Correlation Between Soil Moisture and Dust Emissions: An Investigation for Global Climate Modeling

This work is using the newly available NASA SMAP soil moisture measurement data to evaluate its impact on the atmospheric dust emissions. Dust is an important component of atmospheric aerosols, which affects both climate and air quality. In this work, we focused on semi-desert regions, where dust em...

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Main Authors: Fredrickson, Carley, Tan, Qian
Format: Other/Unknown Material
Language:unknown
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/2060/20170001399
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spelling ftnasantrs:oai:casi.ntrs.nasa.gov:20170001399 2023-05-15T13:06:35+02:00 Correlation Between Soil Moisture and Dust Emissions: An Investigation for Global Climate Modeling Fredrickson, Carley Tan, Qian Unclassified, Unlimited, Publicly available February 2, 2017 application/pdf http://hdl.handle.net/2060/20170001399 unknown Document ID: 20170001399 http://hdl.handle.net/2060/20170001399 Copyright, Distribution under U.S. Government purpose rights CASI Earth Resources and Remote Sensing ARC-E-DAA-TN38795 2017 BASC Symposium; 2-3 Feb. 2017; Berkeley, CA; United States 2017 ftnasantrs 2019-07-20T23:39:57Z This work is using the newly available NASA SMAP soil moisture measurement data to evaluate its impact on the atmospheric dust emissions. Dust is an important component of atmospheric aerosols, which affects both climate and air quality. In this work, we focused on semi-desert regions, where dust emissions show seasonal variations due to soil moisture changes, i.e. in Sahel of Africa. We first identified three Aerosol Robotic Network (AERONET) sites in the Sahel (IER_Cinzana, Banizoumbou, and Zinder_Airport). We then utilized measurements of aerosol optical depth (AOD), fine mode fraction, size distribution, and single-scattering albedo and its wave-length dependence to select dust plumes from the available measurements We matched the latitude and longitude of the AERONET station to the corresponding SMAP data cell in the years 2015 and 2016, and calculated their correlation coefficient. Additionally, we looked at the correlation coefficient with a three-day and a five-day shift to check the impact of soil moisture on dust plumes with some time delay. Due to the arid nature of Banizoumbou and Zinder_Airport, no correlation was found to exist between local soil moisture and dust aerosol load. While IER_Cinzana had soil moisture levels above the satellite threshold of 0.02cm3/cm3, R-value approaching zero indicated no presence of a correlation. On the other hand, Ilorin demonstrated a significant negative correlation between aerosol optical depth and soil moisture. When isolating the analysis to Ilorin's dry season, a negative correlation of -0.593 was the largest dust-isolated R-value recorded, suggesting that soil moisture is driven the dust emission in this semi-desert region during transitional season. Other/Unknown Material Aerosol Robotic Network NASA Technical Reports Server (NTRS)
institution Open Polar
collection NASA Technical Reports Server (NTRS)
op_collection_id ftnasantrs
language unknown
topic Earth Resources and Remote Sensing
spellingShingle Earth Resources and Remote Sensing
Fredrickson, Carley
Tan, Qian
Correlation Between Soil Moisture and Dust Emissions: An Investigation for Global Climate Modeling
topic_facet Earth Resources and Remote Sensing
description This work is using the newly available NASA SMAP soil moisture measurement data to evaluate its impact on the atmospheric dust emissions. Dust is an important component of atmospheric aerosols, which affects both climate and air quality. In this work, we focused on semi-desert regions, where dust emissions show seasonal variations due to soil moisture changes, i.e. in Sahel of Africa. We first identified three Aerosol Robotic Network (AERONET) sites in the Sahel (IER_Cinzana, Banizoumbou, and Zinder_Airport). We then utilized measurements of aerosol optical depth (AOD), fine mode fraction, size distribution, and single-scattering albedo and its wave-length dependence to select dust plumes from the available measurements We matched the latitude and longitude of the AERONET station to the corresponding SMAP data cell in the years 2015 and 2016, and calculated their correlation coefficient. Additionally, we looked at the correlation coefficient with a three-day and a five-day shift to check the impact of soil moisture on dust plumes with some time delay. Due to the arid nature of Banizoumbou and Zinder_Airport, no correlation was found to exist between local soil moisture and dust aerosol load. While IER_Cinzana had soil moisture levels above the satellite threshold of 0.02cm3/cm3, R-value approaching zero indicated no presence of a correlation. On the other hand, Ilorin demonstrated a significant negative correlation between aerosol optical depth and soil moisture. When isolating the analysis to Ilorin's dry season, a negative correlation of -0.593 was the largest dust-isolated R-value recorded, suggesting that soil moisture is driven the dust emission in this semi-desert region during transitional season.
format Other/Unknown Material
author Fredrickson, Carley
Tan, Qian
author_facet Fredrickson, Carley
Tan, Qian
author_sort Fredrickson, Carley
title Correlation Between Soil Moisture and Dust Emissions: An Investigation for Global Climate Modeling
title_short Correlation Between Soil Moisture and Dust Emissions: An Investigation for Global Climate Modeling
title_full Correlation Between Soil Moisture and Dust Emissions: An Investigation for Global Climate Modeling
title_fullStr Correlation Between Soil Moisture and Dust Emissions: An Investigation for Global Climate Modeling
title_full_unstemmed Correlation Between Soil Moisture and Dust Emissions: An Investigation for Global Climate Modeling
title_sort correlation between soil moisture and dust emissions: an investigation for global climate modeling
publishDate 2017
url http://hdl.handle.net/2060/20170001399
op_coverage Unclassified, Unlimited, Publicly available
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source CASI
op_relation Document ID: 20170001399
http://hdl.handle.net/2060/20170001399
op_rights Copyright, Distribution under U.S. Government purpose rights
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