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- Author or Editor: A. Gettelman x
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Abstract
Prognostic precipitation is added to a cloud microphysical scheme for global climate models. Results indicate very similar performance to other commonly used mesoscale schemes in an offline driver for idealized warm rain cases, better than the previous version of the global model microphysics scheme with diagnostic precipitation. In the mixed phase regime, there is significantly more water and less ice, which may address a common bias seen with the scheme in climate simulations in the Arctic. For steady forcing cases, the scheme has limited sensitivity to time step out to the ~15-min time steps typical of global models. The scheme is similar to other schemes with moderate sensitivity to vertical resolution. The limited time step sensitivity bodes well for use of the scheme in multiscale models from the mesoscale to the large scale. The scheme is sensitive to idealized perturbations of cloud drop and crystal number. Precipitation decreases and condensate increases with increasing drop number, indicating substantial decreases in precipitation efficiency. The sensitivity is less than with the previous version of the scheme for low drop number concentrations (N c < 100 cm−3). Ice condensate increases with ice number, with large decreases in liquid condensate as well for a mixed phase case. As expected with prognostic precipitation, accretion is stronger than with diagnostic precipitation and the accretion to autoconversion ratio increases faster with liquid water path (LWP), in better agreement with idealized models and earlier studies than the previous version.
Abstract
Prognostic precipitation is added to a cloud microphysical scheme for global climate models. Results indicate very similar performance to other commonly used mesoscale schemes in an offline driver for idealized warm rain cases, better than the previous version of the global model microphysics scheme with diagnostic precipitation. In the mixed phase regime, there is significantly more water and less ice, which may address a common bias seen with the scheme in climate simulations in the Arctic. For steady forcing cases, the scheme has limited sensitivity to time step out to the ~15-min time steps typical of global models. The scheme is similar to other schemes with moderate sensitivity to vertical resolution. The limited time step sensitivity bodes well for use of the scheme in multiscale models from the mesoscale to the large scale. The scheme is sensitive to idealized perturbations of cloud drop and crystal number. Precipitation decreases and condensate increases with increasing drop number, indicating substantial decreases in precipitation efficiency. The sensitivity is less than with the previous version of the scheme for low drop number concentrations (N c < 100 cm−3). Ice condensate increases with ice number, with large decreases in liquid condensate as well for a mixed phase case. As expected with prognostic precipitation, accretion is stronger than with diagnostic precipitation and the accretion to autoconversion ratio increases faster with liquid water path (LWP), in better agreement with idealized models and earlier studies than the previous version.
Abstract
Satellite measurements from the Atmospheric Infrared Sounder (AIRS) in the upper troposphere over 4.5 yr are used to assess the covariation of upper-tropospheric humidity and temperature with surface temperatures, which can be used to constrain the upper-tropospheric moistening due to the water vapor feedback. Results are compared to simulations from a general circulation model, the NCAR Community Atmosphere Model (CAM), to see if the model can reproduce the variations. Results indicate that the upper troposphere maintains nearly constant relative humidity for observed perturbations to ocean surface temperatures over the observed period, with increases in temperature ∼1.5 times the changes at the surface, and corresponding increases in water vapor (specific humidity) of 10%–25% °C−1. Increases in water vapor are largest at pressures below 400 hPa, but they have a double peak structure. Simulations reproduce these changes quantitatively and qualitatively. Agreement is best when the model is sorted for satellite sampling thresholds. This indicates that the model reproduces the moistening associated with the observed upper-tropospheric water vapor feedback. The results are not qualitatively sensitive to model resolution or model physics.
Abstract
Satellite measurements from the Atmospheric Infrared Sounder (AIRS) in the upper troposphere over 4.5 yr are used to assess the covariation of upper-tropospheric humidity and temperature with surface temperatures, which can be used to constrain the upper-tropospheric moistening due to the water vapor feedback. Results are compared to simulations from a general circulation model, the NCAR Community Atmosphere Model (CAM), to see if the model can reproduce the variations. Results indicate that the upper troposphere maintains nearly constant relative humidity for observed perturbations to ocean surface temperatures over the observed period, with increases in temperature ∼1.5 times the changes at the surface, and corresponding increases in water vapor (specific humidity) of 10%–25% °C−1. Increases in water vapor are largest at pressures below 400 hPa, but they have a double peak structure. Simulations reproduce these changes quantitatively and qualitatively. Agreement is best when the model is sorted for satellite sampling thresholds. This indicates that the model reproduces the moistening associated with the observed upper-tropospheric water vapor feedback. The results are not qualitatively sensitive to model resolution or model physics.
