Abstract

Two commonly used vertical finite difference approximations produce markedly different simulations when adapted to the nine-level Community Climate Model assembled at the National Center for Atmospheric Research. The differences are conveniently illustrated by considering the zonal average temperature and zonal wind, but these different zonal averaged are also associated with differences in the stationary and transient waves in the model. The hydrostatic equation and vertical temperature advection are the main contributors to the differences in the simulations. Other terms produce only minor differences. Except above the equatorial tropopause, the two schemes converge to the same solution with significantly higher vertical resolution. In many respects, this convergent simulation is closer to that produced by one of the approximations on the original nine levels than to that produced by the other. However, the resemblance is not adequate to justify use of that scheme on the coarse grid when other aspects of the simulation are also considered. Higher resolution should be used so that the simulation becomes insensitive to the vertical finite difference approximations.

Abstract

The authors compare short forecast errors and the balance of terms in the moisture and temperature prediction equations that lead to those errors for the Community Atmosphere Model versions 2 and 3 (CAM2 and CAM3, respectively) at T42 truncation. The comparisons are made for an individual model column from global model forecasts at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains site for the April 1997 and June–July 1997 intensive observing periods. The goal is to provide insight into parameterization errors in the CAM, which ultimately should lead to improvements in the way processes are modeled. The atmospheric initial conditions are obtained from the 40-yr ECMWF Re-Analysis (ERA-40). The land initial conditions are spun up to be consistent with those analyses. The differences between the model formulations that are responsible for the major differences in the forecast errors and/or parameterization behaviors are identified. A sequence of experiments is performed, accumulating the changes from CAM3 back toward CAM2 to demonstrate the effect of the differences in formulations.

In June–July 1997 the CAM3 temperature and moisture forecast errors were larger than those of CAM2. The terms identified as being responsible for the differences are 1) the convective time scale assumed for the Zhang–McFarlane deep convection, 2) the energy associated with the conversion between water and ice of the rain associated with the Zhang–McFarlane convection parameterization, and 3) the dependence of the rainfall evaporation on cloud fraction. In April 1997 the CAM2 and CAM3 temperature and moisture forecast errors are very similar, but different tendencies arising from modifications to one parameterization component are compensated by responding changes in another component to yield the same total moisture tendency. The addition of detrainment of water in CAM3 by the Hack shallow convection to the prognostic cloud water scheme is balanced by a responding difference in the advective tendency. A halving of the time scale assumed for the Hack shallow convection was compensated by a responding change in the prognostic cloud water. Changes to the cloud fraction parameterization affect the radiative heating, which in turn modifies the stability of the atmospheric column and affects the convection. The resulting changes in convection tendency are balanced by responding changes in the prognostic cloud water parameterization tendency.

Abstract

Detailed comparisons are made between the climate simulated by a seasonal version of the NCAR Community Climate Mode) (CCM1) at 12 level, R15 spectral resolution, and that revealed by ECMWF operational analyses over 1980–86 truncated to a similar resolution. A variety of circulation statistics are presented to reveal the spatial character and seasonality of CCM1 biases in temperatures, winds, and wave flux quantities. CCM1 biases are typical of current climate models run at similar resolution. Interrelationships between the above biases are a focus of this study, in particular using wave-mean flow interaction diagnostics.

CCM1 exhibits a westerly zonal wind bias in the tropics and a lack of westerlies in the high latitude Southern Hemisphere (SH). The tropical zonal mean meridional circulation (Hadley cell) in the model is approximately a factor of two too weak. The poleward eddy heat flux is accurately simulated, but the poleward eddy momentum flux is severely underestimated, particularly in the SH. There is a resulting excessive large-scale wave drag in the model extratropical upper troposphere, in qualitative agreement with the weak model high latitude westerlies (and temperature bias patterns). Conversely, the model tropical zonal wind bias does not appear to be related to influences by large-scale waves. Wave flux biases are compared for stationary and transient statistics; model stationary waves are in good agreement with observations, while the largest relative momentum flux error is found for higher frequency transient waves.

