The effect of the dynamic surface bareness on dust source function, emission, and distribution

Kim, Dongchul; Chin, Mian; Bian, Huisheng; Tan, Qian; Brown, Molly E.; Tai, Zheng; You, Renjie; Diehl, Tomas; Ginoux, Paul; Kucsera, Tom

doi:10.1002/jgrd.50062

Cited by 13 publications

(19 citation statements)

References 21 publications

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“…Such region‐specific, temporally varying erodibility can be specified by combining the land cover map and the monthly dynamic erodibility map presented in this study. This conclusion is also supported by some recent studies [e.g., Kim et al ., ] that observed improvements in dust emission using a MODIS NDVI (normalized difference vegetation index) based, dynamic dust source function.…”

Section: Discussion and Modeling Perspectivementioning

confidence: 99%

Mapping erodibility in dust source regions based on geomorphology, meteorology, and remote sensing

2014

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Mineral dust in the atmosphere has implications for Earth's radiation budget, biogeochemical cycles, hydrological cycles, human health, and visibility. Currently, the simulated vertical mass flux of dust differs greatly among the existing dust models. While most of the models utilize an erodibility factor to characterize dust sources, this factor is assumed to be static, without sufficient characterization of the highly heterogeneous and dynamic nature of dust source regions. We present a high-resolution land cover map of the Middle East and North Africa (MENA) in which the terrain is classified by visually examining satellite images obtained from Google Earth Professional and Environmental Systems Research Institute Basemap. We show that the correlation between surface wind speed and Moderate Resolution Imaging Spectroradiometer deep blue aerosol optical depth (AOD) can be used as a proxy for erodibility, which satisfactorily represents the spatiotemporal distribution of soil-derived dust sources. This method also identifies agricultural dust sources and eliminates the satellite-observed dust component that arises from long-range transport, pollution, and biomass burning. The erodible land cover of the MENA region is grouped into nine categories: (1) bedrock: with sediment, (2) sand deposit, (3) sand deposit: on bedrock, (4) sand deposit: stabilized, (5) agricultural and urban area, (6) fluvial system, (7) stony surface, (8) playa/sabkha, and (9) savanna/grassland. Our results indicate that erodibility is linked to the land cover type and has regional variation. An improved land cover map, which explicitly accounts for sediment supply, availability, and transport capacity, may be necessary to represent the highly dynamic nature of dust sources in climate models.

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Section: Discussion and Modeling Perspectivementioning

confidence: 99%

Mapping erodibility in dust source regions based on geomorphology, meteorology, and remote sensing

2014

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“…Both satellites and ground-based instruments can be used to measure 44 AOD in the atmosphere, but within the same temporal coordinates and geographic location 45 different instruments could generate different retrievals (Kahn et al, 2007, Kokhanovsky et 46 al., 2007, Liu et al, 2008and Mishchenko et al, 2009 Since the turn of the 21 st century, an upward trend of remotely sensed and ground-based 48 AOD and air pollutants was observed over the Middle East and North Africa (El-Askary 49 2009, Ansmann et al 2011, Yu et al 2013, Chin et al 2014, Yu et al 2015, Farahat et al 50 2016, Solomos et al 2017. This positive trend is attributed to the increase in the Middle 51 Eastern dust activity (Hsu et al, 2012) due to changes in wind speed and soil moisture 52 (Ginoux et al 2001 andKim et al 2013). Yu et al, (2015) concluded that the persistent La 53…”

Section: Introduction 28mentioning

confidence: 99%

Comparative Analysis of MODIS, MISR and AERONET Climatology over the Middle East and North Africa

