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A final summary figure summarizing the results of a study that compares two different downscaling techniques in terms of how they project future change in various aspects of the maple syrup tapping season. Spatially, the larger project uses raster data covering the full range of sugar maple across the northeastern US, but the summary figure represents point data (as an example) at a sugarbush farm in central Wisconsin. The results show that dynamically downscaled models fail to adequately forecast absolute values of future conditions but do capture potential changes in year-to-year variability — a metric of particular concern to producers as it challenges planning. Statistically downscaled models, while they do...
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Long-term historical (derived from GHCN) and future simulated (derived from BCCA) time series analyses for several meteorological variables are provided to several clients within the Northeast Climate Adaptation Science Center (NE CASC) footprint as background of the state of changes in their local climate. Variables include average annual and seasonal temperature and precipitation, extreme temperature and precipitation, wind, and snow depth. Precipitation includes both rain and snow.
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This data takes existing, pre-published (Wang et al. 2015) forest composition data and converts it to ozone precursor emission potential to understand the impact climate change will have on air quality through changes in forest composition.
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