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. The online data files begin with 1929 and are at the time of this writing at the Version 8 software level. 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 Cloud Global summary of day data for 18 surface meteorological elements are derived from the synoptic/hourly observations contained in USAF DATSAV3 Surface data and Federal Climate Complex Integrated Surface Hourly (ISH). Historical data are generally available for 1929 to the present, with data from 1973 to the present being the most complete. For some periods, one or more countries' data may not be available due to data restrictions or communications problems. In deriving the summary of day data, a minimum of 4 observations for the day must be present (allows for stations which report 4 synoptic observations/day). Since the data are converted to constant units (e.g, knots), slight rounding error from the originally reported values may occur (e.g, 9.9 instead of 10.0). The mean daily values described below are based on the hours of operation for the station. For some stations/countries, the visibility will sometimes 'cluster' around a value (such as 10 miles) due to the practice of not reporting visibilities greater than certain distances. The daily extremes and totals--maximum wind gust, precipitation amount, and snow depth--will only appear if the station reports the data sufficiently to provide a valid value. Therefore, these three elements will appear less frequently than other values. Also, these elements are derived from the stations' reports during the day, and may comprise a 24-hour period which includes a portion of the previous day. The data are reported and summarized based on Greenwich Mean Time (GMT, 0000Z - 2359Z) since the original synoptic/hourly data are reported and based on GMT.

Hourly Precipitation Data (HPD) is digital data set DSI-3240, archived at the National Climatic Data Center (NCDC). The primary source of data for this file is approximately 5,500 US National Weather Service (NWS), Federal Aviation Administration (FAA), and cooperative observer stations in the United States of America, Puerto Rico, the US Virgin Islands, and various Pacific Islands. The earliest data dates vary considerably by state and region: Maine, Pennsylvania, and Texas have data since 1900. The western Pacific region that includes Guam, American Samoa, Marshall Islands, Micronesia, and Palau have data since 1978. Other states and regions have earliest dates between those extremes. The latest data in all states and regions is from the present day. The major parameter in DSI-3240 is precipitation amounts, which are measurements of hourly or daily precipitation accumulation. Accumulation was for longer periods of time if for any reason the rain gauge was out of service or no observer was present. DSI 3240_01 contains data grouped by state; DSI 3240_02 contains data grouped by year.

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 Version 7 NOAA Fundamental Climate Data Record (CDR) from Remote Sensing Systems (RSS) contains brightness temperatures that have been inter-calibrated and homogenized 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. These satellite sensors measure the natural microwave emission coming from the Earth’s surface in the spectral band from 19 to 85 GHz. This dataset encompasses data from a total of seven 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 satellite F17. The data record covers the time period from July 1987 through the present with a one month latency. The spatial and temporal resolutions of the CDR files correspond to the original resolution of the source SSMI(S) 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 approximately 15km for the high-frequency channels. 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 information, 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). There are three major changes in the Version 7 processing: (1) the water vapor continuum absorption model was re-derived, (2) the clear-sky bias in cloud water was removed and the data format for cloud water was changed, and (3) the beamfilling correction in the rain algorithm was modified. Relative to Version 6, Version 7 has: (1) increased vapor values in the range of 50-60 mm by 1%, (2) increased vapor values above 60 mm by 2-3%, (3) cloud data changed to the range of cloud water values: -0.05 to 2.45 mm (cloud data format has changed), and (4) increased the global mean rain rates by about 16% (mostly due to changes in the extratropical values).

• 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.

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 Integrated Surface Database (ISD) consists of global hourly and synoptic observations compiled from numerous sources into a gzipped fixed width format. ISD was developed as a joint activity within Asheville's Federal Climate Complex. The database includes over 35,000 stations worldwide, with some having data as far back as 1901, though the data show a substantial increase in volume in the 1940s and again in the early 1970s. Currently, there are over 14,000 "active" stations updated daily in the database. The total uncompressed data volume is around 600 gigabytes; however, it continues to grow as more data are added. ISD includes numerous parameters such as wind speed and direction, wind gust, temperature, dew point, cloud data, sea level pressure, altimeter setting, station pressure, present weather, visibility, precipitation amounts for various time periods, snow depth, and various other elements as observed by each station.

