Assessing landscape dust emission potential using combined ground‐based measurements and remote sensing data
Modeled estimates of eolian dust emission can vary by an order of magnitude due to the spatiotemporal heterogeneity of emissions. To better constrain location and magnitude of emissions, a surface erodibility factor is typically employed in models. Several landscape‐scale schemes representing surfac...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Wiley
2019
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| _version_ | 1797075995142914048 |
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| author | von Holdt, J Eckardt, F Baddock, M Wiggs, G |
| author_facet | von Holdt, J Eckardt, F Baddock, M Wiggs, G |
| author_sort | von Holdt, J |
| collection | OXFORD |
| description | Modeled estimates of eolian dust emission can vary by an order of magnitude due to the spatiotemporal heterogeneity of emissions. To better constrain location and magnitude of emissions, a surface erodibility factor is typically employed in models. Several landscape‐scale schemes representing surface dust emission potential for use in models have recently been proposed, but validation of such schemes has only been attempted indirectly with medium‐resolution remote sensing of mineral aerosol loadings and high‐resolution land surface mapping. In this study, we used dust emission source points identified in Namibia with Landsat imagery together with field‐based dust emission measurements using a Portable In‐situ Wind Erosion Laboratory wind tunnel to assess the performance of schemes aiming to represent erodibility in global dust cycle modeling. From analyses of the surface and samples taken at the time of wind tunnel testing, a Boosted Regression Tree analysis identified the significant factors controlling erodibility based on Portable In‐situ Wind Erosion Laboratory dust flux measurements and various surface characteristics, such as soil moisture, particle size, crusting degree, and mineralogy. Despite recent attention to improving the characterization of surface dust emission potential, our assessment indicates a high level of variability in the measured fluxes within similar geomorphologic classes. This variability poses challenges to dust modeling attempts based on geomorphology and/or spectral‐defined classes. Our approach using high‐resolution identification of dust sources to guide ground‐based testing of emissivity offers a valuable means to help constrain and validate dust emission schemes. Detailed determination of the relative strength of factors controlling emission can provide further improvement to regional and global dust cycle modeling. |
| first_indexed | 2024-03-06T23:57:58Z |
| format | Journal article |
| id | oxford-uuid:74e5742f-19f0-4cb4-9da4-5a2bd15acec4 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T23:57:58Z |
| publishDate | 2019 |
| publisher | Wiley |
| record_format | dspace |
| spelling | oxford-uuid:74e5742f-19f0-4cb4-9da4-5a2bd15acec42022-03-26T20:06:03ZAssessing landscape dust emission potential using combined ground‐based measurements and remote sensing dataJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:74e5742f-19f0-4cb4-9da4-5a2bd15acec4EnglishSymplectic Elements at OxfordWiley2019von Holdt, JEckardt, FBaddock, MWiggs, GModeled estimates of eolian dust emission can vary by an order of magnitude due to the spatiotemporal heterogeneity of emissions. To better constrain location and magnitude of emissions, a surface erodibility factor is typically employed in models. Several landscape‐scale schemes representing surface dust emission potential for use in models have recently been proposed, but validation of such schemes has only been attempted indirectly with medium‐resolution remote sensing of mineral aerosol loadings and high‐resolution land surface mapping. In this study, we used dust emission source points identified in Namibia with Landsat imagery together with field‐based dust emission measurements using a Portable In‐situ Wind Erosion Laboratory wind tunnel to assess the performance of schemes aiming to represent erodibility in global dust cycle modeling. From analyses of the surface and samples taken at the time of wind tunnel testing, a Boosted Regression Tree analysis identified the significant factors controlling erodibility based on Portable In‐situ Wind Erosion Laboratory dust flux measurements and various surface characteristics, such as soil moisture, particle size, crusting degree, and mineralogy. Despite recent attention to improving the characterization of surface dust emission potential, our assessment indicates a high level of variability in the measured fluxes within similar geomorphologic classes. This variability poses challenges to dust modeling attempts based on geomorphology and/or spectral‐defined classes. Our approach using high‐resolution identification of dust sources to guide ground‐based testing of emissivity offers a valuable means to help constrain and validate dust emission schemes. Detailed determination of the relative strength of factors controlling emission can provide further improvement to regional and global dust cycle modeling. |
| spellingShingle | von Holdt, J Eckardt, F Baddock, M Wiggs, G Assessing landscape dust emission potential using combined ground‐based measurements and remote sensing data |
| title | Assessing landscape dust emission potential using combined ground‐based measurements and remote sensing data |
| title_full | Assessing landscape dust emission potential using combined ground‐based measurements and remote sensing data |
| title_fullStr | Assessing landscape dust emission potential using combined ground‐based measurements and remote sensing data |
| title_full_unstemmed | Assessing landscape dust emission potential using combined ground‐based measurements and remote sensing data |
| title_short | Assessing landscape dust emission potential using combined ground‐based measurements and remote sensing data |
| title_sort | assessing landscape dust emission potential using combined ground based measurements and remote sensing data |
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