Abstract

No abstract available

Abstract

Forecasts of October 2006 are used to investigate southeast Pacific stratocumulus in the Community Atmosphere Model, versions 4 and 5 (CAM4 and CAM5). Both models quickly develop biases similar to their climatic biases, suggesting that parameterized physics are the root of the climate errors. An extensive cloud deck is produced in CAM4, but the cloud structure is unrealistic because the boundary layer is too shallow and moist. The boundary layer structure is improved in CAM5, but during the daytime the boundary layer decouples from the cloud layer, causing the cloud layer to break up and transition toward a more trade wind cumulus structure in the afternoon. The cloud liquid water budget shows how different parameterizations contribute to maintaining these different expressions of stratocumulus. Sensitivity experiments help elucidate the origins of the errors. The importance of the diurnal cycle of these clouds for climate simulations is emphasized.

Abstract

Environment Canada meteorological station hourly sampled air temperatures T _air at four stations in the southwest Yukon were used to identify cloud contamination in the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra clear-sky daytime land surface temperature (LST) and emissivity daily level-3 global 1-km grid product (MOD11A1, Collection 5) that is not flagged by the MODIS quality algorithm as contaminated. The additional cloud masking used qualitative ground-based sky condition observations, collected at two of the four stations, and coincident MODIS quality flag information. The results indicate that air temperature observed at a variety of discrete spatial locations having different land cover is highly correlated with MODIS LST collected at 1-km grid spacing. Quadratic relationships between LST and air temperature, constrained by ground observations of “clear” sky conditions, show less variability than relationships found under “mainly clear” and “mostly cloudy” sky conditions, and the more clouds observed in the sky coincides with a decreasing y intercept. Analysis of MODIS LST and its associated quality flags show a cold bias (<0°C) in the assignment of the ≤3-K-average LST error, indicating MODIS LST has a maximum average error of ≤2 K over a warm surface (>0°C). Analysis of two observation stations shows that unidentified clouds in MODIS LST are between 13% and 17%, a result that agrees well with previous studies. Analysis of daytime values is important because many processes are dependent on daylight and maximum temperature. The daytime clear-sky LST–T _air relationship observed for the good-quality confirmed cloud-free-sky MODIS LST quality flag can be used to discriminate cloud-contaminated grid cells beyond the standard MODIS cloud mask.

Abstract

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 40° and 50° 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 seasonality in their occurrence. Typical periodicities, however, are near 20–30 days, which are shorter than observed, and the simulated amplitudes are weaker than in both observations and previous versions of the model. The simulated response to interannual variations in tropical SSTs is also realistic in CCM3. A simulated index of the Southern Oscillation agrees well with the observed, and the model captures the overall structure and magnitude of observed shifts in tropical and subtropical convergence zones and monthly rainfall anomalies associated with the tropical SST changes.

Abstract

Forecasts of southeast Pacific stratocumulus at 20°S and 85°W during the East Pacific Investigation of Climate (EPIC) cruise of October 2001 are examined with the ECMWF model, the Atmospheric Model (AM) from GFDL, the Community Atmosphere Model (CAM) from NCAR, and the CAM with a revised atmospheric boundary layer formulation from the University of Washington (CAM-UW). The forecasts are initialized from ECMWF analyses and each model is run for 3–5 days to determine the differences with the EPIC field observations.

Observations during the EPIC cruise show a well-mixed boundary layer under a sharp inversion. The inversion height and the cloud layer have a strong and regular diurnal cycle. A key problem common to the models is that the planetary boundary layer (PBL) depth is too shallow when compared to EPIC observations. However, it is suggested that improved PBL depths are achieved with more physically realistic PBL schemes: at one end, CAM uses a dry and surface-driven PBL scheme and produces a very shallow PBL, while the ECWMF model uses an eddy-diffusivity/mass-flux approach and produces a deeper and better-mixed PBL. All the models produce a strong diurnal cycle in the liquid water path (LWP), but there are large differences in the amplitude and phase when compared to the EPIC observations. This, in turn, affects the radiative fluxes at the surface and the surface energy budget. This is particularly relevant for coupled simulations as this can lead to a large SST bias.

