Prediction of monsoon rainfall with a nested grid mesoscale limited area model

At the India Meteorological Department (IMD), New Delhi, a 12-level limited area model with 100 km horizontal resolution has been in use for weather forecasting. The present study uses this model together with a higher horizontal resolution (50 km) and vertical resolution (16-levels) model to examine the impact of increased resolution to simulate mesoscale features of rainfall during monsoon disturbances. The model was run for 22 days in the month of August 1997 and one week in September 1997 during three monsoon depressions and one cyclonic storm in the Bay of Bengal. The model results are compared with observations. The study shows that the model can capture mesoscale convective organization associated with monsoon depression.     

Relationship between summer monsoon rainfall and cyclogenesis over Bay of Bengal during post-monsoon (October–December) season

In this study, an attempt has been made to examine the relationship between summer monsoon rainfall (June–September) and the total number of depressions, cyclones and severe cyclones (TNDC) over Bay of Bengal during the post-monsoon (October–December) season. The seasonal rainfall of the subdivisions (located in south India) (referred as rainfall index – RI), is positively and significantly correlated (r=0.59; significant at >99% level) with the TNDC during the period, 1984–2013. By using the first differences (current season minus previous season), the correlations are enhanced and a remarkably high correlation of 0.87 is observed between TNDC and RI for the recent period, 1993–2013. The average seasonal genesis potential parameter (GPP) showed a very high correlation of 0.84 with the TNDC. A very high correlation of 0.83 is observed between GPP and RI for the period, 1993–2013. The relative vorticity and mid-tropospheric relative humidity are found to be the dominant terms in GPP. The GPP was 3.5 times higher in above (below) normal RI in which TNDC was 4 (2). It is inferred that RI is playing a key role in TNDC by modulating the environmental conditions (low level vorticity and relative humidity) over Bay of Bengal during post-monsoon season which could be seen from the very high correlation of 0.87 (which explains 76% variability in TNDC). For the first time, we show that RI is a precursor for the TNDC over Bay of Bengal during post-monsoon season. Strong westerlies after the SW monsoon season transport moisture over the subdivisions towards Bay of Bengal due to cyclonic circulation. This circulation favours upward motion and hence transport moisture vertically to mid-troposphere which causes convective instability and this in turn favour more number of TNDC, under above-normal RI year.     

Swarm intelligence and neural nets in forecasting the maximum sustained wind speed along the track of tropical cyclones over Bay of Bengal

Tropical cyclones are well-known extreme weather and the cause of considerable damages, injuries and loss of life. The assessment of the maximum sustained wind speed along the track of the tropical cyclones is very important for estimating the strength of the cyclones. The swarm intelligence in the form of ant colony optimization (ACO) technique is introduced in this study to compute the pheromone deposition along the track of tropical cyclones followed by neural nets to forecast the maximum sustained wind speed of the cyclones occurring over the Bay of Bengal of North Indian Ocean. The ACO is a nonlinear problem-based meta-heuristic optimization method for finding approximate solutions to discrete optimization problems and simulates the decision-making processes of ant colony similar to other adaptive learning techniques. The method has shown its application potential in various fields including the prediction of monsoon rainfall. In this study, the amount of pheromone deposition during the successive stages of the cyclones has been estimated. A range of minimum central pressure (MCP), central pressure drop (PD), maximum sustained wind speed (MSWS) and intensity (T-No) associated with the cyclones of Bay of Bengal are utilized to form the input matrix of the neural nets. The neural nets are trained to forecast the maximum sustained wind speed along the track of the tropical cyclones over Bay of Bengal. The result reveals that the errors in forecasting the MSWS along the track of tropical cyclones with 6, 12, 18 and 24 h lead time are 2.6, 2.9, 3.1 and 4.8, respectively. The result is compared with the existing dynamical, statistical and adaptive models to evaluate the skill of the present model. The result is well validated with observation.     

