Search Results (32)

In recent years, China has experienced growing impacts from extreme weather events, emphasizing the importance of understanding regional atmospheric moisture dynamics, particularly Precipitable Water Vapor (PWV), to support sustainable environmental and urban planning. This study utilizes ten years (2013–2022) of Global Navigation Satellite System (GNSS) observations in typical cities in eastern China and proposes a comprehensive multiscale frequency-domain analysis framework that integrates the Fourier transform, Bayesian spectral estimation, and wavelet decomposition to extract the dominant PWV periodicities. Time-series analysis reveals an overall increasing trend in PWV across most regions, with notably declining trends in Beijing, Wuhan, and southern Taiwan, primarily attributed to groundwater depletion, rapid urban expansion, and ENSO-related anomalies, respectively. Frequency-domain results indicate distinct latitudinal and coastal–inland differences in the PWV periodicities. Inland stations (Beijing, Changchun, and Wuhan) display annual signals alongside weaker semi-annual components, while coastal stations (Shanghai, Kinmen County, Hong Kong, and Taiwan) mainly exhibit annual cycles. High-latitude stations show stronger seasonal and monthly fluctuations, mid-latitude stations present moderate-scale changes, and low-latitude regions display more diverse medium- and short-term fluctuations. In the short-term frequency domain, GNSS stations in most regions demonstrate significant PWV periodic variations over 0.5 days, 1 day, or both timescales, except for Changchun, where weak diurnal patterns are attributed to local topography and reduced solar radiation. Furthermore, ERA5-derived vertical temperature profiles are incorporated to reveal the thermodynamic mechanisms driving these variations, underscoring region-specific controls on surface evaporation and atmospheric moisture capacity. These findings offer novel insights into how human-induced environmental changes modulate the behavior of atmospheric water vapor. Full article

For coastal nations and regions, wave energy provides a localized energy solution, decreasing dependency on external energy sources and fostering the sustainable development of local economies. Effective wave height occurrence (EWHO) represents the availability of wave energy and is a crucial parameter for site selection for optimal wave energy. This paper systematically analyzes the distribution of EWHO in China seas areas using significant wave height (SWH) data in the fifth generation of ECMWF atmospheric reanalysis (ERA5) and key climate indices. Employing methods such as climate statistical analysis, linear regression, significance testing, and trend analysis, the study highlights the temporal and spatial distribution characteristics, variation trends, and correlations with climate indices of EWHO. This research aims to provide technical assistance and decision support for the development of wave energy at sea. The results indicate the following conclusions: (1) The high EWHO in the China seas is predominantly located in northern Nanhai, southern Donghai, and the eastern waters of the Philippine Islands. The EWHO is highest in winter. (2) The growth trend of EWHO is most notable in the sea area east of the line connecting the Ryukyu Islands, Taiwan, and the northeastern Philippines, peaking in spring and being relatively weak in winter. (3) The correlation between NINO3 and EWHO is most significant in Nanhai and the northeastern waters of the Philippines, peaking in February with correlation coefficients ranging from −0.30 to −0.50. Full article

The relationship between wind and waves has been extensively studied over time. However, understanding the local wind and wave relationship remains crucial for advancing renewable energy development and optimizing ocean management strategies. This study used wind and wave data collected by the ten weather buoys in the waters surrounding Taiwan to analyze regional sea states. The relationship between wind speed and significant wave height (SWH) was examined using regression analysis. Additionally, machine learning techniques were employed to assess the relative importance of features contributing to SWH growth. The regression analysis revealed that SWH in the waters surrounding Taiwan was not fully developed, with notable discrepancies observed between the waters east and west of Taiwan. According to the power law formula describing the relationship between wind speed and SWH, the eastern waters exhibited a larger prefactor coupled with a smaller scaling exponent, while the western waters manifested a converse parametric configuration. Through an evaluation of four machine learning algorithms, it was determined that wind speed is the most influential factor driving these regional differences, especially in the waters west of Taiwan. Beyond wind speed, air pressure or temperature emerged as the secondary feature factor governing wind–wave interactions in the waters east of Taiwan. Full article

