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    Cascade-based disaggregation of continuous rainfall time series: The influence of climate
    (Göttingen : Copernicus GmbH, 2001) Güntner, A.; Olsson, J.; Calver, A.; Gannon, B.
    Rainfall data of high temporal resolution are required in a multitude of hydrological applications. In the present paper, a temporal rainfall disaggregation model is applied to convert daily time series into an hourly resolution. The model is based on the principles of random multiplicative cascade processes. Its parameters are dependent on (1) the volume and (2) the position in the rainfall sequence of the time interval with rainfall to be disaggregated. The aim is to compare parameters and performance of the model between two contrasting climates with different rainfall generating mechanisms, a semi-arid tropical (Brazil) and a temperate (United Kingdom) climate. In the range of time scales studied, the scale-invariant assumptions of the model are approximately equally well fulfilled for both climates. The model parameters differ distinctly between climates, reflecting the dominance of convective processes in the Brazilian rainfall and of advective processes associated with frontal passages in the British rainfall. In the British case, the parameters exhibit a slight seasonal variation consistent with the higher frequency of convection during summer. When applied for disaggregation, the model reproduces a range of hourly rainfall characteristics with a high accuracy in both climates. However, the overall model performance is somewhat better for the semi-arid tropical rainfall. In particular, extreme rainfall in the UK is overestimated whereas extreme rainfall in Brazil is well reproduced. Transferability of parameters in time is associated with larger uncertainty in the semi-arid climate due to its higher interannual variability and lower percentage of rainy intervals. For parameter transferability in space, no restrictions are found between the Brazilian stations whereas in the UK regional differences are more pronounced. The overall high accuracy of disaggregated data supports the potential usefulness of the model in hydrological applications.
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    Variations in sustainable development goal interactions: Population, regional, and income disaggregation
    (New York, NY [u.a.] : Wiley, 2020) Warchold, Anne; Pradhan, Prajal; Kropp, Jürgen P.
    To fulfill the 2030 Agenda, the complexity of sustainable development goal (SDG) interactions needs to be disentangled. However, this understanding is currently limited. We conduct a cross-sectional correlational analysis for 2016 to understand SDG interactions under the entire development spectrum. We apply several correlation methods to classify the interaction as synergy or trade-off and characterize them according to their monotony and linearity. Simultaneously, we analyze SDG interactions considering population, location, income, and regional groups. Our findings highlight that synergies always outweigh trade-offs and linear outweigh non-linear interactions. SDG 1, 5, and 6 are associated with linear synergies, SDG 3, and 7 with non-linear synergies. SDG interactions vary according to a country's income and region along with the gender, age, and location of its population. In summary, to achieve the 2030 Agenda the detected interactions and inequalities across countries need be tracked and leveraged to “leave no one behind.”