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Improved Temperature Sounding and Quality Control Methodology Using AIRS/AMSU Data: The AIRS Science Team Version 5 Retrieval Algorithm

Improved Temperature Sounding and Quality Control Methodology Using AIRS/AMSU Data: The AIRS Science Team Version 5 Retrieval Algorithm,10.1109/TGRS.2

Improved Temperature Sounding and Quality Control Methodology Using AIRS/AMSU Data: The AIRS Science Team Version 5 Retrieval Algorithm   (Citations: 9)
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This paper describes the Atmospheric Infrared Sounder (AIRS) Science Team Version 5 retrieval algorithm in terms of its three most significant improvements over the method- ology used in the AIRS Science Team Version 4 retrieval al- gorithm: the use of AIRS clear-column radiances in the entire 4.3-μ mC O 2 absorption band in the retrieval of temperature profiles T (p) during both day and night, with tropospheric sound- ing of 15-μ mC O 2 observations now being used primarily in the generation of clear-column radiances ˆ Ri for all channels; development of a new methodology to provide accurate case-by- case error estimates for retrieved geophysical parameters and for channel-by-channel clear column radiances and their use in a new approach for quality control; and an approach to provide AIRS soundings in partially cloudy conditions that does not require use of any microwave data. This new AIRS-only sounding methodol- ogy, referred to as AIRS Version 5 AO, was developed as a backup to AIRS Version 5 should the Advanced Microwave Sounding Unit (AMSU)-A instrument fail. Results are shown that compare the relative performance of the AIRS Version 4, Version 5, and Version 5 AO. Results using Version 5 retrievals in conjunction with different quality control thresholds are also shown for a recent period to demonstrate that empirical coefficients continue to be applicable in later time periods. The Goddard Data and Information Services Center (DISC) is now generating and dis- tributing products derived using the AIRS Science Team Version 5 retrieval algorithm. This paper describes the quality control flags contained in the DISC AIRS/AMSU retrieval products and their intended use for scientific purposes. Index Terms—Atmospheric Infrared Sounder/Advanced Mi- crowave Sounding Unit (AIRS/AMSU), cloud-cleared radiances, error estimates, high spectral-resolution infrared sounders, infrared sounding in cloudy conditions, retrieval methodology.
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    • ...Cloud clearing techniques combining the nine 1.1 ◦ AIRS fields-of-view within one 3.3 ◦ AMSU field-of-view yield successful AIRS+AMSU retrievals over approximately 50% of the planet for both day and night scenes up to 80% cloudy [4]–[6]...
    • ...The overall AIRS v5 retrieval algorithm is described in [6]...
    • ...The Constituent Good flag is an internal indicator set to true if the total water vapor error estimate is less that 35% of the total retrieved water vapor [6], [56]...

    W. W. McMillanet al. Validating the AIRS Version 5 CO Retrieval With DACOM In Situ Measurem...

    • ...<{[SECTION]}>AIRS/AMSU/HSB soundings [1] on the NASA Aqua satellite and...
    • ...Recent approaches include flagging suspect retrievals [1] and use of Bayesian neural network analysis [5], [6], [7]...

    William J. Blackwellet al. Neural network estimation of atmospheric profiles using AIRS/AMSU obse...

    • ...The method for retrieving atmospheric moisture profiles is an iterative least squares solution that minimizes the dependence of the result on the first guess and simplifies assumptions about the properties of the clouds in the scene [Susskind et al., 2003, 2006, 2010]...
    • ...Clear column radiances are estimated using data from these two unique instruments, making the retrieval of temperature and moisture profiles possible in scenes that have up to 80% cloud fraction [Chahine, 1974, 1977; Susskind et al., 2003, 2006, 2010]...
    • ...[10] This study examines AIRS level 2 v5 moisture products, which are available beginning with September 2002 and which include a number of improvements to both moisture retrieval quality and error estimation over previous versions, especially over land [Susskind et al., 2010]...

    Sarah Bedkaet al. An assessment of the absolute accuracy of the Atmospheric Infrared Sou...

    • ...Recent studies show that even in the presence of significant cloudiness, biases in temperature and water vapor are not significantly increased [Wu, 2009; Susskind et al., 2010], despite the reduced sampling frequency [Fetzer et al., 2006]...
    • ...Details of the AIRS algorithms are described by Susskind et al. [2010]...
    • ...It is reassuring that the PBL T bias is similar to the bias in the sub‐tropical free troposphere where AIRS is expected to be particularly reliable [e.g., Susskind et al., 2010]...
    • ...The biases and RMSE values are consistent with prelaunch requirements of the AIRS retrieval algorithm [e.g., Goldberg et al., 2003; Divakarla et al., 2006; Susskind et al., 2010]...
    • ...All these factors are known to increase the apparent error of the AIRS data [e.g., Divakarla et al., 2006; Susskind et al., 2010] and CF, LF and OLR are part of the AIRS L2 Support dataset (results were not included here for the sake of brevity)...

    João P. A. Martinset al. Infrared sounding of the trade-wind boundary layer: AIRS and the RICO ...

    • ...This new approach of determining i using longwave observations and temperature profile using shortwave observations follows theoretical considerations [2,3], and allows for the generation of accurate Quality Controlled values of i and temperature profile under more stressing cloud conditions...

    Joel Susskindet al. Improved determination of surface and atmospheric temperatures using o...

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