M. Mandal

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.

Surface Energy Exchanges during Pre-monsoon Thunderstorm Activity over a Tropical Station Kharagpur

In the present study an attempt has been made to understand the variation of surface energy fluxes such as net radiation, sensible, latent and soil heat during different epochs of thunderstorm activity at Kharagpur. The study also focuses in delineating the difference in the surface energy budget from the days of thunderstorm activity to fair weather days in the pre-monsoon months (April and May) which is locally known as thunderstorm season. For this purpose, experimental data obtained from the Severe Thunderstorms- Observations and Regional Modeling (STORM) programme during pre-monsoon months of 2007, 2009 and 2010 at Kharagpur (22°30′N, 87°20′E), West Bengal, India are used. The present study reveals quick response, in the order of a few days, in the variations of transport of energy fluxes at soil-atmosphere interface to the upper atmosphere vis-à-vis to the occurrence of thunderstorm activity. Rise of surface sensible heat flux to the level of surface latent heat flux a day or two before the occurrence of a thunderstorm has been identified as a precursor signal for the thunderstorm occurrence over Kharagpur. Distinguishable differences are found in the partitioning of the surface energy fluxes to that of net radiation between thunderstorm and non-thunderstorm days. The present study reveals more Bowen’s ratio during thunderstorm days to that of nonthunderstorm days. These results are useful in validating mesoscale model simulations of thunderstorm activity.

Performance of WRF-ARW model in real-time prediction of Bay of Bengal cyclone ‘Phailin’

This study examines the performance of the Advanced Research core of Weather Research and Forecasting (ARW-WRF) model in prediction of the Bay of Bengal cyclone ‘Phailin’. The two-way interactive double-nested model at 27 and 9-km resolutions customized at Indian Institute of Technology Kharagpur (IITKGP) is used to predict the storm on real-time basis and five predictions are made with five different initial conditions. The initial and boundary conditions for the model are derived from the Global Forecasting System (GFS) analysis and forecast respectively. The track of storm is well predicted in all the five forecasts. In particular, the forecast with less initial positional error led to more accurate track and landfall prediction. It is observed that the predicted peak intensity and translation speed of the storm depends strongly on initial intensity error, vertical wind shear and vertical distribution of maximum potential vorticity. The trend of intensification and dissipation of the storm is well predicted by the model in terms of central sea level pressure (CSLP). The intensity in terms of maximum surface wind (MSW) is under-predicted by the model and it is suggested that the MSW estimated from predicted pressure drop may be used as prediction guideline. The storm intensified rapidly during its passage over the high Tropical Cyclone Heat Potential zone and is reasonably well predicted by the model. Though the magnitude of the precipitation is not well predicted, distribution of precipitation is fairly well predicted by the model. The track and intensity of the storm predicted by the customized WRF-ARW is better than that of other NWP models. The landfall (time and position) is also better predicted by the model compared to other NWP models if initialized at cyclonic storm stage. The results indicate that the customized model have good potential for real-time prediction of Bay of Bengal cyclones and encourage further investigation with larger number of cyclones.

Customization of regional climate model (RegCM4) over Indian region

The regional climate model (RegCM4) is customized for 10-year climate simulation over Indian region through sensitivity studies on cumulus convection and land surface parameterization schemes. The model is configured over 30° E–120° E and 15° S–45° N at 30-km horizontal resolution with 23 vertical levels. Six 10-year (1991–2000) simulations are conducted with the combinations of two land surface schemes (BATS, CLM3.5) and three cumulus convection schemes (Kuo, Grell, MIT). The simulated annual and seasonal climatology of surface temperature and precipitation are compared with CRU observations. The interannual variability of these two parameters is also analyzed. The results indicate that the model simulated climatology is sensitive to the convection as well as land surface parameterization. The analysis of surface temperature (precipitation) climatology indicates that the model with CLM produces warmer (dryer) climatology, particularly over India. The warmer (dryer) climatology is due to the higher sensible heat flux (lower evapotranspiration) in CLM. The model with MIT convection scheme simulated wetter and warmer climatology (higher precipitation and temperature) with smaller Bowen ratio over southern India compared to that with the Grell and Kuo schemes. This indicates that a land surface scheme produces warmer but drier climatology with sensible heating contributing to warming where as a convection scheme warmer but wetter climatology with latent heat contributing to warming. The climatology of surface temperature over India is better simulated by the model with BATS land surface model in combination with MIT convection scheme while the precipitation climatology is better simulated with BATS land surface model in combination with Grell convection scheme. Overall, the modeling system with the combination of Grell convection and BATS land surface scheme provides better climate simulation over the Indian region.

Performance of cumulus parameterization schemes in the simulation of Indian Summer Monsoon using RegCM4

