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Jasmine Rémillard and George Tselioudis

Abstract

From its location on the subtropics–midlatitude boundary, the Azores is influenced by both the subtropical high pressure and the midlatitude baroclinic storm regimes and therefore experiences a wide range of cloud structures, from fair-weather scenes to stratocumulus sheets and deep convective systems. This work combines three types of datasets to study cloud variability in the Azores: a satellite analysis of cloud regimes, a reanalysis characterization of storminess, and a 19-month field campaign that occurred on Graciosa Island. Combined analysis of the three datasets provides a detailed picture of cloud variability and the respective dynamic influences, with emphasis on low clouds that constitute a major uncertainty source in climate model simulations. The satellite cloud regime analysis shows that the Azores cloud distribution is similar to the mean global distribution and can therefore be used to evaluate cloud simulation in global models. Regime analysis of low clouds shows that stratocumulus decks occur under the influence of the Azores high pressure system, while shallow cumulus clouds are sustained by cold-air outbreaks, as revealed by their preference for postfrontal environments and northwesterly flows. An evaluation of climate model cloud regimes from phase 5 of CMIP (CMIP5) over the Azores shows that all models severely underpredict shallow cumulus clouds, while most models also underpredict the occurrence of stratocumulus cloud decks. It is demonstrated that the regime analysis can assist in the selection of case studies representing specific climatological cloud distributions. With all the tools now in place, a methodology is suggested to better understand cloud–dynamics interactions and attempt to explain and correct climate model cloud deficiencies.

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George Tselioudis and William B. Rossow

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The recent analysis of Rossow et al. used a clustering technique to derive six tropical weather states (WS) based on mesoscale cloud-type patterns and documented the spatial distribution of those WS and the modes of variability of the convective WS in the tropical western Pacific. In this study, the global tropics are separated into 30° × 30° regions, and a clustering algorithm is applied to the regional WS frequency distributions to derive the dominant modes of weather state variability (or the climate state variability) in each region. The results show that the whole tropical atmosphere oscillates between a convectively active and a convectively suppressed regime with the exception of the eastern parts of the two ocean basins, where the oscillation is between a stratocumulus and a trade cumulus regime. The dominant mode of both those oscillations is the seasonal cycle with the exception of the eastern Indian and western–central Pacific region, where El Niño frequencies dominate. The transitions between the convectively active and suppressed regimes produce longwave (LW) and shortwave (SW) top-of-atmosphere (TOA) radiative differences that are of opposite sign and of similar magnitude, being of order 20–30 W m−2 over ocean and 10–20 W m−2 over land and thus producing an overall balance in the TOA radiative budget. The precipitation differences between the convectively active and suppressed regimes are found to be of order 2.5–3 mm day−1 over ocean and 1–2.4 mm day−1 over land. Finally, the transitions between the stratocumulus and shallow cumulus regimes produce noticeable TOA SW differences of order 10–20 W m−2 and very small TOA LW and precipitation differences. The potential climate feedback implications of the regime radiation and precipitation differences are discussed.

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George Tselioudis, Yuanchong Zhang, and William B. Rossow

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A global meteorological dataset, a global satellite dataset, and a radiative transfer model are combined to map the cloud types in low, near-normal, and high sea level pressure regimes in the northern midlatitudes, and to calculate the radiative balance in those regimes. The prominent cloud feature is a background cloud field that is present most of the time and is modulated by changes in dynamic regime. It consists of a low cloud deck, which becomes optically thicker in the warm seasons over ocean and in the cold seasons over land, and a population of optically thin middle-to-high-top clouds that is mostly middle-top in the cold and mostly high-top in the warm seasons. This background cloud field is modulated by the emergence of a population of optically thick high-top clouds in the low pressure regime and by an increase in the optical thickness of the low clouds in the high pressure regime. The top-of-the-atmosphere (TOA) shortwave flux differences between dynamic regimes show that more sunlight is reflected in the low than in the high pressure regime. In January TOA shortwave flux differences between regimes range between 5 and 20 W m−2 and in July between 20 and 50 W m−2, and those differences are manifested as a net excess cooling at the earth’s surface. The TOA longwave budget shows more heat trapped in the troposphere in the low pressure than in the high pressure regime. The differences in the TOA outgoing longwave fluxes between the two extreme regimes range in all seasons between 5 and 35 W m−2 and are manifested mostly as an additional warming in the atmospheric column. The TOA total flux differences between the low and high pressure regimes change both sign and magnitude with season;in the winter an excess warming of 5–15 W m−2 is found in the low pressure regime while in all other seasons an excess cooling, which ranges between 10 and 40 W m−2, is found. Preliminary investigations with the Goddard Institute for Space Studies GCM show that changes in midlatitude dynamics with climate can produce significant radiation feedbacks.

