A new microwave humidity sounder （MWHS） developed and built by CSSAR was deployed in China in May

2008. The sounder is part of a suit of instruments onboard FY-3 satellite

which measures brightness temperatures from 3 double-sideband channels centered at （183.31±1）GHz

（183.31± 3）GHz and （183.31±7）GHz. Atmospheric emission in these regions is primarily due to water vapor and influences of liquid water. Measurements were compared with simulations obtained using forward radiative transfer equation. The comparison of brightness temperatures showed that the measurements agreed well with model simulations. Humidity profiles were retrieved using back propagation neural network （BP-NN） algorithm and other methods. The results show that humidity profiles derived using back propagation algorithm best agreed with the profiles from radiosonde datasets. Second

compared to the humidity retrievals by AMSU-B retrieval model

root-mean-square （RMS） of relative humidity was comparable with those of AMSU-B in a range of 15% to 25%

and RMS of water vapor density was smaller than 1 g/m 3 . Therefore

it can be used for retrieving atmospheric humidity profiles for operational applications. Meanwhile

the paper firstly uses Mexican hat wavelet function into BP-NN

and the results show that it is comparable with BP-NN. Most importantly

Mexican hat wavelet function can reach convergence quickly and avoid of easily getting stuck in local minima.