The Indian Summer Monsoon (ISM) is driven by organized large-scale convection; hence, its simulation is expected to depend on an appropriate representation of cumulus convection in the model. In the present study, the performance of different cumulus parameterization schemes is examined towards simulations of the ISM. The Regional Climate Model (RegCM4) is coupled with the Community Land Model (CLM 3.5) at 30 km resolution for the period May 1-September 30 for seasonal simulation of the ISM in three consecutive years, 2007, 2008, and 2009. Five numerical experiments with five convection schemes (Kuo, Grell, MIT, GO_ML [Grell over ocean and MIT over land], GL_MO [Grell over land and MIT over ocean]) are conducted for each of these three years. Some important features of the ISM simulated by the model, viz. low level westerly jet, upper level easterly jet, heat low, Tibetan high, etc., are analyzed and compared with that of the National Center for Environmental Prediction (NCEP) reanalysis. We found that the heat low over northwest India and Pakistan in all the three years is better simulated by the model with the MIT convection scheme compared to other convection schemes, whereas spatial distribution and accuracy of surface temperature is better simulated using GL_MO rather than MIT. The low level westerly jet is well captured by the model with MIT with slightly weaker strength compared to the National Center for Environmental Prediction (NCEP) reanalysis. The location and strength of the tropical easterly jet is well predicted in each simulation with some uncertainty in strength, and are better simulated with MIT. The comparison of the model simulated rainfall with 0.5o × 0.5o datasets from the Climate Research Unit (CRU TS3.22) indicates that seasonal and monthly average rainfall are well simulated with MIT and GO_ML; however, the same over central and western India is significantly underestimated by the model with all the convection schemes. Comparatively, higher sensible heat flux and lower latent heat flux are noticed in the model simulation with all schemes. This change of fluxes affects surface temperature and rainfall simulation significantly. The statistical analysis indicates that surface temperature and rainfall are well reproduced by the model with GL_MO and GO_ML, but circulation is better simulated with MIT only. It is observed that although the bias in the model with MIT is slightly higher than that of the two mixed schemes, the spatial distribution and other synoptic features of surface temperature and rainfall during ISM are well simulated. Thus, considering overall performances, the RegCM4 with MIT the cumulus convection scheme provides better simulation of seasonal and monthly features of the monsoon.

Simulation of Severe Land-Falling Bay of Bengal Cyclones During 1995–1999 Using Mesoscale Model MM5

In this study, the nonhydrostatic version of Pennsylvania State University (PSU)/National Center for Atmospheric Research (NCAR) mesoscale model MM5 is used to simulate the severe land-falling Bay of Bengal cyclones. The cyclonic storms associated with maximum sustained wind of 48 knots or more are considered severe cyclones. The main objective of the study is to improve model initialization and evaluate the model performance towards prediction of intensity, track, and landfall of these storms. The model configuration used in the present study is primarily based on sensitivity studies conducted earlier by the authors. The vortex specification in the large scale global analysis is rectified using synthetic data in preparation of high resolution reanalysis. The vortex initialization in the model is done through 12 hours nudging to the prepared high-resolution reanalysis. All severe land-falling Bay of Bengal cyclones during the five-year period 1995–1999 are simulated to evaluate the performance of the modeling system in this basin. The storms are simulated at least up to their landfall. The model simulated mean sea level pressure, horizontal wind, and rainfall are compared with observations/best-fit estimation. The simulated tracks of the storms are compared with the best-fit tracks. The average errors in track forecast in the present study are compared with the average error in representing the tracks in the National Center for Environmental Prediction (NCEP) reanalysis, errors in similar other predictions, operational prediction, and forecast difficulty level (FDL) in North Indian Basin. It indicates that the tracks of these storms are relatively better simulated in the present study with the errors less than the FDL in the North Indian Basin and present operational track forecast errors in this basin. Most importantly, the landfall points of these storms are well simulated by the model though the time of landfall delays from actual landfall time as reported by India Meteorology Department (IMD) at an average by five hours. The intensity of these storms is also simulated reasonably well by the model though the sharp deepening of some explosively deepening storms is not well captured.

Impact of Land Surface and Forcing Parameters on the Spin-up Behaviour of Noah Land Surface Model over the Indian Sub-Continent

In the present study, an attempt is made to understand the influence of land surface parameters (such as soil moisture conditions, soil type and vegetation type) and forcing parameters on the model spin-up behaviour of a land surface model (LSM), namely Noah LSM, over the Indian sub-continent. The work presented here primarily aims to understand the optimum initial conditions to achieve the least spin-up time over the subtropical conditions that exist over the region of interest. The study is presented in three major parts. In the first part, a multivariate statistical analysis, namely principle component analysis is employed to investigate how parameters such as precipitation, air temperature, soil moisture, radiation components as well as various parameters that characterize soil and vegetation types influence the model spin-up. The second part deals with the study of the impact of soil and vegetation parameters in different seasons on the model spin-up behaviour. Finally, the third part looks into the influence of initial soil moisture condition and precipitation forcing on the spin-up behaviour of the model in different seasons to obtain the optimum initial conditions for the minimum spin-up time of the model. From the study, it is seen that the soil and vegetation type, as well as the soil moisture content influence the model spin-up significantly. The present study reports that the experiments initialized just before a continuous rainfall event has the least spin-up unless the initial soil is saturated.

Analysis of stability parameters in relation to precipitation associated with pre-monsoon thunderstorms over Kolkata, India

The upper air RS/RW (Radio Sonde/Radio Wind) observations at Kolkata (22.65N, 88.45E) during pre-monsoon season March–May, 2005–2012 is used to compute some important dynamic/thermodynamic parameters and are analysed in relation to the precipitation associated with the thunderstorms over Kolkata, India. For this purpose, the pre-monsoon thunderstorms are classified as light precipitation (LP), moderate precipitation (MP) and heavy precipitation (HP) thunderstorms based on the magnitude of associated precipitation. Richardson number in non-uniformly saturated (Ri*) and saturated atmosphere (Ri); vertical shear of horizontal wind in 0–3, 0–6 and 3–7 km atmospheric layers; energy-helicity index (EHI) and vorticity generation parameter (VGP) are considered for the analysis. The instability measured in terms of Richardson number in non-uniformly saturated atmosphere (Ri∗)

Impact of Initial Condition on Prediction of Bay of Bengal Cyclone 'Viyaru' - A Case Study

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