A “Novel Thunderstorm Alert System” (NOTHAS) has been developed and extensively tested for forecast and warnings of mid-latitude and tropical convective events. The design of the system showed some potential advantages compared to earlier alert systems, mainly in reducing uncertainties in predictions by taking the given maximum hourly local-scale signal. It represents a dynamic tool which allows the use of the probability concept of multivariate distribution and integrating it into general function by taking all convective parameters. It utilizes the latest developed microphysical parameterization scheme using a scale and aerosol awareness convective scheme and the sharpest criteria for mid-latitude storms. NOTHAS shows consistency and some kind of flexibility in post-processing applications, regardless of different parameterizations used in the ensemble or deterministic forecasts. The scientific verification shows a high level of accuracy in all significant scores which indicates that severe weather outlooks produced by NOTHAS for several hours ahead are in good alignment with observed thunderstorm activity. This novel tool shows a good performance which has sufficient merit for further additional testing and system evaluation of different severe mid-latitude and tropical storms, tropical cyclones and other severe weather cases across regions.

In view of the alarming situation related to coronavirus, of particular interest to the public, decision makers, health organizations, experts, professionals (epidemiologists, virologists, infectologists, psychologists, pulmonologists and others), it is also important to obtain seasonal weather outlook with general overview of the weather and climate conditions and how they would potentially affect the state of the COVID-19 transmission because a number of infectious diseases show seasonal features in their incidence. The analysis below represents an attempt to evaluate atmospheric processes that have a different spatiotemporal scale and depend on other modes of climate variability, and patterns of circulation and specific indices that affect seasonal variation and weather characteristics in a region. Based on seasonal outlook, the general impression is that sunny, warmer increase of (1.0 to 2.0 • C) and frequently stormy weather conditions expected during May-June 2020 could likely give some optimistic scenario of slowing down the spreading of the virus further. This is confirmed with the further evaluation of the effective reproduction number, that is expected to decrease from 1.8 at middle of April to 1.2 at the end of June 2020. That is approximately 60-70% reduction during this warmer period. However, the conclusions are still general and should be taken with caution as the situation is changing from day to day and many other factors including climate conditions, population density and medical care quality also play role in virus transmission.

Hurricane Ida ferociously affected many south-eastern and eastern parts of the United States, making it one of the strongest hurricanes in recent years. Advanced forecast and warning tool has been used to track the path of the ex-Hurricane, Ida, as it left New Orleans on its way towards the northeast, accurately predicting significant supercell development above New York City on September 01, 2021. This advanced method accurately detected the area with the highest possible level of convective instability with 24-h lead time and even Level 5, devised in the categorical outlooks legend of the system. Therefore, an extreme level implied a very high probability of the local-scale hazard occurring above the NYC. Cloud model output fields (updrafts and downdrafts, wind shear, near-surface convergence, the vertical component of relative vorticity) show the rapid development of a strong supercell storm with rotating updrafts and a mesocyclone. The characteristic hook-shaped echo signature visible in the reflectivity patterns indicates a signal for a highly precipitable (HP) supercell with the possibility of tornado initiation. Open boundary conditions represent a good basis for simulating a tornado that evolved from a supercell storm, initialized with initial data obtained from a real-time simulation in the period when the bow echo and tornado-like signature occurred. Тhe modeled results agree well with the observations.

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