nisqually glacier response to climate change

Another source of discrepancy between both models comes from the different MB data used to calibrate or train the MB models. This is well in agreement with the known uncertainties of glacier evolution models, with glacier ice thickness being the second largest uncertainty after the future GCM-RCM-RCP climate members used to force the model29. Average ice velocities on the Nisqually Glacier were previously measured at approximately 200 mm/day (8 in) (Hodge 1974). (Zenodo, 2020). The Cryosphere 12, 13671386 (2018). Our previous work31 has shown that linear MB models can be correctly calibrated for data around the mean temperature and precipitation values used during training, giving similar results and performance to deep learning. Glacier ice thickness observations are available for four different glaciers in the regions, which were compared to the estimates used in this model. Map-based methods for estimating glacier equilibrium-line altitudes J. Glaciol. Changes in DDFs with respect to air temperature also strongly depend on albedo, with ice presenting a substantially more nonlinear response than snow. Future projections of glacier-wide MB evolution were performed using climate projections from ADAMONT25. An enhanced temperature-index glacier melt model including the shortwave radiation balance: development and testing for Haut Glacier dArolla, Switzerland. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate. https://doi.org/10.1016/B978-0-12-821575-3.00009-8. a1), but when conditions deviate from this mean training data centroid, the Lasso can only linearly approximate the extremes based on the linear trend set on the main cluster of average values (Fig. Our analyses suggest that these limitations can also be translated to temperature-index MB models, as they share linear relationships between PDDs and melt, as well as precipitation and accumulation. These measurements of surface elevation were begun by personnel of the Tacoma The first main difference is related to the climate data used to force the models. Response of KarakoramHimalayan glaciers to climate variability and S10). A recent study he did found that 80 percent of the glaciers in Alberta and British Columbia could melt in the next 50 years. Conversely, during the accumulation season, glaciers are mostly covered by snow, with a much higher albedo and a reduced role of shortwave radiation in the MB that will persist even under climate change. This implies that specific climatic differences between massifs can be better captured by ALPGM than GloGEMflow. Since both MB models also include monthly temperature data as predictors, this CPDD anomaly was distributed evenly between the ablation season (April 1September 30), following the expected increase in mostly summer temperatures instead of winter temperatures in the future (Fig. Our projections show a strong glacier mass loss for all 29 climate members, with average ice volume losses by the end of the century of 75%, 80%, and 88% compared to 2015 under RCP 2.6 (9%, n=3), RCP 4.5 (17% +11%, n=13) and RCP 8.5 (15% +11%, n=13), respectively (Fig. As Arctic warms, Canada's glaciers playing major role in sea - CBC

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