不同导风系统的云迹风资料及其在台风预报中同化应用的对比分析
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摘要
西太平洋是全球热带气旋发生频率最高的海域,特别是东亚地区的中国和韩国都是受台风影响较为严重的国家。过去由于在海洋上的观测资料不足,对台风登陆前的研究十分有限。而近几年,云迹风等一系列高时空分辨率的气象卫星的非常规资料弥补了海洋上观测资料不足,特别是利用同化方法把非常规资料应用到模式中,可以有效地改善对台风路径的数值预报。
本文首先通过不同导风系统的云迹风资料的对比、云迹风资料和探空风资料的对比,得到CWIS(cloud motion wind inferring system developed by NUIST)云迹风资料的误差特征。然后利用WRF模式的三维变分同化系统将CWIS云迹风资料引入模式,进行台风数值模拟试验和诊断分析,研究了云迹风资料在模式模拟中对台风预报的影响,并对比分析不同导风系统得到的云迹风资料的数值模拟差异。本研究可为提高台风的预报效果提供线索。主要得到以下结果:
1.通过对比CWIS、NSMC(中国气象局国家卫星中心)和JMSC(日本气象卫星中心)云迹风资料,并将这三种云迹风资料与探空风进行比较,评价了CWIS云迹风资料。CWIS的风速与JMSC、RAOB之间有较好的一致性,而CWIS的风向相对于NSMC、JMSC和RAOB差异较大。虽然CWIS存在一些误差,但CWIS云迹风资料可以较好地描述天气形势。
2.同化CWIS单通道的云迹风资料以及同时同化两个通道的云迹风资料对2005年第9号台风“麦莎”的路径预报有明显的改善作用,其中同时同化两个通道(时间间隔为3小时)的路径预报模拟结果更好。
3.CWIS、NSMC和JMSC云迹风资料对2005年第15号台风“卡努”路径预报都有不同程度的改善,减小的平均误差分别为49%、19%和39%。并且3小时间隔的云迹风资料模拟出的台风路径非常接近实况。GTS(探空,地面)资料模拟对台风路径预报出现负面现象,但是合并云迹风资料后,能改进其对台风路径的预报,尤其是合并JMSC云迹风资料后的同化结果比单独同化JMSC云迹风资料和GTS资料的模拟更好。同时同化各云迹风资料和GTS资料减小的平均误差分别为26%、15%和50%。
4.通过对台风2005年第14号“彩蝶”引发的特大暴雨的分析,发现此次暴雨在台风的倒槽内有中尺度对流云团产生。模式的降水预报中,从综合降水范围、中心位置和中心强度来看,云迹风资料对台风降水中心和强度都有较好的模拟能力。
5.积云对流参数化方案在模式模拟台风“彩蝶”路径的影响较大。与Betts-Miller-Janjic(BMJ)方案相比,Kain-Fritcz(KF)方案能够更好地模拟出台风路径。使用KF方案时,选择微物理方案对于台风路径有更好的模拟结果。其中,Ferrier、WSM6和Lin方案非常接近于实况。JMSC云迹风资料在不同模式参数化方案中对台风预报的影响也有明显的差异,在KF方案中,只有选用Kessler方案时,同化云迹风资料才有比控制试验更好的结果。而在BMJ方案中,选用任何微物理方案,同化云迹风资料都比控制试验的结果好。
The western Pacific Ocean is the most frequent sea area where tropical cyclones take place. The East Asia, especially China and Korea are all under the influence of typhoon. In the past, due to a lack of information from observation above the sea, the research of situation before a typhoon landing was rather limited. In recent years, the application of a series of unconventional high resolution spatiotemporal data, for example, satellite cloud motion wind (CMW), complements the defect of observational data above the sea. The assimilation of the unconventional data in models can effectively improve the typhoon track forecast.
