TY - GEN
T1 - Performance analysis of GPS Radio Occultation assimilation for tropical cyclone monitoring
AU - Phunthirawuthi, Parwapath
AU - Wu, Falin
AU - Boonyuen, Pakornpop
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/1
Y1 - 2016/11/1
N2 - This research investigated the impact of Radio Occultation (RO) data assimilation on cyclone monitoring. The global positioning system (GPS) radio occultation limb sounding technique has appeared as an efficient global observing system. This technique cans provide good performance in all weather conditions and without calibration requirement. GPS RO data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) were used for assimilation into the Weather Research and Forecasting (WRF) model. The Typhoon Melor event, which happened during 10 - 17 December 2015, is used as a case study. The experiments are designed in two sets, one is weather forecasting without data assimilation and another one is with RO data assimilation. For both experiments, Global Forecast System (GFS) data were used as initial data for forecasting on WRF model and results were compared with Final analysis (FNL) data from NCEP. This research demonstrated that weather prediction with RO data assimilation could provide positive results in terms of pressure and accumulated precipitation prediction. Moreover, RO data assimilation could provide even better performance, on tropical cyclone monitoring, with the more occultation profiles.
AB - This research investigated the impact of Radio Occultation (RO) data assimilation on cyclone monitoring. The global positioning system (GPS) radio occultation limb sounding technique has appeared as an efficient global observing system. This technique cans provide good performance in all weather conditions and without calibration requirement. GPS RO data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) were used for assimilation into the Weather Research and Forecasting (WRF) model. The Typhoon Melor event, which happened during 10 - 17 December 2015, is used as a case study. The experiments are designed in two sets, one is weather forecasting without data assimilation and another one is with RO data assimilation. For both experiments, Global Forecast System (GFS) data were used as initial data for forecasting on WRF model and results were compared with Final analysis (FNL) data from NCEP. This research demonstrated that weather prediction with RO data assimilation could provide positive results in terms of pressure and accumulated precipitation prediction. Moreover, RO data assimilation could provide even better performance, on tropical cyclone monitoring, with the more occultation profiles.
KW - 3DVAR
KW - Data assimilation
KW - GPS
KW - Radio Occultation
KW - Weather Research and Forecasting (WRF)
UR - https://www.scopus.com/pages/publications/85007507428
U2 - 10.1109/IGARSS.2016.7729563
DO - 10.1109/IGARSS.2016.7729563
M3 - 会议稿件
AN - SCOPUS:85007507428
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2181
EP - 2184
BT - 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Y2 - 10 July 2016 through 15 July 2016
ER -