• S K Roy Bhowmik

Articles written in Journal of Earth System Science

• 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.

• Rainfall analysis for Indian monsoon region using the merged rain gauge observations and satellite estimates: Evaluation of monsoon rainfall features

Objective analysis of daily rainfall at the resolution of 1° grid for the Indian monsoon region has been carried out merging dense land rainfall observations and INSAT derived precipitation estimates. This daily analysis, being based on high dense rain gauge observations was found to be very realistic and able to reproduce detailed features of Indian summer monsoon. The inter-comparison with the observations suggests that the new analysis could distinctly capture characteristic features of the summer monsoon such as north–south oriented belt of heavy rainfall along the Western Ghats with sharp gradient of rainfall between the west coast heavy rain region and the rain shadow region to the east, pockets of heavy rainfall along the location of monsoon trough/low, over the east central parts of the country, over north–east India, along the foothills of Himalayas and over the north Bay of Bengal. When this product was used to assess the quality of other available standard climate products (CMAP and ECMWF reanalysis) at the grid resolution of 2.5°, it was found that the orographic heavy rainfall along Western Ghats of India was poorly identified by them. However, the GPCC analysis (gauge only) at the resolution of 1° grid closely discerns the new analysis. This suggests that there is a need for a higher resolution analysis with adequate rain gauge observations to retain important aspects of the summer monsoon over India. The case studies illustrated show that the daily analysis is able to capture large-scale as well as mesoscale features of monsoon precipitation systems. This study with data of two seasons (2001 and 2003) has shown sufficiently promising results for operational application, particularly for the validation of NWP models.

• 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.

• Doppler weather Radar based Nowcasting of cyclone Ogni

In this paper, we describe offline analysis of Indian Doppler Weather Radar (DWR) data from cyclone Ogni using a suite of radar algorithms as implemented on NEXRAD and the advanced algorithms developed jointly by the National Severe Storms Laboratory (NSSL) and the University of Oklahoma. We demonstrate the applicability of the various algorithms to Indian radar data, the improvement in the quality control and evaluate the benefit of nowcasting capabilities in Indian conditions. New information about the tropical cyclone structure, as derived from application of the algorithms is also discussed in this study.

Finally, we suggest improvements that could be made to the Indian data collection strategies, networking and real-time analysis. Since this is the first study of its kind to process and utilize DWR data in a tropical climate, the suggestions on real-time analysis and data collection strategies made in this paper, would in many cases, be beneficial to other countries embarking on DWR network modernization programs.

• Development of multimodel ensemble based district level medium range rainfall forecast system for Indian region

