This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1038/s41467-021-24113-9. This is version 2 of this Preprint.

Large model parameter and structural uncertainties in global projections of urban heat waves
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Abstract
Urban heat waves (UHWs) are strongly associated with socioeconomic impacts. Reliable projections of these extremes are pressingly needed for local actions in the context of extreme event preparedness and mitigation. Such information, however, is not available because current multi-model projections largely lack a representation of urban areas. Here, we use a newly-developed urban climate emulator framework in combination with global climate simulations to show that, at the urban scale a large proportion of the uncertainty results from choices of model parameter and structural design in projecting UHWs in the next several decades under climate... more
DOI
https://doi.org/10.31223/osf.io/f5pwa
Subjects
Atmospheric Sciences, Civil and Environmental Engineering, Computer Sciences, Earth Sciences, Engineering, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Risk Analysis, Statistics and Probability
Keywords
machine learning, Earth System Modeling, Heat Wave, Risk Analysis, Urban Climate, Urban Environment, Urban Heat Wave
Dates
Published: 2020-06-10 19:35
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