Arctic sea ice conditions have undergone significant changes in recent years, with dramatic reductions in the overall ice extent, ice age, and ice thickness. The decline in Arctic sea ice extent is one of the better-known and more striking examples of a changing Arctic (e.g., Meier et al., 2014; Comiso et al., 2008, 2012, 2017a; Stroeve et al., 2011, 2014). Recent estimates indicate that September Arctic sea ice extent has decreased by approximately 13 % per decade since 1979, with record or near-record minimum extents occurring several times in the last few years (e.g., Perovich et al., 2019). In the Antarctic, the trends are smaller and there is higher interannual variability (e.g., Parkinson and Cavalieri, 2012); overall the Antarctic trends are slightly positive, but with strong regional variability (Comiso et al., 2017b).

Data on sea ice thickness are far less comprehensive, and it is more difficult to determine solid quantitative thickness or volume trends. However, there is broad evidence, from observations (e.g., Kwok, 2018) and models (e.g., Stroeve et al., 2014), that Arctic sea ice thinning trends are even stronger than the extent decrease. One explanation for the stronger decline in ice thickness is the preferential loss of thicker, old ice in comparison with relatively thin first-year ice. For example, Johannessen et al. (1999) and Comiso et al. (2008, 2012) noted that the decline in multiyear sea ice was roughly twice that of first-year ice. In a study examining ice age since the early 1980s, Maslanik et al. (2011) found continued recent loss of the oldest ice types, which accelerated starting in 2005. This trend has continued through 2019 (Perovich et al., 2019; Kwok, 2018).

A continued decline in the sea ice cover and the shift from thick multiyear ice (MYI) to more easily navigable first-year ice (FYI) arguably will have one of the biggest impacts on humans and the Arctic environment (e.g., Pizzolato et al., 2016). In particular, the prospect of new shipping lanes, extraction of oil and gas from previously inaccessible regions, and increased national security concerns associated with easier and more accessible Arctic waters have already been identified as significant economic and cultural changes related to the sea ice cover (Huntington et al., 2007). More open water along the coast will also add to the risk of storm surge and coastal erosion (Vermaire et al., 2013; Francis et al., 2006, 2005; Lynch et al., 2004), and there is some evidence that reductions in sea ice may affect locations far from the Arctic (e.g., Overland, 2016), manifesting particularly through extreme weather in the mid-latitudes (e.g., Cohen at al., 2014; Francis and Vavrus, 2012).

The distribution of the age of Arctic sea ice contributes to the vulnerability of the ice cover during the melt season because older ice is on average thicker than younger ice (Maykut, 1986; Tucker et al., 2001; Yu et al., 2004; Tschudi et al., 2016), at least in terms of thermodynamic growth over several years. Younger ice is more susceptible to deformation and melts out more readily during the summer, whereas older ice is more likely to remain through the melt season if it does not advect out of the Arctic Ocean. However, the thickness increase with age diminishes over time so that as sea ice gets older (Maslanik et al., 2011), its resiliency against melt does not continually increase. The pre-melt distribution of ice age may therefore serve as a descriptive predictor of how much sea ice will disappear during the melt season and indicate where summer ice loss is more likely to occur. Ice thickness observations are becoming more widely and readily available from satellite altimeters such as NASA's Ice, Cloud, and land Elevation Satellite (ICESat; Kwok and Cunningham, 2008) and ESA's CryoSat-2 (Laxon et al., 2013; Kurtz et al., 2014). However, these satellite-derived data cover a limited time span. ICESat collected twice-yearly estimates from 2003 to 2008, and CryoSat-2, launched in 2010, produces complete Arctic-wide fields monthly (Tilling et al., 2016). The laser altimeter on NASA ICESat-2, launched in September 2018 (Markus et al., 2017), provides a significant new source of snow + ice freeboard and potentially thickness. Along with satellite-borne altimeters, NASA's Operation IceBridge has yielded thickness estimates during 2009 through 2019 in selected regions (e.g., Kurtz et al., 2013). Submarine upward-looking sonar has also been used to estimate thickness sporadically since the 1950s over a selected region in the central Arctic. These data have been connected to the satellite altimetry record (Kwok, 2018) to create an intermittent long-term time series over part of the Arctic. While these direct ice thickness estimates are useful, such products lack the long-term and/or the basin-wide coverage that is available from the multi-decadal sea ice age record.

