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.     

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.     

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.     

Uncertainty in land surface temperature simulation over China by CMIP3/CMIP5 models

In this paper, China-based observations are used to evaluate the performance of 24 CMIP3 (phase 3 of the Coupled Model Intercomparison Project) and 10 CMIP5 models in simulating land surface temperature (LST). It is found that all models can generally reproduce the climatology patterns of LST averaged during the period from 1960 to 1999. Further analyses of the regional features of LST show that the discrepancies between the observations and the simulations are smaller in Southwest and East China. Moreover, these models overestimate the temperatures in almost all areas, particularly in July. Although many models have large biases relative to the observations, the spread of the model results is large (i.e., >22 °C in Northwest and Northeast China). For the interannual variations, neither the individual models nor the multi-model mean has a remarkable positive correlation to the observations in the selected subregions. However, most models can capture geographic features during trend evaluations. A multi-model ensemble is believed to be an effective way to limit uncertainties, but the results suggest that its efficiency is restricted to simulating the LST trend. Examination of the surface energy budget indicated that the modeled discrepancies of net shortwave radiation and surface sensible heat flux may be responsible for the LST results, especially in July. It is concluded that the ability of current models in simulating LST over China is still a significant challenge. The spread of the models is large in simulating the climatology, interannual variation, and trend of LSTs. In general, the magnitudes of the spread may be as large as the magnitudes of the observations. Additionally, it is found that multi-model ensembles do not simulate LST with any more skill. Therefore, more work must focus on the limitations of the models' uncertainties in land surface research.     

Understanding the sources of Caribbean precipitation biases in CMIP3 and CMIP5 simulations

We assess the ability of Global Climate Models participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) to simulate observed annual precipitation cycles over the Caribbean. Compared to weather station records and gridded observations, we find that both CMIP3 and CMIP5 models can be grouped into three categories: (1) models that correctly simulate a bimodal distribution with two rainfall maxima in May–June and September–October, punctuated by a mid-summer drought (MSD) in July–August; (2) models that reproduce the MSD and the second precipitation maxima only; and (3) models that simulate only one precipitation maxima, beginning in early summer. These categories appear related to model simulation of the North Atlantic Subtropical High (NASH) and sea surface temperature (SST) in the Caribbean Sea and Gulf of Mexico. Specifically, models in category 2 tend to anticipate the westward expansion of the NASH into the Caribbean in early summer. Early onset of NASH results in strong moisture divergence and MSD-like conditions at the time of the May–June observed precipitation maxima. Models in category 3 tend to have cooler SST across the region, particularly over the central Caribbean and the Gulf of Mexico, as well as a weaker Caribbean low-level jet accompanying a weaker NASH. In these models, observed June-like patterns of moisture convergence in the central Caribbean and the Central America and divergence in the east Caribbean and the Gulf of Mexico persist through September. This analysis suggests systematic biases in model structure may be responsible for biases in observed precipitation variability over the Caribbean and more confidence may be placed in the precipitation simulated by the GCMs that are able to correctly simulate seasonal cycles of SST and NASH.     

Future change of the Indian Ocean basin-wide and dipole modes in the CMIP5

The Indian Ocean sea surface temperature (SST) variability has been represented with the two dominant variability modes: the Indian Ocean basin-wide (IOBW) and dipole (IOD) modes. Here we investigate future changes of the two modes together with mean state and El Niño and Southern Oscillation (ENSO) relationship under the anthropogenic global warming using 20 coupled models that participated in the phase five of Coupled Model Intercomparison Project by comparing the historical run from 1950 to 2005 and the RCP 4.5 run from 2050 to 2099. The five best models are selected based on the evaluation of the 20 models’ performances in simulating the two modes and Indian Ocean basic state for the latest 56 years. They are capable of capturing the IOBW and IOD modes in their spatial distribution, seasonal cycle, major periodicity, and relationship with ENSO to some extent. The five best models project the significant changes in the Indian Ocean mean state and variability including the two dominant modes in the latter part of twenty-first century under the anthropogenic warming scenario. First, the annual mean climatological SST displays an IOD-like pattern change over the Indian Ocean with enhanced warming in the northwestern Indian Ocean and relatively weaker warming off the Sumatra–Java coast. It is also noted that the monthly SST variance is increased over the eastern and southwestern Indian Ocean. Second, the IOBW variability on a quasi-biennial time scale will be enhanced due to the strengthening of the ENSO–IOBW mode relationship although the total variance of the IOBW mode will be significantly reduced particularly during late summer and fall. The enhanced air-sea coupling over the Indian-western Pacific climate in response to El Nino activity in the future projection makes favorable condition for a positive IOD while it tends to derive relatively cold temperature over the eastern Indian Ocean. This positive IOD-like ENSO response weakens the relationship between the eastern Indian Ocean and El Nino while strengthens the relationship with western Indian Ocean. Third, the IOD mode, intrinsic coupled mode of the Indian Ocean may not be changed appreciably under the anthropogenic global warming.     

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.     

