• Alexander, M. A., U. S. Bhatt, J. E. Walsh, M. S. Timlin, J. S. Miller, and J. D. Scott, 2004: The atmospheric response to realistic Arctic sea ice anomalies in an AGCM during winter. J. Climate, 17, 890905.

    • Search Google Scholar
    • Export Citation
  • Ambaum, M. H. P., and B. J. Hoskins, 2002: The NAO troposphere–stratosphere connection. J. Climate, 15, 19691978.

  • Armstrong, R., 2001: Historical Soviet daily snow depth version 2 (HSDSD). National Snow and Ice Data Center, Boulder, CO, CD-ROM.

  • Baldwin, M. P., D. B. Stephenson, D. W. J. Thompson, T. J. Dunkerton, A. J. Charlton, and A. O’Neill, 2003: Stratospheric memory and skill of extended-range weather forecasts. Science, 301, 636640.

    • Search Google Scholar
    • Export Citation
  • Brands, S., R. Manzanas, J. M. Gutiérrez, and J. Cohen, 2012: Seasonal predictability of wintertime precipitation in Europe using the snow advance index. J. Climate, 25, 40234028.

    • Search Google Scholar
    • Export Citation
  • Brasnett, B., 1999: A global analysis of snow depth for numerical weather prediction. J. Appl. Meteor., 38, 726740.

  • Brown, R. D., and B. Bruce, 2010: Canadian Meteorological Centre (CMC) daily snow depth analysis data. National Snow and Ice Data Center Boulder, CO, digital media. [Available online at http://nsidc.org/data/nsidc-0447.html.]

  • Brown, R. D., B. Brasnett, and D. Robinson, 2003: Gridded North American monthly snow depth and snow water equivalent for GCM evaluation. Atmos.–Ocean, 41, 114.

    • Search Google Scholar
    • Export Citation
  • Cess, R. D., and G. L. Potter, 1988: A methodology for understanding and intercomparing atmospheric climate feedback processes in general circulation models. J. Geophys. Res., 93 (D7), 83058314.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., and D. Rind, 1991: The effect of snow cover on the climate. J. Climate, 4, 689706.

  • Cohen, J., and C. Fletcher, 2007: Improved skill of Northern Hemisphere winter surface temperature predictions based on land–atmosphere fall anomalies. J. Climate, 20, 41184132.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., and J. Jones, 2011: A new index for more accurate winter predictions. Geophys. Res. Lett., 38, L21701, doi:10.1029/2011GL049626.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., M. Barlow, P. J. Kushner, and K. Saito, 2007: Stratosphere–troposphere coupling and links with Eurasian land surface variability. J. Climate, 20, 53355343.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., M. Barlow, and K. Saito, 2009: Decadal fluctuations in planetary wave forcing modulate global warming in late boreal winter. J. Climate, 22, 44184426.

    • Search Google Scholar
    • Export Citation
  • Collins, W. D., and Coauthors, 2004: Description of the NCAR Community Atmosphere Model (CAM 3.0). National Center for Atmospheric Research Tech. Note NCAR/TN–464+STR, 226 pp.

  • Dee, D. P., and S. Uppala, 2009: Variational bias correction of satellite radiance data in the ERA-Interim reanalysis. Quart. J. Roy. Meteor. Soc., 135, 18301841.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597.

    • Search Google Scholar
    • Export Citation
  • Deser, C., G. Magnusdottir, R. Saravanan, and A. Phillips, 2004: The effects of North Atlantic SST and sea ice anomalies on the winter circulation in CCM3. Part II: Direct and indirect components of the response. J. Climate, 17, 877889.

    • Search Google Scholar
    • Export Citation
  • Deser, C., R. A. Tomas, and S. Peng, 2007: The transient atmospheric circulation response to North Atlantic SST and sea ice anomalies. J. Climate, 20, 47514767.

    • Search Google Scholar
    • Export Citation
  • Fletcher, C. G., S. C. Hardiman, P. J. Kushner, and J. Cohen, 2009a: The dynamical response to snow cover perturbations in a large ensemble of atmospheric GCM integrations. J. Climate, 22, 12081222.

