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.

This dataset contains daily observations of maximum and minimum temperature, precipitation, snowfall, and snow depth for U.S. Historical Climatology Network observing stations in the contiguous 48 United States. These stations are part of the U.S. Cooperative network, but also have long periods of record.

The United States Historical Climatology Network (USHCN) is a high-quality data set of daily and monthly records of basic meteorological variables from 1218 observing stations across the 48 contiguous United States. Daily data include observations of maximum and minimum temperature, precipitation amount, snowfall amount, and snow depth; monthly data consist of monthly-averaged maximum, minimum, and mean temperature and total monthly precipitation. Most of these stations are U.S. Cooperative Observing Network stations located generally in rural locations, while some are National Weather Service First-Order stations that are often located in more urbanized environments. The USHCN has been developed over the years at the National Oceanic and Atmospheric Administration's (NOAA) National Climatic Data Center (NCDC) to assist in the detection of regional climate change. Furthermore, it has been widely used in analyzing U.S. climte. The period of record varies for each station. USHCN stations were chosen using a number of criteria including length of record, percent of missing data, number of station moves and other station changes that may affect data homogeneity, and resulting network spatial coverage. Collaboration between NCDC and CDIAC on the USHCN project dates to the 1980s (Quinlan et al. 1987). At that time, in response to the need for an accurate, unbiased, modern historical climate record for the United States, the Global Change Research Program of the U.S. Department of Energy and NCDC chose a network of 1219 stations in the contiguous United States that would become a key baseline data set for monitoring U.S. climate. This initial USHCN data set contained monthly data and was made available free of charge from CDIAC. Since then it has been comprehensively updated several times [e.g., Karl et al. (1990) and Easterling et al. (1996)]. The initial USHCN daily data set was made available through CDIAC via Hughes et al. (1992) and contained a 138-station subset of the USHCN. This product was updated by Easterling et al. (1999) and expanded to include 1062 stations. In 2009 the daily USHCN dataset was expanded to include all 1218 stations in the USHCN.

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 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.

This data set contains monthly temperature, precipitation, sea-level pressure, and station-pressure data for thousands of meteorological stations worldwide. The database was compiled from pre-existing national, regional, and global collections of data as part of the Global Historical Climatology Network (GHCN) project, the goal of which is to produce, maintain, and make available a comprehensive global surface baseline climate data set for monitoring climate and detecting climate change. It contains data from roughly 6000 temperature stations, 7500 precipitation stations, 1800 sea level pressure stations, and 1800 station pressure stations. Each station has at least 10 years of data, 40% have more than 50 years of data. Spatial coverage is good over most of the globe, particularly for the United States and Europe. Data gaps are evident over the Amazon rainforest, the Sahara Desert, Greenland, and Antarctica.

Global Historical Climatology Network-hourly (GHCNh) is a multisource collection of weather station (meteorological) observations from the late 18th Century to the present from fixed weather stations over land across the globe. It is replacing the Integrated Surface Dataset (ISD) and will be used to generate the Local Climatological Data and Global Summary of the Day datasets. It is constructed to align with GHCN daily. Version 1 contains approximately 110 separate data sources and will be updated daily using the United States Air Force and NOAA Surface Weather Observations data streams. GHCNh v1 contains the following variables: altimeter; dew_point_temperature; precipitation; pressure_3hr_change; pres_wx_AU1; pres_wx_AU2; pres_wx_AU3; pres_wx_AW1; pres_wx_AW2; pres_wx_AW3; pres_wx_MW1; pres_wx_MW2; pres_wx_MW3; relative_humidity; Remarks; sea_level_pressure; sky_cov_baseht_1; sky_cov_baseht_2; sky_cov_baseht_3; sky_cover_1; sky_cover_2; sky_cover_3; station_level_pressure; dry bulb temperature; visibility; wet_bulb_temperature; wind_direction; wind_gust; wind_speed.

