Grid-point Version Research Articles

Projections and patterns of heat-related mortality impacts from climate change in Southeast Asia

This study aims to investigate the impact of climate change on heat-related mortality in Southeast Asia in the future. The ensemble mean from five General Circulation Models (GCMs) including the Flexible Global Ocean-Atmosphere-Land System Model: Grid-Point Version 3 (FGOALS-g3), Max Planck Institute Earth System Model Version 1.2 (MPI-ESM1-2-LR), EC-Earth3, The Meteorological Research Institute Earth System Model Version 2.0 (MRI-ESM2-0), and Geophysical Fluid Dynamics Laboratory Earth System Model Version 4 (GFDL-ESM4) was used to project severe temperatures and heat indices in Southeast Asia under the Coupled Model Intercomparison Projects Phase 6 (CMIP6). This data was used to correlate with mortality data from the Global Burden of Disease database to quantify heat-related mortality in the region. The ensemble mean results show a reasonable level of accuracy in capturing temperature patterns in the Southeast Asian region with an R2 of 0.96, root mean square error (RMSE) of 0.84 and a standard deviation of residual (SDR) of 0.02. When compared to the baseline (1990–2019), temperature extreme indices are rising across all climatic scenarios, with a substantial increase in the SSP3–7.0 and SSP5–8.5 scenarios, ranging from 10% to 50% over the regions, with the heat index predicted to peak in the middle of the century. The two low-emission scenarios, SSP1-2.6 and SSP2-4.5, on the other hand, anticipate more moderate increases, indicating a potentially less severe impact on the region. As a result, under high-emission scenarios, there is expected to be a significant increase in heat-related mortality across Southeast Asia. The expected impact is estimated to affect between 200 and 300 people per 100,000 people from 2030 to 2079, accordingly. Our results highlight the critical need to address health-related impacts of climate change in this region.

Heat waves related to Quasi-Biweekly variability over Southern China in the FGOALS-g3 model

In the present study, we focused on the heat waves (HW) associated with the quasi-biweekly (QBW, 10–20-day period) variability (QBW-HW) over Southern China (SC, 102º–120ºE, 21º–30ºN) in the Flexible Global Ocean–Atmosphere–Land System Model, GridPoint version 3 (FGOALS-g3), and the HW-associated structures and surface air temperature budget investigated by using model outputs from historical experiment of Coupled Model Intercomparison Project Phase 6 (CMIP6). We found that the anomalous circulations related to the QBW-HW events over SC are closely linked to the southeastward propagation of the wave train from mid-high latitudes and the northwestward-propagating disturbances from the tropics. The results also showed that adiabatic and diabatic heating play a key role in the QBW-HW over SC. These results are in good agreement with observations from previous studies. In addition, QBW-HWs are dry in the FGOALS-g3 model, while observed humid HWs occur over SC. The difference is mainly due to the new boundary layer scheme incorporated in the FGOALS-g3 model, which overestimates the entrainment process at the top of the boundary layer during the QBW-HW over SC, resulting in more and drier air into the boundary layer, and thus less moisture. It implies that the entrainment equation at the top of the boundary layer in the FGOALS-g3 model does need to be improved to be suitable for humid HW processes, although the boundary layer scheme can improve the model precipitation and radiative forcing.

Role of Ocean Initialization in Skillful Prediction of Sahel Rainfall on the Decadal Time Scale

