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Table 1.

Sources of climate data used to generate the baseline climate normal (1961–1990) grids for the ClimateNA software package.

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Fig 1.

Distribution of 4891 weather stations and the baseline data sources (PRISM and WorldClim) within the coverage of ClimateNA.

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Fig 2.

Proportions of variance explained (R square values) by local linear regression in total variation among the nine neighbor pixels for monthly minimum and maximum temperatures, and monthly precipitation across the entire North America.

The extent of the box indicates the 25th and 75th percentiles. The horizontal solid lines inside the boxes indicate the medians.

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Fig 2 Expand

Fig 3.

Relationships between differences in minimum temperatures in January (Tmin01), February (Tmin02) and March (Tmin03) and the change in elevation among the nine neighbor cells at a randomly picked mountain area in British Columbia (latitude = 53.88° and longitude = -125.1°).

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Fig 3 Expand

Table 2.

Comparisons in prediction standard errors between ClimateNA and the baseline climate data for primary monthly climate variables based on evaluations against observations from 4891 weather stations in North America.

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Table 2 Expand

Fig 4.

Illustrations of the model fit (red line) of the piecewise function (linear and nonlinear) for monthly degree-days DD<0 and DD<18 on monthly mean temperature for January for the base line period 1961–1990 for 4891 locations (black points).

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Fig 4 Expand

Fig 5.

Illustrations of the model fit (red line) of the piecewise function (linear and nonlinear) with all (4891) and split samples for monthly degree-days DD>5 and DD>18 on monthly mean temperature for January for the base line period 1961–1990.

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Fig 5 Expand

Table 3.

The amount of variance in observed climate variables explained by ClimateNA derived variables and their prediction standard errors.

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Table 3 Expand

Fig 6.

Landscape image (a) and original forest ecotype map (b) at the north end of Vancouver Island, BC, Canada (centered at Lat. = 50.362° and Long. = -126.385°). Spatial distributions of mean annual temperature (MAT) (c and e) and predicted forest ecotypes (d and f) at the spatial resolutions of 800 x 800 m (c and d) and 80 x 80 m (e and f), respectively.

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Fig 6 Expand