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.
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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Cited
34 citations as recorded by crossref.
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- Detecting Relationship between the North–South Difference in Extreme Precipitation and Solar Cycle in China J. Liu et al. 10.3390/atmos15020175
- How Well Do Gridded Datasets of Observed Daily Precipitation Compare over Australia? S. Contractor et al. 10.1155/2015/325718
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- Impacts of changes in climate extremes on wildfire occurrences in China H. Xing et al. 10.1016/j.ecolind.2023.111288
- Diverse estimates of annual maxima daily precipitation in 22 state-of-the-art quasi-global land observation datasets M. Bador et al. 10.1088/1748-9326/ab6a22
- Evaluating Precipitation Datasets Using Surface Water and Energy Budget Closure S. Hobeichi et al. 10.1175/JHM-D-19-0255.1
- Downscaling of climate extremes over South America – Part I: Model evaluation in the reference climate C. Dereczynski et al. 10.1016/j.wace.2020.100273
- A rule based quality control method for hourly rainfall data and a 1 km resolution gridded hourly rainfall dataset for Great Britain: CEH-GEAR1hr E. Lewis et al. 10.1016/j.jhydrol.2018.07.034
- Uncertainty in gridded precipitation products: Influence of station density, interpolation method and grid resolution S. Herrera et al. 10.1002/joc.5878
- Changes in Observed Daily Precipitation over Global Land Areas since 1950 S. Contractor et al. 10.1175/JCLI-D-19-0965.1
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- 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
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- 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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32 citations as recorded by crossref.
- On the use of indices to study extreme precipitation on sub-daily and daily timescales L. Alexander et al. 10.1088/1748-9326/ab51b6
- Observationally constrained projection of the reduced intensification of extreme climate events in Central Asia from 0.5 °C less global warming D. Peng et al. 10.1007/s00382-019-05014-6
- Historical and projected trends in temperature and precipitation extremes in Australia in observations and CMIP5 L. Alexander & J. Arblaster 10.1016/j.wace.2017.02.001
- Detecting Relationship between the North–South Difference in Extreme Precipitation and Solar Cycle in China J. Liu et al. 10.3390/atmos15020175
- How Well Do Gridded Datasets of Observed Daily Precipitation Compare over Australia? S. Contractor et al. 10.1155/2015/325718
- Human influence on frequency of temperature extremes T. Hu et al. 10.1088/1748-9326/ab8497
- Impacts of changes in climate extremes on wildfire occurrences in China H. Xing et al. 10.1016/j.ecolind.2023.111288
- Diverse estimates of annual maxima daily precipitation in 22 state-of-the-art quasi-global land observation datasets M. Bador et al. 10.1088/1748-9326/ab6a22
- Evaluating Precipitation Datasets Using Surface Water and Energy Budget Closure S. Hobeichi et al. 10.1175/JHM-D-19-0255.1
- Downscaling of climate extremes over South America – Part I: Model evaluation in the reference climate C. Dereczynski et al. 10.1016/j.wace.2020.100273
- A rule based quality control method for hourly rainfall data and a 1 km resolution gridded hourly rainfall dataset for Great Britain: CEH-GEAR1hr E. Lewis et al. 10.1016/j.jhydrol.2018.07.034
- Uncertainty in gridded precipitation products: Influence of station density, interpolation method and grid resolution S. Herrera et al. 10.1002/joc.5878
- 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
- How much does it rain over land? N. Herold et al. 10.1002/2015GL066615
- 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
- Performance evaluation and comparison of observed and reanalysis gridded precipitation datasets over Pakistan S. Iqbal et al. 10.1007/s00704-022-04100-w
- Observed Changes in Extreme Temperature over the Global Land Based on a Newly Developed Station Daily Dataset P. Zhang et al. 10.1175/JCLI-D-18-0733.1
- 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
- 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
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
- Systematic investigation of gridding-related scaling effects on annual statistics of daily temperature and precipitation maxima: A case study for south-east Australia F. Avila et al. 10.1016/j.wace.2015.06.003
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Saved (final revised paper)
Discussed (preprint)
Latest update: 11 Dec 2024
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...