Simulations of the Madden–Julian oscillation in four pairs of coupled and uncoupled global models

The status of the numerical reproduction of the Madden–Julian Oscillation (MJO) by current global models was assessed through diagnoses of four pairs of coupled and uncoupled simulations. Slow eastward propagation of the MJO, especially in low-level zonal wind, is realistic in all these simulations. However, the simulated MJO suffers from several common problems. The MJO signal in precipitation is generally too weak and often eroded by an unrealistic split of an equatorial maximum of precipitation into a double ITCZ structure over the western Pacific. The MJO signal in low-level zonal wind, on the other hand, is sometimes too strong over the eastern Pacific but too weak over the Indian Ocean. The observed phase relationship between precipitation and low-level zonal wind associated with the MJO in the western Pacific and their coherence in general are not reproduced by the models. The seasonal migration in latitude of MJO activity is missing in most simulations. Air–sea coupling generally strengthens the simulated eastward propagating signal, but its effects on the phase relationship and coherence between precipitation and low-level zonal wind, and on their geographic distributions, seasonal cycles, and interannual variability are inconsistent among the simulations. Such inconsistency cautions generalization of results from MJO simulations using a single model. In comparison to observations, biases in the simulated MJO appear to be related to biases in the background state of mean precipitation, low-level zonal wind, and boundary-layer moisture convergence. This study concludes that, while the realistic simulations of the eastward propagation of the MJO are encouraging, reproducing other fundamental features of the MJO by current global models remains an unmet challenge.

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Simulation of the Atlantic meridional overturning circulation in an atmosphere–ocean global coupled model. Part I: a mechanism governing the variability of ocean convection in a preindustrial experiment

A preindustrial climate experiment was conducted with the third version of the CNRM global atmosphere–ocean–sea ice coupled model (CNRM-CM3) for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4). This experiment is used to investigate the main physical processes involved in the variability of the North Atlantic ocean convection and the induced variability of the Atlantic meridional overturning circulation (MOC). Three ocean convection sites are simulated, in the Labrador, Irminger and Greenland–Iceland–Norwegian (GIN) Seas in agreement with observations. A mechanism linking the variability of the Arctic sea ice cover and convection in the GIN Seas is highlighted. Contrary to previous suggested mechanisms, in CNRM-CM3 the latter is not modulated by the variability of freshwater export through Fram Strait. Instead, the variability of convection is mainly driven by the variability of the sea ice edge position in the Greenland Sea. In this area, the surface freshwater balance is dominated by the freshwater input due to the melting of sea ice. The ice edge position is modulated either by northwestward geostrophic current anomalies or by an intensification of northerly winds. In the model, stronger than average northerly winds force simultaneous intense convective events in the Irminger and GIN Seas. Convection interacts with the thermohaline circulation on timescales of 5–10 years, which translates into MOC anomalies propagating southward from the convection sites.     

Future projections of the surface heat and water budgets of the Mediterranean Sea in an ensemble of coupled atmosphere–ocean regional climate models

Within the CIRCE project “Climate change and Impact Research: the Mediterranean Environment”, an ensemble of high resolution coupled atmosphere–ocean regional climate models (AORCMs) are used to simulate the Mediterranean climate for the period 1950–2050. For the first time, realistic net surface air-sea fluxes are obtained. The sea surface temperature (SST) variability is consistent with the atmospheric forcing above it and oceanic constraints. The surface fluxes respond to external forcing under a warming climate and show an equivalent trend in all models. This study focuses on the present day and on the evolution of the heat and water budget over the Mediterranean Sea under the SRES-A1B scenario. On the contrary to previous studies, the net total heat budget is negative over the present period in all AORCMs and satisfies the heat closure budget controlled by a net positive heat gain at the strait of Gibraltar in the present climate. Under climate change scenario, some models predict a warming of the Mediterranean Sea from the ocean surface (positive net heat flux) in addition to the positive flux at the strait of Gibraltar for the 2021–2050 period. The shortwave and latent flux are increasing and the longwave and sensible fluxes are decreasing compared to the 1961–1990 period due to a reduction of the cloud cover and an increase in greenhouse gases (GHGs) and SSTs over the 2021–2050 period. The AORCMs provide a good estimates of the water budget with a drying of the region during the twenty-first century. For the ensemble mean, he decrease in precipitation and runoff is about 10 and 15% respectively and the increase in evaporation is much weaker, about 2% compared to the 1961–1990 period which confirm results obtained in recent studies. Despite a clear consistency in the trends and results between the models, this study also underlines important differences in the model set-ups, methodology and choices of some physical parameters inducing some difference in the various air-sea fluxes. An evaluation of the uncertainty sources and possible improvement for future generation of AORCMs highlights the importance of the parameterisation of the ocean albedo, rivers and cloud cover.     

