include only information about the cloud altitude from active
measurements in the radiative transfer calculations. The syn-
ergy between the lidar and the TIR radiometer measurements
established in this paper allows us to account for the profile
of IWC in the radiative transfer model. Furthermore, the ex-
tinction of aerosols that may be present in the atmosphere
is included in the TIR forward model although further in-
formation on the aerosol type is required. In this study, the
aerosol optical properties were fixed to a predefined aerosol
model and an improvement of our method would be to better
characterize the properties of the aerosols that are actually
present during the measurement. It is worth noting that the
high vertical resolution of the radiative transfer calculations
in the TIR is possible thanks to the numerical efficiency of
the radiative transfer model LIDORT discussed in Sect. 4.1,
which allows us to obtain the radiances and Jacobians for
different atmospheric parameters from a single simulation.

The results for the case study discussed in Sect. 4.2 show,
for certain periods, a quite good agreement of the retrieved
lidar ratios from our synergy algorithm with the literature.
When the cloud is optically very thin, the signal in the TIR
radiometer measurements is very small, resulting in a large
uncertainty in the retrieval, which seems to be rather logi-
cal. However, it is important to keep in mind that the results
depend on several factors. All retrievals shown in this study
were performed for a multiple-scattering factor of η = 0.75
for ice clouds, and the backscatter-to-extinction ratio for
aerosols was fixed to the value for an urban water-soluble
aerosol from the OPAC database. Changing those values may
change the retrievals, and further sensitivity studies with our
algorithm are necessary to evaluate the effects of (1) a vary-
ing multiple-scattering factor and (2) using other aerosol
models.

Furthermore, when regarding ground-based TIR radiome-
ter measurements, a good characterization of the surround-
ing atmosphere, especially the water vapor profile, is cru-
cial since the TIR radiances are very sensitive to water va-
por, which is spatially and temporally highly variable. Hence,
the ECMWF reanalysis profiles used in this study, which
are available for four time steps at 00:00, 06:00, 12:00 and
18:00 UTC and have a spatial resolution of 1°, may not be
accurate enough to characterize the local water vapor profile
at our measurement site during the measurement. It is cer-
tain that a better characterization of the water vapor profile,
e.g., from microwave radiometer measurements, would help
to reduce the uncertainties in our retrievals.

Finally, the quality of the measured TIR radiances plays an
important role. For the case study presented here, the temper-
ature correction of the sensitivity of the instrument results in
a quite large uncertainty because of a large temperature dif-
ference between the temperatures during the measurement
and the calibration. It was shown in Sect. 3.3.2 that it was
not possible to simulate the clear-sky radiances measured
with channel C09. Hence, this channel was not included in
the analysis. This might be due to a bad characterization of

the spectral response function of the instrument as mentioned
above and/or to an insufficient temperature correction. Thus,
another improvement of our method would be to isolate the
instrument from atmospheric temperature influences.

Nevertheless, the first results obtained from this algorithm
are promising and we showed that our method allows us to
converge at the same time towards the measurements of two
very different instruments. However, these results have to be
confirmed in future studies for other measurement periods
and measurement sites.

***Data availability.*** Data used in this paper are available upon re-
quest to the corresponding author.

***Author contributions.*** FH, LCL, FP, and GB conceived the method, developed the retrieval algorithm and discussed the results. FH and LCL analyzed the data and prepared the figures. FH wrote the paper. BD conducted the calibration of the TIR radiometer. TP processed the lidar data. All co-authors reviewed the paper.

***Competing interests.*** The authors declare that they have no conflict of interest.

***Acknowledgements.*** The authors thank the Région Hauts-de-France, the Ministère de l'Enseignement Supérieur et de la Recherche (CPER Climibio) and the European Fund for Regional Economic Development for their financial support. The authors thank the CaPPA project (Chemical and Physical Properties of the Atmosphere) funded by the French National Research Agency (ANR) through the PIA (Programme d'Investissement d'Avenir) under contract ANR-11-LABX-0005-01 and by the Regional Council "Hauts-de-France" and the European Funds for Regional Economic Development (FEDER). The ACTRIS-FR research infrastructure is acknowledged for financial support.

