Tropical cyclones pose disproportionate threats to the least developed countries and small island developing states in the Southern Hemisphere. Long-term trends in tropical cyclone activity in the Northern Hemisphere have usually been linked to seasonal mean state changes, but this conventional explanation does not hold in the Southern Hemisphere. Here, we discover a new pathway: long-term changes in intraseasonal variability modes can significantly influence the long-term trends of tropical cyclone climatology. From 1980 to 2024, the Southern Hemisphere tropical cyclone number decreased by approximately 28%. About 80% of this decline can be attributed to the weakening of Madden-Julian Oscillation circulation during its active phases over the South Indian and South Pacific oceans. Our analysis indicates that the impact of Madden-Julian Oscillation-related lower tropospheric cyclonic rotation exceeds that of the seasonal mean state, resulting in less favorable conditions for tropical cyclone formation. Our findings provide a new perspective on understanding future changes in tropical cyclone activity under anthropogenic warming. The weakening of the Madden-Julian Oscillation has emerged as the primary driver of the declining trend in Southern Hemisphere tropical cyclone occurrence over recent decades—a pathway that outweighs changes in seasonal mean states

Abstract The global ocean meridional overturning circulation (GMOC) is central for ocean transport and climate variations. However, a comprehensive picture of its historical mean state and variability remains vague due to limitations in modelling and observing systems. Incorporating observations into models offers a viable approach to reconstructing climate history, yet achieving coherent estimates of GMOC has proven challenging due to difficulties in harmonizing ocean stratification. Here, we demonstrate that multiscale data assimilation that integrates atmospheric and oceanic observations into two coupled models in a dynamically consistent way robustly retrieves the past 80-year GMOC. By diagnosing volcanic eruption-induced North Atlantic cooling and surface buoyancy loss, we show historic volcanic eruption events are imprinted in variability of the rebuilt GMOC. The Mt. Pinatubo (1991) volcanic eruption produces a multidecadal characteristic of the overturning evolution by the chain of enhancing diapycnal mixing - strengthening deep convection - mediated by eddy activities.

Summer extreme hot events led to catastrophic consequences on North America’s public health, the economy, and crop production. While a significant advance has been made in applying machine learning (ML) to weather forecasts, whether ML is a winner in seasonal climate prediction of extreme hot events over North America is still uncertain. Here, we analyze the spatiotemporal characteristics of the leading modes of extreme high temperature days (EHDs) over western North America (WNA) and create a precursory predictor library for each of the leading EHDs modes. We then construct ML-based prediction models using the library. Although the ML-based models performed perfectly during training, their performance during independent prediction were less satisfactory. In comparison, a physics-based empirical (PE) model using six physical meaningful predictors showed better prediction skills than the ML models. Notably, the PE model can predict abnormal WNA-EHDs in 2021, while all the ML-based models failed. These results highlight the limitations of pure data-driven approaches without the physical constraints, and emphasize the continued value of physically grounded models in seasonal climate prediction.

As global climate change intensifies, temperature variations are becoming increasingly pronounced, significantly impacting the environment and human health. Land surface models (LSMs) and land cover (LC) datasets are crucial in understanding and predicting land-atmosphere interactions and temperature dynamics. Consequently, a systematic evaluation of different LSMs and LC datasets under varying climatic conditions is urgently needed. This study employed four LSMs (CLM, Noah, PX, and RUC) and three LC datasets (MODIS-2010, MODIS-2019, and CGLC-MODIS-LCZ) within the WRF model to assess their temperature performance in the Northern Hemisphere. The results reveal that the CGLC-Noah combination demonstrates the best performance, achieving the optimal result at 44% of the stations across the Northern Hemisphere, followed by MD19-PX at 19%, with its strong performance concentrated primarily in the cold, high-latitude regions of North America and Eastern Europe. Overall, temperatures were underestimated in tropical and polar regions with average mean biases (MB) of - 1.42( degrees)C and - 0.66( degrees)C, respectively. While temperate regions exhibited relatively small MB, ranging from 1( degrees)C to + 1( degrees)C. Furthermore, the study assessed model performance during extreme weather events, finding that all simulations showed optimal performance for both extreme high and low temperatures in tropical regions (all NRMSE >0.8, normalized root mean square error). Conversely, the lowest performance was observed in polar regions (POC), with NRMSE typically below 0.2, indicating a potential area for improvement. These findings are essential for enhancing model accuracy and reliability, ultimately aiding in the development of effective strategies to combat climate change.

