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Uncertainty estimation for operational ocean forecast products-a multi-model ensemble for the North Sea and the Baltic Sea

机译:业务海洋预报产品的不确定性估计 - 北海和波罗的海的多模型集

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摘要

Multi-model ensembles for sea surface temperature (SST), sea surface salinity (SSS), sea surface currents (SSC), and water transports have been developed for the North Sea and the Baltic Sea using outputs from several operational ocean forecasting models provided by different institutes. The individual models differ in model code, resolution, boundary conditions, atmospheric forcing, and data assimilation. The ensembles are produced on a daily basis. Daily statistics are calculated for each parameter giving information about the spread of the forecasts with standard deviation, ensemble mean and median, and coefficient of variation. High forecast uncertainty, i.e., for SSS and SSC, was found in the Skagerrak, Kattegat (Transition Area between North Sea and Baltic Sea), and the Norwegian Channel. Based on the data collected, longer-term statistical analyses have been done, such as a comparison with satellite data for SST and evaluation of the deviation between forecasts in temporal and spatial scale. Regions of high forecast uncertainty for SSS and SSC have been detected in the Transition Area and the Norwegian Channel where a large spread between the models might evolve due to differences in simulating the frontal structures and their movements. A distinct seasonal pattern could be distinguished for SST with high uncertainty between the forecasts during summer. Forecasts with relatively high deviation from the multi-model ensemble (MME) products or the other individual forecasts were detected for each region and each parameter. The comparison with satellite data showed that the error of the MME products is lowest compared to those of the ensemble members.
机译:北海和波罗的海的海面温度(SST),海面盐度(SSS),海面水流(SSC)和水运输的多模型合集已使用由不同的研究所。各个模型在模型代码,分辨率,边界条件,大气强迫和数据同化方面有所不同。乐团每天制作。将为每个参数计算每日统计信息,以提供有关预测范围,标准差,总体平均值和中位数以及变异系数的信息。在Skagerrak,Kattegat(北海和波罗的海之间的过渡地区)和挪威海峡发现了预报高度不确定性,即SSS和SSC。根据收集到的数据,进行了较长期的统计分析,例如与SST的卫星数据进行比较以及评估时空尺度上的预报之间的偏差。在过渡区和挪威海峡发现了SSS和SSC的高度不确定性预测区域,由于模拟额叶结构及其运动的差异,模型之间可能会出现较大的差异。在夏季,预报的SST可能有明显的季节性模式,但不确定性很高。对于每个区域和每个参数,都检测到与多模型集合(MME)产品或其他单个预测具有相对较高偏差的预测。与卫星数据的比较表明,与集合成员相比,MME产品的误差最低。

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