Farahat¹

2018

Preprint

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10 Comparative analysis of MISR MODIS, and AERONET AOD products is performed over 11 seven AERONET stations located in the Middle East and North Africa for the period of 12 2000 -2015. Sites are categorized into dust, biomass burning and mixed. MISR and 13 MODIS AOD agree during high dust seasons but MODIS tends to underestimate AOD 14 during low dust seasons. Over dust dominated sites, MODIS/Terra AOD indicate a 15 negative trend over the time series, while MODIS/Aqua, MISR, and AERONET depict a 16 positive trend. A deviation between MODIS/Aqua and MODIS/Terra was observed 17 regardless of the geographic location and data sampling. The performance of MODIS is 18 similar over the entire region with ~68% of AOD within the 0.05 0.15 AERO τ τ Δ = ± ± 19 confidence range. MISR AOD retrievals fall within 72% of the same confidence range for 20 all sites examined here. Both MISR and MODIS capture aerosol climatology; however few 21 cases were observed where one of the two sensors better captures the climatology over a 22 certain location or AOD range than the other sensor. 23 Niña conditions (Hoell et al., 2013) have caused increment in Saudi Arabian dust activity 54 during 2008 -2012. Energy subsidies also encourages energy overconsumption in the 55 Middle East and North Africa with little incentive to adopt cleaner technology. Lack of 56 applying strict environmental regulations have permitted exacerbated urban air pollution. 57During the last two decades, a large number of satellites, ground stations and computational 58 models contributed to build global and regional maps for the temporal and spatial aerosol 59 distributions. While, ground-based stations and field measurements can identify aerosols 60properties over specific geographic locations, the spare and non-continues data from 61 ground-based sensors scattered over the Middle East and North Africa is not sufficient to 62 provide information on spatial and temporal trends of particulate pollution. On the other 63 hand, satellites imagery could provide a significant source of data mapping over larger 64 areas. 65In the first part of this article, we validated MISR and MODIS retrievals against collocated 80 AERONET observations. We also assessed the consistency in aerosol trends between 81 space-borne sensors and ground-based data. 82In the second part, we evaluated representativeness of satellite-derived aerosol climatology 83 over the study region from the long-term AERONET data for MISR and MODIS AOD 84 products. It is especially relevant for the MISR instrument, as its sampling is limited by 85 once per week observations of the same region from the two overlapping paths. MODIS 86 provides nearly daily observations to the same geographic location; however, the quality of 87 the product diminishes over the bright targets potentially affecting MODIS-derived aerosol 88 climatology. 89The collocated MISR, MODIS and AERONET data were obtained at the MAPSS website 90 (http://giovanni.gsfc.nasa.gov/mapss.html). 91 92 2. Materials and Methods 93 2.1 MISR 94 The Mult...

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“…Barren lands are one of the major sources of atmospheric dusts [2][3][4]. The dust aerosols affect the Earth's radiation budget by scattering and absorbing solar radiation and modifying the structure and properties of clouds [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

A Biophysical Image Compositing Technique for the Global-Scale Extraction and Mapping of Barren Lands

Sharma

Tateishi

Hara

2016

IJGI

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Abstract:As the barren lands play a key role in the interaction between land cover dynamics and climate system, an efficient methodology for the global-scale extraction and mapping of the barren lands is important. The discriminative potential of the existing soil/bareness indexes was assessed by collecting globally distributed reference data belonging to major land cover types. The existing soil/bareness indexes parameterized at the local scale did not work satisfactorily everywhere at the global level. A new technique called the Biophysical Image Composite (BIC) is proposed in the research by exploiting time-series of the multi-spectral data to capture global-scale barren land attributes effectively. The BIC is a false color composite image made up of Normalized Difference Vegetation Index (NDVI), short wave infrared reflectance, and green reflectance, which were specially selected from the highest vegetation activity period by avoiding signals from the seasonal snowfall. The drastic contrast between the barren lands and vegetation as exhibited by the BIC provides a robust extraction and mapping of the barren lands, and facilitates its visual interpretation. Random Forests based supervised classification approach was applied on the BIC for the mapping of global barren lands. A new global barren land cover map of year 2013 was produced with high accuracy. The comparison of the resulted map with an existing map of the same year showed a substantial discrepancy between two maps due to methodological variation. To cope with this problem, the BIC based mapping methodology, with a special account of the land surface phenological changes, is suggested to standardize the global-scale estimates and mapping of the barren lands.

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The effect of the dynamic surface bareness on dust source function, emission, and distribution

Cited by 13 publications

References 21 publications

Mapping erodibility in dust source regions based on geomorphology, meteorology, and remote sensing

Mapping erodibility in dust source regions based on geomorphology, meteorology, and remote sensing

Comparative Analysis of MODIS, MISR and AERONET Climatology over the Middle East and North Africa

A Biophysical Image Compositing Technique for the Global-Scale Extraction and Mapping of Barren Lands

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