Publications by Philip Stier


An AeroCom/AeroSat study: Intercomparison of Satellite AODDatasets for Aerosol Model Evaluation

Atmospheric Chemistry and Physics Discussions European Geosciences Union (2020)

N Schutgens, A Sayer, A Heckel, C Hsu, H Jethva, G de Leeuw, P Leonard, R Levy, A Lipponen, A Lyapustin, P North, T Popp, C Poulson, V Sawyer, L Sogacheva, G Thomas, O Torres, Y Wang, S Kinne, M Schulz, P Stier


Global response of parameterised convective cloud fields to anthropogenic aerosol forcing

Atmospheric Chemistry and Physics Copernicus GmbH 20 (2020) 4445-4460

Z Kipling, L Labbouz, P Stier

<jats:p>Abstract. The interactions between aerosols and convective clouds represent some of the greatest uncertainties in the climate impact of aerosols in the atmosphere. A wide variety of mechanisms have been proposed by which aerosols may invigorate, suppress or change the properties of individual convective clouds, some of which can be reproduced in high-resolution limited-area models. However, there may also be mesoscale, regional or global adjustments which modulate or dampen such impacts which cannot be captured in the limited domain of such models. The Convective Cloud Field Model (CCFM) provides a mechanism to simulate a population of convective clouds, complete with microphysics and interactions between clouds, within each grid column at resolutions used for global climate modelling, so that a representation of the microphysical aerosol response within each parameterised cloud type is possible. Using CCFM within the global aerosol–climate model ECHAM–HAM, we demonstrate how the parameterised cloud field responds to the present-day anthropogenic aerosol perturbation in different regions. In particular, we show that in regions with strongly forced deep convection and/or significant aerosol effects via large-scale processes, the changes in the convective cloud field due to microphysical effects are rather small; however in a more weakly forced regime such as the Caribbean, where large-scale aerosol effects are small, a signature of convective invigoration does become apparent. </jats:p>


Bounding global aerosol radiative forcing of climate change

Reviews of Geophysics American Geophysical Union 58 (2019) e2019RG000660

N Bellouin, J Quaas, S Kinne, P Stier, D Watson-Parris, O Boucher, KS Carslaw, M Christensen, A-L Daniau, JL Dufresne, G Feingold, S Fiedler, P Forster, A Gettelman, JM Haywood, U Lohmann, F Malavelle, T Mauritsen, DT McCoy, G Myhre, J Muelmenstaedt, A Possner, M Rugenstein, O Sourdeval, V Toll

Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth's radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This review provides a new range of aerosol radiative forcing over the industrial era based on multiple, traceable, and arguable lines of evidence, including modeling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes constrain the forcing from aerosol‐radiation interactions. A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol‐driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction is less clear, and the influence on mixed‐phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to a 68% confidence interval for the total aerosol effective radiative forcing of ‐1.6 to ‐0.6 W m−2, or ‐2.0 to ‐0.4 W m−2 with a 90% likelihood. Those intervals are of similar width to the last Intergovernmental Panel on Climate Change assessment but shifted toward more negative values. The uncertainty will narrow in the future by continuing to critically combine multiple lines of evidence, especially those addressing industrial‐era changes in aerosol sources and aerosol effects on liquid cloud amount and on ice clouds.


Constraining the Twomey effect from satellite observations: Issues and perspectives

Atmospheric Chemistry and Physics Discussions European Geosciences Union (2020)

J Quaas, A Antti, B Cairns, M Christensen, H Deneke, A Ekman, G Feingold, A Fridlind, E Gryspeerdt, O Hasekamp, Z Li, A Lipponen, P-L Ma, J Muelmenstaedt, A Nenes, J Penner, D Rosenfeld, R Schroedner, K Sinclair, O Sourdeval, P Stier, M Tesche, B van Dieedenhoven, M Wendisch


Atmospheric energy budget response to idealized aerosol perturbation in tropical cloud systems