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Christian Jakob, George Tselioudis, and Timothy Hume

Abstract

This study investigates the radiative, cloud, and thermodynamic characteristics of the atmosphere separated into objectively defined cloud regimes in the tropical western Pacific (TWP). A cluster analysis is applied to 2 yr of daytime-only data from the International Satellite Cloud Climatology Project (ISCCP) to identify four major cloud regimes in the TWP region. A variety of data collected at the Department of Energy’s Atmospheric Radiation Measurement Program (ARM) site on Manus Island is then used to identify the main characteristics of the regimes. Those include surface and top-of-the-atmosphere radiative fluxes and cloud properties derived from a suite of ground-based active remote sensors, as well as the temperature and water vapor distribution measured from radiosondes.

The major cloud regimes identified in the TWP area are two suppressed regimes—one dominated by the occurrence of mostly shallow clouds, the other by thin cirrus—as well as two convectively active regimes—one exhibiting a large coverage of optically thin cirrus clouds, the other characterized by a large coverage with optically thick clouds. All four of these TWP cloud regimes are shown to exist with varying frequency of occurrence at the ARM site at Manus. It is further shown that the detailed data available at that site can be used to characterize the radiative, cloud, and thermodynamic properties of each of the regimes, demonstrating the potential of the regime separation to facilitate the extrapolation of observations at one location to larger scales. A variety of other potential applications of the regime separation are discussed.

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William B. Rossow, Yuanchong Zhang, and George Tselioudis

Abstract

Analysis of multiple global satellite products identifies distinctive weather states of the atmosphere from the mesoscale pattern of cloud properties and quantifies the associated diabatic heating/cooling by radiative flux divergence, precipitation, and surface sensible heat flux. The results show that the forcing for the atmospheric general circulation is a very dynamic process, varying strongly at weather space–time scales, comprising relatively infrequent, strong heating events by “stormy” weather and more nearly continuous, weak cooling by “fair” weather. Such behavior undercuts the value of analyses of time-averaged energy exchanges in observations or numerical models. It is proposed that an analysis of the joint time-related variations of the global weather states and the general circulation on weather space–time scales might be used to establish useful “feedback like” relationships between cloud processes and the large-scale circulation.

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George Tselioudis, William B. Rossow, and David Rind

Abstract

The International Satellite Cloud Climatology Project (ISCCP) dataset is used to correlate variations of cloud optical thickness and cloud temperature in today's atmosphere. The analysis focuses on low clouds in order to limit the importance of changes in cloud vertical extent, particle size, and water phase. Coherent patterns of change are observed on several time and space scales. On the planetary scale, clouds in colder, higher latitudes are found to be optically thicker than clouds in warmer, lower latitudes. On the planetary scale, winter clouds are, for the most part, optically thicker than summer clouds. The logarithmic derivative of cloud optical thickness with temperature is used to describe the sign and magnitude of the optical thickness-temperature correlation. The seasonal, latitudinal, and day-to-day variations of this relation are examined for Northern Hemisphere clouds in 1984. The analysis is done separately for clouds over land and ocean. In cold continental clouds, optical thickness increase with temperature, consistent with the temperature variation of the adiabatic cloud water content. In warm continental and in almost all maritime clouds, however, optical thickness decreases with temperature. The behavior of the optical thickness-temperature relation is usually, though not always, the same whether the temperature variations are driven by seasonal, latitudinal, or day-to-day changes. Important exceptions are noted. Some explanations for the observed behavior are proposed.

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Mike Bauer, George Tselioudis, and William B. Rossow

Abstract

The NASA Modeling, Analysis, and Prediction (MAP) Climatology of Mid-Latitude Storm Area (MCMS) project is a set of tools for examining midlatitude cyclones in model-generated data. The MCMS software has two primary tasks. The first task identifies and tracks likely cyclones in sea level pressure fields. Special care is taken to minimize the known problems of this approach near steep or high topography. The second task finds the outermost closed pressure contour that uniquely surrounds each cyclone center, or collection of centers in the case of multicenter cyclones. This enclosed area is then used as a rough proxy for the domain over which a cyclone influences its immediate environment. Here the MCMS software is applied to several decades of reanalysis data. These results are shown to be consistent with the findings of a recent intercomparison of cyclone-finding methods. Besides providing details concerning cyclone storm area, the MCMS software departs from other cyclone-finding methods by providing a comprehensive record concerning every cyclone it processes. The MCMS software also provides extensive diagnostics about the actions of specific operations (filters) and adjustable parameters. The benefits of this accounting are demonstrated and discussed, as are those related to the use of cyclone storm area as a tool for climate research. MCMS datasets are available for several reanalysis products, as is the MCMS software itself, including the source code needed to generate new MCMS datasets and utilities for working with existing ones.