Edited by: Alexander Kokhanovsky

Reviewed by: two anonymous referees

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Saito, M., Iwabuchi, H., Yang, P., Tang, G., King, M. D., and Sekiguchi, M.: Ice particle morphology and microphysical properties of cirrus clouds inferred from combined CALIOP-IIR measurements, J. Geophys. Res.-Atmos., 122, 4440–4462, https://doi.org/10.1002/2016JD026080, 2017.

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L'Ecuyer, T., Haynes, J., Lebsock, M., Suzuki, K., Waliser, D., Wu, D., Kay, J., Gettelman, A., Wang, Z., and Marc-hand, R.: CloudSat mission: Performance and early science after the first year of operation, J. Geophys. Res., 113, D00A18, https://doi.org/10.1029/2008JD009982, 2008.

Strapp, J. W., Albers, F., Reuter, A., Korolev, A. V., Maixner, U., Rashke, E., and Vukovic, Z.: Laboratory measurements of the response of a PMS OAP-2DC, J. Atmos. Ocean. Tech., 18, 1150–1170, https://doi.org/10.1175/1520-0426(2001)018<1150:LMOTRO>2.0.CO;2, 2001.

Stubenrauch, C. J., Rossow, W. B., Kinne, S., Ackerman, S., Cesana, G., Chepfer, H., Girolamo, L. D., Getzewich, B., Guignard, A., Heidinger, A., Maddux, B. C., Menzel, W. P., Minnis, P., Pearl, C., Platnick, S., Poulsen, C., Riedi, J., Sun-Mack, S., Walther, A., Winker, D., Zeng, S., and Zhao, G.: Assessment of global cloud datasets from satellites: Project and database initiated by the GEWEX radiation panel, B. Amer. Meteorol. Soc., 94, 1031–1049, https://doi.org/10.1175/BAMS-D-12-00117.1, 2013.

Turner, D. D. and Eloranta, E. W.: Validating mixed-phase cloud optical depth retrieved from infrared observations with high spectral resolution lidar, IEEE Geosci. Remote S., 5, 285–288, https://doi.org/10.1109/LGRS.2008.915940, 2008.

Vidot, J., Baran, A. J., and Brunel, P.: A new ice cloud parameterization for infrared radiative transfer simulation of cloudy radiances: Evaluation and optimization with IIR observations and ice cloud profile retrieval products, J. Geophys. Res.-Atmos., 120, 6937–6951, https://doi.org/10.1002/2015JD023462, 2015.

Winker, D. M., Pelon, J. R., and McCormick, M. P.: The CALIPSO mission: spaceborne lidar for observation of aerosols and clouds, Proc. SPIE, 4893, Lidar Remote Sensing for Industry and Environment Monitoring III (21 March 2003), https://doi.org/10.1117/12.466539, 2003.

Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., Hunt, W. H., and Young, S. A.: Overview of the CALIPSO mission and CALIOP data processing algorithms, J. Atmos. Ocean. Tech., 26, 2310–2323, https://doi.org/10.1175/2009JTECHA1281.1, 2009.

Winker, D. M., Pelon, J., Coakley Jr., J. A., Ackerman, S. A., Charlson, R. J., Colarco, P. R., Flamant, P., Fu, Q., Hoff, R. M., Kitaka, C., Kubar, T. L., Le Treut, H., McCormick, M. P., Mégie, G., Poole, L., Powell, K., Trepte, C., Vaughan, M. A., and Wielicki, B. A.: The CALIPSO mission: A global 3D view of aerosols and clouds, B. Am. Meteorol. Soc., 91, 1211–1230, https://doi.org/10.1175/2010BAMS3009.1, 2010.

Wylie, D. P., Menzel, W. P., Woolf, H. M., and Strabala, K. I.: Four years of global cirrus cloud statistics using HIRS, J. Climate, 7, 1972–1986, https://doi.org/10.1175/1520-0442(1994)007<1972:FYOGCC>2.0.CO;2, 1994.

Young, S. A.: Analysis of lidar backscatter profiles in optically thin clouds, Appl. Optics, 34, 7019–7031, https://doi.org/10.1364/AO.34.007019, 1995.

Zhang, Y., Macke, A., and Albers, F.: Effect of crystal size spectrum and crystal shape on stratiform cirrus radiative forcing, Atmos. Res., 52, 59–75, https://doi.org/10.1016/S0169-8095(99)00026-5, 1999.

