Impact of bogus vortex for track and intensity prediction of tropical cyclone

The initialization scheme designed to improve the representation of a tropical cyclone in the initial condition is tested during Orissa super cyclone (1999) over Bay of Bengal using the fifth-generation Pennsylvania State University — National Center for Atmospheric Research (Penn State — NCAR) Mesoscale Model (MM5). A series of numerical experiments are conducted to generate initial vortices by assimilating the bogus wind information into MM5. Wind speed and location of the tropical cyclone obtained from best track data are used to define maximum wind speed, and centre of the storm respectively, in the initial vortex. The initialization scheme produced an initial vortex that was well adapted to the forecast model and was much more realistic in size and intensity than the storm structure obtained from the NCEP analysis. Using this scheme, the 24-h, 48-h, and 72-h forecast errors for this case was 63, 58, and 46 km, respectively, compared with 120, 335, and 550 km for the non-vortex initialized case starting from the NCEP global analysis. When bogus vortices are introduced into initial conditions, the significant improvements in the storm intensity predictions are also seen. The impact of the vortex size on the structure of the initial vortex is also evaluated. We found that when the radius of maximum wind (RMW) of the specified vortex is smaller than that of which can be resolved by the model, the specified vortex is not well adapted by the model. In contrast, when the vortex is sufficiently large for it to be resolved on horizontal grid, but not so large to be unrealistic, more accurate storm structure is obtained.     

Evaluation of the Hurricane Weather Research and Forecasting (HWRF) model for tropical cyclone forecasts over the North Indian Ocean (NIO)

Natural Hazards - The Hurricane Weather Research and Forecast (HWRF) model, which was operational at the US National Centers for Environmental Prediction, was ported in India Meteorological...     

A comparative study of implicit and explicit initialization for a tropical barotropic model

The explicit nonlinear normal mode initialization (ENMI) scheme is applied to a tropical barotropic limited area shallow water model in spherical coordinates. The model is formulated by considering potential enstrophy conserving finite difference scheme. It is seen from the results of this study that the ENMI scheme is fully capable of filtering out the spurious gravity wave oscillations. The results are compared with those using an implicit nonlinear normal mode initialization (INMI). The latter scheme gives equally satisfactory results, requiring less computational time than the explicit scheme.     

Estimation of maximum seasonal tropical cyclone damage in the Atlantic using climate models

Natural Hazards - There are several different estimates of the observed cyclone damage potential of tropical cyclones based on observations of size, intensity and track. For the analysis of climate...     

Impact of horizontal resolution on prediction of tropical cyclones over Bay of Bengal using a regional weather prediction model

The present study is carried out to examine the performance of a regional atmospheric model in forecasting tropical cyclones over the Bay of Bengal and its sensitivity to horizontal resolution. Two cyclones, which formed over the Bay of Bengal during the years 1995 and 1997, are simulated using a regional weather prediction model with two horizontal resolutions of 165 km and 55 km. The model is found to perform reasonably well towards simulation of the storms. The structure, intensity and track of the cyclones are found to be better simulated by finer resolution of the model as compared to the coarse resolution. Rainfall amount and its distribution are also found to be sensitive to the model horizontal resolution. Other important fields, viz., vertical velocity, horizontal divergence and horizontal moisture flux are also found to be sensitive to model horizontal resolution and are better simulated by the model with finer horizontal grids.     

Assimilation of Indian radar data with ADAS and 3DVAR techniques for simulation of a small-scale tropical cyclone using ARPS model

The center for Analysis and Prediction of Storms (CAPS) has developed a radar data assimilation system. The system consists of several principal components: (1) a program that quality-controls and remaps (or super-ob) radar data to the analysis grid, (2) a Bratseth analysis method (ADAS), or a 3DVAR method for analyzing all the data except for clouds and precipitation, (3) a cloud and hydrometer analysis package that applies diabetic adjustments to the temperature field, and (4) a non-hydrostatic forecast model named ARPS. In this study, the system is applied to a small cyclone named OGNI, which formed over Bay of Bengal, India during the last week of October 2006. Three experiments are carried out to test the impact of the radar data from Chennai, India. These experiments include (1) using NCEP GFS data to initialize the ARPS model (2) using initial and boundary condition produced from the ADAS and the cloud analysis, (3) using initial and boundary condition produced from the 3DVAR and cloud analysis. The inter-comparison of results reveals that the experiment with the 3DVAR assimilation technique produces more realistic forecast to capture the genesis, structure, and northward movement of the cyclone in the short-range time scale.     

