ALBERT

Description: [1]  A new ensemble of climate models is becoming available and provides the basis for climate change projections. Here we show a first analysis indicating that the models in the new ensemble agree better with observations than those in older ones, and that the poorest models have been eliminated. Most models are strongly tied to their predecessors, andsome also exchange ideas and code with other models, thus supportingan earlier hypothesis that the models in the new ensemble are not independent of each other, nor independent of the earlier generation. Based on one atmosphere model, we show how statistical methods can identify similarities between model versions and complement process understanding in characterizing how and why a model has changed. We argue that the inter-dependence of models complicates the interpretation of multi model ensembles, but largely goes unnoticed.

Description: The tropical tropopause layer (TTL) is the dominant region for entry of tropospheric air into the global stratosphere. Despite significant theoretical advances and a rapidly growing archive of satellite data, important science questions related to the control of humidity and the chemical composition of air entering the stratosphere remain unanswered. Many processes are involved, including large-scale ascent, atmospheric waves, and cloud microphysics. Further progress requires better analysis of current and past observations as well as new observational campaigns in which in situ observations on both balloons and aircraft platforms are coordinated with satellite observations.

Description: [1]  We have developed a new cirrus model incorporating sectional ice microphysics from the Community Aerosol and Radiation Model for Atmospheres (CARMA) in the latest version of NCAR's Community Atmosphere Model (CAM5). Comparisons with DARDAR and 2C-ICE show that CAM5/CARMA improves cloud fraction, ice water content, and ice water path compared to the standard CAM5. Prognostic snow in CAM5/CARMA increases overall ice mass and results in a melting layer at ~4 km in the tropics that is largely absent in CAM5. Subgrid scale supersaturation following Wilson and Ballard (1999) improves ice mass and relative humidity. Increased middle and upper tropospheric condensate in CAM5/CARMA requires a reduction in low-level cloud for energy balance, resulting in a 3.1 W m -2 improvement in shortwave cloud forcing and a 3.8 W m -2 improvement in downwelling shortwave flux at the surface compared to CAM5 and CERES. Total and clear sky longwave upwelling flux at the top are improved in CAM5/CARMA by 1.0 and 2.6 W m -2 respectively. CAM has a 2–3 K cold bias at the tropical tropopause mostly from the prescribed ozone file. Correction of the prescribed ozone or nudging the CAM5/CARMA model to GEOS5-DAS meteorology yields tropical tropopause temperatures and water vapor that agree with COSMIC and MLS. CAM5 relative humidity appears to be too large resulting in a +1.5 ppmv water vapor bias at the tropical tropopause when using GEOS5-DAS meteorology. In CAM5/CARMA, 75% of the cloud ice mass originates from ice particles detrained from convection compared to 25% from in situ nucleation.

Description: [1]  A climate model (CESM-CAM5) is used to identify processes controlling Southern Ocean (30–70 °S) absorbed shortwave radiation (ASR). In response to 21st century Representative Concentration Pathway 8.5 (RCP8.5) forcing, both sea ice loss (2.6 Wm -2 ) and cloud changes (1.2 Wm -2 ) enhance ASR, but their relative importance depends on location and season. Poleward of ~55 °S, surface albedo reductions and increased cloud liquid water content (LWC) have competing effects on ASR changes. Equatorward of ~55 °S, decreased LWC enhances ASR. The 21st century cloud LWC changes result from warming and near-surface stability changes, but appear unrelated to a small (1°) poleward shift in the eddy-driven jet. In fact, 21st century ASR changes are 5x greater than ASR changes resulting from large (5°) naturally occurring jet latitude variability. More broadly, these results suggest that thermodynamics (warming and near-surface stability), not poleward jet shifts, control 21st century Southern Ocean shortwave climate feedbacks.

Description: [1]  A comprehensive General Circulation Model (GCM) is used to estimate the climate impact of aviation emissions of black carbon (BC) and sulfate (SO 4 ) aerosols. Aviation BC is found not to exert significant radiative forcing impacts, when BC nucleating efficiencies in line with observations are used. Sulfate emissions from aircraft are found to alter liquid clouds at altitudes below emission (~200 hPa); contributing to shortwave cloud brightening through enhanced liquid water path and drop number concentration in major flight corridors, particularly in the N. Atlantic. Global averaged sulfate direct and indirect effects on liquid clouds of 46 mWm −2 are larger than the warming effect of aviation induced cloudiness of 16 mWm −2 . The net result of including contrail cirrus and aerosol effects is a global averaged cooling of −21 ± 11 mWm −2 . These aerosol forcings should be considered with contrails in evaluating the total global impact of aviation on climate.

