Dust Forecast Model Research Articles

Improvements of ADAM3 by Incorporating New Dust Emission Reduction Formulations Based on Real-Time MODIS NDVI

Dust events in Northeast Asia have several adverse effects on human health, agricultural land, infrastructure, and transport. Wind speed is the most important factor in determining the total dust emission at the land surface; however, various land-surface conditions must be considered as well. Recently, the Korea Meteorological Administration updated the dust emission reduction factor (RF) in the Asian Dust Aerosol Model 3 (ADAM3) using data from the normalized difference vegetation index (NDVI) of the Moderate Resolution Imaging Spectroradiometer (MODIS). We evaluated the improvements of ADAM3 according to soil types. We incorporated new RF formulations in the evaluation based on real-time MODIS NDVI data obtained over the Asian dust source regions in northern China during spring 2017. This incorporation improved the simulation performance of ADAM3 for the PM10 mass concentration in Inner Mongolia and Manchuria for all soil types, except Gobi. The ADAM3 skill scores for sand, loess, and mixed types in a 24 h forecast increased by 6.6%, 20.4%, and 13.3%, respectively, compared with those in forecasts employing the monthly RF based on the NDVI data. As surface conditions in the dust source regions continually change, incorporating real-time vegetation data is critical to improving performance of dust forecast models such as ADAM3.

Biological crust in sand and dust storm source areas of Asia and its impact on dust emission

Even though the biological crusts are critical to dust emissions, no sand and dust forecast model have considered the impacts of the biological crust in dust emission scheme. This situation mainly comes from two scientific difficulties: there is no large scale regional biological crust data available that can be used in the forecast model; there is no quantification of how biological crusts impact on sand emission. In this way, we studied the distribution of biological soil crust in sand and dust storm source areas of Central and East Asia using Moderate Resolution Imaging Spectroradiometer satellite surface reflectance data collected in 2000–2019 to determine its potential impact on dust emission according to two empirical schemes. We further evaluated the relationships between soil crust coverage, roughness length, and dust emission to study SDS source areas. We found that biological crust is widely distributed in SDS source areas of Central and East Asia, with coverage rates of 19.8% in Central Asian deserts, 23.1% in the Gobi Desert, and 17.3%–32.8% in Chinese deserts (p > 0.05). Cyanobacteria and lichen coverage has increased in Chinese deserts, reflecting the recent impacts of the Project of Returning Farmland to Grassland and Farmland to Forests. However, biological soil crust coverage has not increased in Central Asian deserts or the Gobi Desert, and that in Central Asian deserts continues to decrease, demonstrating the complexity of the combined effects of human activities and climate change on its distribution. Biological soil crust increased the roughness length of Central and East Asian SDS source areas by 0.14–0.62 mm. The suppression of dust emission due to biological soil crust did not change among years during the study period. The horizontal and vertical dust flux inhibition coefficient (DFIC) were 2.0–11.0 and 1.7–2.9 (p > 0.05), respectively, clearly showing a suppressive effect. Improvement of the ecological environment in some deserts can lead to the ability of these crusts to inhibit dust erosion errors that must be considered in the dust emission scheme for areas where crust coverage has improved.

Representations of dynamics size distributions of mineral dust over East Asia by a regional sand and dust storm model

Particles larger than 5.0 μm in diameter are important to keep the size distribution for mineral dust but it is difficult to represent them in numerical models due to the complex emission process and quick gravitational deposition. To improve this situation, the cumulative distribution function of the Weibull distribution is used to represent the instant wind larger than the model grid-mean wind speeds of the sectional dust forecast model, China Meteorological Administration Unified Atmospheric Chemistry Environment/Dust (CUACE/Dust). Size distributions for dessert soil texture in China and mass median diameters for the three lognormal populations of dust flux released are also improved from observations in Asian source areas. With all these updating, the mass size distribution of dust flux from the model is much closer to the observed value, which changes the original unreasonable single-peak distribution, coming close to the distribution trend with increasing particle size bins. It then improves the emission for coarse particles larger than 10.0 μm in source areas. Moreover, both the varied values and changing shape patterns of column volume particle size distributions simulated in the downwind areas compatible to the observed by the global AErosol RObotic NETwork (AERONET) achieving an obvious improvement for the size distribution of coarse particles larger than 5.0 μm in these downwind areas.

