Forecasting COVID-19-Associated Hospitalizations under Different Levels of Social Distancing in Lombardy and Emilia-Romagna, Northern Italy: Results from an Extended SEIR Compartmental Model.

The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of 17 April 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world's centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment L was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations; on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic.

The typhoon-induced drying of the Maritime Continent.

The Maritime Continent plays a role in the global circulation pattern, due to the energy released by convective condensation over the region which influences the global atmospheric circulation. We demonstrate that tropical cyclones contribute to drying the Maritime Continent atmosphere, influencing the definition of the onset of the dry season. The process was investigated using observational data and reanalysis. Our findings were confirmed by numerical experiments using low- and high-resolution versions of the CMCC-CM2 General Circulation Model contributing to the HighResMIP CMIP6 effort.

Remote subsurface ocean temperature as a predictor of Atlantic hurricane activity.

Predicting North Atlantic hurricane activity months in advance is of great potential societal significance. The ocean temperature, both in terms of North Atlantic/tropical averages and upper ocean heat content, is demonstrated to be a significant predictor. To investigate the relationship between the thermal state of the Atlantic Ocean and the tropical cyclone (TC) activity in terms of accumulated cyclone energy (ACE), we use observed 1980-2015 TC records and a 1/4° resolution global ocean reanalysis. This paper highlights the nonlocal effect associated with eastern Atlantic Ocean temperature, via a reduction of wind shear, and provides additional predictive skill of TC activity, when considering subsurface temperature instead of sea surface temperature (SST) only. The most active TC seasons occur for lower than normal wind shear conditions over the main development region, which is also driven by reduced trade wind strength. A significant step toward operationally reliable TC activity predictions is gained after including upper ocean mean temperatures over the eastern Atlantic domain. Remote effects are found to provide potential skill of ACE up to 3 months in advance. These results indicate that consideration of the upper 40-m ocean average temperature improves upon a prediction of September Atlantic hurricane activity using only SST.

Observed shift towards earlier spring discharge in the main Alpine rivers.

In this study, we analyse the observed long-term discharge time-series of the Rhine, the Danube, the Rhone and the Po rivers. These rivers are characterised by different seasonal cycles reflecting the diverse climates and morphologies of the Alpine basins. However, despite the intensive and varied water management adopted in the four basins, we found common features in the trend and low-frequency variability of the spring discharge timings. All the discharge time-series display a tendency towards earlier spring peaks of more than two weeks per century. These results can be explained in terms of snowmelt, total precipitation (i.e. the sum of snowfall and rainfall) and rainfall variability. The relative importance of these factors might be different in each basin. However, we show that the change of seasonality of total precipitation plays a major role in the earlier spring runoff over most of the Alps.

The path integral formulation of climate dynamics.

The chaotic nature of the atmospheric dynamics has stimulated the applications of methods and ideas derived from statistical dynamics. For instance, ensemble systems are used to make weather predictions recently extensive, which are designed to sample the phase space around the initial condition. Such an approach has been shown to improve substantially the usefulness of the forecasts since it allows forecasters to issue probabilistic forecasts. These works have modified the dominant paradigm of the interpretation of the evolution of atmospheric flows (and oceanic motions to some extent) attributing more importance to the probability distribution of the variables of interest rather than to a single representation. The ensemble experiments can be considered as crude attempts to estimate the evolution of the probability distribution of the climate variables, which turn out to be the only physical quantity relevant to practice. However, little work has been done on a direct modeling of the probability evolution itself. In this paper it is shown that it is possible to write the evolution of the probability distribution as a functional integral of the same kind introduced by Feynman in quantum mechanics, using some of the methods and results developed in statistical physics. The approach allows obtaining a formal solution to the Fokker-Planck equation corresponding to the Langevin-like equation of motion with noise. The method is very general and provides a framework generalizable to red noise, as well as to delaying differential equations, and even field equations, i.e., partial differential equations with noise, for example, general circulation models with noise. These concepts will be applied to an example taken from a simple ENSO model.

Integration of research advances in modelling and monitoring in support of WFD river basin management planning in the context of climate change.

The integration of scientific knowledge about possible climate change impacts on water resources has a direct implication on the way water policies are being implemented and evolving. This is particularly true regarding various technical steps embedded into the EU Water Framework Directive river basin management planning, such as risk characterisation, monitoring, design and implementation of action programmes and evaluation of the "good status" objective achievements (in 2015). The need to incorporate climate change considerations into the implementation of EU water policy is currently discussed with a wide range of experts and stakeholders at EU level. Research trends are also on-going, striving to support policy developments and examining how scientific findings and recommendations could be best taken on board by policy-makers and water managers within the forthcoming years. This paper provides a snapshot of policy discussions about climate change in the context of the WFD river basin management planning and specific advancements of related EU-funded research projects. Perspectives for strengthening links among the scientific and policy-making communities in this area are also highlighted.