The role of the intra-daily SST variability in the Indian monsoon variability and monsoon-ENSO–IOD relationships in a global coupled model

The impact of diurnal SST coupling and vertical oceanic resolution on the simulation of the Indian Summer Monsoon (ISM) and its relationships with El Ni?o-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events are studied through the analysis of four integrations of a high resolution Coupled General Circulation Model (CGCM), but with different configurations. The only differences between the four integrations are the frequency of coupling between the ocean and atmosphere for the Sea Surface Temperature (SST) parameter (2 vs. 24?h coupling) and/or the vertical oceanic resolution (31 vs. 301 levels) in the CGCM. Although the summer mean tropical climate is reasonably well captured with all the configurations of the CGCM and is not significantly modified by changing the frequency of SST coupling from once to twelve per day, the ISM–ENSO teleconnections are rather poorly simulated in the two simulations in which SST is exchanged only once per day, independently of the vertical oceanic resolution used in the CGCM. Surprisingly, when 2?h SST coupling is implemented in the CGCM, the ISM–ENSO teleconnection is better simulated, particularly, the complex lead-lag relationships between the two phenomena, in which a weak ISM occurs during the developing phase of an El Ni?o event in the Pacific, are closely resembling the observed ones. Evidence is presented to show that these improvements are related to changes in the characteristics of the model’s El Ni?o which has a more realistic evolution in its developing and decaying phases, a stronger amplitude and a shift to lower frequencies when a 2-hourly SST coupling strategy is implemented without any significant changes in the basic state of the CGCM. As a consequence of these improvements in ENSO variability, the lead relationships between Indo-Pacific SSTs and ISM rainfall resemble the observed patterns more closely, the ISM–ENSO teleconnection is strengthened during boreal summer and ISM rainfall power spectrum is in better agreement with observations. On the other hand, the ISM–IOD teleconnection is sensitive to both SST coupling frequency and the vertical oceanic resolution, but increasing the vertical oceanic resolution is degrading the ISM–IOD teleconnection in the CGCM. These results highlight the need of a proper assessment of both temporal scale interactions and coupling strategies in order to improve current CGCMs. These results, which must be confirmed with other CGCMs, have also important implications for dynamical seasonal prediction systems or climate change projections of the monsoon.     

Thirty-two-year ocean–atmosphere coupled downscaling of global reanalysis over the Intra-American Seas

This study examines the oceanic and atmospheric variability over the Intra-American Seas (IAS) from a 32-year integration of a 15-km coupled regional climate model consisting of the Regional Spectral Model (RSM) for the atmosphere and the Regional Ocean Modeling System (ROMS) for the ocean. It is forced at the lateral boundaries by National Centers for Environmental Prediction-Department of Energy (NCEP-DOE R-2) atmospheric global reanalysis and Simplified Ocean Data Assimilation global oceanic reanalysis. This coupled downscaling integration is a free run without any heat flux correction and is referred as the Regional Ocean–Atmosphere coupled downscaling of global Reanalysis over the Intra-American Seas (ROARS). The paper examines the fidelity of ROARS with respect to independent observations that are both satellite based and in situ. In order to provide a perspective on the fidelity of the ROARS simulation, we also compare it with the Climate Forecast System Reanalysis (CFSR), a modern global ocean–atmosphere reanalysis product. Our analysis reveals that ROARS exhibits reasonable climatology and interannual variability over the IAS region, with climatological SST errors less than 1 °C except along the coastlines. The anomaly correlation of the monthly SST and precipitation anomalies in ROARS are well over 0.5 over the Gulf of Mexico, Caribbean Sea, Western Atlantic and Eastern Pacific Oceans. A highlight of the ROARS simulation is its resolution of the loop current and the episodic eddy events off of it. This is rather poorly simulated in the CFSR. This is also reflected in the simulated, albeit, higher variance of the sea surface height in ROARS and the lack of any variability in the sea surface height of the CFSR over the IAS. However the anomaly correlations of the monthly heat content anomalies of ROARS are comparatively lower, especially over the Gulf of Mexico and the Caribbean Sea. This is a result of ROARS exhibiting a bias of underestimation (overestimation) of high (low) clouds. ROARS like CFSR is also able to capture the Caribbean Low Level Jet and its seasonal variability reasonably well.     

