Multi-physics ensemble snow modelling in the western Himalaya

Pritchard, David M. W.; Forsythe, Nathan; O'Donnell, Greg; Fowler, Hayley J.; Rutter, Nick

doi:https://doi.org/10.5194/tc-14-1225-2020

Articles | Volume 14, issue 4

https://doi.org/10.5194/tc-14-1225-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-14-1225-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 4

Research article

|

14 Apr 2020

Research article |

| 14 Apr 2020

Multi-physics ensemble snow modelling in the western Himalaya

David M. W. Pritchard, Nathan Forsythe, Greg O'Donnell, Hayley J. Fowler, and Nick Rutter

Supplement

https://doi.org/10.5194/tc-14-1225-2020-supplement

Data sets

The High Asia Refined analysis (HAR) KLIMATOLOGIE TU-Berlin http://www.klima-ds.tu-berlin.de/har/

MODIS MCD43A3 Version 6 Albedo Model dataset USGS https://lpdaac.usgs.gov/products/mcd43a3v006/

MOD11A1 Version 6 product USGS https://lpdaac.usgs.gov/products/mod11a1v006/

MODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid, Version 6 NSIDC https://nsidc.org/data/mod10a1

Climate data from the Concordia site EvK2CNR http://share.evk2cnr.org/

Model code and software

FSM model code R. Essery https://github.com/RichardEssery/FSM

Extended FSM version R. Essery https://github.com/RichardEssery/FSM2

Short summary

This study compares different snowpack model configurations applied in the western Himalaya. The results show how even sparse local observations can help to delineate climate input errors from model structure errors, which provides insights into model performance variation. The results also show how interactions between processes affect sensitivities to climate variability in different model configurations, with implications for model selection in climate change projections.