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Harshvardhan, S. E. Schwartz, C. M. Benkovitz, and G. Guo

Abstract

Anthropogenic aerosols are hypothesized to decrease cloud drop radius and increase cloud droplet number concentration enhancing cloud optical depth and albedo. Here results have been used from a chemical transport model driven by the output of a numerical weather prediction model to identify an incursion of sulfate-laden air from the European continent over the mid–North Atlantic under the influence of a cutoff low pressure system during 2–8 April 1987. Advanced Very High Resolution Radiometer (AVHRR) measurements of visible and near-infrared radiance are used to infer microphysical properties of low-altitude (T = 260–275 K) maritime clouds over the course of the event. Examination of the cloud optical depth, drop radius, and drop number concentration on the high- and low-sulfate days has allowed identification of the increase in cloud droplet number concentration and decrease in cloud drop radius associated with the sulfate incursion. These observations are consistent with the Twomey mechanism of indirect radiative forcing of climate by aerosols.

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J. E. Penner, R. J. Charlson, J. M. Hales, N. S. Laulainen, R. Leifer, T. Novakov, J. Ogren, L. F. Radke, S. E. Schwartz, and L. Travis

Anthropogenic aerosols are composed of a variety of aerosol types and components including water-soluble inorganic species (e.g., sulfate, nitrate, ammonium), condensed organic species, elemental or black carbon, and mineral dust. Previous estimates of the clear sky forcing by anthropogenic sulfate aerosols and by organic biomass-burning aerosols indicate that this forcing is of sufficient magnitude to mask the effects of anthropogenic greenhouse gases over large regions. Here, the uncertainty in the forcing by these aerosol types is estimated. The clear sky forcing by other anthropogenic aerosol components cannot be estimated with confidence, although the forcing by these aerosol types appears to be smaller than that by sulfate and biomass-burning aerosols.

The cloudy sky forcing by anthropogenic aerosols, wherein aerosol cloud condensation nuclei concentrations are increased, thereby increasing cloud droplet concentrations and cloud albedo and possibly influencing cloud persistence, may also be significant. In contrast to the situation with the clear sky forcing, estimates of the cloudy sky forcing by anthropogenic aerosols are little more than guesses, and it is not possible to quantify the uncertainty of the estimates.

In view of present concerns over greenhouse gas-induced climate change, this situation dictates the need to quantify the forcing by anthropogenic aerosols and to define and minimize uncertainties in the calculated forcings. In this article, a research strategy for improving the estimates of the clear sky forcing is defined. The strategy encompasses five major, and necessarily coordinated, activities: surface-based observations of aerosol chemical and physical properties and their influence on the radiation field; aircraft-based observations of the same properties; process studies to refine model treatments; satellite observations of aerosol abundance and size distribution; and modeling studies to demonstrate consistency between the observations, to provide guidance for determination of the most important parameters, and to allow extension of the limited set of observations to the global scale. Such a strategy, if aggressively implemented, should allow these effects to be incorporated into climate models in the next several years. A similar strategy for defining the magnitude of the cloudy sky forcing should also be possible, but the less firm understanding of this forcing suggests that research of a more exploratory nature be carried out before undertaking a research strategy of the magnitude recommended for the clear sky forcing.

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Stanley G. Benjamin, Dezsö Dévényi, Stephen S. Weygandt, Kevin J. Brundage, John M. Brown, Georg A. Grell, Dongsoo Kim, Barry E. Schwartz, Tatiana G. Smirnova, Tracy Lorraine Smith, and Geoffrey S. Manikin

Abstract

The Rapid Update Cycle (RUC), an operational regional analysis–forecast system among the suite of models at the National Centers for Environmental Prediction (NCEP), is distinctive in two primary aspects: its hourly assimilation cycle and its use of a hybrid isentropic–sigma vertical coordinate. The use of a quasi-isentropic coordinate for the analysis increment allows the influence of observations to be adaptively shaped by the potential temperature structure around the observation, while the hourly update cycle allows for a very current analysis and short-range forecast. Herein, the RUC analysis framework in the hybrid coordinate is described, and some considerations for high-frequency cycling are discussed.

