Search Results (5)

Cyclone Mocha, classified as an Extremely Severe Cyclonic Storm (ESCS), followed an unusual northeastward trajectory while exhibiting a well-defined eyewall structure. It experienced rapid intensification (RI) before making landfall along the Myanmar coast. It caused heavy rainfall (~90 mm) and gusty winds (~115 knots) over the coastal regions of Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) countries, such as the coasts of Bangladesh and Myanmar. The factors responsible for the RI of the cyclone in lower latitudes, such as sea surface temperature (SST), tropical cyclone heat potential (TCHP), vertical wind shear (VWS), and mid-tropospheric moisture content, are studied using the National Ocean and Atmospheric Administration (NOAA) SST and National Center for Medium-Range Weather Forecasting (NCMRWF) Unified Model (NCUM) global analysis. The results show that SST and TCHP values of 30 °C and 100 (KJ cm⁻²) over the Bay of Bengal (BoB) favored cyclogenesis. However, a VWS (ms⁻¹) and relative humidity (RH; %) within the range of 10 ms⁻¹ and >70% also provided a conducive environment for the low-pressure system to transform into the ESCS category. The physical mechanism of RI and recurvature of the Mocha cyclone have been investigated using forecast products and compared with Cooperative Institute for Research in the Atmosphere (CIRA) and Indian Meteorological Department (IMD) satellite observations. The key results indicate that a dry air intrusion associated with a series of troughs and ridges at a 500 hPa level due to the western disturbance (WD) during that time was very active over the northern part of India and adjoining Pakistan, which brought north-westerlies at the 200 hPa level. The existence of troughs at 500 and 200 hPa levels are significantly associated with a Rossby wave pattern over the mid-latitude that creates the baroclinic zone and favorable for the recurvature and RI of Mocha cyclone clearly represented in the NCUM analysis. Moreover the Q-vector analysis and steering flow (SF) emphasize the vertical motion and recurvature of the Mocha cyclone so as to move in a northeast direction, and this has been reasonably well represented by the NCUM model analysis and the 24, 7-, and 120 h forecasts. Additionally, a quantitative assessment of the system indicates that the model forecasts of TC tracks have an error of 50, 70, and 100 km in 24, 72, and 120 h lead times. Thus, this case study underscores the capability of the NCUM model in representing the physical mechanisms behind the recurving and RI over the BoB. Full article

Coastal countries’ productive capabilities are significantly influenced by the structure, dynamics, and evolution of marine products. In this study, we examined the market development dynamics of marine products across 156 coastal countries from 1995 to 2021, utilizing product space and economic complexity frameworks. We constructed and analyzed the product space of 106 marine products across six major marine industries, investigating the positioning and potential of various coastal countries within this space over three decades. The key findings were as follows: (1) global marine product exports exhibited substantial growth and increased geographical diversification. (2) The marine product space exhibited a core–periphery structure, with high-complexity marine shipbuilding products at the core and resource-based primary products at the periphery. (3) Coastal countries’ positions in the product space could be clustered into four distinct types: (i) complex diversified economies with constrained development potential, (ii) developed and industrialized countries with coexisting complexity and diversification, (iii) small island and developing countries with coexisting specialization and potential, and (iv) single-resource-dependent countries in the Middle East and Gulf of Guinea in Africa. (4) Each type faced unique development opportunities and challenges. We recommend that all economies continually leverage their comparative advantages in complex products. Specifically, type (i) and (ii) countries should focus on strengthening inter-product technological and knowledge networks and developing more integrated industrial chains. Type (iii) and (iv) countries should capitalize on their resources and geographical advantages to develop new, more complex products that align closely with their existing product baskets. Full article

