Search Results (1,137)

In the Atlantic Ocean, the Intertropical Convergence Zone (ITCZ) sustains the climate of northeastern Brazil and northwestern Africa by modulating their rainy and dry seasons. Using observational data, radiosondes and Expendable Bathythermographs (XBTs), we investigated short-term ocean–atmosphere coupling across the ITCZ region along the 38° W meridian. The data represents synchronous measurements of the marine atmospheric boundary layer (MABL) and the ocean’s mixed layer (OML) for the period between 17 October and 8 November 2018. The ITCZ demonstrated pronounced variability in position, intensity, and width, driven by the changes in the predominance of northeast and southeast trade winds. These atmospheric changes directly impacted the Equatorial Divergence (ED), which transitioned from an asymmetric structure with shallower isothermal layer depths (ILDs) (~−14 m) around 11° N to a more homogenous region between 5° N and 10° N, with an average ILD of −21.83 ± 5.23 m. A comparison with ORAS5 and WOA23 indicates that the products reproduce the vertical thermal structure of the WTAO well (r² > 0.9) but systematically overestimate the temperature at the bottom of the ILD by 3–4 °C. The difference between the ILD and the mixed layer depth (MLD) is more pronounced south of the ED due to the Amazon River salinity front, advected by the NECC, but the ILD estimated from XBT data closely matches the MLD estimated for ORAS5 and WOA23 in the ED region. These unprecedented observations showcase, for the first time, short-term ocean–atmosphere coupled variability across the WTAO ITCZ region, highlighting the importance of atmospheric synoptic-scale processes in modulating the OML and the ED. Full article

Tropical cyclones typically weaken rapidly during poleward propagation due to decreasing sea surface temperatures and increasing vertical wind shear. Super Typhoon Oscar (1995) deviated from this pattern by maintaining Category-5 intensity at an anomalously high latitude. This study investigates the oceanic mechanisms driving this resilience by integrating satellite SST data with atmospheric (ERA5) and oceanic (HYCOM) reanalysis products. Our analysis shows that the storm track intersected a persistent marine heatwave (MHW) characterized by a deep thermal anomaly extending to approximately 150 m. This elevated heat content formed a strong stratification barrier at the base of the mixed layer (~32 m) that prevented the typical entrainment of cold thermocline water. Instead, storm-induced turbulence mixed warm subsurface water upward to effectively mitigate the negative cold-wake feedback. This process sustained extreme upward enthalpy fluxes exceeding 210 W m⁻² and generated a regime of thermodynamic compensation that enabled the storm to maintain its structure despite an unfavorable atmospheric environment with moderate-to-strong vertical wind shear (15–20 m s⁻¹). These results indicate that the three-dimensional ocean structure acts as a more reliable predictor of typhoon intensity than SST alone in regions affected by MHWs. As MHWs deepen under climate warming, this cold-wake mitigation mechanism is likely to become a significant factor influencing future high-latitude cyclone hazards. Full article

Peatlands play a critical role in global and regional climate regulation by functioning as long-term carbon sinks, regulating hydrology, and modulating land–atmosphere energy exchange. Intact peat ecosystems store large amounts of organic carbon and stabilize local climate through high water retention and evapotranspiration, whereas peatland degradation disrupts these functions and can transform peatlands into significant sources of greenhouse gas emissions and climate extremes such as drought and fire. Indonesia contains approximately 13.6–40.5 Gt of carbon, around 40% of which is stored on the island of Sumatra. However, tropical peatlands in this region are highly vulnerable to climate anomalies and land-use change. This study investigates the impacts of major climate anomalies—specifically El Niño and positive Indian Ocean Dipole (pIOD) events in 1997/1998, 2015/2016, and 2019—on peatland cover change across South Sumatra, Jambi, Riau, and the Riau Islands. Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager/Thermal Infrared Sensor imagery were analyzed using a Random Forest machine learning classification approach. Climate anomaly periods were identified using El Niño-Southern Oscillation (ENSO) and IOD indices from the National Oceanic and Atmospheric Administration. To enhance classification accuracy and detect vegetation and hydrological stress, spectral indices including the Normalized Difference Vegetation Index (NDVI), Modified Soil Adjusted Vegetation Index (MSAVI), Normalized Difference Water Index (NDWI), and Normalized Difference Drought Index (NDDI) were integrated. The results show classification accuracies of 89–92%, with kappa values of 0.85–0.90. The 2015/2016 El Niño caused the most severe peatland degradation (>51%), followed by the 1997/1998 El Niño (23–38%), while impacts from the 2019 pIOD were comparatively limited. These findings emphasize the importance of peatlands in climate regulation and highlight the need for climate-informed monitoring and management strategies to mitigate peatland degradation and associated climate risks. Full article

