Climate processes

Abstract:

Abstract. Evaluation of the aerosol schemes in current climate models is dependent upon the available observational data. In-situ observations from flight campaigns can provide valuable data about the vertical distribution of aerosol that is difficult to obtain from satellite or ground-based platforms, although they are localised in space and time. Using single-particle soot-photometer (SP2) measurements from the HIAPER Pole-to-Pole Observations (HIPPO) campaign, which consists of many vertical profiles over a large region of the Pacific, we evaluate the meridional and vertical distribution of black carbon (BC) aerosol simulated by the HadGEM3–UKCA and ECHAM5–HAM2 models. Both models show a similar pattern of overestimating the BC column burden compared to that derived from the observations, in many areas by an order of magnitude. However, by sampling the simulated BC mass mixing ratio along the flight track and comparing to the observations, we show that this discrepancy has a rather different vertical structure in the two models: in HadGEM3–UKCA the discrepancy is dominated by excess aerosol in the tropical upper troposphere, while in ECHAM5–HAM2 areas of discrepancy are spread across many different latitudes and altitudes. Using this methodology, we conduct sensitivity tests on two specific elements of the models: biomass-burning emissions and scavenging by convective precipitation. We show that, by coupling the convective scavenging more tightly with convective transport, both the column burden and vertical distribution of BC in HadGEM3–UKCA are much improved with respect to the observations, with a substantial and statistically significant increase in correlation – this demonstrates the importance of a realistic representation of this process. In contrast, updating from GFED2 to GFED3.1 biomass-burning emissions makes a more modest improvement in both models, which is not statistically significant. By comparing our results with a more traditional approach using regional- and monthly-mean vertical profile curves, we show that the point-by-point analysis allows the model improvements to be demonstrated more clearly. We also demonstrate the important role that nudged simulations (where the large-scale model dynamics are continuously relaxed towards a reanalysis) can play in this type of evaluation, allowing statistically significant differences between configurations of the aerosol scheme to be seen where the differences between the corresponding free-running simulations would not be significant.

Abstract:

Meteorological covariation 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 en- hanced 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, a description of extratropical cyclones, based on the relative vorticity of the storm and position in the storm domain, is used to analyse MODerate resolution Imaging Spectroradiometer (MODIS) retrieved τ, fc and Ttop data. This storm-centric description is capable of explaining fc–τrelationships, although the relationships explained represent only a small component of the relationships observed in the MODIS data. This storm-centric approach produces no statistically robust explanation for Ttop–τ relationships, suggesting that large-scale synoptic conditions in the mid-latitudes do not drive Ttop–τ relationships. The primary causes for observed cloud–aerosol relationships are likely to be other factors such as retrieval errors, local meteorology or aerosol–cloud interactions.