In March 2015, data for thirteen Alaskan climate divisions were added to the NClimDiv data set. Data for the new Alaskan climate divisions begin in 1925 through the present and are included in all monthly updates. Alaskan climate data include the following elements for divisional and statewide coverage: average temperature, maximum temperature (highs), minimum temperature (lows), and precipitation. The Alaska NClimDiv data were created and updated using similar methodology as that for the CONUS, but with a different approach to establishing the underlying climatology. The Alaska data are built upon the 1971-2000 PRISM averages whereas the CONUS values utilize a base climatology derived from the NClimGrid data set. In January 2025, the National Centers for Environmental Information (NCEI) began summarizing the State of the Climate for Hawaii. This was made possible through a collaboration between NCEI and the University of Hawaii/Hawaii Climate Data Portal and completes a long-standing gap in NCEI's ability to characterize the State of the Climate for all 50 states. NCEI maintains monthly statewide, divisional, and gridded average temperature, maximum temperatures (highs), minimum temperature (lows) and precipitation data for Hawaii over the period 1991-2025. As of November 2018, NClimDiv includes county data and additional inventory files In March 2015, data for thirteen Alaskan climate divisions were added to the NClimDiv data set. Data for the new Alaskan climate divisions begin in 1925 through the present and are included in all monthly updates. Alaskan climate data include the following elements for divisional and statewide coverage: average temperature, maximum temperature (highs), minimum temperature (lows), and precipitation. The Alaska NClimDiv data were created and updated using similar methodology as that for the CONUS, but with a different approach to establishing the underlying climatology. The Alaska data are built upon the 1971-2000 PRISM averages whereas the CONUS values utilize a base climatology derived from the NClimGrid data set.

As of November 2018, NClimDiv includes county data and additional inventory files.

This dataset replaces the previous Time Bias Corrected Divisional Temperature-Precipitation Drought Index. The new divisional data set (NClimDiv) is based on the Global Historical Climatological Network-Daily (GHCN-D) and makes use of several improvements to the previous data set. For the input data, improvements include additional station networks, quality assurance reviews and temperature bias adjustments. Perhaps the most extensive improvement is to the computational approach, which now employs climatologically aided interpolation. This 5km grid based calculation nCLIMGRID helps to address topographic and network variability. This data set is primarily used by the National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center (NCDC) to issue State of the Climate Reports on a monthly basis. These reports summarize recent temperature and precipitation conditions and long-term trends at a variety of spatial scales, the smallest being the climate division level. Data at the climate division level are aggregated to compute statewide, regional and national snapshots of climate conditions. For CONUS, the period of record is from 1895-present. Derived quantities such as Standardized precipitation Index (SPI), Palmer Drought Indices (PDSI, PHDI, PMDI, and ZNDX) and degree days are also available for the CONUS sites. In March 2015, data for thirteen Alaskan climate divisions were added to the NClimDiv data set. Data for the new Alaskan climate divisions begin in 1925 through the present and are included in all monthly updates. Alaskan climate data include the following elements for divisional and statewide coverage: average temperature, maximum temperature (highs), minimum temperature (lows), and precipitation. The Alaska NClimDiv data were created and updated using similar methodology as that for the CONUS, but with a different approach to establishing the underlying climatology. The Alaska data are built upon the 1971-2000 PRISM averages whereas the CONUS values utilize a base climatology derived from the NClimGrid data set. As of November 2018, NClimDiv includes county data and additional inventory files.

Storm Data is provided by the National Weather Service (NWS) and contain statistics on personal injuries and damage estimates. Storm Data covers the United States of America. The data began as early as 1950 through to the present, updated monthly with up to a 120 day delay possible. NCDC Storm Event database allows users to find various types of storms recorded by county, or use other selection criteria as desired. The data contain a chronological listing, by state, of hurricanes, tornadoes, thunderstorms, hail, floods, drought conditions, lightning, high winds, snow, temperature extremes and other weather phenomena.

