Downstream control of blocking and Rossby wave breaking by extratropical cyclones

从数小时到数世纪的熟练天气和气候预报对于保护生命和生计以及管理气候变化的影响至关重要。世界气象组织的观测系统研究和可预报性实验（THORPEX）是基于这样一种认识而产生的，即尽管数值天气预报不断改进（THORPEX特别考虑了1-14天的提前期），但仍需进一步改进。这些预报中的误差是由于初始条件的误差（混乱的“蝴蝶效应”）、边界条件的误差（例如天气预报中的海面温度误差）和模型公式的误差（所谓的模型误差）造成的。在对流层顶层出现的误差会影响到与高层（~10 km高）急流弯曲有关的行星尺度Rossby波的发展、传播和破裂，从而向下游传播。急流中的脊和槽是与强地面风和雨相关的热带气旋（又名冬季风暴）发展的主要驱动力，以及与夏季热浪和污染物截留造成的健康影响相关的阻塞事件。一种系统误差是由于在全球（和大多数区域）天气预报模式中必须将对流和其他潮湿过程参数化而造成的对流外气旋中的云和辐射等非绝热过程的错误表述。在一个给定的风暴中，这些过程的表示误差的影响会传播到下游，因此会影响未来发展中的风暴或阻塞事件的预测，导致所谓的“预测崩溃”。识别这种系统误差是确定模型改进以减少它们的第一步。该项目的CASE合作伙伴是英国气象局，我们的合作是与“集合预报”和“模型评估和诊断”研究小组。在无缝模型预测系统中，例如英国气象局的业务气候和天气预报模型（称为统一模型），使用系统的一个组件（这里我们使用天气预报组件）识别和减少系统误差可以潜在地改善从几小时到几个世纪的所有预报时间范围的预报。在这个项目中，我们因果关联的对流层顶结构的错误所造成的非绝热过程的错误表示在extratrophic气旋，并确定其对下游的Rossby波破碎和阻塞误差的影响。

Skillful weather and climate forecasts on timescales from hours to centuries are vital for protecting lives and livelihoods and managing the effects of climate change. The Observing System Research and Predictability Experiment (THORPEX) of the World Meteorological Organization grew out of a recognition that, despite continued improvements in numerical weather prediction forecasts (THORPEX specifically considered 1-14 day lead times), further improvements needed to be made. Errors in these forecasts arise due to errors in the initial conditions (the chaotic `butterfly effect'), boundary conditions (e.g. sea surface temperature errors in a weather forecast) and errors in the model formulation (so-called model error). Errors occurring at tropopause level propagate downstream due to their influence on the development, propagation and breaking of the planetary-scale Rossby waves associated with meanders of the upper-level (~10 km high) jet stream. Ridges and troughs in the jet stream are the major driver of the development of extratropical cyclones (a.k.a winter storms) associated with strong surface winds and rain as well as blocking events associated with e.g. summer heatwaves and health impacts due to the trapping of pollutants. One type of systematic error is that due to the mis-representation of diabatic processes such as clouds and radiation in extratropical cyclones, resulting from the necessity to parametrize convection and other moist processes in global (and most regional) weather forecast models. The influence of errors in the representation of these processes in a given storm are propagated downstream and so can affect the forecast of future developing storms or blocking episodes, leading to so-called 'forecast busts'. Identification of such systematic errors is the first step to determining model improvements to reduce them. The CASE partner for this project is the Met Office and our collaboration is with both the 'ensemble forecasting' and 'model evaluation and diagnostics' research groups. In a seamless model prediction system, such as the Met Office's operational climate and weather forecast model (known as the Unified Model), identification and reduction of systematic errors using one component of the system (here we use the weather forecasting component) can potentially improve forecasts across all forecast time horizons from hours to centuries. In this project we causally associate errors in tropopause structure caused by the mis-representation of diabatic processes in extratropical cyclones and determine their influence on downstream error in Rossby-wave breaking and blocking.