EGU2020-20682
https://doi.org/10.5194/egusphere-egu2020-20682
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Future water availability in West Africa: Estimates from high-resolution RCM modeling and multivariate bias correction

Diarra Dieng1, Cornelius Hald1, Patrick Laux1,2, Christof Lorenz1, and Harald Kunstmann1,2
Diarra Dieng et al.
  • 1Karlsruhe Institute of Technology Institute for Meteorology and Climate Research Atmospheric Environmental Research Division (IMK-IFU) Campus Alpin, Regional Climate and Hydrology, Garmisch-Partenkirchen, Germany (diarra.dieng@partner.kit.edu)
  • 2Institute of Geography, University of Augsburg, Augsburg, Germany

Future water availability in West Africa: Estimates from high-resolution RCM modeling and multivariate bias correction

Diarra Dieng1, Cornelius Hald1, Patrick Laux1,2, Christof Lorenz1, Harald Kunstmann1,2

1Institute of Meteorology and Climate Research (IMK-IFU), Campus Alpine, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany,

2Institute of Geography, University of Augsburg, Augsburg, Germany,

 

With a wide range of ecological, climatic, and cultural diversities, West Africa is a rapidly developing region whose agricultural systems remain largely rain-fed and underdeveloped. In this study we examine the potential impacts of climate variability and climate change on the water availability in the mid-21st century in West 
Africa by using high resolution simulations (12km) from the Weather and Research Forecasting (WRF) model and the COSMO-Climate Limited area Modelling (CCLM) for the RCP 4.5 scenario. Our approach is based on the simplified Penman-Monteith (PM) equation for daily ET, which requires the joint information on relative humidity, maximum and minimum daily temperatures, dew point temperature, solar radiation and wind speed. It is not only crucial that the statistical behavior of these modelled variables is close to observations, but also that the interplay between these variables is realistic. We therefore further adapted, applied and analyzed a subsequent bias-correction method for the WRF and CCLM simulations using a nonparametric, trend-preserving quantile mapping approach and a multivariate bias correction approach (MBCn). We present the details of the method and the derived implications for expected water availability in West Africa.

How to cite: Dieng, D., Hald, C., Laux, P., Lorenz, C., and Kunstmann, H.: Future water availability in West Africa: Estimates from high-resolution RCM modeling and multivariate bias correction , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20682, https://doi.org/10.5194/egusphere-egu2020-20682, 2020