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Land surface climate station records

The data downloadable from this page are a subset of the full HadCRUT3 record of global temperatures, which is one of the global temperature records that have underpinned IPCC assessment reports and numerous scientific studies.

The data subset consists of a network of individual land stations that has been designated by the World Meteorological Organization for use in climate monitoring and other data that the Met Office has gained permission from the owners to make available. The data show monthly average temperature values for over 3,000 land stations.


Map of locations

The subset of stations is evenly distributed across the globe and provides a fair representation of changes in mean temperature on a global scale over land.

Map of locations (opens in new window)

Temperature rise

Graphic showing the temperature rise

This subset shows that global average land temperatures have risen over the last 150 years and is very similar to the temperature rises shown by the complete data set.

Graphic showing the temperature rise (opens in new window)

Climate station file data format

The climate station data files are in the following format:

Number= 037760
Lat=   51.2
Long=    0.2
Height= 59
Start year= 1961
End year= 2007
First Good year= 1961
Source ID= 10
Source file= Jones+Anders
Jones data to= 1998
Normals source= Data
Normals source start year= 1961
Normals source end year= 1990
Normals=   3.8   3.9   5.8   8.0  11.3  14.4  16.5  16.2  13.8  10.8   6.6   4.7 
Standard deviations source= Data
Standard deviations source start year= 1961
Standard deviations source end year= 1990
Standard deviations=   2.1   2.0   1.3   0.9   1.1   1.2   1.3   1.2   1.0   1.2   1.1   1.7 
1961   3.9   7.1   7.5  10.3  11.0  14.7  15.9  16.1  15.7  10.9   6.4   2.7 
1962   4.1   4.5   2.5   7.6   9.8  13.0  15.1  14.7  12.6  10.5   5.9   1.7 
1963  -2.7  -0.8   6.2   8.6  10.3  14.7  15.1  14.5  13.1  10.3   8.5   2.0 


  1. Number is a station identifier (usually the number assigned by the World Meteorological Organization).
  2. Height is in metres.
  3. First Good Year — data before that year are suspect.
  4. Source ID is an indicator of the source of the data.
  5. Source File, and Jones data to are internal flags relating this file to other systems.
  6. Normals and standard deviations are produced and used as described in the data set papers. One value for each calendar month (Jan–Dec) in Celsius.
  7. Obs (short for Observations) are monthly average temperatures, in Celsius — one row for each year. Each column is a calendar month (Jan–Dec).
  8. A value of -99 indicates missing data.

Questions and answers about the data sets

Please select a question to open or close the answer.

1. Is the data that you are providing the “value-added” or the “underlying” data?

The data that we are providing is the database used to produce the global temperature series. Some of these data are the original underlying observations and some are observations adjusted to account for non climatic influences, for example changes in observations methods or site location.

The database consists of the “value added” product that has been quality controlled and adjusted to account for identified non-climatic influences. It is the station subset of this value-added product that we have released. Adjustments were only applied to a subset of the stations so in many cases the data provided are the underlying data minus any obviously erroneous values removed by quality control. The Met Office do not hold information as to adjustments that were applied and so cannot advise as to which stations are underlying data only and which contain adjustments.

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2. What about the underlying data?

Underlying data are held by the National Meterological Services and other data providers and such data have in many cases been released for research purposes under specific licences that govern their usage and distribution.

It is important to distinguish between the data released by the NMSs and the truly raw data. e.g. the temperature readings noted by the observer. The data may have been adjusted to take account of non climatic influences, for example changes in observations methods, and in some cases this adjustment may not have been recorded so it may not be possible to recreate the original data as recorded by the observer.

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3. Why is there no comprehensive copy of the underlying data?

The data set of temperatures, which are provided as a gridded product back to 1850 was largely compiled in the 1980s when it was technically difficult and expensive to keep multiple copies of the database.

For IT infrastructure of the time this was an exceedingly large database and multiple copies could not be kept at a reasonable cost. There is no question that anything untoward or unacceptable in terms of best practices at the time occurred.

