本报讯（记者赵金玲）昨日，记者从自治区气候中心了解到，预计2026年广西气候属一般到偏差年景， 年初冷暖起伏大，有阶段性低温过程。全区年平均气温较常年偏高，影响广西的台风有4～5个。 自治区气候中心预计，2026年全区年平均气温20.5℃～21.5℃，较常年偏高，夏秋季可能出现阶段性高 温天气过程。全区平均年总降水量为1450～1650毫米，接近常年，其中桂北偏多一至三成、桂中和桂南 偏少一至二成。 预计2026年暴雨集中期大部地区出现在5—6月、沿海地区出现在7—8月，发生暴雨洪涝灾害的风险高。 影响广西的台风有4～5个，接近常年。总体上，2026年广西气候属一般到偏差年景。 预计2026年1—3月总降水量大部地区偏少，可能出现阶段性气象干旱。冷暖起伏大，发生过程性强降温 和极端低温的可能性大，1月下旬到2月中旬桂北部分地区可能出现阶段性冰冻雨雪天气过程。 前汛期（4—6月）总降水量桂北偏多二至四成，其余地区接近常年，桂北可能出现暴雨洪涝和极端性强 降水过程，桂西和桂北易发生雷暴、冰雹等强对流天气。平均气温大部地区正常至偏高。 后汛期（7—9月）总降水量桂南偏多一至三成，桂北偏少一至三成。平均气温大部地区偏 ...

Core Insights - The article highlights the advancements made by Hohai University in developing a self-controlled ocean-atmosphere coupling prediction system, which has significantly improved climate forecasting capabilities in China [1][2][3]. Group 1: Technological Advancements - The ocean-atmosphere coupling prediction system was developed to reduce reliance on foreign numerical models, addressing significant "bottleneck" risks in climate prediction [2]. - Key breakthroughs include the creation of multi-source ocean-atmosphere observation data assimilation technology, which efficiently integrates satellite, buoy, and vessel data [2]. - The development of ensemble filtering assimilation methods has enhanced the quantification of prediction uncertainties by converting single-value outputs into probabilistic ranges [2]. - A parameter estimation and correction system was established to optimize model parameters, significantly reducing model errors [2]. Group 2: Predictive Accuracy - In 2023, the system successfully predicted a moderate-strength El Niño event nine months in advance, with a prediction accuracy improvement of over 15% compared to international mainstream models [3]. - The system is capable of accurately forecasting other critical climate phenomena, such as the Indian Ocean Dipole, providing reliable climate support for major events like the Beijing Winter Olympics [3]. Group 3: Practical Applications - The prediction system has become an integral part of the national marine environment forecasting center, contributing to decision-making for flood prevention, drought relief, water resource management, food production, energy supply, and major engineering projects [4]. - The system has received national recognition, including certification from the China Meteorological Administration and a first-class award from Jiangsu Province for marine science and technology [4]. - Over the past decade, the team has transitioned from reliance on foreign models to developing a complete set of assimilation technologies, achieving a leap in China's marine environment forecasting capabilities [4].

Core Insights - A recent study reveals a persistent cold water zone in the North Atlantic that has resisted overall warming trends for over a century, linked to the long-term weakening of the Atlantic Meridional Overturning Circulation (AMOC) [1][2] - The study enhances future climate predictions related to Europe, as AMOC significantly impacts European weather patterns [1] Group 1: AMOC and Climate Impact - The AMOC is a large ocean current system that regulates climate by transporting warm, salty water northward and cold water southward, acting like a conveyor belt [1][2] - The weakening of AMOC results in less warm, salty water reaching subpolar regions, leading to observed cooling and freshwater influx in the southern Greenland area [1][2] Group 2: Research Methodology - Researchers analyzed sea temperature and salinity data over the past century to reconstruct changes in the AMOC, comparing it with nearly 100 different climate models [2] - Only models simulating the weakening of AMOC aligned with real-world data, indicating the significance of this phenomenon [2] Group 3: Broader Implications - The cold water zone near southern Greenland is crucial as it is one of the most sensitive areas to ocean circulation changes, affecting weather patterns in Europe, altering rainfall, and modifying jet streams [2] - The slowdown of ocean currents may disrupt marine ecosystems due to changes in salinity and temperature affecting species habitats [2][3]