dorsal/arxiv
View SchemaAnalysis of Water Vapor spatio-temporal structure over the Madrid Area using GPS data
| Authors | Giulio Ruffini, Antonio Rius, Lidia Cucurull, Alex Flores |
|---|---|
| Categories | |
| ArXiv ID | physics/9907006 |
| URL | https://arxiv.org/abs/physics/9907006 |
Abstract
We have analyzed Zenith Wet Delay (ZWD) time series from an experiment over the Madrid (Spain) area obtained from 5 GPS receivers using two different techniques. In the first case a delay correlation analysis of the ZWD time-series has been carried out. We show that for this small network (with a spatial scale of less than 100 km) the correlation between the time series is very strong, and that using windowing techniques a reliable correlation delay time series can be produced for each pair of sites (10 such pairs are available). We use this delay time series together with a frozen flow model to estimate the velocity of a passing front, and compare the results to meteorological data and Numerical Weather Prediction output, showing good agreement. In the second approach, the data is analyzed using Empirical Orthogonal Functions. We demonstrate that the temporally demeaned and normalized analysis yields information about the passing of fronts, while the spatially demeaned data yields orographic information. A common second mode highlights the underlying wave behavior.
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"date_created": "2026-03-02T18:01:24.588000Z",
"date_modified": "2026-03-02T18:01:24.588000Z",
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"abstract": "We have analyzed Zenith Wet Delay (ZWD) time series from an experiment over\nthe Madrid (Spain) area obtained from 5 GPS receivers using two different\ntechniques. In the first case a delay correlation analysis of the ZWD\ntime-series has been carried out. We show that for this small network (with a\nspatial scale of less than 100 km) the correlation between the time series is\nvery strong, and that using windowing techniques a reliable correlation delay\ntime series can be produced for each pair of sites (10 such pairs are\navailable). We use this delay time series together with a frozen flow model to\nestimate the velocity of a passing front, and compare the results to\nmeteorological data and Numerical Weather Prediction output, showing good\nagreement. In the second approach, the data is analyzed using Empirical\nOrthogonal Functions. We demonstrate that the temporally demeaned and\nnormalized analysis yields information about the passing of fronts, while the\nspatially demeaned data yields orographic information. A common second mode\nhighlights the underlying wave behavior.",
"arxiv_id": "physics/9907006",
"authors": [
"Giulio Ruffini",
"Antonio Rius",
"Lidia Cucurull",
"Alex Flores"
],
"categories": [
"physics.ao-ph",
"physics.data-an"
],
"title": "Analysis of Water Vapor spatio-temporal structure over the Madrid Area using GPS data",
"url": "https://arxiv.org/abs/physics/9907006"
},
"schema_id": "dorsal/arxiv",
"source": {
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"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
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