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1. Skilful predictions of the Summer North Atlantic Oscillation

Author: Nick Dunstone, Doug M. Smith, Steven C. Hardiman, Leon Hermanson, Sarah Ineson, Gillian Kay, Chaofan Li, Julia F. Lockwood, Adam A. Scaife, Hazel Thornton, Mingfang Ting, and Lei Wang
Subjects: Geology, QE1-996.5, Environmental sciences, GE1-350
Abstract: Abstract The Summer North Atlantic Oscillation is the primary mode of atmospheric variability in the North Atlantic region and has a significant influence on regional European, North American and Asian summer climate. However, current dynamical seasonal prediction systems show no significant Summer North Atlantic Oscillation prediction skill, leaving society ill-prepared for extreme summers. Here we show an unexpected role for the stratosphere in driving the Summer North Atlantic Oscillation in both observations and climate prediction systems. The anomalous strength of the lower stratosphere polar vortex in late spring is found to propagate downwards and influence the Summer North Atlantic Oscillation. Windows of opportunity are identified for useful levels of Summer North Atlantic Oscillation prediction skill, both in the 50% of years when the late spring polar vortex is anomalously strong/weak and possibly earlier if a sudden stratospheric warming event occurs in late winter. However, we show that model dynamical signals are spuriously weak, requiring large ensembles to obtain robust signals and we identify a summer ‘signal-to-noise paradox’ as found in winter atmospheric circulation Our results open possibilities for a range of new summer climate services, including for agriculture, water management and health sectors.
Published: 2023
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2. Windows of opportunity for predicting seasonal climate extremes highlighted by the Pakistan floods of 2022

Author: Nick Dunstone, Doug M. Smith, Steven C. Hardiman, Paul Davies, Sarah Ineson, Shipra Jain, Chris Kent, Gill Martin, and Adam A. Scaife
Subjects: Science
Abstract: Abstract Skilful predictions of near-term climate extremes are key to a resilient society. However, standard methods of analysing seasonal forecasts are not optimised to identify the rarer and most impactful extremes. For example, standard tercile probability maps, used in real-time regional climate outlooks, failed to convey the extreme magnitude of summer 2022 Pakistan rainfall that was, in fact, widely predicted by seasonal forecasts. Here we argue that, in this case, a strong summer La Niña provided a window of opportunity to issue a much more confident forecast for extreme rainfall than average skill estimates would suggest. We explore ways of building forecast confidence via a physical understanding of dynamical mechanisms, perturbation experiments to isolate extreme drivers, and simple empirical relationships. We highlight the need for more detailed routine monitoring of forecasts, with improved tools, to identify regional climate extremes and hence utilise windows of opportunity to issue trustworthy and actionable early warnings.
Published: 2023
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3. Missing eddy feedback may explain weak signal-to-noise ratios in climate predictions

Author: Steven C. Hardiman, Nick J. Dunstone, Adam A. Scaife, Doug M. Smith, Ruth Comer, Yu Nie, and Hong-Li Ren
Subjects: Environmental sciences, GE1-350, Meteorology. Climatology, QC851-999
Abstract: Abstract The signal-to-noise paradox that climate models are better at predicting the real world than their own ensemble forecast members highlights a serious and currently unresolved model error, adversely affecting climate predictions and introducing uncertainty into climate projections. By computing the magnitude of feedback between transient eddies and large-scale flow anomalies in multiple seasonal forecast systems, this study shows that current systems underestimate this positive eddy feedback, and that this deficiency is strongly linked to weak signal-to-noise ratios in ensemble mean predictions. Improved eddy feedback is further shown to be linked to greater teleconnection strength between the El Niño Southern Oscillation and the Arctic Oscillation and to stronger predictable signals. We also present a technique to estimate the potential gain in skill that may come from eliminating eddy feedback deficiency, showing that skill could double in some extratropical regions, significantly improving predictions of the Arctic Oscillation.
Published: 2022
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4. The Impact of Prescribed Ozone in Climate Projections Run With HadGEM3‐GC3.1

Author: Steven C. Hardiman, Martin B. Andrews, Timothy Andrews, Andrew C. Bushell, Nick J. Dunstone, Harold Dyson, Gareth S. Jones, Jeff R. Knight, Erica Neininger, Fiona M. O'Connor, Jeff K. Ridley, Mark A. Ringer, Adam A. Scaife, Catherine A. Senior, and Richard A. Wood
Subjects: CMIP6, climate sensitivity, prescribed ozone, abrupt‐4xCO2, Physical geography, GB3-5030, Oceanography, GC1-1581
Abstract: Abstract The Coupled Model Intercomparison Project 6 protocol suggests prescribing preindustrial ozone concentrations in abrupt‐4xCO2 simulations. This leads to a mismatch between the thermal tropopause, which rises due to climate change, and the ozone tropopause, which remains fixed. The result is unphysically high ozone concentrations in the upper troposphere, leading to a warm bias in cold point temperature and increased stratospheric water vapor. In the U.K. physical climate model HadGEM3‐GC3.1 this increases the surface climate sensitivity. In the future, other climate models without interactive ozone schemes may face similar problems. We describe a method to interactively redistribute ozone in climate simulations, which removes the inconsistency between the thermal and ozone tropopause heights while retaining the prescribed ozone distribution as closely as possible. This removes unphysical consequences of the tropopause mismatch, while still allowing a fair comparison against other Coupled Model Intercomparison Project 6 model simulations. After each model year, the monthly mean, zonal mean, thermal tropopause is formed based on the previous two model years. The ozone tropopause is defined at 1 km below the thermal tropopause by setting ozone concentrations there to 80 ppbv, and smoothing appropriately. The mass of ozone removed from the troposphere is added to the stratosphere thus conserving the total mass of ozone. This redistribution is then applied proportionally to the 3‐D monthly mean ozone concentrations. The climate model is run for the following year, using this redistributed ozone, and then the whole process is repeated. Results are presented from preindustrial and abrupt‐4xCO2 simulations, but this method can be used for any climate simulation.
Published: 2019
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5. Historical Simulations With HadGEM3‐GC3.1 for CMIP6

Author: Martin B. Andrews, Jeff K. Ridley, Richard A. Wood, Timothy Andrews, Edward W. Blockley, Ben Booth, Eleanor Burke, Andrea J. Dittus, Piotr Florek, Lesley J. Gray, Stephen Haddad, Steven C. Hardiman, Leon Hermanson, Dan Hodson, Emma Hogan, Gareth S. Jones, Jeff R. Knight, Till Kuhlbrodt, Stergios Misios, Matthew S. Mizielinski, Mark A. Ringer, Jon Robson, and Rowan T. Sutton
Subjects: CMIP6, historical simulations, HadGEM3‐GC3.1, AOGCM, Physical geography, GB3-5030, Oceanography, GC1-1581
Abstract: Abstract We describe and evaluate historical simulations which use the third Hadley Centre Global Environment Model in the Global Coupled configuration 3.1 (HadGEM3‐GC3.1) and which form part of the UK's contribution to the sixth Coupled Model Intercomparison Project, CMIP6. These simulations, run at two resolutions, respond to historically evolving forcings such as greenhouse gases, aerosols, solar irradiance, volcanic aerosols, land use, and ozone concentrations. We assess the response of the simulations to these historical forcings and compare against the observational record. This includes the evolution of global mean surface temperature, ocean heat content, sea ice extent, ice sheet mass balance, permafrost extent, snow cover, North Atlantic sea surface temperature and circulation, and decadal precipitation. We find that the simulated time evolution of global mean surface temperature broadly follows the observed record but with important quantitative differences which we find are most likely attributable to strong effective radiative forcing from anthropogenic aerosols and a weak pattern of sea surface temperature response in the low to middle latitudes to volcanic eruptions. We also find evidence that anthropogenic aerosol forcings play a role in driving the Atlantic Multidecadal Variability and the Atlantic Meridional Overturning Circulation, which are key features of the North Atlantic ocean. Overall, the model historical simulations show many features in common with the observed record over the period 1850–2014 and so provide a basis for future in‐depth study of recent climate change.
Published: 2020
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6. Implementation of U.K. Earth System Models for CMIP6

Author: Alistair A. Sellar, Jeremy Walton, Colin G. Jones, Richard Wood, Nathan Luke Abraham, Miroslaw Andrejczuk, Martin B. Andrews, Timothy Andrews, Alex T. Archibald, Lee deMora, Harold Dyson, Mark Elkington, Richard Ellis, Piotr Florek, Peter Good, Laila Gohar, Stephen Haddad, Steven C. Hardiman, Emma Hogan, Alan Iwi, Christopher D. Jones, Ben Johnson, Douglas I. Kelley, Jamie Kettleborough, Jeff R. Knight, Marcus O. Köhler, Till Kuhlbrodt, Spencer Liddicoat, Irina Linova‐Pavlova, Matthew S. Mizielinski, Olaf Morgenstern, Jane Mulcahy, Erica Neininger, Fiona M. O'Connor, Ruth Petrie, Jeff Ridley, Jean‐Christophe Rioual, Malcolm Roberts, Eddy Robertson, Steven Rumbold, Jon Seddon, Harry Shepherd, Sungbo Shim, Ag Stephens, Joao C. Teixiera, Yongming Tang, Jonny Williams, Andy Wiltshire, and Paul T. Griffiths
Subjects: Physical geography, GB3-5030, Oceanography, GC1-1581
Abstract: Abstract We describe the scientific and technical implementation of two models for a core set of experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The models used are the physical atmosphere‐land‐ocean‐sea ice model HadGEM3‐GC3.1 and the Earth system model UKESM1 which adds a carbon‐nitrogen cycle and atmospheric chemistry to HadGEM3‐GC3.1. The model results are constrained by the external boundary conditions (forcing data) and initial conditions. We outline the scientific rationale and assumptions made in specifying these. Notable details of the implementation include an ozone redistribution scheme for prescribed ozone simulations (HadGEM3‐GC3.1) to avoid inconsistencies with the model's thermal tropopause, and land use change in dynamic vegetation simulations (UKESM1) whose influence will be subject to potential biases in the simulation of background natural vegetation. We discuss the implications of these decisions for interpretation of the simulation results. These simulations are expensive in terms of human and CPU resources and will underpin many further experiments; we describe some of the technical steps taken to ensure their scientific robustness and reproducibility.
Published: 2020
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7. Critical Southern Ocean climate model biases traced to atmospheric model cloud errors

Author: Patrick Hyder, John M. Edwards, Richard P. Allan, Helene T. Hewitt, Thomas J. Bracegirdle, Jonathan M. Gregory, Richard A. Wood, Andrew J. S. Meijers, Jane Mulcahy, Paul Field, Kalli Furtado, Alejandro Bodas-Salcedo, Keith D. Williams, Dan Copsey, Simon A. Josey, Chunlei Liu, Chris D. Roberts, Claudio Sanchez, Jeff Ridley, Livia Thorpe, Steven C. Hardiman, Michael Mayer, David I. Berry, and Stephen E. Belcher
Subjects: Science
Abstract: The Southern Ocean is critically important for global climate yet poorly represented by climate models. Here the authors trace sea surface temperature biases in this region to cloud-related errors in atmospheric-model simulated surface heat fluxes and provide a pathway to improve the models.
Published: 2018
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8. Publisher Correction: Critical Southern Ocean climate model biases traced to atmospheric model cloud errors

Author: Patrick Hyder, John M. Edwards, Richard P. Allan, Helene T. Hewitt, Thomas J. Bracegirdle, Jonathan M. Gregory, Richard A. Wood, Andrew J. S. Meijers, Jane Mulcahy, Paul Field, Kalli Furtado, Alejandro Bodas-Salcedo, Keith D. Williams, Dan Copsey, Simon A. Josey, Chunlei Liu, Chris D. Roberts, Claudio Sanchez, Jeff Ridley, Livia Thorpe, Steven C. Hardiman, Michael Mayer, David I. Berry, and Stephen E. Belcher
Subjects: Science
Abstract: 'In the original HTML version of this Article, ref.12 was incorrectly cited in the first sentence of the first paragraph of the Introduction. The correct citation is ref. 2. This has now been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.’
Published: 2018
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9. The Brewer–Dobson Circulation in CMIP6

