Comparative Analysis of the Western Arctic Surface Climate among Observations and Model Simulations

Wanli Wu Research Application Laboratory, National Center for Atmospheric Research, Boulder, Colorado

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Amanda H. Lynch School of Geography and Environmental Sciences, Monash University, Clayton, Australia

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Sheldon Drobot Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado

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James Maslanik Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado

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A. David McGuire U.S. Geological Survey, Alaska Cooperative Fish and Wildlife Research Unit, University of Alaska Fairbanks, Fairbanks, Alaska

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Ute Herzfeld Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado

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Abstract

Accurate estimates of the spatial and temporal variation in terrestrial water and energy fluxes and mean states are important for simulating regional hydrology and biogeochemistry in high-latitude regions. Furthermore, it is necessary to develop high-resolution hydroclimatological datasets at finer spatial resolutions than are currently available from global analyses. This study uses a regional climate model (RCM) to develop a hydroclimatological dataset for hydrologic and ecological application in the Western Arctic. The fifth-generation Penn State–NCAR Mesoscale Model (MM5) forced by global reanalysis products at the boundaries is used to perform 12 yr of simulation (1990 through 2001) over the Western Arctic. An analysis that compares the RCM simulations with independent observationally derived data sources is conducted to evaluate the temporal and spatial distribution of the mean states, variability, and trends during the period of simulation. The RCM simulation of sea level pressure agrees well with the reanalysis in terms of mean states, seasonality, and interannual variability. The RCM also simulates major spatial patterns of the observed climatology of surface air temperature (SAT), but RCM SAT is generally colder in the summertime and warmer in the wintertime in comparison with other datasets. Although there are biases in the mean state of SAT, the RCM simulations of the seasonal and interannual variability of SAT are similar to variability in observationally derived datasets. The RCM also simulates general spatial patterns of observed rainfall, but the modeled mean state of precipitation is characterized by large biases relative to observationally derived datasets. In particular, the RCM tends to overestimate coastal region precipitation but underestimates precipitation in the interior of the Western Arctic. The Arctic terrestrial surface climate trends for the period of 1992 to 2001 of the RCM are similar to those derived from observations, with sea level pressure decreasing 0.15 hPa decade−1, SAT increasing 0.10°C decade−1, and precipitation decreasing slightly in the RCM simulations. In summary, the RCM dataset produced in this study represents an improvement over data currently available from large-scale global reanalysis and provides a consistent meteorological forcing dataset for hydrologic and ecological applications.

* Corresponding author address: Wanli Wu, Research Application Laboratory, National Center for Atmospheric Research, 3450 Mitchell Lane, Boulder, CO 80301. wanliwu@ucar.edu

This article included in Western Arctic Linkage Experiment (WALE) special collection.

Abstract

Accurate estimates of the spatial and temporal variation in terrestrial water and energy fluxes and mean states are important for simulating regional hydrology and biogeochemistry in high-latitude regions. Furthermore, it is necessary to develop high-resolution hydroclimatological datasets at finer spatial resolutions than are currently available from global analyses. This study uses a regional climate model (RCM) to develop a hydroclimatological dataset for hydrologic and ecological application in the Western Arctic. The fifth-generation Penn State–NCAR Mesoscale Model (MM5) forced by global reanalysis products at the boundaries is used to perform 12 yr of simulation (1990 through 2001) over the Western Arctic. An analysis that compares the RCM simulations with independent observationally derived data sources is conducted to evaluate the temporal and spatial distribution of the mean states, variability, and trends during the period of simulation. The RCM simulation of sea level pressure agrees well with the reanalysis in terms of mean states, seasonality, and interannual variability. The RCM also simulates major spatial patterns of the observed climatology of surface air temperature (SAT), but RCM SAT is generally colder in the summertime and warmer in the wintertime in comparison with other datasets. Although there are biases in the mean state of SAT, the RCM simulations of the seasonal and interannual variability of SAT are similar to variability in observationally derived datasets. The RCM also simulates general spatial patterns of observed rainfall, but the modeled mean state of precipitation is characterized by large biases relative to observationally derived datasets. In particular, the RCM tends to overestimate coastal region precipitation but underestimates precipitation in the interior of the Western Arctic. The Arctic terrestrial surface climate trends for the period of 1992 to 2001 of the RCM are similar to those derived from observations, with sea level pressure decreasing 0.15 hPa decade−1, SAT increasing 0.10°C decade−1, and precipitation decreasing slightly in the RCM simulations. In summary, the RCM dataset produced in this study represents an improvement over data currently available from large-scale global reanalysis and provides a consistent meteorological forcing dataset for hydrologic and ecological applications.

* Corresponding author address: Wanli Wu, Research Application Laboratory, National Center for Atmospheric Research, 3450 Mitchell Lane, Boulder, CO 80301. wanliwu@ucar.edu

This article included in Western Arctic Linkage Experiment (WALE) special collection.

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  • Adler, R. F. Coauthors 2003. The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–present). J. Hydrometeor. 4:11471167.

    • Search Google Scholar
    • Export Citation
  • Bogdanova, E. G., B. M. Ilyin, and I. V. Dragomilova. 2002. Application of a comprehensive bias-correction model to precipitation measured at Russian North Pole drifting stations. J. Hydrometeor. 3:700713.

