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recent advances in seasonal and multi-annual tropical cyclone forecasting

Tropical Cyclone research and review 2023年第3期12卷 182-199页

作者： Yuhei Takaya Louis-Philippe Caron Eric Blake Francois Bonnardot Nicolas Bruneau Joanne Camp Johnny Chan Paul Gregory Jhordanne J.Jones Namyoung Kang Philip J.Klotzbach Yuriy Kuleshov Marie-Dominique Leroux Julia F.Lockwood Hiroyuki Murakami Akio Nishimura dushmanta r.pattanaik Tom J.Philp Yohan ruprich-robert ralf Toumi Frederic Vitart Seonghee Won ruifen Zhan Meteorological research Institute Japan Meteorological AgencyIbarakiJapan Ouranos MontrealCanada National Hurricane Center National Oceanic and Atmospheric AdministrationMiamiUSA Meteo-France Direction Interregionale pour l'Ocean IndienSaint-Denisde La ReunionFrance reask LondonUK Bureau of Meteorology VictoriaAustralia City University of Hong Kong Hong KongChina Asia-Pacific Typhoon Collaborative research Center ShanghaiChina Shanghai Typhoon Institute China Meteorological AdministrationShanghaiChina Department of Earth Atmosphericand Planetary SciencesPurdue UniversityWest LafayetteUSA University Corporation for Atmospheric research BoulderUSA Department of Geography Kyungpook National UniversityDaeguRepublic of Korea Department of Atmospheric Science Colorado State UniversityFort CollinsUSA royal Melbourne Institute of Technology(rMIT)University MelbourneAustralia Met Office Hadley Centre ExeterUK National Oceanographic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory PrincetonUSA Japan Meteorological Agency TokyoJapan India Meteorological Department New DelhiIndia Maximum Information LondonUK Barcelona Supercomputing Center BarcelonaSpain Department of Physics Imperial College LondonLondonUK European Centre for Medium-range Weather Forecasts(ECMWF) ReadingUK Korea Meteorological Administration JejuRepublic of Korea Department of Atmospheric and Oceanic Sciences&Institute of Atmospheric Sciences Fudan UniversityShanghaiChina

Seasonal tropical cyclone(TC)forecasting has evolved substantially since its commencement in the early ***,present operational seasonal TC forecasting services still do not meet the requirements of society and stakeholders:current operational products are mainly basin-scale information,while more detailed sub-basin scale information such as potential risks of TC landfall is anticipated for decision *** fill this gap and make the TC science and services move forward,this paper reviews recent research and development in seasonal tropical cyclone(TC)*** particular,this paper features new research topics on seasonal TC predictability in neutral conditions of El Ni˜no–Southern Oscillation(ENSO),emerging forecasting techniques of seasonal TC activity including Machine Learning/Artificial Intelligence,and multi-annual TC *** also review the skill of forecast systems at predicting landfalling statistics for certain regions of the North Atlantic,Western North Pacific and South Indian oceans and discuss the gap that remains between current products and potential user's *** knowledge and advanced forecasting techniques are expected to further enhance the capability of seasonal TC forecasting and lead to more actionable and fit-for-purpose products.

关键词： Tropical cyclones Seasonal forecasting Climate services

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A research progress review on regional extreme events

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Advances in Climate Change research 2018年第3期9卷 161-169页

作者： rEN Fu-Min Blair TrEWIN Manola BrUNET pattanaik dushmanta Andreas WALTEr Omar BADDOUr Maya KOrBEr State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences Beijing 100081 China Bureau of Meteorology Melbourne VIC 3001 Australia Centre for Climate Change Department of Geography University Rovira i Virgili Tarragona 43007 Spain Climatic research Unit School of Environmental Sciences University of East Anglia Norwich NR4 7TJ UK India Meteorological Department New Delhi 110003 India German Meteorological Service (DWD) Offenbach 63067 Germany World Meteorological Organization Geneva 1211 Switzerland

An extreme （weather and climate） event does not only mean that an extreme occurs at a location, but more generally it can impact a certainarea and last a certain period of time, which is defined as a regional extreme event （rEE） with a certain impacted area and duration. The conceptof rEE has been defined to allow mainly objective assessment of the events without a pre-determined boundary and duration. This paper reviewsthe studies on rEEs published during the past 20 years, especially recent years. Mainly in view of methodology, these studies can be divided intothree types studies focusing on spatial simultaneity, studies focusing on temporal persistence, and studies identifying rEEs. The methodsidentifying rEEs include two kinds, e.g., type-I methods stressing rEE＇s temporal persistence within a relatively certain area and type-IImethods focusing on catching a complete rEE. Identification methods proposed in this paper could provide valuable information for variouspurposes, such as real-time monitoring, estimating long-term changes, mechanism diagnosis, forecasting study and even attribution *** on rEEs is important for objectively defining extreme weather and climate events, which depends on the spatial and temporal scales ofinterest. Such an objective definition will support ongoing climate monitoring and improve the assessment of how regional extreme events havechanged over time.

