Community Intercomparison Suite (CIS) v1.4.0: a tool for intercomparing models and observations

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

Exploring Satellite-Derived Relationships between Cloud Droplet Number Concentration and Liquid Water Path Using a Large-Domain Large-Eddy Simulation

Important aspects of the adjustments to aerosol-cloud interactions can be examined using the relationship between cloud droplet number concentration (Nd) and liquid water path (LWP). Specifically, this relation can constrain the role of aerosols in leading to thicker or thinner clouds in response to adjustment mechanisms. This study investigates the satellite retrieved relationship between Nd and LWP for a selected case of mid-latitude continental clouds using high-resolution Large-eddy simulations (LES) over a large domain in weather prediction mode. Since the satellite retrieval uses the adiabatic assumption to derive the Nd, we have also considered adiabatic Nd (NAd) from the LES model for comparison. The joint histogram analysis shows that the NAd-LWP relationship in the LES model and the satellite is in approximate agreement. In both cases, the peak conditional probability (CP) is confined to lower NAd and LWP; the corresponding mean LWP (LWP) shows a weak relation with NAd. The CP shows a larger spread at higher NAd (>50 cm–3), and the LWP increases non-monotonically with increasing NAd in both cases. Nevertheless, both lack the negative NAd-LWP relationship at higher NAd, the entrainment effect on cloud droplets. In contrast, the model simulated Nd-LWP clearly illustrates a much more nonlinear (an increase in LWP with increasing Nd and a decrease in LWP at higher Nd) relationship, which clearly depicts the cloud lifetime and the entrainment effect. Additionally, our analysis demonstrates a regime dependency (marine and continental) in the NAd-LWP relation from the satellite retrievals. Comparing local vs large-scale statistics from satellite data shows that continental clouds exhibit only a weak nonlinear NAd-LWP relationship. Hence a regime-based Nd-LWP analysis is even more relevant when it comes to warm continental clouds and their comparison to satellite retrievals

Opportunistic experiments to constrain aerosol effective radiative forcing

Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide “opportunistic experiments” (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change

Opportunistic experiments to constrain aerosol effective radiative forcing

Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide “opportunistic experiments” (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change

Aerosol-cloud-precipitation interactions

Aerosols are thought to have a large effect on the climate, especially through their interactions with clouds. The magnitude and in some cases the sign of aerosol effects on cloud and precipitation are highly uncertain. Part of the uncertainty comes from the multiple competing effects that aerosols have been proposed to have on cloud properties. In addition, covariation of clouds and aerosol properties with changing meteorological conditions has the ability to generate spurious correlations between cloud and aerosol properties. This work presents a new way to investigate aerosol-cloud-precipitation interactions while accounting for the influence of meteorology on cloud and aerosol. The clouds are separated into cloud regimes, which have similar retrieved cloud properties, to investigate the regime dependence of aerosol-cloud-precipitation interactions. The strong aerosol optical depth (AOD)- cloud fraction (CF) correlation is shown to have the ability to generate spurious correlations. The AOD-CF correlation is accounted for by investigating the frequency of transitions between cloud regimes in different aerosol environments. This time-dependent analysis is also extended to investigate the development of precipitation from each of the regimes as a function of their aerosol environment. A modification of the regime transition frequencies consistent with an increase in stratocumulus persistence over ocean is found with increasing AI (aerosol index). Increases in transitions into the deep convective regime and in the precipitation rate consistent with an aerosol invigoration effect are also found over land. Comparisons to model output suggest that a large fraction of the observed effect on the stratocumulus persistence may be due to aerosol indirect effects. The model is not able to reproduce the observed effects on convective cloud, most likely due to the lack of parametrised effects of aerosol on convection. The magnitude of these effects is considerably smaller than correlations found by previous studies, emphasising the importance of meteorological covariation on observed aerosol-cloud-precipitation interactions.</p

Aerosol-cloud-precipitation interactions

Aerosols are thought to have a large effect on the climate, especially through their interactions with clouds. The magnitude and in some cases the sign of aerosol effects on cloud and precipitation are highly uncertain. Part of the uncertainty comes from the multiple competing effects that aerosols have been proposed to have on cloud properties. In addition, covariation of clouds and aerosol properties with changing meteorological conditions has the ability to generate spurious correlations between cloud and aerosol properties. This work presents a new way to investigate aerosol-cloud-precipitation interactions while accounting for the influence of meteorology on cloud and aerosol. The clouds are separated into cloud regimes, which have similar retrieved cloud properties, to investigate the regime dependence of aerosol-cloud-precipitation interactions. The strong aerosol optical depth (AOD)- cloud fraction (CF) correlation is shown to have the ability to generate spurious correlations. The AOD-CF correlation is accounted for by investigating the frequency of transitions between cloud regimes in different aerosol environments. This time-dependent analysis is also extended to investigate the development of precipitation from each of the regimes as a function of their aerosol environment. A modification of the regime transition frequencies consistent with an increase in stratocumulus persistence over ocean is found with increasing AI (aerosol index). Increases in transitions into the deep convective regime and in the precipitation rate consistent with an aerosol invigoration effect are also found over land. Comparisons to model output suggest that a large fraction of the observed effect on the stratocumulus persistence may be due to aerosol indirect effects. The model is not able to reproduce the observed effects on convective cloud, most likely due to the lack of parametrised effects of aerosol on convection. The magnitude of these effects is considerably smaller than correlations found by previous studies, emphasising the importance of meteorological covariation on observed aerosol-cloud-precipitation interactions.This thesis is not currently available in ORA

Analysis of polarimetric satellite measurements suggests stronger cooling due to aerosol-cloud interactions

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 corresponding 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). Here 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 between −0.84 and −1.72 Wm 2) is more than a factor 2 stronger than the IPCC estimate that includes also other aerosol induced changes in cloud properties

Investigating the controls on the ice crystal number concentration using satellite observations

International audienceThe ice crystal number concentration (Ni) is a key radiative and microphysical property of ice clouds. However, due to sparse in-situ measurements of ice cloud properties, the controls on the Ni have remained difficult to determine from observations. As more advanced treatments of ice clouds are included in global models, it is becoming increasingly important to develop strong observational constraints on these ice cloud processes. In this work, we use the DARDAR-LIM retrieval of Ni to examine the controls on Ni at a global scale. Using a classification for cloud type and reanalysis data to determine the meteorological state, the effects of temperature, a proxy for in-cloud updraught and aerosol concentrations are investigated. Along with a strong impact of temperature and updraught on the Ni, variations in the cloud top Ni consistent with both homogeneous and heterogeneous nucleation are observed. Comparisons with reanalysis aerosol and a proxy for the occurrence of ice nucleating particles show a varying role of aerosols based on the aerosol and cloud properties. This dataset provides a new way to investigate the properties of ice clouds and their controls at a global scale. The results presented here increase our confidence in the retrieved Ni and provide a basis for further studies into mixed phase and ice cloud processes