Comparison of measurements made with two different instruments of the same atmospheric vertical profile

Quality quantifier of indirect measurements

A quality quantifier, referred to as measurement quality quantifier (MQQ), is proposed for indirect measurements. It satisfies the property that the MQQ of the data fusion of two or more independent measurements is the sum of the MQQs of the individual measurements and can also be determined in absolute terms for ill-posed problems. It is calculated from the covariance and Jacobian matrices of the observations, but the same result is also obtained using the covariance and averaging kernel matrices of the retrieved quantities. In the case of measurements of a continuous distribution a quantifier that provides the information distribution can be derived from the MQQ. The proposed quantifiers are herewith used for the quality assessment of atmospheric ozone measurements performed by IASI and MIPAS instruments.

Rigorous determination of stratospheric water vapor trends from MIPAS observations

The trend of stratospheric water vapor as a function of latitude is estimated by the MIPAS measurements by means of a new method that uses the measurement space solution. The method uses all the information provided by the observations avoiding the artifacts introduced by the a priori information and by the interpolation to different vertical grids. The analysis provides very precise values of the trends that, however, are limited by a relatively large systematic error induced by the radiometric calibration error of the instrument. The results show in the five years from 2005 to 2009 a dependence on latitude of the stratospheric (from 37 to 53 km) water vapor trend with a positive value of (0.41 ± 0.16)%yr-1 in the northern hemisphere and less than 0.16%yr-1 in the southern hemisphere.

Optimal use of the information provided by indirect measurements of atmospheric vertical profiles

A procedure for the optimal utilization and representation of the information retrieved from atmospheric observations is discussed. We show that the "measurement-space solution" exclusively contains the information present in the observations, but is not suitable for a representation of the retrieved profile in the form of a graph. The new method of the "null-space regularization", which provides in a complement space an external constraint and makes the solution compliant with this representation, is presented. In this way the measurement and the constraint are separately determined and are given in a vertical grid that can be freely chosen as fine as desired. The method is applied to simulated measurements and is used to define a procedure for data fusion.

Optimal interpolation method for intercomparison of atmospheric measurements

Intercomparison of atmospheric measurements is often a difficult task because of the different spatial response functions of the experiments considered. We propose a new method for comparison of two atmospheric profiles characterized by averaging kernels with different vertical resolutions. The method minimizes the smoothing error induced by the differences in the averaging kernels by exploiting an optimal interpolation rule to map one profile into the retrieval grid of the other. Compared with the techniques published so far, this method permits one to retain the vertical resolution of the less-resolved profile involved in the intercomparison.