https://catalog.snap.uaf.edu/geonetwork/srv/api/records
type: PagedCollection
type: PartialCollectionView
last page: https://catalog.snap.uaf.edu/geonetwork/srv/api/records
total items: 62
next page: https://catalog.snap.uaf.edu/geonetwork/srv/api/records
items per page: 10

SNAP GeoNetwork
type: Catalog
label: SNAP GeoNetwork (Scenarios Network for Alaska & Arctic Planning)
open search description: eng/portal.opensearch
uri lookup endpoint: eng/rdf.search?any=
publisher: Scenarios Network for Alaska & Arctic Planning
themes: Continents, countries, sea regions of the world.
language: eng
dataset: Scenarios Network for Alaska & Arctic Planning
dataset: Continents, countries, sea regions of the world.
dataset: WWW:LINK-1.0-http--link-
dataset: URL to web-accessible folder containing downloads for this data set.
dataset: Projected Monthly Temperature Products - 10 min CMIP5/AR5
dataset: Historical Derived DOF/DOT/LOGS - 2 km CRU TS
dataset: Historical and Projected Decadal Average Monthly Snowfall Equivalent and the Ratio of Snowfall Equivalent to Precipitation 771m CMIP5/AR5/CRU TS3.1
dataset: Elsner et al., 2010: Implications of 21st century climate change for the hydrology of Washington State
dataset: McAfee et al., 2014: Statistically downscaled projections of snow/rain partitioning for Alaska
dataset: Walsh et al., 2018: Downscaling of climate model output for Alaskan stakeholders
dataset: Littell et al., 2018: Alaska Snowpack Response to Climate Change: Statewide Snowfall Equivalent and Snowpack Water Scenarios
dataset: ScienceBase Catalog Record
dataset: Alaska VIC Hydrologic Model Output (1950-2099): Decadal Averages of Monthly Summaries
dataset: New projections of 21st century climate and hydrology for Alaska and Hawaii
dataset: Mizukami, N., A. J. Newman, A. W. Wood, E. D. Gutmann, and J. J. Hamman, 2022: 21st century hydrologic projections for Alaska and Hawaii. Boulder, CO: UCAR/NCAR/RAL.
dataset: Chukchi Sea Seaward Landfast Ice Edge (SLIE) Extent Summarized by Month and 9-year Periods
dataset: WWW:LINK-1.0-http--link-Mahoney AR, Bieniek P, Danielson S, Einhorn AH, Hedstrom KS, Jones JM, Klenz, T. (University of Alaska, Fairbanks, AK). 2024. Landfast ice climatology within the Arctic OCS. Anchorage (AK): U.S. Department of the Interior, Bureau of Ocean Energy Management. 121 p. Report No.: OCS Study BOEM 2024-034
dataset: WWW:LINK-1.0-http--link-Mahoney, A. R., H. Eicken, A. G. Gaylord, and R. Gens (2014), Landfast sea ice extent in the Chukchi and Beaufort Seas: The annual cycle and decadal variability, Cold Reg. Sci. Tech., 103(0), 41-56, doi:
dataset: Data download
dataset: Github Repository
dataset: Dataset DOI
dataset: Fresco et al., 2025: Modeling the loss of climate protection from spruce beetles (Dendroctonus rufipennis) under changing conditions in Alaska's forests
dataset: Scenarios Network for Alaska and Arctic Planning
dataset: https://catalog.snap.uaf.edu/geonetwork/srv/resources/persons/d721470e4086

Scenarios Network for Alaska & Arctic Planning
type: Organization

Continents, countries, sea regions of the world.
type: ConceptScheme
uri: https://catalog.snap.uaf.edu:/geonetwork/srv/eng/thesaurus.download

https://catalog.snap.uaf.edu:/geonetwork/records/8b51ce8c-7fd9-4541-9736-990c0a008005
type: CatalogRecord
conforms to: 32557.html
issued: 2023-09-06
modified: 2023-09-06

