Continuous Subdaily Meteorological Records at Signy Station, the South Orkney Islands 1947 - 1994 ...

The data consists of a CSV file of mean sea level pressure (MSLP, in hPa), 1.25 m temperature (in celsius), 10 m wind speed (in knots), 10 m wind direction (in degree), and relative humidity (in percentage) measured at Signy Station (Latitude 60 degress 43'0"S, Longitude 45 degrees 36'...

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Bibliographic Details
Main Authors: Colwell, Steve, Lu, Hua
Format: Dataset
Language:English
Published: NERC EDS UK Polar Data Centre 2023
Subjects:
Online Access:https://dx.doi.org/10.5285/d74b142c-7981-4a6a-9321-cf904a5668e6
https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/01767
Description
Summary:The data consists of a CSV file of mean sea level pressure (MSLP, in hPa), 1.25 m temperature (in celsius), 10 m wind speed (in knots), 10 m wind direction (in degree), and relative humidity (in percentage) measured at Signy Station (Latitude 60 degress 43'0"S, Longitude 45 degrees 36'0"W) for the period of 1947 - 1994. These data were used by Lu et al. (2023) to study extreme high temperature events in the South Orkney Islands (SOIs). Funding was provided by the Natural Environment Research Council (NERC) to the Atmosphere, Ice and Climate Programme of British Antarctic Survey (BAS), NERC National Capability International grant SURface FluxEs In AnTarctica (NE/X009319/1) and the European Union's Horizon 2020 research and innovation framework programme under Grant agreement no. 101003590 (PolarRES). ... : Signy Station was established by the United Kingdom in 1944 on Signy Island and operated as a year-round meteorological station from 1947 to 1995. A description of the station can be found at https://www.bas.ac.uk/polar-operations/sites-and-facilities/facility/signy/. For the first time, the Signy meteorological record is made available continuously from 1947 to 1994. Paper-based historical weather observations collected at Signy Station during 1947 - 1954 and 1970 - 1981 have recently been digitized by a team at the British Antarctic Survey. The team developed an automated deep-learning Optical Character Recognition (OCR) model which extracts the records from scanned versions of the paper copies automatically. The OCR model output was then put through a series of quality control procedures including human examination of the outputs. Records outside these periods that already existed in electronic form have also been quality controlled ...