What determines the distribution of shallow convective mass flux through cloud base?

The distribution of cloud-base mass flux is studied using large-eddy simulations (LES) of two reference cases, one representing conditions over the tropical ocean, and another one representing mid-latitude conditions over land. To examine what sets the difference between the two distributions, nine additional LES cases are set up as variations of the two reference cases. We find that the total surface heat flux and its changes over the diurnal cycle do not influence the distribution shape. The latter is also not determined by the level of organization in the cloud field. It is instead determined by the ratio of the surface sensible heat flux to the latent heat flux, the Bowen ratio $B$. $B$ sets the thermodynamic efficiency of the moist convective heat cycle, which determines the portion of the total surface heat flux that can be transformed into mechanical work of convection against mechanical dissipation. The thermodynamic moist heat cycle sets the average mass flux per cloud $\langle m \rangle$, and through $\langle m \rangle$ it also controls the shape of the distribution. An expression for $\langle m \rangle$ is derived based on the moist convective heat cycle and is evaluated against LES. This expression can be used in shallow cumulus parameterizations as a physical constraint on the mass flux distribution. The similarity between the mass flux and the cloud area distributions indicate that $B$ also has a role in shaping the cloud area distribution, which could explain its different shapes and slopes observed in previous studies.Comment: submitted to J. Atmos. Sci., revise

A virtual centre at the interface of basic and applied weather and climate research

The Hans-Ertel Centre for Weather Research is a network of German universities, research institutes and the German Weather Service (Deutscher Wetterdienst, DWD). It has been established to trigger and intensify basic research and education on weather forecasting and climate monitoring. The performed research ranges from nowcasting and short-term weather forecasting to convective-scale data assimilation, the development of parameterizations for numerical weather prediction models, climate monitoring and the communication and use of forecast information. Scientific findings from the network contribute to better understanding of the life-cycle of shallow and deep convection, representation of uncertainty in ensemble systems, effects of unresolved variability, regional climate variability, perception of forecasts and vulnerability of society. Concrete developments within the research network include dual observation-microphysics composites, satellite forward operators, tools to estimate observation impact, cloud and precipitation system tracking algorithms, large-eddy-simulations, a regional reanalysis and a probabilistic forecast test product. Within three years, the network has triggered a number of activities that include the training and education of young scientists besides the centre's core objective of complementing DWD's internal research with relevant basic research at universities and research institutes. The long term goal is to develop a self-sustaining research network that continues the close collaboration with DWD and the national and international research community

QUANTITATIVE PRECIPITATION FORECASTING IN MOUNTAINOUS REGIONS - PUSHED AHEAD BY MAP

The improvement of Quantitative Precipitation Forecast (QPF) in mountainous area was the central supporting objective of the MAP project P1 devoted to the study of orographic precipitation. This paper attempts to review the main MAP-related achievements towards QPF improvement and to highlight the MAP-impact for developing QPF research and operational strategies

Tropical cyclones in global storm-resolving models

Recent progress in computing and model development has initiated the era of global storm-resolving modeling and with it the potential to transform weather and climate prediction. Within the general theme of vetting this new class of models, the present study evaluates nine global-storm resolving models in their ability to simulate tropical cyclones (TCs). Results show that, broadly speaking, the models produce realistic TCs and remove longstanding issues known from global models such as the deficiency to accurately simulate TC intensity. However, TCs are strongly affected by model formulation, and all models suffer from unique biases regarding the number of TCs, intensity, size, and structure. Some models simulated TCs better than others, but no single model was superior in every way. The overall results indicate that global storm-resolving models are able to open a new chapter in TC prediction, but they need to be improved to unleash their full potential

The Added Value of Large-Eddy and Storm-Resolving Models for Simulating Clouds and Precipitation

More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve convective storms (storm-resolving for short), the vertical velocity variance becomes resolved and a better physical basis is achieved for representing clouds and precipitation. Similarly to past studies we found an improved representation of precipitation at kilometer scales, as compared to models with parameterized convection. The main precipitation features (location, diurnal cycle and spatial propagation) are well captured already at kilometer scales, and refining resolution to hectometer scales does not substantially change the simulations in these respects. It does, however, lead to a reduction in the precipitation on the time-scales considered – most notably over the ocean in the tropics. Changes in the distribution of precipitation, with less frequent extremes are also found in simulations incorporating hectometer scales. Hectometer scales appear to be more important for the representation of clouds, and make it possible to capture many important aspects of the cloud field, from the vertical distribution of cloud cover, to the distribution of cloud sizes, and to the diel (daily) cycle. Qualitative improvements, particularly in the ability to differentiate cumulus from stratiform clouds, are seen when one reduces the grid spacing from kilometer to hectometer scales. At the hectometer scale new challenges arise, but the similarity of observed and simulated scales, and the more direct connection between the circulation and the unconstrained degrees of freedom make these challenges less daunting. This quality, combined with already improved simulation as compared to more parameterized models, underpins our conviction that the use and further development of storm-resolving models offers exciting opportunities for advancing understanding of climate and climate change

