Indian Ocean variability in the CMIP5 multi-model ensemble: the zonal dipole mode

The performance of 21 Coupled Model Intercomparison Project Phase 5 (CMIP5) models in the simulation of the Indian Ocean Dipole (IOD) mode is evaluated. Compared to CMIP3, CMIP5 models exhibit a similar spread in IOD intensity. A detailed diagnosis was carried out to understand whether CMIP5 models have shown improvement in their representation of the important dynamical and thermodynamical feedbacks in the tropical Indian Ocean. These include the Bjerknes dynamic air-sea feedback, which includes the equatorial zonal wind response to sea surface temperature (SST) anomaly, the thermocline response to equatorial zonal wind forcing, the ocean subsurface temperature response to the thermocline variations, and the thermodynamic air-sea coupling that includes the wind-evaporation-SST and cloud-radiation-SST feedback. Compared to CMIP3, the CMIP5 ensemble produces a more realistic positive wind-evaporation-SST feedback during the IOD developing phase, while the simulation of Bjerknes dynamic feedback is more unrealistic especially with regard to the wind response to SST forcing and the thermocline response to surface wind forcing. The overall CMIP5 performance in the IOD simulation does not show remarkable improvements compared to CMIP3. It is further noted that the El Niño-Southern Oscillation (ENSO) and IOD amplitudes are closely related, if a model generates a strong ENSO, it is likely that this model also simulates a strong IOD.     

The Indian Ocean subtropical dipole mode simulated in the CMIP3 models

Using observation data and outputs from the “twentieth-century climate in coupled models” (20c3m) control runs of coupled general circulation models submitted to the Coupled Model Intercomparison Project, phase 3 (CMIP3), the ability of CMIP3 models to simulate the Indian Ocean subtropical dipole (IOSD) and its influence on the rainfall anomaly over the southern African region is investigated. Many models simulate the IOSD, but the location and shape of the sea surface temperature anomaly vary among models. This model bias is closely linked to the bias in simulating the anomalous strengthening and southward shift of the subtropical high. Almost all models fail to simulate the rainfall anomaly associated with the IOSD owing to the inaccurate simulation of the location of sea surface temperature and sea level pressure anomalies.     

Future change of global monsoon in the CMIP5

This study investigates future changes of Global Monsoon (GM) under anthropogenic global warming using 20 coupled models that participated in the phase five of Coupled Model Intercomparison Project (CMIP5) by comparing two runs: the historical run for 1850–2005 and the Representative Concentration Pathway (RCP) 4.5 run for 2006–2100. A metrics for evaluation of models’ performance on GM is designed to document performance for 1980–2005 and best four models are selected. The four best models’ multi-model ensemble (B4MME) projects the following changes in the twenty-first century under the RCP4.5 scenario. (1) Monsoon domain will not change appreciably but land monsoon domain over Asia tends to expand westward by 10.6 %. (2) The annual mean and range of GM precipitation and the percentage of local summer rainfall will all amplify at a significant level over most of the global region, both over land and over ocean. (3) There will be a more prominent northern-southern hemispheric asymmetry and eastern-western hemispheric asymmetry. (4) Northern Hemisphere (NH) monsoon onset will be advanced and withdrawal will be delayed. (5) Changes in monsoon precipitation exhibits huge differences between the NH and the Southern hemisphere (SH). The NH monsoon precipitation will increase significantly due to increase in temperature difference between the NH and SH, significant enhancement of the Hadley circulation, and atmospheric moistening, against stabilization of troposphere. There is a slight decrease of the Walker circulation but not significant against the inter-model spread. There are important differences between the CMIP 3 and CMIP5 results which are discussed in detail.     

ENSO modes of the equatorial Pacific Ocean in observations and CMIP5 models

El Niño/Southern Oscillation (ENSO) is the predominant interannual variability of the global climate system. How might ENSO change in a warmer world? The dominant two Combined Empirical Orthogonal Functions (CEOF) of the equatorial ocean temperature and zonal and vertical motion identify two modes that shown a transition in the eastern Pacific from a warming eastward/downward motion to a cooling westward/upward flow. These results also suggest consistent changes to the west and at depths down to 300 m. These dominate CEOFs provide a compact tool for assessing Coupled Model Intercomparison Project Phase 5 ocean model output for both the recent historical period and for the latter part of the twenty first century. Most of the analyzed models replicate well the spatial patterns of the dominant observational CEOF modes, but nearly always underestimate the magnitudes. Comparing model output for the twentieth and twenty first centuries there is very little change between the spatial patterns of the ENSO modes of the two periods. This lack of response to climate change is shown to be partly related to competing influences of climatic changes in the mean ocean circulation.     

