Climate change threatens mental health via increasing exposure to the social and economic disruptions created by extreme weather and large-scale climatic events, as well as through the anxiety associated with recognising the existential threat posed by the climate crisis. Considering the growing levels of climate change awareness across the world, negative emotions like anxiety and worry about climate-related risks are a potentially pervasive conduit for the adverse impacts of climate change on mental health. In this study, we examined how negative climate-related emotions relate to sleep and mental health among a diverse non-representative sample of individuals recruited from 25 countries, as well as a Norwegian nationally-representative sample. Overall, we found that negative climate-related emotions are positively associated with insomnia symptoms and negatively related to self-rated mental health in most countries. Our findings suggest that climate-related psychological stressors are significantly linked with mental health in many countries and draw attention to the need for cross-disciplinary research aimed at achieving rigorous empirical assessments of the unique challenge posed to mental health by negative emotional responses to climate change.

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In hydro-meteorological trend analysis, an alteration in the given variable is detected by considering the long-term series as a whole. Whereas the long-term trend may be absent, the significance of hidden (short-durational) sub-trends in the series may be important for environmental management practices. In this paper, a graphical approach of identifying trend or sub-trends using nonparametric cumulative rank difference (CRD) was proposed. To confirm the significance of the visualized trend, the CRD was translated from the graphical to a statistical metric. To assess its capability, the performance of the CRD method was compared with that of the well-known Mann-Kendall (MK) test. The graphical and statistical CRD techniques were applied to detect trends and subtrends in the annual rainfall of 10 River Nile riparian countries (RNRCs). The co-occurrence of the trend evolutions in the rainfall with those of the large-scale oceanatmosphere interactions was analyzed. The power of the CRD method was shown to closely agree with that of the MK test under the various circumstances of sample sizes, variations, linear trend slopes, and serial correlations. At the level of significance a = 5 %, the long-term trends were found present in 30 % of the RNRCs. However at a = 5 %, the main downward (upward) sub-trends were found significant in 30 (60 %) of the RNRCs. Generally at a = 1 %, linkages of the trend evolutions in the rainfall of the RNRCs were found to those of the influences from the Atlantic and Indian Oceans. At a = 5 %, influences from the Pacific Ocean on the rainfall trends of some countries were also evident.

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