Articles | Volume 10, issue 6
https://doi.org/10.5194/cp-10-2171-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/cp-10-2171-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Dec 2014
Research article |
| 12 Dec 2014
Investigating uncertainties in global gridded datasets of climate extremes
R. J. H. Dunn
CORRESPONDING AUTHOR
Met Office Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK
M. G. Donat
ARC Centre of Excellence for Climate System Science and Climate Change Research Centre, UNSW, Sydney, NSW 2052, Australia
L. V. Alexander
ARC Centre of Excellence for Climate System Science and Climate Change Research Centre, UNSW, Sydney, NSW 2052, Australia
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35 citations as recorded by crossref.
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- Human influence on frequency of temperature extremes T. Hu et al. 10.1088/1748-9326/ab8497
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- Changes in Observed Daily Precipitation over Global Land Areas since 1950 S. Contractor et al. 10.1175/JCLI-D-19-0965.1
- FROGS: a daily 1° × 1° gridded precipitation database of rain gauge, satellite and reanalysis products R. Roca et al. 10.5194/essd-11-1017-2019
- Delineating village-level drought risk in Marinduque Island, Philippines A. Salvacion 10.1007/s11069-022-05795-w
- The Sensitivity of Daily Temperature Variability and Extremes to Dataset Choice M. Gross et al. 10.1175/JCLI-D-17-0243.1
- Reduced Risks of Temperature Extremes From 0.5°C less Global Warming in the Earth's Three Poles B. Tang et al. 10.1029/2021EF002525
- Observational uncertainty and regional climate model evaluation: A pan‐European perspective S. Kotlarski et al. 10.1002/joc.5249
- Contemporary climate change velocity for near-surface temperatures over India D. Sachan et al. 10.1007/s10584-022-03418-8
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- Changes in temperature extremes on the Tibetan Plateau and their attribution H. Yin et al. 10.1088/1748-9326/ab503c
- Mapping meteorological drought hazard in the Philippines using SPI and SPEI A. Salvacion 10.1007/s41324-021-00402-9
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- Global observed long-term changes in temperature and precipitation extremes: A review of progress and limitations in IPCC assessments and beyond L. Alexander 10.1016/j.wace.2015.10.007
- An overview of observed changes in precipitation totals and extremes over global land, with a focus on Africa T. Yate & G. Ren 10.1016/j.earscirev.2025.105063
- Temperature and precipitation extremes in century‐long gridded observations, reanalyses, and atmospheric model simulations M. Donat et al. 10.1002/2016JD025480
- Projection of extreme precipitation induced by Arctic amplification over the Northern Hemisphere J. Liu et al. 10.1088/1748-9326/ac0acc
- Reassessing changes in diurnal temperature range: Intercomparison and evaluation of existing global data set estimates P. Thorne et al. 10.1002/2015JD024584
- An Observation-Based Dataset of Global Sub-Daily Precipitation Indices (GSDR-I) D. Pritchard et al. 10.1038/s41597-023-02238-4
- Development of an Updated Global Land In Situ‐Based Data Set of Temperature and Precipitation Extremes: HadEX3 R. Dunn et al. 10.1029/2019JD032263
- Urbanization Effects in Estimating Surface Air Temperature Trends in the Contiguous United States S. Huang et al. 10.3390/land13030388
- Land use change impacts on climate extremes over the historical period M. Zhang et al. 10.1007/s00382-024-07375-z
- Evaluating the ability of gridded climate datasets to capture temperature and precipitation trends and extremes E. Smith et al. 10.1038/s41598-025-97570-7
2 citations as recorded by crossref.
- Understanding and assessing uncertainty of observational climate datasets for model evaluation using ensembles M. Zumwald et al. 10.1002/wcc.654
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Latest update: 24 Apr 2025
Short summary
Observational data sets contain uncertainties, e.g. from the instrument accuracy, as well as from the fact that usually only a single method is used in processing. We have performed an assessment of the size of the uncertainties associated with choices in the method used. The largest effects come from changes which affect the station network or the gridding method used. However, for the temperature indices in places with many stations, these changes have little effect on the long-term behaviour.
Observational data sets contain uncertainties, e.g. from the instrument accuracy, as well as...
