• Anderson, E. A., 1973: National Weather Service River Forecast System—Snow Accumulation and Ablation Model. NOAA Tech. Memo. NWS HYDRO-17, 271 pp.

    • Search Google Scholar
    • Export Citation
  • Anderson, E. A., 1976: A point energy and mass balance model of a snow cover. NOAA Tech. Rep. 19, 150 pp.

  • Anderson, R. M., , Koren V. I. , , and Reed S. M. , 2006: Using SSURGO data to improve Sacramento Model a priori parameter estimates. J. Hydrol., 320, 103116.

    • Search Google Scholar
    • Export Citation
  • Burnash, R. J. C., 1995: The NWS river forecast system—Catchment modeling. Computer Models of Watershed Hydrology, V. P. Singh, Ed., Water Resources Publications, 311–366.

    • Search Google Scholar
    • Export Citation
  • Burnash, R. J. C., , Ferral R. L. , , and McGuire R. A. , 1973: A generalized streamflow simulation system—Conceptual modeling 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.

    • Search Google Scholar
    • Export Citation
  • Cognitore, P., 2005: An investigation of multisensor precipitation estimates (MPE) and operational use of MPE at the Middle Atlantic River Forecast Center (MARFC). NOAA/National Weather Service, Middle Atlantic River Forecast Center Tech. Rep. 2005-03, 16 pp.

    • Search Google Scholar
    • Export Citation
  • 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, 140158.

    • Search Google Scholar
    • Export Citation
  • Daly, C., , Gibson W. P. , , Doggett M. , , Smith J. , , and Taylor G. , 2004: Up-to-date monthly climate maps for the conterminous United States. Proc. 14th Conf. on Applied Climatology, Seattle, WA, Amer. Meteor. Soc., P5.1. [Available online at http://ams.confex.com/ams/84Annual/techprogram/paper_71444.htm.]

    • Search Google Scholar
    • Export Citation
  • Ding, F., , Kitzmiller D. , , Riley D. , , Shrestha K. , , Moreda F. , , and Seo D.-J. , 2005a: Evaluation of the range correction algorithm and convective stratiform separation algorithm for improving hydrological modeling. Preprints, 32nd Conf. on Radar Meteorology, Albuquerque, NM, Amer. Meteor. Soc., 13R.2. [Available online at http://ams.confex.com/ams/32Rad11Meso/techprogram/paper_96543.htm.]

    • Search Google Scholar
    • Export Citation
  • Ding, F., , Kitzmiller D. , , Seo D.-J. , , Riley D. , , Dietz C. , , Pham C. , , and Miller D. , 2005b: A multi-site evaluation of the range correction and convective-stratiform separation algorithms for improving WSR-88D rainfall estimates. Preprints, 19th Conf. on Hydrology, San Diego, CA, Amer. Meteor. Soc., P2.11. [Available online at http://ams.confex.com/ams/Annual2005/techprogram/paper_86418.htm.]

    • Search Google Scholar
    • Export Citation
  • Finnerty, B. D., , Smith M. B. , , Seo D.-J. , , Koren V. , , and Moglen G. E. , 1997: Space–time sensitivity of the Sacramento model to radar-gage precipitation inputs. J. Hydrol., 203, 2138.

    • Search Google Scholar
    • Export Citation
  • Fulton, R. A., , Breidenbach J. P. , , Seo D. J. , , Miller D. A. , , and O’Bannon T. , 1998: The WSR-88D rainfall algorithm. Wea. Forecasting, 13, 377395.

    • Search Google Scholar
    • Export Citation
  • Fulton, R. A., , Ding F. , , and Miller D. , 2003: Truncation errors in historical WSR-88D rainfall products. Preprints, 31st Int. Conf. on Radar Meteorology, Seattle, WA, Amer. Meteor. Soc., P2B.7. [Available online at http://ams.confex.com/ams/32BC31R5C/techprogram/paper_63261.htm.]

    • Search Google Scholar
    • Export Citation
  • Greene, D., , and Hudlow M. , 1982: Hydrometeorologic grid mapping procedures. Int. Symp. on Hydrometeorology, Denver, CO, AWRA, 20 pp.

  • Hardegree, S. P., , Van Vactor S. S. , , Levinson D. H. , , and Winstra A. , 2008: Evaluation of NEXRAD radar precipitation products for natural resource applications. Rangeland Ecol. Manage., 61, 346353.

    • Search Google Scholar
    • Export Citation
  • Jayakrishnan, R., , Srinivasan R. , , and Arnold J. G. , 2004: Comparison of raingage and WSR-88D Stage III precipitation data over the Texas–Gulf basin. J. Hydrol., 292, 135152.

