Paleoclimate records provide a critical long-term perspective on natural climate variability, essential for understanding contemporary climate variations. However, existing paleoclimate proxies lack sufficient spatial-temporal coverage for studying high-impact weather extremes like tropical cyclones (TCs). Here we introduce a multi-source framework that contextualizes the contemporary TC landfalls in East Asia against a multi-century baseline (1368-1911) reconstructed from historical documents. Leveraging pre-industrial and contemporary-era data, the analysis reveals that the relatively small shift toward earlier landfalls in the contemporary era (1946-2020) falls well within the range of fluctuations documented historically (1651-1900). Rather than indicating detectable anthropogenic changes, these results suggest the dominance of natural variability in modulating landfall timing. Our work also suggests consistent natural controls of TC timing in contemporary and pre-industrial eras. This consistency lends credibility to pre-industrial observational datasets and climate simulations, providing a robust template for assessing changes in the seasonality of high-impact extremes.

Future precipitation projections rely heavily on climate models, underscoring the need to evaluate their ability to simulate historical precipitation changes. Using multiple atmospheric models and ensemble simulations, we estimate the forced signals driven by sea surface warming and the direct effects of greenhouse gases and aerosols, as well as the atmospheric internal variability in precipitation trends since 1980. We find that forced precipitation trends are generally consistent across models, while atmospheric internal variability significantly influences regional patterns. Additionally, a few model members can reasonably well reproduce the observed pattern of precipitation trends. We highlight some regional wetting and drying are likely driven by forcings rather than the atmospheric internal variability. Zonal-mean trends over land reveal a "wet gets wetter, dry gets drier" paradigm in the Northern Hemisphere, while the Southern Hemisphere shows drying near 45 degrees S associated with jet stream shifts. These results help improve our understanding of historical precipitation changes.

Aerosol effects on precipitation are crucial factors in climate change, yet they remain poorly understood, representing a large source of uncertainty in climate models. In the Geophysical Fluid Dynamics Laboratory (GFDL) Earth system model, version 4 (ESM4), simulated historical century-scale trends of global land precipitation demonstrate significant drying biases compared to observations, even when imposing observed historical variations of sea surface temperature and sea ice concentrations (LongAMIP simulations). These biases manifest as overestimated decreasing trends in precipitation over tropical-subtropical land and underestimated increases in higher latitudes. In this study, we investigate the "fast response" of land precipitation to historical anthropogenic aerosol emissions and its contributions to the model trend biases, by conducting idealized ESM4 LongAMIP experiments with emissions of either black carbon (BC) or sulfate (SO4) aerosol precursors set to near-preindustrial levels (1850). Local aerosol effects, occurring through alteration of atmospheric energy balance and circulation, emerge as critical drivers of excessive precipitation declines in the LongAMIP runs in some regions: 1) over East Asia, a negative SO4 effect and a positive BC effect contribute to the simulated negative trend bias in LongAMIP; 2) for regions of Africa, the negative fast response to BC and SO4 partially contributes to the overestimated precipitation decline; and 3) over west-central North America, the negative fast response to BC in the model contributes toward underestimating a modest observed increasing precipitation trend. However, over South Asia, eastern North America, and northwest Eurasia, the fast responses of precipitation to aerosols cannot account for the LongAMIP model bias (in the opposite direction), indicating the dominant influence of other factors.

With record-breaking temperatures over 2023-2024 and extreme events observed around the world, there is currently a debate in the scientific literature and media as to whether global warming is accelerating. Here we address this question from a regional perspective; determining regions where an increase in the rate of warming is detected in surface temperature observations. Our results show that there are coherent space-time systems of acceleration in warming since 1970 that are consistent across multiple surface temperature datasets. We show that accelerated warming has occurred in different regions and is mostly present at mid-latitudes of the Northern Hemisphere. There is notable variability in the onset of regional accelerations: the timings vary from the 1980s to 2010s. Our results provide some nuance about the ongoing debate about global warming acceleration by identifying the source regions and their timings.

