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Balaji, C.

On the Possibility of Retrieving Near-Surface Rain Rate from the Microwave Sounder Saphir of the Megha-Tropiques Mission

Abstract Views :261 | PDF Views:91

Authors

C. Balaji ¹, C. Krishnamoorthy ¹, R. Chandrasekar ¹

Affiliations
1 Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600 036, IN

Source

Current Science, Vol 106, No 4 (2014), Pagination: 587-593

Abstract

In this study, ab initio atmospheric profiles generated through high-resolution calculations from the community weather model WRF, suitably matched up with both TRMM Microwave Imager (TMI) and Precipitation Radar (PR) instruments of the TRMM satellite were used to compute simulated brightness temperatures (BTs) corresponding to SAPHIR frequencies, through an in-house polarized radiative transfer code. An artificial neural network was then constructed and trained to return the near-surface rain (NSR) rate given the six BTs corresponding to SAPHIR. For accomplishing the retrievals, measured BTs of SAPHIR (level 1 data) were used. NSR rates were calculated for two precipitating systems, namely (i) cyclone Neelam and (ii) cyclone Phailin. Rain rates thus estimated were then validated with the TMI-PR combined rain product of TRMM (2A12). The results showed that there is good agreement between the two. An inter-comparison between rain rates derived from MADRAS and SAPHIR was also done. This unexpected ability of the SAPHIR radiances provide us with the rainfall signature opens up new vistas in achieving the mission objectives of Megha-Tropiques.

Keywords

Brightness Temperatures, Megha-Tropiques, Neelam, Phailin, SAPHIR.

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Retrieval of the Vertical Rainfall Structure from the Madras Imager Data of the Megha-Tropiques Satellite

Abstract Views :248 | PDF Views:84

Authors

C. Balaji ¹, K. Srinivasa Ramanujam ²

Affiliations
1 Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600 036, IN
2 Department of Electrical and Computer Engineering, Colorado State University, Fort Collins 80523, US

Source

Current Science, Vol 104, No 12 (2013), Pagination: 1627-1634

Abstract

A physically based algorithm for the retrieval of vertical cloud and rain structure from the MADRAS imager data of Megha-Tropiques is developed. A communitydeveloped meso-scale numerical weather simulation software, WRF, has been used for simulation of thermodynamic, cloud and rain profiles for a cyclone case. The WRF simulated profiles in conjunction with two of the rain-measuring instruments on-board the TRMM satellite, the TMI and the TRMM PR, are used as a priori cloud and rain profiles database. These profiles were input to an in-house radiative transfer code. Brightness temperatures at MADRAS imager frequencies were simulated to complete the generation of a priori database. Brightness temperatures were also simulated for TMI channels for comparison, wherever possible.

Sample MADRAS data were downloaded and retrievals were performed for the MADRAS channels. The retrieved wind speed, column-integrated liquid water and surface rain rate were compared against the Level 2 data of Megha-Tropiques mission. A comparison of daily averaged rain rate with TMI retrievals was also made. The results show that the retrieval algorithm is robust and able to retrieve the vertical cloud and rain structure even in the absence of a radar on-board the Megha-Tropiques.

Keywords

Geophysical Retrievals, Inverse Problems, Megha-Tropiques, Passive Microwave Remote Sensing.

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Impact of Cloud Parameterization Schemes on The Simulation of Cyclone Vardah using the WRF Model

Abstract Views :231 | PDF Views:85

Authors

C. P. R. Sandeep ¹, C. Krishnamoorthy ¹, C. Balaji ¹

Affiliations
1 Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600 036, IN

Source

Current Science, Vol 115, No 6 (2018), Pagination: 1143-1153

Abstract

The objective of this study is to examine the sensitivity of cumulus and microphysics schemes when simulating the track, intensity and inner core structure of the very severe cyclonic storm (VSCS) Vardah using the Weather Research and Forecasting (WRF) model. Four cumulus parameterization schemes (CPS) and six microphysics schemes (MPS) were used. Both the track and intensity of cyclone Vardah are seen to be sensitive to the CPS and MPS. New simplified Arakawa– Schubert scheme (NSAS) as CPS and Kessler scheme (KS) as MPS combination has better predicted the track and intensity of the cyclone with respect to the Indian Meteorological Department (IMD) data when compared to other schemes. To verify the robustness of the best set of schemes for cyclone Vardah, two random sets of schemes as well as the best set of schemes were run for cyclones Hudhud and Thane.

Keywords

Cyclone Vardah, Cumulus Parameterization, Microphysics Parameterization, WRF Model.

