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| hasDataset_Title |
- Global Hourly 0.5-degree Land Surface Air Temperature Datasets
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| hasReference |
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Wang A. and X. Zeng, 2013: Development of global hourly 0.5-degree
land surface air temperature datasets. J. Climate, 26, 7676-7691
(DOI: 10.1175/JCLI-D-12-00682.1), URL:
http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-12-00682.1.
Zeng, X. and A. Wang, 2012: What is mean land surface air
temperature?. Eos Trans. AGU, 93(15), 156-156 (DOI:
10.1029/2012EO150006), URL:
http://onlinelibrary.wiley.com/doi/10.1029/2012EO150006/abstract.
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| hasSummary |
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Global hourly 0.5-degree Surface Air Temperature (SAT) datasets were
developed based on four reanalysis products [Modern-Era
Retrospective Analysis for Research and Applications (MERRA for
1979-2009), 40-year ECMWF Re-Analysis (ERA-40 for 1958-2001), ECMWF
Interim Re-Analysis (ERA-Interim for 1979-2009), and NCEP/NCAR
reanalysis for 1948-2009)] and the Climate Research Unit Time Series
version 3.10 (CRU TS3.10) for 1948-2009. The three-step adjustments
included the spatial downscaling to 0.5-degree grid cells, the
temporal interpolation from 6-hourly (in ERA-40 and NCEP/NCAR
reanalysis) to hourly using the MERRA hourly SAT climatology for
each day (and the linear interpolation from 3-hourly in ERA-Interim
to hourly), and the bias correction in both monthly-mean maximum
(Tmax) and minimum (Tmin) SAT using the CRU data.
The final products have exactly the same monthly Tmax and Tmin as
the CRU data, and perform well in comparison with in-situ hourly
measurements over six sites and with a regional daily SAT dataset
over Europe. They agree with each other much better than the
original reanalyses, and the spurious SAT jumps of reanalyses over
some regions are also substantially eliminated. One of the
uncertainties in the final products can be quantified by the
differences in the true monthly mean (using 24-hourly values) and
the monthly averaged diurnal cycle from different final products.
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