The World Ocean Database (WOD) is the largest uniformly formatted, quality-controlled, publicly available historical subsurface ocean profile database. From Captain Cook's second voyage in 1772 to today's automated Argo floats, global aggregation of ocean variable information including temperature, salinity, oxygen, nutrients, and others vs. depth allow for study and understanding of the changing physical, chemical, and to some extent biological state of the World's Oceans. Browse the bucket via the AWS S3 explorer: https://noaa-wod-pds.s3.amazonaws.com/index.html

• Update Frequency: Weekly

Data from this dataset can be downloaded/accessed through this dataset page and Kaggle's API.

Context

Severe weather is defined as a destructive storm or weather. It is usually applied to local, intense, often damaging storms such as thunderstorms, hail storms, and tornadoes, but it can also describe more widespread events such as tropical systems, blizzards, nor'easters, and derechos.

The Severe Weather Data Inventory (SWDI) is an integrated database of severe weather records for the United States. The records in SWDI come from a variety of sources in the NCDC archive. SWDI provides the ability to search through all of these data to find records covering a particular time period and geographic region, and to download the results of your search in a variety of formats. The formats currently supported are Shapefile (for GIS), KMZ (for Google Earth), CSV (comma-separated), and XML.

Content

The current data layers in SWDI are:
- Filtered Storm Cells (Max Reflectivity >= 45 dBZ) from NEXRAD (Level-III Storm Structure Product)
- All Storm Cells from NEXRAD (Level-III Storm Structure Product)
- Filtered Hail Signatures (Max Size > 0 and Probability = 100%) from NEXRAD (Level-III Hail Product)
- All Hail Signatures from NEXRAD (Level-III Hail Product)
- Mesocyclone Signatures from NEXRAD (Level-III Meso Product)
- Digital Mesocyclone Detection Algorithm from NEXRAD (Level-III MDA Product)
- Tornado Signatures from NEXRAD (Level-III TVS Product)
- Preliminary Local Storm Reports from the NOAA National Weather Service
- Lightning Strikes from Vaisala NLDN

Disclaimer:
SWDI provides a uniform way to access data from a variety of sources, but it does not provide any additional quality control beyond the processing which took place when the data were archived. The data sources in SWDI will not provide complete severe weather coverage of a geographic region or time period, due to a number of factors (eg, reports for a location or time period not provided to NOAA). The absence of SWDI data for a particular location and time should not be interpreted as an indication that no severe weather occurred at that time and location. Furthermore, much of the data in SWDI is automatically derived from radar data and represents probable conditions for an event, rather than a confirmed occurrence.

Acknowledgements

Dataset Source: NOAA. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source — http://www.data.gov/privacy-policy#data_policy — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Cover photo by NASA on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

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 CDRs by applying the same methods to present-day and future satellite measurements.

Terrestrial CDRs are composed of sensor data that have been improved and quality controlled over time, together with ancillary calibration data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Other Collections. The data include parameters of database with a geographic location of . The time period coverage is from Unavailable begin date to Unavailable end date in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This NOAA Climate Data Record (CDR) of Zonal Mean Ozone Binary Database of Profiles (BDBP) dataset is a vertically resolved, global, gap-free and zonal mean dataset that was created with a multiple-linear regression model. The dataset has a monthly resolution and spans the period 1979 to 2007. It provides global product in 5 degree zonal bands, and 70 vertical levels of the atmosphere. The regression is based on monthly mean ozone concentrations that were calculated from several different satellite instruments and global ozone soundings. Due to the regression model that was used to create the product, various basis function contributions are provided as unique levels or tiers. To understand the different contributions of basis functions, the data product is provided in five different "Tiers". - Tier 0: raw monthly mean data that was used in the regression model - Tier 1.1: Anthropogenic influences (as determined by the regression model) - Tier 1.2: Natural influences (as determined by the regression model) - Tier 1.3: Natural and volcanic influences (as determined by the regression model) - Tier 1.4: All influences (as determined by the regression model, CDR variable)

