scholarly journals A Multigrid Nonlinear Least Squares Four-Dimensional Variational Data Assimilation Scheme With the Advanced Research Weather Research and Forecasting Model

2018 ◽  
Vol 123 (10) ◽  
pp. 5116-5129 ◽  
Author(s):  
Hongqin Zhang ◽  
Xiangjun Tian
Keyword(s):  
Data Assimilation ◽  
Least Squares ◽  
Nonlinear Least Squares ◽  
Variational Data Assimilation ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Data Assimilation Scheme ◽  
Assimilation Scheme ◽  
Weather Research

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.

scholarly journals Optimization of the WRFV3.7 adjoint model

2018 ◽  
Author(s):  
Qiang Cheng ◽  
Juanjuan Liu ◽  
Bin Wang
Keyword(s):  
Data Assimilation ◽  
Variational Data Assimilation ◽  
Weather Research And Forecasting ◽  
Time Cost ◽  
Input Output ◽  
Adjoint Model ◽  
New Strategy ◽  
Weather Research

Abstract. This work focused on a new strategy for productively improving the performance of adjoint models. By using several techniques including the push/pop-free method, careful Input/Output (IO) analysis and the use of the conception of adjoint locality, we reduced the adjoint cost of the Weather Research and Forecasting plus (WRFPLUS) by almost half on different numbers of processors especially with a slight decrease in total memory. Several experiments are conducted using the four-dimensional variational data assimilation (4DVar) method. The results show that the total time cost of running a 4DVar application is decreased by approximately 1/3.

The Met. Office global three-dimensional variational data assimilation scheme

2000 ◽  
Vol 126 (570) ◽  
pp. 2991-3012 ◽  
Author(s):  
A. C. Lorenc ◽  
S. P. Ballard ◽  
R. S. Bell ◽  
N. B. Ingleby ◽  
P. L. F. Andrews ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Three Dimensional ◽  
Variational Data Assimilation ◽  
Data Assimilation Scheme ◽  
Assimilation Scheme

A Parallel Three-dimensional Variational Data Assimilation Scheme

2011 ◽  
Author(s):  
L. D’Amore ◽  
R. Arcucci ◽  
L. Marcellino ◽  
A. Murli ◽  
Theodore E. Simos ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Three Dimensional ◽  
Variational Data Assimilation ◽  
Data Assimilation Scheme ◽  
Assimilation Scheme
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