May 13, 2024

Evaluating and Improving Snow in the National Water Model, using Observations from the New York State Mesonet


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Version: 1.0

This dataset repository contains the dataset that supports the study of Minder et al. (2024): Evaluating and Improving Snow in the National Water Model, using Observations from the New York State Mesonet. The datasets in this archive include output from distributed simulations of the WRF Hydro model, output from point simulations with the Noah-MP land surface model, and manual and automated snow water equivalent (SWE) observations at New York State Mesonet (NYSM) station locations. The formatting and file naming conventions for each dataset are described in detail in the minder_etal_NWM_snow_dataset_ReadMe.pdf file.

DOI
https://doi.org/10.5065/s0d2-3z51
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4 Files, 10.74 GB Total Size

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Temporal Range
2017-01-01 to 2022-01-01
Temporal Resolution
1.0 hour
0.5 hour
Related Links
N/A
GCMD Science Keywords
  • Atmosphere > Precipitation > Solid Precipitation > Snow
  • Terrestrial Hydrosphere > Surface Water > Surface Water Processes/Measurements > Discharge/Flow
File Media Types
  • application/pdf
  • application/gzip
Support Contact
Arezoo RafieeiNasab
UCAR/NCAR - Research Applications Laboratory
arezoo@ucar.edu

Data Curator
GDEX Curator
UCAR/NCAR - GDEX
gdex@ucar.edu

Credit
This work was supported by NOAA grants NA19OAR4590203 and NA19OAR4590204.
Legal Constraints
Creative Commons Attribution 4.0 International License.
Access Constraints
None
Full Metadata
DIF XML
ISO19139 XML
OAI DC
JSON-LD
Version History
1.0

Latitude Range
40.604014° N to 44.89565° N
Longitude Range
79.62408° W to 72.465866° W
Authors
Arezoo RafieeiNasab
Theodore W. Letcher
Justin R. Minder
Patrick W. Naple
Junhong Wang
Publisher
UCAR/NCAR - GDEX

Suggested Citation
Arezoo RafieeiNasab, Theodore W. Letcher, Justin R. Minder, Patrick W. Naple, Junhong Wang. (2024). Evaluating and Improving Snow in the National Water Model, using Observations from the New York State Mesonet. Version 1.0. UCAR/NCAR - GDEX. https://doi.org/10.5065/s0d2-3z51. Accessed 22 Jul 2024.
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