A channel selection method for hyperspectral atmospheric infrared sounders based on layering

Abstract. This study introduces an effective channel selection method for hyperspectral infrared sounders. The method is illustrated for the Atmospheric InfraRed Sounder (AIRS) instrument. The results are as follows. (1) Using the improved channel selection (ICS), the atmospheric retrievable index is more stable, with the value reaching 0.54. The coverage of the weighting functions is more evenly distributed over height with this method. (2) Statistical inversion comparison experiments show that the accuracy of the retrieval temperature, using the improved channel selection method in this paper, is consistent with that of 1D-Var channel selection. In the stratosphere and mesosphere especially, from 10 to 0.02 hPa, the accuracy of the retrieval temperature of our improved channel selection method is improved by about 1 K. The accuracy of the retrieval temperature of ICS is also improved at lower heights. (3) Statistical inversion comparison experiments for four different regions illustrate latitudinal and seasonal variations and better performance of ICS compared to the numerical weather prediction (NWP) channel selection (NCS) and primary channel selection (PCS) methods. The ICS method shows potential for future applications.

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Channel selection method for hyperspectral atmospheric infrared sounder using AIRS data based on layering

10.5194/amt-2019-183 ◽

2019 ◽

Author(s):

Shujie Chang ◽

Zheng Sheng ◽

Huadong Du ◽

Wei Ge ◽

Wei Zhang

Keyword(s):

Channel Selection ◽

Selection Method ◽

Hyperspectral Data ◽

Great Promise ◽

Improved Method ◽

Atmospheric Infrared Sounder ◽

Selection Scheme ◽

Near Space ◽

Effective Channel ◽

Better Than

Abstract. Because a satellite channel’s ability to resolve hyperspectral data varies with height, an improved channel selection method is proposed based on information content. An effective channel selection scheme for a hyperspectral atmospheric infrared sounder using AIRS data based on layering is proposed. The results are as follows: (1) Using the improved method, the atmospheric retrievable index is more stable, the value reaching 0.54. The distribution of the temperature weight function is more continuous, more closely approximating that of the actual atmosphere; (2) Statistical inversion comparison experiments show that the accuracy of the retrieval temperature, using the improved channel selection method in this paper, is consistent with that of 1Dvar channel selection. In the near space layer especially, from 10 hPa to 0.02 hPa, the accuracy of the retrieval temperature of our improved channel selection method is evidently improved by about 1 K. In general, the accuracy of the retrieval temperature of ICS is improved. Especially, from 100 hPa to 0.01 hPa, the accuracy of ICS can be improved by more than 11 %; (3) Statistical inversion comparison experiments in four typical regions indicate that ICS in this paper is significantly better than NCS and PCS in different regions and shows latitudinal variations. Especially, from 100 hPa to 0.01 hPa, the accuracy of ICS can be improved by 7 % to 13 %, which means the ICS method selected in this paper is feasible and shows great promise for applications.

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Update of Infrared Atmospheric Sounding Interferometer (IASI) channel selection with correlated observation errors for numerical weather prediction (NWP)

Atmospheric Measurement Techniques ◽

10.5194/amt-13-2659-2020 ◽

2020 ◽

Vol 13 (5) ◽

pp. 2659-2680

Author(s):

Olivier Coopmann ◽

Vincent Guidard ◽

Nadia Fourrié ◽

Béatrice Josse ◽

Virginie Marécal

Keyword(s):

Numerical Weather Prediction ◽

Weather Forecasting ◽

Weather Prediction ◽

Channel Selection ◽

Observation Error ◽

Numerical Weather ◽

Atmospheric Sounding ◽

Analysis Error ◽

Concept Of Information ◽

Selection Of

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.

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