Editorial Type:
Article
Article Type:
Research Article

Soil Moisture Initialization Error and Subgrid Variability of Precipitation in Seasonal Streamflow Forecasting

Randal D. Koster Global Modeling and Assimilation Office, NASA/GSFC, Greenbelt, Maryland

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Gregory K. Walker SSAI, Lanham, Maryland

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Sarith P. P. Mahanama SSAI, Lanham, Maryland

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Rolf H. Reichle Global Modeling and Assimilation Office, NASA/GSFC, Greenbelt, Maryland

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Print Publication:
01 Feb 2014
Collections:
NASA Soil Moisture Active Passive (SMAP) – Pre-launch Applied Research
DOI:
https://doi.org/10.1175/JHM-D-13-050.1
Page(s):
69–88
Restricted access

Abstract

Offline simulations over the conterminous United States (CONUS) with a land surface model are used to address two issues relevant to the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which a realistic increase in the spatial resolution of forecasted precipitation would improve streamflow forecasts. The addition of error to a soil moisture initialization field is found to lead to a nearly proportional reduction in large-scale seasonal streamflow forecast skill. The linearity of the response allows the determination of a lower bound for the increase in streamflow forecast skill achievable through improved soil moisture estimation, for example, through the assimilation of satellite-based soil moisture measurements. An increase in the resolution of precipitation is found to have an impact on large-scale seasonal streamflow forecasts only when evaporation variance is significant relative to precipitation variance. This condition is met only in the western half of the CONUS domain. Taken together, the two studies demonstrate the utility of a continental-scale land surface–modeling system as a tool for addressing the science of hydrological prediction.

Corresponding author address: R. D. Koster, Global Modeling and Assimilation Office, Code 610.1, NASA/GSFC, Greenbelt, MD 20771. E-mail: randal.d.koster@nasa.gov

This article is included in the NASA Soil Moisture Active Passive (SMAP) – Pre-launch Applied Research Special Collection.

Abstract

Offline simulations over the conterminous United States (CONUS) with a land surface model are used to address two issues relevant to the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which a realistic increase in the spatial resolution of forecasted precipitation would improve streamflow forecasts. The addition of error to a soil moisture initialization field is found to lead to a nearly proportional reduction in large-scale seasonal streamflow forecast skill. The linearity of the response allows the determination of a lower bound for the increase in streamflow forecast skill achievable through improved soil moisture estimation, for example, through the assimilation of satellite-based soil moisture measurements. An increase in the resolution of precipitation is found to have an impact on large-scale seasonal streamflow forecasts only when evaporation variance is significant relative to precipitation variance. This condition is met only in the western half of the CONUS domain. Taken together, the two studies demonstrate the utility of a continental-scale land surface–modeling system as a tool for addressing the science of hydrological prediction.

Corresponding author address: R. D. Koster, Global Modeling and Assimilation Office, Code 610.1, NASA/GSFC, Greenbelt, MD 20771. E-mail: randal.d.koster@nasa.gov

This article is included in the NASA Soil Moisture Active Passive (SMAP) – Pre-launch Applied Research Special Collection.

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  • Andreadis, K. M., Clark E. A. , Wood A. W. , Hamlet A. F. , and Lettenmaier D. P. , 2005: Twentieth-century drought in the conterminous United States. J. Hydrometeor., 6, 985–1001, doi:10.1175/JHM450.1.

    • Search Google Scholar
    • Export Citation

  • Bierkens, M. F. P., and van Beek L. P. H. , 2009: Seasonal predictability of European discharge: NAO and hydrological response time. J. Hydrometeor., 10, 953–968, doi:10.1175/2009JHM1034.1.

    • Search Google Scholar
    • Export Citation

  • Boone, A., Habets F. , Noilhan J. , and Coauthors, 2004: The Rhone-aggregation land surface scheme intercomparison project: An overview. J. Climate, 17, 187–208, doi:10.1175/1520-0442(2004)017<0187:TRLSSI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Bowling, L. C., Lettenmaier D. P. , Nijssen B. , and Coauthors, 2003: Simulation of high-latitude hydrological processes in the Torne-Kalix basin: PILPS Phase 2e. 1: Experiment description and summary intercomparison. Global Planet. Change, 38, 1–30, doi:10.1016/S0921-8181(03)00003-1.

    • Search Google Scholar
    • Export Citation

  • Budyko, M. I., 1974: Climate and Life. Academic Press, 508 pp.

  • Day, G. N., 1985: Extended streamflow forecasting using NWSRFS. J. Water Resour. Plann. Manage., 111, 157–170, doi:10.1061/(ASCE)0733-9496(1985)111:2(157).

    • Search Google Scholar
    • Export Citation

  • Draper, C. S., Reichle R. H. , De Lannoy G. J. M. , and Liu Q. , 2012: Assimilation of passive and active microwave soil moisture retrievals. Geophys. Res. Lett., 39, L04401, doi:10.1029/2011GL050655.

