scholarly journals A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 1967–2015

2020 ◽  
Author(s):  
Jordi Bolibar ◽  
Antoine Rabatel ◽  
Isabelle Gouttevin ◽  
Clovis Galiez
Keyword(s):  
Deep Learning ◽  
Mass Balance ◽  
Data Science ◽  
Regional Analysis ◽  
Average Error ◽  
High Mountain ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
French Alps ◽  
Mass Losses

Abstract. Glacier surface mass balance (SMB) data are crucial to understand and quantify the regional effects of climate on glaciers and the high-mountain water cycle, yet observations cover only a small fraction of glaciers in the world. We present a dataset of annual glacier-wide surface mass balance of all the glaciers in the French Alps for the 1967–2015 period. This dataset has been reconstructed using deep learning (i.e. a deep artificial neural network), based on direct and remote sensing SMB observations, meteorological reanalyses and topographical data from glacier inventories. This data science reconstruction approach is embedded as a SMB component of the open-source ALpine Parameterized Glacier Model (ALPGM). An extensive cross-validation allowed to assess the method’s validity, with an estimated average error (RMSE) of 0.49 m w.e. a−1, an explained variance (r2) of 79 % and an average bias of +0.017 m w.e. a−1. We estimate an average regional area-weighted glacier-wide SMB of −0.72 ± 0.20 m w.e. a−1 for the 1967–2015 period, with moderately negative mass balances in the 1970s (−0.52 m w.e. a−1) and 1980s (−0.12 m w.e. a−1), and an increasing negative trend from the 1990s onwards, up to −1.39 m w.e. a−1 in the 2010s. Following a topographical and regional analysis, we estimate that the massifs with the highest mass losses for this period are the Chablais (−0.90 m w.e. a−1) and Ubaye and Champsaur ranges (−0.91 m w.e. a−1 both), and the ones presenting the lowest mass losses are the Mont-Blanc (−0.74 m w.e. a−1), Oisans and Haute-Tarentaise ranges (−0.78 m w.e. a−1 both). This dataset (available at: https://doi.org/10.5281/zenodo.3663630) (Bolibar et al., 2020a) – provides relevant and timely data for studies in the fields of glaciology, hydrology and ecology in the French Alps, in need of regional or glacier-specific meltwater contributions in glacierized catchments.

scholarly journals A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 1967–2015

2020 ◽  
Vol 12 (3) ◽  
pp. 1973-1983
Author(s):  
Jordi Bolibar ◽  
Antoine Rabatel ◽  
Isabelle Gouttevin ◽  
Clovis Galiez
Keyword(s):  
Deep Learning ◽  
Mass Balance ◽  
Water Cycle ◽  
Regional Analysis ◽  
Average Error ◽  
High Mountain ◽  
Glacier Mass Balance ◽  
French Alps ◽  
Mass Losses ◽  
Regional Area

Abstract. Glacier mass balance (MB) data are crucial to understanding and quantifying the regional effects of climate on glaciers and the high-mountain water cycle, yet observations cover only a small fraction of glaciers in the world. We present a dataset of annual glacier-wide mass balance of all the glaciers in the French Alps for the 1967–2015 period. This dataset has been reconstructed using deep learning (i.e. a deep artificial neural network) based on direct MB observations and remote-sensing annual estimates, meteorological reanalyses and topographical data from glacier inventories. The method's validity was assessed previously through an extensive cross-validation against a dataset of 32 glaciers, with an estimated average error (RMSE) of 0.55 mw.e.a-1, an explained variance (r2) of 75 % and an average bias of −0.021 mw.e.a-1. We estimate an average regional area-weighted glacier-wide MB of −0.69±0.21 (1σ) mw.e.a-1 for the 1967–2015 period with negative mass balances in the 1970s (−0.44 mw.e.a-1), moderately negative in the 1980s (−0.16 mw.e.a-1) and an increasing negative trend from the 1990s onwards, up to −1.26 mw.e.a-1 in the 2010s. Following a topographical and regional analysis, we estimate that the massifs with the highest mass losses for the 1967–2015 period are the Chablais (−0.93 mw.e.a-1), Champsaur (−0.86 mw.e.a-1), and Haute-Maurienne and Ubaye ranges (−0.84 mw.e.a-1 each), and the ones presenting the lowest mass losses are the Mont-Blanc (−0.68 mw.e.a-1), Oisans and Haute-Tarentaise ranges (−0.75 mw.e.a-1 each). This dataset – available at https://doi.org/10.5281/zenodo.3925378 (Bolibar et al., 2020a) – provides relevant and timely data for studies in the fields of glaciology, hydrology and ecology in the French Alps in need of regional or glacier-specific annual net glacier mass changes in glacierized catchments.

