It Is Normal: The Probability Distribution of Temperature Extremes

Details

• Journal Title:
  Climate
• Personal Author:
  Krakauer, Nir Y.
• NOAA Program & Office:
  CESSRST (Cooperative Science Center for Earth System Sciences and Remote Sensing Technologies) ; Education and outreach
• Description:
  The probability of heat extremes is often estimated using the non-stationary generalized extreme value distribution (GEVD) applied to time series of annual maximum temperature. Here, this practice was assessed using a global sample of temperature time series, from reanalysis (both at the grid point and the region scale) as well as station observations. This assessment used forecast negative log-likelihood as the main performance measure, which is particularly sensitive to the most extreme heat waves. It was found that the computationally simpler normal distribution outperforms the GEVD in providing probabilistic year-ahead forecasts of temperature extremes. Given these findings, it is suggested to consider alternatives to the GEVD for assessing the risk of extreme heat.
• Source:
  Climate, 12(12), 204
• DOI:
  https://doi.org/10.3390/cli12120204
• ISSN:
  2225-1154
• Format:
  PDF
• Publisher:
  MDPI AG
• Document Type:
  Journal Article
• Funding:
  Grant no. NA22SEC4810016
• License:
  https://creativecommons.org/licenses/by/4.0/
• Rights Information:
  CC BY
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:616c7b221aa32401a5001780b7bba62e0b5407e78abdf6fe459691b3313ded0a4569fcbaf3a9adee53a043e3cd8c45f458a763dec9adc95a8bb1efe73c7bafeb
• Download URL:
  https://repository.library.noaa.gov/view/noaa/70201/noaa_70201_DS1.pdf
• File Type:
  [PDF - 408.12 KB ]