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The Indian Summer Monsoon Rainfall (ISMR) varies on a wide range of timescales, from interannual to multi-centennial. Slight variations of seasonal rainfall amounts strongly affect livelihood, which mostly relies on rain-fed agriculture. Improving our understanding of multi-scale variations of ISMR is thus critical to advance its potential predictability and reduce society vulnerability to climate change.Here, we explore such multi-scale variations by analyzing a multi-complexity ensemble of transient simulations ran with the IPSL Earth system model from mid- to late Holocene (6000 years BP to 1950). First, we show that orbital forcing induces low-frequency changes in the ISMR mean state, with near-linear drying from mid- to late Holocene. The relative long term response between land and ocean is compared to available observations from pollen and lakes over land and ocean sediments to assess the realism of the simulation over the broad Indian sector. Second, we show that interannual-to-decadal variability increases along the period despite the drying trend of the ISMR mean state. We isolated a relationship with a concomitant increase in SST variance in the tropical Pacific, especially in its eastern equatorial part. Is the increased variability in precipitation and SST part of the same large-scale response of local variability to long term insolation? Or is the increased variability in precipitation induced by the strengthening of ENSO variability? In addition, we'll use high resolution paleo records from coral and shell over the Indo-Pacific sector and from speleothems and tree rings over land to assess the realism of the simulated changes in long term teleconnections. [ABSTRACT FROM AUTHOR]

The turbulent fluxes across the ocean/atmosphere interface, which represent one of the main drivers of the global atmospheric and oceanic circulations, are parameterized in climate models. To improve the representation of turbulent fluxes, a new parameterization has been developed in the IPSL model. It takes into account the gustiness effects which are calculated thanks to the coupling between the bulk formula (used to compute the surface turbulent fluxes) and the thermal and the convection schemes (that provide the deep and free convection effect on the subgrid variability of surface winds).Here we investigate how this new effect modulates the ocean-atmosphere interactions and feedbacks. We consider both atmosphere only and coupled ocean-atmosphere simulations ran with the IPSL climate model. We focus on the thermodynamical and the dynamical adjustments of the atmospheric and oceanic circulation induced by the coupling between gustiness and turbulent fluxes.In atmospheric stand-alone simulations, the gustiness has a direct effect on turbulent fluxes through the increase of low-level wind used for their calculation. This increases wind stress and leads to indirect effect by reducing the low-level wind. In addition, gustiness significantly impacts latent heat flux in weak wind regions. This modifies the zonal humidity gradient in the Pacific Ocean, which affects the Walker circulation. In coupled ocean-atmosphere simulations, part of the latent heat flux effect is offset by the ocean adjustment through ocean heat storage and sea surface temperature changes. A feedback loop between the wind stress and ocean circulation also affects the overall ocean and atmospheric circulations. The relative amplitude of these feedbacks will be discussed, considering the role of changes in surface turbulent fluxes on ocean and atmospheric circulations, which control heat transports and inter-basin teleconnections. [ABSTRACT FROM AUTHOR]

The Indian and West African monsoons vary on a large variety of timescales, with alternation of extremely wet and dry years having huge impacts on local economy and society. Some of these extreme monsoon events result from the chaotic nature of climate. They are also favored by teleconnection with various modes of climate variability ranging from interannual (e.g., El Nino Southern Oscillation and the Indian Ocean dipole) to decadal (e.g., Atlantic dipole and Atlantic meridional oscillation) timescales. However the relationships between extreme monsoon years and these multi-time scales of varability are not fully understood. The last 6000 years offers a wide range of test cases to analyze these relationships and the diversity of events.The mid-Holocene, 6000 years BP, is characterized by increased monsoon precipitation in West Africa and India compared to modern conditions. This is caused by the Earth's orbital configuration. The seasonal cycle of incoming solar radiation was enhanced in the northern Hemisphere and reduced it in the southern Hemisphere, thereby enhancing the monsoon flow between ocean and land. The retreat of the two monsoon systems back to present day conditions has been punctuated by periods of rapid transitions and periods of mega droughts that had significant imprints on the environment.We consider extreme monsoon events in a multi-complexity ensemble of transient simulations of the last 6000 years ran with the IPSL Earth system model. These simulations allow us to analyze the monsoon response to Earth's orbit and trace gazes, and how multiscale interactions affect extreme African and Indian monsoon events. First results indicate that interannual to decadal variability in Indian precipitation increases with time when its mean amount decreases. This likely relates to increased ENSO variability in the model, the latter being consistent with paleo-reconstructions from coral and bivalves in the Pacific. By sorting the results in different frequency band or type of extreme events, we also explore the relative changes in variability between the Indian and African monsoon, the characteristics of period with high monsoon or prolonged droughts as well as their relationship with modes of climate variability. [ABSTRACT FROM AUTHOR]

