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

Zhejiang presents an ideal and demanding test case. This coastal province in southeastern China is home to roughly 66.7 million people and an economy exceeding 9 trillion CNY in 2024, yet nearly 75 percent of its land is covered by hills and mountains, with only about 20 percent plains and a sliver of rivers and lakes. Rapid urbanization compounds the challenge, since weather stations are sparse, unevenly distributed, and subject to relocations, instrumentation changes, and gaps in the historical record. Ground observations offer accuracy but limited spatial coverage; satellite land surface temperature products offer detail but generally begin only in the early 2000s and are vulnerable to cloud cover, terrain shading, and atmospheric interference; reanalysis products such as ERA5 provide continuity but at coarse spatial resolutions, typically around 0.25 degrees or coarser, far too blunt to resolve the fine thermal texture of mountainous landscapes.

The team’s solution is an elegant two-part construction they call a spatial-background residual framework. First, they built a high-resolution climatological baseline from an existing hourly, 1-kilometer gridded temperature dataset covering 2008 to 2018, which had itself been developed using the INCA data-fusion framework with reanalysis fields and dense automatic weather station observations. This baseline serves purely as a spatial background, encoding how temperature varies across the terrain on each calendar day of the year. Second, daily temperature residuals—the departures of each station observation from that climatological expectation—were calculated for every meteorological station across the full 1961 to 2020 period. Because these residuals are computed directly from observed temperatures, they inherently preserve the long-term warming trend and interannual variability, while the baseline contributes the terrain-driven spatial detail. Summing the interpolated residual field with the baseline yields the finished reconstruction.

A critical methodological question was how best to interpolate those daily residuals across space. The researchers evaluated three schemes representing different levels of topographic correction and complexity: plain inverse distance weighting, or IDW, which relies only on spatial proximity; a lapse-rate-adjusted version of IDW, in which station temperatures are first corrected to grid-cell elevation using a fixed adiabatic lapse rate of 6.0 degrees Celsius per kilometer; and a multiple linear regression incorporating longitude, latitude, and elevation as predictors. Using leave-one-out cross-validation, in which each station is successively withheld and predicted from the others, the team assessed performance with mean absolute error, root-mean-square error, and the coefficient of determination across decades, seasons, and elevation zones.

The verdict was striking: the simplest method won. IDW without any lapse-rate correction consistently delivered the lowest errors and highest skill, achieving the best performance at roughly 68 percent of stations for daily minimum temperature, 70.7 percent for mean temperature, and 74.7 percent for maximum temperature. In a representative example from 1971 to 1980, IDW reconstructed minimum temperatures with a mean absolute error of just 0.73 degrees Celsius and an R-squared of 0.987, comfortably beating both rivals. The reason lies in the behavior of the lapse rate itself. Analysis of 60 years of observations revealed that near-surface temperature lapse rates in Zhejiang are strongly non-stationary: they peak in summer, with minimum-temperature lapse rates exceeding 7.0 degrees Celsius per kilometer in mountainous areas during July and August, yet collapse toward zero or even turn negative in winter lowlands, where temperature inversions prevail. Applying a fixed correction therefore risks systematic, elevation-related biases—a caution with implications well beyond Zhejiang.

The errors that do remain follow clear and intelligible patterns. Reconstruction accuracy improved steadily from the 1960s onward as station density grew, and summer months outperformed winter months because spatial temperature gradients are weaker in warm weather. Low-elevation areas below 400 meters consistently yielded smaller errors than high-elevation zones, where complex terrain and sparse instrumentation conspire against interpolation. Spatially, larger uncertainties cluster in the mountainous southwest, including parts of Lishui and western Wenzhou, while the plains around Hangzhou, Shaoxing, and Jinhua show excellent agreement, with most stations achieving R-squared values above 0.90 and many above 0.95. Across the entire 60-year span, the annual mean error for all three temperature variables stayed within plus or minus 0.1 degrees Celsius, with no systematic drift across decades—a testament to the temporal stability of the method.

