Atmospheric and Oceanic Sciences

Balancing the global mean sea level (GMSL) budget is essential for understanding sea level changes. Large uncertainty after 1960 is reduced by accounting for recent observational advances. Budget closure occurs within 0.18 millimeters per year for all periods analyzed (1960-2023, 1993-2023, and 2005-2023). Trends for these three periods are 2.06, 3.41, and 3.94 millimeters per year, revealing an increase in the rate. The annual residual between observed GMSL and the sum of contributions is only between -13 and 10 millimeters since 1960 and ±5 millimeters after 2005. Further, the GMSL acceleration budget is now closed. The principal drivers for the GMSL trend (acceleration) since 1960 are 43% (41%) from thermosteric ocean expansion, 27% (9%) from glacier melting, 15% (16%) from Greenland, 12% (13%) from Antarctic, and 3% (21%) from land water storage. Results highlight the importance of data processing and bias correction techniques in tracking GMSL and its contributions.

Abstract This study investigates spatiotemporal changes in socioeconomic exposure to tropical cyclone-induced precipitation (TCP) extremes across China using high-resolution rainfall and gridded population datasets. Results show that extreme TCP exhibits a significant increasing trend over central–southern China, while decreasing trends are observed in parts of the Yangtze River Delta. These contrasting patterns are linked to changes in TC characteristics, including intensified precipitation rates and reduced translation speeds over coastal regions, which enhance rainfall persistence and accumulation and thereby contribute to increasing extreme TCP events inland. Regions with high socioeconomic exposure are mainly concentrated in southeastern and central–eastern China. Based on a modified exposure index that integrates physical hazard and socioeconomic factors, we find that although exposure is jointly determined by these components, its recent increase is primarily driven by intensified TCP intensity and duration, with population growth and economic development further amplifying the impacts. Population and Gross Domestic Product exposure to extreme TCP events (>200 mm) increase by approximately 27% and 17%, respectively, with pronounced spatial heterogeneity. Rapid urbanization and economic expansion in recent decades have further elevated vulnerability to TC-induced precipitation extremes. This multiscale framework provides actionable insights for prioritizing mitigation and adaptation strategies, enhancing climate resilience in high-risk zones.

Abstract. Unsustainable human activities have driven global ecological degradation. In China, decades of restoration policies have been implemented to reverse this trend in severely degraded regions with catastrophic soil erosion, transforming them into landscapes of ecological recovery. However, the evolution of soil erosion in these regions remains poorly quantified due to the absence of high-resolution, long-term, and high-frequency monitoring data. Here, to address this gap and provide a reliable spatiotemporal benchmark dataset, we conducted the first 10–30 m quarterly wall-to-wall land change mapping for China's flagship ecological restoration site: the Loess Plateau, based on the developed cross-temporal consistency-constraint deep learning framework. The dataset was generated using over 10 TB of Sentinel and Landsat imagery and documents land-cover dynamics across 100 quarterly time steps from 2000 to 2024, showing an overall accuracy of 81.44 % based on 40 000 annotated samples and 79.8 % for third-party validation sources. The resulting maps record pronounced land-cover dynamics, including forest expansion (+13 131 km2), cropland expansion (+28 095 km2), and bare land reduction (−65 029 km2) over the past decades. Furthermore, the produced dataset was combined with environmental factors to measure the 25-year water-induced soil erosion, where comparison with government survey data shows strong consistency, with a mean absolute error of 4.50 %. The dataset further illustrates that long-term ecological interventions have substantially reduced erosion intensity in the region by 30 % over the past 25 years, from 13.34 to 9.35 t (hm2 a)−1. Based on this benchmark, the long-term, fine-grained soil erosion becomes possible to estimate. The data-driven analysis indicates that current erosion is most severe in the central and southwestern Loess Plateau, and scenario modeling based on multiple factors suggests that optimized vegetation distribution – including grassland expansion and cropland-to-forest conversion – could potentially reduce future erosion intensity to 6.42 t (hm2 a)−1. This dataset provides a comprehensive benchmark for erosion mitigation in the Loess Plateau and its underlying drivers, providing critical insights for sustainable land management, ecological restoration, and policy development both in China and across fragile ecosystems worldwide. The land-cover maps and soil erosion maps are available at https://doi.org/10.57760/sciencedb.33656 (Cheng et al., 2026).

