利用局地分析和预报系统LAPS（Local Analysis and Prediction System）和多时空尺度分析系统STMAS（Space-Time Multiscale Analysis System）对北京、 华北和中国3个不同区域的区域自动站观测资料和全球预报系统GFS（Global Forecast System）背景场资料，在1，5，10和20 km等4种分辨率的网格上进行融合试验，从算法的角度对比分析LAPS和STMAS在融合效果上的差异，并利用国家级自动站数据对LAPS和STMAS一年内逐时融合结果进行独立性检验。结果表明，在东部观测密集区，LAPS和STMAS都有不错的表现，STMAS能够解析出观测中细小的特征，融合结果更接近实际观测，相对而言LAPS则平滑作用明显，容易损失观测信息；在资料稀疏地区，STMAS的优势更为明显，由粗网格到细网格逐层分尺度进行分析，使粗网格尺度的误差得到快速修正，避免不同尺度观测信息的混淆，青藏高原等地区的融合结果得到有效改善。此外，地形高度调整的不合理性对LAPS、 STMAS在山区的融合效果有所影响。
To test fusion effects of LAPS (Local Analysis and Prediction System) and STMAS (Space-Time Multiscale Analysis System) system at different spatial scales, different resolution conditions on the surface temperature, LAPS and STMAS fusion test were performedin Beijing, North China and the Country 3 different areas, using the regional automatic weather station observations and GFS (Global Forecast System) background information on 1, 5, 10 and 20 km four kinds of grid resolution, the differences of LAPS and STMAS fusion effect was analyzed from algorithm angle, and a year of hourly fusion analysis results by LAPS and STMAS was statistical analyzed using the national automatic station data. The results showed that: LAPS and STMAS both havegood performance in the observation-intensive areas, STMAS can resolve the small features in the observations, andthe fusion results by STMAS are more closer to the actual observation and that by LAPS relatively smooth obvious, and possibly losing observational information; the confusion of the longwave and shortwave information in data sparse areas can be avoided because of the multi-scale analysis of STMAS that the background field can be corrected more efficiently using observations; in addition, the irrational nature of the terrain height adjustment has affect the fusion effect of LAPS and STMAS in the mountains.
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