New research – cryosphere (October 11, 2016)
Posted by Ari Jokimäki on October 11, 2016
Some of the latest papers on climate change impacts on cryosphere are shown below. First a few highlighted papers with abstracts and then a list of some other papers. If this subject interests you, be sure to check also the other papers – they are by no means less interesting than the highlighted ones.
Grounding line retreat of Pope, Smith, and Kohler Glaciers, West Antarctica, measured with Sentinel-1a radar interferometry data (Scheuchl et al. 2016) http://onlinelibrary.wiley.com/doi/10.1002/2016GL069287/abstract
Abstract: We employ Sentinel-1a C band satellite radar interferometry data in Terrain Observation with Progressive Scans mode to map the grounding line and ice velocity of Pope, Smith, and Kohler glaciers, in West Antarctica, for the years 2014–2016 and compare the results with those obtained using Earth Remote Sensing Satellites (ERS-1/2) in 1992, 1996, and 2011. We observe an ongoing, rapid grounding line retreat of Smith at 2 km/yr (40 km since 1996), an 11 km retreat of Pope (0.5 km/yr), and a 2 km readvance of Kohler since 2011. The variability in glacier retreat is consistent with the distribution of basal slopes, i.e., fast along retrograde beds and slow along prograde beds. We find that several pinning points holding Dotson and Crosson ice shelves disappeared since 1996 due to ice shelf thinning, which signal the ongoing weakening of these ice shelves. Overall, the results indicate that ice shelf and glacier retreat in this sector remain unabated.
On the recent contribution of the Greenland ice sheet to sea level change (van den Broeke et al. 2016) http://www.the-cryosphere.net/10/1933/2016/
Abstract: We assess the recent contribution of the Greenland ice sheet (GrIS) to sea level change. We use the mass budget method, which quantifies ice sheet mass balance (MB) as the difference between surface mass balance (SMB) and solid ice discharge across the grounding line (D). A comparison with independent gravity change observations from GRACE shows good agreement for the overlapping period 2002–2015, giving confidence in the partitioning of recent GrIS mass changes. The estimated 1995 value of D and the 1958–1995 average value of SMB are similar at 411 and 418 Gt yr−1, respectively, suggesting that ice flow in the mid-1990s was well adjusted to the average annual mass input, reminiscent of an ice sheet in approximate balance. Starting in the early to mid-1990s, SMB decreased while D increased, leading to quasi-persistent negative MB. About 60 % of the associated mass loss since 1991 is caused by changes in SMB and the remainder by D. The decrease in SMB is fully driven by an increase in surface melt and subsequent meltwater runoff, which is slightly compensated by a small (< 3 %) increase in snowfall. The excess runoff originates from low-lying (< 2000 m a.s.l.) parts of the ice sheet; higher up, increased refreezing prevents runoff of meltwater from occurring, at the expense of increased firn temperatures and depleted pore space. With a 1991–2015 average annual mass loss of ~ 0.47 ± 0.23 mm sea level equivalent (SLE) and a peak contribution of 1.2 mm SLE in 2012, the GrIS has recently become a major source of global mean sea level rise.
Tropical Pacific SST drivers of recent Antarctic sea ice trends (Purich et al. 2016) http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-16-0440.1
Abstract: A strengthening of the Amundsen Sea Low from 1979-2013 has been shown to largely explain the observed increase in Antarctic sea ice concentration in the eastern Ross Sea and decrease in the Bellingshausen Sea. Here we show that while these changes are not generally seen in freely-running coupled climate model simulations, they are reproduced in simulations of two independent coupled climate models; one constrained by observed sea surface temperature anomalies in the tropical Pacific, and the other by observed surface wind-stress in the tropics. Our analysis confirms previous results and strengthens the conclusion that the phase change in the Interdecadal Pacific Oscillation from positive to negative over 1979-2013 contributed to the observed strengthening of the Amundsen Sea Low and associated pattern of Antarctic sea ice change during this period. New support for this conclusion is provided by simulated trends in spatial patterns of sea ice concentrations that are similar to those observed. Our results highlight the importance of accounting for teleconnections from low to high latitudes in both model simulations and observations of Antarctic sea ice variability and change.
