DIAGNOSTIC ANALYSIS AND VERIFICATION OF PREDICTION OF THE TROPICAL PACIFIC SEA SURFACE TEMPERATURE ANOMALIES DURING 1997 ~ 1998

By comparing with ENSO events that ever happened in the history, the basic features and probable causes of the anomalous sea surface temperature of the tropical Pacific Ocean during 1997 and 1998 have been analyzed diagnostically. It is found that the 1997/1998 El Nino had significant abnormalities and peculiarities. It differs from the previous El Ni?o events falling into the simple “eastern pattern” or “western pattern”. The predictions of 1997/1998 El Ni?o event have also been tested with an intermediate ocean-atmosphere coupled dynamic model. The results show that the skills of the 0～24 lead month forecasts for the warm event are all above 0.5. The predictions of the mature phase and the later stages of the warm event are better than those of the beginning phase.     

Assessing spatial and attribute errors in large national datasets for population distribution models: a case study of Philadelphia county schools

Geospatial technologies and digital data have developed and disseminated rapidly in conjunction with increasing computing efficiency and Internet availability. The ability to store and transmit large datasets has encouraged the development of national infrastructure datasets in geospatial formats. National datasets are used by numerous agencies for analysis and modeling purposes because these datasets are standardized and considered to be of acceptable accuracy for national scale applications. At Oak Ridge National Laboratory a population model has been developed that incorporates national schools data as one of the model inputs. This paper evaluates spatial and attribute inaccuracies present within two national school datasets, Tele Atlas North America and National Center of Education Statistics (NCES). Schools are an important component of the population model, because they are spatially dense clusters of vulnerable populations. It is therefore essential to validate the quality of school input data. Schools were also chosen since a validated schools dataset was produced in geospatial format for Philadelphia County; thereby enabling a comparison between a local dataset and the national datasets. Analyses found the national datasets are not standardized and incomplete, containing 76 to 90 percent of existing schools. The temporal accuracy of updating annual enrollment values resulted in 89 percent inaccuracy for 2003. Spatial rectification was required for 87 percent of NCES points, of which 58 percent of the errors were attributed to the geocoding process. Lastly, it was found that by combining the two national datasets, the resultant dataset provided a more useful and accurate solution.     

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.     

A One-dimensional Ensemble Forecast and Assimilation System for Fog Prediction

A probabilistic fog forecast system was designed based on two high resolution numerical 1-D models called COBEL and PAFOG. The 1-D models are coupled to several 3-D numerical weather prediction models and thus are able to consider the effects of advection. To deal with the large uncertainty inherent to fog forecasts, a whole ensemble of 1-D runs is computed using the two different numerical models and a set of different initial conditions in combination with distinct boundary conditions. Initial conditions are obtained from variational data assimilation, which optimally combines observations with a first guess taken from operational 3-D models. The design of the ensemble scheme computes members that should fairly well represent the uncertainty of the current meteorological regime. Verification for an entire fog season reveals the importance of advection in complex terrain. The skill of 1-D fog forecasts is significantly improved if advection is considered. Thus the probabilistic forecast system has the potential to support the forecaster and therefore to provide more accurate fog forecasts.     

2001年兰州地区春季沙尘暴天气的对比分析

2 0 0 1年 4月 ,兰州地区连续出现了两次区域性强沙尘暴天气。文中从天气概况、气候背景、地面和高空环流形势等方面 ,对两次沙尘暴天气进行了分析。结果表明 ,两次沙尘暴天气过程是在同样的大尺度环流背景下产生的 ,都是由冷锋后偏北大风引起的。但由于造成两次沙尘暴天气的冷空气强度、锋区南压程度、冷空气移动路径等不同 ,因此造成两次沙尘暴天气影响范围、强度也有所不同。同时 ,兰州地区 2 0 0 1年冬季气温异常偏高 ,春季降水偏少以及本地区特殊的地理、地形环境 ,加剧了大风、沙尘暴的出现频次和强度。通过分析 ,初步总结出了此类天气的预报思路和要点。     

光学测微器的原理、检定及误差分析

着重讨论了高精度光学测微器的基本工作原理、检定方法及误差分析。     

1997/1998年热带太平洋海温异常的诊断分析与预报检验

通过与历史上已发生的ENSO事件的比较，对1997－1998年热带太平洋海温异常的基本特征和可能成因进行了诊断分析，发现1997／1998年E1Nino事件具有显著的异常性和独特性，不同于以往单纯的东部型或西部型E1Nino。对用一个简化海气耦合动力学模式做1998／1998年E1Nino事件的预报进行检验。结果表明该模式对这次暖事件超前0－24个月的预报技巧均在0．5以上，模式对暖事件的成熟位相及以后阶段的预报比对暖事件的开始阶段预报得好。     

黄沙坪矿田的综合找矿模式及其在隐伏矿床预测中的应用

黄沙坪矿田的综合找矿模式可概括为已知黄沙坪铅锌矿床成矿模式、地质地球化学及地球物理找矿标志以及最优找矿方法。黄沙坪铅锌矿床成矿母岩与中酸性高侵位岩体有关,倒转背斜轴部及其纵横断裂交汇处控制矿床,走向逆冲断裂带、间层断裂或虚脱带、岩体侵入接触带等控制矿体;矿床范围内有重力、磁力、电性、放射性等异常,出现成矿元素及重矿物指示标志;探查岩体(探岩)、圈定远景区(圈区)找矿床赋存部位(找位)、寻工业矿体(寻体)是最优找矿方法。此综合找矿模式在隐伏矿床预测中的应用经钻探验证取得了积极效果。     

A Synoptic Climatology of Severe Storms in Virginia*

A synoptic climatology is developed for Virginia using 21 years of late spring and summer surface and upper air observations. The climatology is produced by applying a combination of principal components analysis and cluster analysis such that each day is classified into one of a distinct number of synoptic situations. Days on which at least one severe storm occurred in Virginia are merged with the synoptic climatology. A majority of severe storms are associated with one synoptic situation distinguished by moderate instability and a high moisture content.     

上海热浪与健康监测预警系统

用1989～1998年上海逐日4次气象观测资料,应用美国特拉华大学的SSC天气分类方法确定逐日天气类型,形成了10年逐日天气类型日历。并通过天气类型与死亡率的对比分析,确定MT+类型是上海地区形成热浪的“侵人型”气团,是具有最高死亡率的天气类型。采用逐步回归方法建立了MT+类型下因受热浪侵袭而超正常死亡数的回归方程。在此基础上建立了上海热浪与健康监测预警系统。通过1999年气象和死亡实况资料检验,系统对热浪及因此引起的死亡具有较好的监测和预警效果。