1 European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading RG2 9 AX, UK; [EMAIL_ADDRESS] (G.A. ); [EMAIL_ADDRESS] (J.M. ); [EMAIL_ADDRESS] (M.C. ); [PERSON].-P.); [EMAIL_ADDRESS] (A.B. ); [EMAIL_ADDRESS] (N.W. ); [EMAIL_ADDRESS] (J.M.-S.); [EMAIL_ADDRESS] (P.R.J. ); [PERSON]ESS] (I.S. ); [EMAIL_ADDRESS] (H.J. ); [EMAIL_ADDRESS] (G.C. ); [EMAIL_ADDRESS] (C.M. ); [EMAIL_ADDRESS] (C.P. ); [EMAIL_ADDRESS] (E.Z)  
offline and coupled applications, the land-surface modelling activity at ECMWF has been substantially and continuously expanded. An improved soil hydrology [8], a new snow scheme [9] and a multi-year satellite-based vegetation climatology [10] have been included in the operational IFS. These have had a positive impact on both the global water cycle and near-surface atmospheric variables compared to the original TESSEL (Tiled ECMWF Scheme for Surface Exchanges over Land) scheme used in ECMWF ERA-40 reanalysis [11] and in the ERA-Interim reanalysis [12], compared to HTESSEL used in ERA5 [13] and ERA5 Land [14]. In particular the quality of seasonal predictions during extreme events associated with soil moisture-precipitation feedback was enhanced with the soil hydrology as in the European summer heat-wave in 2003 [15]. The new snow scheme resulted in a substantial reduction of near-surface temperature errors in snow-dominated areas by improving the thermal energy exchange at the surface (i.e., northern territories of Eurasia and Canada) [16]. More recently, the fixed maximum vegetation Leaf Area Index (LAI) field was replaced by a monthly climatology for LAI. This resulted in a reduction of near-surface temperature errors in the mid-latitude and tropical areas, particularly evident in Boreal spring and summer. The bare ground evaporation has been also enhanced over deserts and sparse vegetated areas by considering a lower stress limit in agreement with experimental findings (e.g., [17]) and results in a more realistic soil moisture for dry-lands. These model components are schematically illustrated in Figure 1 along with prospective developments. Beyond the important day-to-day experience of running the land-surface scheme in an operational NWP environment, the participation in international projects such as AMMA (African Monsoon Multidisciplinary Analysis [18]) and GLACE2 (Global Land-Atmosphere Coupling Experiment-2), helped to better understand the mechanisms and areas of strong coupling between the land surface and the atmosphere based on experiments where the ECMWF IFS model was coupled with a realistic set of soil moisture fields. With a continuous increase in spatial resolution and more broad applications of LSMs, as well as the growing availability of a range of diverse observations, a clear need for a more complex and accurate process representation is emerging. This continuous research effort aims at improving the land surface model parametrization for better surface prediction and ultimately better NWP and atmospheric composition forecasts. The current improvements are targeting different components of the land surface model, namely, the vegetation parametrization, the snow component, the soil hydrology, the open water/lake parametrization and also the representation of urban areas. Figure 1: Simplified representation of the main ECLand system components and its prospective evolution (inner light green box) as part of the full Integrated Forecasting System (outer yellow box) where the current ECLand main components are within the light grey box. An efficient and scalable land surface system is essential for a routine NWP and service environment and can facilitate a paradigm shift for an Earth-Observation driven model development ([PERSON] et al. [19]) under an Earth System framework, while linking with new possibilities brought by machine learning and Artificial Intelligence (AI) tools ([PERSON] et al. [20]).