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Abrupt enhancement of convective activity over the subtropical western North Pacific around 20°N, 150°E is known as the convection jump (CJ) caused by the ocean–atmosphere coupling, which is one of the important factors inducing the end of the Baiu season in Japan. Using atmospheric reanalysis and observation data for 1974 – 2021, this diagnosis is made for the influences of Rossby wave propagation and breaking, high-potential vorticity (PV) intrusion, and cutoff lows over the western North Pacific on CJ occurrence. Preceding CJ occurrence, southeastward Rossby-wave propagation is discernible along the upstream of the mid-Pacific trough in the upper troposphere, and its energy accumulates over the northeast of the CJ region. The subsequent wave breaking near the exit region of the Asian jet induces the southwestward intrusion of high-PV airmass toward the northeast of the CJ region, which is concurrent with the enhancement of convective activity. The high-PV intrusion may also be interpreted as westward-moving, upper-level cutoff lows migrating from the mid-Pacific trough. The diagnosis of Q-vector indicates that variations in the extratropical upper-tropospheric circulation induce dynamical ascent, contributing to the onset and maintenance of convective activity over the CJ region. Moreover, the PV budget analysis suggests that the persistent positive advection of PV at the edge of the high-PV intrusion nearly counterbalances the intense low-PV generation by diabatic heating associated with the CJ. These results indicate that the CJ is influenced by extratropical upper-tropospheric variations as well as the coupled atmosphere–ocean system in the subtropical western North Pacific. [ABSTRACT FROM AUTHOR]

The Greenland Sea is a key region for open ocean convection and ventilation, which exhibit a large variability with periods of strong convection and shutdowns. After a long period of weak winter convection (from the 1970s to the early 1990s), a recovery has been reported, beginning in the 1990s and intensifying in the early 2000s until 2013. Using ISAS, an optimal interpolation product based on Argo observations, we document a recent significant weakening of deep convection between 2014 and 2020, accompanied by a continuous warming of the mixed layer but also a freshening after 2014. These hydrographic changes likely increase the ocean stratification and precondition the shutdown of winter convection. We suggest that these property changes result from a shift of the large scale atmospheric circulation, affecting the source of Atlantic Water to the Nordic seas, causing a freshening of about −0.1 g kg−1 that spreads into the Greenland Sea. Plain Language Summary: The Greenland Sea is a key region for the climate system. There, during winter, the ocean loses heat to the atmosphere in a process called "deep convection," that results in the formation of dense water masses that ventilate and fill the deeper layers of the ocean. The Greenland Sea exhibits a high variability in the intensity of winter deep convection, but the scientific community is still debating on which processes trigger or stop convection. After a recovery period of convection, mainly in the beginning of the 21st century, convection has stopped again after 2014 and at least until 2020. Here, we suggest that this new shutdown is mainly caused by changes in the ocean upper layer temperature and salinity that increase the upper ocean buoyancy, making it more difficult to trigger deep convection during winter. We further propose that the main mechanism driving the ocean properties changes is a shift of the large scale atmospheric circulation, which affects the amount and properties of Atlantic Water transported to the Greenland Sea. Key Points: After a period of intense deep convection since 2002, convection in the Greenland Sea has weakened from 2014 to 2020The upper salinity and temperature in the months prior of convection are driving the deep convection variabilityThe upper salinity changes are resulting from changes in large scale pattern of advection [ABSTRACT FROM AUTHOR]

The HVAC control panels of a sample of 10 passenger cars were investigated and evaluated in terms of the type and layout of the controls. The evaluation method of the layout for the same task execution is based on Keystroke Level Model (KLM). According to this method, the results in the manual adjustment of the AC parameters with rotary knobs were better than in the panel with the push buttons, for the same function. The automatic AC control significantly reduces the time and number of actions, thus reducing the driver's workload for the HVAC setting. However, the automatic operation could not provide preferable thermal conditions under some conditions or because of individual preferences, making a manual readjustment necessary

