Coupled Atmosphere Ocean General Circulation Model Research Articles

A multi-model analysis of the resolution influence on precipitation climatology in the Gulf Stream region

Using climate simulations from coupled and uncoupled general circulation models, this study investigates the influence of horizontal resolution in both atmospheric and oceanic model components on the mean precipitation over the Gulf Stream (GS) region. For this purpose, three sets of model experiments are analyzed. The first two examine the effects of increasing horizontal resolution of an atmospheric general circulation model (AGCM) gradually from 100 to 10 km under fixed oceanic settings. Specifically, the AGCM is either forced with prescribed observed sea surface temperature (SST) (the first case) or coupled to a non-eddy-resolving ocean general circulation model (OGCM) at a fixed horizontal resolution near 100 km (the second case). The third set of experiments examines the effects of the oceanic resolution with a pair of long-term simulations by another coupled ocean–atmosphere general circulation model (CGCM), in which the OGCM is run respectively at non-eddy-resolving (100 km) and eddy-resolving (10 km) resolutions, while the AGCM resolution remains fixed at 50 km for both runs. In general, all simulations qualitatively reproduce the gross features of the mean GS precipitation and its annual cycle. At similar AGCM resolutions, the uncoupled models produce a GS rain band that is more realistic in both structure and strength compared to the coupled models with non-eddy-resolving oceans. This is because the prescribed observed SST better represents the gradient near the oceanic front than the non-eddy-resolving OGCMs simulate. An increase from the baseline AGCM resolution produces enhanced climatological GS precipitation, both large-scale and convective, with the latter more tightly confined to the oceanic front. The enhancement, however, is moderate and further increases in resolution achieves diminishing results. On the other hand, an increase in oceanic resolution from non-eddy-resolving to eddy resolving scheme results in more consistent simulations with observations in both intensity and structure of the rain band. The major increase is in the convective precipitation near the much-tightened SST gradient associated with the oceanic front. Therefore, the intensity improvement caused by oceanic resolution increases is more effective than that from atmospheric resolution increases. Further analyses show that the improvement of Gulf Stream precipitation climatology due to model horizontal resolution increases can be understood in terms of the atmospheric surface pressure adjustment to the sharper SST gradient near the oceanic front, which leads to stronger atmospheric surface convergence and upper level divergence. The associated ascending motion contributes to the precipitation band located in the Gulf Stream.

A method for estimating and assessing modes of interannual variability in coupled climate models

