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The snow man : a true story
\"Discover the true story of a man who lived alone in the mountains with a hobby of measuring snowfall that led to groundbreaking data tracking in climate change studies\"-- Provided by publisher.
Book
Inter-comparison of field snow measurements using different instruments in Türkiye
Snow is important in Türkiye especially in the mountainous eastern areas where it may stay on the ground for more than half of the year. This region plays a vital role in feeding the water resources of the trans-boundary Euphrates-Tigris Basin, supporting crucial dams for water supply, irrigation and energy production. Thus, easy, frequent, correct and economical ways of measuring the snowpack is crucial. The snow properties at specific locations in the mountainous eastern regions over the two snow seasons (2018 and 2019) were studied by using different instruments and techniques, snow pit (box/cylinder/wedge cutter types), snow tube (Federal Sampler) and SnoTel (Snowpack Analyzer). The results point out a 1.7%-7.1% variation between different cutter type snow density measurements within snow pit analysis and the long-term utilized snow tube observations show a closer relation to box/cylinder type cutters. As for the continuous SnoTel observations, a variation of 2.4%-9.8% with various cutter types and a 5.9% difference regarding the snow tube density results are detected. These findings indicate a close range among different instruments, but it is the best when all three systems complement each other to characterize the snowpack effectively in the complex terrain since each has its own advantages.
Journal Article
Non-specific and ski-specific performance development in peri-pubertal cross-country skiers
PurposeTo evaluate non-specific and ski-specific performance development in male (M) and female (F) peri-pubertal cross-country skiers and to evaluate their relationship with cross-country skiing (XCS) performance and biological maturation within each age category and sex.MethodsTwenty-one and 19 athletes under 14 and 16 years old, respectively (U14 and U16), were tested for biological maturation; non-specific speed, agility, strength, endurance, and balance; ski-specific speed, agility, and endurance. XCS index was considered as average percentage time-gap from the winner in four official races. Sex and age-category effects were verified and a model predicting XCS index was extrapolated for each group.ResultsPerformance capacities raised across age categories (p < 0.05) except for non-specific speed, agility, balance, and relative arm strength (p > 0.05). F showed advanced biological maturation and greater balance than M (p < 0.05), while M showed higher performance capacities (p < 0.05). XCS index was not related to biological maturation within each group (p > 0.05); its variance was explained by non-specific speed and ski-specific upper-body endurance in M-U14 (p = 0.014), lower-limb strength and ski-specific agility in M-U16 and F-U14 (both p = 0.001), ski-specific upper-body endurance in F-U16 (p = 0.002).ConclusionSki-specific performance capacities still develop during peri-puberty, with peri-pubertal M overperforming with respect to F of comparable performance level. XCS index was not influenced by biological maturation withing each age category, but it was rather explained by specific parameters that commonly undergo the “adolescent spurts”, accordingly to the average biological maturation level of M and F athletes of each age category.
Journal Article
Review of Snow Data Assimilation Methods for Hydrological, Land Surface, Meteorological and Climate Models: Results from a COST HarmoSnow Survey
The European Cooperation in Science and Technology (COST) Action ES1404 “HarmoSnow”, entitled, “A European network for a harmonized monitoring of snow for the benefit of climate change scenarios, hydrology and numerical weather prediction” (2014-2018) aims to coordinate efforts in Europe to harmonize approaches to validation, and methodologies of snow measurement practices, instrumentation, algorithms and data assimilation (DA) techniques. One of the key objectives of the action was “Advance the application of snow DA in numerical weather prediction (NWP) and hydrological models and show its benefit for weather and hydrological forecasting as well as other applications.” This paper reviews approaches used for assimilation of snow measurements such as remotely sensed and in situ observations into hydrological, land surface, meteorological and climate models based on a COST HarmoSnow survey exploring the common practices on the use of snow observation data in different modeling environments. The aim is to assess the current situation and understand the diversity of usage of snow observations in DA, forcing, monitoring, validation, or verification within NWP, hydrology, snow and climate models. Based on the responses from the community to the questionnaire and on literature review the status and requirements for the future evolution of conventional snow observations from national networks and satellite products, for data assimilation and model validation are derived and suggestions are formulated towards standardized and improved usage of snow observation data in snow DA. Results of the conducted survey showed that there is a fit between the snow macro-physical variables required for snow DA and those provided by the measurement networks, instruments, and techniques. Data availability and resources to integrate the data in the model environment are identified as the current barriers and limitations for the use of new or upcoming snow data sources. Broadening resources to integrate enhanced snow data would promote the future plans to make use of them in all model environments.
