Relevant bibliographies by topics / Godard algorithm

Academic literature on the topic 'Godard algorithm'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Godard algorithm"

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Suthendran, K., and T. Arivoli. "Performance Comparison of Variable Step Size Techniques of Sato and Godard-Based Blind Equalizer." Fluctuation and Noise Letters 14, no. 03 (June 29, 2015): 1550024. http://dx.doi.org/10.1142/s0219477515500248.

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The modern digital high speed wireless communication system demands quick convergence rate and low steady state error. The balancing between the demands can be achieved by opting step size. Thus, it is essential to define new algorithms to equalize channels and mitigate noise in communications. It is renowned that time varying step size blind equalization technique can speed up the convergence rate and minimize the misadjustment. This work presents a variable step size (VSS) approach based on godard blind equalization algorithm to resolve the conflict between the convergence rate and precision of the fixed step-size godard algorithm. The results of this projected approach is compared with the existing variable step size sato algorithm for a pulse amplitude modulated (PAM) input symbol.
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Kummerow, Christian D., David L. Randel, Mark Kulie, Nai-Yu Wang, Ralph Ferraro, S. Joseph Munchak, and Veljko Petkovic. "The Evolution of the Goddard Profiling Algorithm to a Fully Parametric Scheme." Journal of Atmospheric and Oceanic Technology 32, no. 12 (December 2015): 2265–80. http://dx.doi.org/10.1175/jtech-d-15-0039.1.

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AbstractThe Goddard profiling algorithm has evolved from a pseudoparametric algorithm used in the current TRMM operational product (GPROF 2010) to a fully parametric approach used operationally in the GPM era (GPROF 2014). The fully parametric approach uses a Bayesian inversion for all surface types. The algorithm thus abandons rainfall screening procedures and instead uses the full brightness temperature vector to obtain the most likely precipitation state. This paper offers a complete description of the GPROF 2010 and GPROF 2014 algorithms and assesses the sensitivity of the algorithm to assumptions related to channel uncertainty as well as ancillary data. Uncertainties in precipitation are generally less than 1%–2% for realistic assumptions in channel uncertainties. Consistency among different radiometers is extremely good over oceans. Consistency over land is also good if the diurnal cycle is accounted for by sampling GMI product only at the time of day that different sensors operate. While accounting for only a modest amount of the total precipitation, snow-covered surfaces exhibit differences of up to 25% between sensors traceable to the availability of high-frequency (166 and 183 GHz) channels. In general, comparisons against early versions of GPM’s Ku-band radar precipitation estimates are fairly consistent but absolute differences will be more carefully evaluated once GPROF 2014 is upgraded to use the full GPM-combined radar–radiometer product for its a priori database. The combined algorithm represents a physically constructed database that is consistent with both the GPM radars and the GMI observations, and thus it is the ideal basis for a Bayesian approach that can be extended to an arbitrary passive microwave sensor.
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Biscaro, Thiago S., and Carlos A. Morales. "Continental Passive Microwave-Based Rainfall Estimation Algorithm: Application to the Amazon Basin." Journal of Applied Meteorology and Climatology 47, no. 7 (July 1, 2008): 1962–81. http://dx.doi.org/10.1175/2007jamc1744.1.

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Abstract This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM–PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h−1 (PR) and −0.157 mm h−1 (S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 (PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM–Large-Scale Biosphere–Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h−1. NESDIS1 overestimated for both wind regimes but presented the best westerly representation. NESDIS2, GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.
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TAO, Wei-Kuo, Stephen LANG, Takamichi IGUCHI, and Yi SONG. "Goddard Latent Heating Retrieval Algorithm for TRMM and GPM." Journal of the Meteorological Society of Japan. Ser. II 100, no. 2 (2022): 293–320. http://dx.doi.org/10.2151/jmsj.2022-015.

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Koshigoe, S., A. Teagle, and C. H. Tsay. "A Rapidly Convergent Adaptive Controller Applied to Suppression of Random Noise Transmission." Journal of Vibration and Acoustics 120, no. 2 (April 1, 1998): 449–54. http://dx.doi.org/10.1115/1.2893850.

