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

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

Impact of Doppler weather radar data on thunderstorm simulation during STORM pilot phase—2009

This study assesses the impact of Doppler weather radar (DWR) data (reflectivity and radial wind) assimilation on the simulation of severe thunderstorms (STS) events over the Indian monsoon region. Two different events that occurred during the Severe Thunderstorms Observations and Regional Modeling (STORM) pilot phase in 2009 were simulated. Numerical experiments—3DV (assimilation of DWR observations) and CNTL (without data assimilation)—were conducted using the three-dimensional variational data assimilation technique with the Advanced Research Weather Research and Forecasting model (WRF-ARW). The results show that consistent with prior studies the 3DV experiment, initialized by assimilation of DWR observations, performed better than the CNTL experiment over the Indian region. The enhanced performance was a result of improved representation and simulation of wind and moisture fields in the boundary layer at the initial time in the model. Assimilating DWR data caused higher moisture incursion and increased instability, which led to stronger convective activity in the simulations. Overall, the dynamic and thermodynamic features of the two thunderstorms were consistently better simulated after ingesting DWR data, as compared to the CNTL simulation. In the 3DV experiment, higher instability was observed in the analyses of thermodynamic indices and equivalent potential temperature (θ _e) fields. Maximum convergence during the mature stage was also noted, consistent with maximum vertical velocities in the assimilation experiment (3DV). In addition, simulated hydrometeor (water vapor mixing ratio, cloud water mixing ratio, and rain water mixing ratio) structures improved with the 3DV experiment, compared to that of CNTL. From the higher equitable threat scores, it is evident that the assimilation of DWR data enhanced the skill in rainfall prediction associated with the STS over the Indian monsoon region. These results add to the body of evidence now which provide consistent and notable improvements in the mesoscale model results over the Indian monsoon region after assimilating DWR fields.     

Real-time nowcast of a cloudburst and a thunderstorm event with assimilation of Doppler weather radar data

Extreme weather events such as cloudburst and thunderstorms are great threat to life and property. It is a great challenge for the forecasters to nowcast such hazardous extreme weather events. Mesoscale model (ARPS) with real-time assimilation of DWR data has been operationally implemented in India Meteorological Department (IMD) for real-time nowcast of weather over Indian region. Three-dimensional variational (ARPS3DVAR) technique and cloud analysis procedure are utilized for real-time data assimilation in the model. The assimilation is performed as a sequence of intermittent cycles and complete process (starting from reception, processing and assimilation of DWR data, running of ARPS model and Web site updation) takes less than 20 minutes. Thus, real-time nowcast for next 3 h from ARPS model is available within 20 minutes of corresponding hour. Cloudburst event of September 15, 2011, and thunderstorm event of October 22, 2010, are considered to demonstrate the capability of ARPS model to nowcast the extreme weather events in real time over Indian region. Results show that in both the cases, ARPS3DVAR and cloud analysis technique are able to extract hydrometeors from radar data which are transported to upper levels by the strong upward motion resulting in the distribution of hydrometeors at various isobaric levels. Dynamic and thermodynamic structures of cloudburst and thunderstorm are also well simulated. Thus, significant improvement in the initial condition is noticed. In the case of cloudburst event, the model is able to capture the sudden collisions of two or more clouds during 09–10 UTC. Rainfall predicted by the model during cloudburst event is over 100 mm which is very close to the observed rainfall (117 mm). The model is able to predict the cloudburst with slight errors in time and space. Real-time nowcast of thunderstorm shows that movement, horizontal extension, and north–south orientation of thunderstorm are well captured during first hour and deteriorate thereafter. The amount of rainfall predicted by the model during thunderstorm closely matches with observation with slight errors in the location of rainfall area. The temporal and spatial information predicted by ARPS model about the sudden collision/merger and broken up of convective cells, intensification, weakening, and maintaining intensity of convective cells has added value to a human forecast.     

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.     

