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Barry E. Schwartz, Dennis M. Rodgers, and J. Todd Hawes

Abstract

An experiment is reported in which derived diagnostic parameters computed from Limited-area Fine-Mesh (LFM) model gridpoint data were examined to determine subjectively whether their availability in real time would assist the forecaster in interpreting and understanding the model's forecast of the weather. Specifically, model products thought to relate to the development of mesoscale convective weather systems (MCSs) were combined into a composite forecast and compared with the standard ensemble of LFM products for 25 episodes of significant convective activity. An objective verification of the LFM forecasts themselves was not attempted. Both 12 and 24 h forecasts from the 1200 UTC run were considered. In a majority of cases, it was evident that derived diagnostic gridpoint data added information about parameter patterns and values important to MCS development that was not obvious from viewing the conventional model products alone. Two case studies demonstrate how information about 850 mb moisture convergence and lower tropospheric temperature advection can help to understand why the model predicted a maximum in vertical velocity (and precipitation) in a region that did not look favorable for large-scale ascent as diagnosed from the conventional output.

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M. J. Schwartz, J. W. Barrett, P. W. Fieguth, P. W. Rosenkranz, M. S. Spina, and D. H. Staelin

Abstract

An imaging microwave radiometer with eight double-sideband channels centered on the 118-GHz oxygen resonance was flown on a high-altitude aircraft over a tropical cyclone in the Coral Sea. The measurements clearly resolved an eyewall of strong convection and a warm core within the eye. Brightness temperatures observed within the eye were approximately 10 K warmer than those observed in clear air 100 km or more away. This warming extended somewhat beyond the eyewall in the highest (most opaque) channel. The temperature profile in the eye, central pressure, and convective cell-top altitudes are inferred from the data.

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S. Solomon, R. R. Garcia, J. J. Olivero, R. M. Bevilacqua, P. R. Schwartz, R. T. Clancy, and D. O. Muhleman

Abstract

Two-dimensional model calculations of the photochemistry and transport of carbon monoxide in the stratosphere, mesosphere, and lower thermosphere are presented. Results are compared to available observations at midlatitudes, where both observation and theory suggest that mesospheric CO abundances are larger on average in winter than in summer. The calculations also indicate that extremely large densities of CO should be found in the polar night mesosphere and upper stratosphere, but at present no high-latitude data are available for direct comparison. However, it is suggested that such a latitudinal distribution implies that the midlatitude region can exhibit unusually large abundances of CO under conditions of large-scale planetary wave activity. Two midlatitude observations during late January 1982 am shown to be consistent with this possibility.

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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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Scott D. Landolt, Roy M. Rasmussen, Alan J. Hills, Warren Underwood, Charles A. Knight, Albert Jachcik, and Andrew Schwartz

Abstract

The National Center for Atmospheric Research (NCAR) developed an artificial snow-generation system designed to operate in a laboratory cold chamber for testing aircraft anti-icing fluids under controlled conditions. Flakes of ice are produced by shaving an ice cylinder with a rotating carbide bit; the resulting artificial snow is dispersed by turbulent airflows and falls approximately 2.5 m to the bottom of the device. The resulting fine ice shavings mimic snow in size, distribution, fall velocity, density, and liquid water equivalent (LWE) snowfall rate. The LWE snowfall rate can be controlled using either a mass balance or a precipitation gauge, which measures the snowfall accumulation over time, from which the computer derives the LWE rate. LWE snowfall rates are calculated every 6 s, and the rate the ice cylinder is fed into the carbide bit is continually adjusted to ensure that the LWE snowfall rate matches a user-selected value. The system has been used to generate LWE snowfall rates ranging from 0 to 10 mm h−1 at temperatures from −2 to −30°C and densities of approximately 0.1–0.5 g cm−3. Comparisons of the snow-machine fluid tests with the outdoor fluid tests have shown that the snow machine can mimic natural outdoor rates under a broad range of conditions.

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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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BRIAN J. BUTTERWORTH, ANKUR R. DESAI, STEFAN METZGER, PHILIP A. TOWNSEND, MARK D. SCHWARTZ, GRANT W. PETTY, MATTHIAS MAUDER, HANNES VOGELMANN, CHRISTIAN G. ANDRESEN, TRAVIS J. AUGUSTINE, TIMOTHY H. BERTRAM, WILLIAM O.J. BROWN, MICHAEL BUBAN, PATRICIA CLEARY, DAVID J. DURDEN, CHRISTOPHER R. FLORIAN, TREVOR J. IGLINSKI, ERIC L. KRUGER, KATHLEEN LANTZ, TEMPLE R. LEE, TILDEN P. MEYERS, JAMES K. MINEAU, ERIK R. OLSON, STEVEN P. ONCLEY, SREENATH PALERI, ROSALYN A. PERTZBORN, CLAIRE PETTERSEN, DAVID M. PLUMMER, LAURA RIIHIMAKI, ELICEO RUIZ GUZMAN, JOSEPH SEDLAR, ELIZABETH N. SMITH, JOHANNES SPEIDEL, PAUL C. STOY, MATTHIAS SÜHRING, JONATHAN E. THOM, DAVID D. TURNER, MICHAEL P. VERMEUEL, TIMOTHY J. WAGNER, ZHIEN WANG, LUISE WANNER, LOREN D. WHITE, JAMES M. WILCZAK, DANIEL B. WRIGHT, and TING ZHENG

CAPSULE SUMMARY

A regional-scale observational experiment designed to address how the atmospheric boundary layer responds to spatial heterogeneity in surface energy fluxes.

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Brian J. Butterworth, Ankur R. Desai, Philip A. Townsend, Grant W. Petty, Christian G. Andresen, Timothy H. Bertram, Eric L. Kruger, James K. Mineau, Erik R. Olson, Sreenath Paleri, Rosalyn A. Pertzborn, Claire Pettersen, Paul C. Stoy, Jonathan E. Thom, Michael P. Vermeuel, Timothy J. Wagner, Daniel B. Wright, Ting Zheng, Stefan Metzger, Mark D. Schwartz, Trevor J. Iglinski, Matthias Mauder, Johannes Speidel, Hannes Vogelmann, Luise Wanner, Travis J. Augustine, William O. J. Brown, Steven P. Oncley, Michael Buban, Temple R. Lee, Patricia Cleary, David J. Durden, Christopher R. Florian, Kathleen Lantz, Laura D. Riihimaki, Joseph Sedlar, Tilden P. Meyers, David M. Plummer, Eliceo Ruiz Guzman, Elizabeth N. Smith, Matthias Sühring, David D. Turner, Zhien Wang, Loren D. White, and James M. Wilczak

Abstract

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models.

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