Article Type:
Research Article

Improvement of the Temperature and Moisture Retrievals in the Lower Troposphere Using AIRS and GPS Radio Occultation Measurements

Shu-Peng Ho National Center for Atmospheric Research, * Boulder, Colorado

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Ying-Hwa Kuo National Center for Atmospheric Research,* and University Corporation for Atmospheric Research, Boulder, Colorado

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Sergey Sokolovskiy University Corporation for Atmospheric Research, Boulder, Colorado

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Print Publication:
01 Oct 2007
DOI:
https://doi.org/10.1175/JTECH2071.1
Page(s):
1726–1739
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Abstract

Accurate temperature and water vapor profiles in the middle and lower troposphere (LT) are crucial for understanding the water cycle, cloud systems, and energy balance. Global positioning system (GPS) radio occultation (RO) is the first technique that can provide a high-vertical-resolution all-weather refractivity profile, which is a function of pressure, temperature, and moisture. However, in the moist LT over the Tropics, the refractivity retrievals from GPS RO data are often significantly negatively biased because of tracking errors and propagation effects related to sharp vertical moisture gradients that may result in superrefraction (SR). The Atmospheric Infrared Sounder (AIRS) is a nadir-viewing sounder that can measure vertical temperature and moisture profiles with about 1–2-km vertical resolution. However, AIRS observations cannot usually obtain accurate temperature and water vapor profiles in the planetary boundary layer (PBL) because of the poor resolving power in the LT. This study uses simulations based on radiosonde profiles by combining the AIRS and the GPS RO measurements to obtain the best temperature and moisture retrievals in the LT. Different approaches are used for the drier LT and the moist LT. For the drier LT, where GPS RO data are not affected by SR errors, a multivariable regression algorithm for inverting the combined AIRS and GPS RO measurements is used. In the moist LT (e.g., SR on top of PBL), the combined AIRS and GPS RO regression inversion above the LT is used as the first guess for AIRS-only physical retrieval, which is extended into the LT. The results show that combining AIRS and GPS RO data effectively constrains the individual solutions, and therefore significantly improves inversion results. The algorithm is also applied for all available radiosonde profiles (19 profiles) over a 1-month period from the site characterized by strong SR on top of the PBL. Retrieved temperature and water vapor profiles yield unbiased low-resolution refractivity profiles in the PBL.

* The National Center for Atmospheric Research is sponsored by the National Science Foundation

Corresponding author address: Dr. Shu-Peng Ho, Atmospheric Chemistry Division, National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307-3000. Email: spho@ucar.edu

Abstract

Accurate temperature and water vapor profiles in the middle and lower troposphere (LT) are crucial for understanding the water cycle, cloud systems, and energy balance. Global positioning system (GPS) radio occultation (RO) is the first technique that can provide a high-vertical-resolution all-weather refractivity profile, which is a function of pressure, temperature, and moisture. However, in the moist LT over the Tropics, the refractivity retrievals from GPS RO data are often significantly negatively biased because of tracking errors and propagation effects related to sharp vertical moisture gradients that may result in superrefraction (SR). The Atmospheric Infrared Sounder (AIRS) is a nadir-viewing sounder that can measure vertical temperature and moisture profiles with about 1–2-km vertical resolution. However, AIRS observations cannot usually obtain accurate temperature and water vapor profiles in the planetary boundary layer (PBL) because of the poor resolving power in the LT. This study uses simulations based on radiosonde profiles by combining the AIRS and the GPS RO measurements to obtain the best temperature and moisture retrievals in the LT. Different approaches are used for the drier LT and the moist LT. For the drier LT, where GPS RO data are not affected by SR errors, a multivariable regression algorithm for inverting the combined AIRS and GPS RO measurements is used. In the moist LT (e.g., SR on top of PBL), the combined AIRS and GPS RO regression inversion above the LT is used as the first guess for AIRS-only physical retrieval, which is extended into the LT. The results show that combining AIRS and GPS RO data effectively constrains the individual solutions, and therefore significantly improves inversion results. The algorithm is also applied for all available radiosonde profiles (19 profiles) over a 1-month period from the site characterized by strong SR on top of the PBL. Retrieved temperature and water vapor profiles yield unbiased low-resolution refractivity profiles in the PBL.

* The National Center for Atmospheric Research is sponsored by the National Science Foundation

Corresponding author address: Dr. Shu-Peng Ho, Atmospheric Chemistry Division, National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307-3000. Email: spho@ucar.edu

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