Author: Marta Abalos, Natalia Calvo, Samuel Benito-Barca, Hella Garny, Steven C Hardiman, Pu Lin, Martin B Andrews, Neal Butchart, Rolando Garcia, Clara Orbe, David Saint-Martin, Shingo Watanabe, and Kohei Yoshida
Subjects: Meteorology And Climatology
Abstract: The Brewer–Dobson circulation (BDC) is a key feature of the stratosphere that models need to accurately represent in order to simulate surface climate variability and change adequately. For the first time, the Climate Model Intercomparison Project includes in its phase 6 (CMIP6) a set of diagnostics that allow for careful evaluation of the BDC. Here, the BDC is evaluated against observations and reanalyses using historical simulations. CMIP6 results confirm the well-known inconsistency in the sign of BDC trends between observations and models in the middle and upper stratosphere. Nevertheless, the large uncertainty in the observational trend estimates opens the door to compatibility. In particular, when accounting for the limited sampling of the observations, model and observational trend error bars overlap in 40 % of the simulations with available output. The increasing CO2 simulations feature an acceleration of the BDC but reveal a large spread in the middle-to-upper stratospheric trends, possibly related to the parameterized gravity wave forcing. The very close connection between the shallow branch of the residual circulation and surface temperature is highlighted, which is absent in the deep branch. The trends in mean age of air are shown to be more robust throughout the stratosphere than those in the residual circulation.
Published: 2021
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10. Using large ensembles to quantify the impact of sudden stratospheric warmings and their precursors on the North Atlantic Oscillation

Author: Philip E. Bett, Adam A. Scaife, Steven C. Hardiman, Hazel E. Thornton, Xiaocen Shen, Lin Wang, and Bo Pang
Subjects: Atmospheric Science
Abstract: Sudden-stratospheric-warming (SSW) events are often followed by significant weather and climate impacts at the surface. By affecting the North Atlantic Oscillation (NAO), SSWs can lead to periods of extreme cold in parts of Europe and North America. Previous studies have used observations and free-running climate models to try to identify features of the atmosphere prior to an SSW that can determine the subsequent impact at the surface. However, the limited observational record makes it difficult to accurately quantify these relationships. Here, we instead use a large ensemble of seasonal hindcasts. We first test whether the hindcasts reproduce the observed characteristics of SSWs and their surface signature. We find that the simulations are statistically indistinguishable from the observations, in terms of the overall risk of an SSW per winter (56 %), the frequency of SSWs with negative NAO responses (65 %), the magnitude of the NAO responses, and the frequency of wavenumber-2-dominated SSWs (26 %). We also assess the relationships between prior conditions and the NAO response in the 30 d following an SSW. We find that there is little information in the precursor state to guide differences in the subsequent NAO behaviour between one SSW and another, reflecting the substantial natural variability between SSW events. The strongest relationships with the NAO response are from pre-SSW sea level pressure anomalies over the polar cap and from zonal-wind anomalies in the lower stratosphere, both exhibiting correlations of around 0.3. The pre-SSW NAO has little bearing on its post-SSW state. The strength of the pre-SSW zonal-wind anomalies at 10 hPa is also not significantly correlated with the NAO response. Finally, we find that the mean NAO response in the first 10 d following wave-2-dominated SSWs is much more strongly negative than in wave-1 cases. However, the subsequent response in days 11–30 is very similar regardless of the dominant wavenumber. In all cases, the composite mean responses are the result of very broad distributions from individual SSW events, necessitating a probabilistic analysis using large ensembles.
Published: 2023

11. Deriving Global OH Abundance and Atmospheric Lifetimes for Long‐Lived Gases: A Search for CH3CCl3 Alternatives

Author: Qing Liang, Martyn P. Chipperfield, Eric L. Fleming, N. Luke Abraham, Peter Braesicke, James B. Burkholder, John S. Daniel, Sandip Dhomse, Paul J. Fraser, Steven C. Hardiman, Charles H. Jackman, Douglas E. Kinnison, Paul B. Krummel, Stephen A. Montzka, Olaf Morgenstern, Archie McCulloch, Jens Mühle, Paul A. Newman, Vladimir L. Orkin, Giovanni Pitari, Ronald G. Prinn, Matthew Rigby, Eugene Rozanov, Andrea Stenke, Fiona Tummon, Guus J. M. Velders, Daniele Visioni, and Ray F. Weiss
Published: 2017
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12. Long-range prediction and the stratosphere

Author: Adam A. Scaife, Mark P. Baldwin, Amy H. Butler, Andrew J. Charlton-Perez, Daniela I. V. Domeisen, Chaim I. Garfinkel, Steven C. Hardiman, Peter Haynes, Alexey Yu Karpechko, Eun-Pa Lim, Shunsuke Noguchi, Judith Perlwitz, Lorenzo Polvani, Jadwiga H. Richter, John Scinocca, Michael Sigmond, Theodore G. Shepherd, Seok-Woo Son, and David W. J. Thompson
Subjects: Atmospheric Science
Abstract: Over recent years there have been concomitant advances in the development of stratosphere-resolving numerical models, our understanding of stratosphere–troposphere interaction, and the extension of long-range forecasts to explicitly include the stratosphere. These advances are now allowing for new and improved capability in long-range prediction. We present an overview of this development and show how the inclusion of the stratosphere in forecast systems aids monthly, seasonal, and annual-to-decadal climate predictions and multidecadal projections. We end with an outlook towards the future and identify areas of improvement that could further benefit these rapidly evolving predictions., Atmospheric Chemistry and Physics, 22 (4), ISSN:1680-7375, ISSN:1680-7367
Published: 2022

13. The Impact of Prescribed Ozone in Climate Projections Run With HadGEM3‐GC3.1

Author: Mark A. Ringer, Jeff Ridley, Richard Wood, Harold Dyson, Erica Neininger, Catherine A. Senior, Fiona M. O'Connor, Gareth S. Jones, Steven C. Hardiman, Nick Dunstone, Adam A. Scaife, Jeff Knight, Andrew C. Bushell, Timothy Andrews, and Martin B. Andrews
Subjects: Global and Planetary Change, Ozone, Atmospheric sciences, prescribed ozone, chemistry.chemical_compound, lcsh:Oceanography, chemistry, abrupt‐4xCO2, General Earth and Planetary Sciences, Environmental Chemistry, Environmental science, Climate sensitivity, climate sensitivity, lcsh:GC1-1581, lcsh:GB3-5030, lcsh:Physical geography, CMIP6
Abstract: The Coupled Model Intercomparison Project 6 protocol suggests prescribing preindustrial ozone concentrations in abrupt‐4xCO2 simulations. This leads to a mismatch between the thermal tropopause, which rises due to climate change, and the ozone tropopause, which remains fixed. The result is unphysically high ozone concentrations in the upper troposphere, leading to a warm bias in cold point temperature and increased stratospheric water vapor. In the U.K. physical climate model HadGEM3‐GC3.1 this increases the surface climate sensitivity. In the future, other climate models without interactive ozone schemes may face similar problems. We describe a method to interactively redistribute ozone in climate simulations, which removes the inconsistency between the thermal and ozone tropopause heights while retaining the prescribed ozone distribution as closely as possible. This removes unphysical consequences of the tropopause mismatch, while still allowing a fair comparison against other Coupled Model Intercomparison Project 6 model simulations. After each model year, the monthly mean, zonal mean, thermal tropopause is formed based on the previous two model years. The ozone tropopause is defined at 1 km below the thermal tropopause by setting ozone concentrations there to 80 ppbv, and smoothing appropriately. The mass of ozone removed from the troposphere is added to the stratosphere thus conserving the total mass of ozone. This redistribution is then applied proportionally to the 3‐D monthly mean ozone concentrations. The climate model is run for the following year, using this redistributed ozone, and then the whole process is repeated. Results are presented from preindustrial and abrupt‐4xCO2 simulations, but this method can be used for any climate simulation.
Published: 2019

14. The Brewer-Dobson circulation in CMIP6

Author: Shingo Watanabe, Samuel Benito-Barca, Clara Orbe, Steven C. Hardiman, Marta Abalos, Neal Butchart, Natalia Calvo, Pu Lin, David Saint-Martin, Rolando R. Garcia, Kohei Yoshida, Martin B. Andrews, and Hella Garny
Subjects: Atmospheric Science, Physics, QC1-999, Física atmosférica, Forcing (mathematics), Residual, Stratosphärische Zirkulation, Brewer-Dobson circulation, Chemistry, Acceleration, Circulation (fluid dynamics), Climatology, Environmental science, Climate model, Gravity wave, QD1-999, Stratosphere
Abstract: The Brewer–Dobson circulation (BDC) is a key feature of the stratosphere that models need to accurately represent in order to simulate surface climate variability and change adequately. For the first time, the Climate Model Intercomparison Project includes in its phase 6 (CMIP6) a set of diagnostics that allow for careful evaluation of the BDC. Here, the BDC is evaluated against observations and reanalyses using historical simulations. CMIP6 results confirm the well-known inconsistency in the sign of BDC trends between observations and models in the middle and upper stratosphere. Nevertheless, the large uncertainty in the observational trend estimates opens the door to compatibility. In particular, when accounting for the limited sampling of the observations, model and observational trend error bars overlap in 40 % of the simulations with available output. The increasing CO2 simulations feature an acceleration of the BDC but reveal a large spread in the middle-to-upper stratospheric trends, possibly related to the parameterized gravity wave forcing. The very close connection between the shallow branch of the residual circulation and surface temperature is highlighted, which is absent in the deep branch. The trends in mean age of air are shown to be more robust throughout the stratosphere than those in the residual circulation.
Published: 2021

15. Implementation of U.K. Earth system models for CMIP6

Author: Jamie Kettleborough, Nathan Luke Abraham, Harry Shepherd, Jonny Williams, Timothy Andrews, Irina Linova-Pavlova, Chris D. Jones, Sungbo Shim, Alistair Sellar, Alexander T. Archibald, L. K. Gohar, Mark Elkington, Erica Neininger, Steven C. Hardiman, Olaf Morgenstern, Harold Dyson, Colin Jones, Jon Seddon, Jeremy Walton, Lee de Mora, Jean-Christophe Rioual, Martin B. Andrews, Eddy Robertson, Jeff Ridley, Alan Iwi, Paul T. Griffiths, Ben Johnson, Douglas I. Kelley, Jeff Knight, Richard Wood, Emma Hogan, Malcolm J. Roberts, Spencer Liddicoat, Piotr Florek, Richard J. Ellis, Andy Wiltshire, Ruth Petrie, Till Kuhlbrodt, Stephen Haddad, Jane Mulcahy, Peter Good, Miroslaw Andrejczuk, Joao C. Teixiera, Ag Stephens, Fiona M. O'Connor, S. T. Rumbold, Yongming Tang, Matthew S. Mizielinski, and Marcus O. Köhler
Subjects: Scheme (programming language), 010504 meteorology & atmospheric sciences, Computer science, 010502 geochemistry & geophysics, 01 natural sciences, Ecology and Environment, Atmospheric Sciences, Interpretation (model theory), lcsh:Oceanography, Environmental Chemistry, lcsh:GC1-1581, Boundary value problem, Robustness (economics), lcsh:Physical geography, 0105 earth and related environmental sciences, computer.programming_language, Global and Planetary Change, Coupled model intercomparison project, Forcing (recursion theory), Industrial engineering, Earth system science, 13. Climate action, General Earth and Planetary Sciences, Tropopause, lcsh:GB3-5030, computer
Abstract: We describe the scientific and technical implementation of two models for a core set of\ud experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6).\ud The models used are the physical atmosphere-land-ocean-sea ice model HadGEM3-GC3.1 and the\ud Earth system model UKESM1 which adds a carbon-nitrogen cycle and atmospheric chemistry to\ud HadGEM3-GC3.1. The model results are constrained by the external boundary conditions (forcing data)\ud and initial conditions.We outline the scientific rationale and assumptions made in specifying these.\ud Notable details of the implementation include an ozone redistribution scheme for prescribed ozone\ud simulations (HadGEM3-GC3.1) to avoid inconsistencies with the model's thermal tropopause, and land use\ud change in dynamic vegetation simulations (UKESM1) whose influence will be subject to potential biases in\ud the simulation of background natural vegetation.We discuss the implications of these decisions for\ud interpretation of the simulation results. These simulations are expensive in terms of human and CPU\ud resources and will underpin many further experiments; we describe some of the technical steps taken to\ud ensure their scientific robustness and reproducibility.
Published: 2020

