**Please note, the temperature portion of this dataset has been superseded by a newer version. Users should not use this version except in rare cases (e.g., when reproducing previous studies that used this version). The precipitation subset of this dataset is still the latest version available.** The Global Historical Climatology Network Monthly (GHCN-M) Version 2 dataset created by the NCDC contains historical temperature, precipitation, and pressure data for thousands of land stations worldwide. The period of record varies from station to station, with several thousand extending back to 1950 and several hundred being updated monthly. Both historical and near-real-time GHCN-M data undergo rigorous quality assurance reviews. These reviews include pre-processing checks on source data, time series checks that identify spurious changes in the mean and variance, spatial comparisons that verify the accuracy of the climatological mean and the seasonal cycle, and neighbor checks that identify outliers from both a temporal and a spatial perspective. Only one file for the temperature data is available from the archive (file is for period of record ending in 2011), but precipitation data has been archived daily since 2012.

**Please note, GHCN-Monthly provides climatological observations for four elements; monthly mean maximum temperature, minimum temperature, mean temperature, and monthly total precipitation. Precipitation are available in version 2, monthly mean maximum and minimum temperature in version 3, and monthly mean temperature is also now available in the Version 4 BETA release. Users of monthly mean temperature should use the most recently available fully operational version except in some cases (e.g., when reproducing previous studies that used a previous version).** Since the early 1990s the Global Historical Climatology Network-Monthly (GHCN-M) dataset has been an internationally recognized source of data for the study of observed variability and change in land surface air temperature. It provides monthly mean temperature data for 7280 stations from 226 countries and territories, ongoing monthly updates of more than 2000 stations to support monitoring of current and evolving climate conditions, and homogeneity adjustments to remove non-climatic influences that can bias the observed temperature record. The release of version 3 monthly mean temperature data in 2011 introduced a number of improvements and changes from the previous release that included consolidating "duplicate" series, updating records from recent decades, and the use of new approaches to homogenization and quality assurance.

**Please note, GHCN-Monthly provides climatological observations for four elements; monthly mean maximum temperature, minimum temperature, mean temperature, and monthly total precipitation. Precipitation are available in version 2, monthly mean maximum and minimum temperature in version 3, and monthly mean temperature is also now available in the Version 4 BETA release. Users of monthly mean temperature should use the most recently available fully operational version except in some cases (e.g., when reproducing previous studies that used a previous version).** Since the early 1990s the Global Historical Climatology Network-Monthly (GHCN-M) dataset has been an internationally recognized source of data for the study of observed variability and change in land surface air temperature. It provides monthly mean temperature data for 7280 stations from 226 countries and territories, ongoing monthly updates of more than 2000 stations to support monitoring of current and evolving climate conditions, and homogeneity adjustments to remove non-climatic influences that can bias the observed temperature record. The release of version 3 monthly mean temperature data in 2011 introduced a number of improvements and changes from the previous release that included consolidating "duplicate" series, updating records from recent decades, and the use of new approaches to homogenization and quality assurance.

**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 Global Historical Climatology Network (GHCN) Version 1 is a comprehensive, global, surface, baseline, climate data set designed for monitoring and detecting climate change. Comprised of surface station observations of temperature, precipitation, and pressure, all GHCN data are monthly. GHCN was produced jointly by the NCDC, Arizona State University, and the Carbon Dioxide Information Analysis Center (CDIAC) at Oak Ridge National Laboratory (ORNL). GHCN version 1 was released in August of 1992 and has data from ~6,000 Temperature stations ~7,500 Precipitation stations ~2,000 Pressure stations The earliest station data was from 1697. The most recent is from 1990. Version 1 was created from 15 source data sets. Quality Control includes visual inspection of graphs of all station time series, tests for precipitation digitized 6 months out of phase, tests for different stations having identical data, and other tests.

**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 Global Historical Climatology Network (GHCN) Version 1 is a comprehensive, global, surface, baseline, climate data set designed for monitoring and detecting climate change. Comprised of surface station observations of temperature, precipitation, and pressure, all GHCN data are monthly. GHCN was produced jointly by the NCDC, Arizona State University, and the Carbon Dioxide Information Analysis Center (CDIAC) at Oak Ridge National Laboratory (ORNL). GHCN version 1 was released in August of 1992 and has data from ~6,000 Temperature stations ~7,500 Precipitation stations ~2,000 Pressure stations The earliest station data was from 1697. The most recent is from 1990. Version 1 was created from 15 source data sets. Quality Control includes visual inspection of graphs of all station time series, tests for precipitation digitized 6 months out of phase, tests for different stations having identical data, and other tests.

The GHCN-Monthly Temperature Version 4 dataset consists of monthly mean temperature (both raw and bias corrected data), monthly mean maximum, and minimum temperature. GHCN-M is the core global land surface air temperature dataset used for climate monitoring and assessment activities. GHCN-M version 4 contains monthly mean temperature for over 25,000 stations across the globe and brings consistency with temperature observations found in the GHCN-Daily dataset.

The Global Historical Climatology Network - Daily (GHCN-Daily/GHCNd) dataset integrates daily climate observations from approximately 30 different data sources. Version 3 was released in September 2012 with the addition of data from two additional station networks. Changes to the processing system associated with the version 3 release also allowed for updates to occur 7 days a week rather than only on most weekdays. Version 3 contains station-based measurements from well over 90,000 land-based stations worldwide, about two thirds of which are for precipitation measurement only. Other meteorological elements include, but are not limited to, daily maximum and minimum temperature, temperature at the time of observation, snowfall and snow depth. Over 25,000 stations are regularly updated with observations from within roughly the last month. The dataset is also routinely reconstructed (usually every week) from its roughly 30 data sources to ensure that GHCNd is generally in sync with its growing list of constituent sources. During this process, quality assurance checks are applied to the full dataset. Where possible, GHCNd station data are also updated daily from a variety of data streams. Station values for each daily update also undergo a suite of quality checks.