The seasonal mean of a climate variable consists of: slow-external; slow-internal; and intraseasonal components. Using an analysis of variance-based method, the interannual variability of the seasonal mean from an ensemble of coupled atmosphere-ocean general circulation model (CGCM) realisations is separable into these three components. Eigenvalue decomposition is applied to the covariance matrices to obtain, for each component, the dominant modes of variability (eigenvectors) and their associated variance (eigenvalues) for the climate variable. Here, a method is described that assesses the modes of interannual variability in CGCMs against those obtained from reanalysis data based on observations. A metric is defined based on the pattern correlation between the observed and modelled modes of variability, and the ratio of their associated variances. This metric is applied to monthly mean southern hemisphere 500 hPa geopotential height from the second half of the 20th century. It is shown that CGCMs have clear differences in the slow-component of modes of interannual variability, related to external forcings and/or slowly-varying internal variability. References C. S. Frederiksen and X. Zheng. Coherent structures of interannual variability of the atmospheric circulation: the role of intraseasonal variability. Frontiers in Turbulence and Coherent Structures , World Scientific Lecture Notes in Complex Systems , Vol. 6, Eds Jim Denier and Jorgen Frederiksen, World Scientific Publications, 87–120, 2007. doi:10.1142/6320 C. E. Leith. The standard error of time-average estimates of climatic means. J. Appl. Meteor. , 12:1066–1069, 1973. 2.0.CO;2>doi:10.1175/1520-0450(1973)012 2.0.CO;2 X. Zheng and C. S. Frederiksen. Variability of seasonal-mean fields arising from intraseasonal variability: part 1, methodology. Clim. Dynam. , 23:177–191, 2004. doi:10.1007/s00382-004-0428-7 C. S. Frederiksen and X. Zheng. Variability of seasonal-mean fields arising from intraseasonal variability. Part 3: Application to SH winter and summer circulations. Clim. Dynam. , 28:849–866, 2007. doi:10.1007/s00382-006-0214-9 S. Grainger, C. S. Frederiksen and X. Zheng. A method for evaluating the modes of variability in general circulation models. ANZIAM J. , 50:C399–C412, 2008. http://journal.austms.org.au/ojs/index.php/ANZIAMJ/article/view/1431 G. A. Meehl, C. Covey, K. E. Taylor, T. Delworth, R. J. Stouffer, M. Latif, B. McAvaney and J. F. B. Mitchell. The WCRP CMIP3 multimodel dataset: A new era in climate change research. Bull. Amer. Meteor. Soc. , 88:1383–1394, 2007. doi:10.1175/BAMS-88-9-1383 K. E. Taylor, R. J. Stouffer and G. A. Meehl. An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc. 93:485–498, 2012. doi:10.1175/BAMS-D-11-00094.1 X. Zheng, M. Sugi and C. S. Frederiksen. Interannual variability and predictability in an ensemble of climate simulations with the MRI-JMA AGCM. J. Meteor. Soc. Jap. , 82:1–18, 2004. doi:10.2151/jmsj.82.1 H. von Storch and F. W. Zwiers. Statistical Analysis in Climate Research. Cambridge University Press , 484pp, 1999. doi:10.1017/cbo9780511612336 S. Grainger, C. S. Frederiksen and X. Zheng. Modes of interannual variability of Southern Hemisphere atmoshperic circulation in CMIP3 models: assessment and projections. Clim. Dynam. 41:479–500, 2013. doi:10.1007/s00382-012-1659-7 S. Grainger, C. S. Frederiksen and X. Zheng. Estimating components of covariance between two climate variables using model ensembles. ANZIAM J. , 52:C318–C332, 2011. http://journal.austms.org.au/ojs/index.php/ANZIAMJ/article/view/3928 G. P. Compo, J. S. Whitaker, P. D. Sardeshmukh, N. Matsui, R. J. Allan, X. Yin, B. E. Gleason, R. S. Vose, G. Rutledge, P. Bessemoulin, S. Bronnimann, M. Brunet, R. I. Crouthamel, A. N. Grant, P. Y. Groisman, P. D. Jones, M. C. Kruk, A. C. Kruger, G. J. Marshall, M. Maugeri, H. Y. Mok, O. Nordli, T. F. Ross, R. M. Trigo, X. L. Wang, S. D. Woodruff and S. J. Worley. The Twentieth Century Reanalysis Project. Quart. J. Roy. Meteor. Soc. 137:1–28, 2011. doi:10.1002/qj.776 N. A. Rayner, D. E. Parker, E. B. Horton, C. K. Folland, L. V. Alexander, D. P. Rowell, E. C. Kent and A. Kaplan. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. , 108(D14):4407, 2003. doi:10.1029/2002JD002670

