Abstract's details
Spectral analysis of microwave radiometers brightness temperatures and atmosphere water vapour content.
CoAuthors
Event: 2015 Ocean Surface Topography Science Team Meeting
Session: Instrument Processing: Corrections
Presentation type: Type Oral
Contribution: PDF file
Abstract:
The wet tropospheric correction (WTC) plays a critical role on the altimetry mission budget error due to its large spatial and temporal variability.
Ubelmann et al 2013 has shown the effect of the WTC on the performance of the future SWOT mission using simulated 2D fields obtained from spectral analysis of existing WTC measurement provided by radiometers.
We propose here to compare the power density spectra (PSD) of the water vapour estimated from different microwave radiometers MWR (2-channels radiometers (23.8 GHz, 37GHz) as AltiKa MWR, 3-channels radiometers (18.7GHz, 23.8 GHz, 34 GHz) as Jason-2 AMR, multi-channels radiometers (such as AMSRE) and Numerical Weather Prediction analysis (ECMWF).
The differences in terms of linearity, slopes and the level white noise plateau are discussed and are related to the power density spectra of the observed brightness temperatures at various observation frequencies and different temporal rates. The impacts of the instrument spatial resolution, the interpolation scheme and the retrieval algorithm spectra are discussed as well.
Conclusions are drawn on the architecture and the processing of radiometer measurements on future altimetry missions with larger constraint on spatial resolution and budget errors.
Ubelmann et al 2013 has shown the effect of the WTC on the performance of the future SWOT mission using simulated 2D fields obtained from spectral analysis of existing WTC measurement provided by radiometers.
We propose here to compare the power density spectra (PSD) of the water vapour estimated from different microwave radiometers MWR (2-channels radiometers (23.8 GHz, 37GHz) as AltiKa MWR, 3-channels radiometers (18.7GHz, 23.8 GHz, 34 GHz) as Jason-2 AMR, multi-channels radiometers (such as AMSRE) and Numerical Weather Prediction analysis (ECMWF).
The differences in terms of linearity, slopes and the level white noise plateau are discussed and are related to the power density spectra of the observed brightness temperatures at various observation frequencies and different temporal rates. The impacts of the instrument spatial resolution, the interpolation scheme and the retrieval algorithm spectra are discussed as well.
Conclusions are drawn on the architecture and the processing of radiometer measurements on future altimetry missions with larger constraint on spatial resolution and budget errors.