The 2dF Galaxy Redshift Survey: luminosity dependence of galaxy clustering

We investigate the dependence of the strength of galaxy clustering on intrinsic luminosity using the Anglo-Australian two degree field galaxy redshift survey (2dFGRS). The 2dFGRS is over an order of magnitude larger than previous redshift surveys used to address this issue. We measure the projected two-point correlation function of galaxies in a series of volume-limited samples. The projected correlation function is free from any distortion of the clustering pattern induced by peculiar motions and is well described by a power law in pair separation over the range     . The clustering of     galaxies in real space is well-fitted by a correlation length     and power-law slope     . The clustering amplitude increases slowly with absolute magnitude for galaxies fainter than M *, but rises more strongly at higher luminosities. At low luminosities, our results agree with measurements from the Southern Sky Redshift Survey 2 by Benoist et al. However, we find a weaker dependence of clustering strength on luminosity at the highest luminosities. The correlation function amplitude increases by a factor of 4.0 between     and −22.5, and the most luminous galaxies are 3.0 times more strongly clustered than L * galaxies. The power-law slope of the correlation function shows remarkably little variation for samples spanning a factor of 20 in luminosity. Our measurements are in very good agreement with the predictions of the hierarchical galaxy formation models of Benson et al.     

The effect of particle size distributions on the dynamics of falling precipitation zones

A simplistic study of the dynamics of a falling particle ensemble is described. It shows the effect created by the introduction of particle size distributions on precipitation onset and duration and compares it to the case where air motions or pressure fields triggered by the particles are neglected. The assumption of homogeneously sized raindrops seems adequate if precipitation rates and total rainfall are considered. As soon as timing is involved a more refined treatment is required.     

Are estimated costs of stringent mitigation biased?

We take issue with the claim by Tavoni and Tol (Clim Chang 100:769–778, 2010) that reviews of the macroeconomic costs of achieving the 2 °C climate target have been affected by selection bias and have underestimated the costs. Although many more cost estimates are available in the literature, they have restricted their survey to the data in the EMF22 study, with a limited set of model solutions for the 2 °C target. They have applied the methodology of observational meta-analysis inappropriately to policy meta-analysis, where the number of results is often very small and the basis for imputing a statistical distribution does not usually exist. They have mixed direct costs with net costs in terms of %GDP. Their method of “correcting” for missing data with (high) costs of stringent mitigation could equally be applied to correcting the data for omission of mitigation options such as biomass energy with carbon capture so reducing the cost estimates. And finally they implicitly assume that the same policy combinations and mitigation options are applied for all climate scenarios, when more stringent scenarios may require more stringent policies and options, such as regulation or BECCS. The conclusion from the literature is more appropriately that the costs are highly uncertain, that they can equally be positive or negative (gains) and that models which fail to solve for stringent mitigations are not fit for purpose.