Ninth International Conference on Permafrost ... - IARC Research

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Mountain Permafrost Parameters Simulated by Regional Climate ModelsNadine SalzmannNational Center for Atmospheric Research (NCAR/ISSE), Boulder, CO, USAChristian HauckInstitute for Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), GermanyLinda O. MearnsNational Center for Atmospheric Research (NCAR/ISSE), Boulder, CO, USAIntroductionPermafrost as a thermal phenomenon is strongly affected bythe changes in the atmospheric condition (Haeberli & Beniston1998). However, for a significant time of the year the seasonalsnow cover decouples the ground from the atmosphereand thus considerably influences the ground thermal regime(Zhang 2005). As a consequence, permafrost conditions areaffected by climatic change twofold: directly by changes inthe atmospheric condition, and indirectly by the changes inthe duration and dynamics of the seasonal snow cover. Thesensitivity of permafrost on these two interacting variables isnot clear in detail so far, and neither is how the atmosphereand thus also the seasonal snow cover will change.Snow accumulation and snowmelt in mountain topographyhave nonuniform and high spatial variability mainly causedby the local topography, which interacts among others withatmospheric stability, precipitation, moisture distribution,radiation, wind and avalanches. Measuring and modelingof snow parameters in complex mountain topography isthus a challenging task. Among the most promising tools tosimulate climate variables in mountain areas are RegionalClimate Models (Leung & Qian 2003). Due to their higherspatial resolution compared to GCM, they better resolvethe atmospheric dynamics caused by the heterogeneoussurfaces such as mountain topographies. The benefits ofusing RCM simulations for permafrost modeling in complexhigh mountain topography have been demonstrated bySalzmann et al. 2007a,b. However, the performance of snowrepresentation in RCMs related to permafrost has not beenvalidated in detail so far and most likely differs for differentregions and models.With large projects such as NARCCAP in North Americaor PRUDENCE and ENSEMBLES in Europe, there isnow increasing RCM output available for further use bythe impact community. However, the performance of thesemodel outputs must be proven for specific applicationsbecause model performance is not simply transferablebetween variables and regions.This study aims at investigating the performance of RCMsto simulate seasonal snow cover in mountain environments,with regard on further modeling of subsurface processes.Study Site and DataStudy siteWe focus on a relatively small area (about 500 km2)in the Colorado Rocky Mountains—the Upper ColoradoRiver Basin (UCRB). This basin is surrounded by someof the highest peaks of the Rocky Mountains. Because thestreamflow of this area is a major contributor to the ColoradoRiver’s annual run off, this area is relatively well equippedwith snow measurement stations (see next section).DataAll RCM simulations used in this study have beenperformed within the North American Regional ClimateChange Program NARCCAP (http://www.narccap.ucar.edu/). Here, we analyze only NCEP-Reanalyses driven runs,since they allow us to compare the RCM output directly withobservations. They are all run with a grid spacing of 50 kmand cover the UCRB by 10 grid boxes. The following RCMsimulations are used here:• ECPC (Experimental Climate Prediction Center):Scripps Institution of Oceanography, La Jolla, CA, USA.• MRCC (Modèle Régional Canadien du Climat):Ouranos Consortium, Montreal (Quebec), Canada.• RegCM3 (REGional Climate Model): UC Santa Cruz,ITCP, USA.The observations we use are point measurement fromSNOTEL stations. There are 45 stations located in theUCRB, many of them providing data since 1981.In addition to the SNOTEL data, we use high-resolutionreanalyses (NARR; North American Regional Reanalyses)for comparison purposes. NARR has a grid spacing of 32km and covers UCRB by 26 grid boxes. NARR data aresupposed to be especially valuable for hydrological studies.First AnalysisWe have analyzed the total volume of accumulatedprecipitation for the individual grid boxes and the average ofall grid boxes covering the UCRB. The RCM outputs werecompared to SNOTEL and NARR data. The total volumeof accumulated precipitation and their temporal distributionshowed overall good agreement.We also compared the 2 m air temperature. The NARCCAPruns simulated generally higher air temperature than NARR,and particularly than SNOTEL.The results for the annual snow cycles for two time periodsare shown in the following Figures. Most obvious are thedeviations between NARCCAP (and NARR!) and SNOTEL.Some of these deviations can certainly be explained by gridelevation differences between NARCCAP and SNOTEL,which is also apparent from air temperature, where263
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 tAcknowledgmentsThis study is financially supported by the Swiss NationalScience Foundation’s program for prospect researcher.We acknowledge the NARCCAP modeling groups forproviding us preliminary simulation results.NARR data are provided by the NOAA/OAR/ESRL PSD,Boulder, Colorado, USA, http://www.cdc.noaa.gov/SNOTEL data are provided by Natural ResourcesConservation Service, United States Department ofAgriculture.Figure 1.Figure 2.SNOTEL overall shows lowest temperatures. Furthermore,the SNOTEL sites are generally located where the snowpack lasts long. Therefore, it can be assumed that SNOTELobservations slightly overestimate SWE relatively to theaverage of SWE over the whole region of the UCRB. Also,RegCM3 produces small SWE values in each year, whichpartly can be explained by the too-high air temperature thatis simulated by RegCM3 (not shown).ReferencesHaeberli, W. & Beniston, M. 1998. Climate change and itsimpact on glaciers and permafrost in the Alps. Ambio27(4): 258-265.Jansson, P.