Abstract Sahel summer rainfall has undergone persistent drought from the 1970s to 1980s, causing severe human life and economic losses. Many studies pointed out that the decadal variations of Sahel rainfall are mainly modulated by low-frequency sea surface temperature (SST) variations in different ocean basins. However, how this modulation contributes to the decadal prediction skill of Sahel rainfall remains unknown. This study provided an affirmative response using the decadal hindcasts initialized by a dimensional-reduced projection four-dimensional variational (DRP-4DVar) data assimilation method to incorporate only ocean analysis data into the gridpoint version 2 of the Flexible Global Ocean–Atmosphere–Land System Model (FGOALS-g2). The hindcasts reveal the benefits of the DRP-4DVar approach for improving the Sahel rainfall decadal prediction skill measured by the anomaly correlation coefficient (ACC), root-mean-square error, ACC difference, and mean square skill score. The decadal variations of SSTs in the Atlantic, Mediterranean Sea, Indian Ocean, and Pacific as well as correct representations of the associated Sahel rainfall–SST relationships are well predicted, thus leading to skillful predictions of Sahel rainfall. In particular, the initialization of SSTs in the Atlantic and Mediterranean Sea plays a more important role in skillful Sahel rainfall predictions than in the other basins. The prediction skill of Sahel rainfall by the FGOALS-g2 prediction system is significantly higher than those by most phase 5 and 6 of the Coupled Model Intercomparison Project (CMIP5&6) prediction systems initialized only with ocean analysis data. This result is likely attributed to a more accurate relationship between Sahel rainfall and SST by the FGOALS-g2 prediction system than by the CMIP5&6 prediction systems. Significance Statement Previous studies have shown limited success in predicting Sahel rainfall. By using an advanced coupled data assimilation method constrained only by ocean observational data, we achieve a high decadal prediction skill for Sahel rainfall. The successful prediction is attributed to accurately predicted decadal variations of sea surface temperatures in the Atlantic, Mediterranean Sea, Indian Ocean, and Pacific as well as their relationships with Sahel rainfall. Our results can provide references for future decadal predictions of Sahel rainfall and motivate the need to evaluate the contributions of the initialization of the ocean versus the other climate components (e.g., atmosphere or land) to Sahel rainfall predictions.

Influence of the North American Dipole on ENSO onset as simulated by a coupled ocean–Atmosphere model

The North American Dipole (NAD) is a north–south seesaw pattern of sea level pressure anomalies over the western tropical North Atlantic and northeastern North America. Previous observational studies have demonstrated that the NAD can affect the outbreak of El Niño–Southern Oscillation (ENSO) events. The present study analyzed the NAD–ENSO relationship as simulated by a coupled ocean–atmosphere model—namely, the Flexible Global Ocean–Atmosphere–Land System model, gridpoint version 2 (FGOALS-g2). Results indicated that the model can replicate a distinct dipole comprised of a low over northeastern North America and a high over the western tropical North Atlantic, which is the signature feature of the NAD. Further analysis verified that the winter NAD can initiate the central equatorial Pacific warming in the subsequent winter by effectively forcing an anticyclonic flow and sea surface temperature (SST) warming over the northeastern subtropical Pacific (NESP) during late winter or early spring. In addition, the probability of an El Niño event was increased by a factor of 1.8 in the assimilation experiment with the NAD. By comparison, the winter Northern Atlantic Oscillation had no significant impact on the occurrence of ENSO a year later owing to its failure to induce the SST and surface wind anomalies over the NESP.摘要北美偶极子(NAD)是热带北大西洋西部和北美东北部的南北向海平面气压异常偶极型模态.以往的观测研究表明, NAD可以有效地影响ENSO事件的爆发. 本文利用全球耦合模式FGOALS-g2, 评估了NAD与ENSO的关系. 结果表明, 该模式能较好地重现NAD模态. 进一步的分析验证了冬季NAD可以通过强迫冬末春初副热带东北太平洋上空的反气旋和暖海温的出现, 在随后的冬季触发El Niño事件. 此外, 在同化NAD实验中, 发生El Niño事件的概率增加了将近一倍. 相比之下, NAO未能在副热带东北太平洋上空引起表面风和海温的异常, 因而不能有效地激发次年冬季ENSO事件.

