Western Canadian Cryospheric Network WC2N (2005-2010) Investigators: Andrew Bush (U. Alberta); John Clague (SFU); Garry Clarke (UBC); Stephen Déry (UNBC); Peter Jackson (UNBC); Shawn Marshall (U. Calgary); Brian Menounos (UNBC); Dan Moore (UBC); Dan Smith (U. Victoria); Eric Steig (U. Washington); Roger Wheate (UNBC) Research Collaborators: Doug Clark (Western Washington University); Mike Demuth (Natural Resources Canada); Howard Conway (U. Washington); Kenichi Matsuoka (U. Washington); Joseph McConnell (Desert Research Institute – U. Nevada); Al Rasmussen (U Washington); Sonia Talwar (Natural Resources Canada); Paul Whitfield (Environment Canada) Research Partners: BC Hydro; BC Ministry of Sustainable Resources Management; BC Parks; BC Ministry of Environment (MoE); Columbia Basin Trust (CBT); Fisheries and Oceans Canada (DFO); Environment Canada - Cryosphere System in Canada (CRYSYS); Environment Canada - Meteorological Service of Canada (MSC); Global Land Ice Measurement from Space (GLIMS); Natural Resources Canada - National Glaciology Programme (NGP); Natural Resources Canada - Terrain Sciences Division National Snow and Ice Data Center (NSIDC); Parks Canada -

60°N PG 54°N 49°N 2

Western Canadian Cryospheric Network (WC2N) Research Objectives Document N. Pacific climate variability and glacier extent (400 yrs to present) A: remote sensing / mapping ~1850 – present (UNBC) B: tree rings and ice cores ~1000 - ~1850 Detail meteorological processes and their links to glacier nourishment (mass balance) and hydrology Predict how glaciers will respond to projected climate change over the next 50-150 years The Western Canadian Cryospheric Network has three primary goals. We first wish to document climate variability and the extent of glaciers from 400 years to present. We choose the last 400 years for these reasons. Most glaciers reached their maximum downvalley extent during the last 400 years and allows us to consider the total volumetric change through time and its relation to climate variability. Second we seek to understand local-scale, meteorological processes and how they relate to glacier fluctuations. These important processes will be used with glaciological models to detail the links between climate and glacier mass nourishment Finally, using the output from themes one and two we will then model how future climate change will likely affect glaciers and glacier runoff in western Canada.

Remote Sensing of Glaciers Landsat Images (since 1972) photos > Little Ice Age ~ 1850 Most glaciers are remote ….

Castle Glacier (near McBride) 1 km

These images from the Advanced Land Imager (ALI) on NASA’s Earth Observing-1 (EO-1) satellite show Jakobshavn Glacier in 2001 and 2010. http://earthobservatory.nasa.gov/IOTD/view.php?id=44625

Remote Sensing of Glaciers Image processing can be used to: Extract glacier extents (compare with map vectors) b. Identify surface characteristics (e.g. accumulation-ablation) c. Volume loss from DEMs d. Animation – image series e. Glacier velocity 

Edziza: extents from NTDB 66, TRIM 85, Landsat 2000 5 km

Spectral characteristics of snow and ice

The spectral curve explains why glaciers look blue-green on a 5-4-3 composite   (why?) .. and enables distinguishing snow/ice from clouds (why?) http://asterweb.jpl.nasa.gov/gallery-detail.asp?name=Aletsch

2. Image classification –or thresholding  Accumulation area (snow); Ablation (ice) ... and firn (wet snow)

Improved Glacier Outlines Landsat TM 7-4-2 TRIM Ice Layer as Mask Raw Glacier Outlines Improved Glacier Outlines Landsat TM 7-4-2 TRIM Ice Layer as Mask Water Detection (NDWI) Ratio 3/5 Ratio 3/5 >= 2 1 – Mapping of Glaciers Challenges: 1: Clouds 2: Late lying snow 3: Internal rocks 4: Pro-glacial lakes 5: Debris-cover 6: Ice divides I’d like to walk you though a sequence of images that summarizes our procedures. Circles: Lake, debris-cover, small glacier not correctly mapped in TRIM Note that water index was tried but not used – dirty lakes are problematic. We used brute force instead (manual editing)

3. Thickness loss and volume estimates from DEMs Klinaklini Glacier comparing = subtracting temporal DEMs gives an estimate of depth lost

4. Animation series: Klinaklini Glacier 1992

2006 1992

Scud Glacier (2002) Satellite imagery of glaciers will also be used to understand ice dynamics at the local scale. Development of glaciological models requires knowledge of ice motion. Until satellite imagery most methods of estimating the surface motion of ice were completed in the file using costly and time consuming ground surveys. Shown here are two satellite images corrected for topographic distortion taken almost 1 year apart. Note the displacement of patterns on the ice as I shift back and forth between the two images. For this portion of the Scud Glacier – located in NW BC – the surface velocities are about 100 m per year.

Scud Glacier (2003) 0.5 km

5. Glacier velocity Klinaklini Glacier Annual movement ranges from 30 – 500 m / year mostly in summer) Length of vector proportional to change between sequential Images Oct 2001/Sep 2002 Uses ENVI COSI-CORR