Preprints
https://doi.org/10.5194/tc-2021-98
https://doi.org/10.5194/tc-2021-98

  13 Apr 2021

13 Apr 2021

Review status: a revised version of this preprint is currently under review for the journal TC.

Multilayer observation and estimation of the snowpack cold content in a humid boreal coniferous forest in eastern Canada

Achut Parajuli1,2, Daniel F. Nadeau1,2, François Anctil1,2, and Marco Alves1,2 Achut Parajuli et al.
  • 1Department of Civil and Water Engineering, Université Laval, Québec, Canada
  • 2CentrEau, Quebec Water Research Centre, Université Laval, Québec, Canada

Abstract. Cold content (CC) is an internal energy state within a snowpack and is defined by the energy deficit required to attain isothermal snowmelt temperature (0 °C). For any snowpack, fulfilling the cold content deficit is a pre-requisite before the onset of the snowmelt. Cold content for a given snowpack thus plays a critical role because it affects both the timing and the rate of snowmelt. Estimating the cold content is a labour-intensive task as it requires extracting in-situ snow temperature and density. Hence, few studies have focused on characterizing this snowpack variable. This study describes the multilayer cold content of a snowpack and its variability across four sites with contrasting canopy structures within a coniferous boreal forest in southern Québec, Canada, throughout winter 2017–18. The analysis was divided into two steps. In the first step, the observed CC data from weekly snowpits for 60 % of the snow cover period were examined. During the second step, a reconstructed time series of CC was produced and analyzed to highlight the high-resolution temporal variability of CC for the full snow cover period. To accomplish this, the Canadian Land Surface Scheme (CLASS; featuring a single-layer snow model) was first implemented to obtain simulations of the average snow density at each of the four sites. Next, an empirical procedure was used to produce realistic density profiles, which, when combined with in situ continuous snow temperature measurements from an automatic profiling station, provides a time series of CC estimates at half-hour intervals for the entire winter. At the four sites, snow persisted on the ground for 218 days, with melt events occurring on 42 of those days. Based on snowpit observations, the largest mean CC (−2.62 MJ m−2) was observed at the site with the thickest snow cover. The maximum difference in mean CC between the four study sites was −0.47 MJ m−2, representing a site-to-site variability of 20 %. Before analyzing the reconstructed CC time series, a comparison with snowpit data confirmed that CLASS yielded reasonable estimates of the snow water equivalent (SWE) (R2 = 0.64 and percent bias (Pbias) = −17.1 %), bulk snow density (R2 = 0.71 and Pbias = 1.6 %), and bulk cold content (R2 = 0.90 and Pbias = −2.0 %). A snow density profile derived by utilizing an empirical formulation also provided reasonable estimates of cold content (R2 = 0.42 and Pbias = 5.17 %). Thanks to these encouraging results, the reconstructed and continuous CC series could be analyzed at the four sites, revealing the impact of rain-on-snow and cold air pooling episodes on the variation of CC. The continuous multilayer cold content time series also provided us with information about the effect of stand structure, local topography, and meteorological conditions on cold content variability. Additionally, a weak relationship between canopy structure and CC was identified.

Achut Parajuli et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2021-98', Anonymous Referee #1, 04 May 2021
  • RC2: 'Comment on tc-2021-98', Keith Jennings, 11 May 2021

Achut Parajuli et al.

Achut Parajuli et al.

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Short summary
Cold content is the energy required to attain an isothermal (0 °C) state and resulting in the snow surface melt. This study focuses on determining the multi-layer cold content (30-min time steps) relying on field measurements, snow temperature profile, and empirical formulation in four distinct forest sites of Montmorency Forest, eastern Canada. We present novel research, where effect of forest structure, local topography, and meteorological conditions on cold content variability is explored.