This study aims to investigate the effects of Chan-Hom (2015) typhoon-induced variations in enthalpy flux (EF) and moisture flux (MF) on intensity variations and rainfall. Chan-Hom (2015) made landfall at Zhoushan, then changed its direction and moved towards Korea. This analysis used ERA5 reanalyzed data, encompassing daily surface latent and sensible heat flux, along with wind measurements at a height of 10 m. Furthermore, wind components and specific humidity data from the 1000–200 hPa level in ERA5 were utilized to compute the MF and MF convergence, in accordance with the equations outlined in the methodology. This study examines the correlation among typhoon intensity, precipitation, MF, and EF. The mechanism by which Typhoon Chan-Hom has caused a decline in sea surface temperature (SST) was analyzed. Typhoons need a higher EF that can affect them before landfall to maintain their intensity. The highest LHF was observed (340 W/m²) prior to typhoon landfall, indicating that LHF responds to intensity-induced wind during Chan-Hom. Typhoon-induced rainfall is mainly controlled by the MF convergence, rather than the typhoon intensity. The spatial and temporal distributions of MF and MF convergence (MFC) during typhoon formation to landfall reveal that the symmetric MFC is dominated by typhoon intensity; a symmetrical structure is observed when the intensity is high. MFC includes wind convergence and moisture advection. Wind convergence dominates the MFC during typhoons, but moisture advection forms at the eyewall. MF during the typhoon’s landfall can relate to the amount of rainfall that occurred over the land. However, the rainfall pattern changed after landfall, and the typhoon changed its direction. SST cooling observed in the study area is mainly due to the upwelling process with strong cyclonic winds. Full article

The Indian monsoon is an important component of the tropical climate system. Studies suggest that both precipitation from the NNU-2K AF experiments and Little Ice Age (LIA) proxy data reveal a significant 56-year period in the Indian summer monsoon (ISM). Volcanic activity influences the multi-year and decadal characteristics of Indian monsoon precipitation. A comparative analysis of multi-decadal variations in ISM precipitation from the AF experiments and the single-factor sensitivity experiments shows a correlation of 0.45 (p < 0.05), indicating dependence on volcanic activity. The 56-year period of ISM precipitation in the AF experiments is consistent with both the single-factor sensitivity experiments and precipitation influenced by volcanic activity. Further analysis reveals that cooling over Eurasia and warming of the Indian Ocean weaken the thermal contrast between land and sea, thereby reducing ISM intensity and decreasing ISM precipitation. Conversely, enhanced volcanic activity induces widespread cooling across the Northern Hemisphere, which shifts the Intertropical Convergence Zone (ITCZ) southward. This reduction in evaporative capacity and moisture content within the monsoon region ultimately decreases precipitation across the monsoon belt. Full article

The background error covariance matrix (BE) is a fundamental component of data assimilation (DA) systems. Its impact on both the DA process and subsequent forecast performance depends on model configuration and the types of observations assimilated. However, few studies have specifically examined BE behavior in the context of satellite DA for regional tropical cyclone (TC) prediction. In this study, we develop the BE and evaluate its structure for a TC forecasting system over the western North Pacific. A total of six BEs are modeled using three control variable (CV) schemes (aligned with the CV5, CV6, and CV7 options available in the Weather Research and Forecasting DA system (WRFDA)) with training data from two distinct periods: the TC season and the winter season. Results demonstrate that the BE structure is sensitive to the training data used. The performance of TC-season BEs derived from different CV schemes is assessed for TC track forecasting through the assimilation of microwave sounder satellite brightness temperature data. The evaluation is based on a set of 14 cases from 2018 that exhibited large official track forecast errors. The CV7 BE, which uses the x- and y-direction wind components as CVs, captures finer small-scale momentum error features and yields greater forecast improvement at shorter lead-times (24 h). In contrast, the CV6 BE, which employs stream function (ψ) and unbalanced velocity potential (χ_u) as CVs, incorporates more large-scale momentum error information. The inherent multivariate couplings among analysis variables in this scheme also allow for closer fits to satellite microwave brightness temperature data, which is particularly crucial for forecasting TCs that primarily develop over oceans where conventional observations are scarce. Consequently, it enhances the large-scale environmental field more effectively and delivers superior forecast skill at longer lead times (48 h and 72 h). Full article

