Retrieval of Normalized Gamma Size Distribution Parameters using Precipitation Imaging Package (PIP) Snowfall Observations during ICE-POP 2018

IF 2.6 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of Applied Meteorology and Climatology Pub Date : 2023-02-28 DOI:10.1175/jamc-d-21-0266.1
A. Tokay, L. Liao, R. Meneghini, C. N. Helms, S. Munchak, D. Wolff, P. Gatlin
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Abstract

Parameters of the normalized gamma particle size distribution (PSD) have been retrieved from the Precipitation Image Package (PIP) snowfall observations collected during the International Collaborative Experiment - PyeongChang Olympics and Paralympic (ICE-POP 2018). Two of the gamma PSD parameters, the mass weighted particle diameter (Dmass) and the normalized intercept parameter NW, have median values of 1.15-1.31 mm and 2.84-3.04 log(mm−1 m−3), respectively. This range arises from the choice of the relationship between the maximum versus equivalent diameter, Dmx−Deq, and the relationship between the Reynolds and Best numbers, Re-X. Normalization of snow water equivalent rate (SWER) and ice water content (W) by NW reduces the range in NW resulting in well fitted power law relationship, between SWER/NW and Dmass and between W/NW and Dmass. The bulk descriptors of snowfall are calculated from PIP observations and from the gamma PSD with values of the shape parameter (μ) ranging from −2 to 10. NASA's Global Precipitation Measurement (GPM) mission, which adopted the normalized gamma PSD, assumes μ = 2 and μ = 3 in its two separate algorithms. The mean fractional bias (MFB) of the snowfall parameters changes with μ, where the functional dependence on μ depends on the specific snowfall parameter of interest. The MFB of the total concentration was underestimated by 0.23−0.34 when μ = 2 and by 0.29−0.40 when μ = 3, while the MFB of SWER had a much narrower range (−0.03 to 0.04) for the same μ values.
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基于降水成像包(PIP)的ICE-POP 2018降雪量反演归一化伽玛大小分布参数
归一化伽马粒度分布(PSD)的参数已从国际合作实验-平昌奥运会和残奥会(ICE-POP 2018)期间收集的降水图像包(PIP)降雪观测中检索。两个伽马PSD参数,即质量加权粒径(Dmass)和归一化截距参数NW,其中值分别为1.15-1.31 mm和2.84-3.04 log(mm−1 m−3)。该范围源于最大直径与等效直径Dmx−Deq之间的关系以及雷诺数与最佳数Re-X之间的关系的选择。NW对雪水当量率(SWER)和冰水含量(W)的归一化减小了NW的范围,从而在SWER/NW和Dmass之间以及W/NW和Dmash之间产生了拟合良好的幂律关系。降雪的体积描述符是根据PIP观测和伽马PSD计算的,形状参数(μ)的值范围为−2至10。美国国家航空航天局的全球降水测量(GPM)任务采用了归一化伽马PSD,在其两个独立的算法中假设μ=2和μ=3。降雪参数的平均分数偏差(MFB)随μ而变化,其中对μ的函数依赖性取决于感兴趣的特定降雪参数。当μ=2时,总浓度的MFB被低估了0.23−0.34,当μ=3时,MFB被高估了0.29−0.40,而对于相同的μ值,SWER的MFB范围要窄得多(−0.03到0.04)。
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来源期刊
Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology 地学-气象与大气科学
CiteScore
5.10
自引率
6.70%
发文量
97
审稿时长
3 months
期刊介绍: The Journal of Applied Meteorology and Climatology (JAMC) (ISSN: 1558-8424; eISSN: 1558-8432) publishes applied research on meteorology and climatology. Examples of meteorological research include topics such as weather modification, satellite meteorology, radar meteorology, boundary layer processes, physical meteorology, air pollution meteorology (including dispersion and chemical processes), agricultural and forest meteorology, mountain meteorology, and applied meteorological numerical models. Examples of climatological research include the use of climate information in impact assessments, dynamical and statistical downscaling, seasonal climate forecast applications and verification, climate risk and vulnerability, development of climate monitoring tools, and urban and local climates.
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