Atmospheric Chemistry and Physics Copernicus GmbH 20 (2020) 4523-4544

G Dagan, P Stier, M Christensen, G Cioni, D Klocke, A Seifert

<jats:p>Abstract. The atmospheric energy budget is analysed in numerical simulations of tropical cloud systems to better understand the physical processes behind aerosol effects on the atmospheric energy budget. The simulations include both shallow convective clouds and deep convective tropical clouds over the Atlantic Ocean. Two different sets of simulations, at different dates (10–12 and 16–18 August 2016), are simulated with different dominant cloud modes (shallow or deep). For each case, the cloud droplet number concentration (CDNC) is varied as a proxy for changes in aerosol concentrations without considering the temporal evolution of the aerosol concentration (for example due to wet scavenging, which may be more important under deep convective conditions). It is shown that the total column atmospheric radiative cooling is substantially reduced with CDNC in the deep-cloud-dominated case (by ∼10.0 W m−2), while a much smaller reduction (∼1.6 W m−2) is shown in the shallow-cloud-dominated case. This trend is caused by an increase in the ice and water vapour content at the upper troposphere that leads to a reduced outgoing longwave radiation, an effect which is stronger under deep-cloud-dominated conditions. A decrease in sensible heat flux (driven by an increase in the near-surface air temperature) reduces the warming by ∼1.4 W m−2 in both cases. It is also shown that the cloud fraction response behaves in opposite ways to an increase in CDNC, showing an increase in the deep-cloud-dominated case and a decrease in the shallow-cloud-dominated case. This demonstrates that under different environmental conditions the response to aerosol perturbation could be different. </jats:p>


tobac v1.0: towards a flexible framework for tracking and analysis of clouds in diverse datasets

Geoscientific Model Development Discussions Copernicus GmbH (2019) 1-31

M Heikenfeld, PJ Marinescu, M Christensen, D Watson-Parris, F Senf, SC van den Heever, P Stier

<jats:p>&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two- or three-dimensional time-varying input. The application of high-level data formats, such as iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the three-dimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. tobac provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data.&lt;/p&gt; </jats:p>


Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation

Atmospheric Chemistry and Physics Copernicus GmbH 19 (2019) 8591-8617

GS Fanourgakis, M Kanakidou, A Nenes, SE Bauer, T Bergman, KS Carslaw, A Grini, DS Hamilton, JS Johnson, VA Karydis, A Kirkevåg, JK Kodros, U Lohmann, G Luo, R Makkonen, H Matsui, D Neubauer, JR Pierce, J Schmale, P Stier, K Tsigaridis, T van Noije, H Wang, D Watson-Parris, DM Westervelt, Y Yang, M Yoshioka, N Daskalakis, S Decesari, M Gysel-Beer, N Kalivitis, X Liu, NM Mahowald, S Myriokefalitakis, R Schrödner, M Sfakianaki, AP Tsimpidi, M Wu, F Yu

