Zink Katrin, Kaufmann Pirmin, Petitpierre Blaise, Broennimann Olivier, Guisan Antoine, Gentilini Eros, Rotach Mathias W
Institute of Meteorology and Geophysics, University of Innsbruck, 6020, Innsbruck, Austria.
Federal Office of Meteorology and Climatology MeteoSwiss, 8044, Zürich, Switzerland.
Int J Biometeorol. 2017 Jan;61(1):23-33. doi: 10.1007/s00484-016-1188-x. Epub 2016 Jun 18.
One of the key input parameters for numerical pollen forecasts is the distribution of pollen sources. Generally, three different methodologies exist to assemble such distribution maps: (1) plant inventories, (2) land use data in combination with annual pollen counts, and (3) ecological modeling. We have used six exemplary maps for all of these methodologies to study their applicability and usefulness in numerical pollen forecasts. The ragweed pollen season of 2012 in France has been simulated with the numerical weather prediction model COSMO-ART using each of the distribution maps in turn. The simulated pollen concentrations were statistically compared to measured values to derive a ranking of the maps with respect to their performance. Overall, approach (2) resulted in the best correspondence between observed and simulated pollen concentrations for the year 2012. It is shown that maps resulting from ecological modeling that does not include a sophisticated estimation of the plant density have a very low predictive skill. For inventory maps and the maps based on land use data and pollen counts, the results depend very much on the observational site. The use of pollen counts to calibrate the map enhances the performance of the model considerably.
数值花粉预报的关键输入参数之一是花粉源的分布。一般来说，有三种不同的方法来绘制这种分布图：（1）植物清单，（2）结合年度花粉计数的土地利用数据，以及（3）生态建模。我们使用了所有这些方法的六幅示例地图，以研究它们在数值花粉预报中的适用性和实用性。使用数值天气预报模型COSMO - ART依次利用每一幅分布图模拟了2012年法国豚草花粉季。将模拟的花粉浓度与测量值进行统计比较，以得出这些地图在性能方面的排名。总体而言，方法（2）在2012年观测到的和模拟的花粉浓度之间产生了最佳的对应关系。结果表明，不包括对植物密度进行精确估算的生态建模所生成的地图预测能力非常低。对于清单地图以及基于土地利用数据和花粉计数的地图，结果在很大程度上取决于观测站点。使用花粉计数来校准地图可显著提高模型的性能。
