The study examined station observations from the National Institute of Meteorology, or INMET. Hourly air-temperature readings from stations in 14 municipalities were checked for missing observations and periods of incomplete coverage. Daily means were then calculated from the available hourly records and aggregated into monthly means so that the observations could be compared with ERA5-Land at the same temporal scale. The evaluation was statewide and station-based, focusing on monthly mean temperature rather than daily extremes, hourly heat events or other near-surface variables.

ERA5-Land is produced by the European Centre for Medium-Range Weather Forecasts and combines observations, satellite information and numerical modeling to reconstruct atmospheric conditions. For this analysis, the researchers used monthly reanalysis data obtained from the Copernicus platform at a spatial resolution of 0.1°. Values originally expressed in Kelvin were converted to degrees Celsius, and the reanalysis series were extracted for the locations and periods corresponding to the weather stations. This approach tested whether a continuous gridded product could provide a useful alternative to the unevenly distributed observation network in Mato Grosso.

The local setting matters because Mato Grosso covers approximately 903,357 square kilometres and includes transitions among the Amazon, Cerrado and Pantanal biomes. The study described two broadly defined climatic periods, with a rainy season mainly from October to April and a dry season from May through September. Mean annual air temperature generally ranges from 23 to 27 °C, while annual precipitation varies from approximately 1,200 to 2,000 mm, with greater rainfall volumes in the northern part of the state. The combination of environmental heterogeneity, elevation differences and pronounced seasonality created a demanding test for a regional reanalysis estimate.

Observed temperatures varied with both location and elevation. Among the higher-altitude stations, Alto Araguaia at 753 metres above sea level recorded a mean annual temperature of 23.73 °C, Campo Verde at 747 metres recorded 23.70 °C and Alto Taquari at 862 metres recorded 22.39 °C. At lower elevations, Cuiabá averaged 27.21 °C and Sorriso 26.14 °C. The highest monthly temperatures were recorded in September and October at all the stations. Cuiabá recorded the highest values among them, reaching 29.85 °C in September, 28.87 °C in October and 28.12 °C in November, while the lowest means occurred from June to July, including 19.98 °C at Alto Taquari, 21.14 °C at Alto Araguaia and 21.88 °C at Salto do Céu.

Across Mato Grosso, the coefficient of determination for estimated against observed monthly temperature was greater than 70%, and most locations had values above 80%. Guiratinga recorded an R² of 92.5%, and Rondonópolis reached 91.9%. The smallest municipal RMSE was 0.48 °C at Sinop. Guiratinga and Tangará da Serra had the largest station-level RMSE values, at 1.02 °C and 1.08 °C, respectively, showing that the generally strong statewide performance did not eliminate local departures. The largest monthly deviations reported were −1.28 °C at Guiratinga in April and 1.29 °C at Tangará da Serra in October.

Seasonality was especially clear in the aggregate error statistics. Monthly RMSE was highest in August, September and October, at 0.95 °C, 1.03 °C and 0.94 °C, respectively. Mean bias was also most positive in September and October, when ERA5-Land estimates were 0.59 °C and 0.48 °C above the corresponding station observations. The numerical results indicate positive bias at 11 of the 14 stations, or 78.5%. Although the source article contains some inconsistent wording about the overall direction of bias, the reported values support a general pattern of overestimation in the warmest late-dry-season months, with both positive and negative departures at individual sites.

Principal component analysis was used to investigate patterns in the monthly errors between observed and estimated temperatures. The first two components explained 45.6% of the variability in the error data: 33.1% was attributed to the first component and 12.5% to the second. PC1 was associated with spatial differences among municipalities, indicating that the magnitude and direction of discrepancies were not homogeneous across the state. Sinop, Sorriso and Santo Antônio do Leste contributed strongly to this axis and generally had smaller differences between estimated and observed temperatures. PC2 was related to the seasonal cycle, with larger errors concentrated from June through October and mainly in negative PC2 values, while smaller errors from December through March occupied the positive region of the component space.

