15 research outputs found
Assessment of aerosol–cloud–radiation correlations in satellite observations, climate models and reanalysis
Representing large-scale co-variability between variables related to aerosols, clouds and radiation is one of many aspects of agreement with observations desirable for a climate model. In this study such relations are investigated in terms of temporal correlations on monthly mean scale, to identify points of agreement and disagreement with observations. Ten regions with different meteorological characteristics and aerosol signatures are studied and correlation matrices for the selected regions offer an overview of model ability to represent present day climate variability. Global climate models with different levels of detail and sophistication in their representation of aerosols and clouds are compared with satellite observations and reanalysis assimilating meteorological fields as well as aerosol optical depth from observations. One example of how the correlation comparison can guide model evaluation and development is the often studied relation between cloud droplet number and water content. Reanalysis, with no parameterized aerosol–cloud coupling, shows weaker correlations than observations, indicating that microphysical couplings between cloud droplet number and water content are not negligible for the co-variations emerging on larger scale. These observed correlations are, however, not in agreement with those expected from dominance of the underlying microphysical aerosol–cloud couplings. For instance, negative correlations in subtropical stratocumulus regions show that suppression of precipitation and subsequent increase in water content due to aerosol is not a dominating process on this scale. Only in one of the studied models are cloud dynamics able to overcome the parameterized dependence of rain formation on droplet number concentration, and negative correlations in the stratocumulus regions are reproduced
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Small global-mean cooling due to volcanic radiative forcing
In both the observational record and atmosphere-ocean general circulation model (AOGCM) simulations of the last ∼∼ 150 years, short-lived negative radiative forcing due to volcanic aerosol, following explosive eruptions, causes sudden global-mean cooling of up to ∼∼ 0.3 K. This is about five times smaller than expected from the transient climate response parameter (TCRP, K of global-mean surface air temperature change per W m−2 of radiative forcing increase) evaluated under atmospheric CO2 concentration increasing at 1 % yr−1. Using the step model (Good et al. in Geophys Res Lett 38:L01703, 2011. doi:10.1029/2010GL045208), we confirm the previous finding (Held et al. in J Clim 23:2418–2427, 2010. doi:10.1175/2009JCLI3466.1) that the main reason for the discrepancy is the damping of the response to short-lived forcing by the thermal inertia of the upper ocean. Although the step model includes this effect, it still overestimates the volcanic cooling simulated by AOGCMs by about 60 %. We show that this remaining discrepancy can be explained by the magnitude of the volcanic forcing, which may be smaller in AOGCMs (by 30 % for the HadCM3 AOGCM) than in off-line calculations that do not account for rapid cloud adjustment, and the climate sensitivity parameter, which may be smaller than for increasing CO2 (40 % smaller than for 4 × CO2 in HadCM3)
Semiconducting Metal Oxide Based Sensors for Selective Gas Pollutant Detection
A review of some papers published in the last fifty years that focus on the semiconducting metal oxide (SMO) based sensors for the selective and sensitive detection of various environmental pollutants is presented