This study investigates triple-dip La Niña events and their influence on Asian summer monsoon rainfall during the first and third years. In the first year, a significant positive rainfall anomaly extends from the Bay of Bengal to the Yangtze River Basin, concurrent with reduced rainfall over the northern Indian Peninsula and the Indochina Peninsula. This pattern largely reverses during the third year. Convergent empirical and modeling evidence reveal that the distinct rainfall responses are linked to different evolutions of the El Niño–Southern Oscillation (ENSO). In the first year, following a preceding El Niño, La Niña onset is rapid. This rapid onset strengthens the Western Pacific Subtropical High (WPSH) and a negative-phase Scandinavian pattern, which jointly shape the initial rainfall distribution. Conversely, by the third year, sustained La Niña amplifies zonal sea surface temperature (SST) gradients in the equatorial western Pacific. This shifts the WPSH northward and triggers a positive Circumglobal Teleconnection (CGT) pattern, collectively driving the reversed rainfall anomalies. Additionally, the second year exhibits relatively weak rainfall anomalies, as both the La Niña onset rate and the zonal SST gradients are near climatological normals. These results are useful for predicting Asian summer monsoon rainfall.

Wind energy is central to global decarbonization strategies, yet its reversibility under atmospheric carbon dioxide (CO₂) removal remains poorly understood. Here, we quantify the hysteretic response of global wind energy resources to symmetric CO₂ forcing by combining a large ensemble of Earth system model simulations with an industrial wind turbine power curve. The forcing pathway consists of a 1

BACKGROUND AND AIMS:Evidence on the associations between tropical cyclone (TC) exposure and acute coronary syndrome (ACS) remains limited, particularly in developing countries. Therefore, this study aimed to investigate the short-term association between TC exposure and ACS incidence and explore potential effect modifiers. METHODS:This time-stratified case-crossover study included ACS patients from a nationwide registry in mainland China between 2015 and 2022. The Willoughby wind field model was chosen to estimate TC-associated wind speeds, with TC exposure defined as the occurrence of daily maximum sustained wind speeds ≥17.5 m/s. The outcomes included ACS and its subtypes, namely, ST-elevation myocardial infarction, non-ST-elevation myocardial infarction, and unstable angina. Conditional quasi-Poisson models with distributed lag non-linear models were applied to assess TC-ACS associations and lag structures. Subgroup analyses were conducted to identify potential effect modifiers. RESULTS:A total of 2 563 780 individuals (64.0 ± 12.4 years; 68% males) were included. Compared with non-TC days, TC days were associated with longer delays in self-referral to the hospital (5.8 vs 5.3 h) and longer admission-to-catheterization times (1.0 vs 0.9 h). Over the 0-3-day period following TC exposure, the risk of developing ACS increased by 14% (95% confidence interval: 2% to 27%). Stronger associations were observed among males, individuals with lower education levels, and those with more ACS risk factors. CONCLUSIONS:TC exposure may increase the ACS burden by simultaneously increasing the risk of incidence and delaying treatment. The government, the public, and healthcare institutions must collaborate proactively to alleviate the burden of TC-associated ACS.

