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David M. Romps and Andrew M. Vogelmann

Abstract

The two-dimensional (2D) size distribution of clouds in the horizontal plane plays a central role in the calculation of cloud cover, cloud radiative forcing, convective entrainment rates, and the likelihood of precipitation. Here, a simple method is proposed for calculating the area-weighted mean cloud size and for approximating the 2D size distribution from the 1D cloud-chord lengths measured by aircraft and vertically pointing lidar and radar. This simple method (which is exact for square clouds) compares favorably against the inverse Abel transform (which is exact for circular clouds) in the context of theoretical size distributions. Both methods also perform well when used to predict the size distribution of real clouds from a Landsat scene. When applied to a large number of Landsat scenes, the simple method is able to accurately estimate the mean cloud size. As a demonstration, the methods are applied to aircraft measurements of shallow cumuli during the Routine ARM Aerial Facility (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) campaign, which then allow for an estimate of the true area-weighted mean cloud size.

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Johannes Mülmenstädt, Dan Lubin, Lynn M. Russell, and Andrew M. Vogelmann

Abstract

Long time series of Arctic atmospheric measurements are assembled into meteorological categories that can serve as test cases for climate model evaluation. The meteorological categories are established by applying an objective k-means clustering algorithm to 11 years of standard surface-meteorological observations collected from 1 January 2000 to 31 December 2010 at the North Slope of Alaska (NSA) site of the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM). Four meteorological categories emerge. These meteorological categories constitute the first classification by meteorological regime of a long time series of Arctic meteorological conditions. The synoptic-scale patterns associated with each category, which include well-known synoptic features such as the Aleutian low and Beaufort Sea high, are used to explain the conditions at the NSA site. Cloud properties, which are not used as inputs to the k-means clustering, are found to differ significantly between the regimes and are also well explained by the synoptic-scale influences in each regime. Since the data available at the ARM NSA site include a wealth of cloud observations, this classification is well suited for model–observation comparison studies. Each category comprises an ensemble of test cases covering a representative range in variables describing atmospheric structure, moisture content, and cloud properties. This classification is offered as a complement to standard case-study evaluation of climate model parameterizations, in which models are compared against limited realizations of the Earth–atmosphere system (e.g., from detailed aircraft measurements).

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Ryan C. Scott, Dan Lubin, Andrew M. Vogelmann, and Seiji Kato

Abstract

Clouds are an essential parameter of the surface energy budget influencing the West Antarctic Ice Sheet (WAIS) response to atmospheric warming and net contribution to global sea level rise. A 4-yr record of NASA A-Train cloud observations is combined with surface radiation measurements to quantify the WAIS radiation budget and constrain the three-dimensional occurrence frequency, thermodynamic phase partitioning, and surface radiative effect of clouds over West Antarctica (WA). The skill of satellite-modeled radiative fluxes is confirmed through evaluation against measurements at four Antarctic sites (WAIS Divide ice camp and Neumayer, Syowa, and Concordia stations). Owing to perennial high-albedo snow and ice cover, cloud infrared emission dominates over cloud solar reflection and absorption leading to a positive net all-wave cloud radiative effect (CRE) at the surface, with all monthly means and 99.15% of instantaneous CRE values exceeding zero. The annual-mean CRE at the WAIS surface is 34 W m−2, representing a significant cloud-induced warming of the ice sheet. Low-level liquid-containing clouds, including thin liquid water clouds implicated in radiative contributions to surface melting, are widespread and most frequent in WA during the austral summer. In summer, clouds warm the WAIS by 26 W m−2, on average, despite maximum offsetting shortwave CRE. Glaciated cloud systems are strongly linked to orographic forcing, with maximum incidence on the WAIS continuing downstream along the Transantarctic Mountains.

