Greenland ice sheet mass loss has accelerated in the past decade responding to combined glacier discharge and surface melt water runoff increases. During summer, absorbed solar energy, modulated at ...the surface primarily by albedo, is the dominant factor governing surface melt variability in the ablation area. Using satellite-derived surface albedo with calibrated regional climate modeled surface air temperature and surface downward solar irradiance, we determine the spatial dependence and quantitative impact of the ice sheet albedo feedback over 12 summer periods beginning in 2000. We find that, while albedo feedback defined by the change in net solar shortwave flux and temperature over time is positive over 97% of the ice sheet, when defined using paired annual anomalies, a second-order negative feedback is evident over 63% of the accumulation area. This negative feedback damps the accumulation area response to warming due to a positive correlation between snowfall and surface air temperature anomalies. Positive anomaly-gauged feedback concentrated in the ablation area accounts for more than half of the overall increase in melting when satellite-derived melt duration is used to define the timing when net shortwave flux is sunk into melting. Abnormally strong anticyclonic circulation, associated with a persistent summer North Atlantic Oscillation extreme since 2007, enabled three amplifying mechanisms to maximize the albedo feedback: (1) increased warm (south) air advection along the western ice sheet increased surface sensible heating that in turn enhanced snow grain metamorphic rates, further reducing albedo; (2) increased surface downward shortwave flux, leading to more surface heating and further albedo reduction; and (3) reduced snowfall rates sustained low albedo, maximizing surface solar heating, progressively lowering albedo over multiple years. The summer net infrared and solar radiation for the high elevation accumulation area approached positive values during this period. Thus, it is reasonable to expect 100% melt area over the ice sheet within another similar decade of warming.
The Arctic‐wide melt season has lengthened at a rate of 5 days decade−1 from 1979 to 2013, dominated by later autumn freezeup within the Kara, Laptev, East Siberian, Chukchi, and Beaufort seas ...between 6 and 11 days decade−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 752 MJ m−2 during the last decade increases sea surface temperatures by 0.5 to 1.5 °C and largely explains the observed delays in autumn freezeup 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−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.
Key Points
Melt season has lengthenedIncreased sea surface temperatures led to a delay in autumn freezeupIncreased solar absorption melts an extra 1 m of ice
Over the past decade, the Arctic has seen unprecedented declines in the summer sea ice area, leading to larger and longer exposed open water areas. The Atmospheric Infrared Sounder is a useful yet ...underutilized tool to study corresponding atmospheric changes and their feedbacks between 2003 and 2013. Most pronounced warming occurs between November and April, with skin and air temperatures increasing on average 2.5 K and 1.5 K over the Arctic Ocean. In response to sea ice loss, evaporation rates (i.e., moisture flux) increased between August and October by 1.5 × 10−3 g m−2 s−1 (3.8 W m−2 latent heat flux energy), increasing the water vapor feedback and cloud cover. Although most trends are positive over the Arctic Ocean, there is considerable interannual variability. Increasing specific humidity in May and corresponding downward moisture fluxes cause earlier melt onset; warming skin temperatures and radiative responses to increased water vapor and cloud cover in autumn delay freeze‐up.
Key Points
AIRS data reveal a warmer and wetter Arctic
Arctic atmospheric changes drive melt onset and freeze‐up
Satellite passive microwave observations document an overall downward trend in Arctic sea ice extent and area since 1978. While the record minimum observed in September 2002 strongly reinforced this ...downward trend, extreme ice minima were again observed in 2003 and 2004. Although having three extreme minimum years in a row is unprecedented in the satellite record, attributing these recent trends and extremes to greenhouse gas loading must be tempered by recognition that the sea ice cover is variable from year to year in response to wind, temperature and oceanic forcings.
As Arctic sea ice and its overlying snow cover thin, more light penetrates into the ice and upper ocean, shifting the phenology of algal growth within the bottom of sea ice, with cascading impacts on ...higher trophic levels of the Arctic marine ecosystem. While field data or autonomous observatories provide direct measurements of the coupled sea ice‐algal system, they are limited in space and time. Satellite observations of key sea ice variables that control the amount of light penetrating through sea ice offer the possibility to map the under‐ice light field across the entire Arctic basin. This study provides the first satellite‐based estimates of potential sea ice‐associated algal bloom onset dates since the launch of CryoSat‐2 and explores how a changing snowpack may have shifted bloom onset timings over the last four decades.
Plain Language Summary
Light plays a key role in sustaining life in the ocean. In the polar regions, sea ice and its overlying snow cover limit the amount of light reaching the upper Light plays a key role in sustaining life in the ocean. In the polar regions, sea ice and its overlying snow cover limit the amount of light reaching the upper ocean. Ice algae mainly live at the bottom centimeters of the ice and are important primary producers, using CO2 and inorganic nutrients to release O2 and create organic matter that is available to other trophic levels of the marine ecosystem. Every year rapid growth of bottom‐ice algae, known as the bloom onset, is triggered by the return of the sun and the increase in light intensities above that needed for photosynthesis to occur. Studies have shown that ice algae are shade adapted and can bloom under very low light conditions, yet the impact of recent changes in the snow‐ice cover that allow more light to penetrate earlier in the spring season remain uncertain. This study takes satellite data to map how ice algal bloom onset may be changing over time.
