1,721,053 research outputs found
Ice mass balance data PS81/506-1 from Weddell Sea, Antarctica, 2013-2014
No full textIce mass balance (IMB) buoy data PS81/506 from Weddell Sea, Antarctica, 2013-2014. The buoy was deployed together with an automatic weather station buoy (see under related) on sea ice station PS81/506 from Research Vessel Polarstern in the Antarctic Weddell Sea in austral winter 2013 (cruise leg ANT-XXIX/6, AWECS campaign). The IMB buoy provides data between 2013-07-13T12:15:00 and 2014-02-07T01:17:00.
The IMB buoy was kindly provided by the Scottish Association for Marine Science (SAMS). The IMB buoy consisted of a thermistor string of 5 m length, with a 2 cm sensor spacing. Interfaces were determined by hand. The bottom interface was determined from the existence of a knee in the temperature profile where apparent, combined with the heating cycle data. Both the amount of heating, and the ratio of heating at 60s over heating at 30s were used. This is very accurate up until ~day 300, and it is probably about +/- 4 cm after that. The snow interface was determined by the above, and looking at the knee in the temperature profile for each of the four temperature profiles during the day. This is more difficult to pick out, so accuracy here is maybe a few cm. Note flooding occurred at ~day 290 (probably up to freeboard level on ~day 278). The flooding interface was determined from day 250 on, and based mostly on the heating cycle. Clear surface snow melt on ~day 330, and IMB goes isothermal and warm on ~day 350. It may be that the thermistor string was pulled out of the ice, since it is warm at the sensors that were in the ocean
Ice mass balance data PS81/517 from Weddell Sea, Antarctica, 2013
No full textIce mass balance (IMB) buoy data PS81/517 from Weddell Sea, Antarctica, 2013. The buoy was deployed together with an automatic weather station buoy (see under related) on sea ice station PS81/517 from Research Vessel Polarstern in the Antarctic Weddell Sea in austral winter 2013 (cruise leg ANT-XXIX/6, AWECS campaign). The IMB buoy provides data between 2013-07-31T17:28:00 and 2013-10-11T00:30:00.
The IMB buoy was kindly provided by the Scottish Association for Marine Science (SAMS). The IMB buoy consisted of a thermistor string of 5 m length, with a 2 cm sensor spacing. Interfaces were determined by hand. Heating cycle data was of poor quality, so the interfaces were picked mostly based on temperature. The ice interface will be pretty good (~2 cm accuracy), and the snow is probably a bit more inaccurate. The bottom interface was determined from the existence of a knee in the temperature profile where apparent. The top interface was picked based on the transition to constant temperature in the air and the diurnal variability. This may be subject to some bias, but note that the changes are only a few cm until the end where the IMB probably died because it got washed over (based on recorded temperatures). No flooding is apparent in the measurements
Automatic weather station buoy data PS81/506-1 from Weddell Sea, Antarctica, 2013-2014
No full textAutomatic weather station buoy data PS81/506 from Weddell Sea, Antarctica, 2013-2014. The buoy was deployed together with an ice mass balance buoy (see under related) on sea ice station PS81/506 from Research Vessel Polarstern in the Antarctic Weddell Sea in austral winter 2013 (cruise leg ANT-XXIX/6, AWECS campaign). The automatic weather station provides data between 2013-07-12T14:00 and 2013-08-13T14:00. Time is in UTC
Automatic weather station buoy data PS81/517 from Weddell Sea, Antarctica, 2013
No full textAutomatic weather station buoy data PS81/517 from Weddell Sea, Antarctica, 2013. The buoy was deployed together with an ice mass balance buoy (see under related) on sea ice station PS81/517 from Research Vessel Polarstern in the Antarctic Weddell Sea in austral winter 2013 (cruise leg ANT-XXIX/6, AWECS campaign). The automatic weather station provides data between 2013-07-30T19:00 and 2013-11-10T12:00. Time is in UTC
Snow cover simulations and avalanche dynamics simulations for the area of Davos, Switzerland (2011-2014)
No full text<p>Alpine3D model simulations of the snow cover at 100m resolution for the area surrounding Davos for the period October 2010 to September 2014.</p>
<p>Avalanche dynamics simulations using the RAMMS-Extended model of 169 selected avalanches in the same period, using initial conditions as simulated by the Alpine3D model.</p>
<p>This dataset belongs to:</p>
<p>Wever, N., Vera Valero, C., and Techel, F. (2018): <em>Coupled snow cover and avalanche dynamics simulations to evaluate wet snow avalanche activity</em>, J. Geophys. Res. Earth Surf., 123, 1772–1796 <a href="https://doi.org/10.1029/2017JF004515">doi: 10.1029/2017JF004515.</a></p>
Liquid water flow in snow and hydrological implications
No full textThe presence of a snow cover has a strong impact on hydrological processes. In this thesis, the role of the snow cover as an interface between the atmosphere and the soil is assessed. An implementation of a solver for Richards Equation (RE) for water flow in variably saturated porous media in the one-dimensional, physics based snow cover model SNOWPACK is discussed, to solve water flow in snow and soil. The updated SNOWPACK model was validated by comparing simulations for the sites Weissfluhjoch (WFJ) and Col de Porte with an extensive data set of meteorological and snowpack measurements. Solving RE for snow appeared to improve the estimation of liquid water runoff from the snowpack, especially on sub-daily time scales and in deep, stratified snow covers. The onset of snowpack runoff in spring was better predicted when using RE instead of a bucket-type approach. On the sub-daily time scale, the timing of peak runoff was predicted more accurately using RE. For WFJ, the representation of the internal snowpack structure was assessed using snow profiles, snow temperature measurements and data from upward looking ground penetrating radar. In the main winter season, a high agreement