Recent declines in Arctic sea ice and snow extent have led to an increase in the absorption of solar energy at the surface, resulting in additional surface heating and a further decline in snow and ice. Using 34 years of satellite data, 1982–2015, we found that the positive trend in solar absorption over the Arctic Ocean is more than double that over Arctic land, and the magnitude of the ice–albedo feedback is four times that of the snow–albedo feedback in summer. The timing of the high-to-low albedo transition has shifted closer to the greater insolation of the summer solstice over ocean, but further away from the summer solstice over land. Therefore, decreasing sea ice cover, not changes in terrestrial snow cover, has been the dominant radiative feedback mechanism over the last few decades.
Over the last few decades satellites have observed an unprecedented reduction
in Arctic sea ice extent (Pistone et al., 2014; Parkinson et al., 1999;
Stroeve et al., 2012). Sea ice extent has decreased dramatically, with the
10 lowest minimum Arctic sea ice extents after 2007. The Arctic-wide melt
season has become longer from 1979 to 2013 with a rate of 5 days per decade
(Stroeve et al., 2014). September sea ice extent decreased by 45 % from
1979 to 2016, and if current trends continue, some Arctic shelf seas are
forecasted to be ice-free during summer in the 2020s (Onarheim et al., 2018).
Over northern hemispheric land, snow cover extent has been decreasing in all
seasons (Hori et al., 2017). Shrinking sea ice cover and terrestrial snow
cover decrease the reflectivity (albedo) of the surface, resulting in more
absorption of solar (shortwave) radiation, more surface heating, and further
reductions in snow and ice. These processes are known as the sea ice–albedo
feedback over ocean and the snow–albedo feedback over land. Here we examine
how changes in surface albedo over the ocean and land areas of the Arctic
have affected shortwave absorption differently and how this interplay
between albedo and shortwave absorption may change in the future. Results are
presented for the majority of the satellite record, from 1982 to 2015, and
for the pan-Arctic from 60
Between 1979 and 2011, the Arctic top-of-atmosphere (TOA, planetary) albedo decreased from 0.52 to 0.48, and subsequent years with record or near-record low sea ice extent have further increased the amount of heat absorbed in the Arctic (Pistone et al., 2014). As the multiyear ice concentration decreases and is replaced by open water in the summer and thin first-year ice in the winter, the darker surfaces reflect less sunlight and absorb more energy. The total absorbed solar radiation for the Arctic Ocean has therefore increased. Pinker et al. (2014) and Kashiwase et al. (2017) examined shortwave absorption in the upper Arctic Ocean, with the latter finding that increases in open water may have led to a 50 % increase in absorption since 1979.
The recent decreases in Arctic albedo are not entirely due to reduced sea ice
cover, but also due to changes in the terrestrial snow cover (Robinson and
Frei, 2000). Snow extent has decreased over Eurasia and North America since
the late 1980s (Robinson and Frei, 2000; Kato et al., 2006) and is expected
to continue decreasing by 3.7 % (
Though the radiative effects of reduced snow and ice cover are straightforward, changing surface types in the Arctic may initiate albedo interactions that are complex. More open water in the Arctic Ocean has also led to an increase in cloud cover (Liu et al., 2012), which could offset the decreases in summer albedo caused by melting ice (Kato et al., 2006) and the replacement of multiyear ice with thinner first-year ice (Nghiem et al., 2007). In winter, when clouds inhibit radiative cooling of ice and open water, large anomalies in cloud cover may enhance or deter refreezing. This preconditioning of sea ice in the winter can influence the initial ice conditions for the spring melt and affect sea ice concentration (and therefore the Arctic albedo) through the melting season and into the fall of the following year (Letterly et al., 2016; Liu and Key, 2014).
