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Andrew Gettelman

The gap between the availability of information in developed and developing countries in climate and meteorology is described and detailed. The description is based on a recent survey of scientists around the world. The information divide results from the high costs of information and lack of resources in many countries and can be compounded by language difficulties and cultural differences. This has led to the breakdown in the flow of weather and forecast data, the flow of journals to developing countries, and the flow of the results of scientific work back to these same journals from developing countries. With the increasing electronic flow of information, many countries are also limited by costly and low-bandwidth access to the Internet. Several ideas for bridging the information divide are also presented, ranging from electronic distribution of journals, to increasing capacity to deal with information, to a commitment to include all users in new strategies for delivering information.

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Hugh Morrison and Andrew Gettelman

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A new two-moment stratiform cloud microphysics scheme in a general circulation model is described. Prognostic variables include cloud droplet and cloud ice mass mixing ratios and number concentrations. The scheme treats several microphysical processes, including hydrometeor collection, condensation/evaporation, freezing, melting, and sedimentation. The activation of droplets on aerosol is physically based and coupled to a subgrid vertical velocity. Unique aspects of the scheme, relative to existing two-moment schemes developed for general circulation models, are the diagnostic treatment of rain and snow number concentration and mixing ratio and the explicit treatment of subgrid cloud water variability for calculation of the microphysical process rates.

Numerical aspects of the scheme are described in detail using idealized one-dimensional offline tests of the microphysics. Sensitivity of the scheme to time step, vertical resolution, and numerical method for diagnostic precipitation is investigated over a range of conditions. It is found that, in general, two substeps are required for numerical stability and reasonably small time truncation errors using a time step of 20 min; however, substepping is only required for the precipitation microphysical processes rather than the entire scheme. A new numerical approach for the diagnostic rain and snow produces reasonable results compared to a benchmark simulation, especially at low vertical resolution. Part II of this study details results of the scheme in single-column and global simulations, including comparison with observations.

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Andrew Gettelman and Adam H. Sobel

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This study discusses the direct diagnosis of stratosphere–troposphere exchange. The method introduced by Wei is applied to the Goddard Earth Observation System assimilated dataset. In many respects, the results generally agree with those of other studies using the same method and different datasets. However, sensitivity tests and theoretical considerations indicate that the instantaneous two-way exchange may be significantly exaggerated by the Wei method, because the method is rather sensitive to input data errors such as those that are invariably present in assimilated datasets. The method becomes somewhat better conditioned as the results are more heavily averaged, but this also reduces the method’s ability to diagnose two-way exchange. Additionally, when the flux across various surfaces is averaged over the globe and the entire year, the result implies unrealistically large imbalances in the annually averaged mass budget of the stratosphere. This could be caused by modest biases in the model used to perform the data assimilation. Since pure model simulations have an internal dynamical consistency that is lacking in assimilated datasets, the analysis appears to explain the fairly large discrepancies between the two-way fluxes obtained in studies using models and those obtained in studies using assimilated datasets. It may also explain the discrepancies between the net fluxes obtained by the Wei method and those obtained by other methods.

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Elizabeth Berry, Gerald G. Mace, and Andrew Gettelman

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Using information from the A-Train satellites, the properties and radiative effects of eastern Pacific Ocean boundary layer clouds are evaluated in the Community Atmosphere Model, version 5 (CAM5), from the summer of 2007 and 2008. The cloud microphysical properties are inferred using measurements from CloudSat and CALIPSO (CC) that are then used to calculate the broadband radiative flux profiles. Accounting appropriately for sampling differences between the measurements and the simulation, evidence of the “too few, too bright” low cloud bias is found in CAM5. Single-layer low clouds have a frequency of occurrence of 42% from CC, as compared with just 29% in CAM5, and the averaged cloud radiative kernel (CRK) for the model shows stronger cooling. For stratocumulus in particular, the cooling in the model CRK is larger by a factor of 2 relative to the observations, implying an overly sensitive tropical low cloud feedback. Differences in the day/night occurrence of stratocumulus help to explain some of the difference in the CRK. The cloud-type microphysics for liquid clouds is represented reasonably well by the model, with a tendency for smaller water paths and smaller effective radii. Overall, the occurrence and CRK have partially compensating errors such that the net cooling at the top of the atmosphere for eastern Pacific low clouds is −43 W m−2 in CAM5, as compared with −32 W m−2 from CC. The cooling effect in the model is accomplished by fewer low clouds with a narrower range of properties, as compared with more clouds with a broader range of properties in the observation-based dataset.