    • Search Google Scholar
    • Export Citation
  • Koren, V., , Finnerty B. D. , , Schaake J. C. , , Smith M. B. , , Seo D.-J. , , and Duan Q.-Y. , 1999: Scale dependencies of hydrologic models to spatial variability of precipitation. J. Hydrol., 217, 285302.

    • Search Google Scholar
    • Export Citation
  • Koren, V., , Reed S. M. , , Smith M. , , Zhang Z. , , and Seo D.-J. , 2004: Hydrology Laboratory Research Modeling System (HL-RMS) of the U.S. National Weather Service. J. Hydrol., 291, 297318.

    • Search Google Scholar
    • Export Citation
  • Krajewski, W., , and Smith J. , 2002: Radar hydrology: Rainfall estimation. Adv. Water Resour., 25, 13871394.

  • NCEP-CPC, cited 2005: Soil moisture outlooks. [Available online at http://www.cpc.noaa.gov/soilmst/forecasts.shtml.]

  • Over, T. M., , Murphy E. A. , , Ortel T. W. , , and Ishii A. L. , 2007: Comparisons between NEXRAD radar and tipping-bucket gage rainfall data: A case study for DuPage County, Illinois. Proc. World Environmental and Water Resources Congress 2007, Tampa, FL, 1–14.

    • Search Google Scholar
    • Export Citation
  • Reed, S. M., 2003: Deriving flow directions for coarse-resolution (1–4 km) gridded hydrologic modeling. Water Resour. Res., 39, 1238, doi:10.1029/2003WR001989.

    • Search Google Scholar
    • Export Citation
  • Reed, S. M., , and Maidment D. R. , 1999: Coordinate transformations for using NEXRAD data in GIS-based hydrologic modeling. J. Hydrol. Eng., 4, 174182.

    • Search Google Scholar
    • Export Citation
  • Reed, S. M., and Coauthors, 2004: Overall distributed model intercomparison project results. J. Hydrol., 298, 2760.

  • Reed, S. M., , Schaake J. , , and Zhang Z. , 2007: A distributed hydrologic model and threshold frequency-based method for flash flood forecasting at ungauged locations. J. Hydrol., 337, 402420.

    • Search Google Scholar
    • Export Citation
  • Schaake, J. C., , Koren V. , , and Duan Q. , 1996: Simple water balance model for estimating runoff at different spatial and temporal scales. J. Geophys. Res., 101, 74617475.

    • Search Google Scholar
    • Export Citation
  • Seo, D.-J., 1998a: Real-time estimation of rainfall fields using radar rainfall and rain gage data. J. Hydrol., 208, 3752.

  • Seo, D.-J., 1998b: Real-time estimation of rainfall fields using rain gage data under fractional coverage conditions. J. Hydrol., 208, 2536.

    • Search Google Scholar
    • Export Citation
  • Seo, D.-J., , and Breidenbach J. P. , 2002: Real-time correction of spatially nonuniform bias in radar rainfall data using rain gauge measurements. J. Hydrometeor., 3, 93111.

    • Search Google Scholar
    • Export Citation
  • Seo, D.-J., , Breidenbach J. P. , , and Johnson E. R. , 1999: Real-time estimation of mean field bias in radar rainfall data. J. Hydrol., 223, 131147.

    • Search Google Scholar
    • Export Citation
  • Seo, D.-J., , Breidenbach J. P. , , Fulton R. , , Miller D. , , and O’Bannon T. , 2000a: Real-time adjustment of range-dependent biases in WSR-88D rainfall estimates due to nonuniform vertical profile of reflectivity. J. Hydrometeor., 1, 222240.

    • Search Google Scholar
    • Export Citation
  • Seo, D.-J., and Coauthors, 2000b: Final report, interagency memorandum of understanding among the NEXRAD Program, the WSR-88D Operational Support Facility, and the National Weather Service Office of Hydrology. Hydrologic Research Laboratory, Office of Hydrology, NOAA/NWS Tech. Rep.

    • Search Google Scholar
    • Export Citation
  • Seo, D.-J., and Coauthors, 2002: Final report, interagency memorandum of understanding among the NEXRAD Program, the WSR-88D Operational Support Facility, and the National Weather Service Office of Hydrology. Hydrologic Research Laboratory, Office of Hydrology, NOAA/NWS Tech. Rep.

    • Search Google Scholar
    • Export Citation
  • Smith, J. A., , Seo D.-J. , , Baeck M. L. , , and Hudlow M. D. , 1996: An intercomparison study of NEXRAD precipitation estimates. Water Resour. Res., 32, 20352045.

