Will the best WRF please identify itself? 
Choosing the best WRF configuration for precipitation and circulation 
simulations over West Africa.

Erik Noble

The NCAR Weather and Research Forecasting model (WRF) was initially 
developed for forecasting weather and facilitating research into mid-
latitude weather applications. Today, as regional climate modeling 
becomes more prevalent, use of WRF as a regional climate model (RCM) is 
also becoming more widespread. Published studies that demonstrate the 
WRF's performance for downscaling both reanalysis and climate 
projections focus on North America. Less has been reported on testing 
the WRF performance for other regions, particularly for West Africa, 
which is the focus of this work.  

West Africa is of particular interest to climate scientists because of 
its vulnerability to recurring drought, often associated with a late 
onset of the West African Monsoon (WAM) during some summers. WAM 
precipitation events are organized by transient African Easterly Waves 
(AEWs). Although model-based climate studies relate to monthly or 
seasonally mean fields, confidence in predictions of the seasonal 
climate improves if the model realistically captures the 
characteristics of relevant daily weather phenomena. Therefore, a 
series of numerical experiments was conducted to evaluate WRF 
performance for downscaling reanalysis data sets and its simulation of 
AEWs and associated spatial precipitation patterns. Results are 
validated against observational evidence from reanalysis, satellite 
platforms, and results from an RCM already optimized for West Africa. 
This current study aims to optimize the performance of the WRF model as 
a downscaling tool at daily timescales as a first step in evaluating 
its performance for monthly to intraseasonal timescales. The 
suggestions of optimal WRF configurations resulting from this 
evaluation should benefit other investigators planning WRF applications 
over West Africa.  

Initial analyses of current simulations will be discussed with a focus 
on a 2-week period studied during the 2006 African Monsoon 
Multidisciplinary Analyses field campaign.