Mechanisms for stronger warming over drier ecoregions observed since 1979

Previous research found that the warming rate observed for the period 1979–2012 increases dramatically with decreasing vegetation greenness over land between 50°S and 50°N, with the strongest warming rate seen over the driest regions such as the Sahara desert and the Arabian Peninsula, suggesting warming amplification over deserts. To further this finding, this paper explores possible mechanisms for this amplification by analyzing observations, reanalysis data and historical simulations of global coupled atmosphere–ocean general circulation models. We examine various variables, related to surface radiative forcing, land surface properties, and surface energy and radiation budget, that control the warming patterns in terms of large-scale ecoregions. Our results indicate that desert amplification is likely attributable primarily to enhanced longwave radiative forcing associated with a stronger water vapor feedback over drier ecoregions in response to the positive global-scale greenhouse gas forcing. This warming amplification and associated downward longwave radiation at the surface are reproduced by historical simulations with anthropogenic and natural forcings, but are absent if only natural forcings are considered, pointing to new potential fingerprints of anthropogenic warming. These results suggest a fundamental pattern of global warming over land that depend on the dryness of ecosystems in mid- and low- latitudes, likely reflecting primarily the first order large-scale thermodynamic component of global warming linked to changes in the water and energy cycles over different ecosystems. This finding may have important implications in interpreting global warming patterns and assessing climate change impacts.

Net Precipitation of Antarctica: Thermodynamical and Dynamical Parts of the Climate Change Signal

Abstract This paper investigates climate change signals of Southern Hemisphere (SH) moisture flux simulated by three members of one CMIP3 coupled atmosphere–ocean general circulation model (AOGCM) and a multimodel ensemble of CMIP5 simulations. Generally, flux changes are dominated by increased atmospheric moisture due to temperature increase in the future climate projections. An approach is presented to distinguish between thermodynamical and dynamical influences on moisture flux. Furthermore, a physical interpretation of the transport changes due to dynamics is investigated by decomposing atmospheric waves into different length scales and temporal variations. Signals of moisture flux are compared with fluctuations of geopotential height fields as well as climate signals of extratropical cyclones. Moisture flux variability in the synoptic length scale with temporal variations shorter than 8 days can be assigned to the SH storm track. Climate change signals of these atmospheric waves show a distinctive poleward shift. This can be attributed to the climate change signal of extratropical cyclones. Furthermore, the climate change signal of atmospheric waves can be better understood if strong cyclones that intensify especially on the Eastern Hemisphere are taken into account. Antarctic net precipitation is calculated by means of the vertically integrated moisture flux. Future projections show increasing signals of net precipitation, whereas the dynamical part of net precipitation decreases. This can be understood by means of the low-variability component of synoptic-scale waves, which show a decreasing signal, especially off the coast of West Antarctica. This is shown to be due to changing variability of the Amundsen–Bellingshausen Seas low.

Future risk of the maize orange leafhopper, Cicadulina bipunctata, and maize wallaby ear symptom in temperate Japan

AbstractSince the 1980s, the maize orange leafhopper, Cicadulina bipunctata, has been gradually expanding its range in east Asia associated with global warming. This leafhopper induces maize wallaby ear symptom (MWES) on young maize plants and has become a threat to forage maize production in southern parts of temperate Japan since around 2000. In this study, using predictions of future temperature and precipitation calculated from Atmosphere–Ocean Coupled General Circulation Models, the future risk of C. bipunctata expansion and MWES occurrence in Japan (spatial resolution: 1 km2) was predicted. A nominal logistic regression analysis showed a significant contribution of cumulative low temperature during winter to the current distribution of C. bipunctata. The range of C. bipunctata was predicted to expand northward, particularly in Kyushu, Shikoku and the southern part of Honshu after the 2060s. Predicted intensification of MWES would reduce the efficacy of maize cultivars that are currently tolerant to MWES, in southern Kyushu in the 2020s, and in most parts of Kyushu, Shikoku and southwestern Honshu in the 2060s. These results suggest the need for measures to counter further expansion of C. bipunctata and improvement of current tolerant maize cultivars.