The radiative feedbacks of changing snow cover and sea ice in the Northern
Hemisphere have been studied (Perovich and Light, 2015; Fernandes et al.,
2009; Flanner et al., 2011; Perovich et al., 2007). Perovich et al. (2007)
analyzed the changes in solar energy during the melting period in the Arctic,
but only over the period 1998–2004. Flanner et al. (2011) used
TOA fluxes to determine that the total impact of the
cryosphere on radiative forcing between 1979 and 2008 was
With satellite-derived surface radiative flux data now available from the
early 1980s, it is now possible to study the relative effects of changing
snow cover and sea ice on the Arctic surface energy budget. Does the
increasingly early arrival of snowmelt in the spring reduce the Arctic
surface albedo more than the decrease in sea ice during the summer? Have the
climatological changes associated with a warming Arctic affected the
absorption of solar radiation more over land or over sea? Will trends in
Arctic land and ocean surface albedo result in similar trends in solar
radiation absorption in the near future? In this study, we use
satellite-derived surface radiative fluxes from 1982 to 2015 to examine the
interannual changes in surface albedo and the absorption of solar energy
caused by the timing of the melt onset and to estimate the major albedo
feedbacks from the ocean and land. This study focuses on the effects of snow
and ice cover changes on the surface shortwave radiation budget of the Arctic
– defined as the area poleward of 60
The primary dataset for this study is the Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder Extended (APP-x) (Key et al., 2016). APP-x consists of twice-daily 25 km composites at two local solar times in the Arctic (04:00 and 14:00) and Antarctic (02:00 and 14:00) starting in 1982. Data from 1982 through 2015 at 14:00 local solar time (high sun) are employed. APP-x includes surface temperature, surface broadband albedo, sea ice thickness, cloud properties (coverage, optical depth, effective particle size, thermodynamic phase, and top pressure), and radiative fluxes at the surface and TOA. In APP-x, the retrieval of surface albedo involves four steps. First, the reflectances of the two shortwave channels are converted to a broadband reflectance. Then, the TOA broadband reflectance is corrected for anisotropy and atmospheric attenuation and converted from TOA broadband albedo to a surface broadband albedo. Finally, the surface clear-sky broadband albedo is adjusted for the effects of cloud cover in cloudy pixels over snow and ice (Key et al., 2001). The reflectance is also corrected for dependencies on sun-satellite-surface viewing geometry. Uncertainties in the retrieval of surface albedo are larger in cloudy-sky conditions than in clear-sky conditions. Downwelling fluxes at the surface are computed with a neural network, called FLUXNET, which is trained to simulate a radiative transfer model (Key and Schweiger, 1998). The neural network uses derived geophysical variables as input (Key and Wang, 2015). To determine the absorbed shortwave energy at the surface, the downwelling shortwave flux was multiplied by the surface absorption (1 minus albedo) for each pixel. More details of the algorithms are described in Key et al. (2016) and references therein.
The study areas are land and non-land between 60 and 90
Average annual surface shortwave absorption (W m
APP-x data show that annual mean absorbed solar radiation at the Arctic
surface has increased over the 1982–2015 period (Fig. 1). The magnitude of
absorption and the rate of increase, however, were different for land and
ocean. Trends in surface albedo, surface temperature, cloud cover, and
shortwave radiation are calculated using annual mean values with a linear
least-square fit regression over the 34-year period, and confidence
of the trends is calculated using two-tail Student's
The larger trend over ocean than land results from the larger albedo difference between dry, snow-covered sea ice (greater than 0.8) and open water (0.1) (Rösel et al., 2012) than between snow-covered land (0.85) (Greenfell and Perovich, 2004) and land during the melting season (0.2–0.4) (Sturm et al., 2005). Though the change in shortwave absorption over ocean areas outpaces that of land, the greater magnitude of absorption over land, i.e., the actual amount of energy absorbed, is due to greater insolation at lower latitudes. The radiative feedbacks associated with these changes in absorption over both land and ocean are discussed later.