Perhaps the most compelling validation came from real disasters. The team tested ZJ-DAT against two extreme events from 2007, using more than a thousand automatic weather stations as independent ground truth while deliberately excluding any stations that had contributed to the reconstruction. During the cold wave of 4 to 9 March 2007, ZJ-DAT tracked the south-to-north advance of the cold air, accurately reproducing the observed cold centers around Lishui, with R-squared values of 0.65 to 0.79 and root-mean-square errors of 1.01 to 1.67 degrees Celsius. By comparison, the CDAT national dataset managed only moderate agreement, while ERA5 performed poorly, with near-zero or negative correlations and errors approaching 3 degrees Celsius. The heat wave of 30 June to 10 July 2007 told the same story: ZJ-DAT best resolved the core hot zones above 37 degrees Celsius over Jinhua, Shaoxing, and Ningbo and the inland-coastal thermal contrast, while CDAT smoothed away local extremes and ERA5 drifted with warm biases and excessive homogenization. Case studies of cold and heat events in January and July 2020 at four environmentally distinct stations—an island, a mountain site, and two plain stations—further confirmed the reconstruction’s fidelity, with discrepancies generally under 2 degrees Celsius.

Beyond validation, the dataset enabled a first-of-its-kind hazard assessment for the province. Using Gumbel distribution analysis of return periods, the researchers mapped the intensity of extreme cold and heat expected at 5-, 20-, and 50-year recurrence intervals. The results expose stark geographic contrasts in climate risk. Extreme low-temperature hazards concentrate in the northwestern inland regions, where 50-year minimum temperatures plunge below minus 15 degrees Celsius, while the southeastern coast stays comparatively mild. Extreme heat hazards show the opposite pattern, dominated by low-altitude basins in central and northern Zhejiang, where 50-year maximum temperatures climb above 43 to 44 degrees Celsius—figures that carry sobering weight given projections of accelerating heatwave duration under global warming. These maps, grounded in kilometer-scale temperature data rather than coarse reanalysis, offer planners a far sharper picture of where adaptation investments are most needed.

The authors are candid about limitations. Anchoring the reconstruction to a climatology drawn from 2008 to 2018 means the reference field does not reflect the climate state of earlier decades, though because it functions only as a spatial scaffold while temporal signals come from station residuals, warming trends and variability remain intact. The team suggests that future refinements could employ temporally adaptive reference fields. The broader significance, however, is clear: ZJ-DAT demonstrates that a simple, computationally efficient interpolation of station anomalies, layered onto a modern high-resolution climatology, can outperform more elaborate schemes in complex terrain—provided the scheme is chosen with local lapse-rate physics in mind. The framework, and the publicly available dataset released through Zenodo, is designed to be transferable to other topographically complex, observation-limited regions, offering a practical foundation for climate monitoring, extreme-event risk assessment, and adaptation planning as the planet continues to warm.

Subject of Research: High-resolution daily near-surface air temperature reconstruction for Zhejiang Province, China, from 1961 to 2020 using statistical residual interpolation

Article Title: A high-resolution daily temperature reconstruction for Zhejiang Province during 1961–2020 using statistical residual interpolation

Article References: Li, Y., Guo, H., Dong, M., Wu, J., Deng, F., Chen, Y., & Chen, F. (2026). A high-resolution daily temperature reconstruction for Zhejiang Province during 1961–2020 using statistical residual interpolation. Theoretical and Applied Climatology, 157(10), Article 632. https://doi.org/10.1007/s00704-026-06521-3

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06521-3

Keywords: Zhejiang Province, air temperature reconstruction, inverse distance weighting, spatial interpolation, temperature lapse rate, extreme temperature events, heat wave, cold wave, climate monitoring, hazard assessment, ERA5, high-resolution gridded dataset