瑞士伯尔尼夜间气温高分辨率数据集(2007-2022 年)

IF 3.3 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Moritz Burger, Moritz Gubler, Stefan Brönnimann
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引用次数: 0

摘要

为了应对更加炎热的未来,有关城市内部温度分布的信息对全世界的城市都至关重要。近年来,计算高分辨率气温数据集的方法层出不穷。这些数据集通常来源于降尺度技术,用于提高现有数据的空间分辨率。在本研究中,我们提出了一种基于精细缩放的低成本城市温度测量网络和以前开发的土地利用回归方法的方法。该数据集涵盖了一个中等城市地区 16 个夏季(2007-2022 年)的夜间平均气温,并对每年的土地覆被数据进行了调整。该数据集具有较高的空间(50 米)和时间(日)分辨率,在验证中表现良好(两个验证年的均方根误差分别为 0.70 和 0.69 K,平均偏差分别为 +0.41 和 -0.19 K)。该数据集可用于检查空间和时间上非常详细的统计数据,如每年的第一次热浪、累积热风险或年际变化。在此,我们通过两个应用案例对数据集进行了评估,这两个案例分别涉及城市规划和热风险评估,研究人员和从业人员对这两个方面都非常感兴趣。由于低成本测量设备在白天可能存在偏差,数据集目前仅限于夜间温度。在稍作调整后,所介绍的方法可应用于世界各地的城市,从而为研究人员、城市管理部门和私人利益相关者制定热量缓解和适应战略奠定基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

High-resolution dataset of nocturnal air temperatures in Bern, Switzerland (2007–2022)

High-resolution dataset of nocturnal air temperatures in Bern, Switzerland (2007–2022)

High-resolution dataset of nocturnal air temperatures in Bern, Switzerland (2007–2022)

To prepare for a hotter future, information on intra-urban temperature distributions is crucial for cities worldwide. In recent years, different methods to compute high-resolution temperature datasets have been developed. Such datasets commonly originate from downscaling techniques, which are applied to enhance the spatial resolution of existing data. In this study, we present an approach based on a fine-scaled low-cost urban temperature measurement network and a formerly developed land use regression approach. The dataset covers mean nocturnal temperatures of 16 summers (2007–2022) of a medium-sized urban area with adapted land cover data for each year. It has a high spatial (50 m) and temporal (daily) resolution and performs well in validation (RMSEs of 0.70 and 0.69 K and mean biases of +0.41 and −0.19 K for two validation years). The dataset can be used to examine very detailed statistics in space and time, such as first heatwave per year, cumulative heat risks or inter-annual variability. Here, we evaluate the dataset with two application cases regarding urban planning and heat risk assessment, which are of high interest for both researchers and practitioners. Due to potential biases of the low-cost measurement devices during daytime, the dataset is currently limited to night-time temperatures. With minor adaptions, the presented approach is transferable to cities worldwide in order to set a basis for researchers, city administrations and private stakeholders to address their heat mitigation and adaptation strategies.

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来源期刊
Geoscience Data Journal
Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍: Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.
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