37 research outputs found

    Atlantic Multidecadal Variability modulates the climate impacts of El Niño–Southern Oscillation in Australia

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    Atlantic Multidecadal Variability (AMV) modulates El Niño–Southern Oscillation (ENSO) dynamics. Here, we explore the effect of warm (AMV+) and cold (AMV−) AMV conditions on the austral summer teleconnection of ENSO to Australia using idealized simulations performed with the NCAR-CESM1 model. AMV+ strengthens the mean and extreme precipitation and temperature responses to El Niño in south-western Australia and weakens the mean precipitation and temperature impacts in north-eastern Australia. The modulation of La Niña impacts by AMV is asymmetric to El Niño, with a weakening of the mean and extreme precipitation and temperature responses in eastern Australia. Decomposing the total difference in ENSO response between AMV phases, we find that the signals are mainly explained by the direct AMV modulation of ENSO and its teleconnections rather than by changes in background climate induced by AMV. The exception is ENSO-driven fire impacts, where there is a significant increase in burned area in south-eastern Australia only when El Niño and AMV+ co-occur. However, modulation of ENSO between AMV+ and AMV− does offset ∼37% of the decrease in burned area extent during La Niña summers. The altered surface climate response to ENSO in Australia by AMV is attributed to variations in large-scale atmospheric circulation. Under AMV+, there is increased subsidence over western Australia during El Niño associated with a westward shift of the local Walker circulation. A weakening of the upwelling branch of the local Hadley circulation over north-eastern Australia is responsible for the weakening of La Niña impacts in AMV+, accompanied by a strengthening of subsidence in south central Australia due to a weakening of the local Hadley circulation, amplifying La Niña impacts over this region. The results suggest the potential for AMV to drive multidecadal variability in ENSO impacts over Australia

    The Decadal Climate Prediction Project (DCPP) contribution to CMIP6

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    The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Prediction (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the "hiatus", volcanoes), including the study of the mechanisms that determine these behaviours. Groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society

    Hyphal network whole field imaging allows for accurate estimation of anastomosis rates and branching dynamics of the filamentous fungus Podospora anserina

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    The success of filamentous fungi in colonizing most natural environments can be largely attributed to their ability to form an expanding interconnected network, the mycelium, or thallus, constituted by a collection of hyphal apexes in motion producing hyphae and subject to branching and fusion. In this work, we characterize the hyphal network expansion and the structure of the fungus Podospora anserina under controlled culture conditions. To this end, temporal series of pictures of the network dynamics are produced, starting from germinating ascospores and ending when the network reaches a few centimeters width, with a typical image resolution of several micrometers. The completely automated image reconstruction steps allow an easy post-processing and a quantitative analysis of the dynamics. The main features of the evolution of the hyphal network, such as the total length L of the mycelium, the number of "nodes" (or crossing points) N and the number of apexes A, can then be precisely quantified. Beyond these main features, the determination of the distribution of the intra-thallus surfaces (S; i; ) and the statistical analysis of some local measures of N, A and L give new insights on the dynamics of expanding fungal networks. Based on these results, we now aim at developing robust and versatile discrete/continuous mathematical models to further understand the key mechanisms driving the development of the fungus thallus

    Coupled climate response to Atlantic Multidecadal Variability in a multi-model multi-resolution ensemble

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    North Atlantic sea surface temperatures (SSTs) underwent pronounced multidecadal variability during the twentieth and early twenty-first century. We examine the impacts of this Atlantic Multidecadal Variability (AMV), also referred to as the Atlantic Multidecadal Oscillation (AMO), on climate in an ensemble of five coupled climate models at both low and high spatial resolution. We use a SST nudging scheme specified by the Coupled Model Intercomparision Project’s Decadal Climate Prediction Project Component C (CMIP6 DCPP-C) to impose a persistent positive/negative phase of the AMV in the North Atlantic in coupled model simulations; SSTs are free to evolve outside this region. The large-scale seasonal mean response to the positive AMV involves widespread warming over Eurasia and the Americas, with a pattern of cooling over the Pacific Ocean similar to the Pacific Decadal Oscillation (PDO), together with a northward displacement of the inter-tropical convergence zone (ITCZ). The accompanying changes in global atmospheric circulation lead to widespread changes in precipitation. We use Analysis of Variance (ANOVA) to demonstrate that this large-scale climate response is accompanied by significant differences between models in how they respond to the common AMV forcing, particularly in the tropics. These differences may arise from variations in North Atlantic air-sea heat fluxes between models despite a common North Atlantic SST forcing pattern. We cannot detect a widespread effect of increased model horizontal resolution in this climate response, with the exception of the ITCZ, which shifts further northwards in the positive phase of the AMV in the higher resolution configuratio

