Lakes and other surface fresh waterbodies provide drinking water, recreational and economic opportunities, food, and other critical support for humans, aquatic life, and ecosystem health. Lakes are also productive ecosystems that provide habitats and influence global cycles. Chlorophyll concentration provides a common metric of water quality, and is frequently used as a proxy for lake trophic state. Here, we document the generation and distribution of the complete MEdium Resolution Imaging Spectrometer (MERIS; Appendix A provides a complete list of abbreviations) radiometric time series for over 2300 satellite resolvable inland bodies of water across the contiguous United States (CONUS) and more than 5,000 in Alaska. This contribution greatly increases the ease of use of satellite remote sensing data for inland water quality monitoring, as well as highlights new horizons in inland water remote sensing algorithm development. We evaluate the performance of satellite remote sensing Cyanobacteria Index (CI)-based chlorophyll algorithms, the retrievals for which provide surrogate estimates of phytoplankton concentrations in cyanobacteria dominated lakes. Our analysis quantifies the algorithms' abilities to assess lake trophic state across the CONUS. As a case study, we apply a bootstrapping approach to derive a new CI-to-chlorophyll relationship, Chl_BS, which performs relatively well with a multiplicative bias of 1.11 (11%) and mean absolute error of 1.60 (60%). While the primary contribution of this work is the distribution of the MERIS radiometric timeseries, we provide this case study as a roadmap for future stakeholders' algorithm development activities, as well as a tool to assess the strengths and weaknesses of applying a single algorithm across CONUS.

湖泊和其他地表淡水水体为人类、水生生物和生态系统健康提供饮用水、娱乐和经济机会、食物以及其他重要支持。湖泊也是生产性生态系统，提供栖息地并影响全球循环。叶绿素浓度提供了水质的通用指标，经常用作湖泊营养状态的代表。在这里，我们记录了完整的中分辨率成像光谱仪（MERIS；附录 A 提供了完整的缩写列表）辐射时间序列的生成和分布，用于美国本土 (CONUS) 和超过 2300 个卫星可分辨的内陆水体阿拉斯加有 5,000 人。这一贡献大大提高了卫星遥感数据用于内陆水质监测的易用性，以及突出内陆水域遥感算法开发的新视野。我们评估基于卫星遥感蓝藻指数 (CI) 的叶绿素的性能a算法，其检索提供了蓝藻占主导地位的湖泊中浮游植物浓度的替代估计。我们的分析量化了算法评估美国大陆上湖泊营养状态的能力。作为案例研究，我们应用引导方法来推导新的 CI 与叶绿素的关系 Chl _BS，其表现相对较好，乘法偏差为 1.11 (11%)，平均绝对误差为 1.60 (60%)。虽然这项工作的主要贡献是 MERIS 辐射时间序列的分布，但我们提供此案例研究作为未来利益相关者算法开发活动的路线图，以及评估在 CONUS 上应用单一算法的优缺点的工具.