In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

In the long term development of the research on wind waves and their modelling, in particular of the inner and coastal seas, the present situation is framed with a short look at the past, a critical analysis of the present capabilities and a foresight of where the field is likely to go. After a short introduction, Chapter 2 deals with the basic processes at work and their modelling aspects. Chapter 3 highlights the interaction with wind and currents. Chapter 4 stresses the need for a more complete, spectral, approach in data assimilation. Chapter 5 summarizes the situation with a discussion on the present status in wave modelling and a look at what we can expect in the future.