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To imply the gravity of their impact on Christmas celebration, the term Christmas typhoon recently became more popular to refer to tropical cyclones (TC) in the Western North Pacific (WNP) during its less active season. The past 9 years from 2012 to 2020 saw more than 70% (210%) increases in Christmas typhoon occurrences in the WNP (Philippines). Furthermore, Mindanao Island, which is located in southern Philippines, has experienced an unprecedented 480% increase in TC passage in the same period. Here we show that the detected recent increase in Christmas typhoons are mainly associated with the shift of the Pacific Decadal Oscillation to its positive phase in early 2010s, which led to favorable changes in the large-scale environment for TC development such as higher relative vorticity, anomalous low-level westerlies, warmer sea surface temperatures in the central Pacific, and extended WNP subtropical high. We also found that the poleward shift of the Intertropical Convergence Zone and possibly, the recent recovery of the Siberian High contributed to such increased occurrences. As opposed to the more active TC season, there is a wide research gap during the less active season. We aim to fill in this knowledge gap to gain better insights on TC risk reduction.

Slow-moving tropical cyclones (TCs) can cause heavy rain because of their duration of influence. Combined with expected increase in rain rates associated with TCs in a warmer climate, there is growing interest in TC translation speed in the past and future. Here we present that a slowdown trend of the translation speed is not simulated for the period 1951–2011 based on historical model simulations. We also find that the annual-mean translation speed could increase under global warming. Although previous studies show large uncertainties in the future projections of TC characteristics, our model simulations show that the average TC translation speed at higher latitudes becomes smaller in a warmer climate, but the relative frequency of TCs at higher latitudes increases. Since the translation speed is much larger in the extratropics, the increase in the relative frequency of TCs at higher latitudes compensates the reduction of the translation speed there, leading to a global mean increase in TC translation speed. How the translation speed of tropical cyclones has changed in recent decades and will change in the future has been the subject of debate. Model results show that on average, they have not slowed down in the past, but despite a slowing of tropical cyclones at higher latitudes, a poleward shift in their mean track location causes a general speed up under high greenhouse gas emissions.

In recent years, the East Asian (EA) region experienced escalated cost of damages associated with tropical cyclones (TC) during the mature boreal autumn (i.e., September−October). Questions arise whether such increased TC-associated cost of damages are indicative of increasing activity of TCs in EA, particularly during the mature boreal autumn. Here we show evidence of significantly increasing activity of TCs in EA from 1981 to 2019 that is mainly accompanied by an abrupt regime shift in TC passage frequency since 1998. Such trend and shift are robustly linked to the shift of the Pacific Decadal Oscillation (PDO) to its negative phase in the mid-1990s. Characterized by warm sea surface temperature anomalies in the subtropical North Pacific, a negative PDO phase is related to the weakening of the East Asian subtropical jetstream and the westward displacement of the WNP subtropical high, which initiates a favorable steering environment for increased TC passages into the EA region. Contrasting environmental patterns are associated in a positive PDO phase. Considering the prominence of EA in the global economy, our paper contributes additional insights on long-term tropical cyclone risk reduction and management in the region.

An increasing trend along with an abrupt increase in the peak intensity of tropical cyclones (TCs) passing through the Korean Peninsula (KP) are significantly detected from 1981 to 2020 and since 2003, respectively. Here we present observational evidence that such trend and shift are largely attributed with the increased passages of intense TCs in the KP during the mature boreal autumn (i.e., September–October, SO) and linked with the recent shift of the Pacific Decadal Oscillation (PDO) to its negative phase. A negative PDO during SO is related to environmental changes that are favorable for more intense TC passages in the KP including a weakened East Asian subtropical jet stream, weaker vertical wind shear, warmer subtropical sea surface temperature, and stronger low-level relative vorticity. Such findings are expected to provide new insights on understanding regional TC variability and ultimately, contribute to long range TC prediction initiatives in the KP region.

The 2018 boreal summer in the Western North Pacific (WNP) is highlighted by 17 tropical cyclones (TC)—the highest record during the reported reliable years of TC observations. We contribute to the existing knowledge pool on this extreme TC frequency record by showing that the simultaneous highest recorded intensity of the WNP summer monsoon prompted the eastward extension of the monsoon trough and enhancement of tropical convective activities, which are both favorable for TC development. Such changes in the WNP summer monsoon environment led to the extreme TC frequency record during the 2018 boreal summer. Meanwhile, the highest record in TC frequency and the intensity of the WNP summer monsoon are both attributed with the combined increase in the anomalous westerlies originating from the cold tropical Indian Ocean sea surface temperature (SST) anomalies drawn towards the convective heat source that is associated with the warm central Pacific SST anomalies. Our results provide additional insights in characterizing above normal tropical cyclone and summer monsoon activities in the WNP in understanding seasonal predictable horizons in the WNP, and in support of disaster risk and impact reduction.