How accurately do coupled climate models predict the leading modes of Asian-Australian monsoon interannual variability?

Accurate prediction of the Asian-Australian monsoon (A-AM) seasonal variation is one of the most important and challenging tasks in climate prediction. In order to understand the causes of the low accuracy in the current prediction of the A-AM precipitation, this study strives to determine to what extent the ten state-of-the-art coupled atmosphere-ocean-land climate models and their multi-model ensemble (MME) can capture the two observed major modes of A-AM rainfall variability–which account for 43% of the total interannual variances during the retrospective prediction period of 1981–2001. The first mode is associated with the turnabout of warming to cooling in the El Niño-Southern Oscillation (ENSO), whereas the second mode leads the warming/cooling by about 1 year, signaling precursory conditions for ENSO. The first mode has a strong biennial tendency and reflects the Tropical Biennial Oscillation (Meehl in J Clim 6:31–41, 1993). We show that the MME 1-month lead prediction of the seasonal precipitation anomalies captures the first two leading modes of variability with high fidelity in terms of seasonally evolving spatial patterns and year-to-year temporal variations, as well as their relationships with ENSO. The MME shows a potential to capture the precursors of ENSO in the second mode about five seasons prior to the maturation of a strong El Niño. However, the MME underestimates the total variances of the two modes and the biennial tendency of the first mode. The models have difficulties in capturing precipitation over the maritime continent and the Walker-type teleconnection in the decaying phase of ENSO, which may contribute in part to a monsoon “spring prediction barrier” (SPB). The NCEP/CFS model hindcast results show that, as the lead time increases, the fractional variance of the first mode increases, suggesting that the long-lead predictability of A-AM rainfall comes primarily from ENSO predictability. In the CFS model, the correlation skill for the first principal component remains about 0.9 up to 6 months before it drops rapidly, but for the spatial pattern it exhibits a drop across the boreal spring. This study uncovered two surprising findings. First, the coupled models’ MME predictions capture the first two leading modes of precipitation variability better than those captured by the ERA-40 and NCEP-2 reanalysis datasets, suggesting that treating the atmosphere as a slave may be inherently unable to simulate summer monsoon rainfall variations in the heavily precipitating regions (Wang et al. in J Clim 17:803–818, 2004). It is recommended that future reanalysis should be carried out with coupled atmosphere and ocean models. Second, While the MME in general better than any individual models, the CFS ensemble hindcast outperforms the MME in terms of the biennial tendency and the amplitude of the anomalies, suggesting that the improved skill of MME prediction is at the expense of overestimating the fractional variance of the leading mode. Other outstanding issues are also discussed.     

Dynamics of the coupled human–climate system resulting from closed-loop control of solar geoengineering

If solar radiation management (SRM) were ever implemented, feedback of the observed climate state might be used to adjust the radiative forcing of SRM in order to compensate for uncertainty in either the forcing or the climate response. Feedback might also compensate for unexpected changes in the system, e.g. a nonlinear change in climate sensitivity. However, in addition to the intended response to greenhouse-gas induced changes, the use of feedback would also result in a geoengineering response to natural climate variability. We use a box-diffusion dynamic model of the climate system to understand how changing the properties of the feedback control affect the emergent dynamics of this coupled human–climate system, and evaluate these predictions using the HadCM3L general circulation model. In particular, some amplification of natural variability is unavoidable; any time delay (e.g., to average out natural variability, or due to decision-making) exacerbates this amplification, with oscillatory behavior possible if there is a desire for rapid correction (high feedback gain). This is a challenge for policy as a delayed response is needed for decision making. Conversely, the need for feedback to compensate for uncertainty, combined with a desire to avoid excessive amplification of natural variability, results in a limit on how rapidly SRM could respond to changes in the observed state of the climate system.     

