Evaluation of the atmosphere–land–ocean–sea ice interface processes in the Regional Arctic System Model version 1 (RASM1) using local and globally gridded observations (original) (raw)

Abstract

The Regional Arctic System Model version 1 (RASM1) has been developed to provide high-resolution simulations of the Arctic atmosphere-ocean-sea ice-land system. Here, we provide a baseline for the capability of RASM to simulate interface processes by comparing retrospective simulations from RASM1 for 1990-2014 with the Community Earth System Model version 1 (CESM1) and the spread across three recent reanalyses. Evaluations of surface and 2 m air temperature, surface radiative and turbulent fluxes, precipitation, and snow depth in the various models and reanalyses are performed using global and regional datasets and a variety of in situ datasets, including flux towers over land, ship cruises over oceans, and a field experiment over sea ice. These evaluations reveal that RASM1 simulates precipitation that is similar to CESM1, reanalyses, and satellite gauge combined precipitation datasets over all river basins within the RASM domain. Snow depth in RASM is closer to upscaled surface observations over a flatter region than in more mountainous terrain in Alaska. The sea iceatmosphere interface is well simulated in regards to radiation fluxes, which generally fall within observational uncertainty. RASM1 monthly mean surface temperature and radiation biases are shown to be due to biases in the simulated mean diurnal cycle. At some locations, a minimal monthly mean bias is shown to be due to the compensation of roughly equal but opposite biases between daytime and nighttime, whereas this is not the case at locations where the monthly mean bias is higher in magnitude. These biases are derived from errors in the diurnal cycle of the energy balance (radiative and turbulent flux) components. Therefore, the key to advancing the simulation of SAT and the surface energy budget would be to improve the representation of the diurnal cycle of radiative and turbulent fluxes. The development of RASM2 aims to address these biases. Still, an advantage of RASM1 is that it captures the interannual and interdecadal variability in the climate of the Arctic region, which global models like CESM cannot do.

Loading...

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

References (109)

  1. Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The version 2 Global Precipitation Climatology Project (GPCP) monthly pre- cipitation analysis (1979-present), J. Hydrometeorol., 4, 1147- 1167, 2003.
  2. Adler, R. F., Gu, G., and Huffman, G. J.: Estimating clima- tological bias errors for the Global Precipitation Climatol- ogy Project (GPCP), J. Appl. Meteorol. Clim., 51, 84-99, https://doi.org/10.1175/JAMC-D-11-052.1, 2012.
  3. Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S., Anthoni, P., Bernhofer, C., Davis, K., Evans, R., Fuentes, J., Goldstein, A., Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, W., Oechel, W., Paw U, K. T., Pilegaard, K., Schmid, H. P., Valentini, R., Verma, S., Vesala, T., Wilson, K., and Wofsy, S.: FLUXNET: A new tool to study the temporal and spatial variabil- ity of ecosystem-scale carbon dioxide, water vapor, and energy flux densities, B. Am. Meteorol. Soc., 82, 2415-2434, 2001.
  4. Barlage, M., Zeng, X., Wei, H., and Mitchell, K. E.: A global 0.05 • maximum albedo dataset of snow-covered land based on MODIS observations, Geophys. Res. Lett., 32, L17405, https://doi.org/10.1029/2005GL022881, 2005.
  5. Behrangi, A., Christensen, M., Richardson, M., Lebsock, M., Stephens, G., Huffman, G. J., Bolvin, D., Adler, R. F., Gardner, A., Lambrigtsen, B., and Fetzer, E.: Status of high-latitude precipitation estimates from observa- tions and reanalyses, J. Geophys. Res., 121, 4468-4486, https://doi.org/10.1002/2015JD024546, 2016.
  6. Betts, A. K., Ball, J. H., Barr, A. G., Black, T. A., Mc- Caughey, J. H., and Viterbo, P.: Assessing land-surface- atmosphere coupling in the ERA-40 reanalysis with bo- real forest data, Agr. Forest Meteorol., 140, 365-382, https://doi.org/10.1016/j.agrformet.2006.08.009, 2006.
  7. Berg, P., Döscher, R., and Koenigk, T.: Impacts of using spectral nudging on regional climate model RCA4 simu- lations of the Arctic, Geosci. Model Dev., 6, 849-859, https://doi.org/10.5194/gmd-6-849-2013, 2013.
