In June 2014, the first version of the global databank was released (Rennie et al., 2014), which included data from nearly 50 different sources and an algorithm to resolve duplicate stations and piece together complete temperature time series. Since then, there have been monthly updates, appending new data to existing stations. Thanks to user feedback, along with additional analysis described below, minor changes were introduced and implemented to the merge program to ensure the most accurate data were incorporated in the final product. This, along with updates to current sources required a small change to the versioning system. The remainder of this post will highlight the changes implemented in the global land surface databank, version 1.1.0. More information about the structure of the databank, including sources, formats, and merge algorithm, can be found on the databank website (www.surfacetemperatures.org/databank)
Updates to Stage 1 and Stage 2 DataThe databank design includes six data Stages, starting from the original observation to the final quality controlled and bias corrected products. For the purposes of this update, only three stages were modified: digitized data (Stage One), data converted to a common format (Stage Two), and the merged dataset (Stage Three).
Further assessment was also done on one of our sources known as “russsource.” This source contained over 36,000 stations reporting maximum and minimum temperature. While the original format was consistent across all stations, it was discovered that this source included 27 individual sources. It was decided to split these sources up and place them individually in the merge following the source hierarchy defined by the databank working group. Because of some duplication with sources used in GHCN-D, only 20 of the 27 sources were included. In addition, station ID’s were brought into the Stage Two data, so that the merge’s ID test could be implemented. The same was done for the source known as “ghcnsource.”
Other than the above, no additional sources were added to the source hierarchy. One source however was removed (crutem4), because it was determined that the use of these stations as a last resort was causing stations to be unique because of the data changes through bias corrections. Candidate stations from crutem4 were matched with their respective target stations through metadata tests, but were chosen as unique from the data tests, because of these corrections. In order to avoid excessive station duplication, this source was removed.
Changes to Merge Algorithm
The merge algorithm, as described by Rennie et al. 2014, underwent no code changes. However, a couple of thresholds were modified in order to maximize the amount of data the final recommended product would have. The thresholds are defined in a configuration file that is required for the program to run successfully.
The first step of the merge algorithm takes into account the metadata between a target and candidate station, including the stations latitude, longitude, elevation and name. A quasi-probabilistic comparison is made and the result is a metadata metric between 0 and 1. In version 1.0.0, this metric needed to pass a threshold of 0.50 in order to be considered for merging. Analysis showed that too many stations were being pulled through and forcing merges between stations that shouldn’t have. As a result, a stricter threshold of 0.75 was applied, in order to avoid this issue.
In addition, once a candidate station is chosen to merge with a candidate station, it needs to fill in a gap of at least 60 months (5 years) in order to be added to the target station. It was determined that this gap was too large, and target stations with short gaps in its data were not being filled in by qualifying candidate stations. This gap threshold has been reduced to 12 months as a result.
Similar to version 1.0.0, all decisions made were tested against an independent dataset generated from hourly data for US stations available in the Integrated Surface Dataset (Smith et al. 2011). Results only show a small change between the two versions
Version 1.1.0 of the recommended merge contains 35,932 stations (Figure 1), nearly 4,000 stations more than v1.0.0 (32,142). Figure 2 depicts that the addition of stations reflect the most recent period, as there is relatively a 10% increase in the number of stations since 1950. It should be noted that there is a drop in coverage prior to 1950 with the new version. However it is the author’s opinion that this was reflected by removing crutem4 as one of the sources. Including this source had made candidate stations unique, due to differences in its data as a result of the data providers bias corrections. While the number of stations is lower during this time period for v1.1.0, it should be noted that the number of gridboxes used in analysis (Figure 3) was either equal, or slightly higher than v1.0.0.
Stage Three normally includes a merge recommended and endorsed by ISTI, along with variants showing the structural uncertainty of the algorithm. Due to time constraints, these variants are not available, however will be provided at a later date.
|Figure 2: Station count of recommended merge v1.1.0 by year from 1850 to 2014, compared to version 1.0.0, along with GHCN-M version 3.|
|Figure 3: Percentage of global coverage with respect to 5 degree gridboxes for the recommended merger v1.1.0 by year from 1850-2014, comparted to version 1.0.0, along with GHCN-M version 3.|