    HighResMIP versions of EC-Earth: EC-Earth3P and EC-Earth3P-HR - Description, model computational performance and basic validation

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    A new global high-resolution coupled climate model, EC-Earth3P-HR has been developed by the EC-Earth consortium, with a resolution of approximately 40 km for the atmosphere and 0.25° for the ocean, alongside with a standard-resolution version of the model, EC-Earth3P (80 km atmosphere, 1.0 ° ocean). The model forcing and simulations follow the High Resolution Model Intercomparison Project (HighResMIP) protocol. According to this protocol, all simulations are made with both high and standard resolutions. The model has been optimized with respect to scalability, performance, data storage and post-processing. In accordance with the HighResMIP protocol, no specific tuning for the high-resolution version has been applied. Increasing horizontal resolution does not result in a general reduction of biases and overall improvement of the variability, and deteriorating impacts can be detected for specific regions and phenomena such as some Euro-Atlantic weather regimes, whereas others such as the El Niño-Southern Oscillation show a clear improvement in their spatial structure. The omission of specific tuning might be responsible for this. The shortness of the spin-up, as prescribed by the HighResMIP protocol, prevented the model from reaching equilibrium. The trend in the control and historical simulations, however, appeared to be similar, resulting in a warming trend, obtained by subtracting the control from the historical simulation, close to the observational one

    Ocean and land forcing of the record-breaking Dust Bowl heat waves across central United States

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    International audienceThe severe drought of the 1930s Dust Bowl decade coincided with record-breaking summer heatwaves that contributed to the socioeconomic and ecological disaster over North America's Great Plains. It remains unresolved to what extent these exceptional heatwaves, hotter than in historically forced coupled climate model simulations, were forced by sea surface temperatures (SSTs) and exacerbated through human-induced deterioration of land cover. Here we show, using an atmospheric-only model, that anomalously warm North Atlantic SSTs enhance heatwave activity through an association with drier spring conditions resulting from weaker moisture transport. Model devegetation simulations, that represent the widespread exposure of bare soil in the 1930s, suggest human activity fueled stronger and more frequent heatwaves through greater evaporative drying in the warmer months. This study highlights the potential for the amplification of naturally occurring extreme events like droughts by vegetation feedbacks to create more extreme heatwaves in a warmer world

    The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6

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    The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond

    Current and emerging developments in subseasonal to decadal prediction

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    Weather and climate variations of subseasonal to decadal timescales can have enormous social, economic and environmental impacts, making skillful predictions on these timescales a valuable tool for decision makers. As such, there is a growing interest in the scientific, operational and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) timescales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) timescales, while the focus remains broadly similar (e.g., on precipitation, surface and upper ocean temperatures and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal and externally-forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correct, calibration and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Prograame (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis

    Warm phase of AMV damps ENSO through weakened thermocline feedback

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    Interactions between ocean basins affect El Niño–Southern Oscillation (ENSO), altering its impacts on society. Here, we explore the effect of Atlantic Multidecadal Variability (AMV) on ENSO behavior using idealized experiments performed with the NCAR-CESM1 model. Comparing warm (AMV+) to cold (AMV−) AMV conditions, we find that ENSO sea surface temperature (SST) anomalies are reduced by ∼10% and ENSO precipitation anomalies are shifted to the west during El Niño and east during La Niña. Using the Bjerknes stability index, we attribute the reduction in ENSO variability to a weakened thermocline feedback in boreal autumn. In AMV+, the Walker circulation and trade winds strengthen over the tropical Pacific, increasing the background zonal SST gradient. The background changes shift ENSO anomalies westwards, with wind stress anomalies more confined to the west. We suggest the changes in ENSO-wind stress decrease the strength of the thermocline feedback in the east, eventually reducing ENSO growth rate
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