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REFERENCES Bales, R., N. Molotch, T. Painter, M. Dettinger, R. Rice, and J. Dozier (2006), Mountain hydrology of the western United States., Water Resources Research, 42, W08432, doi:08410.01029/02005WR004387. Blanken, P. D., T. A. Black, H. H. Neumann, G. Den Hartog, P. C. Yang, Z. Nesic, R. Staebler, W. Chen, and M. D. Novak (1998), Turbulent flux measurements above and below the overstory of a boreal aspen forest, Boundary-Layer Meteorology, 89, 109–140. Blanken, P. D., T. A. Black, P. C. Yang, H. H. Neumann, Z. Nesic, R. Staebler, G. den Hartog, M. D. Novak, and X. Lee (1997), Energy balance and canopy conductance of a boreal aspen forest: Partitioning overstory and understory components, Journal Of Geophysical Research- Atmospheres, 102, 28915–28927. Caine, N. (1995), Temporal trends in the quality of streamwater in an Alpine environment: Green Lakes valley, Colorado Front Rand, USA, Geografiska Annaler Series A-Physical Geography, 77A, 207–220. Davis, R. E., J. P. Hardy, W. Ni, C. E. Woodcock, J. C. Mckenzie, R. Jordan, and X. Li (1997), Variation of snow cover ablation in the boreal forest: A sensitivity study on the effects of conifer canopy, Journal of Geophysical Research, 102, 29389–29395. Essery, R., J. Pomeroy, J. Parviainen, and P. Storck (2003), Sublimation of snow from coniferous forests in a climate model, Journal Of Climate, 16, 1855–1864. Fassnacht, S. R. (2004), Estimating Alter-shielded gauge snowfall undercatch, snowpack sublimation, and blowing snow transport at six sites in the coterminous USA, Hydrological Processes, 18, 3481–3492. Lundberg, A., and S. Halldin (1994), Evaporation of intercepted snow: Anlaysis of governing factors., Water Resources Research, 30, 2587–2598. McClung, D., and P. Schaerer (1993), The Avalanche Handbook, 271 pp., The Mountaineers, Seattle, Washington. Monin, A. S., and A. M. Obukhov (1954), Basic laws of turbulent mixing in the ground layer of the atmosphere., Tr. Inst. Teor. Geofiz. Akad. Nauk SSSR, 1, 95–115. Montesi, J., K. Elder, R. A. Schmidt, and R. E. Davis (2004), Sublimation of intercepted snow within a subalpine forest canopy at two elevations, Journal of Hydrometeorology, 5, 763–773. Nakai, Y. T., T. Sakamoto, T. Terajima, H. Kiahara, and T. Saito (1994), Snow interception by forest canopies: Weighing a conifer tree, meteorological observation and analysis by hte Penman-Monteith formula, IAHS Publ., 223, 227–236. Niu, G. Y., and Z. L. Yang (2004), Effects of vegetation canopy processes on snow surface energy and mass balances, Journal Of Geophysical Research-Atmospheres, 109. Parviainen, J., and J. W. Pomeroy (2000), Multiple-scale modelling of forest snow sublimation: initial findings, Hydrological Processes, 14, 2669–2681. Pomeroy, J. W., and R. L. H. Essery (1999), Turbulent fluxes during blowing snow: field tests of model sublimation predictions, Hydrological Processes, 13, 2963–2975. Pomeroy, J. W., and D. M. Gray (1995), Snowcover accumulation, relocation and management, NHRI Science Report 7, National Hydrology Research Institute, Environment Canada, 134 pp. Pomeroy, J. W., N. Parviainen, N. Hedstrom, and D. M. Gray (1998), Coupled modeling of forest snow interception and sublimation., Hydrological Processes, 12, 2317–2337. Pomeroy, J. W., and R. A. Schmidt (1993), The use of fractal geometry in modeling intercepted snow accumulation and sublimation., Proceedings of the 50th Eastern Snow Conference., Quebec City, QC, Canada., 50, 1–10. Schmidt, R. A. (1991), Sublimation of snow intercepted by an artificial conifer, Agricultural and Forest Meteorology, 54, 1–27. Schmidt, R. A., R. L. Jairell, and J. W. Pomeroy (1988), Measuring snow interception and loss from an artificial conifer., Proceedings of the 56th Western Snow Conference., Kalispell, MT., 166–169. Schmidt, R. A., and C. A. Troendle (1992), Sublimation of intercepted snow as a global source of water vapor., Proceedings of the 60th Western Snow Conference., Jackson, WY., 60, 1–9. 86
Schmidt, R. A., C. A. Troendle, and J. R. Meiman (1998), Sublimation of snowpacks in subalpine conifer forests, Canadian Journal Of Forest Research-Revue Canadienne De Recherche Forestiere, 28, 501–513. Schuepp, P. H., M. Y. Leclerc, J. I. Macpherson, and R. L. Desjardins (1990), Footprint Prediction Of Scalar Fluxes From Analytical Solutions Of The Diffusion Equation, Boundary-Layer Meteorology, 50, 353–373. Sicart, J. E., J. W. Pomeroy, R. E. Essery, J. Hardy, T. Link, and D. Marks (2004), A sensitivity study of daytime net radiation during snowmelt to forest canopy and atmospheric conditions, Journal of Hydrometeorology, 5, 774–784. Turnipseed, A. A., P. D. Blanken, D. E. Anderson, and R. K. Monson (2002), Energy budget above a high-elevation subalpine forest in complex topography, Agricultural And Forest Meteorology, 110, 177–201. West, A. (1962), Snow evaporation from a forested watershed in the central Sierra Nevada, Journal of Forestry, 60, 481–484. Woo, M. K., and M. A. Giesbrecht (2000), Simulation of snowmelt in a subarctic spruce woodland: Scale considerations, Nordic Hydrology, 31, 301–316. 87
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Proceedings of the 63rd ANNUAL EAST
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FOREWORD T his proceedings volume c
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CONTENTS Foreword..................