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Michael P. Jensen, Andrew M. Vogelmann, William D. Collins, Guang J. Zhang, and Edward P. Luke

Abstract

To aid in understanding the role that marine boundary layer (MBL) clouds play in climate and assist in improving their representations in general circulation models (GCMs), their long-term microphysical and macroscale characteristics are quantified using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the National Aeronautics and Space Administration’s (NASA’s) Terra satellite. Six years of MODIS pixel-level cloud products are used from oceanic study regions off the west coasts of California, Peru, the Canary Islands, Angola, and Australia where these cloud types are common. Characterizations are given for their organization (macroscale structure), the associated microphysical properties, and the seasonal dependencies of their variations for scales consistent with the size of a GCM grid box (300 km × 300 km). MBL mesoscale structure is quantified using effective cloud diameter CD, which is introduced here as a simplified measure of bulk cloud organization; it is straightforward to compute and provides descriptive information beyond that offered by cloud fraction. The interrelationships of these characteristics are explored while considering the influences of the MBL state, such as the occurrence of drizzle.

Several commonalities emerge for the five study regions. MBL clouds contain the best natural examples of plane-parallel clouds, but overcast clouds occur in only about 25% of the scenes, which emphasizes the importance of representing broken MBL cloud fields in climate models (that are subgrid scale). During the peak months of cloud occurrence, mesoscale organization (larger CD) increases such that the fractions of scenes characterized as “overcast” and “clumped” increase at the expense of the “scattered” scenes. Cloud liquid water path and visible optical depth usually trend strongly with CD, with the largest values occurring for scenes that are drizzling. However, considerable interregional differences exist in these trends, suggesting that different regression functionalities exist for each region. For peak versus off-peak months, the fraction of drizzling scenes (as a function of CD) are similar for California and Angola, which suggests that a single probability distribution function might be used for their drizzle occurrence in climate models. The patterns are strikingly opposite for Peru and Australia; thus, the contrasts among regions may offer a test bed for model simulations of MBL drizzle occurrence.

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Kwinten Van Weverberg, Andrew M. Vogelmann, Hugh Morrison, and Jason A. Milbrandt

Abstract

This paper investigates the level of complexity that is needed within bulk microphysics schemes to represent the essential features associated with deep convection. To do so, the sensitivity of surface precipitation is evaluated in two-dimensional idealized squall-line simulations with respect to the level of complexity in the bulk microphysics schemes of H. Morrison et al. and of J. A. Milbrandt and M. K. Yau. Factors examined include the number of predicted moments for each of the precipitating hydrometeors, the number and nature of ice categories, and the conversion term formulations. First, it is shown that simulations of surface precipitation and cold pools are not only a two-moment representation of rain, as suggested by previous research, but also by two-moment representations for all precipitating hydrometeors. Cold pools weakened when both rain and graupel number concentrations were predicted, because size sorting led to larger graupel particles that melted into larger raindrops and caused less evaporative cooling. Second, surface precipitation was found to be less sensitive to the nature of the rimed ice species (hail or graupel). Production of hail in experiments including both graupel and hail strongly depends on an unphysical threshold that converts small hail back to graupel, indicating the need for a more physical treatment of the graupel-to-hail conversion. Third, it was shown that the differences in precipitation extremes between the two-moment microphysics schemes are mainly related to the treatment of drop breakup. It was also shown that, although the H. Morrison et al. scheme is dominated by deposition growth and low precipitation efficiency, the J. A. Milbrandt and M. K. Yau scheme is dominated by riming processes and high precipitation efficiency.

