Data from a long term measurement of Micro Rain Radar （MRR） at a mountain site （Daegwallyeong, DG, one year period of 2005） and a coastal site （Haenam, HN, three years 2004-2006） in South Korea were analyzed to ...Data from a long term measurement of Micro Rain Radar （MRR） at a mountain site （Daegwallyeong, DG, one year period of 2005） and a coastal site （Haenam, HN, three years 2004-2006） in South Korea were analyzed to compare the MRR measured bright band characteristics of stratiform precipitation at the two sites. On average, the bright band was somewhat thicker and the sharpness （average gradient of reflectivity above and below the reflectivity peak） was slightly weaker at DG, compared to those values at HN. The peak reflectivity itself was twice as strong and the relative location of the peak reflectivity within the bright band was higher at HN than at DG. Importantly, the variability of these values was much larger at HN than at DG. The key parameter to cause these differences is suggested to be the difference of the snow particle densities at the two sites, which is related to the degree of riming. Therefore, it is speculated that the cloud microphysical processes at HN may have varied significantly from un-rimed snow growth, producing low density snow particles, to the riming of higher density particles, while snow particle growth at DG was more consistently affected by the riming process, and therefore high density snow particles. Forced uplifting of cloudy air over the mountain area around DG might have resulted in an orographic supercooling effect that led to the enhanced riming of supercooled cloud drops.展开更多
In this study, the vertical profiles of radar refractive factor(Z) observed with an X-band Doppler radar in Jurong on July 13, 2012 in different periods of a stratiform cloud precipitation process were simulated using...In this study, the vertical profiles of radar refractive factor(Z) observed with an X-band Doppler radar in Jurong on July 13, 2012 in different periods of a stratiform cloud precipitation process were simulated using the Sim RAD software, and the contributions of each impact resulting in the bright band were analyzed quantitatively. In the simulation, the parameters inputted into Sim RAD were updated until the output Z profile was nearly consistent with the observation. The input parameters were then deemed to reflect real conditions of the cloud and precipitation. The results showed that a wider(narrower) and brighter(darker) bright band corresponded to a larger(smaller) amount, wider(narrower) vertical distribution, and larger(smaller) mean diameter of melting particles in the melting layer. Besides this,radar reflectivity factors under the wider(narrower) melting layer were larger(smaller). This may be contributed to the adequate growth of larger rain drops in the upper melting layer. Sensitivity experiments of the generation of the radar bright band showed that a drastic increasing of the complex refractive index due to melting led to the largest impact,making the radar reflectivity factor increase by about 15 d BZ. Fragmentation of large particles was the second most important influence, making the value decrease by 10 d BZ. The collision-coalescence between melting particles, volumetric shrinking due to melting, and the falling speed of raindrops made the radar reflectivity factor change by about 3-7d BZ. Shape transformation from spheres to oblate ellipsoids resulted in only a slight increase in the radar reflectivity factors(about 0.2 d BZ), which might be due to the fact that there are few large particles in stratiform cloud.展开更多
The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of significant overestimation in quantitative precipitation estimation(QPE) based on the Z–R(reflectivi...The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of significant overestimation in quantitative precipitation estimation(QPE) based on the Z–R(reflectivity factor–rain rate) relationship.The effects of the bright band on radar-based QPE can be eliminated by vertical profile of reflectivity(VPR) correction. In this study, we applied bright-band correction algorithms to evaluate three different bands(S-, C-and X-band) of dual-polarized radars and to reduce overestimation errors in Z–R relationship–based QPEs. After the reflectivity was corrected by the algorithms using average VPR(AVPR) alone and a combination of average VPR and the vertical profile of the copolar correlation coefficient(AVPR+CC), the QPEs were derived. The bright-band correction and resulting QPEs were evaluated in eight precipitation events by comparing to the uncorrected reflectivity and rain-gauge observations, separately. The overestimation of Z–R relationship–based QPEs associated with the bright band was reduced after correction by the two schemes for which hourly rainfall was less than 5 mm. For the verification metrics of RMSE(root-mean-square error), RMAE(relative mean absolute error) and RMB(relative mean bias) of QPEs, averaged over all eight cases, the AVPR method improved from 2.28,0.94 and 0.78 to 1.55, 0.60 and 0.40, respectively, while the AVPR+CC method improved to 1.44, 0.55 and 0.30, respectively.The QPEs after AVPR+CC correction had less overestimation than those after AVPR correction, and similar conclusions were drawn for all three different bands of dual-polarized radars.展开更多
该文提出一种使用S波段多普勒天气雷达回波三维特征和反射率因子垂直廓线(vertical profile of reflectivity,VPR)来自动识别零度层亮带的方法(简称3DVPR-BBID),并利用2003年6月22日—7月11日和2007年7月合肥雷达资料、2008年6月广州雷...该文提出一种使用S波段多普勒天气雷达回波三维特征和反射率因子垂直廓线(vertical profile of reflectivity,VPR)来自动识别零度层亮带的方法(简称3DVPR-BBID),并利用2003年6月22日—7月11日和2007年7月合肥雷达资料、2008年6月广州雷达资料以及相应的探空资料,同仅使用VPR识别零度层亮带的方法(简称VPR-BBID)进行比较。结果表明:VPR-BBID和3DVPR-BBID在大部分情况下能够有效识别零度层亮带的存在,而且3DVPR-BBID能够减少VPR-BBID产生的误识别。在同探空资料观测的零度层高度的比较中,两种方法确定的零度层高度同实况比较接近,进一步分析表明:3DVPR-BBID确定的零度层高度比VPR-BBID确定的更接近观测值。展开更多
基金funded by the Korean Meteorological Administration Research and Development Program under Grant CATER 2006-2307.
