This set of files includes downscaled historical estimates of decadal means of annual day of freeze or thaw (ordinal day of the year), and length of growing season (numbers of days, 0-365) for each decade from 1910 - 2006 (CRU TS 3.0) or 2009 (CRU TS 3.1) at at 771 x 771 meter spatial resolution. Each file represents a decadal mean of an annual mean calculated from mean monthly data.

This set of files includes downscaled projections of monthly totals, and derived annual, seasonal, and decadal means of monthly total precipitation (in millimeters, no unit conversion necessary) from Jan 2006 - Dec 2100 at 771x771 meter spatial resolution. Each set of files originates from one of five top ranked global circulation models from the CMIP5/AR5 models and RPCs, or is calculated as a 5 Model Average. The downscaling process utilizes PRISM climatological datasets from 1971-2000. Brief descriptions of the datasets: Monthly precipitation totals: The total precipitation, in mm, for the month. For Decadal outputs: 1. Decadal Average Total Monthly Precipitation: 10 year average of total monthly precipitation. Example: All January precipitation files for a decade are added together and divided by ten. 2. Decadal Average Seasonal Precipitation Totals: 10 year average of seasonal precipitation totals. Example: MAM seasonal totals for every year in a decade are added together and divided by ten. 3. Decadal Average Annual Precipitation Totals: 10 year average of annual cumulative precipitation. For seasonal means, the four seasons are referred to by the first letter of 3 months making up that season: * `JJA`: summer (June, July, August) * `SON`: fall (September, October, November) * `DJF`: winter (December, January, February) * `MAM`: spring (March, April, May) Please note that these maps represent climatic estimates only. While we have based our work on scientifically accepted data and methods, uncertainty is always present. Uncertainty in model outputs tends to increase for more distant climatic estimates from present day for both historical summaries and future projections.

This dataset contains climate "indicators" (also referred to as climate indices or metrics) computed over one historical period (1980-2009) using the NCAR Daymet dataset, and two future periods (2040-2069, 2070-2099) using two statistically downscaled global climate model projections, each run under two plausible greenhouse gas futures (RCP 4.5 and 8.5). The indicators within this dataset include: hd: “Hot day” threshold -- the highest observed daily maximum 2 m air temperature such that there are 5 other observations equal to or greater than this value. cd: “Cold day” threshold -- the lowest observed daily minimum 2 m air temperature such that there are 5 other observations equal to or less than this value. rx1day: Maximum 1-day precipitation su: "Summer Days" –- Annual number of days with maximum 2 m air temperature above 25 C dw: "Deep Winter days" –- Annual number of days with minimum 2 m air temperature below -30 C wsdi: Warm Spell Duration Index -- Annual count of occurrences of at least 5 consecutive days with daily mean 2 m air temperature above 90th percentile of historical values for the date cdsi: Cold Spell Duration Index -- Same as WDSI, but for daily mean 2 m air temperature below 10th percentile rx5day: Maximum 5-day precipitation r10mm: Number of days with precipitation > 10 mm cwd: Consecutive wet days –- number of the most consecutive days with precipitation > 1 mm cdd: Consecutive dry days –- number of the most consecutive days with precipitation < 1 mm

This dataset includes downscaled historical estimates of monthly average, minimum, and maximum precipitation and derived annual, seasonal, and decadal means of monthly total precipitation (in millimeters, no unit conversion necessary) from 1901 to 2006 (CRU TS 3.0), 2009 (CRU TS 3.1), 2015 (CRU TS 4.0), 2020 (CRU TS 4.05), or 2023 (CRU TS 4.08) at 2km x 2km spatial resolution. CRU TS 4.0 is only available as monthly averages, minimum, and maximum files. CRU TS 4.05 and 4.08 data are only available as monthly averages. The downscaling process utilizes PRISM climatological datasets from 1961-1990.

This dataset includes 42,120 GeoTIFFs (spatial resolution: 12 km) that represent decadal (15 decades between 1950-2099) means of monthly summaries of the following variables (units, abbreviations and case match those used in the source daily resolution dataset). There are three distinct groups of variables: Meteorological, Water State, and Water Flux. Meteorological Variables - tmax (Maximum daily 2-m air temperature, °C) - tmin (Minimum daily 2-m air temperature, °C) - pcp (Daily precipitation, mm per day) Water State Variables - SWE (Snow water equivalent, mm) - IWE (Ice water equivalent, mm) - SM1 (Soil moisture layer 1: surface to 0.02 m depth, mm) - SM2 (Soil moisture layer 2: 0.02 m to 0.97 m depth, mm) - SM3 (Soil moisture layer 3: 0.97 m to 3.0 m depth, mm) Water Flux Variables - RUNOFF (Surface runoff, mm per day) - EVAP (Actual evapotranspiration, mm per day) - SNOW_MELT (Snow melt, mm per day) - GLACIER_MELT (Ice melt, mm per day) Monthly summary functions, or how the daily frequency source data are condensed into a single monthly value, are as follows: - Sum: pcp, SNOW_MELT, EVAP, GLACIER_MELT, RUNOFF - Mean: tmin, tmax, SM1, SM2, SM3 - Maximum: IWE, SWE The model-scenario combinations used to represent various plausible climate futures are: - ACCESS1-3, RCP 4.5 - ACCESS1-3, RCP 8.5 - CanESM2, RCP 4.5 - CanESM2, RCP 8.5 - CCSM4, RCP 4.5 - CCSM4, RCP 8.5 - CSIRO-Mk3-6-0, RCP 4.5 - CSIRO-Mk3-6-0, RCP 8.5 - GFDL-ESM2M, RCP 4.5 - GFDL-ESM2M, RCP 8.5 - HadGEM2-ES, RCP 4.5 - HadGEM2-ES, RCP 8.5 - inmcm4, RCP 4.5 - inmcm4, RCP 8.5 - MIROC5, RCP 4.5 - MIROC5, RCP 8.5 - MPI-ESM-MR, RCP 4.5 - MPI-ESM-MR, RCP 8.5 - MRI-CGCM3, RCP 4.5 - MRI-CGCM3, RCP 8.5 The .zip files that are available for download are organized by variable. One .zip file has all the models and scenarios and decades and months for that variable. Each GeoTIFF file has a naming convention like this: {climate variable}_{units}_{model}_{scenario}_{month abbreviation}_{summary function}_{decade start}-{decade end}_mean.tif Each GeoTIFF has a 12 km by 12 km pixel size, and is projected to EPSG:3338 (Alaska Albers).