Modern and historical tropical cyclone and tsunami deposits at the coast of Myanmar: Implications for their identification and preservation in the geological record

The catastrophic storm surge of tropical cyclone Nargis in May 2008 demonstrated Myanmar's exposure to coastal flooding. The investigation of sediments left by tropical cyclone Nargis and its predecessors is an important contribution to prepare for the impact of future tropical cyclones and tsunamis in the region, because they may extend the database for long-term hazard assessment beyond the relatively short instrumental and historical record. This study, for the first time, presents deposits of modern and historical tropical cyclones and tsunamis from the coast of Myanmar. The aim is to establish regional sedimentary characteristics that may help to identify and discriminate cyclones and tsunamis in the geological record, and to document post-depositional changes due to tropical weathering in the first years after deposition. These findings if used to interpret older deposits will extend the existing instrumental record of flooding events in Myanmar. Evaluating deposits that can be related to specific events, such as the 2006 tropical cyclone Mala and the 2004 Indian Ocean tsunami, indicates similar sedimentary characteristics for both types of sediments. Landward thinning and fining trends, littoral sediment sources and sharp lower contacts allow for the differentiation from underlying deposits, while discrimination between tropical cyclone and tsunami origin is challenging based on the applied methods. The modern analogues also demonstrate a rather low preservation potential of the sand sheets due to carbonate dissolution, formation of organic top soils, and coastal erosion. However, in coastal depressions sand sheets of sufficient thickness (>10 cm) may be preserved where the shoreline is prograding or stable. In the most seaward swale of a beach-ridge plain at the Rakhine coast, two sand sheets have been identified in addition to the deposits of 2006 tropical cyclone Mala. Based on a combination of optically stimulated luminescence, radiocarbon and ¹³⁷Cs dating, the younger sand layer is related to 1982 tropical cyclone Gwa, while the older sand layer is most probably the result of an event that took place prior to 1950. Comparison with historical records indicates that the archive is only sensitive to tropical cyclones of category 4 (or higher) with landfall directly in or a few tens of kilometres north of the study area. While the presented tropical cyclone records are restricted to the last 100 years, optically stimulated luminescence ages of the beach ridges indicate that the swales landward of the one investigated in this study might provide tropical cyclone information for at least the past 700 years.     

Modeling of tropical cyclone activity over the North Indian Ocean using generalised additive model and machine learning techniques: role of Boreal summer intraseasonal oscillation

Natural Hazards - This study investigates the contribution of Boreal Summer Intraseasonal Oscillation (BSISO) to the tropical cyclone (TC) activity over the North Indian Ocean (NIO) and assesses...     

Prediction of tropical cyclone frequency with a wavelet neural network model incorporating natural orthogonal expansion and combined weights

A nonlinear wavelet neural network (WNN) model with natural orthogonal expansion (NOE) and combined weights is constructed to predict the annual frequency of tropical cyclones (TCF) occurring over the coastal regions of Southern China. Combined weights are obtained by calculating categorical weights, based on the particle swarm projection pursuit, and ranking weights, based on fuzzy mathematics, followed by optimization. The global monthly mean heights at 500?hPa and sea-surface temperature fields are used as two predictors. The linear and nonlinear information of the predictors with reduced dimensions is gathered through the NOE and combined weights, respectively, and treated as the input into the WNN model. This model is first trained with the 55-year (i.e., 1950?C2004) TCF data and then used to predict annual TCFs for the subsequent 5?years (i.e., 2005?C2009). Results show that the mean absolute and relative errors are 0.6175 and 9.34?%, respectively. The impacts of the combined weights, NOE and WNN as well as the traditional multi-regression approach on the TCF prediction are examined. Results show superior performance of the WNN-based model in the annual TCF prediction.     

Sensitivity of simulated cyclone Gonu intensity and track to variety of parameterizations: Advanced hurricane WRF model application

