TY - JOUR
T1 - How well were the early 2017 California Atmospheric River precipitation events captured by satellite products and ground-based radars?
AU - Wen, Yixin
AU - Behrangi, Ali
AU - Chen, Haonan
AU - Lambrigtsen, Bjorn
N1 - Funding Information:
Technology, under a contract with the National Aeronautics and Space Administration. The study is partially supported by the NASA Energy and Water Cycle Study awards (NNH13ZDA001N-NEWS) and NASA WEATHER (NNH13ZDA001N-WEATHER) awards. Additionally, H. Chen acknowledges the support from the NRC Research Associateship Programs awarded at NOAA/Earth System Research Laboratory. Government sponsorship is acknowledged.
Publisher Copyright:
© 2018 Royal Meteorological Society
PY - 2018/11
Y1 - 2018/11
N2 - In January and February of 2017, California experienced multiple heavy storms that caused serious destruction of facilities and economic loss, although it also helped to reduce water storage deficit due to prolonged drought in previous years. These extreme precipitation events were mainly associated with Atmospheric Rivers (ARs) and brought about 174 km3 of water to California according to ground observations. This article evaluates the performance of six commonly used satellite-based precipitation products (IMERG, 3B42RT, PERSIANN, CCS, CMORPH and GSMaP), as well as ground-based radar products (Radar-only and Radar-lgc) in capturing the ARs precipitation rate and distribution. It is found that precipitation maps from all products present heavy precipitation in January and February, with more consistent observations over ocean than land. Though large uncertainties exist in quantitative precipitation estimation (QPE) over land, the ensemble mean of different remote-sensing precipitation products over California is consistent with gauge measurements. Among the six satellite-based products, IMERG correlates the best with gauge observations both in the detection and quantification of precipitation, but it is not the best product in terms of root-mean-square error or bias. Compared to satellite products, ground weather radar shows better precipitation detectability and estimation skill. However, neither radar nor satellite QPE products have good performances in quantifying the peak precipitation intensity during the extreme events, suggesting that further advancement in quantification of extremely intense precipitation associated with ARs in the western United States is needed.
AB - In January and February of 2017, California experienced multiple heavy storms that caused serious destruction of facilities and economic loss, although it also helped to reduce water storage deficit due to prolonged drought in previous years. These extreme precipitation events were mainly associated with Atmospheric Rivers (ARs) and brought about 174 km3 of water to California according to ground observations. This article evaluates the performance of six commonly used satellite-based precipitation products (IMERG, 3B42RT, PERSIANN, CCS, CMORPH and GSMaP), as well as ground-based radar products (Radar-only and Radar-lgc) in capturing the ARs precipitation rate and distribution. It is found that precipitation maps from all products present heavy precipitation in January and February, with more consistent observations over ocean than land. Though large uncertainties exist in quantitative precipitation estimation (QPE) over land, the ensemble mean of different remote-sensing precipitation products over California is consistent with gauge measurements. Among the six satellite-based products, IMERG correlates the best with gauge observations both in the detection and quantification of precipitation, but it is not the best product in terms of root-mean-square error or bias. Compared to satellite products, ground weather radar shows better precipitation detectability and estimation skill. However, neither radar nor satellite QPE products have good performances in quantifying the peak precipitation intensity during the extreme events, suggesting that further advancement in quantification of extremely intense precipitation associated with ARs in the western United States is needed.
KW - Atmospheric River
KW - QPE
KW - extreme events
KW - ground weather radar
KW - remote sensing
KW - satellite
KW - water resources
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U2 - 10.1002/qj.3253
DO - 10.1002/qj.3253
M3 - Article
AN - SCOPUS:85053200770
SN - 0035-9009
VL - 144
SP - 344
EP - 359
JO - Quarterly Journal of the Royal Meteorological Society
JF - Quarterly Journal of the Royal Meteorological Society
ER -