The research, published in Atmospheric and Oceanic Science Letters, examined more than six decades of records, drawing on observations and atmospheric reanalysis data spanning 1961 to 2024. Rather than treating all heatwaves as a single category, the team separated them into three types: events that only push daytime temperatures to extremes, events that only produce anomalously hot nights, and the compound events in which both days and nights remain dangerously hot. Comparing the three across China, the researchers found that compound events are particularly concentrated over the Yangtze River Basin, the densely populated and agriculturally vital region that follows the country’s longest river.

One of the study’s most striking findings concerns rhythm. Compound heatwaves over the basin, the analysis showed, display a pronounced 10–30-day periodicity, a subseasonal cycle often referred to in atmospheric science as quasi-biweekly variability. Daytime-only and nighttime-only heatwaves are less tightly coupled to this rhythm. In other words, the events that deny residents any nighttime relief are not random occurrences scattered through summer; they tend to arrive on a recognizable subseasonal clock, driven by slowly evolving patterns in the large-scale atmospheric circulation.

That rhythmic structure matters for forecasting. Variability on the 10–30-day scale sits in the sweet spot of subseasonal-to-seasonal prediction, the forecast range that lies beyond the two-week limit of reliable weather prediction but shorter than seasonal outlooks. If forecasters can identify the precursors of the compound-heatwave cycle, they may gain a valuable head start in warning hospitals, power grid operators, and agricultural planners that a multi-day stretch of unrelenting heat is becoming more likely.

The study goes beyond identifying the rhythm and reconstructs the physical sequence that produces it. The researchers describe a two-stage process. In the first stage, about a week before a compound heatwave strikes, the region experiences increased upward motion and rainfall. That may sound counterintuitive for a heat event, but the wetter soils left behind by this pre-heatwave precipitation turn out to be a crucial ingredient. Moisture stored in the ground becomes fuel for the atmosphere in the days that follow.

In the second stage, as the event approaches, an atmospheric wave pattern propagates eastward toward the basin. This wave favors anticyclonic conditions over the Yangtze region, the kind of large-scale sinking motion that suppresses cloud formation. With fewer clouds overhead, more solar radiation reaches the surface, intensifying daytime heating. At the same time, the wetter soil supports stronger evapotranspiration, the process by which plants and soil release water vapor into the air. Southwesterly winds add a third ingredient, transporting warm and moist air into the region from lower latitudes.

The combined effect is a lower atmosphere that is simultaneously warm and humid, a state that sustains extreme heat through both halves of the day. During daylight hours, strong incoming solar radiation drives surface temperatures upward. After sunset, the abundant water vapor in the boundary layer, supplied by local evapotranspiration and by moisture transported on southwesterly flow, traps heat near the ground and slows radiative cooling, keeping nighttime temperatures anomalously high. Humid air also raises the heat index, making hot nights feel even more oppressive and dangerous to human health than dry heat of the same temperature.

“Compound heatwaves are not simply daytime heat continuing into the night,” said Prof. Yitian Qian, corresponding author of the study. “They result from the coordinated evolution of atmospheric circulation, radiation, soil moisture and moisture transport over a period of several days.” That framing represents a shift in how scientists think about these events. Rather than viewing a compound heatwave as a daytime extreme that merely lingers, the study presents it as the end product of a multi-day coupling between the sky and the land, in which rainfall a week earlier helps set the stage for humid, sleepless nights to come.

The Yangtze River Basin is a particularly consequential place for this kind of research. Home to hundreds of millions of people and a cornerstone of China’s rice production, the region has repeatedly experienced severe summer heat in recent years, including episodes that strained power supplies and threatened crops. Because compound heatwaves concentrate there more than elsewhere in China, according to the new analysis, understanding their subseasonal precursors carries direct implications for protecting both urban populations and food systems in one of the world’s most economically important river valleys.

The practical payoff of the study lies in early warning. The researchers note that changes in rainfall, soil moisture and large-scale circulation before heatwave onset may provide useful early signals of compound heat extremes. A week of unusually wet weather followed by the arrival of an eastward-moving wave pattern and building anticyclonic conditions could, in principle, be recognized in forecast models as a compound-heatwave signature well before the first extreme day arrives. Soil moisture observations, satellite estimates of evapotranspiration, and monitoring of quasi-biweekly circulation anomalies could all feed into such an early-detection framework.

There is also a broader scientific agenda ahead. The authors indicate that future work will examine how tropical and midlatitude atmospheric variability contribute to these events, and whether the precursor signals identified here can genuinely improve subseasonal prediction skill. If they can, the payoff would extend beyond the Yangtze: many of the world’s major heatwave-prone regions feature similar interactions between soil moisture, moisture transport and slowly evolving circulation patterns. For now, the study offers a clear message about the anatomy of sleepless heat. The nights that offer no relief are not accidents of a single hot afternoon, but the culmination of a week-long collaboration between rain-soaked ground, clearing skies, and rivers of warm, wet air converging over the basin.

