报告题目：Seasonal Hydrologic Predictability: Sources and Limitations
报告人：美国工程院院士、加州大学洛杉矶分校（UCLA）Dennis P. Lettenmaier教授
时间：2016年5月14日（周六）下午15:00-17:00
地点：英东学术会堂二层讲学厅
Dennis Lettenmaier教授，2016年度中国科学院“国际杰出学者”称号获得者。现任美国加州大学洛杉矶分校（UCLA）杰出教授，系美国工程院院士，美国地球物理联合会、美国气象学会与美国科学促进会会士。研究领域包括水文模拟与预报、水文-气象相互作用、水循环变化等，是国际水文气象学界的领军人物。曾担任Journal of Hydrometeorology 创刊主编，Water Resources Research副主编，美国地球物理联合会水文领域主席，全球能量与水循环协调观测计划科学咨询委员会主席，并先后荣获Walter L. Huber奖章，AGU水文科学奖，Walter Orr Roberts Lecturer, Robert E. Horton Lecturer, Walter B. Langbein Lecturer等多项荣誉。作为国际顶级水文科学家和水文气象研究领域杰出领导者，以其创新工作和卓越贡献重塑了国际水文学格局，引领了现代水文学的前沿发展方向。
报告摘要：A set of experiments will be reviewed to understand the extent to which seasonal hydrologic prediction skill is controlled by hydrologic initial conditions as contrasted with climate forecast skill. The study shows that at short lead times (typically up to a few months), hydrologic forecast skill is mostly controlled by hydrologic initial conditions (primarily soil moisture and where and when relevant, snow water storage), but at longer lead times, climate forecast skill dominates. Unfortunately, aside from a few special situations, climate forecast skill for lead times beyond about a month is minimal. Therefore, for practical purposes, hydrologic initial conditions are the primary source of hydrologic forecast skill. This is the premise of the widely used Ensemble Streamflow Prediction (ESP) method. Barriers to the use of seasonal hydrologic forecasts in water resource systems operation will also be investigated. This work was completed approximately a decade ago, which casts light on the potential for improved reservoir system operations through improved forecasts as a function of the usable reservoir storage relative to the mean annual inflow, relative to the simplest forecast (climatology). As a case study, hydroclimatic and hydrologic forecast skill (or lack thereof) in winter, 2016 across the Western U.S. during one of the strongest El Nino events of the historic record will be evaluated, which by past estimates should have been the basis for accurate seasonal climate forecasts.
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