Spatiotemporal distribution of threatened high-latitude snowbed and snow patch habitats in warming climate

Peer reviewe

Regional effects of alternative climate change and management scenarios on timber production, economic profitability and carbon stocks in Norway spruce forests in Finland

We studied regional effects of alternative climate change and management scenarios on timber production, its economic profitability (NPV with 2% interest rate) and carbon stocks over a 90 years simulation period in Norway spruce forests located in southern, central and northern Finland. We also compared the results of optimised management plans (maximizing incomes) and fixed management scenarios. Business-as-usual (BAU) management recommendations were used as basis for alternative management scenarios. The forest ecosystem model SIMA together with a forest optimisation tool was employed. To consider the uncertainties related to climate change, we applied two climate change scenarios (SRES B1 and A2) in addition to the current climate. Results showed that timber production, NPV and carbon stocks of forests would reduce in southern Finland, opposite to northern Finland, and especially under the strong climate change scenario (SRES A2) compared to the current climate. In central Finland, climate change would have little effect. The use of optimised management plans also resulted in higher timber yield, NPV and carbon stock of forests compared to the use of a single management scenario, regardless of forest region and climate scenario applied. In the future, we may need to modify the current BAU management recommendations to properly adapt to the changing climatic conditions.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Statistics of sea-effect snowfall along the Finnish coastline based on regional climate model data

The formation of convective sea-effect snowfall (i.e., snow bands) is triggered by cold air outbreaks over a relatively warm and open sea. Snow bands can produce intense snowfall which can last for several days over the sea and potentially move towards the coast depending on wind direction. We defined the meteorological conditions which statistically favor the formation of snow bands over the north-eastern Baltic Sea of the Finnish coastline and investigated the spatio-temporal characteristics of these snow bands. A set of criteria, which have been previously shown to be able to detect the days favoring sea-effect snowfall for Swedish coastal area, were refined for Finland based on four case study simulations, utilizing a convection-permitting numerical weather prediction (NWP) model (HARMONIE-AROME). The main modification of the detection criteria concerned the threshold for 10 m wind speed: the generally assumed threshold value of 10 ms 1 was decreased to 7 ms(-1). The refined criteria were then applied to regional climate model (RCA4) data, for an 11-year time period (2000-2010). When only considering cases in Finland with onshore wind direction, we found on average 3 d yr(-1) with favorable conditions for coastal sea-effect snowfall. The heaviest convective snowfall events were detected most frequently over the southern coastline. Statistics of the favorable days indicated that the lower 10 m wind speed threshold improved the representation of the frequency of snow bands. For most of the favorable snow band days, the location and order of magnitude of precipitation were closely captured, when compared to gridded observational data for land areas and weather radar reflectivity images. Lightning were observed during one third of the favorable days over the Baltic Sea area

Towards extended shared socioeconomic pathways : A combined participatory bottom-up and top-down methodology with results from the Barents region

A major challenge in planning for adaptation to climate change is to assess future development not only in relation to climate but also in relation to social, economic and political changes that affect the capacity for adaptation or otherwise play a role in decision making. One approach is to use scenario methods. This article presents a methodology that combines top-down scenarios and bottom-up approaches to scenario building, with the aim of articulating local so-called extended socio-economic pathways. Specifically, we used the Shared Socioeconomic Pathways (SSPs) of the global scenario framework as developed by the climate research community to present boundary conditions about potential global change in workshop discussion with local and regional actors in the Barents region. We relate the results from these workshops to the different elements of the global SSPs and discuss potential and limitations of the method in relation to use in decision making processes

