Sensitivity of MM5 and WRF mesoscale model predictions of surface winds in a typhoon to planetary boundary layer parameterizations

Sea surface winds and coastal winds, which have a significant influence on the ocean environment, are very difficult to predict. Although most planetary boundary layer (PBL) parameterizations have demonstrated the capability to represent many meteorological phenomena, little attention has been paid to the precise prediction of winds at the lowest PBL level. In this study, the ability to simulate sea winds of two widely used mesoscale models, fifth-generation mesoscale model (MM5) and weather research and forecasting model (WRF), were compared. In addition, PBL sensitivity experiments were performed using Medium-Range Forecasts (MRF), Eta, Blackadar, Yonsei University (YSU), and Mellor–Yamada–Janjic (MYJ) during Typhoon Ewiniar in 2006 to investigate the optimal PBL parameterizations for predicting sea winds accurately. The horizontal distributions of winds were analyzed to discover the spatial features. The time-series analysis of wind speed from five sensitivity experimental cases was compared by correlation analysis with surface observations. For the verification of sea surface winds, QuikSCAT satellite 10-m daily mean wind data were used in root-mean-square error (RMSE) and bias error (BE) analysis. The MRF PBL using MM5 produced relatively smaller wind speeds, whereas YSU and MYJ using WRF produced relatively greater wind speeds. The hourly surface observations revealed increasingly strong winds after 0300 UTC, July 10, with most of the experiments reproducing observations reliably. YSU and MYJ using WRF showed the best agreements with observations. However, MRF using MM5 demonstrated underestimated winds. The conclusions from the correlation analysis and the RMSE and BE analysis were compatible with the above-mentioned results. However, some shortcomings were identified in the improvements of wind prediction. The data assimilation of topographical data and asynoptic observations along coast lines and satellite data in sparsely observed ocean areas should make it possible to improve the accuracy of sea surface wind predictions.     

A multiple scale modeling system for coastal hurricane wind damage mitigation

Hurricane wind damage constitutes the largest percentage of catastrophic insured losses in the US. Yet the complicated wind structures and their changes are not fully understood and, thus, have not been considered in current risk catastrophic models. To obtain realistic landfall hurricane surface winds, a large eddy simulation (LES) framework in a weather forecasting mode has been developed from a multiple nested Weather Research & Forecasting (WRF) model to explicitly simulate a spectrum of scales from large-scale background flow, hurricane vortex, mesoscale organizations, down to fine-scale turbulent eddies in a unified system. The unique WRF-LES enables the high resolution data to be generated in a realistic environment as a hurricane evolves. In this paper, a simulation of the landfalling Hurricane Katrina is presented to demonstrate various features of the WRF-LES. It shows that the localized damaging winds are caused by the large eddy circulations generated in the hurricane boundary layer. With a sufficient computational power, WRF-LES has the potential to be developed into the next generation operational public wind-field model for hurricane wind damage mitigation.     

海上大气波导研究进展

大气波导是对流层中具有异常大气折射率梯度的大气层,对于评估和预测电磁波传播和海上探测通信系统等具有重要的科学意义和应用价值.以海上发生的大气波导类型为线索总结了与大气波导相关的研究方法.在蒸发波导研究中以相似理论为基础,开发蒸发波导诊断模型为重点,开展区域海域适应性研究;海上悬空波导和表面波导从早期的定性分析到目前精确定量研究过程中,中尺度数值模式逐渐成为极其重要的研究手段,不仅提高了特定天气过程中大气波导模拟预测精度,而且在此基础上开展区域大气波导环境研究,分析其出现规律、气候原因等.针对海上大气波导研究现状,借鉴气象上的手段和技术,开展海上水文气象调查和电波传播实验,结合中尺度数值模式和海气耦合模式,采用同化技术和集合预报等手段,提高海上低空大气波导量化精度.     

