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This paper tries to identify one of the reasons for the poor land skin temperature simulated by a climate model over Greenland. It first compares ICEsat surface height measurements over Greenland with those used by the model and reveals that the surface height of Greenland prescribed in the National Center for Atmospheric Research (NCAR) Community Climate System Model/Community Land Model version 3 (CCSM/CLM3) differs greatly from the satellite measurements from National Aeronautics and Space Administration (NASA) ICEsat at edges and central glacier regions. This deficiency, in part, leads to underestimated skin temperatures at coastal regions-the areas where significant ice sheet melt is observed. Furthermore, sensitivity studies reveal that surface skin temperature simulations of Greenland would be significantly improved if the more accurate surface height is used. The problem of the height used in current global climate model is mainly due to the fact that the model has to use coarse grid size, and within one grid, land surface height has high heterogeneity. How to assign a proper surface height for each model grid and meanwhile adequately present the high heterogeneity of land surface is a great challenge in current model development. [ABSTRACT FROM AUTHOR]

In the Atmospheric Model Intercomparison Project (AMIP) simulations the sea surface temperatures (SSTs) are specified and the oceanic evolution consistent with air–sea interaction is not included. This omission could lead to errors in the atmospheric response to SSTs. At the same time, the AMIP experimental setup is well suited for investigating many aspects of climate variability (e.g., the attribution of the interannual atmospheric variability) and continues to be extensively used. As coupled El Niño–Southern Oscillation (ENSO) SST variability is a dominant factor in determining the predictable component of the observed interannual atmospheric variability, the difference in the atmospheric response to ENSO SSTs between AMIP and coupled simulations is investigated. The results indicate that the seasonal atmospheric response to ENSO between coupled and uncoupled integrations is similar, and the inclusion of oceanic evolution consistent with air–sea interaction does not play a dominant role. The analysis presented in this paper is one step toward assessing differences in atmospheric response to SSTs in coupled and uncoupled simulations, and is required to correctly interpret the results of AMIP simulations. [ABSTRACT FROM AUTHOR]

This paper describes important characteristics of an uncoupled high-resolution land data assimilation system (HRLDAS) and presents a systematic evaluation of 18-month-long HRLDAS numerical experiments, conducted in two nested domains (with 12- and 4-km grid spacing) for the period from 1 January 2001 to 30 June 2002, in the context of the International H2O Project (IHOP_2002). HRLDAS was developed at the National Center for Atmospheric Research (NCAR) to initialize land-state variables of the coupled Weather Research and Forecasting (WRF)–land surface model (LSM) for high-resolution applications. Both uncoupled HRDLAS and coupled WRF are executed on the same grid, sharing the same LSM, land use, soil texture, terrain height, time-varying vegetation fields, and LSM parameters to ensure the same soil moisture climatological description between the two modeling systems so that HRLDAS soil state variables can be used to initialize WRF–LSM without conversion and interpolation. If HRLDAS is initialized with soil conditions previously spun up from other models, it requires roughly 8–10 months for HRLDAS to reach quasi equilibrium and is highly dependent on soil texture. However, the HRLDAS surface heat fluxes can reach quasi-equilibrium state within 3 months for most soil texture categories. Atmospheric forcing conditions used to drive HRLDAS were evaluated against Oklahoma Mesonet data, and the response of HRLDAS to typical errors in each atmospheric forcing variable was examined. HRLDAS-simulated finescale (4 km) soil moisture, temperature, and surface heat fluxes agreed well with the Oklahoma Mesonet and IHOP_2002 field data. One case study shows high correlation between HRLDAS evaporation and the low-level water vapor field derived from radar analysis. [ABSTRACT FROM AUTHOR]