Centennial-scale changes in Atlantic Meridional Overturning Circulation (AMOC) strength might disturb global climate by altering interhemispheric heat transport and CO2 partitioning between the ocean and the atmosphere. Due to the short instrumental record and lack of high-resolution paleo records that so far only resolve millennial-scale changes, centennial-scale changes remain elusive. Here we use radiocarbon ventilation ages from a western equatorial Atlantic sediment core with a remarkably high sedimentation rate to reconstruct AMOC variability during the last deglaciation, with a focus on Heinrich Stadial 1 (HS1; 17.8-14.8 ka). Results from model simulations indicate that ventilation ages serve as a sensitive proxy for AMOC variability under weak overturning conditions (i.e., during HS1) at our study location. Notably, within an overall weakened AMOC condition during HS1, our record shows two centennial-scale AMOC intensifications: one from 16.5 to 15.8 ka and another at ~15.4 ka. These centennial-scale episodes of intensified AMOC briefly revitalized Atlantic interhemispheric heat transport during HS1, resulting in decreased precipitation over northeastern Brazil and short-lived but intense changes in climate elsewhere. These episodes of AMOC intensification likely transported substantial volumes of CO2-rich water from the mid-depth Atlantic to the Southern Ocean, where the CO2 was rapidly outgassed to the atmosphere. Using radiocarbon ages from Atlantic sediments, AMOC variability during Heinrich Stadial 1 is reconstructed, revealing brief intensifications that altered heat transport, reduced rainfall over northeastern Brazil, and likely enhanced atmospheric CO2.

Abstract Drier and warmer climates have allowed fires to increasingly burn carbon-dense peatland ecosystems. Here we document a 2025 Scottish megafire in the UK, which spread rapidly and burned severely across peatlands in Scotland with anomalously low soil moisture, emitting 38,600 MgC (25,200–119,000 MgC). Peat combustion contributed nearly 85% of total emissions, suggesting drier climates increase fire emissions from peat, which can require decades to centuries to recover.

Abstract. Nighttime light (NTL) data serve as critical indicators of human activities and have been widely applied in urbanization monitoring and socioeconomic analyses. The two most widely used global NTL datasets, derived from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and the Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) aboard the Suomi National Polar-orbiting Partnership satellite, differ substantially in spatial resolution and temporal coverage, which hinders their direct integration into a consistent long-term dataset. Previous studies have explored the construction of annual or aggregated NTL data, but these methods often smooth out short-term fluctuations and seasonal variations. Monthly NTL, on the other hand, can provide a more detailed representation of temporal variations. However, the challenge with monthly data lies in maintaining consistent spatial resolution while capturing high-frequency temporal variations tied to economic cycles and seasonal trends, with data gaps persisting, further complicating the generation of continuous, high-resolution monthly NTL datasets. To overcome these challenges, we propose a super-resolution network for DMSP reconstruction, with dedicated pre- and post-processing to generate long-term monthly VIIRS-like NTL products (MVNL). Leveraging multi-modal observations, monthly VIIRS-like products are reconstructed by translating calibrated DMSP data from 1992 to 2013, with 2012 and 2013 serving as the overlapping years between the DMSP and NPP-VIIRS datasets. In particular, the 2013 annual data were used for model training and cross-sensor mapping, and the 2012 monthly NPP-VIIRS data were used as an independent validation benchmark. To construct the long-term VIIRS-like time series, we additionally gap-filled missing observations in the monthly NPP-VIIRS data for 2012–2024 and performed temporal correction to the reconstructed 1992–2012 NTL using the monthly NPP-VIIRS data from 2012 to 2013. Compared with the VIIRS NTL of Earth Observation Group (EOG), the extended dataset shows substantial agreement during the overlapping months in 2012, with a mean R2 of 0.65 and RMSE of 14.27 at the pixel scale and an even higher mean R2 of 0.96 at the city scale, underscoring the reliability of the reconstructed dataset for city-level applications. The 2012 annual composite derived from MVNL shows strong agreement with the EOG product, with R2 values of 0.72 at the pixel scale and 0.98 at the city scale. Moreover, city-level evaluation against radiance-calibrated DMSP products further verifies the reconstruction accuracy, with an R2 exceeding 0.94. Compared with existing NTL datasets, MVNL achieves substantial improvements in resolution, spatial calibration accuracy, and temporal continuity, establishing a continuous and trustworthy data resource. The extended monthly VIIRS-like NTL dataset for 1992–2024 is freely available online at https://doi.org/10.25442/hku.31321315.v2 (Cheng et al., 2026a).

