Earth System Dynamics Discussions最新文献

{"title":"Studying the large-scale effect of leaf thermoregulation using an\u0000Earth system model","authors":"Marvin Heidkamp, F. Ament, Philipp de Vrese, A. Chlond","doi":"10.5194/esd-2020-75","DOIUrl":"https://doi.org/10.5194/esd-2020-75","url":null,"abstract":"Abstract. Plants have the ability to regulate heat and water losses. This process also known as leaf thermoregulation helps to maintain the leaf temperature within an optimal range. In a number of laboratory and field experiments, the leaf temperature has been found to deviate substantially from the ambient temperature. In the present study, we address the question of whether the negative correlation between the leaf temperature excess and the ambient air temperature, which is characteristic of leaf thermoregulation, constitutes a robust feature at larger scales, across a broad range of atmospheric conditions and canopy characteristics. To this end, we developed a new dual-source canopy layer energy balance scheme (CEBa) and implemented it into JSBACH, the land component of the Max Planck Institute for Meteorology's Earth system model (MPI-ESM). The approach calculates the temperature and humidity in the ambient canopy air space, the temperature of the ground surface, and the temperature of the leaf as well as the energy and moisture fluxes between the different compartments. Here leaf thermoregulation is investigated using different modeling approaches, namely a zero-dimensional instantaneous solution of the energy balance as well as offline FLUXNET site experiments and coupled global simulations. With the help of the simulations at the site-level, we can show that the model is capable of reproducing the effect of leaf thermoregulation even though the simulated signal at the canopy scale is less pronounced than indicated by measurements at the leaf scale. However, on a global scale and over longer-timescales, this negative correlation is only simulated in idealized setups that neglect limitations on the plant available water, and even then, the signal is less pronounced than indicated by the short-term observations of individual leaves. When accounting for moisture limitations, we predominantly find positive correlations between leaf temperature excess and the ambient air temperature.","PeriodicalId":11466,"journal":{"name":"Earth System Dynamics Discussions","volume":"44 1","pages":"1-28"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73719369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ESD Ideas: Long-period tidal forcing in geophysics – application to\u0000ENSO, QBO, and Chandler wobble","authors":"P. Pukite","doi":"10.5194/esd-2020-74","DOIUrl":"https://doi.org/10.5194/esd-2020-74","url":null,"abstract":"Abstract. Apart from its known impact to variations in the Earth's length-of-day (LOD) variations, the role of long-period tidal forcing cycles in geophysical behaviours has remained relatively unexplored. To extend this idea, tidal forcing is considered as a causative mechanisms to the following cyclic processes: El Nino Southern Oscillation (ENSO), Quasi-Biennial Oscillation (QBO), and the Chandler wobble. Subtle mathematical insights are required to make the connection to the observed patterns as the underlying periods are not strictly commensurate in relation to harmonics of the tidal cycles. There are three cyclic perturbations in the Earth's behavior that scientists have had difficulty pinning down. The actual understanding is so poor that there is no clear consensus for any of the behaviors, and the actual mechanism in each is considered an as-yet unresolved mystery. One behavior has to do with an oceanic cycle (ENSO), one with an atmospheric cycle (QBO), and one with the solid Earth (Chandler wobble). A consensus agreement is lacking in each of these three behaviors in spite of the fact that there may be an obvious yet mathematically-challenging common-mode cause tying them together. The challenge lies in simplifying the math of fluid dynamics and applying the appropriate signal processing techniques. With that, an elegant analytical framework can be applied to perhaps solve the mystery once and for all.","PeriodicalId":11466,"journal":{"name":"Earth System Dynamics Discussions","volume":"41 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2020-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74268425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spectral nudging in the Tropics","authors":"B. Gómez, G. Miguez-Macho","doi":"10.5194/esd-2020-71","DOIUrl":"https://doi.org/10.5194/esd-2020-71","url":null,"abstract":"Abstract. Spectral nudging allows forcing a selected part of the spectrum of a model's solution with the equivalent part in a reference dataset, such as an analysis, reanalysis or another model. This constrains the evolution in certain scales, typically the synoptic