Ensembles of leading European global coupled climate models show impressive reliability for seasonal climate prediction-including useful output for probabilistic prediction of malaria incidence and crop yield.

[1] A new 46-year hindcast dataset for seasonal-to-annual ensemble predictions has been created using a multi-model ensemble of 5 state-of-the-art coupled atmosphere-ocean circulation models. The multi-model outperforms any of the single-models in forecasting tropical Pacific SSTs because of reduced RMS errors and enhanced ensemble dispersion at all lead-times. Systematic errors are considerably reduced over the previous generation (DEMETER). Probabilistic skill scores show higher skill for the new multi-model ensemble than for DEMETER in the 4 -6 month forecast range. However, substantially improved models would be required to achieve strongly statistical significant skill increases. The combination of ENSEMBLES and DEMETER into a grand multi-model ensemble does not improve the forecast skill further. Annual-range hindcasts show anomaly correlation skill of $0.5 up to 14 months ahead. A wide range of output from the multi-model simulations is becoming publicly available and the international community is invited to explore the full scientific potential of these data. Citation: Weisheimer, A.,

Abstract. The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).

annual-mean evaporation and surface freshwater fluxes, variability and forced change have become comparable and the forced signal has already emerged from internal variability. For quantities with large internal variability and relatively small forced signal such as precipitation, forced change will emerge later on in the twenty-first century over selected regions and seasons. Regardless, the probability distribution of future precipitation anomalies is progressively shifting towards drier conditions. Overall, results highlight that both mean projected forced change and the variability that will accompany forced mean change should be considered in the development of future climate outlooks.

Abstract. The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.

Increased atmospheric carbon dioxide concentration provided warmer atmospheric temperature and higher atmospheric water vapor content, but not necessarily more precipitation. A set of experiments performed with a state-of-the-art coupled general circulation model forced with increased atmospheric CO 2 concentration (2, 4 and 16 times the present-day mean value) were analyzed and compared with a control experiment to evaluate the effect of increased CO 2 levels on monsoons. Generally, the monsoon precipitation responses to CO 2 forcing are largest if extreme concentrations of carbon dioxide are used, but they are not necessarly proportional to the forcing applied. In fact, despite a common response in terms of an atmospheric water vapor increase to the atmospheric warming, two out of the six monsoons studied simulate less or equal summer mean precipitation in the 169CO 2 experiment compared to the intermediate sensitivity experiments. The precipitation differences between CO 2 sensitivity experiments and CTRL have been investigated specifying the contribution of thermodynamic and purely dynamic processes. As a general rule, the differences depending on the atmospheric moisture content changes (thermodynamic component) are large and positive, and they tend to be damped by the dynamic component associated with the changes in the vertical velocity. However, differences are observed among monsoons in terms of the role played by other terms (like moisture advection and evaporation) in shaping the precipitation changes in warmer climates. The precipitation increase, even if weak, occurs despite a weakening of the mean circulation in the monsoon regions (''precipitation-wind paradox''). In particular, the tropical east-west Walker circulation is reduced, as found from velocity potential analysis. The meridional component of the monsoon circulation is changed as well, with larger (smaller) meridional (vertical) scales.

The performance of the new multimodel seasonal prediction system developed in the framework of the European Commission FP7 project called ENSEMBLE-based predictions of climate changes and their impacts (ENSEMBLES) is compared with the results from the previous project [i.e., Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER)]. The comparison is carried out over the five seasonal prediction systems (SPSs) that participated in both projects. Since DEMETER, the contributing SPSs have improved in all aspects with the main advancements including the increase in resolution, the better representation of subgrid physical processes, land, sea ice, and greenhouse gas boundary forcing, and the more widespread use of assimilation for ocean initialization.The ENSEMBLES results show an overall enhancement for the prediction of anomalous surface temperature conditions. However, the improvement is quite small and with considerable space-time variations. In the tropics, ENSEMBLES systematically improves the sharpness and the discrimination attributes of the forecasts. Enhancements of the ENSEMBLES resolution attribute are also reported in the tropics for the forecasts started 1 February, 1 May, and 1 November. Our results indicate that, in ENSEMBLES, an increased portion of prediction signal from the single-models effectively contributes to amplify the multimodel forecasts skill. On the other hand, a worsening is shown for the multimodel calibration over the tropics compared to DEMETER.Significant changes are also shown in northern midlatitudes, where the ENSEMBLES multimodel discrimination, resolution, and reliability improve for February, May, and November starting dates. However, the ENSEMBLES multimodel decreases the capability to amplify the performance with respect to the contributing single models for the forecasts started in February, May, and August. This is at least partly due to the reduced overconfidence of the ENSEMBLES single models with respect to the DEMETER counterparts.Provided that they are suitably calibrated beforehand, it is shown that the ENSEMBLES multimodel forecasts represent a step forward for the potential economical value they can supply. A warning for all potential users concerns the need for calibration due to the degraded tropical reliability compared to DEMETER. In addition, the superiority of recalibrating the ENSEMBLES predictions through the discrimination information is shown.Concerning the forecasts started in August, ENSEMBLES exhibits mixed results over both tropics and northern midlatitudes. In this case, the increased potential predictability compared to DEMETER appears to be balanced by the reduction in the independence of the SPSs contributing to ENSEMBLES. Consequently, for the August start dates no clear advantage of using one multimodel system instead of the other can be evidenced.

Tropospheric ozone (O3) produces harmful effects to forests and crops, leading to a reduction of land carbon assimilation that, consequently, influences the land sink and the crop yield production. To assess the potential negative O3 impacts to vegetation, the European Union uses the Accumulated Ozone over Threshold of 40 ppb (AOT40). This index has been chosen for its simplicity and flexibility in handling different ecosystems as well as for its linear relationships with yield or biomass loss. However, AOT40 does not give any information on the physiological O3 uptake into the leaves since it does not include any environmental constraints to O3 uptake through stomata. Therefore, an index based on stomatal O3 uptake (i.e. PODY), which describes the amount of O3 entering into the leaves, would be more appropriate. Specifically, the PODY metric considers the effects of multiple climatic factors, vegetation characteristics and local and phenological inputs rather than the only atmospheric O3 concentration. For this reason, the use of PODY in the O3 risk assessment for vegetation is becoming recommended. We compare different potential O3 risk assessments based on two methodologies (i.e. AOT40 and stomatal O3 uptake) using a framework of mesoscale models that produces hourly meteorological and O3 data at high spatial resolution (12 km) over Europe for the time period 2000-2005. Results indicate a remarkable spatial and temporal inconsistency between the two indices, suggesting that a new definition of European legislative standard is needed in the near future. Besides, our risk assessment based on AOT40 shows a good consistency compared to both in-situ data and other model-based datasets. Conversely, risk assessment based on stomatal O3 uptake shows different spatial patterns compared to other model-based datasets. This strong inconsistency can be likely related to a different vegetation cover and its associated parameterizations.