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34 63 rd EASTERN SNOW CONFERENCE Newark, Delaware USA 2006 the acquisitions of validating data, with respect to logistic manner, mountainous risks and strictly weather depending planning of field investigations. As PREVAH does not include the redistribution of snow by wind or avalanches the spatial distribution of the SWE cannot be matched perfectly, but the mean values of the modelled SWE are identical to measured catchment means of the SWE. Hence, it seems that the main part of the drifted snow originates from the simulated watershed and remains inside. An additional conceptual module for the snow redistribution by wind and avalanches (Hartmann et al., 1999) should be applied to the model to satisfy these claims. It seems to be obvious, that only in a very good observed catchment area reliable simulation results of high quality can be obtained. ACKNOWLEDGEMENTS This ongoing research was supported by a grant from the Austrian Academy of Sciences under the project SNOWTRANS HOE29, part of the IHP PUB (International Hydrological Program, Prediction in Ungauged Basins). Many thanks to Markus Vollmann for the classification of the ASTER image. The authors are grateful to all the students, colleagues and friends who helped to carry out the exhausting field work. REFERENCES Arnold N., Richards K., Willis I., Sharp M. 1998. Initial results from a semi-distributed, physically based model of glacier hydrology. Hydrological Processes 12: 191–219. Arnold N.S., Willis I. C., Sharp M., Richards K.S., Lawson W. 1996. `A distributed surface energy balance model for a small valley glacier. I. Development and testing for the Haut Glacier d'Arolla, Valais, Switzerland', Journal of Glaciology, 42: 77–89. Auer I., Böhm R., Leymüller M., Schöner W., Kaiser A., Scheifinger H., Langer M., Scheider St., Häberli Ch. 2002. Das Klima des Sonnblicks. Klimaatlas und Klimatographie der GAW Station Sonnblick einschließlich der umgebenden Gebirgsregion. Österreichische Beiträge zu Meteorologie und Geophysik. Heft 28. Zentralanstalt für Meteorologie und Geodynamik, Wien. ISSN 1016–6254. Badoux A. 1999. Untersuchung zur flächendifferenzierten Modellierung von Abfluss und Schmelze in teilvergletscherten Einzugsgebieten. Diploma thesis at the Geographical Institute of ETH, Zürich. Blöschl G., Kirnbauer R., Jansa J., Kraus K., Kuschnig D., Gutknecht D., Reszler C. 2002. Using remote sensing methods for calibrating and verifying a spatially distributed snow model. Österreichische Wasser- und Abfallwirtschaft (ÖWW) 54: 16 pp. Blöschl G., Kirnbauer R., Gutknecht D. 1991. Distributed Snowmelt Simulations in an Alpine Catchment, 1, Model Evaluation on the Basis of Snow Cover Patterns. Water Resources Research, 27(12), 3171–3179. Collins D.N., 1982. Water storage in Alpine glaciers. Hydrological Aspects of Alpine and High Mountain Areas (Proceedings of the Exeter Symposium, July 1982) IAHS Publ, no 138: 113– 122. Doorschot J., Raderschall N., Lehning M. 2001. Measurements and one-dimensional model calculations of snow transport over a mountain ridge. Annals of Glaciology, 32: 153–158. Elder K., Rosenthal W., Davis R.E. 1998. Estimating the spatial distribution of snow water equivalence in a montane watershed. Hydrological Processes 12: 1793–1808. Finsterwalder S., Schunk H. 1887. Der Suldenferner. Zeitschrift des Deutschen und Oesterreichischen Alpenvereins 18: 72–89. Gurtz J., Zappa M., Jasper K., Lang H., Verbunt M., Badoux A., Vitvar T. 2003. A Comparative Study in Modelling Runoff and its Components in Two Mountainous Catchments. Hydrological Processes 17: 297–311. DOI: 10.1002/hyp.1125
