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Scott C. Sheridan, John F. Griffiths, and Richard E. Orville


This study examines the relationship between cloud-to-ground (CG) lightning and surface precipitation using observations from six regions (each on the order of 10000 km2), April through October (1989–93), in the south-central United States. The relationship is evaluated using two different methods. First, regression equations are fit to the data, initially for only the CG lightning flash density and precipitation, and then with additional atmospheric and lightning parameters. Second, days are categorized according to differences in the precipitation-to-CG lightning ratio; the same additional parameters are then examined for differences occurring within each category.

Results show that the relationship between CG lightning and surface precipitation is highly variable; r2 coefficients range from 0.121 in Baton Rouge to 0.601 in Dallas. A measure of the positive CG lightning flash density is the best addition to the model, statistically significant in all regions. When days are categorized, the percentage of lightning that is positive shows the most significant differences between categories, ranging from <4% on days with a “low” precipitation-to-CG lightning ratio, to 12%–36% on days with a “high” ratio. Other lightning parameters give less significant results; however, three atmospheric parameters (CAPE, lifted index, and Showalter index) do show a significant trend suggesting that there is much less instability in the atmosphere on “high” ratio days than on “low” ratio days.

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Jonathan L. Case, John Manobianco, Timothy D. Oram, Tim Garner, Peter F. Blottman, and Scott M. Spratt


The Applied Meteorology Unit has configured the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) to support operational short-range weather forecasting over east-central Florida, including the Kennedy Space Center and Cape Canaveral Air Force Station. The ADAS was modified to assimilate nationally and locally available in situ and remotely sensed observational data into a series of high-resolution gridded analyses every 15 min. The goal for running ADAS over east-central Florida is to generate real-time analysis products that may enhance weather nowcasts and short-range (<6 h) forecasts issued by the 45th Weather Squadron (45 WS), the Spaceflight Meteorology Group (SMG), and the National Weather Service (NWS) at Melbourne, Florida (MLB). The locally configured ADAS has the potential to provide added value because it ingests all operationally available data into a single grid analysis at high spatial and temporal resolutions. ADAS-generated grid analyses can provide forecasters with a tool to develop a more comprehensive understanding of evolving fine-scale weather features than could be obtained by individually examining the disparate data sources.

The potential utility of this ADAS configuration to operational forecasters is demonstrated through a postanalysis case study of a thunderstorm outflow boundary that postponed an Atlas space launch mission, and a Florida cool-season squall line event. In the Atlas case study, a thunderstorm outflow boundary generated strong winds that exceeded the Atlas vehicle limits. A diagnosis of this event, using analysis products during the decaying phase of a Florida summer thunderstorm, illustrates the potential benefits that may be provided to forecasters supporting space launch and landing operations, and to NWS MLB meteorologists generating short-range forecast products. The evolution of analyzed cloud fields from the squall line event were used to track the areal coverage and tendencies of cloud ceiling and cloud-top heights that impact the evaluation of space operation weather constraints and NWS aviation products. These cases also illustrate how the analyses can provide guidance for nowcasts and short-range forecasts of Florida warm-season convection and fire-weather parameters. In addition, some of the sensitivities of the ADAS analyses to selected observational data sources are discussed.

Recently, a real-time version of ADAS was implemented at both SMG and the NWS MLB forecast offices. Future plans of this ADAS configuration include incorporating additional observational datasets and designing visualization products for specific forecast tasks. Finally, the ultimate goal is to use these ADAS analyses to initialize a high-resolution numerical weather prediction model run locally at SMG and the NWS MLB, in order to develop a cycling scheme that preserves fine-scale features such as convective outflow boundaries in short-range numerical forecasts.

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Edward J. Walsh, David W. Hancock III, Donald E. Hines, Robert N. Swift, and John F. Scott


The Surface Contour Radar (SCR) is a 36-GHz computer-controlled airborne system, which produces ocean directional wave spectra with much higher angular resolution than pitch-and-roll buoys. SCR observations of the evolution of the fetch-limited directional wave spectrum are presented which indicate the existence of a fully-developed sea state. The JONSWAP wave growth model for wave energy and frequency was in best agreement with the SCR measurements. The model of Donelan et al. correctly predicted the propagation direction of waves in the asymmetrical fetch situation nearshore. The Donelan et al. parameterization is generalized to permit other growth algorithms to predict the correct direction of propagation in asymmetrical fetch situations.

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Robert F. Adler, George J. Huffman, Alfred Chang, Ralph Ferraro, Ping-Ping Xie, John Janowiak, Bruno Rudolf, Udo Schneider, Scott Curtis, David Bolvin, Arnold Gruber, Joel Susskind, Philip Arkin, and Eric Nelkin


The Global Precipitation Climatology Project (GPCP) Version-2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5° latitude × 2.5° longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit satellite microwave data, geosynchronous-orbit satellite infrared data, and surface rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The dataset is extended back into the premicrowave era (before mid-1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the rain gauge analysis. The dataset archive also contains the individual input fields, a combined satellite estimate, and error estimates for each field. This monthly analysis is the foundation for the GPCP suite of products, including those at finer temporal resolution. The 23-yr GPCP climatology is characterized, along with time and space variations of precipitation.

