The Effects of Climate Downscaling Technique and Observational Dataset on Modeled Ecological Responses: Supporting Data Tables
The Effects of Climate Downscaling Technique and Observational Dataset on Modeled Ecological Responses: Supporting Data Tables
Afshin Pourmokhtarian
Dept. of Civil and Environmental Engineering, Syracuse University
151 Link Hall
Syracuse, NY 13244
Charles Driscoll
Dept. of Civil and Environmental Engineering, Syracuse University
151 Link Hall
Syracuse, NY 13244
John Campbell
USDA Forest Service
271 Mast Rd.
Durham, NH 03824
Katharine Hayhoe
Texas Tech University
Climate Science Center
Lubbock, TX 79409
Anne M. K. Stoner
Texas Tech University
Climate Science Center
Lubbock, TX 79409
These data have been prepared as a supplement to Pourmokhtarian et al. (2016; full citation below), where complete details on methods can be found. We evaluated three downscaling methods: the delta method (or the change factor method); monthly quantile mapping (Bias Correction-Spatial Disaggregation, or BCSD); and daily quantile regression (Asynchronous Regional Regression Model, or ARRM). Additionally, we trained outputs from four atmosphere-ocean general circulation models (AOGCMs) (CCSM3, HadCM3, PCM, and GFDL-CM2.1) driven by higher (A1fi) and lower (B1) future emissions scenarios on two sets of observations (1/8th degree resolution grid vs. individual weather station) to generate the high-resolution climate input for the forest biogeochemical model PnET-BGC (8 ensembles of 6 runs).
This dataset consists of three files - 1) a zip archive file of all raw daily downscaled AOGCMs (csv format; years 1960-2099; delta method 2012-2099 only) which were used as input for PnET-BGC model, 2) a zip archive file of all PnET-BGC output files for each model run (csv format; years 1000-2100), and 3) a pdf document file that describes the content of the input and output files. Data were also used from the following Hubbard Brook longterm datasests: Daily Streamflow Watershed 6: Chemistry of Streamwater at the Hubbard Brook Experimental Forest, Watershed 6: Daily Precipitation Watershed 6: Daily Maximum/Minimum Temperature Data: Daily Solar Radiation Data:
KEYWORD SET: Hubbard Brook Ecosystem Study LTER
climate change, climate variability, ecological modeling, modeling, hydrology, forests, HBEF Watershed 6, HBR, Hubbard Brook LTER, Hubbard Brook, net primary productivity, statistical downscaling, streamwater nitrate, stream, nitrate, uncertainty analysis, watersheds, PnET-BGC, PnET.
KEYWORD SET: LTER Core Research Areas
primary production.
Hubbard Brook Experimental Forest - Watershed 6
West bounding coordinate: -71.743462
East bounding coordinate: -71.735649
North bounding coordinate: 43.957001
South bounding coordinate: 43.949928
  • Pourmokhtarian, A., Driscoll, C.T., Campbell, J.L., Hayhoe, K., and Stoner, A.M.K 2016. The effects of climate downscaling technique and observational dataset on modeled ecological responses. Ecological Applications 0(0):In Press.
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Citation example: Holmes, R.T. 2012. Bird Abundances at Hubbard Brook (1969-2010) and on three replicate plots (1986-2000) in the White Mountain National Forest. Durham, NH. Hubbard Brook Data Archive [Database]. (23 July 2012)

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