Quantifying the impacts of landscape heterogeneity and model resolution on dust emissions in the Arabian Peninsula
Stenchikov, Georgiy L.
Parajuli, Sagar P.
KAUST DepartmentEarth Science and Engineering Program
Physical Science and Engineering (PSE) Division
Red Sea Research Center (RSRC)
Online Publication Date2016-01-11
Print Publication Date2016-04
Permanent link to this recordhttp://hdl.handle.net/10754/621575
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AbstractThis study evaluates the spatiotemporal variability of dust emission in the Arabian Peninsula and quantifies the emission sensitivity to the land-cover heterogeneity by using the Community Land Model version 4 (CLM43) at three different spatial resolutions. The land-cover heterogeneity is represented by the CLM4-default plant function types (PFTs) and the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover types, respectively, at different grids. We area-average surface vegetation data and use the default nearest neighbor method to interpolate meteorological variables. We find that using MODIS data leads to a slightly higher coverage of vegetated land than the default PFT data; the former also gives more dust emission than the latter at 25- and 50-km grids as the default PFT data have more gridcells favoring less dust emission. The research highlights the importance of using proper data-processing methods or dust emission thresholds to preserve the dust emission accuracy in land models. © 2016 Elsevier Ltd.
CitationShi M, Yang Z-L, Stenchikov GL, Parajuli SP, Tao W, et al. (2016) Quantifying the impacts of landscape heterogeneity and model resolution on dust emissions in the Arabian Peninsula. Environmental Modelling & Software 78: 106–119. Available: http://dx.doi.org/10.1016/j.envsoft.2015.12.021.
SponsorsThis work was funded by a KAUST grant entitled "Refinement of Dust Entrainment and Transport Dynamics for Input into the Next Generation Coupled Land-Atmosphere Models." The computations were performed at the Texas Advanced Computing Center. The authors appreciate valuable suggestions from Dr. Charles S. Zender, Dr. Natalie M. Mahowald, and Dr. Qinjian Jin. The authors would like to acknowledge the editorial assistance from Patricia A. Bobeck. Author contributions: M.S., Z.-L.Y., and G.L.S designed the research; M.S. performed the research; M.S., S.P.P., W.T., and S.K. processed the data, and M.S. and Z.-L.Y. wrote the paper.