Climate processes

Abstract:

Meteorological conditions may drive relationships between aerosol and cloud-related properties. It is important to account for the meteorological contribution to observed cloud-aerosol relationships in order to improve understanding of aerosol-cloud-climate interactions. A new method of investigating the contribution of meteorological covariation to observed cloud-aerosol relationships is introduced. Other studies have investigated the contribution of local meteorology to cloud-aerosol relationships. In this paper, a complimentary large-scale view is presented. Extratropical cyclones have been previously shown to affect satellite-retrieved aerosol optical depth (τ), due to enhanced emission of sea salt and sea surface brightness artefacts in regions of higher wind speed. Extratropical cyclones have also been shown to affect cloud-related properties such as cloud fraction (fc) and cloud top temperature (Ttop). Therefore, it seems plausible to hypothesise that extratropical cyclones may drive relationships between cloud-related properties and τ. In this paper, this hypothesis is investigated for extratropical cyclones, henceforth referred to as storms, over the Atlantic Ocean. MODerate resolution Imaging Spectroradiometer (MODIS) retrieved τ, fc and T top data are analysed using a storm-centric coordinate system centred on extratropical cyclones which have been tracked using European Centre for Medium Range Weather Forecasts (ECMWF) reanalysis 850 hPa relative vorticity data. The tracked relative vorticity (ω) is used as a measure of storm strength, while position in the storm-centric domain is used to account for storm structure. Relationships between the cloud-related properties and τ are measured by calculating regression slopes and correlations. The fc-τ relationships are positive, while the Ttop-τ relationships are negative. By shuffling the pairing of the cloud and τ data at each location in the storm-centric domain and within narrow ω bins, the contribution of storm strength and storm structure to the observed relationships can be investigated. It is found that storm strength and storm structure can explain only a small component of the relationships observed in the MODIS data. The primary causes for observed cloud-aerosol relationships are likely to be other factors such as retrieval errors, local meteorology or aerosol-cloud interactions. © 2013 Author(s).

Abstract:

Black carbon (BC) aerosol loadings were measured during the High-performance Instrumented Airborne Platform for Environmental Research Pole-to-Pole Observations (HIPPO) campaign above the remote Pacific from 85°N to 67°S. Over 700 vertical profiles extending from near the surface to max ∼14 km altitude were obtained with a single-particle soot photometer between early 2009 and mid-2011. The data provides a climatology of BC in the remote regions that reveals gradients of BC concentration reflecting global-scale transport and removal of pollution. BC is identified as a sensitive tracer of extratropical mixing into the lower tropical tropopause layer and trends toward surprisingly uniform loadings in the lower stratosphere of ∼1 ng/kg. The climatology is compared to predictions from the AeroCom global model intercomparison initiative. The AeroCom model suite overestimates loads in the upper troposphere/lower stratosphere (∼10×) more severely than at lower altitudes (∼3×), with bias roughly independent of season or geographic location; these results indicate that it overestimates BC lifetime. Key Points A BC climatology is provided for the remote Pacific and Polar regions AeroCom overestimates remote BC with strong altitude dependence Extratropical mixing into the TTL is estimated from BC latitudinal gradients ©2013 The Authors. Geophysical Research Letters published by Wiley on behalf of the American Geophysical Union.

Abstract:

<jats:p>Abstract. The global distribution of cloud condensation nuclei (CCN) is the fundamental quantity that determines how changes in aerosols affect climate through changes in cloud drop concentrations, cloud albedo and precipitation. Aerosol-cloud interaction effects are a major source of uncertainty in climate models so it is important to quantify the sources of uncertainty and thereby direct research efforts. However, the computational expense of global aerosol models has prevented a full statistical analysis of their outputs. Here we perform a variance-based analysis of a global 3-D aerosol microphysics model to quantify the magnitude and leading causes of parametric uncertainty in model-estimated present-day CCN concentrations. Twenty-eight model parameters covering essentially all important aerosol processes, emissions and representation of aerosol size distributions were defined based on expert elicitation. An uncertainty analysis was then performed based on a Monte Carlo-type sampling of an emulator built for each monthly-mean model grid cell from an ensemble of 168 one-year model simulations covering the uncertainty space of the 28 parameters. The standard deviation around the mean CCN varies globally between about ±30% of the mean over some marine regions to ±40–100% over most land areas and high latitudes. The results imply that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol-cloud effects on climate. Variance decomposition enables the importance of the parameters for CCN uncertainty to be quantified and ranked from local to global scales. Among the most important contributors to CCN uncertainty are the sizes of emitted primary particles, including carbonaceous combustion particles from wildfires, biomass burning and fossil fuel use, as well as sulphate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulphur emissions. Aerosol emission-related parameters dominate the uncertainty close to sources, while uncertainty in aerosol microphysical processes becomes increasingly important in remote regions, being dominated by deposition and aerosol sulphate formation during cloud-processing. Most of the 28 parameters are important for CCN uncertainty somewhere on the globe. The results lead to several recommendations for research that would result in improved modelling of cloud-active aerosol on a global scale. </jats:p>

Abstract:

This study uses the UK Chemistry and Aerosols community model (UKCA) within the Hadley Centre Global Environmental Model (HadGEM3), coupled for the first time to an explicit aerosol activation parameterisation, and hence known as UKCA-Activate. We explore the range of uncertainty in estimates of the indirect aerosol effects attributable to the choice of parameterisation of the subgrid-scale variability of vertical velocity in HadGEM-UKCA. Results of simulations demonstrate that the use of a characteristic vertical velocity cannot replicate results derived with a distribution of vertical velocities, and is to be discouraged in GCMs. This study focuses on the effect of the variance (σw2) of a Gaussian pdf (probability density function) of vertical velocity. Fixed values of σw (spanning the range measured in situ by nine flight campaigns found in the literature) and a configuration in which σw depends on turbulent kinetic energy are tested. Results from the mid-range fixed σw and TKE-based configurations both compare well with observed vertical velocity distributions and cloud droplet number concentrations. The radiative flux perturbation due to the total effects of anthropogenic aerosol is estimated at −1.9 W m−2 with σw = 0.1 m s−1, −2.1 W m−2 with σw derived from TKE, −2.25 W m−2 with σw = 0.4 m s−1, and −2.3 W m−2 with σw = 0.7 m s−1. The breadth of this range is 0.4 W m−2, which is comparable to a substantial fraction of the total diversity of current aerosol forcing estimates. Reducing the uncertainty in the parameterisation of σw would therefore be an important step towards reducing the uncertainty in estimates of the indirect aerosol effects. Detailed examination of regional radiative flux perturbations reveals that aerosol microphysics can be responsible for some climate-relevant radiative effects, highlighting the importance of including microphysical aerosol processes in GCMs.