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In order to effectively model the potential impacts of future climate change, there is a requirement for climate data inputs which (a) are of high spatial and temporal resolution, (b) explore a range of future climate change scenarios, (c) are consistent with historical observations in the historical period, and (d) provide an exploration of climate model uncertainty. This paper presents a suite of climate projections for the United Kingdom that conform to these requirements: CHESS-SCAPE. CHESS-SCAPE is a 1 km resolution dataset containing 11 near-surface meteorological variables that can be used to as input to many different impact models. The variables are available at several time resolutions, from daily to decadal means, for the years 1980–2080. It was derived from the state-of-the art regional climate projections in the United Kingdom Climate Projections 2018 (UKCP18) regional climate model (RCM) 12 km ensemble, downscaled to 1 km using a combination of physical and empirical methods to account for local topographic effects. CHESS-SCAPE has four ensemble members, which were chosen to span the range of temperature and precipitation change in the UKCP18 ensemble, representing the ensemble climate model uncertainty. CHESS-SCAPE consists of projections for four emissions scenarios, given by the Representative Concentration Pathways 2.6, 4.5, 6.0 and 8.5, which were derived from the UKCP18 RCM RCP8.5 scenarios using time shifting and pattern scaling. These correspond to UK annual warming projections of between 0.9–1.9 K for RCP2.6 up to 2.8–4.3 K for RCP8.5 between 1980–2000 and 2060–2080. Little change in annual precipitation is projected, but larger changes in seasonal precipitation are seen with some scenarios projecting large increases in precipitation in the winter (up to 22 %) and large decreases in the summer (up to - 39 %). All four RCP scenarios and ensemble members are also provided with bias correction, using the CHESS-met historical gridded dataset as a baseline. With high spatial and temporal resolution, an extensive range of warming scenarios and multiple ensemble members, CHESS-SCAPE provides a comprehensive data resource for modellers of climate change impacts in the UK. The CHESS-SCAPE data are available for download from the NERC EDS Centre for Environmental Data Analysis: 10.5285/8194b416cbee482b89e0dfbe17c5786c. [ABSTRACT FROM AUTHOR]

In order to effectively model the potential impacts of future climate change, there is a requirement for climate data inputs which are a) high spatial and temporal resolution; b) explore a range of future climate change scenarios; c) are consistent with historical observations in the historical period; and d) provide an exploration of climate model uncertainty. This paper presents a suite of climate projections for the United Kingdom that conform to these requirements: CHESS-SCAPE. CHESS-SCAPE is a 1 km resolution dataset containing eleven near-surface meteorological variables that can be used to as input to many different impacts models. The variables are available at several time resolutions, from daily to decadal means, for the years 1980-2080. It was derived from the state-of the art regional climate projections in the United Kingdom Climate Projections 2018 (UKCP18) Regional Climate Model (RCM) UKCP18 12 km ensemble, downscaled to 1 km using a combination of physical and empirical methods to account for local topographic effects. CHESS-SCAPE has four ensemble members, which were chosen to span the range of temperature and precipitation change in the UKCP18 ensemble, representing the ensemble climate model uncertainty. CHESS-SCAPE consists of projections for four emissions scenarios, given by the Representative Concentration Pathways: RCP2.6, 4.5, 6.0 and 8.5, which were derived from the UKCP18 RCM RCP8.5 scenarios using time shifting and pattern scaling. These correspond to UK annual warming projections of between 0.9-1.9 K for RCP2.6 up to 2.8-4.3 K for RCP8.5 between 1980-2000 and 2060-2080. Little change in annual precipitation is projected, but larger changes in seasonal precipitation are seen with some scenarios projecting large increases in precipitation in the winter (up to 22 %) and large decreases in the summer (up to -39 %). All four RCP scenarios and ensemble members are also provided with bias-correction, using the CHESS-met historical gridded dataset as a baseline. With high spatial and temporal resolution, extensive range of warming scenarios and multiple ensemble members, CHESS-SCAPE provides a comprehensive data resource for modellers of climate change impacts in the UK. The CHESS-SCAPE data are available for download from the NERC EDS Centre for Environmental Data Analysis: http://dx.doi.org/10.5285/8194b416cbee482b89e0dfbe17c5786c (Robinson et al., 2022). [ABSTRACT FROM AUTHOR]

In this paper, I will share findings from a qualitative study that offers a thematic analysis of 76 interviews with Muslim patients and families as well as doctors, nurses, allied health professionals, chaplains and community faith leaders across the United Kingdom. The data show that for many Muslims, Islam—its texts and lived practice—is of central importance when they are deliberating about death and dying. Central to these deliberations are virtues rooted within Islamic theology and ethics, the traditions of adab (virtue) and aqhlaq (proper conduct). Themes analysed include theological and moral understandings around the virtues of hope and acceptance. The study provides an analysis of these themes in relation to the experiences of Muslim patients and families arriving at meaning making around death and dying and how this interfaces with their interaction with biomedicine and healthcare. The study shows that the juxtaposition of different values and moral frameworks require careful negotiation when Muslim patients and families encounter the healthcare system. The study also describes how healthcare professionals and staff of other faiths and no faith encounter Muslim beliefs and practices, and the challenges they face in interpreting virtues and values rooted in faith, especially when these are perceived to be mutually opposed or inconsistent. [ABSTRACT FROM AUTHOR]