A comprehensive dataset of microphysical and radiative properties of aerosols and clouds in the boundary layer in the vicinity of Barrow, Alaska, was collected in April 2008 during the Indirect and Semi-Direct Aerosol Campaign (ISDAC). ISDAC's primary aim was to examine the effects of aerosols, including those generated by Asian wildfires, on clouds that contain both liquid and ice. ISDAC utilized the Atmospheric Radiation Measurement Pro- gram's permanent observational facilities at Barrow and specially deployed instruments measuring aerosol, ice fog, precipitation, and radiation. The National Research Council of Canada Convair-580 flew 27 sorties and collected data using an unprecedented 41 stateof- the-art cloud and aerosol instruments for more than 100 h on 12 different days. Aerosol compositions, including fresh and processed sea salt, biomassburning particles, organics, and sulfates mixed with organics, varied between flights. Observations in a dense arctic haze on 19 April and above, withi... Abstract A comprehensive dataset of microphysical and radiative properties of aerosols and clouds in the boundary layer in the vicinity of Barrow, Alaska, was collected in April 2008 during the Indirect and Semi-Direct Aerosol Campaign (ISDAC). ISDAC's primary aim was to examine the effects of aerosols, including those generated by Asian wildfires, on clouds that contain both liquid and ice. ISDAC utilized the Atmospheric Radiation Measurement Pro- gram's permanent observational facilities at Barrow and specially deployed instruments measuring aerosol, ice fog, precipitation, and radiation. The National Research Council of Canada Convair-580 flew 27 sorties and collected data using an unprecedented 41 stateof- the-art cloud and aerosol instruments for more than 100 h on 12 different days. Aerosol compositions, including fresh and processed sea salt, biomassburning particles, organics, and sulfates mixed with organics, varied between flights. Observations in a dense arctic haze on 19 April and above, withi...

The main purpose of this work is to describe a major field project on fog and summarize the preliminary results. Three field phases of the Fog Remote Sensing and Modeling (FRAM) project were conducted over the following two regions of Canada: 1) the Center for Atmospheric Research Experiments (CARE), in Toronto, Ontario (FRAM-C), during the winter of 2005/06, and 2) Lunenburg, Nova Scotia (FRAM-L), during June 2006 and June 2007. Fog conditions observed during FRAM-C were continental in nature, while those conditions observed during FRAM-L were of marine origin. The main objectives of the project were to attain 1) a better description of fog environments, 2) the development of microphysical parameterizations for model applications, 3) the development of remote sensing methods for fog nowcasting/forecasting, 4) an understanding of issues related to instrument capabilities and improvement of the analysis, and 5) an integration of model data with observations to predict and detect fog areas and particle phas... The main purpose of this work is to describe a major field project on fog and summarize the preliminary results. Three field phases of the Fog Remote Sensing and Modeling (FRAM) project were conducted over the following two regions of Canada: 1) the Center for Atmospheric Research Experiments (CARE), in Toronto, Ontario (FRAM-C), during the winter of 2005/06, and 2) Lunenburg, Nova Scotia (FRAM-L), during June 2006 and June 2007. Fog conditions observed during FRAM-C were continental in nature, while those conditions observed during FRAM-L were of marine origin. The main objectives of the project were to attain 1) a better description of fog environments, 2) the development of microphysical parameterizations for model applications, 3) the development of remote sensing methods for fog nowcasting/forecasting, 4) an understanding of issues related to instrument capabilities and improvement of the analysis, and 5) an integration of model data with observations to predict and detect fog areas and particle phas...

The objective of this work is to suggest a new warm-fog visibility parameterization scheme for numerical weather prediction (NWP) models. In situ observations collected during the Radiation and Aerosol Cloud Experiment, representing boundary layer low-level clouds, were used to develop a parameterization scheme between visibility and a combined parameter as a function of both droplet number concentration Nd and liquid water content (LWC). The current NWP models usually use relationships between extinction coefficient and LWC. A newly developed parameterization scheme for visibility, Vis = f (LWC, Nd), is applied to the NOAA Nonhydrostatic Mesoscale Model. In this model, the microphysics of fog was adapted from the 1D Parameterized Fog (PAFOG) model and then was used in the lower 1.5 km of the atmosphere. Simulations for testing the new parameterization scheme are performed in a 50-km innermost-nested simulation domain using a horizontal grid spacing of 1 km centered on Zurich Unique Airport in Switzerland. The simulations over a 10-h time period showed that visibility differences between old and new parameterization schemes can be more than 50%. It is concluded that accurate visibility estimates require skillful LWC as well as Nd estimates from forecasts. Therefore, the current models can significantly over-/underestimate Vis (with more than 50% uncertainty) depending on environmental conditions. Inclusion of Nd as a prognostic (or parameterized) variable in parameterizations would significantly improve the operational forecast models.

Airborne observations from 14 flights in marine stratus over the Gulf of Maine and Bay of Fundy in August and September of 1993 are examined for the relationships among the cloud droplet number concentrations (N_d), the out‐of‐cloud aerosol particle number concentrations (N_a), the major ion concentrations in the cloud water, and turbulence in cloud. There was a wide range of aerosol concentrations, but when low stratus and the main anthropogenic plume from eastern North America were in the same area the plume overrode the cloud. The N_d increased with increasing N_a and cloud water sulfate concentration (cwSO₄⁼), but the relationships were very weak. The separation of the data between smooth and lightly turbulent air substantially improved the ability to explain the variance in the N_d by either of these two quantities. Also, the relative increase in N_d for increases in N_a and cwSO₄⁼ was greater for lightly turbulent air than for smooth air. The estimated minimum size of particles activated in these clouds ranged from 0.14 μm to 0.31 μm, corresponding to average supersaturations of <0.1%. The minimum size tended to be lower for lightly turbulent air and smaller N_a. The results for lightly turbulent air agree well with previously reported parameterizations of the impact of aerosols on N_d, but the results for smooth air do not agree. In general, more knowledge of the physical factors controlling the N_d in stratiform clouds, such as turbulence, is needed to improve not only our ability to represent N_d but also to increase our understanding of the impact of the aerosol particles on the N_d and climate.