The largest positive mean departure among the stations occurred at Tangará da Serra, where ERA5-Land overestimated temperature by 0.90 °C, while Guiratinga showed the largest underestimation, at −0.93 °C. The investigators interpreted these contrasts in relation to topography, land surface characteristics and regional climatic conditions, all of which can affect agreement between a 0.1° reanalysis grid cell and the immediate surroundings of a weather station. The analysis did not independently isolate the contribution of elevation, soil cover or other local factors, so these should be treated as plausible influences identified through the spatial patterns rather than as experimentally demonstrated causes of the errors.

Several limitations constrain the findings. The validation used only 14 stations across a very large state, leaving many local environments without direct observations. Missing hourly records were particularly common in 2021 and 2022, when the authors identified possible operational, maintenance and power-related interruptions associated with the COVID-19 pandemic period. Consistency checks and monthly aggregation helped address the data gaps, but incomplete station records can still affect the observational reference used for comparison. The study also evaluated only monthly mean air temperature, so its results cannot automatically be extended to daily minima, hourly extremes, heat-wave duration or applications requiring kilometer-scale precision.

Within these limits, the study supports ERA5-Land as a useful tool for constructing spatially continuous historical temperature series in Mato Grosso. The reanalysis captured the broad monthly behavior recorded at the INMET stations, including the major influence of elevation, while its strongest systematic departures occurred during the warm September-to-October interval. It appears capable of filling observational gaps and supporting regional agroclimatic and environmental analyses, but the results do not justify treating the product as a universal replacement for direct measurement. Applications requiring finer precision should account for the 0.1° grid, local topography, seasonal bias, missing station data and the fact that some municipalities exhibited errors larger than the generally favorable statewide results imply.

Subject of Research: Evaluation of ERA5-Land monthly mean air-temperature estimates against 14 Mato Grosso weather stations from 2010 to 2024

Article Title: Spatio-temporal evaluation of air temperature estimated by reanalysis of ERA5-land in Mato Grosso, Brazil

Article References: e Silva, I. A. C., da Silva, T. J. A., Bonfim-Silva, E. M., de Oliveira, N. P. R., Meneghetti, L. A. M., & Custódio, A. S. C. (2026). Spatio-temporal evaluation of air temperature estimated by reanalysis of ERA5-land in Mato Grosso, Brazil. Theoretical and Applied Climatology, 157(11), Article 737. https://doi.org/10.1007/s00704-026-06676-z

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06676-z

Keywords: ERA5-Land, air temperature, Mato Grosso, weather stations, atmospheric reanalysis, seasonal bias, climate monitoring, agroclimatology, Brazil, Spatio-temporal, evaluation, temperature

The study examined the BESS, GOSIF, GLASS, MOD17 and VPM products for 2001–2018, evaluating each one through site-scale comparisons, mapped spatial patterns, seasonal and interannual changes, and estimates of uncertainty. The researchers also separated karst terrain from non-karst areas, allowing them to ask whether familiar relationships between vegetation, climate and productivity remained valid in one of China’s most distinctive ecological regions. Karst landscapes cover extensive parts of southwest China and are visually dramatic, but their subsurface drainage, exposed rock and limited soil development can make surface vegetation appear more disconnected from regional water and climate conditions than it does in conventional ecosystems.

To test performance against direct field observations, the study compared the remote-sensing products with GPP derived from flux towers. Such towers measure exchanges of carbon dioxide and other gases between an ecosystem and the atmosphere, providing an independent check on large-scale satellite estimates. GOSIF generally produced the strongest correlations with the flux-tower-derived values, making it the most consistently aligned product with the tower record. VPM, however, showed relatively low estimation errors at several individual sites. These contrasting results demonstrate why a product that tracks temporal observations well may not necessarily minimize absolute error everywhere on the map.