Subject of Research: Subseasonal mechanisms sustaining day–night compound heatwaves over the Yangtze River Basin

Article Title: Why do some heatwaves last through the night in the Yangtze River Basin?

Article References: Why do some heatwaves last through the night in the Yangtze River Basin?. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: compound heatwaves, Yangtze River Basin, subseasonal variability, quasi-biweekly oscillation, soil moisture, evapotranspiration, anticyclone, moisture transport, atmospheric circulation, nighttime heat, early warning, Atmospheric and Oceanic Science Letters

The model, named PI-TGNet, was developed by Dr. Hengde Zhang, a senior engineer at the National Satellite Meteorological Center of China, together with his jointly supervised doctoral students. Its defining feature is written directly into its name: physics-inspired. Rather than allowing a neural network to mine raw data for statistical correlations alone, the researchers embedded physical guidance into the model’s architecture so that it learns the characteristic wind-speed changes that reliably precede thunderstorm gusts. This design choice reflects a growing recognition in the atmospheric science community that purely data-driven approaches, however powerful, can falter when confronted with rare or rapidly evolving phenomena whose training examples are limited. By anchoring the learning process to known physical behavior, PI-TGNet gains a form of structural intuition about where and when convective winds are likely to turn destructive.

What makes the system genuinely multi-source is its fusion of three complementary observing platforms. Ground-based automatic weather stations provide high-frequency point measurements of wind speed and direction at the surface, exactly where gusts do their damage, but the stations are scattered unevenly across the landscape and can easily miss a gust that passes between them. Weather radar offers a rich spatial picture of the convective systems themselves, revealing the reflectivity structures, outflow boundaries, and downdraft signatures that generate surface gusts, yet radar says little directly about the wind a person would actually feel at ground level. Fengyun-4 geostationary satellites contribute continuous wide-area observations of cloud tops and storm dynamics, filling gaps where neither radar nor station coverage is adequate. PI-TGNet weaves these three streams together into a single coherent product: regional thunderstorm-gust identification maps refreshed every 10 minutes at a spatial resolution of 1 kilometer.

The technical mechanism that binds these heterogeneous data together is a cross-attention architecture. Attention mechanisms, borrowed from modern machine learning, allow a model to weigh the relevance of different pieces of information dynamically rather than treating all inputs equally. In PI-TGNet, cross-attention connects the point observations from weather stations with the spatial fields from radar and satellites, so that a sudden wind-speed spike recorded at a single station can direct the model’s focus to the convective structures visible in radar and satellite imagery over the surrounding region. Conversely, an intensifying storm cell seen from space can prime the network to scrutinize nearby station traces for the abrupt changes that signal an imminent gust. This dialogue between sparse point data and dense spatial data is precisely what a human forecaster attempts, often under severe time pressure, when piecing together a gust warning.

Dr. Zhang summarized the philosophy behind the design in remarks accompanying the release: “By incorporating physical guidance into the deep learning model, we enable it not only to recognize abrupt changes in wind-speed curves, but also to focus on the key structures of convective systems.” The statement captures the dual character of the model. On one hand, it behaves like a vigilant observer of surface anemometers, alert to the sharp inflections in wind-speed curves that empirical threshold methods detect only crudely. On the other, it acts like a radar-savvy storm analyst, attending to the organization and evolution of the thunderstorm complexes that produce those curves in the first place. The fusion of both perspectives within a single spatiotemporal network is what distinguishes PI-TGNet from earlier attempts at automated gust detection.

The performance figures reported in the study are striking by the standards of severe-convective-weather verification. When tested on thunderstorm-gust datasets compiled from eastern and southern China, two regions with dense observing networks and frequent warm-season convection, the model achieved a probability of detection of 0.9520, meaning it successfully flagged more than 95 percent of the gust events in the evaluation data. Equally important, it attained a critical success index of 0.8151, a composite measure that penalizes both missed events and false alarms. A critical success index above 0.8 indicates that the vast majority of the model’s gust identifications corresponded to real events, a level of precision that empirical threshold schemes, which typically trade sensitivity for specificity, have struggled to approach. For operational meteorologists, high scores on both metrics translate directly into warnings that are simultaneously more complete and less prone to eroding public trust through unnecessary alarms.

