Within her PhD, Fanny Brun applied the freely available NASA Ames Stereo Pipeline (ASP) tool to ASTER imagery to produce repeat digital elevation models (DEM) of the glacier surfaces across High Mountain Asia (HMA), from which, by subtracting one DEM from another, the volume of glacier change over time can be calculated. This was then used to provide a record of spatially resolved historical geodetic mass balance for the glaciers of High Mountain Asia (HMA).
This NASA Ames Stereo Pipeline (ASP) tool is pretty awesome as far as I can tell, open source, free, and offering a very powerful, repeatable, standardized methodology for generating DEMs from optical satellite imagery of our planet.
Applying this strategy allowed computation of the mass balance of 92% of the glacierized area in HMA, over a longer period (2000 to 2016) than other satellite data sources (e.g. GRACE and IceSat) allowed, and also avoided issues of these alternative satellite data sources, such as difficulties separating the ice signal from water storage in the gravity data, and poor spatial coverage of IceSat at the latitude of HMA. The key findings of this work were:
- This provided the first consistent record of glacier mass balance for the whole HMA region, allowing intercomparisons between climatic zones and constituent mountain ranges
- Specifically, the results shed light on the Nyainqentanglha and Pamir glacier mass changes, for which contradictory estimates exist in the literature.
- Considering only the basins that drain out of HMA, the results of this study showed a mass loss of 14.6 (± 3.1) Gt yr-1 for the period 2000 to 2016, which is very different from the value of 46 (± 3.1) Gt yr-1 provided by previous workers and commonly used in sea level budget studies.
Recently this technique was reapplied to the glaciers of continental Western North America (WNA) in a study led by Brian Menounous. The paper was nicely summarized in a blog by co-author Joe Shea here. The key points of the study highlighted in the blog post are:
- When averaged over all regions, WNA glaciers lost 6.5 (± 2.3) Gt yr-1 during the period 2000
There is short-term variability imposed on the long-term trend of glacier mass loss. Big increases (x6) in glacier mass loss were observed between the first and second half of the study in the southern and central Coast Mountains of BC, which contain the largest volumes of ice in this region.
- A southward shift in the mean position of the jet stream is probably the main factor in #2: this reduced winter precipitation in the central and southern Coast Mountains, and led to more negative mass balances in the last 10 years. Conversely, the jet stream shift produced neutral conditions (and even slight mass gains) in areas that started to get more winter precipitation: the south Cascades and Glacier National Park.
Gridded rates of glacier elevation change (2000-2018) for western North America: early (left), late (middle), and full (right) periods. Circle size is total glacier area in each 1×1 degree grid cell.
I guess the scientists involved in these studies will continue to apply this powerful method to other glaciated continents in the coming years to provide more large scale and consistent records of historical glacier change that can be used to provide insights to help us better understand future glacier behavior.
- Shean, D. E., Alexandrov, O., Moratto, Z. M., Smith, B. E., Joughin, I. R., Porter, C. and Morin, P. (2016) An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery, ISPRS J. Photogramm. Remote Sens., 116, 101–117, doi:10.1016/j.isprsjprs.2016.03.012.
- Brun, F., Berthier, E., Wagnon, P., Kääb, A., & Treichler, D. (2017). A spatially resolved estimate of High Mountain Asia glacier mass balances, 2000-2016. Nature Geoscience, 10 (9), 668–673. https://doi.org/10.1038/ngeo2999
- Menounos, B., Hugonnet, R., Shean, D., Gardner, A., Howat, I., Berthier, E., et al. (2018). Heterogeneous changes in western North American glaciers linked to decadal variability in zonal wind strength. Geophysical Research Letters, 45. https://doi.org/10.1029/2018GL080942