Investigation of the atmospheric mesoscale circulation patterns and their simulation with WRF-CHEM model of the dust storm occurrence over the southern coast of the Caspian Sea

For the very first time, the mesoscale circulation patterns and synoptic-dynamic structure of the atmospheric systems that led to the dust emission to the south coast region of Caspian Sea (SCRCS) were identified and classified using the region synoptic stations’ observations of 2005–2013. Satellite measurements and images, NCEP/NCAR reanalysis data, and Weather Research and Forecasting (WRF) model coupled with Chemistry (WRF-CHEM) model products were also used in this study. Results showed that in 49 % of cases, cyclonic circulations over the Middle East deserts were the main transporter of dust particles into the atmosphere where then transferred to the SCRCS by southerly winds over the Alborz mountains in the lower troposphere and by westerly waves in the middle and upper troposphere. During the warm seasons, the surface heating lead to the development of mesoscale thermal low pressures over the hot deserts on the eastern regions of the Caspian Sea, like Turkmenistan and Qura Qum. Those heat lows were responsible for the 38 % of the occurred events. Turbulence and instabilities in the lower troposphere were identified as the second important dust emitter to the atmosphere where those dust particles transported to the SCRCS with the strong northeasterly wind. The third pattern by 13 % of cases was belonging to the mesoscale thermal low pressure that was developed over the arid regions of Iran like Dasht-é-Kavir. Because of the nature of the turbulence in the lower troposphere and heat lows, the ascent of dust particles by these two mechanisms was limited to a shallow layer in the troposphere. The results of simulation with the WRF-CHEM model, analysis of moderate resolution imaging spectroradiometer (MODIS) images, and spatial zoning of atmospheric optical depth (AOD) confirmed the results of the synoptic study.     

A comprehensive study of surface and upper-air characteristics over two stations on the west coast of India during the occurrence of a cyclonic storm

While qualitative information from meteorological satellites has long been recognized as critical for monitoring weather events such as tropical cyclone activity, quantitative data are required to improve the numerical prediction of these events. In this paper, the sea surface winds from QuikSCAT, cloud motion vectors and water vapor winds from KALPANA-1 are assimilated using three-dimensional variational assimilation technique within Weather Research Forecasting (WRF) modeling system. Further, the sensitivity experiments are also carried out using the available cumulus convective parameterizations in WRF modeling system. The model performance is evaluated using available observations, and both qualitative and quantitative analyses are carried out while analyzing the surface and upper-air characteristics over Mumbai (previously Bombay) and Goa during the occurrence of the tropical cyclone PHYAN at the west coast of Indian subcontinent. The model-predicted surface and upper-air characteristics show improvements in most of the situations with the use of the satellite-derived winds from QuikSCAT and KALPANA-1. Some of the model results are also found to be better in sensitivity experiments using cumulus convection schemes as compared to the CONTROL simulation.     

Prévision des crues éclair

Flash-flood events resulting from paroxystic meteorological events concentrated in time and space are insufficiently documented as they produce destructive effects. They are hardly measurable and present single features that are not transposable to another event. In the South of France, the flash flood of November 1999 gives a perfect illustration of these characteristics. The physical complexity of the process and consequently the volume and the variety of the data to take into account are incompatible with the real time constraint allocated to the forecasters confronted to the occurrence of such phenomena. So, we have to make choices to afford acceptable simplifications to the complete mechanical model. MARINE (‘Modélisation de l'Anticipation du Ruissellement et des Inondations pour des évéNements Extrêmes’) is the operational and robust tool we developed for flash-flood forecasting. This model complies with the criterions of real-time simulation. It is a physically based distributed model composed of two parts: first the flood runoff process simulation in the upstream part of the basin modelled from a rainfall–runoff approach, then the flood propagation in the main rivers described by the Saint-Venant equations. It integrates remote sensed data – Digital Elevation Model, land-use map, hydrographic network for the observations from satellites and the rainfall evolution from meteorological radar. The main goal of MARINE is to supply real time pertinent information to the forecasters. Results obtained on the Orbieu River (Aude, France) show that this model is able to supply pertinent flood hydrograph with a sufficient precision for the forecasting service to take the appropriate safety decisions. Furthermore, MARINE has already been tested in the French National Flood Forecasting Service of Haute-Garonne in real conditions. To cite this article: V. Estupina Borrell et al., C. R. Geoscience 337 (2005).     

