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39 63 rd EASTERN SNOW CONFERENCE Newark, Delaware USA 2006 20 th Century North American Snow Extent Trends: Climate Change or Natural Climate Variability? EXTENDED ABSTRACT ALLAN FREI, 1 GAVIN GONG, 2 DAVID A. ROBINSON, 3 GWANGYONG CHOI, 4 DEBJANI GHATAK, 5 AND YAN GE 6 The purpose of this analysis is to test the null hypothesis that continental scale variations in North American snow cover extent (NA SCE) can be explained by atmospheric circulation alone, without need to invoke additional explanatory factors such as climate change. We test the null hypothesis by (1) presenting what is known about decadal scale variations in twentieth century continental scale NA SCE, and (2) examining historical variations in surface climate, tropospheric and stratospheric circulation, as well as corollary evidence from arctic sea ice variations, to determine whether the available evidence supports or refutes the null hypothesis. In this presentation, preliminary results are presented focusing on snow extent during spring (i.e., March). The full report is being prepared for submission for publication elsewhere. METHODS AND DATA In order to test the null hypothesis, we utilize data sets that extend back to, and beyond, the mid twentieth century. Variations in snow depth, surface temperature and precipitation rate, as well as upper tropospheric and mid stratospheric geopotential heights and wind speeds are examined using time series, composite, and correlation analyses. Time series analyses are used to identify climatic features in these fields that covary over interannual and decadal time scales. To evaluate decadal changes, time series were smoothed using 9-year running means as a low pass filter in order to focus on decadal and longer scale variations. The results and conclusions are robust with regards to changes in the smoothing window size. Observations of snow extent are taken from the NOAA visible based satellite product (Ramsay 1998; Robinson et al. 1999; Helfrich et al. 2006); reconstructed snow extent is from two sources (Brown 2000; Frei et al. 1999); snow depth is from a new gridded product (described in Dyer and Mote 2006); climatological fields are from the NCEP/NCAR Reanalysis project (Kalnay and co-authors 1996); and teleconnection indices are from the NOAA Climate Diagnostic Center, the Climate Research Unit of the University of East Anglia, and the National Center for Atmospheric Research. 1 Department of Geography, Hunter College, Graduate Program in Earth and Environmental Sciences, City University of New York, NY. 2 Department of Earth and Environmental Engineering, Columbia University, NY. 3 Department of Geography, Rutgers University, NJ. 4 Department of Geography, Rutgers University, NJ. 5 Department of Geography, Hunter College, Graduate Program in Earth and Environmental Sciences, City University of New York, NY. 6 Department of Earth and Environmental Engineering, Columbia University, NY.
Page 1 and 2: Proceedings of the 63rd ANNUAL EAST
Page 3 and 4: FOREWORD T his proceedings volume c
Page 5 and 6: CONTENTS Foreword..................
Page 7 and 8: STATEMENT OF PURPOSE The Eastern Sn
Page 9 and 10: EXECUTIVES FOR THE 63rd EASTERN SNO
Page 11 and 12: THE PRESIDENT’S PAGE The 63rd ann
Page 13 and 14: Weisnet Medal for Best Student Pape
Page 15 and 16: 3 63 rd EASTERN SNOW CONFERENCE New
Page 17 and 18: Figure 1. Layer 1 represents the so
Page 19 and 20: Figure 4. The general layout of the
Page 21 and 22: lue color represented no convection
Page 23 and 24: Total Density of Water Profiles The
Page 25 and 26: Figure 11(a). Simulated snow grain
Page 27 and 28: Jordan R, 1991. A one-dimensional t
Page 29 and 30: Campbell Scientific Award for Best
Page 31 and 32: 19 63 rd EASTERN SNOW CONFERENCE Ne
Page 41 and 42: R ∑i ∑ n 2 = 1 NS = − n i = 1
Page 49: 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 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 101 and 102:
89 63 rd EASTERN SNOW CONFERENCE Ne
Page 103 and 104:
METHODS The IMS Product The IMS was
Page 105 and 106:
Figure 1. Microwave spectral charac
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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
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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
Page 127 and 128:
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
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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
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
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ABSTRACT 153 63 rd EASTERN SNOW CON
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DATA USED SSM/I & QuikSCAT Coverage
Page 169 and 170:
Page 171 and 172:
Page 173 and 174:
Page 175 and 176:
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
Page 191 and 192:
Brubaker, K.L., R. Pinker and E. De
Page 193 and 194:
Page 195 and 196:
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
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
Page 209 and 210:
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
Page 221 and 222:
Colbeck SC, Anderson EA. 1982. The
Page 223 and 224:
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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
Page 263 and 264:
Page 265 and 266:
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
Page 321 and 322:
Goita, K., A. Walker, B. Goodison,
Page 323:
TO ERR IS HUMAN, TO FORGET IT WOULD
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