the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 Nov 2025
Continuous meteorological surface and soil records (2004–2024) at the Met Office surface site of Cardington, UK
Abstract. A continuous meteorological and hydrological observational record is described of the Met Office semi-rural field site of Cardington in southern England between 2004 and 2024. The site was designed to carry out boundary layer, fog and air-surface exchange research to improve the representation of process-based physics within the Met Office Unified Model. The site lay in a flat river basin and was laid mainly to cropped grass and was surrounded by arable fields intermixed with small trees and shrubs through most wind sectors. Observations utilised flux masts at various heights, visibility, radiosondes, very near-surface and subsoil in situ sensors in addition to more specialist remote sensing instruments to retrieve atmospheric properties. In addition to boundary layer and surface data, soil properties such as temperature, moisture and water table depth were obtained. All components of the surface energy balance could be determined. Availability of data based on 30 minute time steps over 20 yr, for the combined components of the energy balance not flagged as either bad or missing, amounts to 77 %. The momentum roughness length as determined at the 10 m height for the prevailing wind sector increased from 3 cm to 8 cm over the period predominately due to 52 ha of woodland growth within 1 km of the site. An overview of the site, instrumentation, data availability, quality control, data storage at the UK CEDA repository, and potential uses of the dataset are described. A set meteorological forcing files have also been compiled suitable for driving standalone land surface models configured for a single point.
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Status: final response (author comments only)
- RC1: 'Comment on essd-2025-486', Norbert Kalthoff, 25 Nov 2025
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RC2: 'Comment on essd-2025-486', Anonymous Referee #2, 05 Dec 2025
The manuscript presents a 20-year (2004–2024) record of surface meteorological, radiation, turbulence, and soil–groundwater measurements from the Met Office Cardington site in the UK. The authors describe the station setting, instrumentation, data processing and quality control, and provide examples of potential applications, including land-surface model forcing and analysis of roughness changes due to local land-cover evolution.
While the data record is clearly valuable for the authors’ own modelling and process studies, in its present form I am not convinced that the manuscript fully meets the scope and quality standards of Earth System Science Data. ESSD expects data papers that describe original data sets of broad community relevance, with well-documented processing and uncertainty characterization, and a clear demonstration of their added value and potential for re-use in Earth system sciences. At the moment, the manuscript reads partly as a site/instrumentation report with relatively limited emphasis on what is genuinely new compared to existing Cardington data holdings and how this data product will serve the wider community.Major comments
1. Unclear added value and community relevance relative to existing Cardington data. Cardington has been used extensively in past boundary-layer and land-surface research, and some data streams are already archived and accessible via national data centres. The manuscript needs to much more clearly articulate. What is new in the present data product (variables, time coverage, harmonization, QC, uncertainty quantification, model-ready forcing, etc.) relative to existing archives.
2. For ESSD, a central requirement is a rigorous and transparent treatment of data quality, uncertainties, and temporal homogeneity. Instrument calibration procedures and long-term stability are described only qualitatively for many sensors, with limited quantitative uncertainty budgets. Changes in instrumentation, measurement heights, sampling strategies, and site surroundings (e.g. tree growth, urban expansion) are acknowledged but not systematically treated as inhomogeneities. It is unclear how these changes impact time series continuity and how users should handle them.
3. For some key variables (e.g. latent and sensible heat fluxes, soil moisture profiles, groundwater), quantitative uncertainties and bias estimates are only briefly mentioned or not given. Providing variable-by-variable uncertainty estimates, at least in the form of typical ranges or upper bounds, including contributions from calibration, representativeness, and processing assumptions.
4. Adding a dedicated section on time series homogeneity, listing all major changes (instruments, heights, surrounding land cover) in a table and describing their expected impact on the different variables. Where possible, including simple consistency checks (e.g. energy balance closure statistics, comparison of precipitation with nearby gauges, roughness length estimates vs. independent methods) to underpin the stated data quality.
5. The paper repeatedly highlights the “near-closure” of the surface energy balance as a key strength of the dataset. However, Energy balance closure is not quantified in a systematic way over the 20-year period (e.g. annual closure ratios, distributions of residuals). A dedicated analysis of energy balance closure statistics (e.g. Rn – G – S vs. H+LE), including seasonal dependence and possible trends. A discussion of how to interpret and possibly correct the fluxes if used for model evaluation, and a clear statement that the dataset provides raw fluxes without closure adjustment.
