ALBERT

Description: Tertiary rift-related intraplate basanites from the Batain basin of northeastern Oman have low SiO2 (〈 45.6 wt.%), high MgO (〉 9.73 wt.%) and moderate to high Cr and Ni contents (Cr 〉 261 ppm, Ni 〉 181 ppm), representing near primary magmas that have undergone fractionation of mainly olivine and magnetite. Rare earth element systematics and p-T estimates suggest that the alkaline rocks are generated by different degrees of partial melting (4–13%) of a spinel-peridotite lithospheric mantle containing residual amphibole. The alkaline rocks show restricted variations of 87Sr/86Sr and 143Nd/144Nd ranging from 0.70340 to 0.70405 and 0.51275 to 0.51284, respectively. Variations in Pb isotopes (206Pb/204Pb: 18.59–18.82, 207Pb/204Pb: 15.54–15.56, 208Pb/204Pb: 38.65–38.98) of the alkaline rocks fall in the range of most OIB. Trace element constraints together with Sr–Nd–Pb isotope composition indicate that assimilation through crustal material did not affect the lavas. Instead, trace element variations can be explained by melting of a lithospheric mantle source that was metasomatized by an OIB-type magma that was accumulated at the base of the lithosphere sometimes in the past. Although only an area of less than 1000 km2 was sampled, magmatic activity lasted for about 5.5 Ma with a virtually continuous activity from 40.7 ± 0.7 to 35.3 ± 0.6 Ma. During this period magma composition was nearly constant, i.e. the degree of melting and the nature of the tapped source did not change significantly over time.

Description: Interactions between radiation and clouds are a source of significant uncertainty in current numerical weather prediction (NWP) models. With increased resolution previously neglected effects like the horizontal propagation of radiation will become more important. Future operational models will have to incorporate more realistic description of physical processes and remain computationally efficient.Our approach for tackling these problems in the thermal spectral range is to combine a traditional twostream solver with treatment of subgrid-scale cloud overlap (Črnivec and Mayer, 2019) with the Neighbouring Column Approximation (NCA) model (Klinger and Mayer, 2019), which parametrizes horizontal photon transport between adjacent grid-cells. In addition to a generalized vertical cloud overlap the model introduces horizontal overlap between neighbouring clouds. Thereby the hybrid model includes for the first time both subgrid-scale and grid-scale 3D radiative effects at a reasonable additional computational cost.The performance of the model is evaluated using benchmark Monte-Carlo model MYSTIC (Mayer, 2009) calculations of realistic cloud scenes derived from LES simulations. In addition we assess the benefits of the hybrid model in comparison with classical one-dimensional solvers.

Description: Despite the importance of the Atlantic Meridional Overturning Circulation (AMOC) to the climate, direct measurements are sparse. Before the onset of the current century, many reconstructions of the AMOC rely on linear relationships to the more readily observed surface properties of the Atlantic rather than the temporal sparsely observed subsurface. Sustained records of the AMOC by monitoring arrays are available for almost two decades. However, due to the large number of experiments performed with Earth System Models (ESM), we have large datasets at our disposal that allow us to apply machine learning methods to investigate how robust short sustained observational records can be reconstructed and determine the relative importance of surface and subsurface information for the reconstruction.We train different linear and non-linear machine learning models to infer the AMOC from sea-water properties at different depths, using large ensemble simulations with the Max Planck Institute ESM. During training, we retain consecutive periods of our data for the model evaluation resembling the timescale of our observational record. Subsequently, we investigate the validity of these reconstructions with explainable Machine Learning techniques that map the relevance of the reconstruction back to the model input. We identify regions in the surface and subsurface ocean which appear to be relevant for the reconstruction of the AMOC and compare the quality of the reconstructions using either only surface or only subsurface information. We establish the quality of AMOC reconstructions based on only linear relationships and how robust these reconstructions are to different retained periods.

