数值天气预报中分析同化基本方法的历史发展脉络和评述

数值天气预报中分析同化的基本方法先后经历了多项式函数拟合方法、逐步订正方法、最优插值方法、变分方法和集合卡尔曼滤波方法。本文首先根据相关的经典文献力求本色地介绍这些方法的基本思想和实施的具体要点;然后,着重于它们的上下承接关系,试图阐述同化的历史发展脉络,评述这些方法的显著特征和创新性,以期清晰地理解资料同化的循序渐进的内在发展逻辑。此外,从起源上阐明“主观分析”与“客观分析”、“初猜场”与“背景场”、“分析”与“同化”、以及“更新”、“新息”等基本概念,以期准确地理解和把握“大气资料同化”的由来和内涵。     

A Spatiotemporal Interactive Processing Bias Correction Method for Operational Ocean Wave Forecasts

Numerical models and correct predictions are important for marine forecasting,but the forecasting results are often unable to satisfy the requirements of operational wave forecasting.Because bias between the predictions of numerical models and the actual sea state has been observed,predictions can only be released after correction by forecasters.This paper proposes a spati-otemporal interactive processing bias correction method to correct numerical prediction fields applied to the production and release of operational ocean wave forecasting products.The proposed method combines the advantages of numerical models and Forecast Discussion;specifically,it integrates subjective and objective information to achieve interactive spatiotemporal correc-tions for numerical prediction.The method corrects the single-time numerical prediction field in space by spatial interpolation and sub-zone numerical analyses using numerical model grid data in combination with real-time observations and the artificial judg-ment of forecasters to achieve numerical prediction accuracy.The difference between the original numerical prediction field and the spatial correction field is interpolated to an adjacent time series by successive correction analysis,thereby achieving highly efficient correction for multi-time forecasting fields.In this paper,the significant wave height forecasts from the European Centre for Medium-Range Weather Forecasts are used as background field for forecasting correction and analysis.Results indicate that the proposed method has good application potential for the bias correction of numerical predictions under different sea states.The method takes into account spatial correlations for the numerical prediction field and the time series development of the numerical model to correct numerical predictions efficiently.     

离散时滞双线性系统的近似最优控制

研究具有二次型性能指标的离散时滞双线性系统最优控制问题。对既带有时间超前项又带有时间滞后项的非线性两点边值(TPBV)问题,通过逐次逼近算法(SAA)构造不含超前滞后项的线性非齐次TPBV问题迭代序列。最优控制律由精确的线性反馈项和非线性时滞补偿序列的极限项组成。取补偿项序列的有限次迭代值,获得次优控制律。通过仿真,验证算法的有效性。     

海洋水团的Fisher型逐步判别预报

判别分析是多元分析方法之一,我们将其应用于海洋水团的判别预报。用逐步判别的方法挑选因子,依每个因子的Wilks量进行F—检验,逐步地将判别“能力”强的因子选入。同时将由于其他因子组合而相形见绌者及时剔除。根据矩阵变换的信息,给出了Fisher型逐步判别预报式。将北黄海冷水团强度预报作为示例,给出了筛选因子及建立判别式的全过程。用历史资料检验了预报效果。与习用的Bayes型逐步判别预报进行了对比。     

Extreme Cold Events in North America and Eurasia in November-December 2022: A Potential Vorticity Gradient Perspective

From 17 November to 27 December 2022, extremely cold snowstorms frequently swept across North America and Eurasia. Diagnostic analysis reveals that these extreme cold events were closely related to the establishment of blocking circulations. Alaska Blocking(AB) and subsequent Ural Blocking(UB) episodes are linked to the phase transition of the North Atlantic Oscillation(NAO) and represent the main atmospheric regimes in the Northern Hemisphere. The downstream dispersion and propagation of Rossby...     

INITIATION MECHANISMS FOR A SUCCESSIVE MJO EVENT AND A PRIMARY MJO EVENT DURING BOREAL WINTER OF 2000-2001

Observed outgoing longwave radiation (OLR) and ERA-Interim reanalysis data were analyzed to reveal the initiation processes associated with a successive and a primary MJO event during 2000-2001. It was found that the initiation of the successive event was caused by anomalous ascending motion induced by low-level horizontal temperature advection. The anomalous ascending motion, together with horizontal moisture advection, moistened lower troposphere and led to an unstable stratification and triggered convection. The initiation of the primary MJO event, on the other hand, was caused by the accumulation of anomalous moisture associated with three low-frequency modes, a convectively coupled Kelvin wave (CCKW), an westward-propagating equatorial Rossby wave (ER) and a weak planetary-scale MJO mode. It is the merging of the low-level specific humidity anomalies of the three modes that led to the rapid setup of large-scale convectively unstable stratification and favored the development of the eastward-propagating planetary-scale MJO mode.     