Extreme weather events from climate change challenge infrastructure stability. While water-related engineering enhances disaster resilience, it also impacts ecosystems. Taiwan has implemented Ecological Check and Identification (ECI) since 2003, yet challenges remain in standards, resource allocation, and effectiveness. This study analyzes 35 coastal engineering cases and participated in two engineering projects from five key perspectives. The results show that there are regional differences in the types of projects implemented for ECI. Landscape engineering was the main type in northern Taiwan (31%), water resource engineering was the main type in southern Taiwan (43%), and no cases were found in eastern Taiwan. Most inspections occur in the proposal (24%), planning (22%), and design (22%) stages, with limited post-construction monitoring (14%). Furthermore, ecological assessments were lacking in 49% of cases, and aquatic ecosystems were underrepresented. Inconsistent inspection formats and low species documentation (57% of cases) reduce data comparability and conservation effectiveness. To address these gaps, some recommendations were made, including standardizing inspections, integrating Sustainable Development Goals (SDGs), promoting low-carbon approaches, strengthening public participation, and establishing long-term monitoring. The findings provide policy insights to enhance ECI, supporting sustainable coastal engineering while balancing infrastructure benefits and environmental conservation. Full article

Alterations in reference evapotranspiration (ET₀) and precipitation (PP) resulting from global warming substantially affect water resources and agriculture. This study analyzed trends in ET₀, PP, and key climate variables—including air temperature (T), vapor pressure deficit (VPD), wind speed, and solar radiation (R_s)—across Taiwan from 1995 to 2022. Trends were assessed using the modified Mann–Kendall test and the multivariate Man–Kendall test at both station-wise and multi-station scales. Results indicated that ET₀ was primarily influenced by R_s, followed by T, wind speed, and VPD. Station-wise analysis revealed increasing trends in annual and seasonal T, R_s, and ET₀, while over 50% of wind speed series showed significant declines. Multi-station analysis confirmed an overall rise in ET₀. In eastern Taiwan, rising T and declining VPD and wind speed may increase the risk of pest and disease outbreaks. The arid index exhibited a general downward trend, particularly in summer, with 75% of the stations in eastern Taiwan exhibiting significant declines, suggesting a shift toward drier conditions. These findings imply that fewer crop options may be suitable for cultivation in eastern Taiwan due to water resource constraints. Additionally, seasonal and annual PP showed slight decreases, with a more uneven distribution observed in central Taiwan. Therefore, improving hydraulic facilities and irrigation systems will become important. Furthermore, comparisons between the multivariate Mann–Kendall test and the traditional univariate approach revealed some different results, indicating the need for further research to identify a more reliable approach. Full article

This study proposes a deep neural network (DNN) as a downscaling framework with nonlinear features extracted by kernel principal component analysis (KPCA). KPCA utilizes kernel functions to extract nonlinear features from the source climatic data, reducing dimensionality and denoising. DNN is used to learn the nonlinear and complex relationships among the features extracted by KPCA to predict future regional rainfall patterns and trends in complex island terrain in Taiwan. This study takes Taichung and Hualien, on both the eastern and western sides of Taiwan’s Central Mountain Range, as examples to investigate the future rainfall trends and corresponding uncertainties, providing a reference for water resource management and usage. Since the Water Resources Agency (WRA) of the Ministry of Economic Affairs of Taiwan currently recommends the CMIP5 (AR5) GCM models for Taiwan regional climate assessments, the different emission scenarios (RCP 4.5, RCP 8.5) data simulated by two AR5 GCMs, ACCESS and CSMK3, of the IPCC, and monthly rainfall data of case regions from January 1950 to December 2005 in the Central Weather Administration (CWA) in Taiwan are employed. DNN model parameters are optimized based on historical scenarios to estimate the trends and uncertainties of future monthly rainfall in the case regions. The simulated results show that the probability of rainfall increase will improve in the dry season and will reduce in the wet season in the mid-term to long-term. The future wet season rainfall in Hualien has the highest variability. It ranges from 201 mm to 300 mm, with representative concentration pathways RCP 4.5 much higher than RCP 8.5. The median percentage increase and decrease in RCP 8.5 are higher than in RCP 4.5. This indicates that RCP 8.5 has a greater impact on future monthly rainfall. Full article