The distinction is important because satellite GPP products are not direct photographs of photosynthesis. They combine remotely sensed vegetation and climate variables with assumptions about how plants respond to light, temperature, moisture and carbon availability. The algorithms also differ in the ecosystems and sensors used during calibration, and they may represent uncertainty differently. A product can therefore perform well against one validation metric while falling short against another, particularly in an environmentally heterogeneous region where vegetation types, soil depths and rainfall regimes change over short distances.

All five products agreed on a broad regional signal: annual mean GPP was lower in karst areas than in non-karst areas. This consistency provides a useful indication that the products are capturing a real spatial contrast rather than an artefact that appears in only one dataset. The result is also ecologically plausible, because exposed bedrock, limited soil water and relatively low plant-cover fractions can constrain productivity. The agreement does not mean that every product estimates the magnitude of that difference correctly, but it strengthens the case that lower productivity is a characteristic feature of the karst landscape in the mapped region.

Seasonality was another point of agreement. Mean monthly GPP was generally highest during summer and lowest during winter, reflecting the warm growing season and the strong influence of seasonal plant activity on the land carbon cycle. The gap between karst and non-karst areas was smaller in summer than in other parts of the year. One possible interpretation is that peak-season productivity benefits from the greater availability of water and energy, allowing vegetation in karst systems to approach the productivity of neighbouring landscapes. The available results do not identify a single mechanism, so the finding is best treated as an observed pattern rather than a complete explanation.

The long-term trends were less uniform. BESS, GOSIF, MOD17 and VPM showed significant increases in annual mean GPP across the study period, pointing toward a regional rise in estimated photosynthetic activity. GLASS also indicated an increase, but its trend was weak and not statistically significant. The contrast matters for scientists studying whether southwest China’s ecosystems are becoming more or less productive, because a product with an unstable or uncertain trend could change the apparent strength of a multi-decade change. It also demonstrates why analysts should examine both the direction of remote-sensing signals and the statistical evidence supporting them.

Uncertainty was evaluated using the three-cornered hat, or TCH, method, which is designed to separate errors among related remote-sensing products and provide an estimate of their relative uncertainty. MOD17 had the lowest mean relative uncertainty under this measure, followed by VPM. That result is not the same as declaring either product universally superior. TCH assesses uncertainty within the ensemble and metric, whereas site comparisons assess agreement with observed fluxes; rankings can change when the objective, places sampled and evaluation period change. A product with low modelled uncertainty may still disagree with a tower, while a product with higher uncertainty may capture observed variation well.

Together, the results argue against searching for a universal champion among GPP maps. GOSIF may be attractive when the priority is correlation with flux-tower observations. VPM can offer relatively low errors at some sites, and MOD17 showed the smallest TCH-derived mean relative uncertainty. BESS, GOSIF, MOD17 and VPM also detected significant long-term increases that GLASS did not resolve confidently. Product choice should therefore be tied to the scientific question: a regional trend analysis, seasonal profile, site-level flux study or broad carbon budget may require different performance criteria.

Subject of Research: Comparative evaluation of satellite gross primary productivity products and their uncertainty in southwest China’s karst region.

Article Title: Evaluation of spatiotemporal patterns and uncertainty of multi-source remote sensing GPP products in the Southwest karst region of China

Article References: Dong, H., Wu, L., Li, X., Zhang, Y., Luo, A., & Tian, F. (2026). Evaluation of spatiotemporal patterns and uncertainty of multi-source remote sensing GPP products in the Southwest karst region of China. Scientific Reports. https://doi.org/10.1038/s41598-026-76893-z

Image Credits: AI Generated

DOI: 10.1038/s41598-026-76893-z

Keywords: gross primary productivity, remote sensing, karst ecosystems, carbon cycle, China, uncertainty analysis, flux towers, vegetation productivity, satellite products, climate monitoring, Evaluation, spatiotemporal

