Influence of beech and spruce sub-montane forests on snow cover in Poľana Biosphere Reserve

Biologia ◽  
2017 ◽  
Vol 72 (8) ◽  
Author(s):  
Tomáš Šatala ◽  
Miroslav Tesař ◽  
Miriam Hanzelová ◽  
Martin Bartík ◽  
Václav Šípek ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Biosphere Reserve ◽  
Snow Accumulation ◽  
Physical Parameters ◽  
Open Area ◽  
Snow Water ◽  
Accumulation Phase ◽  
The Difference ◽  
Snow Conditions

AbstractThe aim of the work was to compare the influence of a beech (B) and a spruce stand (S) on the accumulation and melting of snow cover in comparison to an open area (O). The measurements were performed in winter seasons from 2012/13 to 2014/15 in the Hučava catchment, Poľana Biosphere Reserve (BR). We monitored hydrological and physical parameters of snow cover (snow depth – SD, snow water equivalent – SWE, snow density – D) at 13 research plots in 100 m elevation intervals (567–1,259 m a.s.l.). Within one research plot, the listed snow parameters were measured in a stand of spruce (S), beech (B), and at an open area (O).Based on the snow conditions, we found different characters of winter during the monitored period (2012/13 – snow rich, 2013/14 snow poor). For each winter, we tested the difference in the average values of SWE between the stands and the open area separately for the phase of snow accumulation and melting. The differences in the accumulation phase were found significant (

scholarly journals Modeling Snow Depth and Snow Water Equivalent Distribution and Variation Characteristics in the Irtysh River Basin, China

2021 ◽  
Vol 11 (18) ◽  
pp. 8365
Author(s):  
Liming Gao ◽  
Lele Zhang ◽  
Yongping Shen ◽  
Yaonan Zhang ◽  
Minghao Ai ◽  
...  
Keyword(s):  
Snow Cover ◽  
River Basin ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Snow Accumulation ◽  
Implicit Scheme ◽  
Snow Water ◽  
Irtysh River ◽  
Simulation Results ◽  
The Irtysh River

Accurate simulation of snow cover process is of great significance to the study of climate change and the water cycle. In our study, the China Meteorological Forcing Dataset (CMFD) and ERA-Interim were used as driving data to simulate the dynamic changes in snow depth and snow water equivalent (SWE) in the Irtysh River Basin from 2000 to 2018 using the Noah-MP land surface model, and the simulation results were compared with the gridded dataset of snow depth at Chinese meteorological stations (GDSD), the long-term series of daily snow depth dataset in China (LSD), and China’s daily snow depth and snow water equivalent products (CSS). Before the simulation, we compared the combinations of four parameterizations schemes of Noah-MP model at the Kuwei site. The results show that the rainfall and snowfall (SNF) scheme mainly affects the snow accumulation process, while the surface layer drag coefficient (SFC), snow/soil temperature time (STC), and snow surface albedo (ALB) schemes mainly affect the melting process. The effect of STC on the simulation results was much higher than the other three schemes; when STC uses a fully implicit scheme, the error of simulated snow depth and snow water equivalent is much greater than that of a semi-implicit scheme. At the basin scale, the accuracy of snow depth modeled by using CMFD and ERA-Interim is higher than LSD and CSS snow depth based on microwave remote sensing. In years with high snow cover, LSD and CSS snow depth data are seriously underestimated. According to the results of model simulation, it is concluded that the snow depth and snow water equivalent in the north of the basin are higher than those in the south. The average snow depth, snow water equivalent, snow days, and the start time of snow accumulation (STSA) in the basin did not change significantly during the study period, but the end time of snow melting was significantly advanced.

scholarly journals Experimental measurements for improved understanding and simulation of snowmelt events in the Western Tatra Mountains