The Global Historical Climatology Network - Daily (GHCN-Daily/GHCNd) dataset integrates daily climate observations from approximately 30 different data sources. Version 3 was released in September 2012 with the addition of data from two additional station networks. Changes to the processing system associated with the version 3 release also allowed for updates to occur 7 days a week rather than only on most weekdays. Version 3 contains station-based measurements from well over 90,000 land-based stations worldwide, about two thirds of which are for precipitation measurement only. Other meteorological elements include, but are not limited to, daily maximum and minimum temperature, temperature at the time of observation, snowfall and snow depth. Over 25,000 stations are regularly updated with observations from within roughly the last month. The dataset is also routinely reconstructed (usually every week) from its roughly 30 data sources to ensure that GHCNd is generally in sync with its growing list of constituent sources. During this process, quality assurance checks are applied to the full dataset. Where possible, GHCNd station data are also updated daily from a variety of data streams. Station values for each daily update also undergo a suite of quality checks.

**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 Global Historical Climatology Network - Daily (GHCN-Daily) dataset addresses the need for historical daily records over global land areas. Like its monthly counterpart (GHCN-Monthly), GHCN-Daily is a composite of climate records from numerous sources that were merged and then subjected to a suite of quality assurance reviews. The meteorological elements measured for the data set include, but are not limited to, daily maximum and minimum temperature, temperature at the time of observation, precipitation (i.e., rainfall and snow water equivalent), snowfall and snow depth. GHCN-Daily serves as the official archive for daily data from the Global Climate Observing System (GCOS) Surface Network (GSN) and is particularly well suited for monitoring and assessment activities related to the frequency and magnitude of extremes. Sources for the GHCN-Daily data set include, but are not limited, to U.S. Cooperative Summary of the Day, U.S. Fort data, U.S. Climate Reference Network, Community Collaborative Rain, Hail and Snow Network, and numerous international sources. The dataset contains measurements from over 75,000 stations worldwide,about two thirds of which are for precipitation measurement only. Approximately 8500 are regularly updated with observations from within the last month. While most of these sites report precipitation, daily maximum and minimum temperatures are available at more than 25,000 of them, and over 24,000 contain records of snowfall and/or snow depth. The process of integrating data from multiple sources into the GHCN-Daily dataset takes place in three steps: screening the source data for stations whose identity is unknown or questionable; classifying each station in a source dataset either as one that is already represented in GHCN-Daily or as a new site; and mingling the data from the different sources. The first two of these steps are performed whenever a new source dataset or additional stations become available, while the actual mingling of data is part of the automated processing that creates GHCN-Daily on a regular basis. GHCN-Daily data are subject to a suite of quality assurance checks. The checks consist of several types of carefully evaluated tests that detect duplicated data, climatological outliers, and various inconsistencies (internal, temporal, and spatial). Manual review of random samples of flagged values was used to set the threshold for each procedure such that the tests false-positive rate is minimized. In addition, the tests are performed in a deliberate sequence in an effort to enhance the performance of the later checks by detecting errors with the checks applied earlier in the sequence.

**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 Global Historical Climatology Network - Daily (GHCN-Daily) dataset addresses the need for historical daily records over global land areas. Like its monthly counterpart (GHCN-Monthly), GHCN-Daily is a composite of climate records from numerous sources that were merged and then subjected to a suite of quality assurance reviews. The meteorological elements measured for the data set include, but are not limited to, daily maximum and minimum temperature, temperature at the time of observation, precipitation (i.e., rainfall and snow water equivalent), snowfall and snow depth. GHCN-Daily serves as the official archive for daily data from the Global Climate Observing System (GCOS) Surface Network (GSN) and is particularly well suited for monitoring and assessment activities related to the frequency and magnitude of extremes. Sources for the GHCN-Daily data set include, but are not limited, to U.S. Cooperative Summary of the Day, U.S. Fort data, U.S. Climate Reference Network, Community Collaborative Rain, Hail and Snow Network, and numerous international sources. The dataset contains measurements from over 75,000 stations worldwide,about two thirds of which are for precipitation measurement only. Approximately 8500 are regularly updated with observations from within the last month. While most of these sites report precipitation, daily maximum and minimum temperatures are available at more than 25,000 of them, and over 24,000 contain records of snowfall and/or snow depth. The process of integrating data from multiple sources into the GHCN-Daily dataset takes place in three steps: screening the source data for stations whose identity is unknown or questionable; classifying each station in a source dataset either as one that is already represented in GHCN-Daily or as a new site; and mingling the data from the different sources. The first two of these steps are performed whenever a new source dataset or additional stations become available, while the actual mingling of data is part of the automated processing that creates GHCN-Daily on a regular basis. GHCN-Daily data are subject to a suite of quality assurance checks. The checks consist of several types of carefully evaluated tests that detect duplicated data, climatological outliers, and various inconsistencies (internal, temporal, and spatial). Manual review of random samples of flagged values was used to set the threshold for each procedure such that the tests false-positive rate is minimized. In addition, the tests are performed in a deliberate sequence in an effort to enhance the performance of the later checks by detecting errors with the checks applied earlier in the sequence.