## 4 Towards Enhanced Global-Scale Local-Relevant Monitoring and Forecasting
### Improved Diurnal Cycle for Assimilation Purposes  
The availability of new satellite data informative about superficial water over continental surfaces, particularly at low microwave frequencies (L-band and C-band), requires improvements in the description of land surfaces in atmospheric models for the simulation of satellite products, as a preliminary step towards land data assimilation. This is illustrated in the following by few examples.  
Satellite pixels in the microwave frequency range have footprints of several kilometres typically encompass many surface types. It requires horizontal heterogeneities to be accounted for in the forward modelling since most NWP models have horizontal resolutions below 10 km. Indeed, at low microwave frequencies, the emission of a vegetated surface is very different from that of an open water surface (e.g., lake, river) or of a snow covered area. Radiometers dedicated to probe water in the soil are also sensitive to liquid water present in other media (vegetation, lakes, oceans, snow).  
An improved description of inland water bodies has been proposed by [230] for the ECMWF model by using the prognostic lake scheme <<FLake>>. Another important constraint on land surface schemes with this type of observation comes from the fact that remote-sensing instruments probe at most the first 5 cm of soil. However, the water contained in the top soil layer is not the main driver of surface evapotranspiration that is of primary interest in NWP models. What dominates the strength of water losses in the atmosphere or in rivers is the water content over a deeper layer including the root-zone (tens of centimetres to few metres). The usefulness of these satellite data relies on the capacity of land surface schemes to transfer background departures located in the superficial soil layer into relevant increments in the root-zone layer. The simplicity of force-restore equations from the ISBA scheme [320] allows the estimation of analytical Jacobians that relate sensitivity of the superficial soil moisture at a given time T to changes in deep soil moisture at the beginning of an assimilation window [321].  
However, a contradiction appears between the \"analytical expression soil moisture Jacobians\" and the physical understanding of how information can be transferred from the superficial to the deep layer. This unexpected behavior is explained by the use of a single energy balance for bare soil and vegetation, together with the nonlinear behavior of vegetation transpiration near the wilting point. Indeed, an increase in root-zone soil moisture, when above wilting point, enhances vegetation transpiration that cools the surface. A decrease in surface temperature reduces bare soil evaporation and in turn reduces water losses of the superficial layer. Therefore, in a data assimilation system, satellite observations sensitive to the surface soil moisture could appear more informative than they actually are. Studies described in [322] and in [323] reveal that two-layer schemes artificially enhance deep layer corrections because the actual physical transfers (through vertical gradients of water potential) are not explicitly described.  
In conclusion, multi-layer surface schemes with separate surface energy balances are expected to lead to a more realistic extraction of information from remotely sensed superficial soil moisture in land surface models. This work is particularly relevant to illustrate that approaching data assimilation with simplified models may impair the transfer of information from and to the deeper soil layers that control predictive skills in medium and extended range forecasting.