Creating long-term climate data records using transfer functions

Merging data records from different instruments into a consistent long-term data record is challenging process, especially when the parent datasets have a very short overlap or do not overlap at all. In addition, parent datasets can have different vertical resolutions and temporal and spatial samplings. In these cases, there is a need for a transfer standard - an independent data record that overlaps with parent datasets, allowing to characterize differences between the parent datasets and to derive absolute adjustments. In this study we discuss requirements for the transfer standard including long-term stability, spatial and temporal sampling. We estimate how various properties of the transfer standard affect stability of the merged record and derived long-term trends. We assess the impact of the transfer function on the trends of merged datasets from satellite observations, on the examples of merging ozone records from SAGE II / MIPAS / OMPS NASA and temperature records from HALOE / MIPAS, using EMAC, CMAM and WACCM model fields as transfer standards.