CAS-LSM Datasets for the CMIP6 Land Surface Snow and Soil Moisture Model Intercomparison Project

The datasets of the five Land-offline Model Intercomparison Project (LMIP) experiments using the Chinese Academy of Sciences Land Surface Model (CAS-LSM) of CAS Flexible Global-Ocean-Atmosphere-Land System Model Grid-point version 3 (CAS FGOALS-g3) are presented in this study. These experiments were forced by five global meteorological forcing datasets, which contributed to the framework of the Land Surface Snow and Soil Moisture Model Intercomparison Project (LS3MIP) of CMIP6. These datasets have been released on the Earth System Grid Federation node. In this paper, the basic descriptions of the CAS-LSM and the five LMIP experiments are shown. The performance of the soil moisture, snow, and land-atmosphere energy fluxes was preliminarily validated using satellite-based observations. Results show that their mean states, spatial patterns, and seasonal variations can be reproduced well by the five LMIP simulations. It suggests that these datasets can be used to investigate the evolutionary mechanisms of the global water and energy cycles during the past century.

Simulated response of the active layer thickness of permafrost to climate change: 模拟多年冻土活动层厚度对气候变化的响应

The active layer thickness (ALT) in permafrost regions, which affects water and energy exchange, is a key variable for assessing hydrological processes, cold-region engineering, and climate change. In this study, the authors analyzed the variation trends and relative changes of simulated ALTs using the Chinese Academy of Sciences Land Surface Model (CAS-LSM) and the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System Model, gridpoint version 3 (CAS-FGOALS-g3). Firstly, the simulated ALTs produced by CAS-LSM were shown to be reasonable by comparing them with Circumpolar Active Layer Monitoring observations. Then, the authors simulated the ALTs from 1979 to 2014, and their relative changes across the entire Northern Hemisphere from 2015 to 2100. It is shown that the ALTs have an increasing trend. From 1979 to 2014, the average ALTs and their variation trends over all permafrost regions were 1.08 m and 0.33 cm yr−1, respectively. The relative changes of the ALTs ranged from 1% to 58%, and the average relative change was 10.9%. The variation trends of the ALTs were basically consistent with the variation trends of the 2-m air temperature. By 2100, the relative changes of ALTs are predicted to be 10.3%, 14.6%, 30.1%, and 51%, respectively, under the four considered hypothetical climate scenarios (SSP-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). This study indicates that climate change has a substantial impact on ALTs, and our results can help in understanding the responses of the ALTs of permafrost due to climate change.摘要在气候变化背景下, 活动层厚度的变化会对多年冻土区水文,生态,寒区工程等产生较大的影响.本研究利用中科院气候系统模式CAS-FGOALS-g3和陆面过程模式CAS-LSM 模拟分析了活动层厚度的变化趋势和相对变化.结果表明:活动层厚度整体上呈现出增加的趋势.1979 - 2014年, 多年冻土区活动层厚度的区域平均为1.08 m, 变化趋势为0.33 cm yr−1, 其变化趋势与2 m气温变化趋势基本一致, 相对变化范围为1%-58%, 平均为10.9%.在未来四种不同的气候情景(SSP-2.6,SSP2-4.5,SSP3-7.0和SSP5-8.5)下, 到2100年预计活动层厚度的相对变化分别为10.3%,14.6%,30.1%和51%.

Projecting the future vegetation–climate system over East Asia and its RCP-dependence

The future vegetation–climate system over East Asia, as well as its dependence on Representative Concentration Pathways (RCPs), is investigated using a regional climate–vegetation model driven with boundary conditions from Flexible Global Ocean–Atmosphere–Land System Model: Grid-point Version 2. Over most of the region, due to the rising CO2 concentration and climate changes, the model projects greater vegetation density (leaf area index) and gradual shifts of vegetation type from bare ground to grass or from grass to trees; the projected spatial extent of the vegetation shift increases from RCP2.6 to RCP8.5. Abrupt shifts are projected under RCP8.5 over northeast China (with grass replacing boreal needleleaf evergreen trees due to heat stress) and India (with tropical deciduous trees replacing grass due to increased water availability). The impact of vegetation feedback on future precipitation is relatively weak, while its impact on temperature is more evident, especially during DJF over northeast China and India with differing mechanisms. In northeast China, the projected forest loss induces a cooling through increased albedo, and daytime high temperature (Tmax) is influenced more than nighttime low temperature (Tmin); in India, increased vegetation cover induces an evaporative cooling that outweighs the warming effect of an albedo decrease in DJF, leading to a weaker impact on Tmax than on Tmin. Based on a single model, the qualitative aspects of these results may hold while quantitative assessment will benefit from a follow-up regional model ensemble study driven by multiple general circulation models.

