Interactions between a marine heatwave and tropical cyclone Amphan in the Bay of Bengal in 2020

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Rathore, S., Goyal, R., Jangir, B., Ummenhofer, C., Feng, M., & Mishra, M. Interactions between a marine heatwave and tropical cyclone Amphan in the Bay of Bengal in 2020. Frontiers in Climate, 4, (2022): 861477, https://doi.org/10.3389/fclim.2022.861477.Interactions are diagnosed between a marine heatwave (MHW) event and tropical super cyclone Amphan in the Bay of Bengal. In May 2020, an MHW developed in the Bay of Bengal driven by coupled ocean-atmosphere processes which included shoaling of the mixed layer depth due to reduced wind speed, increased net surface shortwave radiation flux into the ocean, increased upper ocean stratification, and increased sub-surface warming. Ocean temperature, rather than salinity, dominated the stratification that contributed to the MHW development and the subsurface ocean warming that also increased tropical cyclone heat potential. The presence of this strong MHW with sea surface temperature anomalies >2.5°C in the western Bay of Bengal coincided with the cyclone track and facilitated the rapid intensification of tropical cyclone Amphan to a super cyclone in just 24 h. This rapid intensification of a short-lived tropical cyclone, with a lifespan of 5 days over the ocean, is unprecedented in the Bay of Bengal during the pre-monsoon period (March-May). As the cyclone approached landfall in northern India, the wind-induced mixing deepened the mixed layer, cooled the ocean's surface, and reduced sub-surface warming in the bay, resulting in the demise of the MHW. This study provides new perspectives on the interactions between MHWs and tropical cyclones that could aid in improving the current understanding of compound extreme events that have severe socio-economic consequences in affected countries.CU acknowledges support from the James E. and Barbara V. Moltz Fellowship for Climate-Related Research and the Independent Research & Development Program at WHOI. MF was supported by the Centre for Southern Hemisphere Oceans Research (CSHOR), which is a joint initiative between the Qingdao National Laboratory for Marine Science and Technology (QNLM), CSIRO, University of New South Wales, and the University of Tasmania

Dynamics of the Southern Hemisphere extratropical atmospheric circulation

The Southern Hemisphere extratropical westerly winds are the strongest time-averaged surface winds on Earth, having a profound impact on weather systems, ocean circulation, Antarctic sea-ice as well as oceanic uptake of heat and carbon. The westerly winds have shown poleward intensification in the last few decades driven primarily by stratospheric ozone depletion with a secondary role played by increasing greenhouse gases. In recent years we have seen early signs of ozone recovery as a result of the Montreal Protocol. Part 1 of this thesis demonstrates that by curbing CFC emissions, the Montreal Protocol also played a critical role in mitigating future surface climate change, equivalent to approximately 25% reduction in global surface warming by 2050. A major feature of the Southern Hemisphere extratropical atmospheric circulation is its strong zonal coherence. However, there are notable zonal asymmetries embedded in the flow, with two important examples being the zonal wave 3 (ZW3) and Amundsen Sea Low (ASL). Although these features have received significant attention from the scientific community, the mechanisms responsible for their presence are still not clear. In Part 2, model experiments suggest that the ZW3 pattern is generated remotely by tropical deep convection and not by the presence of three extratropical landmasses as had previously been assumed. Quantification of ZW3 impacts requires a way to consistently characterize this variability. In Part 3, I formulate a new index for ZW3 which accounts for variability in the structure, phase and amplitude of ZW3. In Part 4, I provide evidence that in contrast to ZW3, the ASL is generated primarily by the interaction between westerly winds and Antarctic orography. Zonally asymmetric features are not only present in the mean circulation but also in the past and projected westerly wind changes in the Southern Hemisphere. These are characterized in Part 5 in reanalysis and models. Following on from this, I demonstrate in ocean model simulations that future projected zonally asymmetric atmospheric changes can drive substantial changes in the ocean circulation in the Pacific and Indian Oceans, accounting for more than 30% of the projected surface ocean warming around parts of Australia (Part 6)

