0000000000201305

AUTHOR

Pilvi Siljamo

0000-0002-2317-9125

showing 2 related works from this author

A statistical model for predicting the inter-annual variability of birch pollen abundance in Northern and North-Eastern Europe

2018

The paper suggests a methodology for predicting next-year seasonal pollen index (SPI, a sum of daily-mean pollen concentrations) over large regions and demonstrates its performance for birch in Northern and North-Eastern Europe. A statistical model is constructed using meteorological, geophysical and biological characteristics of the previous year). A cluster analysis of multi-annual data of European Aeroallergen Network (EAN) revealed several large regions in Europe, where the observed SPI exhibits similar patterns of the multi-annual variability. We built the model for the northern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia and…

Baltic StatesEnvironmental EngineeringRepublic of Belarus010504 meteorology & atmospheric sciencesMeteorologyCorrelation coefficientta1172Birch pollen010501 environmental sciencesSeasonal pollen indexmedicine.disease_causeDisease cluster01 natural sciencesPollen forecastingAnnan biologiRussiaAbundance (ecology)PollenmedicineOther Biological TopicsEnvironmental ChemistryWaste Management and DisposalBetulaFinland0105 earth and related environmental sciencesSwedenModels Statisticalta114NorwayStatistical modelAllergensPollutionBirch pollenGeographyta1181PollenSeasonsPhysical geographyInter-annual variabilityScience of The Total Environment
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MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe

2015

Abstract. This paper presents the first ensemble modelling experiment in relation to birch pollen in Europe. The seven-model European ensemble of MACC-ENS, tested in trial simulations over the flowering season of 2010, was run through the flowering season of 2013. The simulations have been compared with observations in 11 countries, all members of the European Aeroallergen Network, for both individual models and the ensemble mean and median. It is shown that the models successfully reproduced the timing of the very late season of 2013, generally within a couple of days from the observed start of the season. The end of the season was generally predicted later than observed, by 5 days or more…

Atmospheric Sciencemedicine.medical_specialty010504 meteorology & atmospheric sciencesUrban Mobility & EnvironmentClimateAerobiologyUrbanisation010501 environmental sciencesmedicine.disease_cause01 natural sciencesAerobiologyFloweringlcsh:ChemistryPollenddc:550medicineStatistical dispersionAerosol0105 earth and related environmental sciencesEnsemble forecastingEnsemble averageModelingEnsemble forecastingCAS - Climate Air and SustainabilityMiljövetenskaplcsh:QC1-999EuropeBirch pollenlcsh:QD1-999HabitatClimatology[SDE]Environmental SciencesPollenLate seasonEnvironmental scienceELSS - Earth Life and Social SciencesEnvironment & Sustainabilitylcsh:PhysicsEnvironmental Sciences
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