Spatio-temporal variability of summer monsoon rainfall over Orissa in relation to low pressure systems

The summer monsoon rainfall over Orissa occurs mostly due to low pressure systems (LPS) developing over the Bay of Bengal and moving along the monsoon trough. A study is hence undertaken to find out characteristic features of the relationship between LPS over different regions and rain-fall over Orissa during the summer monsoon season (June-September). For this purpose, rainfall and rainy days over 31 selected stations in Orissa and LPS days over Orissa and adjoining land and sea regions during different monsoon months and the season as a whole over a period of 20 years (1980-1999) are analysed. The principal objective of this study is to find out the role of LPS on spatial and temporal variability of summer monsoon rainfall over Orissa. The rainfall has been significantly less than normal over most parts of Orissa except the eastern side of Eastern Ghats during July and hence during the season as a whole due to a significantly less number of LPS days over northwest Bay in July over the period of 1980-1999. The seasonal rainfall shows higher interannual variation (increase in coefficient of variation by about 5%) during 1980-1999 than that during 1901-1990 over most parts of Orissa except northeast Orissa. Most parts of Orissa, especially the region extending from central part of coastal Orissa to western Orissa (central zone) and western side of the Eastern Ghats get more seasonal monsoon rainfall with the development and persistence of LPS over northwest Bay and their subsequent movement and persistence over Orissa. The north Orissa adjoining central zone also gets more seasonal rainfall with development and persistence of LPS over northwest Bay. While the seasonal rainfall over the western side of the Eastern Ghats is adversely affected due to increase in LPS days over west central Bay, Jharkhand and Bangladesh, that over the eastern side of the Eastern Ghats is adversely affected due to increase in LPS days over all the regions to the north of Orissa. There are significant decreasing trends in rainfall and number of rainy days over some parts of southwest Orissa during June and decreasing trends in rainy days over some parts of north interior Orissa and central part of coastal Orissa during July over the period of 1980-1999     

Impact of sea surface temperature in modulating movement and intensity of tropical cyclones

It is well recognized that sea surface temperature (SST) plays a dominant role in the formation and intensification of tropical cyclones. A number of observational/empirical studies were conducted at different basins to investigate the influence of SST on the intensification of tropical cyclones and in turn, modification in SST by the cyclone itself. Although a few modeling studies confirmed the sensitivity of model simulation/forecast to SST, it is not well quantified, particularly for Bay of Bengal cyclones. The present study is designed to quantify the sensitivity of SST on mesoscale simulation of an explosively deepening storm over the Bay of Bengal, i.e., Orissa super cyclone (1999). Three numerical experiments are conducted with climatological SST, NCEP (National Center for Environmental Prediction) skin temperature as SST, and observed SST (satellite derived) toward 5-day simulation of the storm using mesoscale model MM5. At model initial state, NCEP skin temperature and observed SST over the Bay of Bengal are 1–2°C warmer than climatological SST, but cooler by nearly 1°C along the coastline. Observed SST shows a number of warm patches in the Bay of Bengal compared with NCEP skin temperature. The simulation results indicate that the sea surface temperature has a significant impact on model-simulated track and intensity of the cyclonic storm. The track and intensity of the storm is better simulated with the use of satellite-observed SST.     

Some characteristics of very heavy rainfall over Orissa during summer monsoon season

Orissa is one of the most flood prone states of India. The floods in Orissa mostly occur during monsoon season due to very heavy rainfall caused by synoptic scale monsoon disturbances. Hence a study is undertaken to find out the characteristic features of very heavy rainfall (24 hours rainfall ≥125 mm) over Orissa during summer monsoon season (June–September) by analysing 20 years (1980–1999) daily rainfall data of different stations in Orissa. The principal objective of this study is to find out the role of synoptic scale monsoon disturbances in spatial and temporal variability of very heavy rainfall over Orissa. Most of the very heavy rainfall events occur in July and August. The region, extending from central part of coastal Orissa in the southeast towards Sambalpur district in the northwest, experiences higher frequency and higher intensity of very heavy rainfall with less interannual variability. It is due to the fact that most of the causative synoptic disturbances like low pressure systems (LPS) develop over northwest (NW) Bay of Bengal with minimum interannual variation and the monsoon trough extends in west-northwesterly direction from the centre of the system. The very heavy rainfall occurs more frequently with less interannual variability on the western side of Eastern Ghat during all the months and the season except September. It occurs more frequently with less interannual variability on the eastern side of Eastern Ghat during September. The NW Bay followed by Gangetic West Bengal/Orissa is the most favourable region of LPS to cause very heavy rainfall over different parts of Orissa except eastern side of Eastern Ghat. The NW Bay and west central (WC) Bay are equally favourable regions of LPS to cause very heavy rainfall over eastern side of Eastern Ghat. The frequency of very heavy rainfall does not show any significant trend in recent years over Orissa except some places in north-east Orissa which exhibit significant rising trend in all the monsoon months and the season as a whole.     

