Preprints
https://doi.org/10.5194/hessd-4-655-2007
© Author(s) 2007. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
https://doi.org/10.5194/hessd-4-655-2007
© Author(s) 2007. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
02 Apr 2007
Status: this preprint was under review for the journal HESS. A revision for further review has not been submitted.
Precipitation and temperature ensemble forecasts from single-value forecasts
Abstract. A procedure is presented to construct ensemble forecasts from single-value forecasts of precipitation and temperature. This involves dividing the spatial forecast domain and total forecast period into a number of parts that are treated as separate forecast events. The spatial domain is divided into hydrologic sub-basins. The total forecast period is divided into time periods, one for each model time step. For each event archived values of forecasts and corresponding observations are used to model the joint distribution of forecasts and observations. The conditional distribution of observations for a given single-value forecast is used to represent the corresponding probability distribution of events that may occur for that forecast. This conditional forecast distribution subsequently is used to create ensemble members that vary in space and time using the "Schaake Shuffle" (Clark et al, 2004). The resulting ensemble members have the same space-time patterns as historical observations so that space-time joint relationships between events that have a significant effect on hydrological response tend to be preserved.
Forecast uncertainty is space and time-scale dependent. For a given lead time to the beginning of the valid period of an event, forecast uncertainty depends on the length of the forecast valid time period and the spatial area to which the forecast applies. Although the "Schaake Shuffle" procedure, when applied to construct ensemble members from a time-series of single value forecasts, may preserve some of this scale dependency, it may not be sufficient without additional constraint. To account more fully for the time-dependent structure of forecast uncertainty, events for additional "aggregate" forecast periods are defined as accumulations of different "base" forecast periods.
The generated ensemble members can be ingested by an Ensemble Streamflow Prediction system to produce ensemble forecasts of streamflow and other hydrological variables that reflect the meteorological uncertainty. The methodology is illustrated by an application to generate temperature and precipitation ensemble forecasts for the American River in California. Parameter estimation and dependent validation results are presented based on operational single-value forecasts archives of short-range River Forecast Center (RFC) forecasts and medium-range ensemble mean forecasts from the National Weather Service (NWS) Global Forecast System (GFS).
How to cite. Schaake, J., Demargne, J., Hartman, R., Mullusky, M., Welles, E., Wu, L., Herr, H., Fan, X., and Seo, D. J.: Precipitation and temperature ensemble forecasts from single-value forecasts, Hydrol. Earth Syst. Sci. Discuss., 4, 655–717, https://doi.org/10.5194/hessd-4-655-2007, 2007.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Download & links
Download & links
- Preprint
(8096 KB) - Metadata XML
- BibTeX
- EndNote
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
- Printer-friendly version
- Supplement
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
- Printer-friendly version
- Supplement
Viewed
Total article views: 3,083 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 01 Feb 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,816 | 1,178 | 89 | 3,083 | 119 | 104 |
- HTML: 1,816
- PDF: 1,178
- XML: 89
- Total: 3,083
- BibTeX: 119
- EndNote: 104
Cited
69 citations as recorded by crossref.
- Diagnostic verification of hydrometeorological and hydrologic ensembles J. Demargne et al. 10.1002/asl.261
- ImprovedBayesian multimodeling: Integration of copulas andBayesian model averaging S. Madadgar & H. Moradkhani 10.1002/2014WR015965
- CFSv2-Based Seasonal Hydroclimatic Forecasts over the Conterminous United States X. Yuan et al. 10.1175/JCLI-D-12-00683.1
- A review on statistical postprocessing methods for hydrometeorological ensemble forecasting W. Li et al. 10.1002/wat2.1246
- Assessing the Skill of Medium-Range Ensemble Precipitation and Streamflow Forecasts from the Hydrologic Ensemble Forecast Service (HEFS) for the Upper Trinity River Basin in North Texas S. Kim et al. 10.1175/JHM-D-18-0027.1
- Generating Calibrated Ensembles of Physically Realistic, High-Resolution Precipitation Forecast Fields Based on GEFS Model Output M. Scheuerer & T. Hamill 10.1175/JHM-D-18-0067.1
- Correcting Errors in Streamflow Forecast Ensemble Mean and Spread A. Wood & J. Schaake 10.1175/2007JHM862.1
- Eastern U.S. Verification of Ensemble Precipitation Forecasts S. Sharma et al. 10.1175/WAF-D-16-0094.1
- The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems A. Rossa et al. 10.1016/j.atmosres.2010.11.016