Creativity in machines: Music composition using artificial intelligence

In this paper we propose a framework to take the next step towards making creative machines. Taking cue from Turing’s Mind Paper (1950) to more recent studies by Riedl in ‘’The Lovelace 2.0 test of artificial creativity and intelligence’ we try to examine a very creative area of human creativity – music. We have summarized the different works published on artificial intelligence and machine learning implemented for algorithmic music composition. Comparison of different algorithms-techniques including key features, advantages, disadvantages, common issues, trade-off and future aspects are discussed in detail. We then propose our own framework of how machines can be made to learn creativity

Using Machine Learning, Image Processing & Neural Networks to Sense Bullying in K-12 Schools

We all have heard about bullying and we know that it is an immense challenge that schools have to tackle. Many lives have been ruined due to bullying and the fear it implants into students' mind has caused many of them to go into depression which can lead to suicide. Traditional methods [1] need to be accompanied with modern technology to make the method more effective and efficient. If real time alerts are to school staff, they can identify the perpetuator and extricate the victim swiftly. It this proposed method an AI based solution is implemented to monitor students using standard school surveillance technologies and CCTV to maintain a decorum and safe environment in the school premise. Also the proposed method utilizes other unstructured sources such as attendance records, social media activity and general nature of the students to deliver quick response. Artificial Intelligence (AI) techniques like Convolutional Neural Networks (CNN), which includes image processing capabilities, logistic regression methods, LSTM (Long short-term memory), and pre-trained model Darknet-19 is used for classification. Further, the model also included sentiment analysis to identify commonly used abuse terms and noisy labels to improve overall model accuracy.  The model has been trained and validated with the realistic data from all the sources mentioned and has achieved the classification accuracy of 87% for detecting any sign of bullying

Design, evaluation and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble

NARCliM2.0 comprises two Weather Research and Forecasting (WRF) regional climate models (RCMs) downscaling five CMIP6 global climate models contributing to the Coordinated Regional Downscaling Experiment over Australasia at 20 km resolution, and south-east Australia at 4 km convection-permitting resolution. We first describe NARCliM2.0’s design, including selecting two, definitive RCMs via testing seventy-eight RCMs using different parameterisations for planetary boundary layer, microphysics, cumulus, radiation, and land surface model (LSM). We then assess NARCliM2.0's skill in simulating the historical climate versus CMIP3-forced NARCliM1.0 and CMIP5-forced NARCliM1.5 RCMs and compare differences in future climate projections. RCMs using the new Noah-MP LSM in WRF with default settings confer substantial improvements in simulating temperature variables versus RCMs using Noah-Unified. Noah-MP confers smaller improvements in simulating precipitation, except for large improvements over Australia’s southeast coast. Activating Noah-MP’s dynamic vegetation cover and/or runoff options primarily improve simulation of minimum temperature. NARCliM2.0 confers large reductions in maximum temperature bias versus NARCliM1.0 and 1.5 (1.x), with small absolute biases of ~0.5 K over many regions versus over ~2 K for NARCliM1.x. NARCliM2.0 reduces wet biases versus NARCliM1.x by as much as 50 %, but retains dry biases over Australia’s north. NARCliM2.0 is biased warmer for minimum temperature versus NARCliM1.5 which is partly inherited from stronger warm biases in CMIP6 versus CMIP5 GCMs. Under shared socioeconomic pathway (SSP)3-7.0, NARCliM2.0 projects ~3 K warming by 2060–79 over inland regions versus ~2.5 K over coastal regions. NARCliM2.0-SSP3-7.0 projects dry futures over most of Australia, except for wet futures over Australia’s north and parts of western Australia which are largest in summer. NARCliM2.0-SSP1-2.6 projects dry changes over Australia with only few exceptions. NARCliM2.0 is a valuable resource for assessing climate change impacts on societies and natural systems and informing resilience planning by reducing model biases versus earlier NARCliM generations and providing more up-to-date future climate projections utilising CMIP6

Abstracts of National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020

This book presents the abstracts of the papers presented to the Online National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020 (RDMPMC-2020) held on 26th and 27th August 2020 organized by the Department of Metallurgical and Materials Science in Association with the Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, India. Conference Title: National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020Conference Acronym: RDMPMC-2020Conference Date: 26–27 August 2020Conference Location: Online (Virtual Mode)Conference Organizer: Department of Metallurgical and Materials Engineering, National Institute of Technology JamshedpurCo-organizer: Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, IndiaConference Sponsor: TEQIP-