the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Aug 2024
Retrievals of water vapour and temperature exploiting the far-infrared: application to aircraft observations in preparation for the FORUM mission
Abstract. We present the extension of the RAL Infrared Microwave Sounding optimal estimation retrieval scheme to include the use of far-infrared channels in preparation for the upcoming Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission. The evolution and evaluation of the extended scheme is performed in two steps. First, clear-sky retrievals of temperature and water vapour are performed on IASI and FORUM simulations. Improvements of 2 % and 0.2 K are observed in the median mid to upper tropospheric retrievals of water vapour and temperature, respectively, using the FORUM configuration, with an increase of ~ 1 degree of freedom for water vapour and temperature. Secondly, radiances observed from an aircraft flight in the upper troposphere are modified to match the FORUM spectral characteristics. Retrievals from these radiances using the modified code show a strong agreement with contemporaneous in-situ measurements of the atmospheric state, reducing the RMSE by 18 % for water vapour from the a-priori, giving confidence in its performance. This tool is now readily available for use on FORUM observations and can be easily adapted to other far and mid-infrared instrument configurations.
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RC1: 'Comment on egusphere-2024-2419', Anonymous Referee #1, 14 Sep 2024
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General comments:
This work by Panditharatne et al. reports on the adaption of the RAL Infrared Microwave Sounding retrieval processor to the evaluation of data from the far-infrared spectral range. The scheme is tested twofold: first by simulating FORUM-like observations and performing test retrievals of water vapour and temperature in comparison to IASI simulations. Second, simultaneous aircraft nadir measurements from two instruments covering the far- and mid-infrared are used as the input to the retrieval scheme. Results are discussed against vertical profiles of temperature and water vapour from dropsondes during the same flight.
This analysis clearly shows the applicability of the adapted retrieval scheme for the analysis of observations in the far-infrared spectrum. A second aim of the paper (I guess) was to show the improvement of using observations in the far-infrared with respect to pure mid-infrared retrievals (e.g. from IASI). However, I am not really convinced about the outcome of the study in this respect. E.g. assumptions on the measurement uncertainty of the two instruments (FORUM and IASI) are rather different with including all kind of instrumental errors for IASI while using only the spectral noise in case of FORUM. Also, the very different horizontal sampling/resolution between the two instruments has not been taken into consideration.
Still, I would support the publication of the manuscript in AMT after revision on basis of the comments and suggestions below.
Specific comments:
l.91-99:
Please explain a bit more about the species included in LBLRTM as well as the spectroscopy used. Has e.g. the N2-continuum at around 100 cm-1 been simulated? Which water-vapour continuum has been applied?
l.91-99:
It would also be important to know about the uncertainty in the following retrievals introduced by the spectroscopic errors (including errors in the continua). Some discussion about this should be included in the discussions.
l.73, ‘Retrieval Framework’:
Please add (e.g. in a Table) all elements and dimensions of the retrieval state vector, as well as their units. Additionally show (e.g. as supplement) the results and covariances of all parameters of the state vector (surface-temperature, surface emissivity).
In addition, information should be provided about the influence of other spectrally interfering trace gases (e.g. ozone) on the retrievals: e.g. which profiles are used and kept fixed (e.g. also for CO2, etc)? Have their uncertainty been considered for the selection of channels? What is the expected uncertainty introduced in the actual retrieval?
l.108:
Does the a-priori covariance of surface emissivity also contain correlations (off-diagonal elements) in spectral space?
l.111: ‘γi’:
I think i should be a subscript to gamma. Is gamma_i decreasing during the iterations?
l.130:
G, K_x, \hat{x} have not been defined. Please do so.
l.135: as you report for the RMSE the logarithm of specific humidity, has this quantity also been used in the retrieval state vector? Otherwise, why not reporting the RSME directly of what is in the state vector?
l.155:
Please explain more in detail which instrumental errors are considered in the S_y of FSI as well as of IASI and how these have been produced? Also mention the horizonal resolution on ground as well as measurement time related to the FSI versus IASI measurements those S_y values are valid for.
l.167:
Matrices of dimension (mxm) and (nxn) cannot be directly multiplied, please correct/modify.
Figure 5:
Are the water vapour biases plotted as the biases of the log()-values or the real wv-values in the retrieval state vector? If only the log(WV) is shown, please show also the ‘native’ ones.
l.227:
As the retrievals are performed with noise-free simulated ‘measured’ spectral radiances, can you explain more clearly what the median retrieval biases are significant for as a retrieval diagnostics?
l.235, ‘the partial derivatives of the forward model output against components of the state vector also contributes to the retrieval uncertainty’:
Why not writing ‘the Jacobian matrix K’? But why is this mentioned here at all? Is K strongly different between the instruments apart from the channel selection and the different spectral regions?
l.274:
It would be good to mention here also the maximum optical path difference of the interferometer for the measurements used here.
Figure 7, ‘taken from ERA5 around the path of each dropsonde’:
Please quantify what ‘around’ means (delta-time, delta-km)?
l.345:
Can you specify which single errors are included in the instrumental ‘Uncertainty’ curve in Fig. 9? Especially outline also possible errors due to spectral as well as radiometric calibration?
l.362-368:
I would be good to see these results as figures (e.g. in the appendix).
l.364, ‘looser’:
Clearer to say ‘smaller’ or do you mean ‘larger’ values?
l.385, ‘AK-treated’:
Please provide the formula used (including averaging kernel and a-priori profile).
Figure 12a:
Please also show the deviations of WV also as percentage as well as absolute (e.g. in a supplement) differences of WV (ppmv) from the ‘Drops_AK’. With always showing the log-scale plots, it is very difficult to follow the argumentation.
l.398, ‘This tightening of the a-priori temperature covariance also leads to an increase in the water vapour AKs’:
Can you make it plausible why this is the case?
l.436, ‘however this remains within the measurement covariance’:
Has the measurement error also been divided by sqrt(n) where n is the number of samples? Otherwise a direct comparison to the measurement error of one observation might be misleading.
Chapter 8 Conclusions:
Please discuss here (or before, e.g. in the introduction) the general differences in the method as well as the results between your analysis of the aircraft measurements and the work by Warwick et al., 2022 (https://doi.org/10.1029/2020JD034229).
l.484, ‘The performance of IMS was first assessed…’:
It is not clear to me what the aim of the paper is. Is it the assessment of the retrieval code or the assessment of the FORUM vs. IASI performance or the analysis of the aircraft observations? On l.63 it is written: ‘To validate this scheme in the far-infrared..’. However, I’m not convinced how retrieval test, with simulated as well as measured data ‘validates’ the processor? Please try to make this a bit clearer in the introduction and even in the title where the retrieval scheme validation is not mentioned.
l.491, ‘Because FORUM has not flown yet these aspects are not possible to quantify’:
However, there are requirement targets/threshold on the instrumental performance (e.g. calibration, etc) which could have gone into this analysis. Please explain why only the noise was used here.
Technical corrections:
l.110 and elsewhere, ‘Levenburg’:
Should be ‘Levenberg’.
Figure 4, caption:
‘degress of fredom’ -> ‘degrees of freedom’
l.257 and elsewhere, ‘8.8km’:
A space should be between number and unit.
l.325:
‘overlayed’ -> ‘overlaid’ (?)
l.341:
‘are’ -> ‘is’
l.383:
‘colocated’ -> ‘collocated’
l.421:
‘Figure 12’ -> ‘Figure 13’
Citation: https://doi.org/10.5194/egusphere-2024-2419-RC1
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