Polar Cyclone Identification from 4D Climate Data in a Knowledge-Driven Visualization System

abstract: Arctic cyclone activity has a significant association with Arctic warming and Arctic ice decline. Cyclones in the North Pole are more complex and less developed than those in tropical regions. Identifying polar cyclones proves to be a task of greater complexity. To tackle this challenge, a new method which utilizes pressure level data and velocity field is proposed to improve the identification accuracy. In addition, the dynamic, simulative cyclone visualized with a 4D (four-dimensional) wind field further validated the identification result. A knowledge-driven system is eventually constructed for visualizing and analyzing an atmospheric phenomenon (cyclone) in the North Pole. The cyclone is simulated with WebGL on in a web environment using particle tracing. To achieve interactive frame rates, the graphics processing unit (GPU) is used to accelerate the process of particle advection. It is concluded with the experimental results that: (1) the cyclone identification accuracy of the proposed method is 95.6% when compared with the NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data; (2) the integrated knowledge-driven visualization system allows for streaming and rendering of millions of particles with an interactive frame rate to support knowledge discovery in the complex climate system of the Arctic region

Open data observatories: a survey

Open Data Observatories refer to online data platforms that provide free, real-time and historical data. They facilitate collaborative and unified environments for citizens and applications, supplemented with reusable datasets, analysis tools and interactive visualisations. Open Data Observatories collect and integrate various data types from multiple disparate providers. Data types include variables such as weather, traffic and social media, while providers are mainly the interconnected devices, services and individuals in the Internet of Things (IoT). The continually increasing volume and variety of such data require timely integration, management and analysis - yet to be presented in a way that end-users can easily understand. Data that interact in real-time preserve their value and enable a more in-depth understanding of real-world choices. This survey explored Open Data and reviewed twelve data observatories, focusing on their data management approaches. We investigated the observatories aims, designs and data types for some applied domains- namely transport, energy, environment, and social sensing. In what follows, we outlined five research challenges that influence their implementation

CIRA annual report FY 2014/2015

Reporting period July 1, 2014-March 31, 2015

Technologies for a FAIRer use of Ocean Best Practices

The publication and dissemination of best practices in ocean observing is pivotal for multiple aspects of modern marine science, including cross-disciplinary interoperability, improved reproducibility of observations and analyses, and training of new practitioners. Often, best practices are not published in a scientific journal and may not even be formally documented, residing solely within the minds of individuals who pass the information along through direct instruction. Naturally, documenting best practices is essential to accelerate high-quality marine science; however, documentation in a drawer has little impact. To enhance the application and development of best practices, we must leverage contemporary document handling technologies to make best practices discoverable, accessible, and interlinked, echoing the logic of the FAIR data principles [1]

The WWRP Polar Prediction Project (PPP)

Mission statement: “Promote cooperative international research enabling development of improved weather and environmental prediction services for the polar regions, on time scales from hours to seasonal”. Increased economic, transportation and research activities in polar regions are leading to more demands for sustained and improved availability of predictive weather and climate information to support decision-making. However, partly as a result of a strong emphasis of previous international efforts on lower and middle latitudes, many gaps in weather, sub-seasonal and seasonal forecasting in polar regions hamper reliable decision making in the Arctic, Antarctic and possibly the middle latitudes as well. In order to advance polar prediction capabilities, the WWRP Polar Prediction Project (PPP) has been established as one of three THORPEX (THe Observing System Research and Predictability EXperiment) legacy activities. The aim of PPP, a ten year endeavour (2013-2022), is to promote cooperative international research enabling development of improved weather and environmental prediction services for the polar regions, on hourly to seasonal time scales. In order to achieve its goals, PPP will enhance international and interdisciplinary collaboration through the development of strong linkages with related initiatives; strengthen linkages between academia, research institutions and operational forecasting centres; promote interactions and communication between research and stakeholders; and foster education and outreach. Flagship research activities of PPP include sea ice prediction, polar-lower latitude linkages and the Year of Polar Prediction (YOPP) - an intensive observational, coupled modelling, service-oriented research and educational effort in the period mid-2017 to mid-2019

Towards the “Perfect” Weather Warning

This book is about making weather warnings more effective in saving lives, property, infrastructure and livelihoods, but the underlying theme of the book is partnership. The book represents the warning process as a pathway linking observations to weather forecasts to hazard forecasts to socio-economic impact forecasts to warning messages to the protective decision, via a set of five bridges that cross the divides between the relevant organisations and areas of expertise. Each bridge represents the communication, translation and interpretation of information as it passes from one area of expertise to another and ultimately to the decision maker, who may be a professional or a member of the public. The authors explore the partnerships upon which each bridge is built, assess the expertise and skills that each partner brings and the challenges of communication between them, and discuss the structures and methods of working that build effective partnerships. The book is ordered according to the “first mile” paradigm in which the decision maker comes first, and then the production chain through the warning and forecast to the observations is considered second. This approach emphasizes the importance of co-design and co-production throughout the warning process. The book is targeted at professionals and trainee professionals with a role in the warning chain, i.e. in weather services, emergency management agencies, disaster risk reduction agencies, risk management sections of infrastructure agencies. This is an open access book