JDR Vol.12 No.5 pp. 944-955
doi: 10.20965/jdr.2017.p0944


Assimilation Impact of Different GPS Analysis Methods on Precipitation Forecast: A Heavy Rainfall Case Study of Kani City, Gifu Prefecture on July 15, 2010

Shingo Shimizu*,†, Seiichi Shimada**, and Kazuhisa Tsuboki***

*National Research Institute for Earth Science and Disaster Resilience (NIED)
3-1 Tennodai, Tsukuba City, Ibaraki, Japan

Corresponding author

**Graduate School of Frontier Sciences, the University of Tokyo, Tokyo, Japan

***Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, Japan

April 3, 2017
September 7, 2017
Online released:
September 27, 2017
October 1, 2017
GPS precipitable water, data assimilation, precipitation forecast

In this study, we examined variations in predicted precipitable water produced from different Global Positioning System (GPS) zenith delay methods, and assessed the corresponding difference in predicted rainfall after assimilating the obtained precipitable water data. Precipitable water data estimated from the GPS and three-dimensional horizontal wind velocity field derived from the X-band dual polarimetric radar were assimilated in CReSS and rainfall forecast experiments were conducted for the heavy rainfall system in Kani City, Gifu Prefecture on July 15, 2010. In the GPS analysis, a method to simultaneously estimate coordinates and zenith delay, i.e., the simultaneous estimation method, and a method to successively estimate coordinates and zenith delay, i.e., the successive estimation method, were used to estimate precipitable water. The differences generated from using predicted orbit data provided in pseudo-real time from the International GNSS (Global Navigation Satellite System) Service for geodynamics (IGS) versus precise orbit data released after a 10-day delay were examined. The change in precipitable water due to varying the analysis methods was larger than that due to the type of satellite orbit information. In the rainfall forecast experiments, those using the successive estimation method results had a better precision than those using the simultaneous estimation method results. Both methods that included data assimilation had higher rainfall forecast precisions than the forecast precision without precipitable water assimilation. Water vapor obtained from GPS analysis is accepted as important in rainfall forecasting, but the present study showed additional improvements can be attained from incorporating a zenith delay analysis method.

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Last updated on Oct. 20, 2017