东北地区中尺度对流复合体的卫星云图特征

通过１０年（１９８３－１９９２年）卫星云图资料的分析，综合归纳了东北地区中尺度对流复合体（ＮＭＣＣ）的基本特征及其发展演变过程，由于受地理条件的影响，ＮＭＣＣ与美国大平原以及我国西北和华北平原上的ＭＣＣ有明显差别，作为一类特殊的对流性天气系统，ＮＭＣＣ与一般中尺度对流云图特征有明显差异。     

我国南方地区的中尺度对流复合体

根据日本GMS资料和部分常规资料，对我国南方地区春末夏初的10个中尺度对流复合体(MCCs)做了分析。它们的基本特征与美国MCC相近。它们主要活动在夜间，一般在山地背风一侧斜坡上或坡底附近形成;并在对流层中低层中低纬度地区几个天气系统的迭加处获得发展;向东偏南方向移动，与700～500 hPa之间的平均气流方向大体一致，冷云罩面积约为1.4×105 km2,比美洲的(2～3×105 km2)略小;持续时间为12小时左右，比美洲的(10小时)稍长。云区形状呈椭圆形，但偏心率≥0.6。云顶最低温度一般在-86℃以下，出现在冷云罩面积达到最大之前4～6小时。     

一个三重嵌套的中尺度模式及暴雨模拟试验

该文介绍了新近发展的一个高分辨率有限区模式(HLAM)。它是通过三重嵌套在现有计算机(CYBER-992)条件下实现的，其范围、地理位置及侧边界宽度均设计为灵活可变，尤其水平分辨率可按任意倍数提高。利用水平分辨率为50km左右的模式版本进行了实际资料的降水个例实验。结果是令人鼓舞的:(1)与嵌套的低分辨率(格距增大4倍)模式预报比较，不论低压中心位置、强降水落区、雨带走向及降水中心位置的预报都更接近实况;(2)高分辨率模式积分区域虽然缩小，但并未影响预报效果，其48小时预报仍有较高精度。初步试验表明，进一步完善和改进后的HLAM完全可以发展为一个用于中尺度研究及业务使用的高分辨率区域模式。     

A CASE OF MESOSCALE CONVECTIVE COMPLEX EVOLVING INTO A VORTEX*

A case of mesoscale convective complex(MCC) which evolved into a vortex is documented in this paper.As the MCC entered into the dissipating phase,a well-defined spirally banded structure became visible in the satellite image.The blackbody temperature(TBB) of the residual cold-cloud-shield indicates the vortex existed in the layer from 400 to 250 hPa.According to the upper air analysis,the upper level vortex was an anticyclone.The MCC-generated vortex was visualized in the satellite images because it was located in the subtropical high where the wind field was very weak.     

Statistics on the sizes and internal structures of rainshowers

A large sample of radar reflectivity data from essentially a full summer of operation was analyzed to determine the horizontal extents and internal structure of rain areas observed at altitude levels from 2 to 10 km. Results are given on the size distributions of individual cells or patches defined by reflectivity thresholds approximately 4 dBz apart, on the dependence of mean size on altitude and reflectivity threshold, and on the interior structure of the patches as characterized by the number and sizes of higher-threshold patches contained in each echo. In a more detailed analysis of internal structure, the data were restricted to convective echoes in which certain prescribed reflectivities, ranging from about 30 to 50 dBz, were exceeded. It was found that the dependence of mean quantities, such as patch area, on reflectivity and altitude could be approximately described by simple functions, but that the scatter of observations about the mean was usually large.     

A MASCOTTE-based characterization of MCSs over Spain, 2000–2002

A 3-year Mesoscale Convective Systems (MCSs) database, which extends from 2000 to 2002, has been built for the Iberian Peninsula and the Balearic Islands using the objective method MASCOTTE (MAximum Spatial COrrelation Technique). It was originally developed to track the evolution of convective systems over the Amazon region; after modifications, it is able to track MCS evolution even with an hour and a half of missed images and provides essential information of both dynamical and morphological characteristics of MCSs. MASCOTTE is tested against a visual and subjective method, and is found to offer advantages such as automation and a simple and efficient operation that make it very useful for building large MCS databases.Thirty-five MCSs were found between June and October, most of them originated along the Mediterranean coast and near the Pyrenees, showing an increasing occurrence from June to September, when the maximum is found. The regions most influenced by MCS occurrences are Balearic Islands, Valencia, Catalonia, Murcia and the Basque Country. The MCSs tend to be small, short-lived and linear, usually moving eastward or northeastward with low velocities.The MCSs-associated precipitation presents high variability, ranging from 80 to 0 mm h⁻¹ as maximum hourly records. Two different convective regions are identified based on MCS behavior in extreme precipitation events: Northern Spain (the Basque Country) with abundant and continuous precipitation regime but little MCS influence, and the Mediterranean coast, where precipitation is sporadic but much more intense.     

Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5

The identification of the model discrepancy and skill is crucial when a forecast is issued. The characterization of the model errors for different cumulus parameterization schemes (CPSs) provides more confidence on the model outputs and qualifies which CPSs are to be used for better forecasts. Cases of good/bad skill scores can be isolated and clustered into weather systems to identify the atmospheric structures that cause difficulties to the forecasts. The objective of this work is to study the sensitivity of weather forecast, produced using the PSU-NCAR Mesoscale Model version 5 (MM5) during the launch of an Indian satellite on 5th May, 2005, to the way in which convective processes are parameterized in the model. The real-time MM5 simulations were made for providing the weather conditions near the launch station Sriharikota (SHAR). A total of 10 simulations (each of 48 h) for the period 25th April to 04th May, 2005 over the Indian region and surrounding oceans were made using different CPSs. The 24 h and 48 h model predicted wind, temperature and moisture fields for different CPSs, namely the Kuo, Grell, Kain-Fritsch and Betts-Miller, are statistically evaluated by calculating parameters such as mean bias, root-mean-squares error (RMSE), and correlation coefficients by comparison with radiosonde observation. The performance of the different CPSs, in simulating the area of rainfall is evaluated by calculating bias scores (BSs) and equitable threat scores (ETSs). In order to compute BSs and ETSs the model predicted rainfall is compared with Tropical Rainfall Measuring Mission (TRMM) observed rainfall. It was observed that model simulated wind and temperature fields by all the CPSs are in reasonable agreement with that of radiosonde observation. The RMSE of wind speed, temperature and relative humidity do not show significant differences among the four CPSs. Temperature and relative humidity were overestimated by all the CPSs, while wind speed is underestimated, except in the upper levels. The model predicted moisture fields by all CPSs show substantial disagreement when compared with observation. Grell scheme outperforms the other CPSs in simulating wind speed, temperature and relative humidity, particularly in the upper levels, which implies that representing entrainment/detrainment in the cloud column may not necessarily be a beneficial assumption in tropical atmospheres. It is observed that MM5 overestimates the area of light precipitation, while the area of heavy precipitation is underestimated. The least predictive skill shown by Kuo for light and moderate precipitation asserts that this scheme is more suitable for larger grid scale (>30 km). In the predictive skill for the area of light precipitation the Betts-Miller scheme has a clear edge over the other CPSs. The evaluation of the MM5 model for different CPSs conducted during this study is only for a particular synoptic situation. More detailed studies however, are required to assess the forecast skill of the CPSs for different synoptic situations.     

Impact of Doppler Radar Wind in Simulating the Intensity and Propagation of Rainbands Associated with Mesoscale Convective Complexes Using MM5-3DVAR System

Pre-monsoon rainfall around Kolkata (northeastern part of India) is mostly of convective origin as 80% of the seasonal rainfall is produced by Mesoscale Convective Systems (MCS). Accurate prediction of the intensity and structure of these convective cloud clusters becomes challenging, mostly because the convective clouds within these clusters are short lived and the inaccuracy in the models initial state to represent the mesoscale details of the true atmospheric state. Besides the role in observing the internal structure of the precipitating systems, Doppler Weather Radar (DWR) provides an important data source for mesoscale and microscale weather analysis and forecasting. An attempt has been made to initialize the storm-scale numerical model using retrieved wind fields from single Doppler radar. In the present study, Doppler wind velocities from the Kolkata Doppler weather radar are assimilated into a mesoscale model, MM5 model using the three-dimensional variational data assimilation (3DVAR) system for the prediction of intense convective events that occurred during 0600 UTC on 5 May and 0000 UTC on 7 May, 2005. In order to evaluate the impact of the DWR wind data in simulating these severe storms, three experiments were carried out. The results show that assimilation of Doppler radar wind data has a positive impact on the prediction of intensity, organization and propagation of rain bands associated with these mesoscale convective systems. The assimilation system has to be modified further to incorporate the radar reflectivity data so that simulation of the microphysical and thermodynamic structure of these convective storms can be improved.     

广州中尺度模式局地要素预报性能分析

该文简要介绍了华南中尺度模式的地表要素的预报诊断方案, 站点要素时间序列预报情况.用适合站点要素时间序列预报的检验方法, 检验并分析了各要素时间序列预报的性能.表明该中尺度模式的地表要素时间序列预报方案是有效的, 预报具有较高的准确性和应用价值.