Observation system simulation experiments using an ensemble-based method in the northeastern South China Sea

An ensemble-based method for the observation system simulation experiment(OSSE)is employed to design optimal observation stations and assess the present observation stations in the northeastern South China Sea(SCS).We employed the 20-year(1992-2012)sea surface height(SSH)data to design an array to monitor the intraseasonal to interannual variability.The results show that the most key region was found located at the northwest of Luzon Island(LI)where the energetic Luzon cyclonic gyre(LCG)occurs;other key regions include the edge of the LCG,the northwest of the Luzon Strait(LS),and the southwest of Taiwan,China.By contrast,we found that the present observation stations might oversample at the northwest of the LS and undersample at the northwest of LI.In addition,the optimal stations perform better in a larger area than the present stations.In vertical direction,the key layer is located within the upper 200-m depth,of which the surface and subsurface layers are most valuable to the observing system.

Objective array design for three-dimensional temperature and salinity observation:Application to the South China Sea

In this study,a moored array optimization tool(MAOT)was developed and applied to the South China Sea(SCS)with a focus on three-dimensional temperature and salinity observations.Application of the MAOT involves two steps:(1)deriving a set of optimal arrays that are independent of each other for different variables at different depths based on an empirical orthogonal function method,and(2)consolidating these arrays using a K-center clustering algorithm.Compared with the assumed initial array consisting of 17 mooring sites located on a 3°×3°horizontal grid,the consolidated array improved the observing ability for three-dimensional temperature and salinity in the SCS with optimization efficiencies of 19.03%and 21.38%,respectively.Experiments with an increased number of moored sites showed that the most cost-effective option is a total of 20 moorings,improving the observing ability with optimization efficiencies up to 26.54%for temperature and 27.25%for salinity.The design of an objective array relies on the ocean phenomenon of interest and its spatial and temporal scales.In this study,we focus on basin-scale variations in temperature and salinity in the SCS,and thus our consolidated array may not well resolve mesoscale processes.The MAOT can be extended to include other variables and multi-scale variability and can be applied to other regions.

An Economical Approach to Four-dimensional Variational Data Assimilation

Four-dimensional variational data assimilation （4DVar） is one of the most promising methods to provide optimal analysis for numerical weather prediction （NWP）. Five national NWP centers in the world have successfully applied 4DVar methods in their global NWPs, thanks to the increment method and adjoint technique. However, the application of 4DVar is still limited by the computer resources available at many NWP centers and research institutes. It is essential, therefore, to further reduce the computational cost of 4DVar. Here, an economical approach to implement 4DVar is proposed, using the technique of dimension- reduced projection （DRP）, which is called ＂DRP-4DVar.＂ The proposed approach is based on dimension reduction using an ensemble of historical samples to define a subspace. It directly obtains an optimal solution in the reduced space by fitting observations with historical time series generated by the model to form consistent forecast states, and therefore does not require implementation of the adjoint of tangent linear approximation. To evaluate the performance of the DRP-4DVar on assimilating different types of mesoscale observations, some observing system simulation experiments are conducted using MM5 and a comparison is made between adjoint-based 4DVar and DRP-4DVar using a 6-hour assimilation window.

The Sensitive Regions Identified by CNOPs of Three Typhoon Events

In this paper, several sets of observing system simulation experiments (OSSEs) were designed for three typhoon cases to determine whether or not the additional observation data in the sensitive regions identified by conditional nonlinear optimal perturbations (CNOPs) could improve the short-range forecast of typhoons. The results show that the CNOPs capture the sensitive regions for typhoon forecasts, which implies that conducting additional observation in these specific regions and eliminating initial errors could reduce forecast errors. It is inferred from the results that dropping sondes in the CNOP sensitive regions could lead to improvements in typhoon forecasts.

Distributed cooperative task planning algorithm for multiple satellites in delayed communication environment

Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph（DAG）. Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process（DEC-POMDP）. After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.

A Fast Algorithm for Solving CNOP and Associated Target Observation Tests

Conditional Nonlinear Optimal Perturbation （CNOP） is a new method proposed by Mu et al. in 2003, which generalizes the linear singular vector （LSV） to include nonlinearity. It has become a powerful tool for studying predictability and sensitivity among other issues in nonlinear systems. This is because the CNOP is able to represent, while the LSV is unable to deal with, the fastest developing perturbation in a nonlinear system. The wide application of this new method, however, has been limited due to its large computational cost related to the use of an adjoint technique. In order to greatly reduce the computational cost, we hereby propose a fast algorithm for solving the CNOP based on the empirical orthogonal function （EOF）. The algorithm is tested in target observation experiments of Typhoon Matsa using the Global/Regional Assimilation and PrEdiction System （GRAPES）, an operational regional forecast model of China. The effectivity and feasibility of the algorithm to determine the sensitivity （target） area is evaluated through two observing system simulation experiments （OSSEs）. The results, as expected, show that the energy of the CNOP solved by the new algorithm develops quickly and nonlinearly. The sensitivity area is effectively identified with the CNOP from the new algorithm, using 24 h as the prediction time window. The 24-h accumulated rainfall prediction errors （ARPEs） in the verification region are reduced significantly compared with the ＂true state,＂ when the initial conditions （ICs） in the sensitivity area are replaced with the ＂observations.＂ The decrease of the ARPEs can be achieved for even longer prediction times （e.g., 72 h）. Further analyses reveal that the decrease of the 24-h ARPEs in the verification region is attributable to improved simulations of the typhoon＇s initial warm-core, upper level relative vorticity, water vapor conditions, etc., as a result of the updated ICs in the sensitivity area.

An Observational and Numerical Study on the Topographic Influence on Dust Transport in East Asia

Based on observations and numerical simulations, the topographic impacts on dust transport in East Asia were studied. Two regions frequently attacked by dust storms have been confirmed： one is the western part of Inner Mongolia and the southern Mongolia （namely the Mongolia Plateau）, and the other is the Tarim Basin. The most frequent dust storm occurrence area within the first region appears in its hinterland while that of the second one lies in its southern boundary. Moreover, the region from the northeastern edge of the Tibetan Plateau （TP） to the Loess Plateau is attacked by dust storms second frequently. The dust storms frequently occurring over the Mongolia Plateau axe related not only to the abundant sand and dust sources, but also to the special topographic conditions of East Asia. The most significant factor that influences the dust storms forming in the hinterland of the Mongolia Plateau is the canyon low level jet （CLLJ）, which dominates around the southern areas of the Altay-Sayan Mountains with an east-west direction in the beginning of its formation, and is accompanied by significantly enhanced surface wind afterwards. Due to the obstructive effects of the CLLJ, a lot of dust particles carried by the southward down-slope cold air mass would pile up over the southern slope of the Sayan Mountains. Meanwhile, uneven surface conditions are favorable for the dust particles to go up into the upper atmosphere. With the dust particles piling up continuously, a dust layer is formed in the troposphere and can be recognized as a ＇!dust accumulating container＂, which provides abundant dust particles to be transported later to the downstream areas. Additionally, the topographic features of East Asia also exert a great influence on dust transport. Generally, the easterly CLLJ enhances the easterly dust transport. The down-slope air current over the southern Sayan Mountains and the air flow surrounding the TP near its northeastern edge enhance the southward dust transport. Lastly, weather system influences are also examined. The weathers associated with cold fronts frequently appear over the areas of Mongolia and North China in springtime. The cold front system, in general, carries the sand and dust southwards. Among all topographic influencing elements, the rounding effect of the TP is the strongest. Under the combined influences of the cold front and the rounding effect of topography, most sand and dust particles are transported and then deposited over the Loess Plateau.