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(Kongoli et al., 2003). Examination of the AMSU measurements on November 7, 2005 indicated that the 89 GHz frequency channel was not sufficiently sensitive to this newly deposited snow. However, the 150 GHz window frequency channel exhibited scattering response, e.g., depressed brightness temperatures relative to that of 89 GHz (see also Figure 2). Note that frequency channels above 89 GHz are not available for the SSM/I or AMSR-E sensors. This unique capability of the AMSU instrument to retrieve snowfall and to detect newly deposited snow cover could be potentially incorporated and utilized for improved SWE retrievals for new snow. On the other hand, in the blended SWE product, SWE over part of Mongolia as determined by the AMSU product but labeled as “snow-free” land by the IMS is correctly left out. This overestimation of snow cover over Mongolia by the AMSU persisted during much of the winter season of 2006, and is also shown on February 15, 2006 (bottom panels). It is shown that overall, there is better agreement between the microwave-derived SWE and the IMS snow cover, e.g., over Eastern Canada, than in early winter. Exception is areas over Mongolia where overestimation of the AMSU-SWE persists throughout the winter. Examination of MODIS snow cover maps indicated that indeed these areas did not have snow cover, and therefore, they represent “false” snow areas by the AMSU SWE product. Examination of the AMSU measurements over Mongolia indicated relatively small values of the scattering index at 89 GHz (SI89), which is used in the AMSU snow cover extent product to identify snow cover and in the AMSU-SWE product to compute fresh snow SWE (Eq. 2 and 4). This low scattering signal at 89 GHz was present during night-time (low temperatures) and day-time (above freezing temperatures). The presence of scattering in a wide range of atmospheric conditions over Mongolia would be indicative of ground rather than atmospheric effects, e.g., soil grain scattering (Basist et al., 1996). Figure 6 is a plot of the percentage of the retrieved AMSU-SWE area relative to the IMS snow coverage from December 1, 2005 through April 15, 2006 (left-hand vertical axis) and of the overestimated AMSU-SWE area as a percentage of the IMS snow coverage (right-hand vertical axis). It is shown that the net SWE area mapped by the AMSU is at about 75% as compared to that of IMS, which is relatively high for a microwave instrument. The overestimation of snow cover by the AMSU is about 6 % relative to IMS snow coverage. 96
Figure 4. Example of blended SWE product retrievals over Northern Hemisphere on November 7, 2005 and February 15, 2006. Left-hand images depict the blended SWE and the right-hand images depict blended and unblended areas. 97
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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
Page 57 and 58: 45 63 rd EASTERN SNOW CONFERENCE Ne
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 103 and 104: METHODS The IMS Product The IMS was
Page 105 and 106: Figure 1. Microwave spectral charac
Page 107: snow depth and SWE on a weekly basi
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 and 156: The SSM/I snowmelt onset algorithm
Page 157 and 158: 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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