Hello,
I am trying to retrieve daily total_precipitation from ERA5-Land, where each day is based on UTC-06:00.
I understand that ERA5-Land hourly total_precipitation values are cumulative from the start of the day. However, I would like to know if the cumulation adjusts based on time zone?
Suppose I use the daily statistics tool and set the parameters to:
- Dataset: ERA5-Land hourly data from 1981 to 2021
- Product type: Reanalysis
- Variable: Total precipitation
- Pressure level (hPa): -
- Statistic: Daily maximum
- Year: 2006
- Month: January
- Time zone: UTC-07:00
- Frequency: 1-hourly
- Grid (DD): 0.1/0.1
- Geographical area: N 90, W -180, S -90, E 180
My reasoning for using "Daily maximum" as the statistic is that ERA5-Land values are cumulative, so the maximum value is equal to the sum of hourly values if the hourly values did not include previous hours in the day (as in ERA5 not Land data), and assuming that the hourly values are adjusted to accumulate over the course of the day defined in a time zone that is not UTC+00:00. My reasoning for using "UTC-07:00" as the time zone is that (1) I would like to get daily values when each day is defined by UTC-06:00, and (2) the daily maximum occurs for day D at time 00:00 of day D+1 (hence the one hour time shift).
However, this request would not get me the correct numbers if the hourly values accumulate only according to a day as defined by UTC+00:00. If the cumulation does not also adjust to the time zone, there can be two alternative maxima each day, and neither would necessarily correspond to the true daily total_precipitation for a day in UTC-06:00.
Precisely what would the above example request return? Does cumulation adjust based on time zone? If not, then would my next best option (getting daily total_precipitation in UTC+00:00) be to change the time zone parameter to "UTC-01:00" (still accounting for the one-our time shift)? Would it possible to get ERA5-Land daily total precipitation in a different time zone, possibly through some other tool?
Any answers much appreciated,
Jessica Li