Abstract
The global performance of a new two-moment cloud microphysics scheme for a general circulation model (GCM) is presented and evaluated relative to observations. The scheme produces reasonable representations of cloud particle size and number concentration when compared to observations, and it represents expected and observed spatial variations in cloud microphysical quantities. The scheme has smaller particles and higher number concentrations over land than the standard bulk microphysics in the GCM and is able to balance the top-of-atmosphere radiation budget with 60% the liquid water of the standard scheme, in better agreement with retrieved values. The new scheme diagnostically treats both the mixing ratio and number concentration of rain and snow, and it is therefore able to differentiate the two key regimes, consisting of drizzle in shallow, warm clouds and larger rain drops in deeper cloud systems. The modeled rain and snow size distributions are consistent with observations.
Abstract
The global performance of a new two-moment cloud microphysics scheme for a general circulation model (GCM) is presented and evaluated relative to observations. The scheme produces reasonable representations of cloud particle size and number concentration when compared to observations, and it represents expected and observed spatial variations in cloud microphysical quantities. The scheme has smaller particles and higher number concentrations over land than the standard bulk microphysics in the GCM and is able to balance the top-of-atmosphere radiation budget with 60% the liquid water of the standard scheme, in better agreement with retrieved values. The new scheme diagnostically treats both the mixing ratio and number concentration of rain and snow, and it is therefore able to differentiate the two key regimes, consisting of drizzle in shallow, warm clouds and larger rain drops in deeper cloud systems. The modeled rain and snow size distributions are consistent with observations.
Abstract
An ensemble of simulations from different versions of the Community Atmosphere Model in the Community Earth System Model (CESM) is used to investigate the processes responsible for the intermodel spread in climate sensitivity. In the CESM simulations, the climate sensitivity spread is primarily explained by shortwave cloud feedbacks on the equatorward flank of the midlatitude storm tracks. Shortwave cloud feedbacks have been found to explain climate sensitivity spread in previous studies, but the location of feedback differences was in the subtropics rather than in the storm tracks as identified in CESM. The cloud-feedback relationships are slightly stronger in the winter hemisphere. The spread in climate sensitivity in this study is related both to the cloud-base state and to the cloud feedbacks. Simulated climate sensitivity is correlated with cloud-fraction changes on the equatorward side of the storm tracks, cloud condensate in the storm tracks, and cloud microphysical state on the poleward side of the storm tracks. Changes in the extent and water content of stratiform clouds (that make up cloud feedback) are regulated by the base-state vertical velocity, humidity, and deep convective mass fluxes. Within the storm tracks, the cloud-base state affects the cloud response to CO2-induced temperature changes and alters the cloud feedbacks, contributing to climate sensitivity spread within the CESM ensemble.
Abstract
An ensemble of simulations from different versions of the Community Atmosphere Model in the Community Earth System Model (CESM) is used to investigate the processes responsible for the intermodel spread in climate sensitivity. In the CESM simulations, the climate sensitivity spread is primarily explained by shortwave cloud feedbacks on the equatorward flank of the midlatitude storm tracks. Shortwave cloud feedbacks have been found to explain climate sensitivity spread in previous studies, but the location of feedback differences was in the subtropics rather than in the storm tracks as identified in CESM. The cloud-feedback relationships are slightly stronger in the winter hemisphere. The spread in climate sensitivity in this study is related both to the cloud-base state and to the cloud feedbacks. Simulated climate sensitivity is correlated with cloud-fraction changes on the equatorward side of the storm tracks, cloud condensate in the storm tracks, and cloud microphysical state on the poleward side of the storm tracks. Changes in the extent and water content of stratiform clouds (that make up cloud feedback) are regulated by the base-state vertical velocity, humidity, and deep convective mass fluxes. Within the storm tracks, the cloud-base state affects the cloud response to CO2-induced temperature changes and alters the cloud feedbacks, contributing to climate sensitivity spread within the CESM ensemble.