Abstract

Cloud effects have repeatedly been pointed out as the leading source of uncertainty in projections of future climate, yet clouds remain poorly understood and simulated in climate models. Aquaplanets provide a simplified framework for comparing and understanding cloud effects, and how they are partitioned as a function of regime, in large-scale models. This work uses two climate models to demonstrate that aquaplanets can successfully predict a climate model’s sensitivity to an idealized climate change. For both models, aquaplanet climate sensitivity is similar to that of the realistic configuration. Tropical low clouds appear to play a leading role in determining the sensitivity. Regions of large-scale subsidence, which cover much of the tropics, are most directly responsible for the differences between the models. Although cloud effects and climate sensitivity are similar for aquaplanets and realistic configurations, the aquaplanets lack persistent stratocumulus in the tropical atmosphere. This, and an additional analysis of the cloud response in the realistically configured simulations, suggests the representation of shallow (trade wind) cumulus convection, which is ubiquitous in the tropics, is largely responsible for differences in the simulated climate sensitivity of these two models.

Abstract

This study examines the sensitivity of a number of important archetypical tracer problems to the numerical method used to solve the equations of tracer transport and atmospheric dynamics. The tracers' scenarios were constructed to exercise the model for a variety of problems relevant to understanding and modeling the physical, dynamical, and chemical aspects of the climate system. The use of spectral, semi-Lagrangian, and finite volume (FV) numerical methods for the equations is explored. All subgrid-scale physical parameterizations were the same in all model simulations.

The model behavior with a few short simulations with passive tracers is explored, and with much longer simulations of radon, SF₆, ozone, a tracer designed to mimic some aspects of a biospheric source/sink of CO₂, and a suite of tracers designed around the conservation laws for thermodynamics and mass in the model.

Large differences were seen near the tropopause in the model, where the FV core shows a much reduced level of vertical and meridional mixing. There was also evidence that the subtropical subsidence regions are more isolated from Tropics and midlatitudes in the FV core than seen in the other model simulations. There are also big differences in the stratosphere, particularly for age of air in the stratosphere and ozone. A comparison with estimated age of air from CO₂ and SF₆ measurements in the stratosphere suggest that the FV core is behaving most realistically.

A neutral biosphere (NB) test case is used to explore issues of diurnal and seasonal rectification of a tracer with sources and sinks at the surface. The sources and sinks have a zero annual average, and the rectification is associated with temporal correlations between the sources and sinks, and transport. The test suggests that the rectification is strongly influenced by the resolved-scale dynamics (i.e., the dynamical core) and that the numerical formulation for dynamics and transport still plays a critical role in the distribution of NB-like species. Since the distribution of species driven by these processes have a strong influence on the interpretation of the “missing sink” for CO₂ and the interpretation of climate change associated with anthropogenic forcing herein, these issues should not be neglected.

The spectral core showed the largest departures from the predicted nonlinear relationship required by the equations for thermodynamics and mass conservations. The FV and semi-Lagrangian dynamics (SLD) models both produced errors a factor of 2 lower. The SLD model shows a small but systematic bias in its ability to maintain this relationship that was not present in the FV simulation.

The results of the study indicate that for virtually all of these problems, the model numerics still have a large role in influencing the model solutions. It was frequently the case that the differences in solutions resulting from varying the numerics still exceed the differences in the simulations resulting from significant physical perturbations (like changes in greenhouse gas forcing). This does not mean that the response of the system to physical changes is not correct. When results are consistent using different numerical formulations for dynamics and transport it lends confidence to one's conclusions, but it does indicate that some caution is required in interpreting the results.

The results from this study favor use of the FV core for tracer transport and model dynamics. The FV core is, unlike the others, conservative, less diffusive (e.g., maintains strong gradients better), and maintains the nonlinear relationships among variables required by thermodynamic and mass conservation constraints more accurately.