The Passive Microwave Sea Ice Concentration Climate Data Record (CDR) dataset is generated using daily gridded brightness temperatures from the Defense Meteorological Satellite Program (DMSP) series of Special Sensor Microwave Imager (SSM/I) passive microwave radiometers onboard F-8, F-11 and F-13, and from the Special Sensor Microwave Imager/Sounder (SSMIS) data onboard F-17. The sea ice concentrations are an estimate of the fraction of ocean area covered by sea ice for both the north and south Polar Regions. The daily product is produced by combining concentration estimates created using two algorithms developed at the NASA Goddard Space Flight Center (GSFC) that are processed and combined at NSIDC using brightness temperature data from Remote Sensing Systems, Inc. (RSS). The data are gridded on the NSIDC polar stereographic grid with 25 x 25 km grid cells and are available in netCDF file format. The monthly averaged data have the same spatial resolution and format. Improvements since Version 1 include: 1) an extended data record from 2007 to present; 2) using SSMIS data from F-17; 3) a new snow melt variable; 4) netCDF metadata improvements; and 5) updated documentation and source code.

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 GFS data files stored here can be immediately used for OAR/ARL’s NOAA-EPA Atmosphere-Chemistry Coupler Cloud (NACC-Cloud) tool, and are in a Network Common Data Form (netCDF), which is a very common format used across the scientific community. These particular GFS files contain a comprehensive number of global atmosphere/land variables at a relatively high spatiotemporal resolution (approximately 13x13 km horizontal, vertical resolution of 127 levels, and hourly), are not only necessary for the NACC-Cloud tool to adequately drive community air quality applications (e.g., U.S. EPA’s Community Multiscale Air Quality model; https://www.epa.gov/cmaq), but can be very useful for a myriad of other applications in the Earth system modeling communities (e.g., atmosphere, hydrosphere, pedosphere, etc.). While many other data file and record formats are indeed available for Earth system and climate research (e.g., GRIB, HDF, GeoTIFF), the netCDF files here are advantageous to the larger community because of the comprehensive, high spatiotemporal information they contain, and because they are more scalable, appendable, shareable, self-describing, and community-friendly (i.e., many tools available to the community of users). Out of the four operational GFS forecast cycles per day (at 00Z, 06Z, 12Z and 18Z) this particular netCDF dataset is updated daily (/inputs/yyyymmdd/) for the 12Z cycle and includes 24-hr output for both 2D (gfs.t12z.sfcf$0hh.nc) and 3D variables (gfs.t12z.atmf$0hh.nc).

Also available are netCDF formatted Global Land Surface Datasets (GLSDs) developed by Hung et al. (2024). The GLSDs are based on numerous satellite products, and have been gridded to match the GFS spatial resolution (~13x13 km). These GLSDs contain vegetation canopy data (e.g., land surface type, vegetation clumping index, leaf area index, vegetative canopy height, and green vegetation fraction) that are supplemental to and can be combined with the GFS meteorological netCDF data for various applications, including NOAA-ARL's canopy-app. The canopy data variables are climatological, based on satellite data from the year 2020, combined with GFS meteorology for the year 2022, and are created at a daily temporal resolution (/inputs/geo-files/gfs.canopy.t12z.2022mmdd.sfcf000.global.nc)

The Climate Forecast System (CFS) is a model representing the global interaction between Earth's oceans, land, and atmosphere. Produced by several dozen scientists under guidance from the National Centers for Environmental Prediction (NCEP), this model offers hourly data with a horizontal resolution down to one-half of a degree (approximately 56 km) around Earth for many variables. CFS uses the latest scientific approaches for taking in, or assimilating, observations from data sources including surface observations, upper air balloon observations, aircraft observations, and satellite observations.
Please note that the data in this bucket are the CFSv2 Operational Forecasts. To obtain other CFSv2 products such as the Operational Analysis, please visit our website.

