Validation of TRMM and FEWS Satellite Rainfall Estimates with Rain Gauge Measurement over Ashanti Region, Ghana

Leonard K Amekudzi,Marian A Osei,Winifred A Atiah,Emmanuel Quansah,Maureen A Ahiataku,Andreas H Fink,Kwasi Preko,Sylvester K Danuor,Jeffrey N A Aryee

doi:10.4236/acs.2016.64040

Abstract

Satellite rainfall estimates have predominantly been used for climate impact studies due to poor rain gauge network in sub-Saharan Africa. However, there are limited microscale studies within the sub-region that have assessed the performance of these satellite products, which is the focus of the present study. This paper therefore considers validation of Tropical Rainfall Measuring Mission (TRMM) and Famine Early Warning System (FEWS) satellite estimates with rain gauge measurements over Ashanti region of Ghana. First, a consistency assessment of the two gauge data products, the Automatic Rain Gauge (ARG) and Ghana Meteorological Agency (GMet) Standard Rain Gauge (SRG) measurements, was performed. This showed a very good agreement with correlation coefficient of 0.99. Secondly, satellite rainfall products from TRMM and FEWS were validated with the two gauge measurements. Validation results showed good agreement with correlation coefficients of 0.6 and 0.7 for TRMM and FEWS with SRG, and 0.87 and 0.86 for TRMM and FEWS with ARG respectively. Probability Of Detection (POD) and Volumetric Hit Index (VHI) were found to be greater than 0.9. Volumetric Critical Success Index (VCSI) was 0.9 and 0.8 for TRMM and FEWS respectively with low False Alarm Ratio (FAR) and insignificant Volumetric Miss Index (VMI). In general, relatively low biases and RMSE values were observed. The biases were less than 1.3 and 0.8 for TRMM and FEWS-RFE respectively. These indicate high rainfall detection capabilities of both satellite products. In addition, both TRMM and FEWS were able to capture the onset, peak and cessation of the rainy season, as well as the dry spells. Although TRMM and FEWS sometimes under/overestimated rainfall, they have the potential to be used for agricultural and other hydro-climatic impact studies over the region. The Dynamic-Aerosol-Cloud-Chemistry Interactions in West Africa (DACCIWA) project will provide an improved spatial gauge network database over the study area to enhance future validation and other climate impact studies.

Highlights

Rainfall is the primary driver of the hydrologic cycle and the main input for hydro meteorological models and climate studies [1]
The Standard Rain Gauge (SRG) and Automatic Rain Gauge (ARG) were at the same location, which explains the high correlation found in the gauge-gauge inter-comparison
First intercomparison between ARG and Ghana Meteorological Agency (GMet) SRG measurements was performed, showing a good agreement with correlation of 0.99, which was an indication that both gauges provided consistent rainfall measurements over the period under study

Summary

Introduction

Rainfall is the primary driver of the hydrologic cycle and the main input for hydro meteorological models and climate studies [1]. It is an essential resource for socioeconomic activities especially for developing countries that rely solely on rain-fed agriculture [2]. Variations in rainfall totals could have negative implications for rainfall dependent agriculture. Rainfall exhibits inter-annual and multi-decadal variability in West Africa [3] [4]. Several studies have shown a downward trend in rainfall for the period 1970 - 2000 ([5], and references therein). There have been signs of recovery in the 2000s [4] [5]

Objectives

Methods

Results

Conclusion