WRF-Meningitis study

Google-UCAR Africa Meningitis Belt Initiative

In an effort to aid the prototype Earth-gauging system UCAR Google initiative, the NCSU Climate Modeling Laboratory
is performing dynamical downscaling of operational forecasts for the West Africa region.
For this, the Weather Research and Forecast Model (WRF) Version 2 is currently being tested for optimization purposes
and to diagnose added value that dynamical downscaling may provide to operational forecasts.

Preliminary Results

Dynamical Downscaling

Using the WRF climate mode at scales finer than the available coarse-scale operational models (1 degree), we recognize that running the
model at 30km, for example, allows for the forecast of specific districts or other geopolitical divisions within a country.
The figure below atests to the advantages of using finer scale forecasting. The arrows point to a collection of 3 or 4 districts
in the southwest portion of the country of Niger and eastern Burkina-Faso as portrayed by a World Health Organization (WHO)
meningitis alert map (left), and relative humidity in a WRF simulation at 30km resolution (top right) and NNRP1 reanalysis at 2.5km resolution (bottom right).
Some features to look at include the generalization in NNRP1 with larger spacing between categories (i.e. 30-40% RH) whilst a
similar image from the WRF simulation has much more detailed spacing between categories.
Also, notice how the drier, cooler colors cover a larger area of Niger and Burkina-Faso. Because this particular type of meningitis has
been found to be so climate sensitive to changes in humidity regime, such changes in relative humidity can offer valuable information
for stakeholders in the region in terms of supplies and transportation for inoculation purposes.

Ensemble Forecasting

Efforts currently underway at UCAR will seek to use an ensemble of large scale models to provide operational forecasts for the
Africa initiative. The NCSU Climate Modeling Laboratory will also explore the use of ensemble forecasting by downscaling each of the
models in operational mode using WRF. Additionally, we will explore the relative skill and economic value of the ensemble prediction
forecast using the recently published EROC method. Currently underway is a WRF climate mode ensemble using FNL initial conditions
and varying physics in the model to simulate multiple model ensemble.


References and Links

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