Abstract
The major evolution of the National Center for Atmospheric Research Community Atmosphere Model (CAM) is used to diagnose climate feedbacks, understand how climate feedbacks change with different physical parameterizations, and identify the processes and regions that determine climate sensitivity. In the evolution of CAM from version 4 to version 5, the water vapor, temperature, surface albedo, and lapse rate feedbacks are remarkably stable across changes to the physical parameterization suite. However, the climate sensitivity increases from 3.2 K in CAM4 to 4.0 K in CAM5. The difference is mostly due to (i) more positive cloud feedbacks and (ii) higher CO2 radiative forcing in CAM5. The intermodel differences in cloud feedbacks are largest in the tropical trade cumulus regime and in the midlatitude storm tracks. The subtropical stratocumulus regions do not contribute strongly to climate feedbacks owing to their small area coverage. A “modified Cess” configuration for atmosphere-only model experiments is shown to reproduce slab ocean model results. Several parameterizations contribute to changes in tropical cloud feedbacks between CAM4 and CAM5, but the new shallow convection scheme causes the largest midlatitude feedback differences and the largest change in climate sensitivity. Simulations with greater cloud forcing in the mean state have lower climate sensitivity. This work provides a methodology for further analysis of climate sensitivity across models and a framework for targeted comparisons with observations that can help constrain climate sensitivity to radiative forcing.
Abstract
The major evolution of the National Center for Atmospheric Research Community Atmosphere Model (CAM) is used to diagnose climate feedbacks, understand how climate feedbacks change with different physical parameterizations, and identify the processes and regions that determine climate sensitivity. In the evolution of CAM from version 4 to version 5, the water vapor, temperature, surface albedo, and lapse rate feedbacks are remarkably stable across changes to the physical parameterization suite. However, the climate sensitivity increases from 3.2 K in CAM4 to 4.0 K in CAM5. The difference is mostly due to (i) more positive cloud feedbacks and (ii) higher CO2 radiative forcing in CAM5. The intermodel differences in cloud feedbacks are largest in the tropical trade cumulus regime and in the midlatitude storm tracks. The subtropical stratocumulus regions do not contribute strongly to climate feedbacks owing to their small area coverage. A “modified Cess” configuration for atmosphere-only model experiments is shown to reproduce slab ocean model results. Several parameterizations contribute to changes in tropical cloud feedbacks between CAM4 and CAM5, but the new shallow convection scheme causes the largest midlatitude feedback differences and the largest change in climate sensitivity. Simulations with greater cloud forcing in the mean state have lower climate sensitivity. This work provides a methodology for further analysis of climate sensitivity across models and a framework for targeted comparisons with observations that can help constrain climate sensitivity to radiative forcing.
Abstract
Aerosols can influence cloud radiative effects and, thus, may alter interpretation of how Earth’s radiative budget responds to climate forcing. Three different ensemble experiments from the same climate model with different greenhouse gas and aerosol scenarios are used to analyze the role of aerosols in climate feedbacks and their spread across initial condition ensembles of transient climate simulations. The standard deviation of global feedback parameters across ensemble members is low, typically 0.02 W m−2 K−1. Feedbacks from high (8.5 W m−2) and moderate (4.5 W m−2) year 2100 forcing cases are nearly identical. An aerosol kernel is introduced to remove effects of aerosol cloud interactions that alias into cloud feedbacks. Adjusted cloud feedbacks indicate an “aerosol feedback” resulting from changes to climate that increase sea-salt emissions, mostly in the Southern Ocean. Ensemble simulations also indicate higher tropical cloud feedbacks with higher aerosol loading. These effects contribute to a difference in cloud feedbacks of nearly 50% between ensembles of the same model. These two effects are also seen in aquaplanet simulations with varying fixed drop number. Thus aerosols can be a significant modifier of cloud feedbacks, and different representations of aerosols and their interactions with clouds may contribute to multimodel spread in climate feedbacks and climate sensitivity in multimodel archives.
