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Maren Brast, Vera Schemann, and Roel A. J. Neggers

Abstract

In this study, the scale adaptivity of a new parameterization scheme for shallow cumulus clouds in the gray zone is investigated. The eddy diffusivity/multiple mass flux [ED(MF)n] scheme is a bin-macrophysics scheme in which subgrid transport is formulated in terms of discretized size densities. While scale adaptivity in the ED component is achieved using a pragmatic blending approach, the MF component is filtered such that only the transport by plumes smaller than the grid size is maintained. For testing, ED(MF)n is implemented into a large-eddy simulation (LES) model, replacing the original subgrid scheme for turbulent transport. LES thus plays the role of a nonhydrostatic testing ground, which can be run at different resolutions to study the behavior of the parameterization scheme in the boundary layer gray zone. In this range, convective cumulus clouds are partially resolved. The authors find that for quasi-equilibrium marine subtropical conditions at high resolutions, the clouds and the turbulent transport are predominantly resolved by the LES. This partitioning changes toward coarser resolutions, with the representation of shallow cumulus clouds gradually becoming completely carried by the ED(MF)n. The way the partitioning changes with grid spacing matches the behavior diagnosed in coarse-grained LES fields, suggesting that some scale adaptivity is captured. Sensitivity studies show that the scale adaptivity of the ED closure is important and that the location of the gray zone is found to be moderately sensitive to some model constants.

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Vera Schemann, Bjorn Stevens, Verena Grützun, and Johannes Quaas

Abstract

The scale dependency of variance of total water mixing ratio is explored by analyzing data from a general circulation model (GCM), a numerical weather prediction model (NWP), and large-eddy simulations (LESs). For clarification, direct numerical simulation (DNS) data are additionally included, but the focus is placed on defining a general scaling behavior for scales ranging from global down to cloud resolving. For this, appropriate power-law exponents are determined by calculating and approximating the power density spectrum. The large-scale models (GCM and NWP) show a consistent scaling with a power-law exponent of approximately −2. For the high-resolution LESs, the slope of the power density spectrum shows evidence of being somewhat steeper, although the estimates are more uncertain. Also the transition between resolved and parameterized scales in a current GCM is investigated. Neither a spectral gap nor a strong scale break is found, but a weak scale break at high wavenumbers cannot be excluded. The evaluation of the parameterized total water variance of a state-of-the-art statistical scheme shows that the scale dependency is underestimated by this parameterization. This study and the discovered general scaling behavior emphasize the need for a development of scale-dependent parameterizations.

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Thirza W. van Laar, Vera Schemann, and Roel A. J. Neggers

Abstract

The diurnal dependence of cumulus cloud size distributions over land is investigated by means of an ensemble of large-eddy simulations (LESs). A total of 146 days of transient continental shallow cumulus are selected and simulated, reflecting a low midday maximum of total cloud cover, weak synoptic forcing, and the absence of strong surface precipitation. The LESs are semi-idealized, forced by large-scale model output but using an interactive surface. This multitude of cases covers a large parameter space of environmental conditions, which is necessary for identifying any diurnal dependencies in cloud size distributions. A power-law exponential function is found to describe the shape of the cloud size distributions for these days well, with the exponential component capturing the departure from power-law scaling at the larger cloud sizes. To assess what controls the largest cloud size in the distribution, the correlation coefficients between the maximum cloud size and various candidate variables reflecting the boundary layer state are computed. The strongest correlation is found between total cloud cover and maximum cloud size. Studying the size density of the cloud area revealed that larger clouds contribute most to a larger total cloud cover, and not the smaller ones. Besides cloud cover, cloud-base and cloud-top height are also found to weakly correlate with the maximum cloud size, suggesting that the classic idea of deeper boundary layers accommodating larger convective thermals still holds for shallow cumulus. Sensitivity tests reveal that the results are only minimally affected by the representation of microphysics and the output resolution.

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Tobias Marke, Susanne Crewell, Vera Schemann, Jan H. Schween, and Minttu Tuononen

Abstract

Low-level-jet (LLJ) periods are investigated by exploiting a long-term record of ground-based remote sensing Doppler wind lidar measurements supported by tower observations and surface flux measurements at the Jülich Observatory for Cloud Evolution (JOYCE), a midlatitude site in western Germany. LLJs were found 13% of the time during continuous observations over more than 4 yr. The climatological behavior of the LLJs shows a prevailing nighttime appearance of the jets, with a median height of 375 m and a median wind speed of 8.8 m s−1 at the jet nose. Significant turbulence below the jet nose only occurs for high bulk wind shear, which is an important parameter for describing the turbulent characteristics of the jets. The numerous LLJs (16% of all jets) in the range of wind-turbine rotor heights below 200 m demonstrate the importance of LLJs and the associated intermittent turbulence for wind-energy applications. Also, a decrease in surface fluxes and an accumulation of carbon dioxide are observed if LLJs are present. A comprehensive analysis of an LLJ case shows the influence of the surrounding topography, dominated by an open pit mine and a 200-m-high hill, on the wind observed at JOYCE. High-resolution large-eddy simulations that complement the observations show that the spatial distribution of the wind field exhibits variations connected with the orographic flow depending on the wind direction, causing high variability in the long-term measurements of the vertical velocity.

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Florian Rauser, Mohammad Alqadi, Steve Arowolo, Noël Baker, Joel Bedard, Erik Behrens, Nilay Dogulu, Lucas Gatti Domingues, Ariane Frassoni, Julia Keller, Sarah Kirkpatrick, Gaby Langendijk, Masoumeh Mirsafa, Salauddin Mohammad, Ann Kristin Naumann, Marisol Osman, Kevin Reed, Marion Rothmüller, Vera Schemann, Awnesh Singh, Sebastian Sonntag, Fiona Tummon, Dike Victor, Marcelino Q. Villafuerte, Jakub P. Walawender, and Modathir Zaroug

Abstract

The exigencies of the global community toward Earth system science will increase in the future as the human population, economies, and the human footprint on the planet continue to grow. This growth, combined with intensifying urbanization, will inevitably exert increasing pressure on all ecosystem services. A unified interdisciplinary approach to Earth system science is required that can address this challenge, integrate technical demands and long-term visions, and reconcile user demands with scientific feasibility. Together with the research arms of the World Meteorological Organization, the Young Earth System Scientists community has gathered early-career scientists from around the world to initiate a discussion about frontiers of Earth system science. To provide optimal information for society, Earth system science has to provide a comprehensive understanding of the physical processes that drive the Earth system and anthropogenic influences. This understanding will be reflected in seamless prediction systems for environmental processes that are robust and instructive to local users on all scales. Such prediction systems require improved physical process understanding, more high-resolution global observations, and advanced modeling capability, as well as high-performance computing on unprecedented scales. At the same time, the robustness and usability of such prediction systems also depend on deepening our understanding of the entire Earth system and improved communication between end users and researchers. Earth system science is the fundamental baseline for understanding the Earth’s capacity to accommodate humanity, and it provides a means to have a rational discussion about the consequences and limits of anthropogenic influence on Earth. Without its progress, truly sustainable development will be impossible.

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