Waves critically modulate the air‐sea fluxes, and upper‐ocean thermodynamics in a Tropical Cyclone (TC) system. This study improves the modeling of TC intensification by incorporating non‐breaking wave‐induced turbulence and sea spray from breaking waves into an atmosphere‐ocean‐wave coupled model. Notably, wind forecast error decreased by around 10% prior to TCs' peak intensity. The positive feedback of sea spray along with compensatory negative feedback from non‐breaking waves, overall enhanced TCs' intensity. These breaking and non‐breaking wave‐coupled processes consistently cool sea surface temperature, resulting in improvement of the modeled SST. Observed improvements in full‐year TC cases ranging from Categories I to IV in this study suggest that an accurate characterization of ocean wave‐coupled processes is crucial for improving TCs' intensity forecasts and advancing our understanding of severe weather events in both, the atmosphere and ocean. Plain Language Summary Tropical Cyclones (TCs), such as hurricanes and typhoons, are destructive natural disasters that can cause extensive damage. Our study focused on understanding the role of ocean waves and related processes in TCs. Through numerical modeling, we found that ocean waves, specifically breaking and non‐breaking waves, have a substantial influence on TCs' intensity. Breaking waves contribute positively through the production of sea spray droplets, while non‐breaking wave‐induced turbulence has a compensatory negative effect, resulting in an enhancement in TCs' intensity. Incorporating both wave mechanisms into the models improved the accuracy of TCs' intensity and their underlying sea surface temperature. By highlighting the importance of ocean wave‐coupled physics, we aim to enhance our understanding of TCs and improve disaster preparedness to mitigate their impacts on coastal communities. Key Points Full‐year regional hindcast of Tropical Cyclones (TCs) at the North West Australia Inclusion of wave‐coupled processes improves TCs modeling, by reducing forecast errors and enhancing rapid intensification simulations Sea spray increases TC development while nonbreaking wave turbulence has the opposite effect with the first process dominating

In a globally changing climate, there is a growing concern for understanding and predicting compound climate extremes. However, the relationship of compound climate extremes with each other has been mostly analyzed in isolation and/or on regional scales. Little attention has been paid to their simultaneous occurrence and compound impacts worldwide. Here we demonstrate that the compound climate extremes in the Northern Hemisphere during the boreal summer are interconnected from the tropics to the Arctic. This connection originates from the interannual variations of the Indo-Pacific warm pool’s intertropical convergence zone (ITCZ). We demonstrate that the warm pool ITCZ (WPI) convection possibly influences three major teleconnection patterns (i.e. zonal, meridional, and circumglobal) where compound climate extremes occur along the wave train excited by the WPI convection. Most notably, the WPI can sufficiently explain climate variabilities in the North Atlantic region, which influences the occurrence of compound climate extremes in many parts of Europe and North America. Our findings advance the understanding of the interannual global/regional variability of climate extremes and are potentially valuable for predicting seasonal high-impact climate extremes.

In this study, the causes of the increase in global mean tropical cyclone translation speed (TCTS) in the post-satellite era were investigated. Analysis reveals that the global-mean TCTS increased by 0.31 km h−1 per decade over the last 36 years, but the steering flow controlling the local TCTS decreased by −0.24 km h−1 per decade in the major tropical cyclone (TC) passage regions. These values correspond to a change of 5.9% and −5.6% during the analysis period for the mean TCTS and steering flow, respectively. The inconsistency between these two related variables (TCTS and steering flows) is caused by relative TC frequency changes according to basin and latitude. The TCTS is closely related to the latitude of the TC position, which shows a significant difference in mean TCTS between basins. That is, the increased global-mean TCTS is mainly attributed to the following: (1) an increase (4.5% per decade) in the relative proportion of the North Atlantic TCs in terms of global TC's position points (this region has the fastest mean TCTS among all basins); and (2) the poleward shift of TC activities. These two effects account for 76.8% and 25.8% of the observed global-mean TCTS trend, respectively, and thus overwhelm those of the slowing steering flow related to the weakening of large-scale tropical circulation, which leads to a global mean increase in TCTS. Given that TC activity in the North Atlantic is closely related to the Atlantic Multi-decadal Oscillation and a poleward shift of TC exposure is likely induced by global warming, the recent increase in the global-mean TCTS is a joint outcome of both natural variations and anthrophonic effects.

