Southern African summer-rainfall variability, and its teleconnections, on interannual to interdecadal timescales in CMIP5 models

23 pagesInternational audienceThis study provides the first assessment of CMIP5 model performances in simulating southern Africa (SA) rainfall variability in austral summer (Nov–Feb), and its teleconnections with large-scale climate variability at different timescales. Observed SA rainfall varies at three major timescales: interannual (2–8 years), quasi-decadal (8–13 years; QDV) and interdecadal (15–28 years; IDV). These rainfall fluctuations are, respectively, associated with El Niño Southern Oscillation (ENSO), the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO), interacting with climate anomalies in the South Atlantic and South Indian Ocean. CMIP5 models produce their own variability, but perform better in simulating interannual rainfall variability, while QDV and IDV are largely underestimated. These limitations can be partly explained by spatial shifts in core regions of SA rainfall variability in the models. Most models reproduce the impact of La Niña on rainfall at the interannual scale in SA, in spite of limitations in the representation of ENSO. Realistic links between negative IPO are found in some models at the QDV scale, but very poor performances are found at the IDV scale. Strong limitations, i.e. loss or reversal of these teleconnections, are also noted in some simulations. Such model errors, however, do not systematically impact the skill of simulated rainfall variability. This is because biased SST variability in the South Atlantic and South Indian Oceans strongly impact model skills by modulating the impact of Pacific modes of variability. Using probabilistic multi-scale clustering, model uncertainties in SST variability are primarily driven by differences from one model to another, or comparable models (sharing similar physics), at the global scale. At the regional scale, i.e. SA rainfall variability and associated teleconnections, while differences in model physics remain a large source of uncertainty, the contribution of internal climate variability is increasing. This is particularly true at the QDV and IDV scales, where the individual simulations from the same model tend to differentiate, and the sampling error increase

Near-term impacts of climate variability and change on hydrological systems in West and Central Africa

Climate change is expected to significantly impact on the availability of water resources in West and Central Africa through changes in rainfall, temperature and evapotranspiration. Understanding these changes in this region, where surface water is fundamental for economic activity and ecosystem services, is of paramount importance. In this study, we examine the potential impacts of climate variability and change on hydrological systems by the mid-21st century in West and Central Africa, as well as the uncertainties in the different climate-impact modelling pathways. Simulations from nine global climate models downscaled using the Rossby Centre Regional Climate model (RCA4) are evaluated and subsequently bias-corrected using a nonparametric trend-preserving quantile mapping approach. We then use two conceptual hydrological models (GR2M and IHACRES), and a regression-based model built upon multi-timescale sea surface temperatures and streamflow teleconnections, to understand hydrological processes at the subcontinental scale and provide hydrological predictions for the near-term future (2020-2050) under the RCP4.5 emission scenario. The results highlight a zonal contrast in future precipitation between western (dry) and eastern (wet) Sahel, and a robust signal in rising temperature, suggesting an increase in potential evapotranspiration, across the multi-model ensemble. Overall, across the region, a significant increase in discharge (similar to + 5%) is expected by the mid-21st century, albeit with high uncertainties reported over most of Central Equatorial Africa inherent to climate models and gridded observation data quality. Interestingly, in this region, teleconnections-based regression models tend to be an alternative to hydrological models

Identifying drivers of streamflow extremes in West Africa to inform a nonstationary prediction model

West Africa exhibits decadal patterns in the behaviour of droughts and floods, creating challenges for effective water resources management. Proposed drivers of prolonged shifts in hydrological extremes include the impacts of land-cover change and climate variability in the region. However, while future land-degradation or land-use are highly unpredictable, recent studies suggest that prolonged periods of high-flows or increasing flood occurrences could be predicted by monitoring sea-surface temperature (SST) anomalies in the different ocean basins. In this study, we thus examine: i) what ocean basins would be the most suitable for future seamless flood-prediction systems; ii) how these ocean basins affect high-flow extremes (hereafter referred as extreme streamflow); and iii) how to integrate such nonstationary information in flood risk modelling. We first use relative importance analysis to identify the main SST drivers modulating hydrological conditions at both interannual and decadal timescales. At interannual timescales, Pacific Niño (ENSO), tropical Indian Ocean (TIO) and eastern Mediterranean (EMED) constitute the main climatic controls of extreme streamflow over West Africa, while the SST variability in the North and tropical Atlantic, as well as decadal variations of TIO and EMED are the main climatic controls at decadal timescales. Using regression analysis, we then suggest that these SST drivers impact hydrological extremes through shifts in the latitudinal location and the strength of the Intertropical Convergence Zone (ITCZ) and the Walker circulation, impacting the West African Monsoon, especially the zonal and meridional atmospheric water budget. Finally, a nonstationary extreme model, with climate information capturing regional circulation patterns, reveals that EMED SST is the best predictor for nonstationary streamflow extremes, particularly across the Sahel. Predictability skill is, however, much higher at the decadal timescale, and over the Senegal than the Niger catchment. This might be due to stronger impacts of land-use (-cover) and/or catchment properties (e.g. the Inner Delta) on the Niger River flow. Overall, a nonstationary framework for floods can also be applied to drought risk assessment, contributing to water regulation plans and hazard prevention, over West Africa and potentially other parts of the world