6. ESSD articles should allow users to understand and, in principle, reproduce the processing chain from raw measurements to published data. Add a flowchart or table summarizing the complete processing pipeline for each data class (radiation, turbulence, soil, meteorology), including all filters, thresholds, and corrections. Provide more detail on the turbulence processing settings, including references to codes or processing scripts if available. Clearly distinguish between what is in the “primary” data set (as measured/QC’d) and what is part of the derived forcing (gap-filled, aggregated, etc.), ideally with separate DOIs or at least very clearly separated files and documentation.
7. Adding a compact overview table or “data descriptor” section listing, for each product: time resolution, variables, heights, time span, file naming conventions, QC flag scheme, and example file links.Citation: https://doi.org/10.5194/essd-2025-486-RC2 -
RC3: 'Comment on essd-2025-486', Anonymous Referee #3, 14 Dec 2025
General Comments
This manuscript presents a 20-year observational dataset collected at the Met Office Cardington site in the United Kingdom. A key strength of this site is that the surrounding environment has undergone only limited changes over the past two decades, which effectively minimizes the influence of urbanization on climate-related studies. In addition, the site has many ground-based instruments, providing an observational basis for atmospheric research applications. Overall, the scientific value of this dataset is clear.
The manuscript is well structured and generally easy to follow. I recommend publication after minor revisions.
I mainly focus on three aspects:1. incomplete introduction for some remote sensing instruments, which may limit their potential applications; 2. missing measurement uncertainty information for certain instruments or variables; 3. the lack of consistency checks or adjustments among overlapping measurements from different instruments. While the latter may not be mandatory, users should at least be made aware of this issue.
Major Comments
- Section 5 introduces a variety of remote sensing instruments. However, for some instruments, essential information is not sufficiently documented. For instance, it is unclear whether the Doppler lidar operates at 1565 nm or 1.55 μm, and the channel configurations of certain microwave radiometers are not fully provided. This lack of information may limit the usability of the dataset. With complete instrument specifications, users could perform synergistic retrievals of cloud properties or data assimilation using combined observations. Similar issues may arise for other instruments due to missing key information. I therefore recommend either providing the full set of instrument specifications most relevant to users or explicitly referencing detailed technical documentation where this information can be found.
- Climate analysis and data assimilation both require stringent quality control procedures and measurement uncertainties, which are key concerns for users. I note that the core hydrometeorology instrumentation is well documented in terms of quality control. However, this information is missing or incomplete for many other instruments. For some non-core instruments, it may be sufficient to summarize the uncertainty information available in the instrument manuals or to provide appropriate references.
- Some instruments measure similar variables over overlapping time periods, which provides an opportunity for consistency checks and possible inter-instrument adjustments. Examples include measurements from multiple Doppler radars, wind profilers, and radiosonde observations. While such analyses may be beyond the scope of the current manuscript, it would be helpful to explicitly inform users of these overlaps and to remind them to consider potential inconsistencies when combining data from different instruments.
Minor Comments
- Although the manuscript is generally well written, its overall length is relatively large. Some sections appear to have limited importance. For instance, it is unclear whether Section 8 needs to describe the file storage format in such detail. This information could instead be clearly documented on the data webpage.
- Given the richness of the dataset, providing a time series or catalogue of major weather events observed at the site, if possible, would be highly valuable. This would facilitate targeted analyses of specific weather phenomena and could also help users identify and exclude certain outliers in climate studies.
- Lines 345 and 592: please arrange the supplementary materials in the order in which they are cited in the manuscript.
- Section 5.1 devotes substantial space to describing the principles of three-dimensional wind retrieval using Doppler lidar. In my view, these principles are largely consistent with commonly used approaches and may not require such detailed explanation. Instead, I would be more interested in the uncertainties associated with the retrieved three-dimensional wind fields. Similarly, the impact of near-field effects on lidar backscatter measurements warrants further attention. It would be beneficial to inform users of the height range where data uncertainty is expected to be relatively high, or to provide the corresponding quality flags. This also applies to Section 5.3.
- At line 715, the phrase “frequencies between 22.24 and 31.4 GHz” should be made more specific by listing the individual channels and providing their corresponding NEΔT values. For the retrieved temperature and humidity profiles, I also recommend providing retrieval uncertainties profiles, or alternatively referring to relevant technical documentation.