U.S. Historical Climatology Network (USHCN) data are used to quantify national and regional-scale temperature changes in the contiguous United States (CONUS). The dataset provides adjustments for systematic, non-climatic changes that bias temperature trends of monthly temperature records of long-term COOP stations. USHCN is a designated subset of the NOAA Cooperative Observer Program (COOP) Network, with sites selected according to their spatial coverage, record length, data completeness, and historical stability. Version 2.5 was released as a revision to the version 2.0 dataset In October 2012. The processing steps for version 2 and 2.5 are essentially the same, but the version number change reflects modifications to the underlying database as well as coding changes to the pairwise homogenization algorithm (PHA) that improve its overall efficiency. Table 1 (below) lists these modifications. NCEI Technical Reports GHCNM-12-01R (Williams et al., 2012a) and GHCNM-12-02 (Williams et al. 2

Extending through 1994, this data base contains monthly total precipitation and temperature data from 1219 stations in the contiguous U.S. To be included in the Historical Climatology Network (HCN), a station had to be currently active (1994), have at least 80 years of monthly temperature and precipitation data, and have experienced few station changes. These data were derived from a variety of sources including the National Climatic Data Center archives, state climatologists, and published literature. The data base contains several hundred variables, including state number; station number; monthly temperatures (minimum, maximum, and mean); total monthly precipitation; and time of observation. This is probably the best monthly temperature and precipitation data set available for the contiguous U.S. because station moves, instrument changes, urbanization effects, and time-of-observation differences have been considered and, where necessary, the data have been corrected.

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.

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, 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.

Supplementary information dataset for the following article: R. Connolly and M. Connolly (2014). Urbanization bias III. Estimating the extent of bias in the Historical Climatology Network datasets. Open Peer Rev. J., 34 (Clim. Sci.), ver 0.1 (non peer-reviewed draft)

Abstract of article The extent to which two widely-used monthly temperature datasets are affected by urbanization bias was considered. These were the Global Historical Climatology Network (GHCN) and the United States Historical Climatology Network (USHCN). These datasets are currently the main data sources used to construct the various weather station-based global temperature trend estimates. Although the global network nominally contains temperature records for a large number of rural stations, most of these records are quite short, or are missing large periods of data. Only eight of the records with data for at least 95 of the last 100 years are for completely rural stations. In contrast, the U.S. network is a relatively rural dataset, and less than 10% of the stations are highly urbanized. However, urbanization bias is still a significant problem, which seems to have introduced an artificial warming trend into current estimates of U.S. temperature trends. The homogenization adjustments developed by the National Climatic Data Center to reduce the extent of non-climatic biases in the networks were found to be inadequate, inappropriate and problematic for urbanization bias. As a result, the current estimates of the amount of “global warming” since the Industrial Revolution have probably been overestimated.

The U.S. Historical Climatology Network (USHCN) project arose from the need for an accurate, unbiased, and modern historical climate record suitable for detecting and monitoring secular changes in regional climate in the contiguous United States. The initial work of Quinlan et al. (1987) involved the compilation of a database containing monthly temperature and precipitation data from a network of 1219 U.S. stations. The quality of the HCN data was later enhanced with the use of outlier and areal edits, and the data were corrected for time of observation differences, instrument changes, instrument moves, station relocations, and urbanization effects (Karl et al. 1986; Karl and Williams 1987). The HCN has been updated several times since its inception, most recently by Williams et al. (2004). Some of the stations in the HCN are first-order weather stations, but the majority were selected from approximately 5000 U.S. cooperative weather stations.

The data presented in this package are daily observations of maximum and minimum temperature, precipitation amount (liquid equivalent), snowfall amount, and snow depth from 1062 of the 1221 stations comprising the HCN. Data from 1005 of these daily records extend through 2000, while 920 of these extend through 2005. Most station records are essentially complete for at least 50 years; the latest beginning year of record is 1948. Records from 158 stations begin prior to 1900, with that of Charleston, South Carolina beginning the earliest (1871).

References:

Karl, T. R., G. Kukla, and J. Gavin. 1986. Relationship between decreased temperature range and precipitation trends in the United States and Canada, 1941 80. J. Clim. Appl. Meteor. 25:1878-86.

Karl, T. R., and C. N. Williams, Jr. 1987. An approach to adjusting climatological time series for discontinuous inhomogeneities. J. Clim. Appl. Meteor. 26:1744-63.

Quinlan, F. T., T. R. Karl, and C. N. Williams, Jr. 1987. United States Historical Climatology Network (HCN) serial temperature and precipitation data. NDP-019. Carbon Dioxide Information Analysis Center. Oak Ridge National Laboratory, Oak Ridge, Tennessee.

