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.     

Sensitivity of tropical cyclone intensification to boundary layer and convective processes

This study examines the role of the parameterization of convection, planetary boundary layer (PBL) and explicit moisture processes on tropical cyclone intensification. A high-resolution mesoscale model, National Center for Atmospheric Research (NCAR) model MM5, with two interactive nested domains at resolutions 90 km and 30 km was used to simulate the Orissa Super cyclone, the most intense Indian cyclone of the past century. The initial fields and time-varying boundary variables and sea surface temperatures were taken from the National Centers for Environmental Prediction (NCEP) (FNL) one-degree data set. Three categories of sensitivity experiments were conducted to examine the various schemes of PBL, convection and explicit moisture processes. The results show that the PBL processes play crucial roles in determining the intensity of the cyclone and that the scheme of Mellor-Yamada (MY) produces the strongest cyclone. The combination of the parameterization schemes of MY for planetary boundary layer, Kain-Fritsch2 for convection and Mixed-Phase for explicit moisture produced the best simulation in terms of intensity and track. The simulated cyclone produced a minimum sea level pressure of 930 hPa and a maximum wind of 65 m s⁻¹ as well as all of the characteristics of a mature tropical cyclone with an eye and eye-wall along with a warm core structure. The model-simulated precipitation intensity and distribution were in good agreement with the observations. The ensemble mean of all 12 experiments produced reasonable intensity and the best track.     

Prediction of severe tropical cyclones over the Bay of Bengal during 2007–2010 using high-resolution mesoscale model

In this paper, the performance of a high-resolution mesoscale model for the prediction of severe tropical cyclones over the Bay of Bengal during 2007?C2010 (Sidr, Nargis, Aila, and Laila) is discussed. The advanced Weather Research Forecast (WRF) modeling system (ARW core) is used with a combination of Yonsei University PBL schemes, Kain-Fritsch cumulus parameterization, and Ferrier cloud microphysics schemes for the simulations. The initial and boundary conditions for the simulations are derived from global operational analysis and forecast products of the National Center for Environmental Prediction-Global Forecast System (NCEP-GFS) available at 1°lon/lat resolution. The simulation results of the extreme weather parameters such as heavy rainfall, strong wind and track of those four severe cyclones, are critically evaluated and discussed by comparing with the Joint Typhoon Warning Center (JTWC) estimated values. The simulations of the cyclones reveal that the cyclone track, intensity, and time of landfall are reasonably well simulated by the model. The mean track error at the time of landfall of the cyclone is 98?km, in which the minimum error was found to be for the cyclone Nargis (22?km) and maximum error for the cyclone Laila (304?km). The landfall time of all the cyclones is also fairly simulated by the model. The distribution and intensity of rainfall are well simulated by the model as well and were comparable with the TRMM estimates.     

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.     

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.     

Numerical simulation of cyclonic storms FANOOS, NARGIS with assimilation of conventional and satellite observations using 3-DVAR

In this work, the impact of assimilation of conventional and satellite data is studied on the prediction of two cyclonic storms in the Bay of Bengal using the three-dimensional variational data assimilation (3D-VAR) technique. The FANOOS cyclone (December 6?C10, 2005) and the very severe cyclone NARGIS (April 28?CMay 2, 2008) were simulated with a double-nested weather research and forecasting (WRF-ARW) model at a horizontal resolution of 9?km. Three numerical experiments were performed using the WRF model. The back ground error covariance matrix for 3DVAR over the Indian region was generated by running the model for a 30-day period in November 2007. In the control run (CTL), the National Centers for Environmental Prediction (NCEP) global forecast system analysis at 0.5° resolution was used for the initial and boundary conditions. In the second experiment called the VARCON, the conventional surface and upper air observations were used for assimilation. In the third experiment (VARQSCAT), the ocean surface wind vectors from quick scatterometer (QSCAT) were used for assimilation. The CTL and VARCON experiments have produced higher intensity in terms of sea level pressure, winds and vorticity fields but with higher track errors. Assimilation of conventional observations has meager positive impact on the intensity and has led to negative impact on simulated storm tracks. The QSCAT vector winds have given positive impact on the simulations of intensity and track positions of the two storms, the impact is found to be relatively higher for the moderate intense cyclone FANOOS as compared to very severe cyclone NARGIS.     

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.     

