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Title: The ARM Best Estimate Station-based Surface (ARMBESTNS) Data set

The ARM Best Estimate Station-based Surface (ARMBESTNS) data set merges together key surface measurements from the Southern Great Plains (SGP) sites. It is a twin data product of the ARM Best Estimate 2-dimensional Gridded Surface (ARMBE2DGRID) data set. Unlike the 2DGRID data set, the STNS data are reported at the original site locations and show the original information, except for the interpolation over time. Therefore, users have the flexibility to process the data with the approach more suitable for their applications.
Publication Date:
DOE Contract Number:
Product Type:
Research Org(s):
Atmospheric Radiation Measurement (ARM) Archive, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
54 Environmental Sciences; ARMBESTNS
OSTI Identifier:
  1. ARM focuses on obtaining continuous measurements—supplemented by field campaigns—and providing data products that promote the advancement of climate models. ARM data include routine data products, value-added products (VAPs), field campaign data, complementary external data products from collaborating programs, and data contributed by ARM principal investigators for use by the scientific community. Data quality reports, graphical displays of data availability/quality, and data plots are also available from the ARM Data Center. Serving users worldwide, the ARM Data Center collects and archives approximately 20 terabytes of data per month. Datastreams are generally available for download within 48 hours.
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  1. The ARM Best Estimate 2-dimensional Gridded Surface (ARMBE2DGRID) data set merges together key surface measurements at the Southern Great Plains (SGP) sites and interpolates the data to a regular 2D grid to facilitate data application. Data from the original site locations can be found inmore » the ARM Best Estimate Station-based Surface (ARMBESTNS) data set. « less
  2. This NDP presents land-based monthly surface-air-temperature anomalies (departures from a 1951-1970 reference period mean) on a 5° latitude by 10° longitude global grid. Monthly surface-air-temperature anomalies (departures from a 1957-1975 reference period mean) for the Antarctic (grid points from 65°S to 85°S) are presented inmore » a similar way as a separate data set. The data were derived primarily from the World Weather Records and from the archives of the United Kingdom Meteorological Office. This long-term record of temperature anomalies may be used in studies addressing possible greenhouse-gas-induced climate changes. To date, the data have been employed in producing regional, hemispheric, and global time series for determining whether recent (i.e., post-1900) warming trends have taken place. The present updated version of this data set is identical to the earlier version for all records from 1851-1978 except for the addition of the Antarctic surface-air-temperature anomalies beginning in 1957. Beginning with the 1979 data, this package differs from the earlier version in several ways. Erroneous data for some sites have been corrected after a review of the actual station temperature data, and inconsistencies in the representation of missing values have been removed. For some grid locations, data have been added from stations that had not contributed to the original set. Data from satellites have also been used to correct station records where large discrepancies were evident. The present package also extends the record by adding monthly surface-air-temperature anomalies for the Northern (grid points from 85°N to 0°) and Southern (grid points from 5°S to 60°S) Hemispheres for 1985-1990. In addition, this updated package presents the monthly-mean-temperature records for the individual stations that were used to produce the set of gridded anomalies. The periods of record vary by station. Northern Hemisphere data have been corrected for inhomogeneities, while Southern Hemisphere data are presented in uncorrected form. « less
  3. This database contains monthly mean surface temperature and mean sea level pressure data from twenty-nine meteorological stations within the Antarctic region. The first version of this database was compiled at the Climatic Research Unit (CRU) of University of East Anglia, Norwich, United Kingdom. The databasemore » extended through 1988 and was made available in 1989 by the Carbon Dioxide Information Analysis Center (CDIAC) as a Numeric Data Package (NDP), NDP-032. This update of the database includes data through early 1999 for most stations (through 2000 for a few), and also includes all available mean monthly maximum and minimum temperature data. For many stations this means that over 40 years of data are now available, enough for many of the trends associated with recent warming to be more thoroughly examined. Much of the original version of this dataset was obtained from the World Weather Records (WWR) volumes (1951-1970), Monthly Climatic Data for the World (since 1961), and several other sources. Updating the station surface data involved requesting data from countries who have weather stations on Antarctica. Of particular importance