The seasonally varying effect of the Tibetan Plateau on Northern Hemispheric blocking frequency and amplitude

The Northern Hemisphere atmospheric blocking is a primary weather and climate system that accompanies extreme cold spells and heat waves. This study assesses effects of the Tibetan Plateau (TP), the largest continental mountain belt, on the blocking frequency (BF) and amplitude (BA) with progressive TP uplift experiments from 0 to 100 % using a coupled atmosphere–ocean general circulation model. The TP uplift increases the annual-mean BF by 3 and 21 % over the Pacific and Atlantic basins, respectively. A particular focus is placed on the seasonally distinct mechanism in the effects of TP uplift on the boreal winter and summer blockings. During winter, the TP uplift increases the BF over the active centers of both ocean basins via amplifying the eddy kinetic energy of stationary waves. On the other hand, in summer, the TP uplift tends to shift the location of BF northward due to notable poleward displacement of the jet stream and transient eddy activities, particularly over the Atlantic. Compared to the considerable BF increase in both seasons, the amplification of BA due to the TP uplift is much stronger in winter than in summer, reaffirming the seasonally varying TP effect on the blocking. Further analyses reveal that in summer, the TP uplift modulates more effectively the jet displacement than its strength, leading more linear northward shift of jet and BF, especially over the Atlantic. This study will contribute to advances in simulation and prediction of atmospheric blocking events.

Response of the Equatorial Pacific Seasonal Cycle to Orbital Forcing

Abstract The response of the equatorial Pacific Ocean’s seasonal cycle to orbital forcing is explored using idealized simulations with a coupled atmosphere–ocean GCM in which eccentricity, obliquity, and the longitude of perihelion are altered while other boundary conditions are maintained at preindustrial levels. The importance of ocean dynamics in the climate response is investigated using additional simulations with a slab ocean version of the model. Precession is found to substantially influence the equatorial Pacific seasonal cycle through both thermodynamic and dynamic mechanisms, while changes in obliquity have only a small effect. In the precession experiments, western equatorial Pacific SSTs respond in a direct thermodynamic manner to changes in insolation, while the eastern equatorial Pacific is first affected by the propagation of thermocline temperature anomalies from the west. These thermocline signals result from zonal wind anomalies associated with changes in the strength of subtropical anticyclones and shifts in the regions of convection in the western equatorial Pacific. The redistribution of heat from these thermocline signals, aided by the direct thermodynamic effect of insolation anomalies, results in large changes to the strength and timing of the eastern equatorial Pacific seasonal cycle. A comparison of 10 CMIP5 mid-Holocene experiments, in which the primary forcing is due to precession, shows that this response is relatively robust across models. Because equatorial Pacific SST anomalies have local climate impacts as well as nonlocal impacts through teleconnections, these results may be important to understanding paleoclimate variations both inside and outside of the tropical Pacific.

Where were the monsoon regions and arid zones in Asia prior to the Tibetan Plateau uplift?

Abstract The impact of the Tibetan Plateau uplift on the Asian monsoons and inland arid climates is an important but also controversial question in studies of paleoenvironmental change during the Cenozoic. In order to achieve a good understanding of the background for the formation of the Asian monsoons and arid environments, it is necessary to know the characteristics of the distribution of monsoon regions and arid zones in Asia before the plateau uplift. In this study, we discuss in detail the patterns of distribution of the Asian monsoon and arid regions before the plateau uplift on the basis of modeling results without topography from a global coupled atmosphere–ocean general circulation model, compare our results with previous simulation studies and available biogeological data, and review the uncertainties in the current knowledge. Based on what we know at the moment, tropical monsoon climates existed south of 20°N in South and Southeast Asia before the plateau uplift, while the East Asian monsoon was entirely absent in the extratropics. These tropical monsoons mainly resulted from the seasonal shifts of the Inter-Tropical Convergence Zone. There may have been a quasi-monsoon region in central-southern Siberia. Most of the arid regions in the Asian continent were limited to the latitudes of 20–40°N, corresponding to the range of the subtropical high pressure year-around. In the meantime, the present-day arid regions located in the relatively high latitudes in Central Asia were most likely absent before the plateau uplift. The main results from the above modeling analyses are qualitatively consistent with the available biogeological data. These results highlight the importance of the uplift of the Tibetan Plateau in the Cenozoic evolution of the Asian climate pattern of dry–wet conditions. Future studies should be focused on effects of the changes in land–sea distribution and atmospheric CO2 concentrations before and after the plateau uplift, and also on cross-comparisons between numerical simulations and geological evidence, so that a comprehensive understanding of the evolution of the Cenozoic paleoenvironments in Asia can be achieved.