<jats:p>&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties.&lt;/p&gt; &lt;p&gt;There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of &lt;span class="inline-formula"&gt;−24&lt;/span&gt;&amp;amp;thinsp;% and &lt;span class="inline-formula"&gt;−35&lt;/span&gt;&amp;amp;thinsp;% for particles with dry diameters &lt;span class="inline-formula"&gt;&amp;amp;gt;50&lt;/span&gt; and &lt;span class="inline-formula"&gt;&amp;amp;gt;120&lt;/span&gt;&amp;amp;thinsp;nm, as well as &lt;span class="inline-formula"&gt;−36&lt;/span&gt;&amp;amp;thinsp;% and &lt;span class="inline-formula"&gt;−34&lt;/span&gt;&amp;amp;thinsp;% for CCN at supersaturations of 0.2&amp;amp;thinsp;% and 1.0&amp;amp;thinsp;%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (&lt;span class="inline-formula"&gt;&amp;amp;lt;0.1&lt;/span&gt;&amp;amp;thinsp;%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated &lt;span class="inline-formula"&gt;N&lt;sub&gt;3&lt;/sub&gt;&lt;/span&gt; (number concentration of particles with dry diameters larger than 3&amp;amp;thinsp;nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of &lt;span class="inline-formula"&gt;0.2&lt;/span&gt;&amp;amp;thinsp;% (CCN&lt;span class="inline-formula"&gt;&lt;sub&gt;0.2&lt;/sub&gt;&lt;/span&gt;) compared to that for &lt;span class="inline-formula"&gt;N&lt;sub&gt;3&lt;/sub&gt;&lt;/span&gt;, maximizing over regions where new particle formation is important.&lt;/p&gt; &lt;p&gt;An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter.&lt;/p&gt; &lt;p&gt;Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120&amp;amp;thinsp;nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40&amp;amp;thinsp;% during winter and 20&amp;amp;thinsp;% in summer.&lt;/p&gt; &lt;p&gt;In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB &lt;span class="inline-formula"&gt;−13&lt;/span&gt;&amp;amp;thinsp;% and &lt;span class="inline-formula"&gt;−22&lt;/span&gt;&amp;amp;thinsp;% for updraft velocities 0.3 and 0.6&amp;amp;thinsp;m&amp;amp;thinsp;s&lt;span class="inline-formula"&gt;&lt;sup&gt;−1&lt;/sup&gt;&lt;/span&gt;, respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (&lt;span class="inline-formula"&gt;&lt;math xmlns="http://www.w3.org/1998/Math/MathML" id="M15" display="inline" overflow="scroll" dspmath="mathml"&gt;&lt;mrow&gt;&lt;mo&gt;∂&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;N&lt;/mi&gt;&lt;mi mathvariant="normal"&gt;d&lt;/mi&gt;&lt;/msub&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mo&gt;∂&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;N&lt;/mi&gt;&lt;mi mathvariant="normal"&gt;a&lt;/mi&gt;&lt;/msub&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;span&gt;&lt;svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="9faa6b9bc700a00532091cfd69cae419"&gt;&lt;svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-8591-2019-ie00001.svg" width="48pt" height="14pt" src="acp-19-8591-2019-ie00001.png"/&gt;&lt;/svg:svg&gt;&lt;/span&gt;&lt;/span&gt;) and to updraft velocity (&lt;span class="inline-formula"&gt;&lt;math xmlns="http://www.w3.org/1998/Math/MathML" id="M16" display="inline" overflow="scroll" dspmath="mathml"&gt;&lt;mrow&gt;&lt;mo&gt;∂&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;N&lt;/mi&gt;&lt;mi mathvariant="normal"&gt;d&lt;/mi&gt;&lt;/msub&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mo&gt;∂&lt;/mo&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;span&gt;&lt;svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="43pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="9a0c289e263af38b17f8d2715a056c8f"&gt;&lt;svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-8591-2019-ie00002.svg" width="43pt" height="14pt" src="acp-19-8591-2019-ie00002.png"/&gt;&lt;/svg:svg&gt;&lt;/span&gt;&lt;/span&gt;). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities &lt;span class="inline-formula"&gt;&lt;math xmlns="http://www.w3.org/1998/Math/MathML" id="M17" display="inline" overflow="scroll" dspmath="mathml"&gt;&lt;mrow&gt;&lt;mo&gt;∂&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;N&lt;/mi&gt;&lt;mi mathvariant="normal"&gt;d&lt;/mi&gt;&lt;/msub&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mo&gt;∂&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;N&lt;/mi&gt;&lt;mi mathvariant="normal"&gt;a&lt;/mi&gt;&lt;/msub&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;span&gt;&lt;svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="48pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="a47c1357bf9f8959859c5d28931197ed"&gt;&lt;svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-8591-2019-ie00003.svg" width="48pt" height="14pt" src="acp-19-8591-2019-ie00003.png"/&gt;&lt;/svg:svg&gt;&lt;/span&gt;&lt;/span&gt; and &lt;span class="inline-formula"&gt;&lt;math xmlns="http://www.w3.org/1998/Math/MathML" id="M18" display="inline" overflow="scroll" dspmath="mathml"&gt;&lt;mrow&gt;&lt;mo&gt;∂&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;N&lt;/mi&gt;&lt;mi mathvariant="normal"&gt;d&lt;/mi&gt;&lt;/msub&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mo&gt;∂&lt;/mo&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;span&gt;&lt;svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="43pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="2e76a96aacff9b259f027c6bf554be27"&gt;&lt;svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-8591-2019-ie00004.svg" width="43pt" height="14pt" src="acp-19-8591-2019-ie00004.png"/&gt;&lt;/svg:svg&gt;&lt;/span&gt;&lt;/span&gt;; models may be predisposed to be too “aerosol sensitive” or “aerosol insensitive” in aerosol–cloud–climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain inter-model biases on the aerosol indirect effect.&lt;/p&gt; </jats:p>