Air recirculation and ventilation in the coastal regions of the Black Sea

An initial investigation of recirculation is carried out for the coast of the Black Sea. The local mesoscale circulations (land-sea breezes, mountain and valley winds) in coastal areas are shown to be an additional risk factor in creating favorable conditions for air stagnation and accumulation of air pollutants in the surface atmosphere layer. Two types of annual recirculation patterns are revealed for northern and north-eastern coast of the Black Sea. Long-term changes in recirculation are investigated. It is shown that the recirculation parameter values remained quasistable until the mid-1970s. Since 1976–1977, steady intensification of recirculation in both winter and summer is identified.     

3D modelling strategy for weather radar data analysis

Weather radar data, which have obvious spatial characteristics, represent an important and essential data source for weather identification and prediction, and the multi-dimensional visualization and analysis of such data in a three-dimensional (3D) environment are important strategies for meteorological assessments of potentially disastrous weather. The previous studies have generally used regular 3D raster grids as a basic structure to represent radar data and reconstruct convective clouds. However, conducting weather radar data analyses based on regular 3D raster grids is time-consuming and inefficient, because such analyses involve considerable amounts of tedious data interpolation, and they cannot be used to address real-time situations or provide rapid-response solutions. Therefore, a new 3D modelling strategy that can be used to efficiently represent and analyse radar data is proposed in this article. According to the mode by which the radar data are obtained, the proposed 3D modelling strategy organizes the radar data using logical objects entitled radar-point, radar-line, radar-sector, and radar-cluster objects. In these logical objects, the radar point is the basic object that carries the real radar data unit detected from the radar scan, and the radar-line, radar-sector, and radar-cluster objects organize the radar-point collection in different spatial levels that are consistent with the intrinsic spatial structure of the radar scan. Radar points can be regarded as spatial points, and their spatial structure can support logical objects; thus, the radar points can be flexibly connected to construct continuous surface data with quads and volume data with hexahedron cells without additional tedious data interpolation. This model can be used to conduct corresponding operations, such as extracting an isosurface with the marching cube method and a radar profile with a designed sectioning algorithm to represent the outer and inner structure of a convective cloud. Finally, a case study is provided to verify that the proposed 3D modelling strategy has a better performance in radar data analysis and can intuitively and effectively represent the 3D structure of convective clouds.     

A hybrid artificial neural network-based agri-economic model for predicting typhoon-induced losses

Building a model to rapidly simulate the impact of typhoons on agriculture and to predict agricultural losses is crucial and great help for remedial measure and distributing subvention right after the disaster. The relationship between typhoon-related meteorological factors and agricultural losses was first evaluated, and the Pearson??s test was applied to find consequences of both landfall and non-landfall which can be appropriately used to synthesize the possible coverage to suitably describe how typhoons influence agricultural losses. The self-organizing feature map (SOM) was then used to map similar properties of data into the same cluster and display the distribution of input?Coutput patterns. Then, the clusters were adopted as centroids of radial basis function (RBF) neural networks. Finally, two hybrid self-organizing radial basis (SORB) networks that integrated SOM into RBF were constructed for predicting the event-based agricultural losses by feeding two different meteorological inputs (scenarios 1 and 2). The results indicate that the constructed SORB network has great ability to capture the relationship between meteorological characteristics and agricultural losses. Previously, it always takes several days to investigate and evaluate the agricultural damages after typhoons, which is a time-consuming process. In this study, the proposed agri-economic model also demonstrates its outstanding predictability, in real-time, and therefore effectively accelerates the official decision making on agricultural compensation after a typhoon strike.     

Fine spatial structure of flows on satellite radar image of the Baltic Sea

Satellite images of the sea surface demonstrate different dynamic processes at the water–air boundary and in the water layer. The objective of this investigation is to identify the fine structure of flows in the mesoscale vortex with the help of a specially developed method for flow estimation by ship wakes in the sea. The method described in this work made it possible to identify the jet nature and surges of flows in the mesoscale cyclonic vortex in the southern part of the Baltic Sea after long western and southwestern winds.     