The semiconductor industry is a pivotal hub in the global information sector, in which superpowers compete for technological dominance. As a strategic, leading, and foundational sector, it is vital for advancing China’s manufacturing ambitions through new waves of transformation and upgrades. Therefore, of particular concern is the crisis surrounding China’s semiconductor supply chain insecurity and the intensifying U.S. sanctions on China’s high-tech companies. As such, in this study, we utilize data from China’s semiconductor enterprises, investments, and related statistics from 2002 to 2020; industrial agglomeration indicators; and a social network analysis to examine the spatiotemporal pattern, industrial agglomeration, and investment networks of six key value chain segments: wafer materials, packaging materials, semiconductor equipment, integrated circuit (IC) design, manufacturing, and testing/packaging. The research focuses on how these sectors can contribute to sustainable growth and economic responsibility within China’s semiconductor industry. Accordingly, the core questions explored were as follows: what are the provincial-level spatial production dynamics and evolutionary characteristics within China’s semiconductor industry, and how do the inter-provincial investment patterns manifest? The findings reveal the following: (1) The findings reveal a strong concentration of firms in the Eastern Coastal region, particularly in Jiangsu, Shanghai, Zhejiang, and Guangdong. Additionally, IC design exhibits the highest clustering, and other segments such as wafer materials, manufacturing, and packaging/testing are relatively concentrated, whereas equipment distribution is more dispersed. (2) The industry expanded steadily from 2002 to 2013, with a rapid expansion from 2014 to 2020, particularly in Guangdong. (3) Investment patterns are characterized by local and regional focus, strongly influenced by geographical proximity. This study aims to reveal the geographic concentration patterns of China’s semiconductor industry and to explore its investment networks. The findings are intended to provide theoretical support for optimizing sustainable industrial layouts, promoting sustainable industrial practices, and guiding policy formulation. Furthermore, in the broader context of de-globalization, this study offers insights and recommendations for strengthening industrial autonomy and sustainability in response to external challenges, thereby contributing to the sustainable development of a more robust domestic semiconductor supply chain. These insights are particularly significant in safeguarding China’s technological independence and future economic stability amid global tensions. Furthermore, by integrating sustainability into its semiconductor industry, China can create a more resilient, self-sufficient, and environmentally responsible industrial sector, capable of meeting both domestic and global demands. As China continues to expand its semiconductor industry, incorporating sustainable development principles will be essential for long-term success. The sustainable practices not only ensures compliance with environmental regulations but also enhances industrial competitiveness, promotes green techniques and contributes to broader societal goals. This aligns with China’s broader ambitions for sustainable development and positions the country as a key player in the global green technology revolution. Full article

The need to guarantee the geographical origin of food samples has become imperative in recent years due to the increasing amount of food fraud. Stable isotope ratio analysis permits the characterization and origin control of foodstuffs, thanks to its capability to discriminate between products having different geographical origins and derived from different production systems. The Framework 6 EU-project “TRACE” generated hydrogen (²H/¹H), carbon (¹³C/¹²C), nitrogen (¹⁵N/¹⁴N), and sulphur (³⁴S/³²S) isotope ratio data from 227 authentic beef samples. These samples were collected from a total of 13 sites in eight countries. The stable isotope analysis was completed by combining IRMS with a thermal conversion elemental analyzer (TC/EA) for the analysis of δ(²H) and an elemental analyzer (EA) for the determination of δ(¹³C), δ(¹⁵N), and δ(³⁴S). The results show the potential of this technique to detect clustering of samples due to specific environmental conditions in the areas where the beef cattle were reared. Stable isotope measurements highlighted statistical differences between coastal and inland regions, production sites at different latitudes, regions with different geology, and different farming systems related to the diet the animals were consuming (primarily C3- or C4-based or a mixed one). Full article

The influence of topographical characteristics and rainfall intensity on the accuracy of satellite precipitation estimates is of importance to the adoption of satellite data for hydrological applications. This study evaluates the three GPM IMERG V05B products over the arid country of Saudi Arabia. Statistical indices quantifying the performance of IMERG products were calculated under three evaluation techniques: seasonal-based, topographical, and rainfall intensity-based. Results indicated that IMERG products have the capability to detect seasons with the highest precipitation values (spring) and seasons with the lowest precipitation (summer). Moreover, results showed that IMERG products performed well under various rainfall intensities, particularly under light rain, which is the most common rainfall in arid regions. Furthermore, IMERG products exhibited high detection accuracy over moderate elevations, whereas it had poor performance over coastal and mountainous regions. Overall, the results confirmed that the performance of the final-run product surpassed the near-real-time products in terms of consistency and errors. IMERG products can improve temporal resolution and play a significant role in filling data gaps in poorly gauged regions. However, due to the errors in IMERG products, it is recommended to use sub-daily rain gauge data in satellite calibration for better rainfall estimation over arid and semiarid regions. Full article