Abstract
Based on the Backward Four-Dimensional Variational Data Assimilation (Backward-4DVar) system with the Advanced Regional Eta-coordinate Model (AREM), which is capable of assimilating radio occultation data, a heavy rainfall case study is performed using GPS radio occultation (GPS RO) data and routine GTS data on July 5, 2007. The case study results indicate that the use of radio occultation data after quality control can improve the quality of the analysis to be similar to that of the observations and, thus, have a positive effect when improving 24-hour rainfall forecasts. Batch tests for 119 days from May to August during the flood season in 2009 show that only the use of GPS RO data can make positive improvements in both 24-hour and 48-hour regional rainfall forecasts and obtain a better B score for 24-hour forecasts and better TS score for 48-hour forecasts. When using radio occultation refractivity data and conventional radiosonde data, the results indicate that radio occultation refractivity data can achieve a better performance for 48-hour forecasts of light rain and heavy rain.
Highlights
Wang and Zhao [9] proposed the concept of the 3D mapping variation method (3DVM) by placing the initial value of the assimilation at the end of the assimilation window. e use of mapping observations subtly avoids the use of an adjoint model; Wang et al [10] proposed a four-dimensional variational assimilation method to reduce dimensionality projections using historical sample fitting and dimensionality reduction projection techniques
Wang et al [11] combined the advantages of the 3DVM and DRP-4DVar, proposed a backward mapping four-dimensional variational assimilation method (Backward-4DVar, referred to as B-4DVar), and established the Advanced Regional Eta-coordinate Model (AREM) mode of the B-4DVar system. is method avoids tangent-linear and adjoint models and reduces the computational cost of the assimilation window, and because the initial value being generated at the end of the assimilation window, it can reduce the prediction error accumulation throughout the assimilation window, which plays an important role in short-term and nowcasting forecasts, is verified in the observational system experiments
To improve the effect of global positioning system (GPS) radio occultation (GPS RO) refractivity data assimilation and forecasting, this paper adopts a simple quality control scheme for refractivity data: (1) exclude observation data below 3 km with errors in O-B that are too high; (2) set a high vertical resolution due to the GPS RO refractivity data, while keeping the vertical level of the pattern relatively small; unnecessary observations between the two model levels should be eliminated to match the resolution of the model; (3) use standard deviation between the observation data and model simulations to get rid of the outlier data
Summary
Based on the Backward Four-Dimensional Variational Data Assimilation (Backward-4DVar) system with the Advanced Regional Eta-coordinate Model (AREM), which is capable of assimilating radio occultation data, a heavy rainfall case study is performed using GPS radio occultation (GPS RO) data and routine GTS data on July 5, 2007. e case study results indicate that the use of radio occultation data after quality control can improve the quality of the analysis to be similar to that of the observations and, have a positive effect when improving 24-hour rainfall forecasts. Based on the Backward Four-Dimensional Variational Data Assimilation (Backward-4DVar) system with the Advanced Regional Eta-coordinate Model (AREM), which is capable of assimilating radio occultation data, a heavy rainfall case study is performed using GPS radio occultation (GPS RO) data and routine GTS data on July 5, 2007. E case study results indicate that the use of radio occultation data after quality control can improve the quality of the analysis to be similar to that of the observations and, have a positive effect when improving 24-hour rainfall forecasts. Batch tests for 119 days from May to August during the flood season in 2009 show that only the use of GPS RO data can make positive improvements in both 24-hour and 48-hour regional rainfall forecasts and obtain a better B score for 24-hour forecasts and better TS score for 48-hour forecasts. When using radio occultation refractivity data and conventional radiosonde data, the results indicate that radio occultation refractivity data can achieve a better performance for 48-hour forecasts of light rain and heavy rain
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
