阅读理解43-北京市部分地区近两年（2024-2025）高二英语期末真题汇编

1 英语试题·阅读理解43 试题基本信息 。题型：阅读理解(4题，约520词) 。核心知识点：天气预报、人工智能、说明文 ·考查重点：指代关系、段落主旨、细节理解、文章目的 材料剖析 ·文章结构：介绍AI天气预报新方法→对比传统数值模型→分析AI工作原理→指出 A虹面临挑战→探讨混合模型前景 ·核心论点：A虹天气预报相比传统模型更快更准，但在极端天气预测和数据稀缺方面存在 挑战，混合模型可能是未来方向 阅读理解短文 A pair of papers,published in the scientific journal Nature,touts()the potential of new AI weather forecasting approaches-systems that could produce faster and more accurate results than traditional models.They are part of a new wave of AI models sweeping the meteorology 象学)community worldwide. Conventional forecasts rely on a system known as numerical weather prediction.It's a kind of mathematical model that uses complex equations (to predict the way weather systems change over time and space.These equations describe the actual physics behind the movement of air and water in the atmosphere and the oceans.Because there's so much math and physics involved,numerical weather models require extremely high levels of computational power.That makes them expensive and time-consuming to run.It also limits the fine-scale processes that these models can accurately capture. Scientists have come up with various ways to get around these difficulties in traditional models. One strategy is a method known as parameterization-that's when scientists replace the actual physical equations in a model with a simplified program that generally captures the process without forcing the model to represent the actual physics. But artificial intelligence could replace these workarounds,enthusiasts argue,with potentially faster and more accurate results. AI models don't have to represent actual physics in the form of mathematical equations. Instead,they take in large amounts of historical weather data and learn to recognize patterns They then use these patterns to make predictions when presented with new data on present-day weather conditions 2 In principle,the much faster computational speed could provide immense benefits.But some experts note that the changing climate may pose a unique challenge for developing AI weather models.AI systems rely on historical weather data to teach them how to produce accurate forecasts. But certain kinds of weather events,such as heat waves and hurricanes,are growing more intense as the planet warms-and in some cases,they're becoming so extreme that there are few examples at all in the historical record.That could make it difficult for Al weather models to accurately simulate (events that are record-breaking or have never been seen before. Accurately forecasting extreme weather events is one of the most crucial functions for weather models,enabling decision-makers to issue public safety announcements or facilitate evacuations ()with enough time to protect high-risk populations.But if AI models are presented with weather conditions that are entirely foreign to them,it may be hard to predict how they'll react. The authors of the 2021 Royal Society paper point out that when it comes to capturing extremes with limited data,AI systems have produced mixed results-some have performed well while others not that satisfactorily. Hybrid models that include both AI components and numerical model components may run into fewer difficulties with record-breaking events,Russ Schumacher,Colorado's state climatologist, suggested.He noted that numerical models and AI models may end up with different strengths, and human experience will remain valuable for communicating information about the weather. 题目选项列表 1.What does the underlined expression "these workarounds"in Paragraph 4 refer to? (a)High costs. (b)Various methods. (c)Weather systems. (d)Inaccurate results 2.What is Paragraph 5 mainly about? (a)The advantages of artificial intelligence. (b)The application of mathematical equations. (c)The fast collection of historical weather data. (d)The working principles of AI weather models. 3.What can we learn from the passage? (a)Decision-makers find AI forecasts more reliable. (b)AI models will eventually replace numerical ones. (c)Lack of relevant weather data challenges AI systems. (d)AI weather models help to prevent extreme climate events. 4.What's the main purpose of the passage? (a)To raise global climate change awareness. (b)To stress the importance of the historical record. (c)To compare the strengths of weather prediction methods. (d)To suggest a way to improve weather prediction accuracy. 