Editorial Type:
Article
Article Type:
Research Article

Uncertainties in North American Land Data Assimilation Systems over the Contiguous United States

Kingtse C. Mo Climate Prediction Center/NCEP/NWS/NOAA, Camp Springs, Maryland

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Li-Chuan Chen Cooperative Institute for Climate and Satellites, Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland

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Shraddhanand Shukla Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Theodore J. Bohn Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Dennis P. Lettenmaier Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Print Publication:
01 Jun 2012
DOI:
https://doi.org/10.1175/JHM-D-11-0132.1
Page(s):
996–1009
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Abstract

The Environmental Modeling Center (EMC) at the National Centers for Environmental Prediction (NCEP) and the University of Washington (UW) run parallel drought monitoring systems over the continental United States based on the North American Land Data Assimilation System (NLDAS). The NCEP system uses four land surface models (LSMs): Variable Infiltration Capacity (VIC), Noah, Mosaic, and Sacramento (SAC). The UW system uses VIC, SAC, Noah, and the Community Land Model (CLM). An assessment of differences in drought characteristics using both systems for the period 1979–2008 was performed. For soil moisture (SM) percentiles and runoff indices, differences are relatively small among different LSMs in the same system. However, the ensemble mean differences between the two systems are large over the western United States—in some cases exceeding 20% for SM and runoff percentile differences. These differences are most apparent after 2002 when the NCEP system transitioned to use the real-time North American Regional Reanalysis (NARR) and its precipitation gauge station data. (The UW system went into real-time operation in 2005.) Experiments were performed to address the sources of uncertainties. Comparison of simulations using the two systems with different model forcings indicates that the precipitation forcing differences are the primary source of the SM and runoff differences. While temperature, shortwave and longwave radiation, and wind speed forcing differences are also large after 2002, their contributions to SM and runoff differences are much smaller than precipitation.

Corresponding author address: Kingtse Mo, Climate Prediction Center/NCEP/NWS/NOAA, 5200 Auth Rd., Camp Springs, MD 20746. E-mail: kingtse.mo@noaa.gov

Abstract

The Environmental Modeling Center (EMC) at the National Centers for Environmental Prediction (NCEP) and the University of Washington (UW) run parallel drought monitoring systems over the continental United States based on the North American Land Data Assimilation System (NLDAS). The NCEP system uses four land surface models (LSMs): Variable Infiltration Capacity (VIC), Noah, Mosaic, and Sacramento (SAC). The UW system uses VIC, SAC, Noah, and the Community Land Model (CLM). An assessment of differences in drought characteristics using both systems for the period 1979–2008 was performed. For soil moisture (SM) percentiles and runoff indices, differences are relatively small among different LSMs in the same system. However, the ensemble mean differences between the two systems are large over the western United States—in some cases exceeding 20% for SM and runoff percentile differences. These differences are most apparent after 2002 when the NCEP system transitioned to use the real-time North American Regional Reanalysis (NARR) and its precipitation gauge station data. (The UW system went into real-time operation in 2005.) Experiments were performed to address the sources of uncertainties. Comparison of simulations using the two systems with different model forcings indicates that the precipitation forcing differences are the primary source of the SM and runoff differences. While temperature, shortwave and longwave radiation, and wind speed forcing differences are also large after 2002, their contributions to SM and runoff differences are much smaller than precipitation.

Corresponding author address: Kingtse Mo, Climate Prediction Center/NCEP/NWS/NOAA, 5200 Auth Rd., Camp Springs, MD 20746. E-mail: kingtse.mo@noaa.gov
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  • Anderson, E. A., 1973: National Weather Service River Forecast System: Snow accumulation and ablation model. NOAA Tech. Memo. NWS-HYDRO-17, 217 pp.

  • Andreadis, K. M., Clark E. A. , Wood W. , Hamlet A. F. , and Lettenmainer D. P. , 2005: Twentieth-century drought in the conterminous United States. J. Hydrometeor., 6, 985–1001.

    • Search Google Scholar
    • Export Citation

  • Burnash, R. J. C., Ferral R. L. , and McGuire R. A. , 1973: A generalized streamflow simulation system: Conceptual models for digital computers. Joint Federal and State River Forecast Center, U.S. National Weather Service and California Department of Water Resources Tech. Rep., 204 pp.

  • Cosgrove, B. A., 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.

    • Search Google Scholar
    • Export Citation

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

    • Search Google Scholar
    • Export Citation

  • Dirmeyer, P. A., Gao X. , Zhao M. , Guo Z. , Oki T. , and Hanaski N. , 2006: GSWP-2: Multimodel analysis and implications for our perception of the land surface. Bull. Amer. Meteor. Soc., 87, 1381–1397.

    • Search Google Scholar
    • Export Citation

  • Ek, M. B., Mitchell K. E. , Lin Y. , Rogers E. , Grunmann P. , Koren V. , Gayno G. , and Tarpley J. D. , 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J. Geophys. Res., 108, 8851, doi:10.1029/2002JD003296.

    • Search Google Scholar
    • Export Citation

  • Ek, M. B., and Coauthors, 2011: North American Land Data Assimilation System Phase 2 (NLDAS-2): Development and applications. GEWEX News, Vol. 21, No. 2, International GEWEX Project Office, Silver Spring, MD, 6–7.

  • Higgins, R. W., Shi W. , Yarosh E. , and Joyce R. , 2000: Improved United States precipitation quality control system and analysis. NCEP/Climate Prediction Center Atlas 7, U.S. Department of Commerce, 47 pp. [Available online at http://www.cpc.ncep.noaa.gov/research_papers/ncep_cpc_atlas/7/index.html.]

