A Method to Account for QPF Spatial Displacement Errors in Short-Term Ensemble Streamflow Forecasting

To account for spatial displacement errors common in quantitative precipitation forecasts (QPFs), a method using systematic shifting of QPF fields was tested to create ensemble streamflow forecasts. While previous studies addressed spatial displacement using neighborhood approaches, shifting of QPF...

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Main Authors: Bradley Carlberg, Kristie Franz, William Gallus
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Water
Subjects:
Online Access:https://www.mdpi.com/2073-4441/12/12/3505
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spelling doaj-f99f914671bf4816b4bdf2053a43536e2020-12-14T00:02:24ZengMDPI AGWater2073-44412020-12-01123505350510.3390/w12123505A Method to Account for QPF Spatial Displacement Errors in Short-Term Ensemble Streamflow ForecastingBradley Carlberg0Kristie Franz1William Gallus2Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USADepartment of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USADepartment of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USATo account for spatial displacement errors common in quantitative precipitation forecasts (QPFs), a method using systematic shifting of QPF fields was tested to create ensemble streamflow forecasts. While previous studies addressed spatial displacement using neighborhood approaches, shifting of QPF accounts for those errors while maintaining the structure of predicted systems, a feature important in hydrologic forecasts. QPFs from the nine-member High-Resolution Rapid Refresh Ensemble were analyzed for 46 forecasts from 6 cases covering 17 basins within the National Weather Service North Central River Forecast Center forecasting region. Shifts of 55.5 and 111 km were made in the four cardinal and intermediate directions, increasing the ensemble size to 81 members. These members were input into a distributed hydrologic model to create an ensemble streamflow prediction. Overall, the ensemble using the shifted QPFs had an improved frequency of non-exceedance and probability of detection, and thus better predicted flood occurrence. However, false alarm ratio did not improve, likely because shifting multiple QPF ensembles increases the potential to place heavy precipitation in a basin where none actually occurred. A weighting scheme based on a climatology of displacements was tested, improving overall performance slightly compared to the approach using non-weighted members.https://www.mdpi.com/2073-4441/12/12/3505ensemble streamflow predictionflood forecastingquantitative precipitation forecastsspatial displacement errors
collection DOAJ
language English
format Article
sources DOAJ
author Bradley Carlberg
Kristie Franz
William Gallus
spellingShingle Bradley Carlberg
Kristie Franz
William Gallus
A Method to Account for QPF Spatial Displacement Errors in Short-Term Ensemble Streamflow Forecasting
Water
ensemble streamflow prediction
flood forecasting
quantitative precipitation forecasts
spatial displacement errors
author_facet Bradley Carlberg
Kristie Franz
William Gallus
author_sort Bradley Carlberg
title A Method to Account for QPF Spatial Displacement Errors in Short-Term Ensemble Streamflow Forecasting
title_short A Method to Account for QPF Spatial Displacement Errors in Short-Term Ensemble Streamflow Forecasting
title_full A Method to Account for QPF Spatial Displacement Errors in Short-Term Ensemble Streamflow Forecasting
title_fullStr A Method to Account for QPF Spatial Displacement Errors in Short-Term Ensemble Streamflow Forecasting
title_full_unstemmed A Method to Account for QPF Spatial Displacement Errors in Short-Term Ensemble Streamflow Forecasting
title_sort method to account for qpf spatial displacement errors in short-term ensemble streamflow forecasting
publisher MDPI AG
series Water
issn 2073-4441
publishDate 2020-12-01
description To account for spatial displacement errors common in quantitative precipitation forecasts (QPFs), a method using systematic shifting of QPF fields was tested to create ensemble streamflow forecasts. While previous studies addressed spatial displacement using neighborhood approaches, shifting of QPF accounts for those errors while maintaining the structure of predicted systems, a feature important in hydrologic forecasts. QPFs from the nine-member High-Resolution Rapid Refresh Ensemble were analyzed for 46 forecasts from 6 cases covering 17 basins within the National Weather Service North Central River Forecast Center forecasting region. Shifts of 55.5 and 111 km were made in the four cardinal and intermediate directions, increasing the ensemble size to 81 members. These members were input into a distributed hydrologic model to create an ensemble streamflow prediction. Overall, the ensemble using the shifted QPFs had an improved frequency of non-exceedance and probability of detection, and thus better predicted flood occurrence. However, false alarm ratio did not improve, likely because shifting multiple QPF ensembles increases the potential to place heavy precipitation in a basin where none actually occurred. A weighting scheme based on a climatology of displacements was tested, improving overall performance slightly compared to the approach using non-weighted members.
topic ensemble streamflow prediction
flood forecasting
quantitative precipitation forecasts
spatial displacement errors
url https://www.mdpi.com/2073-4441/12/12/3505
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