Brian Medeiros

Exposing global cloud biases in the Community Atmosphere Model (CAM) using satellite observations and their corresponding instrument simulators

AbstractSatellite observations and their corresponding instrument simulators are used to document global cloud biases in the Community Atmosphere Model (CAM) versions 4 and 5. The model–observation comparisons show that, despite having nearly identical cloud radiative forcing, CAM5 has a much more realistic representation of cloud properties than CAM4. In particular, CAM5 exhibits substantial improvement in three long-standing climate model cloud biases: 1) the underestimation of total cloud, 2) the overestimation of optically thick cloud, and 3) the underestimation of midlevel cloud. While the increased total cloud and decreased optically thick cloud in CAM5 result from improved physical process representation, the increased midlevel cloud in CAM5 results from the addition of radiatively active snow. Despite these improvements, both CAM versions have cloud deficiencies. Of particular concern, both models exhibit large but differing biases in the subtropical marine boundary layer cloud regimes that are kn...

Aquaplanets, Climate Sensitivity, and Low Clouds

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, ...

Global Climate Impacts of Fixing the Southern Ocean Shortwave Radiation Bias in the Community Earth System Model (CESM)

AbstractA large, long-standing, and pervasive climate model bias is excessive absorbed shortwave radiation (ASR) over the midlatitude oceans, especially the Southern Ocean. This study investigates both the underlying mechanisms for and climate impacts of this bias within the Community Earth System Model, version 1, with the Community Atmosphere Model, version 5 [CESM1(CAM5)]. Excessive Southern Ocean ASR in CESM1(CAM5) results in part because low-level clouds contain insufficient amounts of supercooled liquid. In a present-day atmosphere-only run, an observationally motivated modification to the shallow convection detrainment increases supercooled cloud liquid, brightens low-level clouds, and substantially reduces the Southern Ocean ASR bias. Tuning to maintain global energy balance enables reduction of a compensating tropical ASR bias. In the resulting preindustrial fully coupled run with a brighter Southern Ocean and dimmer tropics, the Southern Ocean cools and the tropics warm. As a result of the enhan...

The Transpose-AMIP II Experiment and Its Application to the Understanding of Southern Ocean Cloud Biases in Climate Models

AbstractThe Transpose-Atmospheric Model Intercomparison Project (AMIP) is an international model intercomparison project in which climate models are run in “weather forecast mode.” The Transpose-AMIP II experiment is run alongside phase 5 of the Coupled Model Intercomparison Project (CMIP5) and allows processes operating in climate models to be evaluated, and the origin of climatological biases to be explored, by examining the evolution of the model from a state in which the large-scale dynamics, temperature, and humidity structures are constrained through use of common analyses.The Transpose-AMIP II experimental design is presented. The project requests participants to submit a comprehensive set of diagnostics to enable detailed investigation of the models to be performed. An example of the type of analysis that may be undertaken using these diagnostics is illustrated through a study of the development of cloud biases over the Southern Ocean, a region that is problematic for many models. Several models s...

What controls the mean depth of the PBL

The depth of the planetary boundary layer (PBL) is a climatologically important quantity that has received little attention on regional to global scales. Here a 10-yr climatology of PBL depth from the University of California, Los Angeles (UCLA) atmospheric GCM is analyzed using the PBL mass budget. Based on the dominant physical processes, several PBL regimes are identified. These regimes tend to exhibit large-scale geographic organization. Locally generated buoyancy fluxes and static stability control PBL depth nearly everywhere, though convective mass flux has a large influence at tropical marine locations. Virtually all geographical variability in PBL depth can be linearly related to these quantities. While dry convective boundary layers dominate over land, stratocumulus-topped boundary layers are most common over ocean. This division of regimes leads to a dramatic land–sea contrast in PBL depth. Diurnal effects keep mean PBL depth over land shallow despite large daytime surface fluxes. The contrast arises because the large daily exchange of heat and mass between the PBL and free atmosphere over land is not present over the ocean, where mixing is accomplished by turbulent entrainment. Consistent treatment of remnant air from the deep, daytime PBL is necessary for proper representation of this diurnal behavior over land. Many locations exhibit seasonal shifts in PBL regime related to changes in PBL clouds. These shifts are controlled by seasonal variations in buoyancy flux and static stability.

A Characterization of the Present-Day Arctic Atmosphere in CCSM4

Simulation of key features of the Arctic atmosphere in the Community Climate System Model, version 4 (CCSM4) is evaluated against observational and reanalysis datasets for the present-day (1981‐2005). Surface air temperature, sea level pressure, cloud cover and phase, precipitation and evaporation, the atmospheric energy budget, and lower-tropospheric stability are evaluated. Simulated surface air temperatures are found to be slightly too cold when compared with the 40-yr ECMWF Re-Analysis (ERA-40). Spatial patterns and temporal variability are well simulated. Evaluation of the sea level pressure demonstrates some large biases, most noticeably an under simulation of the Beaufort High during spring and autumn. Monthly Arctic-wide biases of up to 13 mb are reported.Cloud cover is underpredicted for all but summermonths, and cloud phase is demonstrated to be different from observations. Despite low cloud cover, simulated all-sky liquid water pathsaretoohigh,whileicewaterpathwasgenerallytoolow.Precipitationisfoundtobeexcessiveovermuch oftheArcticcomparedtoERA-40andtheGlobalPrecipitation ClimatologyProject(GPCP) estimates.With some exceptions, evaporation is well captured by CCSM4, resulting in P 2 E estimates that are too high. CCSM4 energy budget terms show promising agreement with estimates from several sources. The most noticeable exception to this is the top of the atmosphere (TOA) fluxes that are found to be too low while surface fluxes are found to be too high during summer months. Finally, the lower troposphere is found to be too stable when compared to ERA-40 during all times of year but particularly during spring and summer months.

