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Development of the Global Mean Sea Level Pressure Data Set GMSLP2

Authors: Basnett, TA; Parker, DE;

Development of the Global Mean Sea Level Pressure Data Set GMSLP2

Abstract

GMSLP2 is a fully global mean sea-level pressure data set. It is a historical, gridded monthly data set covering the period 1871-1994 and the latest version, GMSLP2.1, has been developed by blending a combination of existing gridded mean sea-level pressure analyses with marine and land observations, using Laplacian interpolation techniques. A range of quality-controls was used to remove random and systematic errors from the observations. However, owing to the scarcity of reliable observed data, especially in the earlier decades, it was subsequently necessary to remove biases from the blended analyses in some areas, such as the Southern Ocean. GMSLP2.1 has already been invaluable for atmospheric model validation purposes and in several empirica; studies, such as a joint CSIRO-Meteorological Office (UKMO) Atlas of El Nino Southern Oscillation and climate variability. A key ongoing use is in connection with atmospheric model simulations of recent climate, aimed at detecting climate change and attributing it to human activities. In addition, GMSLP is being used in connection with the 'Changes to the Climate of the UK' project.

Previously curated at: http://cedadocs.ceda.ac.uk/1080/ The publish date on this item was its original completed date. Main files in this record: Development_of_the_Global_Mean_Sea_Level_Pressure_Data_Set_GMSLP2.pdf Item originally deposited with Centre for Environmental Data Analysis (CEDA) document repository by Miss Poppy Townsend. Transferred to CEDA document repository community on Zenodo on 2022-11-24

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https://id.loc.gov/authorities/subjects/sh2018002590.html, data and information

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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