关键词： Extreme (weather and climate) events regional extreme events research progress review

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Monthly Forecast of Indian Southwest Monsoon rainfall Based on NCEP’s Coupled Forecast System

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Atmospheric and Climate Sciences 2012年第4期2卷 479-491页

作者： dushmanta r. pattanaik Biswajit Mukhopadhyay Arun Kumar Climate Prediction Center National Centres for Environmental Prediction (NCEP)/National Oceanic and Atmospheric Administration (NOAA) Camp Springs USA India Meteorological Department (IMD) New Delhi India

The monthly forecast of Indian monsoon rainfall during June to September is investigated by using the hindcast data sets of the National Centre for Environmental Prediction (NCEP)’s operational coupled model (known as the Climate Forecast System) for 25 years from 1981 to 2005 with 15 ensemble members each. The ensemble mean monthly rainfall over land region of India from CFS with one month lead forecast is underestimated during June to September. With respect to the inter-annual variability of monthly rainfall it is seen that the only significant correlation coefficients (CCs) are found to be for June forecast with May initial condition and September rainfall with August initial conditions. The CFS has got lowest skill for the month of August followed by that of July. Considering the lower skill of monthly forecast based on the ensemble mean, all 15 ensemble members are used separately for the preparation of probability forecast and different probability scores like Brier Score (BS), Brier Skill Score (BSS), Accuracy, Probability of Detection (POD), False Alarm ratio (FAr), Threat Score (TS) and Heidke Skill Score (HSS) for all the three categories of forecasts (above normal, below normal and normal) have been calculated. In terms of the BS and BSS the skill of the monthly probability forecast in all the three categories are better than the climatology forecasts with positive BSS values except in case of normal forecast of June and July. The “TS”, “HSS” and other scores also provide useful probability forecast in case of CFS except the normal category of July forecast. Thus, it is seen that the monthly probability forecast based on NCEP CFS coupled model during the southwest monsoon season is very encouraging and is found to be very useful.

关键词： Indian Monsoon Coupled Model Monthly Forecast Probability Forecast Brier Skill Score Threat Score Heidke Skill Score

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Ensemble of Handcrafted and Deep Learning Model for Histopathological Image Classification

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Computers, Materials & Continua 2022年第11期73卷 4393-4406页

作者： Vasumathi Devi Majety N.Sharmili Chinmaya ranjan pattanaik ELaxmi Lydia Subhi r.M.Zeebaree Sarmad Nozad Mahmood Ali S.Abosinnee Ahmed Alkhayyat Department of Computer Science Engineering Vignan’s Nirula Institute of Technology and Science for WomenGuntur522005India Department of Computer Science Engineering Gayatri Vidya Parishad College of Engineering for WomenVisakhapatnam530048India Department of Computer Science and Engineering Ajay Binay Institute of Technology CuttackOdisha750314India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Energy Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityIraq Computer Technical Engineering Department College of Technical EngineeringThe Islamic UniversityNajaf54001Iraq College of Technical Engineering The Islamic UniversityNajafIraq

Histopathology is the investigation of tissues to identify the symptom of *** histopathological procedure comprises gathering samples of cells/tissues,setting them on the microscopic slides,and staining *** investigation of the histopathological image is a problematic and laborious process that necessitates the expert’s *** the same time,deep learning(DL)techniques are able to derive features,extract data,and learn advanced abstract data *** this view,this paper presents an ensemble of handcrafted with deep learning enabled histopathological image classification(EHCDL-HIC)*** proposed EHCDLHIC technique initially performs Weiner filtering based noise removal *** the images get smoothened,an ensemble of deep features and local binary pattern(LBP)features are *** the classification process,the bidirectional gated recurrent unit(BGrU)model can be *** the final stage,the bacterial foraging optimization(BFO)algorithm is utilized for optimal hyperparameter tuning process which leads to improved classification performance,shows the novelty of the *** validating the enhanced execution of the proposed EHCDL-HIC method,a set of simulations is *** experimentation outcomes highlighted the betterment of the EHCDL-HIC approach over the existing techniques with maximum accuracy of 94.78%.Therefore,the EHCDL-HIC model can be applied as an effective approach for histopathological image classification.

