DEPICT-SNOW: Decoding and predicting the change in future extreme snowfall in the Northern Hemisphere

极端降雪是具有巨大经济和人类影响的重大灾难性气候事件；然而，根据政府间气候变化专门委员会最新的评估报告，对过去和未来的暴雪变化的置信度都很低。这是由于高度不确定的大气环流对气候变化的响应、模式偏差、较差的降雪观测和有限的模式集合。对未来几十年北半球极端降雪变化进行创新和及时的预测/预测，是该项目的首要目标。该项目将使用先进的天气预报模型、大集合/高分辨率建模策略和先进的分析方法，在未来极端降雪变化和预测/预测方面取得重大进展。这些前所未有的大集合、高分辨率天气预报模型模拟是由牛津大学电子研究中心独特而创新的分布式计算项目（Climateprediction.net）以及该计算项目在极端事件归因中的广泛应用实现的。这些骨干季节模拟将采用热力学和动力学分解等先进的分析方法进行分析，并考虑关键的大气环流模式，以突破未来极端降雪变化的控制机制。将使用基于风险和基于故事情节的方法对未来极端降雪进行创新和及时的预测/预测，这两种方法相辅相成。这些对科学界和更广泛的公共部门具有直接的重要性。简而言之，该项目将填补未来极端降雪变化控制机制方面的重大知识空白，向社会通报与未来极端降雪变化相关的定量风险，并指导关键的缓解策略。

Extreme snowfall is a major disastrous climate event that has enormous economic and human impacts; however, according to the latest Assessment Report of the Intergovernmental Panel on Climate Change, there is low confidence in both past and future changes in heavy snowfall. This is due to highly uncertain atmospheric circulation response to climate change, model biases, poor snowfall observations and limited model ensembles. The overarching aim of DEPICTSnow is to pinpoint the controlling mechanisms for, and to produce innovative and timely predictions/projections of future extreme snowfall change in the Northern Hemisphere for the coming decades. DEPICTSnow will use an advanced weather forecast model, large-ensemble/high-resolution modelling strategy and advanced analytical methods to make significant advances in future extreme snowfall change and predictions/projections. These unprecedented large-ensemble, high-resolution weather forecast model simulations are enabled by the University of Oxford's e- Research Centre's unique and innovative distributed computing project (Climateprediction.net) and the extensive application of this computing project in extreme events attribution. These backbone seasonal simulations will be analyzed with advanced analytic methods such as decomposition of thermodynamics and dynamics and considering key atmospheric circulation patterns to make breakthroughs in controlling mechanisms for future extreme snowfall change. Innovative and timely predictions/projections of future extreme snowfall will be produced using both risk-based and storyline-based approaches, which complements each other. These can be of immediate importance to the scientific communities and wider public sectors. In short, DEPICTSnow will fill a significant knowledge gap in the controlling mechanisms of future extreme snowfall change, inform societies of quantitative risks associated with future extreme snowfall change and guide critical mitigation strategies.