Contrary to its currently known characteristics, the nocturnal boundary layer over the Great Plains is frequently populated with a variety of turbulence-producing phenomena. C ASES-99 considers four scientific questions primarily related to the stable, nocturnal boundary layer, including the transition periods. The CASES-99 field program attempted to identify the sources and to quantify the physical characteristics of atmospheric phenomena occurring from the formative stages of the NBL 1 until its eventual breakup during the morning transition. The follow-up pro-1 Acronyms not defined in the text are defined in the appendix.

Abstract. In the present work, atmospheric mineral dust from a MACC-II short reanalysis run for 2 years (2007–2008) has been evaluated over northern Africa and the Middle East using satellite aerosol products (from MISR, MODIS and OMI satellite sensors), ground-based AERONET data, in situ PM10 concentrations from AMMA, and extinction vertical profiles from two ground-based lidars and CALIOP satellite-based lidar. The MACC-II aerosol optical depth (AOD) spatial and temporal (seasonal and interannual) variability shows good agreement with those provided by satellite sensors. The capability of the model to reproduce the AOD, Ångström exponent (AE) and dust optical depth (DOD) from daily to seasonal time-scale is quantified over 26 AERONET stations located in eight geographically distinct regions by using statistical parameters. Overall DOD seasonal variation is fairly well simulated by MACC-II in all regions, although the correlation is significantly higher in dust transport regions than in dust source regions. The ability of MACC-II in reproducing dust vertical profiles has been assessed by comparing seasonal averaged extinction vertical profiles simulated by MACC-II under dust conditions with corresponding extinction profiles obtained with lidar instruments at M'Bour and Santa Cruz de Tenerife, and with CALIOP. We find a good agreement in dust layers structures and averaged extinction vertical profiles between MACC-II, the lidars and CALIOP above the marine boundary layer from 1 to 6 km. Surface dust daily mean concentrations from MACC-II reanalysis has been evaluated with daily averaged PM10 at three monitoring stations of the Sahelian Dust Transect. MACC-II correctly reproduces daily to interannual surface dust concentration variability, although it underestimates daily and monthly means all year long, especially in winter and early spring (dry season). MACC-II reproduces well the dust variability recorded along the station transect which reflects the variability in dust emission by different Saharan sources, but fails in reproducing the sporadic and very strong dust events associated to mesoscale convective systems during the wet season.

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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.

The short-term forecasting of fog is a difficult issue that can have a large societal impact. Radiation fog appears in the surface boundary layer, and its evolution is driven by the interactions between the surface and lower layers of the atmosphere. Current NWP models poorly forecast the life cycle of fog, and improved NWP models are needed before improving the prediction of fog. Six numerical model simulations are compared for two cases from the Paris-Charles de Gaulle (Paris-CdG) fog field experiment. This intercomparison includes both operational and research models, which have significantly different vertical resolutions and physical parameterizations. The main goal of this intercomparison is to identify the capabilities of the various models to forecast fog accurately. An attempt is made to identify the main reasons behind the differences among the various models. This intercomparison reveals that considerable differences among models exist in the surface boundary layer before the fog onset, particularly in cases with light winds. The lower-resolution models crudely forecast the nocturnal inversion, the strong inversion at the top of the fog layer, and the interactions between soil and atmosphere. This intercomparison further illustrates the importance of accurate parameterizations of dew deposition and gravitational settling on the prediction of fog.