This study includes comparing of cloud motion wind datasets from different deriving systems and also comparing CMW data with radiosonde data. These CMW data are from CWIS (cloud motion wind inferring system developed by NUIST), NSMC (China Satellite Meteorological Center) and JMSC (Japan Meteorological Satellite Center). In addition, numerical experiments and diagnostic analyses are conducted for the effect of CWIS CMW data on typhoon forecasting in WRF 3DVAR and analyzed the difference of numerical experiments of three kind of CMW data. This study could be giving a clue of improving the typhoon forecasting. The results are as follows:
Firstly, it was evaluated by comparing three different kinds of CMW data each other and comparing CMW data with radiosonde data for evaluating the CWIS data. The wind speeds measured by CWIS data, are similar to NSMC data and JMSC data, but the wind directions of CWIS data relatively greater than other data. Although there are some errors in CWIS data, it insures good reliability of the weather situation.
Secondly, Both assimilation of one channel and two channels of CWIS data have remarkable improvement in forecasting the track of typhoon Masha (200509). The typhoon track forecasted by assimilation of two channels (the time interval is 3 hours) is much better.
Thirdly, CWIS, NSMC and JMSC data have different grade of improvement in forecasting the track of typhoon Khanun (200515), Three systems yield 49%, 19% and 39% respective reduction in forecast mean error. GTS (radiosonde, surface) data simulation has some negative effect on forecasting typhoon track, but when it is combined with CMW data, the track forecasting is greatly improved. Especially when combined with JMSC data, the result is better than the assimilation of JMSC data and GTS data respectively. The assimilations of three kinds of CMW data and GTS data have 26 %, 15% and 50% in forecast mean error, respectively.
Fourthly, it was analyzed typhoon Nabi (200514) caused heavy rainfalls, which mainly happen in the coastal area of Korea. These heavy rainfalls take placed due to inverted trough, CMW data has good simulation of the typhoon main precipitation area and core.
Fifthly, Convective schemes have great influence on the track of typhoon Nabi. Compared with Betts-Miller-Janjic (BMJ) scheme, Kain-Fritcz (KF) scheme can better simulate typhoon track. When using KF scheme, choosing micro-physical scheme is better than no choosing scheme. The results got by Ferrier, WSM6 and Lin scheme are really close to the observation. JMSC CMW data using different parameterization schemes has different effect on typhoon forecasts. In KF scheme, typhoon track only by Kessler scheme is a better improvement than controlled experiment. In BMJ scheme, every micro-physical method can provide better results than controlled experiment.
本文首先通过不同导风系统的云迹风资料的对比、云迹风资料和探空风资料的对比,得到CWIS(cloud motion wind inferring system developed by NUIST)云迹风资料的误差特征。然后利用WRF模式的三维变分同化系统将CWIS云迹风资料引入模式,进行台风数值模拟试验和诊断分析,研究了云迹风资料在模式模拟中对台风预报的影响,并对比分析不同导风系统得到的云迹风资料的数值模拟差异。本研究可为提高台风的预报效果提供线索。主要得到以下结果:
1.通过对比CWIS、NSMC(中国气象局国家卫星中心)和JMSC(日本气象卫星中心)云迹风资料,并将这三种云迹风资料与探空风进行比较,评价了CWIS云迹风资料。CWIS的风速与JMSC、RAOB之间有较好的一致性,而CWIS的风向相对于NSMC、JMSC和RAOB差异较大。虽然CWIS存在一些误差,但CWIS云迹风资料可以较好地描述天气形势。
2.同化CWIS单通道的云迹风资料以及同时同化两个通道的云迹风资料对2005年第9号台风“麦莎”的路径预报有明显的改善作用,其中同时同化两个通道(时间间隔为3小时)的路径预报模拟结果更好。
3.CWIS、NSMC和JMSC云迹风资料对2005年第15号台风“卡努”路径预报都有不同程度的改善,减小的平均误差分别为49%、19%和39%。并且3小时间隔的云迹风资料模拟出的台风路径非常接近实况。GTS(探空,地面)资料模拟对台风路径预报出现负面现象,但是合并云迹风资料后,能改进其对台风路径的预报,尤其是合并JMSC云迹风资料后的同化结果比单独同化JMSC云迹风资料和GTS资料的模拟更好。同时同化各云迹风资料和GTS资料减小的平均误差分别为26%、15%和50%。
4.通过对台风2005年第14号“彩蝶”引发的特大暴雨的分析,发现此次暴雨在台风的倒槽内有中尺度对流云团产生。模式的降水预报中,从综合降水范围、中心位置和中心强度来看,云迹风资料对台风降水中心和强度都有较好的模拟能力。