- Characterizing the uncertainty in river stage forecasts conditional on point forecast values J. Yan et al. 10.1029/2012WR011818
- Post-processing rainfall forecasts from numerical weather prediction models for short-term streamflow forecasting D. Robertson et al. 10.5194/hess-17-3587-2013
- An effective post-processing of the North American multi-model ensemble (NMME) precipitation forecasts over the continental US S. Khajehei et al. 10.1007/s00382-017-3934-0
- Hydrological monitoring and seasonal forecasting: Progress and perspectives Q. Tang et al. 10.1007/s11442-016-1306-z
- An approach for improving the capability of a coupled meteorological and hydrological model for rainfall and flood forecasts H. Nguyen & D. Bae 10.1016/j.jhydrol.2019.124014
- A hydrologic post-processor for ensemble streamflow predictions L. Zhao et al. 10.5194/adgeo-29-51-2011
- The Science of NOAA's Operational Hydrologic Ensemble Forecast Service J. Demargne et al. 10.1175/BAMS-D-12-00081.1
- A review on climate‐model‐based seasonal hydrologic forecasting: physical understanding and system development X. Yuan et al. 10.1002/wat2.1088
- A method for preferential selection of dates in the Schaake shuffle approach to constructing spatiotemporal forecast fields of temperature and precipitation M. Scheuerer et al. 10.1002/2016WR020133
- Comparative evaluation of maximum likelihood ensemble filter and ensemble Kalman filter for real-time assimilation of streamflow data into operational hydrologic models A. Rafieeinasab et al. 10.1016/j.jhydrol.2014.06.052
- Multivariate—Intervariable, Spatial, and Temporal—Bias Correction* M. Vrac & P. Friederichs 10.1175/JCLI-D-14-00059.1
- A Nonparametric Postprocessor for Bias Correction of Hydrometeorological and Hydrologic Ensemble Forecasts J. Brown & D. Seo 10.1175/2009JHM1188.1
- Ensemble dressing for hydrological applications T. Pagano et al. 10.1002/hyp.9313
- Verification of temperature, precipitation, and streamflow forecasts from the NOAA/NWS Hydrologic Ensemble Forecast Service (HEFS): 2. Streamflow verification J. Brown et al. 10.1016/j.jhydrol.2014.05.030
- Factors Influencing the Performance of Regression-Based Statistical Postprocessing Models for Short-Term Precipitation Forecasts W. Li et al. 10.1175/WAF-D-19-0121.1
- A novel attention-based LSTM cell post-processor coupled with bayesian optimization for streamflow prediction B. Alizadeh et al. 10.1016/j.jhydrol.2021.126526
- Statistical Post-Processing to Improve Hydrometeorological Forecasts 青. 段 10.12677/JWRR.2012.14023
- Evaluating the predictive skill of post‐processed NCEP GFS ensemble precipitation forecasts in China's Huai river basin Y. Liu et al. 10.1002/hyp.9496
- River Forecast Application for Water Management: Oil and Water? K. Werner et al. 10.1175/WCAS-D-12-00044.1
- Integrating weather and climate predictions for seamless hydrologic ensemble forecasting: A case study in the Yalong River basin A. Ye et al. 10.1016/j.jhydrol.2017.01.053
- Multi-model streamflow prediction using conditional bias-penalized multiple linear regression A. Jozaghi et al. 10.1007/s00477-021-02048-3
- A Similarity-Based Implementation of the Schaake Shuffle R. Schefzik 10.1175/MWR-D-15-0227.1
- The New York City Operations Support Tool (OST): Managing Water for Millions of People in an Era of Changing Climate and Extreme Hydrological Events J. Porter et al. 10.1142/S2345737615500086
- Comparison of pre‐ and post‐processors for ensemble streamflow prediction T. Kang et al. 10.1002/asl.276
- Using Meteorological Analogues for Reordering Postprocessed Precipitation Ensembles in Hydrological Forecasting J. Bellier et al. 10.1002/2017WR021245
- Prospects for the open treatment of uncertainty in environmental research J. Brown 10.1177/0309133309357000
- Probabilistic prediction of hydrologic drought using a conditional probability approach based on the meta-Gaussian model Z. Hao et al. 10.1016/j.jhydrol.2016.09.048
- Dynamic-Model-Based Seasonal Prediction of Meteorological Drought over the Contiguous United States J. Yoon et al. 10.1175/JHM-D-11-038.1
- The Ensemble Verification System (EVS): A software tool for verifying ensemble forecasts of hydrometeorological and hydrologic variables at discrete locations J. Brown et al. 10.1016/j.envsoft.2010.01.009
- On the Impact of Short-Range Meteorological Forecasts for Ensemble Streamflow Predictions G. Thirel et al. 10.1175/2008JHM959.1
- Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment S. Jha et al. 10.5194/hess-22-1957-2018
- An improved meta-Gaussian distribution model for post-processing of precipitation forecasts by censored maximum likelihood estimation W. Li et al. 10.1016/j.jhydrol.2019.04.073
- Multiscale Postprocessor for Ensemble Streamflow Prediction for Short to Long Ranges B. Alizadeh et al. 10.1175/JHM-D-19-0164.1
- Verification of Precipitation Forecasts from NCEP’s Short-Range Ensemble Forecast (SREF) System with Reference to Ensemble Streamflow Prediction Using Lumped Hydrologic Models J. Brown et al. 10.1175/JHM-D-11-036.1
