A Review on GRAPES-TMM Operational Model System at Guangzhou Regional Meteorological Center

This review summarizes the general developments of the operational mesoscale modeling based on the Global/Regional Assimilation and Prediction System-Tropical Monsoon Model (GRAPES-TMM) at the Guangzhou Regional Meteorological Center. GRAPES-TMM consists of the Tropical Regional Atmospheric Model System for the South China Sea (TRAMS, a typhoon model with a horizontal resolution of 9 km), the Mesoscale Atmospheric Regional Model System (MARS, 3km) and the fine-scale Rapid Update Cycling (RUC, 1km) forecasting system. The advances of model dynamical core and physical processes are summarized; the progress of model applications is reviewed and evaluated. The results show that the updated 9-3-1 forecasting system provides an overall improved performance on the weather forecasting in south China. Capabilities and limitations as well as the future development of the forecasting system are also discussed     

Performance Evaluation of the GRAPES Model in Wind Simulations Over South China

In the present study, the performance of the GRAPES model in wind simulation over south China was assessed. The simulations were evaluated by using surface observations and two sounding stations in south China. The results show that the GRAPES model could provide a reliable simulation of the distribution and diurnal variation of the wind. It showed a generally overestimated southerly wind speed especially over the Pearl River Delta region and the south of Jiangxi Province as well as the coastal region over south China. GRAPES also exhibited a large number of stations with the opposite surface wind directions over the east of Guangxi and the south of Jiangxi during the nocturnal- to-morning period, as well as an overall overestimation of surface wind over the coastal regions during the afternoon. Although GRAPES could simulate the general evolutional characteristics of vertical wind profile, it underestimated wind speed above 900 hPa and overestimated wind speed below 900 hPa. Though the parameterization scheme of gravity wave drag proved to be an effective method to alleviate the systematic deviation of wind simulation, GRAPES still exhibited large errors in wind simulation, especially in the lower and upper troposphere.     

高阶精度有限差分方案下的非跳点网格试验:基于浅水波方程

非跳点网格在模式动力—物理过程的耦合方面具有独特的优势,但是由于二阶精度差分方案下非跳点网格频散误差较大而很少被使用于数值天气预报模式。随着近年来数值模式计算精度的不断提高,非跳点网格在频散关系方面的计算误差是否会发生变化还有待研究。本文在高阶精度差分格式下通过浅水波方程对跳点网格和非跳点网格的频散关系进行理论分析和数值试验,主要得到以下结论:（1）在低波数区跳点网格的频散关系基本不随计算精度的提高而变化,但是非跳点网格下的频散关系则随着计算精度的提高而更加接近真实解。在四阶精度下,非跳点网格的频散关系已经非常接近跳点网格。（2）差分精度提高以后,在高波数区非跳点网格仍然存在频率极大值,而且极值中心随着计算精度的提高而逐渐向更高波数区移动。跳点网格在计算精度提高以后高波数区的频率仍然随波数单调增加,且更接近真实解。（3）在高阶精度非跳点网格模拟试验的基础上,结合高阶扩散项对高频短波进行滤除,可以得到与二阶精度跳点网格相接近的模拟结果。总之,在高阶精度有限差分方案下利用非跳点网格构造模式动力框架是一种比较可行的做法。     

积云参数化方案中云底质量通量的限制及在高分辨率模式中的应用

对SAS积云参数化方案中的云底质量通量进行限制并将其应用到华南区域高分辨率模式降水预报中,分别对强对流个例和弱对流个例进行模拟和比较,分析了限制云底质量通量之后的积云参数化方案对模式降水预报的影响,并探讨了不同大小的云底质量通量限制对预报结果的敏感性。试验结果表明,对积云参数化方案进行闭合时采用不稳定能量释放假设要比原来的准平衡闭合假设更适用于中小尺度模式。对积云参数化方案的云底质量通量进行限制以后可以有效地消除对流参数化在高分辨率模式中引起的虚假降水,同时又能够合理地引入一些次网格尺度的弱对流的影响,从而改进模式的降水预报效果。敏感性试验结果表明,随着云底质量通量限制程度的变弱,对流参数化方案对模式降水预报的影响会逐渐增强;在一定大小范围内的云底质量通量限制下,强对流个例的总降水量预报结果对于不同大小的限制不如弱对流个例敏感。对两种不同的云底质量通量限制方式进行比较发现,在云底质量通量较大时完全关闭对流参数化方案可以更有效避免对流参数化引起的虚假降水。      

Applicability of Temperature Discrete Equation to NMRF Boundary Layer Scheme in GRAPES Model

By deriving the discrete equation of the parameterized equation for the New Medium-Range Forecast (NMRF) boundary layer scheme in the GRAPES model, the adjusted discrete equation for temperature is obviously different from the original equation under the background of hydrostatic equilibrium and adiabatic hypothesis. In the present research, three discrete equations for temperature in the NMRF boundary layer scheme are applied, namely the original (hereafter NMRF), the adjustment (hereafter NMRF-gocp), and the one in the YSU boundary-layer scheme (hereafter NMRF-TZ). The results show that the deviations of height, temperature, U and V wind in the boundary layer in the NMRF-gocp and NMRF-TZ experiments are smaller than those in the NMRF experiment and the deviations in the NMRF-gocp experiment are the smallest. The deviations of humidity are complex for the different forecasting lead time in the three experiments. Moreover, there are obvious diurnal variations of deviations from these variables, where the diurnal variations of deviations from height and temperature are similar and those from U and V wind are also similar. However, the diurnal variation of humidity is relatively complicated. The root means square errors of 2m temperature (T2m) and 10m speed (V10m) from the three experiments show that the error of NMRF-gocp is the smallest and that of NMRF is the biggest. There is also a diurnal variation of T2m and V10m, where T2m has double peaks and V10m has only one peak. Comparison of the discrete equations between NMRF and NMRF-gocp experiments shows that the deviation of temperature is likely to be caused by the calculation of vertical eddy diffusive coefficients of heating, which also leads to the deviations of other elements.     

非均匀分层下的二阶精度垂直差分方案及其在GRAPES模式中的应用

在非均匀分层下,目前GRAPES（Global/Regional Assimilation and Prediction System）模式中使用的垂直差分方案只能达到一阶精度。本文设计了一种适用于非均匀分层的二阶精度垂直差分方案,并将它应用于改进GRAPES模式动力框架的垂直离散化过程。一维廓线理想试验结果表明:二阶精度方案可以减少差分计算误差,而这种改进的幅度相对于差分计算本身引起的误差来说仍然是比较小的。通过密度流试验对修改后的模式动力框架进行测试,结果表明二阶方案可以保持模式动力框架的准确性和稳定性。进一步利用实际资料开展批量测试,发现二阶方案可以降低模式高空要素场的预报误差,而且这种改进随着预报时间的延长变得更为明显。最后选择一次典型的华南暴雨过程进行模拟,同样发现二阶精度方案对于48小时之后的降水会有一定程度的改进。     

对流参数化与微物理过程的耦合及其对台风预报的影响研究

在SAS（Relaxed Arakawa-schubert Scheme）对流参数化方案中引入对流云和层状云的相互耦合机制,并通过一个台风个例对改进前后两种方案的预报效果进行了比较。试验结果表明：对于台风这种对流云和层状云相互作用非常强烈的天气系统,在对流参数化方案中引入对流云和层状云的耦合机制可以有效地提高模式对台风路径的预报水平,但是对于台风强度的预报效果不明显。考虑对流参数化和微物理过程耦合后模式的参数化降水变弱而格点降水增强,与NCEP再分析资料的对比发现,改进方案对于台风外围的大尺度温度场和湿度场的预报会有所改进,但仍然存在偏干偏冷的现象。对雨和雪的不同处理方式、不同云底条件以及是否考虑雨雪的卷入抬升三个方面进行了敏感性试验,发现72 h内模式预报结果对这些因素的差异不是很敏感。从多个个例的统计结果来看,新方案对台风路径预报的改进效果是比较稳定的。     

LAPS云分析中卫星资料的应用及对GRAPES模式短时预报的影响

通过2013年5月16日广东暴雨个例,利用LAPS分析系统在GRAPES背景场的基础上融合了地面、探空、雷达和卫星资料,比较了LAPS分析系统是否融合卫星资料的云微物理变量(云水、雨水、云冰、云雪)差异;进一步对比讨论了模式提前6 h滚动预报与LAPS反演的云微物理变量的异同,在此基础上探讨了两者对模式降水预报的影响。结果发现,LAPS分析系统融合了卫星资料后,能较好地再现中尺度云团的形态和强度,且能减少一些云微物理变量(云水、云冰、云雪)的虚假中心,大值中心与强降水中心吻合较好;模式滚动预报与LAPS反演的云微物理变量水平和垂直分布差异较大,后者的分布形态基本与观测降水、雷达回波相似,大值中心与强降水中心吻合较好;从两者对模式降水预报的效果来看,LAPS分析的云微物理变量作为模式初始场中的云参数,能改善模式1 h的降水预报,而模式滚动预报的云微物理变量对模式降水预报基本没改善。      

2012年中国南海台风模式预报情况

通过统计和评估中国南海台风模式2012年的预报结果,得出了2012年各种类型热带气旋的预报质量情况。由于在动力过程优化及水物质和边界层的改进方面做了不少工作,使得中国南海台风模式的全年平均距离误差第一次在历史上突破了100 km以下,且无论是24 h、48 h及72 h的路径还是强度预报都比历年要好很多,从2012年全年的台风路径预报效果来看,有一半的台风24 h路径预报误差在100 km以下大部分台风48 h路径预报误差在200 km以下。另外,2012年中国南海台风模式对强TC的路径预报仍然象往年一样要优于弱TC;而强度预报则相反,对于较弱的强热带风暴预报其效果反而最好。个例分析发现副高强度位置及相关的西伸活动对台风路径预报有较大影响;同时,减少模式位势高度的总体平均RMSE误差对台风路径预报准确率的提高有相当重要的作用。      

地形重力波拖曳参数化方案在华南中尺度模式（GRAPES）中的应用试验

在华南中尺度模式GRAPES中发展KA95方案地形重力波拖曳参数化方案(GWDO),并对2012年的2月8—12日影响华南冷空气过程、8月23—24日发生在广东的局地性暴雨和5—8月共4个月的KA95方案预报试验进行检验。结果表明,KA95地形重力波拖曳参数化方案的引入,改善了GRAPES模式对冬、春季低层南风偏强和地面温度偏高的现象,一定程度上纠正了在模式积分过程中出现的南风偏差,改正了在业务预报中因南风偏强而导致温度偏差过大的现象;改善了模式对局地强降水强度和落区的预报,减小了大雨和暴雨的漏报率和预报偏差,提高了GRAPES模式对降水的预报效果。