热带印度洋偶极子与中国夏季年际气候异常关系的年代际变化

利用中国站点观测逐月降水和月平均气温资料以及NCEP/NCAR再分析资料,揭示了热带印度洋偶极子(IOD)与中国夏季气候异常关系的年代际变化.结果表明:IOD与中国夏季年际气候异常的关系既有稳定的一面,又存在着年代际变化.较为稳定的关系表现为:IOD与同年夏季长江黄河之间的降水变化存在显著负相关,与四川气温变化存在显著正相关;IOD与次年夏季四川降水存在显著正相关.伴随发生在20世纪70年代末的大尺度环流年代际转型,IOD与中国气候年际异常的联系亦发生变化:IOD正位相年的同年夏季降水异常型,由中国大部分地区偏少变为长江以南(北)偏多(少),气温由西南地区东部偏暖变为长江以南(北)偏冷(暖);次年夏季降水由全国大部分地区偏多变为长江以南(北)偏少(多),气温由全国大部分地区相关不显著变为黄河以南大部分地区显著偏暖.在IOD负位相年,中国夏季气候异常的特征与IOD正位相年相反.在20世纪70年代末的大尺度年代际气候转犁前后,与IOD相关的东亚大气环流异常特征明显不同.在IOD发展阶段,在70年代末以前,印度夏季风和南海季风偏强,副热带高压势力偏弱,导致中国华南大部分地区降水偏少,华北西部以及内蒙古中部等地降水偏多;70年代末以后,东亚大陆中纬度为弱的东风距平,导致新疆北部降水偏少,气温偏高,华南降水偏多.在IOD次年夏季,70年代末以前,华南、河套以及四川等地盛行偏南气流,降水偏多;70年代末以后,南亚高压和西太平洋副高偏西偏强,华南、江南降水偏少.     

A study of biases in simulation of the Indian Ocean basin mode and its capacitor effect in CMIP3/CMIP5 models

Based on 15 Coupled Model Intercomparison Project (CMIP) phase 3 (CMIP3) and 32 CMIP phase 5 (CMIP5) models, a detailed diagnosis was carried out to understand what compose the biases in simulation of the Indian Ocean basin mode (IOBM) and its capacitor effect. Cloud-radiation-SST (CRS) feedback and wind-evaporation-SST (WES) feedback are the two major atmospheric processes for SST changes. Most CMIP models simulate a stronger CRS feedback and a weaker WES feedback. During boreal fall of the El Niño/Southern Oscillation developing year and the following spring, there are weak biases of suppressed rainfall anomalies over the Maritime Continent and anomalous anticyclone over South Indian Ocean. Most CMIP models simulate reasonable short wave radiation (SWR) and weaker latent heat flux (LHF) anomalies. This leads to a weak bias of atmospheric processes. During winter, however, the rainfall anomalies are stronger due to west bias, and the anomalous anticyclone is comparable to observations. As such, most models simulate stronger SWR and reasonable LHF anomalies, leading to a strong bias of atmospheric processes. The thermocline feedback is stronger in most models. Though there is a deep bias of climatology thermocline, most models capture reasonable sea surface height-induced SST anomalies. Therefore, the effect of oceanic processes offset the weak bias of atmospheric processes in spring, and the tropical Indian Ocean warming persists into summer. However, anomalous northwest Pacific (NWP) anticyclone is weaker due to weak and west bias of the capacitor effect. The unrealistic western Pacific SST anomalies in models favor the westward extension of Rossby wave from the Pacific, weakening the effect of Kelvin wave from the Indian Ocean. Moreover, the western Pacific warming forces the NWP anticyclone move farther north than observations, suggesting a major forcing from the Pacific. Compared to CMIP3, CMIP5 models simulate the feedbacks more realistically and display less diversity. Thus, the overall performance of CMIP5 models is better than that of CMIP3 models.     

The Southwest Indian Ocean thermocline dome in CMIP5 models: Historical simulation and future projection

Using 20 models of the Coupled Model Intercomparison Project Phase 5 (CMIP5), the simulation of the Southwest Indian Ocean (SWIO) thermocline dome is evaluated and its role in shaping the Indian Ocean Basin (IOB) mode following El Niño investigated. In most of the CMIP5 models, due to an easterly wind bias along the equator, the simulated SWIO thermocline is too deep, which could further influence the amplitude of the interannual IOB mode. A model with a shallow (deep) thermocline dome tends to simulate a strong (weak) IOB mode, including key attributes such as the SWIO SST warming, antisymmetric pattern during boreal spring, and second North Indian Ocean warming during boreal summer. Under global warming, the thermocline dome deepens with the easterly wind trend along the equator in most of the models. However, the IOB amplitude does not follow such a change of the SWIO thermocline among the models; rather, it follows future changes in both ENSO forcing and local convection feedback, suggesting a decreasing effect of the deepening SWIO thermocline dome on the change in the IOB mode in the future.     

