Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2020WR029453 |
A multivariate approach to generate synthetic short-to-medium range hydro-meteorological forecasts across locations, variables, and lead times | |
Zachary P. Brodeur; Scott Steinschneider | |
2021-05-21 | |
发表期刊 | Water Resources Research
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出版年 | 2021 |
英文摘要 | The use of hydro-meteorological forecasts in water resources management holds great promise as a soft pathway to improve system performance. Methods for generating synthetic forecasts of hydro-meteorological variables are crucial for robust validation of forecast use, as numerical weather prediction hindcasts are only available for a relatively short period (10-40 years) that is insufficient for assessing risk related to forecast-informed decision-making during extreme events. We develop a generalized error model for synthetic forecast generation that is applicable to a range of forecasted variables used in water resources management. The approach samples from the distribution of forecast errors over the available hindcast period and adds them to long records of observed data to generate synthetic forecasts. The approach utilizes the Skew Generalized Error Distribution (SGED) to model marginal distributions of forecast errors that can exhibit heteroskedastic, auto-correlated, and non-Gaussian behavior. An empirical copula is used to capture covariance between variables, forecast lead times, and across space. We demonstrate the method for medium-range forecasts across Northern California in two case studies for 1) streamflow and 2) temperature and precipitation, which are based on hindcasts from the NOAA/NWS Hydrologic Ensemble Forecast System (HEFS) and the NCEP GEFS/R V2 climate model, respectively. The case studies highlight the flexibility of the model and its ability to emulate space-time structures in forecasts at scales critical for water resources management. The proposed method is generalizable to other locations and computationally efficient, enabling fast generation of long synthetic forecast ensembles that are appropriate for risk analysis. This article is protected by copyright. All rights reserved. |
领域 | 资源环境 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/328695 |
专题 | 资源环境科学 |
推荐引用方式 GB/T 7714 | Zachary P. Brodeur,Scott Steinschneider. A multivariate approach to generate synthetic short-to-medium range hydro-meteorological forecasts across locations, variables, and lead times[J]. Water Resources Research,2021. |
APA | Zachary P. Brodeur,&Scott Steinschneider.(2021).A multivariate approach to generate synthetic short-to-medium range hydro-meteorological forecasts across locations, variables, and lead times.Water Resources Research. |
MLA | Zachary P. Brodeur,et al."A multivariate approach to generate synthetic short-to-medium range hydro-meteorological forecasts across locations, variables, and lead times".Water Resources Research (2021). |
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