Data assimilation of Mt. Fuji observed GPS down-looking occultation data into the JMA mesoscale numerical weather prediction model

2004 ◽  
Author(s):  
Yoshinori Shoji ◽  
Takuya Kawabata ◽  
Yuichi Aoyama ◽  
Hiromu Seko ◽  
Toshitaka Tsuda ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Prediction Model ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Numerical Weather ◽  
Occultation Data ◽  
Mesoscale Numerical Weather Prediction

scholarly journals On the Effect of Model Parameters on Forecast Objects

2017 ◽  
Author(s):  
Caren Marzban ◽  
Corinne Jones ◽  
Ning Li ◽  
Scott Sandgathe
Keyword(s):  
Prediction Model ◽  
Numerical Weather Prediction ◽  
Numerical Models ◽  
Weather Prediction ◽  
Clustering Algorithms ◽  
Numerical Weather Prediction Model ◽  
Model Parameters ◽  
Numerical Weather ◽  
The Impact ◽  
Mesoscale Numerical Weather Prediction

Abstract. Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature "map". However, the field for some quantities such as precipitation generally consists of spatially coherent and disconnected "objects". Certain features of these objects (e.g., number, size, and intensity) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on features of forecast objects. Although, in principle, the objects can be defined by any means, here they are identified via clustering algorithms. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

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