Quantifying ice loss in the eastern Himalayas since 1974 using declassified spy satellite imagery (Maurer et al. 2016) http://www.the-cryosphere.net/10/2203/2016/
Abstract: Himalayan glaciers are important natural resources and climate indicators for densely populated regions in Asia. Remote sensing methods are vital for evaluating glacier response to changing climate over the vast and rugged Himalayan region, yet many platforms capable of glacier mass balance quantification are somewhat temporally limited due to typical glacier response times. We here rely on declassified spy satellite imagery and ASTER data to quantify surface lowering, ice volume change, and geodetic mass balance during 1974–2006 for glaciers in the eastern Himalayas, centered on the Bhutan–China border. The wide range of glacier types allows for the first mass balance comparison between clean, debris, and lake-terminating (calving) glaciers in the region. Measured glaciers show significant ice loss, with an estimated mean annual geodetic mass balance of −0.13 ± 0.06 m w.e. yr−1 (meters of water equivalent per year) for 10 clean-ice glaciers, −0.19 ± 0.11 m w.e. yr−1 for 5 debris-covered glaciers, −0.28 ± 0.10 m w.e. yr−1 for 6 calving glaciers, and −0.17±0.05 m w.e. yr−1 for all glaciers combined. Contrasting hypsometries along with melt pond, ice cliff, and englacial conduit mechanisms result in statistically similar mass balance values for both clean-ice and debris-covered glacier groups. Calving glaciers comprise 18 % (66 km2) of the glacierized area yet have contributed 30 % (−0.7 km3) to the total ice volume loss, highlighting the growing relevance of proglacial lake formation and associated calving for the future ice mass budget of the Himalayas as the number and size of glacial lakes increase.
Quantifying the uncertainty in historical and future simulations of Northern Hemisphere spring snow cover (Thackeray et al. 2016) http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-16-0341.1
Abstract: Projections of 21st century Northern Hemisphere (NH) spring snow cover extent (SCE) from two climate model ensembles are analyzed to characterize their uncertainty. The Fifth Coupled Model Intercomparison Project (CMIP5) multi-model ensemble exhibits variability due to both model differences and internal climate variability, whereas spread generated from a Canadian Earth System Model large ensemble (CanESM-LE) experiment is solely due to internal variability. The analysis shows that simulated 1981-2010 spring SCE trends are slightly weaker than observed (using an ensemble of snow products). Spring SCE is projected to decrease by -3.7±1.1% decade-1 within the CMIP5 ensemble over the 21st century. SCE loss is projected to accelerate for all spring months over the 21st century, with the exception of June (because most snow in this month has melted by the latter half of the 21st century). For 30-year spring SCE trends over the 21st century, internal variability estimated from CanESM-LE is substantial, but smaller than inter-model spread from CMIP5. Additionally, internal variability in NH extratropical land warming trends can affect SCE trends in the near-future (R2 = 0.45), while variability in winter precipitation can also have a significant (but lesser) impact on SCE trends. On the other hand, a majority of the inter-model spread is driven by differences in simulated warming (dominant in March, April, May), and snow cover available for melt (dominant in June). The strong temperature/SCE linkage suggests that model uncertainty in projections of SCE could be potentially reduced through improved simulation of spring season warming over land.