AbstractWe describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Land Model version 4.1 (LM4.1), which builds on component and coupled model developments over 2013–2019 for the coupled carbon‐chemistry‐climate Earth System Model Version 4.1 (ESM4.1) simulation as part of the sixth phase of the Coupled Model Intercomparison Project. Analysis of ESM4.1/LM4.1 is focused on biophysical and biogeochemical processes and interactions with climate. Key features include advanced vegetation dynamics and multi‐layer canopy energy and moisture exchanges, daily fire, land use representation, and dynamic atmospheric dust coupling. We compare LM4.1 performance in the GFDL Earth System Model (ESM) configuration ESM4.1 to the previous generation component LM3.0 in the ESM2G configuration. ESM4.1/LM4.1 provides significant improvement in the treatment of ecological processes from GFDL's previous generation models. However, ESM4.1/LM4.1 likely overestimates the influence of land use and land cover change on vegetation characteristics, particularly on pasturelands, as it overestimates the competitiveness of grasses versus trees in the tropics, and as a result, underestimates present‐day biomass and carbon uptake in comparison to observations.

Recent studies indicate that virtually all global climate models (GCMs) have had difficulty simulating sea surface temperature (SST) trend patterns over the past four decades. GCMs produce enhanced warming in the eastern Equatorial Pacific (EPAC) and Southern Ocean (SO) warming, while observations show intensified warming in the Indo-Pacific Warm Pool (IPWP) and slight cooling in the eastern EPAC and SO. Using Geophysical Fluid Dynamics Laboratory’s latest higher resolution atmospheric model and coupled prediction system, we show the model biases in SST trend pattern have profound implications for near-term projections of high-impact storm statistics, including the frequency of atmospheric rivers (AR), tropical storms (TS) and mesoscale convection systems (MCS), as well as for hydrological and climate sensitivity. If the future SST warming pattern continues to resemble the observed pattern from the past few decades rather than the GCM simulated/predicted patterns, our results suggest (1) a drastically different future projection of high-impact storms and their associated hydroclimate changes, especially over the Western Hemisphere, (2) a stronger global hydrological sensitivity, and (3) substantially less global warming due to stronger negative feedback and lower climate sensitivity. The roles of SST trend patterns over the EPAC, IPWP, SO, and the North Atlantic tropical cyclone Main Development Region (AMDR) are isolated, quantified, and used to understand the simulated differences. Specifically, SST trend patterns in the EPAC and AMDR are crucial for modeled differences in AR and MCS frequency, while those in the IPWP and AMDR are essential for differences in TS frequency over the North Atlantic.

Abstract Precipitation changes in full response to CO2 increase are widely studied but confidence in future projections remains low. Mechanistic understanding of the direct radiative effect of CO2 on precipitation changes, independent from CO2‐induced SST changes, is therefore necessary. Utilizing global atmospheric models, we identify robust summer precipitation decreases across North America in response to direct CO2 forcing. We find that spatial distribution of CO2 forcing at land surface is likely shaped by climatological distribution of water vapor and clouds. This, coupled with local feedback processes, changes in convection, and moisture supply resulting from CO2‐induced circulation changes, could determine North American hydroclimate changes. In central North America, increasing CO2 may decrease summertime precipitation by warming the surface and inducing dry advection into the region to reduce moisture supply. Meanwhile, for the southwest and the east, CO2‐induced shift of subtropical highs generates wet advection, which might mitigate the drying effect from warming.