    • Search Google Scholar
    • Export Citation
  • Smith, M., , Koren V. , , Reed S. , , Zhang Z. , , Seo D.-J. , , Moreda F. , , and Cui Z. , 2006: The distributed model intercomparison project: Phase 2 science plan. Hydrology Laboratory, Office of Hydrologic Development, NOAA/NWS, 46 pp. [Available online at http://www.weather.gov/oh/hrl/dmip/2/docs/dmip_2_plan_march10_06_update.pdf.]

    • Search Google Scholar
    • Export Citation
  • Thielen, J., , Bartholmes J. , , Ramos M.-H. , , and de Roo A. , 2008: The European flood alert system—Part 1: Concept and development. Hydrol. Earth Syst. Sci. Discuss., 5, 257287.

    • Search Google Scholar
    • Export Citation
  • Young, C. B., , Nelson B. , , Bradley A. , , Smith J. , , Peters-Lidard C. , , Kruger A. , , and Baeck M. , 1999: An evaluation of NEXRAD precipitation estimates in complex terrain. J. Geophys. Res., 104, 19 69119 703.

    • Search Google Scholar
    • Export Citation
  • Young, C. B., , Bradley A. A. , , Krajewski W. F. , , Kruger A. , , and Morrissey M. L. , 2000: Evaluating NEXRAD multisensor precipitation estimates for operational hydrologic forecasting. J. Hydrometeor., 1, 241254.

    • Search Google Scholar
    • Export Citation
  • Zhang, Y., , Adams T. , , and Bonta J. V. , 2007: Subpixel-scale rainfall variability and the effects on separation of radar and gauge rainfall errors. J. Hydrometeor., 8, 13481363.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 11 11 3
PDF Downloads 3 3 2

Effects of Retrospective Gauge-Based Readjustment of Multisensor Precipitation Estimates on Hydrologic Simulations

View More View Less
  • 1 National Oceanic and Atmospheric Administration/National Weather Service Office of Hydrologic Development, Silver Spring, Maryland
© Get Permissions
Restricted access

Abstract

This paper presents methodologies for mitigating temporally inconsistent biases in National Weather Service (NWS) real-time multisensor quantitative precipitation estimates (MQPEs) through rain gauge–based readjustments, and examines their effects on streamflow simulations. In this study, archived MQPEs over 1997–2006 for the Middle Atlantic River Forecast Center (MARFC) area of responsibility were readjusted at monthly and daily scales using two gridded gauge products. The original and readjusted MQPEs were applied as forcing to the NWS Distributed Hydrologic Model for 12 catchments in the domain of MARFC. The resultant hourly streamflow simulations were compared for two subperiods divided along November 2003, when a software error that gave rise to a low bias in MQPEs was fixed. It was found that readjustment at either time scale improved the consistency in the bias in streamflow simulations. For the earlier period, independent monthly and daily readjustments considerably improved the streamflow simulations for most basins as judged by bias and correlation. By contrast, for the later period the effects were mixed across basins. It was also found that 1) readjustments tended to be more effective in the cool rather than warm season, 2) refining the readjustment resolution to daily had mixed effects on streamflow simulations, and 3) at the daily scale, redistributing gauge rainfall is beneficial for periods with substantial missing MQPEs.

Corresponding author address: Yu Zhang, National Oceanic and Atmospheric Administration/National Weather Service Office of Hydrologic Development, 1325 East-West Hwy., Silver Spring, MD 20910. E-mail: yu.zhang@noaa.gov

Abstract

This paper presents methodologies for mitigating temporally inconsistent biases in National Weather Service (NWS) real-time multisensor quantitative precipitation estimates (MQPEs) through rain gauge–based readjustments, and examines their effects on streamflow simulations. In this study, archived MQPEs over 1997–2006 for the Middle Atlantic River Forecast Center (MARFC) area of responsibility were readjusted at monthly and daily scales using two gridded gauge products. The original and readjusted MQPEs were applied as forcing to the NWS Distributed Hydrologic Model for 12 catchments in the domain of MARFC. The resultant hourly streamflow simulations were compared for two subperiods divided along November 2003, when a software error that gave rise to a low bias in MQPEs was fixed. It was found that readjustment at either time scale improved the consistency in the bias in streamflow simulations. For the earlier period, independent monthly and daily readjustments considerably improved the streamflow simulations for most basins as judged by bias and correlation. By contrast, for the later period the effects were mixed across basins. It was also found that 1) readjustments tended to be more effective in the cool rather than warm season, 2) refining the readjustment resolution to daily had mixed effects on streamflow simulations, and 3) at the daily scale, redistributing gauge rainfall is beneficial for periods with substantial missing MQPEs.

Corresponding author address: Yu Zhang, National Oceanic and Atmospheric Administration/National Weather Service Office of Hydrologic Development, 1325 East-West Hwy., Silver Spring, MD 20910. E-mail: yu.zhang@noaa.gov
Save