- Lines 539–540 emphasize that “The configuration of JULES here is the MetUM-JULES Regional Atmosphere and Land configuration as described in Bush et al. (2025).” Does Figure 3 use a different configuration from the other data? If the configuration is the same, this statement could be moved earlier to avoid potential confusion.
Data sets
Continuous hydrometeorological record (2004–2024) at the Met Office surface site of Cardington, UK Dataset Collection McGregor, J. Kerr-Munslow, A. Price, J. Osborne, S. Brooke, J. https://catalogue.ceda.ac.uk/uuid/5487380511084413a502c4b229273bc6/
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- 1
General comments: The paper describes a meteorological and hydrological observational record of the Met Office semi-rural field site of Cardington between 2004 and 2024. The paper is well written and structured. I therefore recommend publication after minor modifications.
My main concerns are: a) the introduction could be improved (see detailed comments below) and b) the advertisement for modellers to use the data could be improved. E.g. showing some nighttime data with fog – as fog forecast is still a big issue for modellers. This example could also include the CBL evolution after the fog night. c) I understand that the operators of the flux station don’t want to prescribe which corrections on sensible, latent and soil heat flux should be applied. But they are the most appropriate persons to suggest – at least - “accepted” algorithms.
Detailed comments
1 Introduction
This is a very long paper and not all seems to be so important. It feels like there is a break in the flow (lines 54 – 69, history of the site). I would remove that part.
An introduction should “introduce” the intention/aim of the paper. Here, you mainly focus on the energy balance closure problem – the problem not best/possible solutions. Do you need this in the introduction or could you even move it to section 3? Instead, I missing some information regarding Section 5. I.e., what was the intention for using/installing the non-score instrumentation.
Obviously, there was an aim to install the station: the site was designed to carry out boundary layer, fog and air-surface exchange research to improve the representation of process-based physics within the Met Office Unified Model.
Finally, you should address the reasons why the data set was published and for which model comparisons the dataset might be most relevant. A little bit advertisement could be done.
Table 1: table caption says period 2004–2024 but in the table you already start in 2003.
RAF should be explained – as abbreviations in general.
Line 79 – 80: “….. partition the surface energy balance via the fluxes of heat, moisture and
momentum ……”. For me, momentum is not part of the surface energy balance as net radiation, heat, moisture and soil heat flux are.
2 Site description
Lines 124 – 125: You mention: “An investigation by Grant (1994) showed that the terrain surrounding Cardington can influence the wind field by channelling surface flow along the ridge in a south-west to north-east direction for a stably stratified boundary layer.”
The wind rose shows mainly south-west to north-east directions. So, does stably stratified conditions dominate the wind rose? Do you have separate wind roses for day and night or stable and unstable stratifications?
3 Site set-up and data logging
3.1 Site set-up and data logging
Section and Subsection should not have the same title.
Line 173: Was the raingauge really positioned at surface level which would be very unusual (splashing water).
3.2 Core dataset instrumentation
Table 2: I would not use RH as in the column “Measurement” and “Variable” at the same time (see Rotronic sensor). Otherwise one column in the table could be removed.
Anyway, the title of the first column does not fit all the time. E.g. “Tri-axis sonic anemometer” is not a measurement but a measuring device instrument.
Also: what is the difference between specific humidity as variable and derived property.
Where do you give the units of the different variables (this concerns also Tables 3 and 4)?
3.2.1 Sonic anemometers
Could you say something about the ultrasonic measurements at 0.4 m. The height is close to the distance between the transmitter and receiver, i.e. a lot of the turbulence spectrum is probably not resolved.
General comment: so, no corrections were applied as described by Mauder’s TK3 software?
Line 237: Abbreviation PRT should be explained. Is it pressure, relative humidity and temperature?
3.2.2 Relative humidity
Lines 297 – 299: Have you measured dew point temperature higher than the air temperature? Data flagged or removed? Or indicated as fog detection?
3.2.3 Licor high speed hygrometer
Perhaps I missed it, but did you mention where - in relation to the sonic anemometer (distance and direction) - the Licor is installed?
Line 311: Same question as above: how are the covariances calculated - just from the raw data without any corrections?
3.2.7 Radiation
Line 385: why not just W m-2 instead of (J s⁻¹ m⁻²)?
Line 393: could refer to the WMO report
3.2.8 Subsoil sensors
Lines 553 and 564 (and elsewhere): is there any difference between ground and soil heat flux. I would suggest to use the same wording throughout the text when the same variable is meant. Otherwise it could be confusing.