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Elizabeth Berry, Gerald G. Mace, and Andrew Gettelman

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The distribution of clouds and their radiative effects in the Community Atmosphere Model, version 5 (CAM5), are compared to A-Train satellite data in Southeast Asia during the summer monsoon. Cloud radiative kernels are created based on populations of observed and modeled clouds separately in order to compare the sensitivity of the TOA radiation to changes in cloud fraction. There is generally good agreement between the observation- and model-derived cloud radiative kernels for most cloud types, meaning that the clouds in the model are heating and cooling like clouds in nature. Cloud radiative effects are assessed by multiplying the cloud radiative kernel by the cloud fraction histogram. For ice clouds in particular, there is good agreement between the model and observations, with optically thin cirrus producing a moderate warming effect and cirrostratus producing a slight cooling effect, on average. Consistent with observations, the model also shows that the median value of the ice water path (IWP) distribution, rather than the mean, is a more representative measure of the ice clouds that are responsible for heating. In addition, in both observations and the model, it is cirrus clouds with an IWP of 20 g m−2 that have the largest warming effect in this region, given their radiative heating and frequency of occurrence.

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Jason M. English, Andrew Gettelman, and Gina R. Henderson

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Radiative fluxes are critical for understanding the energy budget of the Arctic region, where the climate has been changing rapidly and is projected to continue to change. This work investigates causes of present-day biases and future projections of top-of-atmosphere (TOA) Arctic radiative fluxes in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Compared to Clouds and the Earth’s Radiant Energy System Energy Balanced and Filled (CERES-EBAF), CMIP5 net TOA downward shortwave (SW) flux biases are larger than outgoing longwave radiation (OLR) biases. The primary contributions to modeled TOA SW flux biases are biases in cloud amount and snow cover extent compared to the GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP) and the newly developed Making Earth System Data Records for Use in Research Environments (MEaSUREs) dataset, respectively (with most models predicting insufficient cloud amount and snow cover in the Arctic), and biases with sea ice albedo. Future projections (2081–90) with representative concentration pathway 8.5 (RCP8.5) simulations suggest increasing net TOA downward SW fluxes (+8 W m−2) over the Arctic basin due to a decrease of surface albedo from melting snow and ice, and increasing OLR (+6 W m−2) due to an increase in surface temperatures. The largest contribution to future Arctic net TOA downward SW flux increases is declining sea ice area, followed by declining snow cover area on land, reductions to sea ice albedo, and reductions to snow albedo on land. Cloud amount is not projected to change significantly. These results suggest the importance of accurately representing both the surface area and albedos of sea ice and snow cover as well as cloud amount in order to accurately represent TOA radiative fluxes for the present-day climate and future projections.

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Andrew Gettelman, Eric J. Fetzer, Annmarie Eldering, and Fredrick W. Irion

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Satellite data from the Atmospheric Infrared Sounder (AIRS) is analyzed to examine regions of the upper troposphere that are supersaturated: where the relative humidity (RH) is greater than 100%. AIRS data compare well to other in situ and satellite observations of RH and provide daily global coverage up to 200 hPa, though satellite observations of supersaturation are highly uncertain. The climatology of supersaturation is analyzed statistically to understand where supersaturation occurs and how frequently. Supersaturation occurs in humid regions of the upper tropical tropopause near convection 10%–20% of the time at 200 hPa. Supersaturation is very frequent in the extratropical upper troposphere, occurring 20%–40% of the time, and over 50% of the time in storm track regions below the tropopause. The annual cycle of supersaturation is consistent for the ∼2.5 yr of data analyzed. More supersaturation is seen in the Southern Hemisphere midlatitudes, which may be attributed to higher temperature variance.

