Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological Aerosols

We have evaluated three prognostic variables in Weather Research and Forecasting (WRF) model, mean daily temperature, daily maximum temperature, and daily minimum temperature using 9 months of model simulations at 36 and 12 km resolution, and compared the results with 1182 observational sites in nor...

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Main Authors: C. A. Skjøth, M. Werner, M. Kryza, B. Adams-Groom, A. Wakeham, M. Lewis, R. Kennedy
Format: Article
Language:English
Published: Wiley 2015-01-01
Series:Advances in Meteorology
Online Access:http://dx.doi.org/10.1155/2015/412658
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author C. A. Skjøth
M. Werner
M. Kryza
B. Adams-Groom
A. Wakeham
M. Lewis
R. Kennedy
author_facet C. A. Skjøth
M. Werner
M. Kryza
B. Adams-Groom
A. Wakeham
M. Lewis
R. Kennedy
author_sort C. A. Skjøth
collection DOAJ
description We have evaluated three prognostic variables in Weather Research and Forecasting (WRF) model, mean daily temperature, daily maximum temperature, and daily minimum temperature using 9 months of model simulations at 36 and 12 km resolution, and compared the results with 1182 observational sites in north and central Europe. The quality of the results is then determined in the context of the governing variables used in crop science, forestry, and aerobiological models. We use the results to simulate the peak of the birch pollen season (aerobiology), growth of barley (crop science), and development of the invasive plant pathogen Hymenoscyphus pseudoalbidus (the cause of ash-dieback). The results show that the crop and aerobiological models are particularly sensitive to grid resolution and much higher quality is obtained from the 12 km simulations compared to 36 km. The results also show that the summer months have a bias, in particular for maximum and minimum temperatures, and that the low/high bias is clustered in two areas: continental and coastal influenced areas. It is suggested that the use of results from meteorological models as an input into biological models needs particular attention in the quality of the modelled surface data as well as the applied land surface modules.
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institution OA Journals
issn 1687-9309
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publisher Wiley
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series Advances in Meteorology
spelling doaj-art-996dfab415e647a4a56db26392ec30c52025-08-20T02:10:17ZengWileyAdvances in Meteorology1687-93091687-93172015-01-01201510.1155/2015/412658412658Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological AerosolsC. A. Skjøth0M. Werner1M. Kryza2B. Adams-Groom3A. Wakeham4M. Lewis5R. Kennedy6National Pollen and Aerobiology Research Unit, Institute of Science and the Environment, University of Worcester, Henwick Grove, Worcester WR2 6AJ, UKNational Pollen and Aerobiology Research Unit, Institute of Science and the Environment, University of Worcester, Henwick Grove, Worcester WR2 6AJ, UKDepartment of Climatology and Atmosphere Protection, University of Wrocław, Ulica Kosiby 8, 51-621 Wrocław, PolandNational Pollen and Aerobiology Research Unit, Institute of Science and the Environment, University of Worcester, Henwick Grove, Worcester WR2 6AJ, UKNational Pollen and Aerobiology Research Unit, Institute of Science and the Environment, University of Worcester, Henwick Grove, Worcester WR2 6AJ, UKNational Pollen and Aerobiology Research Unit, Institute of Science and the Environment, University of Worcester, Henwick Grove, Worcester WR2 6AJ, UKNational Pollen and Aerobiology Research Unit, Institute of Science and the Environment, University of Worcester, Henwick Grove, Worcester WR2 6AJ, UKWe have evaluated three prognostic variables in Weather Research and Forecasting (WRF) model, mean daily temperature, daily maximum temperature, and daily minimum temperature using 9 months of model simulations at 36 and 12 km resolution, and compared the results with 1182 observational sites in north and central Europe. The quality of the results is then determined in the context of the governing variables used in crop science, forestry, and aerobiological models. We use the results to simulate the peak of the birch pollen season (aerobiology), growth of barley (crop science), and development of the invasive plant pathogen Hymenoscyphus pseudoalbidus (the cause of ash-dieback). The results show that the crop and aerobiological models are particularly sensitive to grid resolution and much higher quality is obtained from the 12 km simulations compared to 36 km. The results also show that the summer months have a bias, in particular for maximum and minimum temperatures, and that the low/high bias is clustered in two areas: continental and coastal influenced areas. It is suggested that the use of results from meteorological models as an input into biological models needs particular attention in the quality of the modelled surface data as well as the applied land surface modules.http://dx.doi.org/10.1155/2015/412658
spellingShingle C. A. Skjøth
M. Werner
M. Kryza
B. Adams-Groom
A. Wakeham
M. Lewis
R. Kennedy
Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological Aerosols
Advances in Meteorology
title Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological Aerosols
title_full Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological Aerosols
title_fullStr Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological Aerosols
title_full_unstemmed Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological Aerosols
title_short Quality of the Governing Temperature Variables in WRF in relation to Simulation of Primary Biological Aerosols
title_sort quality of the governing temperature variables in wrf in relation to simulation of primary biological aerosols
url http://dx.doi.org/10.1155/2015/412658
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