Incorporating the Uncertainty of Atmosphere-Land Surface Interactions into Ensemble Forecasts

将大气-地表相互作用的不确定性纳入集合预报

• 批准号: 0130154
• 负责人: Thomas Warner
• 金额: $ 32.77万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-06-15 至 2006-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0130154&HistoricalAwards=false
• 关键词: Incorporating; Uncertainty; Atmosphere; Land; Surface

A common problem with ensemble weather forecasts is the insufficient spread of the ensemble members so that often the true state lies outside the span of the ensemble forecasts. Previous studies indicate that this "lack of spread" is worse near the surface than it is in mid-troposphere, suggesting that part of the problem may be due to the land surface conditions in the model. The PIs seek to improve this situation by perturbing the land surface condition and treating the insolation (incoming solar radiation at the surface) stochastically in the ensemble forecasts. The research has two components: first, an observational/diagnostic study geared toward the understanding of the spatial and temporal characteristics of errors in surface fluxes and insolation. The second component is to design methodologies to link the errors of the surface fluxes to the surface moisture and perturb it. The isolation will be perturbed with stochastic noise. Once suitable candidate methods have been developed, they will be tested in the Rapid Update Cycle or Weather Research and Forecast model ensemble runs by the Forecast System Laboratory, NOAA. Results from this research have the potential of finding their way into operational ensemble weather forecasts.Probabilistic forecasts generated by ensemble predictions are increasing used for a wide variety of purposes, from flood forecasting to assessing the demand for electricity. This research is aimed at improving the quality of ensemble forecasts and enhancing their usefulness. The training that the graduate students receive will help to prepare them for careers in ensemble forecasting where there is a shortage of talented manpower.

合奏天气预报的一个普遍问题是合奏成员的传播不足，因此真正的状态通常位于整体预测的范围之内。 先前的研究表明，这种“缺乏扩散”在表面附近比对流层中部差，这表明该问题的一部分可能是由于模型中的土地表面条件所致。 PI试图通过扰动土地表面状况并在整体预测中随机处理暴发（表面传入太阳辐射）来改善这种情况。 这项研究有两个组成部分：首先，是一项旨在理解表面通量和日光下错误的空间和时间特征的观察/诊断研究。 第二个组成部分是设计方法，以将表面通量的误差与表面湿度联系起来并扰动。 隔离将被随机噪声扰动。 一旦开发出合适的候选方法，它们将在快速更新周期或天气研究中进行测试，并预测模型集合由NOAA预测系统实验室运行。 这项研究的结果有可能找到他们进入运营整体天气预报的方法。整体预测产生的良好预测正在增加用于多种目的，从洪水预测到评估电力需求。 这项研究旨在提高整体预测的质量并提高其实用性。 研究生接受的培训将有助于为他们做好准备，以在没有才华横溢的人力的情况下进行合奏预测。