scholarly journals A differential emissivity imaging technique for measuring hydrometeor mass and type

2021 ◽  
Author(s):  
Dhiraj K. Singh ◽  
Spencer Donovan ◽  
Eric R. Pardyjak ◽  
Timothy J. Garrett
Keyword(s):  
Heat Loss ◽  
Snow Water Equivalent ◽  
Infrared Camera ◽  
Metal Plate ◽  
Thermal Emissivity ◽  
Spatial Dimensions ◽  
Mass Size ◽  
Snow Water ◽  
The Difference ◽  
Heated Metal

Abstract. The Differential Emissivity Imaging Disdrometer (DEID) is a new evaporation-based optical and thermal instrument designed to measure the mass, size, density, and type of individual hydrometeors and their bulk properties. Hydrometeor spatial dimensions are measured on a heated metal plate using an infrared camera by exploiting the much higher thermal emissivity of water compared with metal. As a melted hydrometeor evaporates, its mass can be directly related to the loss of heat from the hotplate assuming energy conservation across the hydrometeor. The heat-loss required to evaporate a hydrometeor is found to be independent of environmental conditions including ambient wind velocity, moisture level, and temperature. The difference in heat loss for snow versus rain for a given mass offers a method for discriminating precipitation phase. The DEID measures hydrometeors at sampling frequencies up to 1 Hz with masses and effective diameters greater than 1 µg and 200 µm, respectively, determined by the size of the hotplate and the thermal camera specifications. Measurable snow water equivalent (SWE) precipitation rates range from 0.001 to 200 mm h−1, as validated against a standard weighing bucket. Preliminary field-experiment measurements of snow and rain from the winters of 2019 and 2020 provided continuous automated measurements of precipitation rate, snow density, and visibility. Measured hydrometeor size distributions agree well with canonical results described in the literature.

scholarly journals Influence of snow ablation and frozen ground on spring runoff generation in the Mogot Experimental Watershed, southern mountainous taiga of eastern Siberia

2006 ◽  
Vol 37 (1) ◽  
pp. 21-29 ◽  
Author(s):  
Kazuyoshi Suzuki ◽  
Jumpei Kubota ◽  
Tetsuo Ohata ◽  
Valery Vuglinsky
Keyword(s):  
Soil Moisture ◽  
Snow Water Equivalent ◽  
Soil Surface ◽  
Eastern Siberia ◽  
Snowmelt Runoff ◽  
Runoff Generation ◽  
Frozen Ground ◽  
Spring Runoff ◽  
Snow Water ◽  
The Difference

Snowmelt runoff is one of the most important discharge events in the southern mountainous taiga of eastern Siberia. The present study was conducted in order to understand the interannual variations in snowmelt infiltration into the frozen ground and in snowmelt runoff generation during the snowmelt period in the southern mountainous taiga in eastern Siberia. Analysis of the obtained data revealed the following: (1) snowmelt infiltration into the top 20 cm of frozen ground is important for evaluating snowmelt runoff generation because frozen ground absorbed from 22.9% (WY1983) to 61.5% (WY1981) of the maximum snow water equivalent. The difference in snowmelt infiltration for the two years appears to have been caused by the difference in snowmelt runoff generation; (2) the snowmelt runoff ratio increased with (i) increase in the fall soil moisture just before the soil surface froze and (ii) increase in the maximum snow water equivalent. The above results imply that the parameters governing snowmelt infiltration in the boreal taiga region in eastern Siberia are fall soil moisture and the maximum snow water equivalent, as is the case in the simple model presented by Gray et al.

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 Utility of late summer transient snowline migration rate on Taku Glacier, Alaska

2011 ◽  
Vol 5 (3) ◽  
pp. 1365-1382
Author(s):  
M. Pelto
Keyword(s):  
Mass Balance ◽  
Migration Rate ◽  
Snow Water Equivalent ◽  
Late Summer ◽  
Ablation Rate ◽  
Field Observations ◽  
Snow Water ◽  
The Mean ◽  
The Difference ◽  
Thematic Mapper Imagery