An explanation for the difference between twentieth and twenty-first century land–sea warming ratio in climate models

A land–sea surface warming ratio (or φ) that exceeds unity is a robust feature of both observed and modelled climate change. Interestingly, though climate models have differing values for φ, it remains almost time-invariant for a wide range of twenty-first century climate transient warming scenarios, while varying in simulations of the twentieth century. Here, we present an explanation for time-invariant land–sea warming ratio that applies if three conditions on radiative forcing are met: first, spatial variations in the climate forcing must be sufficiently small that the lower free troposphere warms evenly over land and ocean; second, the temperature response must not be large enough to change the global circulation to zeroth order; third, the temperature response must not be large enough to modify the boundary layer amplification mechanisms that contribute to making φ exceed unity. Projected temperature changes over this century are too small to breach the latter two conditions. Hence, the mechanism appears to show why both twenty-first century and time-invariant CO₂ forcing lead to similar values of φ in climate models despite the presence of transient ocean heat uptake, whereas twentieth century forcing—which has a significant spatially confined anthropogenic tropospheric aerosol component that breaches the first condition—leads to modelled values of φ that vary widely amongst models and in time. Our results suggest an explanation for the behaviour of φ when climate is forced by other regionally confined forcing scenarios such as geo-engineered changes to oceanic clouds. Our results show how land–sea contrasts in surface and boundary layer characteristics act in tandem to produce the land–sea surface warming contrast.     

Impact of a realistic river routing in coupled ocean–atmosphere simulations of the Last Glacial Maximum climate

The presence of large ice sheets over North America and North Europe at the Last Glacial Maximum (LGM) strongly impacted Northern hemisphere river pathways. Despite the fact that such changes may significantly alter the freshwater input to the ocean, modified surface hydrology has never been accounted for in coupled ocean–atmosphere general circulation model simulations of the LGM climate. To reconstruct the LGM river routing, we use the ICE-5G LGM topography. Because of the uncertainties in the extent of the Fennoscandian ice sheet in the Eastern part of the Kara Sea, we consider two more realistic river routing scenarios. The first scenario is characterised by the presence of an ice dammed lake south of the Fennoscandian ice sheet, and corresponds to the ICE-5G topography. This lake is fed by the Ob and Yenisei rivers. In the second scenario, both these rivers flow directly into the Arctic Ocean, which is more consistent with the latest QUEEN ice sheet margin reconstructions. We study the impact of these changes on the LGM climate as simulated by the IPSL_CM4 model and focus on the overturning thermohaline circulation. A comparison with a classical LGM simulation performed using the same model and modern river basins as designed in the PMIP2 exercise leads to the following conclusions: (1) The discharge into the North Atlantic Ocean is increased by 2,000 m³/s between 38° and 54°N in both simulations that contain LGM river routing, compared to the classical LGM experiment. (2) The ice dammed lake is shown to have a weak impact, relative to the classical simulation, both in terms of climate and ocean circulation. (3) In contrast, the North Atlantic deep convection and meridional overturning are weaker than during the classical LGM run if the Ob and Yenisei rivers flow directly into the Arctic Ocean. The total discharge into the Arctic Ocean is increased by 31,000 m³/s, relative to the classical LGM simulation. Consequentially, northward ocean heat transport is weaker, and sea ice more extensive, in better agreement with existing proxy data.     