Single column models (SCMs) provide an economical framework for developing and diagnosing representations of diabatic processes in weather and climate models. Their economy is achieved at the price of ignoring interactions with the circulation dynamics and with neighboring columns. It has recently been emphasized that this decoupling can lead to spurious error growth in SCM integrations that can totally obscure the error growth due to errors in the column physics that one hopes to isolate through such integrations. This paper suggests one way around this “existential crisis” of single column modeling. The basic idea is to focus on short-term SCM forecast errors, at ranges of 6 h or less, before a grossly unrealistic model state develops and before complex diabatic interactions render a clear diagnosis impossible. To illustrate, a short-term forecast error diagnosis of the NCAR SCM is presented for tropical conditions observed during the Tropical Ocean and Global Atmosphere (TOGA) Coupled Ocean–Atmosphere Response Experiment (COARE). The 21-day observing period is divided into 84 6-h segments for this purpose. The SCM error evolution is shown to be nearly linear over these 6-h segments and, indeed, apart from a vertical mean bias, to be mainly an extrapolation of initial tendencies. The latter are then decomposed into contributions by various components of the column physics, and additional 6-h integrations are performed with each component separately and in combination with others to assess its contribution to the 6-h errors. Initial tendency and 6-h error diagnostics thus complement each other in diagnosing column physics errors by this approach. Although the SCM evolution from one time step to the next is nearly linear, the finite-amplitude adjustments made multiple times within each time step to the temperature and humidity to remove supersaturation and convective instabilities make it necessary to consider nonlinear interactions between the column physics components. One such particularly strong interaction is identified between vertical diffusion and deep convection. The former, though nominally small, is shown to have a profound impact on both the amplitude and timing of the latter, and thence on the small imbalance between the total diabatic heating and adiabatic cooling of ascent in the column. The SCM diagnosis thus suggests that misrepresentation of this interaction, in addition to that of the interacting components themselves, might be a major contributor to the NCAR GCM's tropical simulation errors. [ABSTRACT FROM AUTHOR]

This paper describes the global ocean component of the NCAR Climate System Model. New parameterizations of the effects of mesoscale eddies and of the upper-ocean boundary layer are included. Numerical improvements include a third-order upwind advection scheme and elimination of the artificial North Pole island in the original MOM 1.1 code. Updated forcing fields are used to drive the ocean-alone solution, which is integrated long enough so that it is in equilibrium. The ocean transports and potential temperature and salinity distributions are compared with observations. The solution sensitivity to the freshwater forcing distribution is highlighted, and the sensitivity to resolution is also briefly discussed. [ABSTRACT FROM AUTHOR]

This paper presents the climatology and interannual variation of the East Asian winter monsoon based on the 1979--95 National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis. In addition to documenting the frequency, intensity, and preferred propagation tracks of cold surges and the evolution patterns of related fields, the authors discuss the temporal distribution of the Siberian high and cold surges. Further, the interannual variation of the cold surges and winter monsoon circulation and its relationship with ENSO were examined. There are on average 13 cold surges in each winter season (October--April), of which two are strong cases. The average intensity of cold surges, measured by maximum sea level pressure, is 1053 hPa. The cold surges originate from two source regions: 1) northwest of Lake Baikal, and 2) north of Lake Balkhash. The typical evolution of a cold surge occurs over a period of 5--14 days. Trajectory and correlation analyses indicate that, during this time, high pressure centers propagate southeastward around the edge of the Tibetan Plateau from the mentioned source regions. Some of these high pressure centers then move eastward and diminish over the oceans, while others proceed southward. The signatures of the associated temperature, wind, and pressure fields propagate farther southward and eastward. The affected area encompasses the bulk of the maritime continent. Although the intensity of the Siberian high peaks during December and January, the frequency of cold surges reaches a maximum in November and in March. This result suggests that November through March should be considered as the East Asian winter monsoon season. Two stratifications of cold surges are used to examine the relationship between ENSO and the interannual variation of the winter monsoon. The first one, described as conventional cold surges, indicates that the surge frequency reaches a minimum a year... [ABSTRACT FROM AUTHOR]

The development of the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) will make possible a wealth of new geophysical research opportunities in the areas of atmospheric chemistry, climate forcing, weather system structure and evolution, the carbon and water vapor cycles, and ecosystem processes. In this paper, we present a brief background on the history of the HIAPER project and discuss the modifications made to the basic aircraft [a Gulfstream V (GV) business jet] and the infrastructure systems installed to transform it into an environmental research platform. General aircraft performance capabilities that make the GV uniquely suited for high-altitude, long-range studies of geophysical phenomena are also discussed. The conduct of research with HIAPER will require that suitable instrumentation payloads are available for use on the aircraft, and the processes followed by the National Science Foundation (NSF) and the National Center for Atmospheric Research (NCAR) for the development of an initial platform instrumentation suite to meet critical measurements needs are described. HIAPER's unique configuration and capabilities will make it an effective tool for the conduct of weather and water cycle research, the study of atmospheric chemistry and climate forcing, and the monitoring of biosphere structure and productivity, as we shall discuss. We conclude with an overview of the objectives of the initial HIAPER flight-testing program and the process whereby this new research platform will be made available to members of the scientific community for the support of environmental research. [ABSTRACT FROM AUTHOR]

