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The answer to the second question requires approximations. We chose such to maximize our result. Thus, for the total number of snowflakes that have fallen, our approximation will be higher than the historical value. To determine how many snowflakes have fallen we need to know, how much snow has fallen and the average size of a snowflake. Measurements of snowfall are made locally not globally. Any amount of snow that we project to have fallen on the earth will be, at best, a guess. SNOWFLAKE MODEL Combinations and configurations This is a model for a flat hexagonal snowflake and incorporates dendritic plates. Several simplifications make this model workable and yet remain consistent with what is known about real snowflakes. The model begins, as any good model, with actual snowflakes. (3) Our model applies to dendritic plates: We assume snowflakes have: Hexagonal radial symmetry (six-sided snowflakes), Two-dimensional configuration (flat snowflakes), and The simplest unit of an ice crystal is a hexagonal ring composed of six water molecules. We know that real snowflakes have several documented forms and, although, these may be hexagonal in nature, they are not strictly two-dimensional. They have thickness and the basic building blocks of any ice crystal may be far more complex than a ring of only six water molecules. Thus, any model we develop will underestimate the number of possible snowflake configurations. Each of the above assumptions carries several corollaries that shape our model. Hexagonal radial symmetry implies that: a. Each of the six arms are identical to each other. i. One sixth of the total number of units is used to compose each of the six arms. b. Each arm is bilaterally symmetric. (It is the same on each side of its radial axis.) i. There is a centerline of units. Assume the centerline (radial axis) to be the longest line of each arm. ii. The sidelines (parallel to the centerline) are paired, one on either side of the centerline. iii. The sidelines are made up of many segments of lines each shorter than the centerline. iv. The length of each sideline must be at least three units shorter than the next sideline closer to the centerline and at least three units longer than the next sideline farther from the centerline. 284
----- -------------- ------- ------------ ---------- sideline (3 segments) ------- ----- - ----------- --------- sideline --------------------------------------------------- sideline Radial axis --------------------------------------------------------------- one of six arms --------------------------------------------------- ------- ----- - ----------- --------- ------- ------------ ---------- ----- -------------- We know that the most common form of ice is a tetrahedral structure. Idealized hexagonal rings are found within the tetrahedral form. Close examination of the basal plane of an ice crystal reveals it is composed of a tiling of hexagonal plates each with a diameter of 5.5 angstroms, 4.5 angstroms across the tiling diameter or minor chord and 2.75 angstroms between adjacent oxygen atoms. (1)(5) Using a simple idealized hexagonal ice crystal as a building block, we can approximate how many such blocks or hexagonal tiles must accumulate to form a single axis arm of a snowflake. Ordinary snowflakes vary in size from 0.05 cm. to 1.8 cm. in diameter. A reasonable midrange value for the average radius of a snowflake is 0.66 cm. Thus, a radius axis of an average snowflake is 285
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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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Snow and Climate 37
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Spatial distributions of changes in
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Snow and Climate Posters 43
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Figure 2 presents correlation maps
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CONCLUSIONS Three regional-continen
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Discharge (mm) 20 18 16 14 12 10 8
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ABSTRACT 55 63 rd EASTERN SNOW CONF
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This paper analyzes the synoptic pa
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Cyclones that track west of the App
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The synoptic-scale atmospheric circ
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CONCLUSIONS The record snowfall in
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correlations between April-May snow
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Figure 3. Linear correlations betwe
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winter/early spring could contribut
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Snow Remote Sensing 73
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height averaged 11.4 m with an aver
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strings were buried 20 - 30 cm belo
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Although the λE/Rn fraction was on
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estimated snow depth based on the 2
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important to note that the average
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Schmidt, R. A., C. A. Troendle, and
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METHODS The IMS Product The IMS was
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Figure 1. Microwave spectral charac
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snow depth and SWE on a weekly basi
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Figure 4. Example of blended SWE pr
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Evaluation of the global distributi
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Figure 9. Inter-comparison plots of
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Helfrich, S.R., D. McNamara, B.H.Ra
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105 63 rd EASTERN SNOW CONFERENCE N
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and validated regionally so they ca
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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
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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
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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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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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Page 245 and 246: and mass balances for 540 environme
Page 247 and 248: Temperature, precipitation, windspe
Page 249 and 250: the left in response to snow compac
Page 251 and 252: Pinched-cone dimensions for each sl
Page 253 and 254: Terrain slope (degrees) Terrain slo
Page 255 and 256: ACKNOWLEDGEMENTS This work was fund
Page 257 and 258: Glacial and Periglacial Processes 2
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Page 261 and 262: From linear regression the constant
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
Page 271 and 272: is shown in Figure 4. This variatio
Page 273 and 274: Table 4. The calculated volume flux
Page 277 and 278: Figure 1. Cordillera Blanca regiona
Page 279 and 280: MATERIALS AND METHODS Field Measure
Page 281 and 282: Data analysis techniques We synthes
Page 283 and 284: season, but unacceptable for the dr
Page 285 and 286: significant, although more informat
Page 287 and 288: (a) Liquid Water (mm) Dry Period: M
Page 289 and 290: Future Work We are installing addit
Page 291 and 292: Shuttleworth, W.J., and J.S. Wallac
Page 293 and 294: Snow and Periglacial Processes Post
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Page 299 and 300: 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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