D11.3 Lessons learned
ERA-CLIM2, UERRA, QA4ECV, CLIPC and EUCLEIA are acronyms for five FP7 projects from the 2013 Space Call of FP7 that all share the common objective to prepare for the Copernicus Climate ChangeClimate Change
Climate change refers to a change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer. Climate change may be due to natural internal processes or external forcings such as modulations of the solar cycles, volcanic eruptions and persistent anthropogenic changes in the composition of the atmosphere or in land use. Note that the United Nations Framework Convention on Climate Change (UNFCCC), in its Article 1, defines climate change as: 'a change of climate which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods'. The UNFCCC thus makes a distinction between climate change attributable to human activities altering the atmospheric composition, and climate variability attributa Service (C3S). The capabilities being developed through these five research initiatives form the scientific and technological foundation for the C3S. As part of the overarching coordination among these five projects, each project has described the lessons learned relevant for the development of the operational services in the C3S. These are provided in Sections 2 to 6.
The overarching lessons that the five projects have in common are summarized below. Because ECMWF (who operates the C3S on behalf of the European Union) has started to bring together expertise from across Europe to deliver the service, it is noted that some of the lessons directly translate to parts of the service, whereas direct links are less clear for other lessons (indicated by *). These may warrant special attention in future.
1. Data rescue must be seen as an ongoing effort which requires a permanent infrastructure and knowledge base in order to access the observational data not used so far (partly because of data policies).
2. A commonly agreed metadatametadata
Information about meteorological and climatological data concerning how and when they were measured, their quality, known problems and other characteristics. base is required which links strongly to the international community working with historical earth-system observations.
3. Key people with data assimilation expertise and communication skills are often the bottle neck for timely delivery of complex coupled and/or regional reanalysesreanalyses
Reanalyses are estimates of historical atmospheric, hydrographic or other climate relevant quantities, created by processing past climate data using fixed state-of-the-art weather forecasting or ocean circulation models with data assimilation techniques.
systems. *
4. Actual reanalysis and ECV production turns out to more demanding than anticipated. *
5. Regional reanalysis at the European scale is relatively new and requires significant support because it cannot lean on existing pan-European operational systems.
6. Long term biases in reanalysis datasets (due to model parametrization and changes in observation coverage) need to be monitored and compared with other observational references because they may introduce spurious climate trendstrends
long-term evolution, such as climate change and global warming. Trend analysis is used to describe trends, and can involve linear or multiple regression with time as a covariate. A trend model may be a straight line (linear) or more complex (polynomial), and the long-term rate of change can be described in terms of the time derivative from the trend model.
.
7. Intensive communication and engagement with users is required to decide on priorities concerning physical parameters to be archived, observations to compare to, scales and skill scores to investigate. *
8. There is a need for products to be tailored to the varied needs of different user groups for such products to be useful in their decision making; an information portal needs to speak to all types of users.
9. The huge differences in approach and methodology between the many disciplines need to be brought together to create a credible climate service. *
10. It is vital for users to have a clear understanding of the scientific uncertainties involved and of the robustness of the results relevant to the estimation of low-frequency variability and climate trends. *
11. Interactive traceability chains are a useful and efficient tool for data users to obtain confidenceconfidence
The validity of a finding based on the type, amount, quality, and consistency of evidence (e.g., mechanistic understanding, theory, data, models, expert judgment) and on the degree of agreement. Confidence is expressed qualitatively (Mastrandrea et al., 2010).
in the quality, robustness, and limitations of satellite ECV data records.
12. It is important to maintain close ties to relevant international (ESA, EUMETSAT, NASANASA
National Aeronautics and Space Administration, JAXA) and national space agencies to ensure the availability of the most recent state-of-science satellite level-1 data needed for generation of ECV records.
13. There is a need for a continuous stream of research funding in parallel of the operational C3S to guarantee that the services remain state-of-the-art over time. *
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