论文

LAPS与STMAS地面气温融合效果对比试验

  • 张涛 ,
  • 苗春生 ,
  • 王新
展开
  • 南京信息工程大学大气科学学院, 南京 210044;2. 国家气象信息中心, 北京 100081;3. 中国气象局华风气象影视信息集团, 北京 100081

收稿日期: 2012-09-25

  网络出版日期: 2014-06-28

基金资助

国家自然科学基金项目(41276033);国家科技支撑项目(2012BAH05B00);公益性行业(气象)科研专项(GYHY20120630)

Comparison Tests of the Integration Effect of Surface Temperature by LAPS and STMAS

  • ZHANG Tao ,
  • MIAO Chunsheng ,
  • WANG Xin
Expand
  • College of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China;2. National Meteorological Information Center, Beijing 100081, China;3. China Meteorological Administration, Huafeng Meteorological Media Group, Beijing 100081, China

Received date: 2012-09-25

  Online published: 2014-06-28

摘要

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。

本文引用格式

张涛 , 苗春生 , 王新 . LAPS与STMAS地面气温融合效果对比试验[J]. 高原气象, 2014 , 33(3) : 743 -752 . DOI: 10.7522/j.issn.1000-0534.2013.00046

Abstract

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.

参考文献

[1]Xie Y, Koch S, McGinley J, et al.A space-time multiscale analysis system: A sequential variational analysis approach[J]. Mon Wea Rev, 2011,139: 1224-1240.
[2]Li W, Xie Y, He Z,et al. Application of the multigrid data assimilation method to the China seas' temperature forecast[J]. J Atmos Ocean Technol, 2008, 25(11): 2106-2116.
[3]He Z, Xie Y, Li W, et al. Application of the sequential three-dimensional variational method to assimilating SST in a global ocean model[J]. J Atmos Ocean Technol, 2008, 25: 1018-1033.
[4]Yuan H, Xie Y, Albers S, et al. Impacts of the STMAS cycling data assimilation system on improving severe weather forecasting[C]. 15<sup>th</sup> Symposium on IOAS-AOLS, Seattle, 2011: J13.2.
[5]Guo Ji J, Shinn-Liang S, John A, et al. Precipitation Simulation Associated with Typhoon Sinlaku (2002) in Taiwan Area Using the LAPS Diabatic Initialization for MM5[J]. Atmos Ocean Sci, 2003, 14: 261-288.
[6]李红莉, 崔春光, 王志斌, 等. 中尺度分析系统LAPS应用雷达资料的个例研究[J]. 高原气象, 2009, 28(6): 1443-1452.
[7]李红莉, 万蓉, 谢有才. 利用LAPS系统同化地基GPS水汽资料的应用研究[J]. 热带气象学报, 2010, 26(6): 702-709.
[8]刘瑞霞, 陈洪滨, 师春香, 等. 多源观测数据在LAPS三维云量场分析中的应用[J]. 应用气象学报, 2011, (1): 123-128.
[9]崔春光, 倪允琪, 李红莉, 等. 中国南方暴雨野外试验中尺度气象分析场的建立及其质量评估[J]. 气象学报, 2011, 69(1): 26-40.
[10]王晓芳, 胡伯威, 李红莉, 等. 梅雨期一个伴有前导层状降水对流线的结构特征[J]. 高原气象, 2011, 30(4): 1052-1066.
[11]王叶红, 赵玉春, 李红莉, 等. AREM模式的热启动数值模拟——以2007年7月13日暴雨过程为例[J]. 高原气象, 2011, 30(6): 1488-1504.
[12]周后福, 郭品文, 翟菁, 等. LAPS分析场资料在暴雨中尺度分析中的应用[J]. 高原气象, 2010, 29(2): 461-470.
[13]彭菊香, 李红莉, 崔春光. 华中区域LAPS中尺度分析场的检验与评估[J]. 气象, 2011, 37(2): 170-176.
[14]向玉春, 杨军, 唐仁茂, 等. LAPS在冰雹云模拟中的应用[J]. 应用气象学报, 2012, 23(3): 331-339.
[15]向玉春, 杨军, 李红莉, 等. LAPS资料在人工影响天气中的应用初探[J]. 暴雨灾害, 2009, (3): 271-276.
[16]Barnes S L. A technique for maximizing details in numerical weather map analysis[J]. J Appl Meteor, 1964, 3: 396-409.
[17]DesJardins M, Kocin P J. An interactive Barnes objective map analysis scheme for use with satellite and conventional data[J]. J Climate Appl Meteor, 1983, 22: 1487-1503.
[18]陶士伟, 仲跻芹, 徐枝芳, 等. 地面自动站资料质量控制方案及应用[J]. 高原气象, 2009, 28(5): 1202-1209.
[19]任芝花, 熊安元. 地面自动站观测资料三级质量控制业务系统的研制[J]. 气象, 2007, 33(1): 19-24.
[20]李新, 程国栋, 卢玲. 青藏高原气温分布的空间插值方法比较[J]. 高原气象, 2003, 22(6): 565-573.
文章导航

/