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Diabatic influences on mesoscale structures in extratropical storms

非绝热对温带风暴中尺度结构的影响

基本信息

批准号：
NE/I005218/1
负责人：
Douglas Parker
金额：
$ 37万
依托单位：
University of Leeds
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2010
资助国家：
英国
起止时间：
2010 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FI005218%2F1
关键词：
Diabatic influences mesoscale structures extratropical

项目摘要

The project is aimed at a better understanding and prediction of mesoscale structures in synoptic-scale storms. Such structures include fronts, rain bands, secondary cyclones, sting jets etc, and are important because much of the extreme weather we experience (e.g. strong winds, heavy rain) comes from such regions. Weather forecasting models are able to capture some of this activity correctly, but there is much still to learn. By a combination of measurements and modelling, mainly using the Met Office Unified Model (UM), we will work to better understand how mesoscale processes in cyclones give rise to severe weather and how they can be better represented in models and better forecast. The project is organised into three broad work packages. The first of these aims to look at real mesoscale structures in the atmosphere, using high-resolution in situ and radar measurements to derive their morphology and dynamics. The key to the latter is to calculate the production of potential vorticity by diabatic processes - especially phase changes of water (vapour/liquid/ice) and air-sea fluxes of sensible and latent heat. The associated high-resolution modelling programme will use the UM to simulate a representative number of events, diagnosing the PV tendency in the model and comparing with the measurements. Sensitivity studies and further diagnostics with the model will reveal the sensitivity of the forecasts to the correct representation of these processes and the dynamical consequences of diabatically-generated PV, both on the mesoscale and larger scales. Two student projects will investigate the role of boundary-layer processes in storm behaviour and conduct a statistical investigation of mesoscale precipitation features, based on archived radar and wind profiler data. The second WP examines particular physical processes and the way these are represented in forecast models. Convection cannot be explicitly represented in current large-scale models (it is just beginning to be resolvable by high-resolution local-area models) so it needs to be parameterised. The schemes that are used are not optimised for mid-latitude storms, where convection often initiates at altitude rather than at the Earth's surface. A combination of novel diagnostics and new (or modified) schemes aimed at improving the representation of convection will be developed in this WP. Also addressed here will be the derivation of air-sea fluxes of heat and momentum from aircraft flights, and their use (as part of a larger, ongoing international project) to derive a better parameterisation for these quantities in high wind conditions. Lastly, microphysical measurements made with the FAAM aircraft will be used to derive latent heating/cooling rates as a function of the microphysical environment and used to improve the model simulations in the first WP and to improve microphysical parameterisations in the UM The final WP addresses the problem of predictability, using a combination of ensemble and data assimilation techniques. A unique archive of forecast ensembles produced at the Met Office will be exploited to determine how well the forecast ensemble actually generates realistic mesoscale features, and the skill with which this is done (using standard measures of skill). Model errors in representing convection, air-sea fluxes and microphysics will be investigated to determine their impact on the forecasts for different flow conditions. The relationship between different model variables on the mesoscale is poorly known at present and this will be investigated using ensembles and the results of the measurement programme. Finally, novel approaches to data assimilation will be investigated through a student project.

该项目旨在更好地了解和预测天气尺度风暴的中尺度结构。这些结构包括锋面、雨带、次级气旋、刺状射流等，它们很重要，因为我们经历的许多极端天气（如强风、大雨）都来自这些区域。天气预报模型能够正确地捕捉到其中的一些活动，但还有很多东西需要学习。通过测量和建模的结合，主要使用气象局统一模式（UM），我们将努力更好地了解气旋的中尺度过程是如何引起恶劣天气的，以及如何在模式和预报中更好地反映这些过程。该项目被组织成三个广泛的工作包。第一个目标是观察大气中真实的中尺度结构，使用高分辨率的原位和雷达测量来得出它们的形态和动力学。后者的关键是计算由非绝热过程产生的位涡量，特别是水（蒸汽/液体/冰）的相变和感热和潜热的海气通量。相关的高分辨率建模程序将使用UM来模拟具有代表性的事件，诊断模型中的PV趋势，并与测量结果进行比较。敏感性研究和对模式的进一步诊断将揭示预测对这些过程的正确表示的敏感性，以及在中尺度和更大尺度上绝热产生的PV的动力学后果。两个学生项目将研究边界层过程在风暴行为中的作用，并根据存档的雷达和风廓线数据对中尺度降水特征进行统计调查。第二个WP检查了特定的物理过程以及这些过程在预测模型中的表示方式。对流不能在当前的大尺度模型中明确地表示（它刚刚开始被高分辨率的局部区域模型所解析），所以它需要被参数化。所使用的方案对于中纬度风暴来说并不是最优的，在那里，对流通常是从高空而不是地球表面开始的。新的诊断和新的（或修改的）方案的组合，旨在改善对流的表示将在本WP开发。本文还将讨论飞机飞行产生的海气热通量和动量的推导，以及它们的使用（作为一个更大的、正在进行的国际项目的一部分），以获得大风条件下这些量的更好的参数化。最后，FAAM飞机进行的微物理测量将用于获得潜在的加热/冷却速率作为微物理环境的函数，并用于改进第一个WP中的模型模拟，并改善UM中的微物理参数化。最后的WP解决了可预测性问题，使用集合和数据同化技术的组合。英国气象局制作的一份独特的预报集合档案将被利用，以确定预报集合实际产生现实中尺度特征的程度，以及完成这一任务的技能（使用标准的技能衡量标准）。将研究模型在表示对流、海气通量和微物理方面的误差，以确定它们对不同流动条件下预报的影响。目前对中尺度上不同模式变量之间的关系知之甚少，这将使用集合和测量程序的结果进行研究。最后，我们将透过一个学生专题来探讨资料同化的新方法。