The main scope of this activity was to foster the exchange of expertise between the European Lidar Network (EARLINET) and Latin America Lidar Network (LALINET), and demonstrate the capability of joint research, setting the groundwork for GALION (The Global Atmosphere Watch Aerosol Lidar Observation Network) and future calibration/validation of ESA’s atmospheric satellite missions such as Aeolus and EarthCARE.

The project aimed to design an optical instrument based on Compressive Sensing (CS) for a space applications. Conventional sampling or compression methodologies follow the Shannon-Nyquist theorem, which states that if a signal frequency band or spectrum is limited to a frequency B [Hz], the signal is completely determined by a sample-rate larger than 2xB samples per second. Compressive Sensing (CS) provides a fundamentally new approach to data acquisition or signal sampling.

Background and justification:

Background and justification:

N/A

Within the framework of ESA’s Alcantara initiative international R&D Studies were funded.

The main objectives of this project were to develop the tools and structure to enable routine EarthCARE radar and lidar observations of clouds to be assimilated in the ECMWF Numerical Weather Prediction model and to prepare for the real-time monitoring of the observations to detect instrument degradation or errors. This required adjustments of assimilation tools, such as the observation operators, observation error definition, quality control, data screening and bias correction.

Since 2003 ESA has promoted studies in order to establish scientific requirements, identify the most appropriate measurement techniques, start the associated technology developments, and define the system scenarios for a Next-Generation Gravity Mission (NGGM). Such a mission will make use of the Low-Low Satellite-to-Satellite Tracking (LL-SST) technique to monitor the temporal variations of the Earth gravity field over a long time span but with much higher spatial resolution and with improved temporal resolution.