Numerical Dust Storm Simulation Using Modified Geographical Domain and Data Assimilation: 3DVAR and 4DVAR (WRF-Chem/WRFDA)

Dust storms have severe environmental, economic, health, weather, and climate change impacts. A severe dust storm that hit Egypt on 22 January 2004 was selected as a case study to establish an accurate numerical model to simulate dust storms over Egypt using the Weather Research Forecast with a chem...

Description complète

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Muhammed Eltahan, Sabah Alahmadi
Format:	article
Langue:	EN
Publié:	IEEE 2019
Sujets:	Dust storm WRF-Chem data assimilation 3DVAR 4DVAR MODIS Electrical engineering. Electronics. Nuclear engineering TK1-9971
Accès en ligne:	https://doaj.org/article/d49b140e77d24b94bcc7d277e7286cf0
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

id	oai:doaj.org-article:d49b140e77d24b94bcc7d277e7286cf0
record_format	dspace
spelling	oai:doaj.org-article:d49b140e77d24b94bcc7d277e7286cf02021-11-11T00:01:04ZNumerical Dust Storm Simulation Using Modified Geographical Domain and Data Assimilation: 3DVAR and 4DVAR (WRF-Chem/WRFDA)2169-353610.1109/ACCESS.2019.2930812https://doaj.org/article/d49b140e77d24b94bcc7d277e7286cf02019-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/8782820/https://doaj.org/toc/2169-3536Dust storms have severe environmental, economic, health, weather, and climate change impacts. A severe dust storm that hit Egypt on 22 January 2004 was selected as a case study to establish an accurate numerical model to simulate dust storms over Egypt using the Weather Research Forecast with a chemistry module (WRF-Chem). Two simulation setups using WRF-Chem were conducted using two geographic domains: the first exclusively included dust sources within Egypt, while the second included an external dust source, the Bodélé Depression in southwestern Chad. The first simulation was only able to capture the core of the dust plume from the internal dust source Egyptian Qattara Depression, but the second was able to capture the spatial dust distribution from both the Qattara Depression and the Bodélé Depression. Moreover, the results from our second simulation model had less errors than comparable results using moderate resolution imaging spectroradiometer (MODIS). We then investigated the impact of meteorological data assimilation methods using both three-dimensional and four-dimensional variational assimilation algorithms to simulate the aerosol optical depth of the dust storm using weather research forecast data assimilation (WRFDA) framework.Muhammed EltahanSabah AlahmadiIEEEarticleDust stormWRF-Chemdata assimilation3DVAR4DVARMODISElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 7, Pp 128980-128989 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Dust storm WRF-Chem data assimilation 3DVAR 4DVAR MODIS Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Dust storm WRF-Chem data assimilation 3DVAR 4DVAR MODIS Electrical engineering. Electronics. Nuclear engineering TK1-9971 Muhammed Eltahan Sabah Alahmadi Numerical Dust Storm Simulation Using Modified Geographical Domain and Data Assimilation: 3DVAR and 4DVAR (WRF-Chem/WRFDA)
description	Dust storms have severe environmental, economic, health, weather, and climate change impacts. A severe dust storm that hit Egypt on 22 January 2004 was selected as a case study to establish an accurate numerical model to simulate dust storms over Egypt using the Weather Research Forecast with a chemistry module (WRF-Chem). Two simulation setups using WRF-Chem were conducted using two geographic domains: the first exclusively included dust sources within Egypt, while the second included an external dust source, the Bodélé Depression in southwestern Chad. The first simulation was only able to capture the core of the dust plume from the internal dust source Egyptian Qattara Depression, but the second was able to capture the spatial dust distribution from both the Qattara Depression and the Bodélé Depression. Moreover, the results from our second simulation model had less errors than comparable results using moderate resolution imaging spectroradiometer (MODIS). We then investigated the impact of meteorological data assimilation methods using both three-dimensional and four-dimensional variational assimilation algorithms to simulate the aerosol optical depth of the dust storm using weather research forecast data assimilation (WRFDA) framework.
format	article
author	Muhammed Eltahan Sabah Alahmadi
author_facet	Muhammed Eltahan Sabah Alahmadi
author_sort	Muhammed Eltahan
title	Numerical Dust Storm Simulation Using Modified Geographical Domain and Data Assimilation: 3DVAR and 4DVAR (WRF-Chem/WRFDA)
title_short	Numerical Dust Storm Simulation Using Modified Geographical Domain and Data Assimilation: 3DVAR and 4DVAR (WRF-Chem/WRFDA)
title_full	Numerical Dust Storm Simulation Using Modified Geographical Domain and Data Assimilation: 3DVAR and 4DVAR (WRF-Chem/WRFDA)
title_fullStr	Numerical Dust Storm Simulation Using Modified Geographical Domain and Data Assimilation: 3DVAR and 4DVAR (WRF-Chem/WRFDA)
title_full_unstemmed	Numerical Dust Storm Simulation Using Modified Geographical Domain and Data Assimilation: 3DVAR and 4DVAR (WRF-Chem/WRFDA)
title_sort	numerical dust storm simulation using modified geographical domain and data assimilation: 3dvar and 4dvar (wrf-chem/wrfda)
publisher	IEEE
publishDate	2019
url	https://doaj.org/article/d49b140e77d24b94bcc7d277e7286cf0
work_keys_str_mv	AT muhammedeltahan numericalduststormsimulationusingmodifiedgeographicaldomainanddataassimilation3dvarand4dvarwrfchemwrfda AT sabahalahmadi numericalduststormsimulationusingmodifiedgeographicaldomainanddataassimilation3dvarand4dvarwrfchemwrfda
_version_	1718439633716510720

Numerical Dust Storm Simulation Using Modified Geographical Domain and Data Assimilation: 3DVAR and 4DVAR (WRF-Chem/WRFDA)

Documents similaires