Theoretical Basis and Application of an Analogue- Dynamical Model in the Lorenz System

The theoretical basis and application of an analogue-dynamical model (ADM) in the Lorenz system is studied. The ADM can effectively combine statistical and dynamical methods in which the small disturbance of the current initial value superimposed on the historical analogue reference state can be regarded as a prediction objective. Primary analyses show that under the condition of appending disturbances in model parameters, the model errors of ADM are much smaller than those of the pure dynamical model (PDM). The characteristics of predictability on the ADM in the Lorenz system are analyzed in phase space by conducting case studies and global experiments. The results show that the ADM can quite effectively reduce prediction errors and prolong the valid time of the prediction in most situations in contrast to the PDM, but when model errors are considerably small, the latter will be superior to the former. To overcome such a problem, the multi-reference-state updating can be applied to introduce the information of multi-analogue and update analogue and can exhibit exciting performance in the ADM.     

Characteristics of tropical Pacific SST predictability in coupled GCM forecasts using the NCEP CFS

The limits of predictability of El Niño and the Southern Oscillation (ENSO) in coupled models are investigated based on retrospective forecasts of sea surface temperature (SST) made with the National Centers for Environmental Prediction (NCEP) coupled forecast system (CFS). The influence of initial uncertainties and model errors associated with coupled ENSO dynamics on forecast error growth are discussed. The total forecast error has maximum values in the equatorial Pacific and its growth is a strong function of season irrespective of lead time. The largest growth of systematic error of SST occurs mainly over the equatorial central and eastern Pacific and near the southeastern coast of the Americas associated with ENSO events. After subtracting the systematic error, the root-mean-square error of the retrospective forecast SST anomaly also shows a clear seasonal dependency associated with what is called spring barrier. The predictability with respect to ENSO phase shows that the phase locking of ENSO to the mean annual cycle has an influence on the seasonal dependence of skill, since the growth phase of ENSO events is more predictable than the decay phase. The overall characteristics of predictability in the coupled system are assessed by comparing the forecast error growth and the error growth between two model forecasts whose initial conditions are 1 month apart. For the ensemble mean, there is fast growth of error associated with initial uncertainties, becoming saturated within 2 months. The subsequent error growth follows the slow coupled mode related the model’s incorrect ENSO dynamics. As a result, the Lorenz curve of the ensemble mean NINO3 index does not grow, because the systematic error is identical to the same target month. In contrast, the errors of individual members grow as fast as forecast error due to the large instability of the coupled system. Because the model errors are so systematic, their influence on the forecast skill is investigated by analyzing the erroneous features in a long simulation. For the ENSO forecasts in CFS, a constant phase shift with respect to lead month is clear, using monthly forecast composite data. This feature is related to the typical ENSO behavior produced by the model that, unlike the observations, has a long life cycle with a JJA peak. Therefore, the systematic errors in the long run are reflected in the forecast skill as a major factor limiting predictability after the impact of initial uncertainties fades out.     

Systematic errors in the medium range prediction of the Asian summer monsoon circulation

The present study describes an analysis of Asian summer monsoon forecasts with an operational general circulation model (GCM) of the European Centre for Medium Range Weather Forecasts (ECMWF), U.K. An attempt is made to examine the influence of improved treatment of physical processes on the reduction of systematic errors. As some of the major changes in the parameterization of physical processes, such as modification to the infrared radiation scheme, deep cumulus convection scheme, introduction of the shallow convection scheme etc., were introduced during 1985–88, a thorough systematic error analysis of the ECMWF monsoon forecasts is carried out for a period prior to the incorporation of such changes i.e. summer monsoon season (June–August) of 1984, and for the corresponding period after relevant changes were implemented (summer monsoon season of 1988). Monsoon forecasts of the ECMWF demonstrate an increasing trend of forecast skill after the implementation of the major changes in parameterizations of radiation, convection and land-surface processes. Further, the upper level flow is found to be more predictable than that of the lower level and wind forecasts display a better skill than temperature. Apart from this, a notable increase in the magnitudes of persistence error statistics indicates that the monsoon circulation in the analysed fields became more intense with the introduction of changes in the operational forecasting system. Although, considerable reduction in systematic errors of the Asian summer monsoon forecasts is observed (up to day-5) with the introduction of major changes in the treatment of physical processes, the nature of errors remain unchanged (by day-10). The forecast errors of temperature and moisture in the middle troposphere are also reduced due to the changes in treatment of longwave radiation. Moreover, the introduction of shallow convection helped it further by enhancing the vertical transports of heat and moisture from the lower troposphere. Though, the hydrological cycle in the operational forecasts appears to have enhanced with the major modifications and improvements to the physical parameterization schemes, certain regional peculiarities have developed in the simulated rainfall distribution over the monsoon region. Hence, this study suggests further attempts to improve the formulations of physical processes for further reduction of systematic forecast errors.     