FGOALS-g3 Model Datasets for CMIP6 Flux-Anomaly-Forced Model Intercomparison Project

The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) is an endorsed Model Intercomparison Project in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The goal of FAFMIP is to investigate the spread in the atmosphere-ocean general circulation model projections of ocean climate change forced by increased CO2, including the uncertainties in the simulations of ocean heat uptake, global mean sea level rise due to ocean thermal expansion and dynamic sea level change due to ocean circulation and density changes. The FAFMIP experiments have already been conducted with the Flexible Global Ocean-Atmosphere-Land System Model, gridpoint version 3.0 (FGOALS-g3). The model datasets have been submitted to the Earth System Grid Federation (ESGF) node. Here, the details of the experiments, the output variables and some baseline results are presented. Compared with the preliminary results of other models, the evolutions of global mean variables can be reproduced well by FGOALS-g3. The simulations of spatial patterns are also consistent with those of other models in most regions except the North Atlantic and the Southern Ocean, indicating large uncertainties in the regional sea level projections of these two regions.

CAS FGOALS-g3 Model Datasets for the CMIP6 Scenario Model Intercomparison Project (ScenarioMIP)

This paper describes the datasets from the Scenario Model Intercomparison Project (ScenarioMIP) simulation experiments run with the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System Model, GridPoint version 3 (CAS FGOALS-g3). FGOALS-g3 is driven by eight shared socioeconomic pathways (SSPs) with different sets of future emission, concentration, and land-use scenarios. All Tier 1 and 2 experiments were carried out and were initialized using historical runs. A branch run method was used for the ensemble simulations. Model outputs were three-hourly, six-hourly, daily, and/or monthly mean values for the primary variables of the four component models. An evaluation and analysis of the simulations is also presented. The present results are expected to aid research into future climate change and socio-economic development.

Reduced connection between the East Asian Summer Monsoon and Southern Hemisphere Circulation on interannual timescales under intense global warming

Previous studies show a close relationship between the East Asian Summer Monsoon (EASM) and Southern Hemisphere (SH) circulation on interannual timescales. In this study, we investigate whether this close relationship will change under intensive greenhouse-gas effect by analyzing simulations under two different climate background states: preindustrial era and Representative Concentration Pathway (RCP) 8.5 stabilization from the Community Climate System Model Version 4 (CCSM4). Results show a significantly reduced relationship under stabilized RCP8.5 climate state, such a less correlated EASM with the sea level pressure in the southern Indian Ocean and the SH branch of local Hadley Cell. Further analysis suggests that the collapse of the Atlantic Meridional Overturning Circulation (AMOC) due to this warming leads to a less vigorous northward meridional heat transport, a decreased intertropical temperature contrast in boreal summer, which produces a weaker cross-equatorial Hadley Cell in the monsoonal region and a reduced Interhemispheric Mass Exchange (IME). Since the monsoonal IME acts as a bridge connecting EASM and SH circulation, the reduced IME weakens this connection. By performing freshwater hosing experiment using the Flexible Global Ocean—Atmosphere—Land System model, Grid-point Version 2 (FGOALS-g2), we show a weakened relationship between the EASM and SH circulation as in CCSM4 when AMOC collapses. Our results suggest that a substantially weakened AMOC is the main driver leading to the EASM, which is less affected by SH circulation in the future warmer climate.

