Monitoring snow processes in the Ötztal Alps (Austria) and development of an open source snow model framework

Author(s):  
Michael Warscher ◽  
Florian Hanzer ◽  
Carsten Becker ◽  
Ulrich Strasser

<p>The Rofental is a high Alpine environmental research basin in the Ötztal Alps (Austria, 1890 - 3770 m a.s.l.). The existing measurement network has recently been extended by new stations and sensors that focus on automated recordings of snow cover properties. Core of the network are three automatic weather stations (AWS) that incorporate 10 min. recordings of snow depth (SD), snow water equivalent (SWE), layered snow temperatures, snow surface temperature, snow density, as well as solid and liquid water content of the snowpack. One AWS is extended by a particular setup of two SD and SWE measurements at nearby wind-exposed and sheltered locations, complemented by an acoustic-based snow drift sensor to quantify wind-driven snow redistribution.</p><p>We here present analyses of the publicly available data that focus on snow drift events in an avalanche-prone winter season. The two nearby SWE measurements show differences of around 500% of measured peak SWE at a horizontal distance of only 25 m caused by wind-driven redistribution. In addition, the presented data is used to develop and validate the new open source, distributed snow cover model openAMUNDSEN. We evaluate different integrated energy balance and snow layer schemes and compare the data to results of the ESM-SnowMIP project.</p>

2021 ◽  
Author(s):  
Michael Warscher ◽  
Thomas Marke ◽  
Ulrich Strasser

Abstract. According to the living data process in ESSD, this publication presents extensions of a comprehensive hydrometeorological and glaciological data set for several research sites in the Rofental (1891–3772 m a.s.l., Ötztal Alps, Austria). Whereas the original dataset has been published in a first original version in 2018 (https://doi.org/10.5194/essd-10-151-2018), the new time series presented here originate from meteorological and snow-hydrological recordings that have been collected from 2017 to 2020. Some data sets represent continuations of time series at existing locations, others come from new installations complementing the scientific monitoring infrastructure in the research catchment. Main extensions are a fully equipped automatic weather and snow monitoring station, as well as extensive additional installations to enable continuous observation of snow cover properties. Installed at three high Alpine locations in the catchment, these include automatic measurements of snow depth, snow water equivalent, volumetric solid and liquid water content, snow density, layered snow temperature profiles, and snow surface temperature. One station is extended by a particular arrangement of two snow depth and water equivalent recording devices to observe and quantify wind-driven snow redistribution. They are installed at nearby wind-exposed and sheltered locations and are complemented by an acoustic-based snow drift sensor. The data sets represent a unique time series of high-altitude mountain snow and meteorology observations. We present three years of data for temperature, precipitation, humidity, wind speed, and radiation fluxes from three meteorological stations. The continuous snow measurements are explored by combined analyses of meteorological and snow data to show typical seasonal snow cover characteristics. The potential of the snow drift observations are demonstrated with examples of measured wind speeds, snow drift rates and redistributed snow amounts in December 2019 when a tragic avalanche accident occurred in the vicinity of the station. All new data sets are provided to the scientific community according to the Creative Commons Attribution License by means of the PANGAEA repository (https://www.pangaea.de/?q=%40ref104365).


1987 ◽  
Vol 9 ◽  
pp. 39-44 ◽  
Author(s):  
A.T.C. Chang ◽  
J.L. Foster ◽  
D.K. Hall

Snow covers about 40 million km2of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.


Author(s):  
Anne D. W. Nuijten ◽  
Inge Hoff ◽  
Knut V. Høyland

Heated pavements are used as an alternative to removing snow and ice mechanically and chemically. Usually a heated pavement system is automatically switched on when snowfall starts or when there is a risk of ice formation. Ideally, these systems run based on accurate predictions of surface conditions a couple of hours ahead of time, for which both weather forecasts and reliable surface temperature predictions are needed. The effective thermal conductivity of the snow layer is often described as a function of its density. However the thermal conductivity of a snow layer can vary considerably, not only for snow samples with a different density, but also for snow samples with the same density, but with a variation in the liquid water content. In this paper a physical temperature and surface condition model is described for snow-covered roads. The model is validated for an entire winter season on a heated pavement in Norway. Two different models to describe the thermal conductivity through the snow layer were compared. Results show that the thermal conductivity of the snow layer can be best described as a function of the density for snow with a low liquid water content. For snow with a high water content, the thermal conductivity can be best described as a function of the volume fractions and thermal conductivity of ice, water, and air, in which air and ice are modeled as a series system and water and air/ice in parallel.