20 km annual wet day totals for Alaska, 1980-2100
type: Dataset
abstract: 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.
keyword: wet days
keyword: precipitation
theme: climatologyMeteorologyAtmosphere
spatial: Polygon
  as WKT: <http://www.opengis.net/def/crs/OGC/1.3/CRS84> Polygon((-202.40 49.20, -202.40 71.40, -117.40 71.40, -117.40 49.20, -202.40 49.20))
temporal: 1980-01-01 / 2100-12-31
publisher: Scenarios Network for Alaska and Arctic Planning
accrual periodicity: asNeeded
license: license
license: https://creativecommons.org/licenses/by/4.0/
distribution: WWW:LINK-1.0-http--link-

https://catalog.snap.uaf.edu:/geonetwork/records/ad5baccc-0111-4072-9052-0f92ecfeea6d
type: CatalogRecord
conforms to: 32557.html
issued: 2022-09-23
modified: 2022-09-23

Projected Monthly and Derived Temperature Products - 771m CMIP5/AR5
type: Dataset
abstract: This set of files includes downscaled projections of monthly means, and derived annual, seasonal, and decadal means of monthly mean temperatures (in degrees Celsius, no unit conversion necessary) from Jan 2006 - Dec 2100 at 771x771 meter spatial resolution. 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) The downscaling process utilizes PRISM climatological datasets from 1971-2000. 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.
keyword: climate
keyword: projected-modeled
keyword: decadal
keyword: seasonal
keyword: annual
keyword: temperature
keyword: monthly
keyword: AR5/CMIP5
theme: climatologyMeteorologyAtmosphere
spatial: Polygon
  as WKT: <http://www.opengis.net/def/crs/OGC/1.3/CRS84> Polygon((-180.00 53.00, -180.00 71.416, 180.00 71.416, 180.00 53.00, -180.00 53.00))
temporal: 2006-01-15 / 2100-12-15
issued: 2015-02-23T12:00:00
publisher: Scenarios Network for Alaska and Arctic Planning
accrual periodicity: asNeeded
license: license
license: https://creativecommons.org/licenses/by/4.0/
distribution: URL to web-accessible folder containing downloads for this data set.

https://catalog.snap.uaf.edu:/geonetwork/records/38154af5-c99a-42f9-a240-6ece4f8484a2
type: CatalogRecord
conforms to: 32557.html
issued: 2023-03-03
modified: 2023-03-03

Historical Monthly Temperature Products - 10 min CRU TS 3.22
type: Dataset
abstract: 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.
keyword: climate
keyword: temperature
keyword: monthly
keyword: historical-observed
keyword: NWT
theme: climatologyMeteorologyAtmosphere
spatial: Polygon
  as WKT: <http://www.opengis.net/def/crs/OGC/1.3/CRS84> Polygon((-180.00 -62.00, -180.00 83.6663, 180.00 83.6663, 180.00 -62.00, -180.00 -62.00))
temporal: 1901-01-15 / 2013-12-15
issued: 2015-09-17T12:00:00
publisher: Scenarios Network for Alaska and Arctic Planning
accrual periodicity: asNeeded
license: license
license: https://creativecommons.org/licenses/by/4.0/
distribution: WWW:LINK-1.0-http--link-

https://catalog.snap.uaf.edu:/geonetwork/records/815c6708-b6cf-4a46-b5c8-344851063117
type: CatalogRecord
conforms to: 32557.html
issued: 2025-07-23
modified: 2025-07-23

Projected Monthly Temperature Products - 10 min CMIP5/AR5
type: Dataset
abstract: This set of files includes downscaled projected estimates of monthly temperature (in degrees Celsius, no unit conversion necessary) from 2006-2300* 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. *Some datasets from the five models used in modeling work by SNAP only have data going out to 2100. This metadata record serves to describe all of these models outputs for the full length of future time available. The downscaling process utilizes CRU CL v. 2.1 climatological datasets from 1961-1990 as the baseline for the Delta Downscaling method.
keyword: temperature
keyword: projected
keyword: CMIP5
theme: climatologyMeteorologyAtmosphere
spatial: Polygon
  as WKT: <http://www.opengis.net/def/crs/OGC/1.3/CRS84> Polygon((-222.1694 40.1605, -222.1694 82.593, -71.7651 82.593, -71.7651 40.1605, -222.1694 40.1605))
temporal: 2006-01-01 / 2300-12-31
publisher: Scenarios Network for Alaska and Arctic Planning
accrual periodicity: asNeeded
license: license
license: https://creativecommons.org/licenses/by/4.0/
distribution: Projected Monthly Temperature Products - 10 min CMIP5/AR5