Assimilation of Doppler weather radar observations in a mesoscale model for the prediction of rainfall associated with mesoscale convective systems

Obtaining an accurate initial state is recognized as one of the biggest challenges in accurate model prediction of convective events. This work is the first attempt in utilizing the India Meteorological Department (IMD) Doppler radar data in a numerical model for the prediction of mesoscale convective complexes around Chennai and Kolkata. Three strong convective events both over Chennai and Kolkata have been considered for the present study. The simulation experiments have been carried out using fifth-generation Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation approach is one of the most promising tools available for directly assimilating the mesoscale observations in order to improve the initial state. The horizontal wind derived from the DWR has been used alongwith other conventional and non-conventional data in the assimilation system. The preliminary results from the three dimensional variational (3DVAR) experiments are encouraging. The simulated rainfall has also been compared with that derived from the Tropical Rainfall Measuring Mission (TRMM) satellite. The encouraging result from this study can be the basis for further investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present study indicates that Doppler radar data assimilation improves the initial field and enhances the Quantitative Precipitation Forecasting (QPF) skill.     

Experimental investigation of the face stability of shallow tunnels in sand

Various models have been proposed for the prediction of the necessary support pressure at the face of a shallow tunnel. To assess their quality, the collapse of a tunnel face was modelled with small-scale model tests at single gravity. The development of the failure mechanism and the support force at the face in dry sand were investigated. The observed displacement patterns show a negligible influence of overburden on the extent and evolution of the failure zone. The latter is significantly influenced, though, by the initial density of the sand: in dense sand a chimney-wedge-type collapse mechanism developed, which propagated towards the soil surface. Initially, loose sand did not show any discrete collapse mechanism. The necessary support force was neither influenced by the overburden nor the initial density. A comparison with quantitative predictions by several theoretical models showed that the measured necessary support pressure is overestimated by most of the models. Those by Vermeer/Ruse and Léca/Dormieux showed the best agreement to the measurements.     

Latent and sensible heat fluxes under active and weak phases of the summer monsoon of 1986

An analysis of the meteorological data collected by the research vessel ORV Sagarkanya for the mean latent and sensible heat fluxes over the Arabian Sea has indicated appreciable changes between active and weak phases of the southwest monsoon of 1986. We suggest that: (a) the presence of a core of low level winds associated with the Somali jet and its southward shift during the season, along with (b) a ridge in surface pressure over the central Arabian Sea could be responsible for the deficit in monsoon rainfall along the west coast of India in 1986.     

Meteorological influences on sea level and water temperature in the lower Chesapeake Bay: 1992

The influence of atmospheric forcing on the flow and heat transports in the lower Chesapeake Bay and the adjacent coastal ocean were studied by comparing nontidal sea level and sea surface temperature variations in this region with meteorological data for 1992. Northeasterly and southwesterly winds caused the greatest changes in mean sea level (greater than 0.25 m) throughout the year. Northeastely winds caused a more rapid response than southwesterly winds, causing sea-level rises in less than 6 h. Barometric pressure changes typically contributed approximately 10% to extreme sea-level variations and were less influential than wind stress in most cases. Wind forcing was also responsible for summer events in which the horizontal water temperature gradient between two near-surface locations in the vicinity of the bay mouth vanished. These zero-gradient events corresponded to inflows and outflows at the bay's entrance caused by northeasterly and southwesterly winds, respectively. Wind-induced advection outside the lower Chesapeake Bay was additionally responsible for extreme heat flux variations. Heat gains and losses during the spring and fall occurred in pulsating events related to wind direction but were probably not connected to lower bay processes.     

Simulation of debris flows in the Central Andes based on Open Source GIS: possibilities,limitations, and parameter sensitivity

A GIS-based model framework, designed as a raster module for the Open Source software GRASS, was developed for simulating the mobilization and motion of debris flows triggered by rainfall. Designed for study areas up to few square kilometres, the tool combines deterministic and empirical model components for infiltration and surface runoff, detachment and sediment transport, slope stability, debris flow mobilization, and travel distance and deposition. The model framework was applied to selected study areas along the international road from Mendoza (Argentina) to Central Chile. The input parameters were investigated at the local scale. The model was run for a number of rainfall scenarios and evaluated using field observations and historical archives in combination with meteorological data. The sensitivity of the model to a set of key parameters was tested. The major scope of the paper is to highlight the capabilities of the model—and of this type of models in general—as well as its limitations and possible solutions.     

