cloud_slice_ut_no2

Cloud-slicing steps applied to a cluster of data using as input the partial NO2 columns in molecules/m2 and cloud top heights in hPa.

If successful, the output is NO2 mixing ratios in pptv. Other output is the estimated error on the NO2 mixing ratio and the mean cloud top pressure (hPa) for the cluster.

If the cloud-slicing step is unsuccessful, all values are NaN and a reason the cloud-slicing failed is provided.

Use as part of a Python script:

from uptrop.cloud_slice_ut_no2 import cldslice, CLOUD_SLICE_ERROR_ENUM
# Dummy functions
partial_columns = get_partial_cloud_columns()
cloud_top_heights = get_cloud_top_heights()

ratio, ratio_error, exception_number, mean_cloud_error = cldslice(partial_columns, cloud_top_heights)
if exception_number != 0:
    print(CLOUD_SLICE_ERROR_ENUM[exception_number])
print("Cloud ratio: {}".format(ratio))
print("Cloud ratio error: {}".format(ratio_error))
print("Mean cloud error: {}".format(mean_cloud_error))

uptrop.cloud_slice_ut_no2.cldslice(pcolno2, cldtophgt)

Compute upper troposphere NO2 using partial columns above cloudy scenes.

Determine NO2 mixing ratio by regressing NO2 partial columns against cloud-top heights over cloudy scenes.

Parameters

• pcolno2 (list of floats) – vectors of partial columns in molec/m2

• cldtophgt (list of floats) – corresponding cloud top heights in hPa.

Returns

NO2 volumetric mixing ratio, corresponding estimated error on the cloud-sliced NO2 value, a number to identify which filtering criteria led to loss of data in the case that the cloud-sliced NO2 value ia nan, and the mean cloud pressure of data retained after 10th and 90th percentile filtering.

Return type

tuple