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青藏高原周边对流层顶的时空分布、热力成因及动力效应分析 总被引：4，自引：0，他引：4
利用多套、多种再分析资料的逐日气候平均场,通过对比分析,揭示了青藏高原周边区域对流层顶分布及其季节演变的独特特征,并分析了其热力成因以及气候学效应。结果表明,与同纬度的落矶山和太平洋地区相比,青藏高原及伊朗高原区域对流层顶高度的冬夏变化幅度更大。冬季副热带对流层顶断裂带（热带对流层顶与极地对流层顶之间高度剧烈变化的过渡带）位于青藏与伊朗两个高原上空,春季开始两个高原上空对流层顶抬升迅速,夏季最高可超过热带对流层顶的高度（超过100 hPa）,成为同纬度甚至全球对流层顶最高点。青藏与伊朗两个高原上空对流层顶的剧烈抬高,对应两个高原上空大气气柱比同纬度明显偏暖,同时伴随着青藏与伊朗两个高原上空位势涡度值的明显降低。因此,在青藏与伊朗两个高原区域,由春至夏等熵面强烈下凹,同时等位涡面剧烈抬升;夏季时等位涡面及对流层顶断裂带在青藏高原北部成近乎上下垂直分布,与南北倾斜分布的等位温面接近正交分布。这种特征与夏季同纬度其他地区相对平缓的对流层顶断裂带、等位涡面以及等熵面的经向分布形成强烈对比。进一步研究发现,青藏与伊朗两个高原上空由春至夏迅速发展的强大热源是引起上述对流层顶变化特征的主要原因。不同的是,青藏高原上空主要由发展强烈的对流凝结潜热所主导,而伊朗高原上空则主要由绝热下沉加热引起;此外,由春季至夏季,随着青藏高原地区对流层顶与等熵面剧烈相交分布的形成,南亚高压也逐步控制青藏高原上空,在南亚高压东缘盛行的偏北气流作用下,中高纬度平流层的高位涡空气得以在青藏高原东缘及东亚地区沿剧烈倾斜的等熵面被输送到较低纬度的对流层。与降水的季节演变对比可知,平流层高位涡输送的出现、加强和减弱与夏季降水的发展、加强与减弱成同步对应关系。从而证实了青藏高原影响夏季东亚地区形成独特气候格局的事实,说明在这种影响过程中,平流层-对流层动力相互作用过程不可忽视。 相似文献
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The polarimetric radar network in Jiangsu Province has just been operationalized since 2020. The first intense precipitation event observed by this polarimetric radar network and disdrometer occurred during August 28-29, 2020 and caused severe flooding and serious damage in eastern Jiangsu Province. The microphysics and kinetics for this heavy precipitation convective storm is diagnosed in this study, in order to promote the application of this polarimetric radar network. Drop size distribution (DSD) of this event is estimated from measurements of a ground disdrometer, and the corresponding three-dimensional atmospheric microphysical features are obtained from the multiple polarimetric radars. According to features of updraft and lighting, the evolution of the convective storm is divided into four stages: developing, mature with lightning, mature without lightning and dissipating. The DSD of this event is featured by a large number of raindrops and a considerable number of large raindrops. The microphysical characteristics are similar to those of warm-rain process, and ice-phase microphysical processes are active in the mature stages. The composite vertical structure of the convective storm indicates that deep ZDR and KDP columns coincide with strong updrafts during both mature stages. The hierarchical microphysical structure retrieved by the Hydrometeor Identification Algorithm (HID) shows that depositional growth has occurred above the melting level, and aggregation is the most widespread ice-phase process at the -10℃ level or higher. During negative lightning activity, the presence of strongest updrafts and a large amount of ice-phase graupel by riming between the 0℃ and -35℃ layers generate strong negative electric fields within the cloud. These convective storms are typical warm clouds with very high precipitation efficiency, which cause high concentration of raindrops, especially the presence of large raindrops within a short period of time. The ice-phase microphysical processes above the melting layer also play an important role in the triggering and enhancing of precipitation. 相似文献
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利用S波段双偏振雷达数据,结合再分析数据、自动气象站、探空和二维闪电探测数据,采用多普勒雷达风场反演和粒子相态识别等方法,分析了2019年7月17日江苏省东南部多站破历史记录的超强降水对流风暴的偏振特征和云微物理特征;并选取了打破当地强降水历史记录如皋站和潞城站,分析了影响两站的对流单体的异同。影响如皋的对流风暴几无闪电活动,对流质心接近地面,上升气流相对较弱。且0 ℃和-35 ℃层间霰粒子数目相对较少,闪电几乎不存在。在融化层以下,由于强烈的暖雨过程,较大的冰相粒子落下并融化和低层雨滴的聚并增长,导致低层雨滴数量迅速增加,带来地面极端强降水。潞城地区雷暴活动明显,影响其对流风暴发展旺盛。-35~0 ℃层存在强烈的上升运动,抬升低层大量的液相粒子通过淞附作用形成的霰,并与高层冰晶不断碰撞,在云层中形成强大的电场,产生强烈的负闪,且在地面产生了极强的降水。这表明融化层以上的冰相微观物理过程,对于降水的发生和增强非常重要。 相似文献
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Large-scale atmospheric information plays an important role in the regional model for the forecasts of weather such as tropical cyclone (TC). However, it is difficult to be fully represented in regional models due to domain size and a lack of observation data, particularly at sea used in regional data assimilation. Blending analysis has been developed and implemented in regional models to reintroduce large-scale information from global model to regional analysis. Research of the impact of this large-scale blending scheme for the Global / Regional Assimilation and PrEdiction System (CMA-MESO) regional model on TC forecasting is limited and this study attempts to further progress by examining the adaptivity of the blending scheme using the two-dimensional Discrete Cosine Transform (2D-DCT) filter on the model forecast of Typhoon Haima over Shenzhen, China in 2016 and considering various cut-off wavelengths. Results showed that the error of the 24-hour typhoon track forecast can be reduced to less than 25 km by applying the scale-dependent blending scheme, indicating that the blending analysis is effectively able to minimise the large-scale bias for the initial fields. The improvement of the wind forecast is more evident for u-wind component according to the reduced root mean square errors (RMSEs) by comparing the experiments with and without blending analysis. Furthermore, the higher equitable threat score (ETS) provided implications that the precipitation prediction skills were increased in the 24h forecast by improving the representation of the large-scale feature in the CMA-MESO analysis. Furthermore, significant differences of the track error forecast were found by applying the blending analysis with different cut-off wavelengths from 400 km to 1200 km and the track error can be reduced less than by 10 km with 400 km cut-off wavelength in the first 6h forecast. It highlighted that the blending scheme with dynamic cut-off wavelengths adapted to the development of different TC systems is necessary in order to optimally introduce and ingest the large-scale information from global model to the regional model for improving the TC forecast. In this paper, the methods and data applied in this study will be firstly introduced, before discussion of the results regarding the performance of the blending analysis and its impacts on the wind and precipitation forecast correspondingly, followed by the discussion of the effects of different blending scheme on TC forecasts and the conclusion section. 相似文献
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