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George Tselioudis, William Rossow, Yuanchong Zhang, and Dimitra Konsta

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In this study, the authors apply a clustering algorithm to International Satellite Cloud Climatology Project (ISCCP) cloud optical thickness–cloud top pressure histograms in order to derive weather states (WSs) for the global domain. The cloud property distribution within each WS is examined and the geographical variability of each WS is mapped. Once the global WSs are derived, a combination of CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cloud structure retrievals is used to derive the vertical distribution of the cloud field within each WS. Finally, the dynamic environment and the radiative signature of the WSs are derived and their variability is examined. The cluster analysis produces a comprehensive description of global atmospheric conditions through the derivation of 11 WSs, each representing a distinct cloud structure characterized by the horizontal distribution of cloud optical depth and cloud top pressure. Matching those distinct WSs with cloud vertical profiles derived from CloudSat and CALIPSO retrievals shows that the ISCCP WSs exhibit unique distributions of vertical layering that correspond well to the horizontal structure of cloud properties. Matching the derived WSs with vertical velocity measurements shows a normal progression in dynamic regime when moving from the most convective to the least convective WS. Time trend analysis of the WSs shows a sharp increase of the fair-weather WS in the 1990s and a flattening of that increase in the 2000s. The fact that the fair-weather WS is the one with the lowest cloud radiative cooling capability implies that this behavior has contributed excess radiative warming to the global radiative budget during the 1990s.

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Bernard R. Lipat, Aiko Voigt, George Tselioudis, and Lorenzo M. Polvani

Abstract

Recent analyses of global climate models suggest that uncertainty in the coupling between midlatitude clouds and the atmospheric circulation contributes to uncertainty in climate sensitivity. However, the reasons behind model differences in the cloud–circulation coupling have remained unclear. Here, we use a global climate model in an idealized aquaplanet setup to show that the Southern Hemisphere climatological circulation, which in many models is biased equatorward, contributes to the model differences in the cloud–circulation coupling. For the same poleward shift of the Hadley cell (HC) edge, models with narrower climatological HCs exhibit stronger midlatitude cloud-induced shortwave warming than models with wider climatological HCs. This cloud-induced radiative warming results predominantly from a subsidence warming that decreases cloud fraction and is stronger for narrower HCs because of a larger meridional gradient in the vertical velocity. A comparison of our aquaplanet results with comprehensive climate models suggests that about half of the model uncertainty in the midlatitude cloud–circulation coupling stems from this impact of the circulation on the large-scale temperature structure of the atmosphere, and thus could be removed by improving the climatological circulation in models. This illustrates how understanding of large-scale dynamics can help reduce uncertainty in clouds and their response to climate change.

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Surabi Menon, Anthony D. Del Genio, Dorothy Koch, and George Tselioudis

Abstract

In this paper the coupling of the Goddard Institute for Space Studies (GISS) general circulation model (GCM) to an online sulfur chemistry model and source models for organic matter and sea salt that is used to estimate the aerosol indirect effect is described. The cloud droplet number concentration is diagnosed empirically from field experiment datasets over land and ocean that observe droplet number and all three aerosol types simultaneously; corrections are made for implied variations in cloud turbulence levels. The resulting cloud droplet number is used to calculate variations in droplet effective radius, which in turn allows one to predict aerosol effects on cloud optical thickness and microphysical process rates. The aerosol indirect effect is calculated by differencing the top-of-the-atmosphere net cloud radiative forcing for simulations with present-day versus preindustrial emissions. Both the first and second indirect effects are explored. The sensitivity of the results presented here to cloud parameterization assumptions that control the vertical distribution of cloud occurrence, the autoconversion rate, and the aerosol scavenging rate, each of which feeds back significantly on the model aerosol burden, are tested. The global mean aerosol indirect effect for all three aerosol types ranges from −1.55 to −4.36 W m−2 in the simulations. The results are quite sensitive to the preindustrial background aerosol burden, with low preindustrial burdens giving strong indirect effects, and to a lesser extent to the anthropogenic aerosol burden, with large burdens giving somewhat larger indirect effects. Because of this dependence on the background aerosol, model diagnostics such as albedo-particle size correlations and column cloud susceptibility, for which satellite validation products are available, are not good predictors of the resulting indirect effect.

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