Long tails in regional surface temperature probability distributions with implications for extremes under global warming

Details Long tails in regional surface temperature probability distributions with implications for extremes under global warming Long tails in regional surface temperature probability distributions with implications for extremes under global warming

Feb 2012

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012georl..3904704r&link_type=abstract

Geophysical Research Letters, Volume 39, Issue 4, CiteID L04704

Mathematics

Probability

Global Change: Climate Dynamics (0429, 3309), Global Change: Impacts Of Global Change (1225, 4321), Atmospheric Processes: Climate Change And Variability (1616, 1635, 3309, 4215, 4513), Natural Hazards: Extreme Events (1817, 3235), Nonlinear Geophysics: Probability Distributions, Heavy And Fat-Tailed (3265)

Scientific paper

Prior work has shown that probability distributions of column water vapor and several passive tropospheric chemical tracers exhibit longer-than-Gaussian (approximately exponential) tails. The tracer-advection prototypes explaining the formation of these long-tailed distributions motivate exploration of observed surface temperature distributions for non-Gaussian tails. Stations with long records in various climate regimes in National Climatic Data Center Global Surface Summary of Day observations are used to examine tail characteristics for daily average, maximum and minimum surface temperature probability distributions. Each is examined for departures from a Gaussian fit to the core (here approximated as the portion of the distribution exceeding 30% of the maximum). While the core conforms to Gaussian for most distributions, roughly half the cases exhibit non-Gaussian tails in both winter and summer seasons. Most of these are asymmetric, with a long, roughly exponential, tail on only one side. The shape of the tail has substantial implications for potential changes in extreme event occurrences under global warming. Here the change in the probability of exceeding a given threshold temperature is quantified in the simplest case of a shift in the present-day observed distribution. Surface temperature distributions with long tails have a much smaller change in threshold exceedances (smaller increases for high-side and smaller decreases for low-side exceedances relative to exceedances in current climate) under a given warming than do near-Gaussian distributions. This implies that models used to estimate changes in extreme event occurrences due to global warming should be verified regionally for accuracy of simulations of probability distribution tails.

Affiliated with

Also associated with

No associations

Rating

Long tails in regional surface temperature probability distributions with implications for extremes under global warming does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Long tails in regional surface temperature probability distributions with implications for extremes under global warming, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Long tails in regional surface temperature probability distributions with implications for extremes under global warming will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1839026