Investigating the merits of gauge and satellite rainfall data at local scales in Ghana, West Africa

• Main Authors: Winifred Ayinpogbilla Atiah, Gizaw Mengistu Tsidu, Leonard Kofitse Amekudzi
• Format: Article
• Language: English
• Published: Elsevier 2020-12-01
• Series: Weather and Climate Extremes
• Subjects: Validation; Gauge; Satellite; Data; Hydrology; Agriculture
• Online Access: http://www.sciencedirect.com/science/article/pii/S2212094720303054

Recently increased concerns and potential consequences of the limitation in gauge measurements in Africa have heightened the availability of high Spatio-temporal satellite-based rainfall data for various applications. In contemporary times, there are efforts to develop modeling tools that would aid water resource management to minimize socio-economic losses. However, these models depend on the reliability of inputs, such as high-quality rainfall data at a highly resolved spatio-temporal scale, hence the importance of this study. The present study assessed the abilities of gauge only and satellite-gauge blended rainfall products to replicate the rainfall patterns concerning observations at thirty (30) rain gauge stations in Ghana. Besides, the study focuses on rainfall characteristics that are vital to the agricultural and hydrological sectors in the region. These include an assessment of the skill of satellite rainfall products to represent observed extreme rainfall indices. The analysis shows that all the rainfall products were able to replicate the seasonal rainfall patterns in both the northern and southern parts of the country. The GPCC V7 and CHIRPS V2 have exhibited the best skills at representing these rainfall patterns compared to TRMM 3B42 and CMORPH. Satellite products that blend thermal infrared and passive microwave tend to perform better than IR-only or PM-only products. We observed that both gauge and satellite-based rainfall products generally overestimate low-intensity rainfall and underestimate high rainfall intensity in the region. Also, satellite-based rainfall products are weak in the coasts of the country though CHIRPS represents rainfall patterns on the eastern coast considerably well (correlation of 0.77). The analysis showed that TRMM 3B42 has a dry bias, while CMORPH has a wet bias compared to CHIRPs. Therefore, one can use TRMM 3B42 and CMORPH for drought and flood analysis respectively in a conservative approach. However, CHIRPS is useful for analysis of all extremes events.