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This study examines the interdecadal variations in the frequency and intensity of tropical cyclones (TCs) making landfall in South China (SC) during the period 1975–2018. The annual frequency shows a decrease in 1997 but rises again since 2008 and the annual maximum landfall intensity (MLI) shows an increase since 2012. According to these variations, three subperiods, 1975–1996 (higher frequency but lower MLI), 1997–2011 (lower frequency and MLI) and 2012–2018 (higher frequency and MLI), are defined. The increase in MLI during 2012–2018 is related to the increases in the frequency of (1) TCs undergoing rapid intensification over the South China Sea (SCS) and landfalling in SC, with higher maximum intensity and location of maximum intensity closer to the coast of SC, and (2) intense typhoons (ITYs) over the western North Pacific (WNP), which maintain high intensity before landfall. These changes are closely related to the lower vertical wind shear and higher TC heat potential over the ocean east of the Philippines and the northern part of the SCS. Such an environment is more conducive for TC intensification, leading to the observed increases in the number of rapid-intensifying TCs over the SCS and ITYs over the WNP. Some of these latter TCs move across the SCS and tend to maintain high intensity during landfall in SC. The steering flow also changes, which allows more TCs to enter the SCS, resulting in an increase of ITYs making landfall in SC.

In this paper, U.S. landfalling tropical cyclone (TC) activity is projected for the late twenty-first century using a two-step dynamical downscaling framework. A regional atmospheric model, is run for 27 seasons, to generate tropical storm cases. Each storm case is -resimulated (up to 15 days) using the higher-resolution Geophysical Fluid Dynamics Laboratory hurricane model. Thirteen CMIP3 or CMIP5 climate change scenarios are explored. Robustness of projections is assessed using statistical significance tests and comparing changes across models. The proportion of TCs making U.S. landfall increases for the warming scenarios, due, in part, to an increases in the percentage of TC genesis near the U.S. coast and a change in climatological steering flows favoring more U.S. landfall events. The increases in U.S. landfall proportion leads to an increase in U.S. landfalling category 4–5 hurricane frequency, averaging about + 400% across the models; 10 of 13 models/ensembles project an increase (which is statistically significant in three of 13 models). We have only tentative confidence in this latter increase, which occurs despite a robust decrease in Atlantic basin category 1–5 hurricane frequency, no robust change in Atlantic basin category 4–5 and U.S. landfalling category 1–5 hurricane frequency, and no robust change in U.S. landfalling hurricane intensities. Rainfall rates, averaged within a 100-km radius of the storms, are projected to increase by about 18% for U.S. landfalling TCs. Important caveats to the study include low correlation (skill) for interannual variability of modeled vs. observed U.S. TC landfall frequency and model bias of excessive TC genesis near and east of the U.S. east coast in present-day simulations.

In this study, the performance of sixteen Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating extreme precipitation indices over West Africa has been evaluated. Nine extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) have been used. The performance of CMIP6 models and their ensemble mean was examined by comparing the model results to that of Global Precipitation Climatology Project One-Degree Daily Dataset (GPCP) and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis 3B42 (TRMM) gridded observations during the present-day period 1997–2014 with focus on the summer months (i.e., June–July–August, JJA). Our results show that CMIP6 models reasonably reproduce the spatial patterns of the extreme precipitation indices over the entire region, although their performance is quite different between Sahel and Guinea coast subregions. The gridded observations exhibit significant differences in their estimates of the indices evaluated, and the CMIP6 models are generally closer to GPCP than to TRMM. The models broadly exhibit too many consecutive wet days (CWD) resulting in widespread overestimation over entire West Africa. Also, the heavy (R10 mm) and very heavy (R20 mm) precipitation days are considerably overestimated especially over the mountain regions. Overall, the ensemble mean outperforms any individual model at capturing mean distributions of the extreme precipitation indices, particularly in comparison to the two gridded observations.

The new CNRM-CM6 release of the CNRM/CERFACS atmospheric general circulation model has been used in a rotated/stretched configuration that allows a local horizontal resolution of less than 15 km over the tropical North Atlantic basin. Sea surface temperatures (SST) arise from a previous lower resolution simulation of the Coupled Model Intercomparison Project-5 exercise and corrected through a quantile–quantile method. Moreover, five-member ensemble simulations have been performed for both present and RCP8.5 scenario climates. For validation purposes, another five-member ensemble simulation has been performed with prescribed observed SST. Tracking of tropical cyclones (TCs) in these simulations reveals that the intensity of the simulated TCs are quite realistic and may reach the strongest hurricane ever observed, allowing to distinguish between TC categories in the analysis. Although the model tends to underestimate the occurrence of TCs over low latitudes, the realism of simulated TCs has nevertheless improved compared to previous versions of the model, due to both increased resolution and changes in the parameterizations used in the model. Changes observed in the simulations between present and future climates confirm previous results stating that there is no clear change in the overall number of TCs but an increase in the intensity of major hurricanes as well as an increase of rainfall in all TC categories. A new result suggests that TC activity response to climate warming may be significantly different from 1 month of the hurricane season to another. In our simulations we observe a robust decrease of TCs in the tropics in July while August and September experience a large increase of TCs over the mid-latitudes. Finally, we find a relation between a large increase in TC activity near the African coast and changes in the African atmospheric dynamics and rainfall in September.

