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Embedding Climate Information in Decision Making

PTB Kolloquium

As Earth warms globally, more or less as anticipated by theories and models developed and refined over the last half century, we are finding ourselves confronted by changes in our local environment that are unanticipated.  Meteorological and Hydrological extremes are catching us unprepared, speculation about possible catastrophic changes circulates unchecked; and decision makers at every level are in the dark about the consequences of a warming world.  Climate data abounds, but at a scale and with a quality that makes it inapplicable for all but a small, and particular, group of researchers.  For the rest of us, data creation is ad hoc, insufficiently standardized, lacks relevant quality control, and is intransparently sourced to out of data models.   Partly for these reasons the process for transforming these data into salient information is belabored, so much so that it is often out of date before it is ever applied.  In a period of immense environmental change, we have no reliable mechanism to traceabley connect users to the best available science.  This need not be the case.  Computing now makes it possible to provide data with local granularity globally, and with a physical fidelity that far outstrips what comes from the lowest common denominator of climate modelling — i.e., the basis of the present climate information system.  AI, and a wealth of observational data, make it possible for users to interact with glimpses of possible futures, as provided by the state of the art in science, with immediacy and in a language they understand.  However to make the best use of these technologies, and to spawn the innovation needed to connect users to the best possible information requires new institutions.  EVE (or Earth Virtualization Engines) is proposed as an international cooperation which builds on ongoing efforts in Europe, to make climate change tangible for all. and empower everyone to act to reduce risk and enhance resilience to pending changes.