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The evolution of our environment is complex and controlled by many physical, chemical and biological processes that operate at different time and space scales ranging from small to global. To understand it, we must collect observations from a variety of techniques and instruments. This information can be local or global, acquired over time or in ad hoc research expeditions. For it is from the complementarity between the various observations and modeling that knowledge improves.

IPSL uses a number of instruments and observation methods to understand better the state and evolution of the terrestrial and planetary environments.

Research Expeditions

Station GPS installée durant la campagne AMMA

To understand in details the mechanisms that govern our environment, intensive research expeditions are planned on a specific region and a limited period of time. Several teams are involved in these expeditions and a variety of instruments are used.

Monitoring to detect slow variations

Réseau de mesure NDAAC

Some quantities (ozone, CO2, ...) are monitored during several decades, at few specific sites or representative regions. They are used as indicators of the evolution of our environment, and in particular they are used to check the impact of State regulations and protocols that are established to preserve the environment.

Observing from above to have a global view

Satellite CALIPSO pour l'étude du cycle de l'eau

Only instruments onboard satellites give us a global view of the Earth and planetary environments. IPSL is heavily involved in space missions to observe the Earth and other planets in the solar system. Instruments onboard satellites are designed and realized in our laboratories.

Archive data not to lose memory

The data produced by IPSL are archived and made available to the scientific community, within IPSL as well as at national and international levels. These data are useful to describe and quantify the current changes in reference to the past, and also to better describe and understand the studied environment by comparing the different available data sets.