利用环流特征量进行衡阳干旱预测及其系统开发

对国家气候中心下发的环流特征量,利用SPSS统计分析软件进行方差分析,找到通过一定信度检验的干旱预报因子,建立预报方程。历史回报发现这些预报模型的检验效果并不明显,但把结果按照一定规律订正后准确率明显提高,有较好的指示意义。以此预报模型为基础,开发衡阳市干旱预测系统,系统在2006、2007年的干旱预测中取得比较满意的效果。     

Understanding the dynamical mechanism of year-to-year incremental prediction by nonlinear time series prediction theory

基于年际增量预测(YIP)方法的数学原理,推导得出新的非线性时间序列预测(NP)方法,并从理论上证明了两种预测方法在一定条件下的等效性。以长江中下游地区的夏季降水为例,新的NP方法在使用年际增量作为强迫项时,可以取得与YIP相当的预测效果。而且,通过调整重构维数等参数,能够将预测模型重构于高于一维的相空间中,进而可获得更好的预测效果。研究发现YIP方法除了有物理基础外,还有隐含的动力基础,新NP模型有助于提高短期气候预测的水平。     

Drought prediction

Drought prediction has been an age-old problem, but in more recent times the magnitude of the Sahelian drought has brought into focus the need to improve the techniques for predicting such droughts with some measure of accuracy. Prom the present state of knowledge, drought prediction is difficult, if not impossible. Two major approaches appear to be prominent in the search for appropriate techniques. These include the use of teleconnections and the development of numerical models.Essentially, time-lagged teleconnections rely on the assumption that changes induced in any one area of the world may produce changes elsewhere on a world-wide scale, though time-lagged. The 1972-73 El Nino off the west coast of South America is a good case in point. The development of numerical models which allow the incorporation of not only climatic factors but also man's impact on the natural environment, offers some ray of hope that the general circulation models (GCMs) may help to improve the techniques of drought prediction.     

Monthly prediction of tropical cyclone activity over the South China Sea using the FGOALS-f2 ensemble prediction system

本研究基于新一代FGOALS-f2动力集合预测系统35年(1981-2015年)的热带气旋历史回报试验对南海台风季(7-11月)热带气旋活动超前10天的月预测技巧进行评估,并对2020年南海台风季热带气旋活动进行了实时月预测尝试.结果表明:FGOALS-f2能较好地预测南海热带气旋路径密度演变特征,预测的热带气旋生成个...     

Soil moisture prediction over the Australian continent

Summary This paper describes an attempt to model soil moisture over the Australian continent with an integrated system of dynamic models and a Geographic Information System (GIS) data base. A land surface scheme with improved treatment of soil hydrological processes is described. The non-linear relationships between soil hydraulic conductivity, matric potential and soil moisture are derived from the Broadbridge and White soil model. For a single location, the prediction of the scheme is in good agreement with the measurements of the Hydrological and Atmospheric Pilot Experiment (HAPEX). High resolution atmospheric and geographic data are used in soil moisture prediction over the Australian continent. The importance of reliable land surface parameters is emphasized and details are given for deriving the parameters from a GIS. Predicted soil moisture patterns over the Australian continent in summer, with a 50 km spatial resolution, are found to be closely related to the distribution of soil types, apart from isolated areas and times under the influence of precipitation. This is consistent with the notion that the Australian continent in summer is generally under water stress. In contrast, predicted soil temperatures are more closely related to radiation patterns and changes in atmospheric circulation. The simulation can provide details of soil moisture evolution both in space and time, that are very useful for studies of land use sustainability, such as plant growth modelling and soil erosion prediction.With 12 Figures     

Operational regional prediction

Summary Regional operational prediction requires the development, implementation and steady improvement of a modelling system which comprises different components like the data assimilation scheme, numerical forecast model, postprocessing and application modules as well as packages for monitoring, diagnostics and verification. The text highlights the impact of some of those components like lateral boundary conditions, data assimilation and statistical postprocessing on the quality of operational regional prediction systems and proposes some important research directions for an improvement of the systems from the operational point of view.With 14 Figures     

天气预报现代化的途径

当前华主席、党中央为我们指明了科学技术现代化的目标,要求我们能尽快地实现科学技术现代化。大气科学的中心任务是提高天气予报的准确度,天气予报的进展是整个大气科学发展的基础。因此怎样使我国的天气予报科学实现现代化,是我们气象工作者应该考虑的重要问题。本文想从近代天气予报科学的进展情况讨论一下这个问题。     