India Meteorological Department has implemented district level medium range rainfall forecast system applying multimodel ensemble technique, making use of model outputs of state-of-the-art global models from the five leading global NWP centres. The pre-assigned grid point weights on the basis of anomaly correlation coefficients (CC) between the observed values and forecast values are determined for each constituent model at the resolution of $0.25° × 0.25° utilizing two season datasets (1 June–30 September, 2007 and 2008) and the multimodel ensemble forecasts (day-1 to day-5 forecasts) are generated at the same resolution on a real-time basis. The ensemble forecast fields are then used to prepare forecasts for each district, taking the average value of all grid points falling in a particular district. In this paper, we describe the development strategy of the technique and performance skill of the system during summer monsoon 2009. The study demonstrates the potential of the system for improving rainfall forecasts at five days time scale over Indian region. Districtwise performance of the ensemble rainfall forecast reveals that the technique, in general, is capable of providing reasonably good forecast skill over most states of the country, particularly over the states where the monsoon systems are more dominant. • Evaluation of short-period rainfall estimates from Kalpana-1 satellite using MET software The INSAT Multispectral Rainfall Algorithm (IMSRA) technique for rainfall estimation, has recently been developed to meet the shortcomings of the Global Precipitation Index (GPI) technique of rainfall estimation from the data of geostationary satellites; especially for accurate short period rainfall estimates. This study evaluates the 3-hourly precipitation estimates by this technique as well as the rainfall estimates by the GPI technique using data of the Kalpana-1 satellite, over the Indian region for the south-west monsoon season of 2010 to understand their relative strengths and weaknesses in estimating short period rainfall. The gridded 3 hourly accumulated TRMM satellite (3B42 V6 product or TMPA product) and surface raingauge data for stations over the Indian region for the same period is used as the standard measure of rainfall estimates. The Method for Object-based Diagnostic Evaluation (MODE) utility of the METv3.0 software, has been used for the evaluation purpose. The results show that the new IMSRA technique is closer to the TMPA rainfall estimate, in terms of areal spread, geometric shape and location of rainfall areas, as compared to the GPI technique. The overlap of matching rainfall areas with respect to TMPA rainfall patches is also higher for the IMSRA estimates as compared to the GPI values. However, both satellite rainfall estimates are observed to be generally higher compared to the TMPA measurements. However, the values for the highest 10% of the rainfall rates in any rainfall patch, is generally higher for rainfall measured by the IMSRA technique, as compared to the estimates by the GPI technique. This may partly be due to the capping maximum limit of 3 mm/hr for rainfall measured by the GPI technique limits the total 3-hour accumulation to 9 mm even during heavy rainfall episodes. This is not so with IMSRA technique, which has no such limiting value. However, this general overestimation of the rainfall amount, measured by both techniques, and the greater error in case of IMSRA estimates, is also validated independently with respect to surface raingauge observations. Hence the observed overestimation by the IMSRA technique for the highest 10th percentile rainfall rates in rainfall episodes, is real. This overestimation by the latter technique may become a significant source of error, if the IMSRA estimate is used for monitoring very heavy rainfall episodes. In all other respects, since the IMSRA method shows significant improvement over the GPI, the rainfall estimates by the IMSRA method may be used for operational short period rainfall estimation. • Implementation of Polar WRF for short range prediction of weather over Maitri region in Antarctica India Meteorological Department has implemented Polar WRF model for the Maitri (lat. 70° 45′S, long. 11° 44′E) region at the horizontal resolution of 15 km using initial and boundary conditions of the Global Forecast System (GFS T-382) operational at the India Meteorological Department (IMD). Main objective of this paper is to examine the performance skill of the model in the short-range time scale over the Maitri region. An inter-comparison of the time series of daily mean sea level pressure and surface winds of Maitri for the 24 hours and 48 hours forecast against the corresponding observed fields has been made using 90 days data for the period from 1 December 2010 to 28 February 2011. The result reveals that the performance of the Polar WRF is reasonable, good and superior to that of IMD GFS forecasts. GFS shows an underestimation of mean sea level pressure of the order of 16–17 hPa with root mean square errors (RMSE) of order 21 hPa, whereas Polar WRF shows an overestimation of the order of 3–4 hPa with RMSE of 4 hPa. For the surface wind, GFS shows an overestimation of 1.9 knots at 24 hours forecast and an underestimation of 3.7 knots at 48 hours forecast with RMSE ranging between 8 and 11 knots. Whereas Polar WRF shows underestimation of 1.4 knots and 1.2 knots at 24 hours and 48 hours forecast with RMSE of 5 knots. The results of a case study illustrated in this paper, reveal that the model is capable of capturing synoptic weather features of Antarctic region. The performance of the model is found to be comparable with that of Antarctic Meso-scale Prediction System (AMPS) products. • Growth of cyclone Viyaru and Phailin – a comparative study The tropical cyclone Viyaru maintained a unique quasi-uniform intensity during its life span. Despite being in contact with sea surface for &lt; 120 hr travelling about 2150 km, the cyclonic storm (CS) intensity, once attained, did not intensify further, hitherto not exhibited by any other system over the Bay of Bengal. On the contrary, the cyclone Phailin over the Bay of Bengal intensified into very severe cyclonic storm (VSCS) within about 48 hr from its formation as depression. The system also experienced rapid intensification phase (intensity increased by 30 kts or more during subsequent 24 hours) during its life time and maximum intensity reached up to 115 kts. In this paper, a comparative study is carried out to explore the evolution of the various thermodynamical parameters and possible reasons for such converse features of the two cyclones. Analysis of thermodynamical parameters shows that the development of the lower tropospheric and upper tropospheric potential vorticity (PV) was low and quasi-static during the lifecycle of the cyclone Viyaru. For the cyclone Phailin, there was continuous development of the lower tropospheric and upper tropospheric PV, which attained a very high value during its lifecycle. Also there was poor and fluctuating diabatic heating in the middle and upper troposphere and cooling in the lower troposphere for Viyaru. On the contrary, the diabatic heating was positive from lower to upper troposphere with continuous development and increase up to 6°C in the upper troposphere. The analyses of cross sections of diabatic heating, PV, and the 1000–500 hPa geopotential metre (gpm) thickness contours indicate that the cyclone Viyaru was vertically tilted (westward) and lacked axisymmetry in its structure and converse features (axisymmetric and vertical) that occurred for the cyclone Phailin. In addition, there was a penetration of dry air in the middle troposphere of Viyaru, whereas high moisture existed in the middle troposphere of Phailin. The vertical wind shear (5–10$ms^{−1}\$) near the core of the storm region between 850 and 200 hPa was favourable for both the systems but was higher in the northern region of the cyclone Viyaru. The divergent development of these thermodynamic features conspired to produce converse characteristic of the two cyclones.

