Assessment of Three Long-Term Satellite-Based Precipitation Estimates against Ground Observations for Drought Characterization in Northwestern China
نویسندگان
چکیده
Long-term satellite-based precipitation estimates (LSPE) play a significant role in climatological studies like drought monitoring. In this study, three popular LSPEs (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), Rainfall Estimates Rain Gauge and Satellite Observations (CHIRPS) Multi-Source Weighted-Ensemble Precipitation (MSWEP)) were evaluated on monthly scale ground-based stations for capturing event characteristics over northwestern China 1983 to 2013. To reflect dry or wet evolution, the Standardized Index (SPI) was adopted, Run theory used identify events their characteristics. The conventional statistical indices (relative bias (RB), correlation coefficient (CC), root mean square error (RMSE)), as well categorical (probability of detection (POD), false alarm ratio (FAR), missing (MISS)) are evaluate capability estimating We found that: (1) showed generally satisfactory performance characterizing events. Although have acceptable identifying with POD greater than 60%, they still high (>27%) (>33%); (2) tended overestimate severity, mainly because an overestimation duration; (3) ability CHIRPS replicate temporal evolution SPI values is limited; (4) severe events, PERSIANN-CDR tends precipitation, area; (5) among LSPEs, MSWEP outperformed other two (POD > 66%) features. Finally, we recommend monitoring due its accuracy China. applications, peak value area, CHIRPS’s inferiority must be considered.
منابع مشابه
GRACE Gravity Satellite Observations of Terrestrial Water Storage Changes for Drought Characterization in the Arid Land of Northwestern China
Drought is a complex natural hazard which can have negative effects on agriculture, economy, and human life. In this paper, the primary goal is to explore the application of the Gravity Recovery and Climate Experiment (GRACE) gravity satellite data for the quantitative investigation of the recent drought dynamic over the arid land of northwestern China, a region with scarce hydrological and met...
متن کاملObject-Based Assessment of Satellite Precipitation Products
An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), Climate Prediction center MORPHing technique (CMORPH), and Tropical Rainfall Measurement Mission (TRMM) Multi-Satellite Precipitation Analysis (TMP...
متن کاملError-Component Analysis of TRMM-Based Multi-Satellite Precipitation Estimates over Mainland China
The Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) products have been widely used, but their error and uncertainty characteristics over diverse climate regimes still need to be quantified. In this study, we focused on a systematic evaluation of TMPA’s error characteristics over mainland China, with an improved error-component analysis procedure. We perf...
متن کاملUse of Satellite Observations for Long-Term Exposure Assessment of Global Concentrations of Fine Particulate Matter
BACKGROUND More than a decade of satellite observations offers global information about the trend and magnitude of human exposure to fine particulate matter (PM2.5). OBJECTIVE In this study, we developed improved global exposure estimates of ambient PM2.5 mass and trend using PM2.5 concentrations inferred from multiple satellite instruments. METHODS We combined three satellite-derived PM2.5...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Remote Sensing
سال: 2022
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs14040828