Impact of period and timescale of FDDA analysis nudging on the numerical simulation of tropical cyclones in the Bay of Bengal

In this study, the impact of four-dimensional data assimilation (FDDA) analysis nudging is examined on the prediction of tropical cyclones (TC) in the Bay of Bengal to determine the optimum period and timescale of nudging. Six TCs (SIDR: November 13–16, 2007; NARGIS: April 29–May 02, 2008; NISHA: November 25–28, 2008; AILA: May 23–26, 2009; LAILA: May 18–21, 2010; JAL: November 04–07, 2010) were simulated with a doubly nested Weather Research and Forecasting (WRF) model with a horizontal resolution of 9 km in the inner domain. In the control run for each cyclone, the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) analysis and forecasts at 0.5° resolution are used for initial and boundary conditions. In the FDDA experiments available surface, upper air observations obtained from NCEP Atmospheric Data Project (ADP) data sets were used for assimilation after merging with the first guess through objective analysis procedure. Analysis nudging experiments with different nudging periods (6, 12, 18, and 24 h) indicated a period of 18 or 24 h of nudging during the pre-forecast stage provides maximum impact on simulations in terms of minimum track and intensity forecasts. To determine the optimum timescale of nudging, two cyclone cases (NARGIS: April 28–May 02, 2008; NISHA: November 25–28, 2008) were simulated varying the inverse timescales as 1.0e?4 to 5.0e?4 s^?1 in steps of 1.0e?4 s^?1. A positive impact of assimilation is found on the simulated characteristics with a nudging coefficient of either 3.0e?4 or 4.0e?4 s^?1 which corresponds to a timescale of about 1 h for nudging dynamic (u,v) and thermodynamical (t,q) fields.     

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.     

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.     

Numerical simulation of sea breeze characteristics observed at tropical coastal site,Kalpakkam

Sea breeze characteristics around Kalpakkam tropical coastal site are studied using an Advanced Regional Prediction System (ARPS) mesoscale model, which is non-hydrostatic, compressible atmospheric prediction model following the terrain coordinate system. Various options such as surface physics, atmospheric radiation physics, Coriolis force, microphysics, cumulus parameterization and 1.5 level TKE closure scheme for diffusion are included in the model. A joint meteorological field experiment was carried out by IITM-Pune and IGCAR at Kalpakkam by deploying state-of-the-art sensors and tether balloon systems for observing the height profiles of meteorological parameters. The data obtained from the field experiment are used here to compare the results from numerical simulations. From the simulated results, it is seen that duration of the sea breeze is 6 hours which agrees well with the observations. The height of the Thermal Internal Boundary Layer (TIBL) is also simulated from the vertical profiles of potential temperature. Simulated wind speed and wind directions are compared with the 50 m tower data and potential temperature profiles are compared with the kytoon data. Results are in good agreement with the observed values except during night time wherein a small difference is seen in the wind speed.     

Impact of modification of initial cyclonic structure on the prediction of a cyclone over the Arabian Sea

Most tropical cyclones have very few observations in their vicinity. Hence either they go undetected in standard analyses or are analyzed very poorly, with ill defined centres and locations. Such initial errors obviously have major impact on the forecast of cyclone tracks using numerical models. One way of overcoming the above difficulty is to remove the weak initial vortex and replace it with a synthetic vortex (with the correct size, intensity and location) in the initial analysis. The objective of this study is to investigate the impact of introducing NCAR–AFWA synthetic vortex scheme in the regional model MM5 on the simulation of a tropical cyclone formed over the Arabian Sea during November 2003. Two sets of numerical experiments are conducted in this study. While the first set utilizes the NCEP reanalysis as the initial and lateral boundary conditions, the second set utilizes the NCAR–AFWA synthetic vortex scheme. The results of the two sets of MM5 simulations are compared with one another as well as with the observations and the NCEP reanalysis. It is found that inclusion of the synthetic vortex has resulted in improvements in the simulation of wind asymmetries, warm temperature anomalies, stronger vertical velocity fields and consequently in the overall structure of the tropical cyclone. The time series of the minimum sea level pressure and maximum wind speed reveal that the model simulations are closer to observations when synthetic vortex was introduced in the model. The central minimum pressure reduces by 17 hPa while the maximum wind speed associated with the tropical cyclone enhances by 17 m s ⁻¹ with the introduction of the synthetic vortex. While the lowest central pressure estimated from the satellite image is 988 hPa, the corresponding value in the synthetic vortex simulated cyclone is 993 hPa. Improvements in the overall structure and initial location of the center of the system have contributed to considerable reduction in the vector track prediction errors ie. 642 km in 24 h, 788 km in 48 h and 1145 km in 72 h. Further, simulation with the synthetic vortex shows realistic spatial distribution of the precipitation associated with the tropical cyclone.     

