Performance of the WRF model to simulate the seasonal and interannual variability of hydrometeorological variables in East Africa: a case study for the Tana River basin in Kenya

Noah Misati Kerandi,Joel Arnault,Harald Kunstmann,Patrick Laux

doi:10.1007/s00704-016-1890-y

Abstract

This study investigates the ability of the regional climate model Weather Research and Forecasting (WRF) in simulating the seasonal and interannual variability of hydrometeorological variables in the Tana River basin (TRB) in Kenya, East Africa. The impact of two different land use classifications, i.e., the Moderate Resolution Imaging Spectroradiometer (MODIS) and the US Geological Survey (USGS) at two horizontal resolutions (50 and 25 km) is investigated. Simulated precipitation and temperature for the period 2011–2014 are compared with Tropical Rainfall Measuring Mission (TRMM), Climate Research Unit (CRU), and station data. The ability of Tropical Rainfall Measuring Mission (TRMM) and Climate Research Unit (CRU) data in reproducing in situ observation in the TRB is analyzed. All considered WRF simulations capture well the annual as well as the interannual and spatial distribution of precipitation in the TRB according to station data and the TRMM estimates. Our results demonstrate that the increase of horizontal resolution from 50 to 25 km, together with the use of the MODIS land use classification, significantly improves the precipitation results. In the case of temperature, spatial patterns and seasonal cycle are well reproduced, although there is a systematic cold bias with respect to both station and CRU data. Our results contribute to the identification of suitable and regionally adapted regional climate models (RCMs) for East Africa.

Highlights

Understanding the variability of hydrometeorological variables in water-stressed environments like in East Africa is fundamental in addressing water challenges, especially in the context of climate and land use change
The CORDEX experiment results indicated that the Weather Research and Forecasting (WRF) based on Kain Fritsch (KF) cumulus convection, WRF Single-Moment 5-class (WSM5) microphysics, Yonsei University (YSU) planetary boundary, Dudhia short wave radiation, and Rapid Radiative Transfer Model (RRTM) long wave radiation schemes overestimated rainfall far above all the other regional climate model (RCM) that were assessed
Pohl et al (2011) stated that the horizontal resolution of the RCM could influence the results of simulations in this region; they highlighted the need to study the intraseasonal variability in this region and to conduct further sensitivity experiments with models like WRF due to the relatively high uncertainties associated with the model physics and domain geometry

Summary

Introduction

Understanding the variability of hydrometeorological variables in water-stressed environments like in East Africa is fundamental in addressing water challenges, especially in the context of climate and land use change. Pohl et al (2011) tested a number of WRF model settings (i.e., physical parameterization, land use categories, domain size and number of vertical levels) in simulating the seasonal water cycle over the Equatorial East Africa for 1999 In their study, they found WRF simulations of a spatial resolution of 12 km were closest to that from the Global Precipitation Climatology Project daily (GPCP-1dd) gridded rainfall product, when combining the Kain Fritsch (KF) cumulus scheme with the WRF Single-Moment 6-class (WSM6) microphysics, Asymmetric Convective Model (ACM2) planetary boundary layer, Dudhia short wave radiation, and the Rapid Radiative Transfer Model (RRTM) long wave radiation scheme.

Methods

Results

Conclusion