 |
| Titel |
A Next-Generation Space Geodetic Technique: Profiling of Greenhouse Gases and Climate by Microwave and Infrared-Laser Occultation |
| VerfasserIn |
G. Kirchengast, S. Schweitzer, V. Proschek |
| Konferenz |
EGU General Assembly 2012
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250069734
|
|
|
|
|
|
| Zusammenfassung |
| Since the pioneering GNSS radio occultation (GRO) mission GPS/Met in the mid-1990ties,
and fostered by many missions since then such as CHAMP, Formosat-3/COSMIC and others,
the GRO method was firmly established as a leading space geodetic technique. GRO provides
vital contributions to meteorology and climate applications, like numerical weather prediction
and climate change monitoring, and a range of those are covered in this session.
Building on this success, further advanced techniques for future missions and science
applications emerge beyond GRO. In particular, next-generation occultation between
Low Earth Orbit satellites (LEO-LEO) uses GNSS-type coherent signals beyond
the GRO decimeter waves at centimeter, millimeter, and micrometer wavelengths.
This new technique, termed LEO-LEO microwave and infrared-laser occultation
(LMIO), enables to vastly expand from the GRO refractivity-based sounding of
the thermodynamic structure to a complete set of weather and climate variables,
including thermodynamic ones (pressure, temperature, water vapor), greenhouse gases,
wind speed, and others (Kirchengast and Schweitzer, GRL, 38, L13701, 2011;
www.agu.org/pubs/crossref/2011/2011GL047617.shtml).
LMIO combines microwave occultation signals at cm and mm wavelengths (within 8-25 GHz
and 175-200 GHz) for thermodynamic state profiling with infrared-laser occultation signals
within 2 to 2.5 μm for greenhouse gas and line-of-sight wind profiling; greenhouse
gases include water vapor (H2O), the three key long-lived ones (CO2, CH4, N2O)
and others. We present the fundamentals and discuss the estimated performance of
LMIO-based thermodynamic state and greenhouse gas profiling, including from
quasi-realistic end-to-end performance simulations considering also clouds and
aerosols. To indicate the performance, we found monthly-mean temperature and
greenhouse gas profiles, assuming 30 to 40 native profiles averaged per climatological
“grid cell” per month, accurate to |
|
|
|
|
|
|