Tropospheric Dust and Associated Atmospheric Circulations over the Mediterranean Region with Focus on Romania’s Territory

The aim of this study is to assess the distribution of dust over the Mediterranean region, with a special focus on the territory of Romania. Two parameters are analyzed—Dust Load (DL) and Aerosol Optical Depth (AOD), the data is obtained from the dust forecast model BSC-DREAM8b v2.0, for the period between December 2015 and February 2019. The main geographical features of dust occurrence in the Mediterranean region are presented at the monthly and annual scale. The results show that, for Romania, the dust load is high from February to June, when it reaches its annual maximum. The atmospheric circulation inducing intense dust events over Romania have also been assessed using an objective classification method. A key element for the dust transport from the Sahara toward South-Eastern Europe is represented by the development of a deep cyclone South of Italy, following thereafter a North-East path towards the Balkan peninsula. The results at the regional scale are analyzed in connection with the aerosol optical properties at the local scale (e.g., aerosol optical depth at 440 nm, Absorption Ångström Exponent and Scattering Ångström Exponent at 440 nm and 675 nm, respectively) retrieved from the Aerosol Robotic Network (AERONET-NASA) for Romania, using data from ACTRIS-RO monitoring sites from Iași, Cluj–Napoca, and Bucharest. The differences between the forecast model and the observational data are also explored. Our results also show that the contribution of the natural mineral dust to air pollution in Romania is small, representing not more than 10% of all kinds of aerosols detected over the observation points from the ACTRIS-RO network.

Seasonal Prediction Potential for Springtime Dustiness in the United States

AbstractMost dust forecast models focus on short, subseasonal lead times, that is, 3 to 6 days, and the skill of seasonal prediction is not clear. In this study we examine the potential of seasonal dust prediction in the United States using an observation‐constrained regression model and key variables predicted by a seasonal prediction model developed at National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory, the Forecast‐Oriented Low Ocean Resolution (FLOR) model. Our method shows skillful predictions of spring dustiness 3 to 6 months in advance. It is found that the regression model explains about 71% of the variances of dust event frequency over the Great Plains and 63% over the southwestern United States in March‐May from 2004 to 2016 using predictors from FLOR initialized on 1 December. Variations in springtime dustiness are dominated by springtime climatic factors rather than wintertime factors. Findings here will help development of a seasonal dust prediction system and hazard prevention.

Extreme, wintertime Saharan dust intrusion in the Iberian Peninsula: Lidar monitoring and evaluation of dust forecast models during the February 2017 event

An unprecedented extreme Saharan dust event was registered in winter time from 20 to 23 February 2017 over the Iberian Peninsula (IP). We report on aerosol optical properties observed under this extreme dust intrusion through passive and active remote sensing techniques. For that, AERONET (AErosol RObotic NETwork) and EARLINET (European Aerosol Research LIdar NETwork) databases are used. The sites considered are: Barcelona (41.38°N, 2.17°E), Burjassot (39.51°N, 0.42°W), Cabo da Roca (38.78°N, 9.50°W), Évora (38.57°N, 7.91°W), Granada (37.16°N, 3.61°W) and Madrid (40.45°N, 3.72°W). Large aerosol optical depths (AOD) and low Ångström exponents (AE) are observed. An AOD of 2.0 at 675 nm is reached in several stations. A maximum peak of 2.5 is registered in Évora. During and around the peak of AOD, AEs close to 0 and even slightly negative are measured. With regard to vertically-resolved aerosol optical properties, particle backscatter coefficients as high as 15 Mm−1 sr−1 at 355 nm are recorded at the lidar stations. Layer-mean lidar ratios are found in the range 40–55 sr at 355 nm and 34–61 sr at 532 nm during the event. The particle depolarization ratios are found to be constant inside the dust layer, and consistent from one site to another. Layer-mean values vary in the range 0.19–0.31. Another remarkable aspect of the event is the limited vertical distribution of the dust plume which never exceeds 5 km. The extreme aspect of the event also presented a nice case for testing the ability of two dust forecast models, BSC-DREAM8b and NMMB/BSC-Dust, to reproduce the arrival, the vertical distribution and the intensity of the dust plume over a long-range transport region. In the particular case of the February 2017 dust event, we found a large underestimation in the forecast of the extinction coefficient provided by BSC-DREAM8b at all heights independently of the site. In contrast NMMB/BSC-Dust forecasts presented a better agreement with the observations, especially in southwestern part of the IP. With regard to the forecast skill as a function of lead time, no clear degradation of the prognostic is appreciated at 24, 48 and 72 h for Évora and Granada stations (South). However the prognostic does degrade (bias increases and/or correlation decreases) for Barcelona (North), which is attributed to the fact that Barcelona is at a greater distance from the source region and to the singularity of the event.