This work was supported by the Serrapilheira Institute (grant number Serra-1708-15364 awarded to GOL) and financed in part by the Coordination of Superior Level Staff Improvement (CAPES; finance code 001) in Brazil. GOL is also grateful to a research productivity scholarship provided by the Brazilian National Council for Scientific and Technological Development (CNPq; numbers 310517/2019-2; 308072/2022-7).

The future impacts of climate change on landfalling tropical cyclones are unclear. Regardless of this uncertainty, flooding by tropical cyclones will increase as a result of accelerated sea-level rise. Under similar rates of rapid sea-level rise during the early Holocene epoch most low-lying sedimentary coastlines were generally much less resilient to storm impacts. Society must learn to live with a rapidly evolving shoreline that is increasingly prone to flooding from tropical cyclones. These impacts can be mitigated partly with adaptive strategies, which include careful stewardship of sediments and reductions in human-induced land subsidence.

This study proposes a hybrid intelligence approach based on an extreme gradient boosting regression and genetic algorithm, namely, the XGBR-GA model, incorporating Sentinel-2, Sentinel-1, and ALOS-2 PALSAR-2 data to estimate the mangrove above-ground biomass (AGB), including small and shrub mangrove patches in the Red River Delta biosphere reserve across the northern coast of Vietnam. We used the novel extreme gradient boosting decision tree (XGBR) technique together with genetic algorithm (GA) optimization for feature selection to construct and verify a mangrove AGB model using data from a field survey of 105 sampling plots conducted in November and December of 2018 and incorporated the dual polarimetric (HH and HV) data of the ALOS-2 PALSAR-2 L-band and the Sentinel-2 multispectral data combined with Sentinel-1 (C-band VV and VH) data. We employed the root-mean-square error (RMSE) and coefficient of determination (R2) to evaluate the performance of the proposed model. The capability of the XGBR-GA model was assessed via a comparison with other machine-learning (ML) techniques, i.e., the CatBoost regression (CBR), gradient boosted regression tree (GBRT), support vector regression (SVR), and random forest regression (RFR) models. The XGBR-GA model yielded a promising result (R2 = 0.683, RMSE = 25.08 Mg·ha−1) and outperformed the four other ML models. The XGBR-GA model retrieved a mangrove AGB ranging from 17 Mg·ha−1 to 142 Mg·ha−1 (with an average of 72.47 Mg·ha−1). Therefore, multisource optical and synthetic aperture radar (SAR) combined with the XGBR-GA model can be used to estimate the mangrove AGB in North Vietnam. The effectiveness of the proposed method needs to be further tested and compared to other mangrove ecosystems in the tropics.

The current study extends earlier work that demonstrated future extratropical transition (ET) events will feature greater intensity and heavier precipitation to specifically consider potential changes in the impacts of landfalling ET events in a warming climate. A quasi‐idealized modeling framework allows comparison of highly similar present‐day and future event simulations; the model initial conditions are based on observational composites, increasing representativeness of the results. The future composite ET event features substantially more impactful weather conditions in coastal areas, with heavier precipitation and greater storm intensity. Specifically, a Category 2 present‐day storm attained Category 4 Saffir‐Simpson intensity in the future simulation and maintained greater intensity throughout the entire life cycle, although the storm undergoes less reintensification during the post‐ET process, a result of reduced baroclinic conversion. These findings suggest increased potential for coastal hazards due to stronger tropical cyclone winds and heavier rainfall, leading to more severe coastal flooding and storm surge. Plain Language Summary Earlier studies demonstrate that climate change can amplify the strong winds and heavy rainfall accompanying tropical cyclones (TCs) that are undergoing transformation into midlatitude cyclones. The current study extends earlier work, which focused on oceanic TCs, to specifically consider potential changes in the impacts of landfalling transformation events in a warming climate. The future events feature substantially more impactful weather conditions in coastal areas with heavier rainfall and greater storm intensity. In particular, we find that a Saffir‐Simpson Category 2 tropical storm in present‐day conditions becomes a Category 4 storm in the future, resulting in more extreme weather conditions along high‐latitude coastlines throughout its entire life cycle, even though the storm undergoes less reintensification after it completes the transformation, due to reduced future temperature contrasts in the lower atmosphere The possibility of compound coastal hazards, including stronger winds, lower central pressure, and heavier rainfall, also indicates a heightened risk of coastal flooding and storm surges. Key Points Substantially stronger winds attributed to the intensified transitioning storm are evident, impacting the U.S. East Coast in the future Precipitation analysis features substantial future increases in total rainfall associated with the transitioning storm along the East Coast In the innermost storm core region, rainfall increased at a rate more than double that predicted by Clausius‐Clapeyron scaling

Mangrove forests have survived a number of catastrophic climate events since first appearing along the shores of the Tethys Sea during the late Cretaceous-Early Tertiary. The existence of mangrove peat deposits worldwide attests to past episodes of local and regional extinction, primarily in response to abrupt, rapid rises in sea level. Occupying a harsh margin between land and sea, most mangrove plants and associated organisms are predisposed to be either resilient or resistant to most environmental change. Based on the most recent Intergovernmental Panel on Climate Change (IPCC) forecasts, mangrove forests along arid coasts, in subsiding river deltas, and on many islands are predicted to decline in area, structural complexity, and/or in functionality, but mangroves will continue to expand polewards. It is highly likely that they will survive into the foreseeable future as sea level, global temperatures, and atmospheric CO 2 concentrations continue to rise.