2016 ◽  
Vol 64 (4) ◽  
pp. 316-328 ◽  
Author(s):  
Pavel Krajčí ◽  
Michal Danko ◽  
Jozef Hlavčo ◽  
Zdeněk Kostka ◽  
Ladislav Holko
Keyword(s):  
Spatial Variability ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Water Equivalent ◽  
Flood Forecasting ◽  
Snow Accumulation ◽  
Small Scale ◽  
Climatic Data ◽  
Tatra Mountains ◽  
Snow Water

AbstractSnow accumulation and melt are highly variable. Therefore, correct modeling of spatial variability of the snowmelt, timing and magnitude of catchment runoff still represents a challenge in mountain catchments for flood forecasting. The article presents the setup and results of detailed field measurements of snow related characteristics in a mountain microcatchment (area 59 000 m2, mean altitude 1509 m a. s. l.) in the Western Tatra Mountains, Slovakia obtained in winter 2015. Snow water equivalent (SWE) measurements at 27 points documented a very large spatial variability through the entire winter. For instance, range of the SWE values exceeded 500 mm at the end of the accumulation period (March 2015). Simple snow lysimeters indicated that variability of snowmelt and discharge measured at the catchment outlet corresponded well with the rise of air temperature above 0°C. Temperature measurements at soil surface were used to identify the snow cover duration at particular points. Snow melt duration was related to spatial distribution of snow cover and spatial patterns of snow radiation. Obtained data together with standard climatic data (precipitation and air temperature) were used to calibrate and validate the spatially distributed hydrological model MIKE-SHE. The spatial redistribution of input precipitation seems to be important for modeling even on such a small scale. Acceptable simulation of snow water equivalents and snow duration does not guarantee correct simulation of peakflow at short-time (hourly) scale required for example in flood forecasting. Temporal variability of the stream discharge during the snowmelt period was simulated correctly, but the simulated discharge was overestimated.

Snow accumulation and ablation in disturbed mountain spruce forest in West Tatra Mts

Biologia ◽  
2014 ◽  
Vol 69 (11) ◽  
Author(s):  
Martin Bartík ◽  
Roman Sitko ◽  
Marek Oreňák ◽  
Juraj Slovik ◽  
Jaroslav Škvarenina
Keyword(s):  
Snow Cover ◽  
Open Space ◽  
Snow Water Equivalent ◽  
Reference Value ◽  
Research Area ◽  
Snow Accumulation ◽  
Snow Density ◽  
Tatra Mts ◽  
Snow Water ◽  
The Impact

AbstractIn the presented paper we deal with the impact of the mature spruce stand on the accumulation and melting of snow cover at Červenec research area located in the Western Tatras at an elevation of 1420 m a.s.l. The work analyses the data obtained from the monitoring of snow cover during the period 2009–2014 (6 seasons). Since the season 2012/2013 the measurements have been also performed in a dead part of the stand and in a meadow. The results proved significant impact of the spruce stand on hydro-physical characteristics of snow cover — snow water equivalent, snow density, as well as on their change due to the dieback of the stand. The data measured at individual locations (open space in the forest, open meadow area, living and dead forest) were tested with the paired t-test for the significance of average differences. Average snow water equivalent in the living forest, dead forest and meadow was 42%, 47% and 83% of the reference value measured at the open space in the forest, respectively. The process of snow accumulation and melting was fastest at the open space, followed by the dead forest. In the living forest, the processes were the slowest.

scholarly journals A regional climate model hindcast for Siberia – assessing the added value of snow water equivalent using ESA GlobSnow and reanalyses

2012 ◽  
Vol 6 (6) ◽  
pp. 4637-4671
Author(s):  
K. Klehmet ◽  
B. Geyer ◽  
B. Rockel
Keyword(s):  
Regional Climate Model ◽  
Snow Cover ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Regional Climate ◽  
Snow Accumulation ◽  
Added Value ◽  
Snow Cover Extent ◽  
Snow Water