16. Critical Southern Ocean climate model biases traced to atmospheric model cloud errors

Author: Alejandro Bodas-Salcedo, Patrick Hyder, Dan Copsey, Simon A. Josey, Jeff Ridley, David I. Berry, Jane Mulcahy, Christopher D. Roberts, Kalli Furtado, Jonathan M. Gregory, John M. Edwards, Thomas J. Bracegirdle, Richard P. Allan, Stephen E. Belcher, Chunlei Liu, Steven C. Hardiman, Paul R. Field, Livia Thorpe, Helene T. Hewitt, Michael Mayer, Richard Wood, Keith D. Williams, Claudio Sanchez, and Andrew J. S. Meijers
Subjects: 010504 meteorology & atmospheric sciences, Science, General Physics and Astronomy, Flux, Atmospheric model, 010502 geochemistry & geophysics, Atmospheric sciences, 01 natural sciences, Article, General Biochemistry, Genetics and Molecular Biology, Projection and prediction, Physics::Geophysics, Thermal, lcsh:Science, Physics::Atmospheric and Oceanic Physics, 0105 earth and related environmental sciences, Atmospheric dynamics, Multidisciplinary, Atmospheric models, Physical oceanography, Oceanic climate, General Chemistry, Publisher Correction, Sea surface temperature, Heat flux, 13. Climate action, Environmental science, lcsh:Q, Climate model
Abstract: The Southern Ocean is a pivotal component of the global climate system yet it is poorly represented in climate models, with significant biases in upper-ocean temperatures, clouds and winds. Combining Atmospheric and Coupled Model Inter-comparison Project (AMIP5/CMIP5) simulations, with observations and equilibrium heat budget theory, we show that across the CMIP5 ensemble variations in sea surface temperature biases in the 40–60°S Southern Ocean are primarily caused by AMIP5 atmospheric model net surface flux bias variations, linked to cloud-related short-wave errors. Equilibration of the biases involves local coupled sea surface temperature bias feedbacks onto the surface heat flux components. In combination with wind feedbacks, these biases adversely modify upper-ocean thermal structure. Most AMIP5 atmospheric models that exhibit small net heat flux biases appear to achieve this through compensating errors. We demonstrate that targeted developments to cloud-related parameterisations provide a route to better represent the Southern Ocean in climate models and projections., The Southern Ocean is critically important for global climate yet poorly represented by climate models. Here the authors trace sea surface temperature biases in this region to cloud-related errors in atmospheric-model simulated surface heat fluxes and provide a pathway to improve the models.
Published: 2018

17. The asymmetric response of Yangtze river basin summer rainfall to El Nino/La Nina

Author: Claudia Christine Stephan, Steven C. Hardiman, Nick Dunstone, Hong-Li Ren, Chaofan Li, Doug Smith, Adam A. Scaife, Bo Lu, and Philip E. Bett
Subjects: 010504 meteorology & atmospheric sciences, Renewable Energy, Sustainability and the Environment, asymmetric rainfall response, ENSO, Indian Ocean, Yangtze basin rainfall, seasonal forecasting, Lead (sea ice), Flooding (psychology), Public Health, Environmental and Occupational Health, Climate change, Structural basin, 010502 geochemistry & geophysics, 01 natural sciences, La Niña, El Niño, Climatology, Yangtze river, Environmental science, Precipitation, 0105 earth and related environmental sciences, General Environmental Science
Abstract: The Yangtze river basin, in South East China, experiences anomalously high precipitation in summers following El Niño. This can lead to extensive flooding and loss of life. However, the response following La Niña has not been well documented. In this study, the response of Yangtze summer rainfall to El Niño/La Niña is found to be asymmetric, with no significant response following La Niña. The nature of this asymmetric response is found to be in good agreement with that simulated by the Met Office seasonal forecast system. Yangtze summer rainfall correlates positively with spring sea surface temperatures in the Indian Ocean and northwest Pacific. Indian Ocean sea surface temperatures are found to respond linearly to El Niño/La Niña, and to have a linear impact on Yangtze summer rainfall. However, northwest Pacific sea surface temperatures respond much more strongly following El Niño and, further, correlate more strongly with positive rainfall years. It is concluded that, whilst delayed Indian Ocean signals may influence summer Yangtze rainfall, it is likely that they do not lead to the asymmetric nature of the rainfall response to El Niño/La Niña.
Published: 2018

18. Review of the global models used within phase 1 of the Chemistry–Climate Model Initiative (CCMI)

Author: Simone Tilmes, Béatrice Josse, Slimane Bekki, Patrick Jöckel, David Saint-Martin, N. Luke Abraham, Makoto Deushi, Meiyun Lin, Yousuke Yamashita, Guang Zeng, Rolando R. Garcia, Andrea Stenke, Alexander T. Archibald, Martine Michou, Marion Marchand, Kengo Sudo, Michael Manyin, Sandip Dhomse, Martyn P. Chipperfield, Luke D. Oman, Kane A. Stone, Douglas E. Kinnison, David A. Plummer, Taichu Y. Tanaka, Olaf Morgenstern, Eva Mancini, Giovanni Pitari, Virginie Marécal, Larry W. Horowitz, Kohei Yoshida, Neal Butchart, Steven C. Hardiman, Laura E. Revell, Hideharu Akiyoshi, Robyn Schofield, Michaela I. Hegglin, Fiona M. O'Connor, Eugene Rozanov, National Institute of Water and Atmospheric Research [Wellington] (NIWA), Department of Meteorology [Reading], University of Reading (UOR), Institute for Atmospheric and Climate Science [Zürich] (IAC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], National Centre for Atmospheric Science [Leeds] (NCAS), Natural Environment Research Council (NERC), Department of Chemistry [Cambridge, UK], University of Cambridge [UK] (CAM), National Institute for Environmental Studies (NIES), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), School of Earth and Environment [Leeds] (SEE), University of Leeds, Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), National Center for Atmospheric Research [Boulder] (NCAR), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), DLR Institut für Physik der Atmosphäre (IPA), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Princeton University, Department of Physical and Chemical Sciences [L'Aquila] (DSFC), Università degli Studi dell'Aquila = University of L'Aquila (UNIVAQ), Science Systems and Applications, Inc. [Lanham] (SSAI), NASA Goddard Space Flight Center (GSFC), Environment and Climate Change Canada, Bodeker Scientific, School of Earth Sciences [Melbourne], Faculty of Science [Melbourne], University of Melbourne-University of Melbourne, Massachusetts Institute of Technology (MIT), Graduate School of Environmental Studies [Nagoya], Nagoya University, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), European Project: 603557,EC:FP7:ENV,FP7-ENV-2013-two-stage,STRATOCLIM(2013), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Università degli Studi dell'Aquila (UNIVAQ), Archibald, Alexander [0000-0001-9302-4180], and Apollo - University of Cambridge Repository
Subjects: 010504 meteorology & atmospheric sciences, Chemical transport model, Meteorology, 010502 geochemistry & geophysics, 01 natural sciences, Chemistry climate model, MESSy, Multidisciplinary approach, Erdsystem-Modellierung, Chemistry Climate Modelling, Model development, 0105 earth and related environmental sciences, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], EMAC, 13 Climate Action, Forcing (recursion theory), Global warming, lcsh:QE1-996.5, Chemistry Climate Model Initiative (CCMI), global atmospheric model, 37 Earth Sciences, lcsh:Geology, Atmospheric Chemiestry, Modular Earth Submodel System, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, General Circulation Model, 3701 Atmospheric Sciences
Abstract: We present an overview of state-of-the-art chemistry–climate and chemistry transport models that are used within phase 1 of the Chemistry–Climate Model Initiative (CCMI-1). The CCMI aims to conduct a detailed evaluation of participating models using process-oriented diagnostics derived from observations in order to gain confidence in the models' projections of the stratospheric ozone layer, tropospheric composition, air quality, where applicable global climate change, and the interactions between them. Interpretation of these diagnostics requires detailed knowledge of the radiative, chemical, dynamical, and physical processes incorporated in the models. Also an understanding of the degree to which CCMI-1 recommendations for simulations have been followed is necessary to understand model responses to anthropogenic and natural forcing and also to explain inter-model differences. This becomes even more important given the ongoing development and the ever-growing complexity of these models. This paper also provides an overview of the available CCMI-1 simulations with the aim of informing CCMI data users.
Published: 2017

19. Multimodel climate and variability of the stratosphere

Author: Darryn W. Waugh, Steven Pawson, Paul J. Kushner, N. Butchart, Judith Perlwitz, Hella Garny, Eugene Rozanov, A. J. G. Baumgaertner, Rolando R. Garcia, Kiyotaka Shibata, Lei Wang, John A. Pyle, Veronika Eyring, Kirstin Krüger, Marion Marchand, Scott Osprey, Steven C. Hardiman, Jean-Francois Lamarque, John Austin, Ch. Brühl, Martine Michou, H. Teyssèdre, Paul A. Newman, David A. Plummer, Tetsu Nakamura, Hideharu Akiyoshi, Slimane Bekki, Peter H. Haynes, Sandip Dhomse, Dan Smale, Olaf Morgenstern, Martyn P. Chipperfield, Patrick Jöckel, Martin Dameris, P. Braesicke, Theodore G. Shepherd, W. Tian, Andrew Charlton-Perez, Yousuke Yamashita, Irene Cionni, Michael Sigmond, John F. Scinocca, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Department of Meteorology [Reading], University of Reading (UOR), DLR Institut für Physik der Atmosphäre (IPA), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), NCAS-Climate [Cambridge], Department of Chemistry [Cambridge, UK], University of Cambridge [UK] (CAM)-University of Cambridge [UK] (CAM), Leibniz-Institut für Meereswissenschaften (IFM-GEOMAR), Department of Physics [Toronto], University of Toronto, NASA Goddard Space Flight Center (GSFC), Department of Atmospheric, Oceanic and Planetary Physics [Oxford] (AOPP), University of Oxford, Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado [Boulder]-National Oceanic and Atmospheric Administration (NOAA), National Institute for Environmental Studies (NIES), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), University Corporation for Atmospheric Research (UCAR), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Max Planck Institute for Chemistry (MPIC), Max-Planck-Gesellschaft, School of Earth and Environment [Leeds] (SEE), University of Leeds, National Center for Atmospheric Research [Boulder] (NCAR), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), Johns Hopkins University (JHU), Met Office Hadley Centre ( MOHC ), University of Reading ( UOR ), DLR Institut für Physik der Atmosphäre ( IPA ), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] ( DLR ), University of Cambridge [UK] ( CAM ) -University of Cambridge [UK] ( CAM ), Leibniz-Institut für Meereswissenschaften ( IFM-GEOMAR ), NASA Goddard Space Flight Center ( GSFC ), Department of Atmospheric, Oceanic and Planetary Physics [Oxford] ( AOPP ), University of Oxford [Oxford], Cooperative Institute for Research in Environmental Sciences ( CIRES ), University of Colorado Boulder [Boulder]-National Oceanic and Atmospheric Administration ( NOAA ), National Institute for Environmental Studies ( NIES ), NOAA Geophysical Fluid Dynamics Laboratory ( GFDL ), National Oceanic and Atmospheric Administration ( NOAA ), University Corporation for Atmospheric Research ( UCAR ), SHTI - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales ( LATMOS ), Université de Versailles Saint-Quentin-en-Yvelines ( UVSQ ) -Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Versailles Saint-Quentin-en-Yvelines ( UVSQ ) -Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ), Max Planck Institute for Chemistry ( MPIC ), School of Earth and Environment [Leeds] ( SEE ), National Center for Atmospheric Research [Boulder] ( NCAR ), Groupe d'étude de l'atmosphère météorologique ( CNRM-GAME ), Institut national des sciences de l'Univers ( INSU - CNRS ) -Météo France-Centre National de la Recherche Scientifique ( CNRS ), National Institute of Water and Atmospheric Research [Lauder] ( NIWA ), Canadian Centre for Climate Modelling and Analysis ( CCCma ), Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center ( PMOD/WRC ), Meteorological Research Institute [Tsukuba] ( MRI ), Japan Meteorological Agency ( JMA ), Johns Hopkins University ( JHU ), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), and Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)
Subjects: quasi-biennial oscillation, Atmospheric Science, polar night jet, 010504 meteorology & atmospheric sciences, Soil Science, Aquatic Science, Sudden stratospheric warming, 010502 geochemistry & geophysics, Oceanography, Atmospheric sciences, 01 natural sciences, Geochemistry and Petrology, Polar vortex, Earth and Planetary Sciences (miscellaneous), General circulation model, Southern Hemisphere, Stratosphere, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Ecology, Polar night, Northern Hemisphere, Paleontology, Forestry, Jet stream, stratospheric warmings, Geophysics, [ PHYS.PHYS.PHYS-AO-PH ] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], 13. Climate action, Space and Planetary Science, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, Environmental science, Polar, Dynamik der Atmosphäre, Stratospheric climate
Abstract: The stratospheric climate and variability from simulations of sixteen chemistry-climate models is evaluated. On average the polar night jet is well reproduced though its variability is less well reproduced with a large spread between models. Polar temperature biases are less than 5 K except in the Southern Hemisphere (SH) lower stratosphere in spring. The accumulated area of low temperatures responsible for polar stratospheric cloud formation is accurately reproduced for the Antarctic but underestimated for the Arctic. The shape and position of the polar vortex is well simulated, as is the tropical upwelling in the lower stratosphere. There is a wide model spread in the frequency of major sudden stratospheric warnings (SSWs), late biases in the breakup of the SH vortex, and a weak annual cycle in the zonal wind in the tropical upper stratosphere. Quantitatively, "metrics" indicate a wide spread in model performance for most diagnostics with systematic biases in many, and poorer performance in the SH than in the Northern Hemisphere (NH). Correlations were found in the SH between errors in the final warming, polar temperatures, the leading mode of variability, and jet strength, and in the NH between errors in polar temperatures, frequency of major SSWs, and jet strength. Models with a stronger QBO have stronger tropical upwelling and a colder NH vortex. Both the qualitative and quantitative analysis indicate a number of common and long-standing model problems, particularly related to the simulation of the SH and stratospheric variability. Copyright 2011 by the American Geophysical Union.
Published: 2016