数值天气预报中的不一致性问题综述

近年来随着数值天气预报的不断发展,数值天气预报中出现了一个新的值得注意的问题:预报不一致性,即连续多次预报中,前后两次预报所做出的预报结果之间差异较大的现象。本文较系统地概述了这一问题,总结了预报不一致性的概念、定量分析方法、产生的可能原因及其与预报误差的关系等方面的研究成果。目前预报不一致性的定量分析方法还较少,其适用性和客观性等还需进一步研究。在预报不一致性产生的原因方面,现有的研究仅限于理论上的简要分析,初始误差和模式误差在预报不一致性形成过程中的具体作用等尚不清楚。最后阐述了在预报不一致性研究中存在的一些问题及可能的研究方向。     

T213在降水预报中的统计分析

选取多个预报因子,利用T213资料获取相应的数据资料,通过SAS统计分析软件进行计算,选择相关好的预报因子,进而得到降水预报方程,然后根据全部数据建立的判别函数对数据进行回代、判别比较理论归属和实际归属的偏差。最后在VB语占下制作工作平台。     

Interdecadal change in the Northern Hemisphere seasonal climate prediction skill: part II. predictability and prediction skill

The interdecadal change in seasonal predictability and numerical models’ seasonal forecast skill in the Northern Hemisphere are examined using both observations and the seasonal hindcast from six coupled atmosphere-ocean climate models from the 21 period of 1960–1980 (P1) to that of 1981–2001 (P2). It is shown that the one-month lead seasonal forecast skill of the six models’ multi-model ensemble is significantly increased from P1 to P2 for all four seasons. We identify four possible reasons accounting for the interdecadal change of the seasonal forecast skill. Firstly, the numerical model’s ability to simulate the mean state, the time variability and the spatial structures of the sea surface temperature and precipitation over the tropical Pacific is improved in P2 compared to P1. Secondly, an examination of the potential predictability of the atmosphere, estimated by the ratio of the total variance to the variance due to the internal dynamics of the model atmosphere, reveals that the atmospheric potential predictability is significantly increased after 1980s which is mainly due to an increased influence of El Niño-Southern Oscillation signal over the North Pacific and North American regions. Thirdly, the long-term climate trends in the atmosphere are found to contribute, to some extent, to the increased seasonal forecast skill especially over the Eurasian regions. Finally, the improved ocean observations in P2 may provide better initial conditions for the coupled models’ seasonal forecast.     

11个S2S模式对MJO预报效果的评估分析

利用次季节—季节预报研究计划(Subseasonal to Seasonal Prediction Project, S2S)的多模式产品集,系统评估了产品集中11个模式对MJO的实际预报技巧。如果以距平相关系数ACC为0.5作为有效预报技巧的阈值,S2S各模式的MJO实际预报时效为8～32 d。S2S各模式预报普遍低估了MJO的振幅强度,且预报的MJO传播速度偏慢。通过分析发现,在一个集合预报系统中,集合离散度与均方根误差越接近,它的MJO预报技巧越高。此外,分析S2S各模式MJO预报技巧对起报时间、季节和起报时MJO信号强弱的敏感性发现,当起报时间为冬季且起报时MJO为强信号时,MJO的实际预报技巧较高。     

国内外雾预报技术研究进展

大雾是引起低能见度的主要天气现象.提高雾的预报技术水平是确保交通安全的重要措施.从统计和数值预报两个方面,回顾了过去几十年来国内外在雾预报技术上的主要研究进展,并总结了各种方法的特点及存在的缺陷.在某些情形下,新统计方法的应用提高了雾的预报准确率,但仍然无法摆脱统计方法本身的缺陷.相比较而言,数值模式在大雾预报方面具有更广泛的应用和更大的潜力.在目前的计算机水平下,使用高分辨率的一维雾模式与中尺度天气模式相结合的方法,在一定程度上可以提高雾的预报准确率,该方法在大雾易发区的机场及高速公路沿线具有重要的应用价值.随着计算机能力的不断提高,包含大雾形成和演变的各种复杂过程、具有先进资料同化过程的高分辨率三维雾模式,以及集合数值预报系统将是未来的发展方向.     