There is a lack of consensus on whether North Atlantic tropical cyclone (TC) outer size and structure (i.e., change in outer winds with increasing radius from the TC) will differ by the late twenty-first century. Hence, this work seeks to examine whether North Atlantic TC outer wind field size and structure will change by the late twenty-first century using multiple simulations under CMIP3 SRES A1B and CMIP5 RCP4.5 scenarios. Specifically, our analysis examines data from the GFDL High-Resolution Forecast-Oriented Low Ocean Resolution model (HiFLOR) and two versions of the GFDL hurricane model downscaling climate model output. Our results show that projected North Atlantic TC outer size and structure remain unchanged by the late twenty-first century within nearly all HiFLOR and GFDL hurricane model simulations. Moreover, no significant regional outer size differences exist in the North Atlantic within most HiFLOR and GFDL hurricane model simulations. No changes between the control and late-twenty -first-century simulations exist over the storm life cycle in nearly all simulations. For the simulation that shows significant decreases in TC outer size, the changes are attributed to reductions in storm lifetime and outer size growth rates. The absence of differences in outer size among most simulations is consistent with the process that controls the theoretical upper bound of storm size (i.e., Rhines scaling), which is thermodynamically invariant. However, the lack of complete consensus among simulations for many of these conclusions suggests nontrivial uncertainty in our results.

A substantial number of studies have been published since the Ninth International Workshop on Tropical Cyclones (IWTC-9) in 2018, improving our understanding of the effect of climate change on tropical cyclones (TCs) and associated hazards and risks. These studies have reinforced the robustness of increases in TC intensity and associated TC hazards and risks due to anthropogenic climate change. New modeling and observational studies suggested the potential influence of anthropogenic climate forcings, including greenhouse gases and aerosols, on global and regional TC activity at the decadal and century time scales. However, there are still substantial uncertainties owing to model uncertainty in simulating historical TC decadal variability in the Atlantic, and the limitations of observed TC records. The projected future change in the global number of TCs has become more uncertain since IWTC-9 due to projected increases in TC frequency by a few climate models. A new paradigm, TC seeds, has been proposed, and there is currently a debate on whether seeds can help explain the physical mechanism behind the projected changes in global TC frequency. New studies also highlighted the importance of large-scale environmental fields on TC activity, such as snow cover and air-sea interactions. Future projections on TC translation speed and medicanes are new additional focus topics in our report. Recommendations and future research are proposed relevant to the remaining scientific questions and assisting policymakers.

Abstract High‐resolution atmospheric models are powerful tools for hurricane track and intensity predictions. Although using high resolution contributes to better representation of hurricane structure and intensity, its value in the prediction of steering flow and storm tracks is uncertain. Here we present experiments suggesting that biases in the predicted North Atlantic hurricane tracks in a high‐resolution (approximately 3 km grid‐spacing) model originates from the model's explicit simulation of deep convection. Differing behavior of explicit convection leads to changes in the synoptic‐scale pattern and thereby to the steering flow. Our results suggest that optimizing small‐scale convection activity, for example, through the model's horizontal advection scheme, can lead to significantly improved hurricane track prediction (∼10% reduction of mean track error) at lead times beyond 72 hr. This work calls attention to the behavior of explicit convection in high‐resolution models, and its often overlooked role in affecting larger‐scale circulations and hurricane track prediction.

This study examines the potential impacts of large-scale atmospheric circulations that are forced by sea surface temperatures (SST) on global tropical cyclone (TC) formation. Using the Geophysical Fluid Dynamics Labora-tory (GFDL) global atmosphere and land surface model, version 4 (AM4), under different SST distributions, it is found that the east-west clustering of global TC formation is mainly governed by large-scale circulations in response to given SSTs, instead of direct ocean surface fluxes associated with zonal SST anomalies. Our zonally homogeneous SST simula-tions in the presence of realistic surface coverage show that TC clusters still emerge as a result of the breakdown of zonal circulations related to land-sea distribution, which produce specific "hotspots" for global TC formation. Sensitivity experi-ments with different climate warming scenarios and model physics confirm the persistence of these TC clusters in the absence of all zonal SST variations. These robust results offer new insights into the effects of large-scale circulation and terrain forcing on TC clusters beyond the traditional view of direct SST impacts, which are based on the direct alignment of the warmest SST regions and TC clusters. In addition, our experiments also capture internal variability of the global TC frequency, with an average fluctuation of 6-8 TCs at several dominant frequencies of ;3, 6, and 9 years, even in the absence of all SST interannual variability and ocean coupling. This finding reveals an intrinsic "noise" level of the global TC frequency that one has to take into account when examining the past and future trends in TC activity and their related significance or detectability.SIGNIFICANCE STATEMENT: In this study, the clustering of global tropical cyclone (TC) formation is investi-gated, using global simulations under different idealized sea surface temperature (SST) distributions. Our results show that it is the response of the large-scale tropical circulations to SST anomalies that is mostly responsible for the cluster-ing of global TC formation rather than surface flux differences. It is also found that the tropical atmosphere contains inherent fluctuations in the global TC frequency of 6-8 TCs every 3-9 years, even in the absence of all SST interannual and zonal variability. These results offer new insight into the role of tropical dynamics in governing TC climatology and suggest possible mechanisms underlying the clustering of global TC formation under different climate conditions.