20. The HadGEM2-ES implementation of CMIP5 centennial simulations

Author: Patricia Cadule, M. Doutriaux-Boucher, Alistair Sellar, Scott Osprey, K. D. Corbin, Jemma Gornall, M. Zerroukat, Pierre Friedlingstein, J. Hughes, Fiona M. O'Connor, Steven C. Hardiman, Paul J. Valdes, George C. Hurtt, Kyung-On Boo, Gareth S. Jones, Erika J. Palin, Lesley J. Gray, William Ingram, Jeff Knight, Robert J. Andres, N. Butchart, Andrew Schurer, Rachel M. Law, Nicolas Bellouin, S. Woodward, Thomas Raddatz, Spencer Liddicoat, Michael G. Sanderson, Christopher J Bell, M. Yoshioka, Paul R. Halloran, L. Parsons Chini, Nigel Wood, Jean-Francois Lamarque, Malte Meinshausen, Alessio Bozzo, Chris D. Jones, Institut Pierre-Simon-Laplace (IPSL), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), École normale supérieure - Paris (ENS-PSL), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: Meteorology, 010504 meteorology & atmospheric sciences, SPATIALLY EXPLICIT, Atmospheric model, 010501 environmental sciences, 010502 geochemistry & geophysics, ATMOSPHERE MODEL, SOIL-MOISTURE, 01 natural sciences, chemistry.chemical_compound, Land use, land-use change and forestry, Tropospheric ozone, FUTURE CLIMATE, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, lcsh:QE1-996.5, CLIMATE MODEL, Representative Concentration Pathways, LAND-USE CHANGE, THERMOHALINE CIRCULATION, Earth system science, lcsh:Geology, 20TH-CENTURY TEMPERATURE, Sea surface temperature, chemistry, 13. Climate action, Greenhouse gas, Climatology, SEA-SURFACE TEMPERATURE, SULFUR EMISSIONS, Climate model
Abstract: The scientific understanding of the Earth's climate system, including the central question of how the climate system is likely to respond to human-induced perturbations, is comprehensively captured in GCMs and Earth System Models(ESM). Diagnosing the simulated climate response, and comparing responses across different models, is crucially dependent on transparent assumptions of how the GCM/ESM has been driven – especially because the implementation can involve subjective decisions and may differ between modelling groups performing the same experiment. This paper outlines the climate forcings and setup of the Met Office Hadley Centre ESM, HadGEM2-ES for the CMIP5 set of centennial experiments. We document the prescribed greenhouse gas concentrations, aerosol precursors, stratospheric and tropospheric ozone assumptions, as well as implementation of land-use change and natural forcings for the HadGEM2-ES historical and future experiments following the Representative Concentration Pathways. In addition, we provide details of how HadGEM2-ES ensemble members were initialised from the control run and how the palaeoclimate and AMIP experiments, as well as the "emission-driven" RCP experiments were performed.
Published: 2016

21. The Impact of Two Coupled Cirrus Microphysics–Radiation Parameterizations on the Temperature and Specific Humidity Biases in the Tropical Tropopause Layer in a Climate Model

Author: Steven C. Hardiman, Paul R. Field, Peter Hill, Kalli Furtado, David N. Walters, James Manners, and Anthony J. Baran
Subjects: Physics, Atmospheric Science, 010504 meteorology & atmospheric sciences, Microphysics, Second moment of area, 010502 geochemistry & geophysics, Atmospheric sciences, 01 natural sciences, Moment (mathematics), Nonlinear system, Extinction (optical mineralogy), Climatology, Mixing ratio, Climate model, Cirrus, Physics::Atmospheric and Oceanic Physics, 0105 earth and related environmental sciences
Abstract: The impact of two different coupled cirrus microphysics–radiation parameterizations on the zonally averaged temperature and humidity biases in the tropical tropopause layer (TTL) of a Met Office climate model configuration is assessed. One parameterization is based on a linear coupling between a model prognostic variable, the ice mass mixing ratio qi, and the integral optical properties. The second is based on the integral optical properties being parameterized as functions of qi and temperature, Tc, where the mass coefficients (i.e., scattering and extinction) are parameterized as nonlinear functions of the ratio between qi and Tc. The cirrus microphysics parameterization is based on a moment estimation parameterization of the particle size distribution (PSD), which relates the mass moment (i.e., second moment if mass is proportional to size raised to the power of 2) of the PSD to all other PSD moments through the magnitude of the second moment and Tc. This same microphysics PSD parameterization is applied to calculate the integral optical properties used in both radiation parameterizations and, thus, ensures PSD and mass consistency between the cirrus microphysics and radiation schemes. In this paper, the temperature-non-dependent and temperature-dependent parameterizations are shown to increase and decrease the zonally averaged temperature biases in the TTL by about 1 K, respectively. The temperature-dependent radiation parameterization is further demonstrated to have a positive impact on the specific humidity biases in the TTL, as well as decreasing the shortwave and longwave biases in the cloudy radiative effect. The temperature-dependent radiation parameterization is shown to be more consistent with TTL and global radiation observations.
Published: 2016

22. The Effect of a Well-Resolved Stratosphere on Surface Climate: Differences between CMIP5 Simulations with High and Low Top Versions of the Met Office Climate Model

Author: Tim Hinton, Steven C. Hardiman, Lesley J. Gray, Scott Osprey, and N. Butchart
Subjects: Atmospheric Science, Coupled model intercomparison project, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, 0207 environmental engineering, Mode (statistics), 02 engineering and technology, Unified Model, Atmospheric sciences, 7. Clean energy, 01 natural sciences, 13. Climate action, North Atlantic oscillation, Climatology, Sea ice, Environmental science, Climate model, 020701 environmental engineering, Stratosphere, 0105 earth and related environmental sciences, Teleconnection
Abstract: The importance of using a general circulation model that includes a well-resolved stratosphere for climate simulations, and particularly the influence this has on surface climate, is investigated. High top model simulations are run with the Met Office Unified Model for the Coupled Model Intercomparison Project Phase 5 (CMIP5). These simulations are compared to equivalent simulations run using a low top model differing only in vertical extent and vertical resolution above 15 km. The period 1960–2002 is analyzed and compared to observations and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset. Long-term climatology, variability, and trends in surface temperature and sea ice, along with the variability of the annular mode index, are found to be insensitive to the addition of a well-resolved stratosphere. The inclusion of a well-resolved stratosphere, however, does improve the impact of atmospheric teleconnections on surface climate, in particular the response to El Niño–Southern Oscillation, the quasi-biennial oscillation, and midwinter stratospheric sudden warmings (i.e., zonal mean wind reversals in the middle stratosphere). Thus, including a well-represented stratosphere could improve climate simulation on intraseasonal to interannual time scales.
Published: 2012
Full Text: View/download PDF

23. Publisher Correction: Critical Southern Ocean climate model biases traced to atmospheric model cloud errors

Author: Chunlei Liu, Simon A. Josey, Jeff Ridley, Claudio Sanchez, Michael Mayer, Kalli Furtado, Helene T. Hewitt, Livia Thorpe, David I. Berry, Alejandro Bodas-Salcedo, Patrick Hyder, Richard Wood, Jonathan M. Gregory, Keith D. Williams, Christopher D. Roberts, Andrew J. S. Meijers, Steven C. Hardiman, Paul R. Field, Dan Copsey, John M. Edwards, Thomas J. Bracegirdle, Richard P. Allan, Stephen E. Belcher, and Jane Mulcahy
Subjects: 010506 paleontology, Multidisciplinary, 010504 meteorology & atmospheric sciences, Meteorology, Computer science, business.industry, Science, General Physics and Astronomy, Oceanic climate, Cloud computing, General Chemistry, Atmospheric model, 01 natural sciences, General Biochemistry, Genetics and Molecular Biology, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, lcsh:Q, Paragraph, Hardware_CONTROLSTRUCTURESANDMICROPROGRAMMING, Citation, business, lcsh:Science, Sentence, 0105 earth and related environmental sciences
Abstract: 'In the original HTML version of this Article, ref.12 was incorrectly cited in the first sentence of the first paragraph of the Introduction. The correct citation is ref. 2. This has now been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.’
Published: 2018

24. Skillful Seasonal Prediction of the Southern Annular Mode and Antarctic Ozone

Author: Steven C. Hardiman, Adam A. Scaife, Lesley J. Gray, Craig MacLachlan, William J. M. Seviour, and Neal Butchart
Subjects: Atmospheric Science, Ozone, Mode (statistics), Forecast skill, Atmospheric sciences, Confidence interval, chemistry.chemical_compound, chemistry, North Atlantic oscillation, Polar vortex, Climatology, Environmental science, Hindcast, Predictability
Abstract: Using a set of seasonal hindcast simulations produced by the Met Office Global Seasonal Forecast System, version 5 (GloSea5), significant predictability of the southern annular mode (SAM) is demonstrated during the austral spring. The correlation of the September–November mean SAM with observed values is 0.64, which is statistically significant at the 95% confidence level [confidence interval: (0.18, 0.92)], and is similar to that found recently for the North Atlantic Oscillation in the same system. Significant skill is also found in the prediction of the strength of the Antarctic stratospheric polar vortex at 1 month average lead times. Because of the observed strong correlation between interannual variability in the strength of the Antarctic stratospheric circulation and ozone concentrations, it is possible to make skillful predictions of Antarctic column ozone amounts. By studying the variation of forecast skill with time and height, it is shown that skillful predictions of the SAM are significantly influenced by stratospheric anomalies that descend with time and are coupled with the troposphere. This effect allows skillful statistical forecasts of the October mean SAM to be produced based only on midstratosphere anomalies on 1 August. Together, these results both demonstrate a significant advance in the skill of seasonal forecasts of the Southern Hemisphere and highlight the importance of accurate modeling and observation of the stratosphere in producing long-range forecasts.
Published: 2014