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In this paper, an efficient rapid convergent control algorithm will be developed and will be compared with other adaptive control algorithms using a plate-cavity system. The plate-cavity system used for these numerical experiments is a test bed of noise suppression technology for expendable launch vehicles. It consists of a flexible plate backed by a rigid cavity. Piezoelectric (PZT) actuators are considered to be bonded on both sides of the plate symmetrically. The plate is bombarded with an amplified random noise signal, and the control system is used to suppress the noise inside the cavity generated by the outside sound source. Other control algorithms included for the comparisons are LMS Widrow’s finite impulse response (FIR) adaptive control algorithm [1], and a modified Godard’s algorithm [2]. Comparisons of the random noise attenuation capability, transient and convergence performance, and computational requirements of each algorithm will he made as the order of the controller and relevant convergence parameters are varied.
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Tao, W. K., T. Iguchi, and S. Lang. "Expanding the Goddard CSH Algorithm for GPM: New Extratropical Retrievals." Journal of Applied Meteorology and Climatology 58, no. 5 (May 2019): 921–46. http://dx.doi.org/10.1175/jamc-d-18-0215.1.

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AbstractThe Goddard convective–stratiform heating (CSH) algorithm has been used to retrieve latent heating (LH) associated with clouds and cloud systems in support of the Tropical Rainfall Measuring Mission and Global Precipitation Measurement (GPM) mission. The CSH algorithm requires the use of a cloud-resolving model to simulate LH profiles to build lookup tables (LUTs). However, the current LUTs in the CSH algorithm are not suitable for retrieving LH profiles at high latitudes or winter conditions that are needed for GPM. The NASA Unified-Weather Research and Forecasting (NU-WRF) Model is used to simulate three eastern continental U.S. (CONUS) synoptic winter and three western coastal/offshore events. The relationship between LH structures (or profiles) and other precipitation properties (radar reflectivity, freezing-level height, echo-top height, maximum dBZ height, vertical dBZ gradient, and surface precipitation rate) is examined, and a new classification system is adopted with varying ranges for each of these precipitation properties to create LUTs representing high latitude/winter conditions. The performance of the new LUTs is examined using a self-consistency check for one CONUS and one West Coast offshore event by comparing LH profiles retrieved from the LUTs using model-simulated precipitation properties with those originally simulated by the model. The results of the self-consistency check validate the new classification and LUTs. The new LUTs provide the foundation for high-latitude retrievals that can then be merged with those from the tropical CSH algorithm to retrieve LH profiles over the entire GPM domain using precipitation properties retrieved from the GPM combined algorithm.
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Choi, Jinho, Iickho Song, and Rae-Hong Park. "Some convergence properties of Godard's quartic algorithm." Signal Processing 56, no. 3 (February 1997): 313–20. http://dx.doi.org/10.1016/s0165-1684(96)00178-8.

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Sanderson, Victoria L., Chris Kidd, and Glenn R. McGregor. "A Comparison of TRMM Microwave Techniques for Detecting the Diurnal Rainfall Cycle." Journal of Hydrometeorology 7, no. 4 (August 1, 2006): 687–704. http://dx.doi.org/10.1175/jhm507.1.

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Abstract This paper uses rainfall estimates retrieved from active and passive microwave data to investigate how spatially and temporally dependent algorithm biases affect the monitoring of the diurnal rainfall cycle. Microwave estimates used in this study are from the Tropical Rainfall Measuring Mission (TRMM) and include the precipitation radar (PR) near-surface (2A25), Goddard Profiling (GPROF) (2A12), and PR–TRMM Microwave Imager (TMI) (2B31) rain rates from the version 5 (v5) 3G68 product. A rainfall maximum is observed early evening over land, while oceans generally show a minimum in rainfall during the morning. Comparisons of annual and seasonal mean hourly rain rates and harmonics at both global and regional scales show significant differences between the algorithms. Relative and absolute biases over land vary according to the time of day. Clearly, these retrieval biases need accounting for, either in the physics of the algorithm or through the provision of accurate error estimates, to avoid erroneous climatic signals and the discrediting of satellite rainfall estimations.
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Sharma, V., and V. N. Raj. "Convergence and performance analysis of Godard family and multimodulus algorithms for blind equalization." IEEE Transactions on Signal Processing 53, no. 4 (April 2005): 1520–33. http://dx.doi.org/10.1109/tsp.2005.843725.

