Core Viewpoint - The winter climate in China is expected to be influenced by the La Niña phenomenon, which is predicted to last until early 2026, leading to average national temperatures close to or above normal levels this winter [2][6][7]. Temperature Trends - In October, the national average temperature was 11.1°C, close to the historical average, with a "warm front followed by cold" pattern observed [4]. - The early part of October experienced high temperatures, with some regions in southern China exceeding 38°C, while a significant drop in temperature occurred in the latter part of the month due to cold air masses [5]. La Niña Impact - The La Niña state is expected to result in a winter with average temperatures near or above normal and generally lower precipitation, particularly in southern regions [7]. - The risk of widespread low-temperature rain and snow events in southern China is considered low [7]. Precipitation Patterns - National average precipitation in October was 51.5 mm, which is 51.8% above the historical average, marking the third-highest for this period [8]. - The forecast indicates that certain regions, including northeastern and southwestern areas, will experience above-average precipitation, while others will see near-normal to below-normal levels [9]. Upcoming Weather Forecast - The next ten days are expected to see higher temperatures in most northern regions, with average temperatures 1-3°C above or close to normal levels [8]. - Rainfall is anticipated in various regions, with specific areas in the southwest and south experiencing significant precipitation events [9].

Core Insights - The National Marine Environmental Forecasting Center predicts a cooler state in the equatorial central-eastern Pacific during the autumn and winter of 2025, while most coastal waters of China will experience higher sea temperatures [1][2] Group 1: ENSO Predictions - Experts discussed the changing characteristics of ENSO (El Niño-Southern Oscillation) under global warming, which poses new challenges for climate prediction [1] - The Nino3.4 index is expected to approach or reach the threshold for a La Niña event, indicating a possibility of a weak La Niña occurrence [1] Group 2: Seasonal Sea Temperature Forecasts - Predictions for this winter indicate slightly higher sea temperatures in the Bohai Sea and the southern part of the East China Sea, while the Yellow Sea and central and northern East China Sea will also see elevated temperatures [2] - The South China Sea's temperatures are expected to be close to the long-term average, with a focus on the impact of higher coastal sea temperatures on aquaculture and marine ecological environments [2]

Core Insights - The article discusses the upcoming webinar focused on summer weather outlooks in the Americas and Asia, and their potential impacts on crops, including updates on U.S. spring planting activities and South American late-season progress [1]. Agenda Overview - The agenda includes a review of the South American season, early weather outlook for U.S. spring planting, U.S. planting and production outlook, ENSO (El Niño-Southern Oscillation) and its global impacts, and summer weather in Asia [5]. Event Information - The event is scheduled for April 16, 2025, at 09:00 AM Beijing time, and will be conducted in English [3]. Expert Speakers - The webinar features senior analysts from LSEG, including Isaac Hankes, a senior climate research analyst, and Dong Soon Choi, a senior agricultural analyst [4]. LSEG's Commodity Trading Solutions - LSEG offers market insights, data management solutions, and seamless trading execution capabilities to provide a competitive advantage in commodity trading [8]. - The company emphasizes the importance of obtaining accurate information at the right time and format for successful commodity trading [10]. - LSEG provides tools, fundamentals, forecasts, alternative data, and the latest news to help clients excel in the competitive landscape of commodity trading [11]. Specific Commodity Trading Areas - **Energy Trading**: LSEG covers a wide range of energy assets, including oil, gas, electricity, coal, and carbon, supporting global energy commodity trading platforms [13]. - **Metal Trading**: The company utilizes machine learning and AI to enhance data and analysis for global metal trading, helping clients discover trading opportunities [15]. - **Agricultural Trade**: LSEG employs robust fundamental data and alternative sources, such as weather tracking and satellite imagery, to predict market price trends in agriculture [17]. - **Shipping Trade**: The company provides unique insights into global shipping trade through real-time reporting of vessel movements and port congestion [19]. - **Data Aggregation and Digitalization**: LSEG specializes in standardizing and structuring multiple data sources to generate actionable insights for global trading companies [20].