Investigating the local-scale influence of sea ice on Greenland surface melt

Rapid decline in Arctic sea ice cover in the 21st century may have wide-reaching effects on the Arctic climate system, including the Greenland ice sheet mass balance. Here, we investigate whether local changes in sea ice around the Greenland ice sheet have had an impact on Greenland surface melt. Specifically, we investigate the relationship between sea ice concentration, the timing of melt onset and open-water fraction surrounding Greenland with ice sheet surface melt using a combination of remote sensing observations, and outputs from a reanalysis model and a regional climate model for the period of 1979–2015. Statistical analysis points to covariability between Greenland ice sheet surface melt and sea ice within Baffin Bay and Davis Strait. While some of this covariance can be explained by simultaneous influence of atmospheric circulation anomalies on both the sea ice cover and Greenland melt, within Baffin Bay we find a modest correlation between detrended melt onset over sea ice and the adjacent ice sheet melt onset. This correlation appears to be related to increased transfer of sensible and latent heat fluxes from the ocean to the atmosphere in early sea ice melt years, increasing temperatures and humidity over the ice sheet that in turn initiate ice sheet melt

Generic Supersonic and Hypersonic Configurations

Abstract: A geometry generator for preliminary aerodynamic design, parametric optimization and the preprocessing of CFD boundary conditions is presented. With emphasis on supersonic aircraft components, ranging from waverider caret wings to generic lifting bodies derived from recent aerospace research projects, the simple mathematical basis and its consequent use throughout various applications is illustrated

Warm winter, thin ice?

Winter 2016/2017 saw record warmth over the Arctic Ocean, leading to the least amount of freezing degree days north of 70° N since at least 1979. The impact of this warmth was evaluated using model simulations from the Los Alamos sea-ice model (CICE) and CryoSat-2 thickness estimates from three different data providers. While CICE simulations show a broad region of anomalously thin ice in April 2017 relative to the 2011–2017 mean, analysis of three CryoSat-2 products show more limited regions with thin ice and do not always agree with each other, both in magnitude and direction of thickness anomalies. CICE is further used to diagnose feedback processes driving the observed anomalies, showing 11–13 cm reduced thermodynamic ice growth over the Arctic domain used in this study compared to the 2011–2017 mean, and dynamical contributions of +1 to +4 cm. Finally, CICE model simulations from 1985–2017 indicate the negative feedback relationship between ice growth and winter air temperatures may be starting to weaken, showing decreased winter ice growth since 2012 as winter air temperatures have increased and the freeze-up has been further delayed

Changes in Arctic Melt Season and Implications for Sea Ice Loss

The Arctic-wide melt season has lengthened at a rate of 5 days dec-1 from 1979 to 2013, dominated by later autumn freeze-up within the Kara, Laptev, East Siberian, Chukchi and Beaufort seas between 6 and 11 days dec(exp -1). While melt onset trends are generally smaller, the timing of melt onset has a large influence on the total amount of solar energy absorbed during summer. The additional heat stored in the upper ocean of approximately 752MJ m(exp -2) during the last decade, increases sea surface temperatures by 0.5 to 1.5 C and largely explains the observed delays in autumn freeze-up within the Arctic Ocean's adjacent seas. Cumulative anomalies in total absorbed solar radiation from May through September for the most recent pentad locally exceed 300-400 MJ m(exp -2) in the Beaufort, Chukchi and East Siberian seas. This extra solar energy is equivalent to melting 0.97 to 1.3 m of ice during the summer

Detecting failure of climate predictions

The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055

Estimating snow depth over Arctic sea ice from calibrated dual-frequency radar freeboards

Snow depth on sea ice remains one of the largest uncertainties in sea ice thickness retrievals from satellite altimetry. Here we outline an approach for deriving snow depth that can be applied to any coincident freeboard measurements after calibration with independent observations of snow and ice freeboard. Freeboard estimates from CryoSat-2 (Ku band) and AltiKa (Ka band) are calibrated against data from NASA's Operation IceBridge (OIB) to align AltiKa with the snow surface and CryoSat-2 with the ice–snow interface. Snow depth is found as the difference between the two calibrated freeboards, with a correction added for the slower speed of light propagation through snow. We perform an initial evaluation of our derived snow depth product against OIB snow depth data by excluding successive years of OIB data from the analysis. We find a root-mean-square deviation of 7.7, 5.3, 5.9, and 6.7 cm between our snow thickness product and OIB data from the springs of 2013, 2014, 2015, and 2016 respectively. We further demonstrate the applicability of the method to ICESat and Envisat, offering promising potential for the application to CryoSat-2 and ICESat-2, which launched in September 2018

Estimating snow depth over Arctic sea ice from calibrated dual-frequency radar freeboards