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.     

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.     

Source of a freshwater influx at the last glacial maximum in the Indian Ocean: An alternative interpretation

Recent analysis of a sediment core in the eastern Arabian Sea revealed a negative pulse of about 1% in the δ¹⁸O value of the planktonic Foraminifera around the last glacial maximum (LGM). This pulse has been attributed to (i) increased runoff into the Bay of Bengal from the east-flowing south Indian rivers due to enhancement of the northeast winter monsoon, and (ii) an increase in Arabian sea-surface temperature caused by the weakening of the southwest monsoon at the LGM. We show that the speculation on which the latter hypothesis is based, is not supported by observational data and cannot fully account for the observed magnitude of the spike. With a view to assessing the validity of the first mechanism, we have modelled the mixed layer of the Bay of Bengal as a well-mixed box. The model calculations show that to account for the pulse requires a change of about 10% in either the annual rate of river input or its isotopic composition. For the northeast monsoon to account for the pulse it would mean that the rainfall should have increased by a factor of five to ten during the LGM. No evidence for such an increase is indicated in the available palaeoclimatic data. We explain the freshwater spike by invoking increased discharge of glacial meltwater from the Tibetan plateau into the Bay of Bengal. We show that the proxy climate data from the Indo-Tibetan region that has become available recently provides substantial evidence for the occurrence of a warming event around the LGM, which supports our mechanism.     

Synoptic weather conditions during BOBMEX

We document the flow features, which are associated with the important synoptic systems that affected the Bay of Bengal (BoB) and its neighbourhood and controlled the convective activity there during BOBMEX. The monsoon during July and August, 1999 was subdued. It was slightly more active in the initial phase of BOBMEX that commenced on 15th July 1999 and continued up to first week of August 1999 but weakened during the second half of August. The convection was accordingly affected, reducing the rainfall over India. There were several active and weak spells of convection over the Bay of Bengal that manifested in five low pressure systems, of which two became depressions.     

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.     

Impact of Southern Oscillation on the Frequency of Monsoon Depressions in the Bay of Bengal

The impact of Southern Oscillation on thecyclogenesis over the Bay of Bengal duringthe summer monsoon has been investigated.The analysis of correlation coefficients(CCs) between the frequency of monsoondepressions and the Southern OscillationIndex (SOI) reveals that more depressionsform during July and August of El Niñoyears. Due to this, the seasonal frequencyof monsoon depressions remains little higherduring El Niño epochs even though thecorrelations for June and September are notsignificant. The CCs for July and August aresignificant at the 99% level.The El Niño-Southern Oscillation (ENSO)is known to affect Indian MonsoonRainfall (IMR) adversely. The enhancedcyclogenesis over the Bay of Bengal duringJuly and August is an impact of ENSO whichneeds to be examined closely. Increasedcyclogenesis over the Bay of Bengal may bereducing the deficiency in IMR duringEl Niño years by producing more rainfallover the eastern parts of India duringJuly and August. Thus there is a considerablespatial variation in the impact of ENSOon the monsoon rainfall over India and El Niñoneed not necessarily imply a monsoonfailure everywhere in India.The area of formation of monsoon depressionsshifts eastward during El Niño years.Warmer sea surface temperature (SST) anomaliesprevail over northwest and adjoiningwestcentral Bay of Bengal during premonsoon andmonsoon seasons of El Niño years.May minus March SOI can provide useful predictionsof monsoon depression frequencyduring July and August.     