Present-day Arctic and Antarctic climate of the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3) is presented. The CCM3 simulation is from a prescribed and interannually varying sea surface temperature integration from January 1979 through August 1993. Observations from a variety of sources, including the European Centre for Medium-Range Weather Forecasts analyses, rawinsonde, and surface station data, are used for validation of CCM3's polar climate during this period. Overall, CCM3 can simulate many important polar climatic features and in general is an incremental improvement over CCM2. The 500-hPa polar vortex minima are too deep by 50--100 m and too zonally symmetric. The Arctic sea level pressure maximum is displaced poleward, while the Icelandic region minimum is extended toward Europe, and the Aleutian region minimum is extended toward Asia. The Antarctic circumpolar trough of low sea level pressure is slightly north of the observed position and is 2--3 hPa too low. Antarctic katabatic winds are similar to observations in magnitude and regional variation. The Antarctic surface wind stress is estimated to be 30%--50% too strong in some regions. Polar tropospheric temperatures are 2&deg--4&degC colder than observations, mostly in the summer season. Low-level winter inversions over the Arctic Ocean are only 3&deg--4&degC, rather than the observed 10&degC. In the Antarctic midcontinent they are around 25&deg--30&degC (about 5&deg stronger than observed) and continue to be stronger than observed along the coast. Although water vapor column is uniformly low by 10%--20% compared to analyses in both polar regions, the regional patterns of minima over Greenland and the East Antarctic plateau are well represented. Annual 70&deg to pole CCM3 values are 5.8 kg m[sup-2] for the Arctic and 1.7 kg m[sup-2] for the Antarctic. The regional distribution of precipitation minus evaporation compares reasonably with analyses. (...). [ABSTRACT FROM AUTHOR]

The article reports that the climate change hot spots mapped across the United States. According to climate modeler Gerald Meehl of the National Center for Atmospheric Research (NCAR) in Boulder, Colorado, the latest regional climate highlights regios where climate changes will be bigger than others. Climate modeler Noah Diffenbaugh of Purdue University in West Lafayette, Indiana lay out in the paper, regional climate modeling, which is in press in "Geophysical Research Letters" (GRL). According to the model, the strongest U.S hot spot by far stretches across the Southwest from southern California to west Texas, and intensifies over northern Mexico.

The article focuses on the Legacy Atmospheric Sounding Dataset Project in which data from weather observations and research are captured for archival purposes. Information is provided on the ways in which archival recordings are made, which include 9-track magnetic tapes, microfiche, and print. It is noted that the National Center for U.S. Atmospheric Research (NCAR) maintains an Internet accessible archive.

This study investigates the annual cycle of radiative contributions to global climate feedbacks. A partial radiative perturbation (PRP) technique is used to diagnose monthly radiative perturbations at the top of atmosphere (TOA) due to CO2 forcing; surface temperature response; and water vapor, cloud, lapse rate, and surface albedo feedbacks using NCAR Community Climate System Model, version 3 (CCSM3) output from a Special Report on Emissions Scenarios (SRES) A1B emissions-scenario-forced climate simulation. The seasonal global mean longwave TOA radiative feedback was found to be minimal. However, the global mean shortwave (SW) TOA cloud and surface albedo radiative perturbations exhibit large seasonality. The largest contributions to the negative SW cloud feedback occur during summer in each hemisphere, marking the largest differences with previous results. Results suggest that intermodel spread in climate sensitivity may occur, partially from cloud and surface albedo feedback seasonality differences. Further, links between the climate feedback and surface temperature response seasonality are investigated, showing a strong relationship between the seasonal climate feedback distribution and the seasonal surface temperature response. [ABSTRACT FROM AUTHOR]

