Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty
The need for highly accurate atmospheric wind observations is a high priority in the science community, particularly for numerical weather prediction (NWP). To address this need, this study leverages Aeolus wind lidar level-2B data provided by the European Space Agency (ESA) as a potential compariso...
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Copernicus Publications
2022
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Online Access: | https://doi.org/10.5194/amt-15-2719-2022 https://doaj.org/article/a533f18546a3410f8bac57521dcce9cf |
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ftdoajarticles:oai:doaj.org/article:a533f18546a3410f8bac57521dcce9cf 2023-05-15T13:56:52+02:00 Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty K. E. Lukens K. Ide K. Garrett H. Liu D. Santek B. Hoover R. N. Hoffman 2022-05-01T00:00:00Z https://doi.org/10.5194/amt-15-2719-2022 https://doaj.org/article/a533f18546a3410f8bac57521dcce9cf EN eng Copernicus Publications https://amt.copernicus.org/articles/15/2719/2022/amt-15-2719-2022.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-15-2719-2022 1867-1381 1867-8548 https://doaj.org/article/a533f18546a3410f8bac57521dcce9cf Atmospheric Measurement Techniques, Vol 15, Pp 2719-2743 (2022) Environmental engineering TA170-171 Earthwork. Foundations TA715-787 article 2022 ftdoajarticles https://doi.org/10.5194/amt-15-2719-2022 2022-12-30T23:35:57Z The need for highly accurate atmospheric wind observations is a high priority in the science community, particularly for numerical weather prediction (NWP). To address this need, this study leverages Aeolus wind lidar level-2B data provided by the European Space Agency (ESA) as a potential comparison standard to better characterize atmospheric motion vector (AMV) bias and uncertainty. AMV products from geostationary (GEO) and low Earth orbiting (LEO) satellites are compared with reprocessed Aeolus horizontal line-of-sight (HLOS) global winds observed in August–September 2019. Winds from two Aeolus observing modes are compared with AMVs, namely Rayleigh-clear (RAY; derived from the molecular scattering signal) and Mie-cloudy (MIE; derived from the particle scattering signal). Quality-controlled (QC'd) Aeolus winds are co-located with QC'd AMVs in space and time, and the AMVs are projected onto the Aeolus HLOS direction. Mean co-location differences (MCDs) and the standard deviation (SD) of those differences (SDCDs) are determined and analyzed. As shown in other comparison studies, the level of agreement between AMV and Aeolus wind velocities (HLOSVs) varies with the AMV type, geographic region, and height of the co-located winds, as well as with the Aeolus observing mode. In terms of global statistics, QC'd AMVs and QC'd Aeolus HLOSVs are highly correlated for both observing modes. Aeolus MIE winds are shown to have great potential value as a comparison standard to characterize AMVs, as MIE co-locations generally exhibit smaller biases and uncertainties compared to RAY co-locations. Aeolus RAY winds contribute a substantial fraction of the total SDCDs in the presence of clouds where co-location/representativeness errors are also large. Stratified comparisons with Aeolus HLOSVs are consistent with known AMV bias and uncertainty in the tropics, NH extratropics, the Arctic, and at mid- to upper-levels in clear and cloudy scenes. AMVs in the SH/Antarctic generally exhibit larger-than-expected MCDs and SDCDs, most ... Article in Journal/Newspaper Antarc* Antarctic Arctic Directory of Open Access Journals: DOAJ Articles Aeolus ENVELOPE(161.267,161.267,-77.483,-77.483) Antarctic Arctic Atmospheric Measurement Techniques 15 9 2719 2743 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental engineering TA170-171 Earthwork. Foundations TA715-787 |
spellingShingle |
Environmental engineering TA170-171 Earthwork. Foundations TA715-787 K. E. Lukens K. Ide K. Garrett H. Liu D. Santek B. Hoover R. N. Hoffman Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty |
topic_facet |
Environmental engineering TA170-171 Earthwork. Foundations TA715-787 |
description |
The need for highly accurate atmospheric wind observations is a high priority in the science community, particularly for numerical weather prediction (NWP). To address this need, this study leverages Aeolus wind lidar level-2B data provided by the European Space Agency (ESA) as a potential comparison standard to better characterize atmospheric motion vector (AMV) bias and uncertainty. AMV products from geostationary (GEO) and low Earth orbiting (LEO) satellites are compared with reprocessed Aeolus horizontal line-of-sight (HLOS) global winds observed in August–September 2019. Winds from two Aeolus observing modes are compared with AMVs, namely Rayleigh-clear (RAY; derived from the molecular scattering signal) and Mie-cloudy (MIE; derived from the particle scattering signal). Quality-controlled (QC'd) Aeolus winds are co-located with QC'd AMVs in space and time, and the AMVs are projected onto the Aeolus HLOS direction. Mean co-location differences (MCDs) and the standard deviation (SD) of those differences (SDCDs) are determined and analyzed. As shown in other comparison studies, the level of agreement between AMV and Aeolus wind velocities (HLOSVs) varies with the AMV type, geographic region, and height of the co-located winds, as well as with the Aeolus observing mode. In terms of global statistics, QC'd AMVs and QC'd Aeolus HLOSVs are highly correlated for both observing modes. Aeolus MIE winds are shown to have great potential value as a comparison standard to characterize AMVs, as MIE co-locations generally exhibit smaller biases and uncertainties compared to RAY co-locations. Aeolus RAY winds contribute a substantial fraction of the total SDCDs in the presence of clouds where co-location/representativeness errors are also large. Stratified comparisons with Aeolus HLOSVs are consistent with known AMV bias and uncertainty in the tropics, NH extratropics, the Arctic, and at mid- to upper-levels in clear and cloudy scenes. AMVs in the SH/Antarctic generally exhibit larger-than-expected MCDs and SDCDs, most ... |
format |
Article in Journal/Newspaper |
author |
K. E. Lukens K. Ide K. Garrett H. Liu D. Santek B. Hoover R. N. Hoffman |
author_facet |
K. E. Lukens K. Ide K. Garrett H. Liu D. Santek B. Hoover R. N. Hoffman |
author_sort |
K. E. Lukens |
title |
Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty |
title_short |
Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty |
title_full |
Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty |
title_fullStr |
Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty |
title_full_unstemmed |
Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty |
title_sort |
exploiting aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty |
publisher |
Copernicus Publications |
publishDate |
2022 |
url |
https://doi.org/10.5194/amt-15-2719-2022 https://doaj.org/article/a533f18546a3410f8bac57521dcce9cf |
long_lat |
ENVELOPE(161.267,161.267,-77.483,-77.483) |
geographic |
Aeolus Antarctic Arctic |
geographic_facet |
Aeolus Antarctic Arctic |
genre |
Antarc* Antarctic Arctic |
genre_facet |
Antarc* Antarctic Arctic |
op_source |
Atmospheric Measurement Techniques, Vol 15, Pp 2719-2743 (2022) |
op_relation |
https://amt.copernicus.org/articles/15/2719/2022/amt-15-2719-2022.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-15-2719-2022 1867-1381 1867-8548 https://doaj.org/article/a533f18546a3410f8bac57521dcce9cf |
op_doi |
https://doi.org/10.5194/amt-15-2719-2022 |
container_title |
Atmospheric Measurement Techniques |
container_volume |
15 |
container_issue |
9 |
container_start_page |
2719 |
op_container_end_page |
2743 |
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1766264460903710720 |