How Well Do the CMIP5 Models Simulate the Antarctic Atmospheric Energy Budget?

Abstract The authors evaluate 23 coupled atmosphere–ocean general circulation models from phase 5 of CMIP (CMIP5) in terms of their ability to simulate the observed climatological mean energy budget of the Antarctic atmosphere. While the models are shown to capture the gross features of the energy budget well [e.g., the observed two-way balance between the top-of-atmosphere (TOA) net radiation and horizontal convergence of atmospheric energy transport], the simulated TOA absorbed shortwave (SW) radiation is too large during austral summer. In the multimodel mean, this excessive absorption reaches approximately 10 W m−2, with even larger biases (up to 25–30 W m−2) in individual models. Previous studies have identified similar climate model biases in the TOA net SW radiation at Southern Hemisphere midlatitudes and have attributed these biases to errors in the simulated cloud cover. Over the Antarctic, though, model cloud errors are of secondary importance, and biases in the simulated TOA net SW flux are instead driven mainly by biases in the clear-sky SW reflection. The latter are likely related in part to the models’ underestimation of the observed annual minimum in Antarctic sea ice extent, thus underscoring the importance of sea ice in the Antarctic energy budget. Finally, substantial differences in the climatological surface energy fluxes between existing observational datasets preclude any meaningful assessment of model skill in simulating these fluxes.

A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.

Prediction of inflows into Lake Kariba using a combination of physical and empirical models

ABSTRACTSeasonal climate forecasts are operationally produced at various climate prediction centres around the world. However, these forecasts may not necessarily be appropriately integrated into application models in order to help with decision‐making processes. This study investigates the use of a combination of physical and empirical models to predict seasonal inflows into Lake Kariba in southern Africa. Two predictions systems are considered. The first uses antecedent seasonal rainfall totals over the upper Zambezi catchment as predictor in a statistical model for estimating seasonal inflows into Lake Kariba. The second and more sophisticated method uses predicted low‐level atmospheric circulation of a coupled ocean–atmosphere general circulation model (CGCM) downscaled to the inflows. Forecast verification results are presented for five run‐on 3‐month seasons; from September to June over an independent hindcast period of 14 years (1995/1996 to 2008/2009). Verification is conducted using the relative operating characteristic (ROC) and the reliability diagram. In addition to the presented verification statistics, the hindcasts are also evaluated in terms of their economic value as a usefulness indicator of forecast quality for bureaucrats and to the general public. The models in general perform best during the austral mid‐summer season of DJF (seasonal onset of inflows) and the autumn season of MAM (main inflow season). Moreover, the prediction system that uses the output of the CGCM is superior to the simple statistical approach. An additional forecast of a recent flooding event (2010/2011), which lies outside of the 14‐year verification window, is presented to demonstrate the forecast system's operational capability further during a season of high inflows that caused societal and infrastructure problems over the region.

Twin experiments with the equivalent weights particle filter and HadCM3

This article investigates the use of a particle filter for data assimilation with a full‐scale coupled ocean–atmosphere general circulation model. Synthetic twin experiments are performed to assess the performance of the equivalent weights filter in such a high‐dimensional system. Artificial two‐dimensional sea surface temperature fields are used as observational data every day. Results are presented for different values of the free parameters in the method. Measures of the performance of the filter are root mean square errors, trajectories of individual variables in the model and rank histograms. Filter degeneracy is not observed and the performance of the filter is shown to depend on the ability to keep maximum spread in the ensemble.