Snow depth on sea ice remains one of the largest uncertainties in sea ice thickness retrievals from satellite altimetry. Here we outline an approach for deriving snow depth that can be applied to any coincident freeboard measurements after calibration with independent observations of snow and ice freeboard. Freeboard estimates from CryoSat-2 (Ku band) and AltiKa (Ka band) are calibrated against data from NASA's Operation IceBridge (OIB) to align AltiKa with the snow surface and CryoSat-2 with the ice–snow interface. Snow depth is found as the difference between the two calibrated freeboards, with a correction added for the slower speed of light propagation through snow. We perform an initial evaluation of our derived snow depth product against OIB snow depth data by excluding successive years of OIB data from the analysis. We find a root-mean-square deviation of 7.7, 5.3, 5.9, and 6.7&thinsp;cm between our snow thickness product and OIB data from the springs of 2013, 2014, 2015, and 2016 respectively. We further demonstrate the applicability of the method to ICESat and Envisat, offering promising potential for the application to CryoSat-2 and ICESat-2, which launched in September 2018.</p

Increasing Multiyear Sea Ice Loss in the Beaufort Sea: A New Export Pathway for the Diminishing Multiyear Ice Cover of the Arctic Ocean

Historically, multiyear sea ice (MYI) covered a majority of the Arctic and circulated through the Beaufort Gyre for years. However, increased ice melt in the Beaufort Sea during the early 2000s was proposed to have severed this circulation. Constructing a regional MYI budget from 1997 to 2021 reveals that MYI import into the Beaufort Sea has increased year-round, yet less MYI now survives through summer and is transported onwards in the Gyre. Annual average MYI loss quadrupled over the study period and increased from ∼7% to ∼33% of annual Fram Strait MYI export, while the peak in 2018 (385,000 km2) was similar in magnitude to Fram Strait MYI export. The ice-albedo feedback coupled with the transition toward younger thinner MYI is responsible for the increased MYI loss. MYI transport through the Beaufort Gyre has not been severed, but it has been reduced so severely to prevent it from being redistributed throughout the Arctic Ocean

Atmospheric drivers of Greenland surface melt revealed by self-organizing maps

Recent acceleration in surface melt on the Greenland ice sheet (GrIS) has occurred concurrently with a rapidly warming Arctic and has been connected to persistent, anomalous atmospheric circulation patterns over Greenland. To identify synoptic setups favoring enhanced GrIS surface melt and their decadal changes, we develop a summer Arctic synoptic climatology by employing self-organizing maps. These are applied to daily 500 hPa geopotential height fields obtained from the Modern Era Retrospective Analysis for Research and Applications reanalysis, 1979–2014. Particular circulation regimes are related to meteorological conditions and GrIS surface melt estimated with outputs from the Modèle Atmosphérique Régional. Our results demonstrate that the largest positive melt anomalies occur in concert with positive height anomalies near Greenland associated with wind, temperature, and humidity patterns indicative of strong meridional transport of heat and moisture. We find an increased frequency in a 500 hPa ridge over Greenland coinciding with a 63% increase in GrIS melt between the 1979–1988 and 2005–2014 periods, with 75.0% of surface melt changes attributed to thermodynamics, 17% to dynamics, and 8.0% to a combination. We also confirm that the 2007–2012 time period has the largest dynamic forcing relative of any period but also demonstrate that increased surface energy fluxes, temperature, and moisture separate from dynamic changes contributed more to melt even during this period. This implies that GrIS surface melt is likely to continue to increase in response to an ever warmer future Arctic, regardless of future atmospheric circulation patterns

A baseline evaluation of atmospheric and river discharge conditions in the Hudson Bay Complex during 2016-2018

In this article, we examine atmospheric and river discharge conditions within the Hudson Bay Complex for the BaySys 2016–2018 field program time frame. Investigated in particular is a subset of European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis - Interim (ERA-Interim) atmospheric forcing variables, namely 2-m surface temperature, 10-m surface winds, precipitation, and sea-level pressure, in addition to river discharge. Results from this assessment show that 2016 was characterized by unusually warm conditions (terrestrial and marine) throughout the annual cycle; 2017 by strong cyclone activity in March and high precipitation in January, October, and November; and 2018 by cold and windy conditions throughout the annual cycle. Evaluation of terrestrial conditions showed higher than normal land surface temperatures (the Hudson Bay physical watershed) for all of the 2016–2018 period (excluding a colder than normal spell August–November 2018), particularly in January (2016 and 2017), higher than normal precipitation in October (2016 and 2017), and higher than normal terrestrial discharge to the Hudson Bay Complex in March (2016 and 2017), with drier than average June through October (2016–2018)