Trends in absorbed radiation for selected months over
ocean
Figure 2 shows the spatial pattern of shortwave absorption trends over the
Arctic for April, May, June, and September. These months were chosen because
they illustrate the changes during the annual transition from high to low
snow cover over land (April and May), high to low sea ice cover over ocean
(June), and the annual sea ice minimum (September). Over Arctic land, the
strong increase in absorption due to decreasing springtime snow cover
(Robinson and Frei, 2000; Stone et al., 2002) is seen in May. Absorption
trends in northern Europe, central Siberia, and the Alaskan interior are
particularly affected by this loss in snow, and this spatial pattern of
radiative forcing was also seen by Flanner et al. (2011). Land areas show the
greatest absorption increase from March through May, with average May
absorption increasing by 1 W m
In contrast, most of the sea ice lasts through early summer, but changes in sea ice thickness and the formation of melt ponds still allow for changes in absorption (Perovich and Polashenski, 2012). Sea ice albedo typically decreases with thickness (Lindsay, 2001), and an increase in melt pond fraction (open water) further reduces surface albedo. As higher temperatures cause the surface of the sea ice (0.8 albedo) to begin melting, the thin layer of water atop the ice (0.6 albedo) can reduce the absolute albedo by 20 %. Liquid water more readily absorbs radiation than the surrounding ice and causes more water to pool and create melt ponds, further reducing the ice concentration and albedo of an ice-covered surface (Rösel et al., 2012). Melt ponds that appear early in the melting season allow for greatly increased absorption over sea ice, and may even drive regional-scale sea ice changes in extreme cases (Rösel and Kaleschke, 2012). By late February or early March, sea ice concentration and extent reach their annual maximum under weak sunlight, so absorption trends over the Arctic Ocean are very small. From June to October, however, the multi-decadal changes to the extent, thickness, and the surface albedo of summer sea ice caused the absorption rate to increase faster than absorption over land, particularly in the Beaufort and Chukchi seas. Flanner et al. (2011) also noted that increases in radiative forcing from 1978 to 2008 over lower-latitude Arctic seas were greater than those over land during June–October. Sea ice extent and concentration have decreased over the last few decades, and thick multiyear sea ice that was prevalent in the 1980s and 1990s has lost as much as 50 % of its thickness (Kwok and Rothrock, 2009), if not vanished altogether (Serreze et al., 2007). First-year ice is more susceptible to the formation of melt ponds, which can cause precipitous decreases in albedo (Rösel et al., 2012). The increase in surface absorption over the Arctic Ocean, then, is due to a combination of the replacement of multiyear sea ice with first-year ice and open water over the study period.
Trends in absorbed shortwave radiation over land
While the increase in the absorption of shortwave radiation is largely due to
reductions in sea ice and snow cover extents, the linear correlations between
snow cover anomalies or sea ice extent anomalies and shortwave absorption
anomalies are both approximately
While it can be seen qualitatively that the regional effect of clouds can be
large, quantitatively determining their overall influence on the trend in
absorbed shortwave radiation, i.e., to separate the influence of changes in
cloud cover from changes in sea ice and snow cover, is not possible with the
data available. Instead, we quantify the contribution of clouds by
determining their maximum possible effect on downwelling shortwave radiation
at the surface over the study period. This is performed by using the 34-year
average downwelling shortwave surface flux for each of the sunlit months
(March–September) and the 34-year average cloud cover trend (fractional
cloud cover) to determine the changes in instantaneous surface shortwave
flux. At each grid point in each month, the 34-year average downwelling flux
is multiplied by the cloud cover trend. A positive cloud cover trend will
result in a decrease in the downwelling and vice versa. For this calculation
it is assumed that all clouds are optically thick (“black”) and reflect
almost all incident sunlight, as optically thick clouds would have the
maximum effect on downwelling shortwave radiation. This assumption is valid
based on Wang and Key (1995), who found that visible optical depths for
Arctic clouds are in the range of 5–6, corresponding to a transmittance of
near zero (0.2 %–0.6 %). The average cloud cover trends over land and
ocean are
Even though September experienced the greatest decrease in sea ice extent, the smaller incoming solar flux at this time of year results in smaller absorption increases than those of early summer. The early spring, late fall, and winter months exhibit far weaker trends in shortwave absorption over ocean than land due to lower variability in the sea ice cover and smaller solar fluxes – decreasing to zero in the winter – at the high latitudes.
Surface radiation and cloud cover data from the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications 2 (MERRA-2) reanalysis (Rienecker et al., 2011) are employed to provide verification of the results from APP-x. This study used MERRA-2 version 1.3 and determined the absorbed shortwave radiation trends at the surface from the surface incoming shortwave flux (SWGDN) and surface albedo (ALBEDO) variables.
Trends in absorbed radiation from APP-x over land
Day-of-year range between 0.4 and 0.25 of albedo over ocean and land (blue) from 1982 to 2015. The dotted trend line (red) shows the regression of the DOY midpoint (pink) over the time period.