Predictability of the California Niño/Niña*

Abstract Predictability of a recently discovered regional coupled climate mode called the California Niño (Niña) off Baja California and California is explored using a seasonal prediction system based on the Scale Interaction Experiment-Frontier, version 1 (SINTEX-F1) coupled ocean–atmosphere general circulation model. Because of the skillful prediction of basin-scale El Niño (La Niña), the California Niño (Niña) that co-occurs with El Niño (La Niña) with a peak in boreal winter is found to be predictable at least a couple of seasons ahead. On the other hand, the regional coupled phenomenon peaking in boreal summer without co-occurrence with El Niño (La Niña) is difficult to predict. The difficulty in predicting such an intrinsic regional climate phenomenon may be due to model deficiency in resolving the regional air–sea–land positive feedback processes. The model may also underestimate coastal Kelvin waves with a small offshore scale, which may play an important role in the generation of the California Niño/Niña. It may be improved by increasing horizontal resolution of the ocean component of the coupled model. The present study may provide a guideline to improve seasonal prediction of regional climate modes for important industrial as well as social applications.

Projected impacts of climate change on water availability indicators in a semi-arid region of central Mexico

In many arid and semi-arid regions of the world, the scarcity of water resources, increasing population and the experience of recent droughts are exerting great pressures on water resources. Climate change is anticipated to exacerbate the vulnerability of water resources, which clearly highlights the need for developing sustainable water management policies and appropriate adaptation strategies. In this paper, the likely impact of climate change on water availability indicators in a semiarid region is explored through a case study in a developing country. Queretaro River Basin (QRB) in Central Mexico, is presented as an example of a semi-arid region that is facing growing pressures on the availability of water resources to sustainably meet social, economic and ecological needs. The output of seven downscaled Global Coupled Ocean-Atmosphere General Circulation Models (AOGCMs) for the B1 and A1B greenhouse gas emissions scenarios (GHGES) were used to investigate the likely impacts of climate change on water resources in the QRB. The computed future scenarios of climate change predict that increases in mean annual temperature ranging from 0.8 °C to 4.8 °C and decreases in mean annual precipitation ranging from 17% to 22% could result in a decline of up to 9.16% in the available water for groundwater recharge and runoff by the end of the 21st century. Results also suggest that for the future, both dry and wet events will become more severe and frequent, increasing the vulnerability of water resources and compromising sustainability. Therefore, it is advisable that water management planning considers flexible adaptation strategies in order to allow for adjustment under different scenarios of water availability, if the implementation of unbiased, efficient and economical water resources strategies is to enhance sustainability and resilience to climate change in the long-term.

ENSO Variability Simulated by a Coupled General Circulation Model: ECHAM5/MPI-OM

AbstractThe accurate simulation of the equatorial sea surface temperature (SST) variability is crucial for a proper representation or prediction of the El Nino-Southern Oscillation (ENSO). This paper describes the tropical variability simulated by the Max Planck Institute (MPI) for meteorology coupled atmosphere-ocean general circulation model (CGCM). A control simulation with pre-industrial greenhouse gases is analyzed, and the simulation of key oceanic features, such as SST, is compared with observations. Results from the 400-yr control simulation show that the model's ENSO variability is quite realistic in terms of structure, strength, and period. Also, two related features (the annual cycle of SST and the-phase locking of ENSO events), which are significant in determining the model's performance of realistic ENSO prediction, are further validated to be well reproduced by the MPI climate model, which is an atmospheric model ECHAM5 (which fuses the EC for European Center and HAM for Hamburg) coupled to ...