Effects of aerosol in simulations of realistic shallow cumulus cloud fields in a large domain

ATMOSPHERIC CHEMISTRY AND PHYSICS 19 (2019) 13507-13517

G Spill, P Stier, PR Field, G Dagan


Surprising similarities in model and observational aerosol radiative forcing estimates

Atmospheric Chemistry and Physics Discussions Copernicus GmbH (2019) 1-18

E Gryspeerdt, J Mülmenstädt, A Gettelman, FF Malavelle, H Morrison, D Neubauer, DG Partridge, P Stier, T Takemura, H Wang, M Wang, K Zhang

<jats:p>&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; The radiative forcing from aerosols (particularly through their interaction with clouds) remains one of the most uncertain components of the human forcing of the climate. Observation-based studies have typically found a smaller aerosol effective radiative forcing than in model simulations and were given preferential weighting in the IPCC AR5 report. With their own sources of uncertainty, it is not clear that observation-based estimates are more reliable. Understanding the source of the model-observational difference is thus vital to reduce uncertainty in the impact of aerosols on the climate.&lt;/p&gt; &lt;p&gt;These reported discrepancies arise from the different decompositions of the aerosol forcing used in model and observational studies. Applying the observational decomposition to global climate model output, the two different lines of evidence are surprisingly similar, with a much better agreement on the magnitude of aerosol impacts on cloud properties. Cloud adjustments remain a significant source of uncertainty, particularly for ice clouds. However, they are consistent with the uncertainty from observation-based methods, with the liquid water path adjustment usually enhancing the Twomey effect by less than 50&amp;amp;thinsp;%. Depending on different sets of assumptions, this work suggests that model and observation-based estimates could be more equally weighted in future synthesis studies.&lt;/p&gt; </jats:p>


Analysis of the Atmospheric Water Budget for Elucidating the Spatial Scale of Precipitation Changes Under Climate Change

Geophysical Research Letters American Geophysical Union (AGU) 46 (2019) 10504-10511

G Dagan, P Stier, D Watson‐Parris


tobac 1.2: towards a flexible framework for tracking and analysis of clouds in diverse datasets

GEOSCIENTIFIC MODEL DEVELOPMENT 12 (2019) 4551-4570

M Heikenfeld, PJ Marinescu, M Christensen, D Watson-Parris, F Senf, SC van den Heever, P Stier


The global aerosol-climate model ECHAM6.3-HAM2.3 – Part 2: Cloud evaluation, aerosol radiative forcing and climate sensitivity

Geoscientific Model Development Discussions Copernicus GmbH (2019) 1-52

D Neubauer, S Ferrachat, C Siegenthaler-Le Drian, P Stier, DG Partridge, I Tegen, I Bey, T Stanelle, H Kokkola, U Lohmann

