Real-time numerical shake prediction and updating for earthquake early warning

Ground motion prediction is important for earthquake early warning systems, because the region＇s peak ground motion indicates the potential disaster. In order to predict the peak ground motion quickly and pre- cisely with limited station wave records, we propose a real- time numerical shake prediction and updating method. Our method first predicts the ground motion based on the ground motion prediction equation after P waves detection of several stations, denoted as the initial prediction. In order to correct the prediction error of the initial prediction, an updating scheme based on real-time simulation of wave propagation is designed. Data assimilation technique is incorporated to predict the distribution of seismic wave energy precisely. Radiative transfer theory and Monte Carlo simulation are used for modeling wave propagation in 2-D space, and the peak ground motion is calculated as quickly as possible. Our method has potential to predict shakemap, making the potential disaster be predicted before the real disaster happens. 2008 Ms8.0 Wenchuan earthquake is studied as an example to show the validity of the proposed method.

The Application of ARGO Data to the Global Ocean Data Assimilation Operational System of NCC

In this paper, we have preliminarily studied the application of ARGO (Arrayfor Real-time Geostrophic Oceanography) data to the Global Ocean Data Assimilation System ofNational Climate Center of China (NCC-GODAS), which mainly contains 4 sub-systems such as datapreprocessing, real-time wind stress calculating, variational analysis and interpolating, and oceandynamic model. For the sake of using ARGO data, the relevant adjustment and improvement have beenmade at the corresponding aspects in the subsystems. Using the observation data from 1981 to 2003including the ARGO data of 2001 to July. 2003, we have performed a series of numerical experimentson this system. Comparing with the corresponding results of NCEP, It is illustrated that using ARGOdata can improve the results of NCC-GODAS in the region of the Middle Pacific, for instance SST,SSTA (SST anomalies), Nino index, sea sub-surface temperature, etc. Furthermore, it is obtained thatNCC-GODAS benefits from ARGO data in the other regions such as Atlantic Ocean, Indian Ocean, andextratropical Pacific Ocean much more than in the tropical Pacific.

Accounting for CO2 Variability over East Asia with a Regional Joint Inversion System and Its Preliminary Evaluation

A regional surface carbon dioxide （C02） flux inversion system, the Tan-Tracker-Region, was developed by incor- porating an assimilation scheme into the Community Multiscale Air Quality （CMAQ） regional chemical transport model to resolve fine-scale CO2 variability over East Asia. The proper orthogonal decomposition-based ensemble four-dimensional variational data assimilation approach （POD-4DVar） is the core algorithm for the joint assimilation framework, and simultaneous assimilations of CO2 concentrations and surface CO2 fluxes are applied to help reduce the uncertainty in initial CO2 concentrations. A persistence dynamical model was developed to describe the evolu- tion of the surface CO2 fluxes and help avoid the ＂signal-to-noise＂ problem; thus, CO2 fluxes could be estimated as a whole at the model grid scale, with better use of observation information. The performance of the regional inversion system was evaluated through a group of single-observation-based observing system simulation experiments （OSSEs）. The results of the experiments suggest that a reliable performance of Tan-Tracker-Region is dependent on certain assimilation parameter choices, for example, an optimized window length of approximately 3 h, an ensemble size of approximately 100, and a covariance localization radius of approximately 320 km. This is probably due to the strong diurnal variation and spatial heterogeneity in the fine-scale CMAQ simulation, which could affect the perform- ance of the regional inversion system. In addition, because all observations can be artificially obtained in OSSEs, the performance of Tan-Tracker-Region was further evaluated through different densities of the artificial observation net- work in different CO2 flux situations. The results indicate that more observation sites would be useful to systematic- ally improve the estimation of CO2 concentration and flux in large areas over the model domain. The work presented here forms a foundation for future research in which a thorough estimation of CO2 flux variability over East Asia could be performed with the regional inversion system.