NDLI: Ensemble retrieval of atmospheric temperature profiles from AIRS

Content Provider	Springer Nature Link
Author	Zhang, Jie Li, Zhenglong Li, Jun Li, Jinglong
Copyright Year	2014
Abstract	Satellite-based observations provide great opportunities for improving weather forecasting. Physical retrieval of atmospheric profiles from satellite observations is sensitive to the uncertainty of the first guess and other factors. In order to improve the accuracy of the physical retrieval, an ensemble methodology was developed with an emphasis on perturbing the first guess. In the methodology, a normal probability density function (PDF) is used to select the optimal profile from the ensemble retrievals. The ensemble retrieval algorithm contains four steps: (1) regression retrieval for original first guess; (2) perturbation of the original first guess to generate new first guesses (ensemble first guesses); (3) using the ensemble first guesses and nonlinear iterative physical retrieval to generate ensemble physical results; and (4) the final optimal profile is selected from the ensemble physical results by using PDF. Temperature eigenvectors (EVs) were used to generate the perturbation and generate the ensemble first guess. Compared with the regular temperature profile retrievals from the Atmospheric InfraRed Sounder (AIRS), the ensemble retrievals RMSE of temperature profiles selected by the PDF was reduced between 150 and 320 hPa and below 400 hPa, with a maximum improvement of 0.3 K at 400 hPa. The bias was also reduced in many layers, with a maximum improvement of 0.69 K at 460 hPa. The combined optimal (CombOpt) profile and a mean optimal (MeanOpt) profile of all ensemble physical results were improved below 150 hPa. The MeanOpt profile was better than the CombOpt profile, and was regarded as the final optimal (FinOpt) profile. This study lays the foundation for improving temperature retrievals from hyper-spectral infrared radiance measurements.
Starting Page	559
Ending Page	569
Page Count	11
File Format	PDF
ISSN	02561530
Journal	Advances in Atmospheric Sciences
Volume Number	31
Issue Number	3
e-ISSN	18619533
Language	English
Publisher	Science Press
Publisher Date	2014-04-03
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	ensemble retrieval perturbation eigenvectors PDF AIRS Atmospheric Sciences Meteorology Geophysics/Geodesy
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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