was found for the temporal evolution of snow water equivalent (SWE), snow density, temperature profiles and, to a lesser extent, grain size and type. In the melt season, RE seems to provide a better simulation of the movement of the meltwater front through the snowpack than the bucket scheme, although large discrepancies between simulations, radar data and snow lysimeter measurements remain. The depletion rate of SWE in spring appeared to be overestimated in the model. Strong indications were found that the snow densification process in spring is not adequately simulated, as snow density in spring was consistently underestimated. The soil module of SNOWPACK was verified by comparing soil moisture measurements from 7 stations in the area of Davos, with distributed SNOWPACK simulations using the spatially explicit Alpine3D model. Soil moisture was simulated with varying degrees of success. By investigating cross-correlations between the different sites for measurements and Alpine3D simulations, it was found that the spatially distributed simulations were able to explain a part of the spatial variability in the measurements. This could be mainly attributed to the spatial variability of the snow cover and snow melt. Preliminary results also suggest that streamflow simulations in Alpine3D could benefit from accurate soil moisture simulations. Finally, SNOWPACK was used for simulations of 14 sites in two areas in Switzerland that encountered severe flooding in October 2011, when a large snowfall was followed by a significant warming and rainfall. Thick snow covers had significant capacity for liquid water storage, creating a time lag of several hours between the onset of rainfall and the onset of snowpack runoff, whereas shallow snow covers reacted much quicker. Interestingly, once thick snow covers produced runoff, peak runoff rates exceeded runoff rates from shallow snowpacks and also exceeded the sum of rainfall and snowmelt rates. This suggests that snow settling, wet snow metamorphism and liquid water flow provide an interaction with each other that potentially can enhance snowpack outflow. This model result could have important consequences for understanding the contribution of snowpack runoff in flood events.EFLUMCRYO
Automatic weather station buoy data PS81/515-1 from Weddell Sea, Antarctica, 2013
No full textAutomatic weather station data from a buoy deployed on sea ice station PS81/515-1 from Research Vessel Polarstern in the Antarctic Weddell Sea in austral winter 2013 (cruise leg ANT-XXIX/6, AWECS campaign). The automatic weather station provides data between 2013-07-26T19:00 and 2013-10-03T19:00. Time is in UTC
Snow density and grain size measurements from Snow Micro Pen (SMP) on ice stations PS81/517 and PS81/518 from Weddell Sea, Antarctica, 2013 - links to original files
No full textThis dataset contains SnowMicroPen (SMP) measurements on sea ice stations PS81/517 and PS81/518 from Research Vessel Polarstern in the Antarctic Weddell Sea in austral winter 2013 (cruise leg ANT-XXIX/6, AWECS campaign). The SMP surveyed the uppermost approximately 25-30 cm of the snow surface, and processed output is available at 2.5 mm vertical resolution. The data contains snow density and grain size. Measurements were performed between 2013-07-31 and 2013-08-04. SMP measurements were done in close proximity (approximately 1-2 m distance) of snow pit locations (see Paul et al., 2017), to enable calibration of the instrument. Two perpendicular transects were made in a field that was surveyed using terrestrial laser scanning, to sample the spatial variability of the snow microstructure on sea ice. Further information can be found in Wever et al. (2021)
Future water temperature of rivers in Switzerland under climate change investigated with physics-based models
Full text linkRiver ecosystems are highly sensitive to climate change and projected future increase in air temperature is expected to increase the stress for these ecosystems. Rivers are also an important socio-economic factor impacting, amongst others, agriculture, tourism, electricity production, and drinking water supply and quality. In addition to changes in water availability, climate change will impact river temperature. This study presents a detailed analysis of river temperature and discharge evolution over the 21st century in Switzerland. In total, 12 catchments are studied, situated both on the lowland Swiss Plateau and in the Alpine regions. The impact of climate change is assessed using a chain of physics-based models forced with the most recent climate change scenarios for Switzerland including low-, mid-, and high-emission pathways. The suitability of such models is discussed in detail and recommendations for future improvements are provided. The model chain is shown to provide robust results, while remaining limitations are identified. These are mechanisms missing in the model to correctly simulate water temperature in Alpine catchments during the summer season. A clear warming of river water is modelled during the 21st century. At the end of the century (2080-2090), the median annual river temperature increase ranges between +0.9°C for low-emission and +3.5°C for high-emission scenarios for both lowland and Alpine catchments. At the seasonal scale, the warming on the lowland and in the Alpine regions exhibits different patterns. For the lowland the summer warming is stronger than the one in winter but is still moderate. In Alpine catchments, only a very limited warming is expected in winter. The period of maximum discharge in Alpine catchments, currently occurring during mid-summer, will shift to earlier in the year by a few weeks (low emission) or almost 2 months (high emission) by the end of the century. In addition, a noticeable soil warming is expected in Alpine regions due to glacier and snow cover decrease. All results of this study are provided with the corresponding source code used for this paper.Mathematical Geodesy and Positionin
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