In contrast, sea ice motion can be used to track parcels in a Lagrangian sense and record their age. Several sea ice motion products have been developed by various groups. Most products use some sort of motion-tracking approach to estimate the drift of features or patterns in satellite images. The EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) has two products. One is a low-resolution (62.5 km spacing) product that derives 2 d motions based on passive-microwave and scatterometer inputs (Lavergne et al., 2010). A medium-resolution OSI SAF product based on visible and infrared sensor inputs provides daily coverage at 20 km spatial resolution (Dybkjaer, 2018). Another product, developed by the French National Institute for Ocean Science (IFREMER), combines passive-microwave and scatterometer inputs to produce 3 d motion estimates (Girard-Arduin and Ezraty, 2012). Several of these products were intercompared in Sumata et al. (2014, 2015). High-resolution synthetic-aperture radar (SAR) imagery has also been used to track motion at much finer spatial scales (e.g., Curlander et al., 1985; Kwok et al., 2003; Howell et al., 2018). While high resolution, SAR has had limited spatial and temporal coverage, the data were large and difficult to work with, and reasonable coverage did not start until the mid-1990s. This has changed in recent years, but long-term climate records from SAR are limited.

In this paper, we specifically discuss the “Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors” product (Tschudi et al., 2019a). These sea ice motions derived from satellite instruments and buoys are then used to obtain a continuous, complete, long-term record of sea ice age, the “EASE-Grid Sea Ice Age” product (Tschudi et al., 2019b). Because of its length and completeness, this ice age time series has been used in several studies (Maslanik et al., 2007, 2011; Tschudi et al., 2016, 2010) and reviews of Arctic change (Stroeve et al., 2011; Meier et al., 2014; Perovich et al., 2019) to assess changes in the ice cover. Over time, enhancements and improvements have been made to the ice motion and ice age products. The latest version of the ice motion and age products addresses issues noted by users (Szanyi et al., 2016), and both products are enhanced through a refined optimal interpolation approach that improves the spatial continuity of the gridded motion and age fields. Our focus in this paper is to highlight the changes in the new version, compare the new version with older versions, and provide an updated assessment of ice age trends. As further background, we also document the algorithms and production of the products. Because the ice age product is produced by utilizing the sea ice motion product, we outline the production of the motion product first.

The sea ice motion product is archived and distributed by the NASA Snow and Ice Distributed Active Archive Center (DAAC) at the National Snow and Ice Data Center (NSIDC). The ice motion product provides gridded daily estimates and weekly averages of ice motions for both the Arctic and Antarctic regions. In this section, we describe the basic processing methodology and data sources and note the changes made in the new Version 4 of the product. The version history of the motion product (and the age product discussed in Sect. 3) is summarized in Table 1, including the release date and enhancements for each version.

The EASE-Grid Sea Ice Age product (Tschudi et al., 2019b) builds upon the combined motion product and is also a popular dataset, with over 650 unique users having accessed the data as of this writing (NSIDC, personal communication, 2019). Version 2 of the sea ice age data is also part of NASA's Making Earth System Data Records for Use in Research (MEaSUREs) dataset at NSIDC (Anderson et al., 2014); however, the MEaSUREs product is not regularly updated and does not include the newest enhancements described here. Animations of motion and age have been posted on NOAA's ClimateWatch online magazine (http://www.climate.gov/news-features/videos/old-ice-arctic-vanishingly-rare, last access: 25 February 2020) as well as the NASA Scientific Visualization Studio (https://svs.gsfc.nasa.gov/4750, last access: 25 February 2020). Sea ice age distributions and trends are described annually in the Arctic Report Card (Perovich et al., 2019) and have been analyzed by Maslanik et al. (2007, 2011). The Sea Ice Age product was introduced by Fowler et al. (2004) and described further by Maslanik et al. (2007, 2011), Tschudi et al. (2010), and Stroeve et al. (2011). The ice age product algorithm estimates the age (in years) of Arctic sea ice using input from the previously described sea ice motion product.

Weekly averaged motions are used to reduce computational complexity and to temporally average discretization artifacts in the daily motion data. Also, the 25 km resolution motions are bilinearly interpolated to a 12.5 km resolution grid in order to provide finer granularity in the ice age fields.

At the beginning of the ice motion record, all parcels in the 12.5 km ice age grid are initialized with an age class of “first-year ice”, meaning ice that is less than 1 year old. These parcels are then treated as Lagrangian particles and are advected at weekly time steps with the motion product estimates. When two or more parcels merge into a grid cell, the age of that grid cell is represented as the age of the oldest parcel. Rarely, ice motion results in all parcels being advected out of a grid cell; when this occurs, a new parcel of first-year ice is initialized in that grid cell. During the week of the Arctic sea ice extent minimum, the age of all parcels is increased by 1 year. At each time step, all parcels found within a grid cell that have an ice concentration of less than 15 % are considered to have melted and are no longer considered in determining the ice age. Parcels are tracked for up to 16 years, after which they are no longer considered (such parcels are simply removed).

