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Ontario Climate Data Portal

TitleOntario Climate Data Portal
Publication TypeManual Entry
Year of Publication2013
AuthorsWang, Xiuquan, and Gordon Huang
Citation Key1404
Community Notes

LJB 2.16.2015

From the data report:

... the PRECIS model will be driven by an ensemble of GCMs which are based on the standard HadCM3Q0 model, each GCM has a set of perturbations to its dynamical and physical formulation. These perturbations are made within the known bounds of modelling uncertainty along 4 with HadCM3Q (Wilson et al. 2011). This ensemble of GCMs can be used to estimate the uncertainty in regional climate model results due to uncertainty in driving GCM formulation and the uncertainty in fine-scale climate change due to uncertainties in global and regional model formulation. The external forcing is from the SRES A1B emissions scenario. 

  • Although only one GCM (HadCM3) is used for developing the ensemble, a perturbed physics method is used to capture a range of uncertainty. (more on this here)

notes on PRECIP model evaluation (chapter 3 of report)

PRECIP model evaluation comments
mean daily temps mean daily max temps mean daily min temps mean monthly total precip

the models did not capture mean daily temps well at the following locations and for particular times of year:

summer temps at Toronto Lester B Pearson

summer temps at Toronto City Center Island

winter temps at Wiarton 

winter temps at North Bay

winter temps at Sioux Lookout

the models did not capture mean daily max temps well at the following locations and for particular times of year:

summer Toronto Lester B Pearson

summer Toronto City Center Island

winter Wiarton

winter Sioux Lookout

All models show a shift in the annual cycle of daily minimum temperatures.  The largest model bias is for spring daily minimum temperatures that are warming than observed.  Fall daily minimum temperatures are slightly cooler than observed.

windsor - model spread covers summer observed but large model variability.  smaller variability during winter but models bias wet

London Intl - models capture observed during all months.  typically models have slight wet bias.  summer variability large

Toronto Lester B Pearson - models capture summer precip with large variability. spring and fall wet bias.

Toronto City Center Island - models bias wet all year

Ottawa Macdonald-Cartier - models slight wet bias all year.  summer variability large

Wiarton - models capture observed most months but large summer/fall variability

North Bay - models capture ons most months but best Mar-Jun. dry bias in fall.

Sault Set Marie - dry bias most months but models capture ons half of the time

Sioux Lookout - models capture ons well during summer even though high variability

Timmins Victor Power - models capture obs well during most months

Big Trout Lake Station - models slightly wet in winter, capture ons in summer but higher variability

Moosonee UA Station - models wet in winter but capture obs in summer with smaller variability


from the portal report:

The data sets of this project are derived from the previous high-resolution probabilistic modeling results produced by the IEESC at the University of Regina using the PRECIS model (IEESC 2012). The Hadley Centre has published 17 sets of boundary data from a perturbed physics ensemble (i.e. HadCM3Q0-Q16, known as ‘QUMP’), which is based on Hadley Centre’s HadCM3 model under SRES A1B emissions scenario, for use with PRECIS in order to allow users to generate an ensemble of high-resolution regional simulations (McSweeney and Jones 2010, McSweeney, Jones et al. 2012). Downscaling the 17 PPE ensemble with PRECIS would require very large inputs of computing resources, 3 data storage and data analyses. In order to explore the range of uncertainties while minimizing these requirements, we select a sub-set of 5 members (i.e. HadCM3Q0, Q3, Q10, Q13, and Q15) from the QUMP ensemble according to the Hadley Centre’s recommendation (see HadCM3Q0 is first selected as it is the standard, unperturbed model using the original parameter settings as applied in the atmospheric component of HadCM3. Selection of the remaining four members is based on a) their performances in simulating key features of the climate over Ontario, and b) their ability of sampling the range of outcomes of future changes simulated by the full 17-member ensemble (Bellprat, Kotlarski et al. 2012). We run five PRECIS experiments driven by boundary conditions from the selected GCM members from 1950 to 2099 at its highest horizontal resolution (i.e. 25 km). This allows us to carry out comprehensive analyses by providing full simulation coverage from present day to future. The PRECIS model outputs are extracted and divided into four 31-yr periods: one baseline period (1960-1990), and three future periods (2015-2045, 2035-2065, and 2065-2095), representing its simulations for the province of Ontario under current and future climate forcings. Based upon the 5-member PRECIS ensemble results, we calculated nine percentiles: 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90% for each variable as listed above for the four 31-yr periods, with the purpose of providing useful information for assessing the possible impacts associated with climatic changes at regional or local scales.