- Evaluating the skill of NMME seasonal precipitation ensemble predictions for 17 hydroclimatic regions in continental China F. Ma et al. 10.1002/joc.4333
- Exploring hydrologic post-processing of ensemble streamflow forecasts based on affine kernel dressing and non-dominated sorting genetic algorithm II J. Xu et al. 10.5194/hess-26-1001-2022
- Assessment and modelling of uncertainty in precipitation forecasts from TIGGE using fuzzy probability and Bayesian theory C. Cai et al. 10.1016/j.jhydrol.2019.123995
- Integrating weather and climate prediction: Toward seamless hydrologic forecasting X. Yuan et al. 10.1002/2014GL061076
- Ensemble Bayesian forecasting system Part I: Theory and algorithms H. Herr & R. Krzysztofowicz 10.1016/j.jhydrol.2014.11.072
- Generation of ensemble precipitation forecast from single-valued quantitative precipitation forecast for hydrologic ensemble prediction L. Wu et al. 10.1016/j.jhydrol.2011.01.013
- Uncertainty Quantification in Complex Simulation Models Using Ensemble Copula Coupling R. Schefzik et al. 10.1214/13-STS443
- A Variable-Correlation Model to Characterize Asymmetric Dependence for Postprocessing Short-Term Precipitation Forecasts W. Li et al. 10.1175/MWR-D-19-0258.1
- Calibration and Downscaling Methods for Quantitative Ensemble Precipitation Forecasts N. Voisin et al. 10.1175/2010WAF2222367.1
- Verification of temperature, precipitation, and streamflow forecasts from the NOAA/NWS Hydrologic Ensemble Forecast Service (HEFS): 1. Experimental design and forcing verification J. Brown et al. 10.1016/j.jhydrol.2014.05.028
- An evaluation of post-processed TIGGE multimodel ensemble precipitation forecast in the Huai river basin Y. Tao et al. 10.1016/j.jhydrol.2014.04.040
- A Bayesian Framework for Probabilistic Seasonal Drought Forecasting S. Madadgar & H. Moradkhani 10.1175/JHM-D-13-010.1
- On the deterministic and stochastic use of hydrologic models W. Farmer & R. Vogel 10.1002/2016WR019129
- Towards improved post‐processing of hydrologic forecast ensembles S. Madadgar et al. 10.1002/hyp.9562
- Improvement of rank histograms for verifying the reliability of extreme event ensemble forecasts J. Xu et al. 10.1016/j.envsoft.2017.02.024
- Sample Stratification in Verification of Ensemble Forecasts of Continuous Scalar Variables: Potential Benefits and Pitfalls J. Bellier et al. 10.1175/MWR-D-16-0487.1
- Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
- Ensemble hydrological prediction‐based real‐time optimization of a multiobjective reservoir during flood season in a semiarid basin with global numerical weather predictions F. Wang et al. 10.1029/2011WR011366
- Application of a Medium-Range Global Hydrologic Probabilistic Forecast Scheme to the Ohio River Basin N. Voisin et al. 10.1175/WAF-D-10-05032.1
- An Empirical, Nonparametric Simulator for Multivariate Random Variables with Differing Marginal Densities and Nonlinear Dependence with Hydroclimatic Applications U. Lall et al. 10.1111/risa.12432
- Predictive performance of ensemble hydroclimatic forecasts: Verification metrics, diagnostic plots and forecast attributes Z. Huang & T. Zhao 10.1002/wat2.1580
- The multi temporal/multi-model approach to predictive uncertainty assessment in real-time flood forecasting S. Barbetta et al. 10.1016/j.jhydrol.2017.06.030
- Hydrologic post-processing of MOPEX streamflow simulations A. Ye et al. 10.1016/j.jhydrol.2013.10.055
- Comparative Evaluation of Three Schaake Shuffle Schemes in Postprocessing GEFS Precipitation Ensemble Forecasts L. Wu et al. 10.1175/JHM-D-17-0054.1
- Improving Precipitation Forecasts by Generating Ensembles through Postprocessing D. Shrestha et al. 10.1175/MWR-D-14-00329.1
- Seasonal Prediction of Regional Reference Evapotranspiration Based on Climate Forecast System Version 2 D. Tian et al. 10.1175/JHM-D-13-087.1
Saved
Latest update: 13 Dec 2024
J. Schaake
Office of Hydrologic Development, National Weather Service, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA
J. Demargne
Office of Hydrologic Development, National Weather Service, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA
R. Hartman
California Nevada River Forecast Center, National Weather Service, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA
M. Mullusky
Office of Hydrologic Development, National Weather Service, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA
E. Welles
Office of Hydrologic Development, National Weather Service, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA
L. Wu
Office of Hydrologic Development, National Weather Service, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA
H. Herr
Office of Hydrologic Development, National Weather Service, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA
X. Fan
Office of Hydrologic Development, National Weather Service, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA
D. J. Seo
Office of Hydrologic Development, National Weather Service, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA
Special issue