Seasonality in the relationship between El Nino and Indian Ocean dipole

The seasonal change in the relationship between El Nino and Indian Ocean dipole (IOD) is examined using the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), and the twentieth century simulations (20c3m) from the Geophysical Fluid Dynamics Laboratory Coupled Model, version 2.1. It is found that, both in ERA-40 and the model simulations, the correlation between El Nino (Nino3 index) and the eastern part of the IOD (90?C110°E; 10°S-equator) is predominantly positive from January to June, and then changes to negative from July to December. Correlation maps of atmospheric and oceanic variables with respect to the Nino3 index are constructed for each season in order to examine the spatial structure of their seasonal response to El Nino. The occurrence of El Nino conditions during January to March induces low-level anti-cyclonic circulation anomalies over the southeastern Indian Ocean, which counteracts the climatological cyclonic circulation in that region. As a result, evaporation decreases and the southeastern Indian Ocean warms up as the El Nino proceeds, and weaken the development of a positive phase of an IOD. This warming of the southeastern Indian Ocean associated with the El Nino does not exist past June because the climatological winds there develop into the monsoon-type flow, enhancing the anomalous circulation over the region. Furthermore, the development of El Nino from July to September induces upwelling in the southeastern Indian Ocean, thereby contributing to further cooling of the region during the summer season. This results in the enhancement of a positive phase of an IOD. Once the climatological circulation shifts from the boreal summer to winter mode, the negative correlation between El Nino and SST of the southeastern Indian Ocean changes back to a positive one.     

The Role of the Aerosol Indirect Effect in the Northern Indian Ocean Warming Simulated by CMIP5 Models

The northern Indian Ocean （NIO） experienced a decadal-scale persistent warming from 1950 to 2000, which has influenced both regional and global climate. Because the NIO is a region susceptible to aerosols emis- sion changes, and there are still large uncertainties in the representation of the aerosol indirect effect （ALE） in CMIP5 （Coupled Model Intercomparison Project Phase 5） models, it is necessary to investigate the role of the AIE in the NIO warming simulated by these models. In this study, the authors select seven CMIP5 models with both the aerosol direct and indirect effects to investigate their performance in simulating the basin-wide decadal-scale NIO warming. The results show that the decreasing trend of the downwelling shortwave flux （FSDS） at the surface has the major damping effect on the SST increasing trend, which counteracts the warming effect of greenhouse gases （GHGs）. The FSDS decreasing trend is mostly contrib- uted by the decreasing trend of cloudy-sky surface downwelling shortwave flux （FSDSCL）, a metric used to measure the strength of the AIE, and partly by the clear-sky surface downwelling shortwave flux （FSDSC）. Models with a relatively weaker AIE can simulate well the SST increasing trend, as compared to observation. In contrast, models with a relatively stronger AIE produce a much smaller magnitude of the increasing trend, indicat- ing that the strength of the AIE in these models may be overestimated in the NIO.     

Indian Ocean dipole interpreted in terms of recharge oscillator theory

In this paper we use sea surface height (SSH) derived from satellite altimetry and an analytical linear equatorial wave model to interpret the evolution of the Indian Ocean Dipole (IOD) in the framework of recharge oscillator theory. The specific question we address is whether heat content in the equatorial band, for which SSH is a proxy, is a predictor of IOD development as it is for El Niño and the Southern Oscillation (ENSO) in the Pacific. We find that, as in the Pacific, there are zonally coherent changes in heat content along the equator prior to the onset of IOD events. These changes in heat content are modulated by wind-forced westward propagating Rossby waves in the latitude band 5°–10°S, which at the western boundary reflect into Kelvin waves trapped to the equator. The biennial character of the IOD is affected by this cycling of wave energy between 5° and 10°S and the equator. Heat content changes are a weaker leading indicator of IOD sea surface temperature anomaly development than is the case for ENSO in the Pacific though because other factors are at work in generating IOD variability, one of which is ENSO forcing itself through changes in the Walker Circulation.     

