37 results found
Bellouin N, Quaas J, Gryspeerdt E, et al., 2020, Bounding global aerosol radiative forcing of climate change, Reviews of Geophysics, Vol: 58, Pages: 1-45, ISSN: 8755-1209
Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the im balance 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 modelling approaches, theoretical considerations, and obser vations. 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 aerosol61 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 −1.60 to −0.65 W m−2, or −2.0 to −0.4 W m−2 with a 90% like lihood. Those intervals are of similar width to the last Intergovernmental Panel on Cli mate Change assessment but shifted towards 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.
Gryspeerdt E, Mülmenstädt J, Gettelman A, et al., 2020, Surprising similarities in model and observational aerosol radiative forcing estimates, Atmospheric Chemistry and Physics, Vol: 20, Pages: 613-623, ISSN: 1680-7316
The radiative forcing from aerosols (particularly through their interaction with clouds) remains one of the mostuncertain components of the human forcing of the climate. Observation-based studies have typically found a smaller aerosoleffective radiative forcing than in model simulations and were given preferential weighting in the IPCC AR5 report. With theirown 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.These reported discrepancies arise from the different methods of separating the components of aerosol forcing used in modeland observational studies. Applying the observational decomposition to global climate model output, the two different linesof 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 effectby less than 50%. Depending on different sets of assumptions, this work suggests that model and observation-based estimatescould be more equally weighted in future synthesis studies.
Muelmenstaedt J, Gryspeerdt E, Salzmann M, et al., 2019, Separating radiative forcing by aerosol-cloud interactions and rapid cloud adjustments in the ECHAM-HAMMOZ aerosol-climate model using the method of partial radiative perturbations, Atmospheric Chemistry and Physics, Vol: 19, Pages: 15415-15429, ISSN: 1680-7316
Using the method of offline radiative transfer modeling within the partial radiative perturbation (PRP) approach, the effective radiative forcing by aerosol–cloud interactions (ERFaci) in the ECHAM–HAMMOZ aerosol climate model is decomposed into a radiative forcing by anthropogenic cloud droplet number change and adjustments of the liquid water path and cloud fraction. The simulated radiative forcing by anthropogenic cloud droplet number change and liquid water path adjustment are of approximately equal magnitude at −0.52 and −0.53 W m−2, respectively, while the cloud-fraction adjustment is somewhat weaker at −0.31 W m−2 (constituting 38 %, 39 %, and 23 % of the total ERFaci, respectively); geographically, all three ERFaci components in the simulation peak over China, the subtropical eastern ocean boundaries, the northern Atlantic and Pacific oceans, Europe, and eastern North America (in order of prominence). Spatial correlations indicate that the temporal-mean liquid water path adjustment is proportional to the temporal-mean radiative forcing, while the relationship between cloud-fraction adjustment and radiative forcing is less direct. While the estimate of warm-cloud ERFaci is relatively insensitive to the treatment of ice and mixed-phase cloud overlying warm cloud, there are indications that more restrictive treatments of ice in the column result in a low bias in the estimated magnitude of the liquid water path adjustment and a high bias in the estimated magnitude of the droplet number forcing. Since the present work is the first PRP decomposition of the aerosol effective radiative forcing into radiative forcing and rapid cloud adjustments, idealized experiments are conducted to provide evidence that the PRP results are accurate. The experiments show that using low-frequency (daily or monthly) time-averaged model output of the cloud property fields underestimates the ERF
