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Figure 4. Frequency histogram of all AMSR-E 36.5V GHz Tb for the six Wheaton River basin 25 x 25 km 2 pixels during the 2004-2005 period. The Tb are grouped in bins of 2 K. The bimodal distribution suggests a threshold of 252 K is more suitable for distinguishing between frozen (left distribution) and wet (right distribution) snow using AMSR-E in the Wheaton River basin than the SSM/I threshold of 246 K. The individual pixel sets, while not as clearly defined, also have minima near the threshold of 252 K. Measurements of snowpack properties were obtained in the Wheaton River basin during the spring of 2005. More than fifty snowpits were dug in a variety of locations, encompassing a range of elevations, terrains, and forest cover in an attempt to represent the heterogeneous nature of the region. Characteristics of the snowpack were described and measured, including the general stratigraphy as well as grain size, air and snow temperature, and snow structure at various depths. A comprehensive analysis of these parameters is beyond the scope of this paper. A snow surface dielectric capacitance probe and measurements of snow density were used to derive snow wetness as a percentage of the volume at different depths (Denoth, 1989). Surface and near-surface wetness values were averaged from multiple measurements at each site, and these wetness values were later compared with AMSR-E 36.5V GHz Tb from overpasses obtained less than one hour before or after the ground observations (Figs. 5a and 5b, Table 3). In addition to supporting the new Tb threshold, these observations helped show that the observed Tb response is linked to melting snow and is not the result of liquid precipitation or other events. Once the new Tb threshold was determined, the AMSR-E 36.5V GHz data, along with melt onset and spring transition data, were compared with the melt onset results of the SSM/I 37V GHz data for all six of the Wheaton River basin 25 x 25 km 2 pixels (Figs. 6a and 6b, Table 4). This allowed for a new DAV threshold to be created for the AMSR-E data (Table 2), since the daily fluctuations appear to have increased with the AMSR-E sensor, and also helped to determine if the new thresholds are effective at detecting snowmelt as related to previous snowmelt onset detection studies using SSM/I Tb data. After determining that similar snow melt onset results could be obtained from AMSR-E and SSM/I Tb data gridded at the same 25 x 25 km 2 resolution, the effectiveness of the AMSR-E sensor’s improved spatial resolution was investigated. The AMSR-E swath data were gridded to the EASE-Grid with a resolution of 12.5 x 12.5 km 2 , which is more representative of the 12 km mean spatial resolution of the 36.5V GHz channel (Ashcroft and Wentz, 2004). This gridded resolution allowed for the creation of four finer resolution pixels of information for each 25 x 25 km 2 pixel (Fig. 1b). Elevation data were used to identify the fine-resolution pixels within any 144
coarse-resolution pixel with the highest and lowest mean elevations (Table 5). The AMSR-E 36.5V GHz Tb for these pixels, as well as the snowmelt onset timing, were then compared with the coarser 25 x 25 km 2 data to examine the effects of the AMSR-E sensor’s increased spatial resolution on improving the ability to detect snowmelt in heterogeneous terrain (Figs. 7a and 7b, Table 5). Table 3. Spring 2005 Wheaton River basin snow wetness measurements and AMSR-E 25 km 2 Tb RESULTS The two main techniques used to determine a new snowmelt onset Tb threshold for the AMSR-E 36.5V GHz channel both found the threshold between non-melting and melting snow to be 252 K. The first method, in which the Tb for the six Wheaton basin pixels were compared with air temperature data for 2004 and 2005 (refer to Fig. 3), illustrates that a Tb threshold of around 252 K is an effective boundary between (1,2) non-melting and (3) melting snow near 0°C. In these nonlinear plots, it can be noted that two distinct relationships occur on either side of the 0°C mark. Below 0°C, the Tb are below 252 K and increase very slightly with an increase in temperature. As the temperature approaches and exceeds 0°C, the Tb rapidly increases above 252 K (Fig. 3). This rapid change in the slope of Tb when the air temperature is near 0°C at Tb = 252 K is due to the high sensitivity of microwaves to liquid water within the melting snowpack. The transition from frozen to melting snow is especially clear for pixel B02, which contains the site of the near-surface air temperature observations, as the change in slope between these two conditions at 0°C occurs at the Tb threshold of 252 K (Fig. 3). It is also worth noting that two distinct distributions of Tb occur when compared to air temperatures below 0°C (Fig. 3). The upper Tb response (Fig. 3, #1) is from periods in November from both 2004 and 2005, while the lower response (Fig. 3, #2) is from periods in December of the same years. The cause of the upper response may be related to ice accumulation on trees during the earlier winter months, a condition that was observed in the 2006 winter season. During the winter, especially during unusually warm years, open lakes that have not yet frozen can create 145
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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
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
Page 151 and 152: day and has a mean pixel resolution
Page 153 and 154: Table 1. Wheaton River basin EASE-G
Page 155: The SSM/I snowmelt onset algorithm
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
Page 167 and 168: DATA USED SSM/I & QuikSCAT Coverage
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Page 179 and 180: independent of regions. This greatl
Page 181 and 182: slightly vary the IMS with this pro
Page 183 and 184: imagery, the higher latitudes rely
Page 185 and 186: 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 195 and 196: The Sierra Nevada del Cocuy region
Page 197 and 198: Colombia Venezuela Glacier Series R
Page 199 and 200: 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
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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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ABSTRACT 211 63 rd EASTERN SNOW CON
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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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ABSTRACT 231 63 rd EASTERN SNOW CON
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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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247 63 rd EASTERN SNOW CONFERENCE N
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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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