In this work, the Max Planck Institute for Meteorology Grand Ensemble (MPI-GE) is used to quantify the climate system’s internal variability. The MPI-GE is a large ensemble of a single state-of-the-art comprehensive climate model and its use is crucial to evaluate average changes in summer monthly means and extreme temperatures. Initially, model simulations are examined in terms of their ability to accurately reproduce the observed climatic regimes in the Mediterranean region for the historical period. The ERA5 reanalysis dataset is employed as a reference and the corresponding trends and frequencies of occurrence of temperature-extreme events are compared between these datasets. Subsequently, the MPI-GE is used as a tool for examining the effect of the climate system’s internal variability focusing on the Mediterranean summer temperatures under different levels of global warming. Understanding and decoupling the effects of internal variability and anthropogenic forcing on climate trends remain a key challenge. It is found that in the rcp8.5 scenario, the frequency of summer extreme temperatures is higher than that in the rcp2.6 scenario. Especially in the Greek region, the frequency is 1.5 times higher in rcp8.5 than in rcp2.6

Abstract For the purpose of identifying the key processes and sectors involved in the interaction between Earth and socio-economic systems, we review existing studies on those processes/sectors through which the climate impacts socio-economic systems, which then in turn affect the climate. For each process/sector, we review the direct physical and ecological impacts and, if available, the impact on the economy and greenhouse gas (GHG) emissions. Based on this review, land sector is identified as the process with the most significant impact on GHG emissions, while labor productivity has the largest impact on the gross domestic product (GDP). On the other hand, the energy sector, due to the increase in the demand for cooling, will have increased GHG emissions. Water resources, sea level rise, natural disasters, ecosystem services, and diseases also show the potential to have a significant influence on GHG emissions and GDP, although for most of these, a large effect was reported only by a limited number of studies. As a result, more studies are required to verify their influence in terms of feedbacks to the climate. In addition, although the economic damage arising from migration and conflict is uncertain, they should be treated as potentially damaging processes.

A model of ground surface heat exchange explaining the observed delay in temperature response to external radiation variations has been proposed. According to the model, the phase shift between external radiative forcing and surface temperature for a homogeneous half-space is 45°. The phase shift decreases if there is a low-conductive layer at the Earth's surface. The model verification has been conducted using meteorological data, actinometric data, temperature data from soil monitoring (for 1-day to 11-year cycles), and empirical data on the delay in temperature response to long-term variations in external radiative forcing (orbital cycles). The verification has indicated that the proposed model can explain most of the observed time delays for different-scale radiative forcings; i.e., this is the most versatile model without ignoring other mechanisms that are specific for different time scales and geographical situations. [ABSTRACT FROM AUTHOR]

The Earth climate system has an intrinsic mechanism to maintain its energy conservation by impelling opposite changes in meridional ocean and atmosphere heat transports. This mechanism is briefed as the Bjerknes compensation (BJC). We set up a global coupled two-hemisphere box model in this study, and obtain an analytical solution to the BJC of this system. In the two-hemisphere model, the thermohaline circulation is interhemispheric and parameterized by the density difference between two polar boxes. The symmetric poleward atmosphere heat and moisture transports are considered and parameterized by the temperature gradient between tropical and polar boxes. Different from the BJC in the one-hemisphere box model that depends only on the local climate feedback, the BJC here is determined by both local climate feedback and temperature change. The asymmetric thermohaline circulation leads to a better BJC in the Northern Hemisphere than in the Southern Hemisphere. Furthermore, an analytical solution to the probability of a valid BJC (i.e., negative BJC) is derived, which is determined only by the local climate feedback. The probability of a valid BJC is very high under reasonable climate feedback. Based on observational data, the climate feedback can be estimated and the BJC in real world can be calculated using the analytical formulae. It is found that at the decadal and longer timescales the BJC for both hemispheres are robust in reality. [ABSTRACT FROM AUTHOR]

Climate change and variability remain a pressing global challenge directly and indirectly affecting human health. This has increased the demand for usable climate information for adaptation to climate related health challenges and for building effective response strategies. Climate services for health can help to enhance human well-being and in extreme cases can save human lives by reducing morbidity and mortality. Very little has been done and understood about how we can enhance climate services for health. The main aim of this perspective article is to bring empirical evidence, conceptual clarity and interdisciplinary approaches to policy makers and practitioners dealing with this crucial issue. The article explores the application of a holistic, broadly termed ‘systems’ approach to climate services for health in the context of adaptation and resilience. It uses illustrative examples from Ethiopia, Bhutan and Germany to demonstrate and elaborate the application and merits of the systems approach to emerging climate services for health. The systems approach improves conceptual thinking about climate services for health. In addition, it is a valuable analytical framework that unifies the diverse stakeholders involved in health adaptation and resilience planning, interventions and policy making. This perspective article fills in the existing gaps in scientific literature on the subject and enhances conceptualisation of climate services for health. It makes suggestions to improve understanding of climate services for health.