Glacier evolution modelling with deep learning: challenges and opportunities

2020 ◽  
Author(s):  
Jordi Bolibar ◽  
Antoine Rabatel ◽  
Isabelle Gouttevin ◽  
Clovis Galiez ◽  
Thomas Condom ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Deep Learning ◽  
Mass Balance ◽  
Open Source ◽  
Data Science ◽  
Data Availability ◽  
Alternative Methods ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Challenges And Opportunities

<div>Glacier surface mass balance (SMB) and glacier evolution modelling have traditionally been tackled with physical/empirical methods, and despite some statistical studies very few efforts have been made towards machine learning approaches. With the end of this past decade, we have witnessed an impressive increase in the available amount of data, mostly coming from remote sensing products and reanalyses, as well as an extensive list of open-source tools and libraries for data science. Here we introduce a first effort to use deep learning (i.e. a deep artificial neural network) to simulate glacier-wide surface mass balance at a regional scale, based on direct and remote sensing SMB data, climate reanalysis and multitemporal glacier inventories. Coupled with a parameterized glacier-specific ice dynamics function, this allows us to simulate the evolution of glaciers for a whole region. This has been developed as the ALpine Parameterized Glacier Model (ALPGM), an open-source Python glacier evolution model. To illustrate this data science approach, we present the results of a glacier-wide surface mass balance reconstruction of all the glaciers in the French Alps from 1967-2015. These results were analysed and compared with all the available observations in the region as well as another physical/empirical SMB reconstruction study. We observe some interesting differences between the two SMB reconstructions, which further highlight the interest of using alternative methods in glacier modelling. Due to (relatively) recent advances in data availability and open tools (e.g. Tensorflow, Keras, Pangeo) this research field is ripe for progress, with many interesting challenges and opportunities lying ahead. To conclude, some perspectives on data science glacier modelling are discussed, based on the limitations of our current approach and on upcoming tools and methods, such as convolutional and physics-informed neural networks. </div>

scholarly journals Quantifying mass balance processes on the Southern Patagonia Icefield

2015 ◽  
Vol 9 (1) ◽  
pp. 25-35 ◽  
Author(s):  
M. Schaefer ◽  
H. Machguth ◽  
M. Falvey ◽  
G. Casassa ◽  
E. Rignot
Keyword(s):  
Mass Balance ◽  
Reanalysis Data ◽  
Ice Thickness ◽  
Surface Mass Balance ◽  
Mass Balances ◽  
Surface Mass ◽  
Mass Losses ◽  
Southern Patagonia ◽  
Spatially Distributed ◽  
The Individual

Abstract. We present surface mass balance simulations of the Southern Patagonia Icefield (SPI) driven by downscaled reanalysis data. The simulations were evaluated and interpreted using geodetic mass balances, measured point balances and a complete velocity field of the icefield for spring 2004. The high measured accumulation of snow of up to 15.4 m w.e. yr−1 (meters water equivalent per year) as well as the high measured ablation of up to 11 m w.e. yr−1 is reproduced by the model. The overall modeled surface mass balance was positive and increasing during 1975–2011. Subtracting the surface mass balance from geodetic balances, calving fluxes were inferred. Mass losses of the SPI due to calving were strongly increasing from 1975–2000 to 2000–2011 and higher than losses due to surface melt. Calving fluxes were inferred for the individual glacier catchments and compared to fluxes estimated from velocity data. Measurements of ice thickness and flow velocities at the glaciers' front and spatially distributed accumulation measurements can help to reduce the uncertainties of the different terms in the mass balance of the Southern Patagonia Icefield.

