Abstract

Abstract. The Infrared Atmospheric Sounding Interferometer (IASI) is an essential instrument for numerical weather prediction (NWP). It measures radiances at the top of the atmosphere using 8461 channels. The huge amount of observations provided by IASI has led the community to develop techniques to reduce observations while conserving as much information as possible. Thus, a selection of the 300 most informative channels was made for NWP based on the concept of information theory. One of the main limitations of this method was to neglect the covariances between the observation errors of the different channels. However, many centres have shown a significant benefit for weather forecasting to use them. Currently, the observation-error covariances are only estimated on the current IASI channel selection, but no studies to make a new selection of IASI channels taking into account the observation-error covariances have yet been carried out. The objective of this paper was therefore to perform a new selection of IASI channels by taking into account the observation-error covariances. The results show that with an equivalent number of channels, accounting for the observation-error covariances, a new selection of IASI channels can reduce the analysis error on average in temperature by 3 %, humidity by 1.8 % and ozone by 0.9 % compared to the current selection. Finally, we go one step further by proposing a robust new selection of 400 IASI channels to further reduce the analysis error for NWP.

Highlights

  • The use of satellite observations in data assimilation systems has greatly advanced numerical weather prediction (NWP) models

  • The results show that with an equivalent number of channels, accounting for the observation-error covariances, a new selection of Infrared Atmospheric Sounding Interferometer (IASI) channels can reduce the analysis error on average in temperature by 3 %, humidity by 1.8 % and ozone by 0.9 % compared to the current selection

  • The objective of this paper is to perform a new selection of IASI channels by taking into account the observation-error covariances in order to extract a maximum amount of information in a limited number of channels

Read more

Summary

Introduction

The use of satellite observations in data assimilation systems has greatly advanced numerical weather prediction (NWP) models. The Infrared Atmospheric Sounding Interferometer (IASI) is one of the most important satellite instruments supporting NWP centres. This sounder was jointly developed by the Centre National d’Études Spatiales (CNES) and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). The methods for reducing the data volume are channel selection, spatial sampling or principle component analysis. A study by Rabier et al (2002) has highlighted an iterative method that sequentially selects the channels with the highest information content. The Rodgers’ method was used to select the most informative channels of infrared sounders

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call