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.

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