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4. How can you be sure that the global temperature record is accurate?

The methodology is peer reviewed. There are three independent sets of global temperature that all clearly show the rise in global temperatures over the last 150 years. Furthermore, the strong scientific evidence that climate is changing as a result of human influence is also based on the growing evidence that other aspects of the climate system are changing; these include the atmosphere getting moister , global rainfall patterns changing, reductions in snow cover, glacier volume, and Arctic sea ice, increases in sea level and changes in global scale circulation patterns. There are also numerous changes in phenological records which point towards a general warming and support the veracity of the instrumental record.

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5. Why have you not previously shared the HadCRUT data?

We have always provided the gridded HadCRUT product freely and without restriction for research usage. The data set is available through the Met Office, CRU and BADC and has been used widely in research papers and the media.

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6. What about the underpinning observations on which the gridbox averages are based ?

The Met Office is not in a position to release that portion of the underpinning land station data for which we have yet to gain permission from the ultimate rights holders.

The data are owned by other countries and institutions and any such release would need to be agreed with these data providers. We are in the process of seeking this agreement from the owners of the underpinning data, so that we will be hopefully in a position to release more data in the future. The underpinning ocean data component of HadCRUT is available publicly at

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7. Why are you releasing a subset of the data now?

We can only release data from NMSs when we have permission from them to do so. In the meantime we are releasing data from a network of stations designated by the World Meteorological Organisation for climate monitoring together with any additional data for which we have permission to release.

We will release more of the remaining station data once we have the permissions in place to do so. We are dependent on international approvals to enable this final step and cannot guarantee that we will get permission from all data owners.

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8. Why these stations?

The RBCN network was designated by the World Meteorological Organisation for monitoring global, hemispheric and regional climate.

To compile the list of stations we have released, we have taken the WMO Regional Basic Climatological Network (RBCN) and Global Climate Observing System (GCOS) Surface Network stations, cross-matched it and released the unambiguous matches. We also include those stations which we have permission to release.

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9. Will releasing a subset skew the principal findings?

No, the network is designated to capture regional and global scale changes and, except for the earlier part of the record in the 19th century, data reporting is relatively evenly spread so this should not cause an issue.

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10. Does this subset constitute a new data set?

This is not a new data set. Data sets are only released when they have gone through the proper process of scientific review.

It is important that due scientific process is followed if we are to have confidence in our findings. If we were proposing this as a new data set then we would have submitted it for peer review and only released it once accepted. The three principal data sets have all undergone this process and therefore retain primacy.

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11. Why aren’t all the underpinning land station records available for free?

Making observations costs substantial amounts of money and requires a degree of technical expertise and training to meet internationally agreed standards prescribed by the World Meteorological Organisation. Furthermore, these data, even at a monthly mean resolution, can have significant economic value to the rights holders. In many parts of the world, National Meteorological Services (NMSs) are expected to act as commercial entities. Removing potential revenue streams could substantially harm many such organisations. We therefore cannot guarantee that all NMSs will permit release of station level data.

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12. When will you release more?

We will release more of the remaining station data once we have the permissions in place to do so. We are dependent on international approvals to enable this final step and cannot guarantee that we will get permission from all data owners.

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13. How have you dealt with the FOI requests regarding releasing the underpinning global temperature data?

We take our responsibilities under the Freedom of Information Act very seriously and have, in all cases, handled and responded to requests in accordance with its obligations under the legislation.

We have been consistent in our responses in stating that the Met Office is not in a position to release the underpinning land station data as we do not have the authority to do so as the data are owned by other countries and any such release would need to be agreed with data providers. We are in the process of seeking this agreement from all the owners of the underpinning data, so that we will be hopefully in a position to release more data in the future.

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14. What have you done to gain permissions?

We, with the Climatic Research Unit have written a letter to all rights holders requesting permission to publish the underlying station data. We are monitoring responses and actively pursuing the rights holders for a decision.

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15. Who is ultimately responsible for the land data record?

The University of East Anglia’s Climatic Research Unit has the responsibility for the land climate data portion of HadCRUT.

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16. Why is this responsibility with the UEA/CRU and not the Met Office Hadley Centre?

During the 1980’s the UEA/CRU was funded, primarily by the United States ‘Department of Energy’, to collate a global land temperature record. Since then they have undertaken several major updates to the record increasing station density and time series completeness. This is why the UEA/CRU owns the primary IPR (Intellectual Property Rights) for the land climate records.

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17. So does the Met Office Hadley Centre have any involvement with the land climate data?

Since 2002 the Met Office Hadley Centre has formally assisted UEA/CRU by providing quality control and real-time updates for the land climate data set. The Met Office Hadley Centre is entirely responsible for the global sea surface temperature component of the global mean temperature and also responsible for merging these series to create the HadCRUT product. This underpinning ocean data component of HadCRUT is available publicly at

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18. Are there gaps in your data sets?

By virtue that observations are not available from every location around the world, there will be places from which data are not received. HadCRUT does not infill any of these gaps in the data.

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19. As there are gaps in the HadCRUT data set, does this have an effect on the global temperatures announced so far?

The HadCRUT product headline number provides an estimate solely for that portion of the globe where data is reported. This coverage changes over time and needs to be accounted for. Climate change is not identical everywhere around the globe. The HadCRUT product comes with uncertainty estimates. The main reason for this uncertainty is the sampling effect which is particularly large back in the late 19th Century when observational coverage was poorer. The warming trend is much larger than uncertainty estimates so the headline finding of a warming world is unaffected by sampling issues.

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20. If some land stations are shown to be incorrect does this invalidate the whole data set?

A single station or even a hand full of stations that are incorrect will not materially impact the global estimates although they will have impacts at the immediate regional level. Any issues or discrepancies arising from the data would be rectified as a matter of course as soon as we are informed of them.

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21. I can find more data on the web for a station than you hold, why is this?

Our data sets include all the historical data that were available at the time when CRUTEM3 was published. Following that we only undertake monthly updates to the most-recent portion of the record. When further historical records are found to supplement a station these are applied only at the time when a new data set version is released. This allows us to better control the accurate update of the temperature records and ensures that the record does not change substantially between versions except for the most recent period to allow intercomparison of published research.

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22. I can see obviously erroneous individual values in the data - do these make it through to the final product?

The gridding code includes a final check against the station record standard deviations which removes observations that are very different from observations, so most obviously erroneous values don't make it through. There are, inevitably, a few bad individual observations that are included in the final product, but as the product is an average of observations from many stations their effect is negligible upon regional or global scale means.

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23. Do sources for a station differ over time?

The historical component of the record is generally (but not always) from a single source, but updates depend upon data routinely exchanged between National Met Services in the form of CLIMAT messages and this source may differ from that for the historical record.

A single source is generally the case, but it isn't always. Sources of much of the early CRU data are documented within US DoE Tech Reports 22, 27 and 17.

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24. I am having problems unzipping the data files. What is the solution?

We are aware that some users are getting error messages when trying to unzip the data files. The following are some suggestions for how to get around this problem.

  • If you have a choice of web browser, try using Firefox, Google Chrome or Opera, as these browsers do not appear to generate errors.
  • If you are using Internet Explorer, please consult the advice in this article in the Microsoft Knowledge Base.
  • If you still have problems with Internet Explorer, try changing your Internet Options to disable the use of HTTP 1.1.

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25. How do I use the code that you have linked from this web page to calculate gridded statistics from the data files?

The code is a computer programme that is held in two files, using the scripting language "PERL".

The first, called "station_gridder.perl", takes the data files and creates a gridded data set. The second, called "make_global_average_ts_ascii.perl", calculates the time series of global average temperatures from the gridded files that were created by the first program.

You will need PERL installed on your computer. This is available from

You will then need to create a directory (or folder), place the two code files in it, and also create a directory (folder) in it called "station_files" into which you should extract the station files from the zip file found on this page.