    • Search Google Scholar
    • Export Citation
  • Fletcher, C. G., P. J. Kushner, A. Hall, and X. Qu, 2009b: Circulation responses to snow albedo feedback in climate change. Geophys. Res. Lett., 36, L09702, doi:10.1029/2009GL038011.

    • Search Google Scholar
    • Export Citation
  • Folland, C., A. A. Scaife, J. Lindesay, and D. B. Stephenson, 2011: How potentially predictable is northern European winter climate a season ahead? Int. J. Climatol., 32, 801818.

    • Search Google Scholar
    • Export Citation
  • Ge, Y., and G. Gong, 2008: Observed inconsistencies between snow extent and snow depth variability at regional/continental scales. J. Climate, 21, 10661082.

    • Search Google Scholar
    • Export Citation
  • Hardiman, S. C., P. J. Kushner, and J. Cohen, 2008: Investigating the ability of general circulation models to capture the effects of Eurasian snow cover on winter climate. J. Geophys. Res., 113, D21123, doi:10.1029/2008JD010623.

    • Search Google Scholar
    • Export Citation
  • Honda, M., J. Inoue, and S. Yamane, 2009: Influence of low Arctic sea-ice minima on anomalously cold Eurasian winters. Geophys. Res. Lett., 36, L08707, doi:10.1029/2008GL037079.

    • Search Google Scholar
    • Export Citation
  • Ineson, S., and A. A. Scaife, 2009: The role of the stratosphere in the European climate response to El Niño. Nat. Geosci., 2, 3236.

    • Search Google Scholar
    • Export Citation
  • Ineson, S., A. A. Scaife, J. R. Knight, J. C. Manners, N. J. Dunstone, L. J. Gray, and J. D. Haigh, 2011: Solar forcing of winter climate variability in the Northern Hemisphere. Nat. Geosci., 4, 753757.

    • Search Google Scholar
    • Export Citation
  • Jeong, J.-H., C.-H. Ho, D. L. Chen, and T.-W. Park, 2008: Land surface initialization using an offline CLM3 simulation with the GSWP-2 forcing dataset and its impact on CAM3 simulations of the boreal summer climate. J. Hydrometeor., 9, 12311248.

    • Search Google Scholar
    • Export Citation
  • Jeong, J.-H., T. Ou, H. W. Linderholm, B.-M. Kim, S.-J. Kim, J.-S. Kug, and D. Chen, 2011: Recent recovery of the Siberian high intensity. J. Geophys. Res., 116, D23102, doi:10.1029/2011JD015904.

    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., W. Ebisuzaki, J. Woollen, S.-K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 16311643.

    • Search Google Scholar
    • Export Citation
  • Kim, K.-Y., 2002: Investigation of ENSO variability using cyclostationary EOFs of observational data. Meteor. Atmos. Phys., 81, 149168.

    • Search Google Scholar
    • Export Citation
  • Kim, K.-Y., G. R. North, and J. Huang, 1996: EOFs of one-dimensional cyclostationary time series: Computations, examples, and stochastic modeling. J. Atmos. Sci., 53, 10071017.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2004: Realistic initialization of land surface states: Impacts on subseasonal forecast skill. J. Hydrometeor., 5, 10491063.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., S. P. P. Mahanama, B. Livneh, D. P. Lettenmaier, and R. H. Reichle, 2010a: Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow. Nat. Geosci., 3, 613616.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2010b: Contribution of land surface initialization to subseasonal forecast skill: First results from a multi-model experiment. Geophys. Res. Lett., 37, L02402, doi:10.1029/2009GL041677.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2011: The second phase of the Global Land–Atmosphere Coupling Experiment: Soil moisture contributions to subseasonal forecast skill. J. Hydrometeor., 12, 805822.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., and F. Yang, 2003: Comparative influence of snow and SST variability on extratropical climate in northern winter. J. Climate, 16, 22482261.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., Q. Zhang, P. Peng, and B. Jha, 2005: SST-forced atmospheric variability in an atmospheric general circulation model. J. Climate, 18, 39533967.

