Evaluation of Seasonal Differences Among Three NOAA Climate Data Records of Precipitation

IF 3.1 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of Hydrometeorology Pub Date : 2023-07-07 DOI:10.1175/jhm-d-22-0108.1
O. Prat, B. Nelson
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Abstract

Three satellite precipitation datasets – CMORPH, PERSIANN-CDR, and GPCP – from the NOAA/Climate Data Record program were evaluated in their ability to capture seasonal differences in precipitation for the period 2007-2018 over the conterminous United States. Data from the in-situ US Climate Reference Network (USCRN) provided reference precipitation measurements and collocated atmospheric conditions (temperature) at the daily scale. Satellite precipitation products’ (SPP) performance with respect to cold season precipitation was compared to warm season and full-year analysis for benchmarking purposes. Considering an ensemble of typical performance metrics including accuracy, false alarm ratio, probability of detection, probability of false detection, and the King-Gupta efficiency (KGE) that combines correlation, bias, and variability, we found that the three SPPs displayed better performances during the warm season than during the cold season. Among the three datasets, CMORPH displayed better performance – smaller bias, higher correlation, and a better KGE score – than the two other SPPs on an annual basis and during the warm season. During the cold season, CMORPH showed the worst performance at higher latitudes over areas experiencing recurring snow, or frozen and mixed precipitation. CMORPH’s performances were further degraded compared to PERSIANN-CDR and GPCP when considering freezing temperatures (T<0°C) due to the inability to microwave sensors to retrieve precipitation over snow-covered surface. However, for cold rainfall events detected simultaneously by the satellite and the USCRN stations (i.e., conditional case), CMORPH performance noticeably improved but remained inferior to the two other datasets. The quantification of seasonal precipitation errors and biases for three satellite precipitation datasets presented in this work provides an objective basis for the improvement of rainfall retrieval algorithms of the next generation of satellite precipitation products.
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3个NOAA降水气候数据记录的季节差异评价
评估了来自NOAA/气候数据记录项目的三个卫星降水数据集(CMORPH、persann - cdr和GPCP)捕捉2007-2018年美国连续地区降水季节差异的能力。来自美国原位气候参考网(USCRN)的数据提供了参考降水测量值和日尺度的大气条件(温度)。卫星降水产品(SPP)在冷季降水方面的表现与暖季和全年分析进行了比较,以达到基准目的。考虑到典型的性能指标,包括准确性、误报率、检测概率、误检概率和King-Gupta效率(KGE),结合相关性、偏差和可变性,我们发现三种SPPs在温暖季节比在寒冷季节表现得更好。在三个数据集中,CMORPH在年度和暖季表现出比其他两个spp更好的性能-偏差较小,相关性较高,KGE评分更高。在寒冷季节,CMORPH在高纬度地区反复出现降雪或冰冻和混合降水的地区表现最差。当考虑冻结温度(T<0°C)时,由于微波传感器无法检索积雪表面的降水,CMORPH的性能与PERSIANN-CDR和GPCP相比进一步下降。然而,对于卫星和USCRN站点同时探测到的冷降雨事件(即有条件的情况),CMORPH的性能明显提高,但仍低于其他两个数据集。本文对三个卫星降水数据集的季节降水误差和偏差进行了量化,为改进下一代卫星降水产品的降水检索算法提供了客观依据。
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来源期刊
Journal of Hydrometeorology
Journal of Hydrometeorology 地学-气象与大气科学
CiteScore
7.40
自引率
5.30%
发文量
116
审稿时长
4-8 weeks
期刊介绍: The Journal of Hydrometeorology (JHM) (ISSN: 1525-755X; eISSN: 1525-7541) publishes research on modeling, observing, and forecasting processes related to fluxes and storage of water and energy, including interactions with the boundary layer and lower atmosphere, and processes related to precipitation, radiation, and other meteorological inputs.
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