LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Benestad, R.E.; Senan, R.; Balmaseda, M; Ferranti, L; Orsolini, Yvan; Melsom, A. (2011)
Publisher: Co-Action Publishing
Journal: Tellus A
Languages: English
Types: Article
Subjects:

Classified by OpenAIRE into

arxiv: Physics::Atmospheric and Oceanic Physics, Astrophysics::Earth and Planetary Astrophysics, Physics::Geophysics
Current seasonal forecast models involve simple schemes for representing sea ice, such as imposing climatological values. The spread of ensemble forecasts may in principle be biased due to common boundary conditions prescribed in the high latitudes. The degree of sensitivity in the 2-metre temperature, associated with seasonal time scales and the state of the June–August sea ice, is examined through a set of experiments with a state-of-the-art coupled ocean-atmosphere model. Here we present a suite of numerical experiments examining the effect of different sea ice configurations on the final ensemble distribution. We also compare the sensitivity of the 2-metre temperature to sea ice boundary conditions and sea surface temperature perturbation in the initial conditions. One objective of this work was to test a simple scheme for a more realistic representation of sea ice variations that allows for a spread in the Polar surface boundary conditions, captures the recent trends and doesn’t smudge the sea ice edges. We find that the use of one common set of boundary conditions in the polar regions has little effect on the subsequent seasonal temperatures in the low latitudes, but nevertheless a profound influence on the local temperatures in the mid-to-high latitudes.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Anderson, D., Stockdale, T., Balmaseda, M., Ferranti, L., Vitart, F. and co-authors. 2006. Seasonal Forecast System 3. ECMWF Newsletter, 19-25.
    • Balmaseda, M., Freeanti, L., Molteni, F. and Palmer, T. N. 2009. Impact of 2007 and 2008 Arctic Ice Anomalies on the Atmospheric Circulation: Implications for Long-Range Predictions. Technical Memorandum 595. ECMWF, http://www.ecmwf.int/publications/ library/do/references/list/show?id=89212.
    • Balmaseda, M. A., Vidard, A. and Anderson, D. L. T. 2007. The ECMWF System 3 ocean analysis system. Technical Memorandum 508. ECMWF.
    • Balmaseda, M. A., Ferranti, L., Molteni, F. and Palmer, T. N. 2010. Impact of 2007 and 2008 Arctic ice anomalies on the atmospheric circulation: implications for long-range predictions. QJRMS, doi:10.1002/qj.661.
    • Benestad, R. E. 2005. On Latitudinal Profiles of Zonal Means. Geophys. Res. Lett. 32, doi:10.1029/2005GL023652.
    • Benestad, R. E. 2006. Can we expect more extreme precipitation on the monthly time scale? J. Clim. 19, 630-637.
    • Benestad, R. E. and Chen, D. 2006. The use of a Calculus-based Cyclone Identification method for generating storm statistics. Tellus, 58A, 473-486, doi:10.1111/j.1600-0870.2006.00191.x.
    • Benestad, R. E., Hanssen-Bauer, I. and Førland, E. J. 2002. Empirically downscaled temperature scenarios for Svalbard. Atm. Sci. Lett., 3, Issue 2-4, doi.10.1006/asle.2002.0051, 71-93.
    • Derome, J., Brunet, G., Plante, A., Gagnon, N., Boer, G. J. and coauthors. 2001. Seasonal Predictions Based on Two Dynamical Models. Atm.-Ocean, 39(4), 485-501.
    • Deser, C., Magnusdottir, G., Saravanan, R. and Phillips, A. 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. Clim. 17, 877-889.
    • Dix, M. R. and Hunt, B. G. 1995. Chaotic influences and the problem of deterministic seasonal predictions. Int. J. Climatol. 15(7), 729-752.
    • Doblas-Reyes, F. J., Hagedorn, R. and Palmer, T. N. 2007. Developments in dynamical seasonal forecasting relevant to agricultural management. Clim. Res. 33, 19-26.
    • Francis, J. A., Chan, W., Leathers, D. J., Miller, J. R. and Veron, D. E. 2009. Winter Northern Hemisphere weather patterns remember summer Arctic sea ice extent. Geophys. Res. Lett. 36, L07503 doi:10.1029/2009GL037274.
    • Hill, T. and Lewicki, P. 2005. Statistics: Methods and Applications : A Comprehensive Reference for Science, Industry, and Data Mining. Tulsa, OK, USA: StatSoft.
    • Holland, M. M., bitz, C. M. and Tremblay, B. 2006. Future abrupt reductions in the summer Arctic sea ice. Geophys. Res. Lett. 33, L23503, doi:10.1029/2006GL028024.
    • Johansson, Å. 2007. Prediction skill of the NAO and PNA from Daily to Seasonal Time Scales. J. Clim. 20, 1957-1975.
