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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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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1766339832579096576 |