ones, while allowing the others to evolve freely. In a limited area model (LAM) setting, spectral nudging is commonly used to impose the large-scale circulation in the interior of the domain, so that the high resolution features in the LAM's forecast are consistent with the global circulation patterns. In a previous study developed over a Mid-Latitude domain, we investigated two parameters of spectral nudging that are often overlooked despite having a significant impact on the model solution. First, the cut-off wave number, which is the parameter determining the scales that are nudged and has a critical impact on the spatial structure of the model solution. Second, the spin-up time, which is the time required to balance the nudging force with the model internal climate and roughly indicates the starting point from when the results of the simulation contain useful information. The question remains if our conclusions for Mid-Latitudes are applicable to other areas of the planet. Tropical Latitudes offer an interesting testbed as its atmospheric dynamics has unique characteristics with respect to that further North and yet it is the result of the same underlying physical principles. We study the impact of these two parameters in a domain centred in the Gulf of Mexico, with a particular aim to evaluate their performance related to hurricane modelling. We perform 4-day simulations along 6 monthly periods between 2010 and 2015, testing several spectral nudging configurations. Our results indicate that the optimal cut off wavenumber lies between 1000 Km and 1500 Km depending on the studied variable and that the spin-up time required is at least 72 h to 96 h, which is consistent with our previous work. We evaluate our findings in four hurricane cases, allowing for at least 96 h of spin-up time before the system becomes a tropical storm. Results confirm that the experiments with cut-off wavenumbers near the Rossby Radius of Deformation perform best. We also propose a novel approach in which a different cut-off wavenumber is used for each variable. Our tests in the hurricane cases show that the latter set up is able to outperform all of the other spectral nudging experiments when compared to observations.\u0000","PeriodicalId":11466,"journal":{"name":"Earth System Dynamics Discussions","volume":"173 1","pages":"1-26"},"PeriodicalIF":0.0,"publicationDate":"2020-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73164509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A continued role of short-lived climate forcers under the Shared Socioeconomic Pathways","authors":"M. Lund, B. Aamaas, C. W. Stjern, Z. Klimont, T. Berntsen, B. Samset","doi":"10.5194/ESD-11-977-2020","DOIUrl":"https://doi.org/10.5194/ESD-11-977-2020","url":null,"abstract":"Abstract. Mitigation of non-CO 2 emissions plays a key role in meeting the Paris\u0000Agreement ambitions and sustainable development goals. Implementation of\u0000respective policies addressing these targets mainly occur at sectoral and\u0000regional levels, and designing efficient mitigation strategies therefore\u0000relies on detailed knowledge about the mix of emissions from individual\u0000sources and their subsequent climate impact. Here we present a comprehensive\u0000dataset of near- and long-term global temperature responses to emissions of\u0000CO 2 and individual short-lived climate forcers (SLCFs) from 7 sectors\u0000and 13 regions – for both present-day emissions and their continued evolution as\u0000projected under the Shared Socioeconomic Pathways (SSPs). We demonstrate the key\u0000role of CO 2 in driving both near- and long-term warming and\u0000highlight the importance of mitigating methane emissions from agriculture,\u0000waste management, and energy production as the primary strategy to further\u0000limit near-term warming. Due to high current emissions of cooling SLCFs,\u0000policies targeting end-of-pipe energy sector emissions may result in net\u0000added warming unless accompanied by simultaneous methane and/or CO 2 \u0000reductions. We find that SLCFs are projected to play a continued role in\u0000many regions, particularly those including low- to medium-income countries,\u0000under most of the SSPs considered here. East Asia, North America, and Europe will\u0000remain the largest contributors to total net warming until 2100, regardless\u0000of scenario, while South Asia and Africa south of the Sahara overtake Europe\u0000by the end of the century in SSP3-7.0 and SSP5-8.5. Our dataset is made\u0000available in an accessible format, aimed also at decision makers, to\u0000support further assessment of the implications of policy implementation at\u0000the sectoral and regional scales.","PeriodicalId":11466,"journal":{"name":"Earth System Dynamics Discussions","volume":"26 1","pages":"977-993"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86446934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of