2024年11月27日 时政类语篇型填空专项训练（人工智能创新有助于应对极端天气）（4篇，含答案与译文） -2025届高三英语二轮复习专项

2024年11月27日 时政类语篇型填空专项训练（人工智能创新有助于应对极端天气） AI innovations aid extreme weather management Passage 1 Artificial intelligence has been 1. (increase) applied 2. (tackle) the 3. (grow) threat of extreme weather events such as heavy rainfall, hail and storms, according to groundbreaking innovations unveiled recently by the China Meteorological(气象) Administration. The administration showcased 16 innovations in urban meteorological science at a conference in Beijing 4. Monday, 5. are part of 103 research breakthroughs in AI 6. (apply), radar 7. (network) and short-term heavy rainfall forecasting. These 8. (achieve) 9. (deliver) by the Urban Meteorological Science and Technology Alliance, initiated by the Beijing Meteorological Service last year and 10. (comprise) meteorological departments from 38 major cities. Passage 2 Beijing's Leadsee-Precip, a global deep-learning model 1. (design) to generate precipitation forecasts from meteorological circulation fields, is one of the domestically developed AI-powered forecasting systems 2. excels in 3. (predict) rainfall 4. (distribute) and intensity. Deep-learning weather forecasting models have surpassed traditional numerical models in both 5. (accurate) and 6. (efficient), said Feng Jin, head of the Leadsee development team and a researcher at the Institute of Urban Meteorology. AI-driven global circulation models or GCMs, which integrate traditional numerical weather prediction 7. (technical) with machine learning, can deliver forecasts in no more than a minute — a dramatic improvement over the 30-minute processing time 8. (require) by conventional models, Feng said. However, current GCMs lack 9. (detail) atmospheric and precipitation data, which Leadsee compensates for by focusing 10. rainfall prediction, he added. Passage 3 "Leadsee 1. (address) critical gaps in AI global circulation models, 2. (particular) in forecasting extreme rainfall," Feng said, adding that the model ensures precision even with imbalanced rainfall data. During Typhoon Gaemi, which 3. (make) landfall in Fujian province and Taiwan in July, Leadsee 4. (success) forecasted a shift in rainfall patterns over Beijing, enabling local authorities 5. (adjust) flood prevention strategies effectively. The Beijing Meteorological Service conducted a comprehensive 6. (assess) based on 7. (refer) provided by Leadsee, 8. (conclude) that Gaemi's impact on the Beijing area would significantly weaken, Feng said. Additionally, 9. (evaluate) of the model during this year's flood season demonstrated a 20 percent improvement in forecasting accuracy for heavy rainfall compared 10. mainstream models. Passage 4 Beyond Beijing, the Shenzhen Meteorological Bureau in Guangdong province has developed an AI-based system 1. heavy rainfall nowcasting, and the effective lead time for nowcasting of heavy rainfall has 2. (extend) from one hour to two hours. Leveraging high-resolution datasets from radar, satellites and weather stations, ... ...