We show how collocations between the Microwave Humidity Sounder (MHS) onboard NOAA-18 and the Cloud Profiling Radar (CPR) onboard the CloudSat CPR can be located
and how they can be used.
Frequent collocations between the two sensors exist.
We describe three applications.
Firstly, we use the collocations to validate an operational Ice Water Path (IWP) product from MHS measurements, produced by the National Environment Satellite, Data and Information System (NESDIS) in the Microwave Surface and Precipitation Products System (MSPPS). IWP values from the CloudSat CPR are found to be significantly larger than
those from the MSPPS, probably because thin clouds are transparent to microwave radiation.
Secondly, we look at the statistics of the relation between CPR IWP and MHS channel 5 brightness temperature.
We study these statistics in two datasets: the collocated dataset, and a dataset consisting of simulated radiances,
obtained with generated atmospheres input to the Atmospheric Radiative Transfer Simulator.
We find that the variability in the measurements is larger than the variability in the simulated radiances.
Finally, we use the collocations to train an Artificial Neural Network. The article describes how such a neural network can be used to develop a new
IWP product from microwave radiances.
We also study the effect of adding infrared measurements from the High
Resolution Infrared Radiation Sounder (HIRS), channels 8 and 11.
This should improve the retrieval quality, because thin clouds are transparent to microwave radiation but visible in the infrared. In reality, we find only a small improvement.
The reason for this is still under investigation.
The work is described in more detail
in the Master's Thesis by first author Gerrit Holl.