Publications by Duncan Watson-Parris


Assessing California wintertime precipitation responses to various climate drivers

Journal of Geophysical Research: Atmospheres American Geophysical Union 125 (2020) e2019JD031736

RJ Allen, J-F Lamarque, D Watson-Parris, D Olivie

Understanding how drivers of climate change affect precipitation remains an important area of research. Although several robust precipitation responses have been identified under continued increases in greenhouse gases (GHGs), considerable uncertainty remains. This is particularly the case at regional scales, including the West Coast of the United States and California. Here, we exploit idealized, single forcing simulations from the Precipitation Driver Response Model Intercomparison Project (PDRMIP) to address how climate drivers impact California wintertime precipitation. Consistent with recent work, GHGs including carbon dioxide and methane, as well as solar forcing, yield a robust increase in California wintertime precipitation. We also find robust California precipitation responses to aerosols but with opposite responses for sulfate versus black carbon aerosol. Sulfate aerosol increases California wintertime precipitation, whereas black carbon reduces it. Moreover, California precipitation is more sensitive to aerosols, particularly regional emissions from Europe and Asia, than to GHGs. These precipitation responses are consistent with shifts in the jet stream and altered moisture fluxes. Although the idealized nature of PDRMIP simulations precludes a formal attribution, our results suggest that aerosols can perturb precipitation and fresh water resources along the West Coast of the United States.


Constraining uncertainty in aerosol direct forcing

Geophysical Research Letters American Geophysical Union 47 (2020) e2020GL087141

D Watson-Parris, N Bellouin, L Deaconu, N Schutgens, M Yoshioka, L Regayre, K Pringle, J Johnson, C Smith, K Carslaw, P Stier

The uncertainty in present-day anthropogenic forcing is dominated by uncertainty in the strength of the contribution from aerosol. Much of the uncertainty in the direct aerosol forcing can be attributed to uncertainty in the anthropogenic fraction of aerosol in the present-day atmosphere, due to a lack of historical observations. Here we present a robust relationship between total present-day aerosol optical depth and the anthropogenic contribution across three multi-model ensembles and a large single-model perturbed parameter ensemble. Using observations of aerosol optical depth, we determine a reduced likely range of the anthropogenic component and hence a reduced uncertainty in the direct forcing of aerosol.


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.


Up to two billion times acceleration of scientific simulations with deep neural architecture search

CoRR abs/2001.08055 (2020)

MF Kasim, D Watson-Parris, L Deaconu, S Oliver, P Hatfield, DH Froula, G Gregori, M Jarvis, S Khatiwala, J Korenaga, J Topp-Mugglestone, E Viezzer, SM Vinko

Computer simulations are invaluable tools for scientific discovery. However, accurate simulations are often slow to execute, which limits their applicability to extensive parameter exploration, large-scale data analysis, and uncertainty quantification. A promising route to accelerate simulations by building fast emulators with machine learning requires large training datasets, which can be prohibitively expensive to obtain with slow simulations. Here we present a method based on neural architecture search to build accurate emulators even with a limited number of training data. The method successfully accelerates simulations by up to 2 billion times in 10 scientific cases including astrophysics, climate science, biogeochemistry, high energy density physics, fusion energy, and seismology, using the same super-architecture, algorithm, and hyperparameters. Our approach also inherently provides emulator uncertainty estimation, adding further confidence in their use. We anticipate this work will accelerate research involving expensive simulations, allow more extensive parameters exploration, and enable new, previously unfeasible computational discovery.


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

Geoscientific Model Development Discussions Copernicus Publications (2019)

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

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.


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

Atmospheric Chemistry and Physics Copernicus GmbH (2019)

GS Fanourgakis, M Kanakidou, A Nenes, 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, J Schmale, PHILIP Stier, K Tsigaridis, T van Noije, H Wang, DUNCAN Watson-Parris, DM Westervelt

