116 research outputs found
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Modelling the fate of surface melt on the Larsen C Ice Shelf
Surface melt lakes lower the albedo of ice shelves, leading to additional surface melting. This can substantially alter the surface energy balance and internal temperature and density profiles of the ice shelf. Evidence suggests that melt lakes also played a pivotal role in the sudden collapse of the Larsen B Ice Shelf in 2002. Here a recently developed, high-physical-fidelity model accounting for the development cycle of melt lakes is applied to the Larsen C Ice Shelf, Antarctica’s most northern ice shelf and one where melt lakes have been observed. We simulate current conditions on the ice shelf using weather station and reanalysis data and investigate the impacts of potential future increases in precipitation and air temperature on melt lake formation, for which concurrent increases lead
to an increase in lake depth. Finally, we assess the viability in future crevasse propagation through the ice shelf due to surface meltwater accumulation
Skillful spring forecasts of September Arctic sea ice extent using passive microwave sea ice observations
In this study, we demonstrate skillful spring forecasts of detrended September Arctic sea ice extent using passive microwave observations of sea ice concentration (SIC) and melt onset (MO). We compare these to forecasts produced using data from a sophisticated melt pond model, and find similar to higher skill values, where the forecast skill is calculated relative to linear trend persistence. The MO forecasts shows the highest skill in March–May, while the SIC forecasts produce the highest skill in June–August, especially when the forecasts are evaluated over recent years (since 2008). The high MO forecast skill in early spring appears to be driven primarily by the presence and timing of open water anomalies, while the high SIC forecast skill appears to be driven by both open water and surface melt processes. Spatial maps of detrended anomalies highlight the drivers of the different forecasts, and enable us to understand regions of predictive importance. Correctly capturing sea ice state anomalies, along with changes in open water coverage appear to be key processes in skillfully forecasting summer Arctic sea ice
Validation of "(fr)AGILE": A quick tool to identify multidimensional frailty in the elderly
Background Several tools have been proposed and validated to operationally define frailty. Recently, the Italian Frailty index (IFi), an Italian modified version of Frailty index, has been validated but its use in clinical practice is limited by long time of administration. Therefore, the aim of this study was to create and validate a quick version of the IFi (AGILE). Methods Validation study was performed by administering IFi and AGILE, after a Comprehensive Geriatric Assessment (CGA) in 401 subjects aged 65 or over (77 +/- 7 years). AGILE was a 10-items tool created starting from the more predictive items of the four domains of frailty investigated by IFi (mental, physical, socioeconomic and nutritional). AGILE scores were stratified in light, moderate and severe frailty. At 24 months of follow-up, death, disability (taking into account an increase in ADL lost >= 1 from the baseline) and hospitalization were considered. Area under curve (AUC) was evaluated for both IFi and AGILE. Results Administration time was 9.5 +/- 3.8 min for IFi administered after a CGA, and 2.4 +/- 1.2 min for AGILE, regardless of CGA (p < 0.001). With increasing degree of frailty, prevalence of mortality increased progressively from 6.5 to 41.8% and from 9.0 to 33.3%, disability from 16.1 to 64.2% and from 22.1 to 59.8% and hospitalization from 17.2 to 58.7% and from 27.0 to 52.2% with AGILE and IFi, respectively (p = NS). Relative Risk for each unit of increase in AGILE was 56, 44 and 24% for mortality, disability and hospitalization, respectively and was lower for IFi (8, 7 and 4% for mortality, disability and hospitalization, respectively). The AUC was higher in AGILE vs. IFi for mortality (0.729 vs. 0.698), disability (0.715 vs. 0.682) and hospitalization (0.645 vs. 0.630). Conclusions Our study shows that AGILE is a rapid and effective tool for screening multidimensional frailty, able to predict mortality, disability and hospitalization, especially useful in care settings that require reliable assessment instruments with short administration time
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A mathematical model of melt lake development on an ice shelf
The accumulation of surface meltwater on ice shelves can lead to the formation of melt lakes. Melt lakes have been implicated in ice shelf collapse; Antarctica's Larsen B Ice Shelf was observed to have a large amount of surface melt lakes present preceding its collapse in 2002. Such collapse can affect ocean circulation and temperature, cause habitat loss and contribute to sea level rise through the acceleration of tributary glaciers. We present a mathematical model of a surface melt lake on an idealised ice shelf. The model incorporates a calculation of the ice shelf surface energy balance, heat transfer through the firn, the production and percolation of meltwater into the firn, the formation of ice lenses and the development and refreezing of surface melt lakes.
