Atmospheric and Oceanic Sciences

The slowing of the Atlantic meridional overturning circulation (AMOC) under anthropogenic warming has been suggested to significantly impact Earth's climate. Here, we isolate and quantify the AMOC impact on atmospheric rivers (ARs) across the twenty-first century using coupled climate model simulations. We find that a weakened AMOC promotes AR frequency in mid-latitudes by intensifying the prevailing westerly winds, especially at the west coast of North America, which dramatically enhances AR-induced precipitation in wintertime California. Aside from dynamic processes, the weakened AMOC can also modulate ARs through thermodynamic processes. It reduces AR frequency and related precipitation over the Arctic and Greenland while increasing AR frequency and associated precipitation along the eastern coast of South America and around Antarctica, owing primarily to AMOC-induced moisture decrease and increase in the Northern and Southern Hemispheres, respectively. Our findings highlight the role of the AMOC in future regional hydroclimate and climate extreme shift.

Methane (CH4) emissions have been detected at glacier margins globally, with subglacial CH4 production identified beneath the Greenland Ice Sheet. Despite its potential role in carbon cycling, an assessment of the sources, production pathways and prevalence of subglacial CH4 export is lacking. Here we report on extensive sampling of 26 meltwater streams across the entire western margin of the Greenland Ice Sheet, revealing a radiocarbon age of 1.5–4.4 thousand years before present for pervasive, biogenic CH4 laterally transported by emerging subglacial supersaturated meltwater. These ages corroborate a smaller-than-present Greenland Ice Sheet during the Holocene Thermal Maximum (11–5 thousand years ago before present), stimulating proglacial organic matter accumulation, which was then overridden by subsequent glacial advance. Applying a continuum degradation model, we demonstrate that western Greenland’s subglacial organic matter can support CH4 release for another 200 years, with a lateral flux of 715 (481–1,020) tonnes per year from its land-terminating sectors. We highlight the pertinence of subglacial carbon cycling to the release of CH4 from all glacial environments globally, and a dynamic sensitivity of the Greenland Ice Sheet not yet fully realized in ice sheet models, via the isotopic assessment of subglacial CH4. Methane in modern subglacial meltwater coming from the western Greenland Ice Sheet largely dates back to the period following the Holocene Thermal Maximum, when a smaller ice sheet allowed organic matter accumulation and biological methane production after ice readvance.

Abstract. Nitrogen dioxide (NO2) is a critical air pollutant with significant environmental and human health impacts, yet global and long-term NO2 datasets with daily continuity and fine spatial resolution remain limited. In this study, we construct a continuous global daily NO2 concentration (https://doi.org/10.5281/zenodo.13842191, Mu and Tao, 2025) spanning from 2005 to 2023 at a 0.1° resolution using the advanced Air Transformer deep learning framework that integrates satellite observations, ground-based measurements, meteorological reanalysis, land-use information, and auxiliary geophysical variables. The resulting dataset shows robust performance across diverse regions and pollution regimes, with improved spatial consistency and reduced biases relative to existing global products. Based on this dataset, we characterize the spatiotemporal evolution of global NO2 concentrations over the past two decades. Global annual mean NO2 increased from 2005 to 2015, followed by a moderate decline during 2016–2019, a pronounced decrease in 2020 associated with COVID-19-related reductions in economic activity and transportation, and a partial rebound thereafter, reaching 3.38 ppbv in 2023. The Northern Hemisphere and tropical regions largely followed the global trend, whereas the Southern Hemisphere exhibited distinct behaviour, with relatively stable or declining NO2 levels prior to 2015, a sharp decrease in 2020, and a stronger post-pandemic rebound during 2021–2023. As one of the global, multi-decadal NO2 datasets with daily resolution, this dataset provides a valuable resource for air quality assessment, exposure analysis, and atmospheric model evaluation.

