DOI: 10.5061/dryad.pnvx0k6xk
title: Global record-breaking recurrence rates indicates more widespread and intense surface air temperature and precipitation extremes

description: We analysed the global geographical characteristics of how extreme surface
 air temperature and rainfall have evolved, based on the recurrence rate of
 record-breaking events, and found hot spots with anomalously high as well
 as regions with anomalously low numbers of record-breaking events. The
 recurrence rate was defined as the proportion of the actual count of
 record-breaking events over time to the number expected in a
 hypothetically stable climate. In a stable climate, the data is
 independent and identically distributed (iid) if the data is sampled at
 intervals that makes the autocorrelation between data points negligible.
 Anomalous recurrence rates indicate shifts in the tails of statistical
 distributions, and our analysis of record-high annual mean surface air
 temperatures revealed highest recurrence rates in the tropics, as opposed
 to the polar regions with the fastest warming. We present new evidence for
 extremely hot years becoming more common and widespread over the 1950-2023
 period, based on recurrence rates as well as the global surface area
 fraction with daily mean surface air temperature exceeding 30°C and 40°C.
 A similar analysis for annual total precipitation highlights regions with
 increasingly more extreme annual precipitation as well as record-low
 annual precipitation typically associated with drought conditions. A
 multi-model ensemble of 306 runs with global climate models (CMIP6
 SSP2-45) reproduced the statistics of record-breaking high annual mean
 surface air temperatures, but there were some differences with the
 reanalysis on annual total precipitation record-breaking recurrence rates.
 The global climate model simulations suggested a slightly altered
 geographical pattern for record-breaking annual precipitation recurrence
 rates, especially over parts of the Arctic. 
description: Analysis using R and R-markdown script. Data from the ERA5 and
 NCEP2 reanalyses as well as global glimate models (CMIP6
 SSP2-45).
description: # Global record-breaking recurrence rates indicates more widespread and
 intense surface air temperature and precipitation extremes
 [https://doi.org/10.5061/dryad.pnvx0k6xk](https://doi.org/10.5061/dryad.pnvx0k6xk) A gzipped tar archive is provided containing R-markdown script, necessary data in R-binary and the output of the analysis: record-temperatures.Rmd, record-temperatures.pdf, record.stats.rda, and records.cmip6ssp245.rda. ## Description of the data and file structure The R-markdown script (record-temperatures.Rmd) and R-binaries (*.rda) are provided for replication of the analysis and for the sake of transparency. The PDF file contains the output of running the R-markdown scripts, showing the R-code, figures and results and a replication of the analysis should give the same results. Hence, the PDF file should be sufficient for examining these files, and the other files are there for those who want to replicate the analysis. The analysis can be replicated using R-studio if the rda-files are stored in the same directory as the R-markdown file. In this case, the rda-files are temporary data files generated by the R-markdown scrip itself (quite time consuming) and the R-code shows how they have been generated from the ERA5 reanalysis or CMIP6 global climate model simulations - all these require that the original data has been organised into netCDF files in certain file structure. The R-markdown may be adapted to carry out similar type of analyses.  ## Sharing/Access information The data is also available from FigShare: * [https://figshare.com/articles/journal_contribution/Record-breaking_statistics/25019738/2](http://...) Data was derived from the following sources: * ERA5, NCEP2 and CMIP6 SSP2-45 ## Code/Software The output of the R-markdown (PDF documents) indicate which versions of R and R-packages that are needed to run it. Make sure to use a later release of the esd-package accessible from [https://github.com/metno/esd](https://github.com/metno/esd).