Crop diversity, climate change adaptation and resilience: good practice cases from Africa

As part of the Integrated Seed Sector Development in Africa (ISSD Africa) program’s activities for 2020, the Agrobiodiversity, seeds and climate change action learning group (Theme 3) documented and analyzed a series of good crop diversification practice cases from Africa, which were published in an ISSD Africa working paper [https:// hdl.handle.net/10568/115012]. This brief presents a synthesis of the working paper

Mobilizing crop diversity for climate change adaptation and resilience: Field experiences from Africa

In recent years, a number of international initiatives have piloted various forms of support for novel configurations of actors to work together to conserve and use agrobiodiversity in sustainable agricultural production systems and to equitably share benefits derived from those activities. These configurations operate at farm, community, national and international levels. Among these initiatives, Bioversity International (now the Alliance of Bioversity International and CIAT) and partners have researched the effectiveness of using agrobiodiversity, in particular in the form of crop and crop variety diversity, as an adaptive practice. The hypothesis informing this research is that crop diversification can result in positive livelihood outcomes, such as food and nutritional security, income generation and good health. These outcomes, in turn, could lead to (increased) resilience of rural households and communities to environmental, socio- economic and climatic shocks. In this working paper, we present a number of case studies that to a certain extent have “delivered” on this impact pathway. The case studies were compiled during the year 2020, the year that COVID-19 spread across the globe with devastating consequences for countries, communities and households everywhere

Women and ARVâ based prevention: opportunities and challenges

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138349/1/jia29419.pd

Development of New Analytical Strategies for the Analysis of Peptides and Proteins By Mass Spectrometry in Biofluids

Chapter 1: The first chapter of this thesis is dedicated to the principles and the applications of peptides and proteins quantification by mass spectrometry. The problematic of monoclonal antibodies analysis is also presented in this chapter. Chapter 2: The second chapter focuses on the development of an analytical method for the absolute quantification of the des-acyl ghrelin and ghrelin peptides. Chapter 3: The third chapter describes the application of differential ion mobility spectrometry. Chapter 4: The fourth chapter is dedicated to the development of an immunoaffinitybased extraction procedure for the MS analysis of monoclonal antibodies glycoforms in plasma samples. Chapter 5: The fifth chapter presents preliminary study focused on the quantification of peptides in plasma using the high resolution mass spectrometry (HRSIM/MS)

Peptides OFFGEL electrophoresis: a suitable pre-analytical step for complex eukaryotic samples fractionation compatible with quantitative iTRAQ labeling.

International audienceABSTRACT: BACKGROUND: The proteomes of mammalian biological fluids, cells and tissues are complex and composed of proteins with a wide dynamic range. The effective way to overcome the complexity of these proteomes is to combine several fractionation steps. OFFGEL fractionation, recently developed by Agilent Technologies, provides the ability to pre-fractionate peptides into discrete liquid fractions and demonstrated high efficiency and repeatability necessary for the analysis of such complex proteomes. RESULTS: We evaluated OFFGEL fractionator technology to separate peptides from two complex proteomes, human secretome and human plasma, using a 24-wells device encompassing the pH range 3-10. In combination with reverse phase liquid chromatography, peptides from these two samples were separated and identified by MALDI TOF-TOF. The repartition profiles of the peptides in the different fractions were analyzed and explained by their content in charged amino acids using an algorithmic model based on the possible combinations of amino acids. We also demonstrated for the first time the compatibility of OFFGEL separation technology with the quantitative proteomic labeling technique iTRAQ allowing inclusion of this technique in complex samples comparative proteomic workflow. CONCLUSION: The reported data showed that OFFGEL system provides a highly valuable tool to fractionate peptides from complex eukaryotic proteomes (plasma and secretome) and is compatible with iTRAQ labeling quantitative studies. We therefore consider peptides OFFGEL fractionation as an effective addition to our strategy and an important system for quantitative proteomics studies

Pseudoprogression in Glioblastoma: Role of Metabolic and Functional MRI-Systematic Review

Background: Glioblastoma is the most frequent malignant primitive brain tumor in adults. The treatment includes surgery, radiotherapy, and chemotherapy. During follow-up, combined chemoradiotherapy can induce treatment-related changes mimicking tumor progression on medical imaging, such as pseudoprogression (PsP). Differentiating PsP from true progression (TP) remains a challenge for radiologists and oncologists, who need to promptly start a second-line treatment in the case of TP. Advanced magnetic resonance imaging (MRI) techniques such as diffusion-weighted imaging, perfusion MRI, and proton magnetic resonance spectroscopic imaging are more efficient than conventional MRI in differentiating PsP from TP. None of these techniques are fully effective, but current advances in computer science and the advent of artificial intelligence are opening up new possibilities in the imaging field with radiomics (i.e., extraction of a large number of quantitative MRI features describing tumor density, texture, and geometry). These features are used to build predictive models for diagnosis, prognosis, and therapeutic response. Method: Out of 7350 records for MR spectroscopy, GBM, glioma, recurrence, diffusion, perfusion, pseudoprogression, radiomics, and advanced imaging, we screened 574 papers. A total of 228 were eligible, and we analyzed 72 of them, in order to establish the role of each imaging modality and the usefulness and limitations of radiomics analysis