Dust model intercomparison (DMIP) study over Asia: Overview

Abstract

[1] An intercomparison study involving eight dust emission/transport models over Asia (DMIP) has been completed. Participating dust models utilize a variety of dust emission schemes, horizontal and vertical resolutions, numerical methods, and different meteorological models. Two huge dust episodes occurred in spring 2002 and were used for the DMIP study. Meteorological parameters, dust emission flux and dust concentration (diameter < 20 mm) are compared within the same domain on the basis of PM and NIES lidar measurements. We found that modeled dust concentrations between the 25% and 75% percentiles generally agreed with the PM observations. The model results correctly captured the major dust onset and cessation timing at each observation site. However, the maximum concentration of each model was 2-4 times different. Dust emission fluxes from the Taklimakan Desert and Mongolia differ immensely among the models, indicating that the dust source allocation scheme over these regions differs greatly among the various modeling groups. This suggests the measurements of dust flux and accurate updated land use information are important to improve the models over these regions. The dust vertical concentration profile at Beijing, China, and Nagasaki, Japan, has a large scatter (more than two times different) among the models. For Beijing, the scaled dust profile has a quite similar vertical profile and shows relatively good agreement with the lidar extinction profile. However, for Nagasaki, the scaled dust profiles do not agree. These results indicate that modeling of dust transport and removal processes between China and Japan is another important issue in improving dust modeling.

Top‐down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS‐Chem adjoint model

“…Quantitative description of processes such as sandblasting and saltation bombardment in a chemistry transport model (CTM) requires knowledge of many parameters that can not be accurately characterized spatially and temporally, including surface wind speed, soil moisture, soil texture, surface cover type, and topography [Ginoux et al, 2001;Tegen et al, 2002;Zender et al, 2003]. Not surprisingly, recent estimates in CTMs span from a few hundreds to over 4000 Tg for annual global dust emissions [Huneeus et al, 2011] and vary by several orders of magnitude for emissions of dust events at regional scales [Uno et al, 2006]. An observation-based approach, therefore, is needed to reduce these large uncertainties in estimates of dust emissions.…”

Inverse Modeling of Asian Dust Emissions with POPC Observations: A TEMM Dust Sand Storm 2014 Case Study

“…However, the complicated dependence of the dust emission process on land-surface conditions makes accurate estimation of the distribution and intensity of dust emissions difficult. In fact, a dust model intercomparison project (Uno et al 2006) found that dust emission amounts estimated by eight CTMs showed large variation, sometimes differing by a factor of ten. This result indicates that there is considerable uncertainty in the estimation of dust emissions.…”

The Impact of Ground-Based Observations on the Inverse Technique of Aeolian Dust Aerosol

“…The dust-emission process itself is another highly uncertain aspect of the overall dust process (Mikami et al 2005). It is difficult to measure it directly, and its estimation in models varies widely for different events (Uno et al 2006). Therefore, a data-assimilation technique is often used by researchers (Yumimoto 2008;Sekiyama et al 2010).…”