Improvements to the AERIoe Thermodynamic Profile Retrieval Algorithm

Temperature and humidity profiles in the atmospheric boundary layer (i.e., from the surface to 3 km) can be retrieved from ground-based spectral infrared observations made by the atmospheric emitted radiance interferometer (AERI) at high temporal and moderate vertical resolution. However, the retrie...

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Published in:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Main Authors: David D. Turner, W. Greg Blumberg
Format: Article in Journal/Newspaper
Language:English
Published: IEEE 2019
Subjects:
Online Access:https://doi.org/10.1109/JSTARS.2018.2874968
https://doaj.org/article/8bd2f9efd1344760a1913d7a5023dc3e
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spelling ftdoajarticles:oai:doaj.org/article:8bd2f9efd1344760a1913d7a5023dc3e 2023-05-15T15:08:28+02:00 Improvements to the AERIoe Thermodynamic Profile Retrieval Algorithm David D. Turner W. Greg Blumberg 2019-01-01T00:00:00Z https://doi.org/10.1109/JSTARS.2018.2874968 https://doaj.org/article/8bd2f9efd1344760a1913d7a5023dc3e EN eng IEEE https://ieeexplore.ieee.org/document/8576572/ https://doaj.org/toc/2151-1535 2151-1535 doi:10.1109/JSTARS.2018.2874968 https://doaj.org/article/8bd2f9efd1344760a1913d7a5023dc3e IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 12, Iss 5, Pp 1339-1354 (2019) Atmospheric measurements infrared radiometry remote sensing Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809 article 2019 ftdoajarticles https://doi.org/10.1109/JSTARS.2018.2874968 2022-12-31T12:47:48Z Temperature and humidity profiles in the atmospheric boundary layer (i.e., from the surface to 3 km) can be retrieved from ground-based spectral infrared observations made by the atmospheric emitted radiance interferometer (AERI) at high temporal and moderate vertical resolution. However, the retrieval is an ill-posed problem, and thus there are multiple thermodynamic solutions that might satisfy the observed radiances. Previous work developed a physical-iterative method called AERIoe that retrieved temperature and water vapor mixing ratio profiles from these radiance observations in both clear and cloudy conditions. The AERIoe algorithm was modified to enforce two physical constraints, namely that the derived relative humidity must be less than 100% and that the potential temperature must be monotonically increasing with height above some thin potentially subadiabatic layer after each iteration. Furthermore, additional observations including in situ surface meteorology, numerical weather prediction model output, microwave brightness temperatures, and partial profiles of water vapor from a Raman lidar were incorporated into the observation vector of the retrieval along with the infrared radiance observations. The addition of these new observations markedly improved the accuracy of the temperature profiles, especially above 2 km, and the water vapor profiles relative to radiosondes. These improvements are seen using cases from the tropics, mid-latitudes, and Arctic. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12 5 1339 1354
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Atmospheric measurements
infrared radiometry
remote sensing
Ocean engineering
TC1501-1800
Geophysics. Cosmic physics
QC801-809
spellingShingle Atmospheric measurements
infrared radiometry
remote sensing
Ocean engineering
TC1501-1800
Geophysics. Cosmic physics
QC801-809
David D. Turner
W. Greg Blumberg
Improvements to the AERIoe Thermodynamic Profile Retrieval Algorithm
topic_facet Atmospheric measurements
infrared radiometry
remote sensing
Ocean engineering
TC1501-1800
Geophysics. Cosmic physics
QC801-809
description Temperature and humidity profiles in the atmospheric boundary layer (i.e., from the surface to 3 km) can be retrieved from ground-based spectral infrared observations made by the atmospheric emitted radiance interferometer (AERI) at high temporal and moderate vertical resolution. However, the retrieval is an ill-posed problem, and thus there are multiple thermodynamic solutions that might satisfy the observed radiances. Previous work developed a physical-iterative method called AERIoe that retrieved temperature and water vapor mixing ratio profiles from these radiance observations in both clear and cloudy conditions. The AERIoe algorithm was modified to enforce two physical constraints, namely that the derived relative humidity must be less than 100% and that the potential temperature must be monotonically increasing with height above some thin potentially subadiabatic layer after each iteration. Furthermore, additional observations including in situ surface meteorology, numerical weather prediction model output, microwave brightness temperatures, and partial profiles of water vapor from a Raman lidar were incorporated into the observation vector of the retrieval along with the infrared radiance observations. The addition of these new observations markedly improved the accuracy of the temperature profiles, especially above 2 km, and the water vapor profiles relative to radiosondes. These improvements are seen using cases from the tropics, mid-latitudes, and Arctic.
format Article in Journal/Newspaper
author David D. Turner
W. Greg Blumberg
author_facet David D. Turner
W. Greg Blumberg
author_sort David D. Turner
title Improvements to the AERIoe Thermodynamic Profile Retrieval Algorithm
title_short Improvements to the AERIoe Thermodynamic Profile Retrieval Algorithm
title_full Improvements to the AERIoe Thermodynamic Profile Retrieval Algorithm
title_fullStr Improvements to the AERIoe Thermodynamic Profile Retrieval Algorithm
title_full_unstemmed Improvements to the AERIoe Thermodynamic Profile Retrieval Algorithm
title_sort improvements to the aerioe thermodynamic profile retrieval algorithm
publisher IEEE
publishDate 2019
url https://doi.org/10.1109/JSTARS.2018.2874968
https://doaj.org/article/8bd2f9efd1344760a1913d7a5023dc3e
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 12, Iss 5, Pp 1339-1354 (2019)
op_relation https://ieeexplore.ieee.org/document/8576572/
https://doaj.org/toc/2151-1535
2151-1535
doi:10.1109/JSTARS.2018.2874968
https://doaj.org/article/8bd2f9efd1344760a1913d7a5023dc3e
op_doi https://doi.org/10.1109/JSTARS.2018.2874968
container_title IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
container_volume 12
container_issue 5
container_start_page 1339
op_container_end_page 1354
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