The Japanese eel (Anguilla japonica) is the most prevalent freshwater eel species in Taiwan. However, its population has undergone a significant decline in recent decades due to factors such as overfishing, habitat destruction, and the effects of climate change. Urgent action is needed to conserve this species. Before implementing conservation measures, it is imperative to ascertain the distribution of Japanese eels in Taiwan’s rivers. This study’s primary objective was to assess the effectiveness of eDNA analysis as a method for detecting Japanese eels. To achieve this goal, we compared eDNA analysis data with results obtained from electrofishing, with the Fengshan and Shimen Rivers serving as our designated test sites. Additionally, we collected water samples from 34 other rivers across Taiwan to comprehensively assess the species’ wider distribution using eDNA analysis. Our findings demonstrated eDNA analysis’s viability for detecting Japanese eels. Of the 36 rivers tested, Japanese eel DNA was detected in samples from 21 rivers, scattered across northern, eastern, southern, and western Taiwan, with no specific concentration in any region. We also noted reduced detectability of Japanese eel DNA in highly polluted rivers, indicating that river pollution may have a potential impact on their population. In the future, expanding eDNA analysis to more rivers could identify additional rivers that Japanese eels inhabit. Subsequently, resource management and conservation efforts can be focused on these identified habitats. Furthermore, developing advanced eDNA-based methods for estimating the abundance or biomass of Japanese eels could enhance the flexibility of management and conservation measures. Full article

This study investigated microplastic distribution characteristics by collecting surface seawater from sea areas to the south of Jeju Island in August 2020. The average microplastic abundance was 0.46 ± 0.27 particles/L (n = 23), and PE had a high ratio, averaging 53%. The levels of fragments and fibers were observed to be 69% and 31% on average, respectively. The most common size of the microplastics was on average 0.02–0.30 mm at a level of 69%. We found a higher abundance of microplastics in the study area than in other open waters such as the Arctic Central Basin and the Atlantic Ocean, whereas the abundance was lower than that in previous studies on coastal areas. We studied an area of open sea connecting China, Japan, and the Pacific Ocean, and, in this region, the microplastic distribution varies depending on sea currents in the surrounding areas. In the summer, the western and central regions of the study sea area have low salinity levels due to discharge from China’s Yangtze River. This generally indicates that high-density plastic deposits are found in the Yangtze River estuary, and low-density plastics are found in the study area. Furthermore, this implies that low- and high-density plastics are transported in water for long periods of time due to the Taiwan Warm Current and because the eastern sea area has high salinity. Full article

Three typhoons, Meranti, Malakas, and Megi, occurred successively in eastern Taiwanese waters in September 2016, causing extreme waves (significant wave height > 10.0 m), and these events were selected to investigate the effect of model grid resolution and wave–wave interaction on simulating typhoon-driven waves. The WAVEWATCH III (WW3) model, with 0.50 deg, 0.25 deg, 0.20 deg, 0.10 deg, and 0.05 deg grid resolutions, and two reanalysis wind fields were adopted to simulate ocean waves during these three typhoons. The results indicated that the exertion of the Climate Forecast System version 2 (CFSv2) winds over the WW3 model with 0.10 deg grid resolution yielded optimum simulations of typhoon waves in a compromise between accuracy and elapsed time. In the present study, the WW3 model modeled nonlinear wave–wave interactions using discrete interaction approximation (DIA). The numerical experiments revealed that the underestimations of typhoon waves were significant when the WW3 model excluded nonlinear wave–wave interactions, especially when employing a higher grid resolution. This study also found that the WW3 model is superior to the Wind Wave Model III (WWM-III) using the CFSv2 winds because the WWM-III tended to overestimate the extreme waves in all three of these eastern Taiwan typhoon events that occurred in September 2016. Full article

A fully coupled tide-surge-wave model was developed to study the influence of different computational domains on typhoon wave characteristics in the waters surrounding Taiwan. Three typhoons were selected as study cases: Meranti, Malakas, and Megi, which successively impacted Taiwan in September 2016. Superposition of the CFSV2 winds blended with ERA5 winds onto the tide-surge-wave model yielded optimum simulations of typhoon waves. Storm wave responses along the eastern shelf of Taiwan resulting from three typhoons were examined in four model domains. The first domain (D01) was primarily situated in the region where giant waves were generated. The second domain (D02) covered an area extending from 114° E to 130° E and 19° N to 29° N. The third domain (D03) southwardly included the entire Bashi Channel, from longitudes of 111° E to 135° E and latitudes of 18° N to 30° N. The fourth domain (D04) was the largest among the four computational domains; it extended from longitudes of 105° E to 140° E and latitudes of 15° N to 31° N. The simulated sea state responses indicated that the smaller computational domains were inadequate for typhoon-driven storm wave computation purposes, although the areas of D01 and D02 reached approximately 0.75 and 1.38 million km², respectively, encompassing all of Taiwan Island and adjacent waters. Our results suggest that utilizing at least D03 or a larger model domain (e.g., D04) is essential to account for the remote wind effect of typhoons on wave simulations in Taiwanese waters. Full article