  8. Berg, P., Döscher, R., and Koenigk, T.: On the effects of con- straining atmospheric circulation in a coupled atmosphere-ocean Arctic regional climate model, Clim. Dynam., 46, 3499-3515, https://doi.org/10.1007/s00382-015-2783-y, 2016.
  9. Bromwich, D. H., Cassano, J. J., Klein, T., Heinemann, G., Hines, K. M., Steffen, K., and Box, J. E.: Mesoscale modeling of kata- batic winds over Greenland with the Polar MM5, Mon. Weather Rev., 129, 2290-2309, 2001.
  10. Bromwich, D. H., Hines, K. M., and Bai, L.-S.: Develop- ment and testing of Polar Weather Research and Forecast- ing model: 2. Arctic Ocean, J. Geophys. Res., 114, D08122, https://doi.org/10.1029/2008JD010300, 2009.
  11. Bromwich, D. H., Wilson, A. B., Bai, L.-S., Moore, G. W. K., and Bauer, P.: A comparison of the regional Arc- tic System Reanalysis and the global ERA-Interim Reanaly- sis for the Arctic, Q. J. Roy. Meteor. Soc., 142, 644-658, https://doi.org/10.1002/qj.2527, 2016.
  12. Broxton, P., Zeng, X., and Dawson, N.: Why do global re- analyses and land data assimilation products underestimate snow water equivalent?, J. Hydrometeorol., 17, 2743-2761, https://doi.org/10.1175/JHM-D-16-0056.1, 2016.
  13. Brunke, M. A., Fairall, C. W., Zeng, X., Eymard, L., and Curry, J. A.: Which bulk aerodynamic flux algorithms are least problem- atic in computing ocean surface turbulent fluxes?, J. Climate, 16, 619-635, 2003.
  14. Brunke, M. A., Zhou, M., Zeng, X., and Andreas, E. L: An in- tercomparison of bulk aerodynamic algorithms used over sea ice with data from the Surface Heat Budget for the Arctic Ocean (SHEBA) experiment, J. Geophys. Res., 111, C09001, https://doi.org/10.1029/2005JC002907, 2006.
  15. Cassano, J. J., Box, J. E., Bromwich, D. H., Li, L., and Steffen, K.: Evaluation of Polar MM5 simulations of Greenland's atmo- spheric circulation, J. Geophys. Res., 106, 33867-33889, 2001.
  16. Cassano, J. J., Higgins, M. E., and Seefeldt, M. W.: Performance of the Weather Research and Forecasting Model for month-long pan-Arctic simulations, Mon. Weather Rev., 139, 3469-3488, 2011.
  17. Cassano, J. J., DuVivier, A., Roberts, A., Hughes, M., Seefeldt, M., Brunke, M., Craig, A., Fisel, B., Gutowski, W., Hamman, J., Hig- gins, M., Maslowski, W., Nijssen, B., Osinski, R., and Zeng, X.: Development of the Regional Arctic System Model (RASM): Near surface atmospheric climate sensitivity, J. Climate, 30, 5729-5753, https://doi.org/10.1175/JCLI-D-15-0775.1, 2017.
  18. Comiso, J. C. and Hall, D. K.: Climate trends in the Arctic as ob- served from space, Wires Clim. Change, 5, 389-409, 2014.
  19. Comiso, J. C., Parkinson, C. L., Gersten, R., and Stock, L.: Acceler- ated decline in the Arctic sea ice cover, Geophys. Res. Lett., 35, L01703, https://doi.org/10.1029/2007GL031972, 2008.
  20. Craig, A. P., Vertenstein, M., and Jacob, R.: A new flex- ible coupler for Earth system modeling developed for CCSM4 and CESM1, Int. J. High Perform. C., 26, 31-42, https://doi.org/10.1177/1094342011428141, 2012.
  21. Dawson, N., Broxton, P., Zeng, X., Leuthold, M., Barlage, M., and Holbrook, P.: Evaluation of Snow Initializations for NCEP Global and Regional Forecasting Models, J. Hydrometeorol., 17, 1885-1901, https://doi.org/10.1175/JHM-D-15-0227.1, 2016.
