The Copernicus Climate Change Service (C3S) Global Land and Marine Observations Database aims to produce a comprehensive land-based meteorological data archive and inventory spanning the entire history of instrumental observations. This requires the compilation of available land-based station meteorological data and information (metadata) from all known available in situ meteorological data repositories/sources at multiple timescales (e.g. sub-daily, daily, and monthly) (Thorne et al., 2018). Observations form the foundational basis for understanding how our climate has changed and continues to change. By collecting, documenting, and curating these sources in partnership with the National Oceanic and Atmospheric Administration's National Centers for Environmental Information (NOAA/NCEI) the long-term and fail-safe availability of these meteorological data sources can be assured for future generations.

This work is being carried out by the Irish Climate Analysis and Research UnitS (ICARUS), Maynooth University, Ireland (lead institute), under contract with C3S. The C3S aims to support adaptation and mitigation policies of the European Union by providing consistent and authoritative information about climate change (https://climate.copernicus.eu, last access: 7 November 2019). C3S is implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Commission to make climate data and information more easily available to society. To assist us in this task we have sub-contracted partners in the United Kingdom (UK) at the Met Office, the National Oceanographic Centre, and the Science and Technology Facilities Council. We are also working closely with NOAA/NCEI, who are based in the United States. Data sources for the database include major collections of historic weather data archived at NOAA/NCEI, as well as substantial holdings of meteorological in situ observations used for numerical weather prediction and climate reanalysis at ECMWF. Many additional sources of data from national weather service providers, atmospheric research institutions, and the multitude of historical data rescue activities taking place around the world will also be included.

Building the database requires the development of data source inventories, retrieving data from all available sources, converting the data to a common representation, merging them into harmonized records, and applying quality checks at all levels. Over time, the database will be continually updated with additional observations as they become available. Access to the database will be provided by C3S via an internet-based climate data store (CDS) (https://cds.climate.copernicus.eu, last access: 7 November 2019), which will also offer many other datasets and tools needed to enable the development of applications of the data for a variety of purposes.

However, while compiling these data inventories it has become clear that many data sources contain stations with demonstrably incorrect location coordinates. This is most obvious for those land-based stations which, when mapped, have coordinates that situate them over a water body. Until such issues are resolved, these stations cannot be included in the process to be served via the CDS. Critically, many of these issues are related to stations located in regions of the world where a sparsity of climate data currently exists, such as Southeast Asia and South America. Therefore, a goal of this classroom-based exercise was to resolve these station location issues so that these important stations can be included in the CDS.

To quantify the number of currently inventoried land-based stations that were potentially situated over a water body, mapping software tools were used. All of the station location points were first mapped according to the coordinates provided in each data source. Next, using the mapping tools, all station points were overlaid on a global country boundary shape file. Stations that did not lie within the shape file land boundaries were deemed to be situated in the ocean. Using this process, a total of 7975 stations with daily data and 9144 stations with monthly data have been identified in the sources inventoried to date as not being situated on land. These spurious station location cases arose from a broad range of primary data sources. They were next checked to see if they could be identified as actual buoys, platforms, or ships. If not, then they were extracted from the inventory for further consideration.

Figure 1 shows the stations with daily and monthly data that have been identified as having location issues. These stations are classified as land-based stations, but are located over a water body, with most stations lying just off the coast, which indicates a geo-coordinate precision issue. To give a sense of the scale of the location problems, Fig. 2 presents a histogram of the number of stations (with both daily and monthly data) and the distance from land in metres (m). Figure 2 also shows that 10 256 stations located in the ocean are within 1000 m of land, 1259 are within 4000 m, 876 are within 7000 m, 423 are within 10 000 m, 255 are within 13 000 m, 146 are within 16 000 m, and the balance of 66 stations are within 22 000 m. There were 2838 stations that could not be mapped due to missing latitude or longitude coordinates. The results in Fig. 2 show that most stations lie within 1000 m (1 km) of land, which suggests that they are either lighthouses, platforms, buoys, or that they are land stations with coordinate precision issues.