<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;thinsp;% and &lt;span class="inline-formula"&gt;−35&lt;/span&gt;&amp;thinsp;% for particles with dry diameters &lt;span class="inline-formula"&gt;&amp;gt;50&lt;/span&gt; and &lt;span class="inline-formula"&gt;&amp;gt;120&lt;/span&gt;&amp;thinsp;nm, as well as &lt;span class="inline-formula"&gt;−36&lt;/span&gt;&amp;thinsp;% and &lt;span class="inline-formula"&gt;−34&lt;/span&gt;&amp;thinsp;% for CCN at supersaturations of 0.2&amp;thinsp;% and 1.0&amp;thinsp;%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (&lt;span class="inline-formula"&gt;&amp;lt;0.1&lt;/span&gt;&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;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;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;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;thinsp;% during winter and 20&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;thinsp;% and &lt;span class="inline-formula"&gt;−22&lt;/span&gt;&amp;thinsp;% for updraft velocities 0.3 and 0.6&amp;thinsp;m&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>


Analysis of the atmospheric water budget for elucidating the spatial scale of precipitation changes under climate change

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

G Dagan, P Stier, D Watson-Parris

Global mean precipitation changes due to climate change were previously shown to be relatively small and well constrained by the energy budget. However, local precipitation changes can be much more significant. In this paper we propose that for large enough scales, for which the water budget is closed (precipitation [P] roughly equals evaporation [E]), changes in P approach the small global mean value. However, for smaller scales, for which P and E are not necessarily equal and convergence of water vapor still plays a role, changes in P could be much larger due to dynamical contributions. Using 40 years of two reanalysis data sets, 39 CMIP5 models and additional numerical simulations, we identify the scale of transition in the importance of the different terms in the water budget to precipitation to be ~3500-4000 km and demonstrate its relation to the spatial scale of precipitation changes under climate change.


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

Geoscientific Model Development Copernicus GmbH (2019)

M Heikenfeld, PJ Marinescu, MATTHEW Christensen, DUNCAN Watson-Parris, F Senf, SC van den Heever, PHILIP Stier

<jats:p>Abstract. 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. The tobac framework 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. </jats:p>


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

GEOSCIENTIFIC MODEL DEVELOPMENT (2019)

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

© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. We introduce and evaluate aerosol simulations with the global aerosol-climate model ECHAM6.3-HAM2.3, which is the aerosol component of the fully coupled aerosol-chemistry-climate model ECHAM-HAMMOZ. Both the host atmospheric climate model ECHAM6.3 and the aerosol model HAM2.3 were updated from previous versions. The updated version of the HAM aerosol model contains improved parameterizations of aerosol processes such as cloud activation, as well as updated emission fields for anthropogenic aerosol species and modifications in the online computation of sea salt and mineral dust aerosol emissions. Aerosol results from nudged and free-running simulations for the 10-year period 2003 to 2012 are compared to various measurements of aerosol properties. While there are regional deviations between the model and observations, the model performs well overall in terms of aerosol optical thickness, but may underestimate coarse-mode aerosol concentrations to some extent so that the modeled particles are smaller than indicated by the observations. Sulfate aerosol measurements in the US and Europe are reproduced well by the model, while carbonaceous aerosol species are biased low. Both mineral dust and sea salt aerosol concentrations are improved compared to previous versions of ECHAM-HAM. The evaluation of the simulated aerosol distributions serves as a basis for the suitability of the model for simulating aerosol-climate interactions in a changing climate.


Efficacy of climate forcings in PDRMIP models

Journal of Geophysical Research: Atmospheres American Geophysical Union 124 (2019) 12824-12844

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.


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

Atmospheric Chemistry and Physics Discussions Atmospheric Chemistry and Physics 19 (2019) 8591-8617

GS Fanourgakis, M Kanakidou, A Nenes, T Bergman, KS Carslaw, A Grini, DS Hamilton, JS Johnson, VA Karydis, A Kirkevag, JK Kodros, U Lohmann, G Luo, R Makkonen, H Matsui, D Neubauer, J Schmale, P Stier, K Tsigaridis, T van Noije, H Wang, D Watson-Parris, DM Westervelt

<p>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. <br/> <p>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 −24 % and −35 % for particles with dry diameters &gt;50 and &gt;120 nm, as well as −36 % and −34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations (≺0.1 %) 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 N3 (number concentration of particles with dry diameters larger than 3 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 0.2 % (CCN0.2) compared to that for N3, maximizing over regions where new particle formation is important. <br/> <p>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. <br/> <p>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 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 % during winter and 20 % in summer. <br/> <p>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 −13 % and −22 % for updraft velocities 0.3 and 0.6 m s−1, 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 (∂Nd/∂Na) and to updraft velocity (∂Nd/∂w). 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 ∂Nd/∂Na and ∂Nd/∂w; 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.</p></p></p></p></p>


