2023/11/24-30 Central Asia Heatwave
High Temperatures in Central Asia November 2023 heatwave likely influenced by both human-driven climate change and natural variability
Press Summary (First published 2023/12/05)
Heatwaves similar to the Central Asia November 2023 heatwave are between 1 ºC and 5 ºC hotter in the present than they would have been in the past.
This was a somewhat uncommon event.
We mostly ascribe the high temperatures of the November 2023 heatwave to human driven climate change and natural climate variability likely played a modest role.
Event Description
In late November 2023, Central Asia experienced unseasonably warm temperatures, setting new records for warmth in this time of the year. A daily minimum temperature of 19.6°C was observed in Bakarly, Turkmenistan, indicating an extremely unusual warm temperature for November, resembling that of a summer night. Uzbekistan broke its national temperature record for November, with temperatures exceeding the climatology by 3-6°C on average. The warm spell extends further northeast into Kazakhstan, leading to exceptionally warm weather in certain regions.
The impact of winter warm spells in Central Asia remains poorly understood, largely due to a scarcity of information and research in the region. However, the adverse effects of similar winter warm spells have been extensively documented in other regions. These effects include detrimental impacts on vegetation and animal life, as well as potential disruptions to water supplies in subsequent seasons.
The Surface Pressure Anomalies reveal negative anomalies across most regions, with the most significant deviation reaching up to -10hPa over the northern Caspian Sea. Concurrently, positive Temperature Anomalies are observed in the same regions, particularly notable in Uzbekistan and eastern Kazakhstan, where temperatures exceed climatology by over 5 ºC. Precipitation Data indicates this event was characterized by dry conditions in most regions, while Windspeed Data reveals the presence of moderate winds over land areas.
Climate and Data Background for the Analysis
According to the IPCC AR6 report, there is high confidence that warm spells and heatwaves have significantly increased in frequency or intensity in West Central Asia, and high confidence in a human contribution to the observed increase (p. 1632). The IPCC report further states that there is high confidence in the increases of hot temperature extremes in West Central Asia.
Our analysis approach rests on looking for weather situations similar to those of the event of interest having been observed in the past. For this event, we have medium-high confidence in the robustness of our approach given the available climate data, as the event is similar to other past events in the data record.
ClimaMeter Analysis
We analyze here (see Methodology for more details) how events similar to the low pressure system leading to Central Asia November 2023 heatwave have changed in the present (2001–2022) compared to what they would have looked like if they had occurred in the past (1979–2000) in the region [45°E 75°E 30°N 50°N]. The Surface Pressure Changes show that pressure over the Aktobe region has become higher in more recent events. The Temperature Changes show that similar events produce temperatures in the present climate that are between 1 ºC and 5 ºC hotter than what they would have been in the past, particularly in the southern part of the region. The Precipitation Changes show that similar events are slightly wetter in the present than in the past. We also note that Similar Past Events are now occurring earlier in the year, shifting from November and December to October and November. The Changes in Urban Areas show that Tashkent (Uzbekistan), Kabul (Afghanistan) and Islamabad (Pakistan) are 1.5 to 3°C warmer in the present than in the past.
Finally, we find that sources of natural climate variability, notably the Atlantic Multidecadal Oscillation, may have only partly influenced the event. This means that the changes we see in the event compared to the past may be mostly due to human driven climate change.
Conclusion
Based on the above, we conclude that heatwaves similar to the Central Asia November 2023 heatwave are between 1 ºC and 5 ºC hotter in the present than they would have been in the past. We interpret the Central Asia November 2023 heatwave as an uncommon event whose characteristics can mostly be ascribed to human driven climate change.
Contact Authors
Davide Faranda, IPSL-CNRS, France 📨davide.faranda@lsce.ipsl.fr 🗣️French, Italian, English
Chen Chen, CCRS, Singapore 📨CHEN_Chen@nea.gov.sg 🗣️English, Chinese
Chenyu Dong, NUS, Singapore 📨chenyu.dong@u.nus.edu 🗣️English, Chinese
Gianmarco Mengaldo, NUS, Singapore 📨mpegim@nus.edu.sg 🗣️ English, Italian
Additional Information : Complete Output of the Analysis
NB1: The following output is specifically intended for scientists and contain details that are fully understandable only by reading the methodology described in Faranda, D., Bourdin, S., Ginesta, M., Krouma, M., Noyelle, R., Pons, F., Yiou, P., and Messori, G.: A climate-change attribution retrospective of some impactful weather extremes of 2021, Weather Clim. Dynam., 3, 1311–1340, https://doi.org/10.5194/wcd-3-1311-2022, 2022.
NB2: Colorscales may vary from the ClimaMeter figure presented above.
The figure shows the average of surface pressure anomaly (msl) (a), average 2-meter temperatures anomalies (t2m) (e), cumulated total precipitation (tp) (i), and average wind-speed (wspd) in the period of the event. Average of the surface pressure analogs found in the counterfactual [1979-2000] (b) and factual periods [2001-2022] (c), along with corresponding 2-meter temperatures (f, g), cumulated precipitation (j, k), and wind speed (n, o). Changes between present and past analogues are presented for surface pressure ∆slp (d), 2 meter temperatures ∆t2m (h), total precipitation ∆tp (i), and windspeed ∆wspd (p): color-filled areas indicate significant anomalies with respect to the bootstrap procedure. Violin plots for past (blue) and present (orange) periods for Quality Q analogs (q), Predictability Index D (r), Persistence Index Θ (s), and distribution of analogs in each month (t). Violin plots for past (blue) and present (orange) periods for ENSO (u), AMO (v) and PDO (w). Number of the Analogues occurring in each subperiod (blue) and linear trend (black). Values for the peak day of the extreme event are marked by a blue dot. Horizontal bars in panels (q,r,s,u,v,w) correspond to the mean (black) and median (red) of the distributions.