Comparisons suggest more efforts are required to parameterize wind flow around shrub vegetation elements for predicting aeolian flux

Upon interacting with the atmosphere, vegetation could alter the wind distribution and consequently the erodibility of nearby region. The parameterization of wind distribution around vegetation is crucial for the prediction of surface aeolian flux. This paper compared the performances of existing empirical distribution models in the estimation of aeolian flux for shrub vegetation, focusing on distribution pattern and vegetation porosity (main parameter of distribution function). Predicted dust fluxes directly entrained by air flow show weak sensitivity to both distribution pattern and porosity in the case of low vegetation density, which suggests some aspects in dust forecast models might be simplified. However, both distribution pattern and porosity show significant effect on sand saltation transport rate in the lee of vegetation element and, consequently, on the formation and evolution of surface aeolian landforms. The contribution of dust fluxes released in wind increase zone to the total emission by using current parameterizations increases with both the decrease of wind speed and the increase of vegetation density. Nevertheless, the parameterization of wind increase zone needs to be validated and improved by further experimental and numerical investigations.

Origin and pathways of the mineral dust transport to two Spanish EARLINET sites: Effect on the observed columnar and range-resolved dust optical properties

In this paper, is presented a method for estimation of the effect of the transport process to aerosol optical properties. Aerosol optical data retrieved by lidars and sun-photometer measurements, are applied to Saharan dust events observed simultaneously at the two EARLINET/AERONET sites of Barcelona and Granada during the periods of June–September of 2012 and 2013. For this purpose, elastic lidar profiles and sun-photometer columnar retrievals are analyzed together with satellite observations and dust forecast models. Granada presents more than twice Saharan dust outbreaks compared to Barcelona. The scenarios favoring the Saharan dust outbreaks are identified in both places. The mineral dust originating in the Sahara region and arriving at both stations is usually transport wither over the Atlas Mountains or through an Atlantic pathway. Analyses of dust events affecting both stations reveal how differences in the transport process lead to differences in the aerosol optical properties measured at each station. Mean dust related Ångström exponent is 1.8 times higher in Barcelona than in Granada. This difference is a result of the additional contribution of anthropogenic aerosol, mainly in the aerosol fine mode, during the transport of the mineral dust plume over the Iberian Peninsula.

A 3D multi-threshold, region-growing algorithm for identifying dust storm features from model simulations

ABSTRACTDust storms cause significant damage to health, property, and the environment worldwide every year. To help mitigate the damage, dust forecast models simulate and predict upcoming dust events, providing valuable information to scientists, decision makers, and the public. These simulation outputs are in four-dimensions (i.e., latitude, longitude, elevation, and time) and represent spatially heterogeneous dust storm features and their evolution over space and time. This research investigates and proposes an automatic multi-threshold, region-growing-based algorithm to identify critical dust storm features from 3D dust storm simulations. A multi-threshold scheme is defined for the identification of dust storm features with different dust concentrations. Based on the multi-thresholds, dust storm features are iteratively identified by developing a region-growing algorithm that splits a clustered dust storm feature into multiple sub-features. The proposed approach is compared with three commonly used methods in image processing and thunderstorm identification. The proposed approach outperforms the other three methods in sensitivity and quantitative/qualitative accuracy. This research approach may also be slightly adjusted to identify critical 3D features from simulation outputs for other severe weather and geographical phenomena.

Forecasting the northern African dust outbreak towards Europe in April 2011: a model intercomparison

Abstract. In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 h using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distribution was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. Our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.

