Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods
Abstract This study evaluates the impact of assimilating moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) data using different data assimilation (DA) methods on dust analyses and forecasts over North Africa and tropical North Atlantic. To do so, seven experiments are...
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ftdoajarticles:oai:doaj.org/article:c405c887edf44f3ca72dbeca123d434f 2023-11-12T04:22:39+01:00 Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods Yonghan Choi Shu‐Hua Chen Chu‐Chun Huang Kenneth Earl Chih‐Ying Chen Craig S. Schwartz Toshihisa Matsui 2020-04-01T00:00:00Z https://doi.org/10.1029/2019MS001890 https://doaj.org/article/c405c887edf44f3ca72dbeca123d434f EN eng American Geophysical Union (AGU) https://doi.org/10.1029/2019MS001890 https://doaj.org/toc/1942-2466 1942-2466 doi:10.1029/2019MS001890 https://doaj.org/article/c405c887edf44f3ca72dbeca123d434f Journal of Advances in Modeling Earth Systems, Vol 12, Iss 4, Pp n/a-n/a (2020) aerosol assimilation dust model GSI aerosol optical depth (AOD) deep blue AOD Sahara Desert Physical geography GB3-5030 Oceanography GC1-1581 article 2020 ftdoajarticles https://doi.org/10.1029/2019MS001890 2023-10-15T00:38:01Z Abstract This study evaluates the impact of assimilating moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) data using different data assimilation (DA) methods on dust analyses and forecasts over North Africa and tropical North Atlantic. To do so, seven experiments are conducted using the Weather Research and Forecasting dust model and the Gridpoint Statistical Interpolation analysis system. Six of these experiments differ in whether or not AOD observations are assimilated and the DA method used, the latter of which includes the three‐dimensional variational (3D‐Var), ensemble square root filter (EnSRF), and hybrid methods. The seventh experiment, which allows us to assess the impact of assimilating deep blue AOD data, assimilates only dark target AOD data using the hybrid method. The assimilation of MODIS AOD data clearly improves AOD analyses and forecasts up to 48 hr in length. Results also show that assimilating deep blue data has a primarily positive effect on AOD analyses and forecasts over and downstream of the major North African source regions. Without assimilating deep blue data (assimilating dark target only), AOD assimilation only improves AOD forecasts for up to 30 hr. Of the three DA methods examined, the hybrid and EnSRF methods produce better AOD analyses and forecasts than the 3D‐Var method does. Despite the clear benefit of AOD assimilation for AOD analyses and forecasts, the lack of information regarding the vertical distribution of aerosols in AOD data means that AOD assimilation has very little positive effect on analyzed or forecasted vertical profiles of backscatter. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Journal of Advances in Modeling Earth Systems 12 4 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
aerosol assimilation dust model GSI aerosol optical depth (AOD) deep blue AOD Sahara Desert Physical geography GB3-5030 Oceanography GC1-1581 |
spellingShingle |
aerosol assimilation dust model GSI aerosol optical depth (AOD) deep blue AOD Sahara Desert Physical geography GB3-5030 Oceanography GC1-1581 Yonghan Choi Shu‐Hua Chen Chu‐Chun Huang Kenneth Earl Chih‐Ying Chen Craig S. Schwartz Toshihisa Matsui Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods |
topic_facet |
aerosol assimilation dust model GSI aerosol optical depth (AOD) deep blue AOD Sahara Desert Physical geography GB3-5030 Oceanography GC1-1581 |
description |
Abstract This study evaluates the impact of assimilating moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) data using different data assimilation (DA) methods on dust analyses and forecasts over North Africa and tropical North Atlantic. To do so, seven experiments are conducted using the Weather Research and Forecasting dust model and the Gridpoint Statistical Interpolation analysis system. Six of these experiments differ in whether or not AOD observations are assimilated and the DA method used, the latter of which includes the three‐dimensional variational (3D‐Var), ensemble square root filter (EnSRF), and hybrid methods. The seventh experiment, which allows us to assess the impact of assimilating deep blue AOD data, assimilates only dark target AOD data using the hybrid method. The assimilation of MODIS AOD data clearly improves AOD analyses and forecasts up to 48 hr in length. Results also show that assimilating deep blue data has a primarily positive effect on AOD analyses and forecasts over and downstream of the major North African source regions. Without assimilating deep blue data (assimilating dark target only), AOD assimilation only improves AOD forecasts for up to 30 hr. Of the three DA methods examined, the hybrid and EnSRF methods produce better AOD analyses and forecasts than the 3D‐Var method does. Despite the clear benefit of AOD assimilation for AOD analyses and forecasts, the lack of information regarding the vertical distribution of aerosols in AOD data means that AOD assimilation has very little positive effect on analyzed or forecasted vertical profiles of backscatter. |
format |
Article in Journal/Newspaper |
author |
Yonghan Choi Shu‐Hua Chen Chu‐Chun Huang Kenneth Earl Chih‐Ying Chen Craig S. Schwartz Toshihisa Matsui |
author_facet |
Yonghan Choi Shu‐Hua Chen Chu‐Chun Huang Kenneth Earl Chih‐Ying Chen Craig S. Schwartz Toshihisa Matsui |
author_sort |
Yonghan Choi |
title |
Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods |
title_short |
Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods |
title_full |
Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods |
title_fullStr |
Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods |
title_full_unstemmed |
Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods |
title_sort |
evaluating the impact of assimilating aerosol optical depth observations on dust forecasts over north africa and the east atlantic using different data assimilation methods |
publisher |
American Geophysical Union (AGU) |
publishDate |
2020 |
url |
https://doi.org/10.1029/2019MS001890 https://doaj.org/article/c405c887edf44f3ca72dbeca123d434f |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Journal of Advances in Modeling Earth Systems, Vol 12, Iss 4, Pp n/a-n/a (2020) |
op_relation |
https://doi.org/10.1029/2019MS001890 https://doaj.org/toc/1942-2466 1942-2466 doi:10.1029/2019MS001890 https://doaj.org/article/c405c887edf44f3ca72dbeca123d434f |
op_doi |
https://doi.org/10.1029/2019MS001890 |
container_title |
Journal of Advances in Modeling Earth Systems |
container_volume |
12 |
container_issue |
4 |
_version_ |
1782337627463090176 |