The NOAA Monthly U.S. Climate Gridded Dataset (NClimGrid) consists of four climate variables derived from the GHCN-D dataset: maximum temperature, minimum temperature, average temperature and precipitation. Each file provides monthly values in a 5x5 lat/lon grid for the Continental United States. Data is available from 1895 to the present. In March 2015, new Alaska data was included in the nClimDiv dataset. The Alaska nClimDiv data were created and updated using similar methodology as that for the CONUS. It includes maximum temperature, minimum temperature, average temperature and precipitation. In January 2025, the National Centers for Environmental Information (NCEI) began summarizing the State of the Climate for Hawaii. This was made possible through a collaboration between NCEI and the University of Hawaii/Hawaii Climate Data Portal and completes a long-standing gap in NCEI's ability to characterize the State of the Climate for all 50 states. NCEI maintains monthly statewide, divisional, and gridded average temperature, maximum temperatures (highs), minimum temperature (lows) and precipitation data for Hawaii over the period 1991-2025.

Overview

Global Surface Summary of the Day is derived from The Integrated Surface Hourly (ISH) dataset. The ISH dataset includes global data obtained from the USAF Climatology Center, located in the Federal Climate Complex with NCDC. The latest daily summary data are normally available 1-2 days after the date-time of the observations used in the daily summaries.

Content

Over 9000 stations' data are typically available.

The daily elements included in the dataset (as available from each station) are: Mean temperature (.1 Fahrenheit) Mean dew point (.1 Fahrenheit) Mean sea level pressure (.1 mb) Mean station pressure (.1 mb) Mean visibility (.1 miles) Mean wind speed (.1 knots) Maximum sustained wind speed (.1 knots) Maximum wind gust (.1 knots) Maximum temperature (.1 Fahrenheit) Minimum temperature (.1 Fahrenheit) Precipitation amount (.01 inches) Snow depth (.1 inches)

Indicator for occurrence of: Fog, Rain or Drizzle, Snow or Ice Pellets, Hail, Thunder, Tornado/Funnel

Querying BigQuery tables

You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.github_repos.[TABLENAME]. Fork this kernel to get started to learn how to safely manage analyzing large BigQuery datasets.

Acknowledgements

This public dataset was created by the National Oceanic and Atmospheric Administration (NOAA) and includes global data obtained from the USAF Climatology Center. This dataset covers GSOD data between 1929 and present, collected from over 9000 stations. Dataset Source: NOAA

Use: This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source — http://www.data.gov/privacy-policy#data_policy — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Photo by Allan Nygren on Unsplash

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Climate Reconstruction. The data include parameters of reconstructions (precipitation) with a geographic location of North America. The time period coverage is from 11500 to 0 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

The Severe Weather Data Inventory (SWDI) is an integrated database of severe weather records for the United States. SWDI enables a user to search through a variety of source data sets in the NCDC (now NCEI) archive in order to find records covering a particular time period and geographic region, and then to download the results of the search in a variety of formats. The formats currently supported are Shapefile (for GIS), KMZ (for Google Earth), CSV (comma-separated), and XML. The current data layers in SWDI are: Storm Cells from NEXRAD (Level-III Storm Structure Product); Hail Signatures from NEXRAD (Level-III Hail Product); Mesocyclone Signatures from NEXRAD (Level-III Meso Product); Digital Mesocyclone Detection Algorithm from NEXRAD (Level-III MDA Product); Tornado Signature from NEXRAD (Level-III TVS Product); Preliminary Local Storm Reports from the NOAA National Weather Service; Lightning Strikes from Vaisala NLDN.

The NOAA Weather and Climate Toolkit is an application that provides simple visualization and data export of weather and climatological data archived at NCDC. The Toolkit also provides access to weather and climate web services provided from NCDC and other organizations. The Viewer provides tools for displaying custom data overlay, Web Map Services (WMS), animations and basic filters. The export of images and movies is provided in multiple formats. The Data Exporter allows for data export in both vector point/line/polygon and raster grid formats. Current data types supported include: CF-compliant Fridded NetCDF; Generic CF-compliant Irregularly-Spaced/Curvilinear Gridded NetCDF/HDF; GRIB1, GRIB2, GINI, GEMPAK, HDF(CF-compliant) and more gridded formats; GPES Satellite AREA Files; NEXRAD Radar Data(Level-II and Level-III); U.S. Drought Monitor Service from the National Drought Mitigation Center (NDMC); OPeNDAP support for Gridded Datasets