Abstract
Aerosols can influence cloud radiative effects and, thus, may alter interpretation of how Earth’s radiative budget responds to climate forcing. Three different ensemble experiments from the same climate model with different greenhouse gas and aerosol scenarios are used to analyze the role of aerosols in climate feedbacks and their spread across initial condition ensembles of transient climate simulations. The standard deviation of global feedback parameters across ensemble members is low, typically 0.02 W m−2 K−1. Feedbacks from high (8.5 W m−2) and moderate (4.5 W m−2) year 2100 forcing cases are nearly identical. An aerosol kernel is introduced to remove effects of aerosol cloud interactions that alias into cloud feedbacks. Adjusted cloud feedbacks indicate an “aerosol feedback” resulting from changes to climate that increase sea-salt emissions, mostly in the Southern Ocean. Ensemble simulations also indicate higher tropical cloud feedbacks with higher aerosol loading. These effects contribute to a difference in cloud feedbacks of nearly 50% between ensembles of the same model. These two effects are also seen in aquaplanet simulations with varying fixed drop number. Thus aerosols can be a significant modifier of cloud feedbacks, and different representations of aerosols and their interactions with clouds may contribute to multimodel spread in climate feedbacks and climate sensitivity in multimodel archives.
Abstract
This study documents and evaluates the boundary layer and energy budget response to record low 2007 sea ice extents in the Community Atmosphere Model version 4 (CAM4) using 1-day observationally constrained forecasts and 10-yr runs with a freely evolving atmosphere. While near-surface temperature and humidity are minimally affected by sea ice loss in July 2007 forecasts, near-surface stability decreases and atmospheric humidity increases aloft over newly open water in September 2007 forecasts. Ubiquitous low cloud increases over the newly ice-free Arctic Ocean are found in both the July 2007 and the September 2007 forecasts. In response to the 2007 sea ice loss, net surface [top of the atmosphere (TOA)] energy budgets change by +19.4 W m−2 (+21.0 W m−2) and −17.9 W m−2 (+1.4 W m−2) in the July 2007 and September 2007 forecasts, respectively. While many aspects of the forecasted response to sea ice loss are consistent with physical expectations and available observations, CAM4’s ubiquitous July 2007 cloud increases over newly open water are not. The unrealistic cloud response results from the global application of parameterization designed to diagnose stratus clouds based on lower-tropospheric stability (CLDST). In the Arctic, the well-mixed boundary layer assumption implicit in CLDST is violated. Requiring a well-mixed boundary layer to diagnose stratus clouds improves the CAM4 cloud response to sea ice loss and increases July 2007 surface (TOA) energy budgets over newly open water by +11 W m−2 (+14.9 W m−2). Of importance to high-latitude climate feedbacks, unrealistic stratus cloud compensation for sea ice loss occurs only when stable and dry atmospheric conditions exist. Therefore, coupled climate projections that use CAM4 will underpredict Arctic sea ice loss only when dry and stable summer conditions occur.
Abstract
This study documents and evaluates the boundary layer and energy budget response to record low 2007 sea ice extents in the Community Atmosphere Model version 4 (CAM4) using 1-day observationally constrained forecasts and 10-yr runs with a freely evolving atmosphere. While near-surface temperature and humidity are minimally affected by sea ice loss in July 2007 forecasts, near-surface stability decreases and atmospheric humidity increases aloft over newly open water in September 2007 forecasts. Ubiquitous low cloud increases over the newly ice-free Arctic Ocean are found in both the July 2007 and the September 2007 forecasts. In response to the 2007 sea ice loss, net surface [top of the atmosphere (TOA)] energy budgets change by +19.4 W m−2 (+21.0 W m−2) and −17.9 W m−2 (+1.4 W m−2) in the July 2007 and September 2007 forecasts, respectively. While many aspects of the forecasted response to sea ice loss are consistent with physical expectations and available observations, CAM4’s ubiquitous July 2007 cloud increases over newly open water are not. The unrealistic cloud response results from the global application of parameterization designed to diagnose stratus clouds based on lower-tropospheric stability (CLDST). In the Arctic, the well-mixed boundary layer assumption implicit in CLDST is violated. Requiring a well-mixed boundary layer to diagnose stratus clouds improves the CAM4 cloud response to sea ice loss and increases July 2007 surface (TOA) energy budgets over newly open water by +11 W m−2 (+14.9 W m−2). Of importance to high-latitude climate feedbacks, unrealistic stratus cloud compensation for sea ice loss occurs only when stable and dry atmospheric conditions exist. Therefore, coupled climate projections that use CAM4 will underpredict Arctic sea ice loss only when dry and stable summer conditions occur.