Key Points
New processing methods to satellite data allow for daily under‐ice light mapping
Satellite approaches allow for scaling up to the pan‐Arctic scale
Phenology of ice‐algal bloom onset is strongly tied to snow cover variability
Pan-Arctic sea ice thickness has been monitored over recent decades by satellite radar altimeters such as CryoSat-2, which emits Ku-band radar waves that are assumed in publicly available sea ice ...thickness products to penetrate overlying snow and scatter from the ice–snow interface. Here we examine two expressions for the time delay caused by slower radar wave propagation through the snow layer and related assumptions concerning the time evolution of overlying snow density. Two conventional treatments introduce systematic underestimates of up to 15 cm into ice thickness estimates and up to 10 cm into thermodynamic growth rate estimates over multi-year ice in winter. Correcting these biases would impact a wide variety of model projections, calibrations, validations and reanalyses.
Mean sea ice thickness is a sensitive indicator of Arctic climate change and is in long-term decline despite significant interannual variability. Current thickness estimations from satellite radar ...altimeters employ a snow climatology for converting range measurements to sea ice thickness, but this introduces unrealistically low interannual variability and trends. When the sea ice thickness in the period 2002–2018 is calculated using new snow data with more realistic variability and trends, we find mean sea ice thickness in four of the seven marginal seas to be declining between 60 %–100 % faster than when calculated with the conventional climatology. When analysed as an aggregate area, the mean sea ice thickness in the marginal seas is in statistically significant decline for 6 of 7 winter months. This is observed despite a 76 % increase in interannual variability between the methods in the same time period. On a seasonal timescale we find that snow data exert an increasingly strong control on thickness variability over the growth season, contributing 46 % in October but 70 % by April. Higher variability and faster decline in the sea ice thickness of the marginal seas has wide implications for our understanding of the polar climate system and our predictions for its change.
A new long-term data record of Fram Strait sea ice area export from 1935 to 2014 is developed using a combination of satellite radar images and station observations of surface pressure across Fram ...Strait. This data record shows that the long-term annual mean export is about 880 000 km2, representing 10 % of the sea-ice-covered area inside the basin. The time series has large interannual and multi-decadal variability but no long-term trend. However, during the last decades, the amount of ice exported has increased, with several years having annual ice exports that exceeded 1 million km2. This increase is a result of faster southward ice drift speeds due to stronger southward geostrophic winds, largely explained by increasing surface pressure over Greenland. Evaluating the trend onwards from 1979 reveals an increase in annual ice export of about +6 % per decade, with spring and summer showing larger changes in ice export (+11 % per decade) compared to autumn and winter (+2.6 % per decade). Increased ice export during winter will generally result in new ice growth and contributes to thinning inside the Arctic Basin. Increased ice export during summer or spring will, in contrast, contribute directly to open water further north and a reduced summer sea ice extent through the ice–albedo feedback. Relatively low spring and summer export from 1950 to 1970 is thus consistent with a higher mid-September sea ice extent for these years. Our results are not sensitive to long-term change in Fram Strait sea ice concentration. We find a general moderate influence between export anomalies and the following September sea ice extent, explaining 18 % of the variance between 1935 and 2014, but with higher values since 2004.
Regional climate model runs using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesocale Model modified for use in polar regions (Polar MM5), calibrated ...by independent in situ observations, demonstrate coherent regional patterns of Greenland ice sheet surface mass balance (SMB) change over a 17-yr period characterized by warming (1988–2004). Both accumulation and melt rates increased, partly counteracting each other for an overall negligible SMB trend. However, a 30% increase in meltwater runoff over this period suggests that the overall ice sheet mass balance has been increasingly negative, given observed meltwater-induced flow acceleration. SMB temporal variability of the whole ice sheet is best represented by ablation zone variability, suggesting that increased melting dominates over increased accumulation in a warming scenario. The melt season grew in duration over nearly the entire ablation zone by up to 40 days, 10 days on average. Accumulation area ratio decreased by 3%. Albedo reductions are apparent in five years of the Moderate Resolution Imaging Spectroradiometer (MODIS) derived data (2000–04). The Advanced Very High Resolution Radiometer (AVHRR)-derived albedo changes (1988–99) were less consistent spatially. A conservative assumption as to glacier discharge and basal melting suggests an ice sheet mass loss over this period greater than 100 km³ yr¹, framing the Greenland ice sheet as the largest single glacial contributor to recent global sea level rise. Surface mass balance uncertainty, quantified from residual random error between model and independent observations, suggests two things: 1) changes smaller than approximately 200 km³ yr−1would not satisfy conservative statistical significance thresholds (i.e., two standard deviations) and 2) although natural variability and model uncertainty were separated in this analysis, the magnitude of each were roughly equivalent. Therefore, improvements in model accuracy and analysis of longer periods (assuming larger changes) are both needed for definitive mass balance change assessments.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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