This set of files includes downscaled historical estimates of monthly temperature (in degrees Celsius, no unit conversion necessary) from 1901 - 2013 (CRU TS 3.22) at 10 min x 10 min spatial resolution. The downscaling process utilizes CRU CL v. 2.1 climatological datasets from 1961-1990.

This set of files includes downscaled future projections of vapor pressure (units=hPa) at a 1km spatial scale. This data has been prepared as model input for the Integrated Ecosystem Model (IEM). There can be errors or serious limitations to the application of this data to other analyses. The data constitute the result of a downscaling procedure using 2 General Circulation Models (GCM) from the Coupled Model Intercomparison Project 5 (CMIP5) for RCP 8.5 scenario (2006-2100) monthly time series and Climatic Research Unit (CRU) TS2.0 (1961-1990,10 min spatial resolution) global climatology data. Please note that this data is used to fill in a gap in available data for the Integrated Ecosystem Model (IEM) and does not constitute a complete or precise measurement of this variable in all locations. RCPs: 8.5 Centers, Model Names, Versions, and Acronyms: National Center for Atmospheric Research,Community Earth System Model 4,NCAR-CCSM4 Meteorological Research Institute,Coupled General Circulation Model v3.0,MRI-CGCM3 Methods of creating downscaled relative humidity data: 1. The GCM input data are distributed as relative humidity along with the CRU CL 2.0, therefore no conversion procedure was necessary before beginning the downscaling procedure. 2. Proportional Anomalies generated using the 20c3m Historical relative humidity data 1961-1990 climatology and the projected relative humidity data (2006-2100). 3. These proportional anomalies are interpolated using a spline interpolation to a 10min resolution grid for downscaling with the CRU CL 2.0 Relative Humidity Data. 4. The GCM proportional anomalies are multiplied by month to the baseline CRU CL 2.0 10min relative humidity climatology for the period 1961-1990. Creating a downscaled relative humidity projected time series 2006-2100. 5. Due to the conversion procedure and the low quality of the input data to begin with, there were values that fell well outside of the range of acceptable relative humidity (meaning that there were values >100 percent), these values were re-set to a relative humidity of 95 at the suggestion of the researchers involved in the project. It is well known that the CRU data is spotty for Alaska and the Circumpolar North, due to a lack of weather stations and poor temporal coverage for those stations that exist. 6. The desired output resolution for the AIEM modeling project is 1km, so the newly created downscaled time series is resampled to this resolution using a standard bilinear interpolation resampling procedure. 7. The final step was to convert the downscaled relative humidity data to vapor pressure using the calculation below, which uses a downscaled temperature data set created utilizing the same downscaling procedure. EQUATION: saturated vapor pressure = 6.112 x exp(17.62 x temperature/(243.12+temperature)) vapor pressure = (relative humidity x saturated vapor pressure)/100

This dataset consists of observed and modeled wind data at an hourly temporal resolution for 67 communities in Alaska. Hourly ASOS/AWOS wind data (speed and direction) available via the Iowa Environmental Mesonet AK ASOS network were accessed and assessed for completeness, and 67 of those stations were determined to be sufficiently complete for climatological analysis. Those data were cleaned to produce regular hourly data, and adjusted via a combination of changepoint analysis and quantile mapping to correct for potential changes in sensor location and height. Historical (ERA-Interim reanalysis) and projected (GFDL-CM3 and NCAR-CCSM4) outputs from a dynamical downscaling effort were extracted at pixels intersecting the chosen communities and were bias-corrected using the cleaned station data. This bias-corrected historical and projected data along with cleaned station data make up the entirety of this dataset as a collection of CSV files, for each combination of community and origin (station or model name).

This data set consists of PRSIM precipitation climatologies for Alaska in GeoTIFF format. The files in this data set are available from the PRISM Climate Group as text files but have been processed into GeoTIFFs. These are monthly climatologies with a resolution of 771m. Units are millimeters. There are multiple climatological periods currently available through PRISM, but only one is currently available through SNAP in this dataset: 1971-2000.

This set of files includes downscaled historical estimates of monthly total precipitation (in millimeters, no unit conversion necessary, rainwater equivalent) from 1901 - 2013 (CRU TS 3.22) at 10 min x 10 min spatial resolution with global coverage. The downscaling process utilizes CRU CL v. 2.1 climatological datasets from 1961-1990.

