A Decade of Climate Scenarios: The Ouranos Consortium Modus Operandi

Abstract

The first 10 years of the Ouranos Consortium are reviewed with a focus on the creation and delivery of climate scenarios for a wide range of users.

PyWPS: overview, new features in version 4 and existing implementations

“…Ouranos is a consortium on regional climatology based in Montréal, whose mission is to support adaptation to climate change [40]. This involves working with engineers, biologists, urban planners and professionals from dozens of different disciplines to understand their climate data needs and provide them with clear, understandable and actionable information.…”

“…This involves working with engineers, biologists, urban planners and professionals from dozens of different disciplines to understand their climate data needs and provide them with clear, understandable and actionable information. To speed-up and standardize the delivery of climate services to users and facilitate collaborations with academics, Ouranos has been developing with the Centre de Recherche en Informatique de Montréal (CRIM) and the Birdhouse community a climate service platform based on WPS [40]. The platform includes a handful of thematic servers powered by PyWPS, offering tools to search data catalogues, compute climate indices, subset and aggregate climate data, run hydrological models using climate projections and a number of other specialized algorithms.…”

Preparing local climate change scenarios for the Netherlands using resampling of climate model output

“…Scenarios of future climate change are important tools to assist society to prepare for future climate conditions (Dessai et al 2005, Wilby et al 2009. Climate scenarios are plausible future climate states, containing sets of climatological variables that are (to a certain degree) physically consistent (van den Hurk et al 2013a, Huard et al 2014).…”

“…For instance, Whetton et al (2012) describe for Australia an iterative methodology in which the most relevant GCM results are selected in consultation with the end users. A similar approach is followed in Canada (Huard et al 2014). While many of these scenarios share similar approaches, different choices are made on a detailed level, for instance concerning the actual model data that is used.…”

“…While many of these scenarios share similar approaches, different choices are made on a detailed level, for instance concerning the actual model data that is used. These decisions often depend on expert judgment (Murphy et al 2007, Lenderink et al 2007, Huard et al 2014.…”