<jats:p>&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; The global aerosol-climate model ECHAM6.3-HAM2.3 (E63H23) and the previous model versions ECHAM5.5-HAM2.0 (E55H20) and ECHAM6.1-HAM2.2 (E61H22) are evaluated using global observational datasets for clouds and precipitation. In E63H23 low cloud amount, liquid and ice water path and cloud radiative effects are more realistic than in previous model versions. E63H23 has a more physically based aerosol activation scheme, improvements in the cloud cover scheme, changes in detrainment of convective clouds, changes in the sticking efficiency for accretion of ice crystals by snow, consistent ice crystal shapes throughout the model, changes in mixed phase freezing and an inconsistency in ice crystal number concentration (ICNC) in cirrus clouds was removed. Biases that were identified in E63H23 (and in previous model versions) are a too low cloud amount in stratocumulus regions, deep convective clouds in the Atlantic and Pacific oceans form too close to the continents and there are indications that ICNCs are overestimated.&lt;/p&gt; &lt;p&gt;Since clouds are important for effective radiative forcing due to aerosol-radiation and aerosol-cloud interactions (ERF&lt;sub&gt;ari+aci&lt;/sub&gt;) and equilibrium climate sensitivity (ECS), also differences in ERF&lt;sub&gt;ari+aci&lt;/sub&gt; and ECS between the model versions were analyzed. ERF&lt;sub&gt;ari+aci&lt;/sub&gt; is weaker in E63H23 (&amp;amp;minus;1.0&amp;amp;thinsp;W&amp;amp;thinsp;m&lt;sup&gt;&amp;amp;minus;2&lt;/sup&gt;) than in E61H22 (&amp;amp;minus;1.2&amp;amp;thinsp;W&amp;amp;thinsp;m&lt;sup&gt;&amp;amp;minus;2&lt;/sup&gt;) (or E55H20; &amp;amp;minus;1.1&amp;amp;thinsp;W&amp;amp;thinsp;m&lt;sup&gt;&amp;amp;minus;2&lt;/sup&gt;). This is caused by the weaker shortwave ERF&lt;sub&gt;ari+aci&lt;/sub&gt; (new aerosol activation scheme and sea salt emission parameterization in E63H23, more realistic simulation of cloud water) overcompensating the weaker longwave ERF&lt;sub&gt;ari+aci&lt;/sub&gt; (removal of an inconsistency in ICNC in cirrus clouds in E61H22).&lt;/p&gt; &lt;p&gt;The decrease in ECS in E63H23 (2.5&amp;amp;thinsp;K) compared to E61H22 (2.8&amp;amp;thinsp;K) is due to changes in the entrainment rate for shallow convection (affecting the cloud amount feedback) and a stronger cloud phase feedback.&lt;/p&gt; </jats:p>


Global response of parameterised convective cloud fields to anthropogenic aerosol forcing

Atmospheric Chemistry and Physics Discussions Copernicus GmbH (2019) 1-25

Z Kipling, L Labbouz, P Stier

<jats:p>&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; The interactions between aerosols and convective clouds represent some of the greatest uncertainties in the climate impact of aerosols in the atmosphere. A wide variety of mechanisms have been proposed by which aerosols may invigorate, suppress, or change the properties of individual convective clouds, some of which can be reproduced in high-resolution limited-area models. However, there may also be mesoscale, regional or global adjustments which modulate or dampen such impacts which cannot be captured in the limited domain of such models. The Convective Cloud Field Model (CCFM) provides a mechanism to explicitly simulate a population of convective clouds within each grid column at resolutions used for global climate modelling, so that a representation of the microphysical aerosol response within each parameterised cloud type is possible.&lt;/p&gt; &lt;p&gt;Using CCFM within the global aerosol–climate model ECHAM–HAM, we demonstrate how the parameterised cloud field responds to the present-day anthropogenic aerosol perturbation in different regions. In particular, we show that in regions with strongly-forced deep convection and/or significant aerosol effects via large-scale processes, the changes in the convective cloud field due to microphysical effects is rather small; however in a more weakly-forced regime such as the Caribbean, where large-scale aerosol effects are small, a signature of convective invigoration does become apparent.&lt;/p&gt; </jats:p>


Ensembles of global climate model variants designed for the quantification and constraint of uncertainty in aerosols and their radiative forcing

Journal of Advances in Modeling Earth Systems American Geophysical Union 11 (2019) 3728-3754

M Yoshioka, LA Regayre, KJ Pringle, JS Johnson, GW Mann, DG Partridge, DMH Sexton, GMS Lister, N Schutgens, P Stier, Z Kipling, N Bellouin, J Browse, BBB Booth, CE Johnson, B Johnson, JDP Mollard, L Lee, KS Carslaw