  • Idso, S. B., 1981: A set of equations for full spectrum and 8- to 14-μm and 10.5- to 12.5- μm thermal radiation from cloudless skies. Water Resour. Res., 17, 295–304.

    • Search Google Scholar
    • Export Citation

  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437–471.

  • Keyantash, J., and Dracup J. A. , 2002: The quantification of drought: An evaluation of drought indices. Bull. Amer. Meteor. Soc., 83, 1167–1180.

    • Search Google Scholar
    • Export Citation

  • Kimball, J. S., Running S. W. , and Nemani R. R. , 1997: An improved method for estimating surface humidity from daily minimum temperature. Agric. For. Meteor., 85, 87–98.

    • Search Google Scholar
    • Export Citation

  • Koren, V., Schaake J. , Mitchell K. , Duan Q.-Y. , Chen F. , and Baker J. M. , 1999: A parameterization of snowpack and frozen ground intended for NCEP weather and climate models. J. Geophys. Res., 104 (D16), 19 569–19 585.

    • Search Google Scholar
    • Export Citation

  • Liang, X., Lettenmainer D. P. , Wood E. F. , and Burges S. J. , 1994: A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophys. Res., 99 (D7), 14 415–14 428.

    • Search Google Scholar
    • Export Citation

  • Maurer, E. P., Wood A. W. , Adam J. C. , Lettenmaier D. P. , and Nijssen B. , 2002: A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States. J. Climate, 15, 3237–3251.

    • Search Google Scholar
    • Export Citation

  • McKee, T. B., Doesken N. J. , and Kleist J. , 1993: The relationship of drought frequency and duration to time scales. Preprints, Eighth Conf. on Applied Climatology, Anaheim, CA, Amer. Meteor. Soc., 179–184.

  • McKee, T. B., Doesken N. J. , and Kleist J. , 1995: Drought monitoring with multiple time scales. Preprints, Ninth Conf. on Applied Climatology, Dallas, TX, Amer. Meteor. Soc., 233–236.

  • Mo, K. C., 2008: Model-based drought indices over the United States. J. Hydrometeor., 9, 1212–1230.

  • NCDC, cited 2011: Billion dollar U.S. weather/climate disasters, 1980-2010. [Available online at http://www.ncdc.noaa.gov/oa/reports/billionz.html.]

  • Nijssen, B., Schnur R. , and Lettenmaier D. P. , 2001: Global retrospective estimation of soil moisture using the Variable Infiltration Capacity land surface model 1980–93. J. Climate, 14, 1790–1808.

    • Search Google Scholar
    • Export Citation

  • Oleson, K. W., and Coauthors, 2007: CLM 3.5 documentation. Tech. Memo. NCAR/CGD Terrestrial Science Section, Climate and Global Dynamics, 34 pp. [Available online at http://www.cgd.ucar.edu/tss/clmdistribution/clm3.5/CLM3_5_documentation.pdf.]

  • Pinker, R. T., and Coauthors, 2003: Surface radiation budgets in support of the GEWEX Continental-Scale International Project (GCIP) and the GEWEX Americas Prediction Project (GAPP), including the North American Data Assimilation System (NLDAS) project. J. Geophys. Res., 108, 8844, doi:10.1029/2002JD003301.

    • Search Google Scholar
    • Export Citation

  • Robock, A., and Coauthors, 2003: Evaluation of the North American Land Data Assimilation System over the southern Great Plains during the warm season. J. Geophys. Res., 108, 8846, doi:10.1029/2002JD003245.

    • Search Google Scholar
    • Export Citation

  • Shukla, S., and Wood A. W. , 2008: Use of a standardized runoff index for characterizing hydrologic drought. Geophys. Res. Lett., 35, L02405, doi:10.1029/2007GL032487.

    • Search Google Scholar
    • Export Citation

  • Svoboda, M., and Coauthors, 2002: The drought monitor. Bull. Amer. Meteor. Soc., 83, 1181–1190.

  • Tennessee Valley Authority, 1972: Heat and mass transfer between a water surface and the atmosphere. Water Resources Research Laboratory Rep. 14, Tennessee Valley Authority, Division of Water Control Planning, Engineering Laboratory Rep. 0-6803, 166 pp.

  • Thornton, P. E., and Running S. W. , 1999: An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation. Agric. For. Meteor., 93, 211–228.

    • Search Google Scholar
    • Export Citation

  • Wang, A., Bohn T. J. , Mahanama S. P. , Koster R. D. , and Lettenmaier D. P. , 2009: Multi model reconstruction of drought over the continental United States. J. Climate, 22, 2694–2712.

    • Search Google Scholar
    • Export Citation

  • Wood, A. W., and Lettenmaier D. P. , 2006: A test bed for new seasonal hydrologic forecasting approaches in the western United States. Bull. Amer. Meteor. Soc., 87, 1699–1712.

    • Search Google Scholar
    • Export Citation

  • Xia, Y., Ek M. , Wei H. , and Ming J. , 2012a: Comparative analysis of relationships between NLDAS-2 forcings and model outputs. Hydrol. Processes, 26, 467–474, doi:10.1002/hyp.8240.

    • Search Google Scholar
    • Export Citation

  • Xia, Y., and Coauthors, 2012b: Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products. J. Geophys. Res., 117, D03109, doi:10.1029/2011JD016048.

    • Search Google Scholar
    • Export Citation
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