LEO satellite constellations, led by deployments such as Starlink, are playing an increasingly pivotal role in enabling global broadband connectivity. However, the reliability and performance of these space-based networks are highly sensitive to environmental dynamics, particularly localized weather phenomena that exhibit strong spatio-temporal variability. In this study, we present a continental-scale geospatial analysis of weather-induced performance degradation in the Starlink LEO network, with a focus on the contiguous United States. Leveraging a unique dataset comprising more than 870,000 terminal hours of minute-level telemetry from 1,292 Starlink terminals, we integrate high-resolution localized weather observations to quantify the impact of various meteorological conditions. We evaluated key performance indicators (KPIs)-including ping latency, ping drop rate, and signal quality-using spatial join techniques and time-aligned correlation with classified weather events. Our analysis reveals that severe weather events, such as thunderstorms with heavy rain or snow, have a pronounced effect on network performance. In particular, more than 55% affected terminals experienced substantial degradation. Temporal continuity analysis at the minute level shows that such degradation can lead to sustained impairments or full service outages lasting from several minutes to multiple hours.This work contributes to the first large-scale empirical study linking LEO satellite Internet performance with fine-grained weather data in both space and time. Our findings offer actionable insights for geospatial predictive modeling, weather-aware network provisioning, and resilient satellite communication system design. We also propose a framework for incorporating weather-inferred performance variability into future geospatial planning and service-level forecasting tools for LEO-based Internet systems.

翻译：低轨卫星星座，以星链（Starlink）等部署为代表，在实现全球宽带连接方面正发挥日益关键的作用。然而，这些天基网络的可靠性和性能对环境动态，尤其是表现出强烈时空变化的局部天气现象高度敏感。在本研究中，我们针对星链低轨卫星网络因天气引起的性能下降，开展了一项大陆尺度的地理空间分析，重点关注美国本土。利用包含来自1,292个星链终端的超过87万终端小时分钟级遥测数据的独特数据集，我们整合了高分辨率的局部天气观测，以量化不同气象条件的影响。我们评估了关键性能指标（KPI），包括ping延迟、ping丢包率和信号质量，采用了空间连接技术和与分类天气事件时间对齐的相关性分析。我们的分析揭示，恶劣天气事件，如伴随强降雨或降雪的雷暴，对网络性能有显著影响。尤其值得注意的是，超过55%受影响的终端经历了严重的性能下降。分钟级的时间连续性分析显示，此类性能下降可能导致持续数分钟至数小时的连接损伤或完全服务中断。本研究是首次结合细粒度天气数据，从空间和时间两个维度对低轨卫星互联网性能进行大规模实证研究。我们的发现为地理空间预测建模、天气感知网络规划以及弹性卫星通信系统设计提供了可操作的见解。我们还提出一个框架，用于将天气推断的性能变异性纳入未来低轨卫星互联网系统的地理空间规划和服务水平预测工具中。