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| Titel |
Regional scale monitoring of atmospheric water vapor content with GNSS infrastructure and numerical model predictions |
| VerfasserIn |
Szabolcs Rózsa, András Zénó Gyöngyösi, Judit Bartholy, Anikó Kern, Tamás Weidinger, Anna Decsi, Ambrus Kenyeres, Ferenc Dombai, József Ádám |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250083667
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| Zusammenfassung |
| Water, which is present in the troposphere in all three phases, has a unique feature among atmospheric components. Besides the formation of clouds and precipitation, it has a key role in atmospheric energy transport and it is the most important greenhouse gas. Due to its temporal and spatial variability, the monitoring of water in the atmosphere requires observations with high temporal and spatial resolution. The water content in the air can be measured directly by radiosondes, in order to monitor the vertical structure of the lower 30-35 km. In addition, remote sensing devices installed on spacecrafts, airframes and the Earth's surface are also available for the measurement of water content. These sensors yield the total water amount of a column of air, the so-called precipitable water (PW) content, in units of kg m-2 or mm. Global Navigation Satellite Systems (GNSS) are capable to monitor various parameters of the atmosphere. With the establishment of the active GNSS network in Hungary, it became feasible to quantify and monitor PW from GNSS observations. The advantage of this solution is the high spatial and temporal resolution of the observations. Modeling of the weather system is performed by the numerical solution of the atmospheric hydro-thermodynamic set of equations. Based on the actual weather as initial condition, the parameters of the expected weather can be estimated. In this study two different meteorological models (WRF and DBCRAS) – run at the Department of Meteorology at Eotvos Lorand University for weather research and forecasting purposes – are compared with the PW estimates provided by the GNSS infrastructure for 7 months in 2011. Deviation between measured data from different sources is near 1 mm in most cases. Forecast PW values show larger deviation from measured data, which results from weather condition dependent forecast errors. |
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