The climate response to increased CO2 concentration is generally studied using climate models that have finite spatial and temporal resolutions. Different parameterizations of the effect of unresolved processes can result in different representations of small-scale fluctuations in the climate model. The representation of small-scale fluctuations can, on the other hand, affect the modeled climate response. In this study the mechanisms by which enhanced small-scale fluctuations alter the climate response to CO2 doubling are investigated. Climate experiments with preindustrial and doubled CO2 concentrations obtained from a comprehensive climate model [ECHAM5/Max Planck Institute Ocean Model (MPI-OM)] are analyzed both with and without enhanced small-scale fluctuations. By applying a stochastic model to the experimental results, two different mechanisms are found. First, the small-scale fluctuations can change the statistical behavior of the global mean temperature as measured by its statistical damping. The statistical damping acts as a restoring force that determines, according to the fluctuation–dissipation theory, the amplitude of the climate response to a change in external forcing (here, CO2 doubling). Second, the small-scale fluctuations can affect processes that occur only in response to the CO2 increase, thereby altering the change of the effective forcing on the global mean temperature. [ABSTRACT FROM AUTHOR]

Spatial and temporal changes in high-latitude moisture convergence simulated by the National Center for Atmospheric Research Community Climate System Model, version 3 (CCSM3) are investigated. Moisture convergence is calculated using the aerological method with model fields of specific humidity and winds spanning the periods from 1960 to 1999 and 2070 to 2089. The twenty-first century incorporates the A2 scenario from the Special Report on Emissions Scenarios. The model’s realism in reproducing the twentieth-century moisture convergence is evaluated by comparison with values derived from the 40-yr ECMWF Re-Analysis (ERA-40). In the area north of 75°N, the simulated moisture convergence is similar to observations during summer, but it is larger in winter, spring, and autumn. The model also underestimates (overestimates) the mean annual moisture convergence in the eastern (western) Arctic. Late twenty-first century annual, seasonal, and regional changes are determined by applying a self-organizing map technique to the model’s sea level pressure fields to identify dominant atmospheric circulation regimes and their corresponding moisture convergence fields. Changes in moisture convergence from the twentieth to the twenty-first century result primarily from thermodynamic effects (∼70%), albeit shifts in the frequency of dominant circulation patterns exert a relatively large influence on future changes in the eastern Arctic. Increased moisture convergence in the central Arctic (North Atlantic) stems mainly from thermodynamic changes in summer (winter). Changes in the strength and location of poleward moisture gradients are most likely responsible for projected variations in moisture transport, which are in turn a consequence of increasing anthropogenic greenhouse gas emissions as prescribed by the A2 scenario. [ABSTRACT FROM AUTHOR]

The impacts of initialized land surface conditions on the monthly prediction were investigated using ensemble simulations from the Community Atmosphere Model version 3 (CAM3). The land surface initialization was based on an offline calculation of Community Land Model version 3 driven by observation-based meteorological forcings from the Global Soil Wetness Project 2 (GSWP2). A simple but effective correction method was applied to the GSWP2 forcings prior to the offline calculation to reduce the discrepancies between the observation-forced land surface conditions and the modeling system, which can cause climate drift and initial shock problems. The climatological mean of GSWP2 forcings was adjusted to that of the target model (CAM3), while the monthly anomalies were scaled to the model statistics and high-frequency synoptic variabilities were included. Ensemble hindcast experiments with and without land surface initialization were conducted for the boreal summer (May–September), for 1983–95. The initialization process is shown to prevent climate drift and to transfer the atmospheric anomalies to the land surface memory. Statistical analyses of the simulation results reveal that the land surface initialization increased the externally forced variance over most continental regions, which is translated to enhanced potential predictability, particularly for regions with strong land–atmosphere coupling. [ABSTRACT FROM AUTHOR]

The Monte Carlo Independent Column Approximation (McICA) method for computing domain-average radiative fluxes is unbiased with respect to the full ICA, but its flux estimates contain conditional random noise. Results for five experiments are used to assess the impact of McICA-related noise on simulations of global climate made by the NCAR Community Atmosphere Model (CAM). The experiment with the least noise (an order of magnitude below that of basic McICA) is taken as the reference. Two additional experiments help demonstrate how the impact of noise depends on the time interval between calls to the radiation code. Each experiment is an ensemble of seven 15-month simulations. Experiments with very high noise levels feature significant reductions to cloudiness in the lowermost model layer over tropical oceans as well as changes in highly related quantities. This bias appears immediately, stabilizes after a couple of model days, and appears to stem from nonlinear interactions between clouds and radiative heating. Outside the Tropics, insignificant differences prevail. When McICA sampling is confined to cloudy subcolumns and when, on average, 50% more samples, relative to basic McICA, are drawn for selected spectral intervals, McICA noise is much reduced and the results of the simulation are almost statistically indistinguishable from the reference. This is true both for mean fields and for the nature of fluctuations on scales ranging from 1 day to at least 30 days. While calling the radiation code once every 3 h instead of every hour allows the CAM additional time to incorporate McICA-related noise, the impact of noise is enhanced only slightly. In contrast, changing the radiative time step by itself produces effects that generally exceed the impact of McICA’s noise. [ABSTRACT FROM AUTHOR]