Abstract Under global warming and enhanced ocean–atmosphere interactions, Guangdong Province, China, experienced an unprecedented cloud‐to‐ground (CG) lightning outbreak in April 2024. The lightning density reached 10.26 flashes·km −2 , 5.3 times the 2015–2023 April mean and even higher than summer climatological peaks. Using lightning observations, radar, sounding, ERA5 reanalysis, and HadISST data, combined with correlation/regression analyses, multivariate empirical orthogonal function (MV‐EOF) analysis, and Mann–Kendall tests, this study investigates the underlying mechanisms focusing on cloud microphysics, atmospheric circulation, and sea surface temperature anomaly (SSTA) forcing. Results show that the extreme event resulted from synergistic effects of cloud microphysical, dynamic, and thermodynamic conditions. Abnormally enhanced upper‐tropospheric ice phase particles and intense updrafts established a favorable vertical structure for lightning electrification, supported by higher convective available potential energy (CAPE) and elevated radar echo tops. Intensified low‐level and upper‐level jets jointly enhanced water vapor transport and upward motion. A decaying El Niño contributed to an anomalous Philippine anticyclone and moisture transport. A significant regime shift around 2005 indicates an increasing influence of the northern Indian Ocean on lightning over South China, independent of the El Niño–Southern Oscillation (ENSO). The 2024 Indian Ocean warming guided the jet stream to intensify dynamic lifting. Warm SSTAs in the Southern Hemisphere provided positive feedback. This study clarifies the cross‐scale mechanisms and highlights the critical role of dynamic lifting, providing a scientific basis for regional lightning prediction under global warming.

Given the large number of record-breaking tropical cyclones (TCs) in recent years, there is a pressing need to investigate how strong TCs respond to climate change. Here we find that the annual maximum lifetime maximum intensity (LMI) of TC in the western North Pacific is strongly correlated with the temperature of a subsurface water mass, exhibiting a multi-decadal V-shaped structure in the past four decades. This water mass originally forms and is subducted in the eastern North Pacific under the center of the North Pacific High (NPH). It is then transported along a subsurface path over approximately four years to the western boundary. Correspondingly, the annual maximum LMI can be predicted several years in advance based on the intensity of NPH. We propose a mechanism in which the highly variable heat content of the subsurface water mass modulates the under-storm sea surface temperature through TC-induced mixing and upwelling process.

Abstract High‐resolution climate simulations are essential to study sub‐daily extreme precipitation, yet their computational demands make long‐term large‐ensemble simulations over a large geographical region often infeasible. We introduce a case‐selective dynamical downscaling (CSDD) framework that reconstructs extreme precipitation statistics at convection‐permitting resolution by simulating only periods when extreme rainfall occurs, rather than performing continuous simulations. Using low‐resolution precipitation as a predictor, we identify and downscale time windows associated with extreme events. Applied to a 30‐year regional climate simulation, CSDD reproduces the statistical distribution of 1–6‐hourly precipitation extremes from a full continuous convection‐permitting simulation at roughly 10 of the computational cost. Because cases are independent, they can be executed in parallel, enabling substantial wall‐time reductions. For applications targeting extreme precipitation, notably climate storylines, CSDD provides a physically grounded and computationally efficient way to supplement storylines with reliable extreme‐value statistics, bridging storyline and statistical approaches to climate extremes.

