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Abstract Machine learning (ML) models are successful with weather forecasting and have shown progress in climate simulations, yet leveraging them for useful climate predictions needs exploration. Here we show this feasibility using Neural General Circulation Model (NeuralGCM), a hybrid ML-physics atmospheric model developed by Google, for seasonal predictions of large-scale atmospheric variability and Northern Hemisphere tropical cyclone (TC) activity. Inspired by physical model studies, we simplify boundary conditions, assuming sea surface temperature (SST) and sea ice follow their climatological cycle but persist anomalies present at the initialization time. With such forcings, NeuralGCM can generate 100 simulation days in ~8 minutes with a single Graphics Processing Unit (GPU), while simulating realistic atmospheric circulation and TC climatology patterns. This configuration yields useful seasonal predictions (July–November) for the tropical atmosphere and various TC activity metrics. Notably, the predicted and observed TC frequency in the North Atlantic and East Pacific basins are significantly correlated during 1990–2023 (r=~0.7), suggesting prediction skill comparable to existing physical GCMs. Despite challenges associated with model resolution and simplified boundary forcings, the model-predicted interannual variations demonstrate significant correlations with the observation, including the sub-basin TC tracks (p<0.1) and basin-wide accumulated cyclone energy (p<0.01) of the North Atlantic and North Pacific basins. These findings highlight the promise of leveraging ML models with physical insights to model TC risks and deliver seamless weather-climate predictions. 

Changing atmospheric circulations shift global weather patterns and their extremes, profoundly affecting human societies and ecosystems. Studies using atmospheric reanalysis and climate model data indicate diverse circulation changes in recent decades but show discrepancies in magnitude and even direction, underscoring the urgent need for validation with independent, climate-quality measurements. Here we show statistically significant changes in tropospheric circulation over the past two decades using satellite-observed, height-resolved cloud motion vectors from the Multi-angle Imaging SpectroRadiometer (MISR). Upper tropospheric cloud motion speeds in the mid-latitudes have increased by up to about 4 m s−1 decade−1. This acceleration is primarily because of the strengthening of meridional flow, potentially indicating more poleward storm tracks or intensified extratropical cyclones. The Northern and Southern Hemisphere tropics shifted poleward at rates of 0.42 ± 0.22 and 0.02 ± 0.14° latitude decade−1 (95% confidence interval), respectively, whereas the corresponding polar fronts shifted at rates of 0.37 ± 0.31 and 0.31 ± 0.21° latitude decade−1. We also show that the widely used ERA5 reanalysis winds subsampled to the MISR are in good agreement with the climatological values and trends of the MISR but indicate probable ERA5 biases in the upper troposphere. These MISR-based observations provide critical benchmarks for refining reanalysis and climate models to advance our understanding of climate change impacts on cloud and atmospheric circulations. 

Abstract Wind energy plays a critical role in mitigating climate change and meeting growing energy demands. However, the long-term impacts of anthropogenic warming on wind resources, particularly their seasonal variations and potential compounding risks, remain understudied. Here we analyze large-ensemble climate simulations in high-emission scenarios to assess the projected changes in near-surface wind speed and their broader implications. Our analyses show robust wind changes including a decrease of wind speed (i.e., stilling) up to ~15% during the summer months in Northern Midlatitudes. This stilling is linked to amplified warming of the midlatitude land and the overlying troposphere. Despite regional and model uncertainties, robust signals of warming-induced wind stilling will likely emerge from natural climate variations in the late 21st century under the high-emission scenarios. Importantly, the summertime wind stilling coincides with a projected surge in cooling demand, and their compounding may disrupt the energy supply-demand balance earlier. These findings highlight the importance of considering the seasonal responses of wind resources and the associated climate-energy risks in a warming climate. By integrating these insights into future energy planning decisions, we can better adapt to a changing climate and ensure a reliable and resilient energy future. 

The future risk of tropical cyclones (TCs) strongly depends on changes in TC frequency, but models have persistently produced contrasting projections. A satisfactory explanation of the projected changes also remains elusive. Here we show a warming-induced contraction of tropical convection delays and reduces TC formation. This contraction manifests as stronger equatorial convection and weaker off-equatorial convection. It has been robustly projected by climate models, particularly in the northern hemisphere. This contraction shortens TC seasons by delaying the poleward migration of the intertropical convergence zone. At seasonal peaks of TC activity, the equatorial and off-equatorial components of this contraction are associated with TC-hindering environmental changes. Finally, the convection contraction and associated warming patterns can partly explain the ensemble spread in projecting future TC frequency. This study highlights the role of convection contraction and provides motivation for coordinated research to solidify our confidence in future TC risk projections. 

