Progress in Lightning Forecast by Using Numerical Weather Models and Model Outputs

Lightning can threaten human and equipment safety. An indicator of sever convective weather, it plays an important role in atmospheric chemistry. The intensive studies have advanced the lightning forecast in the mesoscale weather models and its application in global climate models. There are three methods to forecast lightning by using numerical weather models: Numerical diagnosis prediction based on synoptic background filed statistical relations; Flash rate parameterization developed with the relationship between dynamical, microphysical and electrification processes, and The numerical weather model coupled with the explicit electrification and lightning parameterization schemes. In this paper, the research progress in lightning forecast with three above-mentioned methods were reviewed, and the future research issues on lightning forecast were also discussed.     

Review of Development and Application of High Resolution Global Climate System Model

Climate models have been used as an important tool to quantitatively study climate variability and to predict or project climate change in the future. One of the most important pathways for development and improvement of climate system model is to increase the spatial resolution and improve the corresponding physical parameterization schemes, which is very important for understanding climate change and improving climate prediction skill. Based on a brief introduction of the importance of developing high-resolution global climate system model, a review of recent progresses in the development and application of high-resolution models was summarized. The paper also introduced the current situation and problems for the development and evaluation of high-resolution models and focused on the key scientific and technical bottlenecks which restrict the development of high-resolution models, including the development of dynamic framework of the high-resolution ocean and atmospheric models and massive high performance parallel computing, the improvement of the sub-grid physical parameterization scheme, and mesoscale air-sea interaction. Meanwhile, the scientific objects and experiments design of the international high resolution climate model intercomparison project (HiResMIP) of the coupled model intercomparison project phase 6 (CMIP6) was introduced. Finally, we prospect the future developments and evaluations of high-resolution climate models in China was proposed.     

Customization of WRF-ARW model with physical parameterization schemes for the simulation of tropical cyclones over North Indian Ocean

The convection and planetary boundary layer (PBL) processes play significant role in the genesis and intensification of tropical cyclones (TCs). Several convection and PBL parameterization schemes incorporate these processes in the numerical weather prediction models. Therefore, a systematic intercomparison of performance of parameterization schemes is essential to customize a model. In this context, six combinations of physical parameterization schemes (2 PBL Schemes, YSU and MYJ, and 3 convection schemes, KF, BM, and GD) of WRF-ARW model are employed to obtain the optimum combination for the prediction of TCs over North Indian Ocean. Five cyclones are studied for sensitivity experiments and the out-coming combination is tested on real-time prediction of TCs during 2008. The tracks are also compared with those provided by the operational centers like NCEP, ECMWF, UKMO, NCMRWF, and IMD. It is found that the combination of YSU PBL scheme with KF convection scheme (YKF) provides a better prediction of intensity, track, and rainfall consistently. The average RMSE of intensity (13?hPa in CSLP and 11?m?s^?1 in 10-m wind), mean track, and landfall errors is found to be least with YKF combination. The equitable threat score (ETS) of YKF combination is more than 0.2 for the prediction of 24-h accumulated rainfall up to 125?mm. The vertical structural characteristics of cyclone inner core also recommend the YKF combination for Indian seas cyclones. In the real-time prediction of 2008 TCs, the 72-, 48-, and 24-h mean track errors are 172, 129, and 155?km and the mean landfall errors are 125, 73, and 66?km, respectively. Compared with the track of leading operational agencies, the WRF model is competing in 24?h (116?km error) and 72?h (166?km) but superior in 48-h (119?km) track forecast.     

可变分辨率展宽网格在区域物理参数化大气模式中的应用

将有限区域展宽网格方法应用于区域物理参数化大气模式中，来检验其模拟湿物理过程的能力。展宽网格模型旨在在一个大的有限空间区域中得到我们所关注的小区域的高分辨率。运用展宽网格模型对南美地区进行模拟的结果表明：当拥有充足的物理参数集时，模型模拟效果良好；并且，如果改进计算机功率，便可得到与始终保持高分辨率模拟具有可比性的输出结果。     

