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机构地区:[1]国家气象中心,北京100081
出 处:《气象》2016年第12期1498-1505,共8页Meteorological Monthly
基 金:公益性行业(气象)科研专项(GYHY201306002)资助
摘 要:面对数值天气预报模式发展中的制约,如今气象界提出了预报员数据同化(data assimilation,DA)的理念,即将预报员的能力有机地融入到数值预报模式中以便发挥各自的优势。人工订正位涡改进模式初始场技术即充分体现了这一理念,其原理是利用了在中、高纬度气旋性环流场中,位涡(potential vortictiy,PV)场和卫星水汽图像(satellite water vapor imagery,WV)较好的对应关系检验数值预报,进而利用位涡的可反演性通过人工修改位涡场来订正数值预报,并已在部分国家实践中证明有着显著的改进模式预报性能的效果。本研究将通过分析对流层中高层的动力活跃区、位涡分布和卫星水汽图像暗区的关系检验模式偏差,进而通过人工订正位涡场和位涡反演,实现对模式初始场的修改,为预报员主观订正模式初始场、改进模式预报能力提供完整的技术流程。Faced with a series of limitations in developing numerical weather prediction model, a brand new conception of forecaster data assimilation (DA) has been put forward. That is an organic combination between weather forecasters' irreplaceable ability and numerical weather prediction. The improvement on the model initial field by manual correction of potential vorticity is coincident with this conception. By utilizing the principle of correspondence between potential vorticity (PV) and water vapor image (WV) observed by satellite, forecasters can exam the model and manually correct the distribution of PV, and use PV inversion to obtain a well developed model initial field. This technology has been proved efficacious in operational work in some countries. This study takes use of the principles mentioned above to achieve the whole technology and use some experimental results to show the technical processes.
分 类 号:P456[天文地球—大气科学及气象学]
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