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James E. Hansen and Dennis M. Driscoll

Abstract

A stochastic model for hourly temperatures for Big Spring, Tex., has been developed. The governing parameters were deduced from an 11-year developmental sample, and give hourly temperatures as a function of harmonics representing annual and diurnal variations, and a first-order Markov chain process. The latter incorporates adjustments for the seasonal variation of the serial (hour-to-hour) correlation coefficient, and for the seasonal and diurnal variations of the variability and non-normality of frequency distributions of hourly temperatures. Each of the characteristics is given explicitly as a function of hour of the year.

Two 10-year samples were generated and compared to the developmental sample. Criteria were established to determine how well the model duplicates nature. The variability of mean monthly temperature and the frequency of occurrence of low diurnal ranges are underestimated. However, the model gives good estimates of the duration of temperatures below 32°F, and above 65° and 90°F, and of the frequency distribution of monthly 3, 6, 12, 24, 72 and 144 h maximum and minimum temperatures.

The general applicability of the model and its utility are discussed. The model could be used to determine the effects of climatic trends, e.g., a gradual cooling, on the average length of the growing season, the mean number of heating/cooling degree days, and other temperature-related parameters.

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James B. Pollack, David Rind, Andrew Lacis, James E. Hansen, Makiko Sato, and Reto Ruedy

Abstract

The authors have used the Goddard Institute for Space Studies Climate Model II to simulate the response of the climate system to a spatially and temporally constant forcing by volcanic aerosols having an optical depth of 0.15. The climatic changes produced by long-term volcanic aerosol forcing are obtained by differencing this simulation and one made for the present climate with no volcanic aerosol forcing. These climatic changes are compared with those obtained with the same climate model when the C02 content of the atmosphere was doubled (2×C02) and when the boundary conditions associated with the peak of the last ice age were used (18 K). In all three cases, the absolute magnitude of the change in the globally averaged air temperature at the surface is approximately the same, ∼5 K.

The simulations imply that a significant cooling of the troposphere and surface can occur at times of closely spaced, multiple, sulfur-rich volcanic explosions that span time scales of decades to centuries, such as occurred at the end of the nineteenth and beginning of the twentieth centuries. The steady-state climate response to volcanic forcing includes a large expansion of sea ice, especially in the Southern Hemisphere; a resultant large increase in surface and planetary albedo at high latitudes; and sizable changes in the annually and zonally averaged air temperature, ΔT; ΔT at the surface (ΔTs) does not sharply increase with increasing latitude, while ΔT in the lower stratosphere is positive at low latitudes and negative at high latitudes.

In certain ways, the climate response to the three different forcings is similar. Direct radiative forcing accounts for 30% and 25% of the total ΔTs in the volcano and 2×C02 runs, respectively. Changes in atmospheric water vapor act as the most important feedback, and are positive in all three cases. Albedo feedback is a significant, positive feedback at high latitudes in all three simulations, although the land ice feedback is prominent only in the 18 K run.

In other ways, the climate response to the three forcings is quite different. The latitudinal profiles of ΔTs for the three runs differ considerably, reflecting significant variations in the latitudinal profiles of the primary radiative forcing. Partially as a result of this difference in the ΔTs profiles, changes in eddy kinetic energy, beat transport by atmospheric eddies, and total atmospheric heat transport are quite different in the three cases. In fact, atmospheric beat transport acts as a positive feedback at high latitudes in the volcano run and as a negative feedback in the other two runs. These results raise questions about the ease with which atmospheric heat transport can be parameterized in a simple way in energy balance climate models.

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Jean-Christophe Golaz, Vincent E. Larson, James A. Hansen, David P. Schanen, and Brian M. Griffin

Abstract

Every cloud parameterization contains structural model errors. The source of these errors is difficult to pinpoint because cloud parameterizations contain nonlinearities and feedbacks. To elucidate these model inadequacies, this paper uses a general-purpose ensemble parameter estimation technique. In principle, the technique is applicable to any parameterization that contains a number of adjustable coefficients. It optimizes or calibrates parameter values by attempting to match predicted fields to reference datasets. Rather than striving to find the single best set of parameter values, the output is instead an ensemble of parameter sets. This ensemble provides a wealth of information. In particular, it can help uncover model deficiencies and structural errors that might not otherwise be easily revealed. The calibration technique is applied to an existing single-column model (SCM) that parameterizes boundary layer clouds. The SCM is a higher-order turbulence closure model. It is closed using a multivariate probability density function (PDF) that represents subgrid-scale variability. Reference datasets are provided by large-eddy simulations (LES) of a variety of cloudy boundary layers. The calibration technique locates some model errors in the SCM. As a result, empirical modifications are suggested. These modifications are evaluated with independent datasets and found to lead to an overall improvement in the SCM’s performance.