Interannual variations of the boreal summer intraseasonal variability predicted by ten atmosphere–ocean coupled models

The reproducibility of boreal summer intraseasonal variability (ISV) and its interannual variation by dynamical models are assessed through diagnosing 21-year retrospective forecasts from ten state-of-the-art ocean–atmosphere coupled prediction models. To facilitate the assessment, we have defined the strength of ISV activity by the standard deviation of 20–90 days filtered precipitation during the boreal summer of each year. The observed climatological ISV activity exhibits its largest values over the western North Pacific and Indian monsoon regions. The notable interannual variation of ISV activity is found primarily over the western North Pacific in observation while most models have the largest variability over the central tropical Pacific and exhibit a wide range of variability in spatial patterns that are different from observation. Although the models have large systematic biases in spatial pattern of dominant variability, the leading EOF modes of the ISV activity in the models are closely linked to the models’ El Nino-Southern Oscillation (ENSO), which is a feature that resembles the observed ISV and ENSO relationship. The ENSO-induced easterly vertical shear anomalies in the western and central tropical Pacific, where the summer mean vertical wind shear is weak, result in ENSO-related changes of ISV activity in both observation and models. It is found that the principal components of the predicted dominant modes of ISV activity fluctuate in a very similar way with observed ones. The model biases in the dominant modes are systematic and related to the external SST forcing. Thus the statistical correction method of this study based on singular value decomposition is capable of removing a large portion of the systematic errors in the predicted spatial patterns. The 21-year-averaged pattern correlation skill increases from 0.25 to 0.65 over the entire Asian monsoon region after applying the bias correction method to the multi-model ensemble mean prediction.     

Current status of ENSO prediction skill in coupled ocean–atmosphere models

The overall skill of ENSO prediction in retrospective forecasts made with ten different coupled GCMs is investigated. The coupled GCM datasets of the APCC/CliPAS and DEMETER projects are used for four seasons in the common 22 years from 1980 to 2001. As a baseline, a dynamic-statistical SST forecast and persistence are compared. Our study focuses on the tropical Pacific SST, especially by analyzing the NINO34 index. In coupled models, the accuracy of the simulated variability is related to the accuracy of the simulated mean state. Almost all models have problems in simulating the mean and mean annual cycle of SST, in spite of the positive influence of realistic initial conditions. As a result, the simulation of the interannual SST variability is also far from perfect in most coupled models. With increasing lead time, this discrepancy gets worse. As one measure of forecast skill, the tier-1 multi-model ensemble (MME) forecasts of NINO3.4 SST have an anomaly correlation coefficient of 0.86 at the month 6. This is higher than that of any individual model as well as both forecasts based on persistence and those made with the dynamic-statistical model. The forecast skill of individual models and the MME depends strongly on season, ENSO phase, and ENSO intensity. A stronger El Niño is better predicted. The growth phases of both the warm and cold events are better predicted than the corresponding decaying phases. ENSO-neutral periods are far worse predicted than warm or cold events. The skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November. This behavior, often termed the spring predictability barrier, is in part because predictions starting from February or May contain more events in the decaying phase of ENSO.     

Multi-century simulations with the coupled GISS–HYCOM climate model: control experiments

Multi-century climate simulations obtained with the GISS atmospheric general circulation model coupled to the hybrid-isopycnic ocean model HYCOM are described. Greenhouse gas concentrations are held fixed in these experiments to investigate the coupled model’s ability to reproduce the major features of today’s climate with minimal drift. Emphasis is placed on the realism of the oceanic general circulation and its effect on air–sea exchange processes. Several model runs using different closures for turbulent vertical exchange as well as improvements to reduce vertical numerical diffusion are compared with climate observations. As in previous studies, the Southern Ocean emerges as the Achilles Heel of the ocean model; deficiencies in its physical representation had far-reaching consequences in early experiments with the coupled model and have provided the strongest impetus for model improvement. The overarching goal of this work is to add diversity to the pool of ocean models available for climate prediction and thereby reduce biases that may stand in the way of assessing climate prediction uncertainty.

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Analysis of the coupling between the stratospheric meridional wind and the surface level zonal wind during 1979–93 Northern Hemisphere extratropical winters

The coupling between the stratosphere and the troposphere has been investigated by analysing low-frequency variations in: (1) the meridional mass flux into the polar cap (north of 60°N), computed separately for the stratosphere and the troposphere; (2) the polar cap mean surface pressure, and (3) the surface level meridional pressure gradient and zonal wind around 60°N. The analysis has been done for the 1979–93 Northern Hemisphere (NH) winters, using ECMWF reanalysis data. The results show that for all winters the meridional mass flux variations in the stratosphere precede those in the troposphere, by about one day. This result can also be obtained qualitatively with a very simple model, based on the zonally averaged zonal and meridional momentum equations. The lag is not very sensitive to the latitude of the southern boundary of the polar cap. The analysed variations in the polar cap mean surface pressure associated with variations in the meridional mass flux, determine most of the variability in the analysed meridional surface pressure gradient and the associated surface zonal wind around 60°N. The results also show that in the stratosphere the Coriolis force associated with the zonal-mean meridional wind is in near-balance with the convergence of the eddy momentum flux, and in the lower troposphere with the zonal frictional force. In summary, the results indicate that in the extratropical northern winter hemisphere, low-frequency variations in the meridional wind in the stratosphere induce low-frequency variations in the zonal wind near the surface.     