Tropospheric aerosol radiative forcing has persisted for many years as one of the major causes of uncertainty in global climate model simulations. To sample the range of plausible aerosol and atmospheric states and perform robust statistical analyses of the radiative forcing, it is important to account for the combined effects of many sources of model uncertainty, which is rarely done due to the high computational cost. This paper describes the designs of two ensembles of the HadGEM-UKCA global climate model and provides the first analyses of the uncertainties in aerosol radiative forcing and their causes. The first ensemble was designed to comprehensively sample uncertainty in the aerosol state, while the other samples additional uncertainties in the physical model related to clouds, humidity and radiation, thereby allowing an analysis of uncertainty in the aerosol effective radiative forcing. Each ensemble consists of around 200 simulations of the pre-industrial and present-day atmospheres. The uncertainty in aerosol radiative forcing in our ensembles is comparable to the range of estimates from multi-model intercomparison projects. The mean aerosol effective radiative forcing is –1.45 W m–2 (credible interval –2.07 to –0.81 W m–2), which encompasses but is more negative than the –1.17 W m–2 in the 2013 Atmospheric Chemistry and Climate Model Intercomparison Project and –0.90 W m–2 in the IPCC 5th 47 Assessment Report. The ensembles can be used to reduce aerosol radiative forcing uncertainty by challenging them with multiple measurements as well as to isolate potential causes of multi-model differences.


The global aerosol-climate model ECHAM6.3-HAM2.3-Part 1: Aerosol evaluation

GEOSCIENTIFIC MODEL DEVELOPMENT 12 (2019) 1643-1677

I Tegen, D Neubauer, S Ferrachat, C Siegenthaler-Le Drian, I Bey, N Schutgens, P Stier, D Watson-Parris, T Stanelle, H Schmidt, S Rast, H Kokkola, M Schultz, S Schroeder, N Daskalakis, S Barthel, B Heinold, U Lohmann


Efficacy of climate forcings in PDRMIP models

Journal of Geophysical Research: Atmospheres American Geophysical Union (2019)

TB Richardson, PM Forster, CJ Smith, AC Maycock, T Wood, T Andrews, O Boucher, G Faluvegi, D Flaeschner, O Hodnebrog, M Kasoar, A Kirkevåg, J-F Lamarque, J Mülmenstädt, G Myhre, D Olivié, RW Portmann, BH Samset, D Shawki, D Shindell, P Stier, T Takemura, A Voulgarakis, D Watson-Parris

Quantifying the efficacy of different climate forcings is important for understanding the real‐world climate sensitivity. This study presents a systematic multi‐model analysis of different climate driver efficacies using simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). Efficacies calculated from instantaneous radiative forcing deviate considerably from unity across forcing agents and models. Effective radiative forcing (ERF) is a better predictor of global mean near‐surface air temperature (GSAT) change. Efficacies are closest to one when ERF is computed using fixed sea surface temperature experiments and adjusted for land surface temperature changes using radiative kernels. Multi‐model mean efficacies based on ERF are close to one for global perturbations of methane, sulphate, black carbon and insolation, but there is notable inter‐model spread. We do not find robust evidence that the geographic location of sulphate aerosol affects its efficacy. GSAT is found to respond more slowly to aerosol forcing than CO2 in the early stages of simulations. Despite these differences, we find that there is no evidence for an efficacy effect on historical GSAT trend estimates based on simulations with an impulse response model, nor on the resulting estimates of climate sensitivity derived from the historical period. However, the considerable intermodel spread in the computed efficacies means that we cannot rule out an efficacy‐induced bias of ±0.4 K in equilibrium climate sensitivity to CO2 doubling (ECS) when estimated using the historical GSAT trend.


Increased water vapour lifetime due to global warming

Atmospheric Chemistry and Physics Discussions Copernicus GmbH (2019) 1-17

Ø Hodnebrog, G Myhre, BH Samset, K Alterskjær, T Andrews, O Boucher, G Faluvegi, D Fläschner, PM Forster, M Kasoar, A Kirkevåg, J-F Lamarque, D Olivié, TB Richardson, D Shawki, D Shindell, KP Shine, P Stier, T Takemura, A Voulgarakis, D Watson-Parris

