Drought hazards and stakeholder perception: Unraveling the interlinkages between drought severity, perceived impacts, preparedness, and management.

The future risk for droughts and water shortages calls for substantial efforts by authorities to adapt at local levels. Understanding their perception of drought hazards, risk and vulnerability can help to identify drivers of and barriers to drought risk planning and management in a changing climate at the local level. This paper presents a novel interdisciplinary drought case study in Sweden that integrates soft data from a nationwide survey among more than 100 local practitioners and hard data based on hydrological measurements to provide a holistic assessment of the links between drought severity and the perceived levels of drought severity, impacts, preparedness, and management for two consecutive drought events. The paper highlights challenges for drought risk planning and management in a changing climate at the local level and elaborates on how improved understanding of local practitioners to plan for climate change adaptation can be achieved.

Uni- and multivariate bias adjustment methods in Nordic catchments: Complexity and performance in a changing climate.

For climate-change impact studies at the catchment scale, meteorological variables are typically extracted from ensemble simulations provided by global and regional climate models, which are then downscaled and bias-adjusted for each study site. For bias adjustment, different statistical methods that re-scale climate model outputs have been suggested in the scientific literature. They range from simple univariate methods that adjust each meteorological variable individually, to more complex and more demanding multivariate methods that take existing relationships between meteorological variables into consideration. Over the past decade, several attempts have been made to evaluate such methods in various regions. There is, however, still no guidance for choosing appropriate bias adjustment methods for a study at hand. In particular, the question whether the benefits of potentially improved adjustments outweigh the cost of increased complexity, remains unanswered. This paper presents a comprehensive evaluation of the performance of two commonly used univariate and two multivariate bias adjustment methods in reproducing numerous univariate, multivariate and temporal features of precipitation and temperature series in different catchments in Sweden. The paper culminates in a discussion on trade-offs between the potential benefits (i.e., skills and added value) and disadvantages (complexity and computational demand) of each method to offer plausible, defensible and actionable insights from the standpoint of climate-change impact studies in high latitudes. We concluded that all selected bias adjustment methods generally improved the raw climate model simulations, but that not a single method consistently outperformed the other methods. There were, however, differences in the methods' performance for particular statistical features, indicating that other practical aspects such as computational time and heavy theoretical requirements should also be taken into consideration when choosing an appropriate bias adjustment method.

SDG partnerships may perpetuate the global North-South divide.

The 2030 Agenda for Sustainable Development gives equal emphasis to developed ("Northern") countries and developing ("Southern") countries. Thus, implementation of the Sustainable Development Goals (SDGs) demands coherent collaboration to transform society across all countries. Yet, there has been little research published on SDG partnerships and this is the first study to explore the extent to which partners from Northern and Southern countries are involved in them and their focus. It identifies that involvement is unequally distributed and may perpetuate the North-South divide in countries' resources, including access to data and scientific capacities. Most notably, partners from low-income countries are involved in far fewer partnerships than partners from countries in all other World Bank income categories, although the former are least able to develop sustainably. As such, all those promoting sustainable development from governmental, private and third-sector organisations need to address global inequalities in establishing and implementing SDG partnerships if, collectively, they are to facilitate delivery of Agenda 2030.

Including hydrological self-regulating processes in peatland models: Effects on peatmoss drought projections.

The water content of the topsoil is one of the key factors controlling biogeochemical processes, greenhouse gas emissions and biosphere - atmosphere interactions in many ecosystems, particularly in northern peatlands. In these wetland ecosystems, the water content of the photosynthetic active peatmoss layer is crucial for ecosystem functioning and carbon sequestration, and is sensitive to future shifts in rainfall and drought characteristics. Current peatland models differ in the degree in which hydrological feedbacks are included, but how this affects peatmoss drought projections is unknown. The aim of this paper was to systematically test whether the level of hydrological detail in models could bias projections of water content and drought stress for peatmoss in northern peatlands using downscaled projections for rainfall and potential evapotranspiration in the current (1991-2020) and future climate (2061-2090). We considered four model variants that either include or exclude moss (rain)water storage and peat volume change, as these are two central processes in the hydrological self-regulation of peatmoss carpets. Model performance was validated using field data of a peatland in northern Sweden. Including moss water storage as well as peat volume change resulted in a significant improvement of model performance, despite the extra parameters added. The best performance was achieved if both processes were included. Including moss water storage and peat volume change consistently reduced projected peatmoss drought frequency with >50%, relative to the model excluding both processes. Projected peatmoss drought frequency in the growing season was 17% smaller under future climate than current climate, but was unaffected by including the hydrological self-regulating processes. Our results suggest that ignoring these two fine-scale processes important in hydrological self-regulation of northern peatlands will have large consequences for projected climate change impact on ecosystem processes related to topsoil water content, such as greenhouse gas emissions.

Effect of climate change on soil temperature in Swedish boreal forests.

Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions.