排序方式： 共有16条查询结果，搜索用时 18 毫秒
1.
风廓线雷达资料质量控制及其同化应用 总被引：6，自引：0，他引：6
为更好地同化风廓线雷达观测资料开展了相应的质量控制与同化应用研究。针对2013年5月广东地区13部风廓线雷达的观测数据,采用经验正交函数(EOF) 分析方法对其进行质量控制。相比原始观测,经过质量控制的风场提高(降低)了来自时空大(小)尺度的贡献,较好地滤除了小尺度高频脉动,也较好地保留了大尺度平均状态与局地中小尺度系统的共同影响,并且更加接近ECMWF再分析场。此外,还对质量控制后的数据进行了垂直稀疏化。分别计算了质量控制前、后风廓线雷达观测与NCEP 6 h预报场的差值,对比差值的特征发现,经过质量控制的数据的观测增量更好地满足了高斯分布与无偏假设。针对一个实际天气个例,基于GRAPES 3D-Var同化系统,分析了质量控制后的风廓线雷达资料对模式分析与预报的影响。试验表明,在循环同化过程中加入风廓线雷达资料可以更好地描述模式初始场低层风场的特征,从而对强降水的位置与强度做出更好的预报。针对2013年5月的批量试验表明,同化风廓线雷达资料使短期降水预报有明显的改善。 相似文献
2.
This study investigated the impacts of increasing model resolutions and shortening forecast lead times on the quantitative precipitation forecast(QPF) for heavy-rainfall events over south China during the rainy seasons in 2013–2020.The control experiment, where the analysis-forecast cycles run with model resolutions of about 3 km, was compared to a lower-resolution experiment with model resolutions of about 9 km, and a longer-term experiment activated 12 hours earlier. Rainfall forecasting in th... 相似文献
3.
对2009年8月—2012年8月广东省地基GPS反演的可降水量(GPS/PWV)资料进行分析,建立了该资料的质量控制方案。该方案能合理剔除取值不合理的"离群"资料及与背景场偏差较大的资料。选取2010年5月6—7日及2012年4月27—28日两次前汛期降水过程进行数值试验,经过质量控制,只允许与背景场偏差较小的GPS/PWV资料进入GRAPES三维变分同化系统。并对初始湿度场进行合理调整,使数值预报模式的24 h累积降水量的量级和落区的预报得到明显改进,从而提高数值预报模式的降水预报能力。 相似文献
4.
We first analyzed GPS precipitable water vapor (GPS/PWV) available from a ground-based GPS observation network in Guangdong from 1 August 2009 to 27 August 2012 and then developed a method of quality control before GPS/PWV data is assimilated into the GRAPES 3DVAR system. This method can reject the outliers effectively. After establishing the criterion for quality control, we did three numerical experiments to investigate the impact on the precipitation forecast with and without the quality-controlled GPS/PWV data before they are assimilated into the system. In the numerical experiments, two precipitation cases (on 6 to 7 May, 2010 and 27 to 28 April, 2012 respectively) that occurred in the annually first raining season of Guangdong were selected. The results indicated that after quality control, only the GPS/PWV data that deviates little from the NCEP/PWV data can be assimilated into the system, has reasonable adjustment of the initial water vapor above Guangdong, and eventually improves the intensity and location of 24-h precipitation forecast significantly. 相似文献
5.
Nowadays, ensemble forecasting is popular in numerical weather prediction (NWP). However, an ensemble may not produce a perfect Gaussian probability distribution owing to limited members and the fact that some members significantly deviate from the true atmospheric state. Therefore, event samples with small probabilities may downgrade the accuracy of an ensemble forecast. In this study, the evolution of tropical storms (weak typhoon) was investigated and an observed tropical storm track was used to limit the probability distribution of samples. The ensemble forecast method used pure observation data instead of assimilated data. In addition, the prediction results for three tropical storm systems, Merbok, Mawar, and Guchol, showed that track and intensity errors could be reduced through sample optimization. In the research, the vertical structures of these tropical storms were compared, and the existence of different thermal structures was discovered. One possible reason for structural differences is sample optimization, and it may affect storm intensity and track. 相似文献
6.
The mesoscale ensemble prediction system based on the Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS (EPS)) has been pre-operational since April 2020 at South China Regional Meteorological Center (SCRMC), which was developed by the Guangzhou Institute of Tropical and Marine Meteorology (GITMM). To better understand the performance of the CMA-TRAMS (EPS) and provide guidance to forecasters, we assess the performance of this system on both deterministic and probabilistic forecasts from April to September 2020 in this study through objective verification. Compared with the control (deterministic) forecasts, the ensemble mean of the CMATRAMS (EPS) shows advantages in most non-precipitation variables. In addition, the threat score indicates that the CMA-TRAMS (EPS) obviously improves light and heavy rainfall forecasts in terms of the probability-matched mean. Compared with the European Center for Medium-range Weather Forecasts operational ensemble prediction system (ECMWF-EPS), the CMA-TRAMS (EPS) improves the probabilistic forecasts of light rainfall in terms of accuracy, reliability and discrimination, and this system also improves the heavy rainfall forecasts in terms of discrimination. Moreover, two typical heavy rainfall cases in south China during the pre-summer rainy season are investigated to visually demonstrate the deterministic and probabilistic forecasts, and the results of these two cases indicate the differences and advantages (deficiencies) of the two ensemble systems. 相似文献
7.
设计基于GRAPES_Meso的不同试验模拟2014年3月28日-4月8日的广东前汛期降水过程,评估风廓线资料对同化和预报的影响。对资料同化后分析增量的分析表明:相比同化时仅使用自动气象站资料,风廓线雷达资料对1000 hPa到850 hPa纬向风增量均有贡献,在850 hPa,700 hPa高度以上贡献迅速减小。应用3个试验的预报结果计算探空站、风廓线雷达站预报值与观测值的11 d均方根误差发现,同化加入风廓线雷达资料对各预报要素的改善在850 hPa高度最明显,其中风速预报误差显著降低,为0.7 m·s-1。此外,风廓线雷达资料对700 hPa风速预报有一定改善,而在925 hPa高度模拟效果反而降低。通过对2014年3月30日12:00（世界时）的个例分析发现,同化加入风廓线雷达资料的风速预报均方根误差在大雨级别以上的降水落区更大,其原因还有待于进一步研究。 相似文献
8.
Extreme rainfall is common from May to October in south China. This study investigates the key deviation ofinitial fields on ensemble forecast of a persistent heavy rainfall event from May 20 to 22, 2020 in Guangdong Province, south China by comparing ensemble members with different performances. Based on the rainfall distribution and pattern, two types are selected for analysis compared with the observed precipitation. Through the comparison of the thermal and dynamic fields in the middle and lower layers, it can be found that the thermal difference between the middle and lower layers was an important factor which led to the deviation of precipitation distribution. The dynamic factors also have some effects on the precipitation area although they were not as important as the thermal factors in this case. Correlating accumulated precipitation with atmospheric state variables further corroborates the above conclusion. This study suggests that the uncertainty of the thermal and dynamic factors in the numerical model can have a strong impact on the quantitative skills of heavy rainfall forecasts. 相似文献
9.
为了在资料同化中更好地应用多尺度同化技术,针对当前GRAPES多尺度3D-Var同化系统中背景误差协方差设置的缺陷,探讨如何引入随时间演变的多尺度信息的方法。首先,基于GRAPES模式集合预报系统,利用集合预报结果构造了新型的背景误差协方差,该新型协方差的标准差与相关关系能随着时间演变而发生变化,即具有时间依赖特征。然后,为了考虑背景误差协方差的多尺度特征,针对不同尺度背景场将该新型协方差进行不同程度的缩放,即假设不同尺度的背景误差单变量标准差与相关尺度以及多变量相关系数与原估计值之间存在一定的比例关系。通过选择不同的缩放系数,其对应的分析增量将产生不同量值与尺度的变化,即可对相应的分析场进行多尺度调整。 相似文献
10.
基于GRAPES模式的广州地区大气输送扩散参数及其对PM2.5预报的应用 总被引：1，自引：0，他引：1
利用2010年11月—2011年11月广州地区PM2.5逐时监测资料以及GRAPES模式计算的四种大气输送扩散参数预报值,分析评估模式描述四种大气输送扩散参数的性能及其预报广州地区PM2.5浓度的可行性,结果表明：GRAPES模式不同时刻起报的地面通风系数、平均通风系数和湍流动能的预报稳定性与一致性较好,而垂直交换系数相对较差。垂直交换系数、地面通风系数、平均通风系数和湍流动能的量级分别为101、103、103和10-1～100。PM2.5浓度与大气输送扩散参数呈显著负相关,其中PM2.5与14时起报的垂直交换系数相关性最好。使用临界成功指数CSI对PM2.5浓度进行预报检验,得到垂直交换系数对PM2.5的预报稳定性较好,垂直交换系数能大概判别PM2.5为“污染”与“清洁”情况,临界成功指数部分可达70%。垂直交换系数与PM2.5浓度存在显著的超前滞后相关,预报PM2.5浓度是否为“污染”与“清洁”可同时参考原序列及滞后序列的预报效果。 相似文献