Quantitative interpretation of SMP signals - CGISS

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Quantitative interpretation of SMP signals - CGISS

Quantitative interpretation ofSMP signalsH.P. MarshallBSU, CRRELM. SchneebeliSLFJ. JohnsonCRRELSnow Characterization Workshop, April 13-15, 2009


Emperical Relationships• Textural Index [Schneebeli, Pielmeier,Johnson, 1999, CRST]TI=1.45+5.72 CV


SMP hardnessshows goodagreement handhardness profiles• Serial sectionshows similarboundaries andtexture indextrend makessense


Emperical Relationships• Density [Pielmeier, 2003; Stahli et al, J Glac, 2003]Rho=55.6 * ln(mR)+317.4 [kg/m^3][Marshall, 2005]


Emperical RelationshipsThermal conductivity [Stahli et al, J Glac, 2003; Dadic,Schneebeli, Lehning, Hutterli, Ohmura, in press JGR ]


parameterization of thermal conductivityusing penetration hardness


summit snow profile - top 0.5 mSnowMicroPenshapesizedensityNIP


Summit Temperature100 mm depth 300 mm depthTemperature measuredTemperature simulated 1 mm layer resolutionTemperature simulated 100 mm layer resolution


Summit temperature simulationsimulationlayer thickness100 mm1 mm


Hardness analysis• Spatial variability [e.g. Kronholm,2003,…]• Temporal variability [Birkeland et al,2004, Annals…]• Weak layer thickness [Lutz et al, 2005,CRST]


But SMP has detailedmicrostructural signal


Similar features can be found in nearby profiles,and coincide with layer boundaries from manualprofiles and radar measurements[Marshall, Schneebeli, Koh, 2007, CRST]


Snow under rapid loadingbehaves nearly linear elastically


Mechanical Properties• Physics-based model [Schneebeli &Johnson, 98, Annals; Johnson andSchneebeli, 99, CRST]• Further improvements [Sturm et al, 04(Manali); Marshall and Johnson, in review,JGR]


Basic structural element[Johnson and Schneebeli, 99, CRST]


Multiple structural elementssimultaneously engaged with SMP tip


Simulated signal shows similarstructure to field measurements


Retrieval of microstructural andmicromechanical properties• [Johnson and Schneebeli, 99, CRST]• L,F,delta, k, microscale stress/strain atrupture, microscale elastic modulus• {derivation on board}


Improvement to physical theory• Removed assumption of uniformrandom distribution of elements[Sturm et al, 2004]


Use typical parameters, generateMonte-Carlo, check results


Isolated sources of error, andmade modifications• Overlapping ruptures• Solve exactly for delta• Remove increase in force during rupture(digitization)• Include all force values in calculation


Correction for overlapping ruptures


Accuracy of retrieving L


Accuracy of retrieving f


Accuracy of retrieving delta


Real data is noisy, includes forcevariations not due to ruptures• Rupture force threshold [Johnson and Schneebeli, 99]• Rupture slope threshold [Kronholm et al]• Air signals typically have ruptures ~0.01N


Resulting microstructural parameters aresensitive to snow type


Application to 4 snow types


Application to 8 snow types


Basic statistics


Emperical Models


Basic microstructural parameters


Derived micromechanical parameters


Scaling to macroscale


Scaling Elastic Modulus


Scaling Compressive strength


Macro scale mechanicalproperties important formodeling stress on slope

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