The practical implications extend across several high-stakes sectors. Aviation is perhaps the most exposed: microbursts and gust fronts have historically been implicated in takeoff and landing accidents, and even with modern wind-shear detection systems at major airports, the suddenness of thunderstorm outflows keeps them on the list of most-feared weather hazards. Ground transportation faces its own exposure, as crosswinds capable of overturning high-sided vehicles can materialize along a highway corridor with little lead time. Outdoor work, from construction cranes to festival staging to maritime operations in coastal waters, similarly depends on warnings that arrive early enough to matter. A 10-minute update cycle at kilometer-scale resolution, generated automatically from data that national meteorological services already collect, could give duty forecasters a continuously refreshed picture of gust risk rather than a patchwork of threshold alarms.

The choice of a 1-kilometer grid is also significant in the context of nowcasting trends. Thunderstorm gusts are inherently small-scale phenomena, and identification products coarser than the storms themselves tend to smear the risk across broad areas, diluting its usefulness. By producing maps at a resolution comparable to the width of a typical gust front, PI-TGNet aligns its output with the spatial scale at which decisions are actually made, whether that decision is rerouting air traffic, pausing crane operations, or issuing a public alert for a specific district. The 10-minute cadence matches the tempo of convective evolution, in which a storm can mature from innocuous cell to wind-producing system within the span of a single conventional observation cycle.

The research team is explicit that the current results mark a beginning rather than an endpoint. Their stated plans include evaluating the model under different regional and meteorological conditions, a necessary step because convection in eastern China’s humid coastal plains behaves differently from convection in other climatic regimes, and a network trained on one environment may not transfer cleanly to another. The team also intends to incorporate additional atmospheric physics into the framework, deepening the physical constraints that guide the network’s learning. Both efforts target the same goal: generalizability. A gust-identification system is only as valuable as the range of conditions over which it can be trusted, and the researchers frame their future work as building toward more refined and reliable technical support for regional severe-convective-weather monitoring and early warning.

The broader significance of the study lies in its demonstration of how physics-informed machine learning can address one of the hardest classes of forecasting problems: rare, fast, small, and dangerous. Thunderstorm gusts sit at the intersection of every factor that makes severe weather difficult to warn against, and the fact that a multi-source deep learning model can push detection probabilities above 0.95 while keeping false alarms in check suggests a viable path forward. As geostationary satellites deliver ever richer imagery, radar networks expand, and surface stations multiply, the raw ingredients for such systems will only improve. The remaining work, as Dr. Zhang and his students recognize, is to ensure that the algorithms fusing those ingredients remain grounded in the physics of the storms themselves, so that when the wind rises without warning, the warning arrives first.

Subject of Research: Physics-inspired multi-source deep learning for thunderstorm gust identification

Article Title: Multi-source observations improve thunderstorm gust identification

Article References: Multi-source observations improve thunderstorm gust identification. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: thunderstorm gusts, deep learning, PI-TGNet, weather radar, Fengyun-4 satellites, automatic weather stations, nowcasting, severe convective weather, cross-attention mechanism, early warning, China Meteorological Administration, Atmospheric and Oceanic Science Letters

The spatial structure of the 2025 anomalies was as noteworthy as their magnitude. Rather than a uniform wetting, the year displayed a striking north-south contrast across central and eastern China, with conditions skewed toward a wetter north and a drier south. This dipole pattern matters enormously for water resource management, agriculture and flood defense, because it concentrates hydrological stress in different regions at different times. In the north, above-normal rainfall swollen by record-breaking seasonal rain episodes filled reservoirs and saturated soils, while parts of the south faced periods of deficit that required careful allocation of irrigation supplies. Climate scientists note that such reversed or amplified precipitation gradients are consistent with the kind of circulation disruptions expected as the East Asian summer monsoon responds to a warming background climate, though attribution of any single year’s pattern requires careful analysis beyond the scope of the annual summary.

Temperature statistics for the year were dominated by the persistence of heat rather than a single spectacular spike. The annual count of high-temperature days, a metric that tracks how often stations exceeded defined heat thresholds, climbed to a new historical maximum, underscoring that 2025 was not merely warm on average but repeatedly hot in ways that stress human health, power grids and crop development. Central and eastern China endured the fourth-strongest large-scale heatwave since systematic records began in 1961, an event distinguished by its spatial footprint and intensity. Compounding the summer burden, autumn brought so-called “autumn tiger” episodes, a colloquial Chinese term for unseasonably hot spells that arrive after the nominal end of summer and extend the season of heat stress well into what should be a cooling period. The combination of an exceptional summer heatwave and lingering autumn warmth pushed cumulative heat exposure metrics to levels without precedent in the observational archive.

The precipitation side of the ledger was equally remarkable, with multiple seasonal benchmarks falling in the same year. The rainfall amount and duration of the North China rainy season both set new records, a doubly significant outcome because the length of the rainy season governs how long soils remain saturated and how sustained flood risk persists across the densely populated North China Plain. Separately, the West China autumn rain phenomenon, a characteristic autumnal rainfall regime over the country’s western interior, also reached record intensity, and national autumn precipitation as a whole established a new high. For three distinct seasonal precipitation measures to break records simultaneously is unusual and points to a persistently anomalous circulation configuration during the second half of the year, with moisture transport pathways repeatedly directed toward regions where they produced prolonged, heavy and impactful rainfall.

