Development of a dynamic dust source map for NMME-DREAM v1.0 model based on MODIS Normalized Difference Vegetation Index (NDVI) over the Arabian Peninsula

Abstract

We developed a time-dependent dust source map for the NMME Dust Regional Atmospheric Model (DREAM v1.0) based on the satellite MODIS Normalized Difference Vegetation Index (NDVI). Areas with NDVI < 0.1 are classified as active dust sources. The updated modeling system is tested for dust emission capabilities over SW Asia using a mesoscale model grid increment of 0.1 • × 0.1 • for a period of 1 year (2016). Our results indicate significant deviations in simulated aerosol optical depths (AODs) compared to the static dust source approach and general increase in dust loads over the selected domain. Comparison with MODIS AOD indicates a more realistic spatial distribution of dust in the dynamic source simulations compared to the static dust sources approach. The modeled AOD bias is improved from −0.140 to 0.083 for the case of dust events (i.e., for AOD > 0.25) and from −0.933 to −0.424 for dust episodes with AOD > 1. This new development can be easily applied to other time periods, models, and different areas worldwide for a local fine tuning of the parameterization and assessment of its performance.

Evaluation of Nine Operational Models in Forecasting Different Types of Synoptic Dust Events in the Middle East

“…Global Forecast Grids (GFS) re-analysis data (https://rda.ucar.edu/datasets/ds084.1/, accessed on 17 April 2021) with 0.5 • × 0.5 • horizontal resolution are used to prepare synoptic maps of the mean sea level pressure (MSLP), temperature and geopotential heights at 850 and 500 hPa levels during the dust storms. Due to the impact of various factors (dust schemes, initial and boundary conditions, soil characteristics, dynamic processes, spatial resolution) that affect the forecasting and simulations of dust events from numerical models [43,51,53,70], the outputs of 9 operational dust forecasting models included in https://sds-was.aemet.es (accessed on 12-14 April 2021) are examined and inter-compared during the selected dust storms in the Middle East. The AOD outputs of the models related to their forecasting (initial time 24 h before the valid time) were extracted from the archives of their data.…”

“…In general, the model forecasts for several dust events of different types and meteorological conditions over the Middle East revealed specific difficulties in representing the AOD over the dust source regions, which may be related to topography, surface and dynamic meteorological parameters [51,53]. Therefore, the source of the errors in dust forecasting models is very diverse including surface parameters such as soil texture, vegetation, land use and soil moisture, as well as atmospheric parameters such as wind, precipitation, and the instability associated with boundary layer related quantities.…”

“…Due to the importance of forecasting dust storms in order to mitigate their negative impacts, many studies have been conducted to evaluate the performance of numerical dust forecasting models in the Middle East [47,[51][52][53]. Beegum et al [34] investigated the predictability of seven dust events in the Arabian Peninsula using the CHIMERE model coupled with the WRF weather forecast model.…”

The Potential of GRASP/GARRLiC Retrievals for Dust Aerosol Model Evaluation: Case Study during the PreTECT Campaign

“…It consists of the meteorological core NCEP-NMME (Nonhydrostatic Mesoscale Model on E-grid) atmospheric model [43]. DREAM [44][45][46] is a numerical model developed to simulate and predict the atmospheric life cycle of mineral dust including dust emission, dust horizontal and vertical turbulent mixing, long-range transport and dust deposition, using an Euler-type nonlinear partial differential equation for dust mass continuity. The model is configured at 0.2 • × 0.2 • resolution and includes 8 dust size bins with effective radius of 0.15, 0.25, 0.45, 0.78, 1.3, 2.2, 3.8 and 7.1 µm respectively.…”

Spatiotemporal Analysis of MODIS NDVI in the Semi-Arid Region of Kurdistan (Iran)

“…Several climate research projects focused on the quantification of vegetation cover to study the emergence of drought [2][3][4][5]. Also, the relation of dust storms with vegetation cover has been the subject of several studies [4,6,7]. The emergence of drought and massive dust storms in the Middle East needs special attention, as does the study of vegetation cover.…”