文摘Data from a long term measurement of Micro Rain Radar （MRR） at a mountain site （Daegwallyeong, DG, one year period of 2005） and a coastal site （Haenam, HN, three years 2004-2006） in South Korea were analyzed to compare the MRR measured bright band characteristics of stratiform precipitation at the two sites. On average, the bright band was somewhat thicker and the sharpness （average gradient of reflectivity above and below the reflectivity peak） was slightly weaker at DG, compared to those values at HN. The peak reflectivity itself was twice as strong and the relative location of the peak reflectivity within the bright band was higher at HN than at DG. Importantly, the variability of these values was much larger at HN than at DG. The key parameter to cause these differences is suggested to be the difference of the snow particle densities at the two sites, which is related to the degree of riming. Therefore, it is speculated that the cloud microphysical processes at HN may have varied significantly from un-rimed snow growth, producing low density snow particles, to the riming of higher density particles, while snow particle growth at DG was more consistently affected by the riming process, and therefore high density snow particles. Forced uplifting of cloudy air over the mountain area around DG might have resulted in an orographic supercooling effect that led to the enhanced riming of supercooled cloud drops.
基金National Natural Science Foundation of China(41275043)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘In this study, the vertical profiles of radar refractive factor(Z) observed with an X-band Doppler radar in Jurong on July 13, 2012 in different periods of a stratiform cloud precipitation process were simulated using the Sim RAD software, and the contributions of each impact resulting in the bright band were analyzed quantitatively. In the simulation, the parameters inputted into Sim RAD were updated until the output Z profile was nearly consistent with the observation. The input parameters were then deemed to reflect real conditions of the cloud and precipitation. The results showed that a wider(narrower) and brighter(darker) bright band corresponded to a larger(smaller) amount, wider(narrower) vertical distribution, and larger(smaller) mean diameter of melting particles in the melting layer. Besides this,radar reflectivity factors under the wider(narrower) melting layer were larger(smaller). This may be contributed to the adequate growth of larger rain drops in the upper melting layer. Sensitivity experiments of the generation of the radar bright band showed that a drastic increasing of the complex refractive index due to melting led to the largest impact,making the radar reflectivity factor increase by about 15 d BZ. Fragmentation of large particles was the second most important influence, making the value decrease by 10 d BZ. The collision-coalescence between melting particles, volumetric shrinking due to melting, and the falling speed of raindrops made the radar reflectivity factor change by about 3-7d BZ. Shape transformation from spheres to oblate ellipsoids resulted in only a slight increase in the radar reflectivity factors(about 0.2 d BZ), which might be due to the fact that there are few large particles in stratiform cloud.
基金funded by a China National 973 Program on Key Basic Research project (Grant No.2014CB441401)the Beijing Municipal Natural Science Foundation (Grant No.8141002)the Public Welfare Industry (Meteorology) of China (Grant No.GYHY201106046)
文摘The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of significant overestimation in quantitative precipitation estimation(QPE) based on the Z–R(reflectivity factor–rain rate) relationship.The effects of the bright band on radar-based QPE can be eliminated by vertical profile of reflectivity(VPR) correction. In this study, we applied bright-band correction algorithms to evaluate three different bands(S-, C-and X-band) of dual-polarized radars and to reduce overestimation errors in Z–R relationship–based QPEs. After the reflectivity was corrected by the algorithms using average VPR(AVPR) alone and a combination of average VPR and the vertical profile of the copolar correlation coefficient(AVPR+CC), the QPEs were derived. The bright-band correction and resulting QPEs were evaluated in eight precipitation events by comparing to the uncorrected reflectivity and rain-gauge observations, separately. The overestimation of Z–R relationship–based QPEs associated with the bright band was reduced after correction by the two schemes for which hourly rainfall was less than 5 mm. For the verification metrics of RMSE(root-mean-square error), RMAE(relative mean absolute error) and RMB(relative mean bias) of QPEs, averaged over all eight cases, the AVPR method improved from 2.28,0.94 and 0.78 to 1.55, 0.60 and 0.40, respectively, while the AVPR+CC method improved to 1.44, 0.55 and 0.30, respectively.The QPEs after AVPR+CC correction had less overestimation than those after AVPR correction, and similar conclusions were drawn for all three different bands of dual-polarized radars.
文摘该文提出一种使用S波段多普勒天气雷达回波三维特征和反射率因子垂直廓线(vertical profile of reflectivity,VPR)来自动识别零度层亮带的方法(简称3DVPR-BBID),并利用2003年6月22日—7月11日和2007年7月合肥雷达资料、2008年6月广州雷达资料以及相应的探空资料,同仅使用VPR识别零度层亮带的方法(简称VPR-BBID)进行比较。结果表明:VPR-BBID和3DVPR-BBID在大部分情况下能够有效识别零度层亮带的存在,而且3DVPR-BBID能够减少VPR-BBID产生的误识别。在同探空资料观测的零度层高度的比较中,两种方法确定的零度层高度同实况比较接近,进一步分析表明:3DVPR-BBID确定的零度层高度比VPR-BBID确定的更接近观测值。