within this study are the additional data obtained from Australia, Britain and New Zealand. Recording Antarctic station data is particularly prone to errors. This is mostly due to climatic extremes, the nature of Antarctic science, and the variability of meteorological staff at Antarctic stations (high turnover and sometimes untrained meteorological staff). For this compilation, as many sources as possible were contacted in order to obtain as close to official `source' data as possible. Some error checking has been undertaken and hopefully the final result is as close to a definitive database as possible. This NDP consists of this html documentation file, an ASCII text version of this file, six temperature files (three original CRU files for monthly maximum, monthly minimum, and monthly mean temperature and three equivalent files slightly reformatted at CDIAC), two monthly mean pressure data files (one original CRU file and one slightly reformatted CDIAC version of the file), four graphics files that describe the station network and the nature of temperature and pressure trends, a file summarizing annual and mean-monthly trends in surface temperatures over Antarctica, a file summarizing monthly Antarctic surface temperature anomalies with respect to the period 1961-90, a station inventory file, and 3 FORTRAN and 3 SAS routines for reading the data that may be incorporated into analysis programs that users may devise. These 23 files have a total size of approximately 2 megabytes and are available via the Internet through CDIAC's Web site or anonymous FTP (File Transfer Protocol) server, and, upon request, various magnetic media. « less
  4. This database contains surface synoptic weather reports for the entire globe, gathered from various available data sets. The reports were processed, edited, and rewritten to provide a single dataset of individual observations of clouds, spanning the 57 years 1952-2008 for ship data and the 39more » years 1971-2009 for land station data. In addition to the cloud portion of the synoptic report, each edited report also includes the associated pressure, present weather, wind, air temperature, and dew point (and sea surface temperature over oceans). This data set is called the "Extended Edited Cloud Report Archive" (EECRA). The EECRA is based solely on visual cloud observations from weather stations, reported in the WMO synoptic code (WMO, 1974). Reports must contain cloud-type information to be included in the archive. Past data sources include those from the Fleet Numerical Oceanographic Center (FNOC, 1971-1976) and the National Centers for Environmental Prediction (NCEP, 1977-1996). This update uses data from a new source, the 'Integrated Surface Database' (ISD, 1997-2009; Smith et al., 2011). Our past analyses of the EECRA identified a subset of 5388 weather stations that were determined to produce reliable day and night observations of cloud amount and type. The update contains observations only from this subset of stations. Details concerning processing, previous problems, contents, and comments are available in the archive's original documentation . The EECRA contains about 81 million cloud observations from ships and 380 million from land stations. The data files have been compressed using unix. Unix/linux users can "uncompress" or "gunzip" the files after downloading. If you're interested in the NDP-026C database, then you'll also want to explore its related data products, NDP-026D and NDP-026E. « less
  5. Surface temperatures and thickness-derived temperatures from a 63-station, globally distributed radiosonde network have been used to estimate global, hemispheric, and zonal annual and seasonal temperature deviations. Most of the temperature values used were column-mean temperatures, obtained from the differences in height (thickness) between constant-pressure surfacesmore » at individual radiosonde stations. The pressure-height data before 1980 were obtained from published values in Monthly Climatic Data for the World. Between 1980 and 1990, Angell used data from both the Climatic Data for the World and the Global Telecommunications System (GTS) Network received at the National Meteorological Center. Between 1990 and 1995, the data were obtained only from GTS, and since 1995 the data have been obtained from National Center for Atmospheric Research files. The data are evaluated as deviations from the mean based on the interval 1958-1977. The station deviations have been averaged (with equal weighting) to obtain annual and seasonal temperature deviations for the globe, the Northern and Southern Hemispheres, and the following latitudinal zones: North (60° N-90° N) and South (60° S-90° S) Polar; North (30° N-60° N) and South (30° S-60° S) Temperate; North (10° N-30° N) and South (10° S-30° S) Subtropical; Tropical(30° S-30° N); and Equatorial (10° S-10° N). The seasonal calculations are for the standard meteorological seasons (i.e., winter is defined as December, January, and February; spring is March, April, and May, etc.) and the annual calculations are for December through the following November (i.e., for the four meteorological seasons). For greater details, see Angell and Korshover (1983) and Angell (1988, 1991) « less