Hasekamp OP, Gryspeerdt E, Quaas J, 2019, Analysis of polarimetric satellite measurements suggests stronger cooling due to aerosol-cloud interactions, Nature Communications, Vol: 9, ISSN: 2041-1723
Anthropogenic aerosol emissions lead to an increase in the amount of Cloud Condensation Nuclei and consequently an increase in cloud droplet number concentration and cloud albedo. The cor-responding negative radiative forcing due to aerosol cloud interactions (RFaci) is one of the most uncertain radiative forcing terms as reported in the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). We show that previous observation-based studies underestimate aerosol-cloud interactions because they used measurements of aerosol optical properties that are not directly related to cloud formation and are hampered by measurement uncertainties. We have overcome this problem by the use of new polarimetric satellite retrievals of the relevant aerosol properties (aerosol number, size, shape). The resulting estimate of RFaci= -1.14 Wm−2(range be-tween -0.84 and -1.72 Wm−2) is more than a factor 2 stronger than the IPCC estimate that includes
Gryspeerdt E, Smith T, O'Keeffe E, et al., 2019, The impact of ship emission controls recorded by cloud properties, Geophysical Research Letters, Vol: 46, Pages: 12547-12555, ISSN: 0094-8276
The impact of aerosols on cloud properties is one of the leading uncertainties in the human forcing of the climate. Ships are large, isolated sources of aerosol creating linear cloud formations known as shiptracks. These are an ideal opportunity to identify and measure aerosol-cloud interactions. This work uses over 17,000 shiptracks during the implementation of fuel sulphur content regulations to demonstrate the central role of sulphate aerosol in ship exhaust for modifying clouds. By connecting individual shiptracks to transponder data, it is shown that almost half of shiptracks are likely undetected, masking a significant contribution to the climate impact of shipping. A pathway to retrieving ship sulphate emissions is demonstrated, showing how cloud observations could be used to monitor air pollution.
Gryspeerdt E, Goren T, Sourdeval O, et al., 2019, Constraining the aerosol influence on cloud liquid water path, Atmospheric Chemistry and Physics, Vol: 19, Pages: 5331-5347, ISSN: 1680-7316
The impact of aerosols on cloud properties is one of the largest uncertainties in the anthropogenic radiative forcing of the climate. Significant progress has been made in constraining this forcing using observations, but uncertainty remains, particularly in the magnitude of cloud rapid adjustments to aerosol perturbations. Cloud liquid water path (LWP) is the leading control on liquid-cloud albedo, making it important to observationally constrain the aerosol impact on LWP.Previous modelling and observational studies have shown that multiple processes play a role in determining the LWP response to aerosol perturbations, but that the aerosol effect can be difficult to isolate. Following previous studies using mediating variables, this work investigates use of the relationship between cloud droplet number concentration (Nd) and LWP for constraining the role of aerosols. Using joint-probability histograms to account for the non-linear relationship, this work finds a relationship that is broadly consistent with previous studies. There is significant geographical variation in the relationship, partly due to role of meteorological factors (particularly relative humidity). The Nd–LWP relationship is negative in the majority of regions, suggesting that aerosol-induced LWP reductions could offset a significant fraction of the instantaneous radiative forcing from aerosol–cloud interactions (RFaci).However, variations in the Nd–LWP relationship in response to volcanic and shipping aerosol perturbations indicate that the Nd–LWP relationship overestimates the causal Nd impact on LWP due to the role of confounding factors. The weaker LWP reduction implied by these “natural experiments” means that this work provides an upper bound to the radiative forcing from aerosol-induced changes in the LWP.