35 63 rd EASTERN SNOW CONFERENCE Newark, Delaware USA 2006 Güntner A., Uhlenbrook S., Seibert J., Leibundgut C. 1999. Multi-criterial validation of TOPMODEL in a mountainous catchment. Hydrological Processes 13: 1603–1620. Hartman M.D., Baron J.S., Lammers R.B., Cline D.W., Band L.E., Liston G.E. Tague C. 1999. Simulations of snow distribution and hydrology in a mountain basin. Water Resources Research, 35(5): 1587–1603. Hock R. 1999. A distributed temperature-index ice- and snowmelt model including potential direct solar radiation. Journal of Glaciology 45(149): 101–111. Hock R., Holmgren B. 2005. A distributed surface energy-balance model for complex topography and its application to Storglaciären, Sweden. Journal of Glaciology 51(172): 25–36. Hoinkes H. 1970. Methoden und Möglichkeiten von Massenhaushaltsstudien auf Gletschern. Ergebnisse der Meßreihe Hintereisferner (Ötztaler Alpen) 1953–1968. Zeitschrift für Gletscherkunde und Glazialgeologie, 6, 37 – 90. Hynek B., Schöner W. 2004. Massenhaushalt 2002/2003 der Gletscher in der Goldberggruppe. 101–102. Jahresbericht des Sonnblick-Vereines: 1–15. Eigenverlag der Zentralanstalt für Meteorologie und Geodynamik, Wien. Kaser G., Fountain A., Jansson P. 2003. A manual for monitoring the mass balance of mountain glaciers. IHP-VI, Technical Documents in Hydrology No. 59, UNESCO, Paris, 2003. Kirnbauer R, Blöschl G, Gutknecht D. 1994. Entering the Era of Distributed Snow Models. Nordic Hydrology 25: 1–24. Klok E.J., Jasper K., Roelofsma K.P., Gurtz J., Badoux A. 2001. Distributed hydrological modelling of a heavily glaciated Alpine river basin. Hydrological Sciences Journal—Journal Des Sciences Hydrologiques 46: 553–570. Lang H., Braun L. 1990. On the Information content of air Temperature in the Context of Snow Melt Estimation. In: Hydrology of Mountainous Areas, L. Molar (Ed.). IAHS Publ. no. 190: 347–354. Lehning M., Voelksch I., Gustafsson D., Nguyen T.A., Stähli M., Zappa M. 2006. Influence of snow, forest, soil and local meteorological forcing on mountain catchment hydrology. Hydrological Processes, in press: DOI: 10.1002/hyp.6204. Lehning M., Doorschot J., Bartelt P. 2000. A snowdrift index based on SNOWPACK model calculations. In Annals of Glaciology, 31: 382–386. Marks D., Domingo J., Susong D., Link T., Garen D. 1999. A spatially distributed energy balance snowmelt model for application in mountain basins. Hydrological Processes 13:1935–1959. Nash J.E., Sutcliffe J.V. 1970. River flow forecasting through conceptual models (1), a discussion of principles. Journal of Hydrology 10 (3): 282–290. Ohmura A. 2001. Physical Basis for the Temperature-Based Melt-Index Method. Journal of Applied Meteorology 40, No. 4: 753–761. DOI: 10.1175/1520- 0450(2001)0402.0.CO;2 Østrem G., Brugman M. 1991. Glacier mass-balance measurements—A manual for field and office work: Environment Canada, National Hydrology Research Institute Science Report No. 4, and Norwegian Water Resources and Energy Administration, 224 p. Pellicciotti F., Brock B., Strasser U., Burlando P., Funk M. Corripio J. 2005. An enhanced temperature-index glacier melt model including the shortwave radiation balance: development and testing for Haut Glacier d’Arolla, Switzerland. Journal of Glaciology 51(175): 573–587. Ross B.B., Contractor D.N., Shanholtz V.O. 1979. A Finite Element Model Of Overland And Channel Flow For Assessing The Hydrologic Impact Of Landuse Change. Journal of Hydrology 41: 1–30. Schaefli B., Hingray B., Niggli M., Musy A. 2005. A conceptual glacio-hydrological model for high mountainous catchments, Hydrology and Earth System Sciences Discussions 2: 73–117. Sevruk B. (ed.) 1986. Correction of Precipitation Measurements. ETH/IASH/WMO Workshop on the Correction of Precipitation Measurements. Zürich, April 1–3, 1985, Zuercher Geographische Schriften, Heft 23.
Page 1 and 2: Proceedings of the 63rd ANNUAL EAST
Page 3 and 4: FOREWORD T his proceedings volume c
Page 5 and 6: CONTENTS Foreword..................