5.积云对流参数化方案在模式模拟台风“彩蝶”路径的影响较大。与Betts-Miller-Janjic(BMJ)方案相比,Kain-Fritcz(KF)方案能够更好地模拟出台风路径。使用KF方案时,选择微物理方案对于台风路径有更好的模拟结果。其中,Ferrier、WSM6和Lin方案非常接近于实况。JMSC云迹风资料在不同模式参数化方案中对台风预报的影响也有明显的差异,在KF方案中,只有选用Kessler方案时,同化云迹风资料才有比控制试验更好的结果。而在BMJ方案中,选用任何微物理方案,同化云迹风资料都比控制试验的结果好。
The western Pacific Ocean is the most frequent sea area where tropical cyclones take place. The East Asia, especially China and Korea are all under the influence of typhoon. In the past, due to a lack of information from observation above the sea, the research of situation before a typhoon landing was rather limited. In recent years, the application of a series of unconventional high resolution spatiotemporal data, for example, satellite cloud motion wind (CMW), complements the defect of observational data above the sea. The assimilation of the unconventional data in models can effectively improve the typhoon track forecast.
This study includes comparing of cloud motion wind datasets from different deriving systems and also comparing CMW data with radiosonde data. These CMW data are from CWIS (cloud motion wind inferring system developed by NUIST), NSMC (China Satellite Meteorological Center) and JMSC (Japan Meteorological Satellite Center). In addition, numerical experiments and diagnostic analyses are conducted for the effect of CWIS CMW data on typhoon forecasting in WRF 3DVAR and analyzed the difference of numerical experiments of three kind of CMW data. This study could be giving a clue of improving the typhoon forecasting. The results are as follows:
Firstly, it was evaluated by comparing three different kinds of CMW data each other and comparing CMW data with radiosonde data for evaluating the CWIS data. The wind speeds measured by CWIS data, are similar to NSMC data and JMSC data, but the wind directions of CWIS data relatively greater than other data. Although there are some errors in CWIS data, it insures good reliability of the weather situation.
Secondly, Both assimilation of one channel and two channels of CWIS data have remarkable improvement in forecasting the track of typhoon Masha (200509). The typhoon track forecasted by assimilation of two channels (the time interval is 3 hours) is much better.
Thirdly, CWIS, NSMC and JMSC data have different grade of improvement in forecasting the track of typhoon Khanun (200515), Three systems yield 49%, 19% and 39% respective reduction in forecast mean error. GTS (radiosonde, surface) data simulation has some negative effect on forecasting typhoon track, but when it is combined with CMW data, the track forecasting is greatly improved. Especially when combined with JMSC data, the result is better than the assimilation of JMSC data and GTS data respectively. The assimilations of three kinds of CMW data and GTS data have 26 %, 15% and 50% in forecast mean error, respectively.
Fourthly, it was analyzed typhoon Nabi (200514) caused heavy rainfalls, which mainly happen in the coastal area of Korea. These heavy rainfalls take placed due to inverted trough, CMW data has good simulation of the typhoon main precipitation area and core.
Fifthly, Convective schemes have great influence on the track of typhoon Nabi. Compared with Betts-Miller-Janjic (BMJ) scheme, Kain-Fritcz (KF) scheme can better simulate typhoon track. When using KF scheme, choosing micro-physical scheme is better than no choosing scheme. The results got by Ferrier, WSM6 and Lin scheme are really close to the observation. JMSC CMW data using different parameterization schemes has different effect on typhoon forecasts. In KF scheme, typhoon track only by Kessler scheme is a better improvement than controlled experiment. In BMJ scheme, every micro-physical method can provide better results than controlled experiment.
引文
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[1]白洁,王洪庆,陶祖珏.GMS卫星红外云图云迹风的反演,北京大学学报(自然科学版),1997,33(1):85-92.
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