scholarly journals Comments on Uncertainty budget in snow thickness and snow water equivalent estimation using GPR and TDR techniques by Di Paolo et al.

2017 ◽  
Author(s):  
Anonymous
Keyword(s):  
Snow Water Equivalent ◽  
Uncertainty Budget ◽  
Snow Water ◽  
Snow Thickness

scholarly journals Uncertainty budget in snow thickness and snow water equivalent estimation using GPR and TDR techniques

2016 ◽  
Author(s):  
Federico Di Paolo ◽  
Barbara Cosciotti ◽  
Sebastian E. Lauro ◽  
Elisabetta Mattei ◽  
Mattia Callegari ◽  
...  
Keyword(s):  
Traditional Method ◽  
Snow Water Equivalent ◽  
Uncertainty Budget ◽  
Radar Data ◽  
Complete Analysis ◽  
Fundamental Parameter ◽  
Non Invasive ◽  
Electromagnetic Methods ◽  
Snow Water ◽  
Snow Thickness

Abstract. Snow water equivalent is a fundamental parameter for hydrological and climate change studies but its measurement is usually time consuming and destructive. Electromagnetic methods could be a valid alternative to conventional techniques, being fast and non-invasive. In this work we analyze the reliability of a combined GPR/TDR method to estimate snow thickness and snow water equivalent. To estimate GPR accuracy we perform a calibration test where measured and predicted radar data are compared in terms of two-way travel time. Furthermore we implement a complete analysis of the uncertainty budget in order to evaluate the "weight" of each uncertainty on the snow parameters computation chain. We found that GPR, supported by TDR data, is quite reliable as it measures snow thickness and snow water equivalent with an accuracy comparable to that of a traditional method but, in general, with a slightly larger uncertainty.

scholarly journals Mass and heat balance of snowpatches in Basen nunatak, Dronning Maud Land, Antarctica, in summer

2013 ◽  
Vol 59 (218) ◽  
pp. 1093-1105 ◽  
Author(s):  
Matti Leppäranta ◽  
Onni Järvinen ◽  
Elisa Lindgren
Keyword(s):  
Heat Balance ◽  
Snow Water Equivalent ◽  
Research Programme ◽  
Surface Energy Flux ◽  
Meltwater Runoff ◽  
Dronning Maud Land ◽  
Snow Water ◽  
Antarctic Research ◽  
The Mean ◽  
Snow Thickness

AbstractAn experimental study concerning the mass and heat balance of snowpatches was performed during the Finnish Antarctic Research Programme (FINNARP) 2004 and 2010 summer expeditions to Basen nunatak (73°03′ S, 13°25′ W). Data were collected from a snow stake line, snow pits and automated weather and snow recording systems. One 100 m perennial snowpatch and several smaller seasonal patches (<10 m) were monitored. Snow thickness decreased by 4.0–6.3 mm d−1 due to sublimation, compression and, close to lateral boundaries, meltwater runoff. The vertical mass loss was 1–2 mm snow water equivalent (SWE) d−1 and the lateral decay was −10 cm d−1. The net radiation was 20.2 W m−2 and the mean latent heat flux was −15.5 W m−2 .The mean surface energy flux was 4.9 W m −2 and the heat loss to the ground was 1.5 W m−2. Thin snow decayed faster due to surface thermomechanical erosion and melt from the bottom where the soil was heated by the solar radiation. Between the summers of 2004 and 2010, the thickness of the perennial snowpatch decreased by 230 mm.

scholarly journals Why Do Global Reanalyses and Land Data Assimilation Products Underestimate Snow Water Equivalent?

2016 ◽  
Vol 17 (11) ◽  
pp. 2743-2761 ◽  
Author(s):  
Patrick D. Broxton ◽  
Xubin Zeng ◽  
Nicholas Dawson
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Snow Water Equivalent ◽  
Primary Reason ◽  
Snow Water ◽  
Land Data Assimilation ◽  
Freezing Temperatures ◽  
Data Assimilation System ◽  
Assimilation System ◽  
Snow Thickness

Abstract There is a large uncertainty of snow water equivalent (SWE) in reanalyses and the Global Land Data Assimilation System (GLDAS), but the primary reason for this uncertainty remains unclear. Here several reanalysis products and GLDAS with different land models are evaluated and the primary reason for their deficiencies are identified using two high-resolution SWE datasets, including the Snow Data Assimilation System product and a new dataset for SWE and snowfall for the conterminous United States (CONUS) that is based on PRISM precipitation and temperature data and constrained with thousands of point snow observations of snowfall and snow thickness. The reanalyses and GLDAS products substantially underestimate SWE in the CONUS compared to the high-resolution SWE data. This occurs irrespective of biases in atmospheric forcing information or differences in model resolution. Furthermore, reanalysis and GLDAS products that predict more snow ablation at near-freezing temperatures have larger underestimates of SWE. Since many of the products do not assimilate information about SWE and snow thickness, this indicates a problem with the implementation of land models and pinpoints the need to improve the treatment of snow ablation in these systems, especially at near-freezing temperatures.

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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