区域中尺度模式云微物理参数化方案特征及其在中国的适用性

云微物理参数化方案在数值模式中起着重要的作用,是影响数值天气预报和气候预测准确性的最大因素。系统回顾了中尺度数值模式中云微物理参数化方案的研究进展,并统计分析了最近十余年云微物理参数化方案在中国范围内的敏感性试验研究成果。Lin方案和Rutledge-Hobbs方案奠定了中尺度模式中云微物理参数化方案的基础,其他方案都是直接或间接在这2个方案的基础上从多方面改进而形成的。这些改进主要体现在:①水凝物粒子分类数目;②冰核活化;③粒子谱分布描述函数;④粒子谱截距的取值;⑤粒子间相互转换阈值大小的设定。中国范围内云微物理参数化方案敏感性试验研究成果统计表明,使用WRF模式中Lin方案的模拟效果较好,MM5模式采用Goddard和Reisner方案效果较好。     

冻土模式的改进和发展

本研究首先对当今常用的冻土模式进行了改进。以土壤总焓和土壤水总质量替代原来的温度和体积水含量作为方程预报量,使冰水相变速率项变为诊断量,避免了原冻土模式计算过程中由于冰水相变速率项预估的误差造成计算过程中的温度偏差。同时对该新形式模式所发展的诊断量方程组设计了合理省时的数值计算方案。实验表明,改进后模式的模拟结果与观测值有较好的吻合。此外,分析比较了目前常用的3种冻融方案的理论基础及模拟结果,发现基于热力学平衡态推导得到的包含土壤水势影响的参数化方案能很好地模拟土壤的冻融变化过程,不同的冻融方案会对土壤内的温度、水量及表面的感热和潜热模拟结果产生较大的影响。      

大气数值模式中城市效应参数化方案研究进展

介绍了对城市效应影响大气运动的物理过程,以及在不同尺度大气模式中如何合理考虑这些物理过程,对进一步发展完善城市效应参数化方案中亟待解决的问题及困难作了论述,并着重强调了不同城市冠层参数化方案的优缺点。结论认为,随着城市的扩张,城市效应对大气运动的影响是数值模拟研究中一个不可或缺的物理过程,城市冠层模式的引入可以有效地提高数值模拟效果。对于不同尺度的数值模拟研究工作,应该采取不同的城市效应影响方案。目前,由于冠层模式中涉及的物理过程十分复杂,冠层模式还有待进一步完善,此外冠层方案的验证工作,尤其是应用城市地表能量平衡观测资料进行的验证工作还应该进一步深入开展。     

基于土壤植被不同参数化方法的流域蒸散发模拟

植被和土壤是水循环中的重要载体,模拟流域水循环时植被和土壤的参数化也显得尤为重要。通过对比流域蒸散发模拟中分布式模型和集总式概念模型的土壤植被参数化方法,计算了潘家口水库流域不同时间尺度上的流域蒸散发,分析了不同时间尺度下流域蒸散发的影响因素。通过分析得出:(1)分布式水文模型中的植被参数化方法包括对植被时空分布与变化的描述,以及与之相关的土壤-植被-大气中水分和能量的传输过程的描述。(2)从GBHM模型与流域水热耦合平衡模型的对比分析可知,在流域尺度上,年实际蒸散发与潜在蒸散发之间呈互补的高度非线性关系;但在山坡和小时时间尺度上,实际蒸散发与潜在蒸散发之间呈正比关系,并可近似为线性正比关系。(3)基于流域水热耦合平衡模型在不同时间尺度的参数化分析可知,考虑植被土壤水分和植被覆盖度能改善对流域蒸散发的年际和季节变化的模拟精度;土壤水分和植被的影响随着时间尺度变小表现得越来越显著。     

Progress of the Climate Extension of Weather Research and Forecast(CWRF)Model Application in China

With the development of regional climate simulation, CWRF, the new generation regional climate model, is increasingly used in climate research because of its advanced capability and high skill. The CWRF application in China was introduced from three aspects: its modifications of WRF physics parameterizations, the construction of modeling domain and lateral boundary conditions, the case simulation study and comparison with RegCM, illustrating the accuracy and advantage of CWRF in regional climate simulations. Furthermore, two major CWRF developmental prospects in China were explored: one was to incorporate more accurate physical parameterization schemes and optimized multi-physics ensemble approach; the other was to nest CWRF in GCMs for short-term climate operational forecast and long-term climate change prediction and impact assessment. The status of CWRF applications in China was summarized and the outlook of its further development was pointed out, which provided a meaningful reference for more general research and application.     