An HWRF-based ensemble assessment of the land surface feedback on the post-landfall intensification of Tropical Storm Fay (2008)

While tropical cyclones (TCs) usually decay after landfall, Tropical Storm Fay (2008) initially developed a storm central eye over South Florida by anomalous intensification overland. Unique to the Florida peninsula are Lake Okeechobee and the Everglades, which may have provided a surface feedback as the TC tracked near these features around the time of peak intensity. Analysis is done with the use of an ensemble model-based approach with the Developmental Testbed Center (DTC) version of the Hurricane WRF (HWRF) model using an outer domain and a storm-centered moving nest with 27- and 9-km grid spacing, respectively. Choice of land surface parameterization and small-scale surface features may influence TC structure, dictate the rate of TC decay, and even the anomalous intensification after landfall in model experiments. Results indicate that the HWRF model track and intensity forecasts are sensitive to three features in the model framework: land surface parameterization, initial boundary conditions, and the choice of planetary boundary layer (PBL) scheme. Land surface parameterizations such as the Geophysical Fluid Dynamics Laboratory (GFDL) Slab and Noah land surface models (LSMs) dominate the changes in storm track, while initial conditions and PBL schemes cause the largest changes in the TC intensity overland. Land surface heterogeneity in Florida from removing surface features in model simulations shows a small role in the forecast intensity change with no substantial alterations to TC track.     

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.     

Real-time prediction of a severe cyclone ��Jal�� over Bay of Bengal using a high-resolution mesoscale model WRF (ARW)

Real-time predictions for the JAL severe cyclone formed in November 2010 over Bay of Bengal using a high-resolution Weather Research and Forecasting (WRF ARW) mesoscale model are presented. The predictions are evaluated with different initial conditions and assimilation of observations. The model is configured with two-way interactive nested domains and with fine resolution of 9?km for the region covering the Bay of Bengal. Simulations are performed with NCEP GFS 0.5° analysis and forecasts for initial/boundary conditions. To examine the impact of initial conditions on the forecasts, eleven real-time numerical experiments are conducted with model integration starting at 00, 06, 12, 18 UTC 4 Nov, 5?Nov and 00, 06, 12 UTC 6 Nov and all ending at 00 UTC 8 Nov. Results indicated that experiments starting prior to 18 UTC 04 Nov produced faster moving cyclones with higher intensity relative to the IMD estimates. The experiments with initial time at 18 UTC 04 Nov, 00 UTC 05 Nov and with integration length of 78?h and 72?h produced best prediction comparable with IMD estimates of the cyclone track and intensity parameters. To study the impact of observational assimilation on the model predictions FDDA, grid nudging is performed separately using (1) land-based automated weather stations (FDDAAWS), (2) MODIS temperature and humidity profiles (FDDAMODIS), and (3) ASCAT and OCEANSAT wind vectors (FDDAASCAT). These experiments reduced the pre-deepening period of the storm by 12?h and produced an early intensification. While the assimilation of AWS data has shown meagre impact on intensity, the assimilation of scatterometer winds produced an intermittent drop in intensity in the peak stage. The experiments FDDAMODIS and FDDAQSCAT produced minimum error in track and intensity estimates for a 90-h prediction of the storm.     

Sensitivity of inland decay of North Atlantic tropical cyclones to soil parameters

Using the HURDAT best track analysis of track and intensity of tropical cyclones that made landfall over the continental United States during the satellite era (1980?C2005), we analyze the role of land surface variables on the cyclone decay process. The land surface variables considered in the present study included soil parameters (soil heat capacity and its surrogate soil bulk density), roughness, topography and local gradients of topography. The sensitivity analysis was carried out using a data-adaptive genetic algorithm approach that automatically selects the most suitable variables by fitting optimum empirical functions that estimates cyclone intensity decay in terms of given observed variables. Analysis indicates that soil bulk density (soil heat capacity) has a dominant influence on cyclone decay process. The decayed inland cyclone intensities were found to be positively correlated with the cube of the soil bulk density (heat capacity). The impact of the changes in soil bulk density (heat capacity) on the decayed cyclone intensity is higher for higher intensity cyclones. Since soil bulk density is closely related to the soil heat capacity and inversely proportional to the thermal diffusivity, the observed relationship can also be viewed as the influence of cooling rate of the land surface, as well as the transfer of heat and moisture underneath a land-falling storm. The optimized prediction function obtained by statistical model processes in the present study that predicts inland intensity changes during 6-h interval showed high fitness index and small errors. The performance of the prediction function was tested on inland tracks of eighteen hurricanes and tropical storms that made landfall over the United States between 2001 and 2010. The mean error of intensity prediction for these cyclones varied from 1.3 to 15.8 knots (0.67?C8.12?m?s^?1). Results from the data-driven analysis thus indicate that soil heat flux feedback should be an important consideration for the inland decay of tropical cyclones. Experiments were also undertaken using Weather Research Forecasting (WRF) Advanced Research Version (ARW ver 3.3) to assess the sensitivity of the soil parameters (roughness, heat capacity and bulk density) on the post-landfall structure of select storms. The model was run with 1-km grid spacing, limited area single domain with boundary conditions from the North American Regional Reanalysis. Of different experiments, only the surface roughness change and soil bulk density (heat capacity) change experiments showed some sensitivity to the intensity change. The WRF results thus have a low sensitivity to the land parameters (with only the roughness length showing some impact). This calls for reassessing the land surface response on post-landfall characteristics with more detailed land surface representation within the mesoscale and hurricane modeling systems.     

