Articles | Volume 10, issue 4
https://doi.org/10.5194/esd-10-765-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-10-765-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Nov 2019
Research article |
| 22 Nov 2019
| 22 Nov 2019
Changes in statistical distributions of sub-daily surface temperatures and wind speed
Robert J. H. Dunn
CORRESPONDING AUTHOR
Met Office Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK
Kate M. Willett
Met Office Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK
David E. Parker
Met Office Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK
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Cited
16 citations as recorded by crossref.
- Spatiotemporal changes of climatic parameters extreme quantiles and their role on evaporation in N. Iran (Golestan province) K. Solaimani & S. Bararkhanpour 10.1007/s12517-021-09300-8
- Characterizing temporal trends of meteorological extremes in Southern and Central Ontario, Canada L. Shah et al. 10.1016/j.wace.2022.100411
- Temporal variations of the contribution of combustion-derived water vapor to urban humidity during winter in Xi'an, China S. Liu et al. 10.1016/j.scitotenv.2022.154711
- Comparison of Bayesian and frequentist quantile regressions in studying the trend of discharge changes in several hydrometric stations of the Gorganroud basin in Iran K. Ghorbani et al. 10.2166/wcc.2023.305
- On the effect of reference periods on trends in percentile-based extreme temperature indices R. Dunn & C. Morice 10.1088/1748-9326/ac52c8
- Increasing Global Terrestrial Diurnal Temperature Range for 1980–2021 X. Huang et al. 10.1029/2023GL103503
- Temporal Variations of the Contribution of Combustion-Derived Water Vapor to Urban Humidity During Winter in Xi’An, China S. Liu et al. 10.2139/ssrn.3994594
- Seasonal relationship between climatic variables and evaporation based on Bayesian quantile regression method in southern Caspian region K. Solaimani 10.1007/s12517-022-10263-7
- Asynchronous changes in terrestrial near-surface wind speed among regions across China from 1973 to 2017 T. Chuan et al. 10.1016/j.atmosres.2024.107220
- Low-wind climatology (1979–2018) over Europe from ERA5 reanalysis C. Gutiérrez et al. 10.1007/s00382-024-07123-3
- Spatiotemporal changes of evaporation in Golestan province based on quantile regressions S. Ahmadi et al. 10.2166/wcc.2023.506
- Comparison of ERA5 surface wind speed climatologies over Europe with observations from the HadISD dataset M. Molina et al. 10.1002/joc.7103
- Development of an Updated Global Land In Situ‐Based Data Set of Temperature and Precipitation Extremes: HadEX3 R. Dunn et al. 10.1029/2019JD032263
- The added value of high‐resolution EURO‐CORDEX simulations to describe daily wind speed over Europe M. Molina et al. 10.1002/joc.7877
- Discussion on “Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach” A. Poppick 10.1007/s13253-023-00537-2
- Mind the (spectral) gap: how the temporal resolution of wind data affects multi-decadal wind power forecasts N. Effenberger et al. 10.1088/1748-9326/ad0bd6
16 citations as recorded by crossref.
- Spatiotemporal changes of climatic parameters extreme quantiles and their role on evaporation in N. Iran (Golestan province) K. Solaimani & S. Bararkhanpour 10.1007/s12517-021-09300-8
- Characterizing temporal trends of meteorological extremes in Southern and Central Ontario, Canada L. Shah et al. 10.1016/j.wace.2022.100411
- Temporal variations of the contribution of combustion-derived water vapor to urban humidity during winter in Xi'an, China S. Liu et al. 10.1016/j.scitotenv.2022.154711
- Comparison of Bayesian and frequentist quantile regressions in studying the trend of discharge changes in several hydrometric stations of the Gorganroud basin in Iran K. Ghorbani et al. 10.2166/wcc.2023.305
- On the effect of reference periods on trends in percentile-based extreme temperature indices R. Dunn & C. Morice 10.1088/1748-9326/ac52c8
- Increasing Global Terrestrial Diurnal Temperature Range for 1980–2021 X. Huang et al. 10.1029/2023GL103503
- Temporal Variations of the Contribution of Combustion-Derived Water Vapor to Urban Humidity During Winter in Xi’An, China S. Liu et al. 10.2139/ssrn.3994594
- Seasonal relationship between climatic variables and evaporation based on Bayesian quantile regression method in southern Caspian region K. Solaimani 10.1007/s12517-022-10263-7
- Asynchronous changes in terrestrial near-surface wind speed among regions across China from 1973 to 2017 T. Chuan et al. 10.1016/j.atmosres.2024.107220
- Low-wind climatology (1979–2018) over Europe from ERA5 reanalysis C. Gutiérrez et al. 10.1007/s00382-024-07123-3
- Spatiotemporal changes of evaporation in Golestan province based on quantile regressions S. Ahmadi et al. 10.2166/wcc.2023.506
- Comparison of ERA5 surface wind speed climatologies over Europe with observations from the HadISD dataset M. Molina et al. 10.1002/joc.7103
- Development of an Updated Global Land In Situ‐Based Data Set of Temperature and Precipitation Extremes: HadEX3 R. Dunn et al. 10.1029/2019JD032263
- The added value of high‐resolution EURO‐CORDEX simulations to describe daily wind speed over Europe M. Molina et al. 10.1002/joc.7877
- Discussion on “Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach” A. Poppick 10.1007/s13253-023-00537-2
- Mind the (spectral) gap: how the temporal resolution of wind data affects multi-decadal wind power forecasts N. Effenberger et al. 10.1088/1748-9326/ad0bd6
Latest update: 25 Apr 2024
Short summary
Using a sub-daily dataset of in situ observations, we have performed a study to see how the distributions of temperatures and wind speeds have changed over the last 45 years. Changes in the location or shape of these distributions show how extreme temperatures or wind speeds have changed. Our results show that cool extremes are warming more rapidly than warm ones in high latitudes but that in other parts of the world the opposite is true.
Using a sub-daily dataset of in situ observations, we have performed a study to see how the...
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