Notice: Due to funding limitations, this data set was recently changed to a “Basic” Level of Service. Learn more about what this means for users and how you can share your story here: Level of Service Update for Data Products.This data set contains snow pack properties, such as depth and snow water equivalent (SWE), from the NOAA National Weather Service's National Operational Hydrologic Remote Sensing Center (NOHRSC) SNOw Data Assimilation System (SNODAS). SNODAS is a modeling and data assimilation system developed by NOHRSC to provide the best possible estimates of snow cover and associated parameters to support hydrologic modeling and analysis.

The Snowstorm Database is a collection of over 500 snowstorms dating back to 1900 and updated operationally. Only storms having large areas of heavy snowfall (10-20 inches or greater) are included. The spatial extent includes the contiguous U.S. but the most storms are in the eastern two thirds of the U.S. This is the only comprehensive data set with starting and ending dates along with daily and total storm snowfall for large snowstorms from 1900 to the present. The data is archived in shapefile format, one shapefile per storm. Shapefiles are a non-proprietary spatial format widely used in Geographical Information Systems (GIS). Each shapefile contains daily and storm total snowfall for weather stations that were affected by the snowstorm. The snowfall data comes from the Global Historical Climatological Network - Daily (GHCN-D).

This data set contains snow observations (snow depth, snowfall, and snow water equivalent) from several networks (CA-Hydro, CoCoRaHS, US Bureau of Reclamation, Idaho Transportation Department, SNOTEL, CNRA, DRI, UUNET, BCHYDRO, RAWS and several avalanche centers) with over 6000 locations throughout the United States and Canada. The temporal resolution varies from 6 hourly to daily depending on the station. These data were quality controlled and provided by NOAA MADIS.

Weather, snow, stream, topographic, and vegetation data are presented from the South Mountain Experimental Catchments from water years 2007-2013 (10-1-2007 to 9-30-2013). The data provide detailed information on the weather and hydrologic response for four highly instrumented catchments in the late stages of woodland encroachment. Hourly data from six meteorologic stations and four weirs have been carefully processed and quality checked, are serially complete, and ideal for hydrologic, ecosystem, and biogeochemical modeling. Topographic and vegetation data, as well as stream and drainage area delineations are Lidar-derived. This study site was established in 2007 as a collaborative, long-term research laboratory to address the impacts of western juniper (Juniperus occidentalis Hook) encroachment and treatments in the interior Great Basin region of the western USA. For more information about this dataset, contact: Patrick R. Kormos: patrick.kormos@ars.usda.gov Danny G. Marks: ars.danny@gmail.com

This data set provides daily 4 km snow water equivalent (SWE) and snow depth over the conterminous United States. It was developed at the University of Arizona (UA) under the support of the NASA MAP and SMAP Programs. The data were created by assimilating in-situ snow measurements from the National Resources Conservation Service's SNOTEL network and the National Weather Service's COOP network with modeled, gridded temperature and precipitation data from PRISM.

This map displays the expected total accumulation of new snow over the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.The dataset includes incremental and cumulative snowfall data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the amount by time (incremental) or accumulation by time (cumulative) layers to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces gridded forecasts of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.snow.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

This resource contains snow metrics for a future climate scenario and represents a subset of the SnowClim Dataset (https://www.hydroshare.org/resource/acc4f39ad6924a78811750043d59e5d0/). The SnowClim Dataset was developed following the methods presented in Lute et al., (in prep). The future snow data was created by first downscaling 4 km climate forcings from the Weather Research and Forecasting (WRF) model (Rasmussen and Liu, 2017) over a thirteen year period representing conditions under RCP 8.5 during 2071-2100 and then using this climate data to force the SnowClim snow model. Snow model outputs were summarized into snow metrics at ~210 m spatial resolution for the western US.

Additional details about forcing data preparation, model physics, model calibration, and application to the western US domain can be found in: Lute, A. C., Abatzoglou, J., and Link, T.: SnowClim v1.0: high-resolution snow model and data for the western United States, Geosci. Model Dev., 15, 5045–5071, https://doi.org/10.5194/gmd-15-5045-2022, 2022.

The National Forest Climate Change Maps project was developed by the Rocky Mountain Research Station (RMRS) and the Office of Sustainability and Climate to meet the needs of national forest managers for information on projected climate changes at a scale relevant to decision making processes, including forest plans. The maps use state-of-the-art science and are available for every national forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation, air temperature, snow (including snow residence time and April 1 snow water equivalent), and stream flow.