Performing the same analysis as before on MERRA-2 data produced similar results. The trends in absorbed radiation for the month of June from APP-x and MERRA-2 show similar patterns, though with larger magnitudes in APP-x (Fig. 4). The reanalysis data show an increase in absorption over ocean during June and mixed trends over land, which correspond spatially to APP-x trends. The results were consistent with APP-x, with increasing, uniform ocean heating during high summer and changes over land influenced by factors other than surface albedo. The most obvious differences between the reanalysis data and APP-x occur over the central Arctic Ocean, where MERRA-2 absorption trends are weaker than those in APP-x. The cause of this difference is due to the fixed albedo value that MERRA-2 assigns to sea ice, which does not take sea ice thickness or melt ponds into account. As seen in the APP-x results, thinner ice and irregularities in the ice surfaces increase the absorbed surface radiation.
The trends in solar energy absorption at the surface are both a result of, and a forcing for, changes in surface albedo. As increasing solar absorption over the Arctic continues to affect land and ocean differently, we now explore how the timing of the low-albedo portion of the year has changed over time and how the timing relates to the available solar energy. Markus et al. (2009) determined that between 1979 and 2007, nearly all regions of the Arctic showed a trend towards earlier annual melting and later refreezing, which self-enhances as sea ice thickness decreases. Results presented here are consistent with their analysis and expand upon the surface energy implications.
Using APP-x data, we are able to track the changes of land and ocean albedo throughout the study period. The impacts on the surface energy budget are apparent in Fig. 2. However, the absolute timing of the low-albedo period as well as the shift in timing of this period over the last few decades require further examination. One approach to analyzing these changes in the land and ocean albedo is to determine the day of year (DOY) on which the average albedo over land and over ocean reached their minima for each year. However, due to late freezing and thawing events and dynamically driven changes in the sea ice edge, changes in the albedo minimum DOY do not accurately explain trends in absorbed solar energy over the last 34 years. We find that using the DOY range from when the Arctic transitioned from a relatively low albedo (the day that albedo first went below 0.4) to a very low albedo (the day that albedo went below 0.25) provides a better metric for comparing the changes in albedo over land and ocean (Fig. 5). Figure 5 shows that the majority of the snow cover over land melts earlier in the year than sea ice, which is due to higher sun and temperatures at a lower latitude. Terrestrial snow cover also melts earlier because the snow-free land adjacent to snow-covered land warms faster than the unfrozen ocean around the sea ice.
An examination of Fig. 5 shows that the Arctic has reached a lower-albedo state
increasingly early in the calendar year over both land and ocean since 1982.
A linear fit of the midpoint between the days of year at which the 0.4 and
0.25 albedo levels were reached shows a decrease of 0.64 days year
The regression in time of the low-albedo period towards earlier in the year over both land and ocean may have important radiative implications in the future. Over ocean, the low-albedo period was reached 2 weeks closer to the summer solstice (DOY 172) in 2015 than in 1982–1985, with the low-albedo range midpoint going from DOY 188 to DOY 167. Over land, the low-albedo range midpoint regressed nearly 20 days away from the summer solstice, closer to DOY 152. Though both land and sea experienced lower albedos migrating closer to the beginning of the year, the low-albedo period over land now occurs before the summer solstice, while the low-albedo period over the ocean occurs closer to the solstice and therefore at a time with much greater solar insolation. Even though the insolation during the low-albedo period is greater today than it was in the early portion of the study, the midpoint of the low-albedo interval has regressed past the summer solstice in the last few years (Fig. 5). This implies that current trends in sea ice changes may cause the albedo transition to occur even further towards the beginning of the year, thereby experiencing weaker insolation, similar to the regression of the low-albedo period over land. As such, the differences between land and ocean absorbed shortwave radiation trends may grow smaller as their albedo transition occurs earlier in the year.
