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

This study investigates four types of synoptic dust events in the Middle East region, including cyclonic, pre-frontal, post-frontal and Shamal dust storms. For each of these types, three intense and pervasive dust events are analyzed from a synoptic meteorological and numerical simulation perspective. The performance of 9 operational dust models in forecasting these dust events in the Middle East is qualitatively and quantitatively evaluated against Terra-MODIS observations and AERONET measurements during the dust events. The comparison of model AOD outputs with Terra-MODIS retrievals reveals that despite the significant discrepancies, all models have a relatively acceptable performance in forecasting the AOD patterns in the Middle East. The models enable to represent the high AODs along the dust plumes, although they underestimate them, especially for cyclonic dust storms. In general, the outputs of the NASA-GEOS and DREAM8-MACC models present greater similarity with the satellite and AERONET observations in most of the cases, also exhibiting the highest correlation coefficient, although it is difficult to introduce a single model as the best for all cases. Model AOD predictions over the AERONET stations showed that DREAM8-MACC exhibited the highest R2 of 0.78, followed by NASA_GEOS model (R2 = 0.74), which both initially use MODIS data assimilation. Although the outputs of all models correspond to valid time more than 24 h after the initial time, the effect of data assimilation on increasing the accuracy is important. The different dust emission schemes, soil and vegetation mapping, initial and boundary meteorological conditions and spatial resolution between the models, are the main factors influencing the differences in forecasting the dust AODs in the Middle East.

Modeling Dust in East Asia by CESM and Sources of Biases

East Asian dust has a significant impact on regional and global climate. In this study, we evaluate the spatial distributions and temporal variations of dust extinction profiles and dust optical depth (DOD) over East Asia simulated from the Community Earth System Model (CESM) with satellite retrievals from Luo et al. (2015a, 2015b) (L15), Yu et al. (2015) (Y15), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) level 3 (CAL-L3) products. Both L15 and Y15 are based on CALIPSO products but use different algorithms to separate dust from non-dust aerosols. We find high model biases of dust extinction in the upper troposphere over the Taklamakan Desert, Gobi Desert, and Tibetan Plateau, especially in the summer (June-July-August, JJA). CESM with dust emission scheme of Kok et al. (2014a, 2014b) has the best agreement with dust extinction profiles and DOD from L15 in the Taklamakan Desert and Tibetan Plateau. CESM with the default dust emission scheme of Zender et al. (2003a) underpredicts DOD in the Tibetan Plateau compared with observations from L15 due to the underestimation of local dust emission. Large uncertainties exist in observations from L15, Y15, and CAL-L3 and have significant impacts on the model evaluation of dust spatial distributions. We also assess dust surface concentrations and 10 m wind speed with meteorological records from weather stations in the Taklamakan and Gobi Deserts during dust events. CESM underestimates dust surface concentrations at most weather stations due to the inability of CESM to capture strong surface wind events.

Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system

A new windblown dust emission treatment was incorporated in the Community Multiscale Air Quality (CMAQ) modeling system. This new model treatment has been built upon previously developed physics-based parameterization schemes from the literature. A distinct and novel feature of this scheme, however, is the incorporation of a newly developed dynamic relation for the surface roughness length relevant to small-scale dust generation processes. Through this implementation, the effect of nonerodible elements on the local flow acceleration, drag partitioning, and surface coverage protection is modeled in a physically based and consistent manner. Careful attention is paid in integrating the new windblown dust treatment in the CMAQ model to ensure that the required input parameters are correctly configured. To test the performance of the new dust module in CMAQ, the entire year 2011 is simulated for the continental United States, with particular emphasis on the southwestern United States (SWUS) where windblown dust concentrations are relatively large. Overall, the model shows good performance with the daily mean bias of soil concentrations fluctuating in the range of ±1 μg m-3 for the entire year. Springtime soil concentrations are in quite good agreement (normalized mean bias of 8.3%) with observations, while moderate to high underestimation of soil concentration is seen in the summertime. The latter is attributed to the issue of representing the convective dust storms in summertime. Evaluations against observations for seven elevated dust events in the SWUS indicate that the new windblown dust treatment is capable of capturing spatial and temporal characteristics of dust outbreaks.

Identifying errors in dust models from data assimilation

Airborne mineral dust is an important component of the Earth system and is increasingly predicted prognostically in weather and climate models. The recent development of data assimilation for remotely sensed aerosol optical depths (AODs) into models offers a new opportunity to better understand the characteristics and sources of model error. Here we examine assimilation increments from Moderate Resolution Imaging Spectroradiometer AODs over northern Africa in the Met Office global forecast model. The model underpredicts (overpredicts) dust in light (strong) winds, consistent with (submesoscale) mesoscale processes lifting dust in reality but being missed by the model. Dust is overpredicted in the Sahara and underpredicted in the Sahel. Using observations of lighting and rain, we show that haboobs (cold pool outflows from moist convection) are an important dust source in reality but are badly handled by the model's convection scheme. The approach shows promise to serve as a useful framework for future model development.

The importance of rare, high-wind events for dust uplift in northern Africa

Dust uplift is a nonlinear thresholded function of wind speed and therefore particularly sensitive to the long tails of observed wind speed probability density functions. This suggests that a few rare high-wind events can contribute substantially to annual dust emission. Here we quantify the relative roles of different wind speeds to dust-generating winds using surface synoptic observations of dust emission and wind from northern Africa. The results show that winds between 2 and 5 m s^-1 above the threshold cause the most emission. Of the dust-generating winds, 25% is produced by very rare events occurring only at 0.1 to 1.4% of the time, depending on the region. Dust-producing winds are underestimated in ERA-I, since it misses the long tail found in observations. ERA-I overpredicts (underpredicts) the frequency of emission strength winds in the southern (northern) regions. These problems cannot be solved by simple tunings. Finally, we show that rare events make the largest contribution to interannual variability in dust-generating winds and that ERA severely underestimates this interannual variability.