Announcement of Opportunity: Clear sky/Non precipitating conditions products

A Saphir/Madras retrieval scheme has been developed to retrieve the integrated and vertical distribution of atmospheric water vapour. The algorithm deals with clear and cloudy but non-precipitating scenes, over land and ocean. The retrieval is performed in the Madras Level 1B resolution of the 89 GHz chanbel, at a 10 km horizontal resolution.  
 
The inversion algorithm is based on a neural network scheme that follows the approach described in (Aires et al., 2001; Karbou et al. 2005). A preliminary calibration procedure (Aires et al., 2009) is used to ensure Radiative Transfer Model (RTM) coherency with the chosen reference RTM: RTTOV. The retrievals over land surfaces are made possible by the use of a priori information on the microwave surface emissivities (Prigent et al. 2006).

The retrieval of relative humidity (%) is performed in 6 atmospheric layers:

• 20.400 to 208.16 hPa;

• 208.16 to 376.91 hPa;

• 376.91 to 543.05 hPa;

• 543.05 to 725.55 hPa;

• 725.55 to 902.41 hPa;

• 902.41 to 1013.25 hPa.

The integrated water vapour is given in kg.m-2. 
 
In addition to the water vapour, additional geophysical variables are retrieved such as continental surface temperature and microwave emissivities, or wind speed at 2m over ocean. However these additional retrieved parameters needs further validation. 
 
For more information, contact Filipe Aires (filipe.aires@lmd.jussieu.fr) or Hélène Brogniez (helene.brogniez@latmos.ipsl.fr). 

References:

  • Aires, F., F. Bernardo, H. Brogniez, and C. Prigent, Calibration for the inversion of satellite observations, J. of Applied Meteorology, 2009, submitted.
  • C. Prigent, F. Aires, and W.B. Rossow, Land Surface Microwave Emissivities over the Globe for a Decade. Bulletin of the American Meteorological Society, DOI:10.1175/BAMS-87-11-1573, pp. 1572-1584, Nov. 2006.
  • Karbou, F., Aires, F., Prigent, C. Retrieval of temperature and water vapor atmospheric profiles over Africa using AMSU microwave observations. Journal of Geophysical Research, Vol. 110, No. D7, D07109 10.1029/2004JD005318, 13 April 2005.
  • F. Aires, C. Prigent, W.B. Rossow, and M. Rothstein, A new neural network approach including first-guess for retrieval of atmospheric water vapor, cloud liquid water path, surface temperature and emissivities over land from satellite microwave observations, Journal of Geophysical Research, vol. 106, No. D14, pp. 14,887-14,907, July 27, 2001.