https://catalog.snap.uaf.edu:/geonetwork/records/5bdac624-203c-4a65-bfca-1c3f5bf738db
type: CatalogRecord
conforms to: 32557.html
issued: 2022-11-01
modified: 2022-11-01

Historical and Projected Hourly Wind Data for Alaskan Communities, 1980-2099
type: Dataset
abstract: 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).
keyword: wind
keyword: modeled
keyword: observed
keyword: CMIP5
keyword: WRF
keyword: projected
keyword: Alaska
theme: climatologyMeteorologyAtmosphere
spatial: Polygon
  as WKT: <http://www.opengis.net/def/crs/OGC/1.3/CRS84> Polygon((-185.88 51.87, -185.88 71.28, -131.5722 71.28, -131.5722 51.87, -185.88 51.87))
temporal: 1980-01-01 / 2099-12-31
publisher: Scenarios Network for Alaska and Arctic Planning
accrual periodicity: asNeeded
language: eng
license: license
distribution: WWW:LINK-1.0-http--link-

https://catalog.snap.uaf.edu:/geonetwork/records/ec1c0ddb-7af0-4815-9d62-71bba58f9a45
type: CatalogRecord
conforms to: 32557.html
issued: 2022-08-18
modified: 2022-08-18

Historical Derived DOF/DOT/LOGS - 2 km CRU TS
type: Dataset
abstract: 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 2x2 kilometer spatial resolution. Each file represents a decadal mean of an annual mean calculated from mean monthly data. **Day of freeze or thaw units are ordinal day 15-350 with the below special cases.** *Day of Freeze (DOF)* `0` = Primarily Frozen `365` = Rarely Freezes *Day of Thaw (DOT)* `0` = Rarely Freezes `365` = Primarily Frozen *Length of Growing Season (LOGS)* is simply the number of days between the DOT and DOF. ---- The spatial extent includes Alaska, the Yukon Territories, British Columbia, Alberta, Saskatchewan, and Manitoba. Each set of files originates from the Climatic Research Unit (CRU, http://www.cru.uea.ac.uk/) TS 3.0 or 3.1 dataset. TS 3.0 extends through December 2006 while 3.1 extends to December 2009. **Day of Freeze, Day of Thaw, Length of Growing Season calculations:** Estimated ordinal days of freeze and thaw are calculated by assuming a linear change in temperature between consecutive months. Mean monthly temperatures are used to represent daily temperature on the 15th day of each month. When consecutive monthly midpoints have opposite sign temperatures, the day of transition (freeze or thaw) is the day between them on which temperature crosses zero degrees C. The length of growing season refers to the number of days between the days of thaw and freeze. This amounts to connecting temperature values (y-axis) for each month (x-axis) by line segments and solving for the x-intercepts. Calculating a day of freeze or thaw is simple. However, transitions may occur several times in a year, or not at all. The choice of transition points to use as the thaw and freeze dates which best represent realistic bounds on a growing season is more complex. Rather than iteratively looping over months …
keyword: thaw
keyword: freeze
keyword: historical
keyword: growing season
theme: climatologyMeteorologyAtmosphere
spatial: Polygon
  as WKT: <http://www.opengis.net/def/crs/OGC/1.3/CRS84> Polygon((-204.9237 36.2218, -204.9237 72.9458, -82.0033 72.9458, -82.0033 36.2218, -204.9237 36.2218))
temporal: 1910-01-15 / 2009-12-15
publisher: Scenarios Network for Alaska and Arctic Planning
accrual periodicity: asNeeded
license: license
license: https://creativecommons.org/licenses/by/4.0/
distribution: Historical Derived DOF/DOT/LOGS - 2 km CRU TS

https://catalog.snap.uaf.edu:/geonetwork/records/d5ad3b51-3ea7-4f40-ac2e-b835dc95152c
type: CatalogRecord
conforms to: 32557.html
issued: 2025-07-23
modified: 2025-07-23

