In summary:
- We want to build a global database of parallel measurements: observations of the same climatic parameter made independently at the same site
- This will help research in many fields
- Studies of how inhomogeneities affect the behaviour of daily data (variability and extreme weather)
- Improvement of daily homogenisation algorithms
- Improvement of robust daily climate data for analysis
- Please help us to develop such a dataset
Introduction
 One way to study the influence of changes in measurement techniques is by making simultaneous measurements with historical and current instruments, procedures or screens. This picture shows three meteorological shelters next to each other in Murcia (Spain). The rightmost shelter is a replica of the Montsouri screen, in use in Spain and many European countries in the late 19th century and early 20th century. In the middle, Stevenson screen equipped with automatic sensors. Leftmost, Stevenson screen equipped with conventional meteorological instruments. |
We intend to build a database with parallel measurements to study non-climatic changes in the climate record. This is especially important for studies on weather extremes where the distribution of the daily data employed must not be affected by non-climatic changes.
There are many parallel measurements from numerous previous studies analysing the influence of different measurement set-ups on average quantities, especially average annual and monthly temperature. Increasingly, changes in the distribution of daily and sub-daily values are also being investigated (Auchmann and Bönnimann, 2012; Brandsma and Van der Meulen, 2008; Böhm et al., 2010; Brunet et al., 2010; Perry et al., 2006; Trewin, 2012; Van der Meulen and Brandsma, 2008). However, the number of such studies is still limited, while the number of questions that can and need to be answered are much larger for daily data.
Unfortunately, the current common practice is not to share parallel measurements and the analyses have thus been limited to smaller national or regional datasets, in most cases simply to a single station with multiple measurement set-ups. Consequently there is a pressing need for a large global database of parallel measurements on a daily or sub-daily scale.
Also datasets from pairs of nearby stations, while officially not parallel measurements, are interesting to study the influence of relocations. Especially, typical types of relocations, such as the relocation of weather stations from urban areas to airports, could be studied this way. In addition, the influence of urbanization can be studied on pairs of nearby stations.
