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David A. Randall

Global atmospheric models are proliferating, in part because of the widespread availability of powerful computers. There are about two dozen global modeling groups at work in the United States today. These groups are put into four categories, considering both laboratories and universities and development and applications. Community models are a special subgroup and in principle are both developed and applied by the community. Most U.S. global modeling groups are focusing on applications rather than on development. This is especially true in the university community, although over the years university groups have made important contributions in the model-development arena. A key role of university groups is to train new model developers at a rate matched to the community's demand for such scientists. A simple but functional conceptual organization of the U.S. global modeling community is suggested.

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David A. Randall and Bruce A. Wielicki

Measurements in atmospheric science sometimes determine universal functions, but more commonly data are collected in the form of case studies. Models are conceptual constructs that can be used to make predictions about the outcomes of measurements. Hypotheses can be expressed in terms of model results, and the best use of measurements is to falsify such hypotheses. Tuning of models should be avoided because it interferes with falsification. Comparison of models with data would be easier if the minimum data requirements for testing some types of models could be standardized.

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Stephen K. Cox, David S. McDougal, David A. Randall, and Robert A. Schiffer
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Bruce A. Wielicki, Robert D. Cess, Michael D. King, David A. Randall, and Edwin F. Harrison

The role of clouds in modifying the earth's radiation balance is well recognized as a key uncertainty in predicting any potential future climate change. This statement is true whether the climate change of interest is caused by changing emissions of greenhouse gases and sulfates, deforestation, ozone depletion, volcanic eruptions, or changes in the solar constant. This paper presents an overview of the role of the National Aeronautics and Space Administration's Earth Observing System (EOS) satellite data in understanding the role of clouds in the global climate system. The paper gives a brief summary of the cloud/radiation problem, and discusses the critical observations needed to support further investigations. The planned EOS data products are summarized, including the critical advances over current satellite cloud and radiation budget data. Key advances include simultaneous observation of radiation budget and cloud properties, additional information on cloud particle size and phase, improved detection of thin clouds and multilayer cloud systems, greatly reduced ambiguity in partially cloud-filled satellite fields of view, improved calibration and stability of satellite-observed radiances, and improved estimates of radiative fluxes at the top of the atmosphere, at the surface, and at levels within the atmosphere. Outstanding sampling and remote sensing issues that affect data quality are also discussed. Finally, the EOS data are placed in the context of other satellite observations as well as the critical surface, field experiment, and laboratory data needed to address the role of clouds in the climate system. It is concluded that the EOS data are a necessary but insufficient condition for solution of the scientific cloud/radiation issues. A balanced approach of satellite, field, and laboratory data will be required. These combined data can span the necessary spatial scales of global, regional, cloud cell, and cloud particle physics (i.e., from 108 to 10−7 m).

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Bruce A. Albrecht, David A. Randall, and Stephen Nicholls

During June and July 1987, a major collaborative experiment (part of The First ISCCP [International Satellite Cloud Climatology Project] Regional Experiment (FIRE) took place off the coast of California to study the extensive fields of stratocumulus clouds that are a persistent feature of subtropical marine boundary layers. For the first time, measurements were made on both the regional scale and on the detailed local scale to permit the widest possible interpretation of the mean, turbulent, microphysical, radiative, and chemical characteristics of stratocumulus, together with the interactions among these quantities that are believed to be important in controlling the structure and evolution of these clouds. Multiple aircraft were used to make detailed, in situ measurements and to provide a bridge between the microscale and features seen from satellites. Ground-based remote-sensing systems on San Nicolas Island captured the time evolution of the boundary-layer structure during the three-week duration of the experiment, and probes flown from tethered balloons were used to measure turbulence at several levels simultaneously, and to collect cloud-microphysical data and cloud-radiative data.

Excellent cloud conditions were present throughout the experiment, although the data show that even this relatively simple cloud system displays fairly complicated structures on a variety of scales. Overall, the operational goals of the experiment were satisfied and preliminary results look very encouraging. The data collected should provide the observational base needed to increase our understanding of how stratocumulus clouds are generated, maintained, and dissipated, and thus provide for better parameterizations in large-scale numerical models and improved methods for retrieving cloud properties by satellite.

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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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Jack Fishman, Kevin W. Bowman, John P. Burrows, Andreas Richter, Kelly V. Chance, David P. Edwards, Randall V. Martin, Gary A. Morris, R. Bradley Pierce, Jerald R. Ziemke, Jassim A. Al-Saadi, John K. Creilson, Todd K. Schaack, and Anne M. Thompson

We review the progress of tropospheric trace gas observations and address the need for additional measurement capabilities as recommended by the National Research Council. Tropospheric measurements show pollution in the Northern Hemisphere as a result of fossil fuel burning and a strong seasonal dependence with the largest amounts of carbon monoxide and nitrogen dioxide in the winter and spring. In the summer, when photochemistry is most intense, photochemically generated ozone is found in large concentrations over and downwind from where anthropogenic sources are largest, such as the eastern United States and eastern China. In the tropics and the subtropics, where photon flux is strong throughout the year, trace gas concentrations are driven by the abundance of the emissions. The largest single tropical source of pollution is biomass burning, as can be seen readily in carbon monoxide measurements, but lightning and biogenic trace gases may also contribute to trace gas variability. Although substantive progress has been achieved in seasonal and global mapping of a few tropospheric trace gases, satellite trace gas observations with considerably better temporal and spatial resolution are essential to forecasting air quality at the spatial and temporal scales required by policy makers. The concurrent use of atmospheric composition measurements for both scientific and operational purposes is a new paradigm for the atmospheric chemistry community. The examples presented illustrate both the promise and challenge of merging satellite information with in situ observations in state-of-the-art data assimilation models.