四个耦合模式ENSO后报试验的“春季预报障碍”

用CliPAS计划中3个气候模式和中国科学院大气物理研究所耦合模式FGOALS-g短期气候异常回报试验结果,将动力和统计方法相结合,考察了1982—2003年厄尔尼诺/拉尼娜事件发展期和衰减期海表温度春季可预报性障碍现象。结果表明,所考察的耦合模式对ENSO事件预报的误差发展存在明显的季节依赖性,最大误差增长通常发生在春季,发生显著的可预报性障碍现象。进一步分析发现厄尔尼诺事件和拉尼娜事件在发展期的季节预报障碍现象比衰减期明显,以厄尔尼诺事件发展期春季可预报性障碍现象最为显著,拉尼娜事件衰减期季节预报障碍现象不显著。研究还发现,预报误差的增长在ENSO事件冷暖位相具有显著的非对称性,发展期暖位相预报误差强于冷位相,而衰减期冷位相的预报误差比暖位相大。通过回归分析,诊断了海-气相互作用的强度,发现耦合系统在春季最不稳定,使预报误差最易在春季发展,从而导致可预报性障碍。     

The most predictable patterns and prediction skills of subseasonal prediction of rainfall over the Indo-Pacific regions by the NCEP Climate Forecast System

Climate Dynamics - The most predictable patterns and prediction skills of subseasonal rainfall prediction for the Indo-Pacific regions are investigated using the daily hindcast product of the NCEP...     

Application of statistical techniques to the analysis and prediction of ENSO: Bayesian oscillation patterns as a prediction scheme

Here we study the low-frequency variability of the tropical Indian and Pacific basins with a new statistical technique, Bayesian oscillation patterns (BOP). To describe the climatic system in this region, zonal wind and sea surface temperature (SST) are the selected variables. Their variability can be explained in terms of a reduced number of frequencies and spatial patterns. These are identified for each field by a statistical procedure. With the help of the patterns and the frequencies a predictive scheme is devised and applied in two forecast experiments. In the first, zonal wind anomalies are predicted using patterns and frequencies identified in the wind field. A more sophisticated scheme, a linear model which includes non-harmonic oscillations and interactions between patterns, is used when forecasting SST seasonal anomalies in the Niño3 region. In this case, the predictors include the values of the frequencies identified in the BOP analysis of both wind and SST fields, and thecorresponding patterns.     

A maritime boundary-layer model for the prediction of fog

A two-dimensional boundary-layer model is described. The model is designed to predict and study the effects of meteorological changes on the formation and dissipation of fog and stratus. Radiational heat loss along with the transport of static energy, moisture and momentum are treated. Cloud droplet distributions are parameterized using a gamma distribution from which radiative properties and droplet fall velocities are computed. Turbulent exchange coefficients are calculated using the Monin-Obukhov theory of similitude which accounts for variations in atmospheric stability. Although the boundary-layer depth depends only on turbulent intensity during stable atmospheric conditions, its growth during unstable conditions is determined from the capping inversion's intensity and the amount of turbulence generated at the surface.Several experiments are presented which demonstrate the effects of various meteorological parameters on the formation and duration of stratus and fog. Energy-budget analyses show the importance of each of the physical processes being modeled.Although not new, radiative transfer processes are shown to be extremely important in the transfer of heat from the boundary layer and in the process of fog formation. Fog formation location is highly sensitive to the moisture content upstream, whereas changes in wind speed had much less effect in the variance of fog location.Numerical experiments with other processes such as back radiation from the atmosphere, haze and cloud droplet population, are described and shown to have smaller effects.     

A radiative-conductive model for the prediction of radiation fog

A conductive-radiative model is used to predict the formation and growth of radiation fog. This is accomplished by solving numerically the heat and mass transport equations in conjunction with an approximate form of the radiative transfer equation. The equations of motion in simplified form are included in the physical system to make use of Blackadar's (1962) formulation of the exchange coefficient of the boundary layer.It is found for a number of hypothetical test cases that the model gives results which appear to represent real physical conditions. One actual situation is tested. Results show that the model reproduces better than qualitatively those parameters which are obtained from routine observations.     

太平洋年代际振荡的年代际预测方法

太平洋年代际振荡（PDO）是北太平洋海表温度年代际变率的主模态。由于太平洋年代际振荡对区域乃至全球气候的显著影响,其合理的预测结果可以带来多方面收益。然而,针对太平洋年代际振荡及其有关的海表温度的年代际预测,目前气候模式的预测水平还十分有限,因此,提出了一个新的增量方法。一系列的验证结果表明,增量方法可以有效预测太平洋年代际振荡,其中包括成功预测出其振荡的年代际转折。增量方法的预测过程主要包括3个步骤:（1）采用5 a滑动平均得到太平洋年代际振荡的年代际变率;（2）利用3 a增量形式的预测因子构建预测模型,预测3 a增量的太平洋年代际振荡（DI_PDO）;（3）将预测得到的DI_PDO加上3 a前的观测PDO,得到最后预测的PDO。增量方法亦可以应用到气候系统年代际内部变率的其他模态（如:北大西洋年代际振荡）和其他气候变量的年代际预测（如:海表温度）。