Skip to main content
Log in

Impacts of systematic precipitation bias on simulations of water and energy balances in Northwest America

  • Published:
Advances in Atmospheric Sciences Aims and scope Submit manuscript

Abstract

At high latitudes and in mountainous areas, evaluation and validation of water and energy flux simulations are greatly affected by systematic precipitation errors. These errors mainly come from topographic effects and undercatch of precipitation gauges. In this study, the Land Dynamics (LaD) land surface model is used to investigate impacts of systematic precipitation bias from topography and wind-blowing on water and energy flux simulation in Northwest America. The results show that topographic and wind adjustment reduced bias of streamflow simulations when compared with observed streamflow at 14 basins. These systematic biases resulted in a −50%–100% bias for runoff simulations, a −20%–20% bias for evapotranspiration, and a −40%–40% bias for sensible heat flux, subject to different locations and adjustments, when compared with the control run. Uncertain gauge adjustment leads to a 25% uncertainty for precipitation, a 20%–100% uncertainty for runoff simulation, a less-than-10% uncertainty for evapotranspiration, and a less-than-20% uncertainty for sensible heat flux.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Adam, J. C., and D. P. Lettenmaier, 2003: Ad justment of global gridded precipitation for systematic bias. J. Geophys. Res., 108, 4257, doi:10.1029/2002JD002499.

    Article  Google Scholar 

  • Adam, J. C., E. A. Clark, D. P. Lettenmaier, and E. F. Wood, 2006: Correction of global precipitation products for orographic effects. J. Climate, 19, 15–38.

    Google Scholar 

  • Bogdanova, E. G., V. S. Golubev, B. M. Ilyin, and I. V. Dragomilova, 2002: A new model for bias correction of precipitation measurements, and its application to polar regions of Russia. Russian Meteorology and Hydrology, 10, 68–94.

    Google Scholar 

  • Cosgrove, B, and Coauthors, 2003: Real-time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project. J. Geophys. Res., 108, 8842, doi: 10.1029/2002JD003118.

    Article  Google Scholar 

  • Daly, C., R. P. Neilson, and D. L. Phillips, 1994: A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J. Appl. Meteor., 33, 140–158.

    Article  Google Scholar 

  • Goodison, B. E., P. Y. T. Louie, and D. Yang, 1998: WMO solid precipitation intercomparison. Final Rep., WMO/TD-872, World Meteorological Organization, Geneva, 212pp.

    Google Scholar 

  • Koster, R., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 1138–1140.

    Article  Google Scholar 

  • Legates, D. R., 1987: A climatology of global precipitation. Publications in Climatology, 40(1), 86pp.

  • Legates, D. R., and C. J. Willmott, 1990: Mean seasonal and spatial variability in gauge-corrected, global precipitation. International Journal of Climatology, 10, 111–127.

    Article  Google Scholar 

  • Lohmann, D., and Coauthors, 2004: Streamflow and water balance intercomparisons of four land-surface models in the North American Land Data Assimilation System project. J. Geophys. Res., 109, D07S91, doi:10.1029/2003JD003517.

  • Manabe, S., 1969: Climate and the ocean circulation: 1, The atmospheric circulation and the hydrology of the earth’s surface. Mon. Wea. Rev., 97, 739–805.

    Article  Google Scholar 

  • Matthews, E., 1983: Global vegetation and land use: New high-resolution data bases for climate studies. J. Climate Appl. Meteor., 22, 474–487.

    Article  Google Scholar 

  • Meeson, B. W., F. E. Coprew, J. M. P. McManus, D. M. Myers, J. W. Closs, K.-S. Sun, D. J. Sunday, and P. J. Sellers, 1995: ISLSCP Initiative I—Global Data Sets for Lan-Atmosphere Models, 1987–1988, Vols. 1–5, NASA, CD-ROM, USA NASA GDAAC ISLSCP 001/002/003/004/005.

  • Milly, P. C. D., and A. B. Shmakin, 2002a: Global modeling of land water and energy balances. Part I: The land dynamics (LaD) model. Journal of Hydrometeorology, 3, 283–299.

    Article  Google Scholar 

  • Milly, P. C. D., and A. B. Shmakin, 2002b: Global modeling of land water and energy balances. Part II: Land-characteristic contributions to spatial variability. Journal of Hydrometeorology, 3, 301–310.

    Article  Google Scholar 

  • Milly, P. C. D., and K. A. Dunne, 2002a: Macroscale water fluxes, 1. Quantifying errors in the estimation of basin mean precipitation. Water Resour. Res., 38, 1205, doi: 10.1029/2001WR000759.

    Article  Google Scholar 

  • Milly, P. C. D., and K. A. Dunne, 2002b: Macroscale water fluxes, 2. Water and energy supply control of their interannual variability. Water Resour. Res., 38, 1206, doi: 10.1029/2001WR000760.

    Article  Google Scholar 

  • Mitchell, K. E., and Coauthors, 2004: The multiinstitution North America Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J. Geophys. Res., 109, D07S90, doi:10.1029/2003JD003823.

  • Oki, T., T. Nishimura, and P. Dirmeyer, 1999: Assessment of annual runoff from land surface models using Total Runoff Integrating Pathways (TRIP). J. Meteor. Soc. Japan, 77, 235–255.

    Google Scholar 

  • Xia, Y., 2006: Optimization and uncertainty estimates of WMO regression models for the systematic-bias adjustment of NLDAS precipitation in the United States. J. Geophys. Res., 111, D08102, doi: 10.1029/2005JD006188.

  • Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78, 2539–2558.

    Article  Google Scholar 

  • Yang, D., B. E. Goodison, J. R. Metcalfe, V. S. Golubev, R. Bates, T. Pangburn, and C. L., Hanson, 1998: Accuracy of NWS 8-inch standard non-recording precipitation gague: Results of WMO intercomparison. J. Atmos. Oceanic Technol., 15, 54–68.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Youlong Xia.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Xia, Y., Xu, G. Impacts of systematic precipitation bias on simulations of water and energy balances in Northwest America. Adv. Atmos. Sci. 24, 739–749 (2007). https://doi.org/10.1007/s00376-007-0739-9

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00376-007-0739-9

Key words

Navigation