Percolation Phase Transition of Surface Air Temperature Networks: A new test bed for El Ni\xf1o/La Ni\xf1a simulations

In this work, we studied the air-sea interaction over the tropical central eastern Pacific from a new perspective, climate network. The surface air temperatures over the tropical Pacific were constructed as a network, and the nodes within this network were linked if they have a similar temporal varying pattern. Using three different reanalysis datasets, we verified the percolation phase transition. That is, when the influences of El Niño/La Niña are strong enough to isolate more than 48% of the nodes, the network may abruptly be divided into many small pieces, indicating a change of the network state. This phenomenon was reproduced successfully by a coupled general circulation model, Flexible Global Ocean-Atmosphere-Land System Model Spectral Version 2, but another model, Flexible Global Ocean-Atmosphere-Land System Model Grid-point Version 2, failed. As both models have the same oceanic component, but are with different atmospheric components, the improperly used atmospheric component should be responsible for the missing of the percolation phase transition. Considering that this new phenomenon is only recently noticed, current state-of-the-art models may ignore this process and induce unrealistic simulations. Accordingly, percolation phase transition is proposed as a new test bed, which deserves more attention in the future.

Hydrological Excitations of Polar Motion Derived from Different Variables of Fgoals − g2 Climate Model

Abstract The hydrological contribution to decadal, inter-annual and multi-annual suppress polar motion derived from climate model as well as from GRACE (Gravity Recovery and Climate Experiment) data is discussed here for the period 2002.3-2016.0. The data set used here are Earth Orientation Parameters Combined 04 (EOP C04), Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOAL-g2) and Global Land Data Assimilation System (GLDAS) climate models and GRACE CSR RL05 data for polar motion, hydrological and gravimetric excitation, respectively. Several Hydrological Angular Momentum (HAM) functions are calculated here from the selected variables: precipitation, evaporation, runoff, soil moisture, accumulated snow of the FGOALS and GLDAS climate models as well as from the global mass change fields from GRACE data provided by the International Earth Rotation and Reference System Service (IERS) Global Geophysical Fluids Center (GGFC). The contribution of different HAM excitation functions to achieve the full agreement between geodetic observations and geophysical excitation functions of polar motion is studied here.

Improved ENSO simulation from climate system model FGOALS-g1.0 to FGOALS-g2

This study presents an overview of the improvement in the simulation of El Nino–Southern Oscillation (ENSO) in the latest generation of the Institute of Atmospheric Physics’ coupled general circulation model (CGCM), the Flexible Global Ocean–Atmosphere–Land System model Grid-point Version 2 (FGOALS-g2; hereafter referred to as “g2”) from its predecessor FGOALS-g1.0 (referred to as “g1”), including the more realistic amplitude, irregularity, and ENSO cycle. The changes have been analyzed quantitatively based on the Bjerknes stability index, which serves as a measure of ENSO growth rate. The improved simulation of ENSO amplitude is mainly due to the reasonable representation of the thermocline and thermodynamic feedbacks: On the one hand, the deeper mean thermocline results in a weakened thermocline response to the zonal wind stress anomaly, and the looser vertical stratification of mean temperature leads to a weakened response of anomalous subsurface temperature to anomalous thermocline depth, both of which cause the reduced thermocline feedback in g2; on the other hand, the alleviated cold bias of mean sea surface temperature leads to more reasonable thermodynamic feedback in g2. The regular oscillation of ENSO in g1 is associated with its unsuccessful representation of the role of atmospheric noise over the western–central equatorial Pacific (WCEP) in triggering ENSO events, which arises from the weak synoptic–intraseasonal variability of zonal winds over the WCEP in g1. The asymmetric transition of ENSO in g1 is attributed to the asymmetric effect of thermocline feedback, which is due to the annual cycle of mean upwelling in the eastern Pacific. This study highlights the great impact of improving the representation of mean states on the improved simulation of air–sea feedback processes and ultimately more reasonable depiction of ENSO behaviors in CGCMs.

