Highelevation alpine snow cover

Christian Pluss, Charles Fierz, and Paul M. B. Fohn Relevance and characteristics

High alpine seasonal snow covers are present in mountainous areas around the world. The duration and spatial distribution of alpine snow covers is extremely variable and depends mainly on the geographical location, the climatic conditions, and the elevation of the mountain range. Alpine snow covers are of large economic and social importance in many areas, for example as a water resource for hydropower or as a base for tourism. In all alpine areas the snow cover is an important climate element because of its high albedo and low surface temperature. However, seasonal alpine snow covers may also cause natural hazards such as avalanches or flooding. The snow cover of the Alps - situated in the heart of densely populated Europe -meets all the above-mentioned issues and therefore considerable research effort has been spent towards its investigation.

The central part of the Alps is seasonally snow covered from about December to April above an altitude of 1000 m. The snow cover is highly variable in time and space because of both the complex topography and large differences in elevation within the mountain range. Wind influence as well as variable elevation, slope angles, and surface conditions lead to a highly structured snowpack being spatially inhomogeneous at scales as small as a slope, contrary to the Arctic, Antarctic, or prairie snowpack. Accordingly, the distribution of snow accumulation is very difficult to investigate (Elder et al., 1989; Sturm et al., 1995).

Site

The site of Weissfluhjoch lies in the eastern Swiss Alps near the town of Davos. The measurement site is located at a horizontal site in a southeasterly slope at an altitude of 2540 m a.s.l. (46.83° N, 9.81° E). On this well-equipped site, daily manual observations have been performed since 1936 and today most relevant nivo-meteorological parameters are measured automatically at a half-hourly time step (down- and up-welling shortwave and longwave radiation, air temperature, humidity, wind speed, snow surface temperature, snow depth). The snow cover lasts on average nine months (269 days), from mid-October to mid-July, and the mean snow depth reaches its maximum around mid-April (221 cm). The mean maximum snow water equivalent amounts to 857 mm w.e.

Energy balance

Energy balance investigations over an alpine snow cover were performed mainly in the European Alps and the North American Rocky Mountains. Many of these studies were performed over snow-covered glaciers under melt conditions (see Tables 3.2 and 3.3). All these investigations show that, on a daily basis, net radiation is the primary energy source, while turbulent fluxes are generally of minor importance.

Along with the daily means of air temperature, wind, and albedo, the daily means of energy fluxes at the surface and mass balance at Weissfluhjoch (eastern Swiss Alps) are presented in Fig. 3.5. Using the aforementioned measured forcing data, the snow-cover model SNOWPACK (Bartelt and Lehning, 2002; Lehning et al., 2002a, 2002b) computes the energy balance, allowing for the extracting of parameterized turbulent fluxes.

Despite the high albedo of the snow cover, the shortwave net radiation flux SN is the dominant energy source for the snow cover during most of the investigation period. Longwave net radiation flux LN is, in general, an energy loss and depends mainly on cloud conditions. During the ablation period, net radiative flux Rn is by far the dominant energy source for snowmelt. The magnitude of the turbulent fluxes of sensible and latent heat, HS and HL, respectively, are very small on average, but the daily mean values may exceed the magnitude of net radiative flux and are therefore not negligible for the investigation of short-term processes. At Weissfluhjoch, the small average magnitude of the turbulent fluxes is attributed firstly to the relatively small wind speed at this site and secondly to the frequent changes of the weather patterns, which lead to changes of the sign of these fluxes.

Modeling aspects

The high variability of the alpine snow cover in space and time proves to be very difficult to model. Accumulation depends largely on wind influence and small-scale precipitation differences may lead to very inhomogeneous conditions. The energy fluxes at the snow surface are highly variable due to topographic influence on the radiation fluxes and due to high variability of the turbulent fluxes. Dozier (1980) presented a spatially distributed model for shortwave radiation, Pluss and Ohmura (1997) proposed a modeling approach for longwave radiation. For the turbulent fluxes only very simple models have been proposed so far, despite the fact that over melting snow, the turbulent fluxes may be of considerable importance (Olyphant and Isard, 1988).

For ablation estimation, hydrologic models (see Kirnbauer et al., 1994) have proven to successfully model the spatial distribution of ablation. Fierz et al. (1997) showed that snow temperature profiles could be modeled on several aspects using a distributed energy balance model to drive a point snow-cover model.

Table 3.3 Energy balance over snow covers for selected time periods.

Surface fluxesa

Table 3.3 Energy balance over snow covers for selected time periods.

Surface fluxesa

Type of snow cover

Location

Period

SN

LN

Rnc

Hs

Hl

dH/dtb

High Alpine

Weissfluhjoch,

Nov to Dec 95

-13.7

31.9

18.2

-19.7

5.0

-3.5

Switzerland (47° N)

Jan to Apr 96

-29.7

46.8

17.1

-19.4

7.5

-5.2

May to Jun 96

-86.7

40.8

-45.8

-28.0

-2.5

76.3

Middle Alpine

Col de Porte,

Jan 95

-4.9

11.2

6.3

-6.1

-2.0

1.8

France (61° N)

Apr 95

-46.9

12.5

-34.4

-11.0

-4.1

49.5

Jan to Apr 95

-21.8

14.7

-7.1

-7.7

-2.1

16.9

Jan 94

-6.6

16.0

9.4

-7.0

-2.4

0.0

Apr 94

-25.3

13.8

-11.5

-8.4

-2.5

22.4

Jan to Apr 94

-22.0

17.4

-4.6

-9.9

-2.0

16.5

Snow-covered sea ice

High Arctic ice flow,

May to Jun 56

-48.0

26.3

-21.7

-11.6

12.3

-2.2

North Pole 4, (>85° N)

Jul to Aug 56

-36.7

-14.6

-22.1

2.9

8.4

10.8

Sep to Oct 56

-2.5

13.4

10.9

-1.6

1.0

-10.3

Nov to Dec 56

0.0

11.9

11.9

-9.3

1.3

-3.9

Jan to Mar 57

-0.4

16.5

-16.1

-10.7

0.8

-6.2

a Average surface fluxes in W irr2 over the given period.

b (dH/dt) is the net change rate of the snowpack's internal energy per unit area, which is the negative sum of net radiative (%), sensible heat (Hs) and latent heat (HL) fluxes, but neglecting advective and ground heat fluxes (see Equation 3.1). c The net radiative flux (%) is the sum of net shortwave radiation flux (Sn) and net longwave radiation flux (LN).

Figure 3.5. Daily means and, where appropriate, daily minima and maxima (shaded band) at Weissfluhjoch during the winter 1995/96. The snow cover was continuous from November 2, 1995 to June 11, 1996. Net surface flux is the sum of surface fluxes, which corresponds to the net negative change rate of the snowpack's internal energy per unit area (-dH/dt) neglecting advective and ground heat fluxes (cf. Equation 3.1). Total mass is the accumulated difference of precipitations (snow and rain) to runoff, neglecting sublimation and evaporation (cf. Equation 3.4).

Figure 3.5. Daily means and, where appropriate, daily minima and maxima (shaded band) at Weissfluhjoch during the winter 1995/96. The snow cover was continuous from November 2, 1995 to June 11, 1996. Net surface flux is the sum of surface fluxes, which corresponds to the net negative change rate of the snowpack's internal energy per unit area (-dH/dt) neglecting advective and ground heat fluxes (cf. Equation 3.1). Total mass is the accumulated difference of precipitations (snow and rain) to runoff, neglecting sublimation and evaporation (cf. Equation 3.4).

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Renewable Energy 101

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