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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. doi:10.16904/envidat.600.

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Data and Resources

Metadata

Field Values
DOI
(Publication pending:10.16904/envidat.600)
Publication State Reserved
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)    [Open Data]
Last Updated February 26, 2025, 10:34 AM (UTC+00:00)
Created January 8, 2019, 9:25 AM (UTC+00:00)

Custom Metadata

Custom Field Values
dora_link