This discussion paper reveals the contribution of pollen transport conditions to the inter-annual variability of the seasonal pollen index (SPI). This contribution is quantified as a sensitivity of the pollen model predictions to meteorological variability and is shown to be a noticeable addition to the SPI variability caused by plant reproduction cycles. A specially designed SILAM model re-analysis of pollen seasons 1980–2014 was performed, resulting in the 35 years of the SPI predictions over Europe, which was used to compute the SPI inter-annual variability. The current paper presents the results for birch and grass. Throughout the re-analysis, the source term formulations and habitation maps were kept constant, which allowed attributing the obtained variability exclusively to the pollen release and transport conditions during the flowering seasons. It is shown that the effect is substantial: it amounts to 10–20% (grass) and 20–40% (birch) of the observed SPI year-to-year changes reported in the literature. The phenomenon has well-pronounced spatial- and species-specific patterns. The findings were compared with observation-based statistical models for the SPI prediction, showing that such models highlight the same processes as the analysis with the SILAM model.

中文翻译：

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运输条件对季节性花粉指数变异性的影响

本讨论文件揭示了花粉运输条件对季节性花粉指数 (SPI) 年际变化的贡献。这种贡献被量化为花粉模型预测对气象变异性的敏感性，并被证明是植物繁殖周期引起的 SPI 变异性的显着补充。对 1980-2014 年花粉季节进行了专门设计的 SILAM 模型重新分析，产生了欧洲 35 年的 SPI 预测，用于计算 SPI 年际变化。当前论文介绍了桦树和草的结果。在整个重新分析过程中，源项公式和居住地图保持不变，这允许将获得的变异性完全归因于开花季节的花粉释放和运输条件。结果表明，效果是显着的：它相当于文献中报道的观察到的 SPI 逐年变化的 10-20%（草）和 20-40%（桦木）。这种现象具有明显的空间和物种特异性模式。将结果与基于观测的 SPI 预测统计模型进行了比较，表明这些模型突出了与 SILAM 模型分析相同的过程。