Journal cover Journal topic
The Cryosphere An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/tcd-8-1973-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
23 Apr 2014
Review status
This discussion paper is a preprint. It has been under review for the journal The Cryosphere (TC). The revised manuscript was not accepted.
Simulating more accurate snow maps for Norway with MCMC parameter estimation method
T. M. Saloranta Section for glaciers, snow and ice, Hydrology department, Norwegian water resources and energy directorate (NVE), Postboks 5091 Majorstua, 0301 Oslo, Norway
Abstract. The seNorge snow model produces daily updated maps (1 km × 1 km resolution) of snow conditions for Norway which are used by the national flood, avalanche and landslide forecasting services, among others. The snow model uses gridded observations of daily temperature and precipitation as its input forcing. In this paper the revisions made to the new seNorge snow model code (v.1.1.1) are described, and a systematic model analysis is performed by first revealing the most influential key parameters by the Extended FAST sensitivity analysis and then estimating their probability distributions by the MCMC simulation method, using 565 observations of snow water equivalent (SWE) and snow density (ρ). The MCMC simulation resulted in rather narrow posterior distributions for the four estimated model parameters, and enhanced the model performance and snow map quality significantly, mainly by removing the known significant overestimation biases in SWE and ρ. In the new model version (v.1.1.1) the Nash–Sutcliffe (NS) model performance values are now well positive (NS = 0.61 for SWE and NS = 0.30 for ρ), in contrast to the much lower negative NS-values of the previous model (v.1.1). Moreover, the model evaluation against approximately 400 000 point measurements of snow depth shows improvement in the simulated percentage of "good match"-stations (76–84% before April, and still 65% at the end of April). Future research efforts should focus on decreasing the variability in the model fit with observations (i.e. model precision) by further improvements in the seNorge snow model and its important fundament, the gridded meteorological input data set used as its forcing.

Citation: Saloranta, T. M.: Simulating more accurate snow maps for Norway with MCMC parameter estimation method, The Cryosphere Discuss., https://doi.org/10.5194/tcd-8-1973-2014, 2014.
T. M. Saloranta
Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC C709: 'Review comments for Salorenta', Anonymous Referee #1, 23 May 2014 Printer-friendly Version 
 
RC C994: 'Review', Anonymous Referee #2, 25 Jun 2014 Printer-friendly Version 
 
AC C1069: 'Author's response to referees' comments', Tuomo Saloranta, 03 Jul 2014 Printer-friendly Version Supplement 
T. M. Saloranta
T. M. Saloranta

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