Linux users: Set the first directory you created as your current directory and then type: station_gridder.perl | make_global_average_ts_ascii.perl > global_time_series.txt

Windows users: Open an MS-DOS window, change to the folder you first created and then type: station_gridder.perl | make_global_average_ts_ascii.perl > global_time_series.txt

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26. Why are there differences between the data that were released in December and the data released in January?

Feedback from users and internal review of the data identified a number of minor issues with some of the station data. We have corrected these. The corrections are described online. The minor corrections that have been applied have minimal impact on the global temperature record. Even in the two regions most affected by the changes, the United States and Australasia, the impact is only discernible in the nineteenth century when there are few stations and the published uncertainties are largest. The new version falls within the stated 95% confidence limits of the old version much more than 95% of the time.

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Station files

The stations that we have released are those in the CRUTEM3 database that are also either in the WMO Regional Basic Climatological Network (RBCN) and so freely available without restrictions on re-use; or those for which we have received permission from the national met. service which owns the underlying station data.

The station records are available in a zip file (released January 2010) (ZIP, 7.9 MB).

The previous version of the station records is also available in a zip file (released December 2009) (ZIP, 3.7 MB).

These station records were produced by the Climatic Research Unit, University of East Anglia, in collaboration with the Met Office Hadley Centre.

Code to make gridded fields and global time-series

The main use of these station records is to make gridded fields of temperature anomalies, and time-series of large-scale temperature change. To assist users in making these for themselves, we are providing two Perl programs:

  • station_gridder.perl takes the station data files and makes gridded fields in the same way as used in CRUTEM3. The gridded fields are output in the ASCII format used for distributing CRUTEM3.
  • make_global_average_ts_ascii.perl takes the output of the gridded and makes a global average annual temperature anomaly timeseries, again in the same way as those distributed with CRUTEM3.

This code is provided to enable users to make gridded fields and calculate a global average annual temperature anomaly time series from the station data provided here. Release of this code does not necessarily confer any particular status on any results obtained using it and is provided at users own risk. The official peer-reviewd CRUTEM and HadCRUT data sets continue to reside at This code is released under an Open Source licence that is contained as comments in the code. By running the code you indicate your acceptance of the licence.


The Met Office would like to thank the following countries’ national met. services for kindly agreeing to the release of some or all of their climate data used in constructing the HadCRUT data set. Users of the data are required to abide by any additional conditions for re-use of the data requested from the national met. services as specified below.

Acknowledgements to national met. services
Country National met. service Additional information (including any conditions on re-use)
Australia Bureau of Meteorology Based on the original temperature observations sourced from records held by the Australian Bureau of Meteorology
Austria ZAMG Original data available from
Bahamas Dept of Meteorology -
Bahrain BMS -
Barbados Meteorological Services -
Bermuda BWS -
Bosnia-Herzegovina Meteorological Institute -
Cape Verde   -
China CMA Agreed to release of 92 of the 111 stations used in HadCRUT
Colombia MdMA -
Costa Rica   -
Cyprus Meteorological Service -
Finland FMI For research purposes only
France Metéo-France -
Gambia Dept. of Water Resources -
Germany DWD Agreed to release of all data classified as essential under WMO Res 40
Greece HNMS -
Ireland Met Eirran -
Israel Israel Met Service -
Japan JMA All stations under ownership of JMA, excludes two stations run by US military in Japan.
Liberia Ministry of Transport For research purposes only
Lithuania Lithuanian Hydrometeorological Service -
Luxembourg   -
Mauritius Mauritius Meteorological Services For research or educational purposes only
New Zealand Meteorological Service of New Zealand Original data available online from New Zealand National Institute of Water and Atmospheric Research (NIWA) online Climate Database via
Philippines PAGASA -
Singapore Meteorological Services Division -
Switzerland Meteo-Suisse -
Uruguay Direccion Nacional de Meteorologia -
Uzbekistan Uzhydromet -
Zambia Meteorological Dept. -