Talent on the move: creative human capital migration patterns in UK

The last decade has seen an increasing number of contributions, from both academics and policy makers, focusing on the role of higher education in developing human capital (Charles, 2003; Cramphorn & Woodlhouse, 1999; Preston & Hammond, 2006) and hence contributing to local and regional growth (Faggian & McCann, 2006; Mathur, 1999; Moretti, 2004). Within this broader literature, the role played by more ‘scientific’ types of human capital, such as STEM (science, technology, engineering, and mathematics) graduates and science parks (Bozeman, Dietz, & Gaughan, 2001; Linderlöf & Löfsten, 2004; Löfsten & Lindelöf, 2005), has also been explored. Little attention has been paid so far, to the role played by more ‘creative’ types of human capital. This chapter aims at filling this gap, in light of the central role that the term ‘creative’ took in policy and academic discourses in the UK (Comunian & Faggian, 2011; Comunian & Gilmore, 2015; DCMS, 2006; Powell, 2007; Universities UK, 2010).

Constraining the aerosol influence on cloud fraction

Aerosol-cloud interactions have the potential to modify many different cloud properties. There is significant uncertainty in the strength of these aerosol-cloud interactions in analyses of observational data, partly due to the difficulty in separating aerosol effects on clouds from correlations generated by local meteorology. The relationship between aerosol and cloud fraction (CF) is particularly important to determine, due to the strong correlation of CF to other cloud properties and its large impact on radiation. It has also been one of the hardest to quantify from satellites due to the strong meteorological covariations involved. This work presents a new method to analyze the relationship between aerosol optical depth (AOD) and CF. By including information about the cloud droplet number concentration (CDNC), the impact of the meteorological covariations is significantly reduced. This method shows that much of the AOD-CF correlation is explained by relationships other than that mediated by CDNC. By accounting for these, the strength of the global mean AOD-CF relationship is reduced by around 80%. This suggests that the majority of the AOD-CF relationship is due to meteorological covariations, especially in the shallow cumulus regime. Requiring CDNC to mediate the AOD-CF relationship implies an effective anthropogenic radiative forcing from an aerosol influence on liquid CF of −0.48 W m−2 (−0.1 to −0.64 W m−2), although some uncertainty remains due to possible biases in the CDNC retrievals in broken cloud scenes.

Observational evidence for a negative shortwave cloud feedback in middle to high latitudes

Exploiting the observed robust relationships between temperature and optical depth in extratropical clouds, we calculate the shortwave cloud feedback from historical data, by regressing observed and modeled cloud property histograms onto local temperature in middle to high southern latitudes. In this region, all CMIP5 models and observational data sets predict a negative cloud feedback, mainly driven by optical thickening. Between 45° and 60°S, the mean observed shortwave feedback (−0.91 ± 0.82 W m−2 K−1, relative to local rather than global mean warming) is very close to the multimodel mean feedback in RCP8.5 (−0.98 W m−2 K−1), despite differences in the meridional structure. In models, historical temperature-cloud property relationships reliably predict the forced RCP8.5 response. Because simple theory predicts this optical thickening with warming, and cloud amount changes are relatively small, we conclude that the shortwave cloud feedback is very likely negative in the real world at middle to high latitudes.