Inflexibilidad de EE.UU. y repercusiones de la Perestroika

This article presents a study based on an LES of gas-aerosol partitioning of nitrate in a convective boundary layer. We have shown that when gas-aerosol partition-ing occurs at a timescale comparable to the convective timescale, a structure of updrafts with reduced nitrate mixing ratios and downdrafts with enhanced nitrate mixing ratios arises. These features may appear in observations as rapid fluctua-tions in nitrate mixing ratios. Also, apparent deposition fluxes of aerosol nitrate, which have been observed by measurement studies, have been reproduced by our model.

Our model results show that the horizontal variance of the nitrate mixing ratio and the nitrate flux are maximum when τ_p≈ ¹₂· τ_tand decline for both short and long partitioning timescales. This variance and flux peak at around one third of the boundary layer height, slightly depending on τ_p. For short partitioning timescales, the skewness of the nitrate spatial distribution is predicted to be negative due to the strong negative correlation with the vertical velocity. For longer partitioning timescales, the nitrate skewness increases towards zero. Future observations of these statistical properties of the nitrate mixing ratio may provide information about the partitioning timescale, a quantity that is difficult to measure directly.

At colder conditions, the interaction between turbulence and nitrate reparti-tioning remains qualitatively similar as long as the turbulent properties of the boundary layer remain similar. However, the magnitudes of the nitrate variability and flux are lower at colder conditions, because the phase equilibria at the sur-face and in the upper boundary layer differ to a smaller extent than at warmer conditions.

Acknowledgments

We would like to thank the NCF (Foundation of national computer facilities) for providing the ability to run DALES on the supercomputer Huygens (project SH-060-12). This work is supported by the EU FP7 IP PEGASOS (FP7-ENV-2010/265148).

6

The Generic Aerosol Optics

Toolbox: an aerosol optics module for any atmospheric model

This chapter is in preparation for submission to Geoscientific Model Development Discussions

This paper presents the Generic Aerosol Optics Toolbox (GAOT), a software pack-age for the calculation of the optical properties of homogeneous spherical aerosols.

GAOT includes a lookup table generator that calculates optical properties of pre-defined aerosol modes and stores the results in lookup tables. Usage of such lookup table saves a lot of computational time compared to online calculations.

These lookup tables can be used in any atmospheric model that represents the aerosol composition and the aerosol size distribution. The toolbox also contains coupling code, which takes care of the communication between the model and the lookup table. This code can easily be adapted for any kind of atmospheric model.

The calculations have been evaluated and reproduce the observed characteristic size-dependence of the optical activity of aerosols. Furthermore, the formulas of Rayleigh scattering are reproduced by the calculations of this toolbox. The tool-box has been used in a study with the regional climate model RACMO2 coupled to the regional transport model LOTOS-EUROS. This study concluded that the reduction of aerosol emissions compared to the 1990s is responsible for a tempera-ture increment up to 0.4^◦C in Europe at ground level for the simulated year from May 2008 to May 2009.

6.1 Introduction

Aerosols influence the climate by altering the radiation budget of the earth through scattering and absorption of solar radiation (Hess et al., 1998; Haywood and Boucher, 2000; IPCC, 2007). Over polluted continental regions, the direct forcing of sulphate alone can be as large as that of the combined greenhouse gases, but opposite in sign (e.g. Charlson et al., 1992; Kiehl and Briegleb, 1993). In the last decade, the influence of a number of other aerosol components, like organic carbon, black carbon and mineral dust, on the radiation budget has also been shown (IPCC, 2007). The aerosol effect has masked the real climate sensitivity towards an increase in greenhouse gases to an unknown extent (Anderson et al., 2003). Aerosols are involved in many climate feedback loops, both positive and negative, of which many are related to the interaction between aerosols and radia-tion (Carslaw et al., 2010). Indirect aerosol-climate feedback loops usually involve clouds. However, increased diffuse radiation due to scattering aerosols may also influence photosynthesis and thereby indirectly the climate system (Mercado et al., 2009). In short, to understand the climate impact of aerosols, it is necessary to understand and adequately parameterise the aerosol optical properties in climate models.

The interaction between aerosols and radiation is also explored to obtain in-formation on aerosols through remote sensing. Aerosol optical properties are mea-sured through ground-based networks (e.g. AERONET; Holben et al., 2001) and satellite-based sensors (e.g. MODIS; Justice et al., 1998). The obtained remote-sensing data provide information for the entire atmospheric column. Information on the entire column is of great importance to evaluate chemistry transport and climate models as they complement traditional ground-based monitoring networks such as EMEP (Lazaridis et al., 2002; EMEP, 2008). Moreover, assimilation of

satellite products into models may be a cost-effective method to better monitor aerosol distributions across large regions (Sekiyama et al., 2010). For improved use of remote-sensing data, it is also important to understand the relationship between the aerosol physical and chemical characteristics on the one side, and their optical properties on the other side.

The relationship between the chemical composition and the scattering coeffi-cient of aerosols has been investigated with simultaneous measurements of these two aspects. White and Roberts (1977) indicated that sulphate and nitrate are the most optically active aerosol species. The relationship between the aerosol optical activity and the aerosol size was not yet mentioned in that study. In ten Brink et al. (1997), it was stated that in the Netherlands, nitrate and sulphate are the dominant (anthropogenic) aerosol species in the size range of maximum light-scattering (0.4 – 1.0 µm diameter). This statement confirmed the findings of White and Roberts (1977), adding the relationship to the aerosol size.

Because of the sensitivity of the aerosol optical properties to the aerosol size distribution, the aerosol optical properties can only be modelled adequately if the aerosol size distribution is properly represented. This implies that the size range of aerosol emissions should be specified in emission inventories. Furthermore, the size-dependence of aerosol processes (e.g. sedimentation) should be taken into account in model parameterisations. Such a size-resolved representation of aerosols (e.g.

M7; Vignati et al., 2004) is already commonly used in models, so implementation of a proper calculation of the aerosol optical properties is possible in many models.

Modelling teams developing CTMs or GCMs are largely oriented at other pro-cess descriptions than the aerosol optical properties and therefore high-level ex-pertise on this issue is often lacking. Many models include parameterisations for aerosol optical properties, but to a different degree of complexity. For instance, a very simple implementation is a fixed extinction coefficient per bulk mass per aerosol component. Parameterisations of complicated aerosol processes are often tuned to match observations. Arbitrary tuning of processes remains often poorly documented and may include compensations for discrepancies in other processes.

A poor agreement among models with respect to aerosol parameters was shown in a model intercomparison study (Textor et al., 2006), indicating that models are difficult to compare. Parameterisations for aerosol optical properties are particu-larly hard to compare due to the strong non-linear character of aerosol optics. To derive aerosol optical properties from modelled aerosol concentrations, a common toolbox has been developed. This toolbox facilitates many models and improves their description, enhances model comparability and quality.

This article presents the Generic Aerosol Optics Toolbox (GAOT). The theory governing the aerosol optical properties is described in Sect. 6.2. Section 6.3 is a brief description of the toolbox. For a more detailed description, we refer to the supplemented documentation. A few applications in large-scale model are highlighted in Sect. 6.4. We will finalise the article with a summary in Sect. 6.5.