scholarly journals Surface mass balance of glaciers in the French Alps: distributed modeling and sensitivity to climate change

2005 ◽  
Vol 51 (175) ◽  
pp. 561-572 ◽  
Author(s):  
M. Gerbaux ◽  
C. Genthon ◽  
P. Etchevers ◽  
C. Vincent ◽  
J.P. Dedieu
Keyword(s):  
Climate Change ◽  
Mass Balance ◽  
Full Range ◽  
Balance Model ◽  
Surface Mass Balance ◽  
Equilibrium Line Altitude ◽  
Time Step ◽  
Meteorological Model ◽  
Surface Mass ◽  
French Alps

AbstractA new physically based distributed surface mass-balance model is presented for Alpine glaciers. Based on the Crocus prognostic snow model, it resolves both the temporal (1 hour time-step) and spatial (200 m grid-step) variability of the energy and mass balance of glaciers. Mass-balance reconstructions for the period 1981–2004 are produced using meteorological reconstruction from the SAFRAN meteorological model for Glacier de Saint-Sorlin and Glacier d’Argentière, French Alps. Both glaciers lost mass at an accelerated rate in the last 23 years. The spatial distribution of precipitation within the model grid is adjusted using field mass-balance measurements. This is the only correction made to the SAFRAN meteorological input to the glacier model, which also includes surface atmospheric temperature, moisture, wind and all components of downward radiation. Independent data from satellite imagery and geodetic measurements are used for model validation. With this model, glacier sensitivity to climate change can be separately evaluated with respect to a full range of meteorological parameters, whereas simpler models, such as degree-day models, only account for temperature and precipitation. We provide results for both mass balance and equilibrium-line altitude (ELA) using a generic Alpine glacier. The sensitivity of the ELA to air temperature alone is found to be 125 m °C–1, or 160 m °C¯1 if concurrent (Stefan–Boltzmann) longwave radiation change is taken into account.

Early 21st-century glacier surface mass balance across High Mountain Asia derived from remote sensing

2020 ◽  
Author(s):  
Evan Miles ◽  
Michael McCarthy ◽  
Amaury Dehecq ◽  
Marin Kneib ◽  
Stefan Fugger ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mass Balance ◽  
Surface Velocity ◽  
High Mountain ◽  
Surface Mass Balance ◽  
Equilibrium Line Altitude ◽  
Glacier Surface ◽  
Surface Mass ◽  
Early 21St Century ◽  
Debris Cover

<p>Glaciers in High Mountain Asia have experienced intense scientific scrutiny in the past decade due to their hydrological and societal importance. The explosion of freely-available satellite observations has greatly advanced our understanding of their thinning, motion, and overall mass losses, and it has become clear that they exhibit both local and regional variations due to debris cover, surging and climatic regime. However, our understanding of glacier accumulation and ablation rates is limited to a few individual sites, and altitudinal surface mass balance is essentially unknown across the vast region.</p><p>Here we combine recent assessments of ice thickness and surface velocity to correct observed glacier thinning rates for mass redistribution in a flowband framework to derive the first estimates of altitudinal glacier surface mass balance across the region. We first evaluate our results at the glacier scale with all available glaciological field measurements (27 glaciers), then analyze 4665 glaciers (we exclude surging and other anomalous glaciers) comprising 43% of area and 36% of mass for glaciers larger than 2 km<sup>2</sup> in the region. The surface mass balance results allow us to determine the equilibrium line altitude for each glacier for the period 2000-2016.  We then aggregate our altitudinal and hypsometric surface mass balance results to produce idealised profiles for distinct subregions, enabling us to consider the subregional heterogeneity of mass balance and the importance of debris-covered ice for the region’s overall ablation.</p><p>We find clear patterns of ELA variability across the region.  9% of glaciers accumulate mass over less than 10% of their area on average for the study period. These doomed  glaciers are concentrated in Nyainqentanglha, which also has the most negative mass balance of the subregions, whereas accumulation area ratios of 0.7-0.9 are common for glaciers in the neutral-balance Karakoram and Kunlun Shan. We find that surface debris extent is negatively correlated with ELA, explaining up to 1000 m of variability across the region and reflecting the importance of avalanching as a mass input for debris-covered glaciers at lower elevations. However, in contrast with studies of thinning rates alone, we find a clear melt reduction for low-elevation debris-covered glacier areas, consistent across regions, largely resolving the ‘debris cover anomaly’.  </p><p>Our results provide a comprehensive baseline for the health of the High Asian ice reservoirs in the early 21<sup>st</sup> Century. The estimates of altitudinal surface mass balance and ELAs will additionally enable novel strategies for the calibration of glacier and hydrological models. Finally, our results emphasize the potential of combined remote-sensing observations to understand the environmental factors and physical processes responsible for High Asia’s heterogeneous patterns of recent glacier evolution.</p>