<jats:p>&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; The relationship between changes in integrated water vapour (IWV) and precipitation can be characterized by quantifying changes in atmospheric water vapour lifetime. Precipitation isotope ratios correlate with this lifetime, a relationship that helps understand dynamical processes and may lead to improved climate projections. We investigate how water vapour and its lifetime respond to different drivers of climate change, such as greenhouse gases and aerosols. Results from 11 global climate models have been used, based on simulations where CO&lt;sub&gt;2&lt;/sub&gt;, methane, solar irradiance, black carbon (BC), and sulphate have been perturbed separately. A lifetime increase from 8 to 10&amp;amp;thinsp;days is projected between 1986&amp;amp;ndash;2005 and 2081&amp;amp;ndash;2100, under a business-as-usual pathway. By disentangling contributions from individual climate drivers, we present a physical understanding of how global warming slows down the hydrological cycle, due to longer lifetime, but still amplifies the cycle due to stronger precipitation/evaporation fluxes. The feedback response of IWV to surface temperature change differs somewhat between drivers. Fast responses amplify these differences and lead to net changes in IWV per degree surface warming ranging from 6.4&amp;amp;plusmn;0.9&amp;amp;thinsp;%/K for sulphate to 9.8&amp;amp;plusmn;2&amp;amp;thinsp;%/K for BC. While BC is the driver with the strongest increase in IWV per degree surface warming, it is also the only driver with a reduction in precipitation per degree surface warming. Consequently, increases in BC aerosol concentrations yield the strongest slowdown of the hydrological cycle among the climate drivers studied, with a change in water vapour lifetime per degree surface warming of 1.1&amp;amp;plusmn;0.4&amp;amp;thinsp;days/K, compared to less than 0.5&amp;amp;thinsp;days/K for the other climate drivers (CO&lt;sub&gt;2&lt;/sub&gt;, methane, solar irradiance, sulphate).&lt;/p&gt; </jats:p>


Water vapour adjustments and responses differ between climate drivers

Atmospheric Chemistry and Physics Copernicus Publications 19 (2019) 12887–12899-

O Hodnebrog, G Myhre, B Samset, K Alterskjaer, T Andrews, O Boucher, G Faluvegi, D Fläschner, P Forster, M Kasoar, A Kirkevag, J-F Lamarque, D Olivie, T Richardson, D Shawki, D Shindell, KP Shine, P Stier, T Takemura, A Voulgarikis, D Watson-Parris

Water vapour in the atmosphere is the source of a major climate feedback mechanism and potential increases in the availability of water vapour could have important consequences for mean and extreme precipitation. Future precipitation changes further depend on how the hydrological cycle responds to different drivers of climate change, such as greenhouse gases and aerosols. Currently, neither the total anthropogenic influence on the hydrological cycle nor that from individual drivers is constrained sufficiently to make solid projections. We investigate how integrated water vapour (IWV) responds to different drivers of climate change. Results from 11 global climate models have been used, based on simulations where CO2, methane, solar irradiance, black carbon (BC), and sulfate have been perturbed separately. While the global-mean IWV is usually assumed to increase by ∼7 % per kelvin of surface temperature change, we find that the feedback response of IWV differs somewhat between drivers. Fast responses, which include the initial radiative effect and rapid adjustments to an external forcing, amplify these differences. The resulting net changes in IWV range from 6.4±0.9 % K−1 for sulfate to 9.8±2 % K−1 for BC. We further calculate the relationship between global changes in IWV and precipitation, which can be characterized by quantifying changes in atmospheric water vapour lifetime. Global climate models simulate a substantial increase in the lifetime, from 8.2±0.5 to 9.9±0.7 d between 1986–2005 and 2081–2100 under a high-emission scenario, and we discuss to what extent the water vapour lifetime provides additional information compared to analysis of IWV and precipitation separately. We conclude that water vapour lifetime changes are an important indicator of changes in precipitation patterns and that BC is particularly efficient in prolonging the mean time, and therefore likely the distance, between evaporation and precipitation.