Earth’s climate is a complex dynamical system. Its underlying components interact with eachother in linear or nonlinear ways on multiple several spatial and time scales creating possiblepositive and negative feedback loops. Understanding and studying such a system is a difficultchallenge with crucial implications on our society but requires data mining through anextremely large and complex amount of data. In particular, the investigation ofchanges in dynamical and statistical properties in the climate of the past represents aninvaluable opportunity to understand interactions between external forcing (e.g., orbitalparameters) and the internal variability of the climate system. Given a simulatedclimate field embedded on a two dimensional grid, we propose a new methodology to(i) quantify nonlinear changes in variability in simulated climate fields by meansof an information entropy quantifier, (ii) identify regions that undergo changes inentropy in a homogeneous way and (iii) investigate the time dependency of theconnectivity patterns between these regions. To address these points, we analyze twoglobal transient simulations ran with the IPSL Earth system model from mid- to lateHolocene (6000 years BP to 1950). These simulations differ according to theirhorizontal resolution (3.75ox 1.89ovs. 2.5ox 1.27o), their hydrological component(2 vs. 11 layers) and the way vegetation interacts with climate (prescribed versusdynamic). Specifically, we focus on the variability and connectivity of two fields: seasurface temperature (SST) and precipitation. Time resolution is monthly. For agiven field, the input of the algorithm is a two dimensional grid with detrendedanomalies embedded in it. We consider time windows of 100 years of data every20 years and for each time window we compute the entropy of every time seriesembedded in the grid. The entropy serves as a measure of complexity of time series andits computation depends on recurrence plots, an advanced nonlinear data analysistechnique. The product of this first step is then a spatio-temporal entropy field.We then use δ-MAPS, a dimensionality reduction methodology recently proposedby the authors, to reduce the dimensionality of the entropy field by identifyingsemi-autonomous components, referred to as "domains". Domains are defined as spatiallycontiguous, possibly overlapping, structures that undergo changes in entropy in ahomogeneous way. This allows to study both past climate regime shifts and their spatialheterogeneity. Finally, given two sets of domains (in the SST and precipitation fields),for each time window, we compute their signals and infer a functional network ofnetworks (NoN) between them. The NoN is a weighted and potentially directed graphwhich, in a single framework, quantify the interactions between domains in the samefield and the dependency among domains of different fields. A first analysis of thetime dependency of domains’ complexity and of their NoN topology is presented. [ABSTRACT FROM AUTHOR]

The mid-Holocene period (MH) has long been an ideal target for the validation of Global Circulation Model (GCM) results against reconstructions gathered in global datasets. These studies aimed to test the GCM sensitivity mainly to the seasonal changes induced by the orbital parameters (precession). Despite widespread agreement between model results and data on the MH climate, some important differences still exist. There is no consensus on the continental size of the MH thermal climate response, which makes regional quantitative reconstruction critical to obtain a comprehensive understanding of the MH climate patterns. Here, we compare the annual and seasonal outputs from the most recent Paleoclimate Modelling Intercomparison Projects Phase 3 (PMIP3) models with an updated synthesis of climate reconstruction over China, including, for the first time, a seasonal cycle of temperature and precipitation. Most of the models provide a linear response driven by the seasonal forcing (warmer in summer, cooler in winter), which disagrees with the new seasonal data reconstruction over China. We show that to capture the seasonal pattern reconstructed by data, it is critical to assess surface processes. These results pinpoint the crucial importance of including the non-linear of the surface water and energy balance to vegetation changes. [ABSTRACT FROM AUTHOR]

The typical resolution used in CMIP-class Earth system models limits, among others, the ability to assess climate risks that are associated with smaller-scale weather phenomena such as tropical cyclones. We introduce higher-resolution atmosphere-only simulations following the HighResMIP Tier1 protocol. A baseline simulation (LMDZ-OR) is run with LMD-Z, the atmospheric component of the IPSL-CM Earth System model, with CMIP6 physics including the land-surface model ORCHIDEE, at a resolution equivalent to 50km at mid-latitudes. Large-scale parallel I/O with on-the-fly data processing is enabled by the XIOS I/O server. In two additional simulations (ICO-LMDZ-OR), the LMD-Z latitude-longitude dynamical core is replaced by the more scalable DYNAMICO dynamical core, using icosahedral-hexagonal meshes with quasi-uniform resolution of 50km and 25km.We provide a description and preliminary analysis of these simulations. We present the scalability and throughput of LMDZ-OR and ICO-LMDZ-OR. Some differences between LMDZ-OR and ICO-LMDZ-OR with respect to the processing of input datasets, especially orography, are discussed. The climates in LMDZ-OR and ICO-LMD-OR simulations at similar resolutions are compared. Dependence on resolution of key climate features is examined. [ABSTRACT FROM AUTHOR]