25. Kelvin and Rossby-gravity wave packets in the lower stratosphere of some high-top CMIP5 models

Author: François Lott, Seiji Yukimoto, Jean-Philippe Duvel, Elisa Manzini, Marco Giorgetta, Steven C. Hardiman, Pauline Maury, Shingo Watanabe, Sébastien Denvil, N. Butchart, Chiara Cagnazzo, John Scinocca, Thomas Krismer, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), United Kingdom Met Office [Exeter], Istituto di Scienze dell'Atmosfera e del Clima (ISAC), Consiglio Nazionale delle Ricerche [Roma] (CNR), Max-Planck-Institut für Meteorologie (MPI-M), Max-Planck-Gesellschaft, Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Climate Research Department [MRI Tsukuba], Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA)-Japan Meteorological Agency (JMA), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), and National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR)
Subjects: Quasi-biennial Oscillation, Atmospheric Science, Rossby gravity waves, Wave packet, Atmospheric sciences, Physics::Geophysics, CMIP5 models, symbols.namesake, Kelvin waves, Earth and Planetary Sciences (miscellaneous), Gravity wave, Stratosphere, Physics::Atmospheric and Oceanic Physics, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Quasi-biennial oscillation, Physics, Coupled model intercomparison project, Atmospheric wave, Convectively coupled waves, Geophysics, Amplitude, 13. Climate action, Space and Planetary Science, symbols, Kelvin wave
Abstract: International audience; We analyze the stratospheric Kelvin and Rossby-gravity wave packets with periods of a few days in nine high-top (i.e., with stratosphere) models of the fifth Coupled Model Intercomparison Project (CMIP5). These models simulate realistic aspects of these waves and represent them better than the tropospheric convectively coupled waves analyzed in previous studies. There is nevertheless a large spread among the models, and those with a quasi-biennial oscillation (QBO) produce larger amplitude waves than the models without a QBO. For the Rossby-gravity waves this is explained by the fact that models without a QBO never have positive zonal mean zonal winds in the lower stratosphere, a situation that is favorable to the propagation of Rossby-gravity waves. For the Kelvin waves, larger amplitudes in the presence of a QBO is counter intuitive because Kelvin waves are expected to have larger amplitude when the zonal mean zonal wind is negative, and this is always satisfied in models without a QBO. We attribute the larger amplitude to the fact that models tuned to have a QBO require finer vertical resolution in the stratosphere. We also find that models with large precipitation variability tend to produce larger amplitude waves. However, the effect is not as pronounced as was found in previous studies. In fact, even models with weak precipitation variability still have quite realistic stratospheric waves, indicating either that (i) other sources can be significant or that (ii) the dynamical filtering mitigates the differences in the sources between models. © 2014. American Geophysical Union. All Rights Reserved.
Published: 2014

26. The Effect of Climate Change on the Variability of the Northern Hemisphere Stratospheric Polar Vortex

Author: Neal Butchart, Steven C. Hardiman, Andrew Charlton-Perez, Peter A. G. Watson, Scott Osprey, Daniel M. Mitchell, and Lesley J. Gray
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Northern Hemisphere, Climate change, Sudden stratospheric warming, 010502 geochemistry & geophysics, Atmospheric sciences, 01 natural sciences, Vortex, 13. Climate action, Potential vorticity, Polar vortex, Climatology, Environmental science, Climate model, Stratosphere, 0105 earth and related environmental sciences
Abstract: With extreme variability of the Arctic polar vortex being a key link for stratosphere–troposphere influences, its evolution into the twenty-first century is important for projections of changing surface climate in response to greenhouse gases. Variability of the stratospheric vortex is examined using a state-of-the-art climate model and a suite of specifically developed vortex diagnostics. The model has a fully coupled ocean and a fully resolved stratosphere. Analysis of the standard stratospheric zonal mean wind diagnostic shows no significant increase over the twenty-first century in the number of major sudden stratospheric warmings (SSWs) from its historical value of 0.7 events per decade, although the monthly distribution of SSWs does vary, with events becoming more evenly dispersed throughout the winter. However, further analyses using geometric-based vortex diagnostics show that the vortex mean state becomes weaker, and the vortex centroid is climatologically more equatorward by up to 2.5°, especially during early winter. The results using these diagnostics not only characterize the vortex structure and evolution but also emphasize the need for vortex-centric diagnostics over zonally averaged measures. Finally, vortex variability is subdivided into wave-1 (displaced) and -2 (split) components, and it is implied that vortex displacement events increase in frequency under climate change, whereas little change is observed in splitting events.
Published: 2012

27. Climate change projections and stratosphere-troposphere interaction

Author: Neal Butchart, Peter Braesicke, Steven C. Hardiman, Ulrich Cubasch, Martyn P. Chipperfield, Slimane Bekki, Adam A. Scaife, Martine Michou, Thomas Spangehl, Hideharu Akiyoshi, Eugene Rozanov, Ulrike Langematz, Andrew Gettelman, Theodore G. Shepherd, D. Fereday, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Freie Universität Berlin, National Institute for Environmental Studies (NIES), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), NCAS-Climate [Cambridge], Department of Chemistry [Cambridge, UK], University of Cambridge [UK] (CAM)-University of Cambridge [UK] (CAM), School of Earth and Environment [Leeds] (SEE), University of Leeds, National Center for Atmospheric Research [Boulder] (NCAR), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), University of Toronto, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Storm track, [SDE.MCG]Environmental Sciences/Global Changes, 0207 environmental engineering, Climate change, 02 engineering and technology, Atmospheric sciences, 01 natural sciences, Effects of global warming, Extratropical cyclone, Precipitation, 020701 environmental engineering, Stratosphere, 0105 earth and related environmental sciences, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Storm, Europe, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, Abrupt climate change, Environmental science
Abstract: International audience; Climate change is expected to increase winter rainfall and flooding in many extratropical regions as evaporation and precipitation rates increase, storms become more intense and storm tracks move polewards. Here, we show how changes in stratospheric circulation could play a significant role in future climate change in the extratropics through an additional shift in the tropospheric circulation. This shift in the circulation alters climate change in regional winter rainfall by an amount large enough to significantly alter regional climate change projections. The changes are consistent with changes in stratospheric winds inducing a change in the baroclinic eddy growth rate across the depth of the troposphere. A change in mean wind structure and an equatorward shift of the tropospheric storm tracks relative to models with poor stratospheric resolution allows coupling with surface climate. Using the Atlantic storm track as an example, we show how this can double the predicted increase in extreme winter rainfall over Western and Central Europe compared to other current climate projections.
Published: 2012

28. Improved predictability of the troposphere using stratospheric final warmings

Author: Peter Braesicke, Steven C. Hardiman, Slimane Bekki, Tiffany A. Shaw, Martine Michou, Neal Butchart, Andrew Charlton-Perez, Eugene Rozanov, Hideharu Akiyoshi, Rolando R. Garcia, Martin Dameris, Steven Pawson, A. J. G. Baumgaertner, Kiyotaka Shibata, Martyn P. Chipperfield, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Department of Meteorology [Reading], University of Reading (UOR), Department of Applied Physics and Applied Mathematics [New York] (APAM), Columbia University [New York], National Institute for Environmental Studies (NIES), Max Planck Institute for Chemistry (MPIC), Max-Planck-Gesellschaft, STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), NCAS-Climate [Cambridge], Department of Chemistry [Cambridge, UK], University of Cambridge [UK] (CAM)-University of Cambridge [UK] (CAM), School of Earth and Environment [Leeds] (SEE), University of Leeds, DLR Institut für Physik der Atmosphäre (IPA), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), National Center for Atmospheric Research [Boulder] (NCAR), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), NASA Goddard Space Flight Center (GSFC), Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), and Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Soil Science, chemistry-climate models, Aquatic Science, Sudden stratospheric warming, 010502 geochemistry & geophysics, Oceanography, Atmospheric sciences, 01 natural sciences, Troposphere, Geochemistry and Petrology, Polar vortex, Earth and Planetary Sciences (miscellaneous), stratospheric dynamics, Predictability, Stratosphere, Sea level, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Ecology, Northern Hemisphere, Paleontology, Forestry, Geophysics, 13. Climate action, Space and Planetary Science, Climatology, NAO, Climate model, Dynamik der Atmosphäre, Warming
Abstract: International audience; The final warming of the stratospheric polar vortex at the end of northern hemisphere winter is examined in ECMWF ERA-Interim reanalysis data and an ensemble of chemistry climate models, using 20 years of data from each. In some years the final warming is found to occur first in the mid-stratosphere, and in others to occur first in the upper stratosphere. The strength of the winter stratospheric polar vortex, refraction of planetary waves, and the altitudes at which the planetary waves break in the northern extratropics lead to this difference in the vertical profile of the final warming. Years in which the final warming occurs first in the mid-stratosphere show, on average, a more negative NAO pattern in April mean sea level pressure than years in which the warming occurs first in the upper stratosphere. Thus, in the northern hemisphere, additional predictive skill of tropospheric climate in April can be gained from a knowledge of the vertical profile of the stratospheric final warming.
Published: 2011

29. Using transport diagnostics to understand chemistry climate model ozone simulations

Author: Tetsu Nakamura, David Cugnet, Steven Pawson, Slimane Bekki, Jean-Francois Lamarque, Sandip Dhomse, Martyn P. Chipperfield, Marion Marchand, P. Braesicke, Susan E. Strahan, John Scinocca, Douglas E. Kinnison, Eva Mancini, Martine Michou, David A. Plummer, Olaf Morgenstern, Richard S. Stolarski, Giovanni Pitari, N. Butchart, Andrew Gettelman, Steven C. Hardiman, Stacey M. Frith, Hideharu Akiyoshi, John A. Pyle, Yousuke Yamashita, Dan Smale, D. Olivié, W. Tian, Kiyotaka Shibata, Anne R. Douglass, Theodore G. Shepherd, H. Teyssèdre, Universities Space Research Association (USRA), NASA Goddard Space Flight Center (GSFC), National Institute for Environmental Studies (NIES), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre for Atmospheric Science [Cambridge, UK], University of Cambridge [UK] (CAM), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], School of Earth and Environment [Leeds] (SEE), University of Leeds, Science Systems and Applications, Inc. [Lanham] (SSAI), National Center for Atmospheric Research [Boulder] (NCAR), University of L'Aquila [Italy] (UNIVAQ), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), Department of Geosciences [Oslo], Faculty of Mathematics and Natural Sciences [Oslo], University of Oslo (UiO)-University of Oslo (UiO), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Department of Physics [Toronto], University of Toronto, Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), and Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, Ozone, 010504 meteorology & atmospheric sciences, Atmospheric circulation, Soil Science, Aquatic Science, 010502 geochemistry & geophysics, Oceanography, Atmospheric sciences, 01 natural sciences, chemistry.chemical_compound, Geochemistry and Petrology, Stratospheric transport, Earth and Planetary Sciences (miscellaneous), Range (statistics), Stratosphere, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Ecology, Atmospheric models, Paleontology, Forestry, Ozone depletion, Geophysics, chemistry, 13. Climate action, Space and Planetary Science, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, Atmospheric chemistry, Climate model
Abstract: International audience; We use observations of N2O and mean age to identify realistic transport in models in order to explain their ozone predictions. The results are applied to 15 chemistry climate models (CCMs) participating in the 2010 World Meteorological Organization ozone assessment. Comparison of the observed and simulated N2O, mean age and their compact correlation identifies models with fast or slow circulations and reveals details of model ascent and tropical isolation. This process-oriented diagnostic is more useful than mean age alone because it identifies models with compensating transport deficiencies that produce fortuitous agreement with mean age. The diagnosed model transport behavior is related to a model's ability to produce realistic lower stratosphere (LS) O3 profiles. Models with the greatest tropical transport problems compare poorly with O3 observations. Models with the most realistic LS transport agree more closely with LS observations and each other. We incorporate the results of the chemistry evaluations in the Stratospheric Processes and their Role in Climate (SPARC) CCMVal Report to explain the range of CCM predictions for the return-to-1980 dates for global (60°S-60°N) and Antarctic column ozone. Antarctic O3 return dates are generally correlated with vortex Cly levels, and vortex Cly is generally correlated with the model's circulation, although model Cl chemistry and conservation problems also have a significant effect on return date. In both regions, models with good LS transport and chemistry produce a smaller range of predictions for the return-to-1980 ozone values. This study suggests that the current range of predicted return dates is unnecessarily broad due to identifiable model deficiencies.
Published: 2011

