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This listing includes access to the Current Weather API, Daily Forecast API, Hourly Forecast API, and 60 Minute Precipitation Forecast API through AWS DataExchange. Up to 1 Million requests per day.
Materials Project is an open database of computed materials properties aiming to accelerate materials science research. The resources in this OpenData dataset contain the raw, parsed, and build data products.
GEOGLOWS is the Group on Earth Observation's Global Water Sustainability Program. It coordinates efforts from public and private entities to make application ready river data more accessible and sustainably available to underdeveloped regions. The GEOGLOWS Hydrological Model provides a retrospective and daily forecast of global river discharge at 7 million river sub-basins. The stream network is a hydrologically conditioned subset of the TDX-Hydro streams and basins data produced by the United State's National Geospatial Intelligence Agency. The daily forecast provides 3 hourly average discharge in a 51 member ensemble and 15 day lead time derived from the ECMWF Integrated Forecast System (IFS). The retrospective simulation is derived from ERA5 climate reanalysis data and provides daily average streamflow beginning on 1 January 1940. New forecasts are uploaded daily and the retrospective simulation is updated weekly on Sundays to keep the lag time between 5 and 12 days.<br[...]
The worldwide market for Railway Traction Motors is anticipated to reach USD 47.64 billion by 2030. This represents a growth rate of 3.2% till 2030. Traction motors, which are electric motors employed to power the rotation of train wheels, are the driving force behind this market.
A large scale multimodal dataset for Autonomous Trucking. Sensor data was recorded with a heavy truck from MAN equipped with 6 lidars, 6 radars, 4 cameras and a high-precision GNSS. MAN TruckScenes allows the research community to come into contact with truck-specific challenges, such as trailer occlusions, novel sensor perspectives, and terminal environments for the first time. It comprises more than 740 scenes of 20s each within a multitude of different environmental conditions. Bounding boxes are available for 27 object classes, 15 attributes, and a range of more than 230m. The scenes are tagged according to 34 distinct scene tags, and all objects are tracked throughout the scene to promote a wide range of applications.
Global real-time Earth system data deemed by the World Meteorological Organisation (WMO) as essential for provision of services for the protection of life and property and for the well-being of all nations. Data is sourced from all WMO Member countries / territories and retained for 24-hours. Met Office and NOAA operate this Global Cache service curating and publishing the dataset on behalf of WMO.
The C3S seasonal forecast dataset provides global, daily, probabilistic forecasts of the Earth system, enabling users to assess the likelihood of future climate states. These forecasts are particularly valuable for studying slowly evolving climate patterns such as El Niño, La Niña, and the North Atlantic Oscillation (NAO), which can be predicted with greater skill than the chaotic atmosphere. This dataset is derived from the Copernicus Climate Change Service (C3S) archive and includes SEAS5 hindcasts (1981-2016) and forecasts (2017-present) at 1°x1° global resolution. More models from the C3S archive will be updated as they are processed into cloud native format. The planette C3S archive stores this data in cloud native format for easy access and analysis.
Sentinel-2 satellite imagery dataset providing high-resolution optical data for land monitoring, agriculture, and environmental applications.
The Integrated Forecasting System (IFS) is a global forecast model developed by ECMWF. ENS is an ensemble configuration of IFS, containing 51 ensemble members. IFS consists of a numerical model of the Earth system, which includes an atmospheric model at its heart, coupled with models of other Earth system components such as the ocean. The data assimilation system combines the latest weather observations with a recent forecast to obtain the best possible estimate of the current state of the Earth system. These datasets have been translated to cloud-optimized Icechunk Zarr format by dynamical.org. When Icechunk 2.0 is released, these datasets will be updated correspondingly, and updated client libraries will be required for access. To be notified of dataset updates, subscribe to the mailing list. <a href="https:[...]
