Continuous Single-Column Model Evaluation at a Permanent Meteorological Supersite

Uncertainties in numerical predictions of weather and climate are often linked to the representation of unresolved processes that act relatively quickly compared to the resolved general circulation. These processes include turbulence, convection, clouds, and radiation. Single-column model (SCM) simulation of idealized cases and the subsequent evaluation against large-eddy simulation (LES) results has become an often used and relied on method to obtain insight at process level into the behavior of such parameterization schemes; benefits of SCM simulation are the enhanced model transparency and the high computational efficiency. Although this approach has achieved demonstrable success, some shortcomings have been identified; among these, i) the statistical significance and relevance of single idealized case studies might be questioned and ii) the use of observational datasets has been relatively limited. A recently initiated project named the Royal Netherlands Meteorological Institute (KNMI) Parameterization Testbed (KPT) is part of a general move toward a more statistically significant process-level evaluation, with the purpose of optimizing the identification of problems in general circulation models that are related to parameterization schemes. The main strategy of KPT is to apply continuous long-term SCM simulation and LES at various permanent meteorological sites, in combination with comprehensive evaluation against observations at multiple time scales. We argue that this strategy enables the reproduction of typical long-term mean behavior of fast physics in large-scale models, but it still preserves the benefits of single-case studies (such as model transparency). This facilitates the tracing and understanding of errors in parameterization schemes, which should eventually lead to a reduction of related uncertainties in numerical predictions of weather and climate

Overlap Statistics of Cumuliform Boundary-Layer Cloud Fields in Large-Eddy Simulations

Overlap statistics of cumuliform boundary-layer clouds are studied using large-eddy simulations at high resolutions. The cloud overlap is found to be highly inefficient, due to the typical irregularity of cumuliform clouds over a wide range of scales. The detection of such inefficient overlap is enabled in this study by i) applying fine enough discretizations and ii) by limiting the analysis to exclusively cumuliform boundary-layer cloud fields. It is argued that these two factors explain the differences with some previous studies on cloud overlap. In contrast, good agreement exists with previously reported observations of cloud overlap as derived from lidar measurements of liquid water clouds at small cloud covers. Various candidate functional forms are fitted to the results, suggesting that an inverse linear function is most successful in reproducing the observed behavior. The sensitivity of cloud overlap to various aspects is assessed, reporting a minimal or non-systematic dependence on discretization and vertical wind-shear, as opposed to a strong case-dependence, the latter probably reflecting differences in the cloud size distribution. Finally, calculations with an offline radiation scheme suggest that accounting for the inefficient overlap in cumuliform cloud fields in a general circulation model can change the top-of-atmosphere short-wave cloud radiative forcing by −20 to −40 W m−2, depending on vertical discretization. This corresponds to about 50 to 100% of the typical values in areas of persistent shallow cumulus, respectively

Overlap Statistics of Cumuliform Boundary-Layer Cloud Fields in Large-Eddy Simulations

Overlap statistics of cumuliform boundary-layer clouds are studied using large-eddy simulations at high resolutions. The cloud overlap is found to be highly inefficient, due to the typical irregularity of cumuliform clouds over a wide range of scales. The detection of such inefficient overlap is enabled in this study by i) applying fine enough discretizations and ii) by limiting the analysis to exclusively cumuliform boundary-layer cloud fields. It is argued that these two factors explain the differences with some previous studies on cloud overlap. In contrast, good agreement exists with previously reported observations of cloud overlap as derived from lidar measurements of liquid water clouds at small cloud covers. Various candidate functional forms are fitted to the results, suggesting that an inverse linear function is most successful in reproducing the observed behavior. The sensitivity of cloud overlap to various aspects is assessed, reporting a minimal or non-systematic dependence on discretization and vertical wind-shear, as opposed to a strong case-dependence, the latter probably reflecting differences in the cloud size distribution. Finally, calculations with an offline radiation scheme suggest that accounting for the inefficient overlap in cumuliform cloud fields in a general circulation model can change the top-of-atmosphere short-wave cloud radiative forcing by −20 to −40 W m−2, depending on vertical discretization. This corresponds to about 50 to 100% of the typical values in areas of persistent shallow cumulus, respectively

Shallow Cumulus Cloud Fields Are Optically Thicker When They Are More Clustered

Shallow trade cumuli over subtropical oceans are a persistent source of uncertainty in climate projections. Mesoscale organization of trade cumulus clouds has been shown to influence their cloud radiative effect (CRE) through cloud cover. We investigate whether organization can explain CRE variability independently of cloud cover variability. By analyzing satellite observations and high-resolution simulations, we show that increased clustering leads to geometrically thicker clouds with larger domain-averaged liquid water paths, smaller cloud droplets, and consequently, larger cloud optical depths. The relationships between these variables are shaped by the mixture of deep cloud cores and shallower interstitial clouds or anvils that characterize cloud organization. Eliminating cloud cover effects, more clustered clouds reflect up to 20 W/m$^2$ more instantaneous shortwave radiation back to space

Creating a reusable cross-disciplinary multi-scale and multi-physics framework: From AMUSE to OMUSE and beyond

Here, we describe our efforts to create a multi-scale and multi-physics framework that can be retargeted across different disciplines. Currently we have implemented our approach in the astrophysical domain, for which we developed AMUSE (github.com/amusecode/amuse ), and generalized this to the oceanographic and climate sciences, which led to the development of OMUSE (bitbucket.org/omuse ). The objective of this paper is to document the design choices that led to the successful implementation of these frameworks as well as the future challenges in applying this approach to other domains

Formulation of the Dutch Atmospheric Large-Eddy Simulation (DALES) and Overview of Its Applications

The current version of the Dutch Atmospheric Large-Eddy Simulation (DALES) is presented. DALES is a large-eddy simulation code designed for studies of the physics of the atmospheric boundary layer, including convective and stable boundary layers as well as cloudy boundary layers. In addition, DALES can be used for studies of more specific cases, such as flow over sloping or heterogeneous terrain, and dispersion of inert and chemically active species. This paper contains an extensive description of the physical and numerical formulation of the code, and gives an overview of its applications and accomplishments in recent years

Clouds, circulation and climate sensitivity

Fundamental puzzles of climate science remain unsolved because of our limited understanding of how clouds, circulation and climate interact. One example is our inability to provide robust assessments of future global and regional climate changes. However, ongoing advances in our capacity to observe, simulate and conceptualize the climate system now make it possible to fill gaps in our knowledge. We argue that progress can be accelerated by focusing research on a handful of important scientific questions that have become tractable as a result of recent advances. We propose four such questions below; they involve understanding the role of cloud feedbacks and convective organization in climate, and the factors that control the position, the strength and the variability of the tropical rain belts and the extratropical storm tracks