Richmont Graduate University

<strong class="journal-contentHeaderColor">Abstract.</strong> Emulators of Earth System Models (ESMs) are statistical models that approximate selected outputs of ESMs. Owing to their runtime-efficiency, emulators are especially useful whenever vast amounts of data are required, for example, for thoroughly exploring the emission space, for investigating high-impact low-probability events, or for estimating uncertainties and variability. This paper introduces an emulation framework that allows to emulate spatially explicit monthly mean precipitation fields using spatially explicit monthly mean temperature fields as forcing. The emulator is designed as an additional module within the MESMER(-M) emulation framework and its core relies on the concepts of Generalised Linear Models (GLMs). Precipitation at each (land-)grid point and for each month is approximated as a multiplicative model with two factors. The first factor entails the temperature-driven precipitation response and is assumed to follow a Gamma distribution with a logarithmic link function. The second factor is the residual variability of the precipitation field. The residual variability is assumed to be independent of temperature, but may still possess spatial precipitation correlations. Therefore, the monthly residual field is decomposed into independent Principal Components and subsequently approximated and sampled using a Kernel Density Estimation with a Gaussian kernel. The emulation framework is tested and validated using 24 ESMs from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6). For each ESM, we train on a single ensemble member across scenarios and evaluate the emulator performance using simulations with historical and SSP5-8.5 forcing. We show that the framework captures grid point specific precipitation characteristics, such as variability, trend and temporal auto-correlations. In addition, we find that emulated spatial (cross-variable) characteristics are consistent with that of ESMs. The framework is also able to capture compound hot-dry and cold-wet extremes, although it systematically underestimates their occurrence probabilities. The emulation of spatially explicit, coherent monthly temperature and precipitation timeseries is a major step towards the representation of impact-relevant variables of the climate system in a computational efficient manner.

<strong class="journal-contentHeaderColor">Abstract.</strong> Emulators of Earth System Models (ESMs) are statistical models that approximate selected outputs of ESMs. Owing to their runtime-efficiency, emulators are especially useful whenever vast amounts of data are required, for example, for thoroughly exploring the emission space, for investigating high-impact low-probability events, or for estimating uncertainties and variability. This paper introduces an emulation framework that allows to emulate spatially explicit monthly mean precipitation fields using spatially explicit monthly mean temperature fields as forcing. The emulator is designed as an additional module within the MESMER(-M) emulation framework and its core relies on the concepts of Generalised Linear Models (GLMs). Precipitation at each (land-)grid point and for each month is approximated as a multiplicative model with two factors. The first factor entails the temperature-driven precipitation response and is assumed to follow a Gamma distribution with a logarithmic link function. The second factor is the residual variability of the precipitation field. The residual variability is assumed to be independent of temperature, but may still possess spatial precipitation correlations. Therefore, the monthly residual field is decomposed into independent Principal Components and subsequently approximated and sampled using a Kernel Density Estimation with a Gaussian kernel. The emulation framework is tested and validated using 24 ESMs from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6). For each ESM, we train on a single ensemble member across scenarios and evaluate the emulator performance using simulations with historical and SSP5-8.5 forcing. We show that the framework captures grid point specific precipitation characteristics, such as variability, trend and temporal auto-correlations. In addition, we find that emulated spatial (cross-variable) characteristics are consistent with that of ESMs. The framework is also able to capture compound hot-dry and cold-wet extremes, although it systematically underestimates their occurrence probabilities. The emulation of spatially explicit, coherent monthly temperature and precipitation timeseries is a major step towards the representation of impact-relevant variables of the climate system in a computational efficient manner.

Theology and disability studies regularly engage both physical and cognitive impairments, with Peter Bellini’s recent work broadening the field to include even the psychiatric disability of depression (The Cerulean Soul, 2021). Other psychiatric disabilities also stand to be constructively engaged by theological discourse. This study takes up the subjects of anxiety and obsessive-compulsive disorder, especially variants which feature specifically religious anxiety, moral scrupulosity, and pathological guilt, illustrating how transactional understandings of forgiveness and atonement can covary with the symptomatology of such conditions, possibly even exacerbating them. In response, I conscript Martin Luther’s provocative but oft-neglected description of Christ’s “marvelous combat with the Law” in order to stage a uniquely “therapeutic” outlook on atonement in which Christ’s passion is rendered as a struggle with the uniquely psychological contours of moral performance and the felt experience of guilt under divine judgment, offering embodied hope to the anxious and scrupulous conscience.

Youths and parents/caregivers who have experienced multiple forms of severe interpersonal trauma may demonstrate severe and persistent symptoms of complex trauma including high-risk behaviors. Engagement, and sustaining engagement, of these youths and parents/caregivers in evidence-supported trauma treatment is a critical challenge, especially when youths or parents/caregivers have experienced chronic traumas that may be expected to continue into the foreseeable future. An extensive literature review was conducted leading to development of an assessment framework that could increase engagement of youths and parents/caregivers in trauma treatment based on research on chronic trauma, complex trauma, Developmental Trauma Disorder (DTD), and factors that promote engagement. A multi-dimensional assessment guide was developed to enable clinicians to differentiate types of chronic trauma based on a continuum of past, current and expected exposure over time and then to use this guide collaboratively with youths and parents/caregivers to develop priorities for treatment and service planning that matches their needs and strengths. The assessment guide incorporates exposure to intra-familial and community forms of interpersonal trauma, attachment disruptions, established symptoms of PTSD, Complex PTSD and DTD, as well as social-emotional development. The assessment and treatment planning guides proposed in this article expand applicability of evidence-supported trauma-informed therapy to youths and families who have not been engaged by programs offering treatments that are focused on past or single incident traumas or do not address disrupted attachments, multi-generational experiences of adversity, discrimination and community violence, life-threatening dangers or the impact of chronic trauma on youth, parent/caregiver and family development.