Multiple temporal scale variability during the twentieth century in global carbon dynamics simulated by a coupled climate–terrestrial carbon cycle model

A coupled climate–carbon cycle model composed of a process-based terrestrial carbon cycle model, Sim-CYCLE, and the CCSR/NIES/FRCGC atmospheric general circulation model was developed. We examined the multiple temporal scale functions of terrestrial ecosystem carbon dynamics induced by human activities and natural processes and evaluated their contribution to fluctuations in the global carbon budget during the twentieth century. Global annual net primary production (NPP) and heterotrophic respiration (HR) increased gradually by 6.7 and 4.7%, respectively, from the 1900s to the 1990s. The difference between NPP and HR was the net carbon uptake by natural ecosystems, which was 0.6 Pg C year^?1 in the 1980s, whereas the carbon emission induced by human land-use changes was 0.5 Pg C year^?1, largely offsetting the natural terrestrial carbon sequestration. Our results indicate that monthly to interannual variation in atmospheric CO₂ growth rate anomalies show 2- and 6-month time lags behind anomalies in temperature and the NiNO₃ index, respectively. The simulated anomaly amplitude in monthly net carbon flux from terrestrial ecosystems to the atmosphere was much larger than in the prescribed air-to-sea carbon flux. Fluctuations in the global atmospheric CO₂ time series were dominated by the activity of terrestrial vegetation. These results suggest that terrestrial ecosystems have acted as a net neutral reservoir for atmospheric CO₂ concentrations during the twentieth century on an interdecadal timescale, but as the dominant driver for atmospheric CO₂ fluctuations on a monthly to interannual timescale.     

Bulgarian mountains air temperatures and precipitation—statistical downscaling of global climate models and some projections

Measured air temperature and precipitation data from three high mountainous Bulgarian stations were used along with data from 18 global climate models (GCMs). Air temperature and precipitation outputs of preindustrial control experiment were compared with actually observed values. GCM with the best overall performance is BCCR BCM 2.0 for air temperatures (period 1941?C2009) and CGCM 3.1/T47 for precipitation (period 1947?C2009). Statistical methods were used in this research??nonparametric Spearman correlation, Mann?CWhitney test, multiple linear regression, etc. Projections were made for the following future decades: 2015?C2024, 2045?C2054 and 2075?C2084. The best months, described by multiple linear regression (MLR) model of air temperatures, are November, January, March, and May. The worst described are summer months. There is not any pattern in the relationship between constructed MLR models and measured precipitation. Models that perform the best in different months at the three investigated stations are MIUB ECHO-G, GISS AOM, CGCM 3.1/T63, and CNRM CM3 for air temperatures and GFDL CM 2.1, GISS AOM, and MIUB ECHO-G for precipitation. The fit between statistical models' outputs and values observed at stations is different, better in cold part of the year. There will be mixed future changes of air temperatures at all the three high mountainous stations. An increase of temperatures is expected in April, November, and December. A decrease will happen in February, July, and October. Mean annual temperatures are expected to rise by 0.1?°C (Botev) to 0.2?°C (Musala and Cherni vrah) in the decade 2075?C2084, but mean annual temperatures at the end of the period with measurements (2009) has already exceeded by far projected values. Trends in precipitation are mixed both in spatial and in temporal directions. Observed decrease of precipitation, especially in the warm half of the year, is not described well in MLR models. The same is valid for annual amounts, which are projected to be higher than those measured in the end of instrumental period (2009). This is opposite to observed trends in recent decades, especially at stations Cherni vrah and Botev, where a significant decrease of precipitation amounts has happened.