Do MODIS‐defined dust sources have a geomorphological signature?

Baddock, Matthew C.; Ginoux, Paul; Bullard, Joanna E.; Gill, Thomas E.

doi:10.1002/2015gl067327

Cited by 65 publications

(57 citation statements)

References 37 publications

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“…MISR-derived and SeaWiFS-derived DOD were not further utilized because of the limited amount of retrievals and much smaller values and variance in comparison to MODIS-derived one, as found above (Figures 7 and 8). AOD retrievals with all quality flags were used following the recommendation by Baddock et al [44] to derive the dust occurrence numbers, because the quality flag is not well marked over desert regions where a larger standard deviation is always found [4]. Consistent to Baddock et al [44], a threshold DODt = 0.2 was also applied in the present study to count the dust occurrence numbers.…”

Section: Dust Occurrencesmentioning

confidence: 99%

“…AOD retrievals with all quality flags were used following the recommendation by Baddock et al [44] to derive the dust occurrence numbers, because the quality flag is not well marked over desert regions where a larger standard deviation is always found [4]. Consistent to Baddock et al [44], a threshold DODt = 0.2 was also applied in the present study to count the dust occurrence numbers. To avoid the contamination of the use of a threshold constant on the results, a series of threshold values close to 0.2 was applied to the dust event selecting procedure to yield a more robust conclusion.…”

Section: Dust Occurrencesmentioning

confidence: 99%

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Analysis of Dust Aerosol Retrievals Using Satellite Data in Central Asia

Sokolik

2018

Atmosphere

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Several long-term monitoring of aerosol datasets from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra/Aqua, Multi-angle Imaging SpectroRadiometer (MISR), Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) were used to derive the dust aerosol optical depth (DOD) in Central Asia based on the Angstrom exponent parameter and/or the particle shape. All sensors agree very well on the interannual variability of DOD. The seasonal analysis of DOD and dust occurrences identified the largest dust loading and the most frequent dust occurrence in the spring and summer, respectively. No significant trend was found during the research period in terms of both DOD and the dust occurrence. Further analysis of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) aerosol products on a case-by-case basis in most dust months of 2007 suggested that the vertical structure is varying in terms of the extension and the dust loading from one event to another, although dust particles of most episodes have similar physical characteristics (particle shape and size). Our analysis on the vertical structure of dust plumes, the layer-integrated color ratio and depolarization ratio indicates a varied climate effect (e.g., the direct radiative impact) by mineral dust, dependent on the event being observed in Central Asia.

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Section: Dust Occurrencesmentioning

confidence: 99%

Section: Dust Occurrencesmentioning

confidence: 99%

Analysis of Dust Aerosol Retrievals Using Satellite Data in Central Asia

Sokolik

2018

Atmosphere

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“…A surface erodibility factor is typically used in dust models to constrain the observed spatial heterogeneity of emissions (Zender et al, ). Several dust emission mapping schemes at the landscape scale have attempted to account for erodibility as a regulator of emission potential for use in dust models (e.g., Ashpole & Washington, ; Baddock et al, ; Bullard et al, ; Parajuli et al, ; Parajuli & Zender, ). The erodibility factor has typically been based on various physical assumptions of the influence of geomorphology, topography, and hydrology on dust emission (Ginoux et al, ; Zender et al, ).…”

Section: Introductionmentioning

confidence: 99%

“…Our understanding of dust emission processes has been greatly enhanced by studies that have identified dust sources on global, regional, and landscape scales through various remote sensing approaches primarily using the Total Ozone Mapping (TOMS) and more recently the MODIS sensors (e.g., Baddock et al, ; Bullard et al, ; Ginoux et al, ; Huang et al, ; Lee et al, ; O'Loingsigh et al, ; Prospero et al, ; Schepanski et al, , ; Vickery et al, ; Washington et al, ). However, a fuller appreciation of the smaller‐scale controls contributing to the variability in dust emission also depends on the improved characterization of dust sources at a sublandform scale.…”

Section: Introductionmentioning

confidence: 99%

Assessing Landscape Dust Emission Potential Using Combined Ground‐Based Measurements and Remote Sensing Data

et al. 2019

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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.

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“…Moreover, the attribution of dust generation and flux to different dust‐producing landforms and processes is sometimes not straightforward. As a primary reason, spatial resolution of observations, especially from space‐based platforms, such as Moderate Resolution Imaging Spectroradiometer (MODIS), is often too crude to recognize source areas even when, and sometimes because, plumes are dense, notwithstanding recent analyses and progress (Baddock et al, , ; Bullard et al, ; Schepanski et al, ). Successful estimates of AOD (atmospheric optical depth) on a global scale have been derived from Collection 6 MODIS data, the Dark Target, and Deep Blue products in particular (Hsu et al, ; Ridley et al, ).…”

Section: Introductionmentioning

confidence: 99%

Unseen Dust Emission and Global Dust Abundance: Documenting Dust Emission from the Mojave Desert (USA) by Daily Remote Camera Imagery and Wind‐Erosion Measurements

et al. 2018

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A large gap in understanding the effects of atmospheric dust at all spatial scales is uncertainty about how much and whence dust is emitted annually. Direct digital recording of dust emission at high spatial and temporal resolution would together with periodic flux measurements support improved estimates of local‐scale dust flux. Remote camera recording of dust‐emitting settings on and around Soda Lake (Mojave Desert) was conducted every 15 min during daylight between 10 November 2010 and 31 December 2016. Examination of 135,000 images revealed frequent dust events characterized as dust days, 68 per year on average, when dust plumes obscured mountains beyond areas of dust generation. Dust was not observed from examination of satellite retrievals (Moderate Resolution Imaging Spectroradiometer and Geostationary Operational Environmental Satellite System) during six cloudless days of extreme emission. Estimated masses of emitted dust fractions were made from measured horizontal mass flux, sediment particle sizes, and areas of dust generation. Between April 2000 and June 2013, nearly 4 Tg/year of dust (particles < 63 μm) were emitted across the study area. Higher rates (about 7 Tg/year) were estimated following the December 2010 Mojave River flood that deposited sediment across the lake basin. Within the Mojave and Great Basin deserts of western North America, many settings akin to those at Soda Lake similarly emit dust that is rarely detected in satellite retrievals, implying that local and regional dust emissions from western North America are far underestimated and that, by extension to relatively small dust‐source areas across all drylands, global dust emissions may also be greatly underestimated.

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Do MODIS‐defined dust sources have a geomorphological signature?

Cited by 65 publications

References 37 publications

Analysis of Dust Aerosol Retrievals Using Satellite Data in Central Asia

Analysis of Dust Aerosol Retrievals Using Satellite Data in Central Asia

Assessing Landscape Dust Emission Potential Using Combined Ground‐Based Measurements and Remote Sensing Data

Unseen Dust Emission and Global Dust Abundance: Documenting Dust Emission from the Mojave Desert (USA) by Daily Remote Camera Imagery and Wind‐Erosion Measurements

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