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Sonya K. Miller

Researcher at Pennsylvania State University

Publications -  33
Citations -  2896

Sonya K. Miller is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Stratosphere & Tropospheric ozone. The author has an hindex of 20, co-authored 32 publications receiving 2483 citations. Previous affiliations of Sonya K. Miller include Business International Corporation & Goddard Space Flight Center.

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Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia

TL;DR: The results extend previous conclusions that recent Northern Hemisphere surface temperature increases are likely anomalous in a long-term context to at least the past 1,700 years, but with additional strong caveats.
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Atlantic and Pacific multidecadal oscillations and Northern Hemisphere temperatures

TL;DR: A semi-empirical approach that combines climate observations and model simulations to estimate Atlantic- and Pacific-based internal multidecadal variability (termed “AMO” and “PMO,” respectively) is applied and the AMO and PMO are found to explain a large proportion of internal variability in Northern Hemisphere mean temperatures.
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Influence of Anthropogenic Climate Change on Planetary Wave Resonance and Extreme Weather Events

TL;DR: In this article, a specific fingerprint in the zonal mean surface temperature profile that is associated with quasi-resonant amplification of synoptic-scale waves with that wavenumber range becoming trapped within an effective mid-latitude atmospheric waveguide was identified.
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Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures

TL;DR: The authors quantifies a systematic bias in model-observation comparisons arising from differential warming rates between sea surface temperatures and surface air temperatures over oceans, and a further bias arises from the treatment of temperatures in regions where the sea ice boundary has changed.
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On forced temperature changes, internal variability, and the AMO

TL;DR: In this paper, the authors estimate the low-frequency internal variability of NH mean temperature using observed temperature variations, which include both forced and internal variability components, and several alternative model simulations of the (natural + anthropogenic) forced component alone.