The stations with daily data are from 58 different data sources, whereas the stations with monthly data are from 41 different data sources (Table S1 in the Supplement). The majority of the daily station location issues were identified in two sources; NOAA/NCEI's Global Summary of the Day (GSOD) product (2506 stations) and the Global Historical Climate Network Daily (GHCND) dataset (1649 stations). The remaining 56 sources with daily data contain an average of 68 stations with the location issues per source ranging from 1 to 881 stations per source. At the monthly time step the UK Met Office data source has the most station location issues, with 2511 stations identified, and the Monthly Climatic Data for the World (MCDW) data source has the second most, with 844 station location issues identified. The remaining 39 monthly data sources contain an average of 148 stations per source ranging from 1 to 784 stations per source (Table S2 in the Supplement).

Another issue which has come to light involves station clustering along the prime meridian which suggests station geolocation issues. These stations were also extracted from the inventory but are not considered further here. Undoubtedly, there are additional station coordinate issues that lead to the incorrect placement of sites over land (as opposed to over water). Future checks are planned to use comparisons between target stations and apparent neighbouring stations or comparisons to reanalysis products to identify such cases, but this is outside the scope of the present analysis. Such comparisons should highlight stations that are grossly mislocated based upon both the phase and amplitude of annual cycles and synoptic features.

We developed the Geo-locate project so that we could enrol the help of second-year undergraduate geography students at Maynooth University to resolve some of the land-based station geolocation issues identified. The pilot first round of the Geo-locate project was run in the second semester of the 2017/2018 academic year. For this pilot we began with 880 daily resolution stations identified as having location issues. It was decided that three different students would attempt to resolve each station to try and attain triple verification of the revised location. We produced 88 excel sheets with 10 stations in each and divided the 264 students into three groups; each group of 88 was allocated the same 88 excel sheets with one sheet per student.

Each of the stations was supplied with the associated geographic coordinate information, which was known to be incorrect as it placed the station over water. All of the stations that the students worked with were reporting as land-based stations. These stations will, in general, be over water for some combination of resolvable issues. These could include imprecise geographic coordinate information, the incorrect conversion from degrees, minutes, and seconds to decimal degrees, e.g. dropped minus signs placing the station in the incorrect hemisphere (N–S or E–W), or, simply, missing coordinates.

Students were assigned with carrying out a sequential set of tasks to gather evidence to support the relocation of each of the stations and to provide all available evidence to support their conclusions as to why a station's coordinates should be as they indicated. They needed to employ a variety of research tools, including Google Earth, Google Maps, web searches, recourse to dedicated climate data information sources, and a variety of additional research tools and information to determine the improved location of their allocated stations.

The students were provided with step-by-step instructions and guidance on how to best resolve the station location issues. A copy of the student handout sheet that describes the guidance and steps required to complete the assignment is available in the Supplement. Figure 3 shows a summary workflow of the guidance and steps that students were asked to follow. Initially, students were tasked with mapping the stations by importing the station data into Google Earth and visualizing the current station locations. For many of the existing station locations, students were able to determine/narrow down the research focus based on viewing the station locations relative to the surrounding land and the labelled features on the map which may correspond to the station name.

Step 1 involved students first checking the World Meteorological Organization (WMO) Observing Systems Capability Analysis and Review Tool (OSCAR) (https://oscar.wmo.int/surface//index.html#/, last access: 7 November 2019) to see if the station name existed in the database. The OSCAR database is the official metadata repository of the WMO Integrated Global Observing System (WIGOS) for all surface-based observing stations and platforms. For more information see https://www.wmo.int/pages/prog/www/wigos/index_en.html (last access: 7 November 2019). If the station name was not found in the OSCAR database, students were asked to enter the details of their search on their allocated student sheet and move on to the next step. Step 2 involved students checking to see if the station was contained in any of the national meteorological agency station information sheets that were provided. If the station was not in any of the information sheets, the students were again asked to comment and then move on to Step 3. In Step 3, it is suggested that students conduct a web search combining the station name plus some key terms such as “weather station” and “latitude longitude” to try and find any relevant information. If the station name cannot be found using any of the steps, then students were to comment that this station could not be found and record details regarding each step taken. If a revised station location was found, students were required to proceed to the evaluation step. As an extra step, students were required to try to verify the coordinates using alternative sources. For example, even if the WMO OSCAR database contained geographic coordinates for a station, students were asked to verify the coordinates provided by OSCAR by following the instructions in Step 2 (i.e. performing a Google search to locate a country's meteorological agency website and then looking for the station coordinates on the site or checking in one of the station information files that were provided). A snapshot of an example of a completed student sheet is given in the Supplement and shows the details of each step undertaken as well as the outcome.