The Temperatures in the Lower Stratosphere (TLS) (AMSU channel 9 and MSU channel 4) CDR is generated by using National Oceanic and Atmospheric Administration (NOAA), National Aeronautics and Space Administration (NASA), and Europe METeorological Operational satellite-A (Metop/A) satellites which have been calibrated using coincident Global Positioning System (GPS) Radio Occultation (RO) temperature profile measurements from Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) and Challenging Mini-satellite Payload (CHAMP), and Gravity Recovery And Climate Experiment (GRACE) from 2001 to the current. The 'adjusted' MSU/AMSU data in the period of 2001 to 2014 were used as reference data to calibrate other overlapped MSU/AMSU data from 1980 to 2001.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Borehole. The data include parameters of borehole with a geographic location of India, Southcentral Asia. The time period coverage is from 450 to -44 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This page provides access to NOAA FIsheries' data and map page. The page hosts databases, maps and GIS datasets, metadata catalog among many other information and products.

NOAA Fisheries' science-based conservation and management of sustainable fisheries, marine mammals, endangered species, and their habitats have become global models for marine stewardship and sustainability.

ANNOUNCEMENTS: [NOS OFS Version Updates and Implementation of Upgraded Oceanographic Forecast Modeling Systems for Lakes Superior and Ontario; Effective October 25, 2022}(https://www.weather.gov/media/notification/pdf2/scn22-91_nos_loofs_lsofs_v3.pdf)

For decades, mariners in the United States have depended on NOAA's Tide Tables for the best estimate of expected water levels. These tables provide accurate predictions of the astronomical tide (i.e., the change in water level due to the gravitational effects of the moon and sun and the rotation of the Earth); however, they cannot predict water-level changes due to wind, atmospheric pressure, and river flow, which are often significant.

The National Ocean Service (NOS) has the mission and mandate to provide guidance and information to support navigation and coastal needs. To support this mission, NOS has been developing and implementing hydrodynamic model-based Operational Forecast Systems.

This forecast guidance provides oceanographic information that helps mariners safely navigate their local waters. This national network of hydrodynamic models provides users with operational nowcast and forecast guidance (out to 48 – 120 hours) on parameters such as water levels, water temperature, salinity, and currents. These forecast systems are implemented in critical ports, harbors, estuaries, Great Lakes and coastal waters of the United States, and form a national backbone of real-time data, tidal predictions, data management and operational modeling.

Nowcasts and forecasts are scientific predictions about the present and future states of water levels (and possibly currents and other relevant oceanographic variables, such as salinity and temperature) in a coastal area. These predictions rely on either observed data or forecasts from a numerical model. A nowcast incorporates recent (and often near real-time) observed meteorological, oceanographic, and/or river flow rate data. A nowcast covers the period from the recent past (e.g., the past few days) to the present, and it can make predictions for locations where observational data are not available. A forecast incorporates meteorological, oceanographic, and/or river flow rate forecasts and makes predictions for times where observational data will not be available. A forecast is usually initiated by the results of a nowcast.

OFS generally runs four times per day (every 6 hours) on NOAA's Weather and Climate Operational Supercomputing Systems (WCOSS) in a standard Coastal Ocean Modeling Framework (COMF) developed by the Center for Operational Oceanographic Products and Services (CO-OPS). COMF is a set of standards and tools for developing and maintaining NOS’s hydrodynamic model–based operational forecast systems. The goal of COMF is to provide a standard and comprehensive software infrastructure to enhance ease of use, performance, portability, and interoperability of NOS’s operational forecast systems.