사계절 황사단기예측모델 UM-ADAM2의 2010년 황사 예측성능 분석

The Asian dust (Hwangsa) forecasting model, Asian Dust Aerosol Model (ADAM) has been modified by using satelliate monitoring of surface vegetation, which enables to simulate dusts occuring not only in springtime but also for all-year-round period. Coupled with the Unified Model (UM), the operational weather forecasting model at KMA, UM-ADAM2 was implemented for operational dust forecasting since 2010, with an aid of development of Meteorology-Chemistry Interface Processor (MCIP) for usage UM. The performance analysis of the ADAM2 forecast was conducted with concentrations observed at monitoring sites in the source regions in China and the downstream regions of Korea from March to December in 2010. It was found that the UM-ADAM2 model was able to simulate quite well Hwangsa events observed in spring and wintertime over Korea. In the downstream region of Korea, the starting and ending times of dust events were well-simulated, although the surface concentration was slightly underestimated for some dust events. The general negative bias less than in is found and it is likely to be due to other fine aerosol species which is not considered in ADAM2. It is found that the correlation between observed and forecasted concentration increases as forecasting time approaches, showing stably high correlation about 0.7 within 36 hr in forecasting time. This suggests the possibility that there is potential for the UM-ADAM2 model to be used as an operational Asian dust forecast model.

Influence of mineral dust transport on the chemical composition and physical properties of the Eastern Mediterranean aerosol

Bulk aerosol samples were collected from three different coastal rural sites located around the Eastern Mediterranean, (i) Erdemli (ER), Turkey, (ii) Heraklion (HR), Crete, Greece, and (iii) Tel Shikmona (TS), Israel, during two distinct mineral dust periods (October, 2007 and April, 2008) in order to explore the temporal and geographical variability in the aerosol chemical composition. Samples were analyzed for trace elements (Al, Fe, Mn, Ca, Cr, Zn, Cu, V, Ni, Cd, Pb) and water-soluble ions (Cl−, NO3−, SO42−, C2O42−, Na+, NH4+, K+, Mg2+ and Ca2+). The dust events were categorized on the basis of Al concentrations >1000 ng m−3, SKIRON dust forecast model and 3-day back trajectories into three groups namely, Middle East, Mixed and Saharan desert. ER and TS were substantially affected by dust events originating from the Middle East, particularly in October, whilst HR was not influenced by dust transport from the Middle East. Higher AOT values were particularly associated with higher Al concentrations. Contrary to the highest Al concentration: 6300 ng m−3, TS showed relatively lower AI and AOT. Al concentrations at ER were similar for October and April, whilst OMI-AI and AOT values were ∼2 times higher in April. This might be attributed to the weak sensitivity of the TOMS instrument to absorbing aerosols near the ground and optical difference between Middle East and Saharan desert dusts. The lowest enhancement of anthropogenic aerosol species was observed at HR during dust events (nssSO42−/nssCa2+ ∼ 0.13). These species were particularly enhanced when mineral dust arrived at sites after passing through populated and industrialized urban areas.

Assessment of the Met Office dust forecast model using observations from the GERBILS campaign

AbstractThis paper uses aircraft, ground‐based and satellite observations to assess the performance of Met Office dust forecasts during the Geostationary Earth Radiation Budget Intercomparison of Long‐wave and Short‐wave radiation (GERBILS) campaign. The dust forecasts were produced from a 20 km resolution limited‐area numerical weather prediction configuration of the Met Office Unified Model, based over North Africa. Dust uplift was modelled using two modified versions of the Woodward (2001) dust parametrization scheme. The model produced widespread dust over the Sahara desert in response to synoptically driven strong wind events. The modelled aerosol size distribution and short‐wave optical properties compared well with aircraft in situ measurements and retrievals from the Aerosol Robotic Network (AERONET). Better size distributions and extinction coefficients were achieved by fixing the emitted dust size distribution rather than attempting to predict this dynamically. The two versions performed similarly compared to observations of other variables. The interaction of dust with short‐wave and long‐wave radiation compared well with aircraft observations when scaled to allow for local differences in Aerosol Optical Depth (AOD). AODs were on average 50–100% too high over south‐western parts of the Sahara but 20–50% too low over the Sahel when compared to AERONET sites, aircraft profile estimates and satellite retrieval products. This implicated excessive dust emission over central parts of the Sahara and insufficient dust emissions from the Bodélé depression and semi‐arid regions on the southern border of the Sahara. These biases were linked to potential errors in wind speed, soil texture, soil moisture and vegetation, and possible limitations in the dust parametrization, such as the lack of an observationally constrained or geomorphologically based preferential source term. Copyright © 2011 Royal Meteorological Society and Crown copyright, the Met Office