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Michael I. Mishchenko, Brian Cairns, Greg Kopp, Carl F. Schueler, Bryan A. Fafaul, James E. Hansen, Ronald J. Hooker, Tom Itchkawich, Hal B. Maring, and Larry D. Travis

The NASA Glory mission is intended to facilitate and improve upon long-term monitoring of two key forcings influencing global climate. One of the mission's principal objectives is to determine the global distribution of detailed aerosol and cloud properties with unprecedented accuracy, thereby facilitating the quantification of the aerosol direct and indirect radiative forcings. The other is to continue the 28-yr record of satellite-based measurements of total solar irradiance from which the effect of solar variability on the Earth's climate is quantified. These objectives will be met by flying two state-of-the-art science instruments on an Earth-orbiting platform. Based on a proven technique demonstrated with an aircraft-based prototype, the Aerosol Polarimetry Sensor (APS) will collect accurate multiangle photopolarimetric measurements of the Earth along the satellite ground track within a wide spectral range extending from the visible to the shortwave infrared. The Total Irradiance Monitor (TIM) is an improved version of an instrument currently flying on the Solar Radiation and Climate Experiment (SORCE) and will provide accurate and precise measurements of spectrally integrated sunlight illuminating the Earth. Because Glory is expected to fly as part of the A-Train constellation of Earth-orbiting spacecraft, the APS data will also be used to improve retrievals of aerosol climate forcing parameters and global aerosol assessments with other A-Train instruments. In this paper, we detail the scientific rationale and objectives of the Glory mission, explain how these scientific objectives dictate the specific measurement strategy, describe how the measurement strategy will be implemented by the APS and TIM, and briefly outline the overall structure of the mission. It is expected that the Glory results will be used extensively by members of the climate, solar, atmospheric, oceanic, and environmental research communities as well as in education and outreach activities.

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Paul A. Hirschberg, Elliot Abrams, Andrea Bleistein, William Bua, Luca Delle Monache, Thomas W. Dulong, John E. Gaynor, Bob Glahn, Thomas M. Hamill, James A. Hansen, Douglas C. Hilderbrand, Ross N. Hoffman, Betty Hearn Morrow, Brenda Philips, John Sokich, and Neil Stuart

The American Meteorological Society (AMS) Weather and Climate Enterprise Strategic Implementation Plan for Generating and Communicating Forecast Uncertainty (the Plan) is summarized. The Plan (available on the AMS website at www.ametsoc.org/boardpges/cwce/docs/BEC/ACUF/2011-02-20-ACUF-Final-Report.pdf) is based on and intended to provide a foundation for implementing recent recommendations regarding forecast uncertainty by the National Research Council (NRC), AMS, and World Meteorological Organization. It defines a vision, strategic goals, roles and respon- sibilities, and an implementation road map to guide the weather and climate enterprise (the Enterprise) toward routinely providing the nation with comprehensive, skillful, reliable, and useful information about the uncertainty of weather, water, and climate (hydrometeorological) forecasts. Examples are provided describing how hydrometeorological forecast uncertainty information can improve decisions and outcomes in various socioeconomic areas. The implementation road map defines objectives and tasks that the four sectors comprising the Enterprise (i.e., government, industry, academia, and nongovernmental organizations) should work on in partnership to meet four key, interrelated strategic goals: 1) understand social and physical science aspects of forecast uncertainty; 2) communicate forecast uncertainty information effectively and collaborate with users to assist them in their decision making; 3) generate forecast uncertainty data, products, services, and information; and 4) enable research, development, and operations with necessary information technology and other infrastructure. The Plan endorses the NRC recommendation that the National Oceanic and Atmospheric Administration and, in particular, the National Weather Service, should take the lead in motivating and organizing Enterprise resources and expertise in order to reach the Plan's vision and goals and shift the nation successfully toward a greater understanding and use of forecast uncertainty in decision making.

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Gavin A. Schmidt, Reto Ruedy, James E. Hansen, Igor Aleinov, Nadine Bell, Mike Bauer, Susanne Bauer, Brian Cairns, Vittorio Canuto, Ye Cheng, Anthony Del Genio, Greg Faluvegi, Andrew D. Friend, Tim M. Hall, Yongyun Hu, Max Kelley, Nancy Y. Kiang, Dorothy Koch, Andy A. Lacis, Jean Lerner, Ken K. Lo, Ron L. Miller, Larissa Nazarenko, Valdar Oinas, Jan Perlwitz, Judith Perlwitz, David Rind, Anastasia Romanou, Gary L. Russell, Makiko Sato, Drew T. Shindell, Peter H. Stone, Shan Sun, Nick Tausnev, Duane Thresher, and Mao-Sung Yao

Abstract

A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure. Data–model comparisons continue, however, to highlight persistent problems in the marine stratocumulus regions.

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