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Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook

机译：2014年欧洲橄榄花粉分布的多模型集合模拟：现状和展望

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The paper presents the first modelling experiment of the European-scale olive pollen dispersion, analyses the quality of the predictions, and outlines the research needs. A 6-model strong ensemble of Copernicus Atmospheric Monitoring Service (CAMS) was run throughout the olive season of 2014, computing the olive pollen distribution. The simulations have been compared with observations in eight countries, which are members of the European Aeroallergen Network (EAN). Analysis was performed for individual models, the ensemble mean and median, and for a dynamically optimised combination of the ensemble members obtained via fusion of the model predictions with observations. The models, generally reproducing the olive season of 2014, showed noticeable deviations from both observations and each other. In particular, the season was reported to start too early by 8 days, but for some models the error mounted to almost 2 weeks. For the end of the season, the disagreement between the models and the observations varied from a nearly perfect match up to 2 weeks too late. A series of sensitivity studies carried out to understand the origin of the disagreements revealed the crucial role of ambient temperature and consistency of its representation by the meteorological models and heat-sum-based phenological model. In particular, a simple correction to the heat-sum threshold eliminated the shift of the start of the season but its validity in other years remains to be checked. The short-term features of the concentration time series were reproduced better, suggesting that the precipitation events and cold/warm spells, as well as the large-scale transport, were represented rather well. Ensemble averaging led to more robust results. The best skill scores were obtained with data fusion, which used the previous days' observations to identify the optimal weighting coefficients of the individual model forecasts. Such combinations were tested for the forecasting period up to 4 days and shown to remain nearly optimal throughout the whole period.
机译：本文提出了欧洲规模橄榄花粉分散的第一个建模实验，分析了预测的质量，并概述了研究需求。 2014年的橄榄季节运行了哥伦比亚斯大气监测服务（CAMS）的6型型号强大的集合，计算了橄榄花粉分布。将模拟与八个国家的观察结果进行了比较，这些国家是欧洲航空预报（EAN）的成员。对各个模型，集合均值和中值进行分析，以及通过与观察结果的模型预测融合获得的集合构件的动态优化组合。该模型通常再现2014年的橄榄季，显示出与彼此的观察结果明显偏差。特别是，季节据报道，8天的赛季开始较早，但对于一些型号安装到近2周的错误。在赛季结束时，模型与观察之间的分歧从几乎完美的匹配变化，最多2周太晚了。为理解分歧的起源而进行的一系列敏感性研究揭示了环境温度和其代表的一致性的关键作用，气象模型和基于热量的酚类模型。特别地，对热量阈值的简单校正消除了季节开始的偏移，但其在其他年份的有效性仍有待检查。浓缩时间序列的短期特征更好地转载，表明降水事件和冷/温法术以及大规模的运输相当良好。集合平均导致更强大的结果。利用数据融合获得了最佳的技能评分，该数据融合使用了前几天的观察，以确定各个模型预测的最佳加权系数。这些组合对于预测期最多4天测试，并且在整个时期内显示仍然仍然最佳。

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