30. Evidence for changes in stratospheric transport and mixing over the past three decades based on multiple data sets and tropical leaky pipe analysis

Author: Peter Braesicke, Olaf Morgenstern, Dan Smale, Eugene Rozanov, Michaela I. Hegglin, Steven C. Hardiman, Eric A. Ray, Neal Butchart, David A. Plummer, Eva Mancini, Sean M. Davis, G. Pitari, Harald Boenisch, Karen H. Rosenlof, Kiyotaka Shibata, Feng Li, and Fred L. Moore
Subjects: Atmospheric Science, Soil Science, Perturbation (astronomy), Aquatic Science, Oceanography, Atmospheric sciences, Geochemistry and Petrology, Trend surface analysis, Earth and Planetary Sciences (miscellaneous), Stratosphere, Mixing (physics), Earth-Surface Processes, Water Science and Technology, geography, Vulcanian eruption, geography.geographical_feature_category, Ecology, Paleontology, Forestry, Sea surface temperature, Geophysics, Volcano, Space and Planetary Science, Climatology, Environmental science, Climate model
Abstract: [1] Variability in the strength of the stratospheric Lagrangian mean meridional or Brewer-Dobson circulation and horizontal mixing into the tropics over the past three decades are examined using observations of stratospheric mean age of air and ozone. We use a simple representation of the stratosphere, the tropical leaky pipe (TLP) model, guided by mean meridional circulation and horizontal mixing changes in several reanalyses data sets and chemistry climate model (CCM) simulations, to help elucidate reasons for the observed changes in stratospheric mean age and ozone. We find that the TLP model is able to accurately simulate multiyear variability in ozone following recent major volcanic eruptions and the early 2000s sea surface temperature changes, as well as the lasting impact on mean age of relatively short-term circulation perturbations. We also find that the best quantitative agreement with the observed mean age and ozone trends over the past three decades is found assuming a small strengthening of the mean circulation in the lower stratosphere, a moderate weakening of the mean circulation in the middle and upper stratosphere, and a moderate increase in the horizontal mixing into the tropics. The mean age trends are strongly sensitive to trends in the horizontal mixing into the tropics, and the uncertainty in the mixing trends causes uncertainty in the mean circulation trends. Comparisons of the mean circulation and mixing changes suggested by the measurements with those from a recent suite of CCM runs reveal significant differences that may have important implications on the accurate simulation of future stratospheric climate.
Published: 2010

31. Sensitivity of GCM tropical middle atmosphere variability and climate to ozone and parameterized gravity wave changes

Author: Steven C. Hardiman, David Jackson, N. Butchart, Lesley J. Gray, Scott Osprey, Tim Hinton, and Andrew C. Bushell
Subjects: Quasi-biennial oscillation, Atmospheric Science, Ozone, Ecology, Paleontology, Soil Science, Forestry, Aquatic Science, Oceanography, Atmospheric sciences, Atmosphere, chemistry.chemical_compound, Geophysics, chemistry, Space and Planetary Science, Geochemistry and Petrology, Climatology, Ozone layer, Earth and Planetary Sciences (miscellaneous), Upwelling, Climate model, Gravity wave, Stratosphere, Earth-Surface Processes, Water Science and Technology
Abstract: This paper describes the impact of changing the current imposed ozone climatology upon the tropical Quasi-Biennial Oscillation (QBO) in a high top climate configuration of the Met Office U.K. general circulation model. The aim is to help distinguish between QBO changes in chemistry climate models that result from temperature-ozone feedbacks and those that might be forced by differences in climatology between previously fixed and newly interactive ozone distributions. Different representations of zonal mean ozone climatology under present-day conditions are taken to represent the level of change expected between acceptable model realizations of the global ozone distribution and thus indicate whether more detailed investigation of such climatology issues might be required when assessing ozone feedbacks. Tropical stratospheric ozone concentrations are enhanced relative to the control climatology between 20-30 km, reduced from 30-40 km and enhanced above, impacting the model profile of clear-sky radiative heating, in particular warming the tropical stratosphere between 15-35 km. The outcome is consistent with a localized equilibrium response in the tropical stratosphere that generates increased upwelling between 100 and 4 hPa, sufficient to account for a 12 month increase of modeled mean QBO period. This response has implications for analysis of the tropical circulation in models with interactive ozone chemistry because it highlights the possibility that plausible changes in the ozone climatology could have a sizable impact upon the tropical upwelling and QBO period that ought to be distinguished from other dynamical responses such as ozone-temperature feedbacks. Copyright 2010 by the American Geophysical Union.
Published: 2010

32. Chemistry-climate model simulations of spring Antarctic ozone

Author: Steven C. Hardiman, Slimane Bekki, Theodore G. Shepherd, John Scinocca, Hamish Struthers, Greg Bodeker, N. Butchart, Ulrike Langematz, Patrick Jöckel, Eugene Rozanov, Martin Dameris, Olaf Morgenstern, E. Mancini, Sandip Dhomse, John Austin, Marion Marchand, Dan Smale, Jean-Francois Lamarque, Douglas E. Kinnison, Andrew Gettelman, Martyn P. Chipperfield, P. Braesicke, Ch. Brühl, Hideharu Akiyoshi, Tetsu Nakamura, David Cugnet, D. A. Plummer, J. E. Nielsen, Yousuke Yamashita, Giovanni Pitari, H. Teyssèdre, A. J. G. Baumgaertner, Kiyotaka Shibata, John A. Pyle, Martine Michou, Hella Garny, Anne Kubin, S. M. Frith, NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), University Corporation for Atmospheric Research (UCAR), Stockholm University, Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, National Institute for Environmental Studies (NIES), Max Planck Institute for Chemistry (MPIC), Max-Planck-Gesellschaft, STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Bodeker Scientific, NCAS-Climate [Cambridge], Department of Chemistry [Cambridge, UK], University of Cambridge [UK] (CAM)-University of Cambridge [UK] (CAM), United Kingdom Met Office [Exeter], School of Earth and Environment [Leeds] (SEE), University of Leeds, DLR Institut für Physik der Atmosphäre (IPA), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), NASA Goddard Space Flight Center (GSFC), Science Systems and Applications, Inc. [Lanham] (SSAI), National Center for Atmospheric Research [Boulder] (NCAR), Institut für Meteorologie [Berlin], Freie Universität Berlin, University of L'Aquila [Italy] (UNIVAQ), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Institute for Atmospheric and Climate Science [Zürich] (IAC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Department of Physics [Toronto], University of Toronto, Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, Ozone, 010504 meteorology & atmospheric sciences, Mass deficit, Soil Science, Climate change, 010501 environmental sciences, Aquatic Science, Oceanography, Atmospheric sciences, 01 natural sciences, chemistry.chemical_compound, Geochemistry and Petrology, Polar vortex, Montreal Protocol, Earth and Planetary Sciences (miscellaneous), 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Ecology, ozone hole, Antarctic ozone hole, Paleontology, Forestry, Ozone depletion, Vortex, Geophysics, chemistry, 13. Climate action, Space and Planetary Science, chemistry-climate feedback, Climatology, Greenhouse gas, stratosphere, Environmental science, Dynamik der Atmosphäre
Abstract: International audience; Coupled chemistry-climate model simulations covering the recent past and continuing throughout the 21st century have been completed with a range of different models. Common forcings are used for the halogen amounts and greenhouse gas concentrations, as expected under the Montreal Protocol (with amendments) and Intergovernmental Panel on Climate Change A1b Scenario. The simulations of the Antarctic ozone hole are compared using commonly used diagnostics: the minimum ozone, the maximum area of ozone below 220 DU, and the ozone mass deficit below 220 DU. Despite the fact that the processes responsible for ozone depletion are reasonably well understood, a wide range of results is obtained. Comparisons with observations indicate that one of the reasons for the model underprediction in ozone hole area is the tendency for models to underpredict, by up to 35%, the area of low temperatures responsible for polar stratospheric cloud formation. Models also typically have species gradients that are too weak at the edge of the polar vortex, suggesting that there is too much mixing of air across the vortex edge. Other models show a high bias in total column ozone which restricts the size of the ozone hole (defined by a 220 DU threshold). The results of those models which agree best with observations are examined in more detail. For several models the ozone hole does not disappear this century but a small ozone hole of up to three million square kilometers continues to occur in most springs even after 2070.
Published: 2010

33. Multimodel assessment of the upper troposphere and lower stratosphere: Extratropics

Author: Dan Smale, Jean-Francois Lamarque, D. Olivié, Sandip Dhomse, Gloria L. Manney, Ch. Brühl, Tetsu Nakamura, John Scinocca, Veronika Eyring, Gabriele Stiller, A. J. G. Baumgaertner, Simone Tilmes, Steven C. Hardiman, Darryn W. Waugh, D. A. Plummer, Kiyotaka Shibata, Yousuke Yamashita, H. Teyssèdre, Hideharu Akiyoshi, R. Krichevsky, Giovanni Pitari, Slimane Bekki, Peter Hoor, Laura L. Pan, N. Butchart, Martin Dameris, Eugene Rozanov, Theodore G. Shepherd, Andrew Gettelman, John Austin, Olaf Morgenstern, Hella Garny, Seok-Woo Son, Steven Pawson, Juan A. Añel, Martine Michou, Kaley A. Walker, Eva Mancini, W. Tian, Martyn P. Chipperfield, P. Braesicke, John A. Pyle, Douglas E. Kinnison, Patrick Jöckel, Michaela I. Hegglin, S. Frith, Department of Physics [Toronto], University of Toronto, National Center for Atmospheric Research [Boulder] (NCAR), Max Planck Institute for Chemistry (MPIC), Max-Planck-Gesellschaft, Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), New Mexico Institute of Mining and Technology [New Mexico Tech] (NMT), Department of Atmospheric and Oceanic Sciences [Montréal], McGill University = Université McGill [Montréal, Canada], Institute for Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology (KIT), Department of Chemistry [Waterloo], University of Waterloo [Waterloo], DLR Institut für Physik der Atmosphäre (IPA), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), Johns Hopkins University (JHU), National Institute for Environmental Studies (NIES), Environmental Physics Laboratory (EPhysLab), Universidade de Vigo, NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), NCAS-Climate [Cambridge], Department of Chemistry [Cambridge, UK], University of Cambridge [UK] (CAM)-University of Cambridge [UK] (CAM), United Kingdom Met Office [Exeter], School of Earth and Environment [Leeds] (SEE), University of Leeds, NASA Goddard Space Flight Center (GSFC), University of L'Aquila [Italy] (UNIVAQ), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, University of Cambridge [UK] (CAM), Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Institute for Atmospheric and Climate Science [Zürich] (IAC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), and Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, TTL, Soil Science, Zonal and meridional, chemistry-climate models, Aquatic Science, 010502 geochemistry & geophysics, Oceanography, Atmospheric sciences, 01 natural sciences, Upper troposphere/lower stratosphere, Troposphere, Geochemistry and Petrology, Earth and Planetary Sciences (miscellaneous), Extratropical cyclone, medicine, Stratosphere, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Ecology, Paleontology, Forestry, Inversion (meteorology), Seasonality, medicine.disease, Chemistry climate model, Geophysics, 13. Climate action, Space and Planetary Science, Climatology, Environmental science, Dynamik der Atmosphäre, Tropopause, CCMVal, Water vapor, Model-measurement comparison
Abstract: A multimodel assessment of the performance of chemistry-climate models (CCMs) in the extratropical upper troposphere/lower stratosphere (UTLS) is conducted for the first time. Process-oriented diagnostics are used to validate dynamical and transport characteristics of 18 CCMs using meteorological analyses and aircraft and satellite observations. The main dynamical and chemical climatological characteristics of the extratropical UTLS are generally well represented by the models, despite the limited horizontal and vertical resolution. The seasonal cycle of lowermost stratospheric mass is realistic, however with a wide spread in its mean value. A tropopause inversion layer is present in most models, although the maximum in static stability is located too high above the tropopause and is somewhat too weak, as expected from limited model resolution. Similar comments apply to the extratropical tropopause transition layer. The seasonality in lower stratospheric chemical tracers is consistent with the seasonality in the Brewer-Dobson circulation. Both vertical and meridional tracer gradients are of similar strength to those found in observations. Models that perform less well tend to use a semi-Lagrangian transport scheme and/or have a very low resolution. Two models, and the multimodel mean, score consistently well on all diagnostics, while seven other models score well on all diagnostics except the seasonal cycle of water vapor. Only four of the models are consistently below average. The lack of tropospheric chemistry in most models limits their evaluation in the upper troposphere. Finally, the UTLS is relatively sparsely sampled by observations, limiting our ability to quantitatively evaluate many aspects of model performance. Copyright © 2010 by the American Geophysical Union.
Published: 2010

