Advertisement

Alaskan Regional Climate Changes in Dynamically Downscaled CMIP5 Simulations

  • Jing ZhangEmail author
  • Jeremy Krieger
  • Uma Bhatt
  • Chuhan Lu
  • Xiangdong Zhang
Conference paper

Abstract

Global models are the most widely used tools for understanding and assessing climatic variability and changes. However, coarse-resolution limits their capability to capture detailed finer-scale meteorological features, including heterogeneous spatial distributions and high-frequency temporal variability. In this study, the mesoscale Weather Research and Forecasting (WRF) model is used to dynamically downscale a CMIP5 global model simulation (CCSM MOAR output) for a portion of the Arctic marginal zone, encompassing Alaska and surrounding areas, with the aim to improve understanding, representation, and future projection of high-resolution climate changes in the area. Dynamic downscaling of the twentieth century simulation was conducted for the period 1991–2005 and validated against in situ observations archived by the NCDC. Downscaled results generally capture observed conditions well. However, cold biases exist across most of the study area, except for a weak warm bias along the western and northern Alaskan coasts. In addition, downscaled winds are stronger than observations and precipitation is overestimated along the Alaskan panhandle. The biases in the downscaled temperature, wind speed, and precipitation are correctable. The downscaled temperature bias exhibits strong seasonality, with a warm bias in the cold months and a cold bias in the warm months, particularly along the western and northern Alaskan coasts. Seasonality in the wind speed and precipitation biases, however, is relatively small. Under the RCP6 scenario, downscaled regional climate over Alaska and the surrounding areas demonstrate a significant warming trend over the entire study area during the twenty-first century, with the strongest warming occurring over the Arctic Ocean. Precipitation is also projected to increase along Alaska’s coastal areas and over the Arctic Ocean. Interior Alaska, on the other hand, becomes drier in the future climate scenario.

Keywords

Regional climate WRF downscaling Alaska 

Notes

Acknowledgement

This work was supported by the NSF Grants EAR-0943742, PLR-1304684, and ARC-1023592. Computing resources were provided by the Arctic Region Supercomputing Center at the University of Alaska Fairbanks.