The object of the study is the cabins of technological machines, where an unfavorable microclimate is observed. The method of mathematical and computer modeling used in the study is relevant and allows significantly speed up the design process due to the transition from a large number of field tests to virtual numerical experiments. The adaptation of the known mathematical models of thermal radiation and a model of a continuous medium based on the Navier-Stokes and heat transfer equations to the solution of the problem of determining the thermodynamic parameters in the cabins of technological machines has been carried out. The methodology for calculating and selecting the main equipment of the climatic system of the crane cabins has been clarified based on the developed finite element 3D models of the cabins. In addition, thermal protection equipment was used to reduce the load on the climate system. The using of modeling permit significantly speeds up the design process.

The paleotemperature curves for water masses and average annual temperatures have been plotted for the first time on the basis of original and published data for the Central and Eastern Tethys for the Jurassic–Quaternary period. [ABSTRACT FROM AUTHOR]

The derivatives of the annual average temperature are analyzed based on data from 927 weather stations of the Northern Hemisphere from 1955 to 2016. Changes in the derivatives are considered as manifestations of the emergent property of the holistic climate system. A measure for these manifestations is introduced. It has a form of a functional which includes averaging of positive and negative derivatives and calculation of their correlation coefficients. It is established that the sampling distribution of sums of opposite extreme values of derivatives of the annual average temperature is symmetric and has a larger kurtosis than a normal distribution. In the period under study, the values of the measure are already close to their limit values. Therefore, annual estimation of changes in the measure of emergent properties in the multichannel monitoring system is necessary. [ABSTRACT FROM AUTHOR]

We present the results of a geochemical study and their paleogeographic and paleoclimatic interpretation for a cyclically constructed section of the Upper Cretaceous deposits near Staryi Oskol in the Belgorod region. [ABSTRACT FROM AUTHOR]

The climate is a complex, chaotic system with many degrees of freedom. Attaining a deeper level of understanding of climate dynamics is an urgent scientific challenge, given the evolving climate crisis. In statistical physics, many-particle systems are studied using Large Deviation Theory (LDT). A great potential exists for applying LDT to problems in geophysical fluid dynamics and climate science. In particular, LDT allows for understanding the properties of persistent deviations of climatic fields from long-term averages and for associating them to low-frequency, large-scale patterns. Additionally, LDT can be used in conjunction with rare event algorithms to explore rarely visited regions of the phase space. These applications are of key importance to improve our understanding of high-impact weather and climate events. Furthermore, LDT provides tools for evaluating the probability of noise-induced transitions between metastable climate states. This is, in turn, essential for understanding the global stability properties of the system. The goal of this review is manifold. First, we provide an introduction to LDT. We then present the existing literature. Finally, we propose possible lines of future investigations. We hope that this paper will prepare the ground for studies applying LDT to solve problems encountered in climate science and geophysical fluid dynamics. [ABSTRACT FROM AUTHOR]

For the purpose of identifying the key processes and sectors involved in the interaction between Earth and socio-economic systems, we review existing studies on those processes/sectors through which the climate impacts socio-economic systems, which then in turn affect the climate. For each process/sector, we review the direct physical and ecological impacts and, if available, the impact on the economy and greenhouse gas (GHG) emissions. Based on this review, land sector is identified as the process with the most significant impact on GHG emissions, while labor productivity has the largest impact on the gross domestic product (GDP). On the other hand, the energy sector, due to the increase in the demand for cooling, will have increased GHG emissions. Water resources, sea level rise, natural disasters, ecosystem services, and diseases also show the potential to have a significant influence on GHG emissions and GDP, although for most of these, a large effect was reported only by a limited number of studies. As a result, more studies are required to verify their influence in terms of feedbacks to the climate. In addition, although the economic damage arising from migration and conflict is uncertain, they should be treated as potentially damaging processes. [ABSTRACT FROM AUTHOR]