Description: Simulations by climate models are used to project the climate change expected as atmospheric greenhouse gas concentrations rise. How much will the Earth warm? Will south Asia experience stronger monsoons in the future? Will the American Southwest continue to desiccate? How soon will the Arctic become ice free? How fast and how much will sea level rise? Climate models rely on the idea that sound physical principles can be used to translate basic information, such as emissions of carbon dioxide and aerosols, into changes in the energy balance that influence the formation of clouds, which over time play a key role in shaping future climate response to the emissions.

Description: ABSTRACT [1]  Covariance between cloud and precipitation water in shallow marine boundary layer clouds is assessed using collocated satellite observations from CloudSat and the MODerate resolution Imaging Spectroradiometer (MODIS) at spatial scales typical of global models. An analytic construct is presented, which suggests that global models that do not take sub-grid scale cloud-precipitation covariance into account in their microphysical parameterizations may significantly underestimate grid mean microphysical process rates in warm clouds. The proposed framework indicates a mean bias in autoconversion rates of 129% when sub-grid scale cloud water variability is neglected and bias in accretion rates of 60% when sub-grid cloud-precipitation co-variability is neglected at a model grid resolution of 141 km. The bias in accretion rate is dependent on the significant correlation (ρ) found between cloud and precipitation, which in the global mean is found to be ρ = 0.44. The regional distribution of the process rate biases is largely governed by the spatial pattern of cloud water variance. Specific areas of low cloud water variance are found in the subtropical eastern ocean basins and the high-latitudes whereas much of the tropics display relatively larger cloud water variance. These regional distinctions in cloud water variance are associated with commensurate regionality in the process rate biases. The magnitude of the bias has a scale dependence that is governed by the spatial scaling behavior of the cloud and precipitation variances, which follow a power law scaling with exponent of 2/3 at scales below about 10 km and decreasing exponent above this length scale. While the parametric framework reduces biases in the accretion rate estimated from the grid-mean values of cloud and precipitation water, it is shown that it still under-corrects the accretion rate because it neglects the fact that the precipitation fractional area is less than the cloud fractional area and is preferentially co-located with the highest cloud water concentrations. [2]  These results imply that (1) predicting the appropriate balance of autoconversion to accretion in global models requires not only the sub-grid scale cloud water variability but also the sub-grid scale covariability of cloud and precipitation water and (2) the ability of a global model to calculate the correct regional variation in process rates depends crucially on the fidelity of that model to predict or diagnose the spatial distribution of the variance in cloud water.

Description: Cloud microphysical process rates control the amount of condensed water in clouds and impact the susceptibility of precipitation to cloud-drop number and aerosols. The relative importance of different microphysical processes in a climate model is analyzed, and the autoconversion and accretion processes are found to be critical to the condensate budget in most regions. A simple steady-state model of warm rain formation is used to illustrate that the diagnostic rain formulations typical of climate models may result in excessive contributions from autoconversion, compared to observations and large eddy simulation models with explicit bin-resolved microphysics and rain formation processes. The behavior does not appear to be caused by the bulk process rate formulations themselves, because the steady-state model with the same bulk accretion and autoconversion has reduced contributions from autoconversion. Sensitivity tests are conducted to analyze how perturbations to the precipitation microphysics for stratiform clouds impact process rates, precipitation susceptibility and aerosol–cloud interactions (ACI). With similar liquid water path, corrections for the diagnostic rain assumptions in the GCM based on the steady-state model to boost accretion indicate that the radiative effects of ACI may decrease by 20% in the GCM. Links between process rates, susceptibility and ACI are not always clear in the GCM. Better representation of the precipitation process, for example by prognosticating precipitation mass and number, may help better constrain these effects in global models with bulk microphysics schemes.

Description: A comprehensive general circulation model including ice supersaturation is used to estimate the climate impact of aviation induced contrails. The model uses a realistic aviation emissions inventory for 2006 to initiate contrails, and allows them to evolve consistently with the model hydrologic cycle. The radiative forcing from linear contrails is very sensitive to the diurnal cycle. For linear contrails, including the diurnal cycle of air traffic reduces the estimated radiative forcing by 29%, and for contrail cirrus estimates, the radiative forcing is reduced by 25%. Estimated global radiative forcing from linear contrails is 0.0031 ± 0.0005 Wm−2. The linear contrail radiative forcing is found to exhibit a strong diurnal cycle. The contrail cirrus radiative forcing is less sensitive to the diurnal cycle of flights. The estimated global radiative forcing from contrail cirrus is 0.013 ± 0.01 Wm−2. Over regions with the highest air traffic, the regional effect can be as large as 1 Wm−2.