Increased water vapour lifetime due to global warming

Atmospheric Chemistry and Physics Discussions European Geosciences Union (2019)

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

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 CO2, methane, solar irradiance, black carbon (BC), and sulphate have been perturbed separately. A lifetime increase from 8 to 10 days is projected between 1986–2005 and 2081–2100, 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±0.9 %/K for sulphate to 9.8±2 %/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±0.4 days/K, compared to less than 0.5 days/K for the other climate drivers (CO2, methane, solar irradiance, sulphate).


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.


In-situ constraints on the vertical distribution of global aerosol

Atmospheric Chemistry and Physics Discussions European Geosciences Union (2019)

D Watson-Parris, N Schutgens, C Reddington, K Pringle, D Liu, JA Allan, H Coe, K Carslaw, P Stier

Despite ongoing efforts, the vertical distribution of aerosols globally is poorly understood. This in turn leads to large uncertainties in the contributions of the direct and indirect aerosol forcing on climate. Using the Global Aerosol Synthesis and Science Project (GASSP) database – the largest synthesised collection of in-situ aircraft measurements currently available, with more than 1000 flights from 37 campaigns from around the world – we investigate the vertical structure of sub-micron aerosols across a wide range of regions and environments. The application of this unique dataset to assess the vertical distributions of number size distribution and Cloud Condensation Nuclei (CCN) in the global aerosol-climate model ECHAM-HAM reveals that the model underestimates accumulation mode particles in the upper troposphere, especially in remote regions. The processes underlying this discrepancy are explored using different aerosol microphysical schemes and a process sensitivity analysis. These show that the biases are predominantly related to aerosol ageing and removal rather than emissions.


Understanding rapid adjustments to diverse forcing agents

Geophysical Research Letters American Geophysical Union 45 (2018) 12,023-12,031

C Smith, R Kramer, G Myhre, P Forster, T Andrews, O Boucher, D Fläschner, Ø Hodnebrog, M Kasoar, V Kharin, A Kirkevag, J-F Lamarque, J Mülmenstädt, D Olivié, T Richardson, B Samset, D Shindell, P Stier, T Takemura, A Voulgarakis, D Watson-Parris

Rapid adjustments are responses to forcing agents that cause a perturbation to the top of atmosphere energy budget but are uncoupled to changes in surface warming. Different mechanisms are responsible for these adjustments for a variety of climate drivers. These remain to be quantified in detail. It is shown that rapid adjustments reduce the effective radiative forcing (ERF) of black carbon by half of the instantaneous forcing, but for CO2 forcing, rapid adjustments increase ERF. Competing tropospheric adjustments for CO2 forcing are individually significant but sum to zero, such that the ERF equals the stratospherically adjusted radiative forcing, but this is not true for other forcing agents. Additional experiments of increase in the solar constant and increase in CH4 are used to show that a key factor of the rapid adjustment for an individual climate driver is changes in temperature in the upper troposphere and lower stratosphere.


Quantifying the importance of rapid adjustments for global precipitation changes

Geophysical Research Letters American Geophysical Union 45 (2018) 11,399-11,405

G Myhre, RJ Kramer, CJ Smith, O Hodnebrog, P Forster, B Soden, BH Samset, CW Stjern, T Andrews, O Boucher, G Faluvegi, D Fläschner, M Kasoar, A Kirkevåg, J-F Lamarque, D Olivié, T Richardson, D Shindell, P Stier, T Takemura, A Voulgarakis, D Watson-Parris

Different climate drivers influence precipitation in different ways. Here we use radiative kernels to understand the influence of rapid adjustment processes on precipitation in climate models. Rapid adjustments are generally triggered by the initial heating or cooling of the atmosphere from an external climate driver. For precipitation changes, rapid adjustments due to changes in temperature, water vapor and clouds are most important. In this study we have investigated five climate drivers (CO2, CH4, solar irradiance, black carbon (BC), and sulfate aerosols) The fast precipitation response to a doubling of CO2 and a tenfold increase in BC is found to be similar, despite very different instantaneous changes in the radiative cooling, individual rapid adjustments and sensible heating. The model diversity in rapid adjustments is smaller for the experiment involving an increase in the solar irradiance compared to the other climate driver perturbations, and this is also seen in the precipitation changes.