The consequences of this wet, energetic year were felt most acutely during the summer, when exceptionally severe rainstorm processes struck North China, Northeast China and Inner Mongolia. These episodes broke daily and cumulative rainfall records at numerous individual stations, overwhelming urban drainage systems and rural flood defenses alike, and ultimately triggered regional major flooding across the Haihe River Basin, one of China’s principal river systems that drains the Beijing-Tianjin-Hebei heartland. The Haihe Basin has a long and well-documented history of catastrophic floods, and modern water infrastructure was engineered with historical maxima in mind; rainfall events that rewrite those maxima test the assumptions embedded in decades of hydraulic planning. Long-lasting and intense West China autumn rain added a second wave of agricultural disruption, interfering with autumn harvesting operations and delaying winter-wheat sowing, the planting window on which the following year’s wheat harvest depends. Farmers in affected areas faced the difficult choice between harvesting waterlogged fields and risking grain quality losses.

Tropical cyclone activity also ran above normal on both sides of the life-cycle ledger, with the number of storms forming in the western North Pacific and the number making landfall on the Chinese coast both exceeding their climatological averages. Autumn typhoons successively impacted South China, and several systems struck during national holiday periods, when travel surges, crowded tourist destinations and family gatherings dramatically increase the population exposed to coastal and inland hazards. The report highlights that these holiday-timed landfalls carried elevated disaster risk, because evacuation logistics, transportation capacity and emergency communications are all strained when hazards coincide with peak seasonal migration. The concurrence of an active typhoon season with the record autumn rainfall regime illustrates how multiple hazard streams can overlap within a single season, compounding rather than merely adding to regional impacts.

Not every region and season told the same story, and the report is careful to document the counterpoints to the dominant warm-wet narrative. Meteorological drought, defined by sustained precipitation deficits and elevated evaporative demand, displayed prominent regional and sub-seasonal variations, appearing and receding across different areas on timescales short enough to complicate drought monitoring and response. Cold-wave outbreaks occurred more frequently than the long-term norm, a reminder that a warming climate does not eliminate severe winter intrusions and that mid-latitude circulation variability can still deliver sharp, damaging cold snaps. Severe convective weather, including the short-lived but violent storms that produce damaging winds, hail and tornadoes, was active nationwide, and the national total of gale days reached its highest level since 1991. Spring sand-dust events over northern China were also more frequent than the long-term average, linking the year’s weather to the condition of arid and semi-arid source regions upwind.

One of the most consequential findings of the assessment concerns the bottom line of disaster economics. Despite the sheer frequency of extreme weather and climate events through 2025, the overall losses attributed to meteorological disasters came in below the 2015-2024 decadal average. The authors of the report do not interpret this as evidence that the hazards were mild; rather, the outcome reflects the cumulative effect of China’s sustained investment in early warning systems, forecast skill, disaster preparedness, infrastructure hardening and coordinated emergency response, which together reduce the vulnerability that converts a hazardous event into a catastrophic loss. The distinction between hazard frequency and disaster impact is a central theme of modern climate risk science, and 2025 offered a vivid national-scale demonstration that improved forecasting and preparedness can bend the loss curve even as the hazard curve rises.

Taken together, the 2025 assessment contributes to a growing body of evidence that China’s climate is shifting toward conditions in which record warmth, intense precipitation and compound seasonal extremes are no longer rare curiosities but recurring features of the national climate. The annual report series itself, now spanning eight consecutive years in a peer-reviewed international journal, provides a consistent methodological framework that allows year-to-year comparison and long-term trend detection, a resource that climate researchers, water managers, agricultural planners and policy makers increasingly rely upon. As the global mean temperature continues its upward trajectory, the report’s documentation of tied temperature records, simultaneous seasonal precipitation records and a rising count of heat days offers a granular, regionally detailed picture of what a warming world looks like in practice for one of the most populous and economically significant nations on Earth. The full findings are available in Atmospheric and Oceanic Science Letters, published by the Institute of Atmospheric Physics at the Chinese Academy of Sciences.

Subject of Research: The state of China's climate in 2025, including record warmth, precipitation extremes and high-impact weather events.

Article Title: China's 2025 climate: Distinct warm‑wet conditions and multiple new climate records

Article References: China's 2025 climate: Distinct warm‑wet conditions and multiple new climate records. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: China climate 2025, record temperature, precipitation records, Haihe River Basin floods, heatwave, typhoons, autumn rain, drought, cold waves, National Climate Center, Atmospheric and Oceanic Science Letters, climate monitoring