The magnitude of insolation on any given day at the peak solar time is
greater at lower latitudes. Therefore, even small changes in albedo in the
lower Arctic can have large effects on the amount of energy absorbed at the
surface. Conversely, large changes in albedo at higher latitudes are required
to significantly affect shortwave absorption due to the weaker instantaneous
insolation at higher latitudes. For instance, in 1982, the average albedo of
all ocean pixels at 75
However, the magnitude of the flux accumulated over the entire day around the
summer solstice is larger at higher latitudes. Figure 6 provides a simple
illustration of the changes in the accumulated TOA incoming
shortwave flux at 65 and 75
Accumulated top-of-atmosphere incoming shortwave flux for each day
and for the 65
Figure 6 also shows the changes that occur due to a low-albedo regression towards earlier times of the year. Over ocean, the shift in the timing of lower albedos to earlier in the year means that more sunlight was absorbed over the ocean in 2015 than in 1982, all else being equal (e.g., cloud cover). Over land, the regression of low albedo towards earlier in the year still results in an increase in absorbed energy, but it can only increase modestly due to decreasing sunlight further from the summer solstice. This relationship is valid for both the peak solar time and the accumulated absorbed fluxes.
The increased solar absorption due to the temporal regression of the
low-albedo period results in a positive surface albedo feedback. One way to
define the strength of the albedo feedback is the change in net incoming
shortwave radiation with respect to surface temperature due to changes in
surface albedo (Cess and Potter, 1988; Qu and Hall, 2007; Fernandes et al.,
2009):
For a unit temperature change, the net solar radiation absorbed by the Earth
system over ocean is less than that over land in April but about 4 times
as large as that over land in June and July (Fig. 7). The feedback strengths
in June are 16.3 W m
The snow–albedo and ice–albedo feedbacks (Eq. 1) for Arctic land (orange) and ocean (cyan) for the period 1982–2015.
The surface radiation budget of the Arctic is strongly influenced by changes in albedo, cloud cover, moisture, and heat advection. This study examined multi-decadal changes in the amount of solar radiation absorbed at the surface of Arctic land and ocean, together and separately, as a result of changes in albedo due to decreasing sea ice and snow cover. Analyses of the APP-x satellite dataset and the NASA MERRA-2 reanalysis over the 34-year period 1982–2015 determined that the magnitude of shortwave absorption is greater over land than the ocean and that changes in snow and sea ice cover have led to an increase in absorbed shortwave radiation of 10 % over ocean and 2.7 % over land. It was found that the rate of change in absorption over the Arctic Ocean is more than double the rate over Arctic land and that the magnitude of the ice–albedo feedback is 4 times that of the snow–albedo feedback in summer. However, the difference in the trend in shortwave absorption between land and ocean may decrease as the low-albedo period occurs further away from the summer solstice.
The timing of the annual low-albedo period has changed and has changed differently for land and ocean. While similar studies assume a consistent albedo cycle when determining the cryosphere's contribution to the global energy budget (Flanner et al., 2011), here we find that the inclusion of interannual changes to surface albedo results in a significant change to the surface shortwave energy budget of the Arctic between 1982 and 2015. Since 2010, for example, average ocean albedo in the study area during late June has been as low as mid-September albedo in 1982–1985. Similarly, Arctic land is losing its snow cover earlier in the year. If these trends continue, the temporal regression of the low-albedo period over land and ocean will have different effects on absorbed solar radiation in the future because the low-albedo period has moved further from the high-sun/maximum insolation time of year over land but has moved closer to the high-sun time over ocean. This has resulted in an intensification of the ice–albedo feedback more than the snow–albedo feedback, which may decrease as snow and ice melt earlier in the year. The absorption changes illustrate the relative importance of the snow–albedo feedback and the ice–albedo feedback and point toward decreasing sea ice cover, not changes in terrestrial snow cover, as the foremost radiative feedback mechanism affecting recent and likely near-future Arctic climate change.
Data used in this paper are stored publicly and are readily accessible.
APP data (
All authors contributed to the writing of this paper. AL performed much of the data analysis and drafted the paper. YL led the snow–albedo and ice–albedo feedback section. JK formulated the research idea and goals and performed some calculations.
The authors declare that they have no conflict of interest.
This research was supported by the NOAA Climate Data Records program and the Joint Polar Satellite System (JPSS) program office. The views, opinions, and findings contained in this report are those of the authors and should not be construed as an official National Oceanic and Atmospheric Administration or US Government position, policy, or decision. We thank the anonymous reviewers and the editor for their valuable comments and suggestions. Edited by: Chris Derksen Reviewed by: three anonymous referees