    • Search Google Scholar
    • Export Citation
  • Bonan, G. 2002. Ecological Climatology: Concepts and Applications. Cambridge University Press, 690 pp.

  • Briegleb, B. P. 1992. Delta-Eddington approximation for solar radiation in the NCAR Community Climate Model. J. Geophys. Res. 97:76037612.

    • Search Google Scholar
    • Export Citation
  • Drobot, S., J. Maslanik, U. C. Herzfeld, C. Fowler, and W. Wu. 2006. Uncertainty in and precipitation datasets over terrestrial regions of the Western Arctic. Earth Interactions 10.[Available online at http://EarthInteractions.org.].

    • Search Google Scholar
    • Export Citation
  • Grell, G. A., J. Dudhia, and D. S. Stauffer. 1994. A description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5). NCAR Tech. Note, NCAR/TN-398+STR, 117 pp.

  • Hong, S. and H. Pan. 1996. Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev. 124:23222339.

  • Kalnay, E. Coauthors 1996. The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc. 77:437471.

  • Liang, X-Z., J. Pan, J. Zhu, K. E. Kunkel, J. X. L. Wang, and A. Dai. 2006. Regional climate model downscaling of the U.S. summer climate and future change. J. Geophys. Res. 111.D10108, doi:10.1029/2005JD006685.

    • Search Google Scholar
    • Export Citation
  • Jones, P. D. and A. Moberg. 2003. Hemispheric and large-scale surface air temperature variations: An extensive revision and an update to 2001. J. Climate 16:206223.

    • Search Google Scholar
    • Export Citation
  • Mass, C. F. and Y-H. Kuo. 1998. Regional real-time numerical weather prediction: Current status and future potential. Bull. Amer. Meteor. Soc. 79:253263.

    • Search Google Scholar
    • Export Citation
  • McGuire, A. D., F. S. Chapin III, J. E. Walsh, and C. Wirth. 2006. Integrated regional changes in arctic climate feedbacks: Implications for the global climate system. Annu. Rev. Environ. Resour. 31:6191.

    • Search Google Scholar
    • Export Citation
  • McGuire, A. D. Coauthors 2007. The Western Arctic Linkage Experiment: Overview and synthesis. Earth Interactions submitted.

  • Mlawer, E. J., S. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough. 1997. Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res. 102:1666316682.

    • Search Google Scholar
    • Export Citation
  • Moritz, R. E., C. M. Bitz, and E. J. Steig. 2002. Dynamics of recent climate change in the Arctic. Science 297:14971502.

  • Murphy, J. 1999. An evaluation of statistical and dynamical techniques for downscaling local climate. J. Climate 12:22562284.

  • Rawlins, M. A., S. Frolking, R. B. Lammers, and C. J. Vorosmarty. 2006. Effects of uncertainty in climate inputs on simulated evapotranspiration and runoff in the western Arctic. Earth Interactions 10.[Available online at http://EarthInteractions.org.].

    • Search Google Scholar
    • Export Citation
  • Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland, L. V. Alexander, D. P. Rowell, E. C. Kent, and A. Kaplan. 2003. Global analysis 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
  • Reisner, J. R., M. Rasmussen, and R. T. Bruintjes. 1998. Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model. Quart. J. Roy. Meteor. Soc. 124:10711107.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E. 2001. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. 106:71837192.

  • Thompson, D. W. J. and J. M. Wallace. 1998. The Arctic Oscillation signature in the wintertime geopotential height and temperature fields. Geophys. Res. Lett. 25:12971300.

    • Search Google Scholar
    • Export Citation
  • Uppala, S. M. Coauthors 2005. The ERA-40 re-analysis. Quart. J. Roy. Meteor. Soc. 131:29613012.

  • Walsh, J. E., V. Kattsov, D. Portis, and V. Meleshko. 1998. Arctic precipitation and evaporation: Model results and observational estimates. J. Climate 11:7287.

    • Search Google Scholar
    • Export Citation
  • Walsh, J. E., V. M. Kattsov, W. L. Chapman, V. Govorkova, and T. Pavlova. 2002. Comparison of Arctic climate simulations by uncoupled and coupled global models. J. Climate 15:14291446.

    • Search Google Scholar
    • Export Citation
  • Willmott, C. J. and K. Matsuura. 1995. Smart interpolation of annually averaged air temperature in the United States. J. Appl. Meteor. 34:25772586.

    • Search Google Scholar
    • Export Citation
  • Wu, W. and A. H. Lynch. 2000. Response of the seasonal carbon cycle in high latitudes to climate anomalies. J. Geophys. Res. 105:2289722908.

    • Search Google Scholar
    • Export Citation
  • Wu, W., A. H. Lynch, and A. Rivers. 2005. Estimating the uncertainty in a regional climate model related to initial and lateral boundary conditions. J. Climate 18:917933.

    • Search Google Scholar
    • Export Citation
  • Xie, P. and P. Arkin. 1998. Global monthly precipitation estimates from satellite-observed outgoing longwave radiation. J. Climate 11:134164.

    • Search Google Scholar
    • Export Citation
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