Quantifying the impacts of landscape heterogeneity and model resolution on dust emissions in the Arabian Peninsula. (April 2016)

• Record Type: Journal Article
• Authors: Shi, Mingjie; Yang, Zong-Liang; Stenchikov, Georgiy L.; Parajuli, Sagar P.; Tao, Weichun; Kalenderski, Stoitchko
• Is Part Of: Environmental modelling & software. Volume 78(2016:Apr.)
• Page Start: 106
• Page End: 119
• Publication Date: 2016-04
• Subjects: Dust emission -- The Arabian Peninsula -- Vegetation cover fraction -- Model resolution -- CLM4 -- The DEAD model; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.12.021
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: 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 (CLM4 3 ) 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. Highlights: CLM4 can capture the spatiotemporal dust emission features on the Arabian Peninsula. MODIS has slightly higher vegetated coverage and more emission than that of CLM-PFT. The MODIS-based dust emission increases with model resolution. Resolution-dependence is due to the heterogeneity of factors influencing emissions.