Journal Article
Value of information analysis of snow measurements for the scheduling of hydropower production
The scheduling of a hydropower plant is challenging because of inflow uncertainty. During spring there is increased uncertainty when the snow melts. By gathering snow measurements, one learns more about the future inflow, and this might lead to lower spillage risk or higher efficiency. In this paper the value of information of snow measurements is studied. The value of information is representative of how much a test is worth. If the price of acquiring and processing snow measurements is less than the value of information, the test is worth doing. The notion of value of information is also useful for comparing various kinds of snow measurements in different situations. For scheduling a least squares Monte Carlo method is used in this paper. The uncertain inflow is represented by discrete scenarios, while the time-varying spot price is assumed known. Data from a Norwegian power plant are used to fit the inflow and snow distributions as well as prices, water reservoir limits and production release alternatives. The numerical tests show that snow measurements have little value when the reservoir is large compared to the total inflow. When the reservoir is smaller, the probability of overflow is bigger, and the snow measurements can be valuable for the scheduling when the data have high accuracy. The increase in value by using the snow measurements is between 0 and 10% in the different parameter settings considered here.
Journal Article
An Integrated Approach for Site Selection of Snow Measurement Stations
Snowmelt provides a reliable water resource for meeting domestic, agricultural, industrial and hydropower demands. Consequently, estimating the available snow water equivalent is essential for water resource management of snowy regions. Due to the spatiotemporal variability of the snowfall pattern in mountainous areas and difficult access to high altitudes areas, snow measurement is one of the most challenging hydro-meteorological data collection efforts. Development of an optimum snow measurement network is a complex task that requires integration of meteorological, hydrological, physiographical and economic studies. In this study, site selection of snow measurement stations is carried out through an integrated process using observed snow course data and analysis of historical snow cover images from National Oceanic Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) at both regional and local scales. Several important meteorological and hydrological factors, such as monthly and annual rainfall distribution, spatial distribution of average frequency of snow observation (FSO) for two periods of snow falling and melting season, as well as priority contribution of sub-basins to annual snowmelt runoff are considered for selecting optimum station network. The FSO maps representing accumulation of snowfall during falling months and snowpack persistence during melting months are prepared in the GIS based on NOAA-AVHRR historical snow cover images. Basins are partitioned into 250 m elevation intervals such that within each interval, establishment of new stations or relocation/removing of the existing stations were proposed. The decision is made on the basis of the combination of meteorological, hydrological and satellite information. Economic aspects and road access constraints are also considered in determining the station type. Eventually, for the study area encompassing a number of large basins in southwest of Iran, several new stations and relocation of some existing stations are proposed.
Journal Article
Estimation of Avalanche Development and Frontal Velocities Based on the Spectrogram of the Seismic Signals Generated at the Vallée de la Sionne Test Site
The changes in the seismic signals generated by avalanches recorded at three sites along a path at the Vallée de la Sionne (VdlS) experimental site are presented. We discuss and correlate the differences in the duration, signal amplitudes, and frequency content of the sections (Signal ONset (ON), Signal Body (SBO), and Signal TAil and Signal ENd STA-SEN) of the spectrograms with the evolution of the powder, transitional and wet snow avalanches along a path. The development of the avalanche front was quantified using the exponential function in time F (t) = K’ exp (β t) fitted to the shape of the signal ONset (SON section of the spectrogram. The speed of the avalanche front is contained in β. To this end, a new method was developed. The three seismic components were converted into one seismic component (FS), when expressing the vector in polar coordinates. We linked the theoretical function of the shape of the FS-SON section of the spectrogram to the numerical coefficients of its shape after considering the spectrogram as an image. This allowed us to obtain the coefficients K’ and β. For this purpose, the Hough Transform (HT) was applied to the image. The values of the resulting coefficients K’ and β are included in different ranges in accordance with the three types of avalanche. Curves created with these coefficients enable us to estimate the development of the different avalanche types along the path. Our results show the feasibility of classifying the type of avalanche through these coefficients. Average speeds of the avalanches approaching the recording sites were estimated. The speed values of wet and transitional avalanches are consistent with those derived from GEODAR (GEOphysical Doppler radAR) measurements, when available. The absence of agreement in the speed values obtained from seismic signals and GEODAR measurements for powder snow avalanches indicates, for this type of avalanche, a different source of the measured signal. Hence, the use of the two measuring systems proves to be complementary.