This dataset includes quantile-mapped historical and projected model runs of AR5 daily mean mean temperature (tas, degrees C) for each day of every year from 1958 - 2100 at 2.5 x 2.5 degree spatial resolution across 3 CMIP5 models. They are 365 multi-band geotiff files, one file per year, each band representing one day of the year, with no leap years.

This dataset consists of 6000 GeoTIFFs produced by the Geophysical Institute Permafrost Lab (GIPL) Permafrost Model. Six distinct CMIP5 model-scenario combinations were used to force the GIPL model output. Each model-scenario combination includes annual (2021-2120) summaries of the following ten variables: - Mean Annual Ground Temperature (MAGT) at 0.5 m below the surface (°C) - MAGT at 1 m below the surface (°C) - MAGT at 2 m below the surface (°C) - MAGT at 3 m below the surface (°C) - MAGT at 4 m below the surface (°C) - MAGT at 5 m below the surface (°C) - Mean Annual Surface (i.e., 0.01 m depth) Temperature (°C) - Permafrost top (upper boundary of the permafrost, depth below the surface in m) - Permafrost base (lower boundary of the permafrost, depth below the surface in m) - Talik thickness (perennially unfrozen ground occurring in permafrost terrain, m) There are 1000 GeoTIFF files per model-scenario combination. The model-scenario combinations are: - GFDL-CM3, RCP 4.5 - GFDL-CM3, RCP 8.5 - NCAR-CCSM4, RCP 4.5 - NCAR-CCSM4, RCP 8.5 - A 5-Model (GFDL-CM3, NCAR-CCSM4, GISS-E2-R, IPSL-CM5A-LR, MRI-CGCM3) Average, RCP 8.5 - A 5-Model (GFDL-CM3, NCAR-CCSM4, GISS-E2-R, IPSL-CM5A-LR, MRI-CGCM3) Average, RCP 4.5 The file naming convention is `gipl_model_scenario_variable_year.tif` for example: `gipl_GFDL-CM3_rcp45_talikthickness_m_2090.tif` Each GeoTIFF uses the Alaska Albers (EPSG:3338) projection and has a spatial resolution of 1 km x 1 km. All rasters in this dataset have indentical extents, spatial references, and metadata objects. Once extracted, the entire dataset (all 6000 GeoTIFFs) requires 39 GB of disk space. Data are compressed into ten .zip files, one per variable. Each archive will contain all model-scenario combinations and all years for that variable. Each .zip file contains 600 GeoTIFFs. This research was funded by the Broad Agency Announcement Program and the U.S. Army Engineer Research and Development Center and Cold Regions Research and Engineering Laboratory (ERDC-CRREL) under Contract No. W913E521C0010. The GIPL2-MPI/GCM simulations were supported in part by the high-performance computing and data storage resources operated by the Research Computing Systems Group at the University of Alaska Fairbanks Geophysical Institute.

This dataset consists of single band GeoTIFFs containing total annual counts of wet days for each year from 1980-2100 for one downscaled reanalysis (ERA-Interim, 1980-2015) and two downscaled CMIP5 global climate models driven under the RCP 8.5 baseline emissions scenario (NCAR-CCSM4 and GFDL-CM3, 2006-2100), all derived from the same dynamical downscaling effort using the Weather Research and Forecasting (WRF) model (Version 3.5). A day is counted as a "wet day" if the total precipitation for that day is 1 mm or greater.

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 dataset includes downscaled historical estimates of monthly average, minimum, and maximum temperature and derived annual, seasonal, and decadal means of monthly average temperature (in degrees Celsius, no unit conversion necessary) from 1901 to 2006 (CRU TS 3.0), 2009 (CRU TS 3.1), 2015 (CRU TS 4.0), 2020 (CRU TS 4.05), or 2023 (CRU TS 4.08) at 2km x 2km spatial resolution. CRU TS 4.0 is only available as monthly averages, minimum, and maximum files. CRU TS 4.05 and 4.08 are only available as monthly averages. The downscaling process utilizes PRISM climatological datasets from 1961-1990.