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Utsumi, Nobuyuki, F. Joseph Turk, Ziad S. Haddad, Pierre-Emmanuel Kirstetter, and Hyungjun Kim. "Evaluation of Precipitation Vertical Profiles Estimated by GPM-Era Satellite-Based Passive Microwave Retrievals." Journal of Hydrometeorology 22, no. 1 (January 2021): 95–112. http://dx.doi.org/10.1175/jhm-d-20-0160.1.

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AbstractPrecipitation estimation based on passive microwave (MW) observations from low-Earth-orbiting satellites is one of the essential variables for understanding the global climate. However, almost all validation studies for such precipitation estimation have focused only on the surface precipitation rate. This study investigates the vertical precipitation profiles estimated by two passive MW-based retrieval algorithms, i.e., the emissivity principal components (EPC) algorithm and the Goddard profiling algorithm (GPROF). The passive MW-based condensed water content profiles estimated from the Global Precipitation Measurement Microwave Imager (GMI) are validated using the GMI + Dual-Frequency Precipitation Radar combined algorithm as the reference product. It is shown that the EPC generally underestimates the magnitude of the condensed water content profiles, described by the mean condensed water content, by about 20%–50% in the middle-to-high latitudes, while GPROF overestimates it by about 20%–50% in the middle-to-high latitudes and more than 50% in the tropics. Part of the EPC magnitude biases is associated with the representation of the precipitation type (i.e., convective and stratiform) in the retrieval algorithm. This suggests that a separate technique for precipitation type identification would aid in mitigating these biases. In contrast to the magnitude of the profile, the profile shapes are relatively well represented by these two passive MW-based retrievals. The joint analysis between the estimation performances of the vertical profiles and surface precipitation rate shows that the physically reasonable connections between the surface precipitation rate and the associated vertical profiles are achieved to some extent by the passive MW-based algorithms.
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Dissertations / Theses on the topic "Godard algorithm"

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Samarasinghe, Devanarayanage Pradeepa. "Efficient methodologies for real-time image restoration." Phd thesis, 2011. http://hdl.handle.net/1885/9859.

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In this thesis we investigate the problem of image restoration. The main focus of our research is to come up with novel algorithms and enhance existing techniques in order to deliver efficient and effective methodologies, applicable in real-time image restoration scenarios. Our research starts with a literature review, which identifies the gaps in existing techniques and helps us to come up with a novel classification on image restoration, which integrates and discusses more recent developments in the area of image restoration. With this novel classification, we identified three major areas which need our attention. The first developments relate to non-blind image restoration. The two mostly used techniques, namely deterministic linear algorithms and stochastic nonlinear algorithms are compared and contrasted. Under deterministic linear algorithms, we develop a class of more effective novel quadratic linear regularization models, which outperform the existing linear regularization models. In addition, by looking in a new perspective, we evaluate and compare the performance of deterministic and stochastic restoration algorithms and explore the validity of the performance claims made so far on those algorithms. Further, we critically challenge the ne- cessity of some complex mechanisms in Maximum A Posteriori (MAP) technique under stochastic image deconvolution algorithms. The next developments are focussed in blind image restoration, which is claimed to be more challenging. Constant Modulus Algorithm (CMA) is one of the most popular, computationally simple, tested and best performing blind equalization algorithms in the signal processing domain. In our research, we extend the use of CMA in image restoration and develop a broad class of blind image deconvolution algorithms, in particular algorithms for blurring kernels with a separable property. These algorithms show significantly faster convergence than conventional algorithms. Although CMA method has a proven record in signal processing applications related to data communications systems, no research has been carried out to the investigation of the applicability of CMA for image restoration in practice. In filling this gap and taking into account the differences of signal processing in im- age processing and data communications contexts, we extend our research on the applicability of CMA deconvolution under the assumptions on the ground truth image properties. Through analyzing the main assumptions of ground truth image properties being zero-mean, independent and uniformly distributed, which char- acterize the convergence of CMA deconvolution, we develop a novel technique to overcome the effects of image source correlation based on segmentation and higher order moments of the source. Multichannel image restoration techniques recently gained much attention over the single channel image restoration due to the benefits of diversity and redundancy of the information between the channels. Exploiting these benefits in real time applications is often restricted due to the unavailability of multiple copies of the same image. In order to overcome this limitation, as the last area of our research, we develop a novel multichannel blind restoration model with a single image, which eliminates the constraint of the necessity of multiple copies of the blurred image. We consider this as a major contribution which could be extended to wider areas of research integrated with multiple disciplines such as demosaicing.
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Book chapters on the topic "Godard algorithm"

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Randel, David L., Christian D. Kummerow, and Sarah Ringerud. "The Goddard Profiling (GPROF) Precipitation Retrieval Algorithm." In Advances in Global Change Research, 141–52. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-24568-9_8.

