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To understand the global surface energy budget is to understand climate. Because it is impractical to cover the earth with monitoring stations, the answer to global coverage lies in reliable satellite-based estimates. Efforts are underway at NASA and universities to develop algorithms to do this, but such projects are in their infancy. In concert with these ambitious efforts, accurate and precise ground-based measurements in differing climatic regions are essential to refine and verify the satellite-based estimates, as well as to support specialized research. To fill this niche, the Surface Radiation Budget Network (SURFRAD) was established in 1993 through the support of NOAA's Office of Global Programs.
Vast networks of meteorological sensors ring the globe measuring atmospheric state variables, like temperature, humidity, wind speed, rainfall, and atmospheric carbon dioxide, on a continuous basis. These measurements serve earth system science by providing inputs into models that predict weather, climate and the cycling of carbon and water. And, they provide information that allows researchers to detect the trends in climate, greenhouse gases, and air pollution. The eddy covariance method is currently the standard method used by biometeorologists to measure fluxes of trace gases between ecosystems and atmosphere.
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HYdrological cycle in the Mediterranean EXperiemnt. Considering the science and societal issues motivating HyMeX, the programme aims to : improve our understanding of the water cycle, with emphasis on extreme events, by monitoring and modelling the Mediterranean atmosphere-land-ocean coupled system, its variability from the event to the seasonal and interannual scales, and its characteristics over one decade (2010-2020) in the context of global change, assess the social and economic vulnerability to extreme events and adaptation capacity.The multidisciplinary research and the database developed within HyMeX should contribute to: improve observational and modelling systems, especially for coupled systems, better predict extreme events, simulate the long-term water-cycle more accurately, provide guidelines for adaptation measures, especially in the context of global change.