Comparing available rainfall gridded datasets for West Africa and the impact on rainfall-runoff modelling results, the case of Burkina-Faso

Mahé, Gil; Girard, Sabine; New, Mark; Paturel, Jean‐Emmanuel; Cres, Agnès; Dezetter, Alain; Dieulin, Claudine; Boyer, Jean-François; Rouché, Nathalie; Servat, Éric

doi:10.4314/wsa.v34i5.180650

Cited by 16 publications

(10 citation statements)

References 23 publications

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“…In Nigeria, no study has so far been conducted to assess the performance of daily gridded precipitation and temperature data products that can serve as an alternative to the unavailable station datasets. In West Africa, the only study conducted so far was in Burkina-Faso by Mahe et al, [22].…”

Section: Discussionmentioning

confidence: 99%

“…[20] used unified rain gauge data with three daily gauge based gridded rainfall datasets, namely the Indian Meteorological Department (IMD), APHRODITE and Climate Prediction centre (CPC) over India. [21] used IMD dataset for comparison of two satellite datasets, namely, GPCP and Tropical Rainfall Measurement Mission (TRMM) [22]. Compared station datasets with two gridded rainfall datasets, namely Climatic Research Unit (CRU), Hydro-Sciences Montpellier (SIEREM) for Burkina-Faso in West Africa.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Daily Gridded Meteorological Datasets over the Niger Delta Region of Nigeria and Implication to Water Resources Management

Hassan¹,

Kalin²,

White³

et al. 2020

ACS

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Hydro-climatological study is difficult in most of the developing countries due to the paucity of monitoring stations. Gridded climatological data provides an opportunity to extrapolate climate to areas without monitoring stations based on their ability to replicate the Spatio-temporal distribution and variability of observed datasets. Simple correlation and error analyses are not enough to predict the variability and distribution of precipitation and temperature. In this study, the coefficient of correlation (R 2), Root mean square error (RMSE), mean bias error (MBE) and mean wet and dry spell lengths were used to evaluate the performance of three widely used daily gridded precipitation, maximum and minimum temperature datasets from the Climatic Research Unit (CRU), Princeton University Global Meteorological Forcing (PGF) and Climate Forecast System Reanalysis (CFSR) datasets available over the Niger Delta part of Nigeria. The Standardised Precipitation Index was used to assess the confidence of using gridded precipitation products on water resource management. Results of correlation, error, and spell length analysis revealed that the CRU and PGF datasets performed much better than the CFSR datasets. SPI values also indicate a good association between station and CRU precipitation products. The CFSR datasets in comparison with the other data products in many years overestimated and underestimated the SPI. This indicates weak accuracy in predictability, hence not reliable for water resource management in the study area. However, CRU data products were found to perform much better in most of the statistical assessments conducted.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of Daily Gridded Meteorological Datasets over the Niger Delta Region of Nigeria and Implication to Water Resources Management

Hassan¹,

Kalin²,

White³

et al. 2020

ACS

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“…However, the HSM_SIEREM database still has a sufficient number of points, compared to the Global Historical Climatology Network (GHCN) values-2500 gauges, worldwide, for the year 2000 [5], compared to a little less than 1,500 for Africa alone, in our database, for December 1999. that interpolated grids would be created, which would be disseminated for free to the community as the HSM_SIEREM database. This database has already been compared to the CRU for hydrological modeling in Western and Central Africa, and had given better results [7].…”

Section: The Periodmentioning

confidence: 99%

“…It was then decided that interpolated grids would be created, which would be disseminated for free to the community as the HSM_SIEREM database. This database has already been compared to the CRU for hydrological modeling in Western and Central Africa, and had given better results [7].…”

Section: Reference Of the Cru Grid Constitutionmentioning

confidence: 99%

“…To study rainfall changes at the scale of the whole African continent, rainfall grids can be downloaded from several institutions, but it is well-known that the African continent is less documented than other parts of the world [5,6]. This has led to some discrepancies between rainfall calculated from different databases, as has been shown for Western Africa, by Mahé et al [7]. Among the available data sets, Climatic Research Unit of University of East Anglia, UK (CRU) [8,9] is used very often and seems to be the most accurate, compared to other sources.…”

Section: Introductionmentioning

confidence: 99%

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A New 60-Year 1940/1999 Monthly-Gridded Rainfall Data Set for Africa

Dieulin

Mahé

Paturel

et al. 2019

Water

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The African continent has a very low density of rain gauge stations, and long time-seriesfor recent years are often limited and poorly available. In the context of global change, it is veryimportant to be able to characterize the spatio-temporal variability of past rainfall, on the basis ofdatasets issued from observations, to correctly validate simulations. The quality of the rainfall datais for instance of very high importance to improve the efficiency of the hydrological modeling,through calibration/validation experiments.The HydroSciences Montpellier Laboratory (HSM) has a long experience in collecting andmanaging hydro-climatological data. Thus, HSM had initiated a program to elaborate a referencedataset, in order to build monthly rainfall grids over the African continent, over a period of 60 years(1940/1999). The large quantity of data collected (about 7,000 measurement points were used in thisproject) allowed for interpolation using only observed data, with no statistical use of a referenceperiod. Compared to other databases that are used to build the grids of the Global HistoricalClimatology Network (GHCN) or the Climatic Research Unit of University of East Anglia, UK (CRU),the number of available observational stations (a was significantly much higher, including the end ofthe century when the number of measurement stations dropped dramatically, everywhere.Inverse distance weighed (IDW) was the chosen method to build the 720 monthly grids and amean annual grid, from rain gauges. The mean annual grid was compared to the CRU grid. The gridswere significantly different in many places, especially in North Africa, Sahel, the horn of Africa, andthe South Western coast of Africa, with HSM_SIEREM data (database HydroSciencesMontpellier_Système d’Information Environnementales pour les Ressources en Eau et leurModélisation) being closer to the observed rain gauge values. The quality of the grids computed waschecked, following two approaches—cross-validation of the two interpolation methods, ordinarykriging and inverse distance weighting, which gave a comparable reliability, with regards to theobserved data, long time-series analysis, and analysis of long-term signals over the continent,compared to previous studies. The statistical tests, computed on the observed and gridded data,detected a rupture in the rainfall regime around 1979/1980, on the scale of the whole continent; thiswas congruent with the results in the literature. At the monthly time-scale, the most widely observedsignal over the period of 1940/1999, was a significant decrease of the austral rainy season betweenMarch and May, which has not earlier been well-documented. Thus, this would lead to a furtherdetailed climatological study from this HSM_SIEREM database.

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