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International Conference on Large-Scale Scientific Computing

LSSC 2015: Large-Scale Scientific Computing pp 327–334Cite as

Snow Cover Assessment with Regional Climate Model - Problems and Results

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9374))

Abstract

Climate modelling, either global or regional, is usually treated as a typical large-scale scientific computational problem. The regional climate model RegCM, well-known within the meteorological community, is applied in the study to estimate quantitatively the snow water equivalent, which is the most consistent snow cover parameter. Multiple runs for a time window of 14 consecutive winters with different model configurations, in particular with various initial and boundary conditions, have been performed, in an attempt to obtain most adequate representation of the real snow cover. The results are compared with stations’ measurements from the network of the National Institute of Meteorology and Hydrology. Generally all runs yield similar results, where the overall (i.e. over the whole time span) biases are acceptable, but, however, with large discrepancies in the day-by-day comparisons, which is typical for climate modelling studies.

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References

  1. Arakawa, A., Schubert, W.H.: Interaction of a cumulus cloud ensemble with the large-scale environment, Part I. J. Atmos. Sci. 31, 674–701 (1974)

    Article  Google Scholar 

  2. Braun, R.D., Walker, A.E., Goodison, B.: Seasonal snow cover monitoring in Canada: an assessment of Canadian contributions for global climate monitoring. In: Proceedings of the 57th Eastern Snow Conference, Syracuse, NY, pp. 1–11 (2000)

    Google Scholar 

  3. Clifford, D.: Global estimates of snow water equivalent from passive microwave instruments: history, challenges and future developments. Int. J. Remote Sens. 31, 3707–3726 (2010)

    Article  Google Scholar 

  4. 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., Bidlot, 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., Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. soc. 137, 553–597 (2011)

    Article  Google Scholar 

  5. Dickinson, R., Henderson-Sellers, A., Kennedy, P.J.: Biosphere-Atmosphere Transfer Scheme, BATS: version1E as coupled to the NCAR community climate model. NCAR Tech Note NCAR/TN-387+ STR. National Center for Atmospheric Research, Boulder CO (1993)

    Google Scholar 

  6. Giorgi, F., Coppola, E., Solomon, F., Mariotti, L., Sylla, M.B., Bi, X., Elguindi, N., Diro, G.T., Nair, V., Giuliani, G., Turuncoglu, U.U., Cozzini, S., Guttler, I., O’Brien, T.A., Tawfic, A.B., Shalaby, A., Zakey, A.S., Steiner, A.L., Stordal, F., Sloan, L.C., Brankovic, C.: RegCM4: model description and preliminary tests over multiple CORDEX domains. Clim. Res. 52, 7–29 (2012)

    Article  Google Scholar 

  7. Grell, G.A.: Prognostic evaluation of assumptions used by cumulus parametrizations. Mon. Weather Rev. 121, 764–787 (1993)

    Article  Google Scholar 

  8. Grell, G.A., Dudhia, J., Stauer, D.R.: A description of the fifth-generation Penn State/NCAR mesoscale model (mm5). Technical report NCAR/TN-398+ STR, National Center for Atmospheric Research, Boulder CO (1994)

    Google Scholar 

  9. Hancock, S., Baxter, R., Evans, J., Huntley, B.: Evaluating global snow water equivalent products for testing land surface models. Remote Sens. Environ. 128, 107–117 (2013)

    Article  Google Scholar 

  10. Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S.K., Hnilo, J.J., Fiorino, M., Potter, G.L.: NCEP-DOE AMIP- II reanalysis (R-2). Bull. Am. Meteorol. Soc. 83, 1631–1643 (2002)

    Article  Google Scholar 

  11. Kiehl, J.T., Hack, J.J., Bonan, G.B., Boville, B.A., Briegleb, B.P., Williamson, D., Rasch, P.: Description of the NCAR community climate model (ccm3). Technical report NCAR/TN-420+ STR. National Center for Atmospheric Research, Boulder CO (1996)

    Google Scholar 

  12. Liston, G.E.: Representing subgrid snow cover heterogeneities in regional and global models. J. Clim. 17, 1381–1397 (2004)

    Article  Google Scholar 

  13. Oleson, K.W., Dai, Y., Bonan, G., Bosilovich, M., et al.: Technical description of the Community Land Model. National Center for Atmospheric Research Tech Note NCAR/TN-461+ STR, NCAR, Boulder CO (2004)

    Google Scholar 

  14. Oleson, K.W., Niu, G.Y., Yang, Z.L., Lawrence, D.M., et al.: Improvements to the Community Land Model and their impact on the hydrologic cycle. J. Geophys. Res. 113, G01021 (2008). doi:10.1029/2007JD000563

    Google Scholar 

  15. Pal, J.S., Small, E.E., Eltahir, E.A.B.: Simulation of regional-scale water and energy budgets: representation of subgrid cloud and precipitation processes within RegCM. J. Geophys. Res. 105, 29579–29594 (2000)

    Article  Google Scholar 

  16. Steiner, A.L., Pal, J., Giorgi, F., Dickinson, R.E., Chameides, W.L.: Coupling of the Common Land Model (CLM0) to a regional climate model (RegCM). Theoret. Appl. Climatol. 82(3–4), 225–243 (2005)

    Article  Google Scholar 

  17. Yang, F., Kumar, A., Wang, W., Juang, H.-M.H., Kanamitsu, M.: Snow-albedo feedback and seasonal climate variability over North America. J. Clim. 14, 4245–4248 (2001)

    Article  Google Scholar 

  18. Xue, Y., Janjic, Z., Dudhia, J., Vasic, R., De Sales, F.: A review on regional dynamical downscaling in intraseasonal to seasonal simulation/prediction and major factors that affect downscaling ability. Atmos. Res. 147–148(2014), 68–85 (2014)

    Article  Google Scholar 

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Acknowledgments

Deep gratitude to the organizations and institutes (ICTP, ECMWF, NCEP-NCAR, Unidata, MPI-M and all others), which provides free of charge software and data. Without their innovative data services and tools this study would be not possible.

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Authors and Affiliations

  1. National Institute of Meteorology and Hydrology, Bulgarian Academy of Sciences, Tsarigradsko Shose 66, 1784, Sofia, Bulgaria

    Hristo Chervenkov, Todor Todorov & Kiril Slavov

Authors
  1. Hristo Chervenkov
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  2. Todor Todorov
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  3. Kiril Slavov
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Corresponding author

Correspondence to Hristo Chervenkov .

Editor information

Editors and Affiliations

  1. Bulgarian Academy of Sciences, Sofia, Bulgaria

    Ivan Lirkov

  2. Inst. of Inform. & Communication, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Svetozar D. Margenov

  3. Informatics and Mathematical Modell, Technical University of Denmark, Kongens Lyngby, Denmark

    Jerzy Waśniewski

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© 2015 Springer International Publishing Switzerland

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Chervenkov, H., Todorov, T., Slavov, K. (2015). Snow Cover Assessment with Regional Climate Model - Problems and Results. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2015. Lecture Notes in Computer Science(), vol 9374. Springer, Cham. https://doi.org/10.1007/978-3-319-26520-9_36

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  • DOI: https://doi.org/10.1007/978-3-319-26520-9_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26519-3

  • Online ISBN: 978-3-319-26520-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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