Using meteorological reanalysis to identify weather conditions for classifying atmospheric electricity data

Atmospheric electricity Potential Gradient (PG) data has typically been classified by local weather conditions, such as by identifying data recorded during “fair weather” (FW) or in the absence of rainfall “no hydrometeors” (NH), to try and obtain globally representative values. In general, this approach is essential in obtaining global atmospheric circuit (GEC) signals. The weather information needed to do this is, however, only available from some of the sites providing atmospheric electricity measurements. For other sites, meteorological reanalysis – of which there are many products available, spanning different times and scales - may provide a data source for such classification of PG data. This study investigates the integration of ERA5 meteorological reanalysis data to identify FW and NH conditions and improves the quality of data used in long-term atmospheric electricity studies.  

Initial findings investigating the meteorological quantities show a strong correlation between wind speed, total cloud coverage and total precipitation from ERA5 and observed ground-based measurements at the Eskdalemuir and Lerwick sites. This is to be applied to classifying past atmospheric electricity data, specifically of the hourly potential gradient (PG), which were obtained at the Lerwick observatory from 1925 to 1984, and Eskdalemuir observatory, which made atmospheric electricity measurements from 1911-1981 (Harrison & Riddick, 2022; Märcz & Harrison, 2003). 

Identified criteria from ERA5 which best match for FW and NH conditions are implemented in historical data from the Lerwick and Eskdalemuir observatories, enhancing the reliability of past studies which is important for atmospheric electricity analyses. This supports the potential of ERA5 data for providing information to identify FW and NH conditions. From this, we are evaluating a range of methods to use the meteorological reanalysis, with the aim of recovering representative FW data at sites lacking meteorological measurements.