内容来源：https://www.wired.com/story/ai-has-flooded-all-the-weather-apps/

内容总结：

近日，多家天气应用程序正加速引入人工智能技术，为用户提供更个性化、智能化的气象服务。其中，气象公司旗下“风暴雷达”应用推出全新版本，内置AI天气助手，支持用户自定义天气预报图层，并可将天气信息与日历等应用同步，通过文字或模拟播音员语音推送出行建议。该应用目前仅限iOS平台使用，订阅费用为每月4美元，安卓版本预计后续上线。

当前，第三方天气应用市场竞争激烈，除“风暴雷达”外，Carrot Weather、彩虹天气等应用也积极布局AI功能。与此同时，部分气象服务已开始与ChatGPT等人工智能平台集成。行业人士指出，用户对天气信息呈现形式的需求日益多元，如何平衡数据深度与使用便捷性成为产品设计的关键。

在技术层面，多数天气应用的数据来源于美国国家海洋和大气管理局等机构，通过超级计算机和机器学习模型处理气象观测数据。开发者表示，机器学习技术正推动天气预报领域革新，尤其在数据可视化和多模型对比分析方面发挥重要作用。

值得注意的是，随着极端天气事件频发，天气预报面临更高挑战。部分应用尝试以“科学优先”原则运用AI技术，例如在官方预警基础上结合用户位置与日程提供个性化提醒，而非直接预测风险。也有开发者强调，AI功能应注重提升信息透明度，避免过度依赖“黑箱”交互，确保用户能直观理解气象数据本身。

业内专家认为，人工智能在天气应用中的融合仍处于探索阶段，未来需在数据准确性、服务人性化与技术实用性之间寻求更优平衡。

中文翻译：

您或许已注意到，最近天气类应用里悄然多了一抹人工智能的色彩。当科技企业争相将人工智能植入各类产品时，这股浪潮也席卷了朴素的天气应用。

气象频道运营商气象公司近日发布了全新升级的"风暴雷达"应用，其搭载的AI气象助手支持用户自定义天气预报与气象地图的呈现方式，可自由切换雷达、温度、风力、闪电等图层。该应用还能与日历等程序同步，根据您的日程安排发送天气提示与摘要信息。若您感兴趣，甚至能选择复古电台播音员风格的语音播报。与多数天气应用相同，其数据源自美国国家海洋和大气管理局及国家气象局。

这款应用每月订阅费4美元，目前仅支持iOS系统，但安卓版本已在开发计划中。气象公司高级气象学家乔·科瓦尔表示："我们希望打造能提升所有人气象体验的产品，无论是普通用户还是资深追风者。比如您想知道明天何时适合遛狗，不再需要费力比对各种零散数据自行推断。"

虽然手机系统通常会在时间显示旁突出天气信息，谷歌和苹果也已将天气功能深度集成至智能手机，并引入AI技术提供天气洞察与摘要，但第三方天气应用市场依然百花齐放。除"风暴雷达"外，"胡萝卜天气""雨景""顶点天气"等应用各具特色，而"彩虹天气"等新秀更以AI为核心卖点。气象服务也正被整合进AI聊天机器人，例如AccuWeather近期就在ChatGPT平台推出了专属应用。

曾开发热门天气应用Dark Sky的创始人亚当·格罗斯曼指出："每个人对天气应用的需求各异，关注的数据维度与呈现方式各不相同。如何打造一款适合所有人的天气应用？"2020年被苹果收购的Dark Sky最终融入苹果天气服务，格罗斯曼离职后创立了"顶点天气"，致力于开发能更好呈现预报不确定性的服务。

"任何预报都存在误差，但传统天气应用很少明确传达这一点。"格罗斯曼解释道，"我们正尝试重新构建这种信息语境。"气象数据通常来自政府机构，这些通过卫星、雷达、气象气球及地面设备采集的信息，会被输入大气物理模拟系统。虽然传统预报依赖高性能超算，但机器学习模型已能显著提升处理效率（尽管有时会牺牲精度，可通过多模型比对弥补）。

"风暴雷达"和"顶点天气"这类应用通过整合验证多源模型，将海量数据转化为高分辨率地图与可视化呈现，这正是AI能大显身手的领域。格罗斯曼认为："机器学习可能是气象预报领域近年来最重大的变革，而这仅仅是个开始。"

当前美国政府削减了对国家海洋和大气管理局等机构气象监测的投入，将部分数据采集工作转移至私营企业，而极端气候事件日益频发又给预报系统带来更大压力，这些因素共同推动了AI在天气应用中的普及。

科瓦尔强调"风暴雷达"坚持科学优先的AI应用理念："当国家气象局发布预警时，AI不会自行推测风险，而是结合您所在位置的日程安排，精准提示天气对计划的影响。"这款应用采用类似谷歌地图的多层复杂设计，天气爱好者甚至能用小组件铺满屏幕展示所有气象数据。其AI功能旨在简化信息过载，通过摘要或简短描述呈现天气概况，支持文字推送及多种播音员风格语音播报。

