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S. A. Spall

Researcher at Met Office

Publications -  12
Citations -  5403

S. A. Spall is an academic researcher from Met Office. The author has contributed to research in topics: Global warming & Climate change. The author has an hindex of 10, co-authored 12 publications receiving 5111 citations. Previous affiliations of S. A. Spall include Hadley Centre for Climate Prediction and Research & University of Southampton.

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Journal ArticleDOI

Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model

TL;DR: Results from a fully coupled, three-dimensional carbon–climate model are presented, indicating that carbon-cycle feedbacks could significantly accelerate climate change over the twenty-first century.
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Response of ocean ecosystems to climate warming

TL;DR: In this article, the authors examined six coupled climate model simulations to determine the ocean biological response to climate warming between the beginning of the industrial revolution and 2050, and found that global warming leads to a contraction of the highly productive marginal sea ice biome by 42% in the Northern Hemisphere and 17% in Southern Hemisphere, and leads to an expansion of the low productivity permanently stratified subtropical gyre biome by 4.0% in both hemispheres.
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The Carbon Cycle Response to ENSO: A Coupled Climate–Carbon Cycle Model Study

TL;DR: In this paper, a GCM coupled climate-carbon cycle model is used to study the mechanisms involved in the relationship between ENSO and the carbon cycle, and the model simulates the observed temperature, precipitation, and CO 2 response of the climate to the El Nino Southern Oscillation (ENSO) cycle.
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Simulated glacial and interglacial vegetation across Africa: implications for species phylogenies and trans‐African migration of plants and animals

TL;DR: In this paper, a state-of-the-art fully coupled earth system model (HadCM3LC) was used to simulate the distribution of the last glacial maximum (LGM) for the continent of Africa.
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Global fields of sea surface dimethylsulfide predicted from chlorophyll, nutrients and light

TL;DR: In this paper, a new equation was developed whereby DMS is predicted from the product of chlorophyll (C, mg m −3 ), light ( J, mean daily shortwave, W m −2 ) and a nutrient term (Q, dimensionless) using a broken-stick regression.