COG (Cloud-Optimized GeoTIFF) files that together contain the AlphaEarth Foundations annual Satellite Embedding dataset. It contains the annual embeddings for the years from 2018 to 2024, inclusive.
ARCO-OCEAN is an analysis-ready cloud-optimized dataset providing physical properties of the ocean, waves, and sea ice for a period of about 28 years between the 1st of January 1993 and the 30th of June 2021. The dataset includes also atmospheric and hydrological variables that would be needed as boundary conditions and used to drive a numerical simulation. The dataset is the result of collecting, processing, merging and optimizing for the cloud different data sources, all retrospective analyses (reanalyses) or hindcasts of different Earth system components. The dataset has been designed with machine learning in mind, and takes inspiration from similar datasets derived from ERA5.
Iceberg Data Lab's Corporate Biodiversity Footprint (CBF) measures and monitors biodiversity loss across supply chains.
The Climate TRACE coalition has developed and maintains free global hourly Build Margin data, also known as MBERs, that are compliant with the Greenhouse Gas Protocol's Project Protocol electricity sector guidance, Guidelines for Grid-Connected Electricity Projects ("GHGP Guidelines").
Agricultural Testing Market Size, Trends and Insights By Sample (Soil, water, Seed, Plant tissue, Manager, Biosolids), By Application (Quality Assurance, Safety Testing), By Technology (Rapid Technology, Conventional Technology), and By Region - Global Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2022–2030
The projected size of the worldwide Diabetic Food Market is expected to reach USD 19.38 billion, growing at a CAGR of 6.2% until 2030. Diabetic foods are dietary items designed to have reduced carbohydrate and sugar content to help manage glucose levels in individuals with diabetes.
A collection of multi-resolution satellite images from both public and commercial satellites. The dataset is specifically curated for training geospatial foundation models.
The CargoMetrics Maritime Emissions - EU ETS Carbon Tracker reports daily tons of maritime carbon (CO2) emissions that are subject to the European Union Emissions Trading System (EU ETS), the world’s leading greenhouse gas trading scheme. The data are a daily time series published daily during the subscription period.
The National Herbarium of New South Wales is one of the most significant scientific, cultural and historical botanical resources in the Southern hemisphere. The 1.43 million preserved plant specimens have been captured as high-resolution images and the biodiversity metadata associated with each of the images captured in digital form. Botanical specimens date from year 1770 to today, and form voucher collections that document the distribution and diversity of the world's flora through time, particularly that of NSW, Austalia and the Pacific. The data is used in biodiversity assessment, systematic botanical research, ecosystem conservation and policy development. The data is used by scientists, students and the public.
The mnAi dataset includes secured debt by named lender. This unique data set is further segmented by an emissions value assigned by mnAi’s Carbon Emission Variable (CEV).
Geographic (land cover, land elevation, etc.), meteorologic (pluvial, wind, etc.), hydrologic (fluvial, tidal, etc.), hydrodynamic (water surface elevations, flow velocities), and built environment (structures, levees, floodgates, culverts) data used as inputs to and outputs from numerical modeling software for the prediction of flood risk in stochastic and probabilistic frameworks. This data was collected from open sources, such as from the National Oceanographic and Atmospheric Administration (NOAA) or the United States Geological Survey (USGS). The format of these data is modified to suit the needs of the modeling program and software, and then used to predict flooding in Louisiana across a range of scenarios. The modeling software used to predict flooding which utilizes and creates this data is freely available from the United States Army Corps of Engineers Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) and River Analysis System (HEC-RAS). All data i[...]
The datasets include air quality data generated with state-of-the-art HPC software for up-to 84 hours in advance encompassing the states of Connecticut, Delaware, Kentucky, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, Virginia, West Virginia, and the District of Columbia along with the Canadian provinces of Ontario and Quebec. The simulations use a high-resolution grid and NRT satellite data to factor in wildfire emissions.
