An online mineral dust forecast model from meso to global scales: 
description, validation and applications

Carlos Perez Garcia-Pando

We describe the NMMB-BSC-Dust model, a new dust aerosol cycle model embedded online 
within the NCEP Non-hydrostatic Multiscale Model (NMMB). The NMMB is an evolution of the 
operational Non-hydrostatic Mesoscale Model (WRF-NMM) extending from meso to global 
scales. Its unified non-hydrostatic dynamical core is prepared for regional and global simulation 
domains. The new unified system is intended to provide dust forecasts from regional to global 
scales, and to be a useful research framework for dust modeling since natural dust distribution 
and effects are important at global scales but strongly depend on emissions that occur on small 
spatial and temporal scales. We will also present the validation of the model from regional to 
global and from daily to yearly scales. The regional model will be used as a complement of the 
GISS ModelE dust module with the aim of improving our understanding of the dust cycle, in 
particular of the dust emission and wet scavenging processes.

Finally, we will explore one of the current applications of the model. Outbreaks of 
Meningococcal Meningitis are mostly concentrated in Sahel region and have long been related 
to the dry and dusty conditions prevailing in the region. In order to study the potential impacts of 
climate and dust on meningitis epidemics we have performed long term simulations with the 
GISS ModelE and the NMMB-BSC-Dust. In this talk we will present the preliminary results of a 
30 year simulation (February 1979- March 2010) with the regional version of the NMMB-BSC-
Dust. The resolution of the model was set to 0.5 X 0.5 degree. The simulation was reinitialized 
every 24 hours with Reanalysis-2 atmospheric data and NASA GLDAS for soil moisture and 
temperature with a spin-up of 12 hours in which only dust is re-cycled from one day to another. 
The fact that meningitis is an infectious disease brings other complex factors such as 
demography and immunological state to play. Here we will provide a preliminary analysis of the 
dust and climate model data compared to meningitis epidemic outbreaks at national and district 
levels in Niger.