The Saharan Dust Index (SDI) has been designed to evaluate the level of contamination of MSG/SEVIRI Infrared brightness temperatures by Saharan Dust. It aims in particular to correct or flag satellite derived SST values. The present product is derived from a combination of MSG/SEVIRI brightness temperatures at 3.9, 8.7, 10.8 and 12.0 microns as described in Merchant et al, 2006. Since the SDI determination requires use of 3.9 micron brightness temperature, which is contaminated by sun light, the exact caculation is done in nighttime conditions. The values by day result from linear combinations of 8.7, 10.8 , 12.0 and 13.4 micron brightness temperatures. Their coefficients are derived regionally by regressions on the nighttime SDI values calculated the previous night and then interpolated at pixel level.
The SDI products are delivered on a hourly basis in NRT on a regular grid at 0.05 degree resolution, centered at 0N, 0E, in netcdf-4 files. A SDI file contains the following variables (see also the file header) :
- landmask : auxiliary land mask
- sdi : the Saharan Dust Index: It is a dimensionlesss index, values above 0.1 are considered as indicative of a possible Saharan Dust contamination
- sdi_method : describes the method used(daytime, i.e interpolated or nighttime).
- sdi_coeff_age : in case of a daytime method, gives the age of the regression coefficients (a quality information: the smallest the best)
- sst_mask_ind : on a 0 (excellent) to 100 (critical) scale : gives the confidence in the cloud mask used - the same as for SST products- to derive this product
Please note that in case this product has been used for the study described in a paper, an appropriate reference to the origin of the product (Météo-France/CMS) should be given.
Visualisation of the product is also possible through Calypso online tool. Go here.
C.J. Merchant, O. Embury, P. Le Borgne, B. Bellec, (2006) , Saharan dust in nighttime thermal imagery: Detection and reduction of related biases in retrieved sea surface temperature <http://www.sciencedirect.com/science/article/pii/S0034425706001271> , Remote Sensing of Environment, Volume 104, Issue 1, 15 September 2006, Pages 15-30