1987 ◽  
Vol 9 ◽  
pp. 39-44 ◽  
Author(s):  
A.T.C. Chang ◽  
J.L. Foster ◽  
D.K. Hall

Snow covers about 40 million km2 of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.


2019 ◽  
Vol 11 (4) ◽  
pp. 417 ◽  
Author(s):  
John Yackel ◽  
Torsten Geldsetzer ◽  
Mallik Mahmud ◽  
Vishnu Nandan ◽  
Stephen Howell ◽  
...  

Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are acquired during the winter season with coincident in situ snow-thickness observations. Our objective is to describe a methodological framework for estimating relative snow thickness on first-year sea ice based on the variance in σ° from daily time series ASCAT and QuikSCAT scatterometer measurements during the late winter season prior to melt onset. We first describe our theoretical basis for this approach, including assumptions and conditions under which the method is ideally suited and then present observational evidence from four independent case studies to support our hypothesis. Results suggest that the approach can provide a relative measure of snow thickness prior to σ° detected melt onset at both Ku- and C-band frequencies. We observe that, during the late winter season, a thinner snow cover displays a larger variance in daily σ° compared to a thicker snow cover on first-year sea ice. This is because for a given increase in air temperature, a thinner snow cover manifests a larger increase in basal snow layer brine volume owing to its higher thermal conductivity, a larger increase in the dielectric constant and a larger increase in σ° at both Ku- and C bands. The approach does not apply when snow thickness distributions on first-year sea ice being compared are statistically similar, indicating that similar late winter σ° variances likely indicate regions of similar snow thickness.


2004 ◽  
Vol 38 ◽  
pp. 273-278 ◽  
Author(s):  
Manfred Stähli ◽  
Markus Stacheder ◽  
David Gustafsson ◽  
Stefan Schlaeger ◽  
Martin Schneebeli ◽  
...  

AbstractA new in situ sensor for the simultaneous measurement of snow water equivalent, snow density and liquid-water content is presented in this paper. The system consists of radio frequency transmission lines of up to 25 m length cast in a flat PVC band, which can be set up either horizontally to monitor single snow-layer properties or sloping from a mast to the soil surface to determine vertical snowpack properties. The dielectric coefficient along the flat-band cable is measured with a time-domain reflectometer at high frequencies, and with a low-frequency impedance analyzer. The performance of the sensor system was tested during two winter seasons (2001–03) at the high-alpine test site Weissfluhjoch, Davos, Switzerland. The cable suspension and set-up of the sloping cable was shown to be critical with regard to stability and the formation of unwanted air gaps along the cable. Overall, the sensing system proved quite robust and produced results in agreement with manual snowpack observations.


2014 ◽  
Vol 10 (2) ◽  
pp. 145-160
Author(s):  
Katarína Kotríková ◽  
Kamila Hlavčová ◽  
Róbert Fencík

Abstract An evaluation of changes in the snow cover in mountainous basins in Slovakia and a validation of MODIS satellite images are provided in this paper. An analysis of the changes in snow cover was given by evaluating changes in the snow depth, the duration of the snow cover, and the simulated snow water equivalent in a daily time step using a conceptual hydrological rainfall-runoff model with lumped parameters. These values were compared with the available measured data at climate stations. The changes in the snow cover and the simulated snow water equivalent were estimated by trend analysis; its significance was tested using the Mann-Kendall test. Also, the satellite images were compared with the available measured data. From the results, it is possible to see a decrease in the snow depth and the snow water equivalent from 1961-2010 in all the months of the winter season, and significant decreasing trends were indicated in the months of December, January and February


2021 ◽  
Vol 13 (13) ◽  
pp. 2641
Author(s):  
Zeinab Takbiri ◽  
Lisa Milani ◽  
Clement Guilloteau ◽  
Efi Foufoula-Georgiou

