Arctic Emissivity of Snow for Operational Prediction (AESOP) of Weather

伊索将启动诺森比亚大学和气象局之间的合作，以做出必要的基于证据的商业决定，以改变气象局业务天气预报中使用积雪覆盖的北极地区卫星测量的方式。英国气象局需要改进北极地区的短期业务天气预报，由于英国靠近北极，这将导致英国业务季节预报的增强。目前，在北极上空使用这些卫星测量是极其困难的，因为在穿透云层所需的微波频率下，卫星同时观测地表和大气。因此，大量潜在可用的卫星数据目前被天气预报系统拒绝。地面发射率模型的新数据和最新理论进展现在为将地面和大气发射率信号分离到大气层顶部微波亮度温度提供了可能性，从而使以前被丢弃的卫星观测能够用于业务数值天气预报。伊索将为主办组织提供必要的理由和知识，以在其发展周期的适当时间点实施操作系统的变化。这一安排利用现有的科学和专业知识，利用由NERC和欧洲航天局资助的最新科学进展，以满足气象局的两个主要需求。首先，气象局需要地面数据和对在测量边缘冰带附近的北极云、雪和海冰期间进行的空中亮度温度测量的模拟进行评估(MACSSIMIZE：由气象局资助的空中大气测量活动基金)。诺森比亚大学的工作人员最近收集了雪微结构的必要地面测量数据，并对其进行了质量控制(由英国国家科学研究中心和加拿大北极伙伴关系资助，名为“用于模拟微波和热特性的北极雪的特征”)，并可供伊索使用。其次，英国气象局希望利用桑德尔斯和他的同事开发的一种创新的雪排放模型方法(SMRT)。这是对以前使用的单一辐射传输模型方法的实质性发展，因为SMRT中有多个模型表示，它允许估计天气预报系统所需的模型误差。诺森比亚大学将向气象局提供运行它的模型代码和计算专业知识，以供在此地点的时间范围内和之后的协作使用。主办组织将受益于将数据和建模专业知识转换为其业务系统中使用的RTTOV辐射传输模式，并且这一地点将向英国气象局提供明确的证据，证明对其业务模拟方案进行更改的好处。这是促进气象局业务天气预报未来发展变化的关键一步，因为在其业务系统内进行全面数据同化试验的费用非常高昂。

AESOP will initiate a collaboration between Northumbria University and the Met Office to make an evidence-based business decision necessary to change the way satellite measurements in the snow-covered Arctic are used in Met Office operational weather forecasts. The Met Office needs to improve short-range operational weather forecasts in the Arctic, which will lead to enhanced operational seasonal forecasts in the UK due to the close proximity of the UK to the Arctic. It is currently extremely difficult to use these satellite measurements over the Arctic because at the microwave frequencies needed to see through the clouds, the satellites observe both the surface and atmosphere together. Consequently, vast quantities of potentially usable satellite data are currently rejected by weather forecasting systems. New data and recent theoretical advances in surface emissivity models now provides potential for separation of surface and atmospheric emissivity signals to top of atmosphere microwave brightness temperature, thus allowing previously discarded satellite observations to be used for operational numerical weather prediction. AESOP will provide the host organisation with the justification and knowledge needed to implement changes in the operational system at the appropriate point in its development cycle.This placement uses existing science and expertise, leveraging recent scientific advances funded by NERC and the European Space Agency to meet two Met Office primary needs. Firstly, the Met Office requires ground-based data and evaluation of simulations of airborne brightness temperature measurements taken during Measurements of Arctic Clouds, Snow, and Sea Ice nearby the Marginal Ice ZonE (MACSSIMIZE : Met Office funded Facility for Airborne Atmospheric Measurements campaign). The necessary ground measurements of snow microstructure have recently been collected and quality-controlled by staff at Northumbria University (funded by NERC UK and Canada Arctic Partnership bursary 'Characterisation of Arctic snow for modelling microwave and thermal properties') and are available to AESOP. Secondly, the Met Office would like to harness an innovative new snow emission modelling approach (SMRT ) developed by Sandells and colleagues. This is a substantial development over single radiative transfer model approaches previously used due to multiple model representations in SMRT, which allows an estimate of the model error needed for weather forecast systems. Model code and computational expertise to run it will be provided to the Met Office from Northumbria University for collaborative use through and beyond the timescale of this placement.The host organisation will benefit from translation of data and modelling expertise into the RTTOV radiative transfer model used in their operational system, and this placement will provide clear evidence to the Met Office of the benefits of making changes to their operational modelling scheme. This is a critical step to contribute to future developmental changes in the operational weather prediction at the Met Office, as full data assimilation trials within their operational system are hugely expensive.