During the project, teaching staff (consisting of faculty, postdocs, and postgraduate students) provided ongoing support to the second-year students including regular scheduled workshops and question and answer sessions via an online forum. We developed short video tutorials for each of the steps outlined above that students could access via an online e-learning environment. The overall aims and goals of the Global Land and Marine Observations Database activity were also delivered via an introductory lecture by the lead author of the present study. In addition, Dick Dee, the deputy head of the Copernicus Climate Change Service at the time, contributed an introductory video piece outlining the importance of the students' work. The video was shown to students during the introductory lecture to help motivate the students and make them aware of the wider importance of the project to the scientific community. A copy of the Dick Dee introductory video is available at 10.5446/41783.

The assignment deliverables and subsequent project marks (worth 50 % of the overall module) were based on the students completing the following:

A spreadsheet with the station list, original coordinates, and new, updated coordinates. The spreadsheet also required the student to detail how they obtained the updated coordinates and to add comments briefly outlining the sources for the new coordinate information and their justification. An example spreadsheet template is provided in the Supplement. Marks for the completed station .xls file were based on the number of stations completed with full details/comments/supporting information (35 %). However, students were not penalized marks if they were unable to find the correct location, so long as they provided full details of all of the steps conducted and included a full traceable account.

The Geo-locate project has now been run over the 2017/2018 and 2018/2019 academic years. The results are discussed in the following two subsections. Lessons learnt from the pilot project in 2017/2018 were applied in the following year, achieving both greater levels of output and an improved learning experience. In both years a substantial number of geolocation issues appear to have been resolved. The updated station locations from the Geo-locate project must be treated as approximations of the actual locations. Following the student assessment, the locations are now plausible enough that they can be used for certain applications. However, in the available archives, the true location of a station is often unknown owing to poor documentation and retention of metadata, so this is not too distinct from how other station locations from many sources must be treated. The updated locations and the metadata trail of the decisions made will be captured and used in the C3S Global Land and Marine Observations Database and at NOAA/NCEI.

The following statement is taken from the Department of Geography second-year student handbook and sets out the newly revised pedagogical aims of the department's teaching in that year of the programme which this assignment partially aimed to fulfil.

The focus of this second year of the Geography undergraduate programme is on Methods and the Systematic Branches of the Discipline. Students are introduced to different systematic branches of Geography and learn that within both human and physical Geography there have emerged distinctive sub-areas with their own concerns and trajectories. In parallel, year 2 foregrounds the teaching of basic research methods. Students learn to work as individuals and as part of teams, and in the laboratory and in the field, to identify, source, collect and analyse primary and secondary data, and to evaluate and present research results and findings. In addition, students are provided with the opportunity of applying the research skills acquired in year 2 through field work in Ireland and overseas. All students will also learn the basics of GIS (van Eggeraat, 2018).

The specific expected student learning outcomes of the second-year “Methods of Geographical Analysis” (GY202) module, of which the Geo-locate project was part, are as follows.

Upon successful completion of the module, students should be able to

develop further data collection, processing, computer, and presentation skills, based on work in first year and in GY201;

We have shown how second-year undergraduate students in the Maynooth University Geography department can help to rectify geolocation issues in global meteorological database holdings in a transparent manner while gaining valuable skills. Each iteration to date has been improved by reflecting critically upon the delivery and outcomes of the prior year(s). The problem set is well-suited to our second-year methods class, a compulsory module within the honours component of the degree. As resources permit, we aim to expand the exercise to provide an enriched learning experience as well as improved outcomes.

There is no shortage of further work. Currently as part of the C3S Global Land and Marine Observations Database we have inventoried 23 619 sub-daily stations derived from 51 sources, 173 782 daily stations from 137 sources, and 85 186 monthly stations from 55 sources. In addition, new sources of data are being acquired all the time which means that the potential issues with resolving station locations may be an ongoing challenge. For example, we are working closely with the C3S Data Rescue Service to ensure that all rescued climate data is deposited via the new data discovery and deposition web-based service which we are developing (Noone et al., 2019). Work is also ongoing in collaboration with the European Environmental Agency (EEA) in its capacity as the Copernicus in situ lead, and with ECMWF in its capacity as the entrusted entity for C3S. Additional data inputs for the database may also be secured based on the recently enacted EEA–EUMETNET (EUMETNET is a grouping of 31 European National Meteorological Services) agreement on data sharing. We have identified several thousand stations across the existing secured sources that require checking and it is all but certain that newly acquired sources will also contain geolocation issues. Therefore, there is likely to be no issue with running the Geo-locate assignment for years to come.

