Incorrect: The WMO Siting Classification rating indicates how large of a geographic area a weather station likely represents; these guidelines do not ‘forbid’ reporting climate data from certain classes of weather stations, like those operated by the Met Office.
REVIEW
CLAIM: The United Kingdom Meteorological Office (the Met Office) is fabricating data/making up numbers for weather stations that have been closed for years to decades. “There is no plausible scientific purpose in the invention of numbers for non-existent sites which are falsely posing as authentic locations.” For climate reporting purposes, the Met Office is using ‘junk’ weather stations based on the WMO guidelines.
On 31 October 2024, a blogger wrote a post on their website ‘Tallbloke’s Talkshop’ criticizing weather data collected and shared by the United Kingdom Meteorological Office (the Met Office). Namely, the post claims that the Met Office is ‘fabricating data/making up numbers’ for weather stations that no longer exist in the UK.
Several other articles and social media posts echoed these claims, referencing the original blog post. One of these articles was posted by The Daily Sceptic – a known source of climate misinformation, as shown in our past reviews linked here – who described this as a “massive cover-up” to hide non-existent weather stations.
However, as we will detail below, these claims and articles exclude key details and context about what the Met Office presents on their website, how they conduct their research, and the independent reviews of their research by independent climate and meteorological scientists.
The Met Office’s research findings and methods are published in reputable scientific papers – no evidence of ‘fabricated’ data
It is true that some UK Met Office weather stations have closed down, but this is not something they hide, nor does it render the decades of data they’ve collected ‘useless’. As the Met Office explains directly on their page (the same one referenced in recent claims): “This webpage provides long-term climate averages for specific locations across the UK. It is designed to display locations that provide even geographical coverage of the UK, but is not reflective of every weather station that has existed or the current Met Office observation network.”
On the same page, the Met Office also explains that “The averages table shows 30-year averages for the nearest / most similar climate station to your chosen location.” This line answers the question posed in the ‘Tallbloke’s Talkshop’ blog post: “how would any reasonable observer (i.e. the example student) know that the data was not real and simply ‘made up’ by a government agency?” The data is real – not ‘made up’ – and it comes from nearby stations, as clearly explained on the page in question.
But is that the same as ‘fabricating data’? Not at all. Data fabrication is one of the most serious forms of scientific misconduct, whereby researchers fraudulently make up research results and data (see link here). Contrary to recent claims, the Met Office is not fabricating data – they are using accepted scientific methods. As explained to Science Feedback by a UK Met Office spokesperson:
“To suggest we’re fabricating data is not true. Everything we do at the Met Office is based on peer reviewed science and subject to external scrutiny. To ensure we [the Met Office] maintain continuity of long-term datasets we use peer reviewed science methods that, where stations have closed, use well-correlated observations from other nearby stations to help inform long-term average figures […] This method is peer reviewed and similar processes are used across the world to ensure datasets are consistent across historic averaging periods. The paper explaining the methodology can be found here [link]”
There are numerous well-established scientific methods of filling in data gaps; some have been known for decades. As explained in a 2018 Forest Ecosystems paper, while the simplest technique would be ‘filling in’ the missing data, this only works in some situations (e.g., small data gaps). They then explain that “[a] more common approach to complete missing data is to use information from neighboring meteorological stations”[1], referencing methods published in 1996.
The Met Office did not choose their selected method arbitrarily. As detailed in a peer-reviewed International Journal of Climatology paper published in 2005, the Met Office reviewed and compared a number of scientific methods for filling in monthly data gaps, looking at their potential biases and uncertainties.
As explained in that paper, “Relatively few stations have data for every year of a 30-year averaging period from which LTAs [long-term averages] can be calculated. In order to avoid bias caused by averages calculated from different periods, the solution is to fill in the gaps using an appropriate estimation technique.”[2]
Ultimately, the Met Office selected a method which determines six neighboring stations that are most well-correlated to the target station and averages their data to fill in the data gaps for that station. In other words, this method uses data from nearby stations whose data has historically ‘matched’ well with the target station. This is done by comparing data from different months in an ‘apples to apples’ sense (i.e., data from ‘Januaries’ are compared between stations, same for ‘Februaries’, and so on).
As explained in the 2005 International Journal of Climatology paper: “The estimation of missing monthly values prior to gridding provides a dense network of observation data which, together with careful quality control and exclusion of unrepresentative stations, enables detailed and accurate high resolution [1 kilometer x 1 kilometer] gridded datasets to be produced. The accuracy of the estimates was tested, and found to be good especially for temperature and sunshine.”[2]
These gridded datasets can then be used to show regional variations in climate variables, like mean temperature (link here).
So contrary to recent misleading claims, the Met Office is not conducting a ‘massive cover-up’ or ‘fabricating data’ – they are using methods published in peer-reviewed research papers to ensure that decades of useful and important climate data from old stations can still be used to determine long-term averages.
In addition to these methods being peer-reviewed – the gold standard of reputability in scientific research – the Met Office’s research is also independently assessed by experts as explained below.
The Met Office’s research is assessed by external independent scientists with relevant expertise
After Science Feedback asked a Met Office spokesperson whether or not the Met Office’s data and research is externally reviewed, they explained:
“[…] yes as well as our science output being peer reviewed and published in academic papers, we’re also reviewed by external independent experts via the Met Office Hadley Centre Science Review Group (SRG) and Met Office Scientific Advisory Committee (MOSAC)”
As explained on the Met Office’s website, one of the primary roles of MOSAC is to “provide an independent assessment of the quality and relevance of the Met Office’s scientific research which underpins its weather, climate and oceanographic services”. The Met Office’s website explains that “SRG and MOSAC comprises external independent experts in the field of climate science, meteorology, oceanography or numerical weather prediction drawn from UK universities, and from meteorological services and climate institutions of other countries”.
So what do these assessments say about the quality of the Met Office’s research? The final report from the most recent MOSAC meeting – held 16 to 18 January 2024 – includes comments from MOSAC and responses from the Met Office. In that report, MOSAC highlighted the quality and importance of the Met Office’s climate research:
“MOSAC extends its praise for the Met Office’s ongoing leadership and exemplary contributions in the fields of climate and earth system modeling. Specifically, MOSAC highlights the Met Office’s significant involvement and influential role in the Seventh Coupled Model Intercomparison Project (CMIP7) [see note*], underscoring the critical importance of their work in advancing our understanding of climate dynamics and forecasting. This acknowledgment serves to recognize the Met Office’s dedication to excellence in scientific research and its pivotal contributions to global climate initiatives.”
Note:
*As explained by the World Climate Research Program, the Coupled Model Intercomparison Project (CMIP) aims to better understand and predict the effects of natural variability and anthropogenic (human) effects on the climate system. The CMIP7 is the most recent phase of this project.
Met Office weather stations are inspected using multiple inspection standards and remediated or closed if necessary
The ‘Tallbloke’s Talkshop’ blog claims that the Met Office’s weather stations are poorly located and most are not suitable for climate reporting purposes per WMO’s guidelines. However, the blog does not provide evidence or quote from the WMO guidelines to reflect this. Instead, this appears to be a misinterpretation of how these classification systems work.
The ‘WMO Siting Classification for Surface Observing Stations on Land’ provides rules for the exposure of different weather sensors. According to the presence and nature of nearby obstacles (e.g., trees casting shadows) which could affect weather measurements, classifications of Class 1 (low) to Class 5 (high) are assigned. Meteorological readings from lower class sites are more likely to be representative of a wide geographic area than readings from higher class sites.
As explained in the guidance (linked here), a Class 5 site suggests that there are nearby obstacles that create an inappropriate environment (e.g., shade) for the station’s meteorological measurements to be representative of a wide area (i.e., tens of square kilometers [km2] or more). But, contrary to the blog’s claims, higher classification ratings do not necessarily mean the data is ‘junk’ for climate reporting purposes.
In fact, the WMO explains that “[t]he numbers should not be taken to mean that higher class stations are of low value, as there may be very good reasons for the site exposure depending on the purpose for which that station was established”. They continue, explaining “we acknowledge that the use of numbers can easily lead one to suggest a ranking. This is not the purpose and should be avoided.”
Regarding the Met Office specifically, they clearly explain on their website that many of the stations are of higher classes (e.g., Class 3 or 4) and why that’s the case:
“[…] the criteria for a Class 1 rating for temperature suits wide open flat areas with little or no human influenced land use and high amounts of continuous sunshine reaching the screen all year around, however, these conditions are relatively rare in the UK. Mid and higher latitude sites will, additionally, receive more shading from low sun angles than some other stations globally, so shading will most commonly result in a higher CIMO classification – most Stevenson Screens [weather stations] in the UK are Class 3 or 4 for temperature as a result but continue to produce valid high-quality data. WMO guidance does, in fact, not preclude use of Class 5 temperature sites”
As you can check for yourself in the WMO guidance (linked here), it is true – the guidance does not state that Class 5 temperature sites cannot be used for climate reporting purposes. However, it is not for that reason alone that the Met Office still uses higher class stations, but also because they have their own long-standing inspection standards which they use to ensure data quality and minimize uncertainty.
In a comment to Science Feedback, a spokesperson for the Met Office explained:
“In order to provide advice and assistance, all Met Office weather stations are inspected by trained expert Met Office Regional Network Officers at a set interval. Each weather station is assessed against both the World Meteorological Organization inspection standards and Met Office inspection standards.”
As explained to Science Feedback by a Met Office spokesperson, data will only be quoted in climate records if the weather station it came from meets inspection standards:
“If a site is assessed to have fallen below the acceptable Met Office inspection standard, then one of three options can be undertaken:
1) Remedial action taken to improve the condition of the station. Only when site condition improves to the required standard will data again be quoted in climate records.
2) If remedial action cannot be taken but there is a lengthy historical station record or a specific customer need to keep the site open, the station will remain open, but the data will not be quoted in national records.
3) The site can be closed if suitable remedial action is not achievable.”
Read more about their inspection processes and rationale in the link here.
Conclusion
Certain UK Met Office weather stations have closed down after decades of collecting data. However, instead of letting this data go to waste, scientists at the Met Office combine this past data with more recent data from nearby well-correlated stations (i.e., those with similar trends) to look at long-term climate trends. This method is published in reputable peer-reviewed scientific papers and used by other scientists and organizations around the world; it is not ‘data fabrication’ as recent claims have suggested. The Met Office inspects their weather stations using both WMO and Met Office inspection standards, and their research and data are externally reviewed by independent scientists with relevant expertise. Therefore, recent claims implying the Met Office is ‘fabricating data’ or using ‘junk’ weather stations for climate reporting are misleading and lack important context about the scientific rigor of the Met Office’s research.
References:
- 1 – Barrios et al. (2018) Alternative approaches for estimating missing climate data: application to monthly precipitation records in South-Central Chile. Forest Ecosystems.
- 2 – Perry and Hollis (2005) The development of a new set of long-term climate averages for the UK. International Journal of Climatology.
