共 24 条
Evaluation of Satellite-Based Rainfall Estimates against Rain Gauge Observations across Agro-Climatic Zones of Nigeria, West Africa
被引:5
|作者:
Datti, Aminu Dalhatu
[1
,2
]
Zeng, Gang
[1
]
Tarnavsky, Elena
[3
]
Cornforth, Rosalind
[3
]
Pappenberger, Florian
[4
]
Abdullahi, Bello Ahmad
[2
]
Onyejuruwa, Anselem
[1
,2
]
机构:
[1] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteorol, Joint Int Res Lab Climate & Environm Change ILCEC, Key Lab Meteorol Disaster,Minist Educ, Nanjing 210044, Peoples R China
[2] Nigerian Meteorol Agcy NiMet, Nnamdi Azikiwe Int Airport, Abuja 900105, Nigeria
[3] Univ Reading, Dept Meteorol, Reading RG6 6UR, England
[4] European Ctr Medium Range Weather Forecasts ECMWF, Reading RG2 9AX, England
关键词:
evaluation;
satellite rainfall estimates;
gauge observation;
Nigeria;
West Africa;
SAHARAN HEAT LOW;
PRECIPITATION PRODUCTS;
SPATIAL EVALUATION;
VALIDATION;
CLIMATOLOGY;
PERFORMANCE;
TRENDS;
MODEL;
D O I:
10.3390/rs16101755
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Satellite rainfall estimates (SREs) play a crucial role in weather monitoring, forecasting and modeling, particularly in regions where ground-based observations may be limited. This study presents a comprehensive evaluation of three commonly used SREs-African Rainfall Climatology version 2 (ARC2), Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) and Tropical Application of Meteorology using SATellite data and ground-based observation (TAMSAT)- with respect to their performance in detecting rainfall patterns in Nigeria at daily scales from 2002 to 2022. Observed data obtained from the Nigeria Meteorological Agency (NiMet) are used as reference data. Evaluation metrics such as correlation coefficient, root mean square error, mean error, bias, probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) are employed to assess the performance of the SREs. The results show that all the SREs exhibit low bias during the major rainfall season from May to October, and the products significantly overestimate observed rainfall during the dry period from November to March in the Sahel and Savannah Zones. Similarly, over the Guinea Zone, all the products indicate overestimation in the dry season. The underperformance of SREs in dry seasons could be attributed to the rainfall retrieval algorithms, intensity of rainfall occurrence and spatial-temporal resolution. These factors could potentially lead to the accuracy of the rainfall retrieval being reduced due to intense stratiform clouds. However, all the SREs indicated better detection capabilities and less false alarms during the wet season than in dry periods. CHIRPS and TAMSAT exhibited high POD and CSI values with the least FAR across agro-climatic zones during dry periods. Generally, CHIRPS turned out to be the best SRE and, as such, would provide a useful dataset for research and operational use in Nigeria.
引用
收藏
页数:18
相关论文