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Jason C. Knievel, Yubao Liu, Thomas M. Hopson, Justin S. Shaw, Scott F. Halvorson, Henry H. Fisher, Gregory Roux, Rong-Shyang Sheu, Linlin Pan, Wanli Wu, Joshua P. Hacker, Erik Vernon, Frank W. Gallagher III, and John C. Pace


Since 2007, meteorologists of the U.S. Army Test and Evaluation Command (ATEC) at Dugway Proving Ground (DPG), Utah, have relied on a mesoscale ensemble prediction system (EPS) known as the Ensemble Four-Dimensional Weather System (E-4DWX). This article describes E-4DWX and the innovative way in which it is calibrated, how it performs, why it was developed, and how meteorologists at DPG use it. E-4DWX has 30 operational members, each configured to produce forecasts of 48 h every 6 h on a 272-processor high performance computer (HPC) at DPG. The ensemble’s members differ from one another in initial-, lateral-, and lower-boundary conditions; in methods of data assimilation; and in physical parameterizations. The predictive core of all members is the Advanced Research core of the Weather Research and Forecasting (WRF) Model. Numerical predictions of the most useful near-surface variables are dynamically calibrated through algorithms that combine logistic regression and quantile regression, generating statistically realistic probabilistic depictions of the atmosphere’s future state at DPG’s observing sites. Army meteorologists view E-4DWX’s output via customized figures posted to a restricted website. Some of these figures summarize collective results—for example, through means, standard deviations, or fractions of the ensemble exceeding thresholds. Other figures show each forecast, individually or grouped—for example, through spaghetti diagrams and time series. This article presents examples of each type of figure.

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Scott F. Blair, Jennifer M. Laflin, Dennis E. Cavanaugh, Kristopher J. Sanders, Scott R. Currens, Justin I. Pullin, Dylan T. Cooper, Derek R. Deroche, Jared W. Leighton, Robert V. Fritchie, Mike J. Mezeul II, Barrett T. Goudeau, Stephen J. Kreller, John J. Bosco, Charley M. Kelly, and Holly M. Mallinson


A field research campaign, the Hail Spatial and Temporal Observing Network Effort (HailSTONE), was designed to obtain physical high-resolution hail measurements at the ground associated with convective storms to help address several operational challenges that remain unsatisfied through public storm reports. Field phases occurred over a 5-yr period, yielding hail measurements from 73 severe thunderstorms [hail diameter ≥ 1.00 in. (2.54 cm)]. These data provide unprecedented insight into the hailfall character of each storm and afford a baseline to explore the representativeness of the climatological hail database and hail forecasts in NWS warning products. Based upon the full analysis of HailSTONE observations, hail sizes recorded in Storm Data as well as hail size forecasts in NWS warnings frequently underestimated the maximum diameter hailfall occurring at the surface. NWS hail forecasts were generally conservative in size and at least partially calibrated to incoming hail reports. Storm mode played a notable role in determining the potential range of maximum hail size during the life span of each storm. Supercells overwhelmingly produced the largest hail diameters, with smaller maximum hail sizes observed as convection became progressively less organized. Warning forecasters may employ a storm-mode hail size forecast philosophy, in conjunction with other radar-based hail detection techniques, to better anticipate and forecast hail sizes during convective warning episodes.

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Russell S. Vose, Scott Applequist, Mark A. Bourassa, Sara C. Pryor, Rebecca J. Barthelmie, Brian Blanton, Peter D. Bromirski, Harold E. Brooks, Arthur T. DeGaetano, Randall M. Dole, David R. Easterling, Robert E. Jensen, Thomas R. Karl, Richard W. Katz, Katherine Klink, Michael C. Kruk, Kenneth E. Kunkel, Michael C. MacCracken, Thomas C. Peterson, Karsten Shein, Bridget R. Thomas, John E. Walsh, Xiaolan L. Wang, Michael F. Wehner, Donald J. Wuebbles, and Robert S. Young

This scientific assessment examines changes in three climate extremes—extratropical storms, winds, and waves—with an emphasis on U.S. coastal regions during the cold season. There is moderate evidence of an increase in both extratropical storm frequency and intensity during the cold season in the Northern Hemisphere since 1950, with suggestive evidence of geographic shifts resulting in slight upward trends in offshore/coastal regions. There is also suggestive evidence of an increase in extreme winds (at least annually) over parts of the ocean since the early to mid-1980s, but the evidence over the U.S. land surface is inconclusive. Finally, there is moderate evidence of an increase in extreme waves in winter along the Pacific coast since the 1950s, but along other U.S. shorelines any tendencies are of modest magnitude compared with historical variability. The data for extratropical cyclones are considered to be of relatively high quality for trend detection, whereas the data for extreme winds and waves are judged to be of intermediate quality. In terms of physical causes leading to multidecadal changes, the level of understanding for both extratropical storms and extreme winds is considered to be relatively low, while that for extreme waves is judged to be intermediate. Since the ability to measure these changes with some confidence is relatively recent, understanding is expected to improve in the future for a variety of reasons, including increased periods of record and the development of “climate reanalysis” projects.