Gryspeerdt E, 2019, Ruskin and Meteorology, Ruskin, Turner and the Storm Cloud, Editors: Cooper, Johns, Publisher: Paul Holberton Publishing, ISBN: 978-1-911300-60-1
Gryspeerdt E, Sourdeval E, Quaas J, et al., 2018, Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 2: Controls on the ice crystal number concentration, Atmospheric Chemistry and Physics, Vol: 18, Pages: 14351-14370, ISSN: 1680-7316
The ice crystal number concentration (Ni) is a key property of ice clouds, both radiatively and microphysically. Due to sparse in situ measurements of ice cloud properties, the controls on the Ni have remained difficult to determine. As more advanced treatments of ice clouds are included in global models, it is becoming increasingly necessary to develop strong observational constraints on the processes involved.This work uses the DARDAR-Nice Ni retrieval described in Part 1 to investigate the controls on the Ni at a global scale. The retrieved clouds are separated by type. The effects of temperature, proxies for in-cloud updraft and aerosol concentrations are investigated. Variations in the cloud top Ni (Ni(top)) consistent with both homogeneous and heterogeneous nucleation are observed along with differing relationships between aerosol and Ni(top) depending on the prevailing meteorological situation and aerosol type. Away from the cloud top, the Ni displays a different sensitivity to these controlling factors, providing a possible explanation for the low Ni sensitivity to temperature and ice nucleating particles (INP) observed in previous in situ studies.This satellite dataset provides a new way of investigating the response of cloud properties to meteorological and aerosol controls. The results presented in this work increase our confidence in the retrieved Ni and will form the basis for further study into the processes influencing ice and mixed phase clouds.
Sourdeval O, Gryspeerdt E, Krämer M, et al., 2018, Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 1: Method and evaluation, Atmospheric Chemistry and Physics, Vol: 18, Pages: 14327-14350, ISSN: 1680-7316
The number concentration of cloud particles is a key quantity for understanding aerosol–cloud interactions and describing clouds in climate and numerical weather prediction models. In contrast with recent advances for liquid clouds, few observational constraints exist regarding the ice crystal number concentration (Ni). This study investigates how combined lidar–radar measurements can be used to provide satellite estimates of Ni, using a methodology that constrains moments of a parameterized particle size distribution (PSD). The operational liDAR–raDAR (DARDAR) product serves as an existing base for this method, which focuses on ice clouds with temperatures Tc < −30°C.Theoretical considerations demonstrate the capability for accurate retrievals of Ni, apart from a possible bias in the concentration in small crystals when Tc≳ − 50°C, due to the assumption of a monomodal PSD shape in the current method. This is verified via a comparison of satellite estimates to coincident in situ measurements, which additionally demonstrates the sufficient sensitivity of lidar–radar observations to Ni. Following these results, satellite estimates of Ni are evaluated in the context of a case study and a preliminary climatological analysis based on 10 years of global data. Despite a lack of other large-scale references, this evaluation shows a reasonable physical consistency in Ni spatial distribution patterns. Notably, increases in Ni are found towards cold temperatures and, more significantly, in the presence of strong updrafts, such as those related to convective or orographic uplifts. Further evaluation and improvement of this method are necessary, although these results already constitute a first encouraging step towards large-scale observational constraints for Ni. Part 2 of this series uses this new dataset to examine the controls on Ni.
Gryspeerdt E, Sourdeval O, Quaas J, et al., 2018, Ice crystal number concentration estimates from lidar-radar satellite retrievals. Part 2: Controls on the ice crystal number concentration, Publisher: Copernicus Publications
The ice crystal number concentration (Ni) is a keyproperty of ice clouds, both radiatively and microphysically.Due to sparse in situ measurements of ice cloud properties,the controls on theNihave remained difficult to determine.As more advanced treatments of ice clouds are included inglobal models, it is becoming increasingly necessary to de-velop strong observational constraints on the processes in-volved.This work uses the DARDAR-NiceNiretrieval describedin Part 1 to investigate the controls on theNiat a globalscale. The retrieved clouds are separated by type. The ef-fects of temperature, proxies for in-cloud updraft and aerosolconcentrations are investigated. Variations in the cloud topNi(Ni(top)) consistent with both homogeneous and hetero-geneous nucleation are observed along with differing rela-tionships between aerosol andNi(top)depending on the pre-vailing meteorological situation and aerosol type. Away fromthe cloud top, theNidisplays a different sensitivity to thesecontrolling factors, providing a possible explanation for thelowNisensitivity to temperature and ice nucleating particles(INP) observed in previous in situ studies.This satellite dataset provides a new way of investigat-ing the response of cloud properties to meteorological andaerosol controls. The results presented in this work increaseour confidence in the retrievedNiand will form the basis for further study into the processes influencing ice and mixedphase clouds.
Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their propertiesremain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty isthe dependence of cirrus cloud properties on the cloud formation mechanism, which itself is strongly dependent on the localmeteorological conditions.In this work, a classification system (Identification and Classification of Cirrus or IC-CIR) is introduced to identify cirrusclouds by the cloud formation mechanism. Using re-analysis and satellite data, cirrus clouds are separated in four main types:orographic, frontal, convective and synoptic. Through a comparison to convection-permitting model simulations and back-trajectory based analysis, it is shown that these observation-based regimes can provide extra information on the cloud scaleupdraughts and the frequency of occurrence of liquid-origin ice, with the convective regime having higher updraughts and agreater occurrence of liquid-origin ice compared to the synoptic regimes. Despite having different cloud formation mecha-nisms, the radiative properties of the regimes are not distinct, indicating that retrieved cloud properties alone are insufficient tocompletely describe them.This classification is designed to be easily implemented in GCMs, helping improve future model-observation comparisonsand leading to improved parametrisations of cirrus cloud processes
White B, Gryspeerdt E, Stier P, et al., 2017, Uncertainty from the choice of microphysics scheme in convection-permitting models significantly exceeds aerosol effects, Atmospheric Chemistry and Physics Discussions, Vol: 17, Pages: 12145-12175, ISSN: 1680-7367
This study investigates the hydrometeor development and response to cloud droplet number concentration (CDNC) perturbations in convection-permitting model configurations. We present results from a real-data simulation of deep convection in the Congo basin, an idealised supercell case, and a warm-rain large-eddy simulation (LES). In each case we compare two frequently used double-moment bulk microphysics schemes and investigate the response to CDNC perturbations. In the Congo basin simulations both microphysics schemes have large positive biases in surface precipitation, frequency of high radar reflectivities and frequency of cold cloud compared to observations. In all cases, differences in the simulated cloud morphology and precipitation are found to be significantly greater between the microphysics schemes than due to CDNC perturbations within each scheme. Further, we show that the response of the hydrometeors to CDNC perturbations strongly differs not just between microphysics schemes but also between different cases of convection. Sensitivity tests show that the representation of autoconversion is the dominant factor that drives differences in rain production between the microphysics schemes in the idealised precipitating shallow cumulus case and in a sub-region of the Congo basin simulations dominated by liquid-phase processes. In this region, rain mass is also shown to be relatively insensitive to the radiative effects of an overlying layer of ice-phase cloud. In the idealised supercell case, thermodynamic impacts on the storm system using different microphysics parameterisations can equal those due to aerosol effects. These results highlight the large uncertainty in cloud and precipitation responses to aerosol in convection-permitting simulations and have important implications not just for modelling studies of aerosol-convection interaction. These results indicate the continuing need for tighter observational constraints of cloud processes and response to aer
Schutgens N, Tsyro S, Gryspeerdt E, et al., 2017, On the spatio-temporal representativeness of observations, Atmospheric Chemistry and Physics Discussions, Vol: 17, Pages: 9761-9780, ISSN: 1680-7367
The discontinuous spatio-temporal sampling ofobservations has an impact when using them to construct climatologiesor evaluate models. Here we provide estimates ofthis so-called representation error for a range of timescalesand length scales (semi-annually down to sub-daily, 300 to50 km) and show that even after substantial averaging of datasignificant representation errors may remain, larger than typicalmeasurement errors. Our study considers a variety ofobservations: ground-site or in situ remote sensing (PM2.5,black carbon mass or number concentrations), satellite remotesensing with imagers or lidar (extinction). We show thatobservational coverage (a measure of how dense the spatiotemporalsampling of the observations is) is not an effectivemetric to limit representation errors. Different strategiesto construct monthly gridded satellite L3 data are assessedand temporal averaging of spatially aggregated observations(super-observations) is found to be the best, although it stillallows for significant representation errors. However, temporalcollocation of data (possible when observations are comparedto model data or other observations), combined withtemporal averaging, can be very effective at reducing representationerrors. We also show that ground-based and wideswathimager satellite remote sensing data give rise to similarrepresentation errors, although their observational samplingis different. Finally, emission sources and orographycan lead to representation errors that are very hard to reduce,even with substantial temporal averaging.