Clouds and convective self-aggregation in a multi-model ensemble of radiative-convective equilibrium simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique amongst intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than un-aggregated simulations

Impact of Diurnal Warm Layers on Atmospheric Convection

AbstractThis manuscript presents a study of oceanic diurnal warm layers (DWLs) in kilometer‐scale global coupled simulations and their impact on atmospheric convection in the tropics. With the implementation of thin vertical levels in the ocean, DWLs are directly resolved, and sea surface temperature (SST) fluctuations of up to several Kelvin appear in regions with low wind and high solar radiation. The increase of SST during the day causes an abrupt afternoon increase of atmospheric moisture due to enhanced latent heat flux (LHF), followed by an increase in cloud cover (CC) and cloud liquid water (CLW). However, although the diurnal SST amplitude is even exaggerated in comparison to reanalysis, this effect only lasts for 5–6 hr and leads to an absolute difference of 1% for CC and 0.01 kg m−2 for CLW. This can be explained by the fact that the low wind over the SST anomalies dampens their potential effect on the LHF and hence clouds. All in all, the impact of DWLs on convective CC is found to be negligible in the tropical mean.Plain Language Summary: The diurnal fluctuations of sea surface temperature (SST) have been extensively studied for the last decades, but the assessment of the importance of this phenomenon for atmospheric convection on the global scale has come within reach only very recently, thanks to the development of simulations with a horizontal resolution of O(1 km). In this manuscript we show that we can indeed observe an impact of SST fluctuations on moisture in the atmosphere. However, the impact on the amount of clouds in the tropics is found to be short‐lived and its magnitude negligible on average.Key Points: diurnal warm layers (DWLs) increase atmospheric moisture The increase of cloud cover (CC) following the formation of a DWL is immediate and only lasts for several hours The magnitude of the CC increase is small and has no discernible influence on the global mean Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659https://gotm.net/https://hdl.handle.net/21.11116/0000-000C-1447-

A Relationship Between ITCZ Organization and Subtropical Humidity

Motivated by the results of idealized studies on the self-aggregation of convection, we investigate a potential relationship between the degree of organization of the Intertropical Convergence Zone (ITCZ) and humidity based on reanalysis data. We focus on the Atlantic ITCZ and use the number of long convergence lines occurring per month to define the degree of organization. The latter shows a weak enhancement during June to August (JJA) and a large interannual variability. On an interannual time scale and particularly during JJA, a relationship exists between organization and humidity: Years with more organized ITCZs are associated with a moister ITCZ region and drier subtropics. Even though we cannot demonstrate any causality and cannot rule out the presence of another agent, we show that these moisture anomalies are not incompatible with an effect of organization. We also note that the annual cycle in sea surface temperature (SST) gradient may contribute to the intra-annual variability in organization

2013: Preconditioning deep convection with cumulus congestus

ABSTRACT Recent studies have pushed forward the idea that congestus clouds, through their moistening of the atmosphere, could promote deep convection. On the other hand, older studies have tended to relate convective initiation to the large-scale forcing. These two views are here contrasted by performing a time-scale analysis. The analysis combines ship observations, large-eddy simulations, and 1 month of brightness temperature measurements with a focus on the tropical Atlantic and adjacent land areas. The time-scale analysis suggests that previous work may have overstated the importance of congestus moistening in the preconditioning of deep convection. It is found that cumuli congestus transition very rapidly to deep convection, in 2 h over land and 4 h over ocean. This is much faster than the time needed (10 h and longer) by congestus clouds to sufficiently moisten the atmosphere. Moreover, the majority of congestus clouds seem unable to grow into cumulonimbus and the probability of transition does not increase with increasing congestus lifetime (i.e., more moistening). Finally, the presence of cumuli congestus over a given region generally does not enhance the likelihood for deep convection development, either with respect to other regions or to clear-sky conditions. Hence, the results do not support the view of an atmosphere slowly deepening by local moistening, but rather, they may be interpreted as reminiscent of an atmosphere marked by violent and sudden outbursts of convection forced by dynamical effects. This also implies that moisture convergence is more important than local surface fluxes to trigger deep convection over a certain region