  22. Decker, M., Brunke, M. A., Wang, Z., Sakaguchi, K., Zeng, X., and Bosilovich, M. G.: Evaluation of the reanalysis products from GSFC, NCEP, and ECMWF using flux tower observations, J. Climate, 25, 1916-1944, https://doi.org/10.1175/JCLI-D-11- 00004.1, 2012.
  23. Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bid- lot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553-597, 2011.
  24. DeRepentigny, P., Tremblay, L. B., Newton, R., and Pfirman, S.: Patterns of sea ice retreat in the transition to a seasonally ice-free Arctic, J. Climate, 29, 6993-7008, https://doi.org/10.1175/JCLI- D-15-0733.1, 2016.
  25. Dethloff, K., Rinke, A., Lehmann, R., Christensen, J. H., Botzet, M., and Machenhauser, B.: A regional climate model of the Arctic atmosphere, J. Geophys. Res., 101, 23401-23422, 1996.
  26. Dorn, W., Dethloff, K., Rinke, A., Frickenhaus, S., Gerdes, R., Karcher, M., and Kauker, F.: Sensitivities and uncertainties in a coupled regional atmosphere-ocean-ice model with respect to the simulation of Arctic sea ice, J. Geophys. Res., 112, D10118, https://doi.org/10.1029/2006JD007814, 2007.
  27. Döscher, R., Willén, U., Jones, C., Rutgersson, A., Markus Meier, H. E., Hansson, U., and Graham, L. P.: The development of the regional coupled ocean-atmosphere model RCAO, Boreal Envi- ron. Res., 7, 183-192, 2002.
  28. D öscher, R., Wyser, K., Markus Meier, H. E., Qian, M., and Redler, R.: Quantifying Arctic contributions to climate predictability in a regional coupled ocean-ice-atmosphere model, Clim. Dy- nam., 34, 1157-1167, https://doi.org/10.1007/s00382-009-0567- y, 2010.
  29. Du, J., Wang, K., Wang, J., Jiang, S., and Zhou, C.: Diurnal cy- cle of surface air temperature within China in current reanal- yses: Evaluation and diagnostics, J. Climate, 31, 4585-4603, https://doi.org/10.1175/JCLI-D-0773.1, 2018.
  30. Dukowicz, J. K. and Smith, R. D.: Implicit free-surface method for the Bryan-Cox-Semtner ocean model, J. Geophys. Res., 99, 7991-8014, https://doi.org/10.1029/93JC03455, 1994.
  31. DuVivier, A. K. and Cassano, J. J.: Exploration of turbu- lent heat fluxes and wind stress curl in WRF and ERA- Interim during wintertime mesoscale wind events around southeastern Greenland, J. Geophys. Res., 120, 3593-3609, https://doi.org/10.1002/2014JD022991, 2015.
  32. Estilow, T. W., Young, A. H., and Robinson, D. A.: A long-term Northern Hemisphere snow cover extent data record for cli- mate studies and monitoring, Earth Syst. Sci. Data, 7, 137-142, https://doi.org/10.5194/essd-7-137-2015, 2015.
  33. European Centre for Medium-Range Weather Forecasts: ERA-Interim Project, Monthly Means, Research Data Archive at the National Center for Atmospheric Research, https://doi.org/10.5065/D68050NT, 2012.
  34. Gelaro, R., McCarty, W., Suarez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Re- ichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G.- K., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Par- tyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419-5454, 2017.
  35. Glisan, J. M., Gutowski, W. J., Cassano, J. J., and Higgins, M. E.: Effects of spectral nudging in WRF on Arctic tempera- ture and precipitation simulations, J. Climate, 26, 3985-3999, https://doi.org/10.1175/JCLI-D-12-00318.1, 2012.
  36. Grell, G. A. and Dévényi, D.: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques, Geophys. Res. Lett., 29, 1693, https://doi.org/10.1029/2002GL015311, 2002.
  37. Gupta, S. K., Whitlock, C. H., Ritchey, N. A., and Wilber, A. C.: An algorithm for longwave surface radiation budget for total skies (Subsystem 4.6.3), Clouds and Earth's Radiant Energy System (CERES) ATBD, 21 pp., 1997.