Abstract Drivers of multi‐centennial global monsoon variability remain debated, with internal variability poorly understood. Using nine CMIP6 pre‐industrial millennial simulations, we find that the Atlantic meridional overturning circulation (AMOC) correlates with multi‐centennial fluctuations in the Afro‐Asian summer monsoon (AfroASM), which includes the North African (NAFSM) and Asian (ASM) summer monsoons, but shows minimal correlation with other regional monsoons. Increased AMOC variability may amplify AfroASM fluctuations and strengthen NAFSM‐ASM coherence. Precipitation sensitivity to AMOC reaches 0.5%/Sv (ASM) and 1.57%/Sv (NAFSM). Mechanistically, we suggest that AMOC could influence NAFSM via Atlantic meridional temperature gradient and ASM via land‐sea thermal contrast and NAFSM's incursion into the Arabian Sea, altering rainfall through atmospheric circulation. Conversely, AMOC does not significantly alter temperature gradients in other regional monsoons, explaining minimal rainfall responses. These results highlight internally generated AMOC variability as critical factor for understanding Afro‐Asian hydroclimate variability.

Subseasonal precipitation whiplashes, marked by sudden shifts between dry and wet extremes, can disrupt ecosystems and human well-being. Predicting these events two to six weeks in advance is crucial for disaster management. Here, we show that the propagation diversity of the Madden-Julian Oscillation (MJO)-a key source of subseasonal predictability-will alter under anthropogenic warming. This is evidenced by a 40% increase in fast-propagating events by the late 21st century. Fast-propagating MJOs may rise in a period as early as 2028-2063, increasing the global risk of precipitation whiplashes through teleconnections. We propose a heuristic framework diagnosing that MJO's acceleration is primarily driven by enhanced atmospheric stabilization and El Niño-like sea surface warming. The expected rise in fast-propagating MJOs could improve the predictability of subseasonal weather whiplashes, offering critical lead time for disaster preparedness. Understanding these impending shifts is essential for enhancing subseasonal prediction capabilities.

Understanding the relationship between fire activity and climate variability is a major concern for the scientific community and is essential for reducing economic losses and life-threatening fire hazards.However,the drivers of fire activity and the influence of climate variability remain uncertain.Here,we show that the Madden-Julian Oscillation(MJO)—a dominant tropical subseasonal variability-influences fire activity by modulating local fire-supporting weather through atmospheric teleconnections.Our results show that midlatitude fire emissions exhibit significant subseasonal variability,with MJO-related weather influencing the fire intensity and contributing to large fire events.MJO-related fire events account for about 10％-20％of total midlatitude fire events,suggesting that if MJO teleconnections strengthen in the future,fire emissions and associated economic losses could worsen.

Future projections in extreme precipitation depend heavily on climate models. Therefore, assessing their fidelity in reproducing the extreme rainfall characteristics in historical simulation is critical. We evaluated CMIP6 models' performance in reproducing the climatology of daily extremes, focusing on the global land monsoon (GLM) domain that feeds two‐thirds of the world's population. Compared with ERA5, models demonstrate a significant wet bias in GLM domain for the annual maximum daily precipitation (14.14%) and the extreme tail of daily precipitation distributions (32.53%), more than twice the global average. Decomposition of biases reveals that dynamic processes, particularly vertical velocity, primarily drive these biases. Using the quasi‐geostrophic equation, we determined that the component associated with large‐scale adiabatic disturbances () mainly drives vertical velocity biases, with diabatic heating term amplifying them. Furthermore, a significant correlation between biases and baroclinicity biases in midlatitude suggests that baroclinicity biases are a key contributor to the vertical velocity biases.