3 核心词汇详解 1.meteorology 核心词性 名词(，高频核心)：气象学（研究天气、气候等的学科） 例：Meteorology helps predict weather changes.(气象学有助于预测天气变 化) 词性转换 形容词：meteorological(气象的；气象学的) 名词：meteorologist(气象学家) 例：meteorological data(气象数据)、The meteorologist iss2 ied a weather forecast..(气象学家发布了天气预报) 高频搭配 atmospheric meteorology(大气气象学)、applied meteorology(应用气象学) 易混辨析 meteorology vs climate:前者指”研究气象的学科”，是科学领域术语；后 者指”气候”，侧重某地区长期的天气状况 例：The climate here is mild.(这里气候温和)》 2.parameterization 核心词性 名词(，高频核心)：参数化（将复杂过程简化为参数的方法） 例：Parameterization is used in numerical models.(参数化用于数值模型中) 词性转换 动词：parameterize(用参数表示；参数化) 名词：parameter（参数；参量) 例：The model parameterizes the physical processes.(该模型将物理过程参 数化)、Adjust the parameters to improve accuracy..(调整参数以提高准确 性) 高频搭配 physical parameterization(物理参数化)、numerical parameterization(数 值参数化) 易混辨析 parameterization vs simplification:前者指”通过参数进行简化的特定 方法”，多用于科学模型：后者泛指”简化”，适用范围更广 例：the simplification of a problem(问题的简化) 4 3.computational 核心词性 形容词(adj.,高频核心)：计算的；计算机的 例：computational power(计算能力) 词性转换 动词：compute(计算；估算) 名词：computation(计算；运算)、computer(计算机) 例：compute the result(计算结果)、The computation took hours.(计算花 了数小时) 高频搭配 computational efficiency(计算效率)、computational model(计算模型) 易混辨析 computational vs calculated:前者强调”与计算过程或计算机相关的"； 后者指”经过计算的；故意的” 例：a calculated risk（经过权衡的风险) 4.simulate 核心词性 动词(V,高频核心)：模拟；模仿（再现过程或情境）；假装；冒充 例：simulate weather conditions(模拟天气状况)、He simulated illness to avoid work.(他装病逃避工作) 词性转换 名词：simulation(模拟；仿真) 形容词：simulative(模拟的；仿真的) 例：computer simulation(计算机模拟)、simulative experiments(模拟实验) 高频搭配 simulate a process(模拟一个过程)、simulate reality(模拟现实) 易混辨析 simulate vs imitate:前者侧重”通过技术或模型精确再现复杂过程”；后 者侧重”模仿他人的行为、风格等” 例：imitate a singer'svo2ce(模仿歌手的声音) 答案与逐题解析 正确答案：27-30BDCC 1.B (Various methods) 考点：指代关系理解 语境逻辑：前文第三段首句明确提到Scientists have come up with various ways to get around these difficulties in traditional models'”,随后具体解释了”parameterization”这一方法，第四段 开头用”artificial intelligence could replace these workarounds'”承接，可知these workarounds” 指代前文提到的”various ways”(各种方法)。 选项辨析：A.High costs(高成本)是传统模型的问题，非指代内容；C.Weather systems(天 气系统)是预测对象，与”workarounds'”无关；D.Inaccurate results(不准确结果)是可能的后 果，并非被替代的对象。只有B符合上下文逻辑。 5 2.D (The working principles of AI weather models) 考点：段落主旨归纳 语境逻辑：第五段开头指出”AI models don't have to represent actual physics in the form of mathematical equations'”,随后具体说明其工作流程："take in large amounts of historical weather data and learn to recognize patterns”(输入历史数据学习模式)，”"use these patterns to make predictions when presented with new data”(用新模式预测新数据)。整段围绕AI气象模型的 工作原理展开。 选项辨析：A.The advantages of artificial intelligence(AI的优势)范围过大，本段仅聚焦AI 气象模型的工作方式；B.The application of mathematical equations(数学方程的应用)是传 统模型的特点，与AI模型无关；C.The fast collection of historical weather data(历史数据的 快速收集)未提及，本段强调的是数据的”学习”和”应用”，而非”收集”。 3.C (Lack of relevant weather data challenges AI systems) 考点：细节信息理解与推断 语境逻辑：第六段明确提到”certain kinds of weather events...are becoming so extreme that there are few examples at all in the historical record.That could make it difficult for Al weather models to accurately simulate events that are record-breaking or have never been seen before", 第七段进一步指出"when it comes to capturing extremes with limited data,AI systems have produced mixed results”。可见缺乏相关数据是AI系统面临的挑战。 选项辨析：A.Decision-makers find AI forecasts more reliable(决策者认为AI预测更可靠) 文中未提及，且第七段提到AI对极端事件的预测结果”mixed”;B.AI models will eventually replace numerical ones(AI模型将最终取代数值模型)与最后一段”Hybrid models..may run into fewer difficulties”及"human experience will remain valuable”矛盾；D.AI weather models help to prevent extreme climate events(AI模型帮助预防极端气候事件)夸大作用，文中仅说 准确预测极端事件能"enable decision-makers to issue public safety announcements”,而非”预 防”。 4.C (To compare the strengths of weather prediction methods) 考点：文章主旨意图归纳 语境逻辑：文章开头对比传统数值模型(”expensive and time-consuming”)与AI模型(”faster and more accurate'”),随后分别阐述两者的原理，接着指出AI模型在极端事件预测中的数据局 限，最后提到混合模型的可能性及人类经验的价值。整体围绕不同气象预测方法（传统数值模 型、AI模型、混合模型)的特点和优劣展开对比。 选项辨析：A.To raise global climate change awareness(提高全球气候变化意识)并非主旨， 气候变化只是作为AI模型面临挑战的背景提及；B.To stress the importance of the historical record(强调历史记录的重要性)仅为第六段细节，非全文目的；D.To suggest a way to improve weather prediction accuracy(提出提高预测准确性的方法)文中虽提到混合模型，但未聚焦”建 议方法”，而是客观对比现有方法。