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Masters Thesis Distributed modelling of the energy and mass-balance at the surface of Langenferner, Ortles-Cevedale Group/Italy Diploma Thesis submitted to the Faculty of Geo- and Atmospheric Science University of Innsbruck presented by: Stephan Peter Galos supervised by: Priv.-Doz. Dr. Thomas Mölg Innsbruck, September 2010 für Peter... Abstract In order to study the spatial distribution of surface mass balance and the related surface energy fluxes of an alpine glacier, a physically based 2D-model was applied to Langenferner, Ortles-Cevedale Group/Northern Italy for the period 2004-2008. The model was driven by meteorological data from six permanent automatic weather stations in the vicinity of the glacier. Meteorological data from the stations which are maintained by the Hydrographic Office of the Autonomous Province of Bolzano were extrapolated to the glacier surface using simple transfer functions. The energy and mass balance model was optimized using data from an automatic weather station which was temporarily installed nearby the glacier. To validate the results, the model output was compared to stake measurements and snow probing data from the glacier. Modelled annual mean specific mass balance showed a sufficient accordance to the measurements at Langenferner except for the hydrological year 2007/2008. The considerable underestimation of melt ablation in this year could be attributed to deficiencies in the employed albedo parameterization. Model results revealed that the spatial distribution of surface mass balance at Langenferner is strongly dependent on shortwave net radiation while other surface energy fluxes showed less influence on the spatial pattern. In order to test the sensitivity of the model to changes in selected model parameters as well as the meteorological input data, a series of sensitivity tests were performed. The model sensitivity to changes in air temperature shows that an increase of 1°C causes a change in the mean specific mass balance of -1338 mm w.e., which is similar to the result of a 20 % decrease in precipitation. Neglecting topographic shading due to surrounding peaks, in turn, would only lead to a change of -76 mm w.e. in the mean specific mass balance for 2004/05. Finally, some suggestions for further model improvements and perspectives for future work are presented. vii Zusammenfassung Ziel der vorliegenden Arbeit war es, die räumliche und zeitliche Variabilität der Massen- bilanz, sowie der Energieflüsse an der Oberfläche eines alpinen Gletschers mit relativ komplexer Topographie zu studieren. Zu diesem Zweck wurde für den Zeitraum 2004- 2008 ein prozessbasiertes, zweidimensionales Energie- und Massenbilanzmodell auf den Langenferner in der norditalienischen Ortlergruppe angewandt. Als Input für das Modell wurden meteorologische Daten von sechs automatischen Wetterstationen des Lawinen- warndienstes Südtirol im weiteren Umfeld des Gletschers herangezogen. Die Daten dieser Stationen wurden mit Hilfe von einfachen Transferfunktionen auf die Oberfläche des Gletschers extrapoliert. Zur Optimierung des Energie- und Massenbilanzmodells wurde auf die Daten einer automatischen Wetterstation zurückgegriffen, die im Frühjahr 2010 im Rahmen dieser Studie in unmittelbarer Nähe des Gletschers aufgestellt wurde. Daten von Ablationspegeln und Schneesondierungen auf dem Gletscher dienten sowohl zur Optimierung des Modells, als auch zur Validierung der Ergebnisse. Die Übereinstim- mung der modellierten mittleren spezifischen Massenbilanzen mit den Beobachtungen am Langenferner ist im Allgemeinen zufriedenstellend, mit Ausnahme des hydrolog- ischen Jahres 2007/08. Für dieses Jahr wurde die Schmelzablation vom Modell deutlich unterschätzt, was einer Schwäche in der verwendeten Albedoparametrisierung zuge- ordnet werden konnte. Die Modellergebnisse zeigen, dass die räumliche Verteilung der Massenbilanz am Langenferner stark vom Budget der kurzwelligen Strahlung abhängt, während andere Energieflüsse das räumliche Bilanzmuster weniger stark beeinflussen. Um die Empfindlichkeit des Modells auf Änderungen ausgewählter Modellparameter einerseits, und auf Änderungen in den meteorologischen Inputdaten andererseits, zu testen, wurde eine Reihe von Empfindlichkeitsläufen durchgeführt. Diese zeigten, dass die modellierte Bilanz überaus sensibel auf eine Erhöhung der Lufttemperatur um 1°C reagiert (-1338 mm w.e.). Diese Änderung entspricht in etwa einer Änderung des Niederschlags um -20 %. Das Vernachlässigen der Beschattung durch umgebende Gipfel führt hingegen nur zu einer Änderung der mittleren spezifischen Bilanz um -76 mm w.e. Abschließend werden einige Vorschläge zur Weiterentwicklung des Modells sowie mögliche zukünftige Forschungsinhalte präsentiert. ix Contents Abstract vii Zusammenfassung ix List of Abbreviations1 1 Introduction and Study Aim3 1.1 Background.................................3 1.2 Methods and Objective...........................3 1.3 Structure of the Thesis...........................5 2 Investigation Area7 2.1 Geographical Setting............................7 2.2 Climate...................................8 2.3 Historical Aspects..............................9 3 Data 13 3.1 Meteorological Data............................ 13 3.1.1 Weather Stations.......................... 