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sublimated from the snowpack on DOY 60 whereas over 0.6 mm sublimated on DOY 64. At 60 cm above the ground surface snow temperatures fluctuated by less than 5˚ during DOY 60 and by more than 10˚ during DOY 64 (Figure 8). Similarly, diurnal variability in snow temperature was significantly lower on DOY 74 relative to DOY 93; sublimation rates were 0.1 versus 0.6 mm d –1 for these two days, respectively. Temperature fluctuations in the surface layers, associated with cool nights and warm dry days potentially drive significant water vapor movement in the surface layers of the snowpack and enhance sublimation rates. precipitation total sublimation snowpack / total sublimation ratio day of year 82 snowpack sublimation Figure 6. Time series of daily average sublimation measured above the canopy (blue line) and beneath the canopy (red line). Precipitation and the ratio of snowpack sublimation to total sublimation are also shown. 40 30 20 10 precipitation total sublimation canopy sublimation snowpack sublimation 0 60 70 80 90 100 day of year Figure 7. Cumulative sublimation from the snowpack, intercepted snow (canopy), and total sublimation throughout the study period. Cumulative precipitation is also shown. Estimates of snow depth on snow temp profile plots were derived from coincident pit observations when available. In the case of DOY 60, the majority of precipitation was recorded on DOY 59 and early hours of DOY 60 and therefore we assume snow depth equivalent to that measured in the snowpit on DOY 64. In the case of DOY 74, snow depth was difficult to estimate as there was a large (12.45 mm) snowfall event on DOY 73. Thus, we assumed a snow depth of 80 cm, corresponding to the observed snow depth from the snowpit on DOY 84. For DOY 93, we mean
estimated snow depth based on the 2:00 temperature curve which showed a distinct inflection point at the snow–atmosphere interface. Above and below canopy friction velocities were considerably greater for DOY 64 and 93 relative to that on DOY 60 and 74 (Figure 9). The combination of the relatively high air temperatures on these days with sufficient turbulence lead to enhanced near-surface gradients in specific humidity and sublimation. 80 60 40 20 a. DOY = 60 atmosphere b. DOY = 64 c. DOY = 74 d. DOY = 93 snow 0 soil -20 -25 -20 -15 -10 -5 0 -12 -8 -4 0 -20 -15 -10 -5 0 -10 -5 0 5 10 15 temperature, C Figure 8. Snowpack, soil, and air temperature profiles from 80 cm above the ground surface to 20 cm below. Profiles are shown for 4 different days for hours 2, 8, 14, and 20 MST. Dotted horizontal lines represent the snowpack / atmosphere interface. Solid horizontal lines indicate the soil / snowpack interface. below canopy above canopy 83 hour X 20:00 14:00 8:00 2:00 day of year Figure 9. Above (blue lines) and below canopy (green lines) diurnal variability in friction velocity and air temperature for the same 4 days shown in Figure 8.
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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
Page 43 and 44: 31 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: Although the λE/Rn fraction was on
Page 97 and 98: important to note that the average
Page 99 and 100: Schmidt, R. A., C. A. Troendle, and
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
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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
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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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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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