Predictability of Forced, Dissipated and Bounded AtmospheresFor Global, Synoptic, and Mesoscales

在1969年的一篇经典论文中，洛伦茨证明，地球大气的简单(无摩擦和无加热)模型的可预测性原则上限于大约5天。具体地说，这意味着预报误差将超过实际地图上的变化量(比方说风或气压)，在预报的验证时间，即在一段预测期之后。一个更好的模型和/或在最初时间更完整和准确的一套观测结果，可能会在以后达到“无用”的预测，但即使是这些预测的最佳组合，也必须在大约5天内达到。按照这一衡量标准，ECMWF目前使用的实际业务预报模式的可预测性已从1980年的5天增加到1990年的8天。这一运行模型确实包括了加热的影响，以及地球表面对水流的摩擦和地形干扰。对于这些并发症，它不符合洛伦茨使用的理论治疗类型。然而，正是这些复杂的过程可能以某种方式提高了业务模型的可预测性。因此，有用预报的时限尚未确定，提高预报可预测性的方法值得进一步探讨。本奖项支持的研究的目的是通过以下方式估计可实现的可预测性增强：i)改进模型对较大尺度流动成分的处理，这些流动成分具有最明显的预测误差，并且与极地到赤道和大陆-海洋在加热和摩擦/地形干扰方面的对比最直接相关；Ii)用更详细的计算动量、热量和水与下垫面交换的公式来拟合模型的研究版本，以及iii)研究全球尺度预报误差增长率对选定区域的模拟观测误差的敏感性，这些区域假定需要对初始状态进行精细的网格划分。PI在数值天气预报、热带、边界层和山区气象学方面的先前研究与拟议的工作特别相关。这些研究将加深我们对影响可预报性的因素的了解，并可能有助于在未来十年进一步改进数值天气预报。

In a classic 1969 paper, Lorenz proved that the predictability in a simple (frictionless and unheated) model of the earth's atmosphere was, in principle, limited to about five days. Specifically, this meant that the forecast error would exceed the variability (say of wind, or pressure) on the actual map at the verification time of the forecast, after some forecast period. A better model and/or a more complete and accurate set of observations at initial time might reach this time of "useless" forecasts later, but even the best combination of these would have to reach it in about five days. The predictability, by this measure, in an actual operational forecast model now used in the ECMWF has gone from five days in 1980 to eight days in 1990. This operational model does include the effects of heating, and frictional and topographic interference with the flow caused by the earth's surface. With these complications it is not amenable to the type of theoretical treatment used by Lorenz. However, it is possible that precisely these complicating processes somehow enhance the predictability of the operational model. Thus the time limit on useful forecasts has yet to be determined, and ways to enhance the predictability deserve extended exploration. The objective of the research supported under this award is to estimate the attainable enhancement of predictability by: i) Improving the model's treatment of the larger-scale flow components, which have the most obvious forecast errors, and which are most directly linked to pole to equator and continent- ocean contrasts in heating and frictional/topographic interference; ii) Fitting a research version of the model with more detailed formulas for the calculation of momentum, heat, and water exchanges with the underlaying surface, and iii) Studying the sensitivity of the global-scale forecast error growth rate to simulated observational errors in selected regions which are presumed to require fine mesh specification of the initial state. The PI's prior research in Numerical Weather Prediction,and tropical, boundary layer, and mountain meteorology is especially relevant to the proposed work. These studies will increase our understanding of the factors affecting predictability, and are likely to contribute to further improvements in Numerical Weather Prediction over the next decade.