Table 6 seems misplaced in this section
4 Land surface model forcing data
A general comment on the flux data (sensible, latent and ground heat flux). I understand that you don’t want to prescribe which possible flux corrections. But for model comparison: those who generate the data are normally most familiar which algorithms should be applied to derive the best quality data (while modellers are not and would be happy if the data producer would do the job). So, why not provide raw and corrected values? Or at least mention a program which could be applied.
Lines 538 – 555: I understand that the observation – modelling comparison is just meant as an example. Nevertheless, it would be interesting to know, whether the fluxes shown in Figure 3 are just the covariances derived from the raw data or corrections have been applied? And if yes, then which?
The comparison of the sensible heat flux at 0.4 m would be of interest, too. Just for me to know as I mentioned the problem of using a sonic at that height. Or just explain why you didn’t include the data in the comparison.
I would prefer to see some vertical profiles of the sensible and latent flux (although only two levels are available), e.g. averaged over some hours (around midday). These profiles should also give a hint whether data are trustful or maybe outliers. And if the fluxes are not constant (by ± 10%) in the surface layer some explanation would be helpful.
5 Non-core remote sensing instruments
Table 8 includes several acronyms. I suggest to explain them also in the table caption because the table is already referenced in Section 5 but the acronyms are only explained in section 5.1 and 5.2. What exactly is radial turbulence. Could you be more precise.
One general comment: the detailed descriptions of the remote sensing systems listed in Section 5 are quite different. E.g. in section 5.1 equations are given how the wind vectors (u,v) are calculated. The description of the ceilometer is more general. I would harmonise that. Perhaps a reference to books like Atmospheric Measurements (Foken Editor) could be useful where detailed measurement principles and algorithms of most of the remote sensing systems listed in Sections 5.1 to 5.4 are presented.
5.1 Halo Doppler lidars
Line 604: Add signal-to-noise ratio to SNR and replace signal-to-noise ratio by SNR in line 624
Line 635: what is qe and qn
Line 649: here you use φ but in the equation in line 647 you use 𝜑. Anyway, I suggest to use either elevation angle 𝜑 or zenith angle α.
Line 647: if you number the equations, this should be (5)
Line 650: if you introduce u and v, you should do it already ahead of eq. 3 and 4.
Line 655: AT instead of just T.
As mentioned above. Perhaps you just refer to the appropriate literature because section 5.1 is the only one which presents equations.
7 Example of turbulence data⎯ roughness length
The shown example on roughness length and it’s changes over time is interesting. However, I could imagine that some results from CBL and NBL observations in combination with energy balance data would encourage researchers to use the data for model comparisons.
8 Data availability
8.1 File formatting
It’s unusual have only one subsection in a section. I.e., two separate section would be more appropriate. I had problems to access some sources:
Line 869: “Page not found” for http://www.nationalarchives.gov.uk/doc/open-government870
licence/version/3/I got an error message
Line 939 - 946: “DOI Not Found” for wind radar data https://dx.doi.org/10.5285/eb352545ce1b4476b2580a3e5885c00d/
Line 878: I suggest to add the time zone – probably UTC
Line 885 and elsewhere: Does timestamps marks the beginning, center or end of the intervals?
References
I have not checked the references in detail but some inconsistencies are quite obvious.
etc
Miscellaneous
Line 33: If it is “well known” you could omit the sentence. Otherwise remove “well known”.
Line 35: On the other hand, …. . Shouldn’t you better say “additionally, …” because it isn’t in contradiction to something mentioned before.
Line 88: be careful with wording. Do you really mean energy budget or energy balance as discussed before (line 82)? A budget contains a storage term. Try to avoid mixing it up.
Table 1:
The way you list the entries in the table are somewhat inconsistent, e.g. Semicolon, comma, dot, Full stop at the end or no full stop:
In situ; turbulent fluxes
In situ, radiation.
In situ. Fluxes
Line 494: Normally, references should be listed in chronical order.
Typos
Figure 1c: Wind rose: m s-1 correct to m s-1
Figure 2: the labelling (data completeness) is too small.
Line 372: µ instead of u in 0.85 µm.
Line 374: It should be Koschmieder’s law instead of Koschmeider’s law.
Line 478: A dot is missing at the end of the sentence, i.e. after for NO2.
Line 665: Depolarisation instead of Depolarization?
Line 981: remove the second dot.
Table 7: Soil hydraulic conductivity in kg instead of Kg