Meteorological data used to develop and validate the bias-detecting ensemble (BDE)

These data were used to drive and evaluate Jules Investigation Model (JIM) snow simulations. The data provided are the forcing data used for the "deterministic" runs as described in Winstral et al., 2019. The bias-detecting ensemble (Winstral et al., 2019) used observed snow depths (HS) to detect biases in these deterministic simulations related to precipitation and energy inputs to JIM. Simulations that included the BDE evaluations substantially improved JIM simulations.

Funding Information:

This work was supported by:

Funding information not available.

Citation:

Winstral, Adam (2019). Meteorological data used to develop and validate the bias-detecting ensemble (BDE). EnviDat.

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Data and Resources

DEMTXT
1-km resolution DEM used for downscaling gridded NWP data to stations and for...
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READ_METXT
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Station forcing dataCSV
All forcing data need to run JIM at HS and SWE stations. These are data...
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HS and SWE observationsZIP
Automated (HS) and manual (SWE) data used to evaluate model simulations
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Metadata

Field	Values
DOI
Publication State
Authors	Email: adam.winstralfoo(at)slf.ch ORCID: 0000-0003-2556-8359 Given Name: Adam Family Name: Winstral Affiliation: WSL-SLF
Contact Person	Given Name: Adam Family Name: Winstral Email: adam.winstralfoo(at)slf.ch Affiliation: WSL-SLF ORCID: 0000-0003-2556-8359
Subtitles
Publication	Publisher: EnviDat Year: 2019
Dates	Type: Collected Date: 2013-10-01 End Date: 2017-06-30
Version	1.0
Type	dataset
General Type	Dataset
Language	English
Location	Switzerland
Content License	ODbL with Database Contents License (DbCL)
Last Updated	August 23, 2021, 14:23 (UTC)
Created	January 8, 2019, 09:25 (UTC)

Custom Metadata

Custom Field	Values
dora_link