Dataset
HadISDH marine: gridded global monthly ocean surface humidity data version 1.0.0.2019f
Abstract
This is the 1.0.0.2019f version of the HadISDH (Integrated Surface Database Humidity) marine data. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2019.
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). Data are provided in either NetCDF or ASCII format.
This version extends the 1.0.0.2018f version to the end of 2019 and constitutes with no changes other than the addition of 2019 data. Users are advised to read the update document 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/
References:
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.: Development of the HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data, in review, doi:XX.XXXX/essd-XX-XXXX-2020, 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. doi:10.1002/joc.4775.
Details
| Previous Info: |
No news update for this record
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| Previously used record identifiers: |
No related previous identifiers.
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| Access rules: |
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. |
| Data lineage: |
HadISDH-marine is a global ocean surface (~10 m) humidity dataset and is produced by the Met Office Hadley Centre in collaboration with NOC. It is based on the sub-daily ship observations from ICOADS. It is passed to CEDA for archiving and distribution. |
| Data Quality: |
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.
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| File Format: |
These data are provided in NetCDF and ASCII formats, descriptors of the file formats are included in Docs.
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Process overview
| Title | HadISDH.marine: gridded global ocean surface (~10 m) humidity dataset produced by the Met Office Hadley Centre |
| Abstract | HadISDH 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. |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
- long_name: climatology period boundaries
- var_id: climbounds
- units: hPa
- long_name: correlated 2 sigma uncertainty for climatology for actual values
- var_id: abs_clmunc
- units: hPa
- long_name: correlated 2 sigma uncertainty for climatology for anomaly values
- var_id: anoms_clmunc
- units: hPa
- long_name: correlated 2 sigma uncertainty for instrument bias adjustments for actual values
- var_id: abs_instadjunc
- units: hPa
- long_name: correlated 2 sigma uncertainty for instrument bias adjustments for anomaly values
- var_id: anoms_instadjunc
- units: hPa
- long_name: correlated 2 sigma uncertainty for ship height bias adjustments for actual values
- var_id: abs_hgtadjunc
- units: hPa
- long_name: correlated 2 sigma uncertainty for ship height bias adjustments for anomaly values
- var_id: anoms_hgtadjunc
- units: hPa
- long_name: gridbox mean pseudo-station variance (sbarSQ for sampling uncertainty) for gridbox actual values
- var_id: abs_sbarsq
- units: 1
- long_name: intersite correlation (rbar) for actual values
- var_id: abs_rbar
- units: 1
- long_name: intersite correlation (rbar) for anomalies
- var_id: anoms_rbar
- units: 1
- long_name: mean number of pseudo stations within gridbox
- var_id: meanpseudostncount
- var_id: month
- long_name: month of year
- standard_name: air_temperature
- units: deg C
- var_id: tas
- long_name: near surface (~10m) air temperature
- units: deg C
- var_id: tasa
- long_name: near surface (~10m) air temperature anomaly
- units: deg C
- long_name: near surface (~10m) air temperature climatological standard deviations
- var_id: clmstd
- units: deg C
- var_id: clm
- long_name: near surface (~10m) air temperature climatology
- units: deg C
- standard_name: dew_point_temperature
- var_id: tds
- long_name: near surface (~10m) dewpoint temperature
- units: deg C
- var_id: tdsa
- long_name: near surface (~10m) dewpoint temperature anomaly
- units: deg C
- var_id: clmstd
- long_name: near surface (~10m) dewpoint temperature climatological standard deviations
- units: deg C
- var_id: clm
- long_name: near surface (~10m) dewpoint temperature climatology
- standard_name: relative_humidity
- var_id: hurs
- units: %rh
- long_name: near surface (~10m) relative humidity
- units: %rh
- var_id: hursa
- long_name: near surface (~10m) relative humidity anomaly
- units: %rh
- var_id: clmstd
- long_name: near surface (~10m) relative humidity climatological standard deviations
- units: %rh
- var_id: clm
- long_name: near surface (~10m) relative humidity climatology
- units: g/kg
- standard_name: specific_humidity
- var_id: huss
- long_name: near surface (~10m) specific humidity
- units: g/kg
- var_id: hussa
- long_name: near surface (~10m) specific humidity anomaly
- units: g/kg
- var_id: clmstd
- long_name: near surface (~10m) specific humidity climatological standard deviations
- units: g/kg
- var_id: clm
- long_name: near surface (~10m) specific humidity climatology
- units: hPa
- standard_name: water_vapor_partial_pressure_in_air
- var_id: vps
- long_name: near surface (~10m) vapor pressure
- units: hPa
- var_id: vpsa
- long_name: near surface (~10m) vapor pressure anomaly
- units: hPa
- var_id: clmstd
- long_name: near surface (~10m) vapor pressure climatological standard deviations
- units: hPa
- var_id: clm
- long_name: near surface (~10m) vapor pressure climatology
- units: 1
- long_name: number of 1by1 daily grids within gridbox
- var_id: gridcount
- units: 1
- long_name: number of 1by1 daily grids within gridbox climatological standard deviations
- var_id: clmstdgridcount
- units: 1
- long_name: number of 1by1 daily grids within gridbox climatology
- var_id: clmgridcount
- units: 1
- long_name: number of observations within gridbox
- var_id: obscount
- units: 1
- long_name: number of observations within gridbox climatological standard deviations
- var_id: clmstdobscount
- units: 1
- long_name: number of observations within gridbox climatology
- var_id: clmobscount
- units: 1
- long_name: number of pseudo stations within gridbox
- var_id: pseudostncount
- units: hPa
- long_name: uncorrelated 2 sigma combined observation uncertainty for actual values
- var_id: abs_obsunc
- units: hPa
- long_name: uncorrelated 2 sigma combined observations uncertainty for anomaly values
- var_id: anoms_obsunc
- units: hPa
- long_name: uncorrelated 2 sigma sampling uncertainty for gridbox actual values
- var_id: abs_sampunc
- units: hPa
- long_name: uncorrelated 2 sigma sampling uncertainty for gridbox anomaly values
- var_id: anoms_sampunc
- units: hPa
- long_name: uncorrelated 2 sigma uncertainty for measurement for actual values
- var_id: abs_measunc
- units: hPa
- long_name: uncorrelated 2 sigma uncertainty for measurement for anomaly values
- var_id: anoms_measunc
- units: hPa
- long_name: uncorrelated 2 sigma uncertainty for whole number reporting for actual values
- var_id: abs_wholeunc
- units: hPa
- long_name: uncorrelated 2 sigma uncertainty for whole number reporting for anomaly values
- var_id: anoms_wholeunc
- units: hPa
- long_name: uncorrelated combined 2 sigma uncertainty for gridbox actual values
- var_id: abs_stdunc
- units: hPa
- long_name: uncorrelated combined 2 sigma uncertainty for gridbox anomalu values
- var_id: anoms_stdunc
Co-ordinate Variables
- units: degrees_north
- standard_name: latitude
- var_id: latitude
- long_name: gridbox centre latitude
- units: degrees_east
- standard_name: longitude
- var_id: longitude
- long_name: gridbox centre longitude
- standard_name: latitude
- var_id: bounds_lat
- long_name: latitude gridbox boundaries
- standard_name: longitude
- var_id: bounds_lon
- long_name: longitude gridbox boundaries
- long_name: time
- standard_name: time
- var_id: time
- standard_name: time
- long_name: time period boundaries
- var_id: bounds_time
Temporal Range
1973-01-01T00:00:00
2019-12-31T23:59:59
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
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-90.0000° |