In terms of varying the nature of the problem set provided, as alluded to in the introduction, as well as stations incorrectly located over water which are easy to identify, if not to rectify, many could be incorrectly located on land. To identify such land-based locational outliers, we plan to develop a suite of data quality control checking tools. For example, pairwise homogeneity assessment could be used to identify any irregularities in data when compared with data from other stations within a given distance of each other (Dunn et al., 2014; Durre et al., 2008; Menne et al., 2012). This process will be automated as much as possible but there will be a need for visual checks. Stations identified via these approaches could constitute an additional valuable source of data for future iterations of the Geo-locate project providing a greater variety of issues for students and additional tools such as data comparison tools which may enable a more nuanced assessment in future as well as improving learning outcomes for the students.

A further innovation under active consideration could arise from the use of reanalysis data. Reanalysis provides datasets at regular intervals over long periods of time for climate monitoring and research (e.g. Dee et al., 2011) that are produced via data assimilation using a frozen version of a given forecast system. The C3S reanalysis data contains estimates of atmospheric variables such as air temperature, pressure, and wind at varying altitudes. Reanalysis also contains surface variables such as rainfall, soil moisture content, and sea-surface temperature. ECMWF reanalysis products provide estimates for all locations on Earth, and ERA5 will shortly extend back to 1950 (https://www.ecmwf.int/en/research/climate-reanalysis, last access: 7 November 2019). Longer-term reanalysis products now extend back over in excess of 150 years (Slivinski et al., 2019). To address the location issues over land, and also to confirm the relocation of stations currently located in the oceans, in future project iterations we are actively working with the reanalysis groups to investigate the potential to compare the station data with the reanalysis data at the same location or plausible alternative locations provided by the students to identify likely differences due to incorrect station locations. This shall require the development of underlying software and a web-based interface to enable the analysis but would add considerable flexibility and data analysis aspects to future assignments, enriching the learning outcomes.

There is also the potential to further extend the analysis of the data records. The second-year methods class runs throughout the academic year. The Geo-locate project has now been moved up to the first semester in the expectation that, in future years, students might be able to follow through in later assignments in the year which may also touch upon more human geography methodological aspects in addition. Examples could include, but are not limited to

an analysis of the station geophysical measurement series to consider climatology and climate trends in diverse regions of the world and identify potential data issues;

The Geo-locate project which worked with second-year undergraduate geography students has been successful both in terms of educational outcomes and resulting geolocation issues resolution, with 1926 land-based stations with location issues in the original sources ostensibly resolved. In addition, the students identified 91 marine stations. This is a significant result as these stations can now be included in the inventory to be assessed for inclusion in the Copernicus climate data store (CDS). Such a result would have taken many person months, if not person years, of service team members' effort to achieve and would not have benefitted from multiple independent assessments. Many of these stations are situated in regions where there are sparse observations, and the inclusion of these stations in the CDS will allow for a more robust climate assessment in the future. An updated list of all of these stations will be made available through the service as metadata, which will also include all of the student comments and notes.

The results of the student feedback survey are generally positive and indicate that most students gained some of the useful transferrable skills outlined in Sect. 5 and felt like they were involved in a meaningful real-world project. In addition, the students generally felt that the support and guidance given were sufficient in helping them complete this assignment. We will be reading over all of the students' comments and suggestions (positive and negative) and will continue to evolve the project to ensure optimal educational outcomes. Based upon the successful educational outcomes and data problem resolutions attained in the first two rounds of the Geo-locate project, we aim to continue the project for many years to come. Finally, we would encourage other organizations to investigate the potential for engaging university students to help resolve similar data issues. Likewise, students can aid with other projects where labour-intensive tasks exist, and they can gain useful research skills and have the opportunity to work with real data.