The Asian Dust Aerosol Model 2 (ADAM2) with the use of Normalized Difference Vegetation Index (NDVI) obtained from the Spot4/vegetation data

The operational Asian Dust Aerosol Model (ADAM)1 in Korea Meteorological Administration has been modified to the ADAM2 model to be used as an operational forecasting model all year round not only in Korea but also in the whole Asian domain (70-160°E and 5-60°N) using the routinely available World Meteorological Organization (WMO) surface reporting data and the Spot/vegetation Normalized Difference Vegetation Index (NDVI) data for the period of 9 years from 1998 to 2006. The 3-hourly reporting WMO surface data in the Asian domain have been used to re-delineate the Asian dust source region and to determine the temporal variation of the threshold wind speed for the dust rise. The dust emission reduction factor due to vegetation in different surface soil-type regions (Gobi, sand, loess, and mixed soil) has been determined with the use of NDVI data. It is found that the threshold wind speed for the dust rise varies significantly with time (minimum in summer and maximum in winter) and surface soil types with the highest threshold wind speed of 8.0 m s−1 in the Gobi region and the lowest value of 6.0 m s−1 in the loess region. The statistical analysis of the spot/vegetation NDVI data enables to determine the emission reduction factor due to vegetation with the free NDVI value that is the NDVI value without the effect of vegetation and the upper limit value of NDVI for the dust rise in different soil-type regions. The modified ADAM2 model has been implemented to simulate two Asian dust events observed in Korea for the periods from 31 March to 2 April 2007 (a spring dust event) and from 29 to 31 December 2007 (a winter dust event) when the observed PM10 concentration at some monitoring sites in the source region exceeds 9,000 μg m−3. It is found that ADAM2 model successfully simulates the observed high dust concentrations of more than 8,000 μg m−3 in the dust source region and 600 μg m−3 in the downstream region of Korea. This suggests that ADAM2 has a great potential for the use of an operational Asian dust forecast model in the Asian domain.

A method to determine the effect of mineral dust aerosols on air quality

Natural mineral dust storms (DS) from the Arabo-African region blow over the Mediterranean, reach Israel, and add to the anthropogenic particulate pollution. The effects of mineral dust on air quality in Israel were investigated using only PM10 and PM2.5 automatic measurements. The method does not require any other inputs such as satellite observations, model back-trajectories, dust forecast models, or mineralogical analyses. The method employs an automatic algorithm with three thresholds: the half-hour PM10 average must be above 100, this level is maintained for at least 3 h, and the maximum concentration recorded is above 180 μg m −3. The algorithm was designed for Israel, but can be adapted for other locations. The contribution of DS caused PM10 values to exceed the Israeli annual standard of 60 μg m −3 year −1 in 6 of the 12 years examined. The DS contribution to PM10 annual average ranged from 9.4% to 29.5%. The level recommended by WHO, 20 μg m −3 year −1, was exceeded every year even without the DS contribution. The number of days in which the daily Israeli standard (150 μg m −3) was exceeded during the 12 years was 6–20 days per year. The number of days in which the daily standard was exceeded shows an increasing trend of 7 days per decade. PM2.5 in Israel is in the range 40–56% of PM10. PM2.5 values were over the recommended standard with and without DS. The contribution of DS to annual average of PM2.5 ranged from 3.6% to 19.1%. The automatic algorithm was calibrated with a list of Dust Storms identified by visual means supported by mineralogical analysis. Mineralogical analyses of single particles were performed using Environmental Scanning Electron Microscope (ESEM). Two representative samples are given. The main difference is that the particles of the Saudi-Arabian storm had much more palygorskite, while the North-African storm had more sea-salt and organic particles. The mineral composition differences indicate that analysis can differentiate between sources.