The premise of this article is based on an assertion that Engels made in which he stated that "nature works dialectically." In exploring this extraordinary proposal, it is illuminating to examine Engels's own in-depth analysis of unfinished chapter he wrote on the "natural conditions" of Ireland. Within, we observe that concrete organic reality is not a solid thing-like entity but a complex matrix of interconnecting processes that form an organic totality. The organic processes of nature, according to Engels and Marx, are dominated by the climatic process, that "life-awakening force" of soil fertility. However, what determines the form of the local weather system (the local manifestation of the climatic process) is how that system interconnects with the other organic processes of nature—geological structures, vegetation and the soil processes. Subsequently, they all form internal moments of that overall climatic process. The existence of a dialectical reality has profound implications for how we can conceptualise that reality and even more critically how we physically relate to and engage with that dialectical reality, especially when we cultivate those fluid and interconnected forces in agricultural production. [ABSTRACT FROM AUTHOR]

Natural climate variability is partially attributed to solar radiative forcing. The purpose of this study is to contribute to a better understanding of the influence of solar variability on the Earth’s climate system. The object of this work is the estimation of the variation of multiple climatic parameters (temperature, zonal wind, relative and specific humidity, sensible and latent surface heat flux, cloud cover and precipitable water) in response to solar cycle forcing. An additional goal is to estimate the response of the climate system’s parameters to short-term solar variability in multiple forecasting horizons and to evaluate the behavior of the climate system in shorter time scales. The solar cycle is represented by the 10.7 cm solar flux, a measurement collected by terrestrial radio telescopes, and is provided by NOAA/NCEI/STP, whereas the climatic data are provided by the NCEP/NCAR reanalysis 1 project. The adopted methodology includes the development of a linear regression statistical model in order to calculate the climatic parameters’ feedback to the 11-year solar cycle on a monthly scale. Artificial Neural Networks (ANNs) have been employed to forecast the solar indicator time series for up to 6 months in advance. The climate system’s response is further forecasted using the ANN’s estimated values and the regression equations. The results show that the variation of the climatic parameters can be partially attributed to solar variability. The solar-induced variation of each of the selected parameters, averaged globally, was of an order of magnitude of 10−1–10−3, and the corresponding correlation coefficients (Pearson’s r) were relatively low (−0.5–0.5). Statistically significant areas with relatively high solar cycle signals were found at multiple pressure levels and geographical areas, which can be attributed to various mechanisms.

The anthropogenic impact on the Earth's climate system is currently one of the main factors determining climate change over all spatial scales, from local to global. Many scientific investigations have been devoted to the direct and indirect influence of various types of human activity on the state of the Earth's climate system (ECS). Feedbacks that enhance or weaken anthropogenic effects during global warming have been studied in sufficient detail with the help of climate models. Regional models of climatic and meteorological processes that make possible detailed description of the climate properties in urban agglomerations and the role of feedbacks in the development of mesoscale atmospheric processes have been widely developed in recent years. This review is devoted to the description and analysis of mesoscale feedbacks in the climate system, including the energy consumption of an urban economy, which depends on climatic and weather conditions, and the role of these feedbacks in the formation and dynamics of the urban climate and the needs of an urban economy in regards to energy supply. [ABSTRACT FROM AUTHOR]

Systematically observing components of the climate system as well as their processes and interactions are crucial to understand the weather, climate, climate change, etc. In order to launch long-term, continuous, stereoscopic, and integrated meteorological observations for key regions of the climate system in southwestern China where it is sensitive to interactions among multiple layers and exchanges of mass and energy, the Dali National Climate Observatory (DNCO) was established in May 2006. To date, the DNCO has gradually performed an integrated meteorological observation network in a complex terrain region over the southeastern Tibetan Plateau including the conventional observations of weather and climate, and the special observations of radiation, lightning, soil moisture, wind profile, water vapor, water quality, water level, water temperature profile, turbulent fluxes of momentum, sensible heat, latent heat, carbon dioxide, and methane, etc. Furthermore, the DNCO mainly focuses on the field observation experiments and scientific research activities for mountain meteorology. This paper presents an overview of the DNCO including its location, climatology, scientific objectives, research tasks, and existing observation projects. The progresses in observation and associated research including data quality controls and assessments, recent observation results, and regional numerical model tests are summarized. Future works are also discussed.

