Downscaling extremes: A comparison of extreme value distributions in point-source and gridded precipitation data

There is substantial empirical and climatological evidence that precipitation extremes have become more extreme during the twentieth century, and that this trend is likely to continue as global warming becomes more intense. However, understanding these issues is limited by a fundamental issue of spatial scaling: most evidence of past trends comes from rain gauge data, whereas trends into the future are produced by climate models, which rely on gridded aggregates. To study this further, we fit the Generalized Extreme Value (GEV) distribution to the right tail of the distribution of both rain gauge and gridded events. The results of this modeling exercise confirm that return values computed from rain gauge data are typically higher than those computed from gridded data; however, the size of the difference is somewhat surprising, with the rain gauge data exhibiting return values sometimes two or three times that of the gridded data. The main contribution of this paper is the development of a family of regression relationships between the two sets of return values that also take spatial variations into account. Based on these results, we now believe it is possible to project future changes in precipitation extremes at the point-location level based on results from climate models.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS287 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Regional probabilities of precipitation change: A Bayesian analysis of multimodel simulations

Tebaldi et al. [2005] present a Bayesian approach to determining probability distribution functions (PDFs) of temperature change at regional scales, from the output of a multi-model ensemble, run under the same scenario of future anthropogenic emissions. The main characteristic of the method is the formalization of the two criteria of bias and convergence that the REA method [Giorgi and Mearns, 2002] first quantified as a way of assessing model reliability. Thus, the General Circulation Models (AOGCMs) of the ensemble are combined in a way that accounts for their performance with respect to current climate and a measure of each model's agreement with the majority of the ensemble. We apply the Bayesian model to a set of transient experiments under two SRES scenarios. We focus on predictions of precipitation change, for land regions of subcontinental size. We highlight differences in the PDFs of precipitation change derived in regions where models find easy agreement, and perform well in simulating present day precipitation, compared to regions where models have large biases, and/or their future projections disagree. We compare results from the two scenarios, thus assessing the consequences of the two alternative hypotheses, and present summaries based on their averaging

A tool for simulating and communicating uncertainty when modelling species distributions under future climates

Tools for exploring and communicating the impact of uncertainty on spatial prediction are urgently needed, particularly when projecting species distributions to future conditions. We provide a tool for simulating uncertainty, focusing on uncertainty due to data quality. We illustrate the use of the tool using a Tasmanian endemic species as a case study. Our simulations provide probabilistic, spatially explicit illustrations of the impact of uncertainty on model projections. We also illustrate differences in model projections using six different global climate models and two contrasting emissions scenarios. Our case study results illustrate how different sources of uncertainty have different impacts on model output and how the geographic distribution of uncertainty can vary. Synthesis and applications: We provide a conceptual framework for understanding sources of uncertainty based on a review of potential sources of uncertainty in species distribution modelling; a tool for simulating uncertainty in species distribution models; and protocols for dealing with uncertainty due to climate models and emissions scenarios. Our tool provides a step forward in understanding and communicating the impacts of uncertainty on species distribution models under future climates which will be particularly helpful for informing discussions between researchers, policy makers, and conservation practitioners

Simulating North American Weather Types With Regional Climate Models

Regional climate models (RCMs) are able to simulate small-scale processes that are missing in their coarser resolution driving data and thereby provide valuable climate information for climate impact assessments. Less attention has been paid to the ability of RCMs to capture large-scale weather types (WTs). An inaccurate representation of WTs can result in biases and uncertainties in current and future climate simulations that cannot be easily detected by standard model evaluation metrics. Here we define 12 hydrologically important WTs in the contiguous United States (CONUS). We test if RCMs from the North American CORDEX (NA-CORDEX) and the Weather Research and Forecasting (WRF) model large physics ensembles (WRF36) can capture those WTs in the current climate and how they simulate changes in the future. Our results show that the NA-CORDEX RCMs are able to simulate WTs more accurately than members of the WRF36 ensemble. The much larger WRF36 domain in combination with not constraining large-scale conditions by spectral nudging results in lower WT skill. The selection of the driving global climate model (GCM) has a large effect on the skill of NA-CORDEX simulations but a smaller impact on the WRF36 runs. The formulation of the RCM is of minor importance except for capturing the variability within WTs. Changing the model physics or increasing the RCM horizontal grid spacing has little effect. These results highlight the importance of selecting GCMs with accurate synoptic-scale variability for downscaling and to find a balance between large domains that can result in biased WT representations and small domains that inhibit the realistic development of mesoscale processes. At the end of the century, monsoonal flow conditions increase systematically by up to 30% and a WT that is a significant source of moisture for the Northern Plains during the growing seasons decreases systematically up to –30%

