Krishna K. Osuri

Simulation of Bay of Bengal Tropical Cyclones with WRF Model: Impact of Initial and Boundary Conditions

An attempt is made to delineate the relative performances and credentials of GFS, FNL, and NCMRWF global analyses/forecast products as initial and boundary conditions (IBCs) to the WRF-ARW model in the simulation of four Bay of Bengal tropical cyclones (TCs). The results suggest that FNL could simulate horizontal advection of vorticity maxima at 850 hPa; hence, the tracks are more realistic with least errors as compared to GFS and NCMRWF. The mean landfall errors for 24-, 48-, and 72-hour forecasts are 73, 41, and 72 km, respectively. The TC intensity is well captured by NCMRWF IBCs, as it could predict 850 hPa vorticity maxima. The 24-hour accumulated rainfall is well simulated with FNL, and equitable threat score is more than 0.2 up to 100 mm with minimum bias.

Real-Time Track Prediction of Tropical Cyclones over the North Indian Ocean Using the ARW Model

The performance of the Advanced Research version of the Weather Research and Forecasting (ARW) model in real-time prediction of tropical cyclones (TCs) over the north Indian Ocean (NIO) at 27-km resolution is evaluated on the basis of 100 forecasts for 17 TCs during 2007‐11. The analyses are carried out with respectto1)basinsofformation,2)straight-movingandrecurvingTCs,3)TCintensityatmodelinitialization, and 4) season of occurrence. The impact of high resolution (18 and 9km) on TC prediction is also studied. Model results at 27-km resolution indicate that the mean track forecast errors (skill with reference to persistence track) over the NIO were found to vary from 113 to 375km (7%‐51%) for a 12‐72-h forecast. The model showed a right/eastward and slow bias in TC movement. The model is more skillful in track prediction when initialized at the intensity stage of severe cyclone or greater than at the intensity stage of cyclone or lower. The model is more efficient in predicting landfall location than landfall time. The higher-resolution (18 and 9km) predictions yield an improvement in mean track error for the NIO Basin by about 4%‐10% and 8%‐24%, respectively. The 9-km predictions were found to be more accurate for recurving TC track predictions by ;13%‐28% and 5%‐15% when compared with the 27- and 18-km runs, respectively. The 9-km runs improve the intensity prediction by 15%‐40% over the 18-km predictions. This study highlights the capabilities of the operational ARW model over the Indian monsoon region and the continued need for operational forecasts from high-resolution models.

The impact of satellite-derived wind data assimilation on track, intensity and structure of tropical cyclones over the North Indian Ocean

In the present satellite era, remote-sensing data are more useful to improve the initial condition of the model and hence the forecast of tropical cyclones (TCs) when they are in the deep oceans, where conventional observations are unavailable. In this study, an attempt is made to assess the impact of remotely sensed satellite-derived winds on initialization and simulation of TCs over the North Indian Ocean (NIO). For this purpose, four TCs, namely, ‘Nargis’, ‘Gonu’, ‘Sidr’ and ‘KhaiMuk’, are considered, with 13 different initial conditions. Two sets of numerical experiments, with and without satellite-derived wind data assimilation, are conducted using a high-resolution weather research and forecasting (WRF) model. The inclusion of satellite-derived winds through a three-dimensional variational (3DVAR) data assimilation system improves the initial position in 11 cases out of 13 by 34%. The 24-, 48-, 72- and 96-hour mean track forecast improves by 28%, 15%, 41% and 47%, respectively, based on 13 cases. The landfall prediction is significantly improved in 11 cases by about 37%. The intensity prediction also improves by 10–20%. Kinematic and thermodynamic structures of TCs are also better explained, as it could simulate heat and momentum exchange between sea surface and upper air. Due to better simulation of structure, intensity and track, the 24-hour accumulated rainfall intensity and distribution are also well predicted with the assimilation of satellite-derived winds.

Improved Prediction of Bay of Bengal Tropical Cyclones through Assimilation of Doppler Weather Radar Observations

AbstractThe impact on tropical cyclone (TC) prediction from assimilating Doppler weather radar (DWR) observations obtained from the TC inner core and environment over the Bay of Bengal (BoB) is studied. A set of three operationally relevant numerical experiments were conducted for 24 forecast cases involving 5 unique severe/very severe BoB cyclones: Sidr (2007), Aila (2009), Laila (2010), Jal (2010), and Thane (2011). The first experiment (CNTL) used the NCEP FNL analyses for model initial and boundary conditions. In the second experiment [Global Telecommunication System (GTS)], the GTS observations were assimilated into the model initial condition while the third experiment (DWR) used DWR with GTS observations. Assimilation of the TC environment from DWR improved track prediction by 32%–53% for the 12–72-h forecast over the CNTL run and by 5%–25% over GTS and was consistently skillful. More gains were seen in intensity, track, and structure by assimilating inner-core DWR observations as they provided mor...

Impact of Parameterization of Physical Processes on Simulation of Track and Intensity of Tropical Cyclone Nargis (2008) with WRF-NMM Model

The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10 m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error.