scholarly journals Decelerated mass loss of Hurd and Johnsons Glaciers, Livingston Island, Antarctic Peninsula

2013 ◽  
Vol 59 (213) ◽  
pp. 115-128 ◽  
Author(s):  
Francisco J. Navarro ◽  
Ulf Y. Jonsell ◽  
María I. Corcuera ◽  
Alba Martín-Español
Keyword(s):  
Mass Balance ◽  
Total Mass ◽  
Meteorological Conditions ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
The Past ◽  
Mass Losses ◽  
Livingston Island ◽  
Tidewater Glacier ◽  
Observation Period

AbstractA new 10 year surface mass balance (SMB) record of Hurd and Johnsons Glaciers, Livingston Island, Antarctica, is presented and compared with earlier estimates on the basis of local and regional meteorological conditions and trends. Since Johnsons is a tidewater glacier, we also include a calving flux calculation to estimate its total mass balance. The average annual SMB over the 10 year observation period 2002–11 is −0.15 ± 0.10 m w.e. for Hurd Glacier and 0.05 ± 0.10 m w.e. for Johnsons Glacier. Adding the calving losses to the latter results in a total mass balance of −0.09 ± 0.10 m w.e. There has been a deceleration of the mass losses of these glaciers from 1957–2000 to 2002–11, which have nearly halved for both glaciers. We attribute this decrease in the mass losses to a combination of increased accumulation in the region and decreased melt. The increased accumulation is attributed to larger precipitation associated with the recent deepening of the circumpolar pressure trough, while the melt decrease is associated with lower summer surface temperatures during the past decade.

scholarly journals Spatial Heterogeneity in Glacier Mass-Balance Sensitivity across High Mountain Asia

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 776 ◽  
Author(s):  
Rongjun Wang ◽  
Shiyin Liu ◽  
Donghui Shangguan ◽  
Valentina Radić ◽  
Yong Zhang
Keyword(s):  
Climate Change ◽  
Spatial Variability ◽  
Spatial Heterogeneity ◽  
Mass Balance ◽  
High Sensitivity ◽  
High Mountain ◽  
Surface Mass Balance ◽  
Reference Surface ◽  
Surface Mass ◽  
The Relationship

Mass balance of glaciers in High Mountain Asia (HMA) varies substantially across the region. While the spatial variability is attributed to differences in climatic setting and sensitivity of these glaciers to climate change, an assessment of these factors to date has only been performed on a small sample of glaciers and a small set of climate perturbation scenarios. To advance the assessment to larger datasets, we first reconstruct the time series of reference-surface mass balance for 1952–2014 periods using an empirical model calibrated with observed mass balance from 45 glaciers across the HMA. Forcing the model with a set of independent stepwise changes of temperature (±0.5 K to ±6 K) and precipitation (±5% to ±30%), we assess the reference-surface mass balance sensitivity of each glacier in the sample. While the relationship between the change in mass balance and the change in precipitation is linear, the relationship with the change in temperature is non-linear. Spatial heterogeneity in the simulated mass balance sensitivities is attributed to differences in climatic setting, elevation, and the sensitivity of mass-balance profile (gradient) to changes in temperature and precipitation. While maritime and low-lying continental glaciers show high sensitivity to temperature changes and display a uniform mass-balance sensitivity with elevation, the high-lying continental glaciers show high sensitivity to precipitation changes and display a non-uniform mass-balance sensitivity with elevation. Our analysis reveals the dominant drivers of spatial variability in the mass balance sensitivity across the region: temperature as a single driver for maritime glaciers, and a superposition of temperature, precipitation seasonality, and snow/rain differentiation for continental glaciers. Finally, a set of sensitivity tests with perturbed model parameters confirms the robustness of our results. The model’s ability and robustness to resolve spatial patterns in the sensitivities and their drivers implies that simple modeling approaches remain a powerful tool for analyzing glacier response to climate change in HMA.