Abstract. On Taku Glacier, Alaska a combination of field observations of snow water equivalent (SWE) from snowpits and probing in the vicinity of the transient snowline (TSL) are used to quantify the mass balance gradient. The balance gradient is determined from the difference in elevation and SWE from the TSL to snowpits at 1000 m from 1998–2010 and ranges from 2.6–3.8 mm m−1. Probing transects from 950 m–1100 m directly measure SWE and yield a slightly higher balance gradient of 3.3–3.8 mm m−1. TSL is identified in MODIS and Landsat 4 and 7 Thematic Mapper imagery for 31 dates during the 2004–2010 period on Taku Glacier to assess the consistency of its rate of rise and usefulness in assessing mass balance. In 2010, the TSL rose from 750 m on 28 July, 800 m on 5 August, 875 m on 14 August, 925 m on 30 August, and to 975 m on 20 September. The mean observed probing balance gradient was 3.3 mm m−1 and TSL rise was 3.7 m day−1, yielding an ablation rate of 12.2 mm day−1 on Taku Glacier from mid-July to mid-September. A comparison of the TSL rise in the region from 750–1100 m on Taku Glacier during eleven different periods of more than 14 days during the ablation season with repeat imagery indicates a mean TSL rise of 3.7 m day−1 on Taku Glacier, the rate of rise is relatively consistent ranging from 3.0 to 4.8 m day−1. This is useful for ascertaining the final ELA if imagery or observations are not available within a week or two of the end of the ablation season. From mid-July-mid-September the mean ablation from 750–1100 m determined from the TSL rise and the observed balance gradient varied from 11 to 18 mm day−1 on Taku Glacier during the 2004–2010 period.

scholarly journals Converting snow depth to snow water equivalent using climatological variables

2019 ◽  
Vol 13 (7) ◽  
pp. 1767-1784 ◽  
Author(s):  
David F. Hill ◽  
Elizabeth A. Burakowski ◽  
Ryan L. Crumley ◽  
Julia Keon ◽  
J. Michelle Hu ◽  
...  
Keyword(s):  
Snow Depth ◽  
Snow Water Equivalent ◽  
Mean Squared Error ◽  
Weather Data ◽  
Validation Data ◽  
Simple Method ◽  
Avalanche Forecasting ◽  
Mean Temperature ◽  
Snow Water ◽  
The Difference

Abstract. We present a simple method that allows snow depth measurements to be converted to snow water equivalent (SWE) estimates. These estimates are useful to individuals interested in water resources, ecological function, and avalanche forecasting. They can also be assimilated into models to help improve predictions of total water volumes over large regions. The conversion of depth to SWE is particularly valuable since snow depth measurements are far more numerous than costlier and more complex SWE measurements. Our model regresses SWE against snow depth (h), day of water year (DOY) and climatological (30-year normal) values for winter (December, January, February) precipitation (PPTWT), and the difference (TD) between mean temperature of the warmest month and mean temperature of the coldest month, producing a power-law relationship. Relying on climatological normals rather than weather data for a given year allows our model to be applied at measurement sites lacking a weather station. Separate equations are obtained for the accumulation and the ablation phases of the snowpack. The model is validated against a large database of snow pillow measurements and yields a bias in SWE of less than 2 mm and a root-mean-squared error (RMSE) in SWE of less than 60 mm. The model is additionally validated against two completely independent sets of data: one from western North America and one from the northeastern United States. Finally, the results are compared with three other models for bulk density that have varying degrees of complexity and that were built in multiple geographic regions. The results show that the model described in this paper has the best performance for the validation data sets.

scholarly journals Analysis of the Snow Water Equivalent at the AEMet-Formigal Field Laboratory (Spanish Pyrenees) During the 2019/2020 Winter Season Using a Stepped-Frequency Continuous Wave Radar (SFCW)

2021 ◽  
Vol 13 (4) ◽  
pp. 616
Author(s):  
Rafael Alonso ◽  
José María García del Pozo ◽  
Samuel T. Buisán ◽  
José Adolfo Álvarez
Keyword(s):  
Software Defined Radio ◽  
Continuous Wave ◽  
Snow Water Equivalent ◽  
Cosmic Ray ◽  
Relative Dielectric Permittivity ◽  
Near Surface ◽  
Wave Radar ◽  
Spanish Pyrenees ◽  
Snow Water ◽  
Stepped Frequency

