Stochastic climate theory and modeling

Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid-scale parameterizations (SSPs) as well as for model error representation, uncertainty quantification, data assimilation, and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all necessary processes and scales in comprehensive numerical weather and climate prediction models. In many practical applications one is mainly interested in the largest and potentially predictable scales and not necessarily in the small and fast scales. For instance, reduced order models can simulate and predict large-scale modes. Statistical mechanics and dynamical systems theory suggest that in reduced order models the impact of unresolved degrees of freedom can be represented by suitable combinations of deterministic and stochastic components and non-Markovian (memory) terms. Stochastic approaches in numerical weather and climate prediction models also lead to the reduction of model biases. Hence, there is a clear need for systematic stochastic approaches in weather and climate modeling. In this review, we present evidence for stochastic effects in laboratory experiments. Then we provide an overview of stochastic climate theory from an applied mathematics perspective. We also survey the current use of stochastic methods in comprehensive weather and climate prediction models and show that stochastic parameterizations have the potential to remedy many of the current biases in these comprehensive models

Disorientating, fun or meaningful? Disadvantaged families' experiences of a science museum visit

It is widely agreed that there is a need to increase and widen science partici- pation. Informal science learning environments (ISLEs), such as science museums, may provide valuable spaces within which to engage visitors—yet the visitor profile of science museums remains narrow. This paper seeks to understand the experiences of socially disadvantaged families within such spaces. Using a Bourdieusian analytic lens, we analyse qualitative data from a small study conducted with ten parents and ten children from an urban school who visited a large science museum. Data includes pre- and post-interviews, audio recordings and visit fieldnotes. We characterised families’ experiences as falling into three discourses, as ‘disorientating’, ‘fun’ or ‘meaningful’ visits. Analysis identifies how the families’ experiences, and the likelihood of deriving science learning from the visit, were shaped through interactions of habitus and capital. Implications for improving equity and inclusion within ISLEs are discussed

Adoption of telecommuting : modeling the employer's and the employee's decision processes

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1995.Includes bibliographical references (leaves 179-182).by Adriana Teixeira Bernardino.Ph.D

PHYSIOLOGICAL RESISTANCE OF COMMON BEAN LINES TO \u3ci\u3eSclerotinia sclerotiorum\u3c/i\u3e

INTRODUCTION. White mold (WM), caused by the fungus Sclerotinia sclerotiorum, is a serious constraint of common bean during the fall-winter season in Brazil. The most commonly used control measure is fungicide application. However, the high cost and the potentially deleterious effects on human health and environment have motivated the search for new options of WM management. Genetic resistance is a key component of the WM management, because it is easier for farmers to adopt and is environmentally safe. Since 2008, we have screened common bean lines/cultivars for WM resistance from the field trials named Value for Cultivation and Use (VCU) conducted under WM pressure. The lines screened in these trials have been developed by Federal University of Viçosa, Federal University of Lavras, EPAMIG and Embrapa Rice and Beans. Beginning in 2015, we have evaluated the genotypes screened in the VCU trials in comparison to three WM-resistant checks (A195, G122, and Cornell 605) in advanced field trials, straw and/or detached leaflet tests. Here, we present results from the straw and the detached leaflet tests to assess physiological resistance of lines/cultivars originally screened for resistance to foliar diseases and high yield

Defining wet season water quality target concentrations for ecosystem conservation using empirical light attenuation models: A case study in the Great Barrier Reef (Australia)

Optically active water quality components (OAC) transported by flood plumes to nearshore marine environments affect light levels. The definition of minimum OAC concentrations that must be maintained to sustain sufficient light levels for conservation of light-dependant coastal ecosystems exposed to flood waters is necessary to guide management actions in adjacent catchments. In this study, a framework for defining OAC target concentrations using empirical light attenuation models is proposed and applied to the Wet Tropics region of the Great Barrier Reef (GBR) (Queensland, Australia). This framework comprises several steps: (i) light attenuation (Kd(PAR)) profiles and OAC measurements, including coloured dissolved organic matter (CDOM), chlorophyll-a (Chl-a) and suspended particulate matter (SPM) concentrations collected in flood waters; (ii) empirical light attenuation models used to define the contribution of CDOM, Chl-a and SPM to the light attenuation, and; (iii) translation of empirical models into manageable OAC target concentrations specific for wet season conditions. Results showed that (i) Kd(PAR) variability in the Wet Tropics flood waters is driven primarily by SPM and CDOM, with a lower contribution from Chl-a (r2 = 0.5, p < 0.01), (ii) the relative contributions of each OAC varies across the different water bodies existing along flood waters and strongest Kd(PAR) predictions were achieved when the in-situ data were clustered into water bodies with similar satellite-derived colour characteristics (‘brownish flood waters’, r2 = 0.8, p < 0.01, ‘greenish flood waters’, r2 = 0.5, p < 0.01), and (iii) that Kd(PAR) simulations are sensitive to the angular distribution of the light field in the clearest flood water bodies. Empirical models developed were used to translate regional light guidelines (established for the GBR) into manageable OAC target concentrations. Preliminary results suggested that a 90th percentile SPM concentration of 11.4 mg L−1 should be maintained during the wet season to sustain favourable light levels for Wet Tropics coral reefs and seagrass ecosystems exposed to ‘brownish’ flood waters. Additional data will be collected to validate the light attenuation models and the wet season target concentration which in future will be incorporated into wider catchment modelling efforts to improve coastal water quality in the Wet Tropics and the GBR