Short black carbon lifetime inferred from a global set of aircraft observations

npj Climate and Atmospheric Science Nature Research 1 (2018) 31

MT Lund, BH Samset, RB Skeie, D Watson-Parris, JM Katich, JP Schwarz, B Weinzierl

Black Carbon (BC) aerosols substantially affect the global climate. However, accurate simulation of BC atmospheric transport remains elusive, due to shortcomings in modeling and a shortage of constraining measurements. Recently, several studies have compared simulations with observed vertical concentration profiles, and diagnosed a global-mean BC atmospheric residence time of &lt;5 days. These studies have, however, been focused on limited geographical regions, and used temporally and spatially coarse model information. Here we expand on previous results by comparing a wide range of recent aircraft measurements from multiple regions, including the Arctic and the Atlantic and Pacific oceans, to simulated distributions obtained at varying spatial and temporal resolution. By perturbing BC removal processes and using current best-estimate emissions, we confirm a constraint on the global-mean BC lifetime of &lt;5.5 days, shorter than in many current global models, over a broader geographical range than has so far been possible. Sampling resolution influences the results, although generally without introducing major bias. However, we uncover large regional differences in the diagnosed lifetime, in particular in the Arctic. We also find that only a weak constraint can be placed in the African outflow region over the South Atlantic, indicating inaccurate emission sources or model representation of transport and microphysical processes. While our results confirm that BC lifetime is shorter than predicted by most recent climate models, they also cast doubt on the usability of the concept of a “global-mean BC lifetime” for climate impact studies, or as an indicator of model skill.


On the limits of CALIOP for constraining modelled free‐tropospheric aerosol

Geophysical Research Letters American Geophysical Union 45 (2018) 9260-9266

D Watson-Parris, N Schutgens, D Winker, S Burton, R Ferrare, P Stier

The space‐borne Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument provides valuable information on the vertical distribution of global aerosol, and is often used to evaluate vertical aerosol distributions in General Circulation Models (GCMs). Here we show, however, that the detection limit of the CALIOP retrievals mean background aerosol is not detected, leading to substantially skewed statistics that moreover differ significantly by product. In the CALIOP Level 2 product this missing low‐backscatter aerosol results in the retrieved aerosol distribution significantly over‐representing aerosol backscatter and extinction in the mid‐ and upper‐troposphere if taken to be representative of the undetected aerosol. The CALIOP Level 3 product assumes no aerosol where none is detected which then leads to an under‐estimation in the aerosol extinction profile in the upper troposphere. Using the ECHAM‐HAM GCM, we estimate that CALIOP nighttime (daytime) retrievals miss 41% (44%) of aerosol mass in the atmosphere.


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

Geoscientific Model Development Discussions Copernicus Publications 12 (2018) 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

We introduce and evaluate aerosol simulations with the global aerosol–climate model ECHAM6.3–HAM2.3, which is the aerosol component of the fully coupled aerosol–chemistry–climate model ECHAM–HAMMOZ. Both the host atmospheric climate model ECHAM6.3 and the aerosol model HAM2.3 were updated from previous versions. The updated version of the HAM aerosol model contains improved parameterizations of aerosol processes such as cloud activation, as well as updated emission fields for anthropogenic aerosol species and modifications in the online computation of sea salt and mineral dust aerosol emissions. Aerosol results from nudged and free-running simulations for the 10-year period 2003 to 2012 are compared to various measurements of aerosol properties. While there are regional deviations between the model and observations, the model performs well overall in terms of aerosol optical thickness, but may underestimate coarse-mode aerosol concentrations to some extent so that the modeled particles are smaller than indicated by the observations. Sulfate aerosol measurements in the US and Europe are reproduced well by the model, while carbonaceous aerosol species are biased low. Both mineral dust and sea salt aerosol concentrations are improved compared to previous versions of ECHAM–HAM. The evaluation of the simulated aerosol distributions serves as a basis for the suitability of the model for simulating aerosol–climate interactions in a changing climate.

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