Abstract. This study analyzes the added value of a regional climate model hindcast of CCLM compared to global reanalyses in providing a reconstruction of recent past snow water equivalent (SWE) for Siberia. Consistent regional climate data in time and space is necessary due to lack of station data in that region. We focus on SWE since it represents an important snow cover parameter in a region where snow has the potential to feed back to the climate of the whole Northern Hemisphere. The simulation was performed in a 50 km grid spacing for the period 1948 to 2010 using NCEP Reanalysis 1 as boundary forcing. Daily observational reference data for the period of 1987–2010 was obtained by the satellite derived SWE product of ESA DUE GlobSnow that enables a large scale assessment. The analyses includes comparisons of the distribution of snow cover extent, example time series of monthly SWE for January and April, regional characteristics of long-term monthly mean, standard deviation and temporal correlation averaged over subregions. SWE of CCLM is compared against the SWE information of NCEP-R1 itself and three more reanalyses (NCEP-R2, NCEP-CFSR, ERA-Interim). We demonstrate a significant added value of the CCLM hindcast during snow accumulation period shown for January for many subregions compared to SWE of NCEP-R1. NCEP-R1 mostly underestimates SWE during whole snow season. CCLM overestimates SWE compared to the satellite-derived product during April – a month representing the beginning of snow melt in southern regions. We illustrate that SWE of the regional hindcast is more consistent in time than ERA-Interim and NCEP-R2 and thus add realistic detail.

scholarly journals Spatio-temporal variability of snow water equivalent in the extra-tropical Andes Cordillera from distributed energy balance modeling and remotely sensed snow cover

2016 ◽  
Vol 20 (1) ◽  
pp. 411-430 ◽  
Author(s):  
E. Cornwell ◽  
N. P. Molotch ◽  
J. McPhee
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
Remotely Sensed ◽  
Snow Accumulation ◽  
Model Assessment ◽  
Continental Divide ◽  
Average Maximum ◽  
Snow Water ◽  
Andes Cordillera

Abstract. Seasonal snow cover is the primary water source for human use and ecosystems along the extratropical Andes Cordillera. Despite its importance, relatively little research has been devoted to understanding the properties, distribution and variability of this natural resource. This research provides high-resolution (500 m), daily distributed estimates of end-of-winter and spring snow water equivalent over a 152 000 km2 domain that includes the mountainous reaches of central Chile and Argentina. Remotely sensed fractional snow-covered area and other relevant forcings are combined with extrapolated data from meteorological stations and a simplified physically based energy balance model in order to obtain melt-season melt fluxes that are then aggregated to estimate the end-of-winter (or peak) snow water equivalent (SWE). Peak SWE estimates show an overall coefficient of determination R2 of 0.68 and RMSE of 274 mm compared to observations at 12 automatic snow water equivalent sensors distributed across the model domain, with R2 values between 0.32 and 0.88. Regional estimates of peak SWE accumulation show differential patterns strongly modulated by elevation, latitude and position relative to the continental divide. The spatial distribution of peak SWE shows that the 4000–5000 m a.s.l. elevation band is significant for snow accumulation, despite having a smaller surface area than the 3000–4000 m a.s.l. band. On average, maximum snow accumulation is observed in early September in the western Andes, and in early October on the eastern side of the continental divide. The results presented here have the potential of informing applications such as seasonal forecast model assessment and improvement, regional climate model validation, as well as evaluation of observational networks and water resource infrastructure development.

scholarly journals Changes in the snow water equivalent in mountainous basins in Slovakia over recent decades

2015 ◽  
Vol 370 ◽  
pp. 109-116
Author(s):  
K. Hlavčová ◽  
K. Kotríková ◽  
S. Kohnová ◽  
P. Valent
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Snow Accumulation ◽  
Rainfall Runoff ◽  
Mountainous Regions ◽  
Ipcc Report ◽  
Snow Water ◽  
Rainfall Runoff Model ◽  
Runoff Model

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.

