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HadISDH-marine is a global gridded monthly mean ocean surface humidity dataset. Hourly in situ dew point temperature and marine air temperature data from ships are taken from ICOADS from 1973 to 2018. These are then converted to various humidity variables, quality controlled, bias adjusted and averaged over 5° by 5° degree gridboxes for each month. Monthly mean anomalies relative to the 1981-2010 climatology period are currently available along with actual values, climatology and climatological standard deviations. Uncertainty estimates are also available for each gridbox month.
Gridded products are available for six humidity variables in addition to temperature - HadISDH-marine*.1.0.0.2018f:
LATEST VERSION: The current version of HadISDH-marine is 1.0.0.2018f and continues until December 2018. PLEASE NOTE THAT THIS IS A TEST PRODUCT AND HAS NOT YET PASSED THROUGH PEER REVIEW!!! Please provide feedback on any issues and errors found to Kate Willett. Updates and full documentation will appear here in due course...
HadISDH-marine utilises simultaneous subdaily air temperature and dew point temperature data from ships, moored buoys and ocean platforms from ICOADS.3.0.0 and ICOADS.3.0.1 (Freeman et al., 2016) from January 1st 1973 to December 31st 2018. All humidity variables are calculated at hourly resolution.
Hourly humidity and temperature values are quality controlled to to remove gross random errors (bad locations, bad timings, climatological outliers, neighbourhood outliers).
Bias adjustments are also applied to the hourly data to account for increasing ship heights over time and changing proportions of poorly ventilated instruments.
The data are then averaged over 5° by 5° gridboxes centred on -177.5°W and -87.5°S to 177.5°E and 87.5°N for each month as anomalies and actual values. No interpolation is applied.
Data are available as monthly mean anomaly values relative to 1981 to 2010 climatology, actual values, climatologies and a climatological standard deviation.
Uncertainty has been assessed at the observation level for measurement uncertainty, rounding uncertainty, climatology uncertainty, height adjustment uncertainty and ventilation adjustment uncertainty. These are made available at the gridbox monthly mean level along with spatio-temporal sampling uncertainty.
Regional average time series are also available with uncertainties averaged over the region including spatial coverage uncertainty.
Keep in touchFollow us on twitter: @metofficeHadOBS for updates, news and announcements. For more detailed information, follow our HadISDH blog. Here we describe bug fixes, routine updates and other exploratory analysis. |
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We have adapted our versioning system from CRUTEM4, and so the dataset numbering is of the form HadISDH.type.X.Y.Z.1234i. 'type' refers to the variable (e.g., landq=specific humidity). 'X' is for a major change and would be accompanied by a peer-reviewed paper or Met Office Technical Note. 'Y' is a more minor change, e.g., in one of the QC tests or homogenisation algorithms and would be described in a tech-note. 'Z' is a small change, for example addition or changes to data in the past. The last complete year of the dataset is given by '1234', and the final character shows if the dataset is f-final or p-preliminary. Therefore HadISDH.landq.2.0.0.2013p is the preliminary version of the dataset containing data up to the end of 2012.
The python code used was written by Kate Willett, John Kennedy and Robert Dunn. Some of it will be made available later here. We do not intend to provide in-depth support for this code. We do appreciate constructive feedback on this code.
Maintained by: Kate Willett |
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