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Amy Solomon, Matthew D. Shupe, and Nathaniel B. Miller

Abstract

Regional model simulations of the 10–13 July 2012 extreme melt event over the Greenland Ice Sheet (GIS) are used to investigate how low-level liquid-bearing clouds impact surface energy fluxes, and therefore the energy available for melt. A sensitivity study in which the radiation code is modified so that cloud liquid and ice do not emit, absorb, or reflect radiation is used to identify cloud impacts beyond the cloud radiative effect. It is found that Arctic mixed-phase stratocumuli are not produced in the sensitivity experiment, highlighting that cloud radiative fluxes are required to maintain the clouds. A number of feedbacks are found that damp the warming effect of the clouds. Thin mixed-phase clouds increase the downward longwave fluxes by 100 W m−2, but upward daytime surface longwave fluxes increase by 20 W m−2 (60 W m−2 at night) and net shortwave fluxes decrease by 40 W m−2 (partially due to a 0.05 increase in surface albedo), leaving only 40 W m−2 available for melt. This 40 W m−2 is distributed between the turbulent and conductive ground fluxes, so it is only at times of weak turbulent fluxes (i.e., at night or during melt) that this energy goes into the conductive ground flux, providing energy for melt. From these results it is concluded that it is the integrated impact of the clouds over the diurnal cycle (the preconditioning of the snowpack by the clouds at night) that made melt possible during this 3-day period. These findings are extended to understand the pattern of melt observed over the GIS.

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Elin A. McIlhattan, Tristan S. L’Ecuyer, and Nathaniel B. Miller

Abstract

Clouds are a key regulator of Earth’s surface energy balance. The presence or absence of clouds, along with their macroscale and microscale characteristics, is the primary factor modulating the amount of radiation incident on the surface. Recent observational studies in the Arctic highlight the ubiquity of supercooled liquid-containing clouds (LCCs) and their disproportionately large impact on surface melt. Global climate models (GCMs) do not simulate enough Arctic LCCs compared to observations, and thus fail to represent the surface energy balance correctly. This work utilizes spaceborne observations from NASA’s A-Train satellite constellation to explore physical processes behind LCCs and surface energy biases in the Community Earth System Model Large Ensemble (CESM-LE) project output. On average CESM-LE underestimates LCC frequency by ~18% over the Arctic, resulting in a ~20 W m−2 bias in downwelling longwave radiation (DLR) over the ~18 × 106 km2 area examined. Collocated observations of falling snow and LCCs indicate that Arctic LCCs produce precipitation ~13% of the time. Conversely, CESM-LE generates snow in ~70% of LCCs. This result indicates that the Wegener–Bergeron–Findeisen (WBF) process—the growth of ice at the expense of supercooled liquid—may be too strong in the model, causing ice to scavenge polar supercooled cloud liquid too efficiently. Ground-based observations from Summit Station, Greenland, provide further evidence of these biases on a more local scale, suggesting that CESM-LE overestimates snow frequency in LCCs by ~52% at the center of the ice sheet leading to ~21% too few LCCs and ~24 W m−2 too little DLR.

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Michael R. Gallagher, Matthew D. Shupe, and Nathaniel B. Miller

Abstract

The Greenland Ice Sheet (GrIS) plays a crucial role in the Arctic climate, and atmospheric conditions are the primary modifier of mass balance. This analysis establishes the relationship between large-scale atmospheric circulation and principal determinants of GrIS mass balance: moisture, cloud properties, radiative forcing, and temperature. Using self-organizing maps (SOMs), observations from the Integrated Characterization of Energy, Clouds, Atmospheric State, and Precipitation at Summit (ICECAPS) project are categorized by daily sea level pressure (SLP) gradient. The results describe in detail how southerly, northerly, and zonal circulation regimes impact observations at Summit Station, Greenland. This southerly regime is linked to large anomalous increases in low-level liquid cloud formation, cloud radiative forcing (CRF), and surface warming at Summit Station. An individual southerly pattern relates to the largest positive anomalies, with the most extreme 25% of cases leading to CRF anomalies above 21 W m−2 and temperature anomalies beyond 8.5°C. Finally, the July 2012 extreme melt event is analyzed, showing that the prolonged ice sheet warming was related to persistence of these southerly circulation patterns, causing an unusually extended period of anomalous CRF and temperature. These results demonstrate a novel methodology, connecting daily atmospheric circulation to a relatively brief record of observations.

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Nathaniel B. Miller, Matthew D. Shupe, Christopher J. Cox, Von P. Walden, David D. Turner, and Konrad Steffen

Abstract

The surface energy budget plays a critical role in determining the mass balance of the Greenland Ice Sheet, which in turn has significant implications for global sea levels. Nearly three years of data (January 2011–October 2013) are used to characterize the annual cycle of surface radiative fluxes and cloud radiative forcing (CRF) from the central Greenland Ice Sheet at Summit Station. The annual average CRF is 33 W m−2, representing a substantial net cloud warming of the central Greenland surface. Unlike at other Arctic sites, clouds warm the surface during the summer. The surface albedo is high at Summit throughout the year, limiting the cooling effect of the shortwave CRF and thus the total CRF is dominated by cloud longwave warming effects in all months. All monthly mean CRF values are positive (warming), as are 98.5% of 3-hourly cases. The annual cycle of CRF is largely driven by the occurrence of liquid-bearing clouds, with a minimum in spring and maximum in late summer. Optically thick liquid-bearing clouds [liquid water path (LWP) > 30 g m−2] produce an average longwave CRF of 85 W m−2. Shortwave CRF is sensitive to solar zenith angle and LWP. When the sun is well above the horizon (solar zenith angle < 65°), a maximum cloud surface warming occurs in the presence of optically thin liquid-bearing clouds. Ice clouds occur frequently above Summit and have mean longwave CRF values ranging from 10 to 60 W m−2, dependent on cloud thickness.

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Adrien Lacour, Helene Chepfer, Matthew D. Shupe, Nathaniel B. Miller, Vincent Noel, Jennifer Kay, David D. Turner, and Rodrigo Guzman

Abstract

Spaceborne lidar observations from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite provide the first-ever observations of cloud vertical structure and phase over the entire Greenland Ice Sheet. This study leverages CALIPSO observations over Greenland to pursue two investigations. First, the GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP) observations are compared with collocated ground-based radar and lidar observations at Summit, Greenland. The liquid cloud cover agrees well between the spaceborne and ground-based observations. In contrast, ground–satellite differences reach 30% in total cloud cover and 40% in cloud fraction below 2 km above ground level, due to optically very thin ice clouds (IWC < 2.5 × 10−3 g m−3) missed by CALIPSO-GOCCP. Those results are compared with satellite cloud climatologies from the GEWEX cloud assessment. Most passive sensors detect fewer clouds than CALIPSO-GOCCP and the Summit ground observations, due to different detection methods. Second, the distribution of clouds over the Greenland is analyzed using CALIPSO-GOCCP. Central Greenland is the cloudiest area in summer, at +7% and +4% above the Greenland-wide average for total and liquid cloud cover, respectively. Southern Greenland contains free-tropospheric thin ice clouds in all seasons and liquid clouds in summer. In northern Greenland, fewer ice clouds are detected than in other areas, but the liquid cloud cover seasonal cycle in that region drives the total Greenland cloud annual variability with a maximum in summer. In 2010 and 2012, large ice-sheet melting events have a positive liquid cloud cover anomaly (from +1% to +2%). In contrast, fewer clouds (−7%) are observed during low ice-sheet melt years (e.g., 2009).

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Matthew D. Shupe, David D. Turner, Von P. Walden, Ralf Bennartz, Maria P. Cadeddu, Benjamin B. Castellani, Christopher J. Cox, David R. Hudak, Mark S. Kulie, Nathaniel B. Miller, Ryan R. Neely III, William D. Neff, and Penny M. Rowe

Cloud and atmospheric properties strongly influence the mass and energy budgets of the Greenland Ice Sheet (GIS). To address critical gaps in the understanding of these systems, a new suite of cloud- and atmosphere-observing instruments has been installed on the central GIS as part of the Integrated Characterization of Energy, Clouds, Atmospheric State, and Precipitation at Summit (ICECAPS) project. During the first 20 months in operation, this complementary suite of active and passive ground-based sensors and radiosondes has provided new and unique perspectives on important cloud–atmosphere properties.

High atop the GIS, the atmosphere is extremely dry and cold with strong near-surface static stability predominating throughout the year, particularly in winter. This low-level thermodynamic structure, coupled with frequent moisture inversions, conveys the importance of advection for local cloud and precipitation formation. Cloud liquid water is observed in all months of the year, even the particularly cold and dry winter, while annual cycle observations indicate that the largest atmospheric moisture amounts, cloud water contents, and snowfall occur in summer and under southwesterly flow. Many of the basic structural properties of clouds observed at Summit, Greenland, particularly for low-level stratiform clouds, are similar to their counterparts in other Arctic regions.

The ICECAPS observations and accompanying analyses will be used to improve the understanding of key cloud–atmosphere processes and the manner in which they interact with the GIS. Furthermore, they will facilitate model evaluation and development in this data-sparse but environmentally unique region.

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Tristan S. L’Ecuyer, Brian J. Drouin, James Anheuser, Meredith Grames, David Henderson, Xianglei Huang, Brian H. Kahn, Jennifer E. Kay, Boon H. Lim, Marian Mateling, Aronne Merrelli, Nathaniel B. Miller, Sharmila Padmanabhan, Colten Peterson, Nicole-Jeanne Schlegel, Mary L. White, and Yan Xie

Abstract

The Earth’s climate is strongly influenced by energy deficits at the poles that emit more thermal energy than they receive from the sun. Energy exchanges between the surface and atmosphere influence the local environment while heat transport from lower latitudes drives midlatitude atmospheric and oceanic circulations. In the Arctic, in particular, local energy imbalances induce strong seasonality in surface-atmosphere heat exchanges and an acute sensitivity to forced climate variations. Despite these important local and global influences, the largest contributions to the polar atmospheric and surface energy budgets have not been fully characterized. The spectral variation of far-infrared radiation that makes up 60% of polar thermal emission has never been systematically measured impeding progress toward consensus in predicted rates of Arctic warming, sea ice decline, and ice sheet melt.

Enabled by recent advances in sensor miniaturization and CubeSat technology, the Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) mission will document, for the first time, the spectral, spatial, and temporal variations of polar far-infrared emission. Selected under NASA’s Earth Ventures Instrument (EVI) program, PREFIRE will utilize new light weight, low-power, ambient temperature detectors capable of measuring at wavelengths up to 50 micrometers to quantify Earth’s far-infrared spectrum. Estimates of spectral surface emissivity, water vapor, cloud properties, and the atmospheric greenhouse effect derived from these measurements offer the potential to advance our understanding of the factors that modulate thermal fluxes in the cold, dry conditions characteristic of the polar regions.

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