The structure of main modes of the decadal and multidecadal variability of the Atlantic meridional overturning circulation (AMOC) is analyzed for the climate models INM-CM5 (INM RAS), CCSM4 (NCAR), MPI-LR and MPI-MR (MPI). It is shown that oscillations with characteristic periods of 25–35 and 50–70 years are recognized in the models, and the corresponding spatial structures are variations of the intensity and position of the AMOC. Relations connecting changes of thermohaline circulation with external impacts on the system are constructed for the above models. The analysis of stability of calculations relative to the length of data series used for calculations is performed. The optimal impacts leading to the greatest response of the AMOC and influence functions causing its response along the leading modes of low-frequency variability are constructed. The optimal impacts have the form of density anomalies localized in the North Atlantic, and the structures of the corresponding responses are dominated by leading low-frequency modes of variability. The structure of optimal impacts varies greatly from model to model. [ABSTRACT FROM AUTHOR]

We conducted a model-based assessment of changes in permafrost area and carbon storage for simulations driven by RCP4.5 and RCP8.5 projections between 2010 and 2299 for the northern permafrost region. All models simulating carbon represented soil with depth, a critical structural feature needed to represent the permafrost carbon-climate feedback, but that is not a universal feature of all climate models. Between 2010 and 2299, simulations indicated losses of permafrost between 3 and 5 million km2 for the RCP4.5 climate and between 6 and 16 million km2 for the RCP8.5 climate. For the RCP4.5 projection, cumulative change in soil carbon varied between 66-Pg C (1015-g carbon) loss to 70-Pg C gain. For the RCP8.5 projection, losses in soil carbon varied between 74 and 652 Pg C (mean loss, 341 Pg C). For the RCP4.5 projection, gains in vegetation carbon were largely responsible for the overall projected net gains in ecosystem carbon by 2299 (8- to 244-Pg C gains). In contrast, for the RCP8.5 projection, gains in vegetation carbon were not great enough to compensate for the losses of carbon projected by four of the five models; changes in ecosystem carbon ranged from a 641-Pg C loss to a 167-Pg C gain (mean, 208-Pg C loss). The models indicate that substantial net losses of ecosystem carbon would not occur until after 2100. This assessment suggests that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon-climate feedback. [ABSTRACT FROM AUTHOR]

The present study reports a low-rank and sparse decomposition method that separates the mean and the variability of a climate data field. Until now, the application of this technique was limited only in areas such as image processing, web data ranking, and bioinformatics data analysis. In climate science, this method exactly separates the original data into a set of low-rank and sparse components, wherein the low-rank components depict the linearly correlated dataset (expected or mean behavior), and the sparse component represents the variation or perturbation in the dataset from its mean behavior. The study attempts to verify the efficacy of this proposed technique in the field of climatology with two examples of real world. The first example attempts this technique on the maximum wind-speed (MWS) data for the Indian Ocean (IO) region. The study brings to light a decadal reversal pattern in the MWS for the North Indian Ocean (NIO) during the months of June, July, and August (JJA). The second example deals with the sea surface temperature (SST) data for the Bay of Bengal region that exhibits a distinct pattern in the sparse component. The study highlights the importance of the proposed technique used for interpretation and visualization of climate data. [ABSTRACT FROM AUTHOR]

The climate system is driven by internal and external forcings. Among the prime external forcings is the solar radiation, while the human activity is included among the principal intrinsic forcings. This means that basic components of nature and society are substantial parameters of the evolution of the climate system. Therefore, the consideration of the nature and society as a separate system, the nature-society system, will provide a new tool for the investigation of the climate system variability. This paper is focused on the modelling of the evolution of the nature-society system, when considering a series of major natural and anthropogenic processes including several solar–terrestrial coupling mechanisms, biogeochemical cycles, physical processes operating in the terrestrial atmosphere, global climate change, global hydrologic balance and photosynthesis in ocean ecosystems. Among the main goals of this model is to estimate the survivability of the nature-society system under the conditions of limited energy resources. A series of simulation experiments are presented herein demonstrating the ability of the model to operate satisfactorily and reliably under various anthropogenic scenarios. [ABSTRACT FROM AUTHOR]