• Forecasting of cyclone Viyaru and Phailin by NWP-based cyclone prediction system (CPS) of IMD – an evaluation

An objective NWP-based cyclone prediction system (CPS) was implemented for the operational cyclone forecasting work over the Indian seas. The method comprises of five forecast components, namely (a) Cyclone Genesis Potential Parameter (GPP), (b) Multi-Model Ensemble (MME) technique for cyclone track prediction, (c) cyclone intensity prediction, (d) rapid intensification, and (e) predicting decaying intensity after the landfall. GPP is derived based on dynamical and thermodynamical parameters from the model output of IMD operational Global Forecast System. The MME technique for the cyclone track prediction is based on multiple linear regression technique. The predictor selected for the MME are forecast latitude and longitude positions of cyclone at 12-hr intervals up to 120 hours forecasts from five NWP models namely, IMD-GFS, IMD-WRF, NCEP-GFS, UKMO, and JMA. A statistical cyclone intensity prediction (SCIP) model for predicting 12 hourly cyclone intensity (up to 72 hours) is developed applying multiple linear regression technique. Various dynamical and thermodynamical parameters as predictors are derived from the model outputs of IMD operational Global Forecast System and these parameters are also used for the prediction of rapid intensification. For forecast of inland wind after the landfall of a cyclone, an empirical technique is developed. This paper briefly describes the forecast system CPS and evaluates the performance skill for two recent cyclones Viyaru (non-intensifying) and Phailin (rapid intensifying), converse in nature in terms of track and intensity formed over Bay of Bengal in 2013. The evaluation of performance shows that the GPP analysis at early stages of development of a low pressure system indicated the potential of the system for further intensification. The 12-hourly track forecast by MME, intensity forecast by SCIP model, and rapid intensification forecasts are found to be consistent and very useful to the operational forecasters. The error statistics of the decay model shows that the model was able to predict the decaying intensity after landfall with reasonable accuracy. The performance statistics demonstrates the potential of the system for improving operational cyclone forecast service over the Indian seas.

• # Journal of Earth System Science

Volume 129, 2020
All articles
Continuous Article Publishing mode

• # Editorial Note on Continuous Article Publication

Posted on July 25, 2019