SnowClim: Future Climate Data


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Resource type: Composite Resource
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Created: Jul 22, 2021 at 10:35 p.m.
Last updated: Jul 04, 2022 at 2:22 p.m.
DOI: 10.4211/hs.36895c3a2c53409893f5ba02ee142767
Citation: See how to cite this resource
Content types: Multidimensional Content  Geographic Raster Content 
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Abstract

This resource is part of the larger SnowClim Dataset (https://www.hydroshare.org/resource/acc4f39ad6924a78811750043d59e5d0/). This resource contains future climate metrics. Climate metrics were created by downscaling outputs of the Weather Research and Forecasting Model (WRF; Rasmussen and Liu, 2017) for thirteen year pseudo global warming scenario representing conditions for 2071-2100 under RCP8.5 using a combination of local lapse rates and terrain corrections for solar radiation as described in Lute et al., (in prep). Climate metrics are available on a ~210 m grid for the western United States in both netCDF and GeoTiff formats.

Additional information is available 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.

Subject Keywords

Resource Level Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Place/Area Name:
Contiguous Western United States
North Latitude
50.0007°
East Longitude
-101.9979°
South Latitude
28.9987°
West Longitude
-125.0007°

Temporal

Start Date:
End Date:

Content

README.txt

Readme file for: SnowClim: Future Climate Data
(https://www.hydroshare.org/resource/36895c3a2c53409893f5ba02ee142767/)


This .txt file was generated on 4 Nov 2021 by A.C. Lute.


Summary:
------------------------------------------------------------------------
This directory contains climate 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 climate data was created by
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.
Downscaled climate data was summarized into climate metrics at ~210 m
spatial resolution for the western US. Additional details about the
downscaling approach can be found in Lute et al., (in prep).


File Organization:
------------------------------------------------------------------------
Climate metrics are available in separate files. For accessibility,
metrics are available in both GeoTiff and netCDF format. The suffix
'_PGW' indicates that the data represents conditions under the future,
pseudo-global warming scenario. Metrics with values for each month have
values for January through December.


Metrics:
------------------------------------------------------------------------
- downwelling shortwave

	units: W m-2

	Monthly mean downwelling shortwave radiation at the surface, 
	downscaled from WRF (Rasmussen and Liu, 2017; which accounts for 
	cloud cover) using the R insolvent package to correct for aspect, 
	self-shading, and shading by adjacent terrain.

- minimum air temperature (tmin)

	units: °C

	Monthly mean of daily minimum 2m air temperatures, downscaled from 
	WRF (Rasmussen and Liu, 2017) using local lapse rates.

- maximum air temperature (tmax)

	units: °C

	Monthly mean of daily maximum 2m air temperatures, downscaled from 
	WRF (Rasmussen and Liu, 2017) using local lapse rates.

- mean air temperature (tmean)

	units: °C

	Monthly mean of daily mean 2m air temperatures, downscaled from WRF
	(Rasmussen and Liu, 2017) using local lapse rates.

- mean dew point temperature (tdmean)

	units: °C

	Monthly mean of daily mean 2m dewpoint temperatures, downscaled from 
	WRF (Rasmussen and Liu, 2017) using local lapse rates.

- precipitation (ppt)

	units: meters (m)

	Monthly total precipitation, downscaled from WRF (Rasmussen and Liu,
	2017) using local lapse rates and bias corrected using PRISM
	precipitation data (PRISM Climate Group, 2015).

- number of temperature sign changes (tschange)

	units: count

	Annual number of times that temperature (°C) changes sign. 
	Calculated from 4-hourly air temperatures downscaled from WRF 
	(Rasmussen and Liu, 2017) using local lapse rates.


Sharing and access information:
------------------------------------------------------------------------
1. Licenses/restrictions placed on the data: 
This resource is shared under the Creative Commons Attribution CC BY.

2. Links to publications that cite or use the data: 
none yet

3. Links to other publicly accessible locations of the data: 
none

4. Links/relationships to ancillary data sets: 
SnowClim Model and Dataset
(https://www.hydroshare.org/resource/acc4f39ad6924a78811750043d59e5d0/)
SnowClim Model Code
(https://www.hydroshare.org/resource/dc3a40e067bf416d82d87c664d2edcc7/)
SnowClim Pre-industrial Climate Data
(https://www.hydroshare.org/resource/0c852b12f668438fb9f0188a1cc6e8a9/)
SnowClim Pre-industrial Snow Data
(https://www.hydroshare.org/resource/fc621d75985c4695b6758ade312241c6/)
SnowClim Present Climate Data
(https://www.hydroshare.org/resource/7e3678f00ad74bfd881f91d6f6f81494/)
SnowClim Present Snow Data
(https://www.hydroshare.org/resource/2dbd6e849a754c0981b99ee7c09031eb/)
SnowClim Future Snow Data
(https://www.hydroshare.org/resource/96cba44cd74843639f855d7c9e22024b/)

5. Was data derived from another source? 
yes. Climate data was downscaled from the dataset of Rasmussen and Liu,
2017.

6. To cite this data, please reference both of the following: 
Lute, A., J. Abatzoglou, T. Link (2021). SnowClim Model and Dataset, 
	HydroShare, 
	http://www.hydroshare.org/resource/acc4f39ad6924a78811750043d59e5d0
Lute, A.C., John Abatzoglou, and Timothy Link (in prep), SnowClim:
	high-resolution snow model and 	data for the Western United States.
	In preparation for submission to Geoscientific Model Development.


Authors:
------------------------------------------------------------------------
A.C. Lute, University of Idaho 
John Abatzoglou, University of California, Merced 
Timothy Link, University of Idaho


Contact Information:
------------------------------------------------------------------------
Please contact A.C. Lute with questions, concerns, or comments. Current
contact information is available on the webpage this file was downloaded
from.


References:
------------------------------------------------------------------------
Lute, A.C., John Abatzoglou, and Timothy Link (in prep), SnowClim:
	high-resolution snow model and data for the Western United States. 
	In preparation for submission to Geoscientific Model Development. 
PRISM Climate Group, Oregon State University, 
	http://prism.oregonstate.edu, created 27 May 2015. 
Rasmussen, R., and C. Liu. 2017. High Resolution WRF Simulations of the 
	Current and Future Climate of North America. Research Data Archive at
	the National Center for Atmospheric Research, Computational and 
	Information Systems Laboratory. https://doi.org/10.5065/D6V40SXP. 
	Accessed 24 Sep 2018.

Data Services

The following web services are available for data contained in this resource. Geospatial Feature and Raster data are made available via Open Geospatial Consortium Web Services. The provided links can be copied and pasted into GIS software to access these data. Multidimensional NetCDF data are made available via a THREDDS Data Server using remote data access protocols such as OPeNDAP. Other data services may be made available in the future to support additional data types.

Related Resources

The content of this resource is derived from Rasmussen, R., and C. Liu. 2017. High Resolution WRF Simulations of the Current and Future Climate of North America. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://doi.org/10.5065/D6V40SXP. Accessed 24 Sep 2018.
This resource belongs to the following collections:
Title Owners Sharing Status My Permission
SnowClim Model and Dataset A. Lute  Published Open Access

Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydroinformatics Innovation Fellowship NSF Cooperative Agreement No. EAR-1849458
National Science Foundation Integrative Graduate Education and Research Traineeship (IGERT) Program 1249400

How to Cite

Lute, A., J. Abatzoglou, T. Link (2022). SnowClim: Future Climate Data, HydroShare, https://doi.org/10.4211/hs.36895c3a2c53409893f5ba02ee142767

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
CC-BY

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