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| Titel |
Montgomery Potential and Wind Fields on Isentropic Surfaces from GPS Radio Occultation |
| VerfasserIn |
Barbara Scherllin-Pirscher, Andrea Steiner, Gottfried Kirchengast, Stephen Leroy |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250110520
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| Publikation (Nr.) |
 EGU/EGU2015-10523.pdf |
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| Zusammenfassung |
| Atmospheric profiles from Global Positioning System (GPS) radio occultation (RO)
measurements provide precise and accurate information on the thermal structure of the
troposphere and lower stratosphere. Since altitude (and also geopotential height) is based on
accurate knowledge of the position and velocity vectors of the transmitter and receiver
satellites involved, it is possible to obtain highly resolved and accurate vertical information
from RO.
In this study we use observational data from 2007 to 2013 from the RO missions
CHAMP, SAC-C, GRACE-A, and Formosat-3/COSMIC. Using potential temperature as the
vertical coordinate we calculate monthly means of the Montgomery potential on isentropic
surfaces from 300ÂK to 600ÂK (approximately 12 km to 24 km in altitude) with a horizontal
resolution of 5° in latitude and 5° in longitude. Contours of the Montgomery potential on
isentropic surfaces correspond to a stream-function for adiabatic, geostrophic flow.
Subsequently we derive monthly mean geostrophic wind fields (outside the tropics)
from sampling error-corrected fields of the Montgomery potential on isentropic
surfaces.
We find that these climatological RO wind fields clearly capture all of the main wind
features with departures from analysis winds being, in general, smaller than 2Âm s-1.
Larger biases close to the subtropical jet and at high latitudes—biases rarely exceed
10Â%—are caused by the geostrophic approximation. We present monthly mean
wind fields, their annual cycle as well as inter-annual variability related to the El
Niño–Southern Oscillation. This three-dimensional information of high quality from RO
data can subsequently be utilized to investigate atmospheric dynamics close to the
tropopause. |
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