Gryspeerdt E, Quaas J, Goren T, et al., 2017, Technical note: an automated cirrus classification, Publisher: Copernicus Publications
Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their properties remain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty is the dependence of cirrus clouds on the mechanism of formation, which itself is strongly dependent on the local meteorological conditions.In this work, a classification system (Identification and Classification of Cirrus or IC-CIR) is introduced to identify cirrus clouds by their formation mechanisms. Using re-analysis and satellite data, cirrus clouds are separated in four main types: orographic, frontal, convective and in-situ. Through a comparison to convection-permitting model simulations and back-trajectory based analysis, it is shown that the regimes can provide extra information on the properties and origin of cirrus that could not be provided by the retrieved cloud properties or reanalysis data alone. This classification is designed to be easily implemented in GCMs, helping improve future model-observation comparisons and leading to improved parametrisations of cirrus cloud processes.
Gryspeerdt E, Quaas J, Ferrachat S, et al., 2017, Constraining the instantaneous aerosol influence on cloud albedo, Proceedings of the National Academy of Sciences of the United States of America, Vol: 114, Pages: 4899-4904, ISSN: 1091-6490
Much of the uncertainty in estimates of the anthropogenic forcing of climate change comes from uncertainties in the instantaneous effect of aerosols on cloud albedo, known as the Twomey effect or the radiative forcing from aerosol–cloud interactions (RFaci), a component of the total or effective radiative forcing. Because aerosols serving as cloud condensation nuclei can have a strong influence on the cloud droplet number concentration (Nd), previous studies have used the sensitivity of the Nd to aerosol properties as a constraint on the strength of the RFaci. However, recent studies have suggested that relationships between aerosol and cloud properties in the present-day climate may not be suitable for determining the sensitivity of the Nd to anthropogenic aerosol perturbations. Using an ensemble of global aerosol–climate models, this study demonstrates how joint histograms between Nd and aerosol properties can account for many of the issues raised by previous studies. It shows that if the anthropogenic contribution to the aerosol is known, the RFaci can be diagnosed to within 20% of its actual value. The accuracy of different aerosol proxies for diagnosing the RFaci is investigated, confirming that using the aerosol optical depth significantly underestimates the strength of the aerosol–cloud interactions in satellite data.
Heyn I, Block K, Mülmenstädt J, et al., 2017, Assessment of simulated aerosol effective radiative forcings in the terrestrial spectrum, Geophysical Research Letters, Vol: 44, Pages: 1001-1007, ISSN: 1944-8007
In its fifth assessment report (AR5), the Intergovernmental Panel on Climate Change provides a best estimate of the effective radiative forcing (ERF) due to anthropogenic aerosol at −0.9 W m−2. This value is considerably weaker than the estimate of −1.2 W m−2 in AR4. A part of the difference can be explained by an offset of +0.2 W m−2 which AR5 added to all published estimates that only considered the solar spectrum, in order to account for adjustments in the terrestrial spectrum. We find that, in the CMIP5 multimodel median, the ERF in the terrestrial spectrum is small, unless microphysical effects on ice- and mixed-phase clouds are parameterized. In the latter case it is large but accompanied by a very strong ERF in the solar spectrum. The total adjustments can be separated into microphysical adjustments (aerosol “effects”) and thermodynamic adjustments. Using a kernel technique, we quantify the latter and find that the rapid thermodynamic adjustments of water vapor and temperature profiles are small. Observation-based constraints on these model results are urgently needed.