This approach does not consider new ice that may form within a grid cell because it retains only the oldest ice in its accounting. Thus, the product is effectively an estimate of the oldest ice in a given grid cell. Tracking of partial concentration of age categories can provide a more detailed picture of the ice cover (Korosov et al., 2018) and is something we may consider for future versions.

The source motion data for the age product begin in 1978, with the age of all parcels initialized as first-year (0–1 years old) ice. Because the method tracks age over time, several years are needed to build up older ice categories. For this reason, the ice age product begins in 1984. The youngest ice age category is first-year ice (FYI), which is ice that is less than a year old; similarly, second-year ice is 1–2 years old; and so on for older ice age categories. Ice older than 4 years (fifth-year and older ice) makes up a very small percentage of the ice cover, so depicting ice older than this category as a separate field in browse imagery is not undertaken. Therefore, the ice age is frequently categorized as being of ages: 0–1 (i.e., FYI), 1–2, 2–3, 3–4, and more than 4 years old (i.e., fifth-year and older ice).

Version 4 changes. The primary changes in Version 4 of the ice age product result from the changes in the source ice motion products described above. The most substantial change addressed anomalous behavior in the motion and age fields documented by Szanyi et al. (2016). They showed that discontinuities in the interpolated motion field, caused by suboptimal interpolation of buoys with the other data sources, created artificial ice divergence and new ice formation in the Version 3 product. This potentially results in an underestimation of multiyear and an overestimation of first-year ice. The change in the interpolation weighting, described above, reduced this effect as seen in Fig. 3; the Version 3 field has the circular features surrounding the buoys where the buoy contribution suddenly drops out, resulting in a discontinuity where false divergence can occur. The new weighting scheme smooths that discontinuity and eliminates much of the false divergence. The effect of this change can be seen qualitatively in the age fields as less “speckling” of first-year ice interspersed within the multiyear ice pack; the age fields show a more realistic consolidated multiyear ice pack. Qualitatively, the net effect is less first-year ice (the speckling that results from the false divergence) and an increased amount of multiyear ice in Version 4 compared to Version 3 (Fig. 6). This effect becomes much less noticeable during the latter part of the record. There are three reasons for this. First, there is less passive-microwave coverage during the early SMMR period and thus a sparser number of vectors, which will accentuate interpolation-induced artifacts in the data. Similarly, in the early part of the record, there were far fewer buoys, so the buoy interpolation discontinuities are more noticeable. In recent years, there have been enough buoys such that the interpolation distances of neighboring buoys often overlap, so discontinuities with the passive microwave and wind fields are less common. Finally, there is simply much less multiyear ice in recent years, so the discontinuity effects are less pronounced. A quantitative assessment of the version changes in the ice age product is discussed further in Sect. 4 below.

Two other minor changes to the ice age product have been introduced in Version 4. First, the week-numbering convention was slightly modified to be consistent with the motion weeks. Second, browse imagery (Fig. 6) was improved to explicitly show ice-covered ocean areas that are outside of the age and motion domain (e.g., the Canadian Arctic Archipelago).

Validation of sea ice age is difficult because there is no known suitable validation dataset that can be used for a comparison. Here we primarily rely on the fact that the ice age product is directly derived from the ice motion product. Thus, the demonstrated improvement in the motion fields indicates that the age fields are also improved. This is particularly noticeable in the reduction of the circular features in the motion field, which reduces the speckling in the Version 4 age fields. While this is qualitative, we feel this does demonstrate an improvement in the age fields. A recent study (Lee et al., 2017) included the NSIDC ice age fields in a comparison with passive-microwave ice age retrieval methods, including multiyear fraction from the NASA Team algorithm, the OSI-SAF ice type product (Aaboe et al., 2017), and a microwave emissivity approach. The spatial patterns of first-year and multiyear ice in the NSIDC age product matched well with the comparison products, showing that our age product is at least consistent with other approaches.

Here we evaluate how the changes from Version 3 to Version 4 of the products affect the long-term trends and variability in the sea ice age fields. We also provide updated motion and age trends through 2017.