    • Search Google Scholar
    • Export Citation

  • Ducharne, A., Koster R. D. , Suarez M. J. , Stieglitz M. , and Kumar P. , 2000: A catchment-based approach to modeling land surface processes in a general circulation model. (2) Parameter estimation and model demonstration. J. Geophys. Res., 105 (D20), 24 823–24 838.

    • Search Google Scholar
    • Export Citation

  • Entekhabi, D., Reichle R. H. , Koster R. D. , and Crow W. T. , 2010a: Performance metrics for soil moisture retrievals and applications requirements. J. Hydrometeor., 11, 832–840, doi:10.1175/2010JHM1223.1.

    • Search Google Scholar
    • Export Citation

  • Entekhabi, D., and Coauthors, 2010b: The Soil Moisture Active Passive (SMAP) mission. Proc. IEEE, 98, 704–716, doi:10.1109/JPROC.2010.2043918.

    • Search Google Scholar
    • Export Citation

  • Garen, D. C., 1992: Improved techniques in regression-based streamflow volume forecasting. J. Water Resour. Plann. Manage., 118, 654–670, doi:10.1061/(ASCE)0733-9496(1992)118:6(654).

    • Search Google Scholar
    • Export Citation

  • Hamlet, A. F., and Lettenmaier D. P. , 1999: Effects of climate change on hydrology and water resources in the Columbia River basin. J. Amer. Water Resour. Assoc., 35, 1597–1623, doi:10.1111/j.1752-1688.1999.tb04240.x.

    • Search Google Scholar
    • Export Citation

  • Hamlet, A. F., Huppert D. , and Lettenmaier D. P. , 2002: Economic value of long-lead streamflow forecasts for Columbia River hydropower. J. Water Resour. Plann. Manage., 128, 91–101, doi:10.1061/(ASCE)0733-9496(2002)128:2(91).

    • Search Google Scholar
    • Export Citation

  • Kerr, Y. H., and Coauthors, 2010: The SMOS mission: New tool for monitoring key elements of the global water cycle. Proc. IEEE, 98, 666–687, doi:10.1109/JPROC.2010.2043032.

    • Search Google Scholar
    • Export Citation

  • Koster, R. D., and Suarez M. J. , 1999: A simple framework for examining the interannual variability of land surface moisture fluxes. J. Climate, 12, 1911–1917, doi:10.1175/1520-0442(1999)012<1911:ASFFET>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Koster, R. D., and Mahanama S. P. P. , 2012: Land surface controls on hydroclimatic means and variability. J. Hydrometeor., 13, 1604–1620, doi:10.1175/JHM-D-12-050.1.

    • Search Google Scholar
    • Export Citation

  • Koster, R. D., Suarez M. J. , Ducharne A. , Stieglitz M. , and Kumar P. , 2000: A catchment-based approach to modeling land surface processes in a general circulation model: 1. Model structure. J. Geophys. Res., 105, 24 809–24 822.

    • Search Google Scholar
    • Export Citation

  • Koster, R. D., Fekete B. M. , Huffman G. J. , and Stackhouse P. W. Jr., 2006: Revisiting a hydrological analysis framework with International Satellite Land Surface Climatology Project Initiative 2 rainfall, net radiation, and runoff fields. J. Geophys. Res., 111, D22S05, doi:10.1029/2006JD007182.

    • Search Google Scholar
    • Export Citation

  • Koster, R. D., Mahanama S. , Livneh B. , Lettenmaier D. , and Reichle R. , 2010: Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow. Nat. Geosci., 3, 613–616.

    • Search Google Scholar
    • Export Citation

  • Li, H., Luo L. , Wood E. F. , and Schaake J. , 2009: The role of initial conditions and forcing uncertainties in seasonal hydrologic forecasting. J. Geophys. Res., 114, D04114, doi:10.1029/2008JD010969.

    • Search Google Scholar
    • Export Citation

  • Liu, Q., and Coauthors, 2011: The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates in a land data assimilation system. J. Hydrometeor., 12, 750–765, doi:10.1175/JHM-D-10-05000.1.

    • Search Google Scholar
    • Export Citation

  • Luo, L., and Wood E. F. , 2008: Use of Bayesian merging techniques in a multimodel seasonal hydrologic ensemble prediction system for the Eastern United States. J. Hydrometeor., 9, 866–884, doi:10.1175/2008JHM980.1.

    • Search Google Scholar
    • Export Citation

  • Luo, L., Wood E. F. , and Pan M. , 2007: Bayesian merging of multiple climate model forecasts for seasonal hydrological predictions. J. Geophys. Res., 112, D10102, doi:10.1029/2006JD007655.