  38. Hamman, J., Nijssen, B., Brunke, M., Cassano, J., Craig, A., Du- Vivier, A., Hughes, M., Lettenmaier, D. P., Maslowski, W., Os- inski, R., Roberts, A., and Zeng, X.: Land surface climate in the Regional Arctic System Model, J. Climate, 29, 6543-6562, https://doi.org/10.1175/JCLI-D-15-0415.1, 2016.
  39. Hamman, J., Nijssen, B., Roberts, A., Craig, A., Maslowski, W., and Osinski, R.: The Coastal Streamflow Flux in the Re- gional Arctic System Model, J. Geophys. Res., 122, 1683-1701, https://doi.org/10.1002/2016JC012323, 2017.
  40. Hartmann, D. L.: Global Physical Climatology, Academic Press, San Diego, Calif., 1994.
  41. Hines, K. M. and Bromwich, D. H.: Development and testing of Polar WRF. Part I: Greenland Ice Sheet meteorology, Mon. Weather Rev., 136, 1971-1989, https://doi.org/10.1175/2007MWR2112.1, 2008.
  42. Holland, M. M. and Bitz, C. M.: Polar amplification of climate change in coupled models, Clim. Dynam., 21, 221-232, 2003.
  43. Hong, S.-Y., Noh, Y., and Dudhia, J.: A new vertical dif- fusion package with an explicit treatment of entrain- ment processes, Mon. Weather Rev., 134, 2318-2314, https://doi.org/10.1175/MWR3199.1, 2006.
  44. Hunke, E. C., Hebert, D. A., and Lecomte, O.: Level-ice melt ponds in the Los Alamos sea ice model, CICE, Ocean Model., 71, 26- 42, https://doi.org/10.1016/j.ocemod.2012.11.008, 2013.
  45. Hunke, E. C., Lipscomb, W. H., Turner, A. K., Jeffery, N., and El- liott, S.: CICE?: the Los Alamos Sea Ice Model Documentation and Software User's Manual Version 5.1, Los Alamos National Lab., Los Alamos, N.M., LA-CC-06-012, 2015.
  46. Johannessen, O. M., Bengtsson, L., Miles, M. W., Kuzmina, S. I., Semenov, V. A., Alekseev, G. V., Nagurnyi, A. P., Zakharov, V. F., Bobylev, L. P., Pettersson, L. H., Hasselmann, K., and Cattle, H. P.: Arctic climate change: observed and modelled temperature and sea-ice variability, Tellus, 56A, 328-341, 2004.
  47. Jousse, A., Hall, A., Sun, F., and Teixeira, J.: Causes of WRF sur- face energy fluxes biases in a stratocumulus region, Clim. Dy- nam., 46, 571-584, https://doi.org/10.1007/s00382-015-2599-9, 2016.
  48. Kain, J. S.: The Kain-Fritsch convective pa- rameterization: an update, J. Appl. Meteo- rol., 43, 170-181, https://doi.org/10.1175/1520- 0450(2004)043<0170:TKCPAU>2.0.C0;2, 2004.
  49. Kato, S., Loeb, N. G., Rose, F. G., Doelling, D. R., Rutan, D. A., Caldwell, T. E., Yu, L., and Weller, R. A.: Surface irradi- ances consistent with CERES-derived top-of-atmosphere short- wave and longwave irradiances, J. Climate, 26, 2719-2740, https://doi.org/10.1175/JCLI-D-12-00436.1, 2013.
  50. Kay, J. E., Deser, C., Phillips, A., Mai, A., Hannay, C., Strand, G. Arblaster, J. M., Bates, S. C., Danabasoglu, G., Edwards, J., Holland, M., Kushner, P.: The Community Earth System Model (CESM) Large Ensemble Project: A community re- source for studying climate change in the presence of inter- nal climate variability, B. Am. Meterol. Soc., 96, 1333-1349, https://doi.org/10.1175/BAMS-D-13-00255.1, 2015.
  51. Kennedy, J. J., Rayner, N. A., Smith, R. O., Parker, D. E., and Saunby, M.: Reassessing biases and other uncertainties in sea surface temperature observations measured in situ since 1850: 1. Measurement and sampling uncertainties, J. Geophys. Res., 116, D14103, https://doi.org/10.1029/2010JD015218, 2011a.