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Olson, William S., Song Yang, John E. Stout, and Mircea Grecu. "The Goddard Profiling Algorithm (GPROF): Description and Current Applications." In Measuring Precipitation From Space, 179–88. Dordrecht: Springer Netherlands, 2007. http://dx.doi.org/10.1007/978-1-4020-5835-6_14.

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Tsirogiannis, Constantinos, and Christos Tsirogiannis. "Uncovering the Hidden Routes: Algorithms for Identifying Paths and Missing Links in Trade Networks." In The Connected Past. Oxford University Press, 2016. http://dx.doi.org/10.1093/oso/9780198748519.003.0012.

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A network is a simple yet powerful tool for representing a set of relations in the real world. For instance, to represent direct business relations between several people, we can sketch a network where each person is represented by a node and any two people that have done business together are connected by a link. A naive analysis of this network gives a picture of the direct connections between individuals, that is, who has done business, in person, with whom. However, for several network applications it is important to observe more complicated structures, other than the direct connections between the nodes. An example comes from applications in trade networks, where goods are exchanged between several people. In this case, it is important to keep track of the paths that specific goods have traversed in a network; in other words, we want to know the exact sequence of nodes through which a specific item was exchanged. Unfortunately, in some studies of trade networks we may not always know the exact path that certain items followed in the network. This is frequently the case with networks that represent trade relations between sites in an earlier historical period; knowledge of the exact trade paths in such networks has not survived and only fragmentary data is available (Sindbæk 2007, 2013; see in this volume Peeples et al. 2016). The same problem also arises in modern trade networks, when the transactions involved are the result of illegal activities. Such an example is the modern trade network in illicit antiquities. During recent decades, thousands of antiquities were illegally excavated worldwide and exchanged via a global trade network. During the late 1990s and 2000s, the combined efforts of forensic archaeologists and police investigators uncovered a considerable part of the trade network that handled illicit Italian and Greek antiquities in particular (Gill and Chippindale 2006; Gill and Tsirogiannis 2011; Godart et al. 2008). However, a large part of the activities that took place within this network remain unknown and there are some transactions that police investigations were not able to trace.
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Conference papers on the topic "Godard algorithm"

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Josten, A., B. Baeuerle, E. Dornbierer, J. Boesser, F. Abrecht, D. Hillerkuss, and J. Leuthold. "Multiplier-Free Real-Time Timing Recovery Algorithm in the Frequency Domain Based on Modified Godard." In Signal Processing in Photonic Communications. Washington, D.C.: OSA, 2015. http://dx.doi.org/10.1364/sppcom.2015.sps4d.2.

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Josten, A., B. Baeuerle, M. Song, E. Pincemin, D. Hillerkuss, and J. Leuthold. "Modified Godard Algorithm Applied on a Fractional Oversampled Signal to Correct CD, Polarization, and CFO." In Signal Processing in Photonic Communications. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/sppcom.2016.sptu2f.3.

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Malouin, Christian, Philip Thomas, Bo Zhang, Jason O'Neil, and Ted Schmidt. "Natural Expression of the Best-Match Search Godard Clock-Tone Algorithm for Blind Chromatic Dispersion Estimation in Digital Coherent Receivers." In Signal Processing in Photonic Communications. Washington, D.C.: OSA, 2012. http://dx.doi.org/10.1364/sppcom.2012.spth2b.4.

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Nicolas, Xavier, and Shihe Xin. "Computation of Incompressible Three-Dimensional Mixed Convection Flows in Long Aspect Ratio Channels Using an Efficient Finite Difference Method for Vectorial Supercomputers." In ASME 2005 Summer Heat Transfer Conference collocated with the ASME 2005 Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems. ASMEDC, 2005. http://dx.doi.org/10.1115/ht2005-72112.

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Based on Goda’s algorithm and second-order central finite differences, a very efficient vectorized code is tailored to solve 3D incompressible Navier-Stokes equations for mixed convection flows in high streamwise aspect ratio channels. The code takes advantage of incremental factorization method of ADI type, spectral decomposition of the ID Laplace operators and TDMA algorithm. It is validated through experiments of various Poiseuille-Rayleigh-Be´nard flows with steady longitudinal and unsteady transverse rolls.
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Kunt, Cengiz O., Lawrence J. Mignosa, and James T. Pontius. "An Algorithm for Enveloping Linear Structural Response With Application to Spacecraft Stress Analysis." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0146.