13 3.1.2 Sulden Madritsch.......................... 14 3.1.3 AWS Felsköpfl........................... 15 3.1.4 Quality of Meteorological Data.................. 16 3.1.5 Temperature............................. 17 3.1.6 Global Radiation.......................... 17 3.1.7 Relative Humidity......................... 18 3.1.8 Wind Speed............................. 19 3.1.9 Precipitation............................ 19 3.1.10 Air Pressure............................. 20 3.2 Glaciological Data............................. 24 3.3 Topographic Data.............................. 25 4 The Energy and Mass-Balance Model 27 4.1 Development and Application of the EMB-model............ 27 4.2 Energy and Mass Balance of a Glacier Surface.............. 27 xi xii Contents 4.3 Shortwave Radiation............................ 30 4.3.1 Direct Shortwave Radiation.................... 30 4.3.2 Diffuse Shortwave Radiation.................... 31 4.3.3 Effective Cloud Cover Fraction and Cloud Impact........ 33 4.3.4 Topographic Shading at the Measurement Site.......... 33 4.3.5 Topographic Shading in the EMB-Model............. 35 4.3.6 Surface Albedo........................... 35 4.4 Longwave Radiation............................ 36 4.4.1 Incoming Longwave Radiation................... 36 4.4.2 Outgoing Longwave Radiation................... 37 4.5 Turbulent Fluxes.............................. 37 4.5.1 Sensible Heat............................ 37 4.5.2 Latent Heat............................. 38 4.5.3 Stability Correction......................... 38 4.5.4 Roughness Lengths......................... 39 4.6 Surface Temperature and Ground Energy Flux.............. 40 4.7 Surface Accumulation............................ 41 5 Working with the EMB-Model 43 5.1 Model Options and Settings - The mbminfile............... 43 5.2 Meteorological Input - The Input File................... 43 5.3 Topographic Model Input......................... 44 5.3.1 Glacier Mask............................ 44 5.3.2 Elevation.............................. 44 5.3.3 Slope and Aspect.......................... 44 5.3.4 Sky View Factor.......................... 44 5.4 Running the Model............................. 46 5.5 Analysing the Model Output........................ 46 6 Model Optimization on Felsköpfl Data 47 6.1 Incoming Shortwave Radiation....................... 47 6.2 Incoming Longwave Radiation....................... 48 6.3 Air Temperature.............................. 49 6.4 Wind Speed................................. 50 7 Results 53 7.1 The 0D-Model - Stake Balance....................... 53 7.2 The 2D-Model - The Mass Balance of Langenferner........... 55 7.2.1 Vertical Mass Balance Profiles................... 56 7.2.2 The Role of Sublimation...................... 58 7.2.3 The 2008-Problem......................... 58 Contents xiii 7.2.4 The 2006-Problem......................... 60 7.3 Surface Energy Fluxes........................... 61 7.4 Model Sensitivity.............................. 69 7.4.1 Topographic Shading........................ 70 7.4.2 Model Sensitivity - a Summary.................. 71 8 Conclusion 73 8.1 General Aspects............................... 73 8.2 Discussion and Outlook.......................... 74 Bibliography 77 List of Figures 81 List of Tables 83 Appendix A - The mbminfile 85 Appendix B - Output Analysis & Analytools 89 Danksagung 91 Curriculum Vitae 93 List of Abbreviations 0D zero dimensional 2D two dimensional AWS automated weather station DEM digital elevation model D-GPS differential global positioning system EMB energy- and mass balance GPS global positioning system HOB Hydrographic Office of the Autonomous Province of Bolzano LIA Little Ice Age m meter m a.s.l. meter above sea level mm w.e. millimeter water equivalent m w.e. meter water equivalent NCAR National Center for Atmospheric Research NCEP National Center for Environmental Prediction REA re-analysis RMSE root mean square error SEB surface energy balance SVF sky view factor Symbols used in the Text LWin incoming longwave radiation LWnet net longwave radiation LWout outgoing longwave radiation QG ground heat flux QL turbulent flux of latent heat QM melt energy flux QS turbulent flux of sensible heat SWin incoming shortwave radiation SWnet net shortwave radiation SWout outgoing shortwave radiation 1 1 Introduction and Study Aim 1.1
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