The interaction of large scale and mesoscale environment leading to formation of intense thunderstorms over Kolkata Part I: Doppler radar and satellite observations

The weather systems that predominantly affect the eastern and northeastern parts of India during the pre-monsoon summer months (March, April and May) are severe thunderstorms, known as Nor’westers. The storms derive their names from the fact that they frequently strike cities and towns in the southern part of West Bengal in the afternoon from the north-west direction while traveling far from its place of genesis over the Bihar plateau. The storms are devastating in nature particularly due to strong (gusty) winds, heavy rains and hails associated with it. Although these storms are well known for its power of causing damages, studies on them are relatively few due to their small size and sparse network of observations. To address this important issue, the evolution of two Nor’westers of 12 March and 22 May 2003 over Kolkata is studied in detail in this paper using hourly Doppler weather radar (DWR) observations and high resolution Meteosat-5 imageries. In addition, supporting meteorological reports are used to find the large scale conditions that influence the moisture convergence and vertical wind shear. The genesis of both the storms is found to be over Bihar-Jharkhand region and beyond the range of the DWR. The satellite observations are found to be useful in identifying the location and initiation of the storms. The movements of the storms are captured by the DWR estimated vertical cross-section of reflectivities. The Doppler estimate shows that the 12 March storm had a vertical extent of about 10–12 km at the time of maturity and that of 22 May reaching up to 18 km signifying deep convection associated with these events. The genesis, maturity and dissipation are well brought out by the hourly DWR and satellite imageries. The DWR observations suggest that the systems move at a speed of 20–25 m/s. The DWR estimated precipitation shows a detailed spatial distribution around Kolkata with several localized zones of heavy rain and this is found to be well supported by the nearby station observations. This study establishes that DWR observations along with hourly satellite imageries are able to capture the evolution of Nor’westers. The study also shows that the composite DWR-satellite information is a reliable tool for nowcasting the location, time and path of movement of Nor’westers. Based on these observations, a conceptual model of the Nor’wester is proposed.     

The effect of a surface data assimilation technique and the traditional four-dimensional data assimilation on the simulation of a monsoon depression over India using a mesoscale model

The objective of this study is to investigate the impact of a surface data assimilation (SDA) technique, together with the traditional four-dimensional data assimilation (FDDA), on the simulation of a monsoon depression that formed over India during the field phase of the 1999 Bay of Bengal Monsoon Experiment (BOBMEX). The SDA uses the analyzed surface data to continuously assimilate the surface layer temperature as well as the water vapor mixing ratio in the mesoscale model. The depression for the greater part of this study was offshore and since successful application of the SDA would require surface information, a method of estimating surface temperature and surface humidity using NOAA-TOVS satellites was used. Three sets of numerical experiments were performed using a coupled mesoscale model. The first set, called CONTROL, uses the NCEP (National Center for Environmental Prediction) reanalysis for the initial and lateral boundary conditions in the MM5 simulation. The second and the third sets implemented the SDA of temperature and moisture together with the traditional FDDA scheme available in the MM5 model. The second set of MM5 simulation implemented the SDA scheme only over the land areas, and the third set extended the SDA technique over land as well as sea. Both the second and third sets of the MM5 simulation used the NOAA-TOVS and QuikSCAT satellite and conventional upper air and surface meteorological data to provide an improved analysis. The results of the three sets of MM5 simulations are compared with one another and with the analysis and the BOBMEX 1999 buoy, ship, and radiosonde observations. The predicted sea level pressure of both the model runs with assimilation resembles the analysis closely and also captures the large-scale structure of the monsoon depression well. The central sea level pressures of the depression for both the model runs with assimilation were 2–4 hPa lower than the CONTROL. The results of both the model runs with assimilation indicate a larger spatial area as well as increased rainfall amounts over the coastal regions after landfall compared with the CONTROL. The impact of FDDA and SDA, the latter over land, resulted in reduced errors of the following: 1.45 K in temperature, 0.39 m s⁻¹ in wind speed, and 14° in wind direction compared with the BOBMEX buoy observation, and 1.43 m s⁻¹ in wind speed, 43° in wind direction, and 0.75% in relative humidity compared with the CONTROL. The impact of SDA over land and sea compared with SDA over land only showed a further marginal reduction of errors: 0.23 K in air temperature (BOBMEX buoy) and 1.33 m s⁻¹ in wind speed simulations.     

