Articles | Volume 5, issue 2
Geosci. Instrum. Method. Data Syst., 5, 473–491, 2016
https://doi.org/10.5194/gi-5-473-2016
Geosci. Instrum. Method. Data Syst., 5, 473–491, 2016
https://doi.org/10.5194/gi-5-473-2016
Research article
29 Sep 2016
Research article | 29 Sep 2016

Expanding HadISD: quality-controlled, sub-daily station data from 1931

Robert J. H. Dunn et al.

Related authors

Development of the HadISDH.marine humidity climate monitoring dataset
Kate M. Willett, Robert J. H. Dunn, John J. Kennedy, and David I. Berry
Earth Syst. Sci. Data, 12, 2853–2880, https://doi.org/10.5194/essd-12-2853-2020,https://doi.org/10.5194/essd-12-2853-2020, 2020
Short summary
Changes in statistical distributions of sub-daily surface temperatures and wind speed
Robert J. H. Dunn, Kate M. Willett, and David E. Parker
Earth Syst. Dynam., 10, 765–788, https://doi.org/10.5194/esd-10-765-2019,https://doi.org/10.5194/esd-10-765-2019, 2019
Short summary
The INTENSE project: using observations and models to understand the past, present and future of sub-daily rainfall extremes
Stephen Blenkinsop, Hayley J. Fowler, Renaud Barbero, Steven C. Chan, Selma B. Guerreiro, Elizabeth Kendon, Geert Lenderink, Elizabeth Lewis, Xiao-Feng Li, Seth Westra, Lisa Alexander, Richard P. Allan, Peter Berg, Robert J. H. Dunn, Marie Ekström, Jason P. Evans, Greg Holland, Richard Jones, Erik Kjellström, Albert Klein-Tank, Dennis Lettenmaier, Vimal Mishra, Andreas F. Prein, Justin Sheffield, and Mari R. Tye
Adv. Sci. Res., 15, 117–126, https://doi.org/10.5194/asr-15-117-2018,https://doi.org/10.5194/asr-15-117-2018, 2018
Short summary
Comparison of land surface humidity between observations and CMIP5 models
Robert J. H. Dunn, Kate M. Willett, Andrew Ciavarella, and Peter A. Stott
Earth Syst. Dynam., 8, 719–747, https://doi.org/10.5194/esd-8-719-2017,https://doi.org/10.5194/esd-8-719-2017, 2017
Short summary
Investigating uncertainties in global gridded datasets of climate extremes
R. J. H. Dunn, M. G. Donat, and L. V. Alexander
Clim. Past, 10, 2171–2199, https://doi.org/10.5194/cp-10-2171-2014,https://doi.org/10.5194/cp-10-2171-2014, 2014
Short summary

Related subject area

Data base
A universal and multi-dimensional model for analytical data on geological samples
Yutong He, Di Tian, Hongxia Wang, Li Yao, Miao Yu, and Pengfei Chen
Geosci. Instrum. Method. Data Syst., 8, 277–284, https://doi.org/10.5194/gi-8-277-2019,https://doi.org/10.5194/gi-8-277-2019, 2019
Short summary
Sodankylä ionospheric tomography data set 2003–2014
Johannes Norberg, Lassi Roininen, Antti Kero, Tero Raita, Thomas Ulich, Markku Markkanen, Liisa Juusola, and Kirsti Kauristie
Geosci. Instrum. Method. Data Syst., 5, 263–270, https://doi.org/10.5194/gi-5-263-2016,https://doi.org/10.5194/gi-5-263-2016, 2016
Short summary
A 7-year dataset for driving and evaluating snow models at an Arctic site (Sodankylä, Finland)
Richard Essery, Anna Kontu, Juha Lemmetyinen, Marie Dumont, and Cécile B. Ménard
Geosci. Instrum. Method. Data Syst., 5, 219–227, https://doi.org/10.5194/gi-5-219-2016,https://doi.org/10.5194/gi-5-219-2016, 2016
Short summary
The abandoned surface mining sites in the Czech Republic: mapping and creating a database with a GIS web application
Richard Pokorný and Marie Tereza Peterková
Geosci. Instrum. Method. Data Syst., 5, 143–149, https://doi.org/10.5194/gi-5-143-2016,https://doi.org/10.5194/gi-5-143-2016, 2016
Short summary
Determining the focal mechanisms of the events in the Carpathian region of Ukraine
A. Pavlova, O. Hrytsai, and D. Malytskyy
Geosci. Instrum. Method. Data Syst., 3, 229–239, https://doi.org/10.5194/gi-3-229-2014,https://doi.org/10.5194/gi-3-229-2014, 2014
Short summary

Cited articles

ACSM: Prevention of thermal injuries during distance running, Med. Sci. Sports Exerc., 16, iv–xiv, 1984.
Buck, A. L.: New equations for computing vapor pressure and enhancement factor, J. Appl. Meteorol., 20, 1527–1532, 1981.
DeGaetano, A. T.: A quality-control routine for hourly wind observations, J. Atmos. Ocean. Tech., 14, 308–317, 1997.
Dikmen, S. and Hansen, P.: Is the temperature-humidity index the best indicator of heat stress in lactating dairy cows in a subtropical environment?, J. Dairy Sci., 92, 109–116, 2009.
Short summary
We have extended the sub-daily, integrated HadISD back to 1931 to double the time coverage of the dataset. We have updated and improved the station selection and merging procedure, which will be rerun on an annual basis to prevent it becoming out of date. The quality-control code has been rewritten from IDL to Python2.7 to make it clearer and more accessible. We have also calculated humidity and heat-stress variables in HadISD.2.0.0. This increases the value and applicability of this dataset.