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Peter H. Hildebrand, Wen-Chau Lee, Craig A. Walther, Charles Frush, Mitchell Randall, Eric Loew, Richard Neitzel, Richard Parsons, Jacques Testud, François Baudin, and Alain LeCornec

The ELDORA/ASTRAIA (Electra Doppler Radar/Analyese Stereoscopic par Impulsions Aeroporte) airborne Doppler weather radar was recently placed in service by the National Center for Atmospheric Research and the Centre d'étude des Environnements Terrestre et Planetaires in France. After a multiyear development effort, the radar saw its first field tests in the TOGA COARE (Tropical Oceans–Global Atmosphere Coupled Ocean–Atmosphere Response Experiment) field program during January and February 1993. The ELDORA/ASTRAIA radar (herein referred to as ELDORA) is designed to provide high-resolution measurements of the air motion and rainfall characteristics of very large storms, storms that are frequently too large or too remote to be adequately observed by ground-based radars. This paper discusses the measurement requirements and the design goals of the radar and concludes with an evaluation of the performance of the system using data from TOGA COARE.

The performance evaluation includes data from two cases. First, observations of a mesoscale convective system on 9 February 1993 are used to compare the data quality of the ELDORA radar with the National Oceanic and Atmospheric Administration P-3 airborne Doppler radars. The large-scale storm structure and airflow from ELDORA are seen to compare quite well with analyses using data from the P-3 radars. The major differences observed between the ELDORA and P-3 radar analyses were due to the higher resolution of the ELDORA data and due to the different domains observed by the individual radars, a result of the selection of flight track past the storm for each aircraft. In a second example, the high-resolution capabilities of ELDORA are evaluated using observations of a shear-parallel mesoscale convective system (MCS) that occurred on 18 February 1993. This MCS line was characterized by shear-parallel clusters of small convective cells, clusters that were moving quickly with the low-level winds. High-resolution analysis of these data provided a clear picture of the small scale of the storm vertical velocity structure associated with individual convective cells. The peak vertical velocities measured in the high-resolution analysis were also increased above low-resolution analysis values, in many areas by 50%–100%. This case exemplifies the need for high-resolution measurement and analysis of convective transport, even if the goal is to measure and parameterize the large-scale effects of storms. The paper concludes with a discussion of completion of the remaining ELDORA design goals and planned near-term upgrades to the system. These upgrades include an implementation of dual–pulse repetition frequency and development of real-time, in-flight dual-Doppler analysis capability.

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David Randall, Steven Krueger, Christopher Bretherton, Judith Curry, Peter Duynkerke, Mitchell Moncrieff, Brian Ryan, David Starr, Martin Miller, William Rossow, George Tselioudis, and Bruce Wielicki

The Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) was organized to promote the development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on the climate applications. GCSS uses models to analyze and understand observations of the behavior of cloud systems. Cloud-system-resolving models (CSRMs) have sufficient spatial and temporal resolution to represent individual cloud elements, but cover a wide enough range of time and space scales to permit statistical analysis of simulated cloud systems. Results from CSRMs are compared with detailed observations, representing specific cases based on field experiments, and also with statistical composites obtained from satellite and meteorological analyses. Single-column models (SCMs) are the column physics components of atmospheric general circulation models (GCMs). SCMs are used to test cloud parameterizations in an uncoupled mode, by comparison with field data and statistical composites. In the original GCSS strategy, data are collected in various field programs and provided to the CSRM community, which first uses the data to “certify” the CSRMs as reliable tools for the simulation of particular cloud regimes, and then uses the CSRMs to develop parameterizations, which are provided to the GCM community. Results of a rethinking of the scientific strategy of GCSS, which takes into account the practical issues that arise in confronting models with data, are reported on herein. The main elements of the proposed new strategy are a more active role for the large-scale modeling community, an explicit recognition of the importance of data integration, and an increasing use of observed cloud-scale statistics for model evaluations.

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Melvyn Shapiro, Jagadish Shukla, Gilbert Brunet, Carlos Nobre, Michel Béland, Randall Dole, Kevin Trenberth, Richard Anthes, Ghassem Asrar, Leonard Barrie, Philippe Bougeault, Guy Brasseur, David Burridge, Antonio Busalacchi, Jim Caughey, Deliang Chen, John Church, Takeshi Enomoto, Brian Hoskins, Øystein Hov, Arlene Laing, Hervé Le Treut, Jochem Marotzke, Gordon McBean, Gerald Meehl, Martin Miller, Brian Mills, John Mitchell, Mitchell Moncrieff, Tetsuo Nakazawa, Haraldur Olafsson, Tim Palmer, David Parsons, David Rogers, Adrian Simmons, Alberto Troccoli, Zoltan Toth, Louis Uccellini, Christopher Velden, and John M. Wallace

The necessity and benefits for establishing the international Earth-system Prediction Initiative (EPI) are discussed by scientists associated with the World Meteorological Organization (WMO) World Weather Research Programme (WWRP), World Climate Research Programme (WCRP), International Geosphere–Biosphere Programme (IGBP), Global Climate Observing System (GCOS), and natural-hazards and socioeconomic communities. The proposed initiative will provide research and services to accelerate advances in weather, climate, and Earth system prediction and the use of this information by global societies. It will build upon the WMO, the Group on Earth Observations (GEO), the Global Earth Observation System of Systems (GEOSS) and the International Council for Science (ICSU) to coordinate the effort across the weather, climate, Earth system, natural-hazards, and socioeconomic disciplines. It will require (i) advanced high-performance computing facilities, supporting a worldwide network of research and operational modeling centers, and early warning systems; (ii) science, technology, and education projects to enhance knowledge, awareness, and utilization of weather, climate, environmental, and socioeconomic information; (iii) investments in maintaining existing and developing new observational capabilities; and (iv) infrastructure to transition achievements into operational products and services.

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