IMPACT OF FREQUENCY RESPONSE UNCERTAINTIES ON THE ACCURACY OF AOS/C²OMODO RADIOMETER

X. Boulanger¹, L. Hermozo¹, J. Puech¹

¹CNES

The contribution will provide an analysis of the impact of frequency response uncertainties on the brightness temperatures measured by AOS/C²OMODO Radiometers. More particularly, it will give statistical analyses of the variations of Brightness Temperatures ∆TB with respect to Front-End Local Oscillator (LO) shifts, Back-End Intermediate Frequency (IF) shifts, and simulated realistic spectral response of channels. Meso-NH simulations of the Mesoscale Convective System (MCS) Hector have been used as reference to extract more than 3200 convective core-class atmospheric profiles. Those profiles have then been used as inputs of the RTTOV-SCATT v13 radiative transfer model to derive brightness temperatures on which the impact of frequency drifts and spectral response have been finally simulated.

C²OMODO (Convective Core Observations through MicrOwave Derivatives in the trOpics) observation system [1] is the French contribution to the AOS mission with the objective of assessing km-scale vertical mass fluxes of ice (mainly graupel and cloud ice) within convective cores of tropical and sub-tropical convective systems. CNES will provide a tandem of two identical cross-track total power microwave radiometers named C²OMODOR. They will fly on-board two satellites following the same ground track on the AOS inclined (55°) orbit but time-delayed by about 1 to 2 minutes. It will allow the temporal derivatives of Brightness Temperature dTB/dt to be derived [1], [2]. Basically, each C²OMODOR is composed of:

• A high rotation speed (144 rpm) scan mechanism associated with a 20 cm-diameter reflector

• A Quasi-Optical Network (QON) for separation and routing of the 3 co-located beams

• 3 different receivers:

• A 89 GHz direct detection Rx (1 channel)

• A 183.31 GHz Single-Side Band (SSB) Lower Side Band (LSB) heterodyne Rx with the LNA ahead (4 channels)

• A 325.15 GHz Double-Side Band (DSB) heterodyne Rx with the Mixer ahead (5 channels)

• An On-Board Calibration Target (OBCT) for hot source calibration. The cold source calibration will be performed by looking at the cold sky.

The simulation of reference for the whole analysis has been carried out using the Meso-NH model [2], [3]. Meso-NH is the non-hydrostatic mesoscale atmospheric model of the French research community jointly developed by Meteo-France and Laboratoire d’Aérologie for research purposes [4]. This simulation considers an MCS called Hector [1], [2]. RTTOV (Radiative Transfer for Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS)) is a very fast radiative transfer model for passive visible, infrared and microwave downward-viewing satellite radiometers, spectrometers and interferometers [5]. The scattering mode (RTTOV-SCATT) has been applied onto the extracted profiles of the Meso-NH simulation of Hector.

Finally, it will be shown that the bias can be up to several Kelvins on an instantaneous basis (∆TB>2 K for ∆f>100 MHz) and RMS error can be higher than 1.5 K on a statistical basis. Given the current LO and IF accuracy and stability requirements of C²OMODOR, the RMS errors due to LO and IF shifts are lower than 0.25 K. The impact of real Back-End frequency response is less than 0.1 K. A sideband imbalance of ±1 dB for the 325.15 DSB receiver can lead to an RMS error up to 0.2 K.

ACKNOWLEDGMENT

The authors would like to thank the Mission Advisory Group, especially the H. Brogniez (C²OMODO PI), J-P. Chaboureau for providing the Meso-NH simulations, and Thomas Lefebvre for the profiles database classification.

REFERENCES

[1] Brogniez, H. et al. (2022). “Time-delayed Tandem Microwave Observations of Tropical Deep Convection: Overview of the C²OMODO Mission”. Sec. Satellite Missions, Volume 3, Frontiers in Remote Sensing, April 2022. https://doi.org/10.3389/frsen.2022.854735.

[2] Auguste, F. and Chaboureau, J-P. (2022). “Deep Convection as Inferred from the C²OMODO Concept of a Tandem of Microwave Radiometers”. Sec. Satellite Missions, Volume 3, Frontiers in Remote Sensing, April 2022. https://doi.org/10.3389/frsen.2022.852610. 

[3] Lac, C., Chaboureau, J.-P., Masson, V., Pinty, J.-P., Tulet, P., Escobar, J., et al. (2018). “Overview of the Meso-NH Model Version 5.4 and its Applications”. Geosci. Model. Dev.Model Dev. 11, 1929–1969. https://doi.org/10.5194/gmd-11-1929-2018.

[4] http://mesonh.aero.obs-mip.fr/

[5] Saunders, R., Hocking, J., Turner, E., Rayer, P., Rundle, D., Brunel, P., Vidot, J., Roquet, P., Matricardi, M., Geer, A., Bormann, N., and Lupu, C. (2018). “An update on the RTTOV fast radiative transfer model”, Geosci. Model Dev., 11, 2717-2737, https://doi.org/10.5194/gmd-11-2717-2018.