This study addresses the issues of sparse observations from buoys in the tropical Indian Ocean and systematic biases in reanalysis products by proposing a daily-mean wind speed reconstruction framework that integrates multi-source meteorological fields. This study also considers the impact of different source domains on model pre-training, with the goal of providing reliable data support for wind energy assessment. The model was pre-trained using data from the Americas and tropical Pacific buoys as the source domain and then fine-tuned on Indian Ocean buoys as the target domain. Using annual leave-one-out cross-validation, we evaluated the model’s performance against uncorrected ERA5 and CCMP data while comparing three deep reconstruction models. The results demonstrate that deep models significantly reduce reanalysis bias: the RMSE decreases from approximately 1.00 m/s to 0.88 m/s, while R² improves by approximately 8.9% and 7.1% compared to ERA5/CCMP, respectively. The Branch CNN–Transformer outperforms standalone LSTM or CNN models in overall accuracy and interpretability, with transfer learning yielding directional gains for specific wind conditions in complex topography and monsoon zones. The 20-year wind energy data reconstructed using this model indicates wind energy densities 60–150 W/m² higher than in the reanalysis data in open high-wind zones such as the southern Arabian Sea and the Somali coast. This study not only provides a pathway for constructing high-precision wind speed databases for tropical Indian Ocean wind resource assessment but also offers precise quantitative support for delineating priority development zones for offshore wind farms and mitigating near-shore engineering risks. Full article

Ocean winds and waves play a vital role in maritime navigation safety, offshore operations, and coastal zone dynamics. Although both factors have been widely studied individually, the joint characterization of wind and wave events remains limited in the North Indian Ocean. This study, utilizing ERA5 reanalysis data from 1980 to 2022, statistically analyzed the distribution and variation patterns of both wind speed and significant wave height, investigating the occurrence, affected area proportion, frequency, and intensity of SBLWEs. To understand the cause of Strong Breeze and Large Wave Events (SBLWEs), their connections with other phenomena, such as tropical cyclones, were also explored. The results show that regions with strong breezes and large waves are mainly concentrated in the central and western Arabian Sea near Africa and the central and western Bay of Bengal. Monthly averages indicate that wind and wave intensity are much higher during the summer monsoon than in other seasons, with high intensity, probability, and extensive affected areas of SBLWEs. The occurrence probability of SBLWEs is highest in the central and western Arabian Sea (up to ~40%), and the highest probability in the Bay of Bengal is about 20% near the eastern coast of Sri Lanka. The peak period of SBLWEs occurs from June to August, with the largest affected area in July, reaching almost 25%. Over the past 40 years, the number of SBLWEs has shown an increasing trend, with an average of 0.7 events annually. The intensity distribution of SBLWEs resembles that of wind speed and wave height, with the highest intensity areas concentrated in the Bay of Bengal, affected by tropical cyclones. This study can serve as a scientific reference for maritime route planning and offshore operations, helping to reduce the negative impacts of large wind and wave events and enhance navigation safety. Full article