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Guang J. Zhang, Andrew M. Vogelmann, Michael P. Jensen, William D. Collins, and Edward P. Luke

Abstract

This study examines 6 yr of cloud properties observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Terra satellite in five prominent marine boundary layer (MBL) cloud regions (California, Peru, Canary, Angola, and Australia) and investigates their relationships with near-surface meteorological parameters obtained from NCEP reanalyses. About 62 000 independent scenes are used to examine the instantaneous relationships between cloud properties and meteorological parameters that may be used for global climate model (GCM) diagnostics and parameterization. Cloud liquid water path (LWP) generally increases with lower-tropospheric stability (LTS) and lifting condensation level (LCL), whereas cloud drizzle frequency is favored by weak LTS and negligible cold air advection. Cloud fraction (CF) depends strongly on variations in LTS, and to a lesser extent on surface air temperature advection and LCL, although the relationships vary from region to region. The authors propose capturing the effects of these three parameters on CF via their linear combination in terms of a single parameter, the effective lower-tropospheric stability (eLTS). Results indicate that eLTS offers a marked improvement over LTS alone in explaining the median CF variations within the different study regions. A parameterization of CF in terms of eLTS is provided, which produces results that are improved over those of Klein and Hartmann’s LTS-only parameterization. However, the new parameterization may not predict the observed variability correctly, and the authors propose a method that might address this shortcoming via a statistical approach.

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William I. Gustafson Jr, Andrew M. Vogelmann, Zhijin Li, Xiaoping Cheng, Kyle K. Dumas, Satoshi Endo, Karen L. Johnson, Bhargavi Krishna, Tami Fairless, and Heng Xiao

Abstract

The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility recently initiated the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) activity focused on shallow convection at ARM’s Southern Great Plains (SGP) atmospheric observatory in Oklahoma. LASSO is designed to overcome an oft-shared difficulty of bridging the gap from point-based measurements to scales relevant for model parameterization development, and it provides an approach to add value to observations through modeling. LASSO is envisioned to be useful to modelers, theoreticians, and observationalists needing information relevant to cloud processes. LASSO does so by combining a suite of observations, LES inputs and outputs, diagnostics, and skill scores into data bundles that are freely available, and by simplifying user access to the data to speed scientific inquiry. The combination of relevant observations with observationally constrained LES output provides detail that gives context to the observations by showing physically consistent connections between processes based on the simulated state. A unique approach for LASSO is the generation of a library of cases for days with shallow convection combined with an ensemble of LES for each case. The library enables researchers to move beyond the single-case-study approach typical of LES research. The ensemble members are produced using a selection of different large-scale forcing sources and spatial scales. Since large-scale forcing is one of the most uncertain aspects of generating the LES, the ensemble informs users about potential uncertainty for each date and increases the probability of having an accurate forcing for each case.

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Dan Lubin, Damao Zhang, Israel Silber, Ryan C. Scott, Petros Kalogeras, Alessandro Battaglia, David H. Bromwich, Maria Cadeddu, Edwin Eloranta, Ann Fridlind, Amanda Frossard, Keith M. Hines, Stefan Kneifel, W. Richard Leaitch, Wuyin Lin, Julien Nicolas, Heath Powers, Patricia K. Quinn, Penny Rowe, Lynn M. Russell, Sangeeta Sharma, Johannes Verlinde, and Andrew M. Vogelmann

Abstract

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) performed comprehensive meteorological and aerosol measurements and ground-based atmospheric remote sensing at two Antarctic stations using the most advanced instrumentation available. A suite of cloud research radars, lidars, spectral and broadband radiometers, aerosol chemical and microphysical sampling equipment, and meteorological instrumentation was deployed at McMurdo Station on Ross Island from December 2015 through December 2016. A smaller suite of radiometers and meteorological equipment, including radiosondes optimized for surface energy budget measurement, was deployed on the West Antarctic Ice Sheet between 4 December 2015 and 17 January 2016. AWARE provided Antarctic atmospheric data comparable to several well-instrumented high Arctic sites that have operated for many years and that reveal numerous contrasts with the Arctic in aerosol and cloud microphysical properties. These include persistent differences in liquid cloud occurrence, cloud height, and cloud thickness. Antarctic aerosol properties are also quite different from the Arctic in both seasonal cycle and composition, due to the continent’s isolation from lower latitudes by Southern Ocean storm tracks. Antarctic aerosol number and mass concentrations are not only non-negligible but perhaps play a more important role than previously recognized because of the higher sensitivities of clouds at the very low concentrations caused by the large-scale dynamical isolation. Antarctic aerosol chemical composition, particularly organic components, has implications for local cloud microphysics. The AWARE dataset, fully available online in the ARM Program data archive, offers numerous case studies for unique and rigorous evaluation of mixed-phase cloud parameterization in climate models.