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Trude Eidhammer, Hugh Morrison, David Mitchell, Andrew Gettelman, and Ehsan Erfani

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This paper describes a new approach for representing ice microphysics in climate models. In contrast with most previous schemes, this approach does not include separate categories for cloud and precipitating ice and instead uses a single two-moment category to represent all solid hydrometeors. Thus, there is no need for an ice “autoconversion” size threshold parameter, which has a critical impact on simulated climate in the Community Atmosphere Model (CAM5) yet is poorly constrained by theory or observations. Further, in the new treatment, all ice microphysical processes and parameters, including ice effective radius and mean fall speed, are formulated self-consistently and flexibly based on empirical ice particle mass–size and projected area–size relationships. This means that the scheme can represent the physical coupling between bulk particle density, mean fall speed, and effective radius, which is not possible in current schemes. Two different methods for specifying these relationships based on observations are proposed. The new scheme is tested in global simulations using CAM5. Differences in simulations using the two methods for specifying the mass– and projected area–size relationships, particularly the cloud radiative forcing, are attributable mainly to the effects on mean ice particle fall speed, impacting sedimentation and ice water path. With some tuning of parameters involved in calculating homogeneous freezing it produces a similar climate compared to the simulations using the original CAM5 microphysics. Thus, it can produce a comparable climate while improving the physical basis and self-consistency of ice particle properties and parameters.

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Andrew Heymsfield, Martina Krämer, Norman B. Wood, Andrew Gettelman, Paul R. Field, and Guosheng Liu

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Cloud ice microphysical properties measured or estimated from in situ aircraft observations are compared with global climate models and satellite active remote sensor retrievals. Two large datasets, with direct measurements of the ice water content (IWC) and encompassing data from polar to tropical regions, are combined to yield a large database of in situ measurements. The intention of this study is to identify strengths and weaknesses of the various methods used to derive ice cloud microphysical properties. The in situ data are measured with total water hygrometers, condensed water probes, and particle spectrometers. Data from polar, midlatitude, and tropical locations are included. The satellite data are retrieved from CloudSat/CALIPSO [the CloudSat Ice Cloud Property Product (2C-ICE) and 2C-SNOW-PROFILE] and Global Precipitation Measurement (GPM) Level2A. Although the 2C-ICE retrieval is for IWC, a method to use the IWC to get snowfall rates S is developed. The GPM retrievals are for snowfall rate only. Model results are derived using the Community Atmosphere Model (CAM5) and the Met Office Unified Model [Global Atmosphere 7 (GA7)]. The retrievals and model results are related to the in situ observations using temperature and are partitioned by geographical region. Specific variables compared between the in situ observations, models, and retrievals are the IWC and S. Satellite-retrieved IWCs are reasonably close in value to the in situ observations, whereas the models’ values are relatively low by comparison. Differences between the in situ IWCs and those from the other methods are compounded when S is considered, leading to model snowfall rates that are considerably lower than those derived from the in situ data. Anomalous trends with temperature are noted in some instances.

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Peter A. Bogenschutz, Andrew Gettelman, Hugh Morrison, Vincent E. Larson, Cheryl Craig, and David P. Schanen

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This paper describes climate simulations of the Community Atmosphere Model, version 5 (CAM5), coupled with a higher-order turbulence closure known as Cloud Layers Unified by Binormals (CLUBB). CLUBB is a unified parameterization of the planetary boundary layer (PBL) and shallow convection that is centered around a trivariate probability density function (PDF) and replaces the conventional PBL, shallow convection, and cloud macrophysics schemes in CAM5. CAM–CLUBB improves many aspects of the base state climate compared to CAM5. Chief among them is the transition of stratocumulus to trade wind cumulus regions in the subtropical oceans. In these regions, CAM–CLUBB provides a much more gradual transition that is in better agreement with observational analysis compared to CAM5, which is too abrupt. The improvement seen in CAM–CLUBB can be largely attributed to the gradual evolution of the simulated turbulence, which is in part a result of the unified nature of the parameterization, and to the general improved representation of shallow cumulus clouds compared to CAM5. In addition, there are large differences in the representation and structure of marine boundary layer clouds between CAM–CLUBB and CAM5. CAM–CLUBB is also shown to be more robust, in terms of boundary layer clouds, to changes in vertical resolution for global simulations in a preliminary test.

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