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STATEMENT OF PURPOSE The Eastern Sn
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EXECUTIVES FOR THE 63rd EASTERN SNO
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THE PRESIDENT’S PAGE The 63rd ann
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Weisnet Medal for Best Student Pape
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3 63 rd EASTERN SNOW CONFERENCE New
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Figure 1. Layer 1 represents the so
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Figure 4. The general layout of the
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lue color represented no convection
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Total Density of Water Profiles The
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Figure 11(a). Simulated snow grain
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Jordan R, 1991. A one-dimensional t
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Campbell Scientific Award for Best
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19 63 rd EASTERN SNOW CONFERENCE Ne
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R ∑i ∑ n 2 = 1 NS = − n i = 1
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Page 47 and 48: 35 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: important to note that the average
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
Page 123 and 124: Correlation Coe. Correlation Coe. C
Page 125 and 126: Figure 8. SSM/I scattering signatur
Page 127 and 128: Considering the facts mentioned abo
Page 129 and 130: Besides the temporal validation, th
Page 131 and 132: RMSE Non linear Azar Chang Goodison
Page 133 and 134: 63 nd EASTERN SNOW CONFERENCE Newar
Page 135 and 136: http://www.ccin.ca); from simulatio
Page 137 and 138: over the period 1988-2000. With the
Page 139 and 140: Figure 3: Explained variance (R 2 )
Page 141 and 142: correspondence between simulated an
Page 143 and 144: values. Continued development of ne
Page 145 and 146: National Climatic Data Center (2005
Page 147 and 148: Snow Remote Sensing Posters 135
Page 149 and 150:
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
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Figure 5. (a) Scatterplot of snowpa
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For both 2004 and 2005, the AMSR-E
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threshold of ±18 K that reflects t
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ABSTRACT 153 63 rd EASTERN SNOW CON
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DATA USED SSM/I & QuikSCAT Coverage
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157 63 rd EASTERN SNOW CONFERENCE N
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180 160 140 120 100 80 60 40 20 0 1
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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
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FUTURE OF IMS Enhancements to the I
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information never present before on
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Brubaker, K.L., R. Pinker and E. De
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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-
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Pico Bonpland Massif-Sinigüis Glac
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Linder W, Jordan E, 1991. Ice-mass
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Snowpack Processes 193
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63 rd EASTERN SNOW CONFERENCE Newar
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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
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The third pair (Figure 5) represent
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Figure 9: Time evolution of SWE ave
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melting occurs, whereas at the high
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Colbeck SC, Anderson EA. 1982. The
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A B Figure 1. Low-magnification sec
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GB ridge GB groove Figure 3. Higher
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CONCLUSION Figure 5. Indexed electr
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219 63rd EASTERN SNOW CONFERENCE De
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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
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NCDC. 2006. National Climate Data C
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and mass balances for 540 environme
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Temperature, precipitation, windspe
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the left in response to snow compac
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Pinched-cone dimensions for each sl
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Terrain slope (degrees) Terrain slo
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ACKNOWLEDGEMENTS This work was fund
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Glacial and Periglacial Processes 2
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From linear regression the constant
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DATA COLLECTION Figure 1. Location
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Table 1. Comparison of GPS measured
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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
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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
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----- -------------- ------- ------
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No one to date has shown why snowfl
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APPENDIX A Northern Hemisphere Year
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62nd ESC Papers 291
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62 nd EASTERN SNOW CONFERENCE Water
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each other; and, they both decrease
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297 62 nd EASTERN SNOW CONFERENCE W
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comes in the form of precipitation.
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averaged to reduce bias in this var
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RESULTS Figure 2. Flow chart of reg
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Table 6: Actual-Conditions SWE, dep
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307 Table 9: Regression results bet
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Goita, K., A. Walker, B. Goodison,
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TO ERR IS HUMAN, TO FORGET IT WOULD
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