DIVA: Demonstration of an Integrated approach for the Validation and exploitation of Atmospheric missions

Earth observation has a key role to understand the climate, which has an impact in human health and activities. Satellite measurements can help us to improve our knowledge of the climate, but its treatment is difficult due to the amount of data, complexity of the instruments and complexity of the measurements itself. Therefore, a validation of the satellite products is fundamental to ensure its quality.

Different ground-based networks (e.g. in Europe AERONET, EARLINET, PANDONIA, etc.) are collecting long-term records of atmospheric information for, among other goals, satellite validation. These networks are facing several challenges like harmonization of the protocols, data handling, and data distribution. Initiatives to join and homogenize networks are on-going, like ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure). However, there is still a lack of tools that allows the users to manipulate the data collected all together, in a synergistic way, with the goal of creation more advance synergistic products for comparison/validation between them.

DIVA project (prototype) is a hub to collect, handle, archive, and exploit in a synergetic way observational data from ground and space that aims at validating ESA and Copernicus satellite missions and scientific analysis. The system is versatile and integrates ground-based (lidar, photometer and spectrometer), satellite and model data, stand-alone and synergetic algorithms for advanced data products, using data from different platforms and sensors, as well as innovative data mining and data visualization tools. While the system is developed to be used for many algorithms, GRASP (Generalized Retrieval of Aerosol and Surface Properties) has been the first algorithm to be integrated. GRASP allows to exploit the data in a synergistic way, retrieving advanced properties from the combination of several instruments. It is currently used for lidar and photometer, and the spectrometer data is expected to be included soon. It proposes an easy to handle python interface for connecting to the data. The system is especially convenient to handle satellite data because it avoids the necessity of downloading huge datasets. DIVA has finished its first phase, where a prototype has been already developed and the second phase is about to start for maturing the system.