Page 7 and 8: STATEMENT OF PURPOSE The Eastern Sn
Page 9 and 10: EXECUTIVES FOR THE 63rd EASTERN SNO
Page 11 and 12: THE PRESIDENT’S PAGE The 63rd ann
Page 13 and 14: Weisnet Medal for Best Student Pape
Page 15 and 16: 3 63 rd EASTERN SNOW CONFERENCE New
Page 17 and 18: Figure 1. Layer 1 represents the so
Page 19 and 20: Figure 4. The general layout of the
Page 21 and 22: lue color represented no convection
Page 23 and 24: Total Density of Water Profiles The
Page 25 and 26: Figure 11(a). Simulated snow grain
Page 27 and 28: Jordan R, 1991. A one-dimensional t
Page 29 and 30: Campbell Scientific Award for Best
Page 31 and 32: 19 63 rd EASTERN SNOW CONFERENCE Ne
Page 41 and 42: R ∑i ∑ n 2 = 1 NS = − n i = 1
Page 45: 33 63 rd EASTERN SNOW CONFERENCE Ne
Page 49 and 50: Snow and Climate 37
Page 53 and 54: Spatial distributions of changes in
Page 55 and 56: Snow and Climate Posters 43
Page 59 and 60: Figure 2 presents correlation maps
Page 61 and 62: CONCLUSIONS Three regional-continen
Page 65 and 66: Discharge (mm) 20 18 16 14 12 10 8
Page 67 and 68: ABSTRACT 55 63 rd EASTERN SNOW CONF
Page 69 and 70: This paper analyzes the synoptic pa
Page 71 and 72: Cyclones that track west of the App
Page 73 and 74: The synoptic-scale atmospheric circ
Page 75 and 76: CONCLUSIONS The record snowfall in
Page 79 and 80: correlations between April-May snow
Page 81 and 82: Figure 3. Linear correlations betwe
Page 83 and 84: winter/early spring could contribut
Page 85 and 86: Snow Remote Sensing 73
Page 89 and 90: height averaged 11.4 m with an aver
Page 91 and 92: strings were buried 20 - 30 cm belo
Page 93 and 94: Although the λE/Rn fraction was on
Page 95 and 96: estimated snow depth based on the 2
Page 97 and 98:
important to note that the average
Page 99 and 100:
Schmidt, R. A., C. A. Troendle, and
Page 101 and 102:
89 63 rd EASTERN SNOW CONFERENCE Ne
Page 103 and 104:
METHODS The IMS Product The IMS was
Page 105 and 106:
Figure 1. Microwave spectral charac
Page 107 and 108:
snow depth and SWE on a weekly basi
Page 109 and 110:
Figure 4. Example of blended SWE pr
Page 111 and 112:
Evaluation of the global distributi
Page 113 and 114:
Figure 9. Inter-comparison plots of
Page 115 and 116:
Helfrich, S.R., D. McNamara, B.H.Ra
Page 117 and 118:
105 63 rd EASTERN SNOW CONFERENCE N
Page 119 and 120:
and validated regionally so they ca
Page 121 and 122:
109 Test Site Figure 2. Variation o
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Correlation Coe. Correlation Coe. C
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Figure 8. SSM/I scattering signatur
Page 127 and 128:
Considering the facts mentioned abo
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Besides the temporal validation, th
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RMSE Non linear Azar Chang Goodison
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63 nd EASTERN SNOW CONFERENCE Newar
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http://www.ccin.ca); from simulatio
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over the period 1988-2000. With the
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Figure 3: Explained variance (R 2 )
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correspondence between simulated an
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values. Continued development of ne
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National Climatic Data Center (2005
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Snow Remote Sensing Posters 135
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ABSTRACT 63 rd EASTERN SNOW CONFERE
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day and has a mean pixel resolution
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Table 1. Wheaton River basin EASE-G
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The SSM/I snowmelt onset algorithm
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coarse-resolution pixel with the hi
Page 159 and 160:
Figure 5. (a) Scatterplot of snowpa
Page 161 and 162:
For both 2004 and 2005, the AMSR-E
Page 163 and 164:
threshold of ±18 K that reflects t
Page 165 and 166:
ABSTRACT 153 63 rd EASTERN SNOW CON
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DATA USED SSM/I & QuikSCAT Coverage
Page 169 and 170:
Page 171 and 172:
Page 173 and 174:
Page 175 and 176:
180 160 140 120 100 80 60 40 20 0 1
Page 177 and 178:
Page 179 and 180:
independent of regions. This greatl
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slightly vary the IMS with this pro