Tropical cyclone prediction over Bay of Bengal: a comparison of the performance of NCEP operational HWRF, NCAR ARW, and MM5 models

Much progress has been made in the area of tropical cyclone prediction using high-resolution mesoscale models based on community models developed at National Centers for Environmental Predication (NCEP) and National Center for Atmospheric Research (NCAR). While most of these model research and development activities are focused on predicting hurricanes in the Atlantic and Eastern Pacific domains, there has been much interest in using these models for tropical cyclone prediction in the North Indian Ocean region, particularly for Bay of Bengal storms that are known historically causing severe damage to life and property. In this study, the advanced operational hurricane modeling system developed at NCEP, known as the Hurricane Weather Research and Forecast (HWRF) model, is used to simulate two recent Bay of Bengal tropical cyclones??Nargis of November 2007 and Sidr of April 2008. The advanced NCEP operational vortex initialization procedure is adapted for simulating these Bay of Bengal tropical cyclones. Two additional regional models, the NCAR Advanced Research WRF and NCAR/Penn State University Mesoscale Model version 5 (MM5) are also used in simulating these storms. Results from these experiments highlight the superior performance of HWRF model over other models in predicting the Bay of Bengal cyclones. These results also suggest the need for a sophisticated vortex initialization procedure in conjunction with a model designed exclusively for tropical cyclone prediction for operational considerations.     

Simulation of marine boundary layer characteristics using a 1-D PBL model over the Bay of Bengal during BOBMEX-99

The characteristic features of the marine boundary layer (MBL) over the Bay of Bengal during the southwest monsoon and the factors influencing it are investigated. The Bay of Bengal and Monsoon Experiment (BOBMEX) carried out during July–August 1999 is the first observational experiment under the Indian Climate Research Programme (ICRP). A very high-resolution data in the vertical was obtained during this experiment, which was used to study the MBL characteristics off the east coast of India in the north and south Bay of Bengal. Spells of active and suppressed convection over the Bay were observed, of which, three representative convective episodes were considered for the study. For this purpose a one-dimensional multi-level PBL model with a TKE-ε closure scheme was used. The soundings, viz., the vertical profiles of temperature, humidity, zonal and meridional component of wind, obtained onboard ORV Sagar Kanya and from coastal stations along the east coast are used for the study. The temporal evolution of turbulent kinetic energy, marine boundary layer height (MBLH), sensible and latent heat fluxes and drag coefficient of momentum are simulated for different epochs of monsoon and monsoon depressions during BOBMEX-99.The model also generates the vertical profiles of potential temperature, specific humidity, zonal and meridional wind. These simulated values compared reasonably well with the observations available from BOBMEX.     

A statistical cyclone intensity prediction (SCIP) model for the Bay of Bengal

A statistical model for predicting the intensity of tropical cyclones in the Bay of Bengal has been proposed. The model is developed applying multiple linear regression technique. The model parameters are determined from the database of 62 cyclones that developed over the Bay of Bengal during the period 1981–2000. The parameters selected as predictors are: initial storm intensity, intensity changes during past 12 hours, storm motion speed, initial storm latitude position, vertical wind shear averaged along the storm track, vorticity at 850 hPa, Divergence at 200 hPa and sea surface temperature (SST). When the model is tested with the dependent samples of 62 cyclones, the forecast skill of the model for forecasts up to 72 hours is found to be reasonably good. The average absolute errors (AAE) are less than 10 knots for forecasts up to 36 hours and maximum forecast error of order 14 knots occurs at 60 hours and 72 hours. When the model is tested with the independent samples of 15 cyclones (during 2000 to 2007), the AAE is found to be less than 13 knots (ranging from 5.1 to 12.5 knots) for forecast up to 72 hours. The model is found to be superior to the empirical model proposed by Roy Bhowmik et al (2007) for the Bay of Bengal.     

Variations of Indian monsoon precipitation during the last 32 kyr reflected in the surface hydrography of the Western Bay of Bengal

