2023/04/15 Southeast Asia heat peak

15th April 2023 Southeast Asia heat peak influenced by both human-driven Climate Change and Natural Variability

Press Summary (First published 2024/02/26)

Event Description

In April 2023, Southeast Asia sweltered under the grip of intense scorching heat that was part of the heat event commonly known as 2023 Asia heatwave. The heatwave impacted several countries, including India, Bangladesh, Myanmar, Laos, Cambodia, Vietnam, Malaysia, Singapore and the Philippines, where temperatures soared to extraordinary levels, either tying or surpassing previous high temperature records for the month of April. In India temperatures soared above 43 degrees Celsius, Laos, Myanmar and Vietnam experienced highs exceeding 43 degrees Celsius, while Malaysia, Singapore and the Philippines reached temperatures above 37 degrees Celsius. Notably, Thailand was a focal point, grappling with extreme meteorological heat conditions of unprecedented magnitude. The country experienced temperatures of 45 degrees Celsius and above, marking it one of highest ever recorded in the nation, and  triggering widespread health advisories to mitigate the risk of heat-related illnesses.

The extreme event covered here is the heat peak reached on the 15th of April 2023, as part of the 2023 Asia heatwave. On this day, Thailand's Tak province reached a temperature of 45.4°C, contributing to record electricity consumption. The World Weather Attribution (WWA) highlighted that such extreme heat events would have been exceptionally rare in a climate 1.2°C cooler, emphasizing the influence of climate change on the intensity of the Asian heatwave.

The Surface Pressure Anomalies reveal negative anomalies over the domain analyzed. This results in the advection of warm and wet air in the area. Consequently, positive Temperature Anomalies reaching up to 5 °C are observed in a large portion of Thailand. Based on Precipitation Data, this event was characterized by the absence of precipitation over continental areas and wet conditions in the Gulf of Thailand and South China Sea, while Windspeed Data indicate an absence of winds in most areas. Higher temperature anomalies accompanied by the lack of winds and precipitation exacerbate the heat sensation, leading to high humidex levels and pollution episodes.

Climate and Data Background for the Analysis

Anthropogenic climate change has played a significant role in increasing the frequency and intensity of extreme heat events in Southeast Asia, leading to adverse impacts on human health, food security, and overall well-being in the region. Hot extremes, including heatwaves, have become more frequent and intense across most land regions since the 1950s, with high confidence that human-induced climate change is the main driver of these changes (IPCC AR6 WGI SPM - Page 8). Climate-change-related risks are projected to increase progressively in Southeast Asia, with heat stress already affecting human health due to high summer surface air temperatures and humidity in the region. In particular, heat stress and water deficit are affecting human health and food security. Risks due to extreme rainfall and sea level rise are exacerbated in vulnerable Asia. Climatologically, the summer surface air temperature in South, Southeast and Southwest Asia is high, and its coastal area is very humid. In these regions, heat stress is already a medium risk for humans. Large cities are warmer by more than 2 degrees Celsius compared with the surroundings due to heat island effects, exacerbating heat stress conditions. Future warming will cause more frequent temperature extremes and heatwaves especially in densely populated South Asian cities, where working conditions will be exacerbated and daytime outdoor work will become dangerous. The body of literature on the connection between climate change and extreme anthropogenic pollution episodes is essentially based on correlation and regression applied to observation reanalysis but the metrics and methodologies differ making quantitative comparisons difficult. 

Our analysis approach rests on looking for weather situations similar to those of the event of interest having been observed in the past.  For the 15th April 2023 Southeast Asia heat peak 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 pressure system leading to the 15th of April Southeast Asia heat peak have changed in the present (2001–2023) compared to what they would have looked like if they had occurred in the past (1979–2001) in the region [20°W 10°E 25°N 40°N]. The Surface Pressure Changes show no significant changes.  The Temperature Changes show that similar events produce temperatures in the present climate that are between 1 ºC and 2 ºC hotter than what they would have been in the past, over a large area of the region analyzed. The Precipitation Changes show dryer conditions (up to 10 mm/day) on the boundary between Thailand and Cambodia. Windspeed Changes indicate up to a 4 km/h decrease in windiness compared to the past. We also note that Similar Past Events are slightly shifting from occurring in May to March.  Changes in Urban Areas reveal that Vientiane, Tak, and Loei are 1°C to 1.5 °C warmer in the present compared to the past. Additionally, Vientiane and Loei experience up to 4 mm/day less rainfall in the present than in the past, while Tak is up to 2 mm/day wetter.

Finally, we find that sources of natural climate variability, notably the Pacific Decadal 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


Based on the above, we conclude that heat peaks similar to the 15th April Southeast Asia heat peak are between 1 ºC and 2 ºC hotter in the present than they would have been in the past. We interpret the 15th April Southeast Asia heat peak as an event whose characteristics can be ascribed to human driven climate change.

Contact Authors

Gianmarco Mengaldo, NUS, Singapore 📨mpegim@nus.edu.sg 🗣️English, Italian

Davide Faranda, IPSL-CNRS, France 📨davide.faranda@lsce.ipsl.fr 🗣️French, Italian, English

Additional Information : Complete Output of the Analysis

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.