Location

Portland State University

Start Date

2-5-2018 11:00 AM

End Date

2-5-2018 1:00 PM

Subjects

Earth temperature, Atmospheric models, Climatic changes -- Mathematical models

Abstract

Regions of shorter-than-Gaussian temperature distribution tails have been shown to occur in spatially coherent patterns in the current climate using reanalysis. Under such conditions, future changes in extremes due to global warming may manifest in more complex ways than if the underlying distribution were closer to Gaussian. For instance, under a uniform warm shift, the simplest prototype for future warming, a location with a short warm side tail would experience a greater increase in exceedances than if the distribution were Gaussian. This carries meaningful societal and environmental implications including but not limited to negative impacts on human and ecosystem health, agriculture, and the economy. More rapid-than-Gaussian increases in extreme warm threshold exceedances are also projected under future climate simulations in regions of short tails. However, it is not clear whether short tails are already resulting in greater-than-Gaussian increases in extreme warm temperature exceedances. We investigate whether observed changes in extreme warm temperatures have increased at a greater rate in regions of short warm tails than in regions with Gaussian or longer tails. Furthermore, by performing this analysis using station data, we validate and constrain uncertainty related to previous results identifying non-Gaussian short tails using reanalysis. Short warm side tails are identified by via a Kolmogorov-Smirnov/Lilliefors (KS/L) test. We assess four locations for greater-than-Gaussian increases in extreme warm exceedances.

Persistent Identifier

http://archives.pdx.edu/ds/psu/25056

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May 2nd, 11:00 AM May 2nd, 1:00 PM

Assessment of Observed Increases in Extreme Warm Exceedances in Locations with Short Warm Side Tails

Portland State University

Regions of shorter-than-Gaussian temperature distribution tails have been shown to occur in spatially coherent patterns in the current climate using reanalysis. Under such conditions, future changes in extremes due to global warming may manifest in more complex ways than if the underlying distribution were closer to Gaussian. For instance, under a uniform warm shift, the simplest prototype for future warming, a location with a short warm side tail would experience a greater increase in exceedances than if the distribution were Gaussian. This carries meaningful societal and environmental implications including but not limited to negative impacts on human and ecosystem health, agriculture, and the economy. More rapid-than-Gaussian increases in extreme warm threshold exceedances are also projected under future climate simulations in regions of short tails. However, it is not clear whether short tails are already resulting in greater-than-Gaussian increases in extreme warm temperature exceedances. We investigate whether observed changes in extreme warm temperatures have increased at a greater rate in regions of short warm tails than in regions with Gaussian or longer tails. Furthermore, by performing this analysis using station data, we validate and constrain uncertainty related to previous results identifying non-Gaussian short tails using reanalysis. Short warm side tails are identified by via a Kolmogorov-Smirnov/Lilliefors (KS/L) test. We assess four locations for greater-than-Gaussian increases in extreme warm exceedances.