Using aquaplanets to understand the robust responses of comprehensive climate models to forcing

Idealized climate change experiments using fixed sea-surface temperature are investigated to determine whether zonally symmetric aquaplanet configurations are useful for understanding climate feedbacks in more realistic configurations. The aquaplanets capture many of the robust responses of the large-scale circulation and hydrologic cycle to both warming the sea-surface temperature and quadrupling atmospheric CO2. The cloud response to both perturbations varies across models in both Earth-like and aquaplanet configurations, and this spread arises primarily from regions of large-scale subsidence. Most models produce a consistent cloud change across the subsidence regimes, and the feedback in trade-wind cumulus regions dominates the tropical response. It is shown that these trade-wind regions have similar cloud feedback in Earth-like and aquaplanet warming experiments. The tropical average cloud feedback of the Earth-like experiment is captured by five of eight aquaplanets, and the three outliers are investigated to understand the discrepancy. In two models, the discrepancy is due to warming induced dissipation of stratocumulus decks in the Earth-like configuration which are not represented in the aquaplanet. One model shows a circulation response in the aquaplanet experiment accompanied by a cloud response that differs from the Earth-like configuration. Quadrupling atmospheric CO2 in aquaplanets produces slightly greater adjusted forcing than in Earth-like configurations, showing that land-surface effects dampen the adjusted forcing. The analysis demonstrates how aquaplanets, as part of a model hierarchy, help elucidate robust aspects of climate change and develop understanding of the processes underlying them.

Mixed-phase clouds cause climate model biases in Arctic wintertime temperature inversions

Temperature inversions are a common feature of the Arctic wintertime boundary layer. They have important impacts on both radiative and turbulent heat fluxes and partly determine local climate-change feedbacks. Understanding the spread in inversion strength modelled by current global climate models is therefore an important step in better understanding Arctic climate and its present and future changes. Here, we show how the formation of Arctic air masses leads to the emergence of a cloudy and a clear state of the Arctic winter boundary layer. In the cloudy state, cloud liquid water is present, little to no surface radiative cooling occurs and inversions are elevated and relatively weak, whereas surface radiative cooling leads to strong surface-based temperature inversions in the clear state. Comparing model output to observations, we find that most climate models lack a realistic representation of the cloudy state. An idealised single-column model experiment of the formation of Arctic air reveals that this bias is linked to inadequate mixed-phase cloud microphysics, whereas turbulent and conductive heat fluxes control the strength of inversions within the clear state.

Thermodynamic control of anvil cloud amount

Significance Assessing the response of clouds to global warming remains a challenge of climate science. Past research has elucidated what controls the height and temperature of high-level anvil clouds, but the factors that control their horizontal extent remained uncertain. We show that the anvil cloud amount is expected to shrink as the climate warms or when convection becomes more clustered, due to a mechanism rooted in basic energetic and thermodynamic properties of the atmosphere. It is supported by three climate models and consistent with results from a cloud-resolving model and observations. We thus believe that this mechanism is robust and that it adds a new piece to understanding how clouds respond to climate warming. General circulation models show that as the surface temperature increases, the convective anvil clouds shrink. By analyzing radiative–convective equilibrium simulations, we show that this behavior is rooted in basic energetic and thermodynamic properties of the atmosphere: As the climate warms, the clouds rise and remain at nearly the same temperature, but find themselves in a more stable atmosphere; this enhanced stability reduces the convective outflow in the upper troposphere and decreases the anvil cloud fraction. By warming the troposphere and increasing the upper-tropospheric stability, the clustering of deep convection also reduces the convective outflow and the anvil cloud fraction. When clouds are radiatively active, this robust coupling between temperature, high clouds, and circulation exerts a positive feedback on convective aggregation and favors the maintenance of strongly aggregated atmospheric states at high temperatures. This stability iris mechanism likely contributes to the narrowing of rainy areas as the climate warms. Whether or not it influences climate sensitivity requires further investigation.

On the Correspondence between Mean Forecast Errors and Climate Errors in CMIP5 Models

AbstractThe present study examines the correspondence between short- and long-term systematic errors in five atmospheric models by comparing the 16 five-day hindcast ensembles from the Transpose Atmospheric Model Intercomparison Project II (Transpose-AMIP II) for July–August 2009 (short term) to the climate simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and AMIP for the June–August mean conditions of the years of 1979–2008 (long term). Because the short-term hindcasts were conducted with identical climate models used in the CMIP5/AMIP simulations, one can diagnose over what time scale systematic errors in these climate simulations develop, thus yielding insights into their origin through a seamless modeling approach.The analysis suggests that most systematic errors of precipitation, clouds, and radiation processes in the long-term climate runs are present by day 5 in ensemble average hindcasts in all models. Errors typically saturate after few days of hindcasts with amplitud...