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Christopher J. Cox, Taneil Uttal, Charles N. Long, Matthew D. Shupe, Robert S. Stone, and Sandy Starkweather

Abstract

Recent studies suggest that the atmosphere conditions arctic sea ice properties in spring in a way that may be an important factor in predetermining autumn sea ice concentrations. Here, the role of clouds in this system is analyzed using surface-based observations from Barrow, Alaska. Barrow is a coastal location situated adjacent to the region where interannual sea ice variability is largest. Barrow is also along a main transport pathway through which springtime advection of atmospheric energy from lower latitudes to the Arctic Ocean occurs. The cloud contribution is quantified using the observed surface radiative fluxes and cloud radiative forcing (CRF) derived therefrom, which can be positive or negative. In low sea ice years enhanced positive CRF (increased cloud cover enhancing longwave radiative forcing) in April is followed by decreased negative CRF (decreased cloud cover allowing a relative increase in shortwave radiative forcing) in May and June. The opposite is true in high sea ice years. In either case, the combination and timing of these early and late spring cloud radiative processes can serve to enhance the atmospheric preconditioning of sea ice. The net CRF (April and May) measured at Barrow from 1993 through 2014 is negatively correlated with sea ice extent in the following autumn (r 2 = 0.33; p < 0.01). Reanalysis data appear to capture the general timing and sign of the observed CRF anomalies at Barrow and suggest that the anomalies occur over a large region of the central Arctic Ocean, which supports the link between radiative processes observed at Barrow and the broader arctic sea ice extent.

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Christopher J. Cox, David D. Turner, Penny M. Rowe, Matthew D. Shupe, and Von P. Walden

Abstract

The radiative properties of clouds are related to cloud microphysical and optical properties, including water path, optical depth, particle size, and thermodynamic phase. Ground-based observations from remote sensors provide high-quality, long-term, continuous measurements that can be used to obtain these properties. In the Arctic, a more comprehensive understanding of cloud microphysics is important because of the sensitivity of the Arctic climate to changes in radiation. Eureka, Nunavut (80°N, 86°25′W, 10 m), Canada, is a research station located on Ellesmere Island. A large suite of ground-based remote sensors at Eureka provides the opportunity to make measurements of cloud microphysics using multiple instruments and methodologies. In this paper, cloud microphysical properties are presented using a retrieval method that utilizes infrared radiances obtained from an infrared spectrometer at Eureka between March 2006 and April 2009. These retrievals provide a characterization of the microphysics of ice and liquid in clouds with visible optical depths between 0.25 and 6, which are a class of clouds whose radiative properties depend greatly on their microphysical properties. The results are compared with other studies that use different methodologies at Eureka, providing context for multimethod perspectives. The authors’ findings are supportive of previous studies, including seasonal cycles in phase and liquid particle size, weak temperature–phase dependencies, and frequent occurrences of supercooled water. Differences in microphysics are found between mixed-phase and single-phase clouds for both ice and liquid. The Eureka results are compared with those obtained using a similar retrieval technique during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment.

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Benjamin J. Murray, Christoph G. Salzmann, Andrew J. Heymsfield, Steven Dobbie, Ryan R. Neely III, and Christopher J. Cox

Abstract

We are all familiar with the hexagonal shape of snow and ice crystals, and it is well established that their sixfold symmetry is derived from the arrangement of water molecules in a hexagonal crystal structure. However, atmospheric ice crystals with only threefold rotational symmetry are often observed, which is inconsistent with the hexagonal crystal structure of ordinary ice. These crystals are found in a wide range of different cloud types ranging from upper-tropospheric cirrus to contrails and diamond dust and they form at temperatures ranging from about −84° to −5°C. Recent experimental studies of ice crystal structures have shown that ice under a wide range of atmospheric conditions does not always conform to the standard hexagonal crystal structure. Instead, sequences of the hexagonal structure can be interlaced with cubic sequences to create stacking-disordered ice. This degrades the symmetry of the crystal structure so that, instead of having a hexagonal structure, they have a trigonal structure with a corresponding threefold symmetry. Hence, this implies that atmospheric ice crystals with threefold symmetry are made of stacking-disordered ice. We conclude that the presence of trigonal crystals in the atmosphere is consistent with rare Parry arc halos and also show that they have distinct radiative properties compared with hexagonal ice.