Quantifying contributions of model processes to the surface temperature bias in FGOALS‐g2

AbstractTo quantify the annual mean surface temperature bias due to various processes in Flexible Global Ocean‐Atmosphere‐Land‐System model, Grid point version 2 (FGOALS‐g2), the climate feedback‐response analysis method (CFRAM) is used to isolate contributions from both radiative and nonradiative processes in the model by comparing the model simulation with ERA‐Interim reanalysis. The observed surface temperature bias is decomposed into seven partial temperature biases associated with surface albedo, water vapor, cloud, both surface sensible and latent heat fluxes, land/ocean heat transport processes, and atmospheric transport processes. The global mean cold bias (−1.39 K) is mostly attributed to surface albedo and land/ocean heat transport processes while surface latent heat fluxes tend to weaken this bias. Cloud‐induced bias is dominated by shortwave cloud radiative effect (SWCRE) over low‐latitudes and longwave cloud radiative effect (LWCRE) over high latitudes. The mixed layer depth (MLD) bias is consistent with the bias due to ocean heat transport over North Pacific, North Atlantic, and the Southern Ocean. On global scale, contributions of radiative processes and nonradiative processes to the total observed cold bias are comparable, but tend to compensate each other over most regions except for the northern high latitudes. We suggest that the improvements in tropical clouds in the model may significantly decrease the global temperature bias through the interaction between clouds and circulation.

Different warming patterns of tropical Pacific sea surface temperature projected by FGOALS-g2 and FGOALS-s2 under RCP8.5

AbstractThe different patterns of SST changes under the +8.5 W m-2 Representative Concentration Pathway (RCP8.5) projected by the latest two versions of the Flexible Global Ocean-Atmosphere-Land System model (FGOALS-g2 and FGOALS-s2; grid-point version 2 and spectral version 2, respectively), and the potential mechanisms for their formation are studied in this paper. The results show that, although both FGOALS-g2 and FGOALS-s2 project global warming patterns, FGOALS-g2 (FGOALS-s2) projects a La Nina-like (an El Nino-like) mean warming pattern with weakest (strongest) warming over the central (eastern) equatorial Pacific for 2081–2100 relative to 1986–2005 under RCP8.5. A mixed layer heat budget analysis shows that the projected tropical Pacific Ocean warming in both models is primarily caused by atmospheric forcing. The main differences in the heating terms contributing to the SST changes between the two models are seen in the downward longwave radiation and ocean forcing. The minimum SST warming over the...

Evaluation of snow depth and snow cover fraction simulated by two versions of the flexible global ocean-atmosphere-land system model

Based on historical runs, one of the core experiments of the fifth phase of the Coupled Model Intercomparison Project (CMIP5), the snow depth (SD) and snow cover fraction (SCF) simulated by two versions of the Flexible Global Ocean-Atmosphere-Land System (FGOALS) model, Grid-point Version 2 (g2) and Spectral Version 2 (s2), were validated against observational data. The results revealed that the spatial pattern of SD and SCF over the Northern Hemisphere (NH) are simulated well by both models, except over the Tibetan Plateau, with the average spatial correlation coefficient over all months being around 0.7 and 0.8 for SD and SCF, respectively. Although the onset of snow accumulation is captured well by the two models in terms of the annual cycle of SD and SCF, g2 overestimates SD/SCF over most mid- and high-latitude areas of the NH. Analysis showed that g2 produces lower temperatures than s2 because it considers the indirect effects of aerosols in its atmospheric component, which is the primary driver for the SD/SCF difference between the two models. In addition, both models simulate the significant decreasing trend of SCF well over (30°-70°N) in winter during the period 1971–94. However, as g2 has a weak response to an increase in the concentration of CO2 and lower climate sensitivity, it presents weaker interannual variation compared to s2.

Variability of atlantic meridional overturning circulation in FGOALS-g2

The variability of Atlantic Meridional Overturning Circulation (AMOC) in the pre-industrial control experiment of the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 (FGOALS-g2) was investigated using the model outputs with the most stable state in a 512-yr time window from the total 1500-yr period of the experiment. The period of AMOC in FGOALS-g2 is double peaked at 20 and 32 years according to the power spectrum, and 22 years according to an auto-correlation analysis, which shows very obvious decadal variability. Like many other coupled climate models, the decadal variability of AMOC in FGOALS-g2 is closely related to the convection that occurs in the Labrador Sea region. Deep convection in the Labrador Sea in FGOALS-g2 leads the AMOC maximum by 3–4 years. The contributions of thermal and haline effects to the variability of the convection in three different regions [the Labrador, Irminger and Greenland-Iceland-Norwegian (GIN) Seas] were analyzed for FGOALS-g2. The variability of convection in the Labrador and Irminger Seas is thermally dominant, while that in the colder GIN Seas can be mainly attributed to salinity changes due to the lower thermal expansion. By comparing the simulation results from FGOALS-g2 and 11 other models, it was found that AMOC variability can be attributed to salinity changes for longer periods (longer than 35 years) and to temperature changes for shorter periods.