Examines the global correlation and regression patterns of sea level pressure associated with the Southern Oscillation. Reanalysis of the 1958-98 data from the National Centers for Environmental Prediction-National Center for Atmospheric Research; Surface temperature patterns.

The Climate System Model (CSM) consists of atmosphere, ocean, land, and sea-ice components linked by a flux coupler, which computes fluxes of energy and momentum between components. The sea-ice component consists of a thermodynamic formulation for ice, snow, and leads within the ice pack, and ice dynamics using the cavitating-fluid ice rheology, which allows for the compressive strength of ice but ignores shear viscosity. The results of a 300-yr climate simulation are presented, with the focus on sea ice and the atmospheric forcing over sea ice in the polar regions. The atmospheric model results are compared to analyses from the European Centre for Medium-Range Weather Forecasts and other observational sources. The sea-ice concentrations and velocities are compared to satellite observational data. The atmospheric sea level pressure (SLP) in CSM exhibits a high in the central Arctic displaced poleward from the observed Beaufort high. The Southern Hemisphere SLP over sea ice is generally 5 mb lower than observed. Air temperatures over sea ice in both hemispheres exhibit cold biases of 2--4 K. The precipitation-minus-evaporation fields in both hemispheres are greatly improved over those from earlier versions of the atmospheric GCM. The simulated ice-covered area is close to observations in the Southern Hemisphere but too large in the Northern Hemisphere. The ice concentration fields show that the ice cover is too extensive in the North Pacific and subarctic North Atlantic Oceans. The interannual variability of the ice area is similar to observations in both hemispheres. The ice thickness pattern in the Antarctic is realistic but generally too thin away from the continent. The maximum thickness in the Arctic occurs against the Bering Strait, not against the Canadian Archipelago as observed. The ice velocities are stronger than observed in both hemispheres, with a consistently greater turning angle (to the left) in the Southern Hemisphere. They (...). [ABSTRACT FROM AUTHOR]

The National Center for Atmospheric Research's Climate System Model is a comprehensive model of the physical climate system. A 300-yr integration of the model has been carried out without flux correction. The solution shows very little drift in the surface temperature distribution, sea-ice extent, or atmospheric circulation. The lack of drift in the surface climate is attributed to relatively good agreement in the estimates of meridional heat transport in the uncoupled ocean model and that implied by the uncoupled atmospheric model. On the other hand, there is significant drift in the temperature and salinity distributions of the deep ocean. The ocean loses heat at an area-averaged rate of 0.35 W m[sup-2], the upper ocean becomes fresher, and the deep ocean becomes colder and saltier than in the uncoupled ocean model equilibrium or in observations. The cause of this drift is an unreasonably large meridional transport of freshwater in the sea ice model, resulting in the production of excessively cold and salty Antarctic Bottom Water. There is also significant drift in the Arctic basin, with the complete erosion of the surface halocline early in the coupled integration. [ABSTRACT FROM AUTHOR]