This paper discusses the assimilation of significant wave height (Hs) observations from the China France Oceanography SATellite (CFOSAT) into the Global Deterministic Wave Prediction System developed by Environment and Climate Change Canada. We focus on the quantification of background errors in an effort to address the conventional, simplified, homogeneous assumptions made in previous studies using Optimal Interpolation (OI) to generate Hs analysis. A map of Best Correlation Length, L, is generated to count for the inhomogeneity in the wave field. This map was calculated from pairs of Hs forecasts of two grid points shifted in space and time from which a look-up table is derived and used to infer the spatial extent of correlations within the wave field. The wave spectra are then updated from Hs analysis using a frequency shift scheme. Results reveal significant spatial variance in the distribution of L, with notably high values located in the eastern tropical Pacific Ocean, a pattern that is expected due to the persistent swells dominating in this region. Experiments are conducted with spatially varying correlation lengths and a set correlation length of eight grid points in the analysis step. Forecasts from these analyses are validated independently with the Global Telecommunications System buoys and the Copernicus Marine Environment Monitoring Service (CMEMS) altimetry wave height observations. It is found that the proposed statistical method generally outperforms the conventional method with lower standard deviation and bias for both Hs and peak period forecasts. The conventional method has more drastic corrections on Hs forecasts, but such corrections are not robust, particularly in regions with relatively short spatial correlation length scales. Based on the analysis of the CMEMS comparison, the globally varying correlation length produces a positive increment of the Hs forecast, which is globally associated with forecast error reduction lasting up to 24 h into the forecast. Full article

In the effort to mitigate climate change, the Marine Hydrokinetic (MHK) energy from ocean currents emerges as an important renewable source due to its large potential, although it remains underexploited. In the Southwestern Tropical Atlantic, surface potentials linked to the North Brazil Current (NBC) are known, but the subsurface North Brazil Undercurrent (NBUC) remained unquantified. This study addressed this gap by applying a two-step approach using more than 20 years of high-resolution (1/12°) climatological and daily reanalysis data to estimate current power density (CPD) throughout the water column along the Brazilian shelf (4° N–12° S), with focus on energetic hotspots where maximum CPD exceeds 1000 W m⁻². The climatological analysis revealed 12 persistent hotspots (H1–H12). Daily analyses show highly energetic but seasonally variable surface hotspots north of 4° S linked to the NBC (H4–H12; >885 W·m⁻²) and weaker but more stable subsurface hotspots south of 4° S associated with the NBUC at depths of 130–266 m (H1–H3; 831–808 W·m⁻²). These patterns are likely influenced by flow–topography interactions along the continental margin. Overall, subsurface resources exhibit greater reliability than surface counterparts, highlighting the importance of incorporating subsurface dynamics in future MHK assessments and development along the Brazilian margin. Full article

With global warming, tropical islands, as sensitive areas to climate change, exhibit new and significant temperature variation characteristics. Using the high-resolution Hainan Island Regional Reanalysis (HNR) dataset and multi-source data, this study analyzes temperature changes on Hainan Island from 1900 to 2022, focusing on spatiotemporal trends, diurnal patterns, and probability distribution shifts. The findings reveal significant periodic temperature changes: weak warming (0.02–0.08 °C/decade) from 1900 to 1949, a temperature hiatus from 1950 to 1979, and accelerated warming (0.14–0.28 °C/decade) from 1979 to 2022. Coastal plains (0.11 °C/decade) warm faster than inland mountains (0.08 °C/decade), reflecting oceanic and topographic effects. Diurnal temperature variations show topographic dependence, with a maximum range (8–9 °C) in the north during the warm season, and a southwest–northeast gradient in the cold season. Probability density function analysis indicates that the curves for transitional and cold seasons show a noticeable widening and rightward shift, reflecting the increasing frequency of extreme temperature events under the trend of temperature rise. The study also finds that the occurrence time of daily maximum temperature over coastal plains is advancing (−0.05 to −0.1 h/decade). This study fills gaps in understanding tropical island climate responses under global warming and provides new insights into temperature changes over Hainan Island. Full article

Many tropical islands and coastal communities suffer from high energy costs, unreliable electrical supplies, poverty, and underemployment, which are all exacerbated by climate change. Multi-use Ocean Thermal Energy Conversion (OTEC) systems could align with the goals and values of these underserved and remote communities. Developing multi-use OTEC systems could help meet the United Nations’ Sustainable Development Goals #7 (Affordable and Clean Energy) and #13 (Climate Action). Multiple uses of OTEC water and power are explored in this study, including seawater air conditioning, desalination, support for aquaculture in tropical regions, and other uses. A use case for an onshore OTEC plant at the location of the existing OTEC plant in Kona, Hawaii, is examined to determine if sufficient thermal resources exist for OTEC power generation year-round, and to determine the potential for each value-added use. Potential environmental effects are evaluated using a new open-source numerical model for determining the risk from the discharge of large volumes of cold deep seawater in the ocean. Companies currently using the cold deep seawater pumped ashore at the Kona location were surveyed to determine their dependence on and interest in expanded OTEC and cold-water availability at the site. The analysis indicates that multi-use OTEC is feasible, with seawater air conditioning (SWAC), aquaculture, and desalination being the most compatible immediate additions, while future potential exists for adding extraction of critical minerals from seawater and e-fuel generation. Full article