Journal Article
Evaluation of the Antarctic Mesoscale Prediction System based on snow accumulation observations over the Ross Ice Shelf
Recent snow height measurements (2008–15) from nine automatic weather stations (AWSs) on the Ross Ice Shelf are used to examine the synoptic and seasonal variability in snow accumulation, and also to evaluate the performance of the Antarctic Mesoscale Prediction System (AMPS) for precipitation. The number of snow accumulation events varies from one station to another between 2008 and 2015, thus demonstrating geographic dependence. The interannual variability in snow accumulation is too high to determine its seasonality based on the current AWS observations with limited time coverage. Comparison between the AMPS and AWS snow height measurements show that approximately 28% of the AWS events are reproduced by AMPS. Furthermore, there are significant correlations between AMPS and AWS coincident event sizes at five stations (p < 0.05). This finding suggests that AMPS has a certain ability to represent actual precipitation events.
Journal Article
Development of Electronic Snow Depth Measurement System using a Digital Image Processing and Digital Sensors
The aim of this paper was to develop electronic snow depth measurement system using on image recognition technology and ultrasonic technology in real-time measurement of snow depth to overcome disadvantages of legacy systems. Images can be continuously analyzed by collecting them using infrared camera, and accurate measurement was made possible using cross line laser insensitive to snow particles. Also, ultrasonic sensor performed an auxiliary role for double and triple reduction of measurement error. Measurement values are transmitted to the monitoring server on a real-time basis, and they are provided through optimized mobile service. This system was arranged to allow for real-time transfer of accurate measurement values under different bad weathers, and accuracy was confirmed by the experimental results.
Journal Article
Six Consecutive Seasons of High‐Resolution Mountain Snow Depth Maps From Satellite Stereo Imagery
Fine‐scale seasonal snow depth observations can improve estimates of snow water equivalent at critical times of year. Airborne lidar is the current gold standard for snow depth measurement, but it involves high costs and relatively limited coverage. Using very‐high‐resolution satellite stereo images from WorldView‐2, WorldView‐3, and Pléiades‐HR 1A/1B, we produced a six‐year time series (2017–2022) of spatially continuous digital elevation models for an 874 km2 study area over Grand Mesa, Colorado. We generated high‐resolution stereo snow depth maps that capture intra‐ and interannual variability and span multiple anomalous years (58%–158% of median peak SNOTEL snow depth). Comparisons with near‐contemporaneous airborne lidar snow depth measurements showed good agreement, with median offset of −0.13 m, precision of 0.19 m and accuracy of 0.31 m. Our results suggest that satellite stereo can provide snow depth observations with the spatiotemporal coverage needed to improve operational forecast models and inform adaptive management strategies. Plain Language Summary Detailed observations of snow depth can help us better understand how much water is stored as snow during important times of the year. We used high‐resolution images from commercial satellites to create detailed maps of snow‐covered surfaces for a study site in Colorado. Using a technique called stereo photogrammetry, we created precise three‐dimensional models of surface elevation from these images. By subtracting a snow‐free summer ground surface model from the winter snow surface models, we estimated snow depth over large areas and multiple years. Our satellite snow depth estimates agreed with snow depth measurements from airborne lidar and field campaigns. This satellite stereo approach helps us understand how mountain snow depth varies from year to year, providing valuable information to improve models and decisions for water resources management. Key Points Satellite stereo photogrammetry offers repeat, spatially continuous, high‐resolution snow depth measurements over large areas Stereo snow depth measurements are within ∼0.13–0.33 m of near‐contemporaneous airborne lidar and in situ measurements Stereo snow depth captures detailed intra‐ and interannual snow depth variability in low and high snow years
Journal Article