Understanding decadal changes in monsoon rainfall is essential for mitigation policies in the next few decades, but comparatively less is known about the Southern Hemisphere monsoon. We find that decadal variations of the Southern Hemisphere land monsoon (SHLM) have a zonal dipole pattern with a significant periodicity of 10-15 years. This spatial pattern is characterized by wet southern African (SAF) monsoon and Australian monsoon (AUM) but a dry southeastern South American monsoon (SESAM). Moisture budget analysis shows that changes in monsoon circulation explain over 70% of the decadal variation. Tropical dynamics dominate the monsoon circulation change, and extratropical Rossby waves also have a contribution. The wet SAF and AUM but dry SESAM pattern is mainly driven by a tropical sea surface temperature (SST) gradient, specifically warm SST over the western Pacific and cold SST over the tropical Indian, central Pacific, and eastern Pacific Oceans. This gradient enhances the Walker circulation and subtropical highs over the South Indian and South Pacific Oceans, increasing moisture convergence over the SAF and AUM. The resultant Walker circulation change decreases ascending motion over the SESAM. The enhancement of AUM rainfall triggers the Pacific- South American pattern of the Rossby wave train, which propagates eastward along the SH subpolar jet, generating descending motion over the SESAM. The tropical and extratropical mechanisms are verified in a coupled climate model with nudged SST and a simplified model with artificial atmospheric heating imposed over eastern Australia, respectively. Our findings help unify the understanding of decadal variations of the regional monsoons and may add confidence for decadal prediction of SHLM changes in the following decades.

Northwestern China (NWC) has a monsoon-like, arid and semi-arid climate with considerable decadal variability and long-term trends. Decadal prediction of summer precipitation remains challenging due to the mixed influence of external forcing and internal variability. This study shows that the decadal internal variability of domain-averaged summer precipitation over NWC (NWCP) primarily originates from the extratropical North Atlantic dipole (NAD) sea surface temperature anomalies (SSTA), which excite a Eurasian Rossby wave train by enhancing the transient eddy forcing. The resultant anomalous Mongolian cyclone increases the NWCP through the cyclonic vorticity-generated upward moisture transport. By combining this empirical relationship and dynamical models’ predicted NAD SSTA, we attempted a hybrid dynamic-empirical model to predict the decadal internal variability component. After adding the external forcing component, the model can predict the decadal NWCP 7–10 years in advance. Our result opens a pathway for decadal prediction of precipitation in central Eurasia’s dry regions.

The decadal change of tropical cyclone frequency (TCF) has been attributed mainly to the Interdecadal Pacific Oscillation (IPO) and Atlantic Multidecadal Oscillation (AMO). However, the relative importance of these two modes on TCF over the North Pacific (NP) and North Atlantic (NA) oceans remains unclear due to the relatively short reliable observation dataset and the interaction between AMO and IPO. Here, we find that the IPO and AMO have comparable impacts on TCF over both NP and NA, suggesting the IPO could cancel the AMO’s impact on NH TCF. By isolating the effects of solo AMO and solo IPO, respectively, from preindustrial simulation, we demonstrated that the two modes have similar magnitudes of impacts on TC genesis index over the NP (NA). Notably, a significant cancellation (amplification) occurs when the two decadal modes are in the same (opposite) phase. Furthermore, we directly detected TCs in the historical simulation of the 22 CMIP6 models, and selected the five models with the best simulations in decadal modes and TCF. The results confirmed that the IPO’s impact on the NH TCF is very close to that from AMO. Our finding suggests the decadal variation of TCF over the NP and NA would significantly weaken once the two decadal modes evolve into the same phase.

The global ocean meridional overturning circulation (GMOC) is central for ocean transport and climate variations. However, a comprehensive picture of its historical mean state and variability remains vague due to limitations in modelling and observing systems. Incorporating observations into models offers a viable approach to reconstructing climate history, yet achieving coherent estimates of GMOC has proven challenging due to difficulties in harmonizing ocean stratification. Here, we demonstrate that applying multiscale data assimilation scheme that integrates atmospheric and oceanic observations into multiple coupled models in a dynamically consistent way, the global ocean currents and GMOC over the past 80 years are retrieved. While the major historic events are printed in variability of the rebuilt GMOC, the timeseries of multisphere 3-dimensional physical variables representing the realistic historical evolution enable us to advance understanding of mechanisms of climate signal propagation cross spheres and give birth to Artificial Intelligence coupled big models, thus advancing the Earth science.

