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Can Lagrangian Extrapolation of Radar Fields Be Used for Precipitation Nowcasting over Complex Alpine Orography?
被引:57
|作者:
Mandapaka, Pradeep V.
[1
]
Germann, Urs
[1
]
Panziera, Luca
[1
]
Hering, Alessandro
[1
]
机构:
[1] MeteoSwiss, Locarno, Switzerland
关键词:
WEATHER PREDICTION MODELS;
NEIGHBORHOOD VERIFICATION;
SCALE-DEPENDENCE;
MCGILL ALGORITHM;
PART II;
FORECASTS;
PREDICTABILITY;
IMAGES;
FLOW;
EQUITABILITY;
D O I:
10.1175/WAF-D-11-00050.1
中图分类号:
P4 [大气科学(气象学)];
学科分类号:
0706 ;
070601 ;
摘要:
In this study, a Lagrangian radar echo extrapolation scheme (MAPLE) was tested for use in very short-term forecasting of precipitation over a complex orographic region. The high-resolution forecasts from MAPLE for lead times of 5 min-5 h are evaluated against the radar observations for 20 summer rainfall events by employing a series of categorical, continuous, and neighborhood evaluation techniques. The verification results are then compared with those from Eulerian persistence and high-resolution numerical weather prediction model [the Consortium for Small-scale Modeling model (COSMO2)] forecasts. The forecasts from the MAPLE model clearly outperformed Eulerian persistence forecasts for all the lead times, and had better skill compared to COSMO2 up to lead time of 3 h on average. The results also showed that the predictability achieved from the MAPLE model depends on the spatial structure of the precipitation patterns. This study is a first implementation of the MAPLE model over a complex Alpine region. In addition to comprehensive evaluation of precipitation forecast products, some open questions related to the nowcasting of rainfall over a complex terrain are discussed.
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页码:28 / 49
页数:22
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