  52. Kennedy, J. J., Rayner, N. A., Smith, R. O., Parker, D. E., and Saunby, M.: Reassessing biases and other uncertainties in sea surface temperature observations measured in situ since 1850: 2. Biases and homogenization, J. Geophys. Res., 116, D14104, https://doi.org/10.1029/2010JD015220, 2011b.
  53. Large, W. G. and Yeager, S. G.: The global climatology of an in- terannually varying air-sea flux data set, Clim. Dynam., 33, 341- 364, https://doi.org/10.1007/s00382-008-0441-3, 2009.
  54. Lawrence, D. M., Koven, C. D., Swenson, S. C., Riley, W. J., and Slater, A. G.: Permafrost thaw and result- ing soil moisture changes regulate projected high-latitude CO 2 and CH 4 emissions, Environ. Res. Lett., 10, 094011, https://doi.org/10.1088/1748-9326/10/9/094011, 2015.
  55. Li, Z. and Kratz, D. P.: Estimate of shortwave surface radiation bud- get from CERES (Subsystem 4.6.1), Clouds and Earth's Radiant Energy System (CERES) ATBD, 18 pp., 1997.
  56. Li, Z., Leighton, H. G., Masuda, K., and Takashima, T.: Estimation of SW flux absorbed at the surface from TOA reflected flux, J. Climate, 6, 317-330, 1993.
  57. Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A simple hydrologically based model of land surface water and en- ergy fluxes for general circulation models, J. Geophys. Res., 99, 14415-14428, https://doi.org/10.1029/94JD00483, 1994.
  58. Liang, X., Wood, E. F., and Lettenmaier, D. P.: Surface soil moisture parameterization of the VIC-2L model: Evaluation and modifica- tion, Global Planet. Change, 13, 195-206, 1996.
  59. Lindsay, R., Wensnahan, M., Schweiger, A., and Zhang, J.: Eval- uation of seven different atmospheric reanalysis products in the Arctic, J. Climate, 27, 2588-2606, https://doi.org/10.1175/JCLI- D-13-00014.s1, 2014.
  60. Lynch, A. H. and Cullather, R. I.: An investigation of boundary- forcing sensitivities in a regional climate model, J. Geophys. Res., 105, 26603-26617, 2000.
  61. Lynch, A. H., Chapman, W. L., Walsh, J. E., and Weller, G.: De- velopment of a regional climate model of the western Arctic, J. Climate, 8, 1555-1570, 1995.
  62. Lynch, A. H., McGinnis, D. L., and Bailey, D. A.: Snow-albedo feedback and the spring transition in a regional climate system model: Influence of land surface model, J. Geophys. Res., 103, 29037-29049, 1998.
  63. Lynch, A. H., Maslanik, J. A., and Wu, W.: Mechanisms in the de- velopment of anomalous sea ice extent in the western Arctic: A case study, J. Geophys. Res., 106, 28097-28105, 2001.
  64. Maslowski, W., Kinney, J. C., Higgins, M., and Roberts, A.: The future of Arctic sea ice, Annu. Rev. Earth Pl. Sc., 40, 625-654, 2012.
  65. Maykut, G. A.: Energy exchange over young sea ice in the central Arctic, J. Geophys. Res., 23, 3646-3658, 1978.
  66. Maykut, G. A. and Untersteiner, N.: Some results from a time- dependent thermodynamic model of sea ice, J. Geophys. Res., 76, 1550-1575, 1971.
  67. Meier, W., Peng, G., Scott, D. J., and Savoie, M. H.: Ver- ification of a new NOAA/NSIDC passive microwave sea- ice concentration climate record, Polar Res., 33, 21004, https://doi.org/10.3402/polar.v33.21004, 2014.
  68. Meier, W., Fetterer, F., Savoie, M., Mallory, S., Duerr, R., and Stroeve, J.: NOAA/NSIDC Climate Data Record of Passive Mi- crowave Sea Ice Concentration, Version 3, National Snow and Ice Data Center, https://doi.org/10.7265/N59P2ZTG, 2017.
  69. Militzer, J. M., Michaelis, M. C., Semmer, S. R., Norris, K. S., Horst, T. W., Oncley, S. P., Delany, A. C., and Brock, F. V.: Devel- opment of the prototype PAM III/Flux-PAM surface meteorolog- ical station, paper presented at 9th Symposium on Meteorologi- cal Observations and Instrumentation, American Meteorological Society, Charlotte, N.C., 1995.
