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.

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.

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.

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)

Note: This dataset version has been superseded by a newer version. It is highly recommended that users access the current version. Users should only use this version for special cases, such as reproducing studies that used this version. This NOAA Climate Data Record (CDR) from Colorado State University (CSU) contains brightness temperatures that have been improved and quality-controlled over the observation time period. The temperature data are from the Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) series of passive microwave radiometers carried onboard the Defense Meteorological Satellite Program (DMSP) satellites. This dataset encompasses data from a total of nine satellites including the SSM/I sensors on board DMSP satellites F08, F10, F11, F13, F14, and F15 as well as the SSMIS sensors on board DMSP satellites F16, F17, and F18. The data record covers the time period from July 1987 through the present with a 7 to 10 day latency. The spatial and temporal resolutions of the FCDR files correspond to the original resolution of the source TDR observations. There are roughly 15 orbits per day with a swath width of approximately 1400 km resulting in nearly global daily coverage. The spatial resolution of the data is a function of the sensor/channel and varies from approximately ~50 km for the lowest frequency channels to ~15km for the high-frequency channels. The processing of the CDR from the BASE Temperature Data Record (TDR) (also produced by CSU) includes a rigorous quality control of the original TDR data, updated geolocation information, corrections for known issues/problems, and adjustments for residual intercalibration differences between sensors. The output parameters include the observed brightness temperatures for each of the seven SSM/I channels and 24 SSMIS channels at the original sensor channel resolution along with latitude and longitude for each pixel, time, quality flags, and view angle information. The file format is netCDF-4 with added metadata that follow the Climate and Forecast (CF) Conventions and Attribute Convention for Dataset Discovery (ACDD).

This dataset contains gridded daily Normalized Difference Vegetation Index (NDVI) derived from the NOAA Climate Data Record (CDR) of Visible Infrared Imaging Radiometer Suite (VIIRS) Surface Reflectance. The data record spans from 2014 to 10 days before the present using data from NOAA polar orbiting satellites. The data are projected on a 0.05 degree x 0.05 degree global grid. This dataset is one of the Land Surface CDR products produced by the NASA Goddard Space Flight Center (GSFC) and the University of Maryland (UMD). The dataset is in the netCDF-4 file format following ACDD and CF Conventions. The dataset is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program.

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).

The North American Dataset contains sets of Maximum, Minimum and Average Temperature data and Precipitation data that are either (1) raw (non-adjusted though flagged for possible quality issues), (2) adjusted due to time of observation bias (TOB) or (3) put through the Pairwise Homogenization Algorithm (PHA). These files contain North American stations and its data are measured in hundredths of degrees Celsius (without decimal place) for temperature and tenths of millimeters (without decimal place) for Precipitation. Each file includes the entire available Period of Record.

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.

This data set contains 5 minute resolution surface meteorological data from the NOAA Climate Reference Network in NetCDF format. CRN is a network of over 100 stations located throughout the United States set up to provide long-term observations for climate purposes. These data were quality controlled and provided by NOAA MADIS.

U.S. Daily Surface Data consists of several closely related data sets: DSI-3200, DSI-3202, DSI-3206, and DSI-3210. These are archived at the National Climatic Data Center (NCDC). U.S. Daily Surface Data is sometimes called cooperative data or COOP, named after the cooperative observers that recorded the data. In any one year there are about 8,000 stations operating. Most cooperative observers are state universities, state or federal agencies, or private individuals whose stations are managed and maintained by the National Weather Service. Each cooperative observer station may record as little as one parameter (precipitation), or several parameters. U.S. Daily Surface Data is also called Summary of the Day data. The original data was manuscript records, the earliest of which are from the 1800s. Records for approximately 23,000 stations have been archived from the beginning of record through the present. Official surface weather observation standards can be found in the Federal Meteorological Handbook.

Note: This dataset version has been superseded by a newer version. It is highly recommended that users access the current version. Users should only use this version for special cases, such as reproducing studies that used this version. The NOAA Ocean Surface Bundle (OSB) Climate Data Record (CDR) consist of three parts: sea surface temperature, near-surface atmospheric properties, and heat fluxes. This portion of the OSB CDR is the NOAA Climate Data Record (CDR) of Sea Surface Temperature - WHOI. The SST data are found through modeling the diurnal variability in combination with AVHRR observations of sea surface temperature. The data cover a time period from January 1988 - December 2007 at a 3-hourly, quarter-degree resolution.

The Global Data Assimilation System (GDAS) is the system used by the Global Forecast System (GFS) model to place observations into a gridded model space for the purpose of starting, or initializing, weather forecasts with observed data. GDAS adds the following types of observations to a gridded, 3-D, model space: surface observations, balloon data, wind profiler data, aircraft reports, buoy observations, radar observations, and satellite observations. GDAS data are available as both input observations to GDAS and gridded output fields from GDAS. Gridded GDAS output data can be used to start the GFS model. Due to the diverse nature of the assimilated data types, input data are available in a variety of data formats, primarily Binary Universal Form for the Representation of meteorological data (BUFR) and Institute of Electrical and Electronics Engineers (IEEE) binary. The GDAS output is World Meteorological Organization (WMO) Gridded Binary (GRIB).