Historical and Projected Decadal Average Monthly Snowfall Equivalent and the Ratio of Snowfall Equivalent to Precipitation 771m CMIP5/AR5/CRU TS3.1
type: Dataset
abstract: 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"
keyword: precipitation
keyword: snow
keyword: snow water equivalent
keyword: projected
keyword: modeled
keyword: CMIP5
keyword: historical
theme: climatologyMeteorologyAtmosphere
spatial: Polygon
  as WKT: <http://www.opengis.net/def/crs/OGC/1.3/CRS84> Polygon((-178.20 51.20, -178.20 71.40, -130.00 71.40, -130.00 51.20, -178.20 51.20))
temporal: 1970-10-01 / 2099-03-31
issued: 2018-11-16
publisher: Scenarios Network for Alaska and Arctic Planning
accrual periodicity: asNeeded
license: license
distribution: Historical and Projected Decadal Average Monthly Snowfall Equivalent and the Ratio of Snowfall Equivalent to Precipitation 771m CMIP5/AR5/CRU TS3.1
distribution: Elsner et al., 2010: Implications of 21st century climate change for the hydrology of Washington State
distribution: McAfee et al., 2014: Statistically downscaled projections of snow/rain partitioning for Alaska
distribution: Walsh et al., 2018: Downscaling of climate model output for Alaskan stakeholders
distribution: Littell et al., 2018: Alaska Snowpack Response to Climate Change: Statewide Snowfall Equivalent and Snowpack Water Scenarios
distribution: ScienceBase Catalog Record

https://catalog.snap.uaf.edu:/geonetwork/records/2610188c-aa38-4f47-8987-b36ec72cdd0d
type: CatalogRecord
conforms to: 32557.html
issued: 2023-10-12
modified: 2023-10-12

Alaska VIC Hydrologic Model Output (1950-2099): Decadal Averages of Monthly Summaries
type: Dataset
abstract: 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}…
keyword: CMIP5
keyword: modeled
keyword: hydrology
keyword: projected
keyword: historical
theme: climatologyMeteorologyAtmosphere
spatial: Polygon
  as WKT: <http://www.opengis.net/def/crs/OGC/1.3/CRS84> Polygon((-178.20 51.20, -178.20 71.40, -130.00 71.40, -130.00 51.20, -178.20 51.20))
temporal: 1950-01-01 / 2099-12-31
publisher: Scenarios Network for Alaska and Arctic Planning
accrual periodicity: asNeeded
license: license
license: https://creativecommons.org/licenses/by/4.0/
distribution: Alaska VIC Hydrologic Model Output (1950-2099): Decadal Averages of Monthly Summaries
distribution: New projections of 21st century climate and hydrology for Alaska and Hawaii
distribution: Mizukami, N., A. J. Newman, A. W. Wood, E. D. Gutmann, and J. J. Hamman, 2022: 21st century hydrologic projections for Alaska and Hawaii. Boulder, CO: UCAR/NCAR/RAL.

https://catalog.snap.uaf.edu:/geonetwork/records/0084b2b8-64ab-48bd-aacd-9fca5c0ea1f6
type: CatalogRecord
conforms to: 32557.html
issued: 2025-08-21
modified: 2025-08-21