  70. Moritz, R. E., Bitz, C. M., and Steig, E. J.: Dynamics of recent climate change in the Arctic, Science, 297, 1497-1502, 2002.
  71. Morrison, H., Thompson, G., and Tatarskii, V.: Impact of cloud microphysics on the development of trailing stratiform pre- cipitation in a simulated squall line: Comparison of one-and two-moment schemes, Mon. Weather Rev., 137, 991-1007, https://doi.org/10.1175/2008MWR2556.1, 2009.
  72. Nakanishi, M. and Niino, H.: An improved Mellor-Yamada level-3 model: Its numerical stability and application to a regional pre- diction of advection fog, Bound.-Lay. Meteorol., 119, 397-407, https://doi.org/10.1007/s10546-005-9030-8, 2006.
  73. New, M., Lister, D., Hulme, M., and Makin, I.: A high-resolution data set of surface climate over global land areas, Clim. Res., 21, 1-25, https://doi.org/10.3354/cr021001, 2002.
  74. Osborn, T. J. and Jones, P. D.: The CRUTEM4 land-surface air temperature data set: construction, previous versions and dis- semination via Google Earth, Earth Syst. Sci. Data, 6, 61-68, https://doi.org/10.5194/essd-6-61-2014, 2014.
  75. Peng, G., Meier, W. N., Scott, D. J., and Savoie, M. H.: A long-term and reproducible passive microwave sea ice concentration data record for climate studies and monitoring, Earth Syst. Sci. Data, 5, 311-318, https://doi.org/10.5194/essd-5-311-2013, 2013.
  76. Persson, P. O. G., Fairall, C. W., Andreas, E. L, Guest, P. S., and Perovich, D. K.: Measurements near the Atmospheric Surface Flux Group tower at SHEBA: Near-surface condi- tions and surface energy budget, J. Geophys. Res., 107, 8045, https://doi.org/10.1029/2000JC000705, 2002.
  77. Porter, D. F., Cassano, J. J., and Serreze, M. C.: Analysis of the Arctic atmospheric energy budget in WRF: A comparison with reanalyses and satellite observations, J. Geophys. Res., 116, D22108, https://doi.org/10.1029/2011JD016622, 2011.
  78. Reeves Eyre, J. E. J. and Zeng, X.: Evaluation of Greenland near surface air temperature datasets, The Cryosphere, 11, 1591- 1605, https://doi.org/10.5194/tc-11-1591-2017, 2017.
  79. Rinke, A., Gerdes, R., Dethloff, K., Kandlbinder, T., Karcher, M., Kauker, F., Frickenhaus, S., Köberle, C., and Hiller, W.: A case sudy of the anomalous Arctic sea ice condi- tions during 1990: Insights from coupled and uncoupled re- gional climate model simulations, J. Geophys. Res., 108, 4275, https://doi.org/10.1029/2002JD003146, 2003.
  80. Roberts, A., Cassano, J., Döscher, Hinzman, L., Holland, M., Mit- sudera, H., Sumi, A., Walsh, J. E., Alessa, L., Alexeev, V., Arendt, A., Altaweel, M., Bhatt, U., Cherry, J., Deal, C., Elliot, S., Follows, M., Hock, R., Kliskey, A., Lantuit, H., Lawrence, D., Maslowski, W., McGuire, A. D., Overduin, P. P., Overeem, I., Proshutinsky, A., Romanovsky, V., Sushama, L., and Truffer, M.: A science plan for regional Arctic system modeling: A report by the Arctic research community for the National Science Founda- tion Office of Polar Programs, International Arctic Res. Center, Fairbanks, AK, International Arctic Research Center Technical Paper 10-0001, https://doi.org/10.13140/2.1.1828.9441, 2010.
  81. Roberts, A., Craig, A., Maslowski, W., Osinski, R., DuVivier, A., Hughes, M., Nijssen, B., and Brunke, M.: Simulating transient ice-ocean Ekman transport in the Regional Arctic System Model and Community Earth System Model, Ann. Glaciol., 56, 211- 228, 2015.
