Application of Regional Climate Models for Updating Intensity-duration-frequency Curves under Climate Change

Global Climate Models (GCMs) are currently the most powerful tools for accessing changes in the hydrological regime at the watershed scale due to climate change and variability. GCMs, however, have limitations due to their coarse spatial and temporal resolutions. Regional Climate Models (RCMs) are often referred to as suitable alternatives due to their higher resolution of the long-term climate projections. It is expected that RCMs are better for simulating extreme conditions than the GCMs. This present work, investigate the difference in updated IDF (Intensity-Duration-Frequency) relationships developed using GCMs and RCMs. The IDF updating method implemented with the IDF_CC tool for Canada has been used for comparison. The analyses are conducted using 369 selected Environment and Climate Change Canada hydro-meteorological stations from the IDF_CC tool database with record length longer than 20 years. Results for the future period (2020-2100), are based on multi-model ensembles of (i) the RCMs from the NA-CORDEX (North-American Coordinated Regional Climate Downscaling Experiment) project (ensemble 1) (ii) a sub-set of six GCMs from the GCMs available in the IDF_CC tool used as drivers for the RCMs (ensemble 2) and (iii) all 24 GCMs from the IDF_CC tool database (ensemble 3). One representative concentration pathway (RCP), RCP 8.5, is used in the analysis. The RCMs from the NA-CORDEX project selected for this study use six GCMs as drivers to produce the future predictions for the North American continent, including Canada. Two metrics are applied for the comparison of results: (i) the difference in projected precipitation using the multi-model ensemble median; and (ii) the difference in uncertainty range. The uncertainty range is defined in this study as the percentage projected change in future, 25 to 75 quantiles obtained using the RCMs a GCMs ensembles. The regional models from the NA-CORDEX project generated lower extreme precipitation projections than the GCMs for the stations located in the Canadian prairies (provinces of Alberta, Saskatchewan, Manitoba). Stations located at the East and West coasts of Canada show a smaller difference in the projected extremes obtained using GCMs and RCMs. The use of RCMs shows increase in uncertainty when compared to GCMs. This result indicates that even when using regional climate models, it’s advisable to extend the analyses and include as many as possible models from different climate centers.

Tecnopolíticas das mudanças climáticas: modelos climáticos, geopolítica e governamentalidade / The technopolitics of climate change: climate models, geopolitics, and governmentality

Resumo A partir de um estudo empírico sobre a modelagem climática no Instituto Nacional de Pesquisas Espaciais, no Brasil, este artigo discute como a prática da modelagem constitui-se em pragmáticas de governo das mudanças climáticas. Discute como tais pragmáticas dirigem-se à atuação geopolítica do Estado no regime internacional de produção do conhecimento climático global. Indica que a modelagem produz formas de leitura dos fenômenos e futuros impactos das mudanças climáticas em escala local, desdobrando-se em racionalidades governamentais de caráter biopolítico. Discute como a tecnociência da modelagem climática é construída como tecnologia e racionalidade governamental do Estado (governamentalidade), processo aqui chamado de tecnopolítica das mudanças climáticas.

Abstract Based on an empirical study of climate modeling at Brazil's Instituto Nacional de Pesquisas Espaciais, the article explores how climate modeling represents a pragmatic government approach in the realm of climate change. The discussion begins with how this pragmatic approach serves the purposes of the geopolitical action of the State within the international framework of global climate knowledge production. It then shows how modeling engenders forms of interpretation of climate change phenomena and future impacts on the local scale and finds expression in governmental rationalities of a biopolitical nature. In short, the discussion is how the technoscience of climate modeling is constructed as a governmental technology and rationality (governmentality) of the State, a process I call the technopolitics of climate change.

Quantifying Uncertainties in the Modelled Estimates of Extreme Precipitation Events at Upper Thames River Basin.

Assessment of climate change impact on hydrology at watershed scale incorporates downscaling of global scale climatic variables into local scale hydrologic variables and evaluation of future hydrologic extremes. The climatological inputs obtained from several global climate models suffer the limitations due to incomplete knowledge arising from the inherent physical, chemical processes and the parameterization of the model structure. Downscaled output from a single AOGCM with a single emission scenario represents only one of all possible future climate realizations; averaging outputs from multiple AOGCMs might underestimate the extent of future changes in the intensity and frequency of climatological variables. These available methods, thus cannot be representative of the full extent of climate change. Present research, therefore addresses two major questions: (i) should climate research adopt equal weights from AOGCM outputs to generate future climate?; and (ii) what is the probability of the future extreme events to be more severe? This paper explores the methods available for quantifying uncertainties from the AOGCM outputs and provides an extensive investigation of the nonparametric kernel estimator based on choice of bandwidths for investigating the severity of extreme precipitation events over the next century. The Sheather-Jones plug-in kernel estimate appears to be a major improvement over the parametric methods with known distribution. Results indicate increased probabilities for higher intensities and frequencies of events. The applied methodology is flexible and can be adapted to any uncertainty estimation studies with unknown densities. The presented research is expected to broaden our existing knowledge on the nature of the extreme precipitation events and the propagation and quantification of uncertainties arising from the global climate models and emission scenarios.