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References

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Chennai Extreme Rainfall Event of 2015 under Future Climate Projections Using the Pseudo Global Warming Dynamic Downscaling Method

Abstract Views :254 | PDF Views:83

Authors

P. Jyoteeshkumar ¹, P. V. Kiran ¹, C. Balaji ¹

Affiliations
1 Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600 036, IN

Source

Current Science, Vol 118, No 12 (2020), Pagination: 1968-1979

Abstract

Here we report results of a detailed numerical study on the effect of climate change on the characteristics of a very severe rainfall event that occurred in the coastal city of Chennai, Tamil Nadu, India in December 2015. The pseudo global warming (PGW) method was used to obtain the initial and boundary conditions of the future climate and projections were done for the far future, i.e. the year 2075 using the representative concentration pathway scenario of 8.5. The Weather Research and Forecasting (WRF) model was used for simulations with perturbed initial and boundary conditions by the PGW method in a dynamic downscaling framework. The sensitivities of Microphysics and cumulus parameterization schemes in WRF were first studied. The warm rain microphysics (Kessler) scheme and Kain–Fritsch (KF) cumulus scheme showed good agreement with the observed data. Once the best schemes were identified for such an extreme event and for the specific region under consideration, simulations were carried out for future and current climate conditions. Results show that the bulk Richardson number, energy helicity index, K-index, moisture convergence, vertical temperature and mixing ratio all increase significantly in future climate conditions, thereby leading to heavy precipitation. The precipitation in Chennai region increased by 17.37% on the peak rainy day (1 December 2015) in future compared to current. The key takeaway though is that on succeeding days, the amount of precipitation was seen to increase dramatically by 183.5%, 233.9% and 70.8%. This is bound to lead to severe flood events that are likely to continue for more days in the future, thereby posing further risk and potential for damage.

Keywords

Climate Change, Extreme Rainfall Events, Pseudo Global Warming Method, Weather Research And Forecasting.

Full Text

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Impact of data assimilation on a calibrated WRF model for the prediction of tropical cyclones over the Bay of Bengal

Abstract Views :210 | PDF Views:82

Authors

Harish Baki ¹, C. Balaji ², Balaji Srinivasan ¹

Affiliations
1 Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600 036, IN
2 Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600 036, India; Center of Excellence in Atmospheric and Climate Sciences, Indian Institute of Technology Madras, Chennai 600 036, India; Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN

Source

Current Science, Vol 122, No 5 (2022), Pagination: 569-583

Abstract

The main objective of the present study is to examine the impact of three-dimensional variational data assimilation utilizing the multivariate background error covariance (BEC) estimates, in combination with the model calibration, for the simulations of seven tropical cyclones over the Bay of Bengal region. The study indicates that the utilization of multivariate BEC in assimilation influences the model forecasts in terms of wind speed at 10 m height, precipitation, cyclone tracks and cyclone intensity. The assimilation experiments conducted with a previously calibrated model combined with the control variable option 6 (cv6) of BEC have reduced the overall ischolar_main mean square error (RMSE) of 10 m wind speed by 17.02%, precipitation by 11.14%, cyclone track by 41.93% and the intensity by 25.5% when compared to the default model simulations without assimilation. The best experimental set-up is then used for the operational forecast of a recent cyclone Gulab. The results show an RMSE reduction of 18.61% in the cyclone track and 28.99% in intensity forecasts. These results also confirm that the utilization of cv6 BEC in the assimilation of conventional and radiance observations on a calibrated model improves the forecast of tropical cyclones over the Bay of Bengal region.

Keywords

Data assimilation, model calibration, multivariate background error statistics, operational forecast, tropical cyclones.

Full Text

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Thermal Science and Engineering: Quo Vadis?

Hybrid Assimilation on a Parameter-Calibrated Model to Improve the Prediction of Heavy Rainfall Events during the Indian Summer Monsoon

Abstract Views :119 | PDF Views:66

Authors

Sandeep Chinta ¹, V. S. Prasad ², C. Balaji ³

Affiliations
1 Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600 036, IN
2 National Centre for Medium Range Weather Forecasting, A-50, Sector 62, Noida 201 309, IN
3 Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN

Source

Current Science, Vol 124, No 6 (2023), Pagination: 693-703

Abstract

Heavy rainfall events during the Indian summer monsoon cause landslides and flash floods resulting in a significant loss of life and property every year. The exactness of the model physics representation and initial conditions is critical for accurately predicting these events using a numerical weather model. The values of parameters in the physics schemes influence the accuracy of model prediction; hence, these parameters are calibrated with respect to observation data. The present study examines the influence of hybrid data assimilation on a parameter-calibrated WRF model. Twelve events during the period 2018–2020 were simulated in this study. Hybrid assimilation on the WRF model significantly reduced the model prediction error of the variables: rainfall (18.04%), surface air temperature (7.91%), surface air pressure (5.90%) and wind speed at 10 m (27.65%) compared to simulations with default parameters without assimilation.

Keywords

Heavy Rainfall Events, Hybrid Assimilation, Numerical Weather Model, Parameter Calibration, Summer Monsoon.

Full Text

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