GHCN

AcronymDefinition
GHCNGlobal Historical Climatology Network
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Sources of Precipitation Data GHCN GHCN FAO GPCC GPCP Total (Adjusted) (Raw) 762 1607 1357 4258 134 8118 Table 4.
Though the temperature and precipitation data from GHCN climate stations is reliable, still there are many new stations being formed at higher elevation by ICIMOD, WAPDA, PMD and multiple German and Italian organizations.
1961-90 2020s 1961-90 2020s Jan 21.5 21.9 44 51 Feb 22.5 22.7 26 38 Mar 20.0 20.8 34 73 Apr 25.5 26.1 48 61 May 26.2 26.3 122 135 Jun 26.5 26.4 154 167 Jul 26.6 27.0 170 135 Aug 26.8 27.2 160 168 Sep 25.7 26.3 311 313 Oct 25.1 25.7 363 397 Nov 23.7 24.3 312 309 Dec 22.2 23.1 110 113 Sources: IPCC DDC database and one of the SRES scenarios, CSIRO/A1a; and NOAA GHCN Monthly database version 2.
Muchos de estos estudios se basan en datos en la GHCN, Global Historical Climatology Network, la compilacion de datos meteorologicos, disponible en Internet, que esta formada por contribuciones voluntarias de todas partes del mundo.
The GHCN precipitation gauges, like all gauges in the American observing system, measure total liquid precipitation (rain plus melted frozen precipitation).
[21] showed a weak 11-year cycle over 1925-1960; however, the 11-year periodical variation is quite normal in this study, which may be attributed to the difference between GHCN version 3 (this represents a change from the prior use of unadjusted version 2 data) and GHCN version 2.
D'Aleo and Watts point out: "Forty percent of GHCN v2 stations have at least one missing month.
For example, GHCN data were understood to have undergone more rigorous quality checks and be better documented than FAO data; GPCC data are estimated to be more accurate than NASA data.
Boulder observations are taken from the corresponding station in the Global Historical Climatology Network (GHCN)-Daily dataset (Menne et al.
Interestingly, beginning in 1990, NOAA, NASA, and the Global Historical Climatology Network (GHCN), managed by the National Climatic Data Center (NCDC), began a massive and radical series of "adjustments" that invariably injected a dramatic warming bias into the temperature data.
[1], the limited spatial resolution of datasets such as NCEP's reanalysis data, ERA40 data, and the Global Historical Climate Network (GHCN) does not allow for accurate representations over coarse terrain.
The operational version of the gauge-based Global Historical Climatology Network (GHCN; Peterson and Vose 1996) dataset is somewhat wetter, with an anomaly of about 40 mm, while a new experimental version of GHCN (with five times as many stations) has an anomaly of about 80 mm (implying 2017 was the wettest year in the historical record).