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.     

Assessing the influence of assimilating radar-observed radial winds on the simulation of a tropical cyclone

Observations by Doppler weather radar are crucial for nowcasting and short-time forecasting of severe weather events as they bring in refined information of the atmosphere. However, due to the inevitable noises and non-meteorological signals, they cannot be assimilated straightforwardly into a numerical model. In the present study, assimilation of the radial component of wind velocity observed by two Doppler radars is performed in the numerical simulation of Supertyphoon Rammasun (2014) just before its landfall. After several quality-control steps, the radar-observed radial velocities are de-aliased, noise-reduced and assimilated into the model to improve initial conditions for the high-resolution simulation. Results show that only when using global background error covariance matrix can the observational increment be properly assimilated into the model, correcting large-scale background steering flow and yielding a simulated track close to the observed one. However, little improvement is found in simulating the TC core-scale structures by the assimilation of radar velocity as compared to the radar-observed flow, primarily due to the insufficient spatial resolution of the model that may lead to the incorrect representation of the TC core structure and the rejection of some core-region observations during the data assimilation procedure. Moreover, assimilation-induced asymmetries consume a certain portion of mean kinetic energy, preventing the simulated Rammasun from axisymmetrization and thus intensification as compared with the non-assimilated experiment.     

Urban effects of Chennai on sea breeze induced convection and precipitation

Doppler radar derived wind speed and direction profiles showed a well developed sea breeze circulation over the Chennai, India region on 28 June, 2003. Rainfall totals in excess of 100 mm resulted from convection along the sea breeze front. Inland propagation of the sea breeze front was observed in radar reflectivity imagery. High-resolution MM5 simulations were used to investigate the influence of Chennai urban land use on sea breeze initiated convection and precipitation. A comparison of observed and simulated 10m wind speed and direction over Chennai showed that the model was able to simulate the timing and strength of the sea breeze. Urban effects are shown to increase the near surface air temperature over Chennai by 3.0K during the early morning hours. The larger surface temperature gradient along the coast due to urban effects increased onshore flow by 4.0m s⁻¹. Model sensitivity study revealed that precipitation totals were enhanced by 25mm over a large region 150 km west of Chennai due to urban effects. Deficiency in model physics related to night-time forecasts are addressed.     

Tsunami vulnerability assessment in urban areas using numerical model and GIS

Natural disasters can neither be predicted nor prevented. Urban areas with a high population density coupled with the construction of man-made structures are subjected to greater levels of risk to life and property in the event of natural hazards. One of the major and densely populated urban areas in the east coast of India is the city of Chennai (Madras), which was severely affected by the 2004 Tsunami, and mitigation efforts were severely dampened due to the non-availability of data on the vulnerability on the Chennai coast to tsunami hazard. Chennai is prone to coastal hazards and hence has hazard maps on its earth-quake prone areas, cyclone prone areas and flood prone areas but no information on areas vulnerable to tsunamis. Hence, mapping has to be done of the areas where the tsunami of December 2004 had directly hit and flooded the coastal areas in Chennai in order to develop tsunami vulnerability map for coastal Chennai. The objective of this study is to develop a GIS-based tsunami vulnerability map for Chennai by using a numerical model of tsunami propagation together with documented observations and field measurements of the evidence left behind by the tsunami in December 2004. World-renowned and the second-longest tourist beach in the world “Marina” present in this region witnessed maximum death toll due to its flat topography, resulting in an inundation of about 300 m landward with high flow velocity of the order of 2 m/s.     