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.     

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.     

The sensitivity to the microphysical schemes on the skill of forecasting the track and intensity of tropical cyclones using WRF-ARW model

The Advanced Research WRF (ARW) model is used to simulate Very Severe Cyclonic Storms (VSCS) Hudhud (7–13 October, 2014), Phailin (8–14 October, 2013) and Lehar (24–29 November, 2013) to investigate the sensitivity to microphysical schemes on the skill of forecasting track and intensity of the tropical cyclones for high-resolution (9 and 3 km) 120-hr model integration. For cloud resolving grid scale (<5 km) cloud microphysics plays an important role. The performance of the Goddard, Thompson, LIN and NSSL schemes are evaluated and compared with observations and a CONTROL forecast. This study is aimed to investigate the sensitivity to microphysics on the track and intensity with explicitly resolved convection scheme. It shows that the Goddard one-moment bulk liquid-ice microphysical scheme provided the highest skill on the track whereas for intensity both Thompson and Goddard microphysical schemes perform better. The Thompson scheme indicates the highest skill in intensity at 48, 96 and 120 hr, whereas at 24 and 72 hr, the Goddard scheme provides the highest skill in intensity. It is known that higher resolution domain produces better intensity and structure of the cyclones and it is desirable to resolve the convection with sufficiently high resolution and with the use of explicit cloud physics. This study suggests that the Goddard cumulus ensemble microphysical scheme is suitable for high resolution ARW simulation for TC’s track and intensity over the BoB. Although the present study is based on only three cyclones, it could be useful for planning real-time predictions using ARW modelling system.     

Sensitivity of tropical cyclone characteristics to the radial distribution of sea surface temperature

Sea Surface Temperature (SST) is crucial for the development and maintenance of a tropical cyclone (TC) particularly below the storm core region. However, storm data below the core region is the most difficult to obtain, hence it is not clear yet that how sensitive the radial distribution of the SST impact the storm characteristic features such as its inner-core structures, translational speed, track, rainfall and intensity particularly over the Bay of Bengal. To explore the effects of radial SST distribution on the TC characteristics, a series of numerical experiments were carried out by modifying the SST at different radial extents using two-way interactive, triply-nested, nonhydrostatic Advanced Weather Research and Forecast (WRF-ARW) model. It is found that not only the SST under the eyewall (core region) contribute significantly to modulate storm track, translational speed and intensity, but also those outside the eyewall region (i.e., 2–2.5 times the radius of maximum wind (RMW)) play a vital role in defining the storm’s characteristics and structure. Out of all the simulated experiments, storm where the positive radial change of SST inducted within the 75 km of the storm core (i.e., P75) produced the strongest storm. In addition, N300 (negative radial changes at 300 km) produced the weakest storm. Further, it is found that SST, stronger within 2–2.5 times of the RMW for P75 experiment, plays a dominant role in maintaining 10 m wind speed (WS ₁₀), surface entropy flux (SEF) and upward vertical velocity (w) within the eyewall with warmer air temperature (T) and equivalent potential temperature (??_e) within the storm’s eye compared to other experiments.     

