Test of a non-local excess phase delay operator for GPS radio occultation data assimilation

2009 ◽  
Vol 3 (1) ◽  
pp. 033508 ◽  
Author(s):  
Hui Shao
Keyword(s):  
Data Assimilation ◽  
Radio Occultation ◽  
Phase Delay ◽  
Gps Radio Occultation ◽  
Non Local ◽  
Excess Phase ◽  
Occultation Data ◽  
Delay Operator ◽  
Radio Occultation Data

scholarly journals GPS Radio Occultation Data Assimilation in the AREM Regional Numerical Weather Prediction Model for Flood Forecasts

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Wei Cheng ◽  
Youping Xu ◽  
Zhiwu Deng ◽  
Chunli Gu
Keyword(s):  
Data Assimilation ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Radiosonde Data ◽  
Light Rain ◽  
Gps Radio Occultation ◽  
Study Results ◽  
Occultation Data ◽  
Radio Occultation Data

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.

Impact of GPS radio occultation data assimilation on regional weather predictions

GPS Solutions ◽  
2009 ◽  
Vol 14 (1) ◽  
pp. 35-49 ◽  
Author(s):  
Ching-Yuang Huang ◽  
Ying-Hwa Kuo ◽  
Shu-Ya Chen ◽  
Chuen-Tsyr Terng ◽  
Fang-Ching Chien ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Radio Occultation ◽  
Gps Radio Occultation ◽  
Occultation Data ◽  
Radio Occultation Data

Parallelization Strategies for the GPS Radio Occultation Data Assimilation with a Nonlocal Operator in the Weather Research and Forecasting Model

2014 ◽  
Vol 31 (9) ◽  
pp. 2008-2014 ◽  
Author(s):  
Xin Zhang ◽  
Ying-Hwa Kuo ◽  
Shu-Ya Chen ◽  
Xiang-Yu Huang ◽  
Ling-Feng Hsiao
Keyword(s):  
Data Assimilation ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Observation Operator ◽  
Gps Radio Occultation ◽  
Phase Observation ◽  
Excess Phase ◽  
Weather Research

Abstract The nonlocal excess phase observation operator for assimilating the global positioning system (GPS) radio occultation (RO) sounding data has been proven by some research papers to produce significantly better analyses for numerical weather prediction (NWP) compared to the local refractivity observation operator. However, the high computational cost and the difficulties in parallelization associated with the nonlocal GPS RO operator deter its application in research and operational NWP practices. In this article, two strategies are designed and implemented in the data assimilation system for the Weather Research and Forecasting Model to demonstrate the capability of parallel assimilation of GPS RO profiles with the nonlocal excess phase observation operator. In particular, to solve the parallel load imbalance problem due to the uneven geographic distribution of the GPS RO observations, round-robin scheduling is adopted to distribute GPS RO observations among the processing cores to balance the workload. The wall clock time required to complete a five-iteration minimization on a demonstration Antarctic case with 106 GPS RO observations is reduced from more than 3.5 h with a single processing core to 2.5 min with 106 processing cores. These strategies present the possibility of application of the nonlocal GPS RO excess phase observation operator in operational data assimilation systems with a cutoff time limit.

Backpropagation Processing of GPS Radio Occultation Data

2003 ◽  
pp. 415-422 ◽  
Author(s):  
Chi O. Ao ◽  
George A. Hajj ◽  
Thomas K. Meehan ◽  
Stephen S. Leroy ◽  
E. Robert Kursinski ◽  
...  
Keyword(s):  
Radio Occultation ◽  
Gps Radio Occultation ◽  
Occultation Data ◽  
Radio Occultation Data

Evaluation of a Linear Phase Observation Operator with CHAMP Radio Occultation Data and High-Resolution Regional Analysis

2005 ◽  
Vol 133 (10) ◽  
pp. 3053-3059 ◽  
Author(s):  
S. Sokolovskiy ◽  
Y-H. Kuo ◽  
W. Wang
Keyword(s):  
High Resolution ◽  
Radio Occultation ◽  
Regional Analysis ◽  
Observation Error ◽  
Computationally Efficient ◽  
Observation Operator ◽  
Simple Implementation ◽  
Excess Phase ◽  
Occultation Data ◽  
Radio Occultation Data

Abstract In this study a nonlocal, linear observation operator for assimilating radio occultation data is evaluated. The operator consists of modeling the excess phase, that is, integrating the refractivity along straight lines tangent to rays, below a certain height. The corresponding observable is the excess phase integrated through the Abel-retrieved refractivity, along the same lines, below the same height. The operator allows very simple implementation (computationally efficient) while accurately accounting for the horizontal refractivity gradients. This is due to significant cancellation of the linearization and discretization errors when modeling the observable. Evaluation of the operator with Challenging Minisatellite Payload (CHAMP) radio occultation data and grid refractivity fields from high-resolution regional analysis over the continental United States showed reduction of the observation error in the troposphere (below 7 km) 1.5–2 times, compared to the error of local refractivity. The operator is useful for the assimilation of radio occultation data by high-resolution weather models in the troposphere.

Sign in / Sign up

Export Citation Format

Share Document