陆面水文过程研究综述

在简单介绍陆面过程模式发展的基础上，从裸土蒸发、植被蒸散、土壤水传输、排水和径流等五个方面详细综述了陆面模式研究中对水文过程的参数化。目前陆面参数化方案中仍存在很大的不确定性，其中陆面水文过程参数化的关键问题包括：土壤分层、土层厚度、根带分布；参数的代表性和移植；观测资料；径流的参数化。分析了径流在陆面模式中的重要性，及目前陆面模式中对径流参数化存在的不足，介绍了部分陆面模式对径流的模拟研究，讨论了未来工作的研究重点。     

A Study on the Impact of Parameterization of Physical Processes on Prediction of Tropical Cyclones over the Bay of Bengal With NCAR/PSU Mesoscale Model

Prediction of the track and intensity of tropical cyclones is one of the most challenging problems in numerical weather prediction (NWP). The chief objective of this study is to investigate the performance of different cumulus convection and planetary boundary layer (PBL) parameterization schemes in the simulation of tropical cyclones over the Bay of Bengal. For this purpose, two severe cyclonic storms are simulated with two PBL and four convection schemes using non-hydrostatic version of MM5 modeling system. Several important model simulated fields including sea level pressure, horizontal wind and precipitation are compared with the corresponding verification analysis/observation. The track of the cyclones in the simulation and analysis are compared with the best-fit track provided by India Meteorological Department (IMD). The Hong-Pan PBL scheme (as implemented in NCAR Medium Range Forecast (MRF) model) in combination with Grell (or Betts-Miller) cumulus convection scheme is found to perform better than the other combinations of schemes used in this study. Though it is expected that radiative processes may not have pronounced effect in short-range forecasts, an attempt is made to calibrate the model with respect to the two radiation parameterization schemes used in the study. And the results indicate that radiation parameterization has noticeable impact on the simulation of tropical cyclones.     

冻土-气候关系模型评述

冻土-气候关系模型是目前冻土学领域的研究热点,评述了冻土对气候系统的响应模型以及陆面过程模型中的各种冻土参数化方案.建立在传热学基础上的物理模型具有动态性、普适性的优点,适合于冻土工程计算,当把它们推广到面上时,需要对其进行简化.经验模型大都只使用有限的变量,与地理信息系统结合紧密,因此模型具有空间性,较为适合于冻土制图.陆面过程模型中的冻土参数化目前有3类方法:1)限定或修正水热参数;2)比较单位土层中耗热或放热量与可耗热或可放热量而计算产冰率;3)使用土壤基质势定义土壤冻结后的未冻水含量.现有的陆面过程模型中的冻土参数化方案需要进一步的改进.     

分辨率和陆面方案对长江流域短期气候预测影响

利用区域气候模式RegCM4.5,分别选取不同陆面参数化方案和空间分辨率,对5个长江流域降水异常年份进行短期气候回报试验,分析对气温和降水预测效果的影响及其最优组合。结果表明:空间分辨率的提高可以改善流域降水和气温的预测性能;而不同陆面方案引起的地表净辐射能量分布不同及其地表蒸散差异,最终导致流域内气温和降水预测效果不一致。RegCM（CLM4.5+30 km）对流域内小雨预测结果最好,而RegCM（BATS+30 km）预测流域内大雨和暴雨效果最优;RegCM（CLM3.5+30 km）对流域内气温预测能力最好。     

青藏铁路沿线地表和路基表面热力学模式(Ⅲ):参数化方案

以物理过程分析为基础,根据野外实测资料设计了青藏铁路沿线地表和路基表面热力学模式中的大气辐射参数化方案,对直接太阳辐射、大气散射辐射、大气向下长波辐射参数进行处理,得到了较好的结果.在无云大气条件下,对直接太阳辐射透过率和大气散射辐射以太阳天顶角进行参数化;对大气向下长波辐射以大气等效辐射率及气温进行参数化;在云天条件下,基于晴阴比的云量参数化和基于气候资料的云天系数参数化都各有较好的效果.对土壤热通量的参数化方法和拖曳系数的取值问题进行了讨论,更完善的方法还有待于与实验测量工作相结合.     

Impact of physical parameterization schemes on numerical simulation of super cyclone Gonu

The objective of this study is to investigate in detail the sensitivity of cumulus, planetary boundary layer and explicit cloud microphysics parameterization schemes on intensity and track forecast of super cyclone Gonu (2007) using the Pennsylvania State University-National Center for Atmospheric Research Fifth-Generation Mesoscale Model (MM5). Three sets of sensitivity experiments (totally 11 experiments) are conducted to examine the impact of each of the aforementioned parameterization schemes on the storm’s track and intensity forecast. Convective parameterization schemes (CPS) include Grell (Gr), Betts–Miller (BM) and updated Kain–Fritsch (KF2); planetary boundary layer (PBL) schemes include Burk–Thompson (BT), Eta Mellor–Yamada (MY) and the Medium-Range Forecast (MRF); and cloud microphysics parameterization schemes (MPS) comprise Warm Rain (WR), Simple Ice (SI), Mixed Phase (MP), Goddard Graupel (GG), Reisner Graupel (RG) and Schultz (Sc). The model configuration for CPS and PBL experiments includes two nested domains (90- and 30-km resolution), and for MPS experiments includes three nested domains (90-, 30- and 10-km grid resolution). It is found that the forecast track and intensity of the cyclone are most sensitive to CPS compared to other physical parameterization schemes (i.e., PBL and MPS). The simulated cyclone with Gr scheme has the least forecast track error, and KF2 scheme has highest intensity. From the results, influence of cumulus convection on steering flow of the cyclone is evident. It appears that combined effect of midlatitude trough interaction, strength of the anticyclone and intensity of the storm in each of these model forecasts are responsible for the differences in respective track forecast of the cyclone. The PBL group of experiments has less influence on the track forecast of the cyclone compared to CPS. However, we do note a considerable variation in intensity forecast due to variations in PBL schemes. The MY scheme produced reasonably better forecast within the group with a sustained warm core and better surface wind fields. Finally, results from MPS set of experiments demonstrate that explicit moisture schemes have profound impact on cyclone intensity and moderate impact on cyclone track forecast. The storm produced from WR scheme is the most intensive in the group and closer to the observed strength. The possible reason attributed for this intensification is the combined effect of reduction in cooling tendencies within the storm core due to the absence of melting process and reduction of water loading in the model due to absence of frozen hydrometeors in the WR scheme. We also note a good correlation between evolution of frozen condensate and storm intensification rate among these experiments. It appears that the Sc scheme has some systematic bias and because of that we note a substantial reduction in the rain water formation in the simulated storm when compared to others within the group. In general, it is noted that all the sensitivity experiments have a tendency to unrealistically intensify the storm at the later part of the integration phase.     

边界层参数化影响“梅花”台风的敏感性试验

以GRAPES-TCM为试验模式,对1109台风“梅花”进行了36次72 h的预报试验,通过试验分析了2种边界层参数化方案——MRF方案与YSU方案在不同情况下对台风预报的影响.结果显示:“梅花”路径与强度对边界层方案的变化都表现出一定的敏感性,敏感性大小与对流参数化方案、台风的初始强度等因素有关,强度的敏感性比路径更明显;对弱台风的路径与强度,YSU方案的总体预报效果优于MRF方案,对于强台风,2种边界层方案中MRF方案的路径预报效果更好,哪种方案的强度预报效果更好与对流参数化方案有关;无论何种情况,YSU方案预报的“梅花”强度都明显强于MRF方案,YSU方案预报的降水及感热通量与潜热通量总体上大于MRF方案;YSU方案时更多的感热通量和潜热通量与该方案时边界层更强的湍流混合有关,更多的潜热通量导致更多的降水,从而释放更多的潜热,更多的潜热释放以及更多的感热通量导致台风强度更强.     

