Visualizing Model Data Using a Fast Approximation of a Radiative Transfer Model

被引:4
|
作者
Lakshmanan, Valliappa [1 ,2 ]
Rabin, Robert [1 ]
Otkin, Jason [3 ]
Kain, John S. [1 ]
Dembek, Scott [1 ,2 ]
机构
[1] NOAA, Natl Severe Storms Lab, Norman, OK 73069 USA
[2] Univ Oklahoma, Cooperat Inst Mesoscale Meteorol Studies, Norman, OK 73019 USA
[3] Univ Wisconsin, Ctr Space Sci & Engn, Madison, WI 53706 USA
关键词
QUALITY-CONTROL; NEURAL-NETWORK; CLOUD COVER; RESOLUTION; PREDICTION; PARAMETERIZATION; ASSIMILATION; VALIDATION; CONVECTION;
D O I
10.1175/JTECH-D-11-00007.1
中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Visualizing model forecasts using simulated satellite imagery has proven very useful because the depiction of forecasts using cloud imagery can provide inferences about meteorological scenarios and physical processes that are not characterized well by depictions of those forecasts using radar reflectivity. A forward radiative transfer model is capable of providing such a visible-channel depiction of numerical weather prediction model output, but present-day forward models are too slow to run routinely on operational model forecasts. It is demonstrated that it is possible to approximate the radiative transfer model using a universal approximator whose parameters can be determined by fitting the output of the forward model to inputs derived from the raw output from the prediction model. The resulting approximation is very close to the result derived from the complex radiative transfer model and has the advantage that it can be computed in a small fraction of the time required by the forward model. This approximation is carried out on model forecasts to demonstrate its utility as a visualization and forecasting tool.
引用
收藏
页码:745 / 754
页数:10
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