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Decadal Climate Predictions Using Sequential Learning Algorithms
Ensembles of climate models are commonly used to improve climate predictions and assess the
uncertainties associated with them. Weighting the models according to their performances holds the promise of further improving their predictions. Using an ensemble of climate model simulations from the CMIP5 decadal experiments, we quantified the total uncertainty associated with these predictions and the relative importance of model and internal uncertainties. Sequential learning algorithms (SLAs) were used to reduce the forecast errors and reduce the model uncertainties. The reliability of the SLA predictions was also tested, and the advantages and limitations of the different performance measures are discussed. The spatial distribution of the SLAs performance showed that they are skillful and better than the other forecasting methods over large continuous regions. This finding suggests that, despite the fact that each of the ensemble models is not skillful, the models were able to capture some physical processes that resulted in deviations from the climatology and that the SLAs enabled the extraction of this additional information. If time permits I will also present a method for estimating the uncertainties associated with ensemble predictions and demonstrate the resulting improved reliability.

References:
1. Improvement of climate predictions and reduction of their uncertainties using learning algorithms, Atmospheric Chemistry and Physics 15, 8631-8641 (2015).
2. Decadal climate predictions using sequential learning algorithms, Journal of Climate 29, 3787-3809 (2016).
3. The contribution of internal and model variabilities to the uncertainty in CMIP5 decadal climate predictions, Climate Dynamics 49, 3221 (2017).
4. Quantifying the uncertainties in an ensemble of decadal climate predictions. Journal of Geophysical Research: Atmospheres 122, 13,191–13,200 (2017).
5. Learning algorithms allow for improved reliability and accuracy of global mean surface temperature projections. Nature Communications 11, 451 (2020).

Coccoliths are exoskeletal plates, made of highly complex microscopic calcite (CaCO3) crystals with astonishing morphological variety, produced by unicellular algae called Coccolithophores. For decades, their complexity has made coccolith fabrication and its controls alluring to scientists from different fields. Coccoliths grow intracellularly in a specialized vesicle where they presumably interact with chiral additives in a stereospecific manner. Such specific interactions are thought to give rise to numerous crystallographic faces, that convey ultrastructural chirality and convolutedness. We investigated the large coccoliths of Calcidiscus leptoporus by extracting them from within the cells along their growth, imagining them with various electron microscopy techniques at high resolution, and rendering their 3D structure. Our morphological analysis revealed that as the crystals mature, they transition from isotropic rhombohedra to highly anisotropic shapes, while expressing only a single set of crystallographic faces. This observation profoundly challenges the involvement of chiral modifiers. The crystals’ growth pattern showed that their shape is attained via differential growth rates of symmetry related facets with. Additionally, the rhombohedral geometry of the crystals appears to convey ultrastructural chirality in initial coccolith assembly stages. These findings change our understanding of biological control over complex crystal construction and mechanistically simplify the system in which they emerge.

In plants, primary growth is sustained by a shoot apical meristem (SAM) that produce lateral leaf organs from their flanks until floral transition is attained. At this point, the SAM is marked by a dramatic doming of the SAM followed by either lateral formation of flowers e.g: Arabidopsis or by termination of by a flower as in determinate plants like tomato. Irrespective of the developmental track at the shoot apex, floral transition in both growth types is followed by the release of basal axillary buds from Apical Dominance, cues that are regularly emitted by the vegetative SAM. We use tomato shoot apices to understand the molecular changes that are triggered at floral transition by exhaustively profiling transcriptomes of individual SAMs. To that end, we identified dynamic, successive, transient gene expression programs activated along the developmental progression of SAM. I will present our results on how - genetic interrogation of components of these transient gene programs allowed dissociation of the tightly linked process of floral transition and apical dominance release. The relevance of these gene programs for flexibility to form simple to highly compound inflorescence structures will be discussed.