A view of Met Office HQ from front

In depth: Classifying land-based observations

So how exactly do we ensure accurate observations, that are accurate on the day and able to be added to the UK’s ongoing climate records?

The integrity of weather observations is of paramount importance to the Met Office, the UK and global monitoring. Over 300 land-based sites across the UK are providing data on rainfall amounts, temperature, wind speeds and a range of other weather variables.

Despite online speculation, much of which demonstrates a clear misunderstanding or misrepresentation of the facts, Met Office weather stations are subject to stringent national and international guidelines.

We’re a world-leading organisation when it comes to observing our weather and the UK’s changing climate. The Met Office team carries out hundreds of site inspections every year, ensuring adherence to the highest standards, both nationally and internationally.

A rigorous quality assurance system, including a longstanding and well-honed site inspection methodology, ensures that data produced at our sites are as accurate and reliable as they can be.

Assessing quality of observations

In accordance with internationally defined best practice, the Met Office has a long-standing inspection scheme which assesses a station for each meteorological element in terms of its suitability for use in meteorological and climatological products.

The assessment looks at a range of factors to inform the ratings for Met Office stations. This includes instrument conformance, installation and exposure. Ensuring consistency of observations across the UK ensures data used for Met Office forecasts is an acceptable quality, and that we’re adding to the UK’s climate records in a way that maintains the scientific integrity of the data.

The assessment of equipment at Met Office stations has four categories: Excellent, Good, Satisfactory or Unsatisfactory. Where an element of a station is found to be unsatisfactory, it is flagged as such in databases and not used inappropriately in Met Office products and services.

In addition, when assessing output from Met Office weather stations, data is compared to nearby observations, as well as what’s feasible in the synoptic meteorological set-up, to check for any spurious data which needs to be checked, marked as suspect, or not be used in Met Office products and services. Indeed, this does happen on occasion, where an observation has been found to be unsatisfactory, and therefore wasn’t used as an official observation.

International classifications

The Met Office network management and quality control methodology is based on World Meteorological Organization standards and methods to ensure weather and climate data from the UK is as accurate as possible.  

The WMO CIMO classifications of weather stations provide an additional, more simple global assessment scheme, designed to be a broad indicator on how well an instrument meets the siting recommendations defined by WMO and the degree to which it is likely to be representative of the wider geographical area around the station.

So, a Class 1 site would indicate an ideally exposed station, representative of a very large area around it, while a Class 4 or 5 site would be representative of station that has some noted exposure characteristic (partial shading at high latitude locations is a common example) where the surrounding region naturally has greater variation.

Designed for global use, WMO classifications (as stated on their own site) should not be used to suggest a ranking of station quality. Indeed, WMO specifically state, “The use of numbers can easily lead one to suggest a ranking. This is not the purpose and should be avoided… Many sites have been chosen to serve the needs of many users, it is likely that many sites will not be class 1 for all parameters.”

WMO Siting Classifications were designed with reference to a wide range of global environments and the higher classes are simply not always possible in the UK or other locations around the world, which have many densely populated areas, as well as getting more frequent projected shade being on a higher latitude.

For example, 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 thermometry screen all year around - 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.

For absolute clarity, the proximity and scale of any artificial heat sources, areas of water and reflective surfaces is carefully considered by our team of experts and is included in Met Office classifications of sites. The integrity of data collected is of paramount importance to the Met Office, as well as the dedicated experts who inspect and maintain our weather station network.

Scientific integrity

The efforts of a small number of people to undermine the integrity of Met Office observations by obscuring or misrepresenting the facts is an attempt to undermine decades of robust science around the world’s changing climate.

We understand that the data from thousands of independent global weather stations (over the last seven decades) which show a warming trend may be an uncomfortable reality for some. What’s important is that numerous datasets from around the world consistently show that our climate is warming and over 90% of scientists agree that it is human activity that is driving this change.

It is not just land-based weather stations which are observing the Earth’s changing climate. Satellites, radiosondes, ice and sea level measurements, sea-surface observations and a wealth of other equipment continues to tell a consistent and scientifically robust story of the Earth’s rapidly changing climate.

Find out more about weather observation site classification.

Find out more about observations, including some of the misinformation you may encounter.

Find out more on how observations help us forecast the weather.