bedrock data from Morlighem. Who is Bamber, never heard
J Bamber did the heavy lifting on Goginini's ice penetrating radar data set to produce the first bedrock DEMs of Greenland. Morlighem posted a putative refinement implied by surface ice velocity that most notably deepened west Greenland marine outlet troughs. At specific locations, there are also sled radar grids and seismic surveys. Rignot has since added high resolution bathymetry of calving fronts of numerous fjords (not including Jakobshavn).
You could well ask, never mind posted formal errors, what happens when new tracks of ice penetrating radar data that weren't included (ie 2014-15) in Bamber/Morlighem are run against the DEM. There is no annual updating that I know of. Specifically, the radar tracks are sparse so questions have been raised about the accuracy interpolating with 'ordinary kriging' whereas glaciers grinding away on bedrock create an anisotropic landscape. This would be a good project for the forum.
Meanwhile Bamber is working on fixing inter-track interpolation and improving the accuracy of basal reflection depths themselves. On Cresis radargrams, the ordinate is radar return time. Depth is secondarily inferred by assuming constant propagation velocity and attenuation of radio waves in ice whereas it is actually an exponential function of temperature (profile). His other 265 publications (5844 cites) are listed at researchgate.
http://www.the-cryosphere-discuss.net/tc-2016-8/https://www.researchgate.net/profile/Jonathan_BamberNone of this really helps in the specific case of Jakobshavn -- the ice is too rough and too deep. Seismic lines are more effective than radar on basal hydrated till, which approaches 100 m in depth in certain JI over-deepenings. Your bedrock DEM might unfamiliar because people usually tweak color scheme transitions to bring out humps and troughs. Hue is easily rotated in gimp.
the forum not great database for images. just show links to a server ... all images for a glacier get their own folder and the files names include date and satellite. account access data will only be shared via private message
Over the last 36 days, there have been 18 images of Jakobshavn. That number will prove erratic over the melt season due to S1A scheduling priorities and periods of cloud cover. While every 2nd day is very decent and a big improvement over Landsat alone, it is not enough to resolve details of calving cascades.
For that we need to dig into the real-time seismic record. It's hard to believe with 900 forum members, we have yet to unravel the record calving event of 15 Aug 15. It's all laid out in the first link below. We need to get it in gear NOW in case there's more of the same this summer. In fact, why stop with posting one-off images when every calving event can be resolved into its stages.
http://onlinelibrary.wiley.com/doi/10.1002/2015GL066785/fullhttp://library.seg.org/doi/abs/10.1190/geo2015-0154.1Given our total dependence on open source radar, open source satellite, open source seismic, open source weather, open source GPS, open source journals, etc, it might seem churlish for us to squirrel away datasets of glacier imagery. What goes around, comes around.
True, it's time-consuming to sort through incoming for cloud-free imagery and to download multi-GB files from dorky portals, crop out the glacier, align different dates, process in 16-bit, interpret the scene for significant developments, and write up a post.
Yet duplicative proprietary efforts make no sense -- we all have too much to do already, climate change is too important to be playing games. The trick is to string together a pipeline in which each contributor can do their favorite bit (perhaps effortless in their software environment), pass the baton, and see advantages from others running with it.
This is a very different paradigm for western science, collaborative rather than competitive. We're more accustomed to the unscrupulous data-stealing Watson & Crick where it's all about establishing priority, getting credit, and glorifying the individual. However collaborations have proven more effective in data-overload situations requiring inputs from many specialties. No one knows enough any more to go it alone.
People think, 'oh if I share my idea, someone else will run with it and my career will suffer'. The fact is, it won't. It costs them nothing to add another name to a paper. And if your good ideas are so far and few between that they have to be hoarded, there's no future in academics to begin with.