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"

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 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 set of files includes downscaled historical estimates of monthly total precipitation (in mm, no unit conversion necessary) from 1901 - 2005, at 15km x 15km spatial resolution. They include data for Alaska and Western Canada. Each set of files originates from one of five top ranked global circulation models from the CMIP5/AR5 models and RCPs, or is calculated as a 5 Model Average. These outputs are from the Historical runs of the GCMs. The downscaling process utilizes CRU CL v. 2.1 climatological datasets from 1961-1990 as the baseline for the Delta Downscaling method.

These annual fire history grids (0=no fire, 1=fire) were produced directly from the BLM Alaska Fire Service database and the Canadian National Fire Database. They are simply a 1x1km raster representation of their fire history polygon database that can be obtained from: http://fire.ak.blm.gov/predsvcs/maps.php http://cwfis.cfs.nrcan.gc.ca/datamart Note, fire history data is very unreliable before ~1950 in Alaska. Fires may have been recorded in a given year, but that does not mean all fires that occurred were successfully recorded. This data was assembled from every recorded fire that has been entered into Alaska and Canadian databases. This results in several years containing no fires at all.

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 2km x 2km 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 1961-1990. **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 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 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.