[1] Inclusion of mineral dust radiative effects could lead to a significant improvement in the radiation balance of numerical weather prediction models with subsequent improvements in the weather forecast itself. In this study the radiative effects of mineral dust have been fully incorporated into a regional atmospheric dust model. Dust affects the radiative fluxes at the surface and the top of the atmosphere and the temperature profiles at every model time step when the radiation module is processed. These changes influence the atmospheric dynamics, moisture physics, and near-surface conditions. Furthermore, dust emission is modified by changes in friction velocity and turbulent exchange coefficients; dust turbulent mixing, transport, and deposition are altered by changes in atmospheric stability, precipitation conditions, and free-atmosphere winds. A major dust outbreak with dust optical depths reaching 3.5 at 550 nm over the Mediterranean region on April 2002 is selected to assess the radiative dust effects on the atmosphere at a regional level. A strong dust negative feedback upon dust emission (35-45% reduction of the AOD) resulted from the smaller outgoing sensible turbulent heat flux decreasing the turbulent momentum transfer from the atmosphere and consequently dust emission. Significant improvements of the atmospheric temperature and mean sea-level pressure forecasts are obtained over dust-affected areas by considerably reducing both warm and cold temperature biases existing in the model without dustradiation interactions. This study demonstrates that the use of the proposed model with integrated dust and atmospheric radiation represents a promising approach for further improvements in numerical weather prediction practice and radiative impact assessment over dust-affected areas.Citation: Pérez, C., S. Nickovic, G. Pejanovic, J. M. Baldasano, and E. Ö zsoy (2006), Interactive dust-radiation modeling: A step to improve weather forecasts,

Abstract. Dust storms and associated mineral aerosol transport are driven primarily by meso-and synoptic-scale atmospheric processes. It is therefore essential that the dust aerosol process and background atmospheric conditions that drive dust emissions and atmospheric transport are represented with sufficiently well-resolved spatial and temporal features. The effects of airborne dust interactions with the environment determine the mineral composition of dust particles. The fractions of various minerals in aerosol are determined by the mineral composition of arid soils; therefore, a high-resolution specification of the mineral and physical properties of dust sources is needed.Several current dust atmospheric models simulate and predict the evolution of dust concentrations; however, in most cases, these models do not consider the fractions of minerals in the dust. The accumulated knowledge about the impacts of the mineral composition in dust on weather and climate processes emphasizes the importance of including minerals in modeling systems. Accordingly, in this study, we developed a global dataset consisting of the mineral composition of the current potentially dust-producing soils. In our study, we (a) mapped mineral data to a high-resolution 30 s grid, (b) included several mineral-carrying soil types in dust-productive regions that were not considered in previous studies, and (c) included phosphorus.

Published by Copernicus Publications on behalf of the European Geosciences Union. I. Binietoglou et al.: Dust model comparison methodologyAbstract. Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAM-ABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1-6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of −40 to −20 µg m −3 at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies.

Abstract.A dust storm of fearful proportions hit Phoenix in the early evening hours of 5 July 2011. This storm, an American haboob, was predicted hours in advance because numerical, land-atmosphere modeling, computing power and remote sensing of dust events have improved greatly over the past decade. High-resolution numerical models are required for accurate simulation of the small scales of the haboob process, with high velocity surface winds produced by strong convection and severe downbursts. Dust productive areas in this region consist mainly of agricultural fields, with soil surfaces disturbed by plowing and tracks of land in the high Sonoran Desert laid barren by ongoing draught.Model simulation of the 5 July 2011 dust storm uses the coupled atmospheric-dust model NMME-DREAM (Nonhydrostatic Mesoscale Model on E grid, Janjic et al., 2001; Dust REgional Atmospheric Model, Nickovic et al., 2001;Pérez et al., 2006) with 4 km horizontal resolution. A mask of the potentially dust productive regions is obtained from the land cover and the normalized difference vegetation index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The scope of this paper is validation of the dust model performance, and not use of the model as a tool to investigate mechanisms related to the storm. Results demonstrate the potential technical capacity and availability of the relevant data to build an operational system for dust storm forecasting as a part of a warning system. Model results are compared with radar and other satellitebased images and surface meteorological and PM 10 observations. The atmospheric model successfully hindcasted the position of the front in space and time, with about 1 h late arrival in Phoenix. The dust model predicted the rapid uptake of dust and high values of dust concentration in the ensuing storm. South of Phoenix, over the closest source regions (∼25 km), the model PM 10 surface dust concentration reached ∼2500 µg m −3 , but underestimated the values measured by the PM 10 stations within the city. Model results are also validated by the MODIS aerosol optical depth (AOD), employing deep blue (DB) algorithms for aerosol loadings. Model validation included Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), equipped with the lidar instrument, to disclose the vertical structure of dust aerosols as well as aerosol subtypes. Promising results encourage further research and application of high-resolution modeling and satellite-based remote sensing to warn of approaching severe dust events and reduce risks for safety and health.

No abstract