关键词： Histopathological image classification machine learning deep learning handcrafted features bacterial foraging optimization

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Nonlinear Dynamic System Identification of ArX Model for Speech Signal Identification

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Computer Systems Science & Engineering 2023年第7期46卷 195-208页

作者： rakesh Kumar.pattanaik Mihir N.Mohanty Srikanta Ku.Mohapatra Binod Ku.Pattanayak Department of ECE ITERSiksha‘O’Anusandhan(Deemed to be University)BhubaneswarIndia Department of CSE Chitkara University Institute of Engineering&TechnologyPunjabIndia Department of CSE ITERSiksha‘O’Anusandhan(Deemed to be University)BhubaneswarIndia

System Identification becomes very crucial in the field of nonlinear and dynamic systems or practical *** most practical systems don’t have prior information about the system behaviour thus,mathematical modelling is *** authors have proposed a stacked Bidirectional Long-Short Term Memory(Bi-LSTM)model to handle the problem of nonlinear dynamic system identification in this *** proposed model has the ability of faster learning and accurate modelling as it can be trained in both forward and backward *** main advantage of Bi-LSTM over other algorithms is that it processes inputs in two ways:one from the past to the future,and the other from the future to the *** this proposed model a backward-running Long-Short Term Memory(LSTM)can store information from the future along with application of two hidden states together allows for storing information from the past and future at any moment in *** proposed model is tested with a recorded speech signal to prove its superiority with the performance being evaluated through Mean Square Error(MSE)and root Means Square Error(rMSE).The rMSE and MSE performances obtained by the proposed model are found to be 0.0218 and 0.0162 respectively for 500 *** comparison of results and further analysis illustrates that the proposed model achieves better performance over other models and can obtain higher prediction accuracy along with faster convergence speed.

关键词： Nonlinear dynamic system identification long-short term memory bidirectional-long-short term memory auto-regressive with exogenous

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VLSI scaling methods and low power CMOS buffer circuit

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Journal of Semiconductors 2013年第9期34卷 92-99页

作者： Vijay Kumar Sharma Manisha pattanaik Department of Information Technology ABV-Indian Institute of Information Technology & Management

Device scaling is an important part of the very large scale integration （VLSI） design to boost up the success path of VLSI industry, which results in denser and faster integration of the devices. As technology node moves towards the very deep submicron region, leakage current and circuit reliability become the key issues. Both are increasing with the new technology generation and affecting the performance of the overall logic circuit. The VLSI designers must keep the balance in power dissipation and the circuit＇s performance with scaling of the devices. In this paper, different scaling methods are studied first. These scaling methods are used to identify the effects of those scaling methods on the power dissipation and propagation delay of the CMOS buffer circuit. For mitigating the power dissipation in scaled devices, we have proposed a reliable leakage reduction low power transmission gate （LPTG） approach and tested it on complementary metal oxide semiconductor （CMOS） buffer circuit. All simulation results are taken on HSPICE tool with Berkeley predictive technology model （BPTM） BSIM4 bulk CMOS files. The LPTG CMOS buffer reduces 95.16% power dissipation with 84.20% improvement in figure of merit at 32 nm technology node. Various process, voltage and temperature variations are analyzed for proving the robustness of the proposed approach. Leakage current uncertainty decreases from 0.91 to 0.43 in the CMOS buffer circuit that causes large circuit reliability.

关键词： LPTG buffer power dissipation propagation delay scaling nanoscale CMOS figure of merit

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Gate leakage current reduction in IP3 SrAM cells at 45 nm CMOS technology for multimedia applications

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Journal of Semiconductors 2012年第5期33卷 88-92页

作者： r.K.Singh Neeraj Kr.Shukla Manisha pattanaik Bipin Tripathi Kumaon Institute of Technology DwarahatAlmora(Uttarakhand)India ITM University Department of EECEGurgaon(Haryana)India ABV-IIITM VLSI GroupDepartment of ITGwalior(Madhya Pradesh)India

We have presented an analysis of the gate leakage current of the IP3 static random access memory （SrAM） cell structure when the cell is in idle mode（performs no data read/write operations） and active mode （performs data read/write operations）,along with the requirements for the overall standby leakage power,active write and read powers.A comparison has been drawn with existing SrAM cell structures,the conventional 6T,PP, P4 and P3 *** the supply voltage,V_（DD） = 0.8 V,a reduction of 98%,99%,92%and 94%is observed in the gate leakage current in comparison with the 6T,PP,P4 and P3 SrAM cells,respectively,while at V_（DD） = 0.7 V,it is 97%,98%,87%and 84%.A significant reduction is also observed in the overall standby leakage power by 56%〉, the active write power by 44%and the active read power by 99%,compared with the conventional 6T SrAM cell at V_（DD）= 0.8 V,with no loss in cell stability and performance with a small area *** simulation environment used for this work is 45 nm deep sub-micron complementary metal oxide semiconductor（CMOS） technology,t_（ox） = 2.4 nm,K_（thn） = 0.22 V,K_（thp） = 0.224 V,V_（DD） = 0.7 V and 0.8 V,at T = 300 K.

