Observations for


a) Dekadal (i.e., ~10-daily) dust concentration estimates for the selected region from 2000 to the 2006.

Regional Dust Model

This map shows the presence of dust over northern Africa in dekadal (10-day) averages.

Mineral dust particles emitted from arid and semi-arid areas are one of the most important sources of atmospheric desert aerosol mass (Perez et.al.).

Studies have shown that destabilized mucous membranes in the pharynx allow for the meningitis bacteria to pass through the blood, thus increasing the probability of infection. The desert aerosols (dust) are used as a predictive indicator to meningitis epidemics as they tend to destabilize mucous membranes and lead to increased vulnerability of a population.

Aerosol monitoring analyses can be viewed on the Multi-angle Imaging SpectroRadiometer (MISR) and the Ozone Monitoring Instrument (OMI) map pages.

Reference: Perez, C., K. Haustein, et. al, 2011: Atmospheric Dust Modeling from meso to global scales with the online NMMB/BSC-Dust model-Part 1: Model Description, annual simulations and evaluation. Atmos. Chem. Phys., 11, 13001-13027.

Dataset Documentation

Aerosol Index based on a Dust Model

Dekadal PM10 dust concentrations on a 1.25° x 1.25° lat/lon grid
Data Source
Carlos Pérez García-Pando NASA GISS (Regional Dust Model from NASA GISS)*

The map shows an aerosol index based on dekadal averages of a regional dust concentration model at 10 meters. Data is available from 1985-2006.

Dust concentration indicates the presence of particles on the order of ~10 micrometers or less (PM10).


Access the dataset used to create this map.


Contact help@iri.columbia.edu with any technical questions or problems with this Map Room, for example, the forecasts not displaying or updating properly.


The Regional Dust Model interface consists of a clickable map that allows users to generate customized time series graphs.

When a desired northern African location is clicked, a time series graph will be generated that allows users to view recent dust concentration analyses in a seasonal and recent historical perspective.

The interface also allows users to select different scales of spatial averaging.