    • Search Google Scholar
    • Export Citation
  • Oleson, K. W., and Coauthors, 2004: Technical description of the Community Land Model (CLM). National Center for Atmospheric Research Tech. Note NCAR/TN-461+STR, 186 pp.

  • Orsolini, Y. J., and N. G. Kvamstø, 2009: Role of Eurasian snow cover in wintertime circulation: Decadal simulations forced with satellite observations. J. Geophys. Res., 114, D19108, doi:10.1029/2009JD012253.

    • Search Google Scholar
    • Export Citation
  • Overland, J. E., K. R. Wood, and M. Wang, 2011: Warm Arctic—Cold continents: Climate impacts of the newly open Arctic Sea. Polar Res., 30, 15787, doi:10.3402/polar.v30i0.15787.

    • Search Google Scholar
    • Export Citation
  • Peings, Y., H. Douville, R. Alkama, and B. Decharme, 2010: Snow contribution to springtime atmospheric predictability over the second half of the twentieth century. Climate Dyn., 37, 9851004.

    • Search Google Scholar
    • Export Citation
  • Qu, X., and A. Hall, 2006: Assessing snow albedo feedback in simulated climate change. J. Climate, 19, 26172630.

  • Rayner, N. A., and Coauthors, 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407, doi:10.1029/2002JD002670.

    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., N. A. Rayner, T. M. Smith, D. C. Stokes, and W. Wang, 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15, 16091625.

    • Search Google Scholar
    • Export Citation
  • Robinson, D. A., K. F. Dewey, and R. R. Heim, 1993: Global snow cover monitoring: An update. Bull. Amer. Meteor. Soc., 74, 16891696.

  • Rowell, D. P., 1998: Assessing potential seasonal predictability with an ensemble of multidecadal GCM simulations. J. Climate, 11, 109120.

    • Search Google Scholar
    • Export Citation
  • Saito, K., J. Cohen, and D. Entekhabi, 2001: Evolution of atmospheric response to early-season Eurasian snow cover anomalies. Mon. Wea. Rev., 129, 27462760.

    • Search Google Scholar
    • Export Citation
  • Saunders, M. A., B. Qian, and B. Lloyd-Hughes, 2003: Summer snow extent heralding of the winter North Atlantic Oscillation. Geophys. Res. Lett., 30, 1378, doi:10.1029/2002GL016832.

    • Search Google Scholar
    • Export Citation
  • Shukla, J., and Coauthors, 2000: Dynamical seasonal prediction. Bull. Amer. Meteor. Soc., 81, 25932606.

  • Smith, K. L., P. J. Kushner, and J. Cohen, 2011: The role of linear interference in northern annular mode variability associated with Eurasian snow cover extent. J. Climate, 24, 61856202.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., G. W. Branstator, D. Karoly, A. Kumar, N.-C. Lau, and C. Ropelewski, 1998: Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J. Geophys. Res., 103 (C7), 14 29114 324.

    • Search Google Scholar
    • Export Citation
  • Vavrus, S., and D. Waliser, 2008: An improved parametrization for simulating Arctic cloud amount in the CCSM3 climate model. J. Climate, 21, 56735687.

    • Search Google Scholar
    • Export Citation
  • Wang, B., and Coauthors, 2008: Advance and prospectus of seasonal prediction: Assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004). Climate Dyn., 33, 93117.

    • Search Google Scholar
    • Export Citation
  • Winton, M., 2006a: Amplified Arctic climate change: What does surface albedo feedback have to do with it? Geophys. Res. Lett., 33, L03701, doi:10.1029/2005GL025244.

    • Search Google Scholar
    • Export Citation
  • Winton, M., 2006b: Surface albedo feedback estimates for the AR4 climate models. J. Climate, 19, 359365.

  • Woo, S.-H., B.-M. Kim, J.-H. Jeong, S.-J. Kim, and G.-H. Lim, 2012: Decadal changes in surface air temperature variability and cold surge characteristics over northeast Asia and their relation with the Arctic Oscillation for the past three decades (1979–2011). J. Geophys. Res., 117, D18117, doi:10.1029/2011JD016929.