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Abstract An algorithm and a computer program are developed for spacecraft structural analysis to determine the maximum linear static response (stress, deformation, etc.) and the corresponding “worst direction” of the loading. Compared to the brute force approach of repeating the structural analysis to cover all the possible orientations of the load vector, the proposed approach is faster, more accurate, and computationally more efficient. Maximum structural response determination is illustrated through a case study of stress analysis conducted for the TRMM (Tropical Rainfall Measuring Mission) payload developed by NASA Goddard Space Flight Center and NASDA (National Space Development Agency of Japan). The paper includes part of the structural analysis conducted in sizing the Upper Instrument Support Platform, which provides support for two of TRMM’s major instruments.
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Muhammad Lutfor Rahman Khan, Mohammed H. Wondimagegnehu, and Tetsuya Shimamura. "Amplitude banded technique and parallel structure for Godard and Sato algorithms of blind channel equalization." In 2008 11th International Conference on Computer and Information Technology (ICCIT). IEEE, 2008. http://dx.doi.org/10.1109/iccitechn.2008.4803015.

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Meyers, Patrick C., and Ralph R. Ferraro. "Accounting for surface ice and snow in the goddard profiling algorithm rain rate retrievals." In IGARSS 2015 - 2015 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2015. http://dx.doi.org/10.1109/igarss.2015.7326349.

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Srinivasa Ramanujam, K., and C. Balaji. "A Fast Polarized Microwave Radiative Transfer Model for a Raining Atmosphere." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-22228.

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Retrieval of vertical rain structure and hence the estimation of surface rain rate is of central importance to various missions involving remote sensing of the earth’s atmosphere. Typically, remote sensing involves scanning the earth’s atmosphere at visible, infra red and microwave frequencies. While the visible and infra red frequencies can scan the atmosphere with higher spatial resolution, they are not suited for scanning under cloudy conditions as clouds are opaque under these frequencies. However, the longer wavelength microwave radiation can partially penetrate through the clouds without much attenuation thereby making it more suitable for meteorological purposes. The retrieval algorithms used for passive microwave remote sensing involve modeling of the radiation in the earth’s atmosphere where in the clouds and precipitating rain (also known as hydrometeors) emit / absorb / scatter. Additionally, it has been observed that the rain droplets tend to polarize the microwave signal emitted by the earth’s surface. In view of this, the first step in the development of a rainfall retrieval algorithm for any satellite mission is to simulate the radiances (also known as brightness temperatures) that would have been measured by a typical radiometer for different sensor frequencies and resolutions. Towards this, a polarized microwave radiation transfer code has been developed in house for a plane parallel raining atmosphere (henceforth called as forward model) that depicts the physics as seen by a satellite. Physics based retrieval algorithm often involves repeated execution of the forward model for various raining scenario. However, due to the complexity involved in the radiation modeling of the raining atmosphere which is participating in nature, the forward model suffers from the drawback that it requires enormous computational effort. In the present work, a much quicker alternative is proposed wherein the forward model can be replaced with an Artificial Neural Network (ANN) based Fast Forward Model (AFFM). This AFFM can be used in conjunction with an appropriate inverse technique to retrieve the rain structure. Spectral microwave brightness temperatures at frequencies corresponding to the Tropical Rainfall Measuring Mission (TRMM) of National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) are first simulated using an in-house polarized radiate on transfer code for sixteen past cyclones in the North Indian Ocean region in the period (2000–2005), using the hydrometeor profiles retrieved from the Goddard Profiling Algorithm (GPROF) of the Tropical Rainfall Measuring Mission (TRMM)’s Microwave Imager (TMI). This data is split into two sets: while the first set of data is used for training the network, the remainder of the data is used for testing the ANN. The results obtained are very encouraging and shows that neural network is capable of predicting the brightness temperature accurately with the correlation coefficient of over 99%. Furthermore, the execution of the forward model on an Intel Core 2 Quad 3.0 GHz processor based, 8 GB DDR3 RAM workstation took 3 days, while the AFFM delivers the results in 10 seconds.
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