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.

A landfast ice dataset along the Beaufort Sea continental shelf, spanning 1996-2023. Spatial resolution is 100 m. Each month of the ice season (October through July) is summarized over three 9-year periods (1996-2005, 2005-2014, 2014-2023) using the minimum, maximum, median, and mean distance of SLIE from the coastline. The minimum extent indicates the region that was always occupied by landfast ice during a particular calendar month. The median extent indicates where landfast occurred at least 50% of the time. The maximum extent represents regions that may only have been landfast ice on one occasion during the selected time period. The mean SLIE position for the each month and and time period is also included. The dataset is derived from three sources: seaward landfast ice images derived from synthetic aperture radar images from the RadarSAT and EnviSAT constellations (1996-2008), the Alaska Sea Ice Program (ASIP) ice charts (2008-2017, 2019-2022), and the G10013 SIGID-3 Arctic Ice Charts produced by the National Ice Center (NIC; 2017-2019, 2022-2023). Within each GeoTIFF file there are 8 different pixel values representing different characteristics: 0 - Ocean 1 - Maximum Landfast Ice Extent 2 - Median Landfast Ice Extent 3 - Minimum Landfast Ice Extent 4 - Mean Landfast Ice Edge 5 - Land 6 - Out of Domain 7 - Coast Vector Shadow The file naming convention is as follows: Beaufort_$month_$era_SLIE_MMM_summary.tif For example, the name Beaufort_05_2005-2014_SLIE_MMM_summary.tif indicates the file represents data for May 2005-2014.

This dataset consists of sea ice indicators for the Arctic based on daily sea ice concentrations derived from satellite passive microwave measurements. The four indicators available are day of break-up start, day of break-up end, day of freeze-up start, and day of freeze-up end. These “day of year” values indicate the ordinal day of the ice-year on which the event occurred. The ice-year is defined as September 1 through August of the following year. Locally defined indicators can serve as key links between pan-Arctic or global indicators such as sea-ice extent or volume and local uses of sea ice, with the potential to inform community-scale adaptation and response.

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"

A dataset of landfast ice extent along the Alaska coast of the Beaufort Sea and adjacent waters in Canada spanning the winters of 1996-2023. Landfast ice extent is defined as the area between the coast and the seaward landfast ice edge (SLIE), meaning that small areas of open water than can form at the coast springtime will not be represented. Spatial resolution is 100 m. Compilation of the dataset is described in detail by Mahoney et al (2024). In brief, it is derived from three sources: From 1996-2008, the dataset is derived from analysis of sequential synthetic aperture radar (SAR) images from the RadarSAT and EnviSAT constellations, as described by Mahoney et al (2014); From 2008-2023, the data represent an average landfast extent identified in ice charts from the U.S. National Weather Service Alaska Sea Ice Program (ASIP) and the U.S. National Ice Center (NIC). Within each GeoTIFF file there are 5 different pixel values representing different characteristics: 0 - Not Landfast Ice 32 - Coast Vector Shadow 64 - Out of Bounds 128 - Land 255 - Landfast ice The file naming convention is as follows: beaufort_$YYYYMMDD_$source_slie.tif For example, the name beaufort_20170302_asip_and_nic_average_slie.tif indicates the file represents data for March 2, 2017 and that the data is derived from an average of the ASIP and NIC data sources.

These wind speed and direction data are the underlying data displayed in the interactive webtool at http://snap.uaf.edu/tools/airport-winds. Original wind speed/direction observations were made by Automated Surface Observing System (ASOS) and the Automated Weather Observing System (AWOS) stations, and we accessed these data via the Iowa Environmental Mesonet (IEM). These observations were hourly in most cases, and we filtered data to routine measurements (nearest to clock hour) where measurements were more frequent than hourly to generate a true hourly dataset, save for periods of missing data. We used data from 166 weather stations located across Alaska, selected from a pool of 185 stations available in the IEM database for 1980-2019. For inclusion in the app and this dataset, a station must have a reasonably complete record, and must have begun measurements before June 6, 2010. We applied a spike-filtering algorithm to detect spurious spikes and dips, and a changepoint detection plus quantile mapping adjustment to statistically account for the possibility of sensors changing location, height, or surroundings such that the long term (month-scale) wind regimes were affected. **Methodology** --- All hourly ASOS/AWOS wind speed and direction data available via the Iowa Environmental Mesonet AK ASOS network were accessed and assessed for completeness (185 stations), and 166 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. **Attribute Description** --- ts: timestamp (YYYY-mm-dd HH:MM:SS) ws: wind speed (mph) wd: wind direction (degrees) Station identifiers used for locations is available at: https://www.faa.gov/air_traffic/weather/asos/?state=AK

This set of files includes downscaled projections 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 Jan 2006 - Dec 2100 at 2km x 2km spatial resolution across Alaska and parts of Canada. 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) 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. 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.

Mean temperature and precipitation values extracted at community locations across Alaska and Canada from downscaled raster datasets containing historical and projected estimates for these variables.

A landfast ice dataset along the Chukchi Sea continental shelf, spanning 1996-2023. Spatial resolution is 100 m. Each month of the ice season (October through July) is summarized over three 9-year periods (1996-2005, 2005-2014, 2014-2023) using the minimum, maximum, median, and mean distance of SLIE from the coastline. The minimum extent indicates the region that was always occupied by landfast ice during a particular calendar month. The median extent indicates where landfast occurred at least 50% of the time. The maximum extent represents regions that may only have been landfast ice on one occasion during the selected time period. The mean SLIE position for the each month and and time period is also included. The dataset is derived from three sources: seaward landfast ice images derived from synthetic aperture radar images from the RadarSAT and EnviSAT constellations (1996-2008), the Alaska Sea Ice Program (ASIP) ice charts (2008-2017, 2019-2022), and the G10013 SIGID-3 Arctic Ice Charts produced by the National Ice Center (NIC; 2017-2019, 2022-2023). Within each GeoTIFF file there are 8 different pixel values representing different characteristics: 0 - Ocean 1 - Maximum Landfast Ice Extent 2 - Median Landfast Ice Extent 3 - Minimum Landfast Ice Extent 4 - Mean Landfast Ice Edge 5 - Land 6 - Out of Domain 7 - Coast Vector Shadow The file naming convention is as follows: Chukchi_$month_$era_SLIE_MMM_summary.tif For example, the name Chukchi_05_2005-2014_SLIE_MMM_summary.tif indicates the file represents data for May 2005-2014.

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).