The vulnerability, impacts, adaptation and climate services advisory board (VIACS AB v1.0) contribution to CMIP6

This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts and adaptation of natural systems and society in relation to past, ongoing and projected future climate change. Much of this activity is directed toward the co-development of information needed by decision-makers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialogue between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs, and indicated user needs for the gridding and processing of model output

US National Climate Assessment (NCA) Scenarios for Assessing Our Climate Future: Issues and Methodological Perspectives Background Whitepaper for Participants

This whitepaper is intended to provide a starting point for discussion at a workshop for the National Climate Assessment (NCA) that focuses on the use and development of scenarios. The paper will provide background needed by participants in the workshop in order to review options for developing and using scenarios in NCA. The paper briefly defines key terms and establishes a conceptual framework for developing consistent scenarios across different end uses and spatial scales. It reviews uses of scenarios in past U.S. national assessments and identifies potential users of and needs for scenarios for both the report scheduled for release in June 2013 and to support an ongoing distributed assessment process in sectors and regions around the country. Because scenarios prepared for the NCA will need to leverage existing research, the paper takes account of recent scientific advances and activities that could provide needed inputs. Finally, it considers potential approaches for providing methods, data, and other tools for assessment participants. We note that the term 'scenarios' has many meanings. An important goal of the whitepaper (and portions of the workshop agenda) is pedagogical (i.e., to compare different meanings and uses of the term and make assessment participants aware of the need to be explicit about types and uses of scenarios). In climate change research, scenarios have been used to establish bounds for future climate conditions and resulting effects on human and natural systems, given a defined level of greenhouse gas emissions. This quasi-predictive use contrasts with the way decision analysts typically use scenarios (i.e., to consider how robust alternative decisions or strategies may be to variation in key aspects of the future that are uncertain). As will be discussed, in climate change research and assessment, scenarios describe a range of aspects of the future, including major driving forces (both human activities and natural processes), changes in climate and related environmental conditions (e.g., sea level), and evolution of societal capability to respond to climate change. This wide range of scenarios is needed because the implications of climate change for the environment and society depend not only on changes in climate themselves, but also on human responses. This degree of breadth introduces and number of challenges for communication and research

Identifying and developing therapeutic principles for trauma focused work in person-centred and emotion focused therapies

Background: The aim of this research was to identify facilitative therapeutic principles in person-centred and emotion-focused therapy for working with traumatised clients in the early stages of therapy. Methods: Four cases were selected from the Strathclyde Experiential Therapy for Social Anxiety archive: one good and one poor outcome case from each therapeutic approach. Outcomes were considered good and poor based on quantitative outcome measures. Each case met DSM-IV-TR diagnostic criteria for both PTSD and social anxiety. We developed a new method for the identification of therapeutic principles that offers an alternative to current approaches to competency identification. Our method uses a qualitative, bottom-up inductive process analysis. The first three sessions from each case were transcribed and independently analysed by two researchers (one blinded to the outcomes); the third researcher acted as consultant. The transcripts were analysed by focusing on session episode structure and treatment principles. Findings: Four trauma-focused therapist principles were identified: (a) support early relationship building/alliance formation; (b) facilitate client identification and recognition of past events as trauma experiences; (c) facilitate work on traumatic sources of current experiential and interpersonal difficulties; and (d) offer self-agency focused empathy. Conclusions: We conclude that our approach identifies and provides a new method for establishing person-centred experiential therapy principles for early trauma-focused work. Further research is recommended, and limitations are discussed