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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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Christopher J. Cox, Robert S. Stone, David C. Douglas, Diane M. Stanitski, George J. Divoky, Geoff S. Dutton, Colm Sweeney, J. Craig George, and David U. Longenecker

Abstract

Linkages between atmospheric, ecological, and biogeochemical variables in the changing Arctic are analyzed using long-term measurements near Utqiaġvik (formerly Barrow), Alaska. Two key variables are the date when snow disappears in spring, as determined primarily by atmospheric dynamics, precipitation, air temperature, winter snow accumulation, and cloud cover, and the date of onset of snowpack in autumn that is additionally influenced by ocean temperature and sea ice extent. In 2015 and 2016 the snow melted early at Utqiaġvik owing mainly to anomalous warmth during May of both years attributed to atmospheric circulation patterns, with 2016 having the record earliest snowmelt. These years are discussed in the context of a 115-yr snowmelt record at Utqiaġvik with a trend toward earlier melting since the mid-1970s (–2.86 days decade–1, 1975–2016). At nearby Cooper Island, where a colony of seabirds, black guillemots, have been monitored since 1975, timing of egg laying is correlated with Utqiaġvik snowmelt with 2015 and 2016 being the earliest years in the 42-yr record. Ice out at a nearby freshwater lagoon is also correlated with Utqiaġvik snowmelt. The date when snow begins to accumulate in autumn at Utqiaġvik shows a trend toward later dates (+4.6 days decade–1, 1975–2016), with 2016 being the latest on record. The relationships between the lengthening snow-free season and regional phenology, soil temperatures, fluxes of gases from the tundra, and to regional sea ice conditions are discussed. Better understanding of these interactions is needed to predict the annual snow cycles in the region at seasonal to decadal scales and to anticipate coupled environmental responses.

Open access
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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Zhichang Guo, Paul A. Dirmeyer, Randal D. Koster, Y. C. Sud, Gordon Bonan, Keith W. Oleson, Edmond Chan, Diana Verseghy, Peter Cox, C. T. Gordon, J. L. McGregor, Shinjiro Kanae, Eva Kowalczyk, David Lawrence, Ping Liu, David Mocko, Cheng-Hsuan Lu, Ken Mitchell, Sergey Malyshev, Bryant McAvaney, Taikan Oki, Tomohito Yamada, Andrew Pitman, Christopher M. Taylor, Ratko Vasic, and Yongkang Xue

Abstract

The 12 weather and climate models participating in the Global Land–Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land–atmosphere coupling and some intriguing commonalities. In this paper, the causes of variations in coupling strength—both the geographic variations within a given model and the model-to-model differences—are addressed. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage—an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first-stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation–precipitation connection, however, also play a key role.

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Randall M. Dole, J. Ryan Spackman, Matthew Newman, Gilbert P. Compo, Catherine A. Smith, Leslie M. Hartten, Joseph J. Barsugli, Robert S. Webb, Martin P. Hoerling, Robert Cifelli, Klaus Wolter, Christopher D. Barnet, Maria Gehne, Ronald Gelaro, George N. Kiladis, Scott Abbott, Elena Akish, John Albers, John M. Brown, Christopher J. Cox, Lisa Darby, Gijs de Boer, Barbara DeLuisi, Juliana Dias, Jason Dunion, Jon Eischeid, Christopher Fairall, Antonia Gambacorta, Brian K. Gorton, Andrew Hoell, Janet Intrieri, Darren Jackson, Paul E. Johnston, Richard Lataitis, Kelly M. Mahoney, Katherine McCaffrey, H. Alex McColl, Michael J. Mueller, Donald Murray, Paul J. Neiman, William Otto, Ola Persson, Xiao-Wei Quan, Imtiaz Rangwala, Andrea J. Ray, David Reynolds, Emily Riley Dellaripa, Karen Rosenlof, Naoko Sakaeda, Prashant D. Sardeshmukh, Laura C. Slivinski, Lesley Smith, Amy Solomon, Dustin Swales, Stefan Tulich, Allen White, Gary Wick, Matthew G. Winterkorn, Daniel E. Wolfe, and Robert Zamora