Watson-Parris D, Schutgens N, Cook N, et al., 2016, Community Intercomparison Suite (CIS) v1.4.0: a tool for intercomparing models and observations, Geoscientific Model Development, Vol: 9, Pages: 3093-3110, ISSN: 1991-9603
The Community Intercomparison Suite (CIS) is an easy-to-use command-line tool which has been developed to allow the straightforward intercomparison of remote sensing, in situ and model data. While there are a number of tools available for working with climate model data, the large diversity of sources (and formats) of remote sensing and in situ measurements necessitated a novel software solution. Developed by a professional software company, CIS supports a large number of gridded and ungridded data sources "out-of-the-box", including climate model output in NetCDF or the UK Met Office pp file format, CloudSat, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), MODIS (MODerate resolution Imaging Spectroradiometer), Cloud and Aerosol CCI (Climate Change Initiative) level 2 satellite data and a number of in situ aircraft and ground station data sets. The open-source architecture also supports user-defined plugins to allow many other sources to be easily added. Many of the key operations required when comparing heterogenous data sets are provided by CIS, including subsetting, aggregating, collocating and plotting the data. Output data are written to CF-compliant NetCDF files to ensure interoperability with other tools and systems. The latest documentation, including a user manual and installation instructions, can be found on our website (http://cistools.net). Here, we describe the need which this tool fulfils, followed by descriptions of its main functionality (as at version 1.4.0) and plugin architecture which make it unique in the field.
White B, Gryspeerdt E, Stier P, et al., 2016, Can models robustly represent aerosol–convection interactions if their cloud microphysics is uncertain?, Publisher: Copernicus Publications
This study investigates the hydrometeor development and response to cloud droplet number concentration (CDNC)perturbations in convection-permitting model configurations. We present results from a real-data simulation of deep convectionin the Congo basin, an idealised supercell case, and a warm-rain large-eddy simulation (LES). In each case we comparetwo frequently used double-moment bulk microphysics schemes and investigate the response to CDNC perturbations. In theCongo basin simulations both microphysics schemes have large positive biases in surface precipitation, frequency of highradar reflectivities and frequency of cold cloud compared to observations. In all cases, differences in the simulated cloudmorphology and precipitation are found to be significantly greater between the microphysics schemes than due to CDNCperturbations within each scheme. Further, we show that the response of the hydrometeors to CDNC perturbations stronglydiffers not just between microphysics schemes but also between different cases of convection. Sensitivity tests show that the representation of autoconversion is the dominant factor that drives differences in rain production between the microphysicsschemes in the idealised precipitating shallow cumulus case and in a sub-region of the Congo basin simulations dominatedby liquid-phase processes. In this region, rain mass is also shown to be relatively insensitive to the radiative effects of anoverlying layer of ice-phase cloud. In the idealised supercell case, thermodynamic impacts on the storm system using differentmicrophysics parameterisations can equal those due to aerosol effects. These results highlight the large uncertainty in cloud andprecipitation responses to aerosol in convection-permitting simulations and have important implications not just for modellingstudies of aerosol–convection interaction. These results indicate the continuing need for tighter observational constraints ofcloud processes and response to aerosol in a
Schutgens NAJ, Gryspeerdt E, Weigum N, et al., 2016, Will a perfect model agree with perfect observations? The impact of spatial sampling, Atmospheric Chemistry and Physics, Vol: 16, Pages: 6335-6353, ISSN: 1680-7324
Gryspeerdt E, Quaas J, Bellouin N, 2016, Constraining the aerosol influence on cloud fraction, Journal of Geophysical Research: Atmospheres, Vol: 121, Pages: 3566-3583, ISSN: 2169-897X
Aerosol-cloud interactions have the potential to modify many different cloud properties. There is significant uncertainty in the strength of these aerosol-cloud interactions in analyses of observational data, partly due to the difficulty in separating aerosol effects on clouds from correlations generated by local meteorology. The relationship between aerosol and cloud fraction (CF) is particularly important to determine, due to the strong correlation of CF to other cloud properties and its large impact on radiation. It has also been one of the hardest to quantify from satellites due to the strong meteorological covariations involved. This work presents a new method to analyze the relationship between aerosol optical depth (AOD) and CF. By including information about the cloud droplet number concentration (CDNC), the impact of the meteorological covariations is significantly reduced. This method shows that much of the AOD-CF correlation is explained by relationships other than that mediated by CDNC. By accounting for these, the strength of the global mean AOD-CF relationship is reduced by around 80%. This suggests that the majority of the AOD-CF relationship is due to meteorological covariations, especially in the shallow cumulus regime. Requiring CDNC to mediate the AOD-CF relationship implies an effective anthropogenic radiative forcing from an aerosol influence on liquid CF of −0.48 W m−2 (−0.1 to −0.64 W m−2), although some uncertainty remains due to possible biases in the CDNC retrievals in broken cloud scenes.