Context

Weather is the state of the atmosphere, describing for example the degree to which it is hot or cold, wet or dry, calm or stormy, clear or cloudy. Source: https://en.wikipedia.org/wiki/Weather

Content

NOAA’s Global Historical Climatology Network (GHCN) is an integrated database of climate summaries from land surface stations across the globe that have been subjected to a common suite of quality assurance reviews. Two GHCN datasets are available in BigQuery, the GHCN-D (daily) and the GHCN-M (monthly). The data included in the GHCN datasets are obtained from more than 20 sources, including some data from every year since 1763.

For a complete description of data variables available in this dataset, see NOAA’s readme.txt: https://www1.ncdc.noaa.gov/pub/data/ghcn/daily/readme.txt

Update Frequency: daily

Fork this kernel to get started with this dataset.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:ghcn_d

https://cloud.google.com/bigquery/public-data/noaa-ghcn

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.

Banner Photo by Max LaRochelle from Unplash.

Inspiration

Find weather stations close to a specific location?

Daily rainfall amounts at specific station?

Pulling daily min/max temperature (in Celsius) and rainfall (in mm) for the past 14 days?

The Mean Layer Temperature - NOAA CDR V5.0 is a monthly global dataset with 2.5°×2.5° grid resolution covering the period from November 1978 to present. The dataset measures mean layer atmospheric temperatures from the lower-troposphere to the lower-stratosphere. The dataset was inter-calibrated and merged from three generations of microwave sounders, MSU, AMSU-A, and ATMS, with 16 polar-orbiting satellites including TIROS-N, NOAA-6, NOAA-7, NOAA-8, NOAA-9, NOAA-10, NOAA-11, NOAA-12, NOAA-14, NOAA-15, NOAA-18, NOAA-19, MetOp-A, Aqua, SNPP, and NOAA-20. The dataset includes temperature mid-troposphere (TMT, MSU channel 2 merged with AMSU-A channel 5 and ATMS channel 6), temperature upper-troposphere (TUT, MSU channel 3 merged with AMSU-A channel 7 and ATMS channel 8), temperature lower-stratosphere (TLS, MSU channel 4 merged with AMSU-A channel 9 and ATMS channel 10), and temperature lower-troposphere (TLT, derived from combinations of TMT, TUT, and TLS). TLT, TMT, TUT, and TLS measure layer temperatures peaking roughly at 3km, 5km, 10km, and 17km, respectively, above the Earth's surface. Features in the dataset development include a use of backward merging approach, development of an observation- and semi-physically-based algorithm for diurnal drift adjustment, and removal of spurious calibration drifting errors in NOAA-15, NOAA-14, NOAA-12, and NOAA-11 through recalibration. Satellite microwave sounding observations in stable sun-synchronous orbits (Aqua, MetOp-A, SNPP, NOAA-20) were used as a reference in the backward merging process. Bias corrections and satellite recalibration have resulted in inter-consistent CDR records for reliable climate change investigation.

The purpose of this dataset is to record weather to help people get quick access to climate data. Additionally, this dataset is useful for background information or looking at yearly differences.

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.

The U.S. Historical Climatology Network Monthly Data, Version 2.5 consists of precipitation and temperature data "corrected" for changes in station location, instrumentation, and observing practices. The vast majority of stations are from the NOAA Cooperative Observer Program (COOP) Network. Stations have been selected according to coverage, length of data record and completeness, and historical stability. Data includes sets of Maximum, Minimum and Average Temperature 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). The data also is archived with station information and source code for reading 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)

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 - 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.

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.

The NOAA Cooperative Observer Program (COOP) 15-Minute Precipitation Data consists of quality controlled precipitation amounts, which are measurements of 15 minute accumulation of precipitation, including rain and snow for approximately 2,000 observing stations around the country, and several U.S. territories in the Caribbean and Pacific operated or managed by the NOAA National Weather Service (NWS). Stations are primary, secondary, or cooperative observer sites that have the capability to measure precipitation at 15 minute intervals. This dataset contains 15-minute precipitation data (reported 4 times per hour, if precipitation occurred) for U.S. stations along with selected non-U.S. stations in U.S. territories and associated nations. It includes major city locations and many small town locations. Daily total precipitation is also included as part of the data record. The dataset period of record is from May 1970 to December 2013. The dataset is archived by the NOAA National Centers for Environmental Information (NCEI).