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Titel |
HadISD: a quality-controlled global synoptic report database for selected variables at long-term stations from 1973-2011 |
VerfasserIn |
R. J. H. Dunn, K. M. Willett, P. W. Thorne, E. V. Woolley, I. Durre, A. Dai, D. E. Parker, R. S. Vose |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1814-9324
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Digitales Dokument |
URL |
Erschienen |
In: Climate of the Past ; 8, no. 5 ; Nr. 8, no. 5 (2012-10-25), S.1649-1679 |
Datensatznummer |
250005848
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Publikation (Nr.) |
copernicus.org/cp-8-1649-2012.pdf |
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Zusammenfassung |
This paper describes the creation of HadISD: an automatically
quality-controlled synoptic resolution dataset of temperature,
dewpoint temperature, sea-level pressure, wind speed, wind direction
and cloud cover from global weather stations for 1973–2011. The full
dataset consists of over 6000 stations, with 3427 long-term stations
deemed to have sufficient sampling and quality for climate
applications requiring sub-daily resolution. As with other surface
datasets, coverage is heavily skewed towards Northern Hemisphere
mid-latitudes.
The dataset is constructed from a large pre-existing ASCII flatfile
data bank that represents over a decade of substantial effort at data
retrieval, reformatting and provision. These raw data have had
varying levels of quality control applied to them by individual data
providers. The work proceeded in several steps: merging stations with
multiple reporting identifiers; reformatting to netCDF; quality
control; and then filtering to form a final dataset. Particular
attention has been paid to maintaining true extreme values where
possible within an automated, objective process. Detailed validation
has been performed on a subset of global stations and also on UK data
using known extreme events to help finalise the QC tests. Further
validation was performed on a selection of extreme events world-wide
(Hurricane Katrina in 2005, the cold snap in Alaska in 1989 and heat
waves in SE Australia in 2009). Some very initial analyses are
performed to illustrate some of the types of problems to which the
final data could be applied. Although the filtering has removed the
poorest station records, no attempt has been made to homogenise the
data thus far, due to the complexity of retaining the true
distribution of high-resolution data when applying adjustments. Hence
non-climatic, time-varying errors may still exist in many of the
individual station records and care is needed in inferring long-term
trends from these data.
This dataset will allow the study of high frequency variations of
temperature, pressure and humidity on a global basis over the last
four decades. Both individual extremes and the overall population of
extreme events could be investigated in detail to allow for comparison
with past and projected climate. A version-control system has been
constructed for this dataset to allow for the clear documentation of
any updates and corrections in the future. |
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