A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis.
A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis.
复制标题
DOI：
10.1007/s00484-012-0539-5
复制
发表时间：
2013-01
影响因子：
3.2
通讯作者：
Kukkonen J
中科院分区：
文献类型：
--
作者：
Siljamo P;Sofiev M;Filatova E;Grewling Ł;Jäger S;Khoreva E;Linkosalo T;Ortega Jimenez S;Ranta H;Rantio-Lehtimäki A;Svetlov A;Veriankaite L;Yakovleva E;Kukkonen J
本文对大气组合模式系统（SILAM）在桦树花粉扩散中的应用性能进行了评价。该系统中描述的一个配套文件，而目前的研究评估模型的花粉排放模块参数化的细节和气象输入数据的敏感性。突出显示了最重要的参数。分析所考虑的参考年为2006年。结果表明，该模型能够预测约三分之二的过敏性警报，最佳设置的优势比超过12。其他一些统计数字也证实了这些估计。在超过三分之二的情况下，低花粉浓度日也被正确预测。该模型只在花粉浓度中等的情况下才会遇到一定的困难。结果表明，最重要的输入参数是近地表温度，其偏差很容易危及结果。模型对温度随机波动的敏感性要低得多。在花粉发育、释放和散布的各个阶段，其他重要的参数是降水和环境湿度，以及风向。
An evaluation of performance of the System for Integrated modeLling of Atmospheric coMposition (SILAM) in application to birch pollen dispersion is presented. The system is described in a companion paper whereas the current study evaluates the model sensitivity to details of the pollen emission module parameterisation and to the meteorological input data. The most important parameters are highlighted. The reference year considered for the analysis is 2006. It is shown that the model is capable of predicting about two-thirds of allergenic alerts, with the odds ratio exceeding 12 for the best setup. Several other statistics corroborate with these estimations. Low-pollen concentration days are also predicted correctly in more than two-thirds of cases. The model experiences certain difficulties only with intermediate pollen concentrations. It is demonstrated that the most important input parameter is the near-surface temperature, the bias of which can easily jeopardise the results. The model sensitivity to random fluctuations of temperature is much lower. Other parameters important at various stages of pollen development, release, and dispersion are precipitation and ambient humidity, as well as wind direction.
登录
查看更多内容
影响因子：
5
作者：
Efstathiou, Christos;Isukapalli, Sastry;Georgopoulos, Panos
通讯作者：
Georgopoulos, Panos
影响因子：
0.9
作者：
Ranta, Hanna;Kubin, Eero;Bondestam, Kristoffer
通讯作者：
Bondestam, Kristoffer
影响因子：
5
作者：
Sofiev, M;Tuovinen, JP
通讯作者：
Tuovinen, JP
影响因子：
0.9
作者：
Levetin, E;Rogers, CA;Hall, SA
通讯作者：
Hall, SA
影响因子：
6.4
作者：
Siljamo, Pilvi;Sofiev, Mikhail;Shalaboda, Valentina
通讯作者：
Shalaboda, Valentina