  82. Roberts, A. F., Cherry, J., Döscher, R., Elliott, S., and Sushama, L.: Exploring the Potential for Arctic Sys- tem Modeling, B. Am. Meteorol. Soc., 92, 203-206, https://doi.org/10.1175/2010bams2959.1, 2011.
  83. Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.-J., Aresenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin, J. K., Walker, J. P., Lohmann, D., and Toll, D.: The Global Land Data Assimilation System, B. Am. Meteo- rol. Soc., 85, 381-394, https://doi.org/10.1175/BAMS-85-3-381, 2004.
  84. Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., Tripp, P., Kistler, R., Woollen, J., Behringer, D., Liu, H., Stokes, D., Grumbine, R., Gayno, G., Wang, J., Hou, Y.-T., Chuang, H.- Y., Juang, H.-M. J., Sela, J., Iredell, M., Treadon, R., Kleist, D., Van Delst, P., Keyser, D., Derber, J., Ek, M., Meng, J., Wei, H., Yang, R., Lord, S., van den Dool, H., Kumar, A., Wang, W., Long, C., Chelliah, M., Xue, Y., Huang, B., Schemm, J.- K., Ebisuzaki, W., Lin, R., Xie, P., Chen, M, Zhou, S., Higgins, W., Zou, C.-Z., Liu, Q., Chen,Y., Han, Y., and Cucuruul, L.: The NCEP Climate Forecast System reanalysis, B. Am. Meteorol. Soc., 91, 1015-1057, 2010.
  85. Schuur, E. A. G., McGuire, A. D., Schadel, C., Grosse, G., Harden, J. W., Hayes, D. J., Hugelius, G., Koven, C. D., Kuhry, P., Lawrence, D. M., Natali, S. M., Olefeldt, D., Romanovsky, V. E., Schaefer, K., Turetsky, M. R., Treat, C. C., and Vonk, J. E.: Cli- mate change and the permafrost carbon feedback, Nature, 520, 171-179, https://doi.org/10.1038/nature14338, 2015.
  86. Screen, J. A. and Simmonds, I.: The central role of diminishing sea ice in recent Arctic temperature amplification, Nature, 464, 1334-1337, https://doi.org/10.1038/nature09051, 2010.
  87. Serreze, M. C. and Francis, J. A.: The Arctic amplification debate, Climatic Change, 76, 241-264, https://doi.org/10.1007/s10584- 005-9017-y, 2006.
  88. Serreze, M. C., Barrett, A. P. and Lo, F.: Northern high-latitude precipitation by atmospheric reanalyses and satellite retrievals, Mon. Weather Rev., 133, 3407-3430, 2005.
  89. Serreze, M. C., Holland, M. H., and Stroeve, J.: Perspectives on the Arctic's shrinking sea-ice cover, Science, 315, 1533-1536, 2007.
  90. Serreze, M. C., Barrett, A. P., Stroeve, J. C., Kindig, D. N., and Holland, M. M.: The emergence of surface-based Arctic ampli- fication, The Cryosphere, 3, 11-19, https://doi.org/10.5194/tc-3- 11-2009, 2009.
  91. Sheffield, J., Goteti, G., and Wood, E. F.: Development of a 50-year high-resolution global dataset of meteorological forc- ings for land surface modeling, J. Climate, 19, 3088-3111, https://doi.org/10.1175/jcli3790.1, 2006.
  92. Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda, M. G., Huang, X.-Y., Wang, W., and Powers, J. G.: A description of the Advanced Research WRF version 3, National Center for Atmos. Res., Boul- der, Colo., NCAR Tech. Note NCAR/TN-457+STR, 113 pp., https://doi.org/10.5065/D68S4MVH, 2008.
  93. Smith, R., Jones, P., Briegleb, B., Bryan, F., Danabasoglu, G., Den- nis, J., Dukowicz, J., Eden, C., Fox-Kemper, B., Gent, P., Hecht, M., Jayne, S., Jochum, M., Large, W., Lindsay, K., Maltrud, M., Norton, N., Peacock, S., Vertenstein, M., and Yeager, S.: The Parallel Ocean Program (POP) Reference Manual Ocean Com- ponent of the Community Climate System Model (CCSM) and Community Earth System Model (CESM), Los Alamos National Lab., Los Alamos, N.M., Rep. LAUR-10-01853, 2010.
