Retrieval Model
6.6 Error Analysis and Characterisation
Optimal estimation allows a solution to be found that minimizes the differences between the measured and modelled DSCDs, given their errors, the a priori information and its associated errors.
An optimal estimation retrieval is used to obtain the best solution from a set of all possible solutions for the case where the problem is ill posed. The retrieval problem
6.6. Error Analysis and Characterisation 63
here is formally ill posed, as there are more elements in the state vector than there are measurements. There is an infinite set of solutions and the a priori constraint allows a single solution to be determined. The a priori is important to provide a best estimate of components of the state vector for which the measurements provide no information, i.e. in the null space and near-null space of the retrieval problem. The 0◦ profile of BrO retrievals performed here is in the near-null space of the retrieval problem. This is because DSCDs remove almost all information about the 0◦ profile, thus it is not well sampled by the measurements.
6.6.1 Gain Matrix - Contribution Functions
The Gain matrix (Gy) describes how changes in the measurements affect the retrieved state. The contribution functions illustrate how each measurement contributes to the final retrieval. The Gain matrix is calculated from the weighting function and covariance matrices, for its derivation refer to Rodgers(2000).
Gy = δˆx
δy = (KTS−1² K+S−1a )−1KTS−1² (6.6) The contribution functions are extremely complex in this instance as figure 6.3 dis-plays. How each measurement influences the final retrieved state cannot be clearly sep-arated into direct-sun and zenith-sky components using the contribution functions. The averaging kernels discussed in section 6.6.2 address this question more completely.
-4E-008 -2E-008 0 2E-008 4E-008
δx/δy(molecules.cm-3/molecules.cm-2)
0
Direct-sun 87o Profile
-6E-008 -4E-008 -2E-008 0 2E-008 4E-008 6E-008
δx/δy(molecules.cm-3/molecules.cm-2)
0
Direct-sun 84o Profile
-4E-008 0 4E-008 8E-008 1.2E-007
δx/δy (molecules.cm-3/molecules.cm-2)
Direct-sun 75o Profile
-3E-007 -2E-007 -1E-007 0 1E-007
δx/δy (molecules.cm-3/molecules.cm-2)
0
Zenith-sky 75o Profile
-1.6E-007 -1.2E-007 -8E-008 -4E-008 0 4E-008 8E-008
δx/δy (molecules.cm-3/molecules.cm-2)
Zenith-sky 84o Profile
-4E-008 -2E-008 0 2E-008 4E-008 6E-008 8E-008
δx/δy (molecules.cm-3/molecules.cm-2)
Zenith-sky 87o Profile
Figure 6.3: Contribution functions for direct-sun (left panels) and zenith-sky (right panels). The response of the 75◦ SZA state vector profile (top). The 84◦ SZA state vector profile is displayed in the middle and 87◦ SZA state vector profile at the bottom. These contribution functions are calculated for measurements taken on day 254, 2001 at Lauder. The contribution functions illustrate how each measurement contributes to the final retrieved state.
6.6. Error Analysis and Characterisation 65
6.6.2 Averaging Kernel Matrix
Analysis of the smoothing of the true state by the retrieval is essential to understanding what information can be obtained from a set of measurements. The smoothing functions or averaging kernels are vital in the charactization of a retrieval. The averaging kernel matrix (A) describes the sensitivity of the retrieved state (ˆx) to the true state (x). The averaging kernel matrix is calculated from the weighting function and gain matrices.
A= δˆx
δx =GyK= (KTS−1² K+S−1a )−1KTS−1² K (6.7) The rows of A are the averaging kernels and these indicate how the retrieved state rep-resents the true state.
The averaging kernels produced by this retrieval method are not only a function of altitude but also of profile or time (SZA). Each element of the state vector has an averaging kernel that is two-dimensional. So while it is possible to view the averaging kernels in a traditional altitude sense, their variation in the space of profiles (time sense) should also be considered, thus they are best seen as two-dimensional. Contour plots are used to view the averaging kernels and derived quantities such as resolution and area. While contours give the impression of continuity, the values are discrete in both space and time.
Figure 6.4 displays the averaging kernels for the 0 km, 10 km, 20 km, 30 km, and 40 km retrieval points of the 84◦ profile. The black crosses indicate the retrieval points that each of the averaging kernels represent. Ideally the averaging kernel will be focused on this point. The averaging kernels shown in figure 6.4 illustrate clearly how the retrieval is improved by combining measurement geometries. The averaging kernels of the direct-sun only retrieval illustrate how these measurements are sensitive to the lower altitudes.
Conversely, the zenith-sky only retrieval demonstrates this geometry to be more sensitive to the stratosphere. The combination of the two geometries provides enhanced sensitivity over all altitudes.