Anomalously deep earthquakes in northwestern Italy

It is usually assumed that earthquakes in intraplate regions occur in the upper crust, and northwestern Italy is generally assigned to this kind of normal seismicity. In this work, the depth distribution of the events localized in this area by the Istituto Geofisico Geodetico (IGG) seismic network in the period 1991–1997 is analyzed in detail. In particular, the location capability of the network is discussed, adopting as reference quarry blasts (for the epicentral position) and the locations obtained from a dense temporary network (for the depth estimate). Within the so-obtained error limits, the depth distribution of events show a characteristic pattern: while for most of the area covered by the network the well-located seismicity lies within the first 20 km of depth, in a band following the inner arc of the Western Alps, numerous events have anomalously large focal depths, reaching a maximum of 114 km. These depth determinations cannot be attributed to instabilities of the location procedure: different choices of the propagation models used for the hypocentral determination led to very similar depth values, always significantly larger than the standard values for the surrounding areas. A strong correlation has been found between the 3-dimensional distribution of these foci and the P-wave propagation anomalies obtained from tomographic studies, suggesting a direct link between elastic and rheological properties of lower crust and upper mantle in this area.     

卡尔曼滤波模型误差的识别

本文在简述卡尔曼滤波模型基础上讨论了模型误差的检验和估计问题,提出了检验卡尔曼滤波模型误差显著性的几种统计假设检验方法,探讨并给出了估计模型误差的方法和公式。     

基于集合预报的台风“利奇马”登陆后远距离暴雨预报的敏感性分析

2019年第9号台风“利奇马”在8月10日登陆后引发了远距离大范围的暴雨,本文利用ECMWF(EC)和GRAPES全球集合预报模式等资料对暴雨短期预报的误差及原因进行了分析。此次台风远距离暴雨主要集中在8月10日夜间的山东中部地区,EC集合预报对该区域的降水量预报效果总体优于GRAPES集合预报。集合敏感性分析可以识别出和预报变量高相关(敏感)的天气系统,结果表明山东区域平均降水量对同期500 hPa副高、台风西北侧海平面气压和山东北部低层温度较为敏感,而对流层高层的高度及经向风存在更大范围的敏感区。根据暴雨预报TS评分选取EC集合预报成员作为优势组和劣势组,结果表明优势组预报成员表现为山东上空300 hPa低槽前倾,北侧高空偏南急流更强,同时配合低层台风外围偏东风急流,形成高层辐散、低层辐合的有利条件。另外,优势组预报的中纬度低层冷空气和斜压锋区更强,导致优势组在山东中部预报出暴雨,更加接近于实况。     

复杂地形条件下嵌套细网格模式35例数值预报的总结

本文利用一适合复杂地形区的有限区域预报模式系统，分别采用欧洲中期天气预报中心的格点资料和我国国家气象中心的ＤＣＤ电码资料，对１９８１年７月１－３０日和１９８８年８月１０－１４日两时段共３５天作了４８小时预报。形势场和降水预报的主客观评分表明，该模型系统已具备了在业务环境下作预报的可能，该模型预报性能良好，具有较好的强降水预报的能力。     

轨道误差对近实时GPS遥感水汽的影响研究

利用GPS技术近实时探测水汽对于气象预报、气候研究具有重要的应用价值，而近实时探测需要使用GPS卫星的预报星历，预报星历的误差会直接影响到实时水汽探测的精度。利用从IGS资料处理中心下载的精密预报星历和最终星历，对2000年北京GPS水汽试验中的资料进行了解算，并结合探空资料计算的水汽进行了分析。结果表明：以探空为标准，使用精密预报星历计算的水汽总量均方根误差为0．31cm，最终星历为0．30cm，二者差别不大，为0．01cm，证明使用精密预报星历可以满足近实时探测水汽的要求。     

动态Kalman滤波模型误差的影响

动态Kalman滤波模型误差的影响与静态平差模型误差影响不同。它包括观测异常误差影响和动力学模型异常的影响。本文分别讨论了观测异常误差和动力学模型异常误差对当前历元滤波结果的影响及对后续历元滤波结果的影响;构建了异常误差影响表达式,并对各类异常误差的检测方法进行了分析。     

A New Method for the Determination of Area-Averaged Turbulent Surface Fluxes from Low-Level Flights Using Inverse Models

The low-level flight method (LLF) has been combined with linear inverse models (IM) resulting in an LLF+IM method for the determination of area-averaged turbulent surface fluxes. With this combination, the vertical divergences of the turbulent latent and sensible heat fluxes were calculated from horizontal flights. The statistical errors of the derived turbulent surface fluxes were significantly reduced. The LLF+IM method was tested both in numerical and field experiments. Large-eddy simulations (LES) were performed to compare ‘true’ flux profiles with ‘measurements’ of simulated flights in an idealised convective boundary layer. Small differences between the ‘true’ and the ‘measured’ fluxes were found, but the vertical flux divergences were correctly calculated by the LLF+IM method. The LLF+IM method was then applied to data collected during two flights with the Helipod, a turbulence probe carried by a helicopter, and with the research aircraft Do 128 in the LITFASS-98 field campaign. The derived surface fluxes were compared with results from eddy-covariance surface stations and with large-aperture scintillometer data. The comparison showed that the LLF+IM method worked well for the sensible heat flux at 77 and 200 m flight levels, and also for the latent heat flux at the lowest level. The model quality control indicated failures for the latent heat flux at the 200 m level (and higher), which were probably due to large moisture fluctuations that could not be modelled using linear assumptions. Finally the LLF+IM method was applied to more than twenty low-level flights from the LITFASS-2003 experiment. Comparison with aggregated surface flux data revealed good agreement for the sensible heat flux but larger discrepancies and a higher statistical uncertainty for the latent heat flux