These files include climatological summaries of downscaled historical and projected decadal average monthly derived snow variables and summaries at 771 meter spatial resolution across Alaska. There are three types of files: 1). The historical and future snowfall water equivalent (SWE) in millimeters, produced by multiplying snow-day fraction by decadal average monthly precipitation and summing over 6 months from October to March to estimate the total SWE on April 1. 2). The historical and future ratio of SWE to total precipitation (SFEtoP) in percent. SFEtoP is calculated as (SWE / total precipitation) and also represents the six month October to March period. 3). The future difference in SWE with respect to the historical baseline (dSWE) in percent. dSWE is calculated as ((future SWE – historical SWE) / historical SWE) * 100. These data are also summary for the six month October to March period. The historical baseline period is 1970-1999, (file naming convention “H70.99”) and data are calculated from downscaled CRU TS 3.1 data. Projected variables exist for RCP 4.5 and RCP 8.5 emission scenarios and for 5 GCMs: NCAR-CCSM4, GFDL-CM3, GISS-E2-R, IPSL-CM5, and MRI-CGCM3. The 5-model mean (file naming convention "5MM") was also computed. Projections exist for three thirty-year climatologies: the 2020s (2010-2039), the 2050s (2040-2069), and the 2080s (2070-2099). The snow-day fraction data used can be found here: http://ckan.snap.uaf.edu/dataset/projected-decadal-averages-of-monthly-snow-day-fraction-771m-cmip5-ar5 http://ckan.snap.uaf.edu/dataset/historical-decadal-averages-of-monthly-snow-day-fraction-771m-cru-ts3-0-3-1 The precipitation data used can be found here: http://ckan.snap.uaf.edu/dataset/projected-monthly-and-derived-precipitation-products-771m-cmip5-ar5 http://ckan.snap.uaf.edu/dataset/historical-monthly-and-derived-precipitation-products-771m-cru-ts Note: In Littell et al. 2018, "SWE" is referred to as "SFE", and "SFEtoP" as "SFE:P"

These files include climatological summaries of downscaled historical and projected decadal average monthly snowfall (i.e. snow-water) equivalent (SWE) in millimeters, the ratio of snowfall equivalent to precipitation, and future change in snowfall for October-March at 771-meter spatial resolution across the state of Alaska. Data are for summary October to March Alaska climatologies for: 1) historical and future snowfall equivalent (SWE), produced by multiplying snow-day fraction by decadal average monthly precipitation and summing over 6 months from October to March to estimate the total SWE on April 1. 2) historical and future ratio of SWE to precipitation (SFEtoP), SFEtoP is the ratio of October to March total SWE to October to March total precipitation is calculated as total SWE / total precipitation (expressed as percent, 0-100). 3) future change in snowfall equivalent relative to historical ("dSWE"), calculated as (SWE future – SWE historical) / SWE historical (no units, multiply by 100 to obtain percent). The historical reference period is 1970-1999, (file name “H70.99”), calculated from downscaled CRU TS 3.1 data Future climatologies (both RCP 4.5 and 8.5) are for: - 2020s (2010-2039) - 2050s (2040-2069) - 2080s (2070-2099) across 5 GCMs: NCAR-CCSM4, GFDL-CM3, GISS-E2-R, IPSL-CM5, and MRI-CGCM3 as well as a 5-model mean (“5MM”). Following Elsner et al. (2010), <0.1 is rain dominated, 0.1 < SFE:P < 0.4 is transitional, and >0.4 is snow dominated. Only calculated for historical reference climatology 1970-1999 and three future climatologies: 2010-2039, 2040-2069, and 2070-2090, with each climatology representing the mean of three decadal averages from the available decadal grids. Snow fraction data used can be found here: http://ckan.snap.uaf.edu/dataset/projected-decadal-averages-of-monthly-snow-day-fraction-771m-cmip5-ar5 http://ckan.snap.uaf.edu/dataset/historical-decadal-averages-of-monthly-snow-day-fraction-771m-cru-ts3-0-3-1 Precipitation data used can be found here: http://ckan.snap.uaf.edu/dataset/projected-monthly-and-derived-precipitation-products-771m-cmip5-ar5 http://ckan.snap.uaf.edu/dataset/historical-monthly-and-derived-precipitation-products-771m-cru-ts * Note: In Littell et al. 2018, "SWE" is referred to as "SFE", and "SFEtoP" as "SFE:P"

These files include downscaled projections of decadal average monthly snowfall (water) equivalent (SWE) in millimeters for each month of the decades from 2010-2019 to 2090-2099 at 771 x 771 m spatial resolution. Each file represents a decadal average monthly mean. Output is available for the NCAR-CCSM4, GFDL-CM3, GISS-E2-R, IPSL-CM5A-LR, and MRI-CGCM3 models and three emissions scenarios (RCP 4.5, RCP 6.0 and RCP 8.5). SWE estimates were produced by multiplying snow-day fraction ("fs") by decadal average monthly precipitation ("Pr") such that SWE = (fs * Pr) / 100

These files include historical downscaled estimates of decadal average monthly snow-day fraction ("fs", units = percent probability from 1 – 100) for each month of the decades from 1900-1909 to 2000-2009 at 771 x 771 m spatial resolution. Each file represents a decadal average monthly mean. Version 1.0 was completed in 2015 using CMIP3. Version 2.0 was completed in 2018 using CMIP5. For more information on the methodology used to create this dataset, and guidelines for appropriate usage of the dataset, please see the data user's guide here: http://data.snap.uaf.edu/data/Base/AK_771m/historical/CRU_TS/snow_day_fraction/snow_fraction_data_users_guide.pdf

This file includes spatial representations of relative flammability produced through summarization of the ALFRESCO model outputs. These specific outputs are from the Integrated Ecosystem Model (IEM) project, and are from the linear coupled version using AR5/CMIP5 climate inputs (IEM Generation 2). This dataset has been updated to include flammability data summarized over additional time scales as well, done in the same manner as the intial dataset. These ALFRESCO outputs were summarized over three future eras (2010-2039, 2040-2069, 2070-2099) and a historical era (1950-2008), for two future emissions scenarios for five CMIP5 models