scholarly journals Effect of Forest Ecosystems on the Snow Water Equivalent in Relation to Aspect And Elevation in the Hučava River Watershed, Poľana Biosphere Reserve (Slovakia)

2017 ◽  
Vol 36 (3) ◽  
pp. 268-280 ◽  
Author(s):  
Michal Mikloš ◽  
Ilja Vyskot ◽  
Tomáš Šatala ◽  
Katarína Korísteková ◽  
Martin Jančo ◽  
...  
Keyword(s):  
Snow Cover ◽  
Forest Ecosystem ◽  
Forest Ecosystems ◽  
Snow Water Equivalent ◽  
Elevation Gradient ◽  
Biosphere Reserve ◽  
European Beech ◽  
Beech Forests ◽  
Spruce Forests ◽  
Snow Water

AbstractThe aim of this work was to assess how forest ecosystems dominated by Norway spruce (Picea abies (L.) or European beech (Fagus sylvatica L.) affect snow water equivalent (SWE) in relation to aspect and elevation. The research plots were established in a small headwater watershed of the Hučava flow belonging to the Poľana Biosphere Reserve (Central Europe, Inner Western Carpathians). The SWE values in this watershed (approximately 580–1270 m a.s.l.) were monitored during the three winter seasons starting from 2012–2013 to 2014–2015. The results revealed high variability in SWE and in snow cover duration between the studied seasons. The spatial variability was significantly affected by the forest ecosystem, aspect and elevation. The seasonal mean SWE value was lower by about 50–60% in the spruce forests and by about 21–30% in the beech forests compared to the open areas (100%). Over the whole seasons, the whole watershed mean SWE value on the slopes with the northern aspect was mostly higher compared to the slopes with the southern aspect. The effect of aspect was significant mainly in the open areas and in the forests dominated by European beech during the ablation periods of every season. In the case of the sufficient snow cover, the mean SWE value always increased with elevation. The elevation gradient of SWE was steepest at the open areas of the watershed in the peaks of the winter seasons. The three-season mean value of SWE elevation gradient (per 100 m) at the time of snow accumulation peak was equal to 16 mm in the spruce forests, 20 mm in the beech forests and 26 mm in the open areas. The research revealed that SWE is significantly affected by the forest ecosystem whilst its effect is dependent on the occurrence of dominant deciduous or coniferous tree species. However, the effect of forests is closely related to topographic characteristics (aspect and elevation) of a locality.

scholarly journals Snow Water Equivalent Accumulation Patterns from a Trajectory Approach over the U.S. Southern Rocky Mountains

Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 124
Author(s):  
Isaac J. Y. Schrock ◽  
Steven R. Fassnacht ◽  
Antonio-Juan Collados-Lara ◽  
William E. Sanford ◽  
Anna K. D. Pfohl ◽  
...  
Keyword(s):  
Rocky Mountains ◽  
Snow Water Equivalent ◽  
Snow Accumulation ◽  
Southern Rocky Mountains ◽  
Trajectory Approach ◽  
Northern Portion ◽  
Snow Water ◽  
Accumulation Phase ◽  
Linear Fit ◽  
System Variables

The spatial characteristics and patterns of snow accumulation and ablation inform the amount of water stored and subsequently available for runoff and the timing of snowmelt. This paper characterizes the snow accumulation phase to investigate the spatiotemporal snow water equivalent (SWE) distribution by fitting a function to the trajectory plot of the standard deviation versus mean SWE across a domain. Data were used from 90 snow stations for a 34-year period across the Southern Rocky Mountains in the western United States. The stations were divided into sub-sets based on elevation, latitude, and the mean annual maximum SWE. The best function was a linear fit, excluding the first 35 mm of SWE. There was less variability with SWE data compared to snow depth data. The trajectory of the accumulation phase was consistent for most years, with limited correlation to the amount of accumulation. These trajectories are more similar for the northern portion of the domain and for below average snow years. This work could inform where to locate new stations, or be applied to other earth system variables.