"用户可选择从复古气象员到流行文化爱好者等不同播报人格，"科瓦尔说，"个性化正是这款应用的核心。"格罗斯曼则对盲目标榜AI的行为持审慎态度，他的"顶点天气"虽在预报端运用AI，但坚持认为："服务应保持透明性，不该让用户感觉在和聊天机器人对话。理想状态是打开应用就能看到所需内容，而非时刻感知AI的存在。"

英文来源：

You may have noticed a drop of AI in your weather app lately. As companies race to infuse artificial intelligence into every product, the wave has come for the humble weather app.
The Weather Company, operator of the Weather Channel, today released a revamped version of its Storm Radar app, featuring an AI-powered Weather Assistant that lets users customize how they view forecasts and weather maps, toggling between layers like radar, temperature, and weather conditions like wind and lightning.
It can also sync with other apps, like your calendar, to send text notifications and weather summaries that tie info about the upcoming weather into your daily plans. You can stick a voice on it to talk like an old-timey radio weatherman, if you’re into that. Like most weather apps, it gets the data comes from the National Oceanic and Atmospheric Administration (NOAA) and the National Weather Service (NWS).
The app costs $4 per month. It is available on iOS only for now, but the company says an Android version is coming eventually.
“We wanted to build an experience that would be a weather level-up for anybody, really, from a casual observer to a seasoned storm chaser,” says Joe Koval, a senior meteorologist at the Weather Company. “If you're looking for advice on when the weather will be good to walk your dog tomorrow, you no longer have to look at a bunch of different disparate weather data elements and try to figure out the answer to that question yourself.”
You can find the weather on your phone already, of course. Android and iOS devices typically place the weather prominently beside the time. Google and Apple have both fused their weather apps into their smartphones directly. AI features have since been infused, offering insights and summaries about the day to come.
But there are third-party weather apps galore, like Storm Radar, Carrot Weather, Rain Viewer, and Acme Weather—an app from the former Dark Sky app creators. New weather apps like Rainbow Weather aim to be AI-first. Weather services are also being integrated directly into AI chatbots, like Accuweather, which recently launched an app directly in OpenAI’s ChatGPT.
“Everyone has their idea of what they want in a weather app, what data they're interested in, how they're interested in it being presented,” says Adam Grossman, a founder of the DarkSky app. “How do you build a single weather app that works for everybody?”
DarkSky, one of the most popular iOS weather apps, was bought by Apple in 2020 and merged into its Apple Weather service. Grossman eventually left Apple to start Acme Weather, with the goal of making a weather prediction service that better telegraphs the uncertainty of forecasting.
“No matter how good your forecast is, you're going to be wrong,” Grossman says. “That’s something that weather apps traditionally haven’t done a great job of doing. Our approach is trying to figure out how to add those pieces of context back in.”
Repositories of weather information usually come from government sources, like NOAA or other global weather services that collect data from weather satellites, radar, weather balloons, and on-the-ground instruments. All that data is fed into weather prediction models that simulate the physics of the atmosphere. Those predictions are often generated by resource-intensive supercomputers, but machine learning models have trimmed that processing down, making predictions quicker. (Though sometimes less accurate, which can be accounted for by comparing multiple models.)
Weather apps like Storm Radar and Acme Weather translate that bounty of information by corroborating and compiling the models, then helping to create high-resolution maps and a visual representation of the data, an area where AI can also be particularly useful.
“Machine learning is probably the biggest change to weather forecasting in a while,” Grossman says. “And they’re just getting started.”
The push of using AI in weather apps comes in the era where the government has dismantled NOAA and other federal efforts to track and measure weather patterns, leaving parts of the job of data collection to private companies. Weather systems also have a harder time predicting extreme weather events and climate disasters, which are growing ever more frequent.
Koval says Storm Radar is taking a science-first approach to AI in its app.
“If the NWS issues a warning, the AI isn't going to guess the risk,” Koval says. “It's going to cross-reference that official warning with your specific calendar at your location to tell you how it impacts your plan.”
Storm Radar is a more maximalist approach, with layered complexity akin to something like Google Maps. For the real weather sickos, widgets can be customized to cover the screen, displaying any and all weather information available. The AI features of the app aim to simplify that overload of data, letting the AI assistant give a summary or short description of the weather to come. That can come in text form, or via several differently accented voices that aim to sound like TV meteorologists.
“You can choose a persona ranging from a vintage weather person to a pop culture fan,” Koval says. “Personalization is really a key in this app.”
Grossman, who says Acme Weather uses AI on the forecasting side, is skeptical about any service—weather or otherwise—that touts its AI just for the sake of having AI.
“It should feel transparent; it shouldn't feel like you're talking to a chatbot," Grossman says. "If it's about surfacing the right content, you should open it up, and you should see what you need to see. It shouldn’t feel like AI is doing anything for you.”