The mid-Pliocene climate simulated by FGOALS-g2

Abstract. Within the framework of Pliocene Model Intercomparison Project (PlioMIP), the mid-Pliocene warm period (mPWP – 3.264–3.025 Ma BP) climate simulated by the Flexible Global Ocean–Atmosphere–Land System model grid-point version g2 (FGOALS-g2) are analysed in this study. Results show that the model reproduces the large-scale features of the global warming over the land and ocean. The simulated mid-Pliocene global annual mean surface air temperature (SAT) and sea surface temperature (SST) are 4.17 and 2.62 °C warmer than the preindustrial simulation, respectively. In particular, the feature of larger warming over mid–high latitudes is well captured. In the simulated warm mid-Pliocene climate, the Atlantic Meridional Overturning Circulation (AMOC) and El Niño-Southern Oscillation (ENSO) become weaker.

An assessment of Indo-Pacific oceanic channel dynamics in the FGOALS-g2 coupled climate system model

Lag correlations of sea surface temperature anomalies (SSTAs), sea surface height anomalies (SSHAs), subsurface temperature anomalies, and surface zonal wind anomalies (SZWAs) produced by the Flexible Global Ocean-Atmosphere-Land System model: Grid-point Version 2 (FGOALS-g2) are analyzed and compared with observations. The insignificant, albeit positive, lag correlations between the SSTAs in the southeastern tropical Indian Ocean (STIO) in fall and the SSTAs in the central-eastern Pacific cold tongue in the following summer through fall are found to be not in agreement with the observational analysis. The model, however, does reproduce the significant lag correlations between the SSHAs in the STIO in fall and those in the cold tongue at the one-year time lag in the observations. These, along with the significant lag correlations between the SSTAs in the STIO in fall and the subsurface temperature anomalies in the equatorial Pacific vertical section in the following year, suggest that the Indonesian Throughflow plays an important role in propagating the Indian Ocean anomalies into the equatorial Pacific Ocean. Analyses of the interannual anomalies of the Indonesian Throughflow transport suggest that the FGOALS-g2 climate system simulates, but underestimates, the oceanic channel dynamics between the Indian and Pacific Oceans. FGOALS-g2 is shown to produce lag correlations between the SZWAs over the western equatorial Pacific in fall and the cold tongue SSTAs at the one-year time lag that are too strong to be realistic in comparison with observations. The analyses suggest that the atmospheric bridge over the Indo-Pacific Ocean is overestimated in the FGOALS-g2 coupled climate model.

The flexible global ocean-atmosphere-land system model, Grid-point Version 2: FGOALS-g2

This study mainly introduces the development of the Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOALS-g2) and the preliminary evaluations of its performances based on results from the pre-industrial control run and four members of historical runs according to the fifth phase of the Coupled Model Intercomparison Project (CMIP5) experiment design. The results suggest that many obvious improvements have been achieved by the FGOALS-g2 compared with the previous version,FGOALS-g1, including its climatological mean states, climate variability, and 20th century surface temperature evolution. For example,FGOALS-g2 better simulates the frequency of tropical land precipitation, East Asian Monsoon precipitation and its seasonal cycle, MJO and ENSO, which are closely related to the updated cumulus parameterization scheme, as well as the alleviation of uncertainties in some key parameters in shallow and deep convection schemes, cloud fraction, cloud macro/microphysical processes and the boundary layer scheme in its atmospheric model. The annual cycle of sea surface temperature along the equator in the Pacific is significantly improved in the new version. The sea ice salinity simulation is one of the unique characteristics of FGOALS-g2, although it is somehow inconsistent with empirical observations in the Antarctic.