2025年3月12日 · Click on a region to view images and animations for that region. Coverage area depictions are approximate.

GOES-2, known as GOES-B before becoming operational, was a geostationary weather satellite which was operated by the United States National Oceanic and Atmospheric Administration as part of the Geostationary Operational Environmental Satellite system. [4]

GOES 2 was a NASA-developed, NOAA-operated, geosynchronous, and operational spacecraft.

2012年5月29日 · Geostationary Operational Environmental Satellite (GOES) 2nd Generation Series consisted of a group of five satellites, sequentially named GOES-I, J, K, L and M and designated numbers 8 - 12 in place of consecutive letters after launch.

2017年12月14日 · Data describing the environment at geosynchronous orbit. The Synchronous Meteorological Satellites (SMS-1 and SMS-2) and the Geostationary Operational Environmental Satellites (GOES-1, GOES-2, etc.) all carry on board the Space Environment Monitor (SEM) instrument subsystem.

goes卫星系统由部署在 地球静止轨道 的2颗卫星组成，分别为西经75°和西经135°，前者主要观测美洲和大西洋大部，后者主要观测北美和太平洋地区；两个轨位卫星联合可以观测从西经20°至东经165°的大部地区。另外，在轨备份卫星部署在西经105°。

2025年2月11日 · GOES-2-Go is a python package that helps you download GOES-R series (GOES-East/16 and GOES-West/17/18) NetCDF files from the Amazon Web Services archive and provides RGB recipes for various RGB products. The easiest way to install goes2go and its dependencies is with Conda from conda-forge.

GOES-2-go is a python package that makes it easy to find and download the files you want from AWS to your local computer with some additional helpers to visualize and understand the data. The easiest way to install goes2go and its dependencies is with Conda from conda-forge. You may also create the provided Conda environment, environment.yml.

2024年10月10日 · GOES-2-go 是一个用于从 NOAA 在 AWS 上的归档中下载和处理 GOES-16 和 GOES-17 数据的 Python 包。 该项目旨在简化从 AWS 下载所需文件的过程，并提供一些额外的工具来可视化和理解数据。

2024年6月9日 · GOES-2-go 是一个精心设计的Python包，旨在简化从Amazon Web Services（AWS）下载和显示GOES-East和GOES-West卫星数据的过程。借助这个库，科学家、研究人员以及气象爱好者可以轻松地访问这些宝贵的气象数据，并进行高效的数据处理和视觉呈现。