Synergistic mixed-layer height retrieval method using microwave radiometer and lidar ceilometer observations

This paper tackles synergistic mixed-layer height (MLH) estimation via a combination of microwave radiometer (MWR) and lidar ceilometer (LC)-based estimates. While MLH-MWR estimates rely on potential temperature retrievals, MLH-LC estimates rely on aerosol gradients. The pros and cons of MLH retrievals obtained from MWR via the parcel method and from LC via an extended Kalman filter (EKF)-based method are used to motivate the synergistic algorithm. The synergistic algorithm is introduced as a maximum-likelihood combination of MLH-MWR and MLH-LC. Two case examples from the 2013 HOPE campaign at Jülich, Germany, are used to show the robustness of the synergistic method and the effect of surface temperature measurement error. Doppler wind lidar retrievals and radiosonde reference MLH estimates are used for validation.This research is part of the projects PGC2018-094132-B-I00 and MDM-2016-0600 (“CommSensLab” Excellence Unit) funded by Ministerio de Ciencia e Investigación (MCIN)/ Agencia Estatal de Investigación (AEI)/ 10.13039/501100011033/ FEDER. Data were provided by Julich Observatory for Cloud Evolution (JOYCE-CF), a core facility funded by Deutsche Forschungsgemeinschaft via grant DFG LO 901/7-1. The work of M.P.A.S was supported under Grant PRE2018-086054 funded by MCIN/AEI/ 10.13039/501100011033 and FSE “El FSE invierte en tu futuro”. The European Commission collaborated under projects H2020 ACTRIS-IMP (GA871115) and H2020 ATMO-ACCESS (GA-101008004).Peer ReviewedPostprint (author's final draft