LMDzT-INCA dust forecast model developments and associated validation efforts

The nudged atmosphere global climate model LMDzT-INCA is used to forecast global dust fields. Evaluation is undertaken in retrospective for the forecast results of the year 2006. For this purpose AERONET/Photons sites in Northern Africa and on the Arabian Peninsula are chosen where aerosol optical depth is dominated by dust. Despite its coarse resolution, the model captures 48% of the day to day dust variability near Dakar on the initial day of the forecast. On weekly and monthly scale the model captures respectively 62% and 68% of the variability. Correlation coefficients between daily AOD values observed and modelled at Dakar decrease from 0.69 for the initial forecast day to 0.59 and 0.41 respectively for two days ahead and five days ahead. If one requests that the model should be able to issue a warning for an exceedance of aerosol optical depth of 0.5 and issue no warning in the other cases, then the model was wrong in 29% of the cases for day 0, 32% for day 2 and 35% for day 5. A reanalysis run with archived ECMWF winds is only slightly better (r=0.71) but was in error in 25% of the cases. Both the improved simulation of the monthly versus daily variability and the deterioration of the forecast with time can be explained by model failure to simulate the exact timing of a dust event.

Operational retrieval of Asian sand and dust storm from FY-2C geostationary meteorological satellite and its application to real time forecast in Asia

Abstract. This paper describes an operational retrieval algorithm for the sand/dust storm (SDS) from FY-2C/S-VISSR (Stretched-Visible and Infrared Spin-Scan Radiometer) developed at the National Satellite Meteorological Center (NSMC) of China. This algorithm, called Dust Retrieval Algorithm based on Geostationary Imager (DRAGI), is based on the optical and radiative physical properties of SDS in mid-infrared and thermal infrared spectral regions as well as the observation of all bands in the geostationary imager, which include the Brightness Temperature Difference (BTD) in split window channels, Infrared Difference Dust Index (IDDI) and the ratio of middle infrared reflectance to visible reflectance. It also combines the visible and water vapor bands observation of the geostationary imager to identify the dust clouds from the surface targets and meteorological clouds. The output product is validated by and related to other dust aerosol observations such as the synoptic weather reports, surface visibility, aerosol optical depth (AOD) and ground-based PM10 observations. Using the SDS-IDD product and a data assimilation scheme, the dust forecast model CUACE/Dust achieved a substantial improvement to the SDS predictions in spring 2006.

Simulations of Asian Yellow Dust Incursion Over Taiwan for the Spring of 2002 and 2003

Dust storms that occurred in East Asia during the spring of 2002 and 2003 were simulated by a regional dust deflation and transport model. Particular focus was placed on dust incursion events over Taiwan. Two of the events were analyzed in detail to give a complete picture of the three dimensional transport patterns. The general characteristics of dust incursion events were summarized, including the source locations, transport route and distribution pattern in three dimensions, traveling time, duration of incursion, and the seasonal spatial distribution of dust concentration. Significant differences were also found in these characteristics between the two years, the main cause of which was a change in regional climate patterns. The performance of the model developed for this study was evaluated against other dust forecast models, and found to have superior capability for forecasting in the Taiwan area.

Forecasting dust storms using the CARMA-dust model and MM5 weather data

An operational model for the forecast of dust storms in Northern Africa, the Middle East and Southwest Asia has been developed for the United States Air Force Weather Agency (AFWA). The dust forecast model uses the 5th generation Penn State Mesoscale Meteorology Model (MM5) as input to the University of Colorado CARMA dust transport model. AFWA undertook a 60 day evaluation of the effectiveness of the dust model to make short, medium and long- range (72 h) forecasts of dust storms. The study is unique in using satellite and ground observations of dust storms to score the model’s effectiveness using standard meteorological statistics. Each of the main forecast regions was broken down into smaller areas for more detailed analysis. The study found the forecast model is an effective forecast tool with Probability of Detection of dust storm occurrence exceeding 68 percent over Northern Africa, with a 16 percent False Alarm Rate. Southwest Asia forecasts had average Probability of Detection values of 61 percent with False Alarm Rates averaging 10 percent.