Blitzortung.org Data Archive
SQLite Data Archive

The SQLite data archive contains the impact data until to ende of 2023 calculated by blitzortug.org in SQLite3 data files. The file names are build as follows:

S{container}-R{region}-Y{year}-M{first month}-{last month}-N{north bound}-S{south bound}-W{west bound}-E{east bound}.sqlite

Example: The file

S1-R1-Y2023-M01-12-N90-S-90-W-180-E180.sqlitedatabase

contains the data calculated in container 1 for region 1 (Europe 1) between January 1 and December 31, 2023 with a latitude between -90 and 90 degrees and a longitude between -180 and 180 degrees.

For more information about the entries in the data files, see the metadata table of the files.

SQLite Data Archive

The database contains two tables named metadata and strokes. The strokes table contains the following columns:

the strokes table
column description
timetimestamp in nanoseconds since midnight on January 1, 1970
latlatitude in degrees (decimal)
lonlongitude in degrees (decimal)
altaltitude above sea level in meters
polpolarity, -1 or +1
mdsmaximum deviation range in nanoseconds
scssmallest all-covering sector in degrees, formerly called mcg
(example: 210 degrees = the detectors are in a sector of 150 degrees from the impact location)
statusstatus (optional)

Here is an example of how to filter out data entries from an sqlite3 database file.

open the database file:

>sqlite3 S1-R1-Y2023-M01-12-N90-S-90-W-180-E180.sqlite
SQLite version 3.37.2 2022-01-06 13:25:41
Enter ".help" for usage hints.

list the table names:

sqlite> .tables
metadata strokes

read the metadata

sqlite> select Value from metadata where name = 'Description';
This database contains information about possible locations of electromagnetic discharges, calculated from the jsondatabase data provided by the participants of the project Blitzortung.org..

show the preferences

sqlite> .show
echo: off
eqp: off
explain: auto
headers: off
mode: list
nullvalue: ""
output: stdout
colseparator: "|"
rowseparator: "\n"
stats: off
width:
filename: S1-R1-Y2023-M01-12-N90-S-90-W-180-E180.sqlitedatabase

output the number of entries in table strokes

sqlite> select count(*) from strokes;
12583194

set output format to csv

sqlite> .mode csv

output selected strokes

sqlite> select * from strokes where lat < 45 and lat > 44.95 and lon 14 and lon > 13.6;
1673898604479904941, 44.950874, 13.646371, 0, 0, 6140, 73, 322, 13
1673898604479915532, 44.969227, 13.6342, 0, 0,9739, 134, 431,20
1673898604479909643, 44.969513, 13.630484, 0, 0, 5950, 138, 412, 18
1674257357563815319, 44.954322, 13.959775, 0, 0, 14821, 198, 66, 13
...

quit the program

sqlite> .quit
>