Field
Value
Language
dc.contributor.author
Asong, Zilefac Elvis
datacite.creator.affiliationIdentifier
https://ror.org/010x8gc63
en_US
datacite.creator.affiliation
University of Saskatchewan
en_US
datacite.creator.nameIdentifier
https://orcid.org/0000-0001-7086-6764
en_US
dc.contributor.author
Wheater, Howard
datacite.creator.affiliationIdentifier
https://ror.org/010x8gc63
en_US
datacite.creator.affiliation
University of Saskatchewan
en_US
datacite.creator.nameIdentifier
en_US
dc.contributor.author
Pomeroy, John
datacite.creator.affiliationIdentifier
https://ror.org/010x8gc63
en_US
datacite.creator.affiliation
University of Saskatchewan
en_US
datacite.creator.nameIdentifier
en_US
dc.contributor.author
Pietroniro, Alain
datacite.creator.affiliationIdentifier
https://ror.org/026ny0e17
en_US
datacite.creator.affiliation
Environment and Climate Change Canada
en_US
datacite.creator.nameIdentifier
en_US
dc.contributor.author
Elshamy, Mohamed
datacite.creator.affiliationIdentifier
https://ror.org/010x8gc63
en_US
datacite.creator.affiliation
University of Saskatchewan
en_US
datacite.creator.nameIdentifier
https://orcid.org/0000-0002-3621-0021
en_US
dc.date.accessioned
2018-09-20T20:39:22Z
dc.date.available
2018-09-20T20:39:22Z
dc.date.issued
2018-09-20
dc.identifier.uri
https://www.frdr-dfdr.ca/repo/dataset/0eb7926c-6e9b-8a97-57d4-9b06c988d5d3
dc.identifier.uri
https://doi.org/10.20383/101.0111
dc.description
Cold regions hydrology is very sensitive to the impacts of climate warming. Future warming is expected to increase the proportion of winter precipitation falling as rainfall. Snowpacks are expected to undergo less sublimation, form later and melt earlier and possibly more slowly, leading to earlier spring peak streamflow. More physically realistic and sophisticated hydrological models driven by reliable climate forcing can provide the capability to assess hydrologic responses to climate change. However, hydrological processes in cold regions involve complex phase changes and so are very sensitive to small biases in the driving meteorology, particularly temperature and precipitation. Cold regions often have sparse surface observations, particularly at high elevations that generate the major amount of runoff. The effects of mountain topography and high latitudes are not well reflected in the observational record. The best available gridded data in these regions is from the high resolution forecasts of the Global Environmental Multiscale (GEM) atmospheric model and the Canadian Precipitation Analysis (CaPA) reanalysis but this dataset has a short historical record. The EU WATCH ERA-Interim reanalysis (WFDEI) has a longer historical record, but has often been found to be biased relative to observations over Canada. The aim of this study, therefore, is to blend the strengths of both datasets (GEM-CaPA and WFDEI) to produce a less-biased long record product (WFDEI-GEM-CaPA). First, a multivariate generalization of the quantile mapping technique was implemented to bias-correct WFDEI against GEM-CaPA at 3h x 0.125ᵒ resolution during the 2005-2016 period, followed by a hindcast of WFDEI-GEM-CaPA from 1979. **Please note: This dataset is linked to an ESSD paper at https://doi.org/10.5194/essd-12-629-2020. The authors kindly request that you reference this paper in addition to the dataset.
en_US
dc.publisher
Federated Research Data Repository / dépôt fédéré de données de recherche
dc.rights
Creative Commons Attribution 4.0 International (CC BY 4.0)
en_US
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
en_US
dc.subject
cold regions processes
en_US
dc.subject
observations
en_US
dc.subject
bias correction
en_US
dc.subject
North America
en_US
dc.title
A Bias-Corrected 3-hourly 0.125 Gridded Meteorological Forcing Data Set (1979 – 2016) for Land Surface Modeling in North America
en_US
globus.shared_endpoint.name
f163c1b3-9c88-42f6-a7bb-5839ed6c4063
globus.shared_endpoint.path
/6/published/publication_111/
frdr.preservation.status
AIP generation and transfer successful
frdr.preservation.datetime
2018-09-28 13:27:28
datacite.publicationyear
2018
datacite.date.Collected
1979-01-01/2016-12-31
datacite.resourcetype
Dataset
en_US
datacite.relatedidentifier.IsCitedBy
https://doi.org/10.5194/essd-12-629-2020
datacite.geolocation.geolocationBox
31.0625 -149.9375 71.9375 -50.0625
datacite.fundingReference.funderName
en_US
datacite.fundingReference.awardNumber
en_US
datacite.fundingReference.awardTitle
en_US
frdr.crdc.code
RDF1050112
frdr.crdc.group_en
Earth and related environmental sciences
en_US
frdr.crdc.class_en
Atmospheric sciences
en_US
frdr.crdc.field_en
Climate modelling
en_US
frdr.crdc.group_fr
Sciences de la Terre et sciences de l'environnement connexes
fr_CA
frdr.crdc.class_fr
Sciences de l'atmosphère
fr_CA
frdr.crdc.field_fr
Modélisation climatique
fr_CA
Appears in Collections: