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...

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Published in:Journal of Advances in Modeling Earth Systems
Main Authors: Choi, Yonghan, Chen, Shu‐Hua, Huang, Chu‐Chun, Earl, Kenneth, Chen, Chih‐Ying, Schwartz, Craig S., Matsui, Toshihisa
Format: Text
Language:English
Published: John Wiley and Sons Inc. 2020
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Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7375163/
https://doi.org/10.1029/2019MS001890
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spelling ftpubmed:oai:pubmedcentral.nih.gov:7375163 2023-05-15T17:34:43+02:00 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 Chen, Shu‐Hua Huang, Chu‐Chun Earl, Kenneth Chen, Chih‐Ying Schwartz, Craig S. Matsui, Toshihisa 2020-04-04 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7375163/ https://doi.org/10.1029/2019MS001890 en eng John Wiley and Sons Inc. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7375163/ http://dx.doi.org/10.1029/2019MS001890 © 2020. The Authors. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. CC-BY J Adv Model Earth Syst Research Articles Text 2020 ftpubmed https://doi.org/10.1029/2019MS001890 2020-07-26T00:45:33Z 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. Text North Atlantic PubMed Central (PMC) Journal of Advances in Modeling Earth Systems 12 4
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Research Articles
spellingShingle Research Articles
Choi, Yonghan
Chen, Shu‐Hua
Huang, Chu‐Chun
Earl, Kenneth
Chen, Chih‐Ying
Schwartz, Craig S.
Matsui, Toshihisa
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 Research Articles
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.
format Text
author Choi, Yonghan
Chen, Shu‐Hua
Huang, Chu‐Chun
Earl, Kenneth
Chen, Chih‐Ying
Schwartz, Craig S.
Matsui, Toshihisa
author_facet Choi, Yonghan
Chen, Shu‐Hua
Huang, Chu‐Chun
Earl, Kenneth
Chen, Chih‐Ying
Schwartz, Craig S.
Matsui, Toshihisa
author_sort Choi, Yonghan
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 John Wiley and Sons Inc.
publishDate 2020
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7375163/
https://doi.org/10.1029/2019MS001890
genre North Atlantic
genre_facet North Atlantic
op_source J Adv Model Earth Syst
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7375163/
http://dx.doi.org/10.1029/2019MS001890
op_rights © 2020. The Authors.
This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
op_rightsnorm CC-BY
op_doi https://doi.org/10.1029/2019MS001890
container_title Journal of Advances in Modeling Earth Systems
container_volume 12
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