The Guadalfeo Monitoring Network (Sierra Nevada, Spain): 14 years of measurements to understand the complexity of snow dynamics in semiarid regions

Polo, María J.; Herrero, Javier; Pimentel, Rafael; Pérez-Palazón, María J.

doi:https://doi.org/10.5194/essd-11-393-2019

Articles | Volume 11, issue 1

https://doi.org/10.5194/essd-11-393-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Hydrometeorological data from mountain and alpine research...

https://doi.org/10.5194/essd-11-393-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 11, issue 1

19 Mar 2019

| 19 Mar 2019

The Guadalfeo Monitoring Network (Sierra Nevada, Spain): 14 years of measurements to understand the complexity of snow dynamics in semiarid regions

María J. Polo, Javier Herrero, Rafael Pimentel, and María J. Pérez-Palazón

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Final revised paper (published on 19 Mar 2019)
Preprint (discussion started on 12 Nov 2018)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Reviewer 1', J. Ignacio López-Moreno, 27 Nov 2018
RC2: 'Review', Simon Gascoin, 25 Jan 2019
AC1: 'Authors Response to Reviewers', María José Polo, 22 Feb 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by María José Polo on behalf of the Authors (25 Feb 2019) Author's response Manuscript

ED: Publish subject to technical corrections (04 Mar 2019) by John Pomeroy

AR by María José Polo on behalf of the Authors (05 Mar 2019) Author's response Manuscript

Short summary

This work presents the Guadalfeo Monitoring Network in the Sierra Nevada (Spain), a snow monitoring network in the Guadalfeo Experimental Catchment, a semiarid area in southern Europe representative of snowpacks with highly variable dynamics on both annual and seasonal scales and significant topographic gradients. The network includes weather stations and time-lapse cameras to capture the variability of the ablation phases on different spatial scales.