Trend correlations for coastal eutrophication and its main local and whole-sea drivers - Application to the Baltic Sea.

Coastal eutrophication is a major environmental issue worldwide. In the Baltic Sea, eutrophication affects both the coastal waters and the open sea. Various policy frameworks aim to hinder its progress but eutrophication-relevant water quality variables, such as chlorophyll-a concentrations, still exhibit opposite temporal trends in various Baltic Sea marine and coastal waters. In this study, we investigate the temporal-trend linkages of measured water quality variables and their various anthropogenic, climatic and hydrospheric drivers over the period 1990-2020 with focus on the Swedish coastal waters and related marine basins in the Baltic Sea. We find that it is necessary to distinguish more and less isolated coastal waters, based on their water exchanges with the open sea, to capture different coastal eutrophication dynamics. In less isolated coastal waters, eutrophication is primarily related to nitrogen concentrations, while it is more related to phosphorus concentrations in more isolated coastal waters. In the open sea, trends in eutrophication conditions correlate best with trends in climatic and hydrospheric drivers, like wind speed and water salinity, respectively. In the coastal waters, driver signals are more mixed, with considerable influences from anthropogenic land-based nutrient loads and sea-ice cover duration. Summer chlorophyll-a concentration in the open sea stands out as a main change driver of summer chlorophyll-a concentration in less isolated coastal waters. Overall, coastal waters are a melting pot of driver influences over various scales, from local land-based drivers to large-scale total catchment and open sea conditions. The latter in turn depend on long-term integration of pathway-dependent influences from the various coastal parts of the Baltic Sea and their land-based nutrient load drivers, combined with overarching climate conditions and internal feedback loops. As such, our results challenge any unidirectional local source-to-sea paradigm and emphasize a need for concerted local land-catchment and whole-sea measures for robust coastal eutrophication management.

Effects of the tropospheric large-scale circulation on European winter temperatures during the period of amplified Arctic warming.

We investigate factors influencing European winter (DJFM) air temperatures for the period 1979-2015 with the focus on changes during the recent period of rapid Arctic warming (1998-2015). We employ meteorological reanalyses analysed with a combination of correlation analysis, two pattern clustering techniques, and back-trajectory airmass identification. In all five selected European regions, severe cold winter events lasting at least 4 days are significantly correlated with warm Arctic episodes. Relationships during opposite conditions of warm Europe/cold Arctic are also significant. Correlations have become consistently stronger since 1998. Large-scale pattern analysis reveals that cold spells are associated with the negative phase of the North Atlantic Oscillation (NAO-) and the positive phase of the Scandinavian (SCA+) pattern, which in turn are correlated with the divergence of dry-static energy transport. Warm European extremes are associated with opposite phases of these patterns and the convergence of latent heat transport. Airmass trajectory analysis is consistent with these findings, as airmasses associated with extreme cold events typically originate over continents, while warm events tend to occur with prevailing maritime airmasses. Despite Arctic-wide warming, significant cooling has occurred in northeastern Europe owing to a decrease in adiabatic subsidence heating in airmasses arriving from the southeast, along with increased occurrence of circulation patterns favouring low temperature advection. These dynamic effects dominated over the increased mean temperature of most circulation patterns. Lagged correlation analysis reveals that SCA- and NAO+ are typically preceded by cold Arctic anomalies during the previous 2-3 months, which may aid seasonal forecasting.

Variability of sea ice area in the Bohai Sea from 1958 to 2015.

With the backdrop of continuous global change, it is beneficial to create consistent long-term records of sea ice area on regional scales for ice disaster prevention and risk mitigation. In this study, a piecewise multiple nonlinear regression model was developed to reconstruct long-term daily sea ice area dataset in the Bohai Sea from 1958 to 2015 by linking the related meteorological data and the satellite-derived ice area. The validation analysis show that related meteorological status corresponding to physical process had stable skill of predictive ability, which was able to account for 81% of the observational variance under consideration of sea ice state, freezing and melting phases. The reconstructed daily sea ice area dataset was further used to study the interannual and seasonal variability of sea ice area. The annual maximum ice area (AMIA) and the annual average ice area (AAIA) in the Bohai Sea exhibited a decreasing trend with fluctuation of -0.33 ± 0.18% yr-1 and -0.51 ± 0.16% yr-1 over the period of 1958-2015, respectively. The most obvious change of the Bohai Sea ice area occurred in time scale of ~30 years. The whole study period could be divided into slight increasing stage (1958-1980), significant decreasing stage (1980-1995), and moderate increasing stage (1995-2015). In most years, the annual changes of sea ice area showed an unimodal variation and the freezing period (~65 days) was longer than the melting phase (~40 days) due to the relatively higher freezing rate. In addition, high correlations between AAIA and Arctic Oscillation (AO) index (r = -0.60, p < .01) and North Atlantic Oscillation (NAO) index (r = -0.69, p < .01) from 1958 to 2015 suggested AO and NAO are the primary large-scale climate factors driving the sea ice variability in the Bohai Sea.

Fire in Australian savannas: from leaf to landscape.

Savanna ecosystems comprise 22% of the global terrestrial surface and 25% of Australia (almost 1.9 million km2) and provide significant ecosystem services through carbon and water cycles and the maintenance of biodiversity. The current structure, composition and distribution of Australian savannas have coevolved with fire, yet remain driven by the dynamic constraints of their bioclimatic niche. Fire in Australian savannas influences both the biophysical and biogeochemical processes at multiple scales from leaf to landscape. Here, we present the latest emission estimates from Australian savanna biomass burning and their contribution to global greenhouse gas budgets. We then review our understanding of the impacts of fire on ecosystem function and local surface water and heat balances, which in turn influence regional climate. We show how savanna fires are coupled to the global climate through the carbon cycle and fire regimes. We present new research that climate change is likely to alter the structure and function of savannas through shifts in moisture availability and increases in atmospheric carbon dioxide, in turn altering fire regimes with further feedbacks to climate. We explore opportunities to reduce net greenhouse gas emissions from savanna ecosystems through changes in savanna fire management.