A preliminary evaluation of the necessity of using a cumulus parameterization scheme in high-resolution simulations of Typhoon Haiyan (2013)

The Weather Research and Forecasting model was used to test the sensitivity of Typhoon Haiyan (2013) to the use of a cumulus parameterization scheme, specifically the revised Kain–Fritsch (rKF) scheme, at high horizontal resolutions with grid spacing varying from 9 to 2 km. The rKF scheme simulated the typhoon in best agreement with the observation compared with other schemes, but some fundamental drawbacks relating the rKF scheme, e.g., neglecting the momentum adjustment and being less applicable to high-resolution modeling than multi-scaled schemes, could influence the results and were discussed. Initial results showed that the typhoon track simulations benefited little from the use of the rKF scheme or a fine resolution, partially because of the similar large-scale steering flows induced by the analyzed boundary conditions used in each simulation. The influences of using the rKF scheme on typhoon intensity, size, structure, and precipitation were dependent on the grid spacing, and the most apparent changes occurred near a grid length of 4 km. At 9–4-km grid spacings, using the rKF scheme produced typhoons much stronger with more rainfall and surface latent heat flux than did using no cumulus parameterization scheme. At 3- or 2-km grid spacing, using the rKF scheme caused little changes on typhoon intensity, and the changes in precipitation and surface latent heat flux were relatively small. These results suggested that the grid spacing of 2 km for simulations using no cumulus parameterization scheme or the grid spacing of 4 km for simulations using the rKF scheme facilitated reproducing the observed Typhoon Haiyan.     

One step back for a leap forward: toward operational measurements of elements at risk

This study presents the evaluation of 1 year of operational lightning forecasts provided for Europe, using the Weather Research and Forecasting model coupled with a cloud-top height-based lightning parameterization scheme. Three different convective parameterization schemes were employed for parameterizing sub-grid cloud-top heights and consequently driving the lightning scheme. Triggering of the lightning scheme was controlled by means of a model-resolved microphysics-based masking filter, while the formulation for deriving lightning flash rates was also modified, assuming a single “marine” equation instead of the original equations discriminating between continental and marine lightning. Gridded lightning observations were used for evaluating model performance on a dichotomous decision basis. Analysis showed that the lightning scheme is sensitive to the parameterization of convection. In particular, the Kain–Fritsch convective scheme was found to outperform the Grell–Devenyi and Grell–Freitas schemes, showing a statistically significant better performance with respect to lightning prediction. This was most evident during the warm season, while smaller differences among the schemes were recorded during the cold season. Further, for all examined convective schemes, it was found that the application of the masking filter is desirable for improving model performance in terms of lightning forecasting. Last, the reported results revealed that the refinement of the formulation of the lightning parameterization scheme, adhering to a “global” marine equation instead of distinguishing between land and sea lightning, may be necessary in order to obtain reliable lightning forecasts.     

Adaptive Multiscale Permeability Estimation

With multiscale permeability estimation one does not select parameterization prior to the estimation. Instead, one performs a hierarchical search for the right parameterization while solving a sequence of estimation problems with an increasing parameterization dimension. In some previous works on the subject, the same refinement is applied all over the porous medium. This may lead to over-parameterization, and subsequently, to unrealistic permeability estimates and excessive computational work. With adaptive multiscale permeability estimation, the new parameterization at an arbitrary stage in the estimation sequence is such that new degrees of freedom are not necessarily introduced all over the porous medium. The aim is to introduce new degrees of freedom only where it is warranted by the data. In this paper, we introduce a novel adaptive multiscale estimation. The approach is used to estimate absolute permeability from two-phase pressure data in several numerical examples.     

湖泊数值模拟研究现状综述

作为陆面过程的重要组成部分,湖泊在天气气候预测中的作用得到了相关研究者的广泛关注,并成为大气科学研究领域中的一个热点.主要综述了当前湖泊模式的基本类型、所考虑的关键物理过程及其参数化方案,并尝试分析了各个方案的优劣以及模拟效果.相关研究表明,现有的湖泊模式对浅湖的模拟比较成熟,而对深湖和冰湖的模拟有待改进.未来的研究亟需构筑适用于大湖、深湖以及冰湖的参数化方案,发展能全面模拟各类型湖泊的数值模式,并且湖泊数值模拟的改进依赖于今后更多高质量的全球湖泊观测结果.