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Retrieving temperature, water vapour and surface pressure information from refractive‐index profiles derived by radio occultation: A simulation study
Author(s) -
Healy S. B.,
Eyre J. R.
Publication year - 2000
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.49712656606
Subject(s) - radio occultation , surface pressure , covariance , covariance matrix , hydrostatic equilibrium , refractive index , divergence (linguistics) , mathematics , remote sensing , statistics , meteorology , optics , computer science , physics , global positioning system , geology , telecommunications , linguistics , philosophy , quantum mechanics
A one‐dimensional variational retrieval for the assimilation of refractive‐index profiles derived from radio occultation (RO) measurements has been developed. The method is tested by using simulated data to assess the retrieval accuracy and information content of the measurements, using various realistic estimates for the assumed error distributions. Theoretical retrieval‐error estimates given by a solution covariance matrix are in good qualitative agreement with those derived statistically from the comparison of the solution profiles with the precisely defined ‘true’ values. It is demonstrated that the ‘water vapour ambiguity’ inherent in more conventional RO inversion methods is resolved with this approach. It is found that the solution x 2 values, quantifying the fit to the observed refractivities and a priori profile estimates, are in good agreement with the theoretical distribution, suggesting that they could be used for quality‐control purposes. Furthermore, it is shown that the measurements contain significant surface pressure information. This arises through the hydrostatic relationship, as a result of mapping the state‐vector information on pressure levels to height coordinates. The simulations indicate that the measurements in the tropics contain the greatest surface pressure information, with a reduction of the background error of ∼45%. This new result has significance for the design of future observing systems.