Chukchi Sea Landfast Sea Ice Extent Summarized by Month and 9-year Periods
type: Dataset
abstract: 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. These data were updated on August 21, 2025 to rectify the omission of some NIC chart data sources for the 2017-18 and 2018-19 seasons.
keyword: sea ice
keyword: observed
theme: climatologyMeteorologyAtmosphere
theme: oceans
spatial: Polygon
  as WKT: <http://www.opengis.net/def/crs/OGC/1.3/CRS84> Polygon((-172.4834 65.0409, -172.4834 71.7106, -160.5616 71.7106, -160.5616 65.0409, -172.4834 65.0409))
temporal: 1996-10-01 / 2023-07-31
publisher: Scenarios Network for Alaska and Arctic Planning
accrual periodicity: asNeeded
license: license
license: https://creativecommons.org/licenses/by/4.0/
distribution: Chukchi Sea Seaward Landfast Ice Edge (SLIE) Extent Summarized by Month and 9-year Periods
distribution: WWW:LINK-1.0-http--link-Mahoney AR, Bieniek P, Danielson S, Einhorn AH, Hedstrom KS, Jones JM, Klenz, T. (University of Alaska, Fairbanks, AK). 2024. Landfast ice climatology within the Arctic OCS. Anchorage (AK): U.S. Department of the Interior, Bureau of Ocean Energy Management. 121 p. Report No.: OCS Study BOEM 2024-034
distribution: WWW:LINK-1.0-http--link-Mahoney, A. R., H. Eicken, A. G. Gaylord, and R. Gens (2014), Landfast sea ice extent in the Chukchi and Beaufort Seas: The annual cycle and decadal variability, Cold Reg. Sci. Tech., 103(0), 41-56, doi:

https://catalog.snap.uaf.edu:/geonetwork/records/090daa3e-b1f1-4dc5-81f2-b7817bd011ee
type: CatalogRecord
conforms to: 32557.html
issued: 2025-11-03
modified: 2025-11-03

Historical and projected climatic protection from spruce beetle infestation in Alaska, 1988-2099
type: Dataset
abstract: This dataset is the product of a climate-driven model of beetle survival and reproduction in Alaska. We used that model to create this dataset of landscape-level “risk” of the climatic component of beetle infestation across the forested areas of Alaska. This risk component can best be applied as protection of the landscape offered by the climate and is categorized as high, medium, and low. It does not consider other major factors, such as existing beetle and predator populations or forest susceptibility. We computed these values over one historical period (1988-2017) using Daymet data, and three future periods (2010-2039, 2040-2069, 2070-2099) using four statistically downscaled global climate model projections, each run under two plausible greenhouse gas futures (RCP 4.5 and 8.5).
keyword: Spruce beetle
keyword: infestation
keyword: protection
theme: climatologyMeteorologyAtmosphere
spatial: Polygon
  as WKT: <http://www.opengis.net/def/crs/OGC/1.3/CRS84> Polygon((-178.20 51.20, -178.20 71.40, -130.00 71.40, -130.00 51.20, -178.20 51.20))
temporal: 1988-01-01 / 2099-12-31
publisher: Scenarios Network for Alaska and Arctic Planning
accrual periodicity: asNeeded
license: license
license: https://creativecommons.org/licenses/by/4.0/
distribution: Data download
distribution: WWW:LINK-1.0-http--link-Parent dataset
distribution: Github Repository
distribution: Dataset DOI
distribution: Fresco et al., 2025: Modeling the loss of climate protection from spruce beetles (Dendroctonus rufipennis) under changing conditions in Alaska's forests

WWW:LINK-1.0-http--link-
type: Distribution
access URL: http://data.snap.uaf.edu/data/Base/AK_WRF/Arctic_EDS_wet_days_per_year/
format: WWW:LINK-1.0-http--link
access URL: http://data.snap.uaf.edu/data/Base/World/CRU_TS/Historical_Monthly_Temperature_Products_10min_CRU_TS/
access URL: http://data.snap.uaf.edu/data/Base/AK_WRF/Historical_Projected_Hourly_Winds_1980_2099/

URL to web-accessible folder containing downloads for this data set.
type: Distribution
access URL: http://data.snap.uaf.edu/data/Base/AK_771m/projected/AR5_CMIP5_models/Projected_Monthly_and_Derived_Temperature_Products_771m_CMIP5_AR5/
format: WWW:LINK-1.0-http--link