Natural hazards and extreme events in the Baltic Sea region

Funding Information: The development of approaches for calculating design parameters over the Baltic Sea has provided different estimations through time. The difference in these estimations (more than 10 %) is bigger than the effect from climate change calculated from different climate scenarios (a few percentage points). Climate modelling describes future scenarios and provides a coherent calculation of the whole set of environmental parameters, including wind, temperature, icing, and precipitation. One such output is from the Climate and Energy Systems (CES) research project supported by the Nordic Research Council (Thorsteinsson, 2011). This study features both opportunities and risks within the energy sector associated with climate change up to the mid-21st century. Fifteen combinations of regional and global climate models were used. The results, however, did not portray a consensus on the change in storms and extreme winds in the future over the Scandinavian seas (see also Sect. 2.2.1 and Belusic et al., 2019). Funding Information: Financial support. The contributions of Jari Haapala, Laura Tuomi, and Jani Särkkä have been supported by the Strategic Research Council at the Academy of Finland (SmartSea project; grant no. 292 985). Anna Rutgersson and Erik Nilsson have been supported by FORMAS (grant no. 2018-01784). Xiaoli Guo-Larsen has been supported by the Danish ForskEL/EUDP OffshoreWake project (grant no. PSO-5012521/64017-0017). Irina Danilovich’s studies were conducted as part of the “The Nature Resources and Ecological Safety” sub-programme within the framework of the “The Nature Management and Ecology” state research programme during 2016–2020. The contributions of Taru Olsson and Anna Lu-omaranta have been supported by the National Nuclear Waste Management Fund in Finland, Kirsti Jylhä has been supported by the Academy of Finland HEATCLIM project (grant no. 329307), and Taru Olsson has been supported by the Finnish Cultural Foundation (Satakunta Regional Fund). Publisher Copyright: © 2022 Anna Rutgersson et al.A natural hazard is a naturally occurring extreme event that has a negative effect on people and society or the environment. Natural hazards may have severe implications for human life and 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 to save human lives as well as to invest in adaptation options. Natural hazards related to climate change are identified as one of the Grand Challenges in the Baltic Sea region. Here, we summarize existing knowledge about extreme events in the Baltic Sea region with a focus on the past 200 years as well as on 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 levels, ice ridging, heavy precipitation, sea-effect snowfall, river floods, heat waves, ice seasons, and drought. We also address some ecological extremes and the implications of extreme events for society (phytoplankton blooms, forest fires, coastal flooding, offshore infrastructure, and shipping). Significant knowledge gaps are identified, including the response of large-scale atmospheric circulation to climate change and also concerning specific events, for example, the occurrence of marine heat waves and small-scale variability in precipitation. Suggestions for future research include the 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 the expected impacts 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 studied.Peer reviewe

Short-term emergency response planning and risk assessment via an integrated modeling system for nuclear power plants in complex terrain

Short-term predictions of potential impacts from accidental release of various radionuclides at nuclear power plants are acutely needed, especially after the Fukushima accident in Japan. An integrated modeling system that provides expert services to assess the consequences of accidental or intentional releases of radioactive materials to the atmosphere has received wide attention. These scenarios can be initiated either by accident due to human, software, or mechanical failures, or from intentional acts such as sabotage and radiological dispersal devices. Stringent action might be required just minutes after the occurrence of accidental or intentional release. To fulfill the basic functions of emergency preparedness and response systems, previous studies seldom consider the suitability of air pollutant dispersion models or the connectivity between source term, dispersion, and exposure assessment models in a holistic context for decision support. Therefore, the Gaussian plume and puff models, which are only suitable for illustrating neutral air pollutants in flat terrain conditional to limited meteorological situations, are frequently used to predict the impact from accidental release of industrial sources. In situations with complex terrain or special meteorological conditions, the proposing emergency response actions might be questionable and even intractable to decisionmakers responsible for maintaining public health and environmental quality. This study is a preliminary effort to integrate the source term, dispersion, and exposure assessment models into a Spatial Decision Support System (SDSS) to tackle the complex issues for short-term emergency response planning and risk assessment at nuclear power plants. Through a series model screening procedures, we found that the diagnostic (objective) wind field model with the aid of sufficient on-site meteorological monitoring data was the most applicable model to promptly address the trend of local wind field patterns. However, most of the hazardous materials being released into the environment from nuclear power plants are not neutral pollutants, so the particle and multi-segment puff models can be regarded as the most suitable models to incorporate into the output of the diagnostic wind field model in a modern emergency preparedness and response system. The proposed SDSS illustrates the state-of-the-art system design based on the situation of complex terrain in South Taiwan. This system design of SDSS with 3-dimensional animation capability using a tailored source term model in connection with ArcView® Geographical Information System map layers and remote sensing images is useful for meeting the design goal of nuclear power plants located in complex terrain. © 2012 Higher Education Press and Springer-Verlag Berlin Heidelberg