Simulation of very severe cyclone Mala over Bay of Bengal with HWRF modeling system

Tropical cyclone is one of the most devastating weather phenomena all over the world. The Environmental Modeling Center (EMC) of the National Center for Environmental Prediction (NCEP) has developed a sophisticated mesoscale model known as Hurricane Weather Research and Forecasting (HWRF) system for tropical cyclone studies. The state-of-the-art HWRF model (atmospheric component) has been used in simulating most of the features our present study of a very severe tropical cyclone ??Mala??, which developed on April 26 over the Bay of Bengal and crossed the Arakan coast of Myanmar on April 29, 2006. The initial and lateral boundary conditions are obtained from Global Forecast System (GFS) analysis and forecast fields of the NCEP, respectively. The performance of the model is evaluated with simulation of cyclone Mala with six different initial conditions at an interval of 12?h each from 00 UTC 25 April 2006 to 12 UTC 27 April 2006. The best result in terms of track and intensity forecast as obtained from different initial conditions is further investigated for large-scale fields and structure of the cyclone. For this purpose, a number of important predicted fields?? viz. central pressure/pressure drop, winds, precipitation, etc. are verified against observations/verification analysis. Also, some of the simulated diagnostic fields such as relative vorticity, pressure vertical velocity, heat fluxes, precipitation rate, and moisture convergences are investigated for understanding of the characteristics of the cyclone in more detail. The vector displacement errors in track forecasts are calculated with the estimated best track provided by the India Meteorological Department (IMD). The results indicate that the model is able to capture most of the features of cyclone Mala with reasonable accuracy.     

On the initialization of tropical cyclones with a three dimensional variational analysis

A method of initializing tropical cyclones in high-resolution numerical models is developed by modifying a data assimilation system, the NRL atmospheric variational data assimilation system (NAVDAS), which was designed for general mesoscale weather prediction using a three-dimensional variational (3DVAR) analysis with intermittent updates. The method includes the following three upgrades to overcome difficulties resulting from tropical cyclone initialization with the NAVDAS analysis. First, synthetic observation soundings are generated on 9 vertical levels at 49 points for strong storms (v _max?>?23.1?m?s^?1) and 41 points for weak storms around each cyclone center to supplement the observations used by the analysis. Secondly, a vortex relocation method for nested grids is developed to correct the cyclone position in the background fields of the analysis for each nested mesh. Lastly, the 3DVAR analysis is modified to gradually reduce the horizontal length scale and geostrophic coupling constraint near the center of a tropical cyclone for minimizing the problems introduced by improper covariances and coupling constraint used in the analysis. The synthetic observations significantly improve the intensity and structure of the analysis and the track forecast. The vortex relocation significantly improves the first guess background, avoiding the large analysis corrections that would be needed to correct cyclone position, and reducing the imbalance introduced by such large analysis increments. The modifications to the analysis length scale and geostrophic coupling constraint successfully improve the inner core analysis, providing a tighter circulation, and reducing the underestimate of the mass field gradient. Among the three upgrades, the vortex relocation provides the largest improvement to the tropical cyclone initialization and forecast.     

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.     

Tropical cyclone: expressions for velocity components and stability parameter

Tropical cyclones are the most devastating natural calamity forming in the ocean bed and die out in land. The life cycle of a tropical cyclone is mainly classified into four stages: (a) formation or genesis stage, (b) intensification stage, (c) mature stage and (d) decay stage. The intensification and mature stages are also known as tropical storm and cyclone (hurricane) stage, respectively. To develop the model of tropical cyclone we have taken the momentum conservation equation, equation of continuity and equation of hydrostatic balance in cylindrical coordinate system. Also the equation of state and the equation relating the velocity component and stream function are taken into account. We have assumed a suitable analytic form of the radial component of velocity as a function of radial distance (r) from the axis of the cyclone and vertical distance (z) from the sea bed. So in our model we have taken a cyclone as a rotating cylinder. With the use of the expression of the radial component velocity we have solved the governing nonlinear equation in the cylindrical coordinate system of a cyclone using ‘Wentzel–Kramers–Brillouin approximation’ and estimated the transverse velocity on the sea bed and in the vicinity of the eye wall of the cyclone. From the results we also get a path to generalize the tropical cyclone model as a vortex which is a generating curve of a cyclone. We also determine the vertical component of velocity of the cyclone. In this work we define a new parameter called the cyclone stability parameter (CSP). The CSP helps to determine the stability of a tropical cyclone from its genesis.     

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

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