6.6.3 Area of Averaging Kernels
The area of an averaging kernel gives a qualitative indication of the influence of thea priori on the retrieved state. The area of an averaging kernel is the sum of the elements in that averaging kernel. When the area is approximately unity then most of the information on a spatial scale greater than the width of the averaging kernel is being supplied by the measurements rather than thea priori. When the area is close to zero then the retrieved value has come from the a priori information and the measurements have not added any information.
Figure 6.5 shows the area of the averaging kernels that characterise the direct-sun
123456
-0.045 -0.025 -0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.05 0.055 0.06 0.065 0.07 123456
Profile Index 0 10 20 30 40 50 60
Zenith-sky only averaging kernel - 40 km of the 84o profile Zenith-sky only averaging kernel - 30 km of the 84o profile Zenith-sky only averaging kernel - 20 km of the 84o profile Zenith-sky only averaging kernel - 10 km of the 84o profile Zenith-sky only averaging kernel - 0 km of the 84o profile Combined geometries averaging kernel - 0 km of the 84o profile Combined geometries averaging kernel - 10 km of the 84o profile Combined geometries averaging kernel - 20 km of the 84o profile Combined geometries averaging kernel - 30 km of the 84o profile Combined geometries averaging kernel - 40 km of the 84o profile
Figure6.4:Averagingkernelsinaltitudespace(yaxisinkm)andprofilespace(xaxis)fortheBrOprofiles.Theprofileindexreferstothesolarzenithanglecorrespondingtotheprofile:1=0 ◦,2=75 ◦,3=84 ◦,4=87 ◦,5=92 ◦and6=95 ◦.Theseaveragingkernelsarecalculatedformeasurementsmadeonday254,2001atLauder.Themeasurementrangeforthedirect-sunviewinggeometryis63.2 ◦to87.3 ◦andforthezenith-skyviewinggeometryis62.3 ◦to92.0 ◦.Themiddlepanelsdisplaytheaveragingkernelsforaretrievalusingonlythedirect-sunmeasurementsandthelowerpanelsdisplaytheaveragingkernelsforaretrievalusingonlythezenith-skymeasurements.Theupperpanelsdisplaytheaveragingkernelsforaretrievalthatcombinesboththemeasurementgeometries.Theblackcrossoneachoftheplotsindicatestheretrievalpointthattheaveragingkernelrepresents.Thecontoursthereforedisplayhowthetrueatmosphericprofilesaresmoothedtoobtainthisretrievalpoint.
6.6. Error Analysis and Characterisation 67
1 2 3 4 5 6
Profile Index Area - Zenith-sky only retrieval
0 Area - Direct-sun only retrieval
0 Area - combined geometries retrieval
0
Figure 6.5: The area of the averaging kernels in altitude space (y axis in km) and profile space (x axis) for the BrO profiles. The profile index refers to the solar zenith angle corresponding to the profile:
1=0◦, 2=75◦, 3=84◦, 4=87◦, 5=92◦ and 6=95◦. The area of the averaging kernels is calculated for measurements made on day 254, 2001 at Lauder. The area of the averaging kernels, and is a qualitative measure of how much information on the broad structure is being provided from the measurements rather than thea priori. For the state vector profiles 75◦ and 84◦ the retrieved quantities have come from the measurements, the 87◦ profile illustrates how there is a heavy reliance on thea priori data at 20 km due to the fact that the zenith-sky measurement sensitivity is in the higher stratosphere (above 25 km) and the direct-sun sensitivity is close to the surface.
only, zenith-sky only and combined geometry retrievals. This figure shows the direct-sun measurements contribute to the total column, particularly the tropospheric component.
The zenith-sky measurements contribute to the stratospheric sensitivity and rely entirely on the a priori information for the troposphere. The combination of these geometries provides tropospheric and stratospheric sensitivity for the three profiles 75◦, 84◦, 87◦. Where the area of the averaging kernel is negative, similar to where it is much larger than one the retrieved values are not necessarily a good representation of the true atmosphere.
The area of the averaging kernels for the 84◦ profile between 55-65 km and the 87◦ profile between 30 and 40 km is considerably greater than one and considerably less than one for the 87◦ for the 87◦ at ∼20 km. The negative area in the 87◦ profile case is due to the zenith-sky measurement sensitivity being higher in the stratosphere and the direct-sun measurements sensitivity closest the ground. The enhanced stratospheric area can also be explained by referring to the weighting functions which show maximum peaks at the altitudes of high area.
6.6.4 Resolution
Resolution is a useful quantity in the evaluation of the quality of the retrieved data and an essential criterion for reporting retrieved parameters. Resolution has a number of definitions to describe the ‘width’ of the averaging kernel.
Full width half max of the averaging kernel peak is a commonly used definition, though it leads to overestimation of the resolution when the peak of the averaging kernel is
dis-placed from where it should be. Backus-Gilbert spread is another definition and emphases the negative lobes of the averaging kernels. This method of determining the ‘width’ is more complex in its determination.