Gryspeerdt E, Stier P, White BA, et al., 2015, Wet scavenging limits the detection of aerosol effects on precipitation, Atmospheric Chemistry and Physics, Vol: 15, Pages: 7557-7570, ISSN: 1680-7324
Gryspeerdt E, Stier P, Partridge DG, 2014, Links between satellite-retrieved aerosol and precipitation, Atmospheric Chemistry and Physics, Vol: 14, Pages: 9677-9694, ISSN: 1680-7324
Gryspeerdt E, Stier P, Grandey BS, 2014, Cloud fraction mediates the aerosol optical depth-cloud top height relationship, GEOPHYSICAL RESEARCH LETTERS, Vol: 41, Pages: 3622-3627, ISSN: 0094-8276
Gryspeerdt E, Stier P, Partridge DG, 2014, Satellite observations of cloud regime development: the role of aerosol processes, Atmospheric Chemistry and Physics, Vol: 14, Pages: 1141-1158, ISSN: 1680-7324
Gryspeerdt E, Stier P, 2012, Regime-based analysis of aerosol-cloud interactions, GEOPHYSICAL RESEARCH LETTERS, Vol: 39, ISSN: 0094-8276
Rowlands DJ, Frame DJ, Ackerley D, et al., 2012, Broad range of 2050 warming from an observationally constrained large climate model ensemble, NATURE GEOSCIENCE, Vol: 5, Pages: 256-260, ISSN: 1752-0894
Quaas J, Arola A, Cairns B, et al., Constraining the Twomey effect from satellite observations: Issues and perspectives
<jats:p>Abstract. The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (ΔNd,ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol–cloud interactions which also comprises rapid adjustments. These adjustments are essentially the responses of cloud fraction and liquid water path to ΔNd,ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (Nd) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large scale (hundreds of kilometres) ΔNd,ant remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and vertical wind and by droplet sink processes. These operate at scales on the order of 10s of metres at which only localized observations are available and at which no approach exists yet to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are three key uncertainties in determining ΔNd,ant, namely the quantification (i) of the cloud-active aerosol – the cloud condensation nuclei concentrations (CCN) at or above cloud base –, (ii) of Nd, as well as (iii) the statistical approach for inferring the sensitivity of Nd to aerosol particles from the satellite data. A fourth uncertainty
Gryspeerdt E, Smith T, O'Keefe E, et al., Impact of ship emission controls recorded by cloud properties
<jats:p> &lt;p&gt;The impact of aerosols on cloud properties is one of the largest uncertainties in the anthropogenic forcing of the climate system. As large, isolated sources of aerosol, ships provide the ideal opportunity to investigate aerosol-cloud interactions. However, their use for quantifying the aerosol impact on clouds has been limited by a lack on information on the aerosol perturbation generated by the ship.&lt;/p&gt;&lt;p&gt;In this work, satellite cloud observations are combined with ship emissions estimated from transponder data. Using over 17,000 shiptracks during the implementation of emission controls, the central role of sulphate aerosol in controlling shiptrack properties is demonstrated. Meteorological factors are shown to have a significant impact on shiptrack formation, particularly cloud-top relative humidity. Accounting for this meteorological variation, this work also demonstrates the potential for satellite retrievals of ship sulphate emissions, providing a pathway to the use of cloud observations for monitoring air pollution.&lt;/p&gt; </jats:p>
Sourdeval O, Gryspeerdt E, Mülmenstädt J, et al., Satellite-based estimate of the climate forcing due to aerosol - ice cloud interactions
