Copernicus Climate Change Service
Copernicus Climate Change Service

Using the Copernicus Climate Change Service to provide specific climate information for our clients.

Case studies developed:

Supporting UN-Habitat City Resilience Profiling Programme for climate analysis in cities

Lobelia, isardSAT's climate services unit, uses downscaling and bias correction techniques to generate high-resolution, locally-adapted data describing the future climate in the target cities. Lobelia's climate engine is integrated in the CRPP, helping analyse climate trends and link to other types of data as required to allow the definition of a suitable action plan.

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Explore past climate worldwide>


Crop suitability for Oxfam

What will be the most suitable crops in Africa and Central America? In collaboration with Oxfam, Lobelia has developed a crop suitability tool to assess the future of staple crops in different regions. Climate change is expected to disproportionately affect smallholder farmers, who already face numerous risks to their agricultural production. Crop varieties will respond differently to changes in temperature and precipitation at the locations where they are currently grown. A crop suitability index is an important component of assessment studies, including changes to geographical crop distribution under climate change in the coming decades.

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Evaluating the economic impact of extreme storms in the next 50 years for PwC

Lobelia collaborates with PwC on the economic assessment of potential damages derived from extreme climate events.

Lobelia has developed a system to predict trends of extreme climate events at specific locations. The system is fed with observations and climate models, as well as reanalysis and satellite datasets. Data sources include leading European meteorological agencies, ECMWF, Sentinel imagery and various local data providers.

We use computational intelligence techniques to find patterns in the climate models that correlate with the temporal density of extreme events in the past, according to real observations from meteorological agencies. These results are then projected into the future according to the existing climate models.

Interpolation surface for the cold storm extreme index in Catalonia (blue = observations; red = grid elements). Processed by Lobelia, 2019.




agriculture, health, hazards, climate change