Integrated Evaluation and error decomposition of four gridded precipitation products using dense rain gauge observations over the Yunnan-Kweichow Plateau, China

Lu, Tianjian; Xiao, Qingquan; Lu, Hanyu; Ren, Jintong; Yuan, Yongyi; Luo, Xiaoshan; Zhang, Zhijie

doi:10.1080/22797254.2024.2322742

European Journal of Remote Sensing

2024

DOI: 10.1080/22797254.2024.2322742

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Integrated Evaluation and error decomposition of four gridded precipitation products using dense rain gauge observations over the Yunnan-Kweichow Plateau, China

Tianjian Lu,

Qingquan Xiao,

Hanyu Lu

et al.

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Spatiotemporal evaluation of five satellite-based precipitation products under the arid environment of Saudi Arabia

Jazem Ghanim,

Anjum,

Alharbi

et al. 2024

AIP Advances

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In arid regions like Saudi Arabia, accurate precipitation data are crucial for water resource management and climate studies. However, satellite-based precipitation products (SPPs) can contain uncertainties, impacting their reliability. This study evaluated the accuracy of five high-resolution SPPs [IMERG-V06 variants, Tropical Rainfall Measuring Mission (TRMM)-3B42V7, and Soil Moisture to Rain (SM2RAIN)-Advanced SCATterometer (ASCAT)] over Saudi Arabia. We compared daily, monthly, and yearly precipitation estimates from SPPs with in situ rain gauge data (2010–2022) using both continuous and categorical metrics. The evaluation encompassed point-to-pixel comparisons, regional analysis, and national assessments. All SPPs effectively captured the spatiotemporal patterns of precipitation across the country. Notably, monthly estimates showed stronger agreement with rain gauge data than daily estimates, as indicated by higher correlation coefficients. IMERG products generally outperformed SM2RAIN-ASCAT and TRMM, with IMERG-LR exhibiting superior performance in estimating monthly precipitation. However, underestimation of light precipitation events (<2 mm/day) was observed across all SPPs. In addition, their ability to detect moderate and heavy precipitation events remained uncertain, requiring further investigation. While IMERG-FR showed reduced bias and root mean square error compared to IMERG-ER and IMERG-LR, its capability for precipitation event detection did not exhibit significant improvement. This study highlights the need for bias correction of IMERG-LR and IMERG-FR monthly estimates for improved application in hydrometeorological studies in Saudi Arabia. Our findings contribute valuable insights for both data users and SPP algorithm developers, aiming to enhance the accuracy and reliability of satellite-derived precipitation data in arid environments.

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Spatiotemporal evaluation of five satellite-based precipitation products under the arid environment of Saudi Arabia

Jazem Ghanim,

Anjum,

Alharbi

et al. 2024

AIP Advances

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show abstract

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Integrated Evaluation and error decomposition of four gridded precipitation products using dense rain gauge observations over the Yunnan-Kweichow Plateau, China

Cited by 1 publication

References 83 publications

Spatiotemporal evaluation of five satellite-based precipitation products under the arid environment of Saudi Arabia

Spatiotemporal evaluation of five satellite-based precipitation products under the arid environment of Saudi Arabia

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