ALBERT

Description: In recent years, China has launched YaoGan-13 and GaoFen-3, high-resolution synthetic aperture radar (SAR) satellites that can acquire global high-resolution images. The absolute positioning accuracy of such satellites is important for mapping areas without ground reference points and for automated processing. However, satellites without geometric calibration have poor absolute positioning accuracy, greatly restricting their application (e.g., land resource surveys). Therefore, they cannot meet national demands for high-resolution SAR images with good geometric accuracy. Here, we propose a series of methods to improve the absolute positioning accuracy of YaoGan-13 and GaoFen-3, such as the multiple-image combined calibration strategy and geometric calibration model for a real continuously moving configuration, including consideration of atmospheric propagation delay. Using high-accuracy ground control data collected from different areas, the 2-D and 3-D absolute positioning accuracies of YaoGan-13 and GaoFen-3 were assessed after implementation of the improvement measures. Experimental results showed that, after calibration, the 2-D absolute positioning accuracy of YaoGan-13 and GaoFen-3 are improved from 43.86 m to 2.57 m and from 30.34 m to 4.29 m, respectively. In addition, the 3-D absolute positioning accuracies of YaoGan-13 in plane and elevation are 3.21 m and 2.22 m, respectively. Improving the absolute positioning accuracy of these satellites could broaden the scope of their potential applications in the future.

Description: The Beijing 2008 Olympics Research and Development Project (B08RDP), initiated in 2004 under the World Meteorological Organization (WMO) World Weather Research Programme (WWRP), undertook the research and development of mesoscale ensemble prediction systems (MEPSs) and their application to weather forecast support during the Beijing Olympic Games. Six MEPSs from six countries, representing the state-of-the-art regional EPSs with near-real-time capabilities and emphasizing on the 6–36-h forecast lead times, participated in the project. The background, objectives, and implementation of B08RDP, as well as the six MEPSs, are reviewed. The accomplishments are summarized, which include 1) providing value-added service to the Olympic Games, 2) advancing MEPS-related research, 3) accelerating the transition from research to operations, and 4) training forecasters in utilizing forecast uncertainty products. The B08RDP has fulfilled its research (MEPS development) and demonstration (value-added service) purposes. The research conducted covers the areas of verification, examining the value of MEPS relative to other numerical weather prediction (NWP) systems, combining multimodel or multicenter ensembles, bias correction, ensemble perturbations [initial condition (IC), lateral boundary condition (LBC), land surface IC, and model physics], downscaling, forecast applications, data assimilation, and storm-scale ensemble modeling. Seven scientific issues important to MEPS have been identified. It is recognized that the daily use of forecast uncertainty information by forecasters remains a challenge. Development of forecaster-friendly products and training activities should be a long-term effort and needs to be continuously enhanced. The B08RDP dataset is also a valuable asset to the research community. The experience gained in international collaboration, organization, and implementation of a multination regional EPS for a common goal and to address common scientific issues can be shared by the ongoing projects The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble—Limited Area Models (TIGGE-LAM) and North American Ensemble Forecast System—Limited Area Models (NAEFS-LAM).