<jats:p> &lt;p&gt;Substantial efforts have been led over the last decades to improve our understanding of the interactions between clouds and anthropogenic aerosols (aci). The effective radiative forcing associated with these interactions (ERFaci), which combines the radiative forcing (i.e. Twomey effect) and cloud adjustments, still constitutes a large part of our current uncertainties on climate predictions.&lt;/p&gt;&lt;p&gt;Important progress has been made in the assessment of ERFaci for liquid clouds, partly due to advances in the joint use of satellite and modelling data to tackle this problem. More particularly, the retrieval of the droplet number concentration from satellite remote sensing - a property closely related to droplet nucleation processes - has been extremely helpful to better quantify ERFaci. However, similar estimations for ice clouds have for long suffered from a lack of observational constraint on the ice crystal number concentration (N&lt;sub&gt;i&lt;/sub&gt;), a challenging task due to the high complexity of the physical processes associated with the nucleation and growth of ice crystals. However, a novel long-term global dataset of N&lt;sub&gt;i&lt;/sub&gt; from active satellite measurements has recently (DARDAR-Nice) opened the door to new observation-based estimates of RFaci for ice clouds.&lt;/p&gt;&lt;p&gt;This study investigates aerosol - ice clouds interactions using N&lt;sub&gt;i&lt;/sub&gt; profiles from the DARDAR-Nice product together with collocated aerosol information from the Copernicus Atmospheric Monitoring Service (CAMS) reanalyses. A multitude of cloud regimes, subdivided into seasonal and regional bins, are considered in order to disentangle meteorological effects from the aci signature. First results of joint-histograms between N&am
Gryspeerdt E, Stier P, Partridge DG, Satellite observations of cloud regime development: the role of aerosol processes, Publisher: Copernicus GmbH
<jats:p>Abstract. Many different interactions between aerosols and clouds have been postulated based on correlations between satellite retrieved aerosol and cloud properties. Previous studies highlighted the importance of meteorological covariability to the observed correlations. In this work, we make use of multiple temporally-spaced satellite retrievals to observe the development of cloud regimes. The observation of cloud regime development allows us to account for the influences of cloud fraction (CF) and meteorological factors on the aerosol retrieval. By accounting for the aerosol index (AI)-CF relationship we reduce the influence of meteorological correlations compared to "snapshot" studies, finding that simple correlations overestimate any aerosol effect on CF by at least three times. We find an increased occurrence of transitions into the stratocumulus regime over ocean with increases in MODIS Aerosol Index (AI), consistent with the hypothesis that aerosols increase the stratocumulus persistence. We also observe an increase in transitions into the deep convective regime over land, consistent with the aerosol invigoration hypothesis. We find changes in the transitions from the shallow cumulus in different aerosol environments. The strength of these changes is strongly dependent on Low Troposphere Static Stability and 10 m windspeed, but less so on other meteorological factors. Whilst we have reduced the error due to meteorological and CF effects on the aerosol retrieval, meteorological covariation with the cloud and aerosol properties is harder to remove, so these results likely represent an upper bound on the effect of aerosols on cloud development and CF. </jats:p>
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