Stratospheric aerosol injection, or SAI, is the most discussed form of solar geoengineering. The idea is to mimic the cooling effect of large volcanic eruptions by deliberately injecting sulphur dioxide into the stratosphere, where it converts into tiny, long-lived sulphate aerosol particles. These particles scatter incoming sunlight back to space, offsetting some of the warming caused by greenhouse gases. The precedent is real: the 1991 eruption of Mount Pinatubo in the Philippines injected roughly 15 to 20 teragrams of sulphur dioxide into the stratosphere and temporarily lowered global mean surface temperatures by more than one degree Celsius. But deliberate SAI remains deeply controversial, with potential side effects including shifts in regional precipitation, altered temperature gradients between hemispheres and between poles and equator, and delayed recovery of the stratospheric ozone layer. A sudden halt to a deployment could even trigger a catastrophic rapid warming known as the termination shock.

The governance problem is what makes detection so urgent. No global framework currently exists to regulate SAI, despite repeated calls from the United Nations Environment Programme, the European Parliament, and national scientific academies. According to studies under the EU-funded Co-Create project, small-scale outdoor SAI experiments could be carried out today with existing technology at a cost of between 10 and 100 million US dollars, using stratospheric balloons to release anywhere from a few kilograms to a few hundreds of tonnes of sulphur dioxide. Such near-term and mid-term experiments are widely seen as a likely entry point to larger, uncoordinated deployments. A typical moderate volcanic eruption injects a few teragrams of sulphur dioxide, tens of thousands to billions of times more than these exploratory experiments, which is precisely why existing satellites, designed to monitor volcanic plumes, would miss them entirely.

The study tested whether a future satellite instrument could close this surveillance gap. The researchers focused on the Changing-Atmosphere Infra-Red Tomography explorer, or CAIRT, a mission concept that was one of four candidates down-selected in the European Space Agency’s Earth Explorer 11 call. CAIRT would have been the first limb sounder in space to use imaging Fourier-transform thermal infrared technology, observing the limb of the atmosphere at tangent heights from 5 to 115 kilometres with a spectral resolution of 0.25 wavenumbers or better across the mid-infrared range from 718 to 2200 wavenumbers. This design would deliver three-dimensional profiles of trace gases and aerosols with vertical resolution between 1 and 3 kilometres and horizontal resolution between 100 and 300 kilometres, along with temperature profiles resolved to 2 kilometres or finer. Although CAIRT was ultimately not selected for implementation, its scientific goals were recognised as timely, and the concept remains unique in its potential to observe the middle atmosphere.

To evaluate the concept rigorously, the team built what they call a pseudo-reality from state-of-the-art climate model simulations. They used the Community Earth System Model version 2 with the Whole Atmosphere Community Climate Model version 6, run under the Geoengineering Model Intercomparison Project within CMIP6. Specifically, they took the Geo SSP5-34-OS 2.0 scenario, in which sulphur dioxide is injected at four latitudes between roughly 20 and 25 kilometres altitude to hold global warming to 2 degrees Celsius. In the first simulated deployment year, 2034, the injection rates are deliberately tiny: about 0.035 teragrams per year at 15 degrees north, equivalent to roughly 100 tonnes per day, and about 0.005 teragrams per year at 15 degrees south, around 15 tonnes per day. These amounts are characteristic of the near-term experiments that could realistically be performed unilaterally.

From this pseudo-reality, the researchers generated realistic synthetic observations, or pseudo-observations, of what CAIRT would actually measure, using a dedicated Fast Level 2 Simulator that propagates the instrument’s expected random and systematic errors and spatial smoothing characteristics, derived from the mission’s Phase 0 and Phase A feasibility studies. The technique exploits the distinctive rotational-vibrational absorption and emission bands of sulphur dioxide near 8.7 and 7.3 micrometres, and the spectral signatures of sulphate aerosol droplets peaking around 12.5 and 8.3 micrometres, which arise from the undissociated sulphuric acid in the highly acidic stratospheric droplets. Typical total uncertainties for individual retrievals were 0.15 to 0.25 parts per billion in molar fraction for sulphur dioxide and 1.0 to 1.5 parts per trillion in mass fraction for sulphate aerosol, remarkably close to background stratospheric levels.

