A Physics-Based Parameterization of Air–Sea Momentum Flux at High Wind Speeds and Its Impact on Hurricane Intensity Predictions

A new bulk parameterization of the air–sea momentum flux at high wind speeds is proposed based on coupled wave–wind model simulations for 10 tropical cyclones that occurred in the Atlantic Ocean during 1998–2003. The new parameterization describes how the roughness length increases linearly with wind speed and the neutral drag coefficient tends to level off at high wind speeds. The proposed parameterization is then tested on real hurricanes using the operational Geophysical Fluid Dynamics Laboratory (GFDL) coupled hurricane–ocean prediction model. The impact of the new parameterization on the hurricane prediction is mainly found in increased maximum surface wind speeds, while it does not appreciably affect the hurricane central pressure prediction. This helps to improve the GFDL model–predicted wind–pressure relationship in strong hurricanes. Attempts are made to provide physical explanations as to why the reduced drag coefficient affects surface wind speeds but not the central pressure in hurricanes

New parameterization of air-sea exchange coefficients and its impact on intensity prediction under major tropical cyclones

Understanding and quantifying air-sea exchanges of enthalpy and momentum fluxes are crucial for the advanced prediction of tropical cyclone (TC) intensity. Here, we present a new parameterization of air-sea fluxes at extreme wind speeds from 40 m s−1 to 75 m s−1, which covers the range of major TCs. Our approach assumes that the TC can reach its maximum potential intensity (MPI) if there are no influences of external forces such as vertical wind shear or other environmental constraints.This method can estimate the ratio of the enthalpy and momentum exchange coefficient (Ck/Cd) under the most intense TCs without direct flux measurements. The estimation showed that Ck/Cd increases with wind speed at extreme winds above 40 m s−1. Two types of surface layer schemes of the Hurricane Weather and Research Forecast (HWRF) were designed based on the wind speed dependency of the Ck/Cd found at high winds: (i) an increase of Ck/Cd based on decreasing Cd (Cd_DC) and (ii) an increase of Ck/Cd based on increasing Ck (Ck_IC). The modified surface layer schemes were compared to the original HWRF scheme (using nearly fixed Cd and Ck at extreme winds; CTRL) through idealized experiments and real-case predictions. The idealized experiments showed that Cd_DC reduced frictional dissipation in the air-sea interface as well as significantly reduced sea surface cooling, making the TC stronger than other schemes. As a result, Cd_DC reduced the mean absolute error and negative bias by 15.0% (21.0%) and 19.1% (32.0%), respectively, for all lead times of Hurricane Irma in 2017 (Typhoon Mangkhut in 2018) compared to CTRL. This result suggests that new parameterization of Ck/Cd with decreasing Cd at high winds can help improve TC intensity prediction, which currently suffers from underestimating the intensity of the strongest TCs

An Index to Better Estimate Tropical Cyclone Intensity Change in the Western North Pacific

A revised predictor called the net energy gain rate (NGR) is suggested by considering wind dependent drag coefficient based on the existing maximum potential intensity theory. A series of wind speed dependent NGR, known as NGR‐w, is calculated based on pre‐tropical cyclone (TC) averaged ocean temperatures from the surface down to 120 m (at 10‐m intervals) to include the TC‐induced vertical mixing for 13 years (2004–2016) in the western North Pacific. It turns out that the NGR50‐w (NGR‐w based on temperature averaged over top 50 m) has the highest correlation with 24‐h TC intensity change compared with the commonly used sea surface temperature‐based intensification potential (POT), depth‐averaged temperature‐based POT (POTDAT), and constant drag coefficient in the NGR. To demonstrate the effectiveness of the NGR50‐w, we designed and conducted experiments for training (2004–2014) and testing (2015–2016). The model with the NGR50‐w shows greater skill than the model with POTDAT or POT by reducing prediction errors by about 16%

Possible influence of the warm pool ITCZ on compound climate extremes during the boreal summer

Abstract 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.</jats:p

Numerical Simulation of Sea Surface Directional Wave Spectra under Hurricane Wind Forcing