The model is applied to the Larsen C Ice Shelf, where melt lakes have been observed. This region has warmed several times the global average over the last century and the Larsen C firn layer could become saturated with meltwater by the end of the century.
When forced with weather station data, our model produces surface melting, meltwater accumulation, and melt lake development consistent with observations. We examine the sensitivity of lake formation to uncertain parameters, and provide evidence of the importance of processes such as lateral meltwater transport.
We conclude that melt lakes impact surface melt and firn density and warrant inclusion in dynamic-thermodynamic models of ice shelf evolution within climate models, of which our model could form the basis for the thermodynamic component
Solution structure of the inner DysF domain of myoferlin and implications for limb girdle muscular dystrophy type 2b
Mutations in the protein dysferlin, a member of the ferlin family, lead to limb girdle muscular dystrophy type 2B and Myoshi myopathy. The ferlins are large proteins characterised by multiple C2 domains and a single C-terminal membrane-spanning helix. However, there is sequence conservation in some of the ferlin family in regions outside the C2 domains. In one annotation of the domain structure of these proteins, an unusual internal duplication event has been noted where a putative domain is inserted in between the N- and C-terminal parts of a homologous domain. This domain is known as the DysF domain. Here, we present the solution structure of the inner DysF domain of the dysferlin paralogue myoferlin, which has a unique fold held together by stacking of arginine and tryptophans, mutations that lead to clinical disease in dysferlin
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Study of the impact of ice formation in leads upon the sea ice pack mass balance using a new frazil and grease ice parameterization
Leads are cracks in sea ice that often form because of deformation. During winter months, leads expose the ocean to the cold atmosphere, resulting in supercooling and the formation of frazil ice crystals within the mixed layer. Here the authors investigate the role of frazil ice formation in leads on the mass balance of the sea ice pack through the incorporation of a new module into the Los Alamos sea ice model (CICE). The frazil ice module considers an initial cooling of leads followed by a steady-state formation of uniformly distributed single size frazil ice crystals that precipitate to the ocean surface as grease ice. The grease ice is pushed against one of the lead edges by wind and water drag that the authors represent through a variable collection thickness for new sea ice. Simulations of the sea ice cover in the Arctic and Antarctic are performed and compared to a model that treats leads the same as the open ocean. The processes of ice formation in the new module slow down the refreezing of leads, resulting in a longer period of frazil ice production. The fraction of frazil-derived sea ice increases from 10% to 50%, corresponding better to observations. The new module has higher ice formation rates in areas of high ice concentration and thus has a greater impact within multiyear ice than it does in the marginal seas. The thickness of sea ice in the central Arctic increases by over 0.5 m, whereas within the Antarctic it remains unchanged
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Sea-ice-free Arctic during the Last Interglacial supports fast future loss
The Last Interglacial (LIG), a warmer period 130-116 ka before present, is a potential analog for future climate change. Stronger LIG summertime insolation at high northern latitudes drove Arctic land summer temperatures 4-5 °C higher than the preindustrial era. Climate model simulations have previously failed to capture these elevated temperatures, possibly because they were unable to correctly capture LIG sea-ice changes. Here, we show the latest version of the fully-coupled UK Hadley Center climate model (HadGEM3) simulates a more accurate Arctic LIG climate, including elevated temperatures. Improved model physics, including a sophisticated sea-ice melt-pond scheme, result in a complete simulated loss of Arctic sea ice in summer during the LIG, which has yet to be simulated in past generations of models. This ice-free Arctic yields a compelling solution to the longstanding puzzle of what drove LIG Arctic warmth and supports a fast retreat of future Arctic summer sea ice
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