References

  1. Bengtsson, L., Botzett, M., & Esch, M. (1996). Will greenhouse gas-induced warming over the next 50 years lead to higher frequency and greater intensity of hurricanes? Tellus, 48A, 57–73.CrossRefGoogle Scholar
  2. Chen, F., & Dudhia, J. (2001). Coupling an advanced land-surface hydrology model with the PSU/NCAR MM5 modeling system. Part I: Model description and implementation. Monthly Weather Review, 129, 569–585.CrossRefGoogle Scholar
  3. Comiso, J. C., Parkinson, C. L., Gersten, R., & Stock, L. (2008). Accelerated decline in the Arctic sea ice cover. Geophysical Research Letters, 35, L01703.CrossRefGoogle Scholar
  4. Gardner, A. S., Moholdt, G., Cogley, J. G., Wouters, B., Arendt, A. A., Wahr, J., et al. (2013). A reconciled estimate of glacier contributions to sea level rise: 2003 to 2009. Science, 340, 852–857. doi: 10.1126/science1234532.CrossRefGoogle Scholar
  5. Giorgi, F., Jones, C., & Asrar, G. (2009). Addressing climate information needs at the regional level: The CORDEX framework. WMO Bulletin, 58(V3), 175–183.Google Scholar
  6. Grell, G. A., & Devenyi, D. (2002). A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophysical Research. Letters, 29, 1693. doi: 10.1029/2002GL015311.CrossRefGoogle Scholar
  7. Gent, P. R., G. Danabasoglu, L. J. Donner, M. M. Holland, E. C. Hunke, S. R. Jayne et al. (2011). The community climate system model version 4. Journal of Climate, 24(19), 4973–4991.Google Scholar
  8. Hock, R., de Woul, M., Radić, V., & Dyurgerov, M. (2009). Mountain glaciers and ice caps around Antarctica make a large sea-level rise contribution. Geophysical Research Letters, 36, L07501. doi: 10.1029/2008GL037020.CrossRefGoogle Scholar
  9. Iacono, M., Delamere, J., Mlawer, E., Shephard, M., Clough, S., & Collins, W. (2008). Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. Journal of Geophysical Research, 113, D13103.CrossRefGoogle Scholar
  10. Janjic, Z. I. (1994). The step-mountain Eta coordinate model: Further developments of the convection, viscous sublayer and turbulence closure schemes. Monthly Weather Review, 122, 927–945.CrossRefGoogle Scholar
  11. Janjic, Z. I. (1996). The Mellor-Yamada level 2.5 scheme in the NCEP Eta Model. In 11th Conference on Numerical Weather Prediction, Norfolk, VA, American Meteorological Society, pp. 333–334.Google Scholar
  12. Janjic, Z. I. (2002). Nonsingular implementation of the Mellor–Yamada level 2.5 scheme in the NCEP meso model. NCEP Office Note, No. 437, National Centers for Environmental Prediction, 61p.Google Scholar
  13. Kalnay, E., et al. (1996). The NCEP/NCAR 40-year reanalysis project. Bulletin of American Meteorological Society, 77, 437–471.CrossRefGoogle Scholar
  14. Leung, L. R., Mearns, L. O., Giorgi, F., & Wilby, R. (2003). Workshop on regional climate research: Needs and opportunities. Bulletin of American Meteorological Society, 84, 89–95.CrossRefGoogle Scholar
  15. Lynch, A. H., McGinnis, D. L., & Bailey, D. A. (1998). Snow-albedo feedback and the spring transition in a regional climate system model: Influence of land surface model. Journal of Geophysical Research, 103, 29037–29049.CrossRefGoogle Scholar
  16. Mearns, L. O., Gutowski, W. J., Jones, R., Leung, L.-Y., McGinnis, S., Nunes, A. M. B., et al. (2009). A regional climate change assessment program for North America. Eos, 90, 311–312.CrossRefGoogle Scholar
  17. Mellor, G. L., & Yamada, T. (1982). Development of a turbulence closure model for geophysical fluid problems. Review of Geophysics Space Physics, 20, 851–875.CrossRefGoogle Scholar
  18. Morrison, H. C., Thompson, G., & Tatarskii, V. (2009). Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Monthly Weather Review, 137, 991–1007.CrossRefGoogle Scholar
  19. Osterkamp, T. E. (2003). A thermal history of permafrost in Alaska. In Proceedings of Eighth International Conference on Permafrost, Zurich, pp. 863–868.Google Scholar
  20. Skamarock, W. C., et al. (2008). A description of the advanced research WRF version 3. NCAR Technical Note, NCAR/TN–475+STR, 113pp.Google Scholar
  21. Stegall, S. T., & Zhang, J. (2012). Wind field climatology, changes, and extremes in the Chukchi–Beaufort Seas and Alaska North Slope during 1979–2009. Journal of Climate, 25, 8075–8089.CrossRefGoogle Scholar
  22. Stroeve, J. C., Serreze, M. C., Holland, M. M., Kay, J. E., Malanik, J., & Barrett, A. P. (2012). The Arctic’s rapidly shrinking sea ice cover: A research synthesis. Climatic Change, 110, 1005–1027.CrossRefGoogle Scholar
  23. Whitfield, J. (2003). Alaska’s climate: Too hot to handle. Nature, 425, 338–339. doi: 10.1038/425338a.CrossRefGoogle Scholar
  24. Zhang, J., Bhatt, U. S., Tangborn, W. V., & Lingle, C. S. (2007). Climate downscaling for estimating glacier mass balances in northwestern North America: Validation with a USGS benchmark glacier. Geophysical Research Letters, 34, L21505. doi: 10.1029/2007GL031139.CrossRefGoogle Scholar
  25. Zhang, X., & Zhang, J. (2001). Heat and freshwater budgets and pathways in the Arctic Mediterranean in a coupled ocean/sea-ice model. Journal of Oceanography, 57, 207–237.CrossRefGoogle Scholar
  26. Zhang, X., Zhang, J., Krieger, J., Shulski, M., Liu, F., Stegall, S., et al. (2013). Beaufort and Chukchi Seas mesoscale meteorology modeling study, Final Report. U. S. Department of the Interior, Bureau of Ocean Energy Management. OCS Study BOEM 2013-0119, 204p., www.boem.gov/BOEM-2013-0119.

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jing Zhang
    • 1
    • 2
    Email author
  • Jeremy Krieger
    • 3
  • Uma Bhatt
    • 4
  • Chuhan Lu
    • 5
    • 6
  • Xiangdong Zhang
    • 5
  1. 1.Department of PhysicsNorth Carolina A&T State UniversityGreensboroUSA
  2. 2.Department of Energy and Environmental SystemsNorth Carolina A&T State UniversityGreensboroUSA
  3. 3.Arctic Region Supercomputing Center, University of Alaska FairbanksFairbanksUSA
  4. 4.Geophysical Institute, University of Alaska FairbanksFairbanksUSA
  5. 5.International Arctic Research Center, University of Alaska FairbanksFairbanksUSA
  6. 6.Nanjing University of Information Science and TechnologyNanjingChina

Personalised recommendations