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David L. Roberts

Researcher at Hadley Centre for Climate Prediction and Research

Publications -  13
Citations -  2017

David L. Roberts is an academic researcher from Hadley Centre for Climate Prediction and Research. The author has contributed to research in topics: Greenhouse gas & Climate change. The author has an hindex of 12, co-authored 13 publications receiving 1981 citations. Previous affiliations of David L. Roberts include Met Office.

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Anthropogenic climate change for 1860 to 2100 simulated with the HadCM3 model under updated emissions scenarios

TL;DR: In this paper, the authors examined the anthropogenically forced climate response over the historical period, 1860 to present, and projected response to 2100, using updated emissions scenarios and an improved coupled model (HadCM3) that does not use flux adjustments.
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Estimation of natural and anthropogenic contributions to twentieth century temperature change

TL;DR: In this article, the authors used a coupled atmosphere/ocean general circulation model to simulate the climatic response to natural and anthropogenic forcings from 1860 to 1997, and found that the early twentieth century warming can best be explained by a combination of warming due to increases in greenhouse gases and natural forcing, some cooling due to other anthropogenic forcing, and a substantial, but not implausible, contribution from internal variability.
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Indirect sulphate aerosol forcing in a climate model with an interactive sulphur cycle

TL;DR: In this paper, the effects of anthropogenic sulphate aerosol on cloud albedo and on precipitation efficiency were investigated using a new version of the Hadley Centre climate model.
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A comparison of scavenging and deposition processes in global models: Results from the WCRP Cambridge workshop of 1995

TL;DR: In this paper, the authors report on results from a World Climate Research Program workshop on representations of scavenging and deposition processes in global transport models of the atmosphere and provide a survey on the simulation diVerences between models.