Snow makes a great contribution to the hydrological cycle in cold regions. The parameter to characterize available the water from the snow cover is the well-known snow water equivalent (SWE). This paper presents a near-surface-based radar for determining the SWE from the measured complex spectral reflectance of the snowpack. The method is based in a stepped-frequency continuous wave radar (SFCW), implemented in a coherent software defined radio (SDR), in the range from 150 MHz to 6 GHz. An electromagnetic model to solve the electromagnetic reflectance of a snowpack, including the frequency and wetness dependence of the complex relative dielectric permittivity of snow layers, is shown. Using the previous model, an approximated method to calculate the SWE is proposed. The results are presented and compared with those provided by a cosmic-ray neutron SWE gauge over the 2019–2020 winter in the experimental AEMet Formigal-Sarrios test site. This experimental field is located in the Spanish Pyrenees at an elevation of 1800 m a.s.l. The results suggest the viability of the approximate method. Finally, the feasibility of an auxiliary snow height measurement sensor based on a 120 GHz frequency modulated continuous wave (FMCW) radar sensor, is shown.

scholarly journals The Spatiotemporal Patterns and Interrelationships of Snow Cover and Climate Change in Tianshan Mountains

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 404
Author(s):  
Tong Heng ◽  
Xinlin He ◽  
Lili Yang ◽  
Jiawen Yu ◽  
Yulin Yang ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Warming Trend ◽  
Tianshan Mountains ◽  
Spatiotemporal Patterns ◽  
Tianshan Mountain ◽  
Mountainous Areas ◽  
The Future ◽  
Snow Water ◽  
Nighttime Warming

To reveal the spatiotemporal patterns of the asymmetry in the Tianshan mountains’ climatic warming, in this study, we analyzed climate and MODIS snow cover data (2001–2019). The change trends of asymmetrical warming, snow depth (SD), snow coverage percentage (SCP), snow cover days (SCD) and snow water equivalent (SWE) in the Tianshan mountains were quantitatively determined, and the influence of asymmetrical warming on the snow cover activity of the Tianshan mountains were discussed. The results showed that the nighttime warming rate (0.10 °C per decade) was greater than the daytime, and that the asymmetrical warming trend may accelerate in the future. The SCP of Tianshan mountain has reduced by 0.9%. This means that for each 0.1 °C increase in temperature, the area of snow cover will reduce by 5.9 km2. About 60% of the region’s daytime warming was positively related to SD and SWE, and about 48% of the region’s nighttime warming was negatively related to SD and SWE. Temperature increases were concentrated mainly in the Pamir Plateau southwest of Tianshan at high altitudes and in the Turpan and Hami basins in the east. In the future, the western and eastern mountainous areas of the Tianshan will continue to show a warming trend, while the central mountainous areas of the Tianshan mountains will mainly show a cooling trend.

scholarly journals Seasonal Estimates and Uncertainties of Snow Accumulation from CloudSat Precipitation Retrievals

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 363
Author(s):  
George Duffy ◽  
Fraser King ◽  
Ralf Bennartz ◽  
Christopher G. Fletcher
Keyword(s):  
Time Scales ◽  
Snow Water Equivalent ◽  
Spatial Scales ◽  
Snow Accumulation ◽  
High Latitudes ◽  
Percentage Points ◽  
Snow Water ◽  
Time Periods ◽  
Predicted Values ◽  
Good Agreement

CloudSat is often the only measurement of snowfall rate available at high latitudes, making it a valuable tool for understanding snow climatology. The capability of CloudSat to provide information on seasonal and subseasonal time scales, however, has yet to be explored. In this study, we use subsampled reanalysis estimates to predict the uncertainties of CloudSat snow water equivalent (SWE) accumulation measurements at various space and time resolutions. An idealized/simulated subsampling model predicts that CloudSat may provide seasonal SWE estimates with median percent errors below 50% at spatial scales as small as 2° × 2°. By converting these predictions to percent differences, we can evaluate CloudSat snowfall accumulations against a blend of gridded SWE measurements during frozen time periods. Our predictions are in good agreement with results. The 25th, 50th, and 75th percentiles of the percent differences between the two measurements all match predicted values within eight percentage points. We interpret these results to suggest that CloudSat snowfall estimates are in sufficient agreement with other, thoroughly vetted, gridded SWE products. This implies that CloudSat may provide useful estimates of snow accumulation over remote regions within seasonal time scales.

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