April 2026
Hi! I am especially excited to share this month’s “climate viz of the month” blog, which features a graphic that has long been requested by many of my followers. For years, I’ve posted monthly and seasonal zonal mean temperature anomaly graphics as a way to visualize how temperature departures vary across latitude over time. Although these monthly versions reflect more year-to-year variability because of their shorter timescale, they still clearly reveal longer-term climate change signals, including stronger warming across the Northern Hemisphere due in part to its greater land coverage and the continued influence of Arctic amplification. While I realize these visualizations are a bit more technical, especially given the phrase “zonal mean temperature anomalies,” I think they often resonate with people because they provide a different perspective on regional climate change. I also share several other zonal-mean style graphics on my climate change indicators page that emphasize longer-term trends, but many of you have specifically asked what an animated version might look like over time.
On this rainy and cold Memorial Day weekend, I finally decided to take the time to produce this animation. This one shows zonal mean temperature anomalies for every month from January 1950 through December 2025. There are more than 900 frames, so I apologize for the fast pacing, though you can slow the playback using the video controls above. As a reminder, “zonal mean” means that temperature anomalies are averaged across all lines of longitude for each latitude band. For this visualization, I use the NASA/GISS GISTEMPv4 dataset, which is based primarily on surface temperature observations (e.g., weather stations, buoys), and I retain their standard 1951-1980 climatological baseline for calculating anomalies (x-axis). Red bars indicate warmer-than-average conditions for a given latitude band, while blue bars indicate colder-than-average. As an additional visual cue, I include a yellow line and marker highlighting the latitude band with the largest warm anomaly each month. Note that for simplicity and readability, the y-axis is shown with equal spacing by latitude rather than by true Earth surface area, which visually overemphasizes the polar regions because high-latitude bands occupy much less physical area on the globe than regions closer to the equator and tropics.
What patterns and trends do you notice? For me, there are several fascinating climate signals that immediately stand out. One obvious example is the strong tropical warming associated with the 1997-1998 El Niño event, which appears very clearly in the animation. Another striking feature is that after roughly the 2010s, there are effectively very few months where large portions of the tropical and Northern Hemisphere midlatitude bands fall below the long-term average. Arctic amplification is also incredibly apparent, with some monthly temperature anomalies extending beyond the +10°C axis limit in the figure. Other climate characteristics emerge as well, including the much greater month-to-month variability outside of the tropics and the comparatively weak long-term signal over Antarctica (at least from the perspective of this visualization). In my view, this animation is an awesome illustration of climate variability versus long-term human-caused climate change, which is one reason why I have always appreciated this latitudinal perspective for understanding the global climate system. Side note: zonal means are also widely used in atmospheric dynamics and climate model evaluation because latitude is one of the most fundamental organizing coordinates of Earth’s energy balance.
Now moving to the Arctic… The Arctic has been relatively quiet over the past month in a broad sense, but that overall signal hides substantial regional variability. April 2026 averaged among the top 10 warmest Aprils on record for the Arctic Circle region, yet this mean masks a strong spatial contrast. This included colder-than-average conditions over the Canadian Arctic Archipelago alongside much warmer-than-average anomalies across the Siberian and Atlantic sectors, in places exceeding +5°C relative to the 1981-2010 baseline. The largest warm anomalies were centered over the Barents Sea just east of Svalbard and extending into the southern Greenland Sea. In my regional Atlantic Arctic domain, April 2026 was actually the warmest April on record, continuing a sequence that follows March, which also set a record high for that region. On a related note, the freezing degree day season, which I track here as a cumulative measure of cold exposure north of 80°N latitude (defined from July 1 to June 30 and used as a simple proxy for sea ice growth conditions and atmospheric cold accumulation), is now approaching its annual reset in a few weeks. The 2025 to 2026 season currently ranks as the 2nd most anomalous on record in terms of freezing degree day deficits. In other words, it represents the second largest reduction in accumulated cold conditions compared to the historical baseline near the North Pole.
As for sea ice, we sadly still don’t have any new data on ice thickness and volume. I have not yet identified a workaround while we await further updates to the PIOMAS/GIOMAS models (see my prior blog for more details). Total Arctic sea-ice extent was quite low in April, ranking as the 2nd smallest in the satellite era for that month. Sea-ice concentration remained slightly higher than average in the eastern Bering Sea around Alaska, while conditions were much reduced along the Russian coastline. Large swaths of missing ice also persisted across the Barents Sea and Greenland Sea, as well as the Sea of Okhotsk, which has had a historically low-ice year.
The melt season is now well underway, though it is still too early to make any predictions for this year’s September minimum. This reflects the strong sensitivity of Arctic sea-ice evolution to local weather conditions. In recent years, relatively cool and cloudy summers have helped prevent the emergence of new record minimum. As I have discussed in prior blogs, this may reflect a combination of internal decadal climate variability and/or longer-term feedback processes.
Thanks for reading, and let me know what you think about this animation! Past blog posts going back to 2022 are archived below. If you’d like to support the time and effort behind maintaining and updating this site, you can do so here: https://buymeacoffee.com/zacklabe.
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 5/12/2026.
Other Blogs (Monthly):
Other Climate Data Statistics (Monthly):
My Visualizations:
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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.