The global distributions of the air-sea fluxes of heat and freshwater and water mass transformation rates from a control integration of the coupled National Center for Atmospheric Research (NCAR) Climate System Model (CSM) are compared with similar fields from an uncoupled ocean model equilibrium spinup and a new surface climatology. The climatology and uncoupled model use the same bulk-flux forcing scheme and are forced with National Centers for Environmental Prediction (formerly the National Meteorological Center) atmospheric reanalysis data and satellite-based cloud cover, solar flux, and precipitation estimates. The climatological fluxes for the open ocean are adjusted to give a global net balance and are in broad general agreement with standard ship-based estimates. An exception is the ice-free Southern Ocean, where the net heat and evaporative fluxes appear to be too weak but where the observational coverage underlying the reanalyis is quite poor. Major differences are observed between the climatology and the NCAR CSM coupled solution, namely, enhanced tropical and subtropic solar insolation, stronger energy and hydrologic cycles, and excessive high-latitude ice formation/melt producing a several-fold increase in Arctic and Antarctic deep water formation through brine rejection. The anomalous fluxes and corresponding water-mass transformations are closely tied to the coupled ocean model drift, characterized by a reorganization of the vertical salinity distribution. Some error features in the heat flux and sea surface temperature fields are common to both the coupled and uncoupled solutions, primarily in the western boundary currents and the Antarctic circumpolar current, and are thus likely due to the poor representation of the circulation field in the coarse-resolution NCAR ocean model. Other problems particular to the uncoupled spinup are related to the bulk-flux forcing scheme, an example being excess freshwater deposition in the western (...). [ABSTRACT FROM AUTHOR]

The simulation of the tropical western Pacific warm pool is explored with the NCAR Climate System Model (CSM). The simulated sea surface temperatures in the Pacific basin have biases that are similar to other coupled model simulations in this region. In particular, an excessive cold tongue of water extends across the Pacific basin, with warm water on either side of this cold tongue. The warm pool region is also too cold. This cold bias exists in spite of an overestimate in surface net energy flux into this region. To understand the source of this bias in SST, simulations from the uncoupled and fully coupled models are analyzed in terms of biases in surface energy budget. These analyses suggest that the strong constraint of little ocean heat transport out of the warm pool region forces a change in SST gradient that leads to an increase in the atmospheric zonal wind. This increase in zonal wind causes an increase in latent heat flux in the warm pool region. The increase in latent heat flux is required to offset a significant (~35 W m[sup-2]) bias in net surface solar flux. The bias in surface solar flux is due to an underestimate of model cloud shortwave absorption. [ABSTRACT FROM AUTHOR]

The National Center for Atmospheric Research (NCAR) Land Surface Model (LSM, version 1.0) provides a comprehensive treatment of land surface processes for the NCAR Community Climate Model version 3 (CCM3). It replaces the prescribed surface wetness, prescribed snow cover, surface albedo, and surface flux parameterizations used in the CCM2. A 15-yr simulation of the coupled atmosphere (CCM3) and land (LSM1.0) models using observed sea surface temperatures for the period December 1978--September 1993 is used to document the model's land surface climate. The model simulates many of the observed geographic and seasonal patterns of surface air temperature, precipitation, and soil water. In general, the transition seasons (spring, autumn) are better simulated than winter and summer. Annual precipitation and runoff are well simulated for some river basins and poorly simulated for others. In general, precipitation is better simulated than runoff. The inclusion of net land-atmosphere CO2 exchange is an important component of the land model, allowing it to be used for studies of the global carbon cycle. The model simulates annual net primary production that is consistent with other estimates of annual production. The model also simulates a clearly defined growing season based on temperature and soil water. [ABSTRACT FROM AUTHOR]

The dynamical simulation of the standard configuration of the latest version of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3) is examined, including the seasonal variation of its mean state and its intraseasonal and interannual variability. A 15-yr integration in which the model is forced with observed monthly varying sea surface temperatures (SSTs) since 1979 is compared to coexisting observations. Results show that the most serious systematic errors in previous NCAR CCM versions have either been eliminated or substantially reduced. At sea level, CCM3 reproduces the basic observed patterns of the pressure field very well. Simulated surface pressures are higher than observed over the subtropics, however, an error consistent with an easterly bias in the simulated trade winds and low-latitude surface wind stress. Amplitude errors and phase shifts of the subpolar low pressure centers over both hemispheres during winter produce the largest regional errors, which are on the order of 5 mb. In the upper troposphere, both the amplitude and location of the major circulation centers are very well captured by the model, in agreement with relatively small regional biases in the simulated winds. Errors in the zonal wind component at 200 mb are most notable between 408 and 50&deg lat of both hemispheres, where the modeled westerlies are stronger than observed especially over the Southern Hemisphere during winter. A -50% reduction in the magnitude of the zonally averaged westerly bias in the equatorial upper troposphere that plagued previous CCM versions can be attributed to a significantly improved tropical hydrologic cycle and reduced Walker circulation. Over middle latitudes, the CCM3 realistically depicts the main storm tracks, although the transient kinetic energy is generally underestimated, especially over the summer hemispheres. Over lower latitudes, the model simulates tropical intraseasonal oscillations with marked sea (...). [ABSTRACT FROM AUTHOR]

