PNNL

Abstract

Predictions of the Earth system, such as weather forecasts and climate projections, require models informed by observations at many levels. Some methods for integrating models and observations are very systematic and comprehensive (e.g., data assimilation) while some are single purpose and customized (e.g., for model validation). We review current methods and best practices for integrating models and observations, and highlight how best practices and future developments promise an improved model-data fusion of modeling systems in which advanced heterogeneous observation networks to improve predictions across scales (from weather to climate) and throughout the Earth system (including atmosphere, land surface, oceans, cryosphere and chemistry). As the community pushes to develop the next generation of models and data systems, we highlight how better fusion of models and data can improve predictions, and the models themselves. The fusion will come through better use of diverse observations and more integrated modeling systems from weather to climate scales.