Abstract Climate conditions worldwide are influenced by the mean and variability of the tropical Pacific zonal sea surface temperature (SST) gradient. How this gradient responds to greenhouse gas forcing is therefore critical for accurate future climate projections. The nature of the response, however, remains debated: historical model simulations favor a weakening trend, whereas observational records from the same period are characterized by a strengthening trend. To explain this model–observation discrepancy, some attribute the observed trend to internal variability or observational uncertainties, while others suggest that models may inaccurately simulate the radiatively forced response. Past studies have analyzed different trend intervals and observational datasets, potentially contributing to conflicting conclusions about whether observations reflect the forced response. We present a comprehensive analysis of observed zonal SST gradient trends and their statistical significance. We estimate observed trends over all 20-year or longer intervals within the 1870–2024 period and subsequently evaluate these trends against a series of null hypotheses using bootstrapped ensembles of various statistical, conceptual, and geophysical models. Our analysis reveals that both strengthening and weakening trends are observed, depending on the analyzed intervals; however, intervals extending into the 21st century, particularly those since 1950 or those over a century or longer, exhibit statistically significant strengthening trends, suggesting that such trends are unlikely to have emerged from internal variability alone. This finding has implications for the historical and probable near-term transient responses, indicating they are likely radiatively forced. We confirm these findings with multiple observational datasets, demonstrating that data uncertainties minimally influence our conclusions.

Abstract Global warming is driving changes in atmospheric moisture seasonality and an increase in the frequency of prolonged precipitation anomalies. These anomalies are often assumed to be characterized by moisture sourced from oceanic evaporation, rather than being moderated by recycled terrestrial evapotranspiration. However, current indexes used to evaluate hydroclimatic anomalies, which exclude particle tracking, do not account for different precipitation moisture sources. Here, stable isotopes of hydrogen and oxygen are used to differentiate precipitation moisture sources, enabling a novel approach to tracking anomalous dry periods through an isotope‐based Evaporation and Moisture Recycling Index (iEMI). iEMI correlated evaporation‐sourced precipitation with prolonged dry periods for European droughts (2011–2013), the Cape Town South Africa “Day Zero drought” (2015–2018) and the Australian Millennium drought (1997–2010). iEMI aligned best to anomalous precipitation events linked to the strength and phase of the El Niño Southern Oscillation across all sites and could be used for drought management interventions.

Since 2013, China has implemented strict air cleaning policies, yet atmospheric nitrate (NO3−) pollution remains inadequately mitigated in many regions. It is widely recognized that enhanced atmospheric oxidation promotes NO3− formation, undercutting the effectiveness of coal combustion source (CCS) controls. However, the impact of contributions from multiple non-coal combustion sources (NCCS) has consistently been overlooked. Here, we quantify the formation pathways and sources of NO3− in China over the past twelve years through long-term measurements of the dual-isotope composition (δ15N and δ18O) of NO3− combined with machine learning. Our results reveal that, despite substantial shifts in NO3− formation pathways, its formation efficiency remains largely invariant. Moreover, while CCS has reduced its contribution to NO3− by 12.3% as of 2025 in China, four NCCSs, enhanced by the energy transition and climate warming, are emitting more NOx precursors in many regions. Individually, each of these NCCSs now contributes at a level comparable to that of CCS. We estimate a nationally averaged decrease in NO3− concentration of only 7.3% in China in the future, even if CCS’s contribution is further halved relative to 2025 haze day levels. Our study underscores the urgency of implementing coordinated multi-source NOx control strategies to achieve sustained improvements in air quality.

The role of active faults in driving rock uplift is well known, but their influence on rock damage and erosional efficiency remains unclear globally. Using 1744 beryllium-10 ( 10 Be)–derived erosion rates, we show that erosional efficiency is elevated on average within ~15 kilometers of a fault trace and decreases with distance, up to ~100 kilometers. Reverse faults and those longer than 140 kilometers show the strongest effects. This length scale of decay suggests that tectonic damage extends beyond fault-core pulverization on primary faults, possibly including fracturing or grain-to-grain contact weakening due to seismic shaking and distributed deformation on complex fault networks. Machine learning identified fault proximity as a dominant control on erosional efficiency, exceeding precipitation and lithology, particularly when a measure of seismic shaking is included. These findings indicate that active tectonics are associated with erosion not only through uplift but also by enhancing erosional efficiency through long-range rock damage.