This paper reports part of a larger study on the development of systems thinking skills in German 7th grade comprehensive school students regarding the climate. Research has shown a fragmented understanding of climate change among students that hardly accounts for the dynamic interrelations in the climate system and may pose a barrier in understanding adaptation and mitigation strategies (Shepardson et al. 2017, 2011, Calmbach 2016). While much is known the impact of short-term interventions on the general system understanding of students, what is lacking to date is 1) a specific intervention on climate system understanding and 2) insights into the process of developing system understanding in students. Helpful insights in this context come from Conceptual Development theories for they allow the development of systemic thinking to be viewed in terms of conceptual expansion or conceptual change. Starting from these desiderates, a teaching-learning sequence was developed based on the SYSDENE model of system competence (Frischknecht et al. 2008). In the sequence young learners systematically link experiences from formal science education with the experiences at three non-formal learning environments. A mixed-methods approach was used to explore the impact of this 3-month sequence on 19 7th grade students. A written pre-/post-test suggested a significant improvement in Climate System Reconstruction for the group (pre-test Median = 6.75 vs. post-test Median = 12.5, Wilcoxon Test: p =.003, r =.82). However, a qualitative analysis of classroom conversations, interviews and concept maps indicated that cognitive development toward a higher level of system thinking was neither continuous nor did every student reach it. Moreover, the SYSDENE model's Competence Area "Describe System Model" proves critical. Being able to describe the main climate system factors is not sufficient, one also needs to be able to distinct weather from climate and grasp several scientific concepts related to the climate (e.g. greenhouse effect, water cycle, evaporation, reflection) in order to understand climate as a system. [ABSTRACT FROM AUTHOR]

In the present study, the LASG/IAP Climate system Ocean Model version 2 (LICOM2) was implemented to replace the original ocean component in the Community Earth System Model version 1.0.4 (CESM1) to form a new coupled model referred to as CESM1+LICOM2. The simulation results from a 300-yr preindustrial experiment by using this model were evaluated against both observations and the Flexible Global Ocean-Atmosphere-Land System Model with grid-atmospheric model version 2 (FGOALS-g2). It was found that CESM1+LICOM2 simulates well the mean features of the ocean, sea ice, and atmosphere, relative to models used in the Coupled Model Intercomparison Experiment (CMIP5), when compared with observations. The spatial distribution of SST bias in CESM1+LICOM2 is similar to that in the Community Climate System Model version 4 (CCSM4). The simulated climate variabilities, such as ENSO and Pacific decadal oscillation, are also reasonably simulated when compared with observations. The successful implementation of LICOM2 in the CESM1 framework greatly enhances the capability of LICOM2 in conducting high-resolution simulations and model tuning. Compared with FGOALS-g2, the simulations of both SST and Atlantic meridional overturning circulation are significantly improved in CESM1+LICOM2. The former can be mainly attributed to the atmospheric model, and the latter to the improvement in the parameterization of diapycnal mixing. The study provides a base to further improve the present version of LICOM and its functionalities in the coupled model FGOALS at both low and high resolutions. [ABSTRACT FROM AUTHOR]

Using the low-resolution (T31, equivalent to 3.75° × 3.75°) version of the Community Earth System Model (CESM) from the National Center for Atmospheric Research (NCAR), a global climate simulation was carried out with fixed external forcing factors (1850 Common Era. (C.E.) conditions) for the past 2000 years. Based on the simulated results, spatio-temporal structures of surface air temperature, precipitation and internal variability, such as the El Niño-Southern Oscillation (ENSO), the Atlantic Multi-decadal Oscillation (AMO), the Pacific Decadal Oscillation (PDO), and the North Atlantic Oscillation (NAO), were compared with reanalysis datasets to evaluate the model performance. The results are as follows: 1) CESM showed a good performance in the long-term simulation and no significant climate drift over the past 2000 years; 2) climatological patterns of global and regional climate changes simulated by the CESM were reasonable compared with the reanalysis datasets; and 3) the CESM simulated internal natural variability of the climate system performs very well. The model not only reproduced the periodicity of ENSO, AMO and PDO events but also the 3-8 years variability of the ENSO. The spatial distribution of the CESM-simulated NAO was also similar to the observed. However, because of weaker total irradiation and greenhouse gas concentration forcing in the simulation than the present, the model performances had some differences from the observations. Generally, the CESM showed a good performance in simulating the global climate and internal natural variability of the climate system. This paves the way for other forced climate simulations for the past 2000 years by using the CESM. [ABSTRACT FROM AUTHOR]