A third definition utilizes the reciprocal of the averaging kernel peak. The spatial resolution of a retrieval is in this work complicated by the two-dimensional nature of the state vector. Rather than considering horizontal and vertical resolution separately as some ‘width’ of the averaging kernel, the simpler measure of the reciprocal of the diagonal values of Awas used. The diagonal values of Agive the number of degrees of freedom per state vector element. The reciprocal gives the number of state vector elements required to describe a degree of freedom.
1 2 3 4 5 6
Profile Index Resolution - Zenith-sky only retrieval
0 Resolution - Direct-sun only retrieval
0
Resolution - combined geometries retrieval
0
Figure 6.6: The resolution of the retrieval in altitude space (y axis in km) and profile space (x axis) for the BrO profiles. The profile index refers to the solar zenith angle corresponding to the profile: 1=0◦, 2=75◦, 3=84◦, 4=87◦, 5=92◦ and 6=95◦. The resolution is calculated as the number of state vector elements required per degree of freedom. In the troposphere for the state vector profiles 75◦, 84◦, and 87◦ the resolution is 5-15 km and in the stratosphere it is 40 km for the 75◦ profile and 20 km for the 84◦ and 87◦ profiles.
Figure 6.6 displays the resolution for the retrievals for the direct-sun only, zenith-sky only and the combined geometries. The result that the highest resolution is achieved by combining the measurement geometries is not unexpected given the area of the averaging kernels. A resolution of 5-15 km is achieved in the troposphere for the three retrieved profiles 75◦, 84◦ and 87◦. In the stratosphere the resolution is 40 km for the 75◦ profile and 20 km for the 84◦ and 87◦ profiles. The resolution is poorer in the stratosphere for the 75◦ profile retrieval while the area of the averaging kernel is actually good. Conversely, while the area of the averaging kernel for the stratosphere of the 87◦ profile retrieval shows some reliance on a priori information, the resolution is good. This illustrates that all characterisation details need to be considered to best determine the final retrieved quantities.
6.6. Error Analysis and Characterisation 69
Retrieved Profile 0◦ 75◦ 84◦ 87◦ 92◦ 95◦ Total Information content(bits) 0.03 2.9 4.0 2.3 0.02 0.0 13.5
Degrees of Freedom 0.05 2.1 2.6 2.3 0.04 0.0 7.1
Table 6.1: Information Content (bits) and Degrees of Freedom for signal for the direct-sun and zenith-sky combined geometries retrieval. The retrieval is performed for measurements made on day 254, 2001 at Lauder. Two independent pieces of information can be retrieved from the measurements for each of the retrieved profiles of 75◦,84◦ and 87◦.
6.6.5 Degrees of Freedom and Information Content
The degrees of freedom for signal describe the number of useful independent quantities that can be determined from a set of measurements. The degrees of freedom are evaluated by taking the trace of the averaging kernel matrixA. As described in the previous section each value along the diagonal of A can be viewed as the degrees of freedom per retrieval point.
The information content of the measurements can be thought of as a measure of the factor by which knowledge is improved by making the measurement. It can be thought of as a multivariate generalization of the scalar concept of signal-to-noise ratio for the retrieval. Shannon’s definition of information content is the reduction of entropy (or uncertainty) in the state that is achieved by making the measurement:
H= 1
2log2|Sˆ−1Sa|=−1
2log2|I−A| (6.8)
whereSˆis the retrieval covariance (see next section) and the units of Hare bits. Two bits of information means that the volume of the entropy in the state space has been reduced by a factor of four in making the measurement. Iis the identity matrix.
The information content and degrees of freedom for signal are displayed in table 6.1 for measurements taken on day 254, 2001 at Lauder. There are two pieces of independent information for the three retrieved profiles 75◦, 84◦ and 87◦. These details combined with the characterisation of the retrieval obtained from the area of the averaging kernels and the resolution provide a good basis for determining what should be reported from the retrieval. A tropospheric and stratospheric column for the retrieved profiles 75◦, 84◦ and 87◦ can be determined for this retrieval.
6.6.6 Retrieval Error Covariances
The error covariance of the retrieval Sˆ is the summation of the smoothing covariance Ss and retrieval noise covariance Sm:
ˆS= (KTS−1² K+S−1a )−1 (6.9)
Ss= (A−In)Sa(A−In)T (6.10)
Sm =GyS²GTy (6.11)
The covariance due to each forward model parameter (Sf) is a useful error term to evaluate. This covariance provides a quantitative evaluation of the error that a forward model parameter produces in the final retrieved quantity. When this error is too large, consideration should be given to retrieving the forward model parameter. Sf is evaluated as:
Sf =GyKbSbKTbGTy (6.12) The forward model parameter covariance converts the errors in the space of the forward model parameters into the state space. This gives a quantification for the error relative to other errors arising in the retrieval, such as smoothing and retrieval noise.