    • Kauker, F., Kaminski, T., Karcher, M., Giering, R., Gerdes, R. and coauthors. 2009. Adjoint analysis of the 2007 all time Arctic sea-ice minimum. Geophys. Res. Lett. 36, L03707, doi:10.1029/2008GL036323.
    • Kundzewicz, Z. W., Mata, L. J., Arnell, N., Do¨ll, P., Kabat, P. and coauthors. 2007. Climate Change: Impacts, Adaptation and Vulnerabilit. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, United Kingdom and New York, NY, USA.
    • Lorenz, E. 1967. The Nature and Theory of the General Circulation of the Atmosphere. Publication 218. World Meteorological Organization, Geneva, Switzerland.
    • Magnusdottir, G., Deser, C. and Saravanan, R. 2004. The Effects of North Atlantic SST and Sea Ice Anomalies on the Winter Circulation in CCM3. Part I:Main Features and Storm Track Characteristics of the Response. J. Clim. 17, 857-875.
    • Meehl, G. A., Stocker, T. F., Idlingstein, W. D., Gaye, A. T., Gregory, J. M., Kitoh, A., Knutti, R., Murphy, J. M., Noda, A., Raper, S. C. B., Watterson, I. G., Weaver, A. J., Zhao, Z.-C. 2007. Climate Change: The Physical Science Basis. Chap. Global Climate Projections. United Kingdom and New York, NY, USA. Cambridge University Press.
    • Melsom, A. 2009. Ocean sea ice atmosphere heat fluxes over the Arctic Ocean. Note 14/2009. met.no, http://met.no/Forskning/ Publikasjoner 2009.
    • Overland, J. E. and Wang, M. 2010. Large-scale atmospheric circulation changes are associated with the recent loss of Arctic sea ice. Tellus A. 62, 1-9.
    • Persson, A. and Grazzini, F. 2005. User Guide to ECMWF forecast products. Meteorological Bulletin M3.2. ECMWF, www.ecmwf.int/products/forecasts/guide/user_guide.pdf.
    • R Development Core Team. 2004. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0.
    • Reynolds, R. W., Rayner, N. R., Smith, T. M., Stokes, D. C. and Wang, W. 2002. An improved in situ and satellite SST analysis for climate. J. Clim. 15, 1609-1625.
    • Rowell, D. P. 1998. Assessing Potential Seasonal Predictability with an Ensemble of Multidecadal GCM Simulations. J. Clim. 11, 109-120.
    • Seierstad, I. A. and Bader, J. 2008. Impact of a projected future Arctic Sea Ice reduction on extratropical storminess and the NAO. Clim. Dynam. 33, 937-943.
    • Senan, R. and Benestad, R. E. 2009. Transitional irregularity in sea surface temperature from the ECMWF operational ocean analysis. Note 22. met.no, www.met.no.
    • Serreze, M. C., Barrett, A. P., Stroeve, J. C., Kindig, D. N. and Holland, M. M. 2009. The emergence of surface-based Arctic amplification. The Cryosphere 3, 11-19 doi:10.5194/tc-3-11-2009.
    • Singarayer, J. S., Bamber, J. L. and Valdes, P. J. 2006. Twenty-firstCentury Impacts from a Declining Arctic Sea Ice Cover. J. Clim. 19, 1109-1125.
    • Sivakumar, M. V. K. 2007. climate prediction and agriculture: current status and future challenges. Clim. Res. 33, 3-17.
    • Sorteberg, A. and Kvingedal, B. 2006. Atmospheric Forcing on the Barents Sea Winter Ice Extent. J. Clim. 19, 4772-4784.
    • Stockdale, T. N., Anderson, D. L. T., Alves, J. O. S. and Balmaseda, M. A. 1998. Global seasonal rainfall forecasts using a coupled oceanatmosphere model. Nature 392, 370-373.
    • Stroeve, J., Holland, M. M., Meier, W., Scambos, T. and Serreze, M. 2007. Artic sea ice decline: Faster than forecast. Geophys. Res. Lett. 34, L09501 doi:10.1029/3007GL029703.
    • Stroeve, J., Serreze, M., Drobot, S., Gearheard, S., Holland, M. and coauthors. 2008. Arctic Sea Ice Extent Plummets in 2007. Eos 89(2), 13-14.
    • Wilkinson, G. N. and Rogers, C. E. 1973. Symbolic Description of Factorial Models for Analysis of Variance. Appl. Stat. 22, 392- 399.
    • Wilks, D. S. 2006. On “Field Significance” and the False Discovery Rate. J. Appl. Meteorol. Climatol. 45, 1181-1189 doi:10.1175/JAM2404.1.
    • Wilks, D. S. 1995. Statistical Methods in the Atmospheric Sciences. Orlando, Florida, USA, Academic Press.
    • Yan, Z., Bate, S., Chandler, R. E., Isham, V. and Wheater, H. 2006. Changes in extreme wind speeds in NW Europe simulated by generalized linear models. Theoret. Appl. Climatol. 83, 121-137.
  • Inferred research data

    The results below are discovered through our pilot algorithms. Let us know how we are doing!

    Title Trust
    43
    43%
    40
    40%
  • No similar publications.

Share - Bookmark

Cite this article