Retrieving atmospheric temperature profiles from AMSU-A data with neural networks

Back propagation neural networks are used to retrieve atmospheric temperature profiles from NOAA-16 Advanced Microwave Sounding Unit-A (AMSU-A) measurements over East Asia. The collocated radiosonde observation and AMSU-A data over land in 2002-2003 are used to train the network, and the data over land in 2004 are used to test the network. A comparison with the multi-linear regression method shows that the neural network retrieval method can significantly improve the results in all weather conditions. When an offset of 0.5 K or a noise level of ±0.2 K is added to all channels simultaneously, the increase in the overall root mean square (RMS) error is less than 0.1 K. Furthermore, an experiment is conducted to investigate the effects of the window channels on the retrieval. The results indicate that the brightness temperatures of window channels can provide significantly useful information on the temperature retrieval near the surface. Additionally, the RMS errors of the profiles retrieved with the trained neural network are compared with the errors from the International Advanced TOVS (ATOVS) Processing Package (IAPP). It is shown that the network-based algorithm can provide much better results in the experiment region and comparable results in other regions. It is also noted that the network can yield remarkably better results than IAPP at the low levels and at about the 250-hPa level in summer skies over ocean. Finally, the network-based retrieval algorithm developed herein is applied in retrieving the temperature anomalies of Typhoon Rananim from AMSU-A data.     

Reductions of PM<Subscript>2.5</Subscript> in Beijing-Tianjin-Hebei urban agglomerations during the 2008 Olympic Games

The Atmospheric Environmental Monitoring Network successfully undertook the task of monitoring the atmospheric quality of Beijing and its surrounding area during the 2008 Olympics.The results of this monitoring show that high concentrations of PM2.5 pollution exhibited a regional pattern during the monitoring period(1 June-30 October 2008).The PM2.5 mass concentrations were 53 μg m 3,66 μg m 3,and 82 μg m 3 at the background site,in Beijing,and in the Beijing-Tianjin-Hebei urban agglomerations,respectively.The PM2.5 levels were lowest during the 2008 Olympic Games(8-24 August):35 μg m 3 at the background site,42 μg m 3 in Beijing and 57 μg m 3 in the region.These levels represent decreases of 49%,48%,and 56%,respectively,compared to the prophase mean concentration before the Olympic Games.Emission control measures contributed 62%-82% of the declines observed in Beijing,and meteorological conditions represented 18%-38%.The concentration of fine particles met the goals set for a "Green Olympics."     

A numerical study of tropospheric ozone in the springtime in East Asia

The Models-3 Community Multi-scale Air Quality modeling system (CMAQ)coupled with the Regional Atmospheric Modeling System (RAMS)is applied to East Asia to study the transport and photochemical transformation of tropospheric ozone in March 1998．The calculated mixing ratios of ozone and carbon monoxide are compared with ground 1evel observations at three remote sites in Japan and it is found that the model reproduces the observed features very well．Examination of several high episodes of ozone and carbon monoxide indicates that these elevated levels are found in association with continental outflow,demonstrating the critical role of the rapid transport of carbon monoxide and other ozone precursors from the continental boundary layer．In comparison with available ozonesonde data,it is found that the model-calculated ozone concentrations are generally in good agreement with the measurements,and the stratospheric contribution to surface ozone mixing ratios is quite limited．     

Inter-Comparison of lO-year Precipitation Simulated by Several RCMs for Asia

In phase Ⅱ of the Regional Climate Model Inter-comparison Project （RMIP） for Asia, the regional climate has been simulated for July 1988 through December 1998 by five regional climate models and one global variable resolution model. Comparison of the 10-year simulated precipitation with the observations was carried out. The results show that most models have the capacity to reproduce the basic spatial pattern of precipitation for Asia, and the main rainbelt can be reproduced by most models, but there are distinctions in the location and the intensity. Most models overestimate the precipitation over most continental regions. Interannual variability of the precipitation can also be basically simulated, while differences exist between various models and the observations. The biases in the stream field are important reasons behind the simulation errors of the Regional Climate Models （RCMs）. The cumulus scheme and land surface process have large influences on the precipitation simulation. Generally, the Grell cumulus scheme produces more precipitation than the Kuo scheme.     