The National Bathymetric Source (NBS) project creates and maintains high-resolution bathymetry composed of the best available data. This project enables the creation of next-generation nautical charts while also providing support for modeling, industry, science, regulation, and public curiosity. Primary sources of bathymetry include NOAA and U.S. Army Corps of Engineers hydrographic surveys and topographic bathymetric (topo-bathy) lidar (light detection and ranging) data. Data submitted through the NOAA Office of Coast Survey’s external source data process are also included, with gaps in deep water filled through Global Multi-Resolution Topography, a merged model of bathymetry. Different vertical datums and file formats are made available to meet various uses. The BlueTopo folder includes multilayer floating point GeoTIFFs with associated Raster Attribute Tables (RAT) containing elevation, vertical uncertainty, with other quality metrics and source information. These files are arranged in a spatial tiling and resolution scheme corresponding to the Electronic Navigational Chart (ENC) but are not for navigation due to the inclusion of additional non-navigation data and non-navigation vertical datums. For navigational datasets please see the S-102 distribution portal. "nowCOAST" provides public access to BlueTopo through the nowCOAST viewer, web map tile services (WMTS), and links to individual datasets.

NOTE - Upgrade NCEP Global Forecast System to v16.3.0 - Effective November 29, 2022 See notification HERE

The Global Forecast System (GFS) is a weather forecast model produced by the National Centers for Environmental Prediction (NCEP). Dozens of atmospheric and land-soil variables are available through this dataset, from temperatures, winds, and precipitation to soil moisture and atmospheric ozone concentration. The entire globe is covered by the GFS at a base horizontal resolution of 18 miles (28 kilometers) between grid points, which is used by the operational forecasters who predict weather out to 16 days in the future. Horizontal resolution drops to 44 miles (70 kilometers) between grid point for forecasts between one week and two weeks.

The NOAA Global Forecast Systems (GFS) Warm Start Initial Conditions are produced by the National Centers for Environmental Prediction Center (NCEP) to run operational deterministic medium-range numerical weather predictions.
The GFS is built with the GFDL Finite-Volume Cubed-Sphere Dynamical Core (FV3) and the Grid-Point Statistical Interpolation (GSI) data assimilation system.
Please visit the links below in the Documentation section to find more details about the model and the data assimilation systems. The current operational GFS is run at 64 layers in the vertical extending from the surface to the upper stratosphere and on six cubic-sphere tiles at the C768 or 13-km horizontal resolution. A new version of the GFS that has 127 layers extending to the mesopause will be implemented for operation on February 3, 2021. These initial conditions are made available four times per day for running forecasts at the 00Z, 06Z, 12Z and 18Z cycles, respectively. For each cycle, the dataset contains the first guess of the atmosphere states found in the directory ./gdas.yyyymmdd/hh-6/RESTART, which are 6-hour GDAS forecast from the last cycle, and atmospheric analysis increments and surface analysis for the current cycle found in the directory ./gfs.yyyymmdd/hh, which are produced by the data assimilation systems.

S-111 is a data and metadata encoding specification that is part of the S-100 Universal Hydrographic Data Model, an international standard for hydrographic data. This collection of data contains surface water currents forecast guidance from NOAA/NOS Operational Forecast Systems, a set of operational hydrodynamic nowcast and forecast modeling systems, for various U.S. coastal waters and the great lakes. The collection also contains surface current forecast guidance output from the NCEP Global Real-Time Ocean Forecast System (GRTOFS) for some offshore areas. These datasets are encoded as HDF-5 files conforming to the S-111 specification, and are geospatially subset into individual tiles conforming to the NOAA/OCS Nautical Product Tiling Scheme, with filenames indicating the corresponding NOAA Electronic Navigational Chart (ENC) Cell Identifier. A full set of S-111 tiles is created for each new model run cycle, which occurs four times per day for all models except for RTOFS, which updates only once per day. Files are organized using a path naming convention that includes the OFS identifier (e.g. 'cbofs' corresponding with output from the Chesapeake Bay Operational Forecast System) as well as the year, month, day, and hour corresponding with each model run initialization time. Each individual S-111 (HDF-5) file contains all forecast projections from a single model run for that geographic area. In other words, a single S-111 file will contain multiple gridded arrays each containing a forecast valid at a distinct time in the future, out to the forecast horizon of the underlying modeling system. All surface currents forecasts in this collection are computed at a depth of 4.5 meters below water surface, or half the water column depth, whichever is shallower.