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Title: Daily Temperature and Precipitation Data for 223 Former-USSR Stations (NDP-040)

The stations in this dataset are considered by RIHMI to comprise one of the best networks suitable for temperature and precipitation monitoring over the the former-USSR. Factors involved in choosing these 223 stations included length or record, amount of missing data, and achieving reasonably good geographic coverage. There are indeed many more stations with daily data over this part of the world, and hundreds more station records are available through NOAA's Global Historical Climatology Network - Daily (GHCND) database. The 223 stations comprising this database are included in GHCND, but different data processing, updating, and quality assurance methods/checks mean that the agreement between records will vary depending on the station. The relative quality and accuracy of the common station records in the two databases also cannot be easily assessed. As of this writing, most of the common stations contained in the GHCND have more recent records, but not necessarily records starting as early as the records available here. This database contains four variables: daily mean, minimum, and maximum temperature, and daily total precipitation (liquid equivalent). Temperature were taken three times a day from 1881-1935, four times a day from 1936-65, and eight times a day since 1966. Daily mean temperaturemore » is defined as the average of all observations for each calendar day. Daily maximum/minimum temperatures are derived from maximum/minimum thermometer measurements. See the measurement description file for further details. Daily precipitation totals are also available (to the nearest tenth of a millimeter) for each station. Throughout the record, daily precipitation is defined as the total amount of precipitation recorded during a 24-h period, snowfall being converted to a liquid total by melting the snow in the gauge. From 1936 on, rain gauges were checked several times each day; the cumulative total of all observations during a calendar day was presumably used as the daily total. Again, see the measurement description file for further details. « less
Authors:
 [1] ;  [1] ;  [1]
  1. Russian Research Institute of Hydrometeorological Information-World Data Centre
Publication Date:
Report Number(s):
NDP-040
Product Type:
Dataset
Research Org(s):
Environmental System Science Data Infrastructure for a Virtual Ecosystem; Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Subject:
54 ENVIRONMENTAL SCIENCES
OSTI Identifier:
1394937

Razuvaev, V. N., Apasova, E. B., and Martuganov, R. A. Daily Temperature and Precipitation Data for 223 Former-USSR Stations (NDP-040). United States: N. p., Web. doi:10.3334/CDIAC/cli.ndp040.
Razuvaev, V. N., Apasova, E. B., & Martuganov, R. A. Daily Temperature and Precipitation Data for 223 Former-USSR Stations (NDP-040). United States. doi:10.3334/CDIAC/cli.ndp040.
Razuvaev, V. N., Apasova, E. B., and Martuganov, R. A. 1990. "Daily Temperature and Precipitation Data for 223 Former-USSR Stations (NDP-040)". United States. doi:10.3334/CDIAC/cli.ndp040. https://www.osti.gov/servlets/purl/1394937.
@misc{osti_1394937,
title = {Daily Temperature and Precipitation Data for 223 Former-USSR Stations (NDP-040)},
author = {Razuvaev, V. N. and Apasova, E. B. and Martuganov, R. A.},
abstractNote = {The stations in this dataset are considered by RIHMI to comprise one of the best networks suitable for temperature and precipitation monitoring over the the former-USSR. Factors involved in choosing these 223 stations included length or record, amount of missing data, and achieving reasonably good geographic coverage. There are indeed many more stations with daily data over this part of the world, and hundreds more station records are available through NOAA's Global Historical Climatology Network - Daily (GHCND) database. The 223 stations comprising this database are included in GHCND, but different data processing, updating, and quality assurance methods/checks mean that the agreement between records will vary depending on the station. The relative quality and accuracy of the common station records in the two databases also cannot be easily assessed. As of this writing, most of the common stations contained in the GHCND have more recent records, but not necessarily records starting as early as the records available here. This database contains four variables: daily mean, minimum, and maximum temperature, and daily total precipitation (liquid equivalent). Temperature were taken three times a day from 1881-1935, four times a day from 1936-65, and eight times a day since 1966. Daily mean temperature is defined as the average of all observations for each calendar day. Daily maximum/minimum temperatures are derived from maximum/minimum thermometer measurements. See the measurement description file for further details. Daily precipitation totals are also available (to the nearest tenth of a millimeter) for each station. Throughout the record, daily precipitation is defined as the total amount of precipitation recorded during a 24-h period, snowfall being converted to a liquid total by melting the snow in the gauge. From 1936 on, rain gauges were checked several times each day; the cumulative total of all observations during a calendar day was presumably used as the daily total. Again, see the measurement description file for further details.},
doi = {10.3334/CDIAC/cli.ndp040},
year = {1990},
month = {1} }
  1. The U.S. Department of Energy’s (DOE) Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) is a data archive for Earth and environmental science data. The mission of ESS-DIVE is to preserve, expand access to, and improve usability of critical data generated through DOE-sponsored research of terrestrial and subsurface ecosystems. By making ESS research data easily accessible, ESS-DIVE has the potential to advance the scientific understanding and prediction of hydro-biogeochemical and ecosystem processes that occur from bedrock through soil and vegetation to the atmospheric interface.
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