    • Search Google Scholar
    • Export Citation
  • Yeh, T. C., R. T. Wetherald, and S. Manabe, 1983: A model study of the short-term climatic and hydrologic effects of sudden snow-cover removal. Mon. Wea. Rev., 111, 10131024.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 10 10 10
PDF Downloads 8 8 8

Impacts of Snow Initialization on Subseasonal Forecasts of Surface Air Temperature for the Cold Season

View More View Less
  • 1 * Faculty of Earth Systems and Environmental Sciences, Chonnam National University, Gwangju, South Korea
  • | 2 Department of Earth Sciences, University of Gothenburg, Gothenburg, Sweden
  • | 3 Korea Institute of Ocean Science and Technology, Ansan, and School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea
  • | 4 Department of Earth Sciences, University of Gothenburg, Gothenburg, Sweden, and Met Office Hadley Centre, Exeter, United Kingdom
  • | 5 Korea Polar Research Institute, Incheon, South Korea
Restricted access

Abstract

The present study examines the impacts of snow initialization on surface air temperature by a number of ensemble seasonal predictability experiments using the NCAR Community Atmosphere Model version 3 (CAM3) AGCM with and without snow initialization. The study attempts to isolate snow signals on surface air temperature. In this preliminary study, any effects of variations in sea ice extent are ignored and do not explicitly identify possible impacts on atmospheric circulation. The Canadian Meteorological Center (CMC) daily snow depth analysis was used in defining initial snow states, where anomaly rescaling was applied in order to account for the systematic bias of the CAM3 snow depth with respect to the CMC analysis. Two suites of seasonal (3 months long) ensemble hindcasts starting at each month in the colder part of the year (September–April) with and without the snow initialization were performed for 12 recent years (1999–2010), and the predictability skill of surface air temperature was estimated. Results show that considerable potential predictability increases up to 2 months ahead can be attained using snow initialization. Relatively large increases are found over East Asia, western Russia, and western Canada in the later part of this period. It is suggested that the predictability increases are sensitive to the strength of snow–albedo feedback determined by given local climate conditions; large gains tend to exist over the regions of strong snow–albedo feedback. Implications of these results for seasonal predictability over the extratropical Northern Hemisphere and future direction for this research are discussed.

Corresponding author address: Baek-Min Kim, Korea Polar Research Institute, 7-50 Songdo-dong, Yeonsu-gu, Incheon, South Korea. E-mail: bmkim@kopri.re.kr

Abstract

The present study examines the impacts of snow initialization on surface air temperature by a number of ensemble seasonal predictability experiments using the NCAR Community Atmosphere Model version 3 (CAM3) AGCM with and without snow initialization. The study attempts to isolate snow signals on surface air temperature. In this preliminary study, any effects of variations in sea ice extent are ignored and do not explicitly identify possible impacts on atmospheric circulation. The Canadian Meteorological Center (CMC) daily snow depth analysis was used in defining initial snow states, where anomaly rescaling was applied in order to account for the systematic bias of the CAM3 snow depth with respect to the CMC analysis. Two suites of seasonal (3 months long) ensemble hindcasts starting at each month in the colder part of the year (September–April) with and without the snow initialization were performed for 12 recent years (1999–2010), and the predictability skill of surface air temperature was estimated. Results show that considerable potential predictability increases up to 2 months ahead can be attained using snow initialization. Relatively large increases are found over East Asia, western Russia, and western Canada in the later part of this period. It is suggested that the predictability increases are sensitive to the strength of snow–albedo feedback determined by given local climate conditions; large gains tend to exist over the regions of strong snow–albedo feedback. Implications of these results for seasonal predictability over the extratropical Northern Hemisphere and future direction for this research are discussed.

Corresponding author address: Baek-Min Kim, Korea Polar Research Institute, 7-50 Songdo-dong, Yeonsu-gu, Incheon, South Korea. E-mail: bmkim@kopri.re.kr
Save