Historical precipitation and temperature trends and variations over global land regions are compared with sim-ulations of two climate models focusing on grid points with substantial observational coverage from the early twentieth cen-tury. Potential mechanisms for the differences between modeled and observed trends are investigated using subsets of historical forcings, including ones using only anthropogenic greenhouse gases or aerosols, and simulations forced with the ob-served sea surface temperature and sea ice distribution. For century-scale (1915-2014) precipitation trends, underestimated in-creasing or unrealistic decreasing trends are found in the models over the extratropical Northern Hemisphere. The temporal evolution of key discrepancies between the observations and simulations indicates that 1) for averages over 15 & DEG;-45 & DEG;N, while there is not a significant trend in observations, both models simulate reduced precipitation from 1940 to 2014, and 2) for 45 & DEG;-80 & DEG;N observations suggest sizable precipitation increases while models do not show a significant increase, particularly during ;1950-80. The timing of differences between models and observations suggests a key role for aerosols in these dry trend biases over the extratropical Northern Hemisphere. Additionally, 3) for 15 & DEG;S-15 & DEG;N the observed multidecadal decrease over tropical west Africa (1950-80) is only roughly captured by simulations forced with observed sea surface temperature; additionally, 4) in the all-forcing runs, the model with higher global climate sensitivity simulates increasing trends of temperature and precipitation over lands north of 45 & DEG;N that are significantly stronger than the lower-sensitivity model and more consistent with the observed increases. Thus, underestimated greenhouse gas-induced warming}particularly in the lower sensitivity model}may be another important factor, besides aerosols, contributing to the modeled biases in precipitation trends.

Tropical cyclone rapid intensification events often cause destructive hurricane landfalls because they are associated with the strongest storms and forecasts with the highest errors. Multi-decade observational datasets of tropical cyclone behavior have recently enabled documentation of upward trends in tropical cyclone rapid intensification in several basins. However, a robust anthropogenic signal in global intensification trends and the physical drivers of intensification trends have yet to be identified. To address these knowledge gaps, here we compare the observed trends in intensification and tropical cyclone environmental parameters to simulated natural variability in a high-resolution global climate model. In multiple basins and the global dataset, we detect a significant increase in intensification rates with a positive contribution from anthropogenic forcing. Furthermore, thermodynamic environments around tropical cyclones have become more favorable for intensification, and climate models show anthropogenic warming has significantly increased the probability of these changes.

Tropical cyclones operate as heat engines, deriving energy from the thermodynamic disequilibrium between ocean surfaces and atmosphere. Available energy for the cyclones comes primarily from upper-ocean heat content. Here, we show that eastern North Pacific hurricanes reach a given intensity 15% faster on average than western North Pacific typhoons despite having half the available ocean heat content. Eastern North Pacific hurricanes also intensify on average 16% more with a given ocean energy (i.e., air-sea enthalpy flux) than western North Pacific typhoons. As efficient intensifiers, eastern Pacific hurricanes remain small during their intensification period, tend to stay at lower latitudes, and are affected by relatively lower vertical wind shear, a colder troposphere, and a drier boundary layer. Despite a shallower warm upper-ocean layer in the eastern North Pacific, average hurricane-induced sea surface cooling there is only slightly larger than in the western North Pacific due to the opposing influences of stronger density stratification, smaller size, and related wave-interaction effects. In contrast, western North Pacific typhoons encounter a more favorable oceanic environment for development, but several factors cause typhoons to greatly increase their size during intensification, resulting in a slow and inefficient intensification process. These findings on tropical cyclones' basin-dependent characteristics contribute toward a better understanding of TC intensification.