Numerical simulation of sea surface directional wave spectra under hurricane wind forcing was carried out using a high-resolution wave model. The simulation was run for four days as Hurricane Bonnie (1998) approached the U.S. East Coast. The results are compared with buoy observations and NASA Scanning Radar Altimeter (SRA) data, which were obtained on 24 August 1998 in the open ocean and on 26 August when the storm was approaching the shore. The simulated significant wave height in the open ocean reached 14 m, agreeing well with the SRA and buoy observations. It gradually decreased as the hurricane approached the shore. In the open ocean, the dominant wavelength and wave direction in all four quadrants relative to the storm center were simulated very accurately. For the landfall case, however, the simulated dominant wavelength displays noticeable overestimation because the wave model cannot properly simulate shoaling processes. Direct comparison of the model and SRA directional spectra in all four quadrants of the hurricane shows excellent agreement in general. In some cases, the model produces smoother spectra with narrower directional spreading than do the observations. The spatial characteristics of the spectra depend on the relative position from the hurricane center, the hurricane translation speed, and bathymetry. Attempts are made to provide simple explanations for the misalignment between local wind and wave directions and for the effect of hurricane translation speed on wave spectra

Tropical cyclone intensity estimation through convolutional neural network transfer learning using two geostationary satellite datasets

Accurate prediction and monitoring of tropical cyclone (TC) intensity are crucial for saving lives, mitigating damages, and improving disaster response measures. In this study, we used a convolutional neural network (CNN) model to estimate TC intensity in the western North Pacific using Geo-KOMPSAT-2A (GK2A) satellite data. Given that the GK2A data cover only the period since 2019, we applied transfer learning to the model using information learned from previous Communication, Ocean, and Meteorological Satellite (COMS) data, which cover a considerably longer period (2011–2019). Transfer learning is a powerful technique that can improve the performance of a model even if the target task is based on a small amount of data. Experiments with various transfer learning methods using the GK2A and COMS data showed that the frozen–fine-tuning method had the best performance due to the high similarity between the two datasets. The test results for 2021 showed that employing transfer learning led to a 20% reduction in the root mean square error (RMSE) compared to models using only GK2A data. For the operational model, which additionally used TC images and intensities from 6 h earlier, transfer learning reduced the RMSE by 5.5%. These results suggest that transfer learning may represent a new breakthrough in geostationary satellite image–based TC intensity estimation, for which continuous long-term data are not always available

Epigallocatechin-3-gallate protects toluene diisocyanate-induced airway inflammation in a murine model of asthma

AbstractEpigallocatechin-3-gallate (EGCG), a major form of tea catechin, has anti-allergic properties. To elucidate the anti-allergic mechanisms of EGCG, we investigated its regulation of matrix metalloproteinase (MMP-9) expression in toluene diisocyanate (TDI)-inhalation lung tissues as well as TNF-α and Th2 cytokine (IL-5) production in BAL fluid. Compared with untreated asthmatic mice those administrated with EGCG had significantly reduced asthmatic reaction. Also, increased reactive oxygen species (ROS) generation by TDI inhalation was diminished by administration of EGCG in BAL fluid. These results suggest that EGCG regulates inflammatory cell migration possibly by suppressing MMP-9 production and ROS generation, and indicate that EGCG may be useful as an adjuvant therapy for bronchial asthma

In Utero Development of the Fetal Gall Bladder in the Korean Population

OBJECTIVE: To provide reference ranges of the fetal gall bladder in the Korean population. MATERIALS AND METHODS: Fetal gall bladder development was evaluated in well-dated, non-anomalous fetuses in the Korean population between February and April 2003 and the visualization rate and reference values were determined from the obtained data. RESULTS: The visualization rate of the fetal gall bladder increased as gestation advanced to a plateau above 90%, which was maintained between 16 and 34 weeks. The measured parameters from the fetal gall bladder had a significant positive relationship with gestational age (p = 0.000 for all cases), and the correlation of length and area with the gestational age (r = 0.741 and r = 0.690, respectively) was better than the correlation of width, height, and volume with gestational age. The repeatability coefficients and coefficients of variation between the two operators were 5.56 mm and 12.9% for the length and 344.11 mm(2) and 33.52% for the area. The median length of the fetal gall bladder in the Korean population was not significantly different from the mean length of gall bladders in the Caucasian and African-American populations (p = 0.915). CONCLUSION: We have provided reference values for the fetal gall bladder throughout the gestation period in the Korean population