Ninth International Conference on Permafrost ... - IARC Research

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The Importance of Snow Cover Evolution in Rock Glacier Temperature ModelingMatteo DallAmicoDepartment of Civil and Environmental Engineering, University of Trento, ItalyStefano EndrizziDepartment of Civil and Environmental Engineering, University of Trento, ItalyRiccardo RigonDepartment of Civil and Environmental Engineering, University of Trento, ItalyStephan GruberDepartment of Physical Geography, University of Zurich, SwitzerlandIntroductionThe snow cover evolution is one of the crucial factorsaffecting the thermal and hydraulic regime of rock glaciers(Mittaz et al. 2000), as snow strongly controls soil energybalance through its high albedo and insulating properties.Therefore, accurate modeling of the snowpack is absolutelynecessary to reliably describe soil temperatures. Theimportance of accurate snow modeling entails the use ofsophisticated models based on the solution of the snow energybalance and, consequently, on a good parameterization ofradiation and turbulent fluxes (e.g., Jordan 1991). An advanceor delay in estimating the time of snow disappearance wouldcause a strong error in the calculation of the energy balanceat the soil surface, altering the ground heating or freezingand, therefore, affecting the soil temperature profile for thewhole summer.The goal of this work is to simulate and discuss the rockglacier snow evolution in order to analyze the influenceof the snow cover and accumulation/melting time on thetemperature regime of the active layer of a rock glacier.Modeling Features and Case StudyThe model used in the simulation is GEOtop (Rigon etal. 2006), a distributed physically-based model which jointlysolves the energy and water balance of soil (Bertoldi et al.2006) and snow (Zanotti et al. 2004), and accounts for thegeotechnical parameters of unsaturated soils affecting slopestability (Simoni et al. 2007). The model has been improvedrecently to include a correct treatment of frozen soil (Endrizziet al. 2008) and to model snow with a multilayer schemecapable of describing snow metamorphism and watercirculation and refreezing in the snowpack (Endrizzi 2007).Commonly, in alpine climates the soil exchanges heatdirectly with the atmosphere only in a short time window,roughly spanning from June to October, whereas duringwinter and early spring, heat transfer between soil and atmosphereis mediated by the snowpack. Consequently, the heatflux reaching the soil surface is strongly reduced due to highsnow albedo, which reduces net energy input, and to snowinsulating properties, which cause heat conduction to be verysmall below the upper snow layers. In fact, the snow energybalance equation can be written as follows (Oke 1990):∆Q S+∆Q M= R n+ P − H − L − G [W/m 2 ] (1)where the terms in the left-hand side (LHS) represent the heatstorage rate in the snowpack due to sensible heat (∆SQ S) andto latent heat (∆Q M, melting/refreezing and rain on snow). Inthe right-hand side (RHS), R nis the net all-wave radiation,P is the sensible heat flux supplied by precipitation, Hand L are, respectively, the sensible and latent heat fluxesexchanged between the surface (be it snow or soil) and theatmosphere, and G is the heat flux reaching the soil surfaceacting as soil energy input. When the ground is snow-free,the LHS in equation (1) is null, and G is equal to the net∆Q energy S+∆Q flux M exchanged = R n+ Pwith − Hthe − Latmosphere. − G [W/m On 2 ] the other (1)hand, for snow covered ground, G is proportional to thetemperature gradient at the snow-soil interface, namely:G sn=−KT sn− T S1(D + D ) [W/m 2 ] (2)2 sn Swhere K is the snow-soil averaged thermal conductivitycalculated as a harmonic mean, T snis snow temperaturein the layer close to the soil surface, T Sis the soil surfacetemperature, and D snand D Sare the depths of the snow andsurface layer, respectively.Investigated siteSimulations have been carried out on the active rockglacier Murtèl (Upper Engadin, Swiss Alps: 46°26′N,9°49.5′E, 2670 m a.s.l., 15° slope with NW aspect) in whichthe oldest temperature time series of Alpine Permafrost hasbeen measured (Vonder Mühll & Haeberli 1990, Hoelzle etal. 1999). Input data include incoming shortwave radiation(both direct and diffuse), incoming longwave radiation, airtemperature, wind speed and direction, air pressure, andprecipitation.Simulations and ResultsThe simulation spans a period of two hydrological yearsbeginning from October 1997. As the first snowfall normallyoccurs in November, this choice allows the avoidance of theproblem of determining the initial condition of snow on thesurface. Most of the parameters used by the snow model ofGEOtop were simply taken from literature, for example,snow reflectance and snow thermal and hydraulic properties.As only total precipitation was available, the calibration wasreduced to the definition of the threshold air temperaturesabove (below), where precipitation is considered to occur asrain (snow).57G sn=−K1T sn− T S[W/m 2 ] (2)
