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Gill Martin

Researcher at Met Office

Publications -  64
Citations -  3502

Gill Martin is an academic researcher from Met Office. The author has contributed to research in topics: Monsoon & Climate model. The author has an hindex of 21, co-authored 56 publications receiving 2912 citations.

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Development and evaluation of an Earth-System model – HadGEM2

TL;DR: In this paper, the authors describe the development and evaluation of an Earth system model suitable for centennial-scale climate prediction, which includes terrestrial and ocean ecosystems and gas-phase tropospheric chemistry along with their coupled interactions.
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Spatial Patterns of Precipitation Change in CMIP5: Why the Rich Do Not Get Richer in the Tropics

TL;DR: In this paper, changes in the patterns of tropical precipitation and circulation are analyzed in Coupled Model Intercomparison Project phase 5 (CMIP5) GCMs under the representative concentration pathway 8.5 (RCP8.5) scenario.
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Large rainfall changes consistently projected over substantial areas of tropical land

TL;DR: The authors quantifies a direct link between global greenhouse gas emissions and rainfall changes over tropical land, and identifies regions most at risk of large changes, such as southern and east Africa, and shows that despite uncertainty in the location of future rainfall shifts, climate models consistently project that large rainfall changes will occur for a considerable proportion of tropical land over the twenty-first century.
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Atmospheric Blocking and Mean Biases in Climate Models

TL;DR: In this paper, the authors show that much of the atmospheric blocking error diagnosed using common methods of analysis and current climate models is directly attributable to the climatological bias of the model, which explains a large proportion of diagnosed blocking error in models used in the recent Intergovernmental Panel for Climate Change report.
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Analysis and Reduction of Systematic Errors through a Seamless Approach to Modeling Weather and Climate

TL;DR: In this article, two particular systematic errors are examined: tropical circulation and precipitation distribution, and summer land surface temperature and moisture biases over Northern Hemisphere continental regions, each of these errors affects the model performance on time scales ranging from a few days to several decades.