The mesoscale numerical model WRF is used to simulate the No. 8 hurricane Matthew in 2016. The radar and radiometer observations are assimilated by WRF Var. With the verification to the real situation, the process of the hurricane rainstorm is well simulated by WRF in this case that it could basically show the hurricane evolution. We use the simulation results which are model outputs with high spatial and temporal resolution to do diagnostic analysis on the short term heavy rainstorm caused by Matthew, with a comparison between the best track and forecasting tracks using active and passive microwave observations from WRFDA model. In order to analyze the inner structure, the nadiral satellite-based observations were matched between the Microwave Humidity and Temperature Sounder (MWHTS) instrument aboard the FY-3C polar-orbiting platform since Sept 30, 2013 and dual-frequency radar named PR aboard GPM satellite and then separate retrievals are demonstrated in data assimilation for extreme weather with the retrieved root-mean-square errors of about 0.9 K and 17% and 10 mm/h for precipitation products, which demonstrates the impact of 118 GHz observations in data assimilation model.
References
[1]
Petty, G.W. (1994) Physical Retrievals of Over-Ocean Rain Rate from Multichannel Microwave Imagery. Part I: Theoretical Characteristics of Normalized Polarization and Scattering Indices. Meteorology & Atmospheric Physics, 54, 79-99. https://doi.org/10.1007/BF01030053
[2]
Draper, D.W., Newell, D.A., Wentz, F.J. and Skofronick-Jackson, G.M. (2015) The Global Precipitation Measurement (GPM) Microwave Imager (GMI): Instrument Overview and Early On-Orbit Performance. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 8, 3452-3462. https://doi.org/10.1109/JSTARS.2015.2403303
[3]
Blackwell, W.J. and Chen, F.W. (2009) Neural Networks in Atmospheric Remote Sensing. Artech House, Norwood, MA.
[4]
Tikhonov, A.N., Goncharsky, A.V., Stepanov, V.V. and Yagola, A.G. (2013) Numerical Methods for the Solution of Ill-Posed Problems. Springer Science and Business Media, Dordrecht, Netherlands.
[5]
Engeln, A.V., Nedoluha, G., Kirchengast, G. and Bühler, S. (2003) One-Dimensional Variational (1-D Var) Retrieval of Temperature, Water Vapor, and a Reference Pressure from Radio Occultation Measurements: A Sensitivity Analysis. Journal of Geophysical Research Atmospheres, 108, 4337. https://doi.org/10.1029/2002JD002908
[6]
He, J., Zhang, S. and Wang, Z. (2015) Advanced Microwave Atmospheric Sounder (AMAS) Channel Specifications and T/V Calibration Results on FY-3C Satellite. IEEE Transactions on Geoscience & Remote Sensing, 53, 481-493. https://doi.org/10.1109/TGRS.2014.2324173
[7]
Zhang, S.W., Li, J. and Wang. Z.Z. (2012) Design of the Second Generation Microwave Humidity Sounder (MWHS-II) for Chinese Meteorological Satellite FY-3. 2012 IEEE International Geosciences and Remote Sensing Symposium (IGARSS 2012), Munich, Germany, 22-27 July 2012, 4672-4675.
[8]
He, J. and Zhang, S. (2015) Research on Global Profiles and Precipitation Retrievals for FY-3C MWHTS. 2015 IEEE International Geosciences and Remote Sensing Symposium (IGARSS 2015), Milan, Italy, 26-31 July 2015, 4890-4893.
[9]
He, J.Y., Zhang, S.W. and WANG, Z.Z. (2012) The Retrievals and Analysis of Water Vapor Density in Arctic Regions Using FY-3A Satellite MWHS. Radio Science, 47, 301-311.
[10]
He, J.Y. and Zhang, S.W. (2012) Humidity Retrievals in Mid-Latitude and Tropical Regions Using FY-3 MWHS. Journal of Remote Sensing, 3, 581-597.
[11]
Yang, Z.D., Lu, N.M. and Shi, J. (2013) Overview of FY-3 Payload and Ground Application System. IEEE Transactions on Geoscience and Remote Sensing, 12, 4846-4853.
[12]
Surussavadee, C. and Staelin, D.H. (2008) Global Millimeter-Wave Precipitation Retrievals Trained with a Cloud-Resolving Numerical Weather Prediction Model, Part I: Retrieval Design. IEEE Transactions on Geoscience and Remote Sensing, 46, 99-108. https://doi.org/10.1109/TGRS.2007.908302
[13]
Rodgers, C.D. (2000) Inverse Methods for Atmospheric Sounding. World Scientific Publishing, New York. https://doi.org/10.1142/3171
[14]
Surussavadee, C. and Staelin, D.H. (2008) Global Millimeter-Wave Precipitation Retrievals Trained with a Cloud-Resolving Numerical Weather-Prediction Model, Part II: Performance Evaluation. IEEE Transactions on Geoscience and Remote Sensing, 46, 109-118. https://doi.org/10.1109/TGRS.2007.908299
[15]
He, J., Wang, Z. and Zhang, S. (2016) T/V Calibration for Microwave Humidity and Temperature Sounder onboard Chinese FY-3D Satellite. 2016 Progress in Electromagnetic Research Symposium (PIERS), Shanghai, 8-11 August 2016, 510-514.
[16]
Blackwell, W.J. (2005) A Neural-Network Technique for the Retrieval of Atmospheric Temperature and Moisture Profiles from High Spectral Resolution Sounding Data. IEEE Transactions on Geoscience and Remote Sensing, 43, 2535-2546. https://doi.org/10.1109/TGRS.2005.855071