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Supporting files for "Climate change may have limited effect on global risk of potato late blight"

Version 17 2014-06-30, 07:14
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Version 1 2014-06-22, 05:27
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posted on 2014-06-30, 07:14 authored by Adam SparksAdam Sparks

Supporting files for "Climate change may have limited effect on global risk of potato late blight" (Sparks et al. 2014). Code is freely available on GitHub, http://adamhsparks.github.io/Global-Late-Blight-Modelling/.

A2 Files

The A2 climate files files are ensemble models (averages) of the following three models: BCCR BCM2.0 (Bjerknes Centre for Climate Research Bergen Climate Model Version 2.0 Commonwealth Scientific and Industrial Research Organization GCM mark 3), CSIRO mk3.0 (Commonwealth Scientific and Industrial Research Organization GCM mark 3) and INMCM3.0 (Institute for Numerical Mathematics Version 3.0 Model).

The original A2 emission scenario files were obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP Working Group on Coupled Modelling (WGCM) and downscaled using the delta method to 10 arcminute resolution. Data include maximum temperature, minimum temperature, mean temperature, relative humidity and precipitation. Three time-slices are represented: 2000-2019, 2040-2059 and 2080-2099.

 Daily and Monthly Files

These tables contain blight units as calculated by the SimCast model, using HUSWO (Hourly US Weather Observations; NOAA) for resistant and susceptible potato cultivars. These files are used for the creation of the SimCastMeta GAM (Sparks et al. 2011). Daily files are the original blight unit output from the SimCast model (Grünwald et al. 2002) and corresponding temperature and relative humidity values. Monthly files are monthly averages of blight units and corresponding temperature and relative humidity values.

SimCastMeta Look Up Files

These tables contain the blight unit output of the SimCastMeta model along with corresponding temperature and relative humidity values which generate the blight units. Can be used in other applications as a look-up table rather than recreating the whole model in R. 

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