The Standardised Emissions Plus Data Feed provides investors with historical emissions data for corporate entities. The dataset includes Scope 1, Scope 2 (location and market-based), Scope 3 total, the 15 Scope 3 categories, and the Kyoto gases emissions, providing a comprehensive picture of GHG emissions by companies and the climate impact of their full operations and value chains. The dataset covers a global universe of ~6,500 public companies.
The Tropical Cyclone Precipitation, Infrared, Microwave and Environmental Dataset (TC PRIMED) is a dataset centered around passive microwave observations of global tropical cyclones from low-Earth-orbiting satellites. TC PRIMED is a compilation of tropical cyclone data from various sources, including 1) tropical cyclone information from the National Oceanic and Atmospheric Administration (NOAA) National Weather Service National Hurricane Center (NHC) and Central Pacific Hurricane Center (CPHC) and the U.S. Department of Defense Joint Typhoon Warning Center, 2) low-Earth-orbiting satellite observations and products from the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement (GPM) mission constellation satellites, and 3) environmental fields and diagnostics calculated from the European Center for Medium-Range Weather Forecasts (ECMWF) fifth-generation reanalysis (ERA5).
The Global Forecast System (GFS) is a National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) weather forecast model that generates data for dozens of atmospheric and land-soil variables, including temperatures, winds, precipitation, soil moisture, and atmospheric ozone concentration. The system couples four separate models (atmosphere, ocean model, land/soil model, and sea ice) that work together to depict weather conditions. These datasets have been translated to cloud-optimized Icechunk Zarr format by dynamical.org. When Icechunk 2.0 is released, these datasets will be updated correspondingly, and updated client libraries will be required for access. To be notified of dataset updates, subscribe to the mailing list. <a href="https://dynamical.org/catalog/noaa-gfs-fore[...]
NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC). Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends [...]
A dataset of satellite retrievals of atmospheric methane that extends from 30 April 2018 to present.
An AWS Well-Architected Framework Review with the Data Analytics Lens is a focused evaluation of your data architecture against AWS best practices, delivered by Green Custard, an AWS Advanced Tier Services Partner.
The BTC Data Platform Universal Order Process (DPU) efficiently supports control and measurement data provisioning processes while meeting IT security requirements and ensuring demand-oriented scalability in plant control using smart metering systems. It provides a centralized and secure solution for bidirectional communication between remote control users, distribution system operators (DSOs), suppliers, direct marketers, and metering point operators via the central connection of BDEW WEB APIs. The DPU enables highly automated, 24/7 processes, ensuring compliance with regulatory requirements while maintaining a future-proof system architecture. Additionally, it protects the downstream CLS management or control box admin system from direct third-party connections. The platform's various configurations allow it to adapt to the specific roles and requirements of DSOs and suppliers.
NaDIng is a scalable, AI-driven solution that predicts natural disaster risk for critical infrastructure. Initially focused on flood risk, it integrates weather data, satellite alerts, and official maps to assess exposure at the asset level. When risks are detected, it activates generative AI to recommend action plans. Fully integrated with SAP, NaDIng turns environmental uncertainty into proactive decisions.
CEDA is a multi-regional Environmentally-Extended Input-Output (EEIO) model developed to support a wide range of environmental systems analyses—including corporate carbon accounting and sustainable spend analysis. CEDA provides unparalleled global coverage and granularity, representing 95% of the world's GDP across 148 countries and 400 sectors, enabling robust and geographically comprehensive Scope 3 greenhouse gas (GHG) measurement. Open CEDA is the publicly avaialable version of CEDA, now easy to download and available for free for all use cases. For more information please visit our website at openceda.org CEDA 2024, the latest version of CEDA, uses 2022 as its base year, ensuring that emissions factors and economic data reflect the most recent global economic landscape available. To maintain accuracy and relevance, CEDA is updated annually with the latest data releases. At its core, CEDA connects economic exchanges to GHG emissions by quantifying the life-cycle emissions of [...]