Sensors synergy (combining different observational techniques) is widely used for retrieving the microphysical and optical properties of clouds. In order to exploit the techniques involving sensor synergy for cloud property retrievals, there is the need for co-located measurement
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Sensors synergy (combining different observational techniques) is widely used for retrieving the microphysical and optical properties of clouds. In order to exploit the techniques involving sensor synergy for cloud property retrievals, there is the need for co-located measurements in time and space. Nowadays, the availability of suitable combined datasets involving several sensors from different platforms is still limited to fully-equipped anchor stations, expensive in-situ campaigns and few overpasses of satellites above ground-based remote sensing sites. In order to develop novel sensors synergy techniques well-understood co-located data is needed. Because of the difficulty in finding well-validated study cases involving observations from different sensors the creation of realistic synthetic data sets is useful. The purpose of this work is to make use of the EarthCARE end-to-end mission simulator, ECSIM, to create a synthetic datasets that correspond to cloud radar and lidar measurements from several platforms observing the same cloud scene.
ECSIM has been adapted to simulate cloud radar and lidar measurements of ¿realistic¿ synthetic cloud scenes from three different platforms such as ground-based, airborne and spaceborne. The cloud scenes used in this work are generated by LES and cloud revolving models. With ECSIM able to simulate several remote sensing sensors for the same cloud scenes, it is possible to test, validate and conduct sensitivity studies related to new retrieval algorithms. These algorithms may then be applied to real data from in-situ campaigns or observations. As an example, the cloud geometrical thicknesses retrieved from the three platforms will be compared to each other in order to analyze the differences in the stratocumulus cloud retrievals.@en