Intercomparison of remote sounding instruments

Abstract

[1] When intercomparing measurements made by remote sounders, it is necessary to make due allowance for the differing characteristics of the observing systems, particularly their averaging kernels and error covariances. We develop the methods required to do this, applicable to any kind of retrieval method, not only to optimal estimators. We show how profiles and derived quantities such as the total column of a constituent may be properly compared, yielding different averaging kernels. We find that the effect of different averaging kernels can be reduced if the retrieval or the derived quantity of one instrument is simulated using the retrieval of the other. We also show how combinations of measured signals can be found, which can be compared directly. To illustrate these methods, we apply them to two real instruments, calculating the expected amplitudes and variabilities of the diagnostics for a comparison of CO measurements made by a ground-based Fourier Transform spectrometer (FTIR) and the ''measurement of pollution in the troposphere'' instrument (MOPITT), which is mounted on the EOS Terra platform. The main conclusions for this case are the following: (1) Direct comparison of retrieved profiles is not satisfactory, because the expected standard deviation of the difference is around half of the expected natural variability of the true atmospheric profiles. (2) Comparison of the MOPITT profile retrieval with a simulation using FTIR is much more useful, though still not ideal, with expected standard deviation of differences of around 20% of the expected natural variability. (3) Direct comparison of total columns gives an expected standard deviation of about 9%, while comparison of MOPITT with a simulation derived from FTIR improved this to 8%. (4) There is only one combination of measured signals that can be usefully compared. The difference is expected to have a standard deviation of about 5.5% of the expected natural variability, which is mostly due to noise.

A method for colocating satellite <i>X</i><sub>CO<sub>2</sub></sub> data to ground-based data and its application to ACOS-GOSAT and TCCON

“…To compare two observations obtained through optimal estimation properly, the retrievals must be computed around a common a priori profile and the averaging kernels must be applied to account for the effect of smoothing (Rodgers and Connor, 2003). A detailed exposition on applying the averaging kernel correction for a ACOS-GOSAT and TCCON comparison is given in Sect.…”

Satellite observation of atmospheric methane: intercomparison between AIRS and GOSAT TANSO-FTS retrievals

“…The information content, which is usually represented as the DOF, is computed as the trace of the averaging kernel matrix (Rodgers and Connor, 2003). Figure 5 shows the variation of DOFs at different latitudes, and on average the DOF of AIRS CH 4 is approximately 1.1, whereas the mean DOF for the GOSAT-TIR retrieval of CH 4 is approximately 0.61.…”

“…Since intercomparison is made between two space-based sensors, it is necessary to take account of the different characteristics of the observing systems, particularly their averaging kernels, which is usually applied to the "truth" based on the following equation (Rodgers and Connor, 2003):…”

“…This calculation is based on the Eq. (25) from Rodgers and Connor (2003). where a 1 is the total column averaging kernel of AIRS CH 4 ; c c is the total column derived from X c ; andĉ 12 is the related total column using convolved GOSAT-TIR profiles.…”

A new Dobson Umkehr ozone profile retrieval method optimising information content and resolution

“…Monthly averaging was performed as the Umkehr and ozonesonde data were not measured at coincident times. To smooth the ozonesonde data to the lower resolution of the Umkehr retrievals, the difference between the monthly averaged ozonesonde data and the a priori is convolved with the monthly averaged Cpair averaging kernels, which is then added to the a priori (Rodgers and Conner, 2003). As ozonesonde data has an altitude limit at around 35 km, the ozonesonde data were combined with ozone information from the vertically resolved ozone database for Umkehr layers 7 and above.…”