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Dive into the research topics where Doug McNeall is active.

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Featured researches published by Doug McNeall.


Nature | 2014

Uncertainties in the timing of unprecedented climates

Ed Hawkins; Bruce T. Anderson; Noah S. Diffenbaugh; Irina Mahlstein; Richard A. Betts; Gabi Hegerl; Manoj Joshi; Reto Knutti; Doug McNeall; Susan Solomon; Rowan Sutton; Jozef Syktus; Gabriel A. Vecchi

Arising from C. Mora et al. 502, 183–187 10.1038/nature12540 (2013)The question of when the signal of climate change will emerge from the background noise of climate variability—the ‘time of emergence’—is potentially important for adaptation planning. Mora et al. presented precise projections of the time of emergence of unprecedented regional climates. However, their methodology produces artificially early dates at which specific regions will permanently experience unprecedented climates and artificially low uncertainty in those dates everywhere. This overconfidence could impair the effectiveness of climate risk management decisions. There is a Reply to this Brief Communication Arising by Mora, C. et al. Nature 511, http://dx.doi.org/10.1038/nature13524 (2014).


Journal of Hydrometeorology | 2011

Validation of River Flows in HadGEM1 and HadCM3 with the TRIP River Flow Model

Pete Falloon; Richard A. Betts; Andrew J. Wiltshire; Rutger Dankers; Camilla Mathison; Doug McNeall; Paul D. Bates; Mark A. Trigg

AbstractThe Total Runoff Integrating Pathways (TRIP) global river-routing scheme in the third climate configuration of the Met Office Unified Model (HadCM3) and the newer Hadley Centre Global Environmental Model version 1 (HadGEM1) general circulation models (GCMs) have been validated against long-term average measured river discharge data from 40 stations on 24 major river basins from the Global Runoff Data Centre (GRDC). TRIP was driven by runoff produced directly by the two GCMs in order to assess both the skill of river flows produced within GCMs in general and to test this as a method for validating large-scale hydrology in GCMs. TRIP predictions of long-term-averaged annual discharge were improved at 28 out of 40 gauging stations on 24 of the world’s major rivers in HadGEM1 compared to HadCM3, particularly for low- and high-latitude basins, with predictions ranging from “good” (within 20% of observed values) to “poor” (biases exceeding 50%). For most regions, the modeled annual average river flows t...


Progress in Physical Geography | 2011

A review of recent developments in climate change science. Part I: Understanding of future change in the large-scale climate system:

Peter Good; John Caesar; Dan Bernie; Jason Lowe; P van der Linden; Simon N. Gosling; Rachel Warren; Nigel W. Arnell; S Smith; Jonathan L. Bamber; T Payne; Seymour W. Laxon; Meric A. Srokosz; Stephen Sitch; Nicola Gedney; Glen R. Harris; Helene T. Hewitt; Laura Jackson; Chris D. Jones; F. M. O'Connor; Jeff Ridley; M Vellinga; Paul R. Halloran; Doug McNeall

This article reviews some of the major lines of recent scientific progress relevant to the choice of global climate policy targets, focusing on changes in understanding since publication of the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4). Developments are highlighted in the following major climate system components: ice sheets; sea ice; the Atlantic Meridional Overturning Circulation; tropical forests; and accelerated carbon release from permafrost and ocean hydrates. The most significant developments in each component are identified by synthesizing input from multiple experts from each field. Overall, while large uncertainties remain in all fields, some substantial progress in understanding is revealed.


Journal of Cell Science | 2017

Predicting the targeting of tail-anchored proteins to subcellular compartments in mammalian cells

Joseph L. Costello; Inês G. Castro; Fátima Camões; Tina A. Schrader; Doug McNeall; Jing Yang; Evdokia-Anastasia Giannopoulou; Sílvia Gomes; Vivian Pogenberg; Nina A. Bonekamp; Daniela Ribeiro; Matthias Wilmanns; Gregory Jedd; Markus Islinger; Michael Schrader

ABSTRACT Tail-anchored (TA) proteins contain a single transmembrane domain (TMD) at the C-terminus that anchors them to the membranes of organelles where they mediate critical cellular processes. Accordingly, mutations in genes encoding TA proteins have been identified in a number of severe inherited disorders. Despite the importance of correctly targeting a TA protein to its appropriate membrane, the mechanisms and signals involved are not fully understood. In this study, we identify additional peroxisomal TA proteins, discover more proteins that are present on multiple organelles, and reveal that a combination of TMD hydrophobicity and tail charge determines targeting to distinct organelle locations in mammals. Specifically, an increase in tail charge can override a hydrophobic TMD signal and re-direct a protein from the ER to peroxisomes or mitochondria and vice versa. We show that subtle changes in those parameters can shift TA proteins between organelles, explaining why peroxisomes and mitochondria have many of the same TA proteins. This enabled us to associate characteristic physicochemical parameters in TA proteins with particular organelle groups. Using this classification allowed successful prediction of the location of uncharacterized TA proteins for the first time. Summary: Characteristic physicochemical features of tail-anchored membrane proteins, based on the interplay between transmembrane domain hydrophobicity and tail charge, allow prediction of their subcellular localization.


Nature Climate Change | 2018

How much CO 2 at 1.5 °C and 2 °C?

Richard A. Betts; Doug McNeall

The atmospheric concentration of CO2 at the time of passing 1.5 °C or 2 °C is unknown due to uncertainties in climate sensitivity and the concentrations of other GHGs. Impacts studies must account for a wide range of concentrations to avoid either over- or underestimating changes in crop yields and land and marine biodiversity.


IOP Conference Series: Earth and Environmental Science | 2009

Towards the probability of crossing tipping points

Peter G. Challenor; Doug McNeall

Towards the probability of crossing tipping points Peter Challenor and D McNeall What is the tipping point for the Greenland Ice Sheet? Jonathan Bamber, E Steig and D Dahl-Jensen Corrigendum: The topology of non-linear global carbon dynamics: from tipping points to planetary boundaries (2013 Environ. Res. Lett. 8 044048) J M Anderies, S R Carpenter, Will Steffen et al. Stochastic desertification Haim Weissmann and Nadav M. Shnerb Non-Axisymmetric Oscillation of Acoustically Levitated Water Drops at Specific Frequencies Shen Chang-Le, Xie Wen-Jun and Wei Bing-Bo Attribution of atmospheric CO2 and temperature increases to regions: importance of preindustrial land use change Julia Pongratz and Ken Caldeira Tipping points in the terrestrial biosphere


Nature Climate Change | 2014

Pause for thought

Ed Hawkins; Tamsin L. Edwards; Doug McNeall


Earth System Dynamics Discussions | 2012

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

Ben B. B. Booth; D. Bernie; Doug McNeall; Ed Hawkins; John Caesar; Chris A. Boulton; Pierre Friedlingstein; David M. H. Sexton


Geoscientific Model Development | 2013

The potential of an observational data set for calibration of a computationally expensive computer model

Doug McNeall; Peter G. Challenor; James R. Gattiker; Emma J. Stone


Wiley Interdisciplinary Reviews: Climate Change | 2011

Analyzing abrupt and nonlinear climate changes and their impacts

Doug McNeall; Paul R. Halloran; Peter Good; Richard A. Betts

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