Begin by exporting the required data from your Tempo instance. This can typically be done by navigating to the data export or reporting section of Tempo, where you can choose the data sets you want to export. Ensure that the data is exported in a format that PostgreSQL can read, such as CSV or JSON.

Once you have your exported data, prepare it for import into PostgreSQL. This involves cleaning the data to ensure it matches the target schema in your PostgreSQL database. Check for data consistency and format issues, and adjust column headers if necessary to match PostgreSQL table columns.

Ensure that your PostgreSQL database is set up and running. Create the necessary tables that will host the incoming data. Use SQL commands to define the schema, making sure that data types and constraints match those of the data you intend to import.

Move the prepared data files to the server or local system where the PostgreSQL database is hosted. This ensures that the data is accessible and ready for the import process. You can use secure file transfer methods like SCP or SFTP if the data is on a different server.

Utilize PostgreSQL’s built-in COPY command to import the data from the local files into the PostgreSQL tables. This command is efficient and can handle large volumes of data. Use the command in a SQL session like this:
```sql
COPY target_table (column1, column2, ...)
FROM '/path/to/datafile.csv'
WITH (FORMAT csv, HEADER true);
```
Adjust the file path and format options according to your data file’s specifics.

After importing the data, verify its integrity by running SQL queries to compare the row counts and key data points between the original Tempo export and the PostgreSQL tables. This step ensures that all data was transferred correctly and completely.

If you need to perform this data transfer regularly, consider automating the process using scripts. You can write shell scripts or use cron jobs to automate data export from Tempo, data preparation, transfer, and import into PostgreSQL. Ensure you include error handling and logging to monitor the process effectively.

By following these steps, you can successfully migrate data from Tempo to a PostgreSQL database without relying on third-party connectors or integrations.