We explored the driving factors of nonlinear signals in vertical coordinate sequences of stations in a Taiwan global navigation satellite system (GNSS) network, including atmospheric loading (ATML), hydrological loading (HYDL), and non-tidal ocean loading (NTOL) effects. At the same time, we used the finite element analysis software MIDAS to quantify the vertical displacements of different types of monuments due to the thermal expansion effect, including deep drilled braced (DDB) and short drilled braced (SDB). By quantitatively comparing the correction results of GNSS time series with different single mass loading models, we found that there was little difference in the correction of different environmental loading products. We compared different combinations of each loading product to correct the GNSS time series, and finally selected the best combination suitable for Taiwan GNSS network, that is, ATML (GFZ_ECMWF IB) + HYDL (IMLS_MERRA2) + NTOL (IMLS_MPIOM06). We found that the spatial and temporal models of ATML and NTOL are very similar, with non-tidal atmospheric loading and non-tidal ocean loading working together, a pattern that may be related to tropical cyclones. Both models also showed good correction effect on GNSS stations in the western plain of Taiwan, but with limited correction effect in the eastern part of Taiwan. This may be due to the influence of the subtropical monsoon climate in Taiwan and the barrier of the central mountain range, resulting in obvious differences between eastern and western Taiwan. The hydrological loading was found to act in the opposite way to the thermal expansion effect in the temporal domain, indicating that some displacements in hydrological loading may cancel out displacements caused by the thermal expansion effect. This aspect of displacement is not included in the hydrological loading model but should be considered when accurately estimating the temporal and spatial variation of water storage capacity in Taiwan using GNSS observed displacements. Full article

The Shantou-Taiwan shoal fishing ground in southeastern China supports a significant population of pelagic fish, which play a key role in the marine ecosystem. An acoustic survey was carried out using a digital scientific echosounder in June 2019. In this paper, the spatial distribution of pelagic fish is analyzed based on acoustic data using geostatistical analysis tools. Meanwhile, the relationship between fish density from acoustic data and sea surface environment factors were evaluated by using generalized additive models (GAMs) based on the satellite-based oceanographic data of sea surface temperature, sea surface chlorophyll-a concentration, sea surface height and sea surface wind. The results showed the following: (1) Fish density and acoustic biomass have strong spatial correlation; the optimal model for acoustic biomass is exponential and the optimal model for fish density is gaussian; based on optimal model, spatial interpolation analysis of fish density and acoustic biomass was performed using the ordinary kriging method, and the higher values of density and acoustic biomass were located in the central and eastern parts of the study area. The total fish density and acoustic biomass is 2.56 × 10¹⁰ ind. and 1908.99 m²/m, respectively. (2) In vertical distribution, fish gradually move to the middle and lower layers of water during daytime, and gather in the middle and upper layers of water at night. (3) The variance explanation rate of GAM was 88.2% which indicates that the model has an excellent fitting degree, and the results of GAM showed that longitude, sea surface temperature (SST), sea surface wind (SSW), and sea surface height (SSH) had significant effects on fish density. Results of this study were meaningful for understanding the distribution of fishery resources, and as a guide for fish management in the Shantou offshore water. Full article

Connectivity in deep-sea organisms must be considered across both depth gradient and horizontal geographical scales. The depth-differentiation hypothesis suggests that strong environmental gradients (e.g., light, temperature, pressure) and habitat heterogeneity in the deep-sea can create selection pressure, and this can result in genetic population divergence. The hydrothermal vent crab Xenograpsus testudinatus (Xenograpsidae) is common in vents at Kueishan Island, Taiwan, ranging from 10 to about 300 m depths. Xenograpsus testudinatus has also been found in shallow water vents (3–20 m) at Kagoshima and the Izu archipelago of Japan. We examine the sequence divergences in the mitochondrial COI, 16S rRNA and D-loop genes, to test the hypothesis that there is significant genetic differentiation among populations of X. testudinatus along the depth gradient at Kueishan Island (30, 200, 209–224 and 250–275 m), and among different geographical regions (Kueishan, Kagoshima and the Izu archipelago) in the West Pacific. There is neither significant population differentiation among shallow or deep-sea vents, nor between geographical locations. Vertical migration of zoea, upwelling on the eastern coast of Taiwan and the strong effect of the Kuroshio Currents has probably resulted in a high level of planktonic larval dispersal of X. testudinatus along the depth and geographical gradients in the Western Pacific. Full article