Contrasting response of precipitation to aerosol perturbation in the tropics and extratropics explained by energy budget considerations

Geophysical Research Letters American Geophysical Union 46 (2019) 7828-7837

G Dagan, P Stier, D Watson-Parris

Precipitation plays a crucial role in the Earth's energy balance, the water cycle, and the global atmospheric circulation. Aerosols, by direct interaction with radiation and by serving as cloud condensation nuclei, may affect clouds and rain formation. This effect can be examined in terms of energetic constraints, that is, any aerosol‐driven diabatic heating/cooling of the atmosphere will have to be balanced by changes in precipitation, radiative fluxes, or divergence of dry static energy. Using an aqua‐planet general circulation model (GCM), we show that tropical and extratropical precipitation have contrasting responses to aerosol perturbations. This behavior can be explained by contrasting ability of the atmosphere to diverge excess dry static energy in the two different regions. It is shown that atmospheric heating in the tropics leads to large‐scale thermally driven circulation and a large increase in precipitation, while the excess energy from heating in the extratropics is constrained due to the effect of the Coriolis force, causing the precipitation to decrease.


Anthropogenic aerosol forcing – insights from multiple estimates from aerosol-climate models with reduced complexity

Atmospheric Chemistry and Physics Copernicus GmbH 19 (2019) 6821-6841

S Fiedler, S Kinne, WTK Huang, P Räisänen, D O&amp;apos;Donnell, N Bellouin, P Stier, J Merikanto, T van Noije, R Makkonen, U Lohmann

<jats:p>&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; This study assesses the change in anthropogenic aerosol forcing from the mid-1970s to the mid-2000s. Both decades had similar global-mean anthropogenic aerosol optical depths but substantially different global distributions. For both years, we quantify (i) the forcing spread due to model-internal variability and (ii) the forcing spread among models. Our assessment is based on new ensembles of atmosphere-only simulations with five state-of-the-art Earth system models. Four of these models will be used in the sixth Coupled Model Intercomparison Project (CMIP6; &lt;span class="cit" id="xref_altparen.1"&gt;&lt;a href="#bib1.bibx14"&gt;Eyring et al.&lt;/a&gt;, &lt;a href="#bib1.bibx14"&gt;2016&lt;/a&gt;&lt;/span&gt;). Here, the complexity of the anthropogenic aerosol has been reduced in the participating models. In all our simulations, we prescribe the same patterns of the anthropogenic aerosol optical properties and associated effects on the cloud droplet number concentration. We calculate the instantaneous radiative forcing (RF) and the effective radiative forcing (ERF). Their difference defines the net contribution from rapid adjustments. Our simulations show a model spread in ERF from &lt;span class="inline-formula"&gt;−0.4&lt;/span&gt; to &lt;span class="inline-formula"&gt;−0.9&lt;/span&gt;&amp;amp;thinsp;W&amp;amp;thinsp;m&lt;span class="inline-formula"&gt;&lt;sup&gt;−2&lt;/sup&gt;&lt;/span&gt;. The standard deviation in annual ERF is 0.3&amp;amp;thinsp;W&amp;amp;thinsp;m&lt;span class="inline-formula"&gt;&lt;sup&gt;−2&lt;/sup&gt;&lt;/span&gt;, based on 180 individual estimates from each participating model. This result implies that identifying the model spread in ERF due to systematic differences requires averaging over a sufficiently large number of years. Moreover, we find almost identical ERFs for the mid-1970s and mid-2000s for individual models, although there are major model differences in natural aerosols and clouds. The model-ensemble mean ERF is &lt;span class="inline-formula"&gt;−0.54&lt;/span&gt;&amp;amp;thinsp;W&amp;amp;thinsp;m&lt;span class="inline-formula"&gt;&lt;sup&gt;−2&lt;/sup&gt;&lt;/span&gt; for the pre-industrial era to the mid-1970s and &lt;span class="inline-formula"&gt;−0.59&lt;/span&gt;&amp;amp;thinsp;W&amp;amp;thinsp;m&lt;span class="inline-formula"&gt;&lt;sup&gt;−2&lt;/sup&gt;&lt;/span&gt; for the pre-industrial era to the mid-2000s. Our result suggests that comparing ERF changes between two observable periods rather than absolute magnitudes relative to a poorly constrained pre-industrial state might provide a better test for a model's ability to represent transient climate changes.&lt;/p&gt; </jats:p>

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