Matthias Zeeman, Andreas Christen, Sue Grimmond, Daniel Fenner, William Morrison, Gregor Feigel, Markus Sulzer, Nektarios Chrysoulakis
{"title":"多城市大气环境观测活动近时数据管理模块化方法","authors":"Matthias Zeeman, Andreas Christen, Sue Grimmond, Daniel Fenner, William Morrison, Gregor Feigel, Markus Sulzer, Nektarios Chrysoulakis","doi":"10.5194/egusphere-2024-1469","DOIUrl":null,"url":null,"abstract":"<strong>Abstract.</strong> Urban observation networks are becoming denser, more diverse, and more mobile, while being required to provide results in near-time. The Synergy Grant <em>urbisphere</em> funded by the European Research Council (ERC) has multiple simultaneous field campaigns in cities of different sizes collecting data, for improving weather and climate models and services, including assessing the impact of cities on the atmosphere (e.g., heat, moisture, pollutant and aerosol emissions) and people's exposure to extremes (e.g., heat waves, heavy precipitation, air pollution episodes). Here, a solution to this challenge for facilitating diverse data streams, from multiple sources, scales (e.g., indoors, regional-scale atmospheric boundary layer) and cities is presented. For model development and evaluation in heterogeneous urban environments, we need meshed networks of <em>in situ</em> observations with ground-based and airborne (remote-)sensing platforms. In this contribution we describe challenges, approaches and solutions for data management, data infrastructure, and data governance to handle the variety of data streams from primarily novel modular observation networks deployed in multiple cities, in combination with existing data collected by partners, ranging in scale from indoor sensor deployments to regional-scale boundary layer observations. A metadata system documents: (1) sensors/instruments, (2) location and configuration of deployed components, and (3) maintenance and events. This metadata system provides the backbone for converting instrument records to calibrated, location-aware, convention-aligned and quality-assured data products, according to FAIR (Findable, Accessible, Interoperable and Reusable) principles. The data management infrastructure provides services (via, e.g., APIs, Apps, ICEs) for data inspection and subsequent calculations by campaign participants. Some near real-time distributions are made to international networks (e.g., AERONET, Phenocam) or local agencies (e.g., GovDATA) with appropriate attribution. The data documentation conventions, used to ensure structured data sets, in this case are used to improve the delivery of integrated urban services, such as to research and operational agencies, across many cities.","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modular approach to near-time data management for multi-city atmospheric environmental observation campaigns\",\"authors\":\"Matthias Zeeman, Andreas Christen, Sue Grimmond, Daniel Fenner, William Morrison, Gregor Feigel, Markus Sulzer, Nektarios Chrysoulakis\",\"doi\":\"10.5194/egusphere-2024-1469\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Abstract.</strong> Urban observation networks are becoming denser, more diverse, and more mobile, while being required to provide results in near-time. The Synergy Grant <em>urbisphere</em> funded by the European Research Council (ERC) has multiple simultaneous field campaigns in cities of different sizes collecting data, for improving weather and climate models and services, including assessing the impact of cities on the atmosphere (e.g., heat, moisture, pollutant and aerosol emissions) and people's exposure to extremes (e.g., heat waves, heavy precipitation, air pollution episodes). Here, a solution to this challenge for facilitating diverse data streams, from multiple sources, scales (e.g., indoors, regional-scale atmospheric boundary layer) and cities is presented. For model development and evaluation in heterogeneous urban environments, we need meshed networks of <em>in situ</em> observations with ground-based and airborne (remote-)sensing platforms. In this contribution we describe challenges, approaches and solutions for data management, data infrastructure, and data governance to handle the variety of data streams from primarily novel modular observation networks deployed in multiple cities, in combination with existing data collected by partners, ranging in scale from indoor sensor deployments to regional-scale boundary layer observations. A metadata system documents: (1) sensors/instruments, (2) location and configuration of deployed components, and (3) maintenance and events. This metadata system provides the backbone for converting instrument records to calibrated, location-aware, convention-aligned and quality-assured data products, according to FAIR (Findable, Accessible, Interoperable and Reusable) principles. The data management infrastructure provides services (via, e.g., APIs, Apps, ICEs) for data inspection and subsequent calculations by campaign participants. Some near real-time distributions are made to international networks (e.g., AERONET, Phenocam) or local agencies (e.g., GovDATA) with appropriate attribution. 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Modular approach to near-time data management for multi-city atmospheric environmental observation campaigns
Abstract. Urban observation networks are becoming denser, more diverse, and more mobile, while being required to provide results in near-time. The Synergy Grant urbisphere funded by the European Research Council (ERC) has multiple simultaneous field campaigns in cities of different sizes collecting data, for improving weather and climate models and services, including assessing the impact of cities on the atmosphere (e.g., heat, moisture, pollutant and aerosol emissions) and people's exposure to extremes (e.g., heat waves, heavy precipitation, air pollution episodes). Here, a solution to this challenge for facilitating diverse data streams, from multiple sources, scales (e.g., indoors, regional-scale atmospheric boundary layer) and cities is presented. For model development and evaluation in heterogeneous urban environments, we need meshed networks of in situ observations with ground-based and airborne (remote-)sensing platforms. In this contribution we describe challenges, approaches and solutions for data management, data infrastructure, and data governance to handle the variety of data streams from primarily novel modular observation networks deployed in multiple cities, in combination with existing data collected by partners, ranging in scale from indoor sensor deployments to regional-scale boundary layer observations. A metadata system documents: (1) sensors/instruments, (2) location and configuration of deployed components, and (3) maintenance and events. This metadata system provides the backbone for converting instrument records to calibrated, location-aware, convention-aligned and quality-assured data products, according to FAIR (Findable, Accessible, Interoperable and Reusable) principles. The data management infrastructure provides services (via, e.g., APIs, Apps, ICEs) for data inspection and subsequent calculations by campaign participants. Some near real-time distributions are made to international networks (e.g., AERONET, Phenocam) or local agencies (e.g., GovDATA) with appropriate attribution. The data documentation conventions, used to ensure structured data sets, in this case are used to improve the delivery of integrated urban services, such as to research and operational agencies, across many cities.
期刊介绍:
Geoscientific Instrumentation, Methods and Data Systems (GI) is an open-access interdisciplinary electronic journal for swift publication of original articles and short communications in the area of geoscientific instruments. It covers three main areas: (i) atmospheric and geospace sciences, (ii) earth science, and (iii) ocean science. A unique feature of the journal is the emphasis on synergy between science and technology that facilitates advances in GI. These advances include but are not limited to the following:
concepts, design, and description of instrumentation and data systems;
retrieval techniques of scientific products from measurements;
calibration and data quality assessment;
uncertainty in measurements;
newly developed and planned research platforms and community instrumentation capabilities;
major national and international field campaigns and observational research programs;
new observational strategies to address societal needs in areas such as monitoring climate change and preventing natural disasters;
networking of instruments for enhancing high temporal and spatial resolution of observations.
GI has an innovative two-stage publication process involving the scientific discussion forum Geoscientific Instrumentation, Methods and Data Systems Discussions (GID), which has been designed to do the following:
foster scientific discussion;
maximize the effectiveness and transparency of scientific quality assurance;
enable rapid publication;
make scientific publications freely accessible.