The skipjack tuna (Katsuwonus pelamis) is a mesopredator fish species with seasonal abundance in waters off Taiwan. Regional ecological and life-history information has been historically lacking for this species. In recent years, stable isotope analysis (SIA) of carbon and nitrogen has been used to assess predator feeding ecology and broader ecosystem trophic dynamics. This study evaluated comparative skipjack feeding ecology in distinct regions off Taiwan, combining traditional stomach content analysis with SIA of individuals off western (n = 43; 2020) and eastern (n = 347; 2012–2014 and n = 167; 2020) Taiwan. The stomach content analysis showed the most important prey to be ponyfish (Photopectoralis bindus) in western Taiwan and epipelagic squids (Myopsina spp.) and carangids (Decapterus macrosoma;) in eastern Taiwan from 2012 to 2014 and epipelagic carangids (Decapterus spp.) and flying fishes (Cheilopogon spp.) in eastern Taiwan in 2020, suggesting that the skipjack tuna is a generalist predator across regions. In contrast, time-integrated diet estimates from Bayesian mixing models indicated the importance of cephalopods and crustaceans as prey, potentially demonstrating more mesopelagic feeding in less productive waters during skipjack migrations outside the study regions. Skipjack off western Taiwan had a slightly higher estimated trophic position than in the waters off eastern Taiwan, potentially driven by the varying nutrient-driven pelagic food web structures. Skipjack SI values increased with body size off eastern Taiwan but not in western waters, suggesting that opportunistic predation can still result in different predator–prey size dynamics between regions. Full article

In July 2021, Typhoon In-Fa attacked eastern China and broke many records for extreme precipitation over the last century. Such an unrivaled impact results from In-Fa’s slow moving speed and long residence time due to atmospheric circulations. With the supports of 66 networked surface disdrometers over eastern China and collaborative observations from the advanced GPM satellite, we are able to reveal the unique precipitation microphysical properties of the record-breaking Typhoon In-Fa (2021). After separating the typhoon precipitation into convective and stratiform types and comparing the drop size distribution (DSD) properties of Typhoon In-Fa with other typhoons from different climate regimes, it is found that typhoon precipitation shows significant internal differences as well as regional differences in terms of DSD-related parameters, such as mass-weighted mean diameter (D_m), normalized intercept parameter (N_w), radar reflectivity (Z), rain rate (R), and intercept, shape, and slope parameters (N₀, µ, Λ). Comparing different rain types inside Typhoon In-Fa, convective rain (N_w ranging from 3.80 to 3.96 mm⁻¹ m⁻³) shows higher raindrop concentration than stratiform rain (N_w ranging from 3.40 to 3.50 mm⁻¹ m⁻³) due to more graupels melting into liquid water while falling. Large raindrops occupy most of the region below the melting layer in convective rain due to a dominant coalescence process of small raindrops (featured by larger Z_Ku, D_m, and smaller N₀, µ, Λ), while small raindrops account for a considerable proportion in stratiform rain, reflecting a significant collisional breakup process of large raindrops (featured by smaller Z_Ku, D_m, and larger N₀, µ, Λ). Compared with other typhoons in Hainan and Taiwan, the convective precipitation of Typhoon In-Fa shows a larger (smaller) raindrop concentration than that of Taiwan (Hainan), while smaller raindrop diameter than both Hainan and Taiwan. Moreover, the typhoon convective precipitation measured in In-Fa is more maritime-like than precipitation in Taiwan. Based on a great number of surface disdrometer observational data, the GPM precipitation products were further validated for both rain types, and a series of native quantitative precipitation estimation relations, such as Z–R and R–D_m relations were derived to improve the typhoon rainfall retrieval for both ground-based radar and spaceborne radar. Full article