Occasionally there are jumps in the timeseries:
The cause are missing data in ERA.5 file:
Removing inputs/ERA.5 and rerunning using --start correct_troposphere (or similar) solved the problem. Why it occurred in the first place is unclear.
This can be addressed using:
gdalinfo -stats mintpy/inputs/ERA5.h5
which shows
Band 408 Block=93x65 Type=Float32, ColorInterp=Undefined
Minimum=-3.689, Maximum=-1.860, Mean=-2.710, StdDev=0.390
Metadata:
STATISTICS_MAXIMUM=-1.8602414131165
STATISTICS_MEAN=-2.7097257666363
STATISTICS_MINIMUM=-3.6885530948639
STATISTICS_STDDEV=0.38980825591908
STATISTICS_VALID_PERCENT=100
Band 409 Block=93x65 Type=Float32, ColorInterp=Undefined
Minimum=0.000, Maximum=0.000, Mean=0.000, StdDev=0.000
Metadata:
STATISTICS_MAXIMUM=0
STATISTICS_MEAN=0
STATISTICS_MINIMUM=0
STATISTICS_STDDEV=0
STATISTICS_VALID_PERCENT=100
for good and bad data.
Try:
/data/HDF5EOS[535] gdalinfo -stats q1NorthChilesSenD142/mintpy_2014_2026/inputs/ERA5.h5
Occasionally there are jumps in the timeseries:
The cause are missing data in ERA.5 file:
Removing inputs/ERA.5 and rerunning using --start correct_troposphere (or similar) solved the problem. Why it occurred in the first place is unclear.
This can be addressed using:
which shows
for good and bad data.
Try: