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Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Missing Data Imputation Of High-Resolution Temporal Climate Time Series Data, Eben Afrifa-Yamoah, Ute A. Mueller, S. M. Taylor, A. J. Fisher
Missing Data Imputation Of High-Resolution Temporal Climate Time Series Data, Eben Afrifa-Yamoah, Ute A. Mueller, S. M. Taylor, A. J. Fisher
Research outputs 2014 to 2021
© 2020 The Authors. Meteorological Applications published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. Analysis of high-resolution data offers greater opportunity to understand the nature of data variability, behaviours, trends and to detect small changes. Climate studies often require complete time series data which, in the presence of missing data, means imputation must be undertaken. Research on the imputation of high-resolution temporal climate time series data is still at an early phase. In this study, multiple approaches to the imputation of missing values were evaluated, including a structural time series model with Kalman smoothing, …
Multiple Impact Pathways Of The 2015–2016 El Niño In Coastal Kenya, Matt Fortnam, Molly Atkins, Katrina Brown, Tomas Chaigneau, Ankje Frouws, Kemyline Gwaro, Mark Huxham, James Kairo, Amon Kimeli, Bernard Kirui, Katy Sheen
Multiple Impact Pathways Of The 2015–2016 El Niño In Coastal Kenya, Matt Fortnam, Molly Atkins, Katrina Brown, Tomas Chaigneau, Ankje Frouws, Kemyline Gwaro, Mark Huxham, James Kairo, Amon Kimeli, Bernard Kirui, Katy Sheen
Research outputs 2014 to 2021
© 2020, The Author(s). The 2015–2016 El Niño had large impacts globally. The effects were not as great as anticipated in Kenya, however, leading some commentators to call it a ‘non-event’. Our study uses a novel combination of participatory Climate Vulnerability and Capacity Analysis tools, and new and existing social and biophysical data, to analyse vulnerability to, and the multidimensional impacts of, the 2015–2016 El Niño episode in southern coastal Kenya. Using a social-ecological systems lens and a unique dataset, our study reveals impacts overlooked by conventional analysis. We show how El Niño stressors interact with and amplify existing vulnerabilities …