HadISDH.blend: gridded global monthly land and ocean surface humidity data version 126.96.36.1992f
This is the HadISDH.blend 188.8.131.522f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.blend is a near-global gridded monthly mean surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships and weather stations. The observations have been quality controlled and homogenised / bias adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2022.
The data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).
This version extends the previous version to the end of 2022. It combines the latest version of HadISDH.land and HadISDH.marine. and therefore their respective update notes. Users are advised to read the update documents in the Docs section for full details.
To keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.
For more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/
When using the dataset in a paper please cite the following papers (see Docs for link
to the publications) and this dataset (using the "citable as" reference):
Willett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of
the HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,
12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020
Freeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,
Berry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,
Rayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to
the historical marine climate record. International Journal of Climatology.
Willett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,
Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and
temperature record for climate monitoring, Clim. Past, 10, 1983-2006,
Dunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station
data from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.
Smith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent
Developments and Partnerships. Bulletin of the American Meteorological Society, 92,
We strongly recommend that you read these papers before making use of the data, more
detail on the dataset can be found in an earlier publication:
Willett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de
Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface
specific humidity product for climate monitoring. Climate of the Past, 9, 657-677,
No news update for this record
|Previously used record identifiers:||
No related previous identifiers.
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
HadISDH.blend is a global land (~2 m) and ocean (~10 m) surface humidity dataset and is produced by the Met Office Hadley Centre in collaboration with CRU, Maynooth University, NPL, NOAA-NCEI and NOC. It is based on the sub-daily station observations from HadISD (originally from ISD) and ship observations from ICOADS. It is passed to the Centre for Environmental Data Analysis (CEDA) for archiving and distribution. Gridboxes containing both land and marine data are combined using a weighted average with a minimum and maximum weighting of 25% and 75% respectively.
Uncertainty estimates are provided as part of the dataset both at the station and gridbox level, this includes information covering station uncertainty (climatological, homogenisation and measurement uncertainty), gridbox spatial and temporal sampling uncertainty and combined station and sampling uncertainty. See dataset associated documentation for full details.
Data are NetCDF formatted
HadISDH.blend: gridded global land (~2 m) and ocean (~10 m) surface humidity dataset produced by the Met Office Hadley Centre
HadISDH.blend combines HadISDH.marine and HadISDH.land at the 5 degree by 5 degree gridbox monthly mean level. Gridboxes containing both land and marine data are combined using a weighted average with a minimum and maximum weighting of 25% and 75% respectively. HadISDH.marine utilises simultaneous sub-daily temperature and dew point temperature data from ICOADS ship data. All humidity variables are calculated at hourly resolution.
Quality control, buddy checking and bias adjustment is applied at hourly resolution to adjust all observations to an observing height of 10 m, accounting for changing ship heights over time, and to adjust all non-ventilated instruments to mitigate the moist bias. Gridded monthly means, monthly mean anomalies and 1981 to 2010 climatologies are created.
See Docs 'HadISDH.marine process diagram'. Observation measurement, climatological, whole number presence and bias adjustment uncertainties are estimated for each observation and then gridded. 5° by 5° gridboxes are centred on -177.5°W and -87.5°S to 177.5°E and 87.5°N. Given the uneven distribution of observations over time and space, sampling uncertainty is estimated for each gridbox month.
For greater detail please see: Willett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I.: Development of the HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data, in review, doi:XX.XXXX/essd-XX-XXXX-2020, 2020.
Docs contains links to this publication.
HadISDH.land utilises simultaneous subdaily temperature and dew point temperature data from over 3000 quality controlled HadISD stations that have sufficiently long records. All humidity variables are calculated at hourly resolution and monthly means are created. Monthly means are homogenised to detect and adjust for features within the data that do not appear to be of climate origin. While unlikely to be perfect, this process does help remove large errors from the data an improve robustness of long-term climate monitoring. The NCEI's Pairwise Homogenisation Algorithm has been used directly on DPD and T. An indirect PHA method (ID PHA) is used whereby changepoints detected in DPD and T are used to make adjustments to q, e, Tw and RH. Changepoints from DPD are also applied to T. Td is derived from homogenised T and DPD.
See Docs 'HadISDH.land process diagram'. Station measurement, climatological and homogeneity adjustment uncertainties are estimated for each month. Climatological averages are calculated over 1981-2010 and monthly mean climate anomalies obtained. These anomalies (in addition to climatological mean and standard deviation, actual values and uncertainty components) 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. Given the uneven distribution of stations over time and space, sampling uncertainty is estimated for each gridbox month.
For greater detail please see: Willett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014.
Willett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013.
Docs contains links to both these publications.