Hydrography of the Bay of Bengal is highly influenced by the river runoff and rainfall during the southwest monsoon. We have reconstructed δ¹⁸Osw, sea surface salinity and sea surface temperature (SST) changes in the Bay of Bengal by using paired measurements of δ¹⁸O and Mg/Ca in a planktonic foraminifera species Globigerinoides ruber from core SK218/1 in the western Bay of Bengal in order to understand the rainfall variability associated with southwest monsoon over the past 32 kyr. Our SST reconstructions reveal that Bay of Bengal was ～3.2 °C cooler during the LGM as compared to present day temperature and a ～3.5 °C rise in SST is documented from 17 to 10 ka. Both SST and δ¹⁸Osw exhibit greater amplitude fluctuations during MIS 2 which is attributable to the variability of NE monsoon rainfall and associated river discharge into the Bay of Bengal in association with strong seasonal temperature contrast. On set of strengthening phase of SW monsoon was started during Bølling/Allerød as evidenced by the low δ¹⁸Osw values ～14.7 ka. δ¹⁸Osw show consistently lower values during Holocene (with an exception around 5 ka), which suggests that the freshening of Bay of Bengal due to heavy precipitation and river discharge caused by strong SW monsoon. Results of this study signify that the maximum fluctuations of the NE monsoon rainfall during MIS 2 appear to be controlled by the strong seasonality and boundary conditions.     

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.     

Simulation of barotropic wind-driven circulation in the upper layers of Bay of Bengal and Andaman Sea during the southwest and northeast monsoon seasons using observed winds

A two-dimensional, nonlinear, vertically integrated model was used to simulate depth-mean wind-driven circulation in the upper Ekman layers of the Bay of Bengal and Andaman Sea. The model resolution was one third of a degree in the latitude and longitude directions. Monthly mean wind stress components used to drive the model were obtained from the climatic monthly mean wind data compiled by Hastenrath and Lamb. A steady-state solution was obtained after numerical integration of the model for 15 days. The sensitivity of the model to two types of open boundary conditions, namely, a radiation type and clamped type, was tested. A comparison of simulated results for January with available ship drift data showed that the application of the latter along the open boundary could reproduce all the observed features near the boundary and the interior of the model domain. The model was integrated for 365 days to study the circulation during the southwest and northeast monsoon seasons. The model was successful in simulating the broad features of circulation including gyres and eddies observed during both the seasons, the development of north equatorial current during the northeast monsoon period and eastward moving monsoon drift current up to 90°E during the southwest monsoon season. During the latter season, two anticyclonic gyres were observed in the central and the southern parts of the Bay. A cyclonic type of circulation was prevalent in the central and western parts of the Bay of Bengal during the northeast monsoon months of November and December. The simulated western boundary current along the east coast of India, flows northward and southward during the southwest and northeast monsoon seasons respectively. It is presumed that this western boundary current, simulated during both the seasons, is locally wind-driven.     

Observed daily large-scale rainfall patterns during BOBMEX-1999

A daily rainfall dataset and the corresponding rainfall maps have been produced by objective analysis of rainfall data. The satellite estimate of rainfall and the raingauge values are merged to form the final analysis. Associated with epochs of monsoon these rainfall maps are able to show the rainfall activities over India and the Bay of Bengal region during the BOBMEX period. The intra-seasonal variations of rainfall during BOBMEX are also seen using these data. This dataset over the oceanic region compares well with other available popular datasets like GPCP and CMAP. Over land this dataset brings out the features of monsoon in more detail due to the availability of more local raingauge stations.     

Experimental superensemble forecasts of tropical cyclones over the Bay of Bengal

This study entails the implementation of an experimental real time forecast capability for tropical cyclones over the Bay of Bengal basin of North Indian Ocean. This work is being built on the experience gained from a number of recent studies using the concept of superensemble developed at the Florida State University (FSU). Real time hurricane forecasts are one of the major components of superensemble modeling at FSU. The superensemble approach of training followed by real time forecasts produces the best forecasts for tracks and intensity (up to 5 days) of Atlantic hurricanes and Pacific typhoons. Improvements in track forecasts of about 25–35% compared to current operational forecast models has been noted over the Atlantic Ocean basin. The intensity forecasts for hurricanes are only marginally better than the best models. In this paper, we address tropical cyclone forecasts over the Bay of Bengal for the years 1996–2000. The main result from this study is that the position and intensity errors for tropical cyclone forecasts over the Bay of Bengal from the multimodel superensemble are generally less than those of all of the participating models during 1- to 3-day forecasts. Some of the major tropical cyclones, such as the November 1996 Andhra Pradesh cyclone and October 1999 Orissa super cyclone were well handled by this superensemble approach. A conclusion from this study is that the proposed approach may be a viable way to construct improved forecasts of Bay of Bengal tropical cyclone positions and intensity.