Historical geomagnetic field observation data from unpublished handwritten tables created at the Irkutsk Observatory (1890): horizontal component - Vadim Soldatov; Sergey Sokolov (PANGAEA, 2024)
Here we present the digitized timeseries of hourly observations of the geomagnetic field horizontal component (H) in Irkutsk in 1890 from unpublished handwritten monthly tables. Observations of the horizontal component were made with the Edelmann bifilar magnetometer. These data from the Irkutsk Observatory (IRT code) were not initially included in the published annual reports. All date/time marks are converted to UT. Horizontal component is given in nT. The original digital images of the tables are included as well. For reference, we also provide the digitized table as it appears in the original handwritten record (H-1890-source.dat). The data were digitized manually; first column of the table contains date, next 24 columns are hourly values in nT, and the last column is true daily average (TDA). Daily averages for some months (January-July) are missing from the original record, but we were able to recover them from monthly means of the corresponding yearbook https://library.oarcloud.noaa.gov/docs.lib/htdocs/rescue/cd111_pdf/LSN0229.PDF, p.15). In fact, all hourly quantities in the table are not true horizontal intensity values, but deviations from daily averages. To obtain a horizontal intensity value, one should take an hourly value from table and add a corresponding daily average (TDA). You may notice that hourly values start at 1AM and finish at midnight, so midnight refers to the previous day. This was a common convention at that time. All time marks in the source table are local (geographical location of the Observatory was 52°16 extquotesingle19N, 104°18 extquotesingle27E); time shift is 7 hours. Keep in mind that an Orthodox calendar was in use in Russian Empire at those times, so, date shift for the year 1890 was 12 days. To make things clear, we add a short script in Julia performing the above conversion from source table to timeseries.