A 20-km 50-level hourly version of the RUC was implemented into operations at NCEP in April 2002. This followed an initial implementation with 60-km horizontal grid spacing and a 3-h cycle in 1994 and a major upgrade including 40-km horizontal grid spacing in 1998. Verification of forecasts from the latest 20-km version is presented using rawinsonde and surface observations. These verification statistics show that the hourly RUC assimilation cycle improves short-range forecasts (compared to longer-range forecasts valid at the same time) even down to the 1-h projection.

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John S. Kain, Steven J. Weiss, David R. Bright, Michael E. Baldwin, Jason J. Levit, Gregory W. Carbin, Craig S. Schwartz, Morris L. Weisman, Kelvin K. Droegemeier, Daniel B. Weber, and Kevin W. Thomas

Abstract

During the 2005 NOAA Hazardous Weather Testbed Spring Experiment two different high-resolution configurations of the Weather Research and Forecasting-Advanced Research WRF (WRF-ARW) model were used to produce 30-h forecasts 5 days a week for a total of 7 weeks. These configurations used the same physical parameterizations and the same input dataset for the initial and boundary conditions, differing primarily in their spatial resolution. The first set of runs used 4-km horizontal grid spacing with 35 vertical levels while the second used 2-km grid spacing and 51 vertical levels.

Output from these daily forecasts is analyzed to assess the numerical forecast sensitivity to spatial resolution in the upper end of the convection-allowing range of grid spacing. The focus is on the central United States and the time period 18–30 h after model initialization. The analysis is based on a combination of visual comparison, systematic subjective verification conducted during the Spring Experiment, and objective metrics based largely on the mean diurnal cycle of the simulated reflectivity and precipitation fields. Additional insight is gained by examining the size distributions of the individual reflectivity and precipitation entities, and by comparing forecasts of mesocyclone occurrence in the two sets of forecasts.

In general, the 2-km forecasts provide more detailed presentations of convective activity, but there appears to be little, if any, forecast skill on the scales where the added details emerge. On the scales where both model configurations show higher levels of skill—the scale of mesoscale convective features—the numerical forecasts appear to provide comparable utility as guidance for severe weather forecasters. These results suggest that, for the geographical, phenomenological, and temporal parameters of this study, any added value provided by decreasing the grid increment from 4 to 2 km (with commensurate adjustments to the vertical resolution) may not be worth the considerable increases in computational expense.

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Jordan G. Powers, Joseph B. Klemp, William C. Skamarock, Christopher A. Davis, Jimy Dudhia, David O. Gill, Janice L. Coen, David J. Gochis, Ravan Ahmadov, Steven E. Peckham, Georg A. Grell, John Michalakes, Samuel Trahan, Stanley G. Benjamin, Curtis R. Alexander, Geoffrey J. Dimego, Wei Wang, Craig S. Schwartz, Glen S. Romine, Zhiquan Liu, Chris Snyder, Fei Chen, Michael J. Barlage, Wei Yu, and Michael G. Duda

Abstract

Since its initial release in 2000, the Weather Research and Forecasting (WRF) Model has become one of the world’s most widely used numerical weather prediction models. Designed to serve both research and operational needs, it has grown to offer a spectrum of options and capabilities for a wide range of applications. In addition, it underlies a number of tailored systems that address Earth system modeling beyond weather. While the WRF Model has a centralized support effort, it has become a truly community model, driven by the developments and contributions of an active worldwide user base. The WRF Model sees significant use for operational forecasting, and its research implementations are pushing the boundaries of finescale atmospheric simulation. Future model directions include developments in physics, exploiting emerging compute technologies, and ever-innovative applications. From its contributions to research, forecasting, educational, and commercial efforts worldwide, the WRF Model has made a significant mark on numerical weather prediction and atmospheric science.

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