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来自塞尔维亚诺维萨德市区城市气象网络的气温和相对湿度数据集。

Air Temperature and Relative Humidity Datasets from an Urban Meteorological Network in the City Area of Novi Sad (Serbia).

作者信息

Savić Stevan, Šećerov Ivan, Lalić Branislava, Nie Dongyun, Roantree Mark

机构信息

Faculty of Sciences, University of Novi Sad, Trg Dositeja Obradovića 3, 21000 Novi Sad, Serbia.

Faculty of Agriculture, University of Novi Sad, Trg Dositeja Obradovića 8, 21000 Novi Sad, Serbia.

出版信息

Data Brief. 2023 Jul 20;49:109425. doi: 10.1016/j.dib.2023.109425. eCollection 2023 Aug.

DOI:10.1016/j.dib.2023.109425
PMID:37501730
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10369387/
Abstract

This data article describes two groups of datasets which capture, firstly - 10-minutes air temperature (T) and relative humidity (RH) data from 27 urban and non-urban sites over a period of 3.5 years covering 2014-2018; and secondly - hourly T data from 12 urban sites over a period of 2 years covering 2016 and 2017. Both datasets are from urban meteorological network located in the Novi Sad city (Serbia). These datasets have 2 different types of information in the collection: one type provides details about the monitoring sites at which the T and RH sensors are placed, while the second type contains T and RH data at all sensor locations. In all, the 10-minutes dataset contains about 185,000 instances of T and RH data, and the hourly datasets contain 17,544 instances of T data. The 10-minutes datasets were not quality controlled, but the hourly T data has been cleaned and gap-filled so there are 24 measures at each site for each day. There are multiple potential uses, where this data can be applied. It can provide insights in understanding intra-urban and inter-urban research, urban climate modeling on local or micro scales, heat-related public health investigations and urban environment inquiries. It can also be used in machine learning experiments, for example, to test the accuracy of classification algorithms or to build and validate spatio-temporal machine learning functions, either for classification purposes or for gap filling. These datasets are directly citable through its DOIs and available for download from the Zenodo platform or from the Fair Micromet Portal.

摘要

本数据文章描述了两组数据集,第一组是在2014 - 2018年的3.5年时间里,从27个城市和非城市站点采集的10分钟空气温度(T)和相对湿度(RH)数据;第二组是在2016年和2017年的2年时间里,从12个城市站点采集的每小时T数据。这两组数据集均来自位于塞尔维亚诺维萨德市的城市气象网络。这些数据集在收集过程中有两种不同类型的信息:一种类型提供了放置T和RH传感器的监测站点的详细信息,而第二种类型包含所有传感器位置的T和RH数据。总体而言,10分钟数据集包含约185,000个T和RH数据实例,每小时数据集包含17,544个T数据实例。10分钟数据集未进行质量控制,但每小时的T数据已进行清理和填补空缺,因此每个站点每天有24个测量值。该数据有多种潜在用途。它可以为理解城市内部和城市间研究、局部或微观尺度的城市气候建模、与热相关的公共卫生调查以及城市环境调查提供见解。它还可用于机器学习实验,例如,测试分类算法的准确性或构建和验证时空机器学习函数,用于分类目的或填补空缺。这些数据集可通过其数字对象标识符(DOI)直接引用,并可从Zenodo平台或公平微气象门户下载。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2b3/10369387/188a62d640e1/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2b3/10369387/d82012dab53c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2b3/10369387/4a1af74868e9/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2b3/10369387/717c930814e8/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2b3/10369387/ab604f7d463f/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2b3/10369387/188a62d640e1/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2b3/10369387/d82012dab53c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2b3/10369387/4a1af74868e9/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2b3/10369387/717c930814e8/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2b3/10369387/ab604f7d463f/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2b3/10369387/188a62d640e1/gr5.jpg

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本文引用的文献

1
Analysis of air temperature dynamics in the "local climate zones" of Novi Sad (Serbia) based on long-term database from an urban meteorological network.基于城市气象网络的长期数据库,对塞尔维亚诺维萨德(Novi Sad)“地方气候区”的空气温度动态进行分析。
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2
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Environ Monit Assess. 2019 Jan 21;191(2):89. doi: 10.1007/s10661-019-7210-0.