2012, Ditas, F., Shaw, R.A., Siebert, H., Simmel, M., Wehner, B., Wiedensohler, A.

This work presents a unique combination of aerosol, cloud microphysical, thermodynamic and turbulence variables to characterize supersaturation fluctuations in a turbulent marine stratocumulus (SC) layer. The analysis is based on observations with the helicopter-borne measurement platform ACTOS and a detailed cloud microphysical parcel model following three different approaches: (1) From the comparison of aerosol number size distributions inside and below the SC layer, the number of activated particles is calculated as 435±87 cm−3 and compares well with the observed median droplet number concentration of Nd = 464 cm−3. Furthermore, a 50% activation diameter of Dp50≈115 nm was derived, which was linked to a critical supersaturation Scrit of 0.16% via Köhler theory. From the shape of the fraction of activated particles, we estimated a standard deviation of supersaturation fluctuations of σS' = 0.09%. (2) These estimates are compared to more direct thermodynamic observations at cloud base. Therefore, supersaturation fluctuations (S') are calculated based on highly-resolved thermodynamic data showing a standard deviation of S' ranging within 0.1%≤σS'≤0.3 %. (3) The sensitivity of the supersaturation on observed vertical wind velocity fluctuations is investigated with the help of a detailed cloud microphysical model. These results show highest fluctuations of S' with σS'=0.1% at cloud base and a decreasing σS' with increasing liquid water content and droplet number concentration. All three approaches are independent of each other and vary only within a factor of about two.

2018, Costabel, Stephan, Weidner, Christoph, Müller-Petke, Mike, Houben, Georg

The capability of nuclear magnetic resonance (NMR) relaxometry to characterise hydraulic properties of iron-oxide-coated sand and gravel was evaluated in a laboratory study. Past studies have shown that the presence of paramagnetic iron oxides and large pores in coarse sand and gravel disturbs the otherwise linear relationship between relaxation time and pore size. Consequently, the commonly applied empirical approaches fail when deriving hydraulic quantities from NMR parameters. Recent research demonstrates that higher relaxation modes must be taken into account to relate the size of a large pore to its NMR relaxation behaviour in the presence of significant paramagnetic impurities at its pore wall. We performed NMR relaxation experiments with water-saturated natural and reworked sands and gravels, coated with natural and synthetic ferric oxides (goethite, ferrihydrite), and show that the impact of the higher relaxation modes increases significantly with increasing iron content. Since the investigated materials exhibit narrow pore size distributions, and can thus be described by a virtual bundle of capillaries with identical apparent pore radius, recently presented inversion approaches allow for estimation of a unique solution yielding the apparent capillary radius from the NMR data. We found the NMR-based apparent radii to correspond well to the effective hydraulic radii estimated from the grain size distributions of the samples for the entire range of observed iron contents. Consequently, they can be used to estimate the hydraulic conductivity using the well-known Kozeny–Carman equation without any calibration that is otherwise necessary when predicting hydraulic conductivities from NMR data. Our future research will focus on the development of relaxation time models that consider pore size distributions. Furthermore, we plan to establish a measurement system based on borehole NMR for localising iron clogging and controlling its remediation in the gravel pack of groundwater wells.