  94. Smith, R. D., Dukowicz, J. K., and Malone, R. C.: Par- allel ocean circulation modeling, Physica D, 60, 38-61, https://doi.org/10.1016/0167-2789(92)90225-C, 1992.
  95. Steffen, K. and Box, J.: Surface climatology of the Greenland ice sheet: Greenland Climate Network 1995-1999, J. Geophys. Res., 106, 33951-33964, 2001.
  96. Stroeve, J., Holland, M. M., Meier, W., Scambos, T., and Serreze, M.: Arctic sea ice decline: Faster than forecast, Geophysical Research Letters, 34, L09501, https://doi.org/10.1029/2007GL029703, 2007.
  97. Stroeve, J., Serreze, M. C., Holland, M. M., Kay, J. E., Malanik, J., and Barrett, A. P.: The Arctic's rapidly shrinking sea ice cover: a research synthesis, Climatic Change, 110, 1105-1027, https://doi.org/10.1007/s10584-011-0101-1, 2012.
  98. Sturm, M., Holmgren, J., and Perovich, D. K.: Spatial variation in the winter heat flux at SHEBA: estimates from snow-ice interface temperatures, Ann. Glaciol., 33, 213-220, 2001.
  99. Swart, N. C., Fyfe, J. C., Hawkins, E., Kay, J. E., and Jahn, A.: In- fluence of internal variability on Arctic sea-ice trends, Nat. Clim. Change, 5, 86-89, 2015.
  100. Tsamados, M., Feltham, D. L., and Wilchinsky, A. V.: Increased Arctic sea ice volume after anomalously low melting in 2013, Nat. Geosci., 8, 643-646, https://doi.org/10.1038/ngeo2489, 2013.
  101. Turner, A. K. and Hunke, E. C.: Impacts of a mushy-layer ther- modynamic approach in global sea-ice simulations using the CICE sea-ice model, J. Geophys. Res.-Oceans, 120, 1253-1275, https://doi.org/10.1002/2014JC010358, 2015.
  102. Uttal, T., Curry, J. A., McPhee, M. G., Perovich, D. K., Moritz, R. E., Maslanik, J. A., Guest, P. S., Stern, H. L., Moore, J. A., Turenne, R., Heiberg, A., Serreze, M. C., Wylie, D. P., Persson, O. G., Paulson, C. A., Halle, C., Morison, J. H., Wheeler, P. A., Makshtas, A., Welch, H., Shupe, M. D., Intrieri, J. M., Stamnes, K., Lindsey, R. W., Pinkel, R., Pegau, W. S., Stanton, T. P., and Grenfeld, T. C.: Surface Heat Budget of the Arctic Ocean, B. Am. Meteorol. Soc., 83, 255-275, 2002.
  103. Vavrus, S.: The impact of cloud feedbacks on Arc- tic climate under Greenhouse forcing, J. Cli- mate, 17, 603-615, https://doi.org/10.1175/1520- 0442(2004)017<0603:TIOCFO>2.0.CO;2, 2004.
  104. Wang, A. and Zeng, X.: Development of global hourly 0.5 • land surface air temperature datasets, J. Climate, 26, 7676-7691, https://doi.org/10.1175/JCLI-D-12-00682.1, 2013.
  105. Wang, A. and Zeng, X.: Range of monthly mean hourly land surface air temperature diurnal cycle over high northern latitudes, J. Geophys. Res., 119, 5836-5844, https://doi.org/10.1002/2014JD021602, 2014.
  106. Xie, P. P. and Arkin, P. A.: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and nu- merical model outputs, B. Am. Meteorol. Soc., 78, 2539-2558, 1997.
  107. Zhang, X.: Sensitivity of arctic summer sea ice coverage to global warming forcing: towards reducing uncertainty in arctic climate change projections, Tellus, 62A, 220-227, 2010.
  108. Zhang, X. and Walsh, J. E.: Toward a seasonally ice-covered Arc- tic Ocean: scenarios from the IPCC AR4 model simulations, J. Climate, 19, 1730-1747, 2006.
  109. Zhou, C. and Wang, K.: Evaluation of surface fluxes in ERA- Interim using flux tower data, J. Climate, 29, 1573-1582, https://doi.org/10.1175/JCLI-D-15-0523.1, 2016.