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.

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.

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.

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.

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

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.

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.

Data owner is Sachidananda Mishra (sachi.mishra@noaa.gov) and Richard Stumpf at NOAA. This dataset is not publicly accessible because: Data is property of NOAA. It can be accessed through the following means: Sachidananda Mishra (sachi.mishra@noaa.gov) and Richard Stumpf at NOAA. Format: Data is raster format and table format.

This dataset is associated with the following publication: Mishra, S., R. Stumpf, B. Schaeffer, J. Werdell, K. Loftin, and A. Meredith. Evaluation of a satellite-based cyanobacteria bloom detection algorithm using field-measured microcystin data. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 774: 145462, (2021).

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)

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.

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.

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.

NEW GOES-19 Data!! On April 4, 2025 at 1500 UTC, the GOES-19 satellite will be declared the Operational GOES-East satellite. All products and services, including NODD, for GOES-East will transition to GOES-19 data at that time. GOES-19 will operate out of the GOES-East location of 75.2°W starting on April 1, 2025 and through the operational transition. Until the transition time and during the final stretch of Post Launch Product Testing (PLPT), GOES-19 products are considered non-operational regardless of their validation maturity level. Shortly following the transition of GOES-19 to GOES-East, all data distribution from GOES-16 will be turned off. GOES-16 will drift to the storage location at 104.7°W. GOES-19 data should begin flowing again on April 4th once this maneuver is complete.

NEW GOES 16 Reprocess Data!! The reprocessed GOES-16 ABI L1b data mitigates systematic data issues (including data gaps and image artifacts) seen in the Operational products, and improves the stability of both the radiometric and geometric calibration over the course of the entire mission life. These data were produced by recomputing the L1b radiance products from input raw L0 data using improved calibration algorithms and look-up tables, derived from data analysis of the NIST-traceable, on-board sources. In addition, the reprocessed data products contain enhancements to the L1b file format, including limb pixels and pixel timestamps, while maintaining compatibility with the operational products. The datasets currently available span the operational life of GOES-16 ABI, from early 2018 through the end of 2024. The Reprocessed L1b dataset shows improvement over the Operational L1b products but may still contain data gaps or discrepancies. Please provide feedback to Dan Lindsey (dan.lindsey@noaa.gov) and Gary Lin (guoqing.lin-1@nasa.gov). More information can be found in the GOES-R ABI Reprocess User Guide.


NOTICE: As of January 10th 2023, GOES-18 assumed the GOES-West position and all data files are deemed both operational and provisional, so no ‘preliminary, non-operational’ caveat is needed. GOES-17 is now offline, shifted approximately 105 degree West, where it will be in on-orbit storage. GOES-17 data will no longer flow into the GOES-17 bucket. Operational GOES-West products can be found in the GOES-18 bucket.

GOES satellites (GOES-16, GOES-17, GOES-18 & GOES-19) provide continuous weather imagery and monitoring of meteorological and space environment data across North America. GOES satellites provide the kind of continuous monitoring necessary for intensive data analysis. They hover continuously over one position on the surface. The satellites orbit high enough to allow for a full-disc view of the Earth. Because they stay above a fixed spot on the surface, they provide a constant vigil for the atmospheric "triggers" for severe weather conditions such as tornadoes, flash floods, hailstorms, and hurricanes. When these conditions develop, the GOES satellites are able to monitor storm development and track their movements. SUVI products available in both NetCDF and FITS.

This NOAA Climate Data Record (CDR) is a record for the Northern Hemisphere (NH) Snow Cover Extent (SCE) spanning from October 4, 1966 to present, updated monthly after the 10th of each month. Data prior to June 1999 in the NH SCE CDR are based on satellite-derived maps of NH SCE produced weekly by trained NOAA meteorologists. In June 1999 weekly NOAA NH SCE maps ceased production, and were replaced by daily SCE output from the Interactive Multisensor Snow and Ice Mapping System (IMS). The weekly SCE maps are digitized to an 88x88 (cells) Cartesian grid laid over a NH polar stereographic projection. Each grid cell in the NH SCE CDR has a binary value, indicating snow covered or snow free. The NH SCE CDR has been used in international assessments of climate variability and change, and in investigations regarding the role of snow cover in the climate system. Mapping accuracy is such that this product is considered suitable for continental-scale climate studies. The data are updated monthly in netCDF file format with variables including SCE and National Meteorological Center (NMC) grid (88x88 cell) coordinates.

This data set provides a Climate Data Record (CDR) of sea ice concentration from passive microwave data. The CDR algorithm output is a rule-based combination of ice concentration estimates from two well-established algorithms: the NASA Team (NT) algorithm (Cavalieri et al. 1984) and NASA Bootstrap (BT) algorithm (Comiso 1986). The CDR is a consistent, daily and monthly time series of sea ice concentrations from 25 October 1978 through the most recent processing for both the north and south polar regions. All data are on a 25 km x 25 km grid.

Note: A near-real-time version of this data set also exists to fill the gap between the time that this data set is updated through to the present. The data set is called the Near-Real-Time NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration (https://nsidc.org/data/g10016).

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 Paleoceanography. The data include parameters of paleoceanography with a geographic location of Global. The time period coverage is from 100 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 NASA LaRC cloud and clear sky radiation properties dataset is generated using algorithms initially developed for application to TRMM and MODIS imagery within the NASA CERES program. The algorithms have been adapted to operate upon AVHRR, an instrument that has fewer spectral channels than MODIS. This dataset utilizes calibrated AVHRR reflectances from a companion FCDR. Cloud and clear-sky radiation properties are derived globally at the 4 km Global Area Coverage pixel scale during both day and night using this approach. CDR quality variables include: Cloud and clear sky pixel detection (count), Cloud top thermodynamic phase (count), Cloud optical depth (count), Cloud particle effective radius (micrometers), Air pressure at effective cloud top (hPa), Air temperature at effective cloud top (K), and Height at effective cloud top (km). Other Non-CDR Quality Variables include: Air pressure at cloud top (hPa), Air temperature at cloud top (K), Height at cloud top (km), Height at cloud base (km), Air pressure at cloud base (hPa), Overshooting cloud top detection mask (count), Land and sea surface temperature retrieval (K), Shortwave broadband albedo (unit less), Longwave broadband flux (W/m2), Snow and ice cover flag (count), Land and sea surface temperature retrieval quality flag (count), Clear sky pixel classification (count), Cloudy pixel classification (count)

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.

The Snowstorm Database is a collection of over 500 snowstorms dating back to 1900 and updated operationally. Only storms having large areas of heavy snowfall (10-20 inches or greater) are included. The spatial extent includes the contiguous U.S. but the most storms are in the eastern two thirds of the U.S. This is the only comprehensive data set with starting and ending dates along with daily and total storm snowfall for large snowstorms from 1900 to the present. The data is archived in shapefile format, one shapefile per storm. Shapefiles are a non-proprietary spatial format widely used in Geographical Information Systems (GIS). Each shapefile contains daily and storm total snowfall for weather stations that were affected by the snowstorm. The snowfall data comes from the Global Historical Climatological Network - Daily (GHCN-D).

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 Canada. The time period coverage is from 450 to -37 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.