Title: Surface pressure tide climatologies deduced from a quality-controlled network of barometric observations
Language: English
Authors: Schindelegger, Michael
Ray, Richard D. 
Category: Research Article
Forschungsartikel
Keywords: Tides; Surface pressure; In situ atmospheric observations
Issue Date: 2014
Journal: Monthly weather review
Abstract: 
Global “ground truth” knowledge of solar diurnal S1 and semidiurnal S2 surface pressure tides as furnished by barometric in situ observations represents a valuable standard for wide-ranging geophysical and meteorological applications. This study attempts to aid validations of the air pressure tide signature in current climate or atmospheric analysis models by developing a new global assembly of nearly 6900 mean annual S1 and S2 estimates on the basis of station and marine barometric reports from the International Surface Pressure Databank, version 2 (ISPDv2), for a principal time span of 1990–2010. Previously published tidal compilations have been limited by inadequate spatial coverage or by internal inconsistencies and outliers from suspect tidal analyses; here, these problems are mostly overcome through 1) automated data filtering under ISPDv2’s quality-control framework and 2) a meticulously conducted visual inspection of station harmonic decompositions. The quality of the resulting compilation is sufficient to support global interpolation onto a reasonably fine mesh of 1° horizontal spacing. A multiquadric interpolation algorithm, with parameters fine-tuned by frequency and for land or ocean regions, is employed. Global charts of the gridded surface pressure climatologies are presented, and these are mapped to a wavenumber versus latitude spectrum for comparison with long-term means of S1 and S2 from four present-day atmospheric analysis systems. This cross verification, shown to be feasible even for the minor stationary modes of the tides, reveals a small but probably significant overestimation of up to 18% for peak semidiurnal amplitudes as predicted by global analysis models.
DOI: 10.1175/MWR-D-14-00217.1
Library ID: AC11360617
URN: urn:nbn:at:at-ubtuw:3-2299
ISSN: 1520-0493
Organisation: E120 - Department für Geodäsie und Geoinformation 
Publication Type: Article
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