    • Search Google Scholar
    • Export Citation

  • Mahanama, S. P. P., Koster R. D. , Reichle R. H. , and Zubair L. , 2008: The role of soil moisture initialization in subseasonal and seasonal streamflow prediction A case study in Sri Lanka. Adv. Water Resour., 31, 1333–1343, doi:10.1016/j.advwatres.2008.06.004.

    • Search Google Scholar
    • Export Citation

  • Mahanama, S. P. P., Livneh B. , Koster R. D. , Lettenmaier D. , and Reichle R. , 2012: Soil moisture, snow, and seasonal streamflow forecasts in the United States. J. Hydrometeor., 13, 189–203, doi:10.1175/JHM-D-11-046.1.

    • Search Google Scholar
    • Export Citation

  • Pagano, T., Garen D. , and Sorooshian S. , 2004: Evaluation of official western U.S. seasonal water supply outlooks, 1922–2002. J. Hydrometeor., 5, 896–909, doi:10.1175/1525-7541(2004)005<0896:EOOWUS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Reichle, R. H., and Koster R. D. , 2003: Assessing the impact of horizontal error correlations in background fields on soil moisture estimation. J. Hydrometeor., 4, 1229–1242, doi:10.1175/1525-7541(2003)004<1229:ATIOHE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Reichle, R. H., Koster R. D. , Liu P. , Mahanama S. P. P. , Njoku E. G. , and Owe M. , 2007: Comparison and assimilation of global soil moisture retrievals from AMSR-E and SMMR. J. Geophys. Res., 112, D09108, doi:10.1029/2006JD008033.

    • Search Google Scholar
    • Export Citation

  • Reichle, R. H., and Coauthors, 2011: Assessment and enhancement of MERRA land surface hydrology estimates. J. Climate, 24, 6322–6338, doi:10.1175/JCLI-D-10-05033.1.

    • Search Google Scholar
    • Export Citation

  • Rienecker, M. M., and Coauthors, 2011: MERRA: NASA's Modern-Era Retrospective Analysis for Research and Applications. J. Climate, 24, 3624–3648, doi:10.1175/JCLI-D-11-00015.1.

    • Search Google Scholar
    • Export Citation

  • Schaake, J., Pailleux J. , Thielen J. , Arritt R. , Hamill T. , Luo L. , Martin E. , McCollor D. , and Pappenberger F. , 2010: Summary of recommendations of the first workshop on postprocessing and downscaling atmospheric forecasts for hydrologic applications held at Meteo-France, Toulouse, France, 15–18 June 2009. Atmos. Sci. Lett., 11, 59–63, doi:10.1002/asl.267.

    • Search Google Scholar
    • Export Citation

  • Sheffield, J., Goteti G. , and Wood E. F. , 2006: Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. J. Climate, 19, 3088–3111, doi:10.1175/JCLI3790.1.

    • Search Google Scholar
    • Export Citation

  • Wang, E., Zhang Y. , Luo J. , Chiew F. H. S. , and Wang Q. J. , 2011: Monthly and seasonal streamflow forecasts using rainfall-runoff modeling and historical weather data. Water Resour. Res., 47, W05516, doi:10.1029/2010WR009922.

    • 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, doi:10.1175/BAMS-87-12-1699.

    • Search Google Scholar
    • Export Citation

  • Wood, A. W., and Lettenmaier D. P. , 2008: An ensemble approach for attribution of hydrologic prediction uncertainty. Geophys. Res. Lett., 35, L14401, doi:10.1029/2008GL034648.

    • Search Google Scholar
    • Export Citation

  • Wood, A. W., Maurer E. P. , Kumar A. , and Lettenmaier D. P. , 2002: Long-range experimental hydrologic forecasting for the eastern United States. J. Geophys. Res., 107, 4429, doi:10.1029/2001JD000659.

    • Search Google Scholar
    • Export Citation

  • Xia, Y., Ek M. , Wei H. , and Meng J. , 2012: 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

  • Yao, H., and Georgakakos A. P. , 2001: Assessment of Folsom Lake response to historical and potential future climate scenarios. 2: Reservoir management. J. Hydrol., 249, 176–196, doi:10.1016/S0022-1694(01)00418-8.

    • Search Google Scholar
    • Export Citation

  • Yuan, X., and Wood E. F. , 2012: Downscaling precipitation or bias-correcting streamflow? Some implications for CGCM-based ensemble seasonal hydrologic forecast. Water Resour. Res.,48, W12519, doi:10.1029/2012WR012256.

  • Yuan, X., Liang X.-Z. , and Wood E. F. , 2012: WRF ensemble downscaling seasonal forecasts of China winter precipitation during 1982-2008. Climate Dyn., 39, 2041–2058, doi:10.1007/s00382-011-1241-8.

    • Search Google Scholar
    • Export Citation
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