The world has witnessed a significant increase in heatwaves in recent decades, resulting in numerous casualties globally. While studies have focused on mid- and high-latitude regions experiencing unprecedented heatwave occurrences, Southeast Asia (SEA), with its hot climate, dense population, diverse terrains, and underdeveloped economy, remains particularly vulnerable. Surrounded by the world's warmest oceans, SEA is highly susceptible to the increasing frequency, duration, and intensity of heatwaves due to global warming. This study addresses the lack of attention given to SEA heatwaves by focusing on the exceptional 2023 event, which broke temperature records across several countries. The research aims to characterize the event, understand its underlying mechanisms, evaluate forecast performance, assess its likelihood of recurrence, and quantify its far-reaching impacts. This comprehensive analysis provides valuable insights for developing effective risk management strategies in the region.

Existing literature documents the rising global trend of heatwaves and their devastating consequences, with notable examples including the 2003 Western European heatwave (~70,000 excess deaths), the 2010 Russian heatwave (>10,000 deaths), and the 2021 Pacific Northwest heatwave (868 fatalities). Recent research emphasizes the significant surface warming trends in mid- and high-latitude regions. However, studies on heatwaves in SEA are relatively limited, despite the region's inherent vulnerability. While some studies indicate increasing trends in heatwave frequency, duration, and intensity over SEA as a consequence of global warming, a detailed investigation into a specific extreme event like the 2023 heatwave is lacking. This gap in knowledge highlights the necessity of this research.

This study employs a multi-faceted approach to analyze the 2023 Southeast Asia heatwave. Gridded daily maximum 2-meter temperature data from ERA5 reanalysis (1950-2023) and station data from the Global Historical Climatology Network daily (GHCNd) dataset (2023) are used to characterize the spatiotemporal evolution of the heatwave. Areas with record-breaking temperatures are identified at different timescales. Synoptic conditions are analyzed using ERA5 reanalysis data for geopotential height, wind components, specific humidity, and relative humidity at various pressure levels. Outgoing longwave radiation (OLR) data are used for tropical wave analysis, employing wavenumber-frequency spectral analysis to assess the contributions of the Madden-Julian Oscillation (MJO), Equatorial Rossby waves, Kelvin waves, and Mixed-Rossby Gravity waves. Land-atmosphere coupling strength is quantified using a diagnostic based on soil moisture-temperature coupling, considering soil moisture, temperature, actual and potential evaporation, and surface net radiation. The European Centre for Medium-Range Weather Forecasts (ECMWF) operational S2S forecasts are analyzed to evaluate forecast performance, focusing on temperature, high-pressure systems, relative humidity, and soil moisture. The return period of the heatwave is calculated using the generalized extreme value (GEV) distribution and maximum likelihood estimates. Joint probability density functions of key drivers (high-pressure, moisture, and land-atmosphere coupling) are also computed. Finally, the impacts of the heatwave on wildfires (using MODIS fire spot data) and rice production (using USDA data) are assessed.

The 2023 SEA heatwave, particularly the extreme episode from May 4-7, was unprecedented in its intensity and spatial extent. All Continental Southeast Asian countries experienced record-breaking temperatures. The enhanced high-pressure system, influenced by tropical waves (especially Equatorial Rossby and Kelvin waves), played a crucial role, leading to subsidence and moisture divergence. A strong low-pressure system over South China further exacerbated moisture divergence over SEA. The reduction in cloud cover allowed increased solar radiation, leading to rapid warming. The strong land-atmosphere coupling, intensified by soil moisture depletion, further exacerbated surface warming through reduced evaporative cooling and increased sensible heat flux. The ECMWF model effectively predicted the spatial pattern of the heatwave at a 1-week lead time but underestimated its intensity. This underestimation was attributed to the model's limited skill in forecasting soil moisture and thus the land-atmosphere coupling. The return period of the heatwave (4-day mean temperature exceeding 34.3°C) is estimated at 129 years. However, the joint probability of near-surface drying and soil moisture deficiency, triggering strong positive land-atmosphere feedback, was exceptionally low (0.08%). The heatwave resulted in a significant increase in wildfires and a substantial reduction in rice yields across the region.

This study's findings highlight the exceptional nature of the 2023 Southeast Asia heatwave, emphasizing the complex interplay of atmospheric and land-surface processes. The significant role of tropical waves in modulating the high-pressure system and the crucial contribution of land-atmosphere coupling in intensifying the heatwave's severity are key insights. The limitations of the ECMWF model in simulating soil moisture and its implications for heatwave forecasting accuracy are also significant. The long return period and low joint probability of the key drivers underscore the extraordinary nature of this event. The extensive impacts on public health, ecosystems, and agriculture necessitate improved heatwave prediction and risk management strategies.

This research provides a comprehensive understanding of the unprecedented 2023 Southeast Asia heatwave, emphasizing the complex interactions of atmospheric dynamics, land-surface processes, and tropical wave influences. The study underscores the need for improved subseasonal-to-seasonal prediction capabilities, particularly regarding soil moisture and land-atmosphere coupling, to enhance early warning systems and mitigation efforts. Future research should focus on advanced forecasting methods, including improved model representation of key drivers and the integration of dynamical models with machine-learning techniques, to enhance predictive skills for extreme heatwave events in this vulnerable region.

While this study provides a comprehensive analysis of the 2023 Southeast Asia heatwave, several limitations exist. The reliance on reanalysis data for historical climate information introduces uncertainties. The study focuses primarily on the Continental Southeast Asia region and may not fully capture the variability across the entire SEA. The assessment of impacts on agriculture is limited to rice production and may not represent the full extent of agricultural losses. Further research with higher-resolution data and broader impact assessments is recommended to address these limitations.