Philip Stier

Abstract:

We use data from simulations performed with the global aerosol-climate model ECHAM5-HAM to test the proposition that shipping emissions do not have a statistically significant effect on water clouds over tropical oceans on climate scales put forward in earlier satellite based work. We analyse a total of four sensitivity experiments, three of which employ global shipping emissions and one simulation which only employs shipping emissions in the mid-Atlantic Ocean. To ensure comparability to earlier results from observations, we sample the model data using a method previously applied to satellite data aimed at separating ‘clean’ from ‘polluted’ oceanic regions based on i) the location of main shipping routes and ii) wind direction at 10 m above sea level. The model simulations run with realistic present-day shipping emissions show changes in the lower tropospheric aerosol population attributable to shipping emissions across major shipping corridors over tropical oceans. However, we find the resulting effect on cloud properties to be non-distinguishable from natural gradients and variability, that is, gradients of cloud properties sampled across major shipping corridors over tropical oceans are very similar among those simulations. Our results therefore compare well to the earlier findings from satellite observations. Substantial changes of the aerosol population and cloud properties only occur when shipping emissions are increased 10-fold. We find that aerosol advection and rapid aerosol removal from the atmosphere play an important role in determining the non-significant response in i) column integrated aerosol properties and ii) cloud microphysical properties in the realistic simulations. Additionally, high variability and infrequent occurrence of simulated low-level clouds over tropical oceans in ECHAM5-HAM limit the development of aerosol indirect effects because i) in-cloud production of sulphate from ship-emitted sulphuric species via aqueous oxidation pathways is very low and ii) a possible observational signal is blurred out by high variability in simulated clouds. Our results highlight i) the importance of adequately accounting for atmospheric background conditions when determining climate forcings from observations and ii) the effectiveness of buffering mechanisms on micro- and macroscopic scales which limit the emergence of such climate forcings.

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).