ENSO phase-locking to the boreal winter in CMIP3 and CMIP5 models

In this study, the El Nino-Southern Oscillation (ENSO) phase-locking to the boreal winter in CMIP3 and CMIP5 models is examined. It is found that the models that are poor at simulating the winter ENSO peak tend to simulate colder seasonal-mean sea-surface temperature (SST) during the boreal summer and associated shallower thermocline depth over the eastern Pacific. These models tend to amplify zonal advection and thermocline depth feedback during boreal summer. In addition, the colder eastern Pacific SST in the model can reduce the summertime mean local convective activity, which tends to weaken the atmospheric response to the ENSO SST forcing. It is also revealed that these models have more serious climatological biases over the tropical Pacific, implying that a realistic simulation of the climatological fields may help to simulate winter ENSO peak better. The models that are poor at simulating ENSO peak in winter also show excessive anomalous SST warming over the western Pacific during boreal winter of the El Nino events, which leads to strong local convective anomalies. This prevents the southward shift of El Nino-related westerly during boreal winter season. Therefore, equatorial westerly is prevailed over the western Pacific to further development of ENSO-related SST during boreal winter. This bias in the SST anomaly is partly due to the climatological dry biases over the central Pacific, which confines ENSO-related precipitation and westerly responses over the western Pacific.     

Equatorial Atlantic variability and its relation to mean state biases in CMIP5

Coupled general circulation model (GCM) simulations participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) are analyzed with respect to their performance in the equatorial Atlantic. In terms of the mean state, 29 out of 33 models examined continue to suffer from serious biases including an annual mean zonal equatorial SST gradient whose sign is opposite to observations. Westerly surface wind biases in boreal spring play an important role in the reversed SST gradient by deepening the thermocline in the eastern equatorial Atlantic and thus reducing upwelling efficiency and SST cooling in the following months. Both magnitude and seasonal evolution of the biases are very similar to what was found previously for CMIP3 models, indicating that improvements have only been modest. The weaker than observed equatorial easterlies are also simulated by atmospheric GCMs forced with observed SST. They are related to both continental convection and the latitudinal position of the intertropical convergence zone (ITCZ). Particularly the latter has a strong influence on equatorial zonal winds in both the seasonal cycle and interannual variability. The dependence of equatorial easterlies on ITCZ latitude shows a marked asymmetry. From the equator to 15°N, the equatorial easterlies intensify approximately linearly with ITCZ latitude. When the ITCZ is south of the equator, on the other hand, the equatorial easterlies are uniformly weak. Despite serious mean state biases, several models are able to capture some aspects of the equatorial mode of interannual SST variability, including amplitude, pattern, phase locking to boreal summer, and duration of events. The latitudinal position of the boreal spring ITCZ, through its influence on equatorial surface winds, appears to play an important role in initiating warm events.     

The Subsurface and Surface Indian Ocean Dipoles and Their Association with ENSO in CMIP6 models

This study assesses the reproducibility of 31 historical simulations from 1850 to 2014 in the Coupled Model Intercomparison Project phase 6(CMIP6) for the subsurface(Sub-IOD) and surface Indian Ocean Dipole(IOD) and their association with El Ni?o-Southern Oscillation(ENSO). Most CMIP6 models can reproduce the leading east-west dipole oscillation mode of heat content anomalies in the tropical Indian Ocean(TIO) but largely overestimate the amplitude and the dominant period of the Sub-IOD. Associat...     

Simulation of the equatorially asymmetric mode of the Hadley circulation in CMIP5 models

The tropical Hadley circulation (HC) plays an important role in influencing the climate in the tropics and extra-tropics. The realism of the climatological characteristics, spatial structure, and temporal evolution of the long-term variation of the principal mode of the annual mean HC (i.e., the equatorially asymmetric mode, EAM) was examined in model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The results showed that all the models are moderately successful in capturing the HC's climatological features, including the spatial pattern, meridional extent, and intensity, but not the spatial or temporal variation of the EAM. The possible reasons for the poor simulation of the long-term variability of the EAM were explored. None of the models can successfully capture the differences in the warming rate between the tropical Southern Hemisphere (SH) and Northern Hemisphere (NH), which is considered to be an important driver for the variation of the AM. Most of the models produce a faster warming in the NH than in the SH, which is the reverse of the observed trend. This leads to a reversed trend in the meridional gradient between the SH and NH, and contributes to the poor simulation of EAM variability. Thus, this aspect of the models should be improved to provide better simulations of the variability of the HC. This study suggests a possible reason for the poor simulation of the HC, which may be helpful for improving the skill of the CMIP5 models in the future.     

