Long-term high-resolution temperature data of the Compact Rayleigh Autonomous Lidar (CORAL) is used to evaluate temperature and gravity wave (GW) activity in ECMWF Integrated Forecasting System (IFS) over R\’io Grande (53.79$^{\circ}$S, 67.75$^{\circ}$W), which is a hot spot of stratospheric GWs in winter. Seasonal and altitudinal variations of the temperature differences between the IFS and lidar are studied for 2018 with a uniform IFS version. Moreover, interannual variations are considered taking into account updated IFS versions. We find monthly mean temperature differences $<2$~K at 20-40~km altitude. At 45-55~km, the differences are smaller than 4~K during summer. The largest differences are found during winter (4~K in May 2018 and -10~K in August 2018, July 2019 and 2020). The width of the difference distribution (15th/85th percentiles), the root mean square error, and maximum differences between instantaneous individual profiles are also larger during winter ($>\pm10$~K) and increase with altitude. We relate this seasonal variability to middle atmosphere GW activity. In the upper stratosphere and lower mesosphere, the observed temperature differences result from both GW amplitude and phase differences. The IFS captures the seasonal cycle of GW potential energy ($E_p$) well, but underestimates $E_p$ in the middle atmosphere. Experimental IFS simulations without damping by the model sponge for May and August 2018 show an increase in the monthly mean $E_p$ above 45~km from only $\approx10$~\% of the $E_p$ derived from the lidar measurements to 26~\% and 42~\%, respectively. GWs not resolved in the IFS are likely explaining the remaining underestimation of the $E_p$.

The European Centre for Medium-Range Weather Forecasts (ECMWF) mission is to deliver high-quality global medium-range numerical weather predictions and monitoring of the Earth system including hydrology and water resources to its member states for decision making processes. Challenges in this area include the integration of innovative observations into the Earth system; realistic representations of water, energy and carbon cycles; coupling and initialisation of all Earth system components; adequate representation of uncertainties; and supporting the development of user-specific products to enable optimal decision-making under uncertainty. ECMWF is also the operational centre of the European Union’s Copernicus Emergency Management Service (CEMS) providing Global Flood and Fire forecasting systems issuing seasonal and sub-seasonal forecasts. These forecasts, along with reanalysis and reforecast data, are now openly available through the Copernicus Climate Data Store allowing them to be input to other applications and used by decision makers. These data and service enhancements open numerous possibilities to improve integration with water decision-makings systems and processes. However, ensuring these forecasts can be used for such purposes is challenging due to the scale disconnect between a continental or global forecast system and the local scale at which decisions are made. Overcoming this challenge can be achieved by co-designing and optimising the forecasting systems together with the applications sector. This will allow to fully integrate Earth System and impacts modelling in the forecasting systems, thereby enhancing simulation realism. It will also to better tailor specific end products to user requirements and facilitate an improved decision making. An example is the TAMIR project which aims to connect flood forecasts to end user decision making through an impact matrix. This matrix combines flood hazard forecasts, derived by blending hourly radar based nowcasts and medium-range numerical weather predictions, with locally relevant exposure information regarding population and critical infrastructure. Continuous end user engagement ensures that the design of the forecast system remains relevant for their decision-making purposes. Another example is the recently commenced I-CISK project, which will tailor environmental forecast data to meet the requirements set out by end users. This project aims to build upon the wealth of existing data and services by incorporating local knowledge across multiple sectors, timescales and hazards. Working with decision-makers at every step of the project to co-design, co-create, co-implement and co-evaluate a range of tailored climate services that are specific to user needs, will help to provide information that is useful, useable, and used at the local scale. This will include collaborating with users to design effective forecast visualisations and undertaking user-driven evaluation to answer specific questions users have about forecast performance.

The science guiding the \EURECA campaign and its measurements are presented. \EURECA comprised roughly five weeks of measurements in the downstream winter trades of the North Atlantic — eastward and south-eastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, \EURECA marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or, or the life-cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso (200 km) and larger (500 km) scales, roughly four hundred hours of flight time by four heavily instrumented research aircraft, four global-ocean class research vessels, an advanced ground-based cloud observatory, a flotilla of autonomous or tethered measurement devices operating in the upper ocean (nearly 10000 profiles), lower atmosphere (continuous profiling), and along the air-sea interface, a network of water stable isotopologue measurements, complemented by special programmes of satellite remote sensing and modeling with a new generation of weather/climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that \EURECA explored — from Brazil Ring Current Eddies to turbulence induced clustering of cloud droplets and its influence on warm-rain formation — are presented along with an overview \EURECA’s outreach activities, environmental impact, and guidelines for scientific practice.

Energy exchange at the snow-atmosphere interface in winter is important for the evolution of temperature at the surface and within the snow, preconditioning the snowpack for melt during spring. This study illustrates a set of diagnostic tools that are useful for evaluating the energy exchange at the Earth’s surface in an Earth System Model, from a process-based perspective, using in-situ observations. In particular, a new way to measure model improvement using the response of the surface temperature and other surface energy budget (SEB) terms to radiative forcing is presented. These process-oriented diagnostics also provide a measure of the coupling strength between the incoming radiation and the various terms in the SEB, which can be used to ensure that improvements in predictions of user relevant properties, such as 2m temperature, are happening for the right reasons. Correctly capturing such process relationships is a necessary step towards achieving more skilful weather forecasts and climate projections. These diagnostic techniques are applied to assess the impact of a new multi-layer snow scheme in the European Centre for Medium-Range Weather Forecasts’-Integrated Forecast System at two high-Arctic sites (Summit, Greenland and Sodankylä, Finland). The multi-layer scheme is expected to replace a single layer snow scheme in the operational forecasting system, enhancing the 2m temperature forecast reliability and skill across the northern hemisphere in boreal winter.