Forecasting urban temperatures through crowdsourced data from Citizen Weather Stations-Reference-Cited by-同舟云学术

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Forecasting urban temperatures through crowdsourced data from Citizen Weather Stations

Published:2024-07 Issue: Volume:56 Page:102021
ISSN:2212-0955
Container-title:Urban Climate
language:en
Short-container-title:Urban Climate

Author:

Romero Rodríguez Laura,Guerrero Delgado MCarmen,Castro Medina Daniel,Sánchez Ramos José,Álvarez Domínguez Servando

Funder

Ministerio de Ciencia e Innovación

Spain Ministry of Science and Innovation

Publisher

Elsevier BV

Reference50 articles.

1. Nighttime ambient temperature and sleep in community-dwelling older adults;Baniassadi;Sci. Total Environ.,2023

2. The quiet revolution of numerical weather prediction;Bauer;Nature,2015

3. Machine learning bias correction and downscaling of urban heatwave temperature predictions from kilometre to hectometre scale;Blunn;Meteorol. Appl.,2024

4. Mapping the urban heat island at the territory scale: an unsupervised learning approach for urban planning applied to the Canton of Geneva;Boccalatte;Sustain. Cities Soc.,2023

5. Empowering urban climate resilience and adaptation: crowdsourcing weather citizen stations-enhanced temperature prediction;Castro Medina;Sustain. Cities Soc.,2024

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1. Urban fluxes for free: Estimating urban turbulent surface fluxes from crowdsourced meteorological canyon layer observations;City and Environment Interactions;2025-08

2. A real-time and modular weather station software architecture based on microservices;Environmental Modelling & Software;2025-03

3. Data Science and AI for Sustainable Futures: Opportunities and Challenges;Sustainability;2025-02-26

4. Decoding Wildlife Habitat Shifts in a Changing Environment Through Machine Learning;International Journal of Scientific Research in Computer Science, Engineering and Information Technology;2025-01-05

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