Assimilation of ATMS at ECMWF: NOAA-20 data quality assessment and correlated errors
In November 2017 NOAA’s newest operational meteorological satellite, NOAA-20, was launched which carries an ATMS instrument onboard. Short-range NWP forecast model fields provide a very accurate and stable reference for observational data to be compared against. A radiative transfer model is used to transform the model fields into observation space which can then be directly compared to the observed quantities. The data quality of the NOAA-20 ATMS will be assessed in this way and assimilation experiments will be run to evaluate the impact of this new sensor on NWP forecast and analysis accuracy.
The Suomi-NPP ATMS temperature sounding channels exhibit stronger inter-channel error correlations than the corresponding channels on the AMSU-A instrument due to 1/f gain fluctuations in the low-noise amplifier. This effect causes the observation errors to become correlated along scanlines which can be seen as a striped pattern in first guess departure maps. Following the existing methodology which has been used for hyperspectral IR sounders the error covariance matrix is diagnosed for Suomi-NPP ATMS using a posteriori methods and the impact of using this matrix will be assessed by running assimilation experiments.
Mr. Peter Weston ECMWF