Estimating the limit of decadal-scale climate predictability using observational data

Current coupled atmosphere–ocean general circulation models can not simulate decadal variability well, and model errors would have a significant impact on the estimation of decadal predictability. In this study, the nonlinear local Lyapunov exponent method is adopted to estimate the limit of decadal predictability based on 9-year low-pass filtered sea surface temperature (SST) and sea level pressure (SLP) observations. The results show that the limit of decadal predictability of the SST field is relatively large in the North Atlantic, North Pacific, Southern Ocean, tropical Indian Ocean, and western North Pacific, exceeding 7 years at most locations in these regions. In contrast, the limit of the SST field is relatively small in the tropical central–eastern Pacific (4–6 years). Similar to the SST field, the SLP field has a relatively large limit of decadal predictability over the Antarctic, North Pacific, and tropical Indian Ocean (>6 years). In addition, a relatively large limit of decadal predictability of the SLP field also occurs over the land regions of Africa, India, and South America. Distributions of the limit of decadal predictability of both the SST and SLP fields are almost consistent with those of their intensity and persistence on decadal timescales. By examining the limit of decadal predictability of several major climate modes, we found that the limit of decadal predictability of the Pacific decadal oscillation (PDO) is about 9 years, slightly lower than that of the Atlantic multidecadal oscillation (AMO) (about 11 years). In contrast, the northern and southern annular modes have limits of decadal predictability of about 4 and 9 years, respectively. However, the above limits estimated using time-filtered data may overestimate the predictability of decadal variability due to the use of time filtering. Filtered noise with the same spectral characteristics as the PDO and AMO, has a predictability of about 3 years. Future work is required with a longer period of observations or using a more realistic model of decadal variability to assess the real-time decadal predictability.

Skill evaluation of the CanCM4 and its MOS for seasonal rainfall forecast in Malaysia during the early and late winter monsoon periods

This study evaluates the forecast skill of the fourth version of the Canadian coupled ocean–atmosphere general circulation model (CanCM4) and its model output statistics (MOS) to forecast the seasonal rainfall in Malaysia, particularly during early (October–November–December) and late (January–February–March) winter monsoon periods. CanCM4 is the latest component of the Canadian Seasonal to Inter-annual Prediction System (CanSIPS), which is a multi-seasonal climate prediction system developed particularly for Canada but applicable globally. Generally, CanCM4's skill in reproducing the climatology during winter is not as good as in other seasons because of the model's inability to simulate the regional synoptic circulations over the western Maritime Continent. In particular, the model fails to forecast the cold surges and Borneo vortex circulations that play critical roles in moisture horizontal advection. Moreover, its forecast skill during the early winter monsoon period is poorer than during the late period. Interestingly, forecast skill is enhanced when MOS models are applied as the MOS utilizes the predictive signals in the quasi-global predictors from the CanCM4 forecast system. The predictability can be traced to the conventional El Nino–Southern Oscillation (ENSO) and ENSO Modoki signals that are present in the CanCM4 forecast MOS predictor fields. The quasi-global sea-surface temperature and quasi-global sea-level pressure fields are found to be the most useful predictors. Interestingly, CanCM4 forecast signals associated with the Indian Ocean Dipole also contribute to the skill. Skill enhancement is particularly significant for northern Borneo during early monsoon periods in medium- and long-lead forecasts when the CanCM4 has minimal direct skill in the region.

An Analysis of the Linkage of Pacific Subtropical Cells with the Recharge–Discharge Processes in ENSO Evolution

Abstract The Simple Ocean Data Assimilation, version 2.2.4 (SODA 2.2.4), analysis for the period of 1960–2010 is used to study the variability of Pacific subtropical cells (STCs) and its causal relation with tropical climate variability. Results show that the interior STC transport into the equatorial basin through 9°S and 9°N is well connected with equatorial sea surface temperature (SST) (9°S–9°N, 180°–90°W). The highest correlation at interannual time scales is contributed by the western interior STC transport within 160°E and 130°W. It is known that the ENSO recharge–discharge cycle experiences five stages: the recharging stage, recharged stage, warmest SST stage, discharging stage, and discharged stage. A correlation analysis of interior STC transport convergence, equatorial warm water volume (WWV), wind stress curl, and SST identifies the time intervals between the five stages, which are 8, 10, 2, and 8 months, respectively. A composite analysis for El Niño–developing and La Niña–developing events is also performed. The composited ENSO evolutions are in accordance with the recharge–discharge theory and the corresponding time lags between the above denoted five stages are 4–12, 6, 2, and 4 months, respectively. For stronger El Niño events, the discharge due to interior STC transport at 9°N terminates earlier than that at 9°S because of the southward migration of westerly winds following the El Niño peak phase. This study clarifies subsurface transport processes and their time intervals, which are useful for refinement of theoretical models and for evaluating coupled ocean–atmosphere general circulation model results.