Projected Monthly Temperature Products - 10 min CMIP5/AR5
type: Distribution
access URL: https://data.snap.uaf.edu/data/Base/AK_CAN_10min/projected/Projected_Monthly_and_Derived_Temperature_Products_10min_CMIP5_AR5/
format: WWW:LINK-1.0-http--link

Historical Derived DOF/DOT/LOGS - 2 km CRU TS
type: Distribution
access URL: http://data.snap.uaf.edu/data/Base/AK_CAN_2km/historical/CRU_TS/Historical_Derived_DOF_DOT_LOGS_2km_CRU_TS/
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Alaska VIC Hydrologic Model Output (1950-2099): Decadal Averages of Monthly Summaries
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Scenarios Network for Alaska and Arctic Planning
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Andy Mahoney
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Data download
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URL to web-accessible folder containing downloads for this data set.
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Data download
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URL to web-accessible folder containing downloads for this data set.
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Data download
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Github Repository
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WWW:LINK-1.0-http--link-
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URL to web-accessible folder containing downloads for this data set.
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Projected Monthly Temperature Products - 10 min CMIP5/AR5
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Historical Derived DOF/DOT/LOGS - 2 km CRU TS
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Historical and Projected Decadal Average Monthly Snowfall Equivalent and the Ratio of Snowfall Equivalent to Precipitation 771m CMIP5/AR5/CRU TS3.1
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ScienceBase Catalog Record
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Alaska VIC Hydrologic Model Output (1950-2099): Decadal Averages of Monthly Summaries
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New projections of 21st century climate and hydrology for Alaska and Hawaii
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Mizukami, N., A. J. Newman, A. W. Wood, E. D. Gutmann, and J. J. Hamman, 2022: 21st century hydrologic projections for Alaska and Hawaii. Boulder, CO: UCAR/NCAR/RAL.
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Data download
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Github Repository
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WWW:LINK-1.0-http--link-
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URL to web-accessible folder containing downloads for this data set.
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Historical and Projected Decadal Average Monthly Snowfall Equivalent and the Ratio of Snowfall Equivalent to Precipitation 771m CMIP5/AR5/CRU TS3.1
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ScienceBase Catalog Record
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Alaska VIC Hydrologic Model Output (1950-2099): Decadal Averages of Monthly Summaries
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New projections of 21st century climate and hydrology for Alaska and Hawaii
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Mizukami, N., A. J. Newman, A. W. Wood, E. D. Gutmann, and J. J. Hamman, 2022: 21st century hydrologic projections for Alaska and Hawaii. Boulder, CO: UCAR/NCAR/RAL.
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Data download
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Github Repository
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WWW:LINK-1.0-http--link-
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URL to web-accessible folder containing downloads for this data set.
