SQL - Update a table using LAG and based on another column

I have a dashboard with python and dash/plotly that receives inputs from the user and then run a query on Google BigQuery.

One of the queries updates a column (PAY_FT), uses other column (PAY_CLEAN) and a string input from the dashboard.

    DECLARE cpi STRING DEFAULT "C";
    UPDATE `xx.yy.zz` t
    SET
    PAY_FT = s.PAY_FT
    FROM
    (
    SELECT
        RN,
        CASE
        WHEN RN = 1 AND cpi = "S" AND PAY_SHALE_COR = "PAY" THEN 1
        WHEN RN = 1 AND cpi = "C" AND PAY_CLEAN = "PAY" THEN 1
        WHEN RN = 1 THEN 0
        WHEN RN > 1 AND cpi = "S" AND PAY_SHALE_COR = "PAY" THEN 0.2 + (LAG(PAY_FT, 1) OVER(ORDER BY RN))
        WHEN RN > 1 AND cpi = "C" AND PAY_CLEAN = "PAY" THEN 0.2 + (LAG(PAY_FT, 1) OVER(ORDER BY RN))
        ELSE (LAG(PAY_FT, 1) OVER(ORDER BY RN))
        END
        AS PAY_FT
    FROM
        `xx.yy.zz`
    WHERE
        DEPTH_M IS NOT NULL
    )
    s
    WHERE
    t.RN = s.RN

But it's not working as intended. This query returns the following:

It works until DEPTH_M = 102.2, but after that it dows not return the 0.4 from the previous row. So, for example, if we had a "PAY" in DEPTH_M = 103.2, until 103.0 should return 0.4 and in 103.2 it should be 0.6.

How can I fix it?

Here's a sample of my data: SAMPLE.csv

My desired outpu should be:

Let's say that we got another PAY on another row, the output should be:

Thanks in advance.