Regional climate change scenarios over South Asia in the CMIP5 coupled climate model simulations

This paper evaluates the performance of a suite of state-of-art coupled atmosphere–ocean general circulation models (AOGCMs) in their representation of regional characteristics of hydrological cycle and temperature over South Asia. Based on AOGCM experiments conducted for two types of future greenhouse gas emission scenarios (RCP4.5 and RCP8.5) extending up to the end of 21st century, scenarios of temperature and hydrological cycle are presented. The AOGCMs, despite their relatively coarse resolution, have shown a reasonable skill in depicting the hydrological cycle over the South Asian region. However, considerable biases do exist with reference to the observed hydrological cycle and also inter-model differences. The regional climate change scenarios of temperature (T), atmospheric water balance components, precipitation, moisture convergence and evaporation (P, C and E) up to the end of the 21st century based on CMIP5 modeling experiments conducted for (RCP4.5 and RCP8.5) indicate marked increase in both rainfall and temperature into the 21st century, particularly becoming conspicuous after the 2050s. The monsoon rainfall and atmospheric water balance changes under RCP4.5 and RCP8.5 scenarios are discussed in detail in this paper. Spatial patterns of rainfall change projections indicate maximum increase over South Asia in most of the models. Model simulations under scenarios of increased greenhouse gas concentrations suggests that the intensification of the hydrological cycle is driven mainly by the increased moisture convergence due to increase in the water holding capacity of the atmosphere in a warmer environment, the intensification of the hydrological cycle is greater for RCP8.5 compared to RCP4.5, also fewer models indicate increased variance of temperature and rainfall in a warmer environment. While the scenarios presented in this study are indicative of the expected range of rainfall and water balance changes, it must be noted that the quantitative estimates still have large uncertainties associated with them. Five best model mean reveals the general consensus among the AOGCM results and gives the best estimate of the future projection over the South Asian monsoon region.

Comparison between Observed and Model-Simulated Atmospheric Circulation Patterns Associated with Extreme Temperature Days over North America Using CMIP5 Historical Simulations

Abstract Circulation patterns associated with extreme temperature days over North America, as simulated by a suite of climate models, are compared with those obtained from observations. The authors analyze 17 coupled atmosphere–ocean general circulation models contributing to the fifth phase of the Coupled Model Intercomparison Project. Circulation patterns are defined as composites of anomalies in sea level pressure and 500-hPa geopotential height concurrent with days in the tails of temperature distribution. Several metrics used to systematically describe circulation patterns associated with extreme temperature days are applied to both the observed and model-simulated data. Additionally, self-organizing maps are employed as a means of comparing observed and model-simulated circulation patterns across the North American domain. In general, the multimodel ensemble resembles the observed patterns well, especially in areas removed from complex geographic features (e.g., mountains and coastlines). Individual model results vary; however, the majority of models capture the major features observed. The multimodel ensemble captures several key features, including regional variations in the strength and orientation of atmospheric circulation patterns associated with extreme temperatures, both near the surface and aloft, as well as variations with latitude and season. The results from this work suggest that these models can be used to comprehensively examine the role that changes in atmospheric circulation will play in projected changes in temperature extremes because of future anthropogenic climate warming.