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Projected Monthly Temperature Products - 10 min CMIP5/AR5
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Historical Derived DOF/DOT/LOGS - 2 km CRU TS
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Historical and Projected Decadal Average Monthly Snowfall Equivalent and the Ratio of Snowfall Equivalent to Precipitation 771m CMIP5/AR5/CRU TS3.1
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Walsh et al., 2018: Downscaling of climate model output for Alaskan stakeholders
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ScienceBase Catalog Record
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Alaska VIC Hydrologic Model Output (1950-2099): Decadal Averages of Monthly Summaries
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New projections of 21st century climate and hydrology for Alaska and Hawaii
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Mizukami, N., A. J. Newman, A. W. Wood, E. D. Gutmann, and J. J. Hamman, 2022: 21st century hydrologic projections for Alaska and Hawaii. Boulder, CO: UCAR/NCAR/RAL.
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Data download
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Github Repository
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WWW:LINK-1.0-http--link-
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URL to web-accessible folder containing downloads for this data set.
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Projected Monthly Temperature Products - 10 min CMIP5/AR5
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Historical Derived DOF/DOT/LOGS - 2 km CRU TS
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Historical and Projected Decadal Average Monthly Snowfall Equivalent and the Ratio of Snowfall Equivalent to Precipitation 771m CMIP5/AR5/CRU TS3.1
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ScienceBase Catalog Record
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Alaska VIC Hydrologic Model Output (1950-2099): Decadal Averages of Monthly Summaries
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New projections of 21st century climate and hydrology for Alaska and Hawaii
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Mizukami, N., A. J. Newman, A. W. Wood, E. D. Gutmann, and J. J. Hamman, 2022: 21st century hydrologic projections for Alaska and Hawaii. Boulder, CO: UCAR/NCAR/RAL.
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Chukchi Sea Seaward Landfast Ice Edge (SLIE) Extent Summarized by Month and 9-year Periods
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WWW:LINK-1.0-http--link-Mahoney AR, Bieniek P, Danielson S, Einhorn AH, Hedstrom KS, Jones JM, Klenz, T. (University of Alaska, Fairbanks, AK). 2024. Landfast ice climatology within the Arctic OCS. Anchorage (AK): U.S. Department of the Interior, Bureau of Ocean Energy Management. 121 p. Report No.: OCS Study BOEM 2024-034
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title: Mahoney AR, Bieniek P, Danielson S, Einhorn AH, Hedstrom KS, Jones JM, Klenz, T. (University of Alaska, Fairbanks, AK). 2024. Landfast ice climatology within the Arctic OCS. Anchorage (AK): U.S. Department of the Interior, Bureau of Ocean Energy Management. 121 p. Report No.: OCS Study BOEM 2024-034
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WWW:LINK-1.0-http--link-Mahoney, A. R., H. Eicken, A. G. Gaylord, and R. Gens (2014), Landfast sea ice extent in the Chukchi and Beaufort Seas: The annual cycle and decadal variability, Cold Reg. Sci. Tech., 103(0), 41-56, doi:
type: Distribution
access URL: http://dx.doi.org/10.1016/j.coldregions.2014.03.003
title: Mahoney, A. R., H. Eicken, A. G. Gaylord, and R. Gens (2014), Landfast sea ice extent in the Chukchi and Beaufort Seas: The annual cycle and decadal variability, Cold Reg. Sci. Tech., 103(0), 41-56, doi:
format: WWW:LINK-1.0-http--link