As seen in Fig. 3, the change to Version 4 does noticeably affect parts of the daily fields in regions around buoys. Over a weekly period, the changes are less significant because the temporal averaging smooths out the variability in the motions. The weekly average speed is generally faster in Version 4 than in Version 3 (Fig. 7). (The differences in the u and v motion components – not shown – have similar characteristics over the time series.) This change in speed between Version 3 and Version 4 reflects the two major changes made for Version 4: (1) the use of the 15 highest weighted observations for the interpolated combined fields and (2) the correction of the over-filtering of the SSM/I and SSMIS vectors. During the SMMR part of the record, the differences are generally near zero. This is because only the change in weighting had an effect on this period. In the Arctic this primarily changed the influence of the buoys, and there were fewer buoys during the SMMR period. In the Antarctic (Fig. 7b), the change is even smaller because there are no buoys and thus less impact of the adjusted weighting scheme. For the SSM/I and SSMIS period, the Version 4 motions are ∼ 0.5–1.0 cm s-1 faster than Version 3 in the Arctic and ∼ 0–2 cm s-1 faster in the Antarctic. In this period, both the change in weighting and the over-filtering correction affected the motions. Over-filtering of the number of valid SSM/I and SSMIS has a larger effect, especially in the Antarctic, where there are no buoys or wind-derived fields. During 2002–2011, when AMSR-E is included, the Arctic speed difference is reduced with Version 4 speeds ∼ 0.25–0.5 cm s-1 faster. AMSR-E motions did not change between Version 3 and 4; SSM/I and SSMIS were also used in this period, but with higher resolution, more AMSR-E motions were used. Thus, the over-filtering issue in the SSM/I–SSMIS estimates was muted in the AMSR-E period. After the end of AMSR-E the differences increase again. In the Antarctic, there is no notable change because AMSR-E is not used.

There is seasonal variation, with larger differences during the Arctic summer. The main factor is likely overall speeds, as seen in the Version 4 weekly average speed time series (Fig. 8) that show strong seasonal variability in Arctic motions with speeds peaking during summer. In the Antarctic, the version differences are actually largest in winter and smaller in the summer; this may reflect fewer vectors with minimal summer ice cover. Also, in the Antarctic winter, the ice extends far northward and the pack is quite dynamic in response to winds and currents. Other factors also play a role, including the number of vectors from different sources at different times of year (e.g., fewer passive-microwave vectors during summer) and, in the Arctic, the revised weighting scheme that effectively yields more influence of buoys during the summer (when there are fewer passive-microwave motions).

There is also interannual variability (Fig. 8), some of which is related to the SMMR every-other-day sampling, resulting in slower speeds and less variability for the 1979–1987 period (more noticeable in the Antarctic because of the lack of wind-derived and buoy motions). Beyond that, there is an overall positive trend in Arctic sea ice speed of 0.21 cm s-1 per decade in Version 4 versus 0.13 cm s-1 per decade in Version 3. The increasing speed is in general agreement with previous studies that noted a trend toward faster moving ice (e.g., Spreen et al., 2011) and linked the trend to greater response to wind forcing by a thinner ice cover. In the Antarctic, there is also an increasing trend of 0.61 cm s-1 per decade in Version 4 versus 0.41 cm s-1 per decade in Version 3. But as noted above, the differences in the trend values from Version 4 and Version 3 at least partially reflect the effects of the changes in the motion sources and their relative impacts over the time series.

The largest effect of the version change for ice age is, as noted above, the amount of multiyear ice in the early part of the record, particularly in the oldest ice categories. This is illustrated in the time series of ice age (Fig. 9). Both versions show a strong decline in ice ≥ 4 years old over the record, with a steep loss of old ice in the late 1980s through the mid-1990s, which is associated with a persistent positive mode of the Arctic Oscillation (AO; Rigor et al., 2002). A positive AO results in increased drift from the Siberian coast and greater advection of ice out of the Arctic through Fram Strait, which serves to “drain” older ice out of the Arctic (Rigor and Wallace, 2004).

The change to Version 4 results in higher extent of the old ice over most of the early part of the record, with the exception of 1995–1996 (perhaps related to the end of the positive AO period and/or large changes in minimum extent between the two summers). Version 4 extent of ice ≥ 4 years old is on average 367 000 km2 higher than Version 3 for the first 5 years (1984–1988) of the record. This is an effect of the improved interpolation weighting scheme and is a quantitative indication of the reduced speckling discussed earlier. However, the impact dissipates over time; during the last 5 full years of the record (2012–2016), the difference between Version 4 and Version 3 is only 42 000 km2. The amelioration of the difference is likely due to two factors: (1) the transition from SMMR to SSM/I–SSMIS and the resulting improved coverage and (2) the increasing number of buoys over time. As noted above, the 2 d SMMR separation does change the motion discretization and the spatial coverage, so the relative effect of the buoys is greater during the SMMR era. And as buoy coverage increases over the years, there is more overlap in buoy influence, so the change in weighting that increases the distance of buoy influence has a relatively smaller effect. With daily data and better spatial coverage in SSM/I, the differences between the two versions starts to decrease. This decrease continues as buoy coverage increases over the years. And with AMSR-E and its better spatial resolution added in 2002, the differences drop further as the AMSR-E motions start affecting the older ice types in the following years. By 2005, there is very little difference between the two versions. Focusing on the week of 19–25 February, the larger differences between versions of ice ≥ 4 years old and younger ice types are evident (Fig. 10). The younger ice categories show smaller, generally negative differences (i.e., less younger ice in Version 4). Thus, the changes in Version 4 appear to improve the ice age fields by removing much of the artificial divergence noted in Szanyi et al. (2016), thereby reducing the amount of younger ice and increasing the amount of older ice. However, the impact of the version change decreases over time such that there little impact on the age distribution in recent years.

