干旱区生态环境知识资源中心(Arid): Spatiotemporal Assessment and Correction of Gridded Precipitation Products in North Western Morocco

Arid

DOI	10.3390/atmos14081239
	Spatiotemporal Assessment and Correction of Gridded Precipitation Products in North Western Morocco
	Ait Dhmane, Latifa; Moustadraf, Jalal; Rachdane, Mariame; Saidi, Mohamed Elmehdi; Benjmel, Khalid; Amraoui, Fouad; Ezzaouini, Mohamed Abdellah; Ait Sliman, Abdelaziz; Hadri, Abdessamad
通讯作者	Dhmane, LA
来源期刊	ATMOSPHERE
EISSN	2073-4433
出版年	2023
卷号	14 期号:8
英文摘要	Accurate and spatially distributed precipitation data are fundamental to effective water resource management. In Morocco, as in other arid and semi-arid regions, precipitation exhibits significant spatial and temporal variability. Indeed, there is an intra- and inter-annual variability and the northwest is rainier than the rest of the country. In the Bouregreg watershed, this irregularity, along with a sparse gauge network, poses a major challenge for water resource management. In this context, remote sensing data could provide a viable alternative. This study aims precisely to evaluate the performance of four gridded daily precipitation products: three IMERG-V06 datasets (GPM-F, GPM-L, and GPM-E) and a reanalysis product (ERA5). The evaluation is conducted using 11 rain gauge stations over a 20-year period (2000-2020) on various temporal scales (daily, monthly, seasonal, and annual) using a pixel-to-point approach, employing different classification and regression metrics of machine learning. According to the findings, the GPM products showed high accuracy with a low margin of error in terms of bias, RMSE, and MAE. However, it was observed that ERA5 outperformed the GPM products in identifying spatial precipitation patterns and demonstrated a stronger correlation. The evaluation results also showed that the gridded precipitation products performed better during the summer months for seasonal assessment, with relatively lower accuracy and higher biases during rainy months. Furthermore, these gridded products showed excellent performance in capturing different precipitation intensities, with the highest accuracy observed for light rain. This is particularly important for arid and semi-arid regions where most precipitation falls under the low-intensity category. Although gridded precipitation estimates provide global coverage at high spatiotemporal resolutions, their accuracy is currently insufficient and would require improvement. To address this, we employed an artificial neural network (ANN) model for bias correction and enhancing raw precipitation estimates from the GPM-F product. The results indicated a slight increase in the correlation coefficient and a significant reduction in biases, RMSE, and MAE. Consequently, this research currently supports the applicability of GPM-F data in North Western Morocco.
英文关键词	Morocco gridded precipitation products GPM ERA5 sparse gauge network artificial neural network
类型	Article
语种	英语
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:001056177900001
WOS关键词	PERFORMANCE EVALUATION ; RAINFALL PRODUCTS ; GPM IMERG ; SATELLITE ; REGION ; BASIN
WOS类目	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/395480
推荐引用方式 GB/T 7714	Ait Dhmane, Latifa,Moustadraf, Jalal,Rachdane, Mariame,et al. Spatiotemporal Assessment and Correction of Gridded Precipitation Products in North Western Morocco[J],2023,14(8).
APA	Ait Dhmane, Latifa.,Moustadraf, Jalal.,Rachdane, Mariame.,Saidi, Mohamed Elmehdi.,Benjmel, Khalid.,...&Hadri, Abdessamad.(2023).Spatiotemporal Assessment and Correction of Gridded Precipitation Products in North Western Morocco.ATMOSPHERE,14(8).
MLA	Ait Dhmane, Latifa,et al."Spatiotemporal Assessment and Correction of Gridded Precipitation Products in North Western Morocco".ATMOSPHERE 14.8(2023).