Image-based adaptive optics for in vivo imaging in the hippocampus

International audienceAdaptive optics is a promising technique for the improvement of microscopy in tissues. A large palette of indirect and direct wavefront sensing methods has been proposed for in vivo imaging in experimental animal models. Application of most of these methods to complex samples suffers from either intrinsic and/or practical difficulties. Here we show a theoretically optimized wavefront correction method for inhomogeneously labeled biological samples. We demonstrate its performance at a depth of 200 μm in brain tissue within a sparsely labeled region such as the pyramidal cell layer of the hippocampus, with cells expressing GCamP6. This method is designed to be sample-independent thanks to an automatic axial locking on objects of interest through the use of an image-based metric that we designed. Using this method, we show an increase of in vivo imaging quality in the hippocampus. In vivo imaging of neuronal calcium dynamics using two-photon microscopy is an increasingly used method of choice to study neuronal activity at microcircuit level. In the dorsal region CA1 of the hippocampus (the most optically accessible), this technique allows neuronal activity recording, in large fields of view containing hundreds of cells 1. It has led to pioneering discoveries of multineuron dynamics including, for example fear conditioning 2 , spatial navigation 3–5 , epilepsy 6 or quiet rest 7. However, the implementation of this technique remains challenging as it requires, prior to cranial window implantation, surgery to remove the overlaying cortex, which introduces a high variability of " optical access " to the tissue. The main issues are the presence of blood from the capillaries and sometimes from small hemorrhage as well as the quality of the interface between the glass window and the brain surface. The former causes optical absorption and can be reduced by performing the surgery following water restriction to increase the viscosity of the blood 1,5 , while the latter causes optical aberrations. Furthermore, the densely packed layer of CA1 pyramidal neurons is located 200 μ m below the glass window covering the brain; the incoming laser beam is also perturbed by light scattering and optical aberrations during the propagation within the tissue. This problem should be tackled in order to improve detection of calcium probes which is impaired by the lowered contrast of the aberrated images. Even a modest improvement in contrast should lead to the detection of neural activity that otherwise is masked by background fluorescence from brain tissue. Optical aberrations alter the quality of beam focusing, which in turn leads to reduced spatial resolution but also to lower signal and contrast. Thus, even when objects of interest are one order of magnitude larger than the diffraction limited laser focus (e.g. neurons' somata are 10–15 μ m in diameter), the reduction of optical aberrations is critical to increasing the contrast of the fluorescence images. This improvement can be achieved using adaptive optics, a promising tool increasingly used for microscopy 8. Adaptive optics is the process of quantifying optical aberrations through wavefront measurement and correcting them by the use of an adaptive correction element (deformable mirror DM or spatial light modulator SLM). Note that in point-scanning two-photon microscopy the correction is applied on the excitation beam alone and no correction is needed on the detection path. In such microscopes, the wavefront can either be directly measured or indirectly estimated. Direct wave-front measurement relies on introducing a wavefront sensor such as a Shack-Hartmann in the detection part of the microscope. A point source in the sample is then imaged on the sensor. Direct methods have been proposed for two-photon imaging in weakly scattering samples where auto-fluorescence signals can be used to generate a highly localized signal 9,10 , but more complex methods such as coherence gating 11 or near-IR guide stars 12 are required to avoid out-of-focus fluorescence in highly scattering samples. Indirect or sensorless wavefront estimation has the advantage of being easy-to-implement on existing systems as it relies on conventional imaging systems. Indeed, this technique, called image-based adaptive optics, relies on successive image measurements wit