THE APPLICATION OF CONDITIONAL NONLINEAR OPTIMAL PERTURBATION TO THE BINARY TYPHOONS INTERACTION —FENGSHEN AND FUNG-WONG

The interaction between the typhoons Fengshen and Fung-wong over the Western Pacific in 2002 is studied with the Conditional Nonlinear Optimal Perturbation (CNOP) method. The study discovered that the CNOP method reveals the process of one-way interaction between Fengshen and Fung-wong. Moreover, if the region of Fung-wong was selected for verification, the sensitivity area was mainly located in the region of Fengshen and presented a half-ring structure; if the region of Fengshen was selected for verification, most of the sensitivity areas were located in the region between the Fengshen and the subtropical high, far away from Fung-wong. This indicated that Fung-wong is mainly steered by Fengshen, but Fengshen is mainly affected by the subtropical high. The sensitivity experiment showed that the initial errors in the CNOP-identified sensitive areas have larger impacts on the verification-area prediction than those near the typhoon center and their developments take a large proportion in the whole domain. This suggests that the CNOP-identified sensitive areas do have large influence on the verification-area prediction.     

A simple method of calculating the optimal step size in 4DVAR technique

l.IntroductionWithhighlydevelopingofmodernscientifictechnologyandincessantupdatingoftheobservationalsystem,manykindsofnewsourcesofobservationaldataarereadilyobtained,suchassatellitedataandradardata.Ithasbeenacriticalproblemtopuzzleresearcherstoeffectivelyemploythesedatainnumericalcalculation.4DVARtechniquehasgraduallybeenaveryimportanttoolinthemainstreamofnumericalweatherprediction,becauseitisofstrongcapabilityofcombiningandextractingtheusefulinformationfromallkindsofobservationaldata.Thedat…     

MJO随机强迫对CNOP型初始误差演变的影响

用Zebiak-Cane模式和季节内振荡(Madden-Julian Oscillation,MJO)的参数化表述以及条件非线性最优扰动(Conditional Nonlinear Optimal Perturbation,CNOP)方法,分析了以ENSO事件为基态的CNOP型初始误差的空间结构增长规律。结果表明,参数化的MJO对CNOP型初始误差的发展影响较小,其影响主要是使中东太平洋的海表面温度异常增大。CNOP型初始误差比由MJO不确定性产生的模式误差的影响大,前者可能是造成ENSO事件预报不确定性的主要误差来源。由于CNOP型初始误差的局地性,本结论可用来指导ENSO的目标观测和适应性资料同化。     

冬小麦土壤墒情预报及优化灌溉技术的计算机模型

利用土壤水分平衡方程，根据我省冬小麦的生长规律及冬小麦优化灌溉技术推广经验，建立了冬小麦土壤墒情预报及优化灌溉技术的计算机模型，利用该模型，可以较准确地预报未来1个月的土壤墒情变化，并可根据我省小麦的不同发育期给出以最高产量和最佳经济效益为目标的两种灌溉建议。     

均生函数—最优子集回归在高温极值预测中的应用

根据南京等城市1961年以来历年气温极值资料序列，采用均生函数—最优子集回归法设计的短期气候预测模型不但能较好地拟合历史实况，而互对未来l～5年的演变趋势也具有一定的预报能力。