Ni n t h In t e r n at i o n a l Co n f e r e n c e o n Pe r m a f r o s tConclusionsThe work shows that the model is capable of reproducingthe evolution of the snow cover and the temperatures in theactive layer of the rock glacier. Snow evolution, together withthe thermal and hydraulic parameters (DallAmico et al. submitted),is a crucial process to take into consideration whenthe thermal regime of an active layer is to be modeled. A properrepresentation of the snow evolution can provide the righttime window of direct soil exposure to solar radiation and, inturn, a reliable quantification of the soil energy fluxes. Conversely,a poor representation may lead to significant errorsthat propagate and increase the deeper we go in the ground.Figure 1. Simulated vs. measured snow depth and energy fluxinput to the ground in the Murtèl rock glacier.Figure 2. The error in temperature profile depends on snow modelingand becomes bigger the deeper in the ground. “Proper” and “Poor”refer to real measures and delayed modeling, respectivelyAs can be seen in Figure 1, the model proves to simulatewell both the snow depth and the time when snow iscompletely ablated. The heat flux reaching the soil surfaceclearly depends on snow presence. When soil is snow free,the flux is of the order of 50 W/m 2 , but it can drop by anorder of magnitude or more when snow is present.A delay (anticipation) in the estimation of the snow covercomplete ablation date may lead to an underestimation(overestimation) of the ground surface temperature and ofthe temperature profile of the layers below. For example,in Figure 2 the temperature behavior at the soil surface andat 55 cm depth during the snow melting period is reported,considering a “proper” snow simulation (full grey line) anda “poor” delayed snow simulation (dotted grey line). Thesurface temperature increases as the snow is melted, andthe delay between the two scenarios is disappear after fewdays. At 55 cm depth, instead, the delay in the temperatureevolution is still visible after one month, indicating that theerror in snow model will propagate and increase as we godeeper in the soil.ReferencesBertoldi, G., Rigon, R. & Over, T.M. 2006. Impact ofwatershed geomorphic characteristics on the energyand water budgets. J. Hydrometeorology 7: 389-403.DallAmico, M., Endrizzi, S., Rigon, R. & Gruber, S.Submitted. Modelling the thermal regime of a rockglacier active layer using GEOtop. Proceedings ofthe <strong>Ninth</strong> <strong>International</strong> <strong>Conference</strong> on Permafrost,Fairbanks, Alaska, June 29–July 3, 2008.Endrizzi, S. 2007. Snow cover modeling at local and distributedscale over complex terrain. Ph.D. dissertation.Dept. of Civil and Environmental Engineering, Universityof Trento, Italy.Endrizzi, S., Rigon, R. & DallAmico, M. 2008. A soil freeze/thaw model through the soil water characteristic curve.Extended Abstracts, <strong>Ninth</strong> <strong>International</strong> <strong>Conference</strong> onPermafrost, Fairbanks, Alaska, June 29–July 3, 2008.Hoelzle, M., Wegman, M. & Krummenacher, B. 1999.Miniature temperature dataloggers for mapping andmonitoring of permafrost in high mountain areas:first experience from the Swiss Alps. Permafrost andPeriglacial Processes 10: 113-124Jordan R. 1991 A one-dimensional temperature model for asnow cover. Technical documentation for SNTHERM89. CRREL, Hanover, NH, USA.Mittaz, C., Hoelzle, M. & Haeberli, W. 2000. First results andinterpretation of energy-flux measurements of Alpinepermafrost. Annals of Glaciology 31: 275-280.Oke, T.R. 1990. Boundary Layer Climates. Routledge.Rigon, R., Bertoldi, G. & Over, T.M. 2006. GEOtop: Adistributed hydrological model with coupled waterand energy budgets. J. of Hydromet. 7: 371-388.Simoni, S., Zanotti, F., Bertoldi, G. & Rigon, R. 2007.Modelling the probability of occurrence of shallowlandslides and channelized debris flows usingGEOtop-FS. Hydrological. Processes.Vonder Mühll, D. & Haeberli, W. 1990. Thermal characteristicsof the permafrost within an active rock glacier(Murtèl/Corvatsch, Grisons, Swiss Alps). Journal ofGlaciology 36(123): 151-158.Zanotti F., Endrizzi, S., Bertoldi, G. & Rigon, R. 2004. TheGEOTOP snow module. Hydrological. Processes 18:3667-3679. doi:10.1002/hyp.5794.58
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ContentsPreface ...................
