Evaluating the impact of assimilating aerosol optical depth observations on dust forecasts over North Africa and the East Atlantic using different data assimilation methods
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 conducte...
Published in: | Journal of Advances in Modeling Earth Systems |
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Language: | English |
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Online Access: | https://doi.org/10.1029/2019MS001890 |
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ftncar:oai:drupal-site.org:articles_23513 2024-04-28T08:31:06+00:00 Evaluating the impact of assimilating aerosol optical depth observations on dust forecasts over North Africa and the East Atlantic using different data assimilation methods Choi, Yonghan (author) Chen, Shu‐Hua (author) Huang, Chu‐Chun (author) Earl, Kenneth (author) Chen, Chih‐Ying (author) Schwartz, Craig S. (author) Matsui, Toshihisa (author) 2020-04-04 https://doi.org/10.1029/2019MS001890 en eng Journal of Advances in Modeling Earth Systems--J. Adv. Model. Earth Syst.--1942-2466--1942-2466 articles:23513 ark:/85065/d7bv7kw6 doi:10.1029/2019MS001890 Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. article Text 2020 ftncar https://doi.org/10.1029/2019MS001890 2024-04-04T17:32:42Z 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 OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research) Journal of Advances in Modeling Earth Systems 12 4 |
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Open Polar |
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OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research) |
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ftncar |
language |
English |
description |
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. |
author2 |
Choi, Yonghan (author) Chen, Shu‐Hua (author) Huang, Chu‐Chun (author) Earl, Kenneth (author) Chen, Chih‐Ying (author) Schwartz, Craig S. (author) Matsui, Toshihisa (author) |
format |
Article in Journal/Newspaper |
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 |
spellingShingle |
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 |
publishDate |
2020 |
url |
https://doi.org/10.1029/2019MS001890 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
Journal of Advances in Modeling Earth Systems--J. Adv. Model. Earth Syst.--1942-2466--1942-2466 articles:23513 ark:/85065/d7bv7kw6 doi:10.1029/2019MS001890 |
op_rights |
Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
op_doi |
https://doi.org/10.1029/2019MS001890 |
container_title |
Journal of Advances in Modeling Earth Systems |
container_volume |
12 |
container_issue |
4 |
_version_ |
1797588744787722240 |