An observational perspective on tropical cyclone activity over Indian seas in a warming environment

The genesis of tropical cyclones (TCs) over Indian seas comprising of Bay of Bengal (BoB) and Arabian Sea (AS) is highly seasonal with primary maximum in postmonsoon season (mid-September to December) and secondary maximum during premonsoon season (April and May). The present study is focused to demonstrate changes in genesis and intensity of TCs over Indian seas in warming environment. For this purpose, observational data of TCs, obtained from the India Meteorological Department (IMD), are analyzed. The sea surface temperature (SST), surface wind speed, and potential evaporation factor (PEF), obtained from the International Comprehensive Ocean Atmosphere Data Set (ICOADS), are also analyzed to examine the possible linkage with variations in TC activities over Indian seas. The study period has been divided into two epochs: past cooling period (PCP, period up to 1950) and current warming period (CWP, period after 1950) based on SST anomaly (became positive from 1950) over the BoB and AS. The study reveals that the number of severe cyclones (SCS) increases significantly (statistically significant at 99% confidence level) by about 41% during CWP though no such significant change is observed in cyclonic disturbances (CDs) and cyclones (CS) over Indian seas. It is also observed that the rate of dissipation of CS and SCS over Indian seas has been decreasing considerably by about 63 and 71%, respectively, during CWP. The analysis shows that the BoB contributes about 75% in each category of TCs and remaining 25% by the AS towards total of Indian seas. A detailed examination on genesis and intensity of TC over both the basins and the seasons illustrates that significant enhancement of SCS by about 65% during CWP is confined to the postmonsoon season of the BoB. Further, the BoB is sub-divided into northern, central, and southern sectors and the AS into western and eastern sectors based on genesis of TCs and SST gradient. Results show that in postmonsoon season during CWP, the number of SCS increases significantly by about 71% in southern BoB and 300% over western AS.

Simulation of Tropical Cyclones Over Indian Seas: Data Impact Study Using WRF-Var Assimilation System

The track and intensity prediction of TCs require accurate representation of the vortex in the model initial conditions. The sparsity of observations, both near the vortex and in the surrounding environment, causes either undetectability in standard analyses or poor analysis with ill-defined centers and locations. So, much emphasis over the years has been laid on improving the initial conditions of NWP models, particularly high-resolution mesoscale models in a number of ways. The initial errors obviously have a major impact on the forecast of cyclone tracks using numerical models. One way of overcoming the above difficulty is by improving the initial analysis with the assimilation of conventional and nonconventional observations, which include the development and testing of a range of assimilation methods in the numerical weather prediction (NWP) model. Unfortunately, conventional measurements used to initialize forecast models are unavailable over vast areas of the tropical oceans. So, the high-resolution data required for numerical prediction of TC can be derived by tracking cloud features in the satellite imageries, which provide a large amount of data over data-void regions of the oceans. These derived winds can be used to improve the initialization of the model for the TC forecast. The ability to provide high-density wind coverage over large regions of the tropics makes satellite winds particularly useful for studying TCs (Velden et al. 1998).

A Great Escape from the Bay of Bengal ''Super Sapphire-Phailin'' Tropical Cyclone: A Case of Improved Weather Forecast and Societal Response for Disaster Mitigation

AbstractThe very severe cyclonic storm (VSCS) “Phailin (2013)” was the strongest cyclone that hit the eastern coast of the India Odisha state since the supercyclone of 1999. But the same story of casualties was not repeated as that of 1999 where approximately 10 000 fatalities were reported. In the case of Phailin, a record 1 million people were evacuated across 18 000 villages in both the Odisha and Andhra Pradesh states to coastal shelters following the improved operational forecast guidance that benefited from highly skillful and accurate numerical model guidance for the movement, intensity, rainfall, and storm surge. Thus, the property damage and death toll were minimized through the proactive involvement of three-tier disaster management agencies at central, state, and district levels.

A Comparative Study on Performance of Analysis Nudging and 3DVAR in Simulation of a Heavy Rainfall Event Using WRF Modeling System

The present study focuses on the performance-based comparison of simulations carried out using nudging (NUD) technique and three-dimensional variational (3DVAR) data assimilation system (3DV) of a heavy rainfall event occurred during 25–28 June 2005 along the west coast of India. The Indian conventional and nonconventional observations are used in the 3DV experiment. Three numerical experiments are conducted using WRF modeling system, the model is integrated upto 54 hours from the initial time 0000 UTC of 25 June 2005. It is noticed that the meteorological parameters are improved in the resulting high-resolution analyses prepared by NUD and 3DV compared to without data assimilation experiment (i.e., called CNTL experiment). However, after the successful inclusion of observations using the 3DVAR data assimilation technique, the model is able to simulate better structure of the convective organization as well as prominent synoptic features associated with the mid-tropospheric cyclones (MTC) than the NUD experiment and well correlated with the observations. The simulated location and intensity of rainfall is also improved in 3DV simulation as compared with other experiments. Similar results are noticed in the root mean squar errors, correlation coefficients, and Equitable Threat Scores between TRMM and model simulated rainfall for all the three experiments.

The Role of Land Surface Processes on Tropical Cyclones: Introduction to Land Surface Models

The role of land surface processes in land falling tropical cyclones is an area of emerging interest. Tropical cyclones are formed as organized convection over warm water (typically 26.5 °C, Gray, 1968) packing tremendous amounts of energy. Tropical cyclones have a typical size of 200-2000 km with a life span of about one to two weeks. The cyclone and its environment are interlinked. There are a number of environmental factors that are important for sustaining and intensifying a tropical cyclone including low humidity, cooler sea surface temperature (SST), or higher tropopause temperatures, dry air intrusion from land masses, and large vertical wind shear (Gray, 1968; McBride and Zehr, 1981). However a number of environmental conditions can change the evolution of a landfalling storm.