Williams, C. N., R. S. Vose, D. R. Easterling, and M. J. Menne, 2004. United States Historical Climatology Network Daily Temperature, Precipitation, and Snow Data. ORNL/CDIAC-118, NDP-070. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee.

This data set consists of a southern African subset of the Global Historical Climatology Network (GHCN) Version 1 database. All stations with the following bounding coordinates are included in this subset: 5W - 60E and 5N - 35S. There are three files available, one each for precipitation, temperature, and pressure data. Within this subset the oldest data date from 1874 and the most recent from 1990. The GHCN V1 database contains monthly temperature, precipitation, sea-level pressure, and station-pressure data for thousands of meteorological stations worldwide. The database was compiled from pre-existing national, regional, and global collections of data as part of the Global Historical Climatology Network (GHCN) project, the goal of which is to produce, maintain and make available a comprehensive global surface baseline climate data set for monitoring climate and detecting climate change. It contains data from roughly 6000 temperature stations, 7500 precipitation stations, 1800 sea-level pressure stations, and 1800 station-pressure stations. Each station has at least 10 years of data; 40% have more than 50 years of data. Spatial coverage is good over most of the globe, particularly for the United States and Europe. Data gaps are evident over the Amazon rainforest, the Sahara desert, Greenland, and Antarctica. The earliest station data are from 1697; the most recent are from 1990. The database was created from 15 source data sets including: The National Climatic Data Center's (NCDC's) World Weather Records, CAC's Climate Anomaly Monitoring System (CAMS), NCAR's World Monthly Surface Station Climatology, CIRES' (Eischeid/Diaz) Global precipitation data set, P. Jones' Temperature data base for the world, and S. Nicholson's African precipitation database. Quality Control of the database included 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. This detailed analysis has revealed that most stations (95% for temperature and precipitation, 75% for pressure) contain high-quality data. However, gross data-processing errors (e.g., keypunch problems) and discontinuous inhomogeneities (e.g., station relocations and instrumentation changes) do characterize a small number of stations. All major data processing problems have been flagged (or corrected, when possible). Similarly, all major inhomogeneities have been flagged, although no homogeneity corrections were applied. More information can be found at: ftp://daac.ornl.gov/data/safari2k/climate_meteorology/ghcn/comp/ghcn_v1_readme.pdf.

This data set consists of a subset of the Global Historical Climatology Network (GHCN) Version 1 database for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 to 30 degrees W, latitude 25 degrees S to 10 degrees N). There are three files available, one each for precipitation, temperature, and pressure data. Within this subset the oldest data date from 1832 and the most recent from 1990.The GHCN V1 database contains monthly temperature, precipitation, sea-level pressure, and station-pressure data for thousands of meteorological stations worldwide. The database was compiled from pre-existing national, regional, and global collections of data as part of the Global Historical Climatology Network (GHCN) project, the goal of which was to produce, maintain and make available a comprehensive global surface baseline climate data set for monitoring climate and detecting climate change. It contains data from roughly 6000 temperature stations, 7500 precipitation stations, 1800 sea-level pressure stations, and 1800 station-pressure stations. Each station has at least 10 years of data; 40% have more than 50 years of data. Spatial coverage is good over most of the globe, particularly for the United States and Europe. Data gaps are evident over the Amazon rainforest, the Sahara desert, Greenland, and Antarctica. The earliest station data are from 1697; the most recent are from 1990. The database was created from 15 source data sets including:The National Climatic Data Center's (NCDC's) World Weather Records,CAC's Climate Anomaly Monitoring System (CAMS),NCAR's World Monthly Surface Station Climatology,CIRES' (Eischeid/Diaz) Global precipitation data set,P. Jones' Temperature data base for the world, andS. Nicholson's African precipitation database. Quality Control of the GHCN V1 database included 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. This detailed analysis has revealed that most stations (95% for temperature and precipitation, 75% for pressure) contain high-quality data. However, gross data-processing errors (e.g., keypunch problems) and discontinuous inhomogeneities (e.g., station relocations and instrumentation changes) do characterize a small number of stations. All major data processing problems have been flagged (or corrected, when possible). Similarly, all major inhomogeneities have been flagged, although no homogeneity corrections were applied.LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. LBA was a cooperative international research initiative led by Brazil and NASA was a lead sponsor for several experiments. More information about LBA and links to other LBA project sites can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.

