Climate processes

Abstract:

<jats:p>Abstract. In this paper, we present the implementation and evaluation of the aerosol microphysics module SALSA2.0 in the framework of the aerosol–chemistry–climate model ECHAM-HAMMOZ. It is an alternative microphysics module to the default modal microphysics scheme M7 in ECHAM-HAMMOZ. The SALSA2.0 implementation within ECHAM-HAMMOZ is evaluated against observations of aerosol optical properties, aerosol mass, and size distributions, comparing also to the skill of the M7 implementation. The largest differences between the implementation of SALSA2.0 and M7 are in the methods used for calculating microphysical processes, i.e., nucleation, condensation, coagulation, and hydration. These differences in the microphysics are reflected in the results so that the largest differences between SALSA2.0 and M7 are evident over regions where the aerosol size distribution is heavily modified by the microphysical processing of aerosol particles. Such regions are, for example, highly polluted regions and regions strongly affected by biomass burning. In addition, in a simulation of the 1991 Mt. Pinatubo eruption in which a stratospheric sulfate plume was formed, the global burden and the effective radii of the stratospheric aerosol are very different in SALSA2.0 and M7. While SALSA2.0 was able to reproduce the observed time evolution of the global burden of sulfate and the effective radii of stratospheric aerosol, M7 strongly overestimates the removal of coarse stratospheric particles and thus underestimates the effective radius of stratospheric aerosol. As the mode widths of M7 have been optimized for the troposphere and were not designed to represent stratospheric aerosol, the ability of M7 to simulate the volcano plume was improved by modifying the mode widths, decreasing the standard deviations of the accumulation and coarse modes from 1.59 and 2.0, respectively, to 1.2 similar to what was observed after the Mt. Pinatubo eruption. Overall, SALSA2.0 shows promise in improving the aerosol description of ECHAM-HAMMOZ and can be further improved by implementing methods for aerosol processes that are more suitable for the sectional method, e.g., size-dependent emissions for aerosol species and size-resolved wet deposition. </jats:p>

Abstract:

The radiative forcing of anthropogenic aerosol remains a key uncertainty in the understanding of climate change. This study quantifies the model spread in aerosol forcing associated with (i) variability internal to the atmosphere and (ii) differences in the model representation of weather. We do so by performing ensembles of atmosphere-only simulations with four state-of-the-art Earth system models, three of which will be used in the sixth coupled model inter-comparison project (CMIP6, Eyring et al., 2016). In those models we reduce the complexity of the anthropogenic aerosol by prescribing the same annually-repeating patterns of the anthropogenic aerosol optical properties and associated effects on the cloud reflectivity. We quantify a comparably small model spread in the long-term averaged ERF compared to the overall possible range in annual ERF estimates associated with model-internal variability. This implies that identifying the true model spread in ERF associated with differences in the representation of meteorological processes and natural aerosol requires averaging over a sufficiently large number of annual estimates. We characterize the model diversity in clouds and use satellite products as benchmarks. Despite major inter-model differences in natural aerosol and clouds, all models show only a small change in the global-mean ERF due to the substantial change in the global anthropogenic aerosol distribution between the mid-1970s and mid-2000s, the ensemble mean ERF being −0.47Wm−2 for the mid-1970s and −0.51Wm−2 for the mid-2000s. This result suggests that inter-comparing ERF changes between two periods rather than absolute magnitudes relative to pre-industrial might provide a more stringent test for a model's ability for representing climate evolutions.

Abstract:

Abstract. The impact of aerosols on ice- and mixed-phase processes in deep convective clouds remains highly uncertain and the wide range of interacting microphysical processes are still poorly understood. To understand these processes, we analyse diagnostic output of all individual microphysical process rates for two cloud microphysics schemes in the Weather and Research Forecasting model (WRF). We investigate the response of individual processes to changes in aerosol conditions and the propagation of perturbations through the microphysics all the way to the macrophysical development of the convective clouds. We perform simulations for two different cases of idealised supercells using two double-moment bulk microphysics schemes and a bin microphysics scheme. We use simulations with a comprehensive range of values for cloud droplet number concentration (CDNC) and cloud condensation nuclei (CCN) concentration as a proxy for aerosol effects on convective clouds. We have developed a new cloud tracking algorithm to analyse the morphology and time evolution of individually tracked convective cells in the simulations and their response to the aerosol perturbations. This analysis confirms an expected decrease in warm rain formation processes due to autoconversion and accretion for polluted conditions. The height at which the freezing occurs increases with increasing CDNC. However, there is no evidence of a significant increase in the total amount of latent heat release from freezing and riming. The cloud mass and the altitude of the cloud centre of gravity show contrasting responses to changes in proxies for aerosol number concentration between the different microphysics schemes.

Abstract:

The cloud droplet number concentration (Nd) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol‐cloud interactions. Current standard satellite retrievals do not operationally provide Nd, but it can be inferred from retrievals of cloud optical depth (τc) cloud droplet effective radius (re) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78 % is inferred for pixel‐level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1o×1o regions the uncertainty is reduced to 54 % assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in‐situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. Nd uncertainty is dominated by errors in re and, therefore, improvements in re retrievals would greatly improve the quality of the Nd retrievals. Recommendations are made for how this might be achieved. Some existing Nd datasets are compared and discussed, and best practices for the use of Nd data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative Nd estimates are also considered. Firstly, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and secondly, approaches using high‐quality ground‐based observations are examined.