U.S. landfalling tropical cyclone (TC) activity was projected for late 21 st century conditions using a two-step dynamical downscaling framework. A regional atmospheric model, run for 27 seasons, generated tropical storm cases. Each storm case was re-simulated (up to 15 days) using the higher resolution GFDL hurricane model. Thirteen CMIP3 or CMIP5 modeled climate change projections were explored as scenarios. Robustness of projections was assessed using statistical significance tests and comparing the sign of changes derived from different models. The proportion of TCs (tropical storms and hurricanes) making U.S. landfall increases for the warming scenarios (by order 50% or more). For category 1-3 hurricane frequency, a robust decrease is projected (basin-wide), but robust changes are not projected for U.S. landfalling cases. A relatively robust increase in U.S. landfalling category 4-5 hurricane frequency is projected, averaging about +400% across the models; 10 of 13 models/ensembles project an increase (statistically significant in three individual models), while three models projected no change. The most robust projections overall for U.S. landfalling TC activity are for increased near-storm rainfall rates: these increases average +18% (all tropical storms and hurricanes), +26% (all hurricanes), and +37% (major hurricanes). Landfalling hurricane wind speed intensities show no robust signal, in contrast to a ~5% increase in basin-averaged TC intensity; basin-wide Power Dissipation Index (PDI) is projected to decrease, partly due to decreased duration. TC translation speed increases a few percent in most simulations. A caveat is the framework’s low correlation of modeled U.S. TC landfalls vs. observed interannual variations (1980-2016).

Here we present a machine learning-based wind reconstruction model. The model reconstructs hurricane surface winds with XGBoost, which is a decision-tree-based ensemble predictive algorithm. The model treats the symmetric and asymmetric wind fields separately. The symmetric wind field is approximated by a parametric wind profile model and two Bessel function series. The asymmetric field, accounting for asymmetries induced by the storm and its ambient environment, is represented using a small number of Laplacian eigenfunctions. The coefficients associated with Bessel functions and eigenfunctions are predicted by XGBoost based on storm and environmental features taken from NHC best-track and ERA-Interim data, respectively. We use HWIND for the observed wind fields. Three parametric wind profile models are tested in the symmetric wind model. The wind reconstruction model's performance is insensitive to the choice of the profile model because the Bessel function series correct biases of the parametric profiles. The mean square error of the reconstructed surface winds is smaller than the climatological variance, indicating skillful reconstruction. Storm center location, eyewall size, and translation speed play important roles in controlling the magnitude of the leading asymmetries, while the phase of the asymmetries is mainly affected by storm translation direction. Vertical wind shear impacts the asymmetry phase to a lesser degree. Intended applications of this model include assessing hurricane risk using synthetic storm event sets generated by statistical-dynamical downscaling hurricane models.

Atlantic hurricanes are a major hazard to life and property, and a topic of intense scientific interest. Historical changes in observing practices limit the utility of century-scale records of Atlantic major hurricane frequency. To evaluate past changes in frequency, we have here developed a homogenization method for Atlantic hurricane and major hurricane frequency over 1851–2019. We find that recorded century-scale increases in Atlantic hurricane and major hurricane frequency, and associated decrease in USA hurricanes strike fraction, are consistent with changes in observing practices and not likely a true climate trend. After homogenization, increases in basin-wide hurricane and major hurricane activity since the 1970s are not part of a century-scale increase, but a recovery from a deep minimum in the 1960s–1980s. We suggest internal (e.g., Atlantic multidecadal) climate variability and aerosol-induced mid-to-late-20th century major hurricane frequency reductions have probably masked century-scale greenhouse-gas warming contributions to North Atlantic major hurricane frequency.