November 2025
Hi! I am happy to share the first of (hopefully) some new graphics in this ‘climate viz of the month’ blog. For quite a few years now, I’ve been procrastinating on figuring out an efficient way to calculate regional Arctic sea-ice thickness using the PIOMAS dataset (a modeled “reanalysis” product). Part of the delay was technical. The latitude-longitude grid used by PIOMAS, both in how the data are computed and displayed, is unusual. I won’t get into the details here, but it is not exactly straightforward to work with.
Overnight we had some heavy sleet and freezing rain here, which meant I was definitely stuck at home today. So, I finally decided it was time to tackle this problem. As it turns out, it was much easier than I expected. Going forward, I would like to start including one or two graphics showing monthly changes in Arctic sea-ice thickness across different regions and marginal seas (e.g., the Laptev Sea vs. the Beaufort Sea). If that would be useful or interesting, please let me know!
This first graphic shows monthly averaged sea-ice thickness for the region around the North Pole, including all locations north of 85°N. Each line represents one year of data from January through December, shown left to right. Older years are shaded in blue, transitioning to red for more recent years, with 2025 highlighted in bright red. This color progression is meant to emphasize the long-term trend. A clear seasonal cycle is also present. On average, sea ice around the North Pole is thickest in early spring and thinnest in late summer or early fall. The melt season is relatively short this far north, but some seasonality is expected and entirely normal. What is not normal is the long-term decline in sea-ice thickness due to human-caused climate change. To help illustrate this, I have annotated approximate decadal averages from the 1980s through the 2010s. Their placement on the figure reflects the mean thickness for each decade and again highlights the steady thinning of Arctic sea ice over time.
This data is simulated from the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). Regular readers of this blog and my science communication work have probably noticed that I refer to the PIOMAS dataset quite often when discussing Arctic sea-ice thickness and volume. That may seem like an odd choice, given that we now have several satellite-derived estimates of ice thickness from missions such as ICESat-2, CryoSat-2, and SMOS. While these satellite datasets continue to improve and extend their records, they are still too short to provide robust, climate-scale information on long-term trends. This limitation is especially important if we want a dataset that is temporally and spatially consistent over multiple decades. (To be clear, these satellite missions serve many other critical purposes and continued support for them is essential.) So, as a result, I still rely on model-based reanalysis products, such as PIOMAS, to supplement satellite observations. Note that I recently wrote a summary of PIOMAS for the NCAR Climate Data Guide, which provides more detail on its uncertainties, strengths, and limitations, and I recommend checking it out for additional background. Monthly comparisons between PIOMAS and CryoSat-2 during the cold season are also available through the University of Washington’s Polar Science Center within the Applied Physics Laboratory. Overall, PIOMAS performs quite well in capturing the large-scale spatial patterns, variability, and long-term trends suggested by submarine tracks, in situ measurements, and satellite-based thickness estimates (Labe et al. 2018).
Okay, now getting to the data and results. According to PIOMAS, Arctic sea-ice thickness has been at record low levels for much of 2025 north of 85°N, especially since April. This year has also set a new all-time record for the lowest mean ice thickness. In addition, the departure from the previous record low year, set only in 2024, has continued to grow in November. Together, this data indicates that there has been very little thickening of ice so far this freeze season across the high north.
Now for the caveats, as I am obligated to include (this is sometimes where I struggle with messaging/communicating from a scientist by training perspective). The data on this graph are simulated by PIOMAS and therefore carry their own uncertainties. The reason Arctic sea-ice “extent” is more commonly shared in science communication is due to higher quality data and longer historical records. When compared with CryoSat-2 in November, there are relatively larger differences between the two datasets in this exact region of the Arctic. However, comparisons with the Danish Meteorological Institute’s (DMI) operational ocean and sea-ice model, HYCOM-CICE, also reveal very low, and maybe even record-breaking Arctic sea-ice thickness and volume. Given how extreme current conditions are for October and November with PIOMAS, I also initially wondered whether this signal could be related to data issues associated with the transition from SSMIS to AMSR2 (i.e., sea-ice concentration data from satellites is assimilated into PIOMAS). While this satellite transition may still contribute to increased uncertainty, the average sea-ice thickness near the North Pole was already at record low levels well before this became a factor. Taking all of these caveats and uncertainties into account, it is still very safe to say that average sea-ice thickness around the North Pole is near record low levels relative to 1979 (and likely much longer; Schweiger et al. 2019). And according to PIOMAS, current thickness values in this region are unprecedented. Since the area north of 85°N typically contains some of the oldest and most resilient ice, this is not good news at all for the overall health of the Arctic.
Changes in mean surface air temperature anomalies (GISTEMPv4; 1951-1980 baseline), mean Arctic sea ice extent (NSIDC; Sea Ice Index v4), and mean Arctic sea ice volume (PIOMAS v2.1; Zhang and Rothrock, 2003) over the satellite era. Updated 12/11/2025.
Now outside of the North Pole, the story is not any better. The total volume of Arctic sea ice last month set a new record for the lowest November in the PIOMAS dataset. Arctic sea-ice extent has also been setting new daily record lows for this time of year for weeks. At the same time, there have been numerous days with record high temperatures across the northernmost parts of the Arctic due to anomalous heat and moisture transport through the Barents Sea region. As discussed in my last blog (“October 2025”), the Arctic has experienced a historically poor start to the freeze season, particularly on the Atlantic side. The combination of record warmth and low ice puts the Arctic in a bad position heading into 2026. That said, as we know, weather conditions can change rapidly, so this does not tell us much about what summer 2026 will ultimately look like.
But moving into the new year, there is a lot for climate scientists to be watching across the Arctic. Thanks for reading and stay tuned! My previous blogs from this year can be read at https://zacklabe.com/blog-archive-2025, along with my Arctic dashboard statistics stored at https://zacklabe.com/archive-2025/. My Buy Me a Coffee account can also be found at https://buymeacoffee.com/zacklabe, and feel free to follow my posts on Bluesky, LinkedIn, and Mastodon.
Other Blogs (Monthly):
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[2] Witt, J.K., Z.M. Labe, A.C. Warden, and B.A. Clegg (2023). Visualizing uncertainty in hurricane forecasts with animated risk trajectories. Weather, Climate, and Society, DOI:10.1175/WCAS-D-21-0173.1
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[1] Witt, J.K., Z.M. Labe, and B.A. Clegg (2022). Comparisons of perceptions of risk for visualizations using animated risk trajectories versus cones of uncertainty. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, DOI:10.1177/1071181322661308
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The views presented here only reflect my own. These figures may be freely distributed (with credit). Information about the data can be found on my references page and methods page.