convection-permitting extreme precipitation\u0000simulations for the south of France","authors":"Linh N. Luu, R. Vautard, P. Yiou, J. Soubeyroux","doi":"10.5194/esd-2020-77","DOIUrl":"https://doi.org/10.5194/esd-2020-77","url":null,"abstract":"Abstract. In the autumn, the French Mediterranean area is frequently exposed to heavy precipitation events whose daily accumulation can exceed 300 mm. One of the key processes contributing to these precipitation amounts is the deep convection, which can be resolved explicitly by state-or-the-art convection-permitting model to reproduce heavy rainfall events that are comparable to observations. However, this approach has never been used in climate simulation for the Mediterranean coastal region. In this research, we investigate the added values of using three ensembles of climate simulations at convection-permitting resolution (approx. 3 km) in replicating extreme precipitation events in both daily and shorter time scale over the South of France. These three convection-permitting simulations are performed with the Weather Research and Forecasting Model (WRF). They are forced by three EURO-CORDEX simulations, which are also downscaled with WRF at the resolution of 0.11° (approx. 12 km). We found that a convection-permitting approach provides a more realistic representation of extreme daily and 3-hourly rainfall simulations in comparison with EURO-CORDEX simulations. Their similarity with observations allows a use for climate change studies and its impacts.\u0000","PeriodicalId":11466,"journal":{"name":"Earth System Dynamics Discussions","volume":"34 1","pages":"1-24"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80639088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The synergistic impact of ENSO and IOD on Indian summer monsoon rainfall in observations and climate simulations – an information theory perspective","authors":"P. K. Pothapakula, C. Primo, S. Sørland, B. Ahrens","doi":"10.5194/esd-11-903-2020","DOIUrl":"https://doi.org/10.5194/esd-11-903-2020","url":null,"abstract":"Abstract. The El Nino–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are two well-known temporal oscillations in sea surface temperature (SST), which are both thought to influence the interannual variability of Indian summer monsoon rainfall (ISMR). Until now, there has been no measure to assess the simultaneous information exchange (IE) from both ENSO and IOD to ISMR. This study explores the information exchange from two source variables (ENSO and IOD) to one target (ISMR). First, in order to illustrate the concepts and quantification of two-source IE to a target, we use idealized test cases consisting of linear and nonlinear dynamical systems. Our results show that these systems exhibit net synergy (i.e., the combined influence of two sources on a target is greater than the sum of their individual contributions), even with uncorrelated sources in both the linear and nonlinear systems. We test IE quantification with various estimators (linear, kernel, and Kraskov estimators) for robustness. Next, the two-source IE from ENSO and IOD to ISMR is investigated in observations, reanalysis, three global climate model (GCM) simulations, and three nested higher-resolution simulations using a regional climate model (RCM). This (1) quantifies IE from ENSO and IOD to ISMR in the natural system and (2) applies IE in the evaluation of the GCM and RCM simulations. The results show that both ENSO and IOD contribute to ISMR interannual variability. Interestingly, significant net synergy is noted in the central parts of the Indian subcontinent, which is India's monsoon core region. This indicates that both ENSO and IOD are synergistic predictors in the monsoon core region. But, they share significant net redundant information in the southern part of the Indian subcontinent. The IE patterns in the GCM simulations differ substantially from the patterns derived from observations and reanalyses. Only one nested RCM simulation IE pattern adds value to the corresponding GCM simulation pattern. Only in this case does the GCM simulation show realistic SST patterns and moisture transport during the various ENSO and IOD phases. This confirms, once again, the importance of the choice of GCM in driving a higher-resolution RCM. This study shows that two-source IE is a useful metric that helps in better understanding the climate system and in process-oriented climate model evaluation.","PeriodicalId":11466,"journal":{"name":"Earth System Dynamics Discussions","volume":"60 1","pages":"903-923"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84778912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling the Ruin of Forests under Climate Hazards","authors":"P. Yiou, N. Viovy","doi":"10.5194/esd-2020-78","DOIUrl":"https://doi.org/10.5194/esd-2020-78","url":null,"abstract":"Abstract. Estimating