程的不同參數(shù)化引入常用的Morrison方案中，包括自動轉(zhuǎn)換唱蒸，吸積和夾帶混合機制邦鲫。所有模擬都可以再現(xiàn)降水的總體空間分布和時間變化。與低分辨率域相比神汹，高分辨率域中的降水被低估了庆捺。在模擬降水過程中，吸積過程比其他液相過程更重要屁魏。采用考慮雨滴大小的吸積參數(shù)化方法滔以，可使總表面降水最接近觀測值，這是由海德克技能得分支持的氓拼。
