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For us in Taiwan it has always been problems to use global grid data like WorldClim2, because Taiwan (150 km width, 400 km in length) is way smaller than the resolution. The high and complex topography (up to 3952 m a.s.l.) further makes the downscaling of the world climate model difficult. We have almost 2 decades monitoring of the meteorological parameters of the site, and they do differ from the data you showed me. In fact I very much liked to show a slide (see attached) of the unique meteorological condition of the CLM site when I am giving a talk about my research at the CLM site. I liked to draw attention that there are some interesting corners where the "normal" patterns won't fit to.
Basically this site in the worldclim2 data is 15.1 MAT, 2659 MAP, but at the site they've measured 13.5/4300. Our Figure 3 with the site circled:
I’m not sure the best thing to do here. If 13.5/4300 have been measured over decades, i.e., are long-term means, we can use those values instead, but then need to explain why we have a point sitting out in white space (marked on attached figure). This might be confusing to readers. Alternatively, we could note in the caption that site-specific values sometimes differ considerably from global datasets like WorldClim2; this would have the advantage of keeping the data source constant for all the points in the figure.
The text was updated successfully, but these errors were encountered:
Figure 3. Mean annual temperature (°C) and annual precipitation (mm) extracted from WorldClim (Hijmans et al. 2005) for the study sites (black rings) superimposed on the Whittaker biome chart (Biome chart adopted from Ricklefs (2008) plotted with the R package plotbiomes, https://github.com/valentinitnelav/plotbiomes).
Shih-Chieh Chang notes:
Basically this site in the worldclim2 data is 15.1 MAT, 2659 MAP, but at the site they've measured 13.5/4300. Our Figure 3 with the site circled:
I’m not sure the best thing to do here. If 13.5/4300 have been measured over decades, i.e., are long-term means, we can use those values instead, but then need to explain why we have a point sitting out in white space (marked on attached figure). This might be confusing to readers. Alternatively, we could note in the caption that site-specific values sometimes differ considerably from global datasets like WorldClim2; this would have the advantage of keeping the data source constant for all the points in the figure.
The text was updated successfully, but these errors were encountered: