The CLARIS LPB Project aimed at projecting the regional climate change impacts in La Plata Basin (LPB) in South Eastern South America focusing on the 2010-2040 and 2070-2100 periods, and at designing adaptation strategies for agriculture, hydropower, river transportation, water resources and ecosystems in wetlands. Thus, the project was built on three major activities: common activities (WP2 and WP7), climate research activities (WP3 to 6) and design of adaptation strategies (WP8 and WP9).

Our common activities focused on providing common services to all participants (WP7) and on fostering and coordinating dissemination activities at scientific, public, and stakeholder levels (WP2). The CLARIS LPB Data Archive Centre (CLDAC) has played a major role in achieving this objective and also provides a legacy beyond the end of the project. As well as providing access to datasets produced by and used by CLARIS LPB, the CLDAC provides access to software tools developed by the project and guidance for users of climate model outputs, particularly the CLARIS LPB regional model outputs. In parallel, in order to promote interaction between scientists and stakeholders, we structured a dissemination road map based on two main axes: (i) building a social communication field inside the network; and (ii) exploring stakeholder’s perceptions on climate change.

In terms of climate research, CLARIS LPB gathered a unique daily meteorological database (precipitation, temperature, solar radiation, streamflow) over most of the period (1959-2008), with some data updated to 2012. A gridded data set was developed using daily minimum and maximum surface temperatures over 1961-2000 and daily precipitation for the same period. Paleoclimate reconstruction using lake sediment data allowed us to reconstruct past hydrological variability within a broad region of southeastern South America (SESA) including new sites in the LPB and surrounding regions.

The analysis of global climate models over XXth and XXIst centuries suggested that the La Plata basin (extreme hydro-climate conditions as well as lower frequency variability) is influenced differently depending on the pattern of SST anomalies that characterizes El Niño, that the tropical Indian and Atlantic ocean can interfere with the signal coming from the equatorial Pacific, and that local land-atmosphere feedbacks can modulate the remote signal.