Snow residence time (in days) and April 1 snow water equivalent (in mm) were modeled using the spatial analog models of Luce et al., 2014 (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2013WR014844); see also Lute and Luce, 2017 (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017WR020752). These models are built on precipitation and snow data from Snowpack Telemetry (SNOTEL) stations across the western United States and temperature data from the TopoWx dataset (https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.4127).

Raster data are also available for download from RMRS site (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/categories/us-raster-layers.html), along with pdf maps and detailed metadata (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/downloads/NationalForestClimateChangeMapsMetadata.pdf).This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

The Tibetan Plateau has an average altitude of over 4000 m and is the region with the highest altitude and the largest snow cover in the middle and low latitudes of the Northern Hemisphere regions. Snow cover is the most important underlying surface of the seasonal changes on the Tibetan Plateau and an important composing element of ecological environment. Ice and snow melt water is an important water resource of the plateau and its downstream areas. At the same time, plateau snow, as an important land-surface forcing factor, is closely related to disastrous weather (such as droughts and floods) in East Asia, the South Asian monsoon and in the middle and lower reaches of the Yangtze River. It is an important indicator of short-term climate prediction and one of the most sensitive responses to global climate change. The snow depth refers to the vertical depth from the surface of the snow to the ground. It is an important parameter for snow characteristics and one of the conventional meteorological observation elements. It is the key parameter of snow water equivalent estimation, climate effect studies of snow cover, the basin water balance, the simulation and monitoring of snow-melt, and snow disaster evaluation and grading. In this data set, the Tibetan Plateau boundary was determined by adopting the natural topography as the leading factor and by comprehensive consideration of the principles of altitude, plateau and mountain integrity. The main part of the plateau is in the Tibetan Autonomous Region and Qinghai Province, with an area of 2.572 million square kilometers, accounting for 26.8% of the total land area of China. The snow depth observation data are the monthly maximum snow depth data after quality detection and quality control. There are 102 meteorological stations in the study area, most of which were built during the 1950s to 1970s. The data for some months or years for sites existing during this period were missing, and the complete observational records from 1961 to 2013 were adopted. The temporal resolution is daily, the spatial coverage is the Tibetan Plateau, and all the data were quality controlled. Accurate and detailed plateau snow depth data are of great significance for the diagnosis of climate change, the evolution of the Asian monsoon and the management of regional snow-melt water resources.

This data set consists of snow observations for 18 stations in the western Italian Alps. Two types of data are included: monthly snowfall amounts and monthly snow cover duration in days. The period of record varies with each station, with the longest station record including data from 1877 to 1996. The average station record duration is approximately 61 years. Available stations range from 565 meters to 2720 meters in elevation. The data are summaries of snow stake measurements. Daily observations of total snow depth were generally made at 8 a.m. local time. Data were aquired using a snow measuring rod. Snowfall amount was defined as being any increase over the previous day's reading. This measurement may be an underestimate of as much as 10-20% due to snow pack settlement. However, this underestimation is fairly consistent for all measurements. The daily data were then totaled to yield the monthly values.

This data set consists of modeled snow water equivalent (SWE) data for 10 mountain ranges in North America, simulated by the Weather Research and Forecasting (WRF) regional climate model.

Maps of snow depth on a 0.1x0.1 degree grid derived from SYNOP data, provided by WMO RA VI Regional Climate Centre (RCC) an Climate Monitoring

Auxiliary files, code, and data for paper published in The Cryosphere:

Observed snow depth trends in the European Alps 1971 to 2019

https://doi.org/10.5194/tc-15-1343-2021

Auxiliary files:

• aux_paper.zip: Auxiliary figures to the paper (time series showing the consistency of averaging monthly mean snow depth of stations within 500 m elevation bins; times of seasonal snow depth and snow cover duration indices).
• aux_paper_crocus_comparison.zip: Time series comparing spatial statistical gap filling from paper to gap filling using snow depth assimilation into Crocus snow model (only for subset of stations in the French Alps)
• aux_paper_monthly_time_series.zip: Plots of monthly time series of snow depth, for each station.
• aux_paper_spatial_consistency.zip: Aggregate results from spatial consistency (statistical simulation using neighboring stations), and time series of observed versus simulated monthly snow depths.