-E. & Karlberg, L. 2004. Coupled Heat and MassTransfer Model for Soil-Plant-Atmosphere Systems.Stockholm: Royal Institute of Technolgy, Dept. ofCivl and Environmental Engineering, 435 pp.Leung, L.R. & Qian, Y. 2003. The sensitivity of precipitationand snowpack simulations to model resolutionvia nesting in regions of complex terrain. J.Hydrometerology 4: 1025-1043.Salzmann, N., Frei, C., Vidale, P.L. & Hoelzle, M. 2007a.The application of Regional Climate Model outputfor the simulation of high-mountain permafrostscenarios. Global and Planetary Change 56: 188-202, doi:10.1016/j.gloplacha.2006.07.006.Salzmann, N., Noetzli, J., Hauck, C., Gruber, S., Hoelzle, M.& Haeberli, W. 2007b. Ground-surface temperaturescenarios in complex high-mountain topographiesbased on Regional Climate Model results. Journal ofGeophysical Research–Earth Surface 112: F02S12,doi:10.1029/2006JF000527.Zhang, T. 2005. Influence of the seasonal snow cover on theground thermal regime: an overview. Rev. Geophys.43: RG4002, doi:10.1029/2004RG000157.PerspectivesFor permafrost, among the most significant parametersof the seasonal snow cover are the timing and duration ofsignificant snow depth. Therefore, in a next step, we willcompare the duration of the seasonal snow cover and try toassociate the deviations to model intern explanations (e.g.,air temperature). Furthermore, we will apply the time seriesof the RCM simulations as input for a water/heat-coupledsoil model (COUP; Janson & Karlberg 2004) to simulateground surface temperatures, which are not provided by theNARCCAP outputs. Similar analyses are planned for theSchilthorn area in the Swiss Alps with RCM simulationsfrom the PRUDENCE and ENSEMBLES projects.264
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ContentsPreface ...................
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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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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
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Acoustical Surveys of Methane Plume
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Permafrost Delineation Near Fairban
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Preparatory Work for a Permanent Ge
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A Provisional Soil Map of the Trans
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Martian Permafrost Depths from Orbi
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Time Series Analyses of Active Micr
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Impact of Permafrost Degradation on
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DC Resistivity Soundings Across a P
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Modeling Thermal and Moisture Regim
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A Provisional Permafrost Map of the
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Alpine Permafrost Distribution at M
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Cryogenic Formations of the Caucasu
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Modeling Potential Climatic Change
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A Hypothesis: A Condition of Growth
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Modeled Continual Surface Water Sto
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Freeze/Thaw Properties of Tundra So
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Discontinuous Permafrost Distributi
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Thermal Regime Within an Arctic Was
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Seasonal and Interannual Variabilit
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Twelve-Year Thaw Progression Data f
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Continued Permafrost Warming in Nor
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Landsliding Following Forest Fire o
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A Permafrost Model Incorporating Dy
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Seasonal Sources of Soil Respiratio
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Greenland Permafrost Temperature Si
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The Importance of Snow Cover Evolut
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The Account of Long-Term Air Temper
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The Combined Isotopic Analysis of L
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Adaptating and Managing Nunavik’s
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Human Experience of Cryospheric Cha
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HiRISE Observations of Fractured Mo
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A Soil Freeze-Thaw Model Through th
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Mapping and Modeling the Distributi
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First Results of Ground Surface Tem
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Historical Changes in the Seasonall
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Rock Glaciers in the Kåfjord Area,
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Snowpack Evolution on Permafrost, N
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Climate Change in Permafrost Region
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Maximizing Construction Season in a
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Pleistocene Sand-Wedge, Composite-W
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