人工神经网络方法在鹤壁汛期降水预报中的应用

在用经验统计方法和降水判别函数进行24h和12h晴雨预报的基础上，再用BP人工神经网络建立降水量级预报模型。经2003年汛期试用，预报准确率高于上级指导预报准确率，12h预报准确率高于24h预报准确率。     

SIMULATION OF HEAVY RAINFALL IN THE SUMMER OF 1998 OVER CHINA WITH REGIONAL CLIMATE MODEL

The heavy rainfall in the summer of 1998 over China has been simulated with the NCCRegional Climate Model(RegCM_NCC).It was successful for RegCM_NCC to reproduce thelocation and seasonal shift of the seasonal rain belt in the summer of 1998 over China.The rainyseason in the summer of 1998 over China can be divided into 7 episodes,including the pre-summerrainy season in South China.the Meiyu onset over the Yangtze-Huaihe River Basin,shortappearance of North China rain season and the retreat of seasonal rain belt,the second Meiyuseason over the Yangtze River Valley,the rainy period over the Yellow and Huaihe River Valleyand the seasonal retreat of rain belt over North China.The shortcoming of the RegCM_NCC isover-estimation of precipitation amounts.The regions with large latent heat flux,upper soilmoisture and total runoff are located in the rainy area and move with the simulated rain belt duringthe different episodes.On the contrary,the regions with small sensible heat flux are located in thesimulated rainy area and move with the simulated rain belt during the different episodes.     

多模式集合预报技术及其分析与检验

基于国家气象中心天气预报业务平台,对德国、日本、欧洲中心数值预报模式和我国T213模式的夏季预报产品进行检验,在此基础上,通过不同模式对目标区域预报能力的分析,分别应用神经元网络预报技术和基于Ts评分的客观多模式权重系数法(ME),建立了4个模式的集合预报方法,并应用于2005年汛期业务运行。结果表明:ME对短期降水预报技巧高于简单集合平均,因此具有一定的业务应用前景。     

Implementation of a surface runoff model with Horton and Dunne mechanisms into the regional climate model RegCM_NCC

A surface runoff parameterization scheme that dynamically represents both Horton and Dunne runoff generation mechanisms within a model grid cell together with a consideration of the subgrid-scaie soil heterogeneity, is implemented into the National Climate Center regional climate model （RegCM_NCC）. The effects of the modified surface runoff scheme on RegCMANCC performance are tested with an abnormal heavy rainfall process which occurred in summer 1998. Simulated results show that the model with the original surface runoff scheme （noted as CTL） basically captures the spatial pattern of precipitation, circulation and land surface variables, but generally overestimates rainfall compared to observations. The model with the new surface runoff scheme （noted as NRM） reasonably reproduces the distribution pattern of various variables and effectively diminishes the excessive precipitation in the CTL. The processes involved in the improvement of NRM-simulated rainfall may be as follows： with the new surface runoff scheme, simulated surface runoff is larger, soil moisture and evaporation （latent heat flux） are decreased, the available water into the atmosphere is decreased; correspondingly, the atmosphere is drier and rainfall is decreased through various processes. Therefore, the implementation of the new runoff scheme into the RegCMANCC has a significant effect on results at not only the land surface, but also the overlying atmosphere.     

气象卫星云图的多分辨小波分解及人工神经网络降水估计研究

采用多分辨小波分析对卫星图象进行预处理 ,在保留其特征信息的同时 ,减小了数据量 ,改善了神经网络训练过程的收敛性能 ,提高了处理速度。采用这一方法根据 GOES- 8的红外亮温图象和气象雷达资料对巴西圣保罗州中部的降水量估计进行了试验 ,取得了良好的效果。     

REGIONAL DIFFERENCES OF TEMPORAL-SPATIAL CHARACTERISTICS OF AIR-SEA INTERACTIONS IN TROPICAL OCEANS

The singular value decomposition (SVD) of air-sea interaction in the tropical western,central,and eastern Pacific,and the tropical Atlantic and Indian Oceans has been conducted by using theNCEP/NCAR 40-year reanalysis 1000 hPa monthly wind field and COADS monthly sea surfacetemperature (SST).Comparisons of the results suggest that these areas can be divided into threetypes from the viewpoint of air-sea interaction:tropical central-eastern Pacific belongs to monistictype,in which ENSO is the sole important process;tropical western Pacific and Indian Oceansbelong to dualistic type,in which in addition to ENSO.there should be an another importantprocess;tropical Atlantic Ocean belongs to pluralistic type,in which the process is complicatedand the ENSO cycle is not evident.