## 3 Earth Surface Modelling Advances and Links with EO Datasets
### Ocean-Atmosphere Coupling
The use of all-weather SST from AMSR-2 microwave sensor is shown to validate the cold wake 5-day forecast of the Pacific's tropical cyclone Neoguri in July 2014 with the ECMWF high resolution model coupled and uncoupled with ocean (Figure 22). Moreover, the use of in situ SSTs observations has allowed to assess the diurnal variability in the ECMWF coupled forecasts and the advantages of ocean-atmosphere coupling [266]. Indeed, GCMs that resolve the air-sea flux diurnal variability tend to perform significantly better than ones which do not [267; 268; 269; 269; 259]. In the tropics, the mean SST cool bias [270] is reduced, with warmer SST leading to increased precipitation that compares better to climatology [259]. Further motivations for the inclusion of the diurnal cycle in SST is the potential improvement it might provide in predictions of the Madden-Julian Oscillation (MJO, [271]). The results of [259] actually show a reduction in the performance of the MJO index although there is indication that the diurnal coupling produces a stronger and more coherent MJO. Increasing the coupling frequency to resolve the diurnal cycle also enhanced the intensity of MJO convection [272] and changed the magnitude of the El Nino-Southern Oscillation (ENSO) amplitude [268; 273]. In the Southern Ocean, resolving diurnal and intra-diurnal variations leads to a colder mean SST, and stronger westerlies [269], probably due to the resolution of fast-moving storms. It is therefore likely that resolving the diurnal cycle in SST and coupling on these timescales may provide at least part of the picture in improved extended-range predictions. Air-sea exchanges of properties are highly sensitive to wind speed. However, if the wind is gusty or associated with a fast-moving storm, so that the wind direction is variable over the course of the day, then the magnitude of the mean wind, computed from the average zonal and meridional wind components, will be less than the average \"scalar\" wind speed computed from the variable wind speed magnitude. In the state-of-the-art Coupled Ocean Atmosphere Response Experiment (COARE) bulk flux algorithm [274], averaged hourly wind speeds are increased by a gustiness parameter to account for this additional wind speed variance at hourly time scales [275]. Using high resolution Tropical Atmosphere and Ocean (TAO) mooring data [276] showed that the diurnal'mesoscale' gustiness was more than twice as large as the parameterised 'convective' gustiness and that neglecting this diurnal wind variance could cause a mean bias of up to 8 W/m\({}^{2}\) in the latent heat flux component alone. For scaling purposes, a 20 m layer subject to 10 W/m\({}^{2}\) net surface heat flux error over a 1-year period would produce a temperature error in that layer of 4C. In an operational context [277], the wave forecasting and the coupling with atmosphere and ocean models is progressing with detectable benefits both on near surface winds and sea-surface temperatures. The impact of waves on the coupled climate system is also highlighted in [278] for the continuous exchange of heat, energy, water vapor, and carbon dioxide that are relevant from diurnal cycles to extended prediction ranges.