Domain configuration and several physical parameterization settings such as planetary boundary layer, cumulus convection, and ocean–atmosphere surface flux parameterizations can play significant roles in numerical prediction of tropical cyclones. The present study focuses to improve the prediction of the TC Gonu by investigating the sensitivity of simulations to mentioned configurations with the Advanced Hurricane WRF model. The experiments for domain design sensitivity with 27 km resolution has been shown moving the domains towards the east improve the results, due to better account for the large-scale process. The fixed and movable nests on a 9-km grid were considered separately within the coarse domain and their results showed that despite salient improvement in simulated intensity, an accuracy reduction in simulated track was observed. Increasing horizontal resolution to 3 km incredibly reduced the simulated intensity accuracy when compared to 27 km resolution. Thereafter, different initial conditions were experimented and the results have shown that the cyclone of 1000 hPa sea level pressure is the best simulation initial condition in predicting the track and intensity for cyclone Gonu. The sensitivity of simulations to ocean–atmosphere surface-flux parameterizations on a 9-km grid showed the combination of ‘Donelan scheme’ for momentum exchanges along with ‘Large and Pond scheme’ for heat and moisture exchanges provide the best prediction for cyclone Gonu intensity. The combination of YSU and MYJ PBL scheme with KF convection for prediction of track and the combination of YSU PBL scheme with KF convection for prediction of intensity are found to have better performance than the other combinations. These 22 sensitivity experiments also implicitly lead us to the conclusion that each particular forecast aspect of TC (e.g., track, intensity, etc.) will require its own special design.     

Impacts of ENSO and IOD on tropical cyclone activity in the Bay of Bengal

Natural Hazards - The impacts of El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on tropical cyclone (TC) activity (intensity, frequency, genesis location, track and average...     

The role of mid-level vortex in the intensification and weakening of tropical cyclones

The present study examines the dynamics of mid-tropospheric vortex during cyclogenesis and quantifies the importance of such vortex developments in the intensification of tropical cyclone. The genesis of tropical cyclones are investigated based on two most widely accepted theories that explain the mechanism of cyclone formation namely ‘top-down’ and ‘bottom-up’ dynamics. The Weather Research and Forecast model is employed to generate high resolution dataset required for analysis. The development of the mid-level vortex was analyzed with regard to the evolution of potential vorticity (PV), relative vorticity (RV) and vertical wind shear. Two tropical cyclones which include the developing cyclone, Hudhud and the non-developing cyclone, Helen are considered. Further, Hudhud and Helen, is compared to a deep depression formed over Bay of Bengal to highlight the significance of the mid-level vortex in the genesis of a tropical cyclone. Major results obtained are as follows: stronger positive PV anomalies are noticed over upper and lower levels of troposphere near the storm center for Hudhud as compared to Helen and the depression; Constructive interference in upper and lower level positive PV anomaly maxima resulted in the intensification of Hudhud. For Hudhud, the evolution of RV follows ‘top-down’ dynamics, in which the growth starts from the middle troposphere and then progresses downwards. As for Helen, RV growth seems to follow ‘bottom-up’ mechanism initiating growth from the lower troposphere. Though, the growth of RV for the depression initiates from mid-troposphere, rapid dissipation of mid-level vortex destabilizes the system. It is found that the formation mid-level vortex in the genesis phase is significantly important for the intensification of the storm.     

Scale matching of multiscale digital elevation model (DEM) data and the Weather Research and Forecasting (WRF) model: a case study of meteorological simulation in Hong Kong

It is becoming easier to combine geographical data and dynamic models to provide information for problem solving and geographical cognition. However, the scale dependencies of the data, model, and process can confuse the results. This study extends traditional scale research in static geographical patterns to dynamic processes and focuses on the combined scale effect of multiscale geographical data and dynamic models. The capacity for topographical expression under the combined scale effect was investigated by taking multiscale topographical data and meteorological processes in Hong Kong as a case study. A meteorological simulation of the combined scale effect was evaluated against data from Hong Kong Observatory stations. The experiments showed that (1) a digital elevation model (DEM) using 3 arc sec data with a 1 km resolution Weather Research and Forecasting (WRF) model gives better topographical expression and meteorological reproduction in Hong Kong; (2) a fine-scale model is sensitive to the resolution of the DEM data, whereas a coarse-scale model is less sensitive to it; (3) better topographical expression alone does not improve weather process simulation; and (4) uncertainty arising from a scale mismatch between the DEM data and the dynamic model may account for 38 % of the variance in certain meteorological variables (e.g., temperature). This case study gives a clear explanation of the significance and implementation of scale matching for multiscale geographical data and dynamic models.     

On the interaction of mesoscale eddies and a tropical cyclone in the Bay of Bengal

Natural Hazards - Oceanic eddies span over a wide range of sizes and affect the thermodynamic properties of water column. By modifying the thermal structure of the upper ocean, these eddies...     

港口湾水库入库洪水预报模型研究

基于港口湾、胡乐司流域产、汇流分析，提出了分流域、分单元入库洪水预报模型的整体构架，产流计算应用了蓄满产流模型，汇流计算提出了拟线性河网汇流指数模型：Csj=Sso αe^-βA j，实现了汇流系数因入流强度自动调整的目标。