文章基本信息

标题：Estuarine Forecasts at Daily Weather to Subseasonal Time Scales
本地全文：下载
作者：Andrew C. Ross ; Charles A. Stock ; Keith W. Dixon 等
期刊名称：Earth and Space Science
电子版ISSN：2333-5084
出版年度：2020
卷号：7
期号：10
页码：1-20
DOI：10.1029/2020EA001179
出版社：John Wiley & Sons, Ltd.
摘要：Most present forecast systems for estuaries predict conditions for only a few days into the future. However, there are many reasons to expect that skillful estuarine forecasts are possible for longer time periods, including increasingly skillful extended atmospheric forecasts, the potential for lasting impacts of atmospheric forcing on estuarine conditions, and the predictability of tidal cycles. In this study, we test whether skillful estuarine forecasts are possible for up to 35 days into the future by combining an estuarine model of Chesapeake Bay with 35‐day atmospheric forecasts from an operational weather model. When compared with both a hindcast simulation from the same estuarine model and with observations, the estuarine forecasts for surface water temperature are skillful up to about 2 weeks into the future, and the forecasts for bottom temperature, surface and bottom salinity, and density stratification are skillful for all or the majority of the forecast period. Bottom oxygen forecasts are skillful when compared to the model hindcast, but not when compared with observations. We also find that skill for all variables in the estuary can be improved by taking the mean of multiple estuarine forecasts driven by an ensemble of atmospheric forecasts. Finally, we examine the forecasts in detail using two case studies of extreme events, and we discuss opportunities for improving the forecast skill. Plain Language Abstract This paper evaluates a suite of forecasts for Chesapeake Bay water temperature, salinity, and dissolved oxygen created using a numerical model. By comparing the model forecasts with observations, we show that the model forecasts for temperature and salinity are more accurate than reference forecasts of previously observed conditions or the long‐term mean; in other words, the forecasts are skillful. In general, the forecasts are skillful for at least 2 weeks into the future. Improvements to our forecasting system, such as predicting future river discharge into Chesapeake Bay, would likely improve the forecast skill even more. By showing that accurate, skillful forecasts are possible for a much longer time frame than previously considered, this paper takes an important step toward applying forecasts to improve water quality and fisheries management and to prepare for the impacts of extreme events like hurricanes and heat waves.
关键词：Chesapeake Bay;forecasting;prediction;subseasonal