Evaluation of CORDEX-Arctic daily precipitation and temperature-based climate indices over Canadian Arctic land areas

Diaconescu, Emilia Paula; Mailhot, Alain; Brown, Ross; Chaumont, Diane

doi:10.1007/s00382-017-3736-4

Cited by 44 publications

(47 citation statements)

References 87 publications

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“…High values of similarity metrics such as correlation coefficients or NSE do not necessarily imply high distributional or temporal structure similarity (Mo et al, ). The results here are consistent with the general findings of Wong et al () and Diaconescu et al (); however, the graphical techniques presented provide additional insight into the shortcomings of gridded datasets that may not be evident in statistical performance measures (Crout et al, ). For example, in MERRA‐2 T max (Figure c), there is a clear discontinuity where the gridded temperatures are near 0°C.…”

Section: Discussionsupporting

confidence: 91%

“…Gridded hydrometerological products (gridded datasets) can be a complement to the existing sparse data network. Gridded datasets have been used to characterize the variability and trends of hydroclimate systems where observations are sparse or do not exist (e.g., Snauffer, Hsieh, & Cannon, ; Way, Oliva, & Viau, ; Woo & Rouse, ), to assess the outputs of global and regional climate models (e.g., Diaconescu, Mailhot, Brown, & Chaumont, ; Field, Barros, Stocker, & Dahe, ), and to study hydro‐ecological responses to changing climate (e.g., Price et al, ).…”

Section: Introductionmentioning

confidence: 99%

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Evaluating the suitability of three gridded‐datasets and their impacts on hydrological simulation at Scotty Creek in the southern Northwest Territories, Canada

Persaud

Whitfield

Quinton

et al. 2020

Hydrological Processes

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In the southern Northwest Territories (NWT), long time series of historical observations of climate and hydrology are scarce. Gridded datasets have been used as an alternative to instrumental observations for climate analysis in this area, but not for driving models to understand hydrological processes in the southern NWT. The suitability of temperature and precipitation from three-gridded datasets (Australian National University Spline [ANUSPLIN], ERA-Interim, and Modern-Era Retrospective Analysis for Research and Application, Version 2 [MERRA-2]) as forcings for hydrological modelling in a small subcatchment in the southern NWT are assessed. Multiple statistical techniques are used to ensure that structural and temporal attributes of the observational datasets are adequately compared. Daily minimum and maximum air temperatures in gridded datasets are more similar to observations than precipitation. The ANUSPLIN temperature time series are more statistically similar to observations, based on population statistics and temporal structure, than either of ERA-Interim or MERRA-2. The gridded datasets capture the seasonal and annual seasonal variability of precipitation but with large biases.ANUSPLIN precipitation compares better with observations than either ERA-Interim or MERRA-2 precipitation. The biases in these gridded datasets affect run-off simulations.The biases in hydrological simulations are predictable from the statistical differences between gridded datasets and observations and can be used to make informed choices about their use.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Evaluating the suitability of three gridded‐datasets and their impacts on hydrological simulation at Scotty Creek in the southern Northwest Territories, Canada

Persaud

Whitfield

Quinton

et al. 2020

Hydrological Processes

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“…Inuit exposure, sensitivity and adaptive capacity to climate change Inuit exposure to climate change In the exposure layer, extreme weather has the largest degree centrality (C D =27, figure 4, table 3) and would therefore affect many variables within the Inuit vulnerability system. Temperature is the second most central variable (C D =24) and is expected to increase with climate change, leaving the region more prone to disasters such as floods (C D =24) or storm surges (C D =20) [51,52]. Combining quantitative metrics with qualitative systems understanding can help parameterize a vulnerability model.…”

Section: Resultsmentioning

confidence: 99%

A systems network approach for climate change vulnerability assessment

Debortoli

Sayles

Clark

et al. 2018

Environ. Res. Lett.

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Vulnerability to climate change is a product of biophysical and social dynamics. Assessments of community or regional vulnerability, however, often focus on quantitative infrastructure and environmental assessments, or qualitative assessments of a community's social dynamics and livelihood activities. A dearth of integrated quantitative assessments is a major barrier for decision makers who require quantitative outputs and indicators, which can measure where vulnerability is most severe and can be linked to climate projections. Our framework and analysis helps address such gaps by identifying variables to build climate change vulnerability indices, which we pilot here focusing on Inuit communities in the Canadian Arctic. We start with a systematic literature review of community-based vulnerability studies and assess relationships among 58 social and biophysical variables. We then use multiplex network analysis to determine how social and environmental variables interact among and within the key component of vulnerability: exposure, sensitivity, and adaptive capacity. We identify several structurally important variables that interact within and across the three dimensions of vulnerability. This method is transferable as an integrative means of understanding not only the direct causes of vulnerability, but also relations that are less tangible. The approach of multiplex network analysis can be a building block to ongoing development of vulnerability indices within the human dimensions of climate change field.

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“…Here we use highresolution regional climate model simulations and it has been shown that regional climate model simulations provide more realistic information of precipitation, with intensities and frequencies comparable to the recorded station data (Chan et al, 2013), than global climate models. To make a direct comparison between station data and model simulations, some studies remap the gauge measurements onto a regular grid similar to the simulations (Diaconescu et al, 2016), some interpolate the model grid points to the gauge locations (Xie et al, 2019), and some directly choose the grid points closest to the stations (Diaconescu et al, 2018;Pendergrass and Knutti, 2018). Here we choose the simplest way, in that we selected the closest grid point to compare with station observations.…”

Section: Methodsmentioning

confidence: 99%

Power‐law behaviour of hourly precipitation intensity and dry spell duration over the United States

Yang

Franzke

2019

Intl Journal of Climatology

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Precipitation is an important meteorological variable which is critical for weather risk assessment. For instance, intense but short precipitation events can lead to flash floods and landslides. Most statistical modelling studies assume that the occurrence of precipitation events is based on a Poisson process with exponentially distributed waiting times while precipitation intensities are typically described by a gamma distribution or a mixture of two exponential distributions. Here, we show by using hourly precipitation data over the United Sates that the waiting time between precipitation events is non‐exponentially distributed and best described by a fractional Poisson process. A systematic model selection procedure reveals that the hourly precipitation intensities are best represented by a two‐distribution model for about 90% of all stations. The two‐distribution model consists of (a) a generalized Pareto distribution (GPD) model for bulk precipitation event sizes and (b) a power‐law distribution for large and extreme events. Finally, we analyse regional climate model output to evaluate how the climate models represent the high‐frequency temporal structure of U.S. precipitation. Our results reveal that these regional climate models fail to accurately reproduce the power‐law behaviour of intensities and severely underestimate the long durations between events.

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Evaluation of CORDEX-Arctic daily precipitation and temperature-based climate indices over Canadian Arctic land areas

Abstract: the use of reanalyses as reference datasets for the evaluation of RCM mean air temperature and hot extremes over northern Canada, but not for cold extremes and precipitation indices.

Cited by 44 publications

References 87 publications

Evaluating the suitability of three gridded‐datasets and their impacts on hydrological simulation at Scotty Creek in the southern Northwest Territories, Canada

Evaluating the suitability of three gridded‐datasets and their impacts on hydrological simulation at Scotty Creek in the southern Northwest Territories, Canada

A systems network approach for climate change vulnerability assessment

Power‐law behaviour of hourly precipitation intensity and dry spell duration over the United States

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