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imagery, the higher latitudes rely
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MODIS Land Science Team, NASA Godda
Page 187 and 188:
FUTURE OF IMS Enhancements to the I
Page 189 and 190:
information never present before on
Page 191 and 192:
Brubaker, K.L., R. Pinker and E. De
Page 193 and 194:
Page 195 and 196:
The Sierra Nevada del Cocuy region
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Colombia Venezuela Glacier Series R
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Table 4. Glacier Areas of the Ruiz-
Page 201 and 202:
Pico Bonpland Massif-Sinigüis Glac
Page 203 and 204:
Linder W, Jordan E, 1991. Ice-mass
Page 205 and 206:
Snowpack Processes 193
Page 207 and 208:
63 rd EASTERN SNOW CONFERENCE Newar
Page 209 and 210:
In the following paragraph the main
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Figure 1: Variation of the season a
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Figure 3: 8-day composite maps (24
Page 215 and 216:
The third pair (Figure 5) represent
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Figure 9: Time evolution of SWE ave
Page 219 and 220:
melting occurs, whereas at the high
Page 221 and 222:
Colbeck SC, Anderson EA. 1982. The
Page 223 and 224:
Page 225 and 226:
A B Figure 1. Low-magnification sec
Page 227 and 228:
GB ridge GB groove Figure 3. Higher
Page 229 and 230:
CONCLUSION Figure 5. Indexed electr
Page 231 and 232:
219 63rd EASTERN SNOW CONFERENCE De
Page 233 and 234:
Meteorological data for the winter
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monthly probability adjusted data 4
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225 Pullman WA Rawlins WY Leadville
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The daily wind speed can exceed 6.5
Page 241 and 242:
NCDC. 2006. National Climate Data C
Page 243 and 244:
Page 245 and 246:
and mass balances for 540 environme
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Temperature, precipitation, windspe
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the left in response to snow compac
Page 251 and 252:
Pinched-cone dimensions for each sl
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Terrain slope (degrees) Terrain slo
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ACKNOWLEDGEMENTS This work was fund
Page 257 and 258:
Glacial and Periglacial Processes 2
Page 259 and 260:
Page 261 and 262:
From linear regression the constant
Page 263 and 264:
Page 265 and 266:
DATA COLLECTION Figure 1. Location
Page 267 and 268:
Table 1. Comparison of GPS measured
Page 269 and 270:
Transverse Velocity Profiles Surfac
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is shown in Figure 4. This variatio
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Table 4. The calculated volume flux
Page 275 and 276:
Page 277 and 278:
Figure 1. Cordillera Blanca regiona
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MATERIALS AND METHODS Field Measure
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Data analysis techniques We synthes
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season, but unacceptable for the dr
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significant, although more informat
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(a) Liquid Water (mm) Dry Period: M
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Future Work We are installing addit
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Shuttleworth, W.J., and J.S. Wallac
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Snow and Periglacial Processes Post
Page 295 and 296:
Page 297 and 298:
----- -------------- ------- ------
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No one to date has shown why snowfl
Page 301 and 302:
APPENDIX A Northern Hemisphere Year
Page 303 and 304:
62nd ESC Papers 291
Page 305 and 306:
62 nd EASTERN SNOW CONFERENCE Water
Page 307 and 308:
each other; and, they both decrease
Page 309 and 310:
297 62 nd EASTERN SNOW CONFERENCE W
Page 311 and 312:
comes in the form of precipitation.
Page 313 and 314:
averaged to reduce bias in this var
Page 315 and 316:
RESULTS Figure 2. Flow chart of reg
Page 317 and 318:
Table 6: Actual-Conditions SWE, dep
Page 319 and 320:
307 Table 9: Regression results bet
Page 321 and 322:
Goita, K., A. Walker, B. Goodison,
Page 323:
TO ERR IS HUMAN, TO FORGET IT WOULD
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