Click here
to download this notebook.
Crossovers Nadir
[2]:
from casys.readers import CLSTableReader
from casys import CasysPlot, DateHandler, Field, NadirData
NadirData.enable_loginfo()
Dataset definition
[3]:
# Reader definition
table_name = "TABLE_C_J3_B_GDRD"
orf_name = "C_J3_GDRD"
cycle_number = 122
start = DateHandler.from_orf(orf_name, cycle_number, 1, pos="first")
end = DateHandler.from_orf(orf_name, cycle_number, 154, pos="last")
reader = CLSTableReader(
name=table_name,
date_start=start,
date_end=end,
orf=orf_name,
time="time",
longitude="LONGITUDE",
latitude="LATITUDE",
)
# Data container definition
ad = NadirData(source=reader)
var_sla = Field(
name="sla",
source="ORBIT.ALTI - RANGE.ALTI - MEAN_SEA_SURFACE.MODEL.CNESCLS15",
unit="m",
)
Definition of the statistic
Using the add_crossover_stat method:
[4]:
ad.add_crossover_stat(
name="Crossover SLA",
field=var_sla,
max_time_difference="5 days",
stats=["mean", "count"],
temporal_stats_freq=["cycle", "day"],
)
ad.compute()
2025-05-14 10:57:57 INFO Reading ['LONGITUDE', 'LATITUDE', 'sla', 'time']
2025-05-14 10:57:59 INFO Computing diagnostics ['Crossover SLA']
2025-05-14 10:58:00 INFO Computing done.
Compute
[5]:
ad.compute()
2025-05-14 10:58:00 INFO Computing done.
Plot
Graphical display of crossovers
Display daily mean statistic on a graphic:
[6]:
sla_cross_mean_plot = CasysPlot(
data=ad, data_name="Crossover SLA", freq="day", stat="mean"
)
sla_cross_mean_plot.show()
[6]:

Map crossovers upon time
[7]:
cross_delta_plot = CasysPlot(data=ad, data_name="Crossover SLA", delta="time")
cross_delta_plot.show()
[7]:

Map crossovers upon field
[8]:
cross_delta_plot = CasysPlot(data=ad, data_name="Crossover SLA", delta="field")
cross_delta_plot.show()
[8]:

To learn more about crossovers definition, please visit this documentation page.