Abstract

Forecasts by mid-2015 for a strong El Niño during winter 2015/16 presented an exceptional scientific opportunity to accelerate advances in understanding and predictions of an extreme climate event and its impacts while the event was ongoing. Seizing this opportunity, the National Oceanic and Atmospheric Administration (NOAA) initiated an El Niño Rapid Response (ENRR), conducting the first field campaign to obtain intensive atmospheric observations over the tropical Pacific during El Niño.

The overarching ENRR goal was to determine the atmospheric response to El Niño and the implications for predicting extratropical storms and U.S. West Coast rainfall. The field campaign observations extended from the central tropical Pacific to the West Coast, with a primary focus on the initial tropical atmospheric response that links El Niño to its global impacts. NOAA deployed its Gulfstream-IV (G-IV) aircraft to obtain observations around organized tropical convection and poleward convective outflow near the heart of El Niño. Additional tropical Pacific observations were obtained by radiosondes launched from Kiritimati , Kiribati, and the NOAA ship Ronald H. Brown, and in the eastern North Pacific by the National Aeronautics and Space Administration (NASA) Global Hawk unmanned aerial system. These observations were all transmitted in real time for use in operational prediction models. An X-band radar installed in Santa Clara, California, helped characterize precipitation distributions. This suite supported an end-to-end capability extending from tropical Pacific processes to West Coast impacts. The ENRR observations were used during the event in operational predictions. They now provide an unprecedented dataset for further research to improve understanding and predictions of El Niño and its impacts.

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Taneil Uttal, Sandra Starkweather, James R. Drummond, Timo Vihma, Alexander P. Makshtas, Lisa S. Darby, John F. Burkhart, Christopher J. Cox, Lauren N. Schmeisser, Thomas Haiden, Marion Maturilli, Matthew D. Shupe, Gijs De Boer, Auromeet Saha, Andrey A. Grachev, Sara M. Crepinsek, Lori Bruhwiler, Barry Goodison, Bruce McArthur, Von P. Walden, Edward J. Dlugokencky, P. Ola G. Persson, Glen Lesins, Tuomas Laurila, John A. Ogren, Robert Stone, Charles N. Long, Sangeeta Sharma, Andreas Massling, David D. Turner, Diane M. Stanitski, Eija Asmi, Mika Aurela, Henrik Skov, Konstantinos Eleftheriadis, Aki Virkkula, Andrew Platt, Eirik J. Førland, Yoshihiro Iijima, Ingeborg E. Nielsen, Michael H. Bergin, Lauren Candlish, Nikita S. Zimov, Sergey A. Zimov, Norman T. O’Neill, Pierre F. Fogal, Rigel Kivi, Elena A. Konopleva-Akish, Johannes Verlinde, Vasily Y. Kustov, Brian Vasel, Viktor M. Ivakhov, Yrjö Viisanen, and Janet M. Intrieri

Abstract

International Arctic Systems for Observing the Atmosphere (IASOA) activities and partnerships were initiated as a part of the 2007–09 International Polar Year (IPY) and are expected to continue for many decades as a legacy program. The IASOA focus is on coordinating intensive measurements of the Arctic atmosphere collected in the United States, Canada, Russia, Norway, Finland, and Greenland to create synthesis science that leads to an understanding of why and not just how the Arctic atmosphere is evolving. The IASOA premise is that there are limitations with Arctic modeling and satellite observations that can only be addressed with boots-on-the-ground, in situ observations and that the potential of combining individual station and network measurements into an integrated observing system is tremendous. The IASOA vision is that by further integrating with other network observing programs focusing on hydrology, glaciology, oceanography, terrestrial, and biological systems it will be possible to understand the mechanisms of the entire Arctic system, perhaps well enough for humans to mitigate undesirable variations and adapt to inevitable change.

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