This dataset includes five-minute reports with elements for wind speed and direction, visibility, present weather, temperature, dew point temperature, station altimeter, pressure and density altitude, and relative humidity for approximately 900 stations in the U.S., Puerto Rico, the U.S. Virgin Islands, and some Pacific island territories as part of the Automated Surface Observing Systems (ASOS) network. The ASOS Program is a joint effort of the National Weather Service (NWS), the Federal Aviation Administration (FAA), and the Department of Defense (DOD). The ASOS network was designed to support weather forecast activities and aviation operations and, at the same time, support the needs of the meteorological, hydrological, and climatological research communities. The ASOS 5-minute data were collected and processed by the NOAA National Centers for Environmental Information (NCEI).

This Climate Data Record (CDR) contains the daily mean Outgoing Longwave Radiation (OLR) time series in global 1 degree x 1 degree equal-angle gridded maps spanning from January 1, 1979 to December 31, 2013, and continuing daily with a two-day lag. The OLR is estimated directly from the HIRS radiance observations for all sky conditions. The observations from imagers onboard international operational geostationary satellites are incorporated to improve the sampling of the OLR diurnal variation. The Daily OLR CDR is at its initial version 1.2. The data file format is netCDF-4 with CF metadata, and it is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program.

Overview

The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is a global ocean marine meteorological and surface ocean dataset. It is formed by merging many national and international data sources that contain measurements and visual observations from ships (merchant, navy, research), moored and drifting buoys, coastal stations, and other marine and near-surface ocean platforms. Each marine report contains individual observations of meteorological and oceanographic variables, such as sea surface and air temperatures, wind, pressure, humidity, and cloudiness. The coverage is global and sampling density varies depending on date and geographic position relative to shipping routes and ocean observing systems.

Content

The ICOADS dataset contains global marine data from ships (merchant, navy, research) and buoys, each capturing details according to the current weather or ocean conditions (wave height, sea temperature, wind speed, and so on). Each record contains the exact location of the observation which is great for visualizations. The historical depth of the data is quite comprehensive — There are records going back to 1662!

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

Dataset Source: NOAA Category: Meteorological, Climate, Transportation

Citation: National Centers for Environmental Information/NESDIS/NOAA/U.S. Department of Commerce, Research Data Archive/Computational and Information Systems Laboratory/National Center for Atmospheric Research/University Corporation for Atmospheric Research, Earth System Research Laboratory/NOAA/U.S. Department of Commerce, Cooperative Institute for Research in Environmental Sciences/University of Colorado, National Oceanography Centre/Natural Environment Research Council/United Kingdom, Met Office/Ministry of Defence/United Kingdom, Deutscher Wetterdienst (German Meteorological Service)/Germany, Department of Atmospheric Science/University of Washington, and Center for Ocean-Atmospheric Prediction Studies/Florida State University. 2016, updated monthly. International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Release 3, Individual Observations. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory: https://doi.org/10.5065/D6ZS2TR3. Accessed 01 04 2017.

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 Gleb Kozenko on Unsplash

Note: This dataset version has been superseded by a newer version. It is highly recommended that users access the current version. Users should only use this version for special cases, such as reproducing studies that used this version. NOAA Climate Data Record (CDR) of the extended AVHRR Polar Pathfinder (APP-x) cryosphere contains 19 geophysical variables over the Arctic and Antarctic for the period 1982 - present. All of them have undergone various degrees of validation, though not all are considered CDR quality. The variables are (those considered by the developers to be CDR-quality are identified with an asterisk): Surface temperature, all-sky, snow, ice, and land Surface albedo, all-sky Sea ice thickness Surface type Cloud mask Cloud particle thermodynamic phase Cloud optical depth Cloud particle effective radius Cloud temperature Cloud pressure Cloud type Downwelling shortwave radiation at the surface Downwelling longwave radiation at the surface Upwelling shortwave radiation at the surface Upwelling longwave radiation at the surface Upwelling shortwave radiation at the TOA Upwelling longwave radiation at the TOA Shortwave cloud radiative forcing at the surface Longwave cloud radiative forcing at the surface APP-x data products are mapped to a 25 km EASE grid at two local solar times: 04:00 and 14:00 for the Arctic, and 02:00 and 14:00 for the Antarctica. Using local solar time rather than standard UTC times provides better information on diurnal differences at all locations.

The Ocean Heat fluxes Climate Data Record (CDR) is one of three CDRs that make up the NOAA Ocean Surface Bundle (OSB). They can be used to describe essential aspects of the air-sea exchange. This CDR leverages the parameters of surface atmospheric properties and sea surface temperature to calculate the latent and sensible heat fluxes from a neural-network emulator of the TOGA-COARE Bulk Air-Sea Flux Algorithm. The final record is a 3-hourly 0.25-degree resolution grid over the global ice-free oceans from January 1988 to August 2021.

Please note, this dataset has been superseded by a newer version (see below). Users should not use this version except in rare cases (e.g., when reproducing previous studies that used this version).The NOAA Ocean Surface Bundle (OSB) Climate Data Record (CDR) consist of three parts: sea surface temperature, near-surface atmospheric properties, and heat fluxes. This portion of the OSB CDR is the NOAA Climate Data Record (CDR) of Ocean Heat Fluxes. The OSB CDR parameters of near-surface atmospheric and sea surface temperature are used to calculate the latent and sensible heat fluxes from a neural-network emulator of the TOGA-COARE Bulk Air-Sea Flux Algorithm. The data cover a time period from January 1988 - December 2007 at a 3-hourly, quarter-degree resolution.