Digital Signal Processing Reference
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product (Anthes et al.
2000
). Improvement of the southern hemisphere (SH) 500 hPa
height field after assimilating CHAMP data was also shown (Zou et al., 2004).
The RO soundings provide independent information, moreover, the self-calibrated
measurements can be assimilated without bias correction. As most other satellite
observations require bias correction to the model, RO measurements, therefore,
could be used to anchor the bias correction of radiance measurements (e.g., Healy
2008
).
GNSS RO has quickly evolved from an experimental concept to become a major
component of the global observing system, providing data assimilated without bias
correction by several NWP national agencies worldwide. Soon after the launch of
COSMIC constellation, the European Centre for Medium-Range Weather Forecasts
(ECMWF) and the US National Center for Environmental Prediction (NCEP)
started assimilating real-time COSMIC soundings into their operational models and
immediately demonstrated positive impact in the operational analysis and forecasts
(Cucurull and Derber
2008
; Healy
2008
). Later on, the GRAS and TerraSAR-X
and C/NOFS RO data have also been operational assimilated by many weather
centers (e.g., Luntama et al.
2008
; Cucurull et al. 2010; Poli et al.
2010
). For
example, ECMWF started assimilating GPSRO data operationally on December 12,
2006. Clear improvement in the ECMWF operational short-range forecast in both
temperature and height field at 100 hPa after assimilating COSMIC data is indicated
by the reduced bias when comparing the forecast to the radiosonde temperature at
100 hPa in the southern hemisphere (e.g., Fig.
6.4
, adapted from Healy (
2007
)).
Similar improvements have also been reported by many other operational weather
centers, such as Environmental Canada, Meteo France, UK Met Office, Japan
Meteorological Agency and the Australian forecast system (Poli et al.
2007
; Rennie
2008
; LeMarshall et al.
2010
).
Other than being successfully assimilated into the global models, numerous
regional NWP models (e.g., the Weather Research and Forecasting, WRF, model)
also assimilate RO data to improve forecast. Generally, assimilation of refractivity
has been undertaken using a local observation operator or a nonlocal observation
operator (Huang et al.
2005
; Chen et al.
2009
). Positive impacts on the tropical
cyclone simulations were demonstrated after assimilating RO data through varia-
tional (e.g., 3D-Var or 4D-Var) (Huang et al.
2005
; Chen et al.
2009
) or ensemble
based (Liu et al.
2012
) data assimilation systems.
6.5
Climate Applications
The fundamental RO observable is the phase delay of the GNSS radio signals
(related to the propagation time between satellites). Since the time is calibrated
very precisely by ultra stable atomic clocks, no additional satellite or inter-satellite
calibration is needed for the RO observations. In contrary, passive thermal radiation
measurements require periodic calibration to account for the drift of sensitivity of
the sensors, and thus also inter-satellite calibration. Another important feature of
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