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HadISDH is a global gridded monthly mean surface humidity dataset. Quality controlled and homogenised / bias adjusted monthly mean anomalies (relative to a 1981-2010 base period) are provided alongside uncertainty estimates (observation and gridbox sampling). Actual values, climatological mean and standard deviation and no. observations are also provided. The dataset begins in January 1973 and is updated annually.
HadISDH.land is a global gridded monthly mean land surface humidity dataset based on the quality controlled sub-daily HadISD dataset which is in turn based on the ISD dataset from NOAA's NCEI. Hourly dew poinbt temperature and air temperature are converted to various humidity variables and then averaged to monthly values. These are homogenised and averaged over 5° by 5° degree gridboxes for each month.
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. These are then converted to various humidity variables, quality controlled, bias adjusted and averaged over 5° by 5° degree gridboxes for each month.
HadISDH.blend is a global gridded monthly mean land and marine surface humidity dataset combining HadISDH.land and HadISDH.marine.
Gridded products are available for six humidity variables in addition to temperature:
The current version of HadISDH.land is 126.96.36.1990f and continues until December 2020. Only one update will be made this year so this is a final (f) version. Please read the Update Document.
The current version of HadISDH.marine is 188.8.131.520f and continues until December 2020. Only one update will be made this year so this is a final (f) version. Please read the Update Document.
The current version of HadISDH.blend is 184.108.40.2060f and continues until December 2020. Only one update will be made this year so this is a final (f) version.
For previous versions please contact the dataset maintainers.
HadISDH utilises simultaneous subdaily temperature and dew point temperature data from >4500 quality controlled HadISD stations that have sufficiently long records. Further information on the quality control tests and HadISD can be found here. All humdiity 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. We have used NCEI's Pairwise Homogenisation Algorithm directly on DPD and T. We have designed an indirect PHA method (ID PHA) 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. Further information can be found here. Stations with very large (>5 °C in T and Td, > 3 g kg-1 in q and > 15 %rh in RH) adjustments applied are removed.
Measurement, climatological and homogeneity adjustment uncertainty is estimated for each month.
Climatological averages over the 1981 to 2010 period are calculated 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. Further in formation on uncertainty estimates can be found here.
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). 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.
HadISDH.blend combines HadISDH.land and HadISDH.marine. Where both land and marine gridboxes are present a weighted average is taken based on land fraction with a lower limit of 0.25/0.75 enforced when either the land fraction is below 25% or above 75%.
Keep in touch
Follow 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.
Figures from the Willett et al. 2014 paper.
Figures from the Willett et al. 2013 paper.
Figures from State of the Climate and IPCC monitoring plots.
Decadal Trend maps for each variable: LAND; MARINE; BLEND.
Annual and monthly average timeseries for the globe, hemispheres and tropics, including uncertainty estimates: LAND; MARINE; BLEND.
Annual anomaly maps from 1973 onwards for specific humidity: LAND; MARINE; BLEND.
Annual anomaly maps from 1973 onwards for relative humidity: LAND; MARINE; BLEND.
Annual anomaly maps from 1973 onwards for vapour pressure: LAND; MARINE; BLEND.
Annual anomaly maps from 1973 onwards for dew point temperature: LAND; MARINE; BLEND.
Annual anomaly maps from 1973 onwards for wet bulb temperature: LAND; MARINE; BLEND.
Annual anomaly maps from 1973 onwards for air temperature: LAND; MARINE; BLEND.
Annual anomaly maps from 1973 onwards for dew point depression: LAND; MARINE; BLEND.
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.220.127.116.113p is the preliminary version of the dataset containing data up to the end of 2012.
The Python 3 code used (excluding quality control, homogenisation and regional average uncertainty estimates) was written by Kate Willett and can be found here. We do not intend to provide in-depth support for this code. We do appreciate constructive feedback on this code.
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