多普勒天氣雷達(dá)下?lián)舯┝鲌D像識(shí)別
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公益性氣象行業(yè)科研專項(xiàng)(GYHY201306008)和湖北省氣象局科技發(fā)展基金項(xiàng)目(2015Q04)共同資助


Identification of Downbursts Based on WSR88D Doppler Weather Radar Images
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    摘要:

    以下?lián)舯┝骶哂械牡蛯语@著輻散特征為基礎(chǔ),引入圖像識(shí)別中的連通區(qū)識(shí)別技術(shù),開發(fā)出了應(yīng)用于多普勒天氣雷達(dá)的下?lián)舯┝鲌D像識(shí)別算法。首先通過設(shè)置的速度閾值將徑向速度進(jìn)行二值化處理,然后運(yùn)用8鄰域法尋找速度大值區(qū),并采用距離、夾角和正、負(fù)速度差值等條件進(jìn)行約束對(duì)正、負(fù)速度大值區(qū)進(jìn)行配對(duì),最后對(duì)未成功配對(duì)的速度大值區(qū)進(jìn)行鄰近區(qū)域的二次匹配,從而識(shí)別出下?lián)舯┝鲄^(qū)域。利用多個(gè)下?lián)舯┝鱾€(gè)例實(shí)測(cè)的多普勒雷達(dá)數(shù)據(jù)對(duì)該算法進(jìn)行了測(cè)試,結(jié)果表明該算法對(duì)一些較小尺度的下?lián)舯┝鳎绕鋵?duì)受環(huán)境風(fēng)場(chǎng)影響而具有不對(duì)稱輻散特征的下?lián)舯┝饔辛己玫淖R(shí)別效果。

    Abstract:

    According to the significant lowlevel divergence characteristics in the flow field of a downburst and the identification technology of the connected area in pattern recognition, an identification algorithm of downbursts using Doppler radar data is developed. The binary processing of radial velocity is carried out by setting the threshold of speed. The 8neighborhood method is applied for searching big speed value zones, and the big positive and negative speed zones are matched by using constraints such as distance, angle, difference of positive and negative speeds, and so on. The secondary matching for the adjacent areas is conducted on big speed zones where matching failed, thus to identify the alert area of downbursts. Some real radar detection data are used to verify the algorithm. The results show that this algorithm can detect the small scale downburst with the clear lowlevel divergence characteristic, especially for the downburst with asymmetric divergence characteristics that affected by the environment wind field.

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杜牧云,肖艷嬌,吳濤.多普勒天氣雷達(dá)下?lián)舯┝鲌D像識(shí)別[J].氣象科技,2015,43(3):368~372

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  • 收稿日期:2014-06-25
  • 定稿日期:2014-09-16
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  • 在線發(fā)布日期: 2015-06-30
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