the risk of collapse of forests due to extreme climate events is one of the challenges of adaptation to climate change. We adapt a concept from ruin theory, which is widespread in econometrics or the insurance industry, to design a growth/ruin model for trees, under climate hazards that can jeopardize their growth. This model is an elaboration of a classical Cramer-Lundberg ruin model that is used in the insurance industry. The model accounts for the interactions between physiological parameters of trees and the occurrence of climate hazards. The physiological parameters describe interannual growth rates and how trees react to hazards. The hazard parameters describe the probability distributions of occurrence and intensity of climate events. We focus on a drought/heatwave hazard. The goal of the paper is to determine the dependence of ruin and average growth probability distributions as a function of physiological and hazard parameters. From extensive Monte Carlo experiments, we show the existence of a threshold on the frequency of hazards beyond which forest ruin becomes certain in a centennial horizon. We also detect a small effect of strategies to cope with hazards. This paper is a proof-of-concept to quantify collapse (of forests) under climate change.\u0000","PeriodicalId":11466,"journal":{"name":"Earth System Dynamics Discussions","volume":"124 1","pages":"1-21"},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90593678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seasonal discharge response to temperature-driven changes in evaporation and snow processes","authors":"J. Buitink, L. Melsen, A. Teuling","doi":"10.5194/esd-2020-73","DOIUrl":"https://doi.org/10.5194/esd-2020-73","url":null,"abstract":"Abstract. This study analyses how temperature-driven changes in evaporation and snow processes influence the discharge in large river basins. Using a distributed efficient hydrological model at high spatio-temporal resolution, we investigate the relative contribution of snow and evaporation. Comparing two 10-year periods (1980s and 2010s) in the Rhine allowed to determine the contribution of changes in snow, evaporation and precipitation to the discharge. Around half of the observed changes could be explained by the changes induced by snow (11 %), evaporation (19 %) and precipitation (18 %), while 52 % was driven by a combination of these variables. Increased temperature scenarios show that seasonal changes in snow-dynamics could offset a fairly constant negative change in relative runoff induced by evaporation, but not during the melt season. This study shows how the combined effect of temperature-driven changes affect discharge. With many basins around the world depending on meltwater, correct understanding of these changes is vital.","PeriodicalId":11466,"journal":{"name":"Earth System Dynamics Discussions","volume":"94 1","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86039968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconstructing coupled time series in climate systems using three kinds of machine-learning methods","authors":"Yu Huang, Lichao Yang, Zuntao Fu","doi":"10.5194/ESD-11-835-2020","DOIUrl":"https://doi.org/10.5194/ESD-11-835-2020","url":null,"abstract":"Abstract. Despite the great success of machine learning, its application in climate\u0000dynamics has not been well developed. One concern might be how well the\u0000trained neural networks could learn a dynamical system and what will be the\u0000potential application of this kind of learning. In this paper, three machine-learning methods are used: reservoir computer (RC), backpropagation-based (BP)\u0000artificial neural network, and long short-term memory (LSTM) neural network. It shows that the coupling relations or dynamics among variables in\u0000linear or nonlinear systems can be inferred by RC and LSTM, which can be\u0000further applied to reconstruct one time series from the other. Specifically,\u0000we analyzed the climatic toy models to address two questions: (i) what\u0000factors significantly influence machine-learning reconstruction and (ii)\u0000how do we select suitable explanatory variables for machine-learning\u0000reconstruction. The results reveal that both linear and nonlinear coupling\u0000relations between variables do influence the reconstruction quality of\u0000machine learning. If there is a strong linear coupling between two\u0000variables, then the reconstruction can be bidirectional, and both of these\u0000two variables can be an explanatory variable for reconstructing the other.