Numerical simulation of tropical cyclone thane: role of boundary layer and surface drag parameterization schemes

In the recent times, several advanced numerical models are utilized for the prediction of the intensity, track and landfall time of a cyclone. Still there are number of issues concerning their prediction and the limitation of numerical models in addressing those issues. The most pertinent question is how intensive a cyclone can become before it makes a landfall and where the cyclone moves under the ambient large-scale flow. In this paper, detailed study has been carried out using Weather Research Forecast model with two boundary schemes to address the above question by considering a recent tropical cyclone in Bay of Bengal region of North Indian Ocean. In addition, the impact of the surface drag effect on the low-level winds and the intensity of the cyclone are also studied. The result reveals that large differences are noted in the ocean surface fluxes between YSU and MYJ with MYJ producing relatively higher fluxes than YSU. It is found that the YSU scheme produced a better simulation for the THANE cyclone in terms of winds, pressure distribution and cloud fractions. Comparison with available observations indicated the characteristics of horizontal divergence, vorticity and vector track positions produced by YSU experiment are more realistic than with MYJ and other experiments. However, when the drag coefficient is changed as 0.5 or 2.0 from the default values, appreciable changes in the surface fluxes are not noticed. A maximum precipitation is reported in YSU as compared to the MYJ PBL scheme for the tropical cyclone THANE.     

Impact of various synthetic vortices on cyclone track prediction

Sensitivity experiments are conducted for three cases of cyclones for investigating the impact of different vortex initialization schemes on the structure and track prediction of the cyclone using India Meteorological Department’s Limited Area Model. The surface wind and pressure profiles generated using Holland and Rankine initialization schemes differ from each other. These different generated profiles are compared with the actual data and the root mean square error (RMSE) was calculated between them. In case of the Holland vortex, ‘b’ is found to be equal to 1.5 and 2.0 respectively for two cases of very severe cyclonic storms in the Arabian Sea, namely 6–10 June 1998 and 16–20 May 1999 and 2.25 for the severe cyclonic storm in the Bay of Bengal. The ‘α’ parameter in Rankine’s scheme was found to be 0.5 for two cases and 0.4 for the third system. This shows that cyclones differ even if they attain the same intensity. The values of these parameters i.e. ‘b’ and ‘α’ are used for generating the synthetic wind data for individual cyclones and the same is used in the data assimilation system. The analysis and forecast generated for the above cases using the Holland scheme show that the simulated structure has characteristics closer to the actual storm; however, the Rankine scheme shows a weaker circulation. The mean track error for three cases in the Holland scheme is 93, 149, 257 and 307 km in 12-, 24-, 36- and 48-h forecast. The mean track errors for the Rankine scheme are 152, 274, 345 and 327 km, respectively, for the same period.     

Classification of cyclone hazard prone districts of India

Hazards associated with tropical cyclones are long-duration rotatory high-velocity winds, very heavy rain and storm tide. India has a coastline of about 7,516?km of which 5,400?km is along the mainland. The entire coast is affected by cyclones with varying frequency and intensity. The India Meteorological Department (IMD) is the nodal government agency that provides weather services related to cyclones in India. However, IMD has not identified cyclone-prone districts following any specific definition though the districts for which cyclone warnings are issued have been identified. On the other hand, for the purpose of better cyclone disaster management in the country, it is necessary to define cyclone proneness and identify cyclone-prone coastal districts. It is also necessary to decide degree of hazard proneness of a district by considering cyclone parameters so that mitigation measures are prioritised. In this context, an attempt has been made to prepare a list of cyclone hazard prone districts by adopting hazard criteria. Out of 96 districts under consideration, 12, 45, 31 and 08 districts are in very high, high, moderate and low categories of proneness, respectively. In general, the coastal districts of West Bengal, Orissa, Andhra Pradesh and Tamil Nadu are more prone and are in the high to very high category. The cyclone hazard proneness factor is very high for the districts of Nellore, East Godawari, and Krishna in Andhra Pradesh; Yanam in Puducherry; Balasore, Bhadrak, Kendrapara and Jagatsinghpur in Orissa; and South and North 24 Parganas, Medinipur and Kolkata in West Bengal. The results give a realistic picture of degree of cyclone hazard proneness of districts, as they represent the frequency and intensity of land falling cyclones along with all other hazards like rainfall, wind and storm surge. The categorisation of districts with degree of proneness also tallies with observed pictures. Therefore, this classification of coastal districts based on hazard may be considered for all the required purposes including coastal zone management and planning. However, the vulnerability of the place has not been taken into consideration. Therefore, composite cyclone risk of a district, which is the product of hazard and vulnerability, needs to be assessed separately through detailed study.     

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.