scholarly journals Estimating degree-day factors from MODIS for snowmelt runoff modeling

2014 ◽  
Vol 18 (12) ◽  
pp. 4773-4789 ◽  
Author(s):  
Z. H. He ◽  
J. Parajka ◽  
F. Q. Tian ◽  
G. Blöschl
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Threshold Value ◽  
Early Spring ◽  
Snow Accumulation ◽  
New Method ◽  
Snowmelt Runoff ◽  
Degree Day ◽  
Snow Water ◽  
Model Parameter Uncertainty

Abstract. Degree-day factors are widely used to estimate snowmelt runoff in operational hydrological models. Usually, they are calibrated on observed runoff, and sometimes on satellite snow cover data. In this paper, we propose a new method for estimating the snowmelt degree-day factor (DDFS) directly from MODIS snow covered area (SCA) and ground-based snow depth data without calibration. Subcatchment snow volume is estimated by combining SCA and snow depths. Snow density is estimated to be the ratio between observed precipitation and changes in the snow volume for days with snow accumulation. Finally, DDFS values are estimated to be the ratio between changes in the snow water equivalent and difference between the daily temperature and the melt threshold value for days with snow melt. We compare simulations of basin runoff and snow cover patterns using spatially variable DDFS estimated from snow data with those using spatially uniform DDFS calibrated on runoff. The runoff performances using estimated DDFS are slightly improved, and the simulated snow cover patterns are significantly more plausible. The new method may help reduce some of the runoff model parameter uncertainty by reducing the total number of calibration parameters. This method is applied to the Lienz catchment in East Tyrol, Austria, which covers an area of 1198 km2. Approximately 70% of the basin is covered by snow in the early spring season.

scholarly journals Snowfall and snow accumulation processes during the MOSAiC winter and spring season

2021 ◽  
Author(s):  
David N. Wagner ◽  
Matthew D. Shupe ◽  
Ola G. Persson ◽  
Taneil Uttal ◽  
Markus M. Frey ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Temporal Dynamics ◽  
Snow Accumulation ◽  
Blowing Snow ◽  
Drifting Snow ◽  
Snow Water ◽  
Abstract Data ◽  
Good Agreement

Abstract. Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation, and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth (HS) and density retrievals from a SnowMicroPen (SMP) and approximately weekly-measured snow depths along fixed transect paths. Hence, the computed SWE considers surface heterogeneities over an average path length of 1469 m. We used the SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were compared with ERA5 reanalysis snowfall rates for the drift track. Our study shows that the simple fitted HS-SWE function can well be used to compute SWE along a transect path based on SMP SWE retrievals and snow-depth measurements. We found an accumulated snow mass of 34 mm SWE until 26 April 2020. Further, we found that the Vaisala Present Weather Detector 22 (PWD22), installed on a railing on the top deck of research vessel Polarstern was least affected by blowing snow and showed good agreements with SWE retrievals along the transect, however, it also systematically underestimated snowfall. The OTT Pluvio2 and the OTT Parsivel2 were largely affected by wind and blowing snow, leading to higher measured precipitation rates, but when eliminating drifting snow periods, especially the OTT Pluvio2 shows good agreements with ground measurements. A comparison with ERA5 snowfall data reveals a good timing of the snowfall events and good agreement with ground measurements but also a tendency towards overestimation. Retrieved snowfall from the ship-based Ka-band ARM Zenith Radar (KAZR) shows good agreements with SWE of the snow cover and comparable differences as ERA5. Assuming the KAZR derived snowfall as an upper limit and PWD22 as a lower limit of a cumulative snowfall range, we estimate 72 to 107 mm measured between 31 October 2019 and 26 April 2020. For the same period, we estimate the precipitation mass loss along the transect due to erosion and sublimation as between 53 and 68 %. Until 7 May 2020, we suggest a cumulative snowfall of 98–114 mm.

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