\u0000When the linear coupling among variables is absent but with the significant\u0000nonlinear coupling, the machine-learning reconstruction between two\u0000variables is direction dependent, and it may be only unidirectional. Then\u0000the convergent cross mapping (CCM) causality index is proposed to determine\u0000which variable can be taken as the reconstructed one and which as the\u0000explanatory variable. In a real-world example, the Pearson correlation\u0000between the average tropical surface air temperature (TSAT) and the average\u0000Northern Hemisphere SAT (NHSAT) is weak (0.08), but the CCM index of NHSAT\u0000cross mapped with TSAT is large (0.70). And this indicates that TSAT can be well\u0000reconstructed from NHSAT through machine learning. All results shown in this study could provide insights into machine-learning\u0000approaches for paleoclimate reconstruction, parameterization scheme, and\u0000prediction in related climate research. Highlights: i The coupling dynamics learned by machine learning can be used to reconstruct\u0000time series. ii Reconstruction quality is direction dependent and variable dependent for nonlinear\u0000systems. iii The CCM index is a potential indicator to choose reconstructed and\u0000explanatory variables. iv The tropical average SAT can be well reconstructed from the average Northern\u0000Hemisphere SAT.","PeriodicalId":11466,"journal":{"name":"Earth System Dynamics Discussions","volume":"1 1","pages":"835-853"},"PeriodicalIF":0.0,"publicationDate":"2020-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76489889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An investigation of weighting schemes suitable for incorporating large ensembles into multi-model ensembles","authors":"A. Merrifield, L. Brunner, R. Lorenz, I. Medhaug, R. Knutti","doi":"10.5194/ESD-11-807-2020","DOIUrl":"https://doi.org/10.5194/ESD-11-807-2020","url":null,"abstract":"Abstract. Multi-model ensembles can be used to estimate uncertainty in projections of regional climate, but this uncertainty often depends on the constituents of the ensemble. The dependence of uncertainty on ensemble composition is clear when single-model initial condition large ensembles (SMILEs) are included within a multi-model ensemble. SMILEs allow for the quantification of internal variability, a non-negligible component of uncertainty on regional scales, but may also serve to inappropriately narrow uncertainty by giving a single model many additional votes. In advance of the mixed multi-model, the SMILE Coupled Model Intercomparison version 6 (CMIP6) ensemble, we investigate weighting approaches to incorporate 50 members of the Community Earth System Model (CESM1.2.2-LE), 50 members of the Canadian Earth System Model (CanESM2-LE), and 100 members of the MPI Grand Ensemble (MPI-GE) into an 88-member Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble. The weights assigned are based on ability to reproduce observed climate (performance) and scaled by a measure of redundancy (dependence). Surface air temperature (SAT) and sea level pressure (SLP) predictors are used to determine the weights, and relationships between present and future predictor behavior are discussed. The estimated residual thermodynamic trend is proposed as an alternative predictor to replace 50-year regional SAT trends, which are more susceptible to internal variability. Uncertainty in estimates of northern European winter and Mediterranean summer end-of-century warming is assessed in a CMIP5 and a combined SMILE–CMIP5 multi-model ensemble. Five different weighting strategies to account for the mix of initial condition (IC) ensemble members and individually represented models within the multi-model ensemble are considered. Allowing all multi-model ensemble members to receive either equal weight or solely a performance weight (based on the root mean square error (RMSE) between members and observations over nine predictors) is shown to lead to uncertainty estimates that are dominated by the presence of SMILEs. A more suitable approach includes a dependence assumption, scaling either by  1∕N , the number of constituents representing a “model”, or by the same RMSE distance metric used to define model performance. SMILE contributions to the weighted ensemble are smallest (  %) when a model is defined as an IC ensemble and increase slightly (  %) when the definition of a model expands to include members from the same institution and/or development stream. SMILE contributions increase further when dependence is defined by RMSE (over nine predictors) amongst members because RMSEs between SMILE members can be as large as RMSEs between SMILE members and other models. We find that an alternative RMSE distance metric, derived from global SAT and hemispheric SLP climatology, is able to better identify IC members in general and SMILE members in particular as members of the s","PeriodicalId":11466,"journal":{"name":"Earth System Dynamics Discussions","volume":"6 1","pages":"807-834"},"PeriodicalIF":0.0,"publicationDate":"2020-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81371026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}