Falling snow alters its own microwave signatures when it begins to accumulate on the ground, making retrieval of snowfall challenging. This paper investigates the effects of snow-cover depth and cloud liquid water content on microwave signatures of terrestrial snowfall using reanalysis data and multi-annual observations by the Global Precipitation Measurement (GPM) core satellite with particular emphasis on the 89 and 166 GHz channels. It is found that over shallow snow cover (snow water equivalent (SWE) ≤100kg m−2) and low values of cloud liquid water path (LWP 100–150 g m−2), the scattering of light snowfall (intensities ≤0.5mm h−1) is detectable only at frequency 166 GHz, while for higher snowfall rates, the signal can also be detected at 89 GHz. However, when SWE exceeds 200 kg m−2 and the LWP is greater than 100–150 g m−2, the emission from the increased liquid water content in snowing clouds becomes the only surrogate microwave signal of snowfall that is stronger at frequency 89 than 166 GHz. The results also reveal that over high latitudes above 60°N where the SWE is greater than 200 kg m−2 and LWP is lower than 100–150 g m−2, the snowfall microwave signal could not be detected with GPM without considering a priori data about SWE and LWP. Our findings provide quantitative insights for improving retrieval of snowfall in particular over snow-covered terrain.


2012 ◽  
Vol 6 (5) ◽  
pp. 4137-4169 ◽  
Author(s):  
H. Lu ◽  
W. S. Wei ◽  
M. Z. Liu ◽  
X. Han ◽  
W. Hong

Abstract. Snow liquid water content is a very important parameter for snow hydrological processes, avalanche research and snow cover mapping by remote sensing. Snow liquid water content was measured with a portable instrument (Snow Fork) in the Tianshan Station for Snow Cover and Avalanche Research, Chinese Academy of Sciences during the snowmelt period in spring 2010. This study analyzed the temporal and spatial distribution of snow liquid water content in different weather conditions. The average liquid water content of snow in the whole layer exponentially increased and can be calculated using a regression function of prior moving average temperature. The proportion of net radiation, sensible heat flux and latent heat flux in total energy changed in different snowmelt period. During the pre-snowmelt period (0.3% ≤ Wvol < 1%), snow liquid water content and its temporal variation were relatively small, with liquid water accumulated in the coarse snow layer. During the mid-snowmelt period (1% ≤ Wvol < 2.5%), the variation was significant in the upper layer and decreased drastically during the snowfall and the following one to two days. Only the temporal variation decreased after rain or snow (ROS) events. During the late-snowmelt period (Wvol ≥ 2.5%), the distribution and variation of every snow layer showed a~uniform trend, and the effect of ROS events on liquid water content only occurred during rainfall and snowfall.


Author(s):  
K. Hlavčová ◽  
K. Kotríková ◽  
S. Kohnová ◽  
P. Valent

Abstract. Changes in snowpack and duration of snow cover can cause changes in the regime of snow and rain-snow induced floods. The recent IPCC report suggests that, in snow-dominated regions such as the Alps, the Carpathian Mountains and the northern parts of Europe, spring snowmelt floods may occur earlier in a future climate because of warmer winters, and flood hazards may increase during wetter and warmer winters, with more frequent rain and less frequent snowfall. The monitoring and modelling of snow accumulation and snow melting in mountainous catchments is rather complicated, especially due to the high spatial variability of snow characteristics and the limited availability of terrestrial hydrological data. An evaluation of changes in the snow water equivalent (SWE) during the period of 1961–2010 in the Upper Hron river basin, which is representative of the mountainous regions in Central Slovakia, is provided in this paper. An analysis of the snow cover was performed using simulated values of the snow water equivalent by a conceptual semi-distributed hydrological rainfall-runoff model. Due to the poor availability of the measured snow water equivalent data, the analysis was performed using its simulated values. Modelling of the SWE was performed in different altitude zones by a conceptual semi-distributed hydrological rainfall-runoff model. The evaluation of the results over the past five decades indicates a decrease in the simulated snow water equivalent and the snow duration in each altitude zone and in all months of the winter season. Significant decreasing trends were found for December, January and February, especially in the highest altitude zone.


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