A novel tropical cyclone (TC) size estimation model (TC-SEM) in the western North Pacific was developed based on a convolutional neural network (CNN) using geostationary satellite infrared (IR) images. The proposed TC-SEM was tested using three CNN schemes: a single-task regression model that separately estimated the radius of maximum wind (RMW) and the radius of 34 kt wind (R34) of the TC, a multi-task regression model that estimated the RMW and R34 simultaneously, and a multi-task regression model using best-track TC intensity information. For model training, validation, and testing, 29,730, 2505, and 11,624 geostationary satellite images of the region around the center of the TC, respectively, were used, each containing four IR bands: short-wavelength IR (3.7 µm), water vapor (6.7 µm), IR1 (10.8 µm), and IR2 (12.0 µm). The results showed that the multi-task model performed better than the single-task model due to knowledge sharing and its ability to solve multiple interrelated tasks simultaneously. The inclusion of TC intensity information in the multi-task model further improved the performance of the RMW and R34 estimations, with correlations (mean absolute errors) of 0.95 (2.05 nmi) and 0.93 (9.77 nmi), respectively, which represent significant improvements over the performance of existing linear regression statistical methods. The results suggested that this CNN model using geostationary satellite images may be a powerful tool for estimating TC sizes in operational TC forecasts.

Global wave hindcasts are developed using the third generation spectral wave model WAVEWATCH III with the observation‐based source terms (ST6) and a hybrid rectilinear‐curvilinear, irregular‐regular‐irregular grid system (approximately at 0.25°×0.25°). Three distinct global hindcasts are produced: (a) a long‐term hindcast (1979–2019) forced by the ERA5 conventional winds U10 and (b) two short‐term hindcasts (2011–2019) driven by the NCEP climate forecast system (CFS)v2 U10 and the ERA5 neutral winds U10,neu, respectively. The input field for ice is sourced from the Ocean and Sea Ice Satellite Application Facility (OSI SAF) sea‐ice concentration climate data records. These wave simulations, together with the driving wind forcing, are validated against extensive in‐situ observations and satellite altimeter records. The performance of the ST6 wave hindcasts shows promising results across multiple wave parameters, including the conventional wave characteristics (e.g., wave height Hs and wave period) and high‐order spectral moments (e.g., the surface Stokes drift and mean square slope). The ERA5‐based simulations generally present lower random errors, but the CFS‐based run represents extreme sea states (e.g., Hs>10 m) considerably better. Novel wave parameters available in our hindcasts, namely the dominant wave breaking probability, wave‐induced mixed layer depth, freak wave indexes and wave‐spreading factor, are further described and briefly discussed. Inter‐comparisons of Hs from the long‐term (41 years) wave hindcast, buoy measurements and two different calibrated altimeter data sets highlight the inconsistency in these altimeter records arising from different calibration methodology. Significant errors in the low‐frequency bins (period T>15 s) for both wave energy and directionality call for further model development. Plain Language Summary Ocean surface waves are fundamentally important for ocean engineering design, ship navigation, air‐sea exchange of gas, heat, momentum and energy, upper ocean dynamics, and remote sensing of the ocean. Spectral wave modeling is an indispensable tool to estimate sea state information. In this study, we present new global wave hindcasts developed using the state‐of‐the‐art model physics and numerics and the modern reanalysis winds and satellite sea ice records. It is demonstrated through validation against in‐situ observations and altimeter records that the global wave hindcasts perform well across multiple parameters. Meanwhile, intercomparisons of wave height from the long‐term hindcast, buoys, and altimeters reveal inconsistency and potential inhomogeneity in these different data sets. The wave hindcasts we developed, in combination with global wave databases published previously, will form a large ensemble of realizations of historical evolution of sea states simulated with distinct wave physics and wind forcing, which will help quantify sea states in real oceans more accurately. Key Points Global wave hindcasts using the observation‐based source terms are developed and validated against extensive observations The wave hindcasts show promising performance across multiple parameters, including wave height, period, and high‐order spectral moments Intercomparisons of wave height from the hindcast, buoys, and altimeters highlight the inconsistency and inhomogeneity in these data sets