Data download
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access URL: http://data.snap.uaf.edu/data/Base/Other/Spruce_Beetle_Risk
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Github Repository
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access URL: https://github.com/ua-snap/spruce-beetle-risk
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Dataset DOI
type: Distribution
access URL: https://doi.org/10.21429/bmgz-xp71
format: DOI

Fresco et al., 2025: Modeling the loss of climate protection from spruce beetles (Dendroctonus rufipennis) under changing conditions in Alaska's forests
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access URL: https://doi.org/10.1016/j.ecolmodel.2025.111156
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WWW:LINK-1.0-http--link-
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access URL: http://data.snap.uaf.edu/data/Base/AK_WRF/Arctic_EDS_wet_days_per_year/
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access URL: http://data.snap.uaf.edu/data/Base/World/CRU_TS/Historical_Monthly_Temperature_Products_10min_CRU_TS/
access URL: http://data.snap.uaf.edu/data/Base/AK_WRF/Historical_Projected_Hourly_Winds_1980_2099/

URL to web-accessible folder containing downloads for this data set.
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access URL: http://data.snap.uaf.edu/data/Base/AK_771m/projected/AR5_CMIP5_models/Projected_Monthly_and_Derived_Temperature_Products_771m_CMIP5_AR5/
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Projected Monthly Temperature Products - 10 min CMIP5/AR5
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access URL: https://data.snap.uaf.edu/data/Base/AK_CAN_10min/projected/Projected_Monthly_and_Derived_Temperature_Products_10min_CMIP5_AR5/
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Historical Derived DOF/DOT/LOGS - 2 km CRU TS
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access URL: http://data.snap.uaf.edu/data/Base/AK_CAN_2km/historical/CRU_TS/Historical_Derived_DOF_DOT_LOGS_2km_CRU_TS/
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Historical and Projected Decadal Average Monthly Snowfall Equivalent and the Ratio of Snowfall Equivalent to Precipitation 771m CMIP5/AR5/CRU TS3.1
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access URL: https://data.snap.uaf.edu/data/Base/AK_771m/SWE_dSWE_SFEtoPR/
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Elsner et al., 2010: Implications of 21st century climate change for the hydrology of Washington State
type: Distribution
access URL: https://doi.org/10.1007/s10584-010-9855-0
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McAfee et al., 2014: Statistically downscaled projections of snow/rain partitioning for Alaska
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access URL: https://doi.org/10.1002/hyp.9934
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Walsh et al., 2018: Downscaling of climate model output for Alaskan stakeholders
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access URL: https://doi.org/10.1016/j.envsoft.2018.03.021
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Littell et al., 2018: Alaska Snowpack Response to Climate Change: Statewide Snowfall Equivalent and Snowpack Water Scenarios
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access URL: https://doi.org/10.3390/w10050668
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ScienceBase Catalog Record
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Alaska VIC Hydrologic Model Output (1950-2099): Decadal Averages of Monthly Summaries
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access URL: http://data.snap.uaf.edu/data/Base/AK_12km/vic_hydro/
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New projections of 21st century climate and hydrology for Alaska and Hawaii
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access URL: https://doi.org/10.1016/j.cliser.2022.100312
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Mizukami, N., A. J. Newman, A. W. Wood, E. D. Gutmann, and J. J. Hamman, 2022: 21st century hydrologic projections for Alaska and Hawaii. Boulder, CO: UCAR/NCAR/RAL.
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access URL: https://doi.org/10.5065/c3kn-2y77
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Chukchi Sea Seaward Landfast Ice Edge (SLIE) Extent Summarized by Month and 9-year Periods
type: Distribution
access URL: http://data.snap.uaf.edu/data/Base/Other/Landfast_Sea_Ice/Chukchi_MMM
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WWW:LINK-1.0-http--link-Mahoney AR, Bieniek P, Danielson S, Einhorn AH, Hedstrom KS, Jones JM, Klenz, T. (University of Alaska, Fairbanks, AK). 2024. Landfast ice climatology within the Arctic OCS. Anchorage (AK): U.S. Department of the Interior, Bureau of Ocean Energy Management. 121 p. Report No.: OCS Study BOEM 2024-034
type: Distribution
access URL: https://espis.boem.gov/Final%20Reports/BOEM_2024-034.pdf
title: Mahoney AR, Bieniek P, Danielson S, Einhorn AH, Hedstrom KS, Jones JM, Klenz, T. (University of Alaska, Fairbanks, AK). 2024. Landfast ice climatology within the Arctic OCS. Anchorage (AK): U.S. Department of the Interior, Bureau of Ocean Energy Management. 121 p. Report No.: OCS Study BOEM 2024-034
format: WWW:LINK-1.0-http--link

WWW:LINK-1.0-http--link-Mahoney, A. R., H. Eicken, A. G. Gaylord, and R. Gens (2014), Landfast sea ice extent in the Chukchi and Beaufort Seas: The annual cycle and decadal variability, Cold Reg. Sci. Tech., 103(0), 41-56, doi:
type: Distribution
access URL: http://dx.doi.org/10.1016/j.coldregions.2014.03.003
title: Mahoney, A. R., H. Eicken, A. G. Gaylord, and R. Gens (2014), Landfast sea ice extent in the Chukchi and Beaufort Seas: The annual cycle and decadal variability, Cold Reg. Sci. Tech., 103(0), 41-56, doi:
format: WWW:LINK-1.0-http--link

Data download
type: Distribution
access URL: http://data.snap.uaf.edu/data/Base/Other/Spruce_Beetle_Risk
format: WWW:LINK-1.0-http--link

Github Repository
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access URL: https://github.com/ua-snap/spruce-beetle-risk
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Dataset DOI
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access URL: https://doi.org/10.21429/bmgz-xp71
format: DOI

Fresco et al., 2025: Modeling the loss of climate protection from spruce beetles (Dendroctonus rufipennis) under changing conditions in Alaska's forests
type: Distribution
access URL: https://doi.org/10.1016/j.ecolmodel.2025.111156
format: WWW:LINK-1.0-http--link