关键词： gate leakage subthreshold leakage low power deep sub-micron SrAM

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Tropical cyclone track and intensity prediction skill of GFS model over NIO during 2019&2020

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Tropical Cyclone research and review 2022年第1期11卷 36-49页

作者： Ch.Sridevi D.r.pattanaik A.K.Das Akhil Srivastava V.r.Durai C.J.Johny Medha Deshpande P.Suneetha radhika Kanase India Meteorological Department Numerical Weather Prediction DivisionLodhi RoadNew Delhi110003India Indian Institute of Tropical Meteorology MoESPune411008India Dept of Meteorology and Oceanography Andhra UniversityVisakhapatnamAndhra Pradesh530003India

The Tropical Cyclone(TC)track prediction using different NWP models and its verification is the critical task to provide prior knowledge about the model errors,which is beneficial for giving the model guidance-based real-time cyclone warning *** study has attempted to verify the Global Forecast System(GFS)model forecasted tropical cyclone track and intensity over the North Indian Ocean(NIO)for the years 2019 and *** is one of the operational models in the India Meteorological Department(IMD),which provides the medium-range weather forecast up to 10 *** forecasted tracks from the GFS forecast are obtained using a vortex tracker developed by Geophysical Fluid Dynamics Laboratory(GFDL).A total of 13 tropical cyclones formed over the North Indian Ocean,eight during 2019 and five in 2020 have been considered in this *** accuracy of the model predicted tracks and intensity is verified for five days forecasts(120 h)at 6-h intervals;the track errors are verified in terms of Direct Position Error(DPE),Along Track Error(ATE)and Cross-Track Error(CTE).The annual mean DPE over NIO during 2019(51–331 km)is lower than 2020(82–359 km),and the DPE is less than 150 km up to 66 h during 2019 and 48 h during *** positive ATE(76–332 km)indicates the predicted track movement is faster than the observed track during both *** positive CTE values for most forecast lead times suggest that the predicted track is towards the right side of the observed track during both *** cyclone Intensity forecast for the maximum sustained wind speed(Max WS)and central mean sea level pressure(MSLP)are verified in terms of mean error(ME)and root mean square error(rMSE).The errors are lead time ***,most of the time model under-predicted the cyclone intensity during both ***,there is a significant variance in track and intensity errors from the cyclone to cyclone and Bay of Bengal basin to the Arabian Sea basin.

关键词： Tropical cyclone Track prediction GFS NWP Global model GFDL

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Low noise wide bandgap SiC based IMPATT diodes at sub-millimeter wave frequencies and at high temperature

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Journal of Semiconductors 2014年第3期35卷 50-55页

作者： J.Pradhan S.r.pattanaik S.K.Swain G.N.Dash School of Physics Sambalpur University Jyoti Vihar Burla Sambalpur Odisha 767019 India Apex Institute of Technology and Management Bhubaneswar Odisha 752101 India

We have presented a comparative account of the high frequency prospective as well as noise behaviors of wide-bandgap 4H-SiC and 6H-SiC based on different structures of IMPATT diodes at sub-millimeter-wave frequencies up to 2.18 THz. The computer simulation study establishes the feasibility of the SiC based IMPATT diode as a high power density terahertz source. The most significant feature lies in the noise behavior of the SiC IMPATT diodes. It is noticed that the 6H-SiC DDr diode shows the least noise measure of 26.1 dB as compared to that of other structures. Further, it is noticed that the noise measure of the SiC IMPATT diode is less at a higher operating frequency compared to that at a lower operating frequency.

关键词： IMPATT silicon carbide terahertz(THz) science

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A sensitivity analysis of millimeter wave characteristics of SiC IMPATT diodes

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Journal of Semiconductors 2017年第6期38卷 58-65页

作者： S K Swain J Pradhan G N Dash S r.pattanaik School of Physics Sambalpur University Sambalpur Odisha 767019 India College of Engineering Bhubaneswar Bhubaneswar Odisha 751024 India National Institute of Science and Technology Berhampur Odisha 761008 India

Ionization rate coefficients and saturation drift velocities for electrons and holes are the vital material parameters in determining the performance of an IMPATT *** have performed a sensitivity analysis of the millimeter wave characteristics of 4H-SiC and 6H-SiC IMPATT diodes with reference to the above mentioned material data and an operating frequency of 220 *** effect of a small variation in the ionization rate and drift velocity on the device characteristics like break down voltage,efficiency,noise measure and power output has been presented here.

关键词： IMPATT SiC ionization rate saturation drift velocity, millimeter wave

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