scholarly journals Modeling the evolution of the Juneau Icefield between 1971 and 2100 using the Parallel Ice Sheet Model (PISM)

2016 ◽  
Vol 62 (231) ◽  
pp. 199-214 ◽  
Author(s):  
FLORIAN A. ZIEMEN ◽  
REGINE HOCK ◽  
ANDY ASCHWANDEN ◽  
CONSTANTINE KHROULEV ◽  
CHRISTIAN KIENHOLZ ◽  
...  
Keyword(s):  
Mass Balance ◽  
Spatial Interpolation ◽  
Ice Sheet ◽  
Weather Research And Forecasting ◽  
High Mountain ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Orographic Effects ◽  
Ice Volume ◽  
Good Agreement

ABSTRACTWe study the evolution of the Juneau Icefield, one of the largest icefields in North America (>3700 km2), using the Parallel Ice Sheet Model (PISM). We test two climate datasets: 20 km Weather Research and Forecasting Model (WRF) output, and data from the Scenarios Network for Alaska Planning (SNAP), derived from spatial interpolation of observations. Good agreement between simulated and observed surface mass balance was achieved only after substantially adjusting WRF precipitation to account for unresolved orographic effects, while SNAP's climate pattern is incompatible with observations of surface mass balance. Using the WRF data forced with the RCP6.0 emission scenario, the model projects a decrease in ice volume by 58–68% and a 57–63% area loss by 2099 compared with 2010. If the modeled 2070–99 climate is held constant beyond 2099, the icefield is eliminated by 2200. With constant 1971–2010 climate, the icefield stabilizes at 86% of its present-day volume. Experiments started from an ice-free state indicate that steady-state volumes are largely independent of the initial ice volume when forced by identical scenarios of climate stabilization. Despite large projected volume losses, the complex high-mountain topography makes the Juneau Icefield less susceptible to climate warming than low-lying Alaskan icefields.

scholarly journals Relative contribution of surface mass-balance and ice-flux changes to the accelerated thinning of Mer de Glace, French Alps, over1979-2008

2012 ◽  
Vol 58 (209) ◽  
pp. 501-512 ◽  
Author(s):  
Etienne Berthier ◽  
Christian Vincent
Keyword(s):  
Mass Balance ◽  
Cross Sections ◽  
Important Implication ◽  
Mass Conservation ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
French Alps ◽  
Relative Contribution ◽  
Covered Area ◽  
Surface Topographies

AbstractBy subtracting surface topographies from 1979, 1994, 2000 and 2008, we measured icethinning rates increasing from 1 ma-1 (1979-94) to >4 ma-1 (2000-08) on the tongue of Mer de Glace, French Alps. The relative contributions of changes in surface mass balance and ice fluxes to this acceleration in the thinning are estimated using field and remote-sensing measurements. Between 1979-94 and 2000-08, surface mass balance diminished by 1.2mw.e.a-1, mainly because of atmospheric warming. Mass-balance changes induced by the growing debris-covered area and the evolving glacier hypsometry compensated each other. Meanwhile, Mer de Glace slowed down and the ice fluxes through two cross sections at 2200 and 2050ma.s.l. decreased by 60%. Between 1979-94 and 2000-08, two-thirds of the increase in the thinning rates was caused by reduced ice fluxes and one- third by rising surface ablation. However, these numbers need to be interpreted cautiously given our inability to respect mass conservation below our upper cross section. An important implication is that large errors would occur if one term of the continuity equation (e.g. surface mass balance) were deduced from the two others (e.g. elevation and ice-flux changes).

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