THREE-DIMENSIONAL DYNAMIC RESPONSE OF LINED TUNNELS DUE TO INCIDENT SEISMIC WAVES

Formulae are developed to determine the three-dimensional response of twin lined tunnels buried in an infinite medium subjected to seismic loadings using the method of successive reflection. The convergence of the method has been demonstrated both analytically and numerically. The dynamic interaction of the twin tunnels subjected to seismic waves is investigated numerically. It is found that the three-dimensional response of twin tunnels may differ significantly from the two-dimensional response, and that through-soil interaction between the tunnels may also be significant.     

Construction of surface wind stress fields with high temporal resolution using ERS-1 scatterometer data

Wind stress fields with high temporal resolution over the North Pacific have been constructured by using ERS-1 scatterometer data. A simple objective analysis, a successive correction method, was used to construct the fields. Several necessary parameters used in the method are examined by a simulation based on the climatological data. The meridional decorrelation scale of the wind stress depends strongly on the season, while the zonal decorrelation scale is highly stable. We determined the decorrelation scale depending on the location and the time and applied to the successive correction method. The monthly mean field constructed by averaging the daily mean data is free from an aliasing error, which is a serious problem if a simple monthly averaging is applied. The daily wind stress data obtained in the present study represent small time- and spatial-scale variation and large amplitudes compared with data interpolated from simple monthly mean data. The satellite-derived data are also compared with in situ data obtained by meteorological buoys. The satellite wind speeds are lower than in situ wind speeds for every buoy. This underestimation is not due to the present objective analysis, but due to the original data, the ERS-1 Scatterometer Value-Added Product.     

Stochastic inversion of pneumatic cross-hole tests and barometric pressure fluctuations in heterogeneous unsaturated formations

The distributions of permeability and porosity are key factors that control airflow and gas phase transport in unsaturated formations. To understand the behavior of flow and transport in such formations, characterization procedure is a typical approach that has been widely applied to laboratories and fields. As is recognized by most investigations, this approach relies on accurate measurements, and more importantly, an adequate tool to interpret those measurements from experiments. This study presents a pneumatic inverse model that is capable to estimate the distributions of permeability (k) and porosity () with high resolution in heterogeneous unsaturated formations. Based on the concept of sequential successive linear estimator (SSLE), the developed model accounts for compressibility and density of air and estimates the geologic parameters using air pressure measurements from sequential cross-hole pneumatic pumping or injection tests. Four synthetic examples, including a one-dimensional well-posed, a horizontally two-dimensional, and two three-dimensional problems, are used to evaluate the developed model in estimating the distributions of permeability and porosity in unsaturated formations. Results of the numerical experiments are promising. The developed pneumatic inverse model can reconstruct the property (i.e., permeability and porosity) fields if the well-defined conditions are met. With a relatively small number of available measurements, the proposed model can accurately capture the patterns and the magnitudes of estimated properties for unsaturated formations. Results of two complex three-dimensional examples show that the proposed model can map the fracture connectivity using a small number of subsurface pressure measurements and estimate k and in shallow soil layers using spatial variations of barometric pressure.     

Sequential kriging and cokriging: Two powerful geostatistical approaches

A sequential linear estimator is developed in this study to progressively incorporate new or different spatial data sets into the estimation. It begins with a classical linear estimator (i.e., kriging or cokriging) to estimate means conditioned to a given observed data set. When an additional data set becomes available, the sequential estimator improves the previous estimate by using linearly weighted sums of differences between the new data set and previous estimates at sample locations. Like the classical linear estimator, the weights used in the sequential linear estimator are derived from a system of equations that contains covariances and cross-covariances between sample locations and the location where the estimate is to be made. However, the covariances and cross-covariances are conditioned upon the previous data sets. The sequential estimator is shown to produce the best, unbiased linear estimate, and to provide the same estimates and variances as classic simple kriging or cokriging with the simultaneous use of the entire data set. However, by using data sets sequentially, this new algorithm alleviates numerical difficulties associated with the classical kriging or cokriging techniques when a large amount of data are used. It also provides a new way to incorporate additional information into a previous estimation.