TY - JOUR

T1 - Selection of climate change scenario data for impact modelling

AU - Sloth Madsen, M.

AU - Maule, C. Fox

AU - MacKellar, N.

AU - Olesen, J. E.

AU - Christensen, J. Hesselbjerg

PY - 2012/10/1

Y1 - 2012/10/1

N2 - Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.

AB - Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.

KW - crop phenology

KW - method validation

KW - mycotoxins

KW - precipitation

KW - relative humidity

KW - temperature

UR - http://www.scopus.com/inward/record.url?scp=84866718834&partnerID=8YFLogxK

U2 - 10.1080/19440049.2012.712059

DO - 10.1080/19440049.2012.712059

M3 - Journal article

C2 - 22889171

AN - SCOPUS:84866718834

VL - 29

SP - 1502

EP - 1513

JO - Food Additives & Contaminants: Part A

JF - Food Additives & Contaminants: Part A

SN - 1944-0049

IS - 10

ER -