Present-day and future Amazonian precipitation in global climate models: CMIP5 versus CMIP3

The present study aims at evaluating and comparing precipitation over the Amazon in two sets of historical and future climate simulations based on phase 3 (CMIP3) and 5 (CMIP5) of the Coupled Model Intercomparison Project. Thirteen models have been selected in order to discuss (1) potential improvements in the simulation of present-day climate and (2) the potential reduction in the uncertainties of the model response to increasing concentrations of greenhouse gases. While several features of present-day precipitation—including annual cycle, spatial distribution and co variability with tropical sea surface temperature (SST)—have been improved, strong uncertainties remain in the climate projections. A closer comparison between CMIP5 and CMIP3 highlights a weaker consensus on increased precipitation during the wet season, but a stronger consensus on a drying and lengthening of the dry season. The latter response is related to a northward shift of the boreal summer intertropical convergence zone in CMIP5, in line with a more asymmetric warming between the northern and southern hemispheres. The large uncertainties that persist in the rainfall response arise from contrasted anomalies in both moisture convergence and evapotranspiration. They might be related to the diverse response of tropical SST and ENSO (El Niño Southern Oscillation) variability, as well as to spurious behaviours among the models that show the most extreme response. Model improvements of present-day climate do not necessarily translate into more reliable projections and further efforts are needed for constraining the pattern of the SST response and the soil moisture feedback in global climate scenarios.     

Evaluating the performance of CMIP3 and CMIP5 global climate models over the north-east Atlantic region

One of the main sources of uncertainty in estimating climate projections affected by global warming is the choice of the global climate model (GCM). The aim of this study is to evaluate the skill of GCMs from CMIP3 and CMIP5 databases in the north-east Atlantic Ocean region. It is well known that the seasonal and interannual variability of surface inland variables (e.g. precipitation and snow) and ocean variables (e.g. wave height and storm surge) are linked to the atmospheric circulation patterns. Thus, an automatic synoptic classification, based on weather types, has been used to assess whether GCMs are able to reproduce spatial patterns and climate variability. Three important factors have been analyzed: the skill of GCMs to reproduce the synoptic situations, the skill of GCMs to reproduce the historical inter-annual variability and the consistency of GCMs experiments during twenty-first century projections. The results of this analysis indicate that the most skilled GCMs in the study region are UKMO-HadGEM2, ECHAM5/MPI-OM and MIROC3.2(hires) for CMIP3 scenarios and ACCESS1.0, EC-EARTH, HadGEM2-CC, HadGEM2-ES and CMCC-CM for CMIP5 scenarios. These models are therefore recommended for the estimation of future regional multi-model projections of surface variables driven by the atmospheric circulation in the north-east Atlantic Ocean region.     

Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models

There is a long-standing debate on how the El Niño/Southern Oscillation (ENSO) amplitude may change during the twenty-first century in response to global warming. Here we identify the sources of uncertainty in the ENSO amplitude projections in models participating in the Coupled Model Intercomparison Phase 5 (CMIP5) and Phase 6 (CMIP6), and quantify scenario uncertainty, model uncertainty and uncertainty due to internal variability. The model projections exhibit a large spread, ranging from increasing standard deviation of up to 0.6 °C to diminishing standard deviation of up to − 0.4 °C by the end of the twenty-first century. The ensemble-mean ENSO amplitude change is close to zero. Internal variability is the main contributor to the uncertainty during the first three decades; model uncertainty dominates thereafter, while scenario uncertainty is relatively small throughout the twenty-first century. The total uncertainty increases from CMIP5 to CMIP6: while model uncertainty is reduced, scenario uncertainty is considerably increased. The models with “realistic” ENSO dynamics have been analyzed separately and categorized into models with too small, moderate and too large ENSO amplitude in comparison to instrumental observations. The smallest uncertainties are observed in the sub-ensemble exhibiting realistic ENSO dynamics and moderate ENSO amplitude. However, the global warming signal in ENSO-amplitude change is undetectable in all sub-ensembles. The zonal wind-SST feedback is identified as an important factor determining ENSO amplitude change: global warming signal in ENSO amplitude and zonal wind-SST feedback strength are highly correlated across the CMIP5 and CMIP6 models.

     

A diagnostic study of future evaporation changes projected in CMIP5 climate models

It has been pointed out that climatological-mean precipitation-evaporation difference (P–E) should increase under global warming mainly through the increasing saturation level of moisture. This study focuses on evaporation changes under global warming and their dependency on the direct warming effect, on the basis of future projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Over most of the tropical, subtropical and midlatitude regions, the direct contribution from surface temperature increase is found to dominate the projected increase in evaporation. This contribution is nevertheless offset partially, especially over the oceans, by contributions from weakening surface winds and increasing near-surface relative humidity. Greater warming of surface air than of the sea surface also acts to reduce surface evaporation, by reducing both the exchange coefficient and humidity contrast at the surface. Though generally of secondary importance, this contribution is the dominant factor over the subpolar oceans. Over the polar oceans, the effect of sea-ice retreat dominantly contributes to the evaporation increase in winter, whereas the reduced exchange coefficient and surface humidity contrast coupled with the sea-ice retreat account for most of the response during summertime. Over the continents, changes in the surface exchange coefficient, reflecting changes in soil moisture and vegetation among other factors, are important to modulate the direct effects of the warming and the generally reduced surface air relative humidity.     

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.