Persistent artifacts in the NSIDC ice motion dataset and their implications for analysis (Szanyi et al. 2016)
Distributed ice thickness and glacier volume in southern South America (Carrivick et al. 2016) http://www.sciencedirect.com/science/article/pii/S0921818116301515
Century-scale perspectives on observed and simulated Southern Ocean sea ice trends from proxy reconstructions (Hobbs et al. 2016) http://onlinelibrary.wiley.com/doi/10.1002/2016JC012111/abstract
Identifying dynamically induced variability in glacier mass-balance records (Christian et al. 2016) http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-16-0128.1
Impacts of marine instability across the East Antarctic Ice Sheet on Southern Ocean dynamics (Phipps et al. 2016) http://www.the-cryosphere.net/10/2317/2016/
Effects of bryophyte and lichen cover on permafrost soil temperature at large scale (Porada et al. 2016) http://www.the-cryosphere.net/10/2291/2016/
Meltwater Pathways from Marine Terminating Glaciers of the Greenland Ice Sheet (Gillard et al. 2016) http://onlinelibrary.wiley.com/doi/10.1002/2016GL070969/abstract
Assimilation of surface velocities between 1996 and 2010 to constrain the form of the basal friction law under Pine Island Glacier (Gillet-Chaulet et al. 2016) http://onlinelibrary.wiley.com/doi/10.1002/2016GL069937/abstract
Linked trends in the south Pacific sea ice edge and Southern Oscillation Index (Kwok et al. 2016) http://onlinelibrary.wiley.com/doi/10.1002/2016GL070655/abstract
Greenland during the last interglacial: the relative importance of insolation and oceanic changes (Pedersen et al. 2016) http://www.clim-past.net/12/1907/2016/
The impact of melt ponds on summertime microwave brightness temperatures and sea-ice concentrations (Kern et al. 2016) http://www.the-cryosphere.net/10/2217/2016/
The EUMETSAT sea ice concentration climate data record (Tonboe et al. 2016) http://www.the-cryosphere.net/10/2275/2016/
Temperature reconstruction from the length fluctuations of small glaciers in the eastern Alps (northeastern Italy) (Zecchetto et al. 2016) http://link.springer.com/article/10.1007%2Fs00382-016-3347-5
Variability, trends, and predictability of seasonal sea ice retreat and advance in the Chukchi Sea (Serreze et al. 2016) http://onlinelibrary.wiley.com/doi/10.1002/2016JC011977/abstract
Producing cloud-free MODIS snow cover products with conditional probability interpolation and meteorological data (Dong & Menzel, 2016) http://www.sciencedirect.com/science/article/pii/S0034425716303625
ICESat laser altimetry over small mountain glaciers (Treichler & Kääb, 2016) http://www.the-cryosphere.net/10/2129/2016/
Heterogeneous glacier thinning patterns over the last 40 years in Langtang Himal, Nepal (Ragettli et al. 2016) http://www.the-cryosphere.net/10/2075/2016/
Arctic sea ice patterns driven by the Asian Summer Monsoon (Grunseich & Wang, 2016) http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-16-0207.1
Impact of climate warming on snow processes in ny-Ålesund, a polar maritime site at Svalbard (López-Moreno et al. 2016) http://www.sciencedirect.com/science/article/pii/S0921818116303903
Variations in ice velocities of Pine Island Glacier Ice Shelf evaluated using multispectral image matching of Landsat time series data (Han et al. 2016) http://www.sciencedirect.com/science/article/pii/S0034425716303443
Application of GRACE to the assessment of model-based estimates of monthly Greenland Ice Sheet mass balance (2003–2012) (Schlegel et al. 2016) http://www.the-cryosphere.net/10/1965/2016/
Near-real-time Arctic sea ice thickness and volume from CryoSat-2 (Tilling et al. 2016) http://www.the-cryosphere.net/10/2003/2016/
Potential for estimation of snow depth on Arctic sea ice from CryoSat-2 and SARAL/AltiKa missions (Guerreiro et al. 2016) http://www.sciencedirect.com/science/article/pii/S0034425716302711
Sliding of temperate basal ice on a rough, hard bed: creep mechanisms, pressure melting, and implications for ice streaming (Krabbendam, 2016) http://www.the-cryosphere.net/10/1915/2016/
Monte Carlo modelling projects the loss of most land-terminating glaciers on Svalbard in the 21st century under RCP 8.5 forcing (Möller et al. 2016) http://iopscience.iop.org/article/10.1088/1748-9326/11/9/094006/meta
North-east sector of the Greenland Ice Sheet to undergo the greatest inland expansion of supraglacial lakes during the 21st century (Ignéczi et al. 2016) http://onlinelibrary.wiley.com/doi/10.1002/2016GL070338/abstract