Crowdsourced Data Reveal Shortcomings in Precipitation Phase Products for Rain and Snow Partitioning

IF 4.6 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

Geophysical Research Letters Pub Date : 2024-12-23 DOI:10.1029/2024gl112853

Guo Yu, Keith S. Jennings, Benjamin J. Hatchett, Anne W. Nolin, Nayoung Hur, Meghan Collins, Anne Heggli, Sonia Tonino, Monica M. Arienzo

{"title":"Crowdsourced Data Reveal Shortcomings in Precipitation Phase Products for Rain and Snow Partitioning","authors":"Guo Yu, Keith S. Jennings, Benjamin J. Hatchett, Anne W. Nolin, Nayoung Hur, Meghan Collins, Anne Heggli, Sonia Tonino, Monica M. Arienzo","doi":"10.1029/2024gl112853","DOIUrl":null,"url":null,"abstract":"Reanalysis products support our understanding of how the precipitation phase influences hydrology across scales. However, a lack of validation data hinders the evaluation of a reanalysis-estimated precipitation phase. In this study, we used a novel dataset from the Mountain Rain or Snow (MRoS) citizen science project to compare 39,680 MRoS observations from January 2020 to July 2023 across the conterminous United States (CONUS) to assess three precipitation phase products. These products included the Global Precipitation Measurement (GPM) mission Integrated Multi-satellitE Retrievals for GPM (IMERG), the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), and the North American Land Data Assimilation System (NLDAS-2). The overall critical success indices for detecting rainfall (snowfall) for IMERG, MERRA-2, and NLDAS-2 were 0.51 (0.79), 0.49 (0.77), and 0.54 (0.53), respectively. These indices show that IMERG and MERRA-2 reasonably classify snowfall, whereas NLDAS-2 overestimates rainfall. All products performed poorly in detecting subfreezing rainfall and snowfall above 2°C. Therefore, crowdsourced data provides a unique validation source to improve the capabilities of reanalysis products.","PeriodicalId":12523,"journal":{"name":"Geophysical Research Letters","volume":"20 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geophysical Research Letters","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1029/2024gl112853","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

Reanalysis products support our understanding of how the precipitation phase influences hydrology across scales. However, a lack of validation data hinders the evaluation of a reanalysis-estimated precipitation phase. In this study, we used a novel dataset from the Mountain Rain or Snow (MRoS) citizen science project to compare 39,680 MRoS observations from January 2020 to July 2023 across the conterminous United States (CONUS) to assess three precipitation phase products. These products included the Global Precipitation Measurement (GPM) mission Integrated Multi-satellitE Retrievals for GPM (IMERG), the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), and the North American Land Data Assimilation System (NLDAS-2). The overall critical success indices for detecting rainfall (snowfall) for IMERG, MERRA-2, and NLDAS-2 were 0.51 (0.79), 0.49 (0.77), and 0.54 (0.53), respectively. These indices show that IMERG and MERRA-2 reasonably classify snowfall, whereas NLDAS-2 overestimates rainfall. All products performed poorly in detecting subfreezing rainfall and snowfall above 2°C. Therefore, crowdsourced data provides a unique validation source to improve the capabilities of reanalysis products.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Geophysical Research Letters 地学-地球科学综合

CiteScore

9.00

自引率

9.60%

发文量

1588

审稿时长

2.2 months

期刊介绍： Geophysical Research Letters (GRL) publishes high-impact, innovative, and timely research on major scientific advances in all the major geoscience disciplines. Papers are communications-length articles and should have broad and immediate implications in their discipline or across the geosciences. GRLmaintains the fastest turn-around of all high-impact publications in the geosciences and works closely with authors to ensure broad visibility of top papers.