34. Stratosphere-troposphere coupling and annular mode variability in chemistry-climate models

Author: Martyn P. Chipperfield, Dan Smale, Steven C. Hardiman, John Scinocca, Slimane Bekki, Eugene Rozanov, Peter Braesicke, Neal Butchart, Stacey M. Frith, D. A. Plummer, J. Eric Nielsen, Edwin P. Gerber, Sandip Dhomse, Steven Pawson, John Austin, Rolando R. Garcia, Thomas Peter, Marion Marchand, Andrew Gettelman, Hella Garny, Hideharu Akiyoshi, Alexey Yu. Karpechko, John A. Pyle, Theodore G. Shepherd, Martin Dameris, Mark P. Baldwin, Olaf Morgenstern, Center for Atmosphere Ocean Science [NYU] (CAOS), Courant Institute of Mathematical Sciences [New York] (CIMS), New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU)-New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU), NorthWest Research Associates (NWRA), National Institute for Environmental Studies (NIES), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), University Corporation for Atmospheric Research (UCAR), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), NCAS-Climate [Cambridge], Department of Chemistry [Cambridge, UK], University of Cambridge [UK] (CAM)-University of Cambridge [UK] (CAM), United Kingdom Met Office [Exeter], School of Earth and Environment [Leeds] (SEE), University of Leeds, DLR Institut für Physik der Atmosphäre (IPA), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), NASA Goddard Space Flight Center (GSFC), National Center for Atmospheric Research [Boulder] (NCAR), Finnish Meteorological Institute (FMI), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), Institute for Atmospheric and Climate Science [Zürich] (IAC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Centre for Atmospheric Science [Cambridge, UK], University of Cambridge [UK] (CAM), Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Department of Physics [Toronto], University of Toronto, and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Annular modes, Soil Science, Aquatic Science, 010502 geochemistry & geophysics, Oceanography, Atmospheric sciences, 01 natural sciences, Troposphere, Geochemistry and Petrology, Stratosphere-troposphere coupling, Earth and Planetary Sciences (miscellaneous), Chemistry-climate models, Southern Hemisphere, Stratosphere, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Ecology, Mode (statistics), Paleontology, Forestry, Secular variation, numerical modeling, climate change, Geophysics, troposphere, 13. Climate action, Space and Planetary Science, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, Middle latitudes, stratosphere, Polar, Dynamik der Atmosphäre, Climate model
Abstract: International audience; The internal variability and coupling between the stratosphere and troposphere in CCMVal-2 chemistry-climate models are evaluated through analysis of the annular mode patterns of variability. Computation of the annular modes in long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The spatial and temporal structure of the models' annular modes is then compared with that of reanalyses. As a whole, the models capture the key features of observed intraseasonal variability, including the sharp vertical gradients in structure between stratosphere and troposphere, the asymmetries in the seasonal cycle between the Northern and Southern hemispheres, and the coupling between the polar stratospheric vortices and tropospheric midlatitude jets. It is also found that the annular mode variability changes little in time throughout simulations of the 21st century. There are, however, both common biases and significant differences in performance in the models. In the troposphere, the annular mode in models is generally too persistent, particularly in the Southern Hemisphere summer, a bias similar to that found in CMIP3 coupled climate models. In the stratosphere, the periods of peak variance and coupling with the troposphere are delayed by about a month in both hemispheres. The relationship between increased variability of the stratosphere and increased persistence in the troposphere suggests that some tropospheric biases may be related to stratospheric biases and that a well-simulated stratosphere can improve simulation of tropospheric intraseasonal variability.
Published: 2010

35. The decline and recovery of total column ozone using a multimodel time series analysis

Author: Martin Dameris, Veronika Eyring, Martine Michou, Giovanni Pitari, H. Teyssèdre, Darryn W. Waugh, Steven Pawson, Hideharu Akiyoshi, John Scinocca, Marion Marchand, Olaf Morgenstern, S. Frith, Tetsu Nakamura, Steven C. Hardiman, R. J. Wilson, David Cugnet, Douglas E. Kinnison, Andrew Gettelman, David A. Plummer, Slimane Bekki, Eva Mancini, Jean-Francois Lamarque, Luke D. Oman, Kiyotaka Shibata, Sandip Dhomse, Rolando R. Garcia, Theodore G. Shepherd, John A. Pyle, Hella Garny, N. Butchart, Eugene Rozanov, John Austin, Yousuke Yamashita, Martyn P. Chipperfield, P. Braesicke, NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), University Corporation for Atmospheric Research (UCAR), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Morton K. Blaustein Department of Earth and Planetary Sciences [Baltimore], Johns Hopkins University (JHU), National Institute for Environmental Studies (NIES), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), NCAS-Climate [Cambridge], Department of Chemistry [Cambridge, UK], University of Cambridge [UK] (CAM)-University of Cambridge [UK] (CAM), United Kingdom Met Office [Exeter], School of Earth and Environment [Leeds] (SEE), University of Leeds, DLR Institut für Physik der Atmosphäre (IPA), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), NASA Goddard Space Flight Center (GSFC), Science Systems and Applications, Inc. [Lanham] (SSAI), National Center for Atmospheric Research [Boulder] (NCAR), University of L'Aquila [Italy] (UNIVAQ), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Institute for Atmospheric and Climate Science [Zürich] (IAC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Department of Physics [Toronto], University of Toronto, Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, Ozone, 010504 meteorology & atmospheric sciences, Ozone recovery, Soil Science, Ozone decline, chemistry-climate models, Aquatic Science, 010502 geochemistry & geophysics, Oceanography, Atmospheric sciences, 01 natural sciences, Troposphere, chemistry.chemical_compound, Geochemistry and Petrology, Earth and Planetary Sciences (miscellaneous), Stratosphere, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Chlorofluorocarbon, Ecology, Northern Hemisphere, Paleontology, Forestry, Geophysics, chemistry, 13. Climate action, Space and Planetary Science, Climatology, Middle latitudes, Greenhouse gas, stratosphere, Climate model
Abstract: International audience; Simulations of 15 coupled chemistry climate models, for the period 1960–2100, are presented. The models include a detailed stratosphere, as well as including a realistic representation of the tropospheric climate. The simulations assume a consistent set of changing greenhouse gas concentrations, as well as temporally varying chlorofluorocarbon concentrations in accordance with observations for the past and expectations for the future. The ozone results are analyzed using a nonparametric additive statistical model. Comparisons are made with observations for the recent past, and the recovery of ozone, indicated by a return to 1960 and 1980 values, is investigated as a function of latitude. Although chlorine amounts are simulated to return to 1980 values by about 2050, with only weak latitudinal variations, column ozone amounts recover at different rates due to the influence of greenhouse gas changes. In the tropics, simulated peak ozone amounts occur by about 2050 and thereafter total ozone column declines. Consequently, simulated ozone does not recover to values which existed prior to the early 1980s. The results also show a distinct hemispheric asymmetry, with recovery to 1980 values in the Northern Hemisphere extratropics ahead of the chlorine return by about 20 years. In the Southern Hemisphere midlatitudes, ozone is simulated to return to 1980 levels only 10 years ahead of chlorine. In the Antarctic, annually averaged ozone recovers at about the same rate as chlorine in high latitudes and hence does not return to 1960s values until the last decade of the simulations.
Published: 2010

36. Impact of stratospheric ozone on Southern Hemisphere circulation change: A multimodel assessment

Author: Hella Garny, Martyn P. Chipperfield, Nathan P. Gillett, Jean-Francois Lamarque, Patrick Jöckel, P. Braesicke, Hideharu Akiyoshi, Theodore G. Shepherd, Judith Perlwitz, John A. Pyle, Marion Marchand, A. J. G. Baumgaertner, Yousuke Yamashita, Ch. Brühl, Martin Dameris, Olaf Morgenstern, E. Mancini, Kiyotaka Shibata, D. A. Plummer, S. M. Frith, Veronika Eyring, Tetsu Nakamura, Kyong-Hwan Seo, Rolando R. Garcia, W. Tian, Darryn W. Waugh, Sandip Dhomse, Seok-Woo Son, David Cugnet, Edwin P. Gerber, H. Teyssèdre, Martine Michou, N. Butchart, Eugene Rozanov, John Austin, Lorenzo M. Polvani, Giovanni Pitari, Dan Smale, John Scinocca, Steven C. Hardiman, Slimane Bekki, Department of Atmospheric and Oceanic Sciences [Montréal], McGill University = Université McGill [Montréal, Canada], Center for Atmosphere Ocean Science [NYU] (CAOS), Courant Institute of Mathematical Sciences [New York] (CIMS), New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU)-New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU), NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado [Boulder]-National Oceanic and Atmospheric Administration (NOAA), Department of Applied Physics and Applied Mathematics [New York], Columbia University [New York], Department of Earth and Environmental Sciences [New York], Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Department of Atmospheric Sciences [Busan], Pusan National University, DLR Institut für Physik der Atmosphäre (IPA), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), Department of Physics [Toronto], University of Toronto, Johns Hopkins University (JHU), National Institute for Environmental Studies (NIES), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), Max-Planck-Institut für Chemie (MPIC), Max-Planck-Gesellschaft, STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), NCAS-Climate [Cambridge], Department of Chemistry [Cambridge, UK], University of Cambridge [UK] (CAM)-University of Cambridge [UK] (CAM), United Kingdom Met Office [Exeter], School of Earth and Environment [Leeds] (SEE), University of Leeds, NASA Goddard Space Flight Center (GSFC), National Center for Atmospheric Research [Boulder] (NCAR), University of L'Aquila [Italy] (UNIVAQ), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Institute for Atmospheric and Climate Science [Zürich] (IAC), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Soil Science, Climate change, Context (language use), Forcing (mathematics), Aquatic Science, 010502 geochemistry & geophysics, Oceanography, Atmospheric sciences, 01 natural sciences, Ozone hole, CCMVal-2, Geochemistry and Petrology, Ozone layer, Earth and Planetary Sciences (miscellaneous), Hadley cell, Southern Hemisphere, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Ecology, Paleontology, Forestry, Ozone depletion, Geophysics, 13. Climate action, Space and Planetary Science, Climatology, Middle latitudes, Environmental science, Southern Hemisphere climate change
Abstract: International audience; The impact of stratospheric ozone on the tropospheric general circulation of theSouthern Hemisphere (SH) is examined with a set of chemistry‐climate models participatingin the Stratospheric Processes and their Role in Climate (SPARC)/Chemistry‐ClimateModel Validation project phase 2 (CCMVal‐2). Model integrations of both the past andfuture climates reveal the crucial role of stratospheric ozone in driving SH circulationchange: stronger ozone depletion in late spring generally leads to greater polewarddisplacement and intensification of the tropospheric midlatitude jet, and greater expansion ofthe SH Hadley cell in the summer. These circulation changes are systematic as polewarddisplacement of the jet is typically accompanied by intensification of the jet and expansion ofthe Hadley cell. Overall results are compared with coupled models participating in theIntergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4), andpossible mechanisms are discussed. While the tropospheric circulation response appearsquasi‐linearly related to stratospheric ozone changes, the quantitative response to a givenforcing varies considerably from one model to another. This scatter partly results fromdifferences in model climatology. It is shown that poleward intensification of the westerly jetis generally stronger in models whose climatological jet is biased toward lower latitudes.This result is discussed in the context of quasi‐geostrophic zonal mean dynamics.
Published: 2010

