Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the subseasonal to seasonal time range, the Subseasonal to Seasonal (S2S) Prediction research project has been established by the World Weather Research Programme/World Climate Research Programme. A main deliverable of this project is the establishment of an extensive database containing subseasonal (up to 60 days) forecasts, 3 weeks behind real time, and reforecasts from 11 operational centers, modeled in part on the The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database for medium-range forecasts (up to 15 days). The S2S database, available to the research community since May 2015, represents an important tool to advance our understanding of the subseasonal to seasonal time range that has been considered for a long time as a “desert of predictability.” In particular, this database will help identify common successes and shortcomings in the model simulation and prediction of sources of subseasonal to seasonal predictability. For instance, a preliminary study suggests that the S2S models significantly underestimate the amplitude of the Madden–Julian oscillation (MJO) teleconnections over the Euro-Atlantic sector. The S2S database also represents an important tool for case studies of extreme events. For instance, a multimodel combination of S2S models displays higher probability of a landfall over the islands of Vanuatu 2–3 weeks before Tropical Cyclone Pam devastated the islands in March 2015.

The Liguria coastal region in Italy was affected by two heavy rainfall episodes and subsequent severe flooding that occurred at the end of October and the beginning of November 2011. In both cases, the very large accumulated precipitation maxima were associated with intense and quasi-stationary convective systems that developed near the coast, both related to orographic lift and similar low-level mesoscale flow patterns over the Ligurian Sea, giving rise to pronounced convergence lines. This study aims at analysing the main dynamical processes responsible for the onset, lifecycle, intensity and localisation/propagation of the precipitating systems, using the ISAC convection-permitting model MOLOCH applied at different spatial resolutions and comparing model output fields with available observations. The ability of the model in quantitative precipitation forecasting (QPF) is tested with respect to initial conditions and model horizontal resolution. Although precipitation maxima remain underestimated in the model experiments, it is shown that errors in QPF in both amount and position tend to decrease with increasing grid resolution. It is shown that model accuracy in forecasting rainfall amounts and localisation of the precipitating systems critically depends on the ability to represent the cold air outflow from the Po Valley to the Ligurian Sea, which determines the position and intensity of the mesoscale convergence lines over the sea. Such convergence lines controls, together with the lifting produced by the Apennines chain surrounding the coast, the onset of the severe convection.

Major disruptions of the winter season, high-latitude stratospheric polar vortices can result in stratospheric anomalies that persist for months. These sudden stratospheric warming events are recognized as an important potential source of forecast skill for surface climate on subseasonal to seasonal timescales. Realizing this skill in operational subseasonal forecast models remains a challenge, as models must capture both the evolution of the stratospheric polar vortices in addition to their coupling to the troposphere. The processes involved in this coupling remain a topic of open research. We present here the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project. SNAPSI is a new model intercomparison protocol designed to study the role of the Arctic and Antarctic stratospheric polar vortex disturbances for surface predictability in subseasonal to seasonal forecast models. Based on a set of controlled, subseasonal ensemble forecasts of three recent events, the protocol aims to address four main scientific goals. First, to quantify the impact of improved stratospheric forecasts on near-surface forecast skill. Second, to attribute specific extreme events to stratospheric variability. Third, to assess the mechanisms by which the stratosphere influences the troposphere in the forecast models. Fourth, to investigate the wave processes that lead to the stratospheric anomalies themselves. Although not a primary focus, the experiments are furthermore expected to shed light on coupling between the tropical stratosphere and troposphere. The output requested will allow for a more detailed, process-based community analysis than has been possible with existing databases of subseasonal forecasts.

During the MAP D-PHASE (Mesoscale Alpine Programme, Demonstration of Probabilistic Hydrological and Atmospheric Simulation of flood Events in the Alpine region) Operational Period (DOP, 1 June–30 November 2007) the most intense precipitation event observed south of the Alps occurred over the Venice Lagoon. In the early morning of 26 September 2007, a mesoscale convective system formed in an area of convergence between a south-easterly low level jet flowing along the Adriatic Sea and a north-easterly barrier-type wind south of the Alps, and was responsible for precipitation exceeding 320 mm in less than 12 h, 240 mm of which in only 3 h. The forecast rainfall fields, provided by several convection resolving models operated daily for the D-PHASE project, have been compared. An analysis of different aspects of the event, such as the relevant mechanisms leading to the flood, the main characteristics of the MCS, and an estimation of the predictability of the episode, has been performed using a number of high resolution, convection resolving models (MOLOCH, WRF and MM5). Strong sensitivity to initial and boundary conditions and to model parameterization schemes has been found. Although low predictability is expected due to the convective nature of rainfall, the forecasts made more than 24 h in advance indicate that the larger scale environment driving the dynamics of this event played an important role in favouring the achievement of a relatively good accuracy in the precipitation forecasts.