Zhou, C. and Yang, P.: Backscattering peak of ice cloud particles, Opt. Express, 23, 11995–12003, https://doi.org/10.1364/OE.23.011995, 2015.
L'Ecuyer, T., Haynes, J., Lebsock, M., Suzuki, K., Waliser, D., Wu, D., Kay, J., Gettelman, A., Wang, Z., and Marc-hand, R.: CloudSat mission: Performance and early science after the first year of operation, J. Geophys. Res., 113, D00A18, https://doi.org/10.1029/2008JD009982, 2008.

Strapp, J. W., Albers, F., Reuter, A., Korolev, A. V., Maixner, U., Rashke, E., and Vukovic, Z.: Laboratory measurements of the response of a PMS OAP-2DC, J. Atmos. Ocean. Tech., 18, 1150–1170, https://doi.org/10.1175/1520-0426(2001)018<1150:LMOTRO>2.0.CO;2, 2001.

Stubenrauch, C. J., Rossow, W. B., Kinne, S., Ackerman, S., Cesana, G., Chepfer, H., Girolamo, L. D., Getzewich, B., Guignard, A., Heidinger, A., Maddux, B. C., Menzel, W. P., Minnis, P., Pearl, C., Platnick, S., Poulsen, C., Riedi, J., Sun-Mack, S., Walther, A., Winker, D., Zeng, S., and Zhao, G.: Assessment of global cloud datasets from satellites: Project and database initiated by the GEWEX radiation panel, B. Amer. Meteorol. Soc., 94, 1031–1049, https://doi.org/10.1175/BAMS-D-12-00117.1, 2013.

Turner, D. D. and Eloranta, E. W.: Validating mixed-phase cloud optical depth retrieved from infrared observations with high spectral resolution lidar, IEEE Geosci. Remote S., 5, 285–288, https://doi.org/10.1109/LGRS.2008.915940, 2008.

Vidot, J., Baran, A. J., and Brunel, P.: A new ice cloud parameterization for infrared radiative transfer simulation of cloudy radiances: Evaluation and optimization with IIR observations and ice cloud profile retrieval products, J. Geophys. Res.-Atmos., 120, 6937–6951, https://doi.org/10.1002/2015JD023462, 2015.

Winker, D. M., Pelon, J. R., and McCormick, M. P.: The CALIPSO mission: spaceborne lidar for observation of aerosols and clouds, Proc. SPIE, 4893, Lidar Remote Sensing for Industry and Environment Monitoring III (21 March 2003), https://doi.org/10.1117/12.466539, 2003.

Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., Hunt, W. H., and Young, S. A.: Overview of the CALIPSO mission and CALIOP data processing algorithms, J. Atmos. Ocean. Tech., 26, 2310–2323, https://doi.org/10.1175/2009JTECHA1281.1, 2009.

Winker, D. M., Pelon, J., Coakley Jr., J. A., Ackerman, S. A., Charlson, R. J., Colarco, P. R., Flamant, P., Fu, Q., Hoff, R. M., Kitaka, C., Kubar, T. L., Le Treut, H., McCormick, M. P., Mégie, G., Poole, L., Powell, K., Trepte, C., Vaughan, M. A., and Wielicki, B. A.: The CALIPSO mission: A global 3D view of aerosols and clouds, B. Am. Meteorol. Soc., 91, 1211–1230, https://doi.org/10.1175/2010BAMS3009.1, 2010.

Wylie, D. P., Menzel, W. P., Woolf, H. M., and Strabala, K. I.: Four years of global cirrus cloud statistics using HIRS, J. Climate, 7, 1972–1986, https://doi.org/10.1175/1520-0442(1994)007<1972:FYOGCC>2.0.CO;2, 1994.

Young, S. A.: Analysis of lidar backscatter profiles in optically thin clouds, Appl. Optics, 34, 7019–7031, https://doi.org/10.1364/AO.34.007019, 1995.

Zhang, Y., Macke, A., and Albers, F.: Effect of crystal size spectrum and crystal shape on stratiform cirrus radiative forcing, Atmos. Res., 52, 59–75, https://doi.org/10.1016/S0169-8095(99)00026-5, 1999.

Zhou, C. and Yang, P.: Backscattering peak of ice cloud particles, Opt. Express, 23, 11995–12003, https://doi.org/10.1364/OE.23.011995, 2015.