Preliminary observation of a tidal intrusion front inside the mouth of the Chesapeake Bay

In situ sampling during flooding tidal flow and southerly winds shows the up-estuary translation of a surface front along the Thimble Shoal channel, which is located in the southern part of Chesapeake Bay. Currents and surface density were measured using a towed acoustic Doppler current profiler and CTD, and a ship-borne radar was used to monitor the orientation and planform of the front, which varied over time. These preliminary observations suggest that dense shelf water, upwelled to the surface along the coast near Cape Henry, Virginia, can be found well into the southern part of the bay during flood, and that the boundary between the intruding shelf water and less dense estuarine water has many of the same characteristics as tidal intrusion fronts found in smaller scale estuaries.     

城市气象与边界层数值模拟研究

综合评述关于城市气象与边界层数值模拟的近期研究进展,主要就城市气候研究、城市能量平衡、城市热岛研究以及城市陆面过程与城市地表能量平衡模式等方面国内外主要研究工作,结合作者近期的研究工作和认识作一评述.从中提出一些现实与观点方面的问题,给出一些看法和讨论.最后,就当今比较流行并显示十分有效的城市气象和城市边界层数值模拟作一些讨论,着重对这一领域面临的现行研究和未来的挑战,提出一些思考.评述结果表明:①今后需针对我国不同气候区、不同城市特点和建筑物形态特征,开展城市气候、城市地表能量平衡、城市热岛等方面的观测与模拟研究;②在城市气象观测方法与技术导则、观测站网布局、新型观测手段的综合使用等方面的深入研究需进一步展开;③需建立基于时间、天气条件、建筑特征的简单的城市热岛强度预报方法;④可探索采用计算流体力学(CFD)模式作为"桥梁",检验并改进中尺度模式对城市地区的模拟效果.     

Tropical cyclone wind field forcing for surge models: critical issues and sensitivities

Several wind fields developed for Hurricane Katrina (2005) in the US Gulf of Mexico (GOM) are applied with the ADCIRC hydrodynamic model to explore the sensitivity of predictions of coastal surges to wind fields developed by alternative methods. The alternative model predictions are evaluated against water level measurements provided by gages at two coastal locations. It is found that all the post-event analyzed wind fields yield a range of predictions of only ±10% of the available peak surge measurements regardless of whether the wind fields are produced by dynamical boundary layer models, kinematic analysis methods or a blend. However, the richness of meteorological forcing data in the GOM is not typically matched in other basins affected by tropical cyclones and errors may be much larger where storm intensity and size parameters are estimated mainly from satellite data. The attributes and remaining critical deficiencies of current methods for surface wind specification in both data-rich and data-poor environments are reviewed.     

Landslide susceptibility mapping using precipitation data,Mazandaran Province,north of Iran

A tropical cyclone was formed over central northern Africa near Egypt, Libya and Crete, and it moved and deepened toward the north–northeast; meanwhile, the storm destroyed many regions in the west, southwest and central of Turkey. The cyclone carried huge dust from the north of Africa to Turkey and reduced the visibility to less than 1 km and raised the wind speed. As a result of severe storm, some meteorological stations have new extreme values that the strongest wind speed measured was 81 knots in the central region of Turkey. Medicane with wind speed 81 knots especially over Turkey is a rare event. This devastating cyclone carried exceptionally very strong winds (>80 kts) with favorable conditions to follow windstorm conceptual model. The cyclone caused adverse conditions such as excessive injuries, fatal incidents and forest fires. Mesoscale vortex formed and affected particularly the middle and western regions of Turkey. The vertical thermodynamic structure of storm is compared with April values of 40 years of datasets over Istanbul. Moreover, four different winds {measurement masts} of Istanbul Atatürk Airport are used for the microscale analysis of different meteorological parameters during deepened pressure level. In addition, divergence and vorticity of stormy weather are discussed in details during the effective time period of storm by solving equations and validated using ERA-40 reanalysis. We obtained many monitoring data sources such as ground base, radar, radiosonde and satellite display the values of the intensity of wind speed caused by cyclones of tropics have revealed similarities.