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Maurice Blackmon, Byron Boville, Frank Bryan, Robert Dickinson, Peter Gent, Jeffrey Kiehl, Richard Moritz, David Randall, Jagadish Shukla, Susan Solomon, Gordon Bonan, Scott Doney, Inez Fung, James Hack, Elizabeth Hunke, James Hurrell, John Kutzbach, Jerry Meehl, Bette Otto-Bliesner, R. Saravanan, Edwin K. Schneider, Lisa Sloan, Michael Spall, Karl Taylor, Joseph Tribbia, and Warren Washington

The Community Climate System Model (CCSM) has been created to represent the principal components of the climate system and their interactions. Development and applications of the model are carried out by the U.S. climate research community, thus taking advantage of both wide intellectual participation and computing capabilities beyond those available to most individual U.S. institutions. This article outlines the history of the CCSM, its current capabilities, and plans for its future development and applications, with the goal of providing a summary useful to present and future users.

The initial version of the CCSM included atmosphere and ocean general circulation models, a land surface model that was grafted onto the atmosphere model, a sea-ice model, and a “flux coupler” that facilitates information exchanges among the component models with their differing grids. This version of the model produced a successful 300-yr simulation of the current climate without artificial flux adjustments. The model was then used to perform a coupled simulation in which the atmospheric CO2 concentration increased by 1 % per year.

In this version of the coupled model, the ocean salinity and deep-ocean temperature slowly drifted away from observed values. A subsequent correction to the roughness length used for sea ice significantly reduced these errors. An updated version of the CCSM was used to perform three simulations of the twentieth century's climate, and several projections of the climate of the twenty-first century.

The CCSM's simulation of the tropical ocean circulation has been significantly improved by reducing the background vertical diffusivity and incorporating an anisotropic horizontal viscosity tensor. The meridional resolution of the ocean model was also refined near the equator. These changes have resulted in a greatly improved simulation of both the Pacific equatorial undercurrent and the surface countercurrents. The interannual variability of the sea surface temperature in the central and eastern tropical Pacific is also more realistic in simulations with the updated model.

Scientific challenges to be addressed with future versions of the CCSM include realistic simulation of the whole atmosphere, including the middle and upper atmosphere, as well as the troposphere; simulation of changes in the chemical composition of the atmosphere through the incorporation of an integrated chemistry model; inclusion of global, prognostic biogeochemical components for land, ocean, and atmosphere; simulations of past climates, including times of extensive continental glaciation as well as times with little or no ice; studies of natural climate variability on seasonal-to-centennial timescales; and investigations of anthropogenic climate change. In order to make such studies possible, work is under way to improve all components of the model. Plans call for a new version of the CCSM to be released in 2002. Planned studies with the CCSM will require much more computer power than is currently available.

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J. K. Andersen, Liss M. Andreassen, Emily H. Baker, Thomas J. Ballinger, Logan T. Berner, Germar H. Bernhard, Uma S. Bhatt, Jarle W. Bjerke, Jason E. Box, L. Britt, R. Brown, David Burgess, John Cappelen, Hanne H. Christiansen, B. Decharme, C. Derksen, D. S. Drozdov, Howard E. Epstein, L. M. Farquharson, Sinead L. Farrell, Robert S. Fausto, Xavier Fettweis, Vitali E. Fioletov, Bruce C. Forbes, Gerald V. Frost, Sebastian Gerland, Scott J. Goetz, Jens-Uwe Grooß, Edward Hanna, Inger Hanssen-Bauer, Stefan Hendricks, Iolanda Ialongo, K. Isaksen, Bjørn Johnsen, L. Kaleschke, A. L. Kholodov, Seong-Joong Kim, Jack Kohler, Zachary Labe, Carol Ladd, Kaisa Lakkala, Mark J. Lara, Bryant Loomis, Bartłomiej Luks, K. Luojus, Matthew J. Macander, G. V. Malkova, Kenneth D. Mankoff, Gloria L. Manney, J. M. Marsh, Walt Meier, Twila A. Moon, Thomas Mote, L. Mudryk, F. J. Mueter, Rolf Müller, K. E. Nyland, Shad O’Neel, James E. Overland, Don Perovich, Gareth K. Phoenix, Martha K. Raynolds, C. H. Reijmer, Robert Ricker, Vladimir E. Romanovsky, E. A. G. Schuur, Martin Sharp, Nikolai I. Shiklomanov, C. J. P. P. Smeets, Sharon L. Smith, Dimitri A. Streletskiy, Marco Tedesco, Richard L. Thoman, J. T. Thorson, X. Tian-Kunze, Mary-Louise Timmermans, Hans Tømmervik, Mark Tschudi, Dirk van As, R. S. W. van de Wal, Donald A. Walker, John E. Walsh, Muyin Wang, Melinda Webster, Øyvind Winton, Gabriel J. Wolken, K. Wood, Bert Wouters, and S. Zador
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