Both versions of the ice age field show a transition from one dominated by older ice to one dominated by younger ice (Fig. 11). Interannual variability is evident in all ice age classes, particularly first-year ice, which is not surprising given the variability in the summer ice cover. Less variability is seen in older ice. Nonetheless, the decline in older ice is apparent during the persistent positive mode of the Arctic oscillation in the late 1980s through the mid-1990s (Rigor et al., 2002). After 1994, there was some recovery in multiyear ice before beginning a significant decline after 2004. Linear trends are estimated for the Arctic Ocean region. This is a region bounded by the northern coasts of the continents, the Bering Strait, Fram Strait, and the ∼20∘ E meridian between Svalbard and the Fennoscandian Peninsula. The total area of the region is ∼7.8×106 km2. Using this region excises areas where only first-year ice exists, so it focuses on the areas where there is variability in the ice age. There is a strong increasing trend in ice < 1 year old (Table 3) and a similar decreasing trend in ice ≥ 4 years old. Trends in the intermediate ages (1–4 years old) are smaller. This is partly due to smaller extents of these ages as well as the fact that ice transitions through these categories between the larger extents of the oldest and youngest ice.

New versions (4.0) of the sea ice motion (Tschudi et al., 2019a) and sea ice age (Tschudi et al., 2019b) datasets have been produced and are now available at NSIDC. Routine updates will regularly occur when the underlying data – buoy positions, brightness temperature fields, and sea ice concentration fields – become available. This is expected to occur every few months.

Arctic sea ice motion vectors are currently constructed by merging motion vectors estimated using three sources: buoys, passive-microwave satellite imagery, and winds from NCEP–NCAR. In the Antarctic, only the satellite imagery vectors are used. Sea ice age is produced for the Arctic using the weekly sea ice motion product as input, tracking ice parcels, and aging them each year if they neither melt nor advect out of the ice pack.

The most recent sea ice motion algorithm revision incorporates improvements such as an improved vector weighting scheme, corrections to passive-microwave vectors, new browse imagery, and the underlying code base through the use of Python. Furthermore, the Version 4.0 upgrade addresses artifacts in the ice motion resulting from the interpolation. These artifacts did have a noticeable effect on the weekly motion and age fields early in the record, but in more recent years, the effect of these artifacts is diminished due in large part to many more buoys in the Arctic, which results in overlapping influence of buoys and thus fewer artifacts.

We note the decrease in older sea ice over the ice age record, from the 1980s, when older ice constituted ∼ 30 % of the ice pack, to recent years, when older ice occupied less than 5 % of the pack. Tschudi et al. (2016) compared ice age to ice thickness derived from ICESat (Kwok et al., 2009; Kwok and Cunningham, 2008) and NASA's IceBridge campaign (Kurtz et al., 2012, 2013). They found that the thickness–age relationship has an approximate linear fit for the ICESat dataset but that the relationship was much more variable for IceBridge due to the Arctic basin-wide coverage of ICESat thickness data and the more limited areal coverage for IceBridge aircraft-acquired data. The relationship found between ice age and thickness for the basin-wide ICESat dataset suggests that the ice age product may be used as a general indication of the sea ice thickness distribution and could be compared to other Arctic basin-wide sea ice thickness estimations, such as those from CryoSat-2 (Salilla et al., 2019).

The ice motion and age products are continuously being improved. We plan to utilize passive-microwave imagery from the AMSR2 instrument aboard the GCOM-1 satellite in a future release of the motion product, which may reduce the error in motion due to the improved higher spatial resolution of AMSR2 over SSMIS. We also plan to further improve the age product by categorizing the age distribution in each EASE grid cell (as suggested by Korosov et al., 2018) instead of retaining only the oldest ice age. Other improvements in the sea ice motion and age products are under consideration.