TY - JOUR
T1 - Quantifying the impacts of landscape heterogeneity and model resolution on dust emissions in the Arabian Peninsula
AU - Shi, Mingjie
AU - Yang, Zong-Liang
AU - Stenchikov, Georgiy L.
AU - Parajuli, Sagar P.
AU - Tao, Weichun
AU - Kalenderski, Stoitchko
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This 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.
PY - 2016/1/11
Y1 - 2016/1/11
N2 - This 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.
AB - This 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.
UR - http://hdl.handle.net/10754/621575
UR - https://linkinghub.elsevier.com/retrieve/pii/S1364815215301353
UR - http://www.scopus.com/inward/record.url?scp=84953731289&partnerID=8YFLogxK
U2 - 10.1016/j.envsoft.2015.12.021
DO - 10.1016/j.envsoft.2015.12.021
M3 - Article
SN - 1364-8152
VL - 78
SP - 106
EP - 119
JO - Environmental Modelling & Software
JF - Environmental Modelling & Software
ER -