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• 1. [Article] Short-tailed temperature distributions over North America and Implications for Future Changes in Extremes

  Some regions of North America exhibit nonnormal temperature distributions. Shorter-than-Gaussian warm tails are a special subset of these cases, with potentially meaningful implications for future changes ...

  Citation × Citation Citation Abstract Copy Title: Short-tailed temperature distributions over North America and Implications for Future Changes in Extremes Author: Loikith, Paul C., Neelin, J. David Year: 2015 Some regions of North America exhibit nonnormal temperature distributions. Shorter-than-Gaussian warm tails are a special subset of these cases, with potentially meaningful implications for future changes in extreme warm temperatures under anthropogenic global warming. Locations exhibiting shorter-than-Gaussian warm tails would experience a greater increase in extreme warm temperature exceedances than a location with a Gaussian or long warm-side tail under a simple uniform warm shift in the distribution. Here we identify regions exhibiting such behavior over North America and demonstrate the effect of a simple warm shift on changes in extreme warm temperature exceedances. Some locations exceed the 95th percentile of the original distribution by greater than 40% of the time after this uniform shift. While the manner in which distributions change under global warming may be more complex than a simple shift, these results provide an observational baseline for climate model evaluation. Title: Short-tailed temperature distributions over North America and Implications for Future Changes in Extremes Author: Loikith, Paul C., Neelin, J. David Year: 2015 Some regions of North America exhibit nonnormal temperature distributions. Shorter-than-Gaussian warm tails are a special subset of these cases, with potentially meaningful implications for future changes in extreme warm temperatures under anthropogenic global warming. Locations exhibiting shorter-than-Gaussian warm tails would experience a greater increase in extreme warm temperature exceedances than a location with a Gaussian or long warm-side tail under a simple uniform warm shift in the distribution. Here we identify regions exhibiting such behavior over North America and demonstrate the effect of a simple warm shift on changes in extreme warm temperature exceedances. Some locations exceed the 95th percentile of the original distribution by greater than 40% of the time after this uniform shift. While the manner in which distributions change under global warming may be more complex than a simple shift, these results provide an observational baseline for climate model evaluation. Close

• 2. [Article] Surface Temperature Probability Distributions in the NARCCAP Hindcast Experiment: Evaluation Methodology, Metrics, and Results

  Methodology is developed and applied to evaluate the characteristics of daily surface temperature distributions in a six-member regional climate model (RCM) hindcast experiment conducted as part of the ...

  Citation × Citation Citation Abstract Copy Title: Surface Temperature Probability Distributions in the NARCCAP Hindcast Experiment: Evaluation Methodology, Metrics, and Results Author: Loikith, Paul C., Waliser, Duane E., Lee, Huikyo, Kim, Jinwon, Neelin, J. David, Lintner, Benjamin R., McGinnis, Seth, Mattmann, Chris A., Mears, Linda O. Year: 2015 Methodology is developed and applied to evaluate the characteristics of daily surface temperature distributions in a six-member regional climate model (RCM) hindcast experiment conducted as part of the North American Regional Climate Change Assessment Program (NARCCAP). A surface temperature dataset combining gridded station observations and reanalysis is employed as the primary reference. Temperature biases are documented across the distribution, focusing on the median and tails. Temperature variance is generally higher in the RCMs than reference, while skewness is reasonably simulated in winter over the entire domain and over the western United States and Canada in summer. Substantial differences in skewness exist over the southern and eastern portions of the domain in summer. Four examples with observed long-tailed probability distribution functions (PDFs) are selected for model comparison. Long cold tails in the winter are simulated with high fidelity for Seattle, Washington, and Chicago, Illinois. In summer, theRCMs are unable to capture the distribution width and long warm tails for the coastal location of Los Angeles, California, while long cold tails are poorly realized for Houston, Texas. The evaluation results are repeated using two additional reanalysis products adjusted by station observations and two standard reanalysis products to assess the impact of observational uncertainty. Results are robust when compared with those obtained using the adjusted reanalysis products as reference, while larger uncertainties are introduced when standard reanalysis is employed as reference. Model biases identified in this work will allow for further investigation into associated mechanisms and implications for future simulations of temperature extremes. Title: Surface Temperature Probability Distributions in the NARCCAP Hindcast Experiment: Evaluation Methodology, Metrics, and Results Author: Loikith, Paul C., Waliser, Duane E., Lee, Huikyo, Kim, Jinwon, Neelin, J. David, Lintner, Benjamin R., McGinnis, Seth, Mattmann, Chris A., Mears, Linda O. Year: 2015 Methodology is developed and applied to evaluate the characteristics of daily surface temperature distributions in a six-member regional climate model (RCM) hindcast experiment conducted as part of the North American Regional Climate Change Assessment Program (NARCCAP). A surface temperature dataset combining gridded station observations and reanalysis is employed as the primary reference. Temperature biases are documented across the distribution, focusing on the median and tails. Temperature variance is generally higher in the RCMs than reference, while skewness is reasonably simulated in winter over the entire domain and over the western United States and Canada in summer. Substantial differences in skewness exist over the southern and eastern portions of the domain in summer. Four examples with observed long-tailed probability distribution functions (PDFs) are selected for model comparison. Long cold tails in the winter are simulated with high fidelity for Seattle, Washington, and Chicago, Illinois. In summer, theRCMs are unable to capture the distribution width and long warm tails for the coastal location of Los Angeles, California, while long cold tails are poorly realized for Houston, Texas. The evaluation results are repeated using two additional reanalysis products adjusted by station observations and two standard reanalysis products to assess the impact of observational uncertainty. Results are robust when compared with those obtained using the adjusted reanalysis products as reference, while larger uncertainties are introduced when standard reanalysis is employed as reference. Model biases identified in this work will allow for further investigation into associated mechanisms and implications for future simulations of temperature extremes. Close