Description: We recently developed a novel retrieval of cloud top heights and particle size distributions from polarized 2D observations by our airborne specMACS instrument (Kölling et al. 2019; Pörtge et al., 2022). The cloud height is derived by a stereographic approach and effective droplet radius and width of the size distribution are derived from the shape of the cloudbow. Validation of such methods with independent observations is difficult because in-situ observations with sufficient co-location in space and time are rarely available. An alternative is the use of radiative transfer simulations based on the output of high-resolution cloud models where not only the observations but also the "truth" is known. Realistic 3D radiative transfer simulations of specMACS measurements were performed with the 3D radiative transport modelMYSTIC (Mayer, 2009). Overflights over a field of shallow cumuli based on high-resolutionLES simulations carried out with the PALM model were simulated. The clouds develop realistically as the aircraft passed overhead. It is shown that the cloud top heights differ by less than 40m from the model truth. The uncertainty of the retrieved effective radius was shown to be a few micron for complex droplet size distributions within the field-of-view of the instrument. The consideration of the mean wind by the retrieval was shown to be crucial for the accuracy of the results. The temporal evolution of the clouds adds some uncertainty which, in contrast to the effect of the wind cannot be corrected.

Description: The increasing resolution of numerical weather prediction models makes 3D radiative effects more and more important. However, 3D radiative transfer solvers are still computationally expensive, largely preventing their use in operational weather forecasting. To address this issue, we present a new, “dynamic” 3D radiative transfer model that is based on the TenStream solver (Jakub and Mayer, 2015) and delivers a significant speed-up utilizing two main concepts. First, radiation in this model is not calculated from scratch every time the scheme is called, but uses a time-stepping scheme to update the radiative field based on the result from the previous radiation time step. Secondly, the model is based on incomplete solves, performing just the first few steps towards convergence every time it is called. Applied, these two concepts alone allow to produce radiative flux and heating rate fields close to the original TenStream results at dramatically increased speed. In addition, we use an optimized wavelength sampling that allows to noticeably reduce the number of spectral intervals to calculate integrated shortwave and longwave heating rates without a significant loss in precision. Together, these approaches allow to accelerate 3D radiative transfer towards the speed of currently employed 1D solvers. To demonstrate this, we apply the new solver to a precomputed shallow cumulus cloud time series and compare it to both a traditional 1D delta-Eddington solver, the original TenStream solver, as well as to a benchmark solution provided by the 3D Monte Carlo solver MYSTIC (Mayer, 2009).

Description: Cloud radiative heating (CRH) can affect the dynamics and predictability of extratropical cyclones. For an idealized cyclone, we have shown that the impact can be understood from the modulation of latent heating by CRH and subsequently through changes in the large-scale flow. However, CRH is uncertain in models, suggesting that the cloud radiative modulation of latent heating may vary with different representations of CRH and may affect model predictions of extratropical cyclones. Therefore, we quantify CRH uncertainties for an idealized cyclone by performing large eddy simulations and offline radiative transfer calculations. Several factors contributing to CRH uncertainty, such as cloud sub-grid variability, 3-D cloud radiative effects, and ice-optical parameterization, are quantified in different regions of the cyclone. Our results indicate that ice-optical parameterization and unresolved horizontal cloud inhomogeneity are the two factors contributing most to the CRH differences. On the other hand, 3-D radiative effects are comparatively smaller, especially for deep stratiform clouds within the cyclone. Our analysis shows that for a cyclone simulated at a horizontal resolution of 2.5 km, the CRH uncertainty due to unresolved horizontal cloud inhomogeneity is in the same range as the CRH uncertainty due to ice-optical parameterizations. This suggests that improving the ice-optical parameterization may be more important and efficient than increasing the horizontal resolution of the model. Future work should address to what extent changes in CRH due to different ice-optical parameterizations alter the magnitude of latent heating within the warm conveyor belt of the cyclone and ultimately the cyclone dynamics.