The results were striking. In the simulated February 2034 scene, CAIRT-like pseudo-observations clearly detected both injection sites, pinpointed their altitude at 25 to 30 kilometres, and quantified the intercepted sulphur dioxide mass at 3.1 tonnes against a true value of 3.4 tonnes at the northern site, and 0.4 tonnes against 0.5 tonnes at the southern site, biases of roughly 10 and 25 percent. Even the weaker Southern Hemisphere injection, cumulatively only a few hundred tonnes by the end of February, stood well above the detection limit. The plume’s descent, rapid zonal dispersion, and poleward transport were all faithfully captured. In practical terms, this means a CAIRT-like instrument could detect and quantitatively characterise a unilateral geoengineering test within hours to a few days of the first injection, something no current satellite can do.

The technique also proved capable of tracking the aftermath. Over the simulated year 2034, the pseudo-observations followed the conversion of sulphur dioxide into sulphate aerosol as the new layer formed at the injection longitudes, spread zonally to encircle the globe, and then dispersed toward higher latitudes in both hemispheres. Differences between the synthetic observations and the underlying model truth generally did not exceed 10 percent within the plume. The instrument even reproduced the self-lofting of the aerosol plume, a subtle process in which the particles absorb solar radiation, heat the surrounding air diabatically, and lift the layer to higher altitudes over time, a phenomenon recently observed after volcanic eruptions such as Raikoke in 2019.

By contrast, the study’s audit of existing capabilities reads as a catalogue of gaps. Solar occultation instruments like SAGE III/ISS achieve excellent precision but have sparse coverage and would only distinguish SAI perturbations at injection rates of 1 to 2 teragrams of sulphur per year, far above exploratory levels. Limb-scattering instruments such as OMPS-LP have worse signal-to-noise ratios, and both operate in the visible range, so they cannot chemically identify sulphate aerosol. Space LiDARs like EarthCARE’s ATLID detect weak aerosol layers but cannot determine composition, while nadir infrared sounders like IASI can identify sulphate but with little or no vertical resolution. The infrared occultation instrument ACE-FTS is expected to be discontinued within a few years, and several other middle-atmosphere missions are nearing retirement, threatening what researchers have called a data desert in stratospheric composition monitoring.

The message of the study is therefore twofold. First, the world is currently blind to the earliest and most plausible forms of geoengineering, the small tests that could precede larger unilateral deployments. Second, high-spectral-resolution mid-infrared limb emission sounding offers a proven-in-simulation path to closing that gap, with benefits extending well beyond geoengineering oversight to wildfire and space-debris aerosol sources, gravity wave characterisation, and understanding of stratospheric circulation in a changing climate. Whether a CAIRT-like mission flies in the coming decades may determine not just what science can see, but whether the international community can verify, and thus govern, one of the most consequential climate interventions humanity might ever attempt.

Subject of Research: Satellite detection of stratospheric aerosol injection geoengineering using mid-infrared limb emission sounding

Article Title: The enhanced capabilities of mid-infrared limb emission sounding to observe stratospheric aerosol injection geoengineering

Article References: Sellitto, P., Kosary, M., Höpfner, M., Funke, B., Hoffmann, A., Ungermann, J., Errera, Q., Tilmes, S., & Sinnhuber, B.-M. (2026). The enhanced capabilities of mid-infrared limb emission sounding to observe stratospheric aerosol injection geoengineering. Atmospheric Measurement Techniques, 19(19), 6379-6393. https://doi.org/10.5194/amt-19-6379-2026

Image Credits: AI Generated

DOI: 10.5194/amt-19-6379-2026

Keywords: stratospheric aerosol injection, geoengineering, CAIRT, mid-infrared limb sounding, sulphur dioxide, sulphate aerosols, satellite remote sensing, solar radiation management, ESA Earth Explorer, climate monitoring, stratosphere, unilateral deployment

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