Future change of extreme temperature climate indices over East Asia with uncertainties estimation in the CMIP5

How well the climate models simulate extreme temperature over East Asia and how the extreme indices would change under anthropogenic global warming are investigated. The indices studied include hot days (HD), tropical nights (TN), growing degree days (GDD), and cooling degree days (CDD) in summer and heating degree days (HDD) and frost days (FD) in winter. The representative concentration pathway 4.5 (RCP 4.5) experiments for the period of 2075–2099 are compared with historical simulations for the period of 1979–2005 from 15 coupled models that are participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5). To optimally estimate future change and its uncertainty, groups of best models are selected based on Taylor diagrams, relative entropy, and probability density function (PDF) methods previously suggested. Overall, the best models’ multi-model ensemble based on Taylor diagrams has the lowest errors in reproducing temperature extremes in the present climate among three methods. Selected best models in three methods tend to project considerably different changes in the extreme indices from each other, indicating that the selection of reliable models are of critical importance to reduce uncertainties. Three groups of best models show significant increase of summerbased indices but decrease of the winter-based indices. Over East Asia, the most significant increase is seen in the HD (336 ± 23.4% of current climate) and the most significant decrease is appeared in the HDD (82 ± 4.2%). It is suggested that the larger future change in the HD is found over in the Southeastern China region, probably due to a higher local maximum temperature in the present climate. All of the indices show the largest uncertainty over Southeastern China, particularly in the TN (~3.9 times as large as uncertainty over East Asia) and in the HD (~2.4). It is further noted that the TN reveals the largest uncertainty over three East Asian countries (~1.7 and 1.4 over Korea and Japan, respectively). These future changes in extreme temperature events have an important implication for energy-saving applications and human molarity in the future.     

Investigating the Initial Errors that Cause Predictability Barriers for Indian Ocean Dipole Events Using CMIP5 Model Outputs

By analyzing the outputs of the pre-industrial control runs of four models within phase 5 of the Coupled Model Intercomparison Project, the effects of initial sea temperature errors on the predictability of Indian Ocean Dipole events were identified. The initial errors cause a significant winter predictability barrier(WPB) or summer predictability barrier(SPB).The WPB is closely related with the initial errors in the tropical Indian Ocean, where two types of WPB-related initial errors display opposite patterns and a west–east dipole. In contrast, the occurrence of the SPB is mainly caused by initial errors in the tropical Pacific Ocean, where two types of SPB-related initial errors exhibit opposite patterns, with one pole in the subsurface western Pacific Ocean and the other in the upper eastern Pacific Ocean. Both of the WPB-related initial errors grow the fastest in winter, because the coupled system is at its weakest, and finally cause a significant WPB. The SPB-related initial errors develop into a La Ni ?na–like mode in the Pacific Ocean. The negative SST errors in the Pacific Ocean induce westerly wind anomalies in the Indian Ocean by modulating the Walker circulation in the tropical oceans. The westerly wind anomalies first cool the sea surface water in the eastern Indian Ocean. When the climatological wind direction reverses in summer, the wind anomalies in turn warm the sea surface water, finally causing a significant SPB. Therefore, in addition to the spatial patterns of the initial errors, the climatological conditions also play an important role in causing a significant predictability barrier.     

A novel deep neural network model approach to predict Indian Ocean dipole and Equatorial Indian Ocean oscillation indices

Indian Ocean Dipole (IOD) and Equatorial Indian Ocean oscillation (EQUINOO) are important climatic system oscillation events in the Indian Ocean region that affects the Indian summer monsoon rainfall (ISMR). The prime focus of this study is to deliberate the influence of these events on ISMR and an attempt has been made to predict these events for future time scales using a Long short term memory (LSTM) deep learning model. LSTM is a special kind of recurrent neural network (RNN) which specializes in learning long-term dependencies and extracting important features. The features learnt by the model is then ranked using correlational analysis (linear and nonlinear). This approach helps in selecting decisive and imperative set of relevant predictors, which can be employed to predict IOD and EQUINOO. Nonlinear correlational identified predictors are found to forecast with greater precision as to their linear counterparts. The model-calibrated correlation coefficient for IOD and for EQUNIOO was 0.90 and 0.88 respectively at a lead of 5 months. Our proposed model was observed to work at par with the other existing models in terms of various statistical evaluation measures.     

赤道印度洋偶极子对重庆夏季降水的影响分析

利用重庆34个气象台站1961—2017年夏季降水量、NCEP/NCAR的再分析月平均高度场资料和海面温度资料，分析发现，上年秋季尤其是11月的赤道（热带）印度洋偶极子（tropical Indian Ocean dipole, TIOD）模态与重庆夏季降水存在正相关关系。通过前期海面温度对大气环流的影响分析，结果表明：上年11月TIOD和夏季500 hPa高度场的相关与重庆夏季降水和高度场的相关一致，显示出从高纬度到低纬度“+、-、+”的相关分布，反映出当上年11月TIOD正位相（负位相）时，次年夏季环流场表现出乌拉尔山阻塞高压明显（不明显）、中纬度30°～37°N低值系统活跃（不活跃），西太平洋副热带高压偏强（弱）、位置偏南（北）的重庆夏季典型的降水偏多环流特征；前期赤道太平洋ENSO暖事件和前期TIOD事件同时发生时，两个事件的作用相互叠加，使得西太平洋副热带高压加强西伸并且位置偏南，造成重庆夏季降水的异常偏多。