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Dataset

 

HadISDH.land: gridded global monthly land surface humidity data version 4.5.1.2022f

Update Frequency: Not Planned
Latest Data Update: 2023-06-12
Status: Superseded
Online Status: ONLINE
Publication State: Citable
Publication Date: 2023-06-13
DOI Publication Date: 2023-06-13
Download Stats: last 12 months
Dataset Size: 7 Files | 14MB

This dataset has been superseded. See Latest Version here
Abstract

This is the HadISDH.land 4.5.1.2022f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.land is a near-global gridded monthly mean land surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from weather stations. The observations have been quality controlled and homogenised. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and 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. Users are advised to read the update document in the Docs section for full details on all changes from the previous release.

As in previous years, the annual scrape of NOAAs Integrated Surface Dataset for HadISD.3.3.0.2022f, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data.

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., 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.

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,
704-708, doi:10.1175/2011BAMS3015.1

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,
doi:10.5194/cp-9-657-2013.

Citable as:  Willett, K.M.; Dunn, R.J.H.; Thorne, P.W.; Bell, S.; de Podesta, M.; Parker, D.E.; Jones, P.D.; Williams Jr., C.N. (2023): HadISDH.land: gridded global monthly land surface humidity data version 4.5.1.2022f. NERC EDS Centre for Environmental Data Analysis, 13 June 2023. doi:10.5285/8956cf9e31334914ab4991796f0f645a. https://dx.doi.org/10.5285/8956cf9e31334914ab4991796f0f645a
Abbreviation: Not defined
Keywords: HadISDH, humidity, surface, land, gridded, station, specific humidity, temperature, dew point temperature, wet bulb temperature, dew point temperature, vapour pressure, in-situ

Details

Previous Info:
No news update for this record
Previously used record identifiers:
No related previous identifiers.
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.land is a global land surface (~2 m) humidity dataset and is produced by the Met Office Hadley Centre in collaboration with Maynooth University, NOAA NCEI, NPL and CRU. It is based on the quality controlled sub-daily HadISD from the Met Office Hadley Centre which is in turn based on the ISD dataset from NOAA's NCEI. 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.
File Format:
Files are NetCDF formatted.

Process overview

This dataset was generated by the computation detailed below.
Title

HadISDH.land: gridded global land surface humidity dataset produced by the Met Office Hadley Centre

Abstract

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 (the climatological period is dependent on product version) 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.

and

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

Input Description

None

Output Description

None

Software Reference

None

  • units: 1
  • long_name: actual number of stations within gridbox
  • var_id: stncount
  • long_name: climatology period boundaries
  • var_id: climbounds
  • units: 1
  • long_name: intersite correlation (rbar)
  • var_id: rbar
  • units: g/kg
  • long_name: mean gridbox variance (sbar2)
  • var_id: sbar2
  • units: 1
  • long_name: mean number of stations within gridbox
  • var_id: meanstncount
  • var_id: month
  • long_name: month of year
  • units: g/kg
  • standard_name: specific_humidity
  • var_id: huss
  • long_name: near surface (~2m) specific humidity
  • units: g/kg
  • long_name: near surface (~2m) specific humidity anomaly
  • var_id: hussa
  • units: g/kg
  • var_id: clm
  • long_name: near surface (~2m) specific humidity climatology
  • units: g/kg
  • var_id: std
  • long_name: near surface (~2m) specific humidity standard deviation
  • units: g/kg
  • var_id: adjunc
  • long_name: uncorrelated 2 sigma adjustment uncertainty for gridbox
  • units: g/kg
  • var_id: climunc
  • long_name: uncorrelated 2 sigma climatology uncertainty for gridbox
  • units: g/kg
  • var_id: measunc
  • long_name: uncorrelated 2 sigma measurement uncertainty for gridbox
  • units: g/kg
  • var_id: stnunc
  • long_name: uncorrelated 2 sigma observation uncertainty for gridbox
  • units: g/kg
  • var_id: sampunc
  • long_name: uncorrelated 2 sigma sampling uncertainty for gridbox
  • units: g/kg
  • var_id: stdunc
  • long_name: uncorrelated combined 2 sigma uncertainty for gridbox

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
  • units: days
  • standard_name: time
  • long_name: time period boundaries
  • var_id: bounds_time
Coverage
Temporal Range
Start time:
1973-01-01T00:00:00
End time:
2022-12-31T23:59:59
Geographic Extent

 
90.0000°
 
-180.0000°
 
180.0000°
 
-90.0000°