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

Cloud-resolving time-lagged rainfall ensemble forecasts for typhoons in Taiwan: Examples of Saola (2012), Soulik (2013), and Soudelor (2015)

As high resolution is required for numerical models to adequately simulate convective storms and thus produce quantitative precipitation forecasts (QPFs), a time-lagged ensemble out to 8 days at 6-h intervals using a 2.5-km cloud-resolving model is applied to three rainy typhoons that made landfall in Taiwan in recent years: Saola (2012), Soulik (2013), and Soudelor (2015), following an earlier study.For the three typhoons where the worst-case rainfall scenario turned out to happen in Taiwan, the system was able to predict this particular scenario with high accuracy (with a rainfall pattern similar to the observed) at an earliest lead time of about 162 h, 79 h, and 164 h before landfall, and thus provided key information for early preparation. Within the short range (≤72 h), as the predicted tracks converged toward the best track, high-quality QPFs were consistently generated starting at about 36 h, 55 h, and 80 h prior to landfall, respectively, with derived probabilities in good to excellent agreement with the observations, even at extreme thresholds (≥500 and 700 mm in 24 h). Leading up to the track convergence, the probabilities across various rainfall thresholds increased markedly, so their time evolution also provided useful information for decision makers and hazard preparation.The underlying reason behind our results is the high predictability of topographic rainfall in Taiwan produced by the typhoon circulation, which cannot be properly captured without high model resolution. Thus, without compromising the resolution, we demonstrate the advantages of the time-lagged strategy for ensemble forecasting, assuming QPF as the key target forecast parameter

EUREC⁴A: A Field Campaign to Elucidate the Couplings Between Clouds, Convection and Circulation

International audienceTrade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. Numerical models represent this interplay in diverse ways, which translates into different responses of trade-cumuli to climate perturbations. Climate models predict that the area covered by shallow cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of trade-cumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air–sea interactions and convective organization

The multiple activities of BMPs during spinal cord development

Bone morphogenetic proteins (BMPs) are one of the main classes of multi-faceted secreted factors that drive vertebrate development. A growing body of evidence indicates that BMPs contribute to the formation of the central nervous system throughout its development, from the initial shaping of the neural primordium to the generation and maturation of the different cell types that form the functional adult nervous tissue. In this review, we focus on the multiple activities of BMPs during spinal cord development, paying particular attention to recent results that highlight the complexity of BMP signaling during this process. These findings emphasize the unique capacity of these signals to mediate various functions in the same tissue throughout development, recruiting diverse effectors and strategies to instruct their target cells. © 2013 European Union.Work in EM’s laboratory was supported by Grants BFU2010-18959 and CSD2007-00008.Peer Reviewe

A Higher Level Classification of All Living Organisms

We present a consensus classification of life to embrace the more than 1.6 million species already provided by more than 3,000 taxonomists' expert opinions in a unified and coherent, hierarchically ranked system known as the Catalogue of Life (CoL). The intent of this collaborative effort is to provide a hierarchical classification serving not only the needs of the CoL's database providers but also the diverse public-domain user community, most of whom are familiar with the Linnaean conceptual system of ordering taxon relationships. This classification is neither phylogenetic nor evolutionary but instead represents a consensus view that accommodates taxonomic choices and practical compromises among diverse expert opinions, public usages, and conflicting evidence about the boundaries between taxa and the ranks of major taxa, including kingdoms. Certain key issues, some not fully resolved, are addressed in particular. Beyond its immediate use as a management tool for the CoL and ITIS (Integrated Taxonomic Information System), it is immediately valuable as a reference for taxonomic and biodiversity research, as a tool for societal communication, and as a classificatory "backbone" for biodiversity databases, museum collections, libraries, and textbooks. Such a modern comprehensive hierarchy has not previously existed at this level of specificity