A note on analysis of extreme minimum temperatures with the GAMLSS framework

Rydén, Jesper

doi:10.1007/s11600-019-00363-6

Cited by 5 publications

(1 citation statement)

References 33 publications

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“…The underlying assumption of stationarity (e.g., applying a fixed probability over time) may not be entirely valid since climate change can alter the variability and upper bounds (e.g., and k in our GEV analysis, respectively) of extreme events 11 , 13 . The alternative, non-stationary approach 11 , 49 – 51 allows for the probability distributions (and their associated parameters) to vary with time. However, the non-stationary methods generally require either longer-term historical observations or the use of climate models (i.e., GCMs) to project future extremes.…”

Section: Discussionmentioning

confidence: 99%

Exponential increases in high-temperature extremes in North America

Davariashtiyani,

Taherkhani,

Fattahpour

et al. 2023

Sci Rep

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Global warming in the 21st century will alter the frequency of extreme climatic events, such as high-temperature anomalies and “heat waves”. Observations of extreme high temperatures during recent decades have detected upward trends in their frequency of occurrence, and recent state-of-the-art Global Climate Models (GCMs), e.g., Climate Model Intercomparison Projects (CMIPs), notably CMIP5 and CMIP6, have predicted acceleration of temperature trends and high-temperature events by 2100 under projected greenhouse-gas emission scenarios. Hence, the 21st century is expected to experience substantial shifts in the occurrence of extreme events, where present-day, extreme-but-rare high-temperature events will become common during the summer months. The increasing frequency of extreme heat may affect the health and resiliency of social, biological, and infrastructure systems in many regions worldwide, underscoring the need for accurate and reliable long-term assessments of climatic change across global and regional scales. So far, many investigations of high-temperature extremes have been carried out under end-point scenarios, e.g., by comparing GCM-projected changes in the frequency of high-temperature extremes expected in the late 21st century to the late 20th century. In this study, we use extreme value theory and decades of observations of high-temperature extremes at thousands of meteorological stations across North America to investigate continuous shifts in the frequency of extreme high-temperature events due to projected local warming trends. We find that the odds of exceedance of 50-year extreme high-temperature events increases exponentially with increases in mean local temperature. At a majority of the stations studied here, a local mean temperature increase of 0.5–1 $$^{\circ }$$ ∘ C can double the odds of exceedance of 50-year extreme high-temperature events. Based on time-dependent temperature projections, the odds of exceedance of 50-year extreme high-temperature events doubles approximately every 20 years (or sooner) for $$\sim $$ ∼ 96% of the stations. Moreover, we find that, for $$\sim $$ ∼ 80% of the stations in North America, investigated here, the 50-year extreme high-temperature events will be exceeded annually before 2100.

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Section: Discussionmentioning

confidence: 99%

Exponential increases in high-temperature extremes in North America

Davariashtiyani,

Taherkhani,

Fattahpour

et al. 2023

Sci Rep

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Selection of the best fit probability distributions for temperature data and the use of L-moment ratio diagram method: a case study for NSW in Australia

Haddad¹

2021

Theor Appl Climatol

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A tale of two stations: a note on rejecting the Gumbel distribution

Rydén

2022

Acta Geophys.

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The existence of an upper limit for extremes of quantities in the earth sciences, e.g. for river discharge or wind speed, is sometimes suggested. Estimated parameters in extreme-value distributions can assist in interpreting the behaviour of the system. Using simulation, this study investigated how sample size influences the results of statistical tests and related interpretations. Commonly used estimation techniques (maximum likelihood and probability-weighted moments) were employed in a case study; the results were applied in judging time series of annual maximum river flow from two stations on the same river, but with different lengths of observation records. The results revealed that sample size is crucial for determining the existence of an upper bound.

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A note on analysis of extreme minimum temperatures with the GAMLSS framework

Cited by 5 publications

References 33 publications

Exponential increases in high-temperature extremes in North America

Exponential increases in high-temperature extremes in North America

Selection of the best fit probability distributions for temperature data and the use of L-moment ratio diagram method: a case study for NSW in Australia

A tale of two stations: a note on rejecting the Gumbel distribution

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