In most practical occasion, frost is formed on cold surface which is cooled from the ambient temperature. Although the initial cooling stage may account for a small proportion in the whole frosting process, the effects of the initial cooling on frosting characteristics could not be overlooked. In this paper, a semi-empirical model of cryogenic frosting involving the initial cooling process under forced convection is established by employing frost properties correlations and heat and mass balance analysis. The frost thickness calculated by the proposed semiempirical model showed good agreement with experimental data within a maximum error of 15 %. Within the constraints of correlation validity, this model is applicable to conditions where ambient temperatures range from 10 degrees C to 30 degrees C, air flow Reynolds numbers span from 7 x 104 to 1.5 x 105, air humidity varies between 3.5 g/kg and 18 g/kg, and initial cooling durations extend from 15 min to 40 min, and the final wall temperature is decreased to about 80K. The results indicate that frost thickness increases with rising ambient temperature, air humidity, and airflow velocity. Notably, higher rates of frost growth are observed during the initial cooling under conditions of elevated air humidity or increased airflow velocity. The trend in frost mass closely mirrors that of frost thickness, however, a more pronounced increase in frost mass occurs with increasing ambient temperature. Furthermore, extending the duration of initial cooling could accelerate the frost growth rate and cause a higher frost surface temperature.

Notable interdecadal variability in tropical cyclone (TC) genesis frequency within western North Pacific (WNP) has been well documented, yet its physical mechanisms remain unclear. This study demonstrates that the interdecadal variation in the WNP TC genesis frequency during the peak TC season (July-October) is strongly influenced to the boreal winter-spring (January-May) North Atlantic Oscillation (NAO) on interdecadal time scales, with the Pacific meridional mode (PMM) acting as a crucial intermediary. Specifically, the NAO triggers a Eurasian wave train, resulting in positive temperature anomalies over northeastern Asia. These anomalies are subsequently transported to the Kuroshio Extension region by the midlatitude westerlies, which weakens the meridional temperature gradient and reduces the strength of the subtropical westerly jet. As the jet weakens, it induces anomalous negative vorticity and anticyclonic circulation to its north. The anomalous northerly winds east of the anticyclone transport cold and dry air southward to the southeastern side of the anomalous anticyclone, where the air accumulates and sinks. This subsidence then alters the local meridional circulation, promoting anomalous deep convection over the central tropical Pacific. The enhanced tropical convection further excites a northward-propagating Pacific-North American (PNA) wave train, leading to the development of an anomalous low pressure system over the North Pacific. Anomalous westerly winds on the southeastern flank of this system subsequently amplify the PMM through wind-evaporation-sea surface temperature (SST) feedback. The PMM-related SST anomalies ultimately induce anomalous cyclonic circulation over WNP through the Gill response, creating favorable conditions for TC genesis. This result reveals a novel remote subtropical modulator of interdecadal variability in WNP TC genesis, offering valuable insights for improving TC activity predictions.

Extreme high-temperature events have had catastrophic impacts on public health, the economy, crop production, and wildfire occurrences in the United States. In the present study, the physical processes controlling the three leading modes of summer extreme high-temperature days (EHDs) over western North America (WNA) are explored, and a physicsbased empirical model (PEM) is established to predict the spatial pattern of WNA-EHDs. The three leading modes of the WNA-EHDs, accounting for 59% of the total variance, exhibit a trend, an interdecadal variability, and an interannual variability, respectively. It is found that the positive anomalies of EHDs are always dominated by the local barotropic anomalous high pressures (anticyclones), which originate from the different upstream cross-Pacific Rossby wave trains forced by various boundary layer anomalies. The established PEM, with six physically meaningful and independent predictors which related to the formation of the cross-Pacific Rossby wave trains, shows encouraging skill for predicting the three leading modes, approaching the upper limit of predictability for the spatial pattern of WNA-EHDs. The results of this study contribute to the seasonal prediction of the spatial distribution of summer WNA-EHDs.