Abstract
Identical composite analysis of midlatitude cyclones over oceanic regions has been carried out on both output from the NCAR Community Atmosphere Model, version 3 (CAM3) and multisensor satellite data. By focusing on mean fields associated with a single phenomenon, the ability of the CAM3 to reproduce realistic midlatitude cyclones is critically appraised. A number of perturbations to the control model were tested against observations, including a candidate new microphysics package for the CAM. The new microphysics removes the temperature-dependent phase determination of the old scheme and introduces representations of microphysical processes to convert from one phase to another and from cloud to precipitation species. By subsampling composite cyclones based on systemwide mean strength (mean wind speed) and systemwide mean moisture the authors believe they are able to make meaningful like-with-like comparisons between observations and model output. All variations of the CAM tested overestimate the optical thickness of high-topped clouds in regions of precipitation. Over a system as a whole, the model can both over- and underestimate total high-topped cloud amounts. However, systemwide mean rainfall rates and composite structure appear to be in broad agreement with satellite estimates. When cyclone strength is taken into account, changes in moisture and rainfall rates from both satellite-derived observations and model output as a function of changes in sea surface temperature are in accordance with the Clausius–Clapeyron equation. The authors find that the proposed new microphysics package shows improvement to composite liquid water path fields and cloud amounts.
Abstract
Identical composite analysis of midlatitude cyclones over oceanic regions has been carried out on both output from the NCAR Community Atmosphere Model, version 3 (CAM3) and multisensor satellite data. By focusing on mean fields associated with a single phenomenon, the ability of the CAM3 to reproduce realistic midlatitude cyclones is critically appraised. A number of perturbations to the control model were tested against observations, including a candidate new microphysics package for the CAM. The new microphysics removes the temperature-dependent phase determination of the old scheme and introduces representations of microphysical processes to convert from one phase to another and from cloud to precipitation species. By subsampling composite cyclones based on systemwide mean strength (mean wind speed) and systemwide mean moisture the authors believe they are able to make meaningful like-with-like comparisons between observations and model output. All variations of the CAM tested overestimate the optical thickness of high-topped clouds in regions of precipitation. Over a system as a whole, the model can both over- and underestimate total high-topped cloud amounts. However, systemwide mean rainfall rates and composite structure appear to be in broad agreement with satellite estimates. When cyclone strength is taken into account, changes in moisture and rainfall rates from both satellite-derived observations and model output as a function of changes in sea surface temperature are in accordance with the Clausius–Clapeyron equation. The authors find that the proposed new microphysics package shows improvement to composite liquid water path fields and cloud amounts.
Abstract
Microphysics parameterizations in large-scale models often account for subgrid variability in the calculation of process rates by integrating over assumed subgrid distributions of the input variables. The variances and covariances that define distribution width may be specified or diagnosed. The correlation ρ of cloud and rain mass mixing ratio/liquid water content (LWC) is a key input for accurate prediction of the accretion rate and a constant value is typically assumed. In this study, high-frequency aircraft measurements with a spatial resolution of ≈22 cm are used to evaluate the scaling behavior of cloud and rain LWC (q
c
and q
r
, respectively) and to demonstrate how and why covariability varies with length scale
Abstract
Microphysics parameterizations in large-scale models often account for subgrid variability in the calculation of process rates by integrating over assumed subgrid distributions of the input variables. The variances and covariances that define distribution width may be specified or diagnosed. The correlation ρ of cloud and rain mass mixing ratio/liquid water content (LWC) is a key input for accurate prediction of the accretion rate and a constant value is typically assumed. In this study, high-frequency aircraft measurements with a spatial resolution of ≈22 cm are used to evaluate the scaling behavior of cloud and rain LWC (q
c
and q
r
, respectively) and to demonstrate how and why covariability varies with length scale
