• V K Agarwal

      Articles written in Journal of Earth System Science

    • Polarized microwave forward model simulations for tropical storm Fanoos

      C Balaji M Deiveegan S P Venkateshan R M Gairola A Sarkar V K Agarwal

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      In the present study, forward radiative transfer simulations are carried out for the tropical cyclone Fanoos that hit the coast off south India in December 2005. The in-house radiative transfer package used for this study employs the doubling and adding method to calculate radiances leaving the top of the one dimensional precipitating atmosphere. The particle drop size distribution is assumed to follow a modified gamma distribution in respect of the cloud liquid water and cloud ice water content. For precipitation, the Marshall–Palmer particle size distribution is used. All the hydrometeor particles are assumed to be spherical and Lorentz Mie theory is used to evaluate the interaction parameters like absorption, scattering coefficients and polarized scattering matrix. In order to validate the drop size distributions and interaction parameter calculations, the simulated brightness temperatures are compared with the TMI measured brightness temperatures for all the channels. For carrying out this exercise, vertical hydrometeors retrieved by TMI are used as input. The differences between simulated and measured brightness temperatures are found to be within ± 10%. The maximum difference in the brightness temperatures between the present work and the Eddington model which the TRMM algorithm employs is about 4.5K. This may become significant when retrieval of precipitation is attempted by combining the forward model with a suitable retrieval strategy, under tropical conditions.

    • Retrieval of hydrometeors from microwave radiances with a polarized radiative transfer model

      C Balaji M Deiveegan S P Venkateshan R M Gairola A Sarkar V K Agarwal

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      This paper reports the results of a Bayesian-based algorithm for the retrieval of hydrometeors from microwave satellite radiances. The retrieval technique proposed makes use of an indigenously developed polarized radiative transfer (RT) model that drives a data driven optimization engine (Bayesian) to perform retrievals of rain and other hydrometeors in a multi-layer, plane parallel raining atmosphere. For the sake of completeness and for the purposes of comparison, retrievals with Artificial Neural Networks (ANN) have also been done. Retrievals have been done first with a simplified two-layer atmosphere, where assumed values of hydrometeors are given to the forward model and these are taken as ‘measured radiances’. The efficacy of the two retrieval strategies is then tested for this case in order to establish accuracy and speed. The highlight of the work is however, the case study wherein a tropical storm in the Bay of Bengal is taken up, to critically examine the performance of the retrieval algorithm for an extreme event wherein a 14-layer realistic, raining atmosphere has been considered and retrievals are done against Tropical Rainfall Measuring Mission (TRMM) measured radiances. The key novelties of the work are:

      inclusion of polarization from both hydrometeors and oceans in the RT model, and

      populating the database involving atmospheric profiles vs. simulated radiances by profiles of similar rain events in the past.

      In this work, the database was populated with TRMM retrieved profiles for tropical cyclones that occurred earlier in the area of interest (Indian Ocean), rather than with the Goddard Cloud Ensemble profiles. The use of (i) polarization in the forward model and (ii) creation of an a priori database for the retrieval denote the significant departure from the current state-of-the-art in the area.

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