The implied meridional ocean energy transport diagnosed from uncoupled integrations of two atmospheric general circulation models--the National Center for Atmospheric Research Community Climate Model versions 2 and 3 (CCM2 and CCM3)--shows radically different transport characteristics throughout much of the Southern Hemisphere. The CCM2 simulation requires an equatorward transport of energy by the oceans, and the CCM3 exhibits a poleward energy transport requirement, very similar to what is derived from observational analyses. Previous studies have suggested that errors in the implied ocean energy transport are largely attributable to errors in the simulated cloud radiative forcing. The results of this analysis show that although the proper simulation of the radiative effects of clouds is likely to be a necessary condition for realistic meridional ocean energy transport, it is not sufficient. Important changes in the CCM3 equatorial surface latent heat fluxes, associated with a deep formulation for parameterized moist convection, are primarily responsible for the improved ocean energy transport, where this change in the surface energy budget is much more weakly reflected in top-of-atmosphere differences in cloud radiative forcing. [ABSTRACT FROM AUTHOR]

Climatological properties for selected aspects of the thermodynamic structure and hydrologic cycle are presented from a 15-yr numerical simulation conducted with the National Center for Atmospheric Research Community Climate Model, version 3 (CCM3), using an observed sea surface temperature climatology. In most regards, the simulated thermal structure and hydrologic cycle represent a marked improvement when compared with earlier versions of the CCM. Three major modifications to parameterized physics are primarily responsible for the more notable improvements in the simulation: modifications to the diagnosis of cloud optical properties, modifications to the diagnosis of boundary layer processes, and the incorporation of a penetrative formulation for deep cumulus convection. The various roles of these physical parameterization changes will be discussed in the context of the simulation strengths and weaknesses. [ABSTRACT FROM AUTHOR]

The NCAR Climate System Model, version one, is described. The spinup procedure prior to a fully coupled integration is discussed. The fully coupled model has been run for 300 yr with no surface flux corrections in momentum, heat, or freshwater. There is virtually no trend in the surface temperatures over the 300 yr, although there are significant trends in other model fields, especially in the deep ocean. The reasons for the successful integration with no surface temperature trend are discussed. [ABSTRACT FROM AUTHOR]

Five- and 10-day inert trace constituent distributions prognostically simulated with the University of Wisconsin (UW) hybrid isentropic--sigma ( u-- s) model, the nominally identical UW sigma ( s) model, and the National Center for Atmospheric Research Community Climate Model 2 (CCM2) are analyzed and compared in this study. The UW u-- s and s gridpoint models utilize the flux form of the primitive equations, while CCM2 is based on the spectral representation and uses semi-Lagrangian transport (SLT) for trace constituents. Results are also compared against a version of the CCM that uses spectral transport for the trace constituent. These comparisons 1) contrast the spatial and temporal evolution of the filamentary transport of inert trace constituents simulated with the UW u-- s and s models against a "state of the art" GCM under both isentropic and noni-sentropic conditions and 2) examine the ability of the models to conserve the initial trace constituent maximum value during 10-day integrations. Results show that the spatial distributions of trace constituent evolve in a similar manner, regardless of the transport scheme or model type. However, when compared to the UW u-- smodel's ability to simulate filamentary structure and conserve the initial trace constituent maximum value, results from the other models in this study indicate substantial spurious dispersion. The more accurate conservation demonstrated with the UW u-- smodel is especially noticeable within extratropical amplifying baroclinic waves, and it stems from the dominance of two-dimensional, quasi-horizontal isentropic exchange processes in a stratified baroclinic atmosphere. [ABSTRACT FROM AUTHOR]

The article offers information on the impact of climate change on the U.S.'s temperature. According to Gerald Meehl from the National Center for Atmospheric Research in Boulder, Colorado, the climate change has retained mark on the extreme temperature in the country, whereby, based on the data from various weather stations, the warm days doubled the number of cold days since January 2000 up to November 2009. Further information on the impact of climate change in the U.S. is presented.