37. Multimodel assessment of the upper troposphere and lower stratosphere : Tropics and global trends

Author: W. Tian, Juan A. Añel, John Scinocca, Stefanie Kremser, Steven Pawson, Patrick Jöckel, Giovanni Pitari, Kiyotaka Shibata, Slimane Bekki, Masatomo Fujiwara, Jung-Hyun Kim, Ch. Brühl, Jean-Francois Lamarque, Olaf Morgenstern, Martine Michou, Dan Smale, Andrew Gettelman, H. Teyssèdre, Thomas Birner, Steven C. Hardiman, John A. Pyle, Michaela I. Hegglin, Eva Mancini, Sandip Dhomse, Theodore G. Shepherd, P. Braesike, Martin Dameris, Seok-Woo Son, Martyn P. Chipperfield, Markus Rex, Marion Marchand, Douglas E. Kinnison, Hideharu Akiyoshi, D. A. Plummer, N. Butchart, Eugene Rozanov, John Austin, Hella Garny, National Center for Atmospheric Research [Boulder] (NCAR), Department of Physics [Toronto], University of Toronto, Department of Atmospheric and Oceanic Sciences [Montréal], McGill University = Université McGill [Montréal, Canada], Hokkaido University [Sapporo, Japan], Department of Atmospheric Science [Fort Collins], Colorado State University [Fort Collins] (CSU), Freie Universität Berlin, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Environmental Physics Laboratory (EPhysLab), Universidade de Vigo, National Institute for Environmental Studies (NIES), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Department of Chemistry [Cambridge, UK], University of Cambridge [UK] (CAM), Max-Planck-Institut für Chemie (MPIC), Max-Planck-Gesellschaft, United Kingdom Met Office [Exeter], School of Earth and Environment [Leeds] (SEE), University of Leeds, DLR Institut für Physik der Atmosphäre (IPA), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), Institute for Climate and Atmospheric Science [Leeds] (ICAS), University of Leeds-University of Leeds, University of L'Aquila [Italy] (UNIVAQ), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), NASA Goddard Space Flight Center (GSFC), Environment and Climate Change Canada, Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Canadian Centre for Climate Modelling and Analysis (CCCma), Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Tropopause, Climate, TTL, 0207 environmental engineering, Soil Science, chemistry-climate models, 02 engineering and technology, Aquatic Science, Oceanography, Atmospheric sciences, 01 natural sciences, Troposphere, Geochemistry and Petrology, Earth and Planetary Sciences (miscellaneous), Extratropical cyclone, 020701 environmental engineering, Stratosphere, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Ecology, Cloud fraction, Paleontology, Humidity, Forestry, Chemistry, Geophysics, 13. Climate action, Space and Planetary Science, Climatology, Dynamik der Atmosphäre, Climate model, CCMVal, Water vapor
Abstract: International audience; The performance of 18 coupled Chemistry Climate Models (CCMs) in the Tropical Tropopause Layer (TTL) is evaluated using qualitative and quantitative diagnostics. Trends in tropopause quantities in the tropics and the extratropical Upper Troposphere and Lower Stratosphere (UTLS) are analyzed. A quantitative grading methodology for evaluating CCMs is extended to include variability and used to develop four different grades for tropical tropopause temperature and pressure, water vapor and ozone. Four of the 18 models and the multi‐model mean meet quantitative and qualitative standards for reproducing key processes in the TTL. Several diagnostics are performed on a subset of the models analyzing the Tropopause Inversion Layer (TIL), Lagrangian cold point and TTL transit time. Historical decreases in tropical tropopause pressure and decreases in water vapor are simulated, lending confidence to future projections. The models simulate continued decreases in tropopause pressure in the 21st century, along with ∼1K increases per century in cold point tropopause temperature and 0.5–1 ppmv per century increases in water vapor above the tropical tropopause. TTL water vapor increases below the cold point. In two models, these trends are associated with 35% increases in TTL cloud fraction. These changes indicate significant perturbations to TTL processes, specifically to deep convective heating and humidity transport. Ozone in the extratropical lowermost stratosphere has significant and hemispheric asymmetric trends. O3 is projected to increase by nearly 30% due to ozone recovery in the Southern Hemisphere (SH) and due to enhancements in the stratospheric circulation. These UTLS ozone trends may have significant effects in the TTL and the troposphere.
Published: 2010

38. The Met Office HadGEM3-ES chemistry–climate model: evaluation of stratospheric dynamics and its impact on ozone

Author: Fiona M. O'Connor, S. T. Rumbold, Neal Butchart, and Steven C. Hardiman
Subjects: Ozone, 010504 meteorology & atmospheric sciences, lcsh:QE1-996.5, 0207 environmental engineering, Northern Hemisphere, Flux, 02 engineering and technology, 010502 geochemistry & geophysics, Atmospheric sciences, 01 natural sciences, Ozone depletion, lcsh:Geology, Troposphere, chemistry.chemical_compound, chemistry, 13. Climate action, Climatology, Ozone layer, 020701 environmental engineering, Stratosphere, Water vapor, 0105 earth and related environmental sciences
Abstract: Free-running and nudged versions of a Met Office chemistry–climate model are evaluated and used to investigate the impact of dynamics versus transport and chemistry within the model on the simulated evolution of stratospheric ozone. Metrics of the dynamical processes relevant for simulating stratospheric ozone are calculated, and the free-running model is found to outperform the previous model version in 10 of the 14 metrics. In particular, large biases in stratospheric transport and tropical tropopause temperature, which existed in the previous model version, are substantially reduced, making the current model more suitable for the simulation of stratospheric ozone. The spatial structure of the ozone hole, the area of polar stratospheric clouds, and the increased ozone concentrations in the Northern Hemisphere winter stratosphere following sudden stratospheric warmings, were all found to be sensitive to the accuracy of the dynamics and were better simulated in the nudged model than in the free-running model. Whilst nudging can, in general, provide a useful tool for removing the influence of dynamical biases from the evolution of chemical fields, this study shows that issues can remain in the climatology of nudged models. Significant biases in stratospheric vertical velocities, age of air, water vapour, and total column ozone still exist in the Met Office nudged model. Further, these can lead to biases in the downward flux of ozone into the troposphere.
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39. Tropospheric jet response to Antarctic ozone depletion: An update with Chemistry-Climate Model Initiative (CCMI) models.

Author: Seok-Woo Son, Bo-Reum Han, Chaim I Garfinkel, Seo-Yeon Kim, Rokjin Park, N Luke Abraham, Hideharu Akiyoshi, Alexander T Archibald, N Butchart, Martyn P Chipperfield, Martin Dameris, Makoto Deushi, Sandip S Dhomse, Steven C Hardiman, Patrick Jöckel, Douglas Kinnison, Martine Michou, Olaf Morgenstern, Fiona M O’Connor, and Luke D Oman
Published: 2018
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40. The asymmetric response of Yangtze river basin summer rainfall to El Niño/La Niña.

Author: Steven C Hardiman, Nick J Dunstone, Adam A Scaife, Philip E Bett, Chaofan Li, Bo Lu, Hong-Li Ren, Doug M Smith, and Claudia C Stephan
Published: 2018
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41. Tropospheric jet response to Antarctic ozone depletion: An update with Chemistry-Climate Model Initiative (CCMI) models

Author: Steven C. Hardiman, N. Luke Abraham, Yousuke Yamashita, Martine Michou, Olaf Morgenstern, Seok-Woo Son, Guang Zeng, Chaim I. Garfinkel, Patrick Jöckel, Kane A. Stone, Andrea Stenke, Sandip Dhomse, Fiona M. O'Connor, Luke D. Oman, Martyn P. Chipperfield, Laura E. Revell, Bo-Reum Han, N. Butchart, Martin Dameris, Eugene Rozanov, Douglas E. Kinnison, David A. Plummer, Rokjin J. Park, Hideharu Akiyoshi, Andrea Pozzer, Makoto Deushi, Simone Tilmes, Seo-Yeon Kim, and Alexander T. Archibald
Subjects: 010504 meteorology & atmospheric sciences, Southern Hemisphere circulation, 010502 geochemistry & geophysics, Atmospheric sciences, 01 natural sciences, Chemistry climate model, Troposphere, MESSy, Ozone layer, Erdsystem-Modellierung, 14. Life underwater, Hadley cell, Southern Hemisphere, 0105 earth and related environmental sciences, General Environmental Science, Coupled model intercomparison project, Jet (fluid), EMAC, Renewable Energy, Sustainability and the Environment, Public Health, Environmental and Occupational Health, westerly jet, Ozone depletion, Antarctic ozone depletion, 13. Climate action, CCMI, ozone depletion, Southern Hemisphere jet trends, chemistry-climate model initiative (CCMI), Environmental science, Chemistry-Climate Model Initiative
Abstract: The Southern Hemisphere (SH) zonal-mean circulation change in response to Antarctic ozone depletion is re-visited by examining a set of the latest model simulations archived for the Chemistry-Climate Model Initiative (CCMI) project. All models reasonably well reproduce Antarctic ozone depletion in the late 20th century. The related SH-summer circulation changes, such as a poleward intensification of westerly jet and a poleward expansion of the Hadley cell, are also well captured. All experiments exhibit quantitatively the same multi-model mean trend, irrespective of whether the ocean is coupled or prescribed. Results are also quantitatively similar to those derived from the Coupled Model Intercomparison Project phase 5 (CMIP5) high-top model simulations in which the stratospheric ozone is mostly prescribed with monthly- and zonally-averaged values. These results suggest that the ozone-hole-induced SH-summer circulation changes are robust across the models irrespective of the specific chemistry-atmosphere-ocean coupling. ISSN:1748-9326 ISSN:1748-9318
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42. Eurasian mid-latitude jet stream bridges an Atlantic to Asia summer teleconnection in heat extremes

Author: Yu Nie, Hong-Li Ren, Jinqing Zuo, Jie Wu, Adam A Scaife, Nick J Dunstone, and Steven C Hardiman
Subjects: heat extremes, teleconnection, Rossby wave packet, jet stream, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Science, Physics, QC1-999
Abstract: Northern Europe and Northeast Asia, which are climatologically mild and temperate in early summer, both witnessed record-breaking heat extremes in June 2023. With a focus on the subseasonal time scale, this study highlights a teleconnected relationship in historical early-summer heat extremes between Northern Europe and Northeast Asia. By diagnosing the thermal budget and wave activity flux, we show that over one third of historical Northeast Asian heat extremes are initialized by Eurasian mid-latitude Rossby wave packets. The wave packets manifest as strong anticyclonic anomalies over subpolar North Atlantic, cyclonic anomalies over Ural region and anticyclonic anomalies over Northeast Asia, which directly cause coexisting heat extremes in Northern Europe and Northeast Asia. Such wave packets are strongly modulated by the Eurasian jet stream. By carrying out numerical experiments, we further explain why the wave packet is significant in early summer. We find that the quasi-stationary response of the Eurasian midlatitude Rossby wave packets to a specified heating in subpolar North Atlantic is dependent on the background jet structure. In early summer, the double-jet state over Eurasia favors Rossby wave propagation. This is of great practical importance for accurate prediction of Northeast Asian heat extreme amplitude and location.
Published: 2024
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