Editorial Type:
Article
Article Type:
Research Article

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

Yu Zhang National Oceanic and Atmospheric Administration/National Weather Service Office of Hydrologic Development, Silver Spring, Maryland

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Seann Reed National Oceanic and Atmospheric Administration/National Weather Service Office of Hydrologic Development, Silver Spring, Maryland

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David Kitzmiller National Oceanic and Atmospheric Administration/National Weather Service Office of Hydrologic Development, Silver Spring, Maryland

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Print Publication:
01 Jun 2011
DOI:
https://doi.org/10.1175/2010JHM1200.1
Page(s):
429–443
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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
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