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Andrew M. Vogelmann, Greg M. McFarquhar, John A. Ogren, David D. Turner, Jennifer M. Comstock, Graham Feingold, Charles N. Long, Haflidi H. Jonsson, Anthony Bucholtz, Don R. Collins, Glenn S. Diskin, Hermann Gerber, R. Paul Lawson, Roy K. Woods, Elisabeth Andrews, Hee-Jung Yang, J. Christine Chiu, Daniel Hartsock, John M. Hubbe, Chaomei Lo, Alexander Marshak, Justin W. Monroe, Sally A. McFarlane, Beat Schmid, Jason M. Tomlinson, and Tami Toto

A first-of-a-kind, extended-term cloud aircraft campaign was conducted to obtain an in situ statistical characterization of continental boundary layer clouds needed to investigate cloud processes and refine retrieval algorithms. Coordinated by the Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF), the Routine AAF Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign operated over the ARM Southern Great Plains (SGP) site from 22 January to 30 June 2009, collecting 260 h of data during 59 research flights. A comprehensive payload aboard the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft measured cloud microphysics, solar and thermal radiation, physical aerosol properties, and atmospheric state parameters. Proximity to the SGP's extensive complement of surface measurements provides ancillary data that support modeling studies and facilitates evaluation of a variety of surface retrieval algorithms. The five-month duration enabled sampling a range of conditions associated with the seasonal transition from winter to summer. Although about twothirds of the flights during which clouds were sampled occurred in May and June, boundary layer cloud fields were sampled under a variety of environmental and aerosol conditions, with about 77% of the cloud flights occurring in cumulus and stratocumulus. Preliminary analyses illustrate use of these data to analyze aerosol– cloud relationships, characterize the horizontal variability of cloud radiative impacts, and evaluate surface-based retrievals. We discuss how an extended-term campaign requires a simplified operating paradigm that is different from that used for typical, short-term, intensive aircraft field programs.

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John H. Seinfeld, Gregory R. Carmichael, Richard Arimoto, William C. Conant, Frederick J. Brechtel, Timothy S. Bates, Thomas A. Cahill, Antony D. Clarke, Sarah J. Doherty, Piotr J. Flatau, Barry J. Huebert, Jiyoung Kim, Krzysztof M. Markowicz, Patricia K. Quinn, Lynn M. Russell, Philip B. Russell, Atsushi Shimizu, Yohei Shinozuka, Chul H. Song, Youhua Tang, Itsushi Uno, Andrew M. Vogelmann, Rodney J. Weber, Jung-Hun Woo, and Xiao Y. Zhang

Although continental-scale plumes of Asian dust and pollution reduce the amount of solar radiation reaching the earth's surface and perturb the chemistry of the atmosphere, our ability to quantify these effects has been limited by a lack of critical observations, particularly of layers above the surface. Comprehensive surface, airborne, shipboard, and satellite measurements of Asian aerosol chemical composition, size, optical properties, and radiative impacts were performed during the Asian Pacific Regional Aerosol Characterization Experiment (ACE-Asia) study. Measurements within a massive Chinese dust storm at numerous widely spaced sampling locations revealed the highly complex structure of the atmosphere, in which layers of dust, urban pollution, and biomass- burning smoke may be transported long distances as distinct entities or mixed together. The data allow a first-time assessment of the regional climatic and atmospheric chemical effects of a continental-scale mixture of dust and pollution. Our results show that radiative flux reductions during such episodes are sufficient to cause regional climate change.

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