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Himawari-9, stationed at 140.7E, owned and operated by the Japan Meteorological Agency (JMA), is a geostationary meteorological satellite, with Himawari-8 as on-orbit back-up, that provides constant and uniform coverage of east Asia, and the west and central Pacific regions from around 35,800 km above the equator with an orbit corresponding to the period of the earth’s rotation. This allows JMA weather offices to perform uninterrupted observation of environmental phenomena such as typhoons, volcanoes, and general weather systems. Archive data back to July 2015 is available for Full Disk (AHI-L1b-FLDK) products in the bucket. For questions regarding Himawari-9 imagery specifications, visit the JMA site at https://www.data.jma.go.jp/mscweb/en/himawari89/spacesegment/spsgahi.html. For examples of Full Disk Himawari-9 imagery coverage, visit the NOAA Himawari-9 data page at https://www.ospo.noaa.gov/Products/imagery/himawari.html.

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The National Climate Database (NCDB) seeks to be the definitive source of climate data for energy applications. The goal of the NCDB is to provide unbiased high temporal and spatial resolution climate data needed for renewable energy modeling. The NCDB seeks to maintain the inherent relationship between the various parameters that are needed to model solar, wind, hydrology and load and provide data for multiple important climate scenarios.

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The "Unified Forecast System" (UFS) is a community-based, coupled, comprehensive Earth Modeling System. The Hierarchical Testing Framework (HTF) serves as a comprehensive toolkit designed to enhance the testing capabilities within UFS "repositories". It aims to standardize and simplify the testing process across various "UFS Weather Model" (WM) components and associated modules, aligning with the Hierarchical System Development (HSD) approach and NOAA baseline operational metrics. The HTF provides a structured methodology for test case design and execution, which enhances code management practices, fosters user accessibility, and promotes adherence to established testing protocols. It enables developers to conduct testing efficiently and consistently, ensuring code integrity and reliability through the use of established technologies such as CMake and[...]

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UPDATE TO GHCN PREFIXES - The NODD team is working on improving performance and access to the GHCNd data and will be implementing an updated prefix structure. For more information on the prefix changes, please see the "READ ME on the NODD Github". If you have questions, comments, or feedback, please reach out to nodd@noaa.gov with GHCN in the subject line. Global Historical Climatology Network - Daily is a dataset from NOAA that contains daily observations over global land areas. It contains station-based measurements from land-based stations worldwide, about two thirds of which are for precipitation measurement only. Other meteorological elements include, but are not limited to, daily maximum and minimum temperature, temperature at the time of observation, snowfall and snow depth. It is a composite of climate records from numerous sources that were merged together and subjected to a com[...]

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The last several hurricane seasons have been active with records being set for the number of tropical storms and hurricanes in the Atlantic basin. These record-breaking seasons underscore the importance of accurate hurricane forecasting. Imperative to increased forecasting skill for hurricanes is the development of the Hurricane Forecast Analysis System or HAFS. To accelerate improvements in hurricane forecasting, this project has the following goals: 1) To improve the HAFS. The HAFS is NOAA’s next-generation multi-scale numerical model, with data assimilation package and ocean coupling, which will provide an operational analysis and forecast out to seven days, with reliable and skillful guidance on hurricane track and intensity (including rapid intensification), storm size, genesis, storm surge, rainfall and tornadoes associated with hurricanes. 2) To integrate into the Unified Forecasting System(UFS). The UFS is a community-based, coupled compreh[...]

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Digital Earth Africa (DE Africa) provides free and open access to a copy of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) monthly and daily products over Africa. The CHIRPS rainfall maps are produced and provided by the Climate Hazards Center in collaboration with the US Geological Survey, and use both rain gauge and satellite observations. The CHIRPS-2.0 Africa Monthly dataset is regularly indexed to DE Africa from the CHIRPS monthly data. The CHIRPS-2.0 Africa Daily dataset is likewise indexed from the CHIRPS daily data. Both products have been converted to cloud-opitmized GeoTIFFs, and can be accessed through DE Africa’s Open Data Cube. This means the full archive of CHIRPS daily and monthly rainfall can be easily used for inspection or analysis across DE Africa platforms, including the user-interactive DE Africa Map. For more information on the dataset, see the CHIRPS website.

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The Global Biodiversity Information Facility (GBIF) is an international network and data infrastructure funded by the world's governments providing global data that document the occurrence of species. GBIF currently integrates datasets documenting over 1.6 billion species occurrences, growing daily. The GBIF occurrence dataset combines data from a wide array of sources including specimen-related data from natural history museums, observations from citizen science networks and environment recording schemes. While these data are constantly changing at GBIF.org, periodic snapshots are taken and made available on AWS.

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The Unified Forecast System Subseasonal to Seasonal prototypes consist of reforecast data from the UFS atmosphere-ocean coupled model experimental prototype version 5, 6, 7, and 8 produced by the Medium Range and Subseasonal to Seasonal Application team of the UFS-R2O project. The UFS prototypes are the first dataset released to the broader weather community for analysis and feedback as part of the development of the next generation operational numerical weather prediction system from NWS. The datasets includes all the major weather variables for atmosphere, land, ocean, sea ice, and ocean waves. Acknowledgment - The Unified Forecast System (UFS) atmosphere-ocean coupled model experimental version # data used in this study are made available through the UFS Research to Operations (UFS-R2O) project sponsored by the National Weather Service (NWS) Office of Science and Technology Integration (OSTI) Modeling Program Division and the National Oceanic and Atmospheric Adminis[...]

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The National Blend of Models (NBM) is a nationally consistent and skillful suite of calibrated forecast guidance based on a blend of both NWS and non-NWS numerical weather prediction model data and post-processed model guidance. The goal of the NBM is to create a highly accurate, skillful and consistent starting point for the gridded forecast.

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High resolution climate data to help assess the impacts of climate change primarily on agriculture. These open access datasets of climate projections will help researchers make climate change impact assessments.