Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model
Prediction of Saharan dust customarily requires complex aerosols models and observations. A previous study of the Miami, Florida dust record in conjunction to reanalysis data discovered a possible source of subseasonal predictability using a dust-transport-efficiency (DTE) index. Development of the...
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ftosti:oai:osti.gov:1853243 2023-07-30T04:05:27+02:00 Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model Kramer, S. J. Kirtman, B. P. 2022-08-18 application/pdf http://www.osti.gov/servlets/purl/1853243 https://www.osti.gov/biblio/1853243 https://doi.org/10.1029/2020jd033802 unknown http://www.osti.gov/servlets/purl/1853243 https://www.osti.gov/biblio/1853243 https://doi.org/10.1029/2020jd033802 doi:10.1029/2020jd033802 54 ENVIRONMENTAL SCIENCES 2022 ftosti https://doi.org/10.1029/2020jd033802 2023-07-11T10:10:54Z Prediction of Saharan dust customarily requires complex aerosols models and observations. A previous study of the Miami, Florida dust record in conjunction to reanalysis data discovered a possible source of subseasonal predictability using a dust-transport-efficiency (DTE) index. Development of the Subseasonal Forecast Experiment (SubX) has expanded global forecast products; producing multi-model ensemble forecasts out to 45 days. Retrospective forecast data from the Community Climate System Model version 4.0 (CCSM4) is used in direct comparison to National Centers for Environmental Prediction (NCEP) reanalysis to evaluate the CCSM4 subseasonal forecast and DTE index prediction skill of weekly dust variability. Successful prediction of weekly dust transport using the DTE index is variable year-to-year. The DTE most successfully predicts dust when there is high variability in the tropical winds, likely due to a fluctuating subtropical high, and is not dependent on the overall mean flow or total dust mass transported. The CCSM4 SubX retrospective forecast well represents North Atlantic meteorology out to week-3 in both mean flow and variability. Dust transport can be predicted using the DTE index and CCSM4 SubX retrospective forecasts at week-1 leads to the same success as contemporaneous NCEP reanalysis. Other/Unknown Material North Atlantic SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Journal of Geophysical Research: Atmospheres 126 7 |
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SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
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54 ENVIRONMENTAL SCIENCES |
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54 ENVIRONMENTAL SCIENCES Kramer, S. J. Kirtman, B. P. Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model |
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54 ENVIRONMENTAL SCIENCES |
description |
Prediction of Saharan dust customarily requires complex aerosols models and observations. A previous study of the Miami, Florida dust record in conjunction to reanalysis data discovered a possible source of subseasonal predictability using a dust-transport-efficiency (DTE) index. Development of the Subseasonal Forecast Experiment (SubX) has expanded global forecast products; producing multi-model ensemble forecasts out to 45 days. Retrospective forecast data from the Community Climate System Model version 4.0 (CCSM4) is used in direct comparison to National Centers for Environmental Prediction (NCEP) reanalysis to evaluate the CCSM4 subseasonal forecast and DTE index prediction skill of weekly dust variability. Successful prediction of weekly dust transport using the DTE index is variable year-to-year. The DTE most successfully predicts dust when there is high variability in the tropical winds, likely due to a fluctuating subtropical high, and is not dependent on the overall mean flow or total dust mass transported. The CCSM4 SubX retrospective forecast well represents North Atlantic meteorology out to week-3 in both mean flow and variability. Dust transport can be predicted using the DTE index and CCSM4 SubX retrospective forecasts at week-1 leads to the same success as contemporaneous NCEP reanalysis. |
author |
Kramer, S. J. Kirtman, B. P. |
author_facet |
Kramer, S. J. Kirtman, B. P. |
author_sort |
Kramer, S. J. |
title |
Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model |
title_short |
Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model |
title_full |
Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model |
title_fullStr |
Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model |
title_full_unstemmed |
Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model |
title_sort |
saharan dust transport predictability utilizing a subseasonal experiment (subx) model |
publishDate |
2022 |
url |
http://www.osti.gov/servlets/purl/1853243 https://www.osti.gov/biblio/1853243 https://doi.org/10.1029/2020jd033802 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
http://www.osti.gov/servlets/purl/1853243 https://www.osti.gov/biblio/1853243 https://doi.org/10.1029/2020jd033802 doi:10.1029/2020jd033802 |
op_doi |
https://doi.org/10.1029/2020jd033802 |
container_title |
Journal of Geophysical Research: Atmospheres |
container_volume |
126 |
container_issue |
7 |
_version_ |
1772817371571945472 |