#
# Define hydrometeors and sensors.
#
sensors = [getattr(mcrf.sensors, n) for n in args.sensors]
#
# Add a priori providers.
#
observation_error = mcrf.liras.ObservationError(sensors,
forward_model_error=False,
scene=scene)
observation_error.noise_scaling["lcpr"] = 1
data_provider.add(ice.a_priori[0])
data_provider.add(ice.a_priori[1])
data_provider.add(snow.a_priori[0])
data_provider.add(snow.a_priori[1])
data_provider.add(rain.a_priori[0])
data_provider.add(rain.a_priori[1])
data_provider.add(cloud_water_a_priori)
data_provider.add(h2o_a_priori)
data_provider.add(observation_error)
data_provider.add(observations)
#
# Run the retrieval.
#
retrieval = CloudRetrieval(hydrometeors, sensors, data_provider)
else:
kwargs = {"ice_psd": ice.psd, "liquid_psd": rain.psd}
data_provider = ModelDataProvider(99, scene=scene.upper(), **kwargs)
#
# Define hydrometeors and sensors.
#
sensors = [lcpr]
#
# Add a priori providers.
#
observation_errors = mcrf.liras.ObservationError(sensors)
data_provider.add(ice.a_priori[0])
data_provider.add(ice.a_priori[1])
data_provider.add(snow.a_priori[0])
data_provider.add(snow.a_priori[1])
data_provider.add(rain.a_priori[0])
data_provider.add(rain.a_priori[1])
data_provider.add(observation_errors)
data_provider.add(observations)
#
# Run the retrieval.
#
retrieval = CloudRetrieval(hydrometeors, sensors, data_provider)
retrieval.setup()
snow_psd=snow.psd,
liquid_psd=liquid.psd,
scene=scene.upper())
#
# Define hydrometeors and sensors.
#
hydrometeors = [ice, rain]
sensors = [lcpr, mwi, ici]
#
# Add a priori providers.
#
data_provider.add(ice.a_priori[0])
data_provider.add(ice.a_priori[1])
data_provider.add(snow.a_priori[0])
data_provider.add(snow.a_priori[1])
data_provider.add(rain.a_priori[0])
data_provider.add(rain.a_priori[1])
data_provider.add(cloud_water_a_priori)
data_provider.add(rh_a_priori)
data_provider.add(mcrf.liras.ObservationError(sensors))
data_provider.add(observations)
#
# Define hydrometeors and sensors.
#
hydrometeors = [ice, rain]