期刊
ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES
卷 46, 期 3, 页码 369-381出版社
KOREAN METEOROLOGICAL SOC
DOI: 10.1007/s13143-010-1008-x
关键词
MAPLE; VET algorithm; Korean radar network
资金
- National Institute of Meteorological Research of South Korea [NIMR-2009-C-1]
- Korea Meteorological Administration [NIMR-2009-C-1] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
A Variational Echo Tracking (VET) technique has been applied to four months of archived data from the South Korean radar network in order to examine the influence of the various user-selectable parameters on the skill of the resulting 20-min to 4-h nowcasts. The latter are computed over a (512 x 512) array at 2-km resolution. After correcting the original algorithm to take into account the motion of precipitation across the boundaries of such a smaller radar network, we concluded that the set of default input parameters initially assumed is very close to the optimum combination. Decreasing to (5 sx 5) or increasing to (50 x 50) the default vector density of (25 x 25), using two or three maps for velocity determination, varying the relative weights for the constraints of conservation of reflectivity and of the smoothing of the velocity vectors, and finally the application of temporal smoothing all had only marginal effects on the skill of the forecasts. The relatively small sensitivity to significant variations of the VET default parameters is a direct consequence of the fact that the major source of the loss in forecast skill cannot be attributed to errors in the forecast motion, but to the unpredictable nature of the storm growth and decay. Changing the time interval between maps, from 20 to 10 minutes, and significantly increasing the reflectivity threshold from 15 to 30 dBZ had a more noticeable reduction on the forecast skill. Comparisons with the Eulerian zero velocity forecast and with a single vector forecast have also been performed in order to determine the accrued skill of the VET algorithm. Because of the extensive stratiform nature of the precipitation areas affecting the Korean peninsula, the increased skill is not as large as may have been anticipated. This can be explained by the greater extent of the precipitation systems relative to the size of the radar coverage domain.
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