Abstract Landfalling tropical cyclones (LTCs) are the most devastating disaster to affect the U.S., while the demonstration of skillful subseasonal (between 10 days and one season) prediction of LTCs is less promising. Understanding the mechanisms governing the subseasonal variation of TC activity is fundamental to improving its forecast, which is of critical interest to decision-makers and the insurance industry. This work reveals three localized atmospheric circulation modes with significant 10–30 days subseasonal variations: Piedmont Oscillation (PO), Great America Dipole (GAD), and the Subtropical High ridge (SHR) modes. These modes strongly modulate precipitation, TC genesis, intensity, track, and landfall near the U.S. coast. Compared to their strong negative phases, the U.S. East Coast has 19 times more LTCs during the strong positive phases of PO, and the Gulf Coast experiences 4–12 times more frequent LTCs during the positive phases of GAD and SHR. Results from the GFDL SPEAR model show a skillful prediction of 13, 9, and 22 days for these three modes, respectively. Our findings are expected to benefit the prediction of LTCs on weather timescale and also suggest opportunities exist for subseasonal predictions of LTCs and their associated heavy rainfalls. 

Airborne bacteria are an influential component of the Earth’s microbiomes, but their community structure and biogeographic distribution patterns have yet to be understood. We analyzed the bacterial communities of 370 air particulate samples collected from 63 sites around the world and constructed an airborne bacterial reference catalog with more than 27 million nonredundant 16S ribosomal RNA (rRNA) gene sequences. We present their biogeographic pattern and decipher the interlacing of the microbiome co-occurrence network with surface environments of the Earth. While the total abundance of global airborne bacteria in the troposphere (1.72 × 10 24 cells) is 1 to 3 orders of magnitude lower than that of other habitats, the number of bacterial taxa (i.e., richness) in the atmosphere (4.71 × 10 8 to 3.08 × 10 9 ) is comparable to that in the hydrosphere, and its maximum occurs in midlatitude regions, as is also observed in other ecosystems. The airborne bacterial community harbors a unique set of dominant taxa (24 species); however, its structure appears to be more easily perturbed, due to the more prominent role of stochastic processes in shaping community assembly. This is corroborated by the major contribution of surface microbiomes to airborne bacteria (averaging 46.3%), while atmospheric conditions such as meteorological factors and air quality also play a role. Particularly in urban areas, human impacts weaken the relative importance of plant sources of airborne bacteria and elevate the occurrence of potential pathogens from anthropogenic sources. These findings serve as a key reference for predicting planetary microbiome responses and the health impacts of inhalable microbiomes with future changes in the environment. 

Abstract Earlier studies have proposed many semiempirical relations between climate and tropical cyclone (TC) activity. To explore these relations, this study conducts idealized aquaplanet experiments using both symmetric and asymmetric sea surface temperature (SST) forcings. With zonally symmetric SST forcings that have a maximum at 10°N, reducing meridional SST gradients around an Earth-like reference state leads to a weakening and southward displacement of the intertropical convergence zone. With nearly flat meridional gradients, warm-hemisphere TC numbers increase by nearly 100 times due particularly to elevated high-latitude TC activity. Reduced meridional SST gradients contribute to a poleward expansion of the tropics, which is associated with a poleward migration of the latitudes where TCs form or reach their lifetime maximum intensity. However, these changes cannot be simply attributed to the poleward expansion of Hadley circulation. Introducing zonally asymmetric SST forcings tends to decrease the global TC number. Regional SST warming—prescribed with or without SST cooling at other longitudes—affects local TC activity but does not necessarily increase TC genesis. While regional warming generally suppresses TC activity in remote regions with relatively cold SSTs, one experiment shows a surprisingly large increase of TC genesis. This increase of TC genesis over relatively cold SSTs is related to local tropospheric cooling that reduces static stability near 15°N and vertical wind shear around 25°N. Modeling results are discussed with scaling analyses and have implications for the application of the “convective quasi-equilibrium and weak temperature gradient” framework. 

Tropical cyclones (TC) are one of the most severe storm systems on Earth and cause significant loss of life and property upon landfall in coastal areas. A better understanding of their variability mechanisms will help improve the TC seasonal prediction skill and mitigate the destructive impacts of the storms. Early studies focused primarily on tropical processes in regulating the variability of TC activity, while recent studies suggest also some long-range impacts of extratropical processes, such as lateral transport of dry air and potential vorticity by large-scale waves. Here we show that stationary waves in the Northern Hemisphere integrate tropical and extratropical impacts on TC activity in July through October. In particular, tropical upper-tropospheric troughs (TUTTs), as part of the summertime stationary waves, are associated with the variability of large-scale environmental conditions in the tropical North Atlantic and North Pacific and significantly correlated to the variability of TC activity in these basins. TUTTs are subject to the modulation of diabatic heating in various regions and are the preferred locations for extratropical Rossby wave breaking (RWB). A strong TUTT in a basin is associated with enhanced RWB and tropical−extratropical stirring in that basin, and the resultant changes in the tropical atmospheric conditions modulate TC activity. In addition, the anticorrelation of TUTTs between the North Atlantic and North Pacific makes the TC activity indices over the two basins compensate each other, rendering the global TC activity less variable than otherwise would be the case if TUTTs were independent.