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Convective sea‐effect snowfall, in the form of snowbands, is observed over the northern Baltic Sea annually. Quasi‐stationary snowbands may last up to several days over the sea and, depending on the wind direction, move towards the coast. This study provides climatology of spatial and temporal occurrence of snowbands in Finland for a 48‐year period (1973–2020). We used a set of detection criteria together with ERA5 reanalysis at off‐shore areas and FMIClimGrid gridded observational data for on‐shore areas to find the days favouring snowband formation. Only those snowband days (SBD) when snow reached the Finnish coastal mainland were considered. The total annual number of SBDs in Finland varied from 6 to 40 with an average of 16. SBDs were detected most frequently over the Gulf of Bothnia near the western coast of the country. The largest increase in snow depth (SDI) during an SBD (67 cm/day) also took place on the western coast, although the long‐term mean of SDI (3–5 cm/day) was highest over the southern coast. Throughout the country, November and December showed the highest frequency of SBDs. However, between the periods 1973–1996 and 1997–2020, the seasonal cycle of SBDs shifted 1 month forward from late autumn to mid‐winter as the decrease in the number of SBDs during December as well as the increase during January and February were statistically significant in Finland. In northern Baltic Sea, long‐term increases in monthly means of sea surface temperature (SST) and air temperature at the atmospheric level of 850 hPa (T850) were in line with the decadal changes in the occurrence of SBDs. The increasing trend in SST favours the formation of snowbands but in late autumn the probability for snowband formation decreased because even larger increases in T850 resulted in diminishing differences between SST and T850. [ABSTRACT FROM AUTHOR]

A natural hazard is a naturally occurring extreme event with a negative effect on people and society or the environment. Natural hazards may have severe implications for human life and they can potentially generate economic losses and damage ecosystems. A better understanding of their major causes, probability of occurrence, and consequences enables society to be better prepared and to save human lives and to invest in adaptation options. Natural Hazards related to climate change are identified as one of the Grand Challenges in the Baltic Sea region. We here summarise existing knowledge of extreme events in the Baltic Sea region with the focus on past 200 years, as well as future climate scenarios. The events considered here are the major hydro-meteorological events in the region and include wind storms, extreme waves, high and low sea level, ice ridging, heavy precipitation, sea-effect snowfall, river floods, heat waves, ice seasons, and drought. We also address some ecological extremes and implications of extreme events for society (phytoplankton blooms, forest fires, coastal flooding, offshore infrastructures, and shipping). Significant knowledge gaps are identified, including the response of large scale atmospheric circulation to climate change, but also concerning specific events, for example, occurrences of marine heat waves and small-scale variability of precipitation. Suggestions for future research includes further development of high-resolution Earth System models, and the potential use of methodologies for data analysis (statistical methods and machine learning). With respect to expected impact of climate change, changes are expected for sea-level, extreme precipitation, heat waves and phytoplankton blooms (increase) and cold spells and severe ice winters (decrease). For some extremes (drying, river flooding and extreme waves) the change depends on the area and time period studies. [ABSTRACT FROM AUTHOR]

A sea-effect snowfall accumulated a national record-breaking snowdrift of 73 cm in Merikarvia, on the west coast of Finland, in less than one day on 8 January 2016. A good understanding of such heavy sea-effect snowfalls in the present climate is essential if we want to assess the probability of their occurrence and intensity in the future. Since very few in situ observations were made of the Merikarvia snowfall event in the sea area where the convection cells developed, we investigated the case with an ERA5 reanalysis, the Global Navigation Satellite System (GNSS), and the numerical weather prediction model HARMONIE, using weather radar information as a reference. We aimed to study the feasibility of the reanalysis and GNSS methods for investigating the basic characteristics of the snowband. In addition, we examined whether the assimilation of observed radar reflectivities could improve the HARMONIE simulations. In addition to snowfall patterns, the vertical structure of the atmosphere during the sea-effect snowfall case was analysed. HARMONIE was able to simulate the intensity of the sea-effect snowfall situation well, but the spatial spread of the snowfall remained too narrow, and the snowband was located slightly too far north compared to the radar observations. Assimilation of radar reflectivities increased the simulated moisture content in the vertical direction and spread the precipitation area horizontally, especially in the north-south direction, but shifted the most intense precipitation even more to the north. The location of the snowfall area was captured by ERA5, but the intensity was estimated to be considerably weaker, and the site of the most intense snowfall was more offshore compared to the radar observations and HARMONIE simulations. The vertical structure of specific humidity was similar and of the same order of magnitude in HARMONIE and ERA5. The GNSS, ERA5 and HARMONIE showed reasonably good agreement on the precipitable water content. The case study demonstrated that the three methods, and combinations of them, can be useful in order to obtain the best possible view of local severe weather events as possible. [ABSTRACT FROM AUTHOR]

Bias correction of precipitation and temperature of five Regional Climate Models (RCMs) was carried out using Distribution Based Scaling (DBS) method with two versions for precipitation adjustment: single gamma and double gamma. This data were then used as input for a hydrological model to simulate changes in floods by the end of this century, and the results were compared to corresponding changes simulated using delta change approach. The results show that while the DBS adjustment significantly improves the RCM precipitations and temperatures compared to observations, especially the double gamma distribution does not always preserve trends of the uncorrected RCM data. The simulation of floods in the control period is improved by the DBS adjustment with no significant differences between single and double gamma. However, some scenarios are still unable to match the observed hydrology adequately due to remaining biases especially in near zero winter temperatures. These scenarios may produce an unrealistic climate change signal and should therefore be discarded from further use. A simple criterion for evaluating the adequate performance of the RCMs and hydrological models compared to observed floods is presented. The results of climate change simulations show that extreme summer precipitations increase more than average values in Finland. The changes in floods by 2070-2099 vary in different regions depending on season and the main flood producing mechanism (snowmelt or heavy rain). The changes in floods simulated with the DBS adjusted RCM data are mostly similar as with delta change approach, but the DBS method produces larger range of changes. [ABSTRACT FROM AUTHOR]