Multi-criteria performance evaluation of gridded precipitation and temperature products in data sparse region

Lawal, Ibrahim Mohammed and Bertram, Douglas and White, Christopher John and Jagaba, Ahmad Hussaini and Hassan, Ibrahim and Shuaibu, Abdulrahman (2021) Multi-criteria performance evaluation of gridded precipitation and temperature products in data sparse region. Atmosphere, 12 (12). 1597. ISSN 2073-4433 (https://doi.org/10.3390/atmos12121597)

[thumbnail of Lawal-etal-Atmosphere-2021-Multi-criteria-performance-evaluation-of-gridded-precipitation-and-temperature-products]
Preview
Text. Filename: Lawal_etal_Atmosphere_2021_Multi_criteria_performance_evaluation_of_gridded_precipitation_and_temperature_products.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo

Download (1MB)| Preview

Abstract

Inadequate climate data stations often make hydrologic modelling process quite a challenging task in data-sparse regions. Gridded climate data is being used as an alternative, however their accuracy to replicate the climatology of the region of interest with low level of uncertainty is important to water resource planning. This study utilized several performance metrics and multi-criteria decision to assess the skill of the widely used gridded precipitation and temperature data against quality controlled observed station record in Lake Chad basin. The study findings revealed that the products differ in their skills across the selected performance metrics, although promising especially with regards to temperature. However, there are some inherent weaknesses in replicating the observed station data. Princeton University Global Meteorological Forcing precipitation showed the worst skill with Kling Gupta Efficiency of (0.13 – 0.50), mean modified index of agreement of 0.68, and similarity coefficient (SU = 0.365), relative to other products with satisfactory skill across all stations. There are varying degree of mismatch in unidirectional precipitation and temperature trends, although satisfactory in replicating the hydro-climatic information with low level of uncertainty. Assessment based on multi-criteria decision revealed that Climate Research Unit, Global Precipitation Climatology Centre and Climate Prediction Centre precipitation and Climate Research Unit and Princeton University Global Meteorological Forcing temperature data exhibit better skill in terms similarity and are recommended for application in hydrologic impact studies, especially in the quantification of projected climate hazards and vulnerabilities for better water policy decision making in Lake Chad Basin.

ORCID iDs

Lawal, Ibrahim Mohammed ORCID logoORCID: https://orcid.org/0000-0002-4130-9739, Bertram, Douglas ORCID logoORCID: https://orcid.org/0000-0003-4291-5842, White, Christopher John, Jagaba, Ahmad Hussaini, Hassan, Ibrahim and Shuaibu, Abdulrahman;