This study has developed a unified framework for modeling economic growth through Caputo fractional differential equations. The framework has established the existence and uniqueness of solutions by employing a generalized fixed-point approach. In particular, the analysis has introduced and utilized new classes of symmetric operators, including symmetric Lipschitz-type mappings, symmetric Kannan-type contractions, and symmetric Chatterjea-type contractions. These mappings are based on a refined symmetric Lipschitz condition that enables the examination of the behavior of their iterative sequences. The study has focused on several forms of symmetric contractions defined on metric spaces endowed with a binary relation, providing a setting that generalizes and unifies various existing fixed-point theorems. This framework has extended classical results by Goebel and Sims, Goebel and Japon-Pineda, and others. Finally, to illustrate the practical significance of the theoretical findings, the developed results have been applied to demonstrate the existence of solutions for fractional models of economic growth and a related Fredholm integral equation. Full article

Benthic δ¹⁸O and δ¹³C values, as well as the mean grain size (MS) of sortable silt (SS), were used to construct the records of deep-water ventilation during the last 300 ka, at core GC02. This core is located at 4430 m water depth on the Madagascar basin near the Southwest Indian Ocean mid-ridge (SWIR). Decreased values of MS of SS reveal a weakened Antarctic Bottom Water (AABW) in the glacial periods, while increased values indicate enhanced AABW in the interglacial periods. The MS of SS record in GC02 exhibited a particularly good synchronization with a record based on the δ¹³C gradient between the North Atlantic and tropical Pacific Ocean, indicating that AABW is dominated by the overturning strength of the Atlantic meridional overturning circulation (AMOC), and showed a higher generation rate in the early stages of the glacial periods. A rapid reduction in δ¹³C occurred in MIS 2, 4, and 6; the MS values in GC02 and winter sea ice (WSI) also exhibited significant decreases and increases, respectively. By controlling the transport of ventilated water mass to deep waters and polar heat transport, in the Indian Ocean, both the change in AABW intensity and the Southern Ocean ice volume result from changes in the AMOC under the orbital modulation background. In the Southwest Indian Ocean, AMOC has a larger effect on ice volume during glacial periods, while its effect on AABW is relatively strong during interglacial periods. Full article

Background: Although tone acquisition is one of the most challenging aspects for adult second language (L2) learners, research remains limited on how learners from non-tonal first language (L1) backgrounds develop across proficiency levels. The current study examined Mandarin disyllabic tone sequences produced by learners at three proficiency levels. Methods: This study recorded the Mandarin tone production of beginner, intermediate, and advanced Korean learners and evaluated their accuracy and error patterns to determine whether similarities between L1 and L2 prosodic systems affect tone sequence difficulty. Results: Across groups, tone sequence rankings were consistent, differing mainly in accuracy rates. Learners showed an advantage in producing sequences aligned with Korean tonal patterns, such as T1–T1 and T3–T1, which were the easiest to produce. In contrast, sequences without Korean counterparts, particularly those ending in T2, remained the most difficult at all proficiency levels. Conclusions: Neurolinguistic evidence suggests that tones lacking L1 motor representations are disadvantaged by limited motor templates and weaker auditory coding, which together account for persistent difficulty with T2 sequences. Interestingly, T2 in word-initial position improved with experience, as increased exposure and practice helped learners form new sensorimotor routines supported by strengthened auditory–motor coupling. Over time, such experience-dependent neural reorganization enables more precise execution of rising F0 movements when tones occur at the beginning of a sequence, whereas carry-over interference from preceding tones continues to hinder accuracy in word-final position. This study provides insight into how sensorimotor and auditory systems interact in L2 tone learning, offering a neurocognitive framework for understanding prosodic transfer. Full article