Page 8 and 9:
Mapping and Modeling the Distributi
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Satellite Observations of Frozen Gr
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xiiIce Wedge Thermal Regime in Nort
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xivPermafrost Response to Dynamics
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xvi
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NICOP SponsorsUniversitiesUniversit
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Deep Permafrost Studies at the Lupi
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Effect of Fire on Pond Dynamics in
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Cryological Status of Russian Soils
Page 28 and 29: Acoustical Surveys of Methane Plume
Page 30 and 31: Permafrost Delineation Near Fairban
Page 32 and 33: Preparatory Work for a Permanent Ge
Page 34 and 35: A Provisional Soil Map of the Trans
Page 36 and 37: Martian Permafrost Depths from Orbi
Page 38 and 39: Time Series Analyses of Active Micr
Page 40 and 41: Impact of Permafrost Degradation on
Page 42 and 43: DC Resistivity Soundings Across a P
Page 44 and 45: Modeling Thermal and Moisture Regim
Page 46 and 47: A Provisional Permafrost Map of the
Page 48 and 49: Alpine Permafrost Distribution at M
Page 50 and 51: Cryogenic Formations of the Caucasu
Page 52 and 53: Modeling Potential Climatic Change
Page 54 and 55: A Hypothesis: A Condition of Growth
Page 56 and 57: Modeled Continual Surface Water Sto
Page 58 and 59: Freeze/Thaw Properties of Tundra So
Page 60 and 61: Discontinuous Permafrost Distributi
Page 62 and 63: Thermal Regime Within an Arctic Was
Page 64 and 65: Seasonal and Interannual Variabilit
Page 66 and 67: Twelve-Year Thaw Progression Data f
Page 68 and 69: Continued Permafrost Warming in Nor
Page 70 and 71: Landsliding Following Forest Fire o
Page 72 and 73: A Permafrost Model Incorporating Dy
Page 74 and 75: Seasonal Sources of Soil Respiratio
Page 76 and 77: Greenland Permafrost Temperature Si
Page 80 and 81: The Account of Long-Term Air Temper
Page 82 and 83: The Combined Isotopic Analysis of L
Page 84 and 85: Adaptating and Managing Nunavik’s
Page 86 and 87: Human Experience of Cryospheric Cha
Page 88 and 89: HiRISE Observations of Fractured Mo
Page 90 and 91: A Soil Freeze-Thaw Model Through th
Page 92 and 93: Mapping and Modeling the Distributi
Page 94 and 95: First Results of Ground Surface Tem
Page 96 and 97: Historical Changes in the Seasonall
Page 98 and 99: Rock Glaciers in the Kåfjord Area,
Page 100 and 101: Snowpack Evolution on Permafrost, N
Page 102 and 103: Climate Change in Permafrost Region
Page 104 and 105: Maximizing Construction Season in a
Page 106 and 107: Pleistocene Sand-Wedge, Composite-W
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370Huang, B. 339Hugelius, G. 105, 1
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