This database is a companion to the Historical Climatology Network (HCN) database for the contiguous United States (see NDP019). The database contains monthly temperature (minimum, maximum, and mean) and total monthly precipitation data for 47 Alaskan stations. These data were derived from a variety of sources including the National Climatic Data Center archives, the state climatologist for Alaska, and published literature. The period of record varies by station. The longest record is for the Sitka Magnetic Observatory (1828) and most records extend through 1990. Unlike the HCN database for the contiguous U.S., adjustments have not been made to these climate records for time-of-observation differences, instrument changes, or station moves. The data are in three files [one data file that contains all four climate variables, one station inventory file, and one station history file]. The file sizes range from 3.5 kB to 1.7 MB.

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.

The table States is part of the dataset NOAA Global Historical Climatology Network daily, available at https://redivis.com/datasets/yfsr-31rajeys9. It contains 73 rows across 2 variables.

Contains global weather station locations with data for monthly means from 1981 through 2010 for: Daily Mean Temperature °C Daily Maximum Temperature °C Daily Minimum Temperature °C Precipitation in mm Highest Daily Temperature °C Lowest Daily Temperature °C Additional monthly fields containing the equivalent values in °F and inches are available at the far right of the attribute table. GHCND stations were included if there were at least fifteen average daily values available in each month for all twelve months of the year, and for at least ten years between 1981 and 2010. 3,197 of the 7,480 stations did not collect or lacked sufficient precipitation data. These data are compiled from archived station values which have not undergone rigorous curation, and thus, there may be unexpected values, particularly in the daily extreme high and low fields. Esri is working to further curate this layer and will make updates as improvements are found. If your area of study is within the United States, we recommend using the U.S. Historical Climate - Monthly Averages for GHCN-D Stations 1981 - 2010 layer because the data in that service were compiled from web services produced by the Applied Climate Information System ( ACIS). ACIS staff curate the values for the U.S., including correcting erroneous values, reconciling data from stations that have been moved over their history, etc., thus the data in the U.S. service is of higher quality. Revision History: Initially Published: 6 Feb 2019 Updated: 12 Feb 2019 - Improved initial extraction algorithm to remove stations with extreme values. This included values higher than the highest temperature ever recorded on Earth, or those with mean values that were considerably different than adjacent neighboring stations.Updated: 18 Feb 2019 - Updated after finding an error in initial processing that excluded a 2,870 stations. Updated 16 Apr 2019 - We learned more precise coordinates for station locations were available from the Enhanced Master Station History Report (EMSHR) published by NOAA NCDC. With the publication of this layer the geometry and attributes for 635 of 7,452 stations now have more precise coordinates. The schema was updated to include the NCDC station identifier and elevation fields for feet and meters are also included. A large subset of the EMSHR metadata is available via EMSHR Stations Locations and Metadata 1738 to Present. Cite as:

Esri, 2019: World Historical Climate - Monthly Averages for GHCN-D Stations for 1981 - 2010. ArcGIS Online, Accessed April 2019. https://www.arcgis.com/home/item.html?id=ed59d3b4a8c44100914458dd722f054f Source Data: Station locations compiled from: Initially compiled using station locations from ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/ghcnd-stations.txt Menne, M.J., I. Durre, B. Korzeniewski, S. McNeal, K. Thomas, X. Yin, S. Anthony, R. Ray, R.S. Vose, B.E.Gleason, and T.G. Houston, 2012: Global Historical Climatology Network - Daily (GHCN-Daily), Version 3.24 Amended to use the most recent station locations from Russell S. Vose, Shelley McNeill, Kristy Thomas, Ethan Shepherd (2011): Enhanced Master Station History Report of March 2019. NOAA National Climatic Data Center. Access Date: April 10, 2019 doi:10.7289/V5NV9G8D. Station Monthly Means compiled from Daily Data: ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/ghcnd_all.tar.gz Menne, M.J., I. Durre, B. Korzeniewski, S. McNeal, K. Thomas, X. Yin, S. Anthony, R. Ray, R.S. Vose, B.E.Gleason, and T.G. Houston, 2012: Global Historical Climatology Network - Daily (GHCN-Daily), Version 3.24