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Thomas C. Peterson, Richard R. Heim Jr., Robert Hirsch, Dale P. Kaiser, Harold Brooks, Noah S. Diffenbaugh, Randall M. Dole, Jason P. Giovannettone, Kristen Guirguis, Thomas R. Karl, Richard W. Katz, Kenneth Kunkel, Dennis Lettenmaier, Gregory J. McCabe, Christopher J. Paciorek, Karen R. Ryberg, Siegfried Schubert, Viviane B. S. Silva, Brooke C. Stewart, Aldo V. Vecchia, Gabriele Villarini, Russell S. Vose, John Walsh, Michael Wehner, David Wolock, Klaus Wolter, Connie A. Woodhouse, and Donald Wuebbles

Weather and climate extremes have been varying and changing on many different time scales. In recent decades, heat waves have generally become more frequent across the United States, while cold waves have been decreasing. While this is in keeping with expectations in a warming climate, it turns out that decadal variations in the number of U.S. heat and cold waves do not correlate well with the observed U.S. warming during the last century. Annual peak flow data reveal that river flooding trends on the century scale do not show uniform changes across the country. While flood magnitudes in the Southwest have been decreasing, flood magnitudes in the Northeast and north-central United States have been increasing. Confounding the analysis of trends in river flooding is multiyear and even multidecadal variability likely caused by both large-scale atmospheric circulation changes and basin-scale “memory” in the form of soil moisture. Droughts also have long-term trends as well as multiyear and decadal variability. Instrumental data indicate that the Dust Bowl of the 1930s and the drought in the 1950s were the most significant twentieth-century droughts in the United States, while tree ring data indicate that the megadroughts over the twelfth century exceeded anything in the twentieth century in both spatial extent and duration. The state of knowledge of the factors that cause heat waves, cold waves, floods, and drought to change is fairly good with heat waves being the best understood.

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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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Randall M. Dole, J. Ryan Spackman, Matthew Newman, Gilbert P. Compo, Catherine A. Smith, Leslie M. Hartten, Joseph J. Barsugli, Robert S. Webb, Martin P. Hoerling, Robert Cifelli, Klaus Wolter, Christopher D. Barnet, Maria Gehne, Ronald Gelaro, George N. Kiladis, Scott Abbott, Elena Akish, John Albers, John M. Brown, Christopher J. Cox, Lisa Darby, Gijs de Boer, Barbara DeLuisi, Juliana Dias, Jason Dunion, Jon Eischeid, Christopher Fairall, Antonia Gambacorta, Brian K. Gorton, Andrew Hoell, Janet Intrieri, Darren Jackson, Paul E. Johnston, Richard Lataitis, Kelly M. Mahoney, Katherine McCaffrey, H. Alex McColl, Michael J. Mueller, Donald Murray, Paul J. Neiman, William Otto, Ola Persson, Xiao-Wei Quan, Imtiaz Rangwala, Andrea J. Ray, David Reynolds, Emily Riley Dellaripa, Karen Rosenlof, Naoko Sakaeda, Prashant D. Sardeshmukh, Laura C. Slivinski, Lesley Smith, Amy Solomon, Dustin Swales, Stefan Tulich, Allen White, Gary Wick, Matthew G. Winterkorn, Daniel E. Wolfe, and Robert Zamora

Abstract

Forecasts by mid-2015 for a strong El Niño during winter 2015/16 presented an exceptional scientific opportunity to accelerate advances in understanding and predictions of an extreme climate event and its impacts while the event was ongoing. Seizing this opportunity, the National Oceanic and Atmospheric Administration (NOAA) initiated an El Niño Rapid Response (ENRR), conducting the first field campaign to obtain intensive atmospheric observations over the tropical Pacific during El Niño.

The overarching ENRR goal was to determine the atmospheric response to El Niño and the implications for predicting extratropical storms and U.S. West Coast rainfall. The field campaign observations extended from the central tropical Pacific to the West Coast, with a primary focus on the initial tropical atmospheric response that links El Niño to its global impacts. NOAA deployed its Gulfstream-IV (G-IV) aircraft to obtain observations around organized tropical convection and poleward convective outflow near the heart of El Niño. Additional tropical Pacific observations were obtained by radiosondes launched from Kiritimati , Kiribati, and the NOAA ship Ronald H. Brown, and in the eastern North Pacific by the National Aeronautics and Space Administration (NASA) Global Hawk unmanned aerial system. These observations were all transmitted in real time for use in operational prediction models. An X-band radar installed in Santa Clara, California, helped characterize precipitation distributions. This suite supported an end-to-end capability extending from tropical Pacific processes to West Coast impacts. The ENRR observations were used during the event in operational predictions. They now provide an unprecedented dataset for further research to improve understanding and predictions of El Niño and its impacts.

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