Abstract. Controlling ozone (O3) in rapidly urbanizing megacities in Southeast and East Asia remains a challenge. O3 is a secondary pollutant formed through nonlinear photochemical reactions with its precursors: nitrogen oxides (NOx) and volatile organic compounds (VOCs). Observation-based quantification of precursor sensitivity remains scarce, limiting actionable O3 control. To address this, we leverage airborne observations from the NASA DC-8 during the ASIA-AQ campaign conducted in February and March 2024 across four Asian megacities: Metro Manila, the Seoul Metropolitan Area, the Tainan–Kaohsiung Metropolitan Area, and the Bangkok Metropolitan Region. These extensive measurements of various trace gases were used to constrain a zero-dimensional box model and estimate the net production rates of Ox (POx, Ox = O3 + NO2). Precursor sensitivity regimes were characterized for each megacity by generating isopleths of POx across varying levels of NOx and VOCs. The analysis revealed that Manila and Tainan–Kaohsiung exhibited predominantly NOx-sensitive conditions, favoring NOx reduction as an effective O3 mitigation strategy, while Bangkok showed a more mixed sensitivity, suggesting combined NOx and VOC reductions. In contrast, Seoul exhibited a primarily VOC-sensitive regime associated with its higher NOx conditions relative to the other cities, underscoring the importance of VOC-focused strategies. In addition, to quantitatively assess sensitivity transitions, we computed orthogonal distances from the isopleth transition boundaries for all four study areas. Diurnal analyses of these distances revealed a shift from more VOC-sensitive conditions in the morning toward more NOx-sensitive regimes in the afternoon. These findings provide critical insights for formulating effective, city-specific O3 control policies in urban environments.

The East Asian summer monsoon anomalies, responsible for floods and droughts across China, pose great challenges to the climate resilience of human society. However, mechanisms and impacts of decadal-scale monsoon variability remain poorly understood due to limited instrumental data. Our annual-resolution speleothem record (1787-2007 CE) from China, along with simulation results, reveals a persistent monsoon weakening since the end of the Little Ice Age, superimposed by decadal oscillations. Five monsoon extremes, triggered by diminished solar output and further amplified by ocean-atmosphere processes in the Atlantic and Pacific oceans, caused widespread megadroughts in China. One marked flood-drought abrupt alternation in the 1850s substantially contributed to the Taiping Rebellion (1851-1864 CE). Our findings demonstrate that monsoon anomalies can cause crop failure and exacerbate overpopulation, ultimately leading to social unrest, particularly in regions experiencing rapid demographic expansion.

Abstract Rainfall among the Amazon has been shown to decline sharply once forest loss exceeds a critical threshold, typically around 30%–40%. However, future interactions between climate change and deforestation on this threshold remain unclear. We model their combined effects by 2050 on rainfall and temperature. Our findings indicate that climate and land‐use change lower the deforestation threshold for rainfall decline—from 50% forest loss under land‐use change alone to 45% under SSP1‐2.6 and 10% under SSP5‐8.5 (90 × 90 km reference grids). Land‐use change alone is projected to warm the region by 0.29°C, while the combined effects under SSP5‐8.5 lead to 1.4°C warming. Annual rainfall is projected to decline by 1.7% due to land‐use change alone and up to 13.9% under SSP1‐2.6. Future climates amplify the importance of forests in maintaining moisture supply for rainfall. These findings underscore the growing vulnerability of the Southern Amazon to rainfall disruption and reduced land–atmosphere system resilience.

Abstract. The Atlantic meridional overturning circulation (AMOC) is expected to decline dramatically over the 21st century, with severe impacts for Northern Hemisphere climate. After 20 years of sustained monitoring in the subtropics, a detectable AMOC weakening trend is now beginning to emerge. However, continuous observations at subpolar latitudes are currently too short-lived to determine any weakening signal above the large-amplitude interannual variability. Here, we introduce a new subpolar observing configuration, SCOTIA (Scotland–Canada overturning array), combining parts of the existing OSNAP mooring array with scattered CTD and Argo data, to extend the record of subpolar AMOC backward in time to cover the subtropical monitoring period, 2004–2024. SCOTIA facilitates a rigorous comparison of the decadal-scale variability in transports and overturning at subpolar and subtropical latitudes. Our results show subpolar AMOC varies on pentadal to decadal timescales with an amplitude comparable to that observed in the subtropics. Anomalously high overturning during 2016–2020 was driven by increased southward transports in the density classes associated with Labrador Sea Water. We find no statistically significant trend in subpolar AMOC during the period 2004–2024.