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Robinson, D.A., 2003. ‘Recent variability of northern hemisphere snow cover.’ Preprints: Seventh Conference on Polar Meteorology and Oceanography, Hyannis, MA, American Meteorological Society, paper 13.12, 6. Rogers, E., T. Black, B. Ferrier, Y. Lin, D. Parrish, and G. DiMego, 2001. ‘Changes to the NCEP Meso Eta Analysis and Forecast System: Increase in resolution, new cloud microphysics, modified precipitation assimilation, modified 3DVAR analysis.’ NWS Technical Procedures Bulletin 488, NOAA/NWS, Washington DC. Romanov, P., Gutman G. and Csiszar I., 2000. ‘Automated monitoring of snow cover over North America with multispectral satellite data’ J. Appl. Meteorol., 39, 1866–1880. Romanov, P., D. Tarpley, G. Gutman, and T. Carroll, 2003. ‘Mapping and monitoring of the snow cover fraction over North America.’ J. Geophys. Res., 108(D16), 8619. Romanov, P. and D.Tarpley, 2003. ‘Automated monitoring of snow cover over South America using GOES Imager data. Int. J. Remote Sens., 24(5), 1119–1125. Schmit T.J., M. M. Gunshor, W.P. Menzel, J. Li, S. Bachmeier, J.J. Gurka, 2005. ‘Introducing the Next-generation Advanced Baseline Imager (ABI) on GOES-R’. Bull. Amer. Meteor. Soc., 8, 1079–109. Shaman, J., M.A.Cane, A.Kaplan, 2005. ‘The relationship between Tibetan snow depth, ENSO, river discharge and the monsoons of Bangladesh.’ Int. J. Remote Sens., 26(17), 3735–3748. Sheffeild, J.; Pan, M.; Wood, E.F.; Mitchell, K.E.; Houser, P.R.; Schaake, J.C.; Robock, A.; Lohmann, D.; Cosgrove, B.; Duan, Q.; Luo, L.; Higgins, R.W.; Pinker, R.T.; Tarpley, J.D.; Ramsay, B.H., Journal of Geophysical Research-Atmospheres, November 21, 2003 (Vol. 108, No. D22, 8849, Paper No. 10.1029/2002JD003274) United States Department of Commerce, National Oceanic and Atmospheric Administration (USDOC / NOAA), 2005. New Priorities for the 21 st Century – NOAA’s Strategic Plan, Updated for FY 2006 – FY 2011. NOAA's Strategic Planning Office, Silver Spring, MD. Wadhams, P., 2000. Ice in the ocean. Gordon and Breach Science Publishers. 351. 180
181 63 rd EASTERN SNOW CONFERENCE Newark, Delaware USA 2006 Retreat of Tropical Glaciers in Colombia and Venezuela from 1984 to 2004 as Measured from ASTER and Landsat Images ABSTRACT JENNIFER N. MORRIS, 1 ALAN J. POOLE, 2 AND ANDREW G. KLEIN 3 Like glaciers throughout the world, tropical glaciers in the northern Andes have retreated during the last century. In this study, the retreat of Andean glaciers in Colombian and Venezuela has been mapped from Landsat and ASTER images acquired between 1984 and 2004. Glacier retreat has been mapped for three glaciated regions in Columbia, the Sierra Nevada de Santa Marta, the Sierra Nevada del Cocuy, and the Ruiz-Tolima Massif as has the retreat of the single remaining glacier on the Pico Bonpland Massif in Venezuela. From the Landsat archives, several satellite images spanning the Landsat record were selected based on cloud cover over the glaciers and which provided adequate temporal coverage. All selected satellite images of the study sites were coregistered to each other with a root mean square (RMS) error for the ground control points of less than 20 meters. Snow and ice extent in each image was classified using the Normalized Difference Snow Index (NDSI) method and a density slice was used to create a binary snow/ice map. The total glaciated area on each individual peak was then determined from the classified snow and ice areas. This approach was found to be effective in determining glacier area. Incorporating historical data, a time series of glacier retreat from the early 1950s to 2003 was established. All four studied regions studied showed glacier retreat over this period. In the 1950s, the overall area of glaciers studied in Colombia and Venezuela glaciers was 91.36 km 2 in the 1950s. By 2003, the glaciers had retreated to approximately 62.07 km 2 which represents a total ice loss of 32%. Keywords: Remote Sensing, Colombia, Venezuela, Tropical Glaciers INTRODUCTION As one indicator of global change, glaciers around the world have been studied. Topical glaciers are of particular interest to study because the distinct characteristics of tropical climates make glacier-climate interactions different from the mid- and high-latitudes (Kaser 1999). However, not all tropical glaciers have been comprehensively studied because their remoteness can limit accessibility and extensive cloud cover can preclude extended temporal studies from remote sensing. The recent increase in availability of satellite images over glacier regions has increased the likelihood of studies throughout these regions. The tropical glaciers of Colombia and Venezuela, the focus of this study, were at a recent maximum extent during the Little Ice Age and have receded since this time (Kaser 1999). 1 Department of Geography, MS 3147, Texas A&M University, College Station TX 77843-3147 USA email: jenmorris@tamu.edu. 2 Department of Geography, MS 3147, Texas A&M University, College Station TX 77843-3147 USA email: alanpoole@tamu.edu 3 Department of Geography, MS 3147, Texas A&M University, College Station TX 77843-3147 USA email: klein@geog.tamu.edu
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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 )
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
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 175 and 176: 180 160 140 120 100 80 60 40 20 0 1
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: 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
Page 207 and 208: 63 rd EASTERN SNOW CONFERENCE Newar
Page 209 and 210: In the following paragraph the main
Page 211 and 212: Figure 1: Variation of the season a
Page 213 and 214: Figure 3: 8-day composite maps (24
Page 215 and 216: The third pair (Figure 5) represent
Page 217 and 218: Figure 9: Time evolution of SWE ave
Page 219 and 220: melting occurs, whereas at the high
Page 221 and 222: Colbeck SC, Anderson EA. 1982. The
Page 223 and 224: ABSTRACT 211 63 rd EASTERN SNOW CON
Page 225 and 226: A B Figure 1. Low-magnification sec
Page 227 and 228: GB ridge GB groove Figure 3. Higher
Page 229 and 230: CONCLUSION Figure 5. Indexed electr
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Page 233 and 234: Meteorological data for the winter
Page 235 and 236: monthly probability adjusted data 4
Page 237 and 238: 225 Pullman WA Rawlins WY Leadville
Page 239 and 240: The daily wind speed can exceed 6.5
Page 241 and 242: 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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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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