Code (working copy, not cleaned, all written in R statistical software): code.zip

• to read in the different data sources
• to do quality checks and data processing
• to perform statistical analyses as in paper
• to produce figures and tables as in paper

Data:

• Daily and monthly stations snow depth and depth of snowfall, as .zips, grouped by data provider.
• Information on column content is provided in separate files "data_[daily|monthly]_00_column_names_content.txt".
• > 2000 stations from Austria, Germany, France, Italy, Switzerland, and Slovenia
• Meta data (name, latitude, longitude, elevation) in "meta_all.csv", along with an interactive map "meta_interactive_map.html", and column information in "meta_00_column_names_content.txt".
• If you use the data you agree to adhere to the respective data provider's terms as listed in "00_DATA_LICENSE_AND_TERMS.PDF"
• The license terms especially (and additionally to any other terms of the single data providers) include: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. [from CC BY 4.0]

Version history:

v1.2: uploaded data

v1.1: changes to aux-paper.zip and code.zip as consequence from submitting a revised manuscript

v1.0: initial upload

This data contains location information for 1 of Ontario’s snow monitoring networks: * Surface Water Monitoring Centre (SWMC) Snow course data is collected by: * conservation authorities * Ontario Power Generation * Ministry of Natural Resources (MNR) districts Data is collected twice a month from November 15 until May 15. The Surface Water Monitoring Centre uses this data to assess: * current snow cover * frozen ground conditions * snowpack * potential snowmelt * contributions to streamflow The snow data is located in a corporate water and climate database. This data helps MNR and conservation authorities assess the potential for flood at the local and provincial scale.

This data set consists of a Northern Hemisphere subset of the Canadian Meteorological Centre (CMC) operational global daily snow depth analysis. Data include daily analyzed snow depths, as well as monthly means and climatologies of snow depth and estimated snow water equivalent (SWE).

This NOAA Climate Data Record (CDR) is a record for the Northern Hemisphere (NH) Snow Cover Extent (SCE) spanning from October 4, 1966 to present, updated monthly after the 10th of each month. Data prior to June 1999 in the NH SCE CDR are based on satellite-derived maps of NH SCE produced weekly by trained NOAA meteorologists. In June 1999 weekly NOAA NH SCE maps ceased production, and were replaced by daily SCE output from the Interactive Multisensor Snow and Ice Mapping System (IMS). The weekly SCE maps are digitized to an 88x88 (cells) Cartesian grid laid over a NH polar stereographic projection. Each grid cell in the NH SCE CDR has a binary value, indicating snow covered or snow free. The NH SCE CDR has been used in international assessments of climate variability and change, and in investigations regarding the role of snow cover in the climate system. Mapping accuracy is such that this product is considered suitable for continental-scale climate studies. The data are updated monthly in netCDF file format with variables including SCE and National Meteorological Center (NMC) grid (88x88 cell) coordinates.

This data set consists of snow cover observations collected at the Rosemount, MN site operated by Dr. John Baker of the USDA/ARS. See the README file for more complete information.

Notice: If you are having difficulties subsetting SNODAS data via Polaris, please contact nsidc@nsidc.org.

Observational reports of daily snow fall (1200 UTC to 1200 UTC) are made by members of the NWS Automated Surface Observing Systems (ASOS) network and NWS Cooperative Observer Network (COOP). Reports from approximately 2,000 stations across the US including Alaska and Hawaii are sent on a daily basis to the Climate Prediction Center (CPC).CPC processes these reports once per day. All reports for the same day are put into an ASCII text file whose name includes the date of observation. These data are used by CPC in its role of supporting the Joint Agricultural Weather Facility (JAWF).

The National Forest Climate Change Maps project was developed by the Rocky Mountain Research Station (RMRS) and the Office of Sustainability and Climate to meet the needs of national forest managers for information on projected climate changes at a scale relevant to decision making processes, including forest plans. The maps use state-of-the-art science and are available for every national forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation, air temperature, snow (including snow residence time and April 1 snow water equivalent), and stream flow.Snow residence time (in days) and April 1 snow water equivalent (in mm) were modeled using the spatial analog models of Luce et al., 2014 (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2013WR014844); see also Lute and Luce, 2017 (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017WR020752). These models are built on precipitation and snow data from Snowpack Telemetry (SNOTEL) stations across the western United States and temperature data from the TopoWx dataset (https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.4127). They were calculated for the historical (1975-2005) and future (2071-2090) time periods, along with absolute and percent change.Raster data are also available for download from RMRS site (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/categories/us-raster-layers.html), along with pdf maps and detailed metadata (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/downloads/NationalForestClimateChangeMapsMetadata.pdf).