Long time-scale potential predictability in an ensemble of coupled climate models

A diagnostic multi-model ensemble potential predictability study of surface air temperature is performed using data from nine models participating in the Coupled Model Intercomparison Project (CMIP1). The data are considered to be a sample of results from the population of models embodying current abilities to simulate the climate system and represent a range of numerics, resolution and of physical parametrizations. The potential predictability of pentadal, decadal, and 25-year means is analyzed. The multi-model ensemble provides a statistically stable estimate of the potential predictability variance fraction (ppvf) with a narrow confidence interval. This is not the case for individual models with modest lengths of simulation data nor, by implication, for the instrument-based observational record. Potential predictability is found predominately over the high-latitude oceans. There is evidence also for potential predictability at tropical latitudes in the Pacific and Atlantic, but not the Indian oceans, on the shorter of the time scales. The potential predictability variance fraction decreases with increasing time scale but appreciable values exist at all of the time scales considered, especially for the Southern Ocean and for the North Atlantic. Values over land, while statistically non-zero, are small. The autocorrelation structure of the data is investigated to account for its effect on the statistical estimation of the ppvf and to indicate the extent to which the data reflect simple oceanic damping of white noise atmospheric forcing. Ensemble autocorrelation structures differ between tropical and extra-tropical latitudes (at least on the time scales considered) with more oscillatory behaviour implied in tropical regions compared to high latitudes. It appears that the results are inconsistent with simple ocean damping and that higher order autocorrelation structures of temperature cannot be neglected generally or in the determination of the potential predictability. The statistical results suggest that predictability in the extratropics is associated with long ocean time scales while in the tropics it is associated with the coupled atmosphere-ocean system. Physically based analyses are required to understand this long time scale behaviour and an ensemble view is also needed in order to determine the behaviour that is robust across models and the real system.     

Seasonal to interannual climate predictability in mid and high northern latitudes in a global coupled model

The upper limit of climate predictability in mid and high northern latitudes on seasonal to interannual time scales is investigated by performing two perfect ensemble experiments with the global coupled atmosphere–ocean–sea ice model ECHAM5/MPI-OM. The ensembles consist of six members and are initialized in January and July from different years of the model’s 300-year control integration. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric climate parameters. The predictability of the atmospheric circulation is small except for southeastern Europe, parts of North America and the North Pacific, where significant predictability occurs with a lead time of up to half a year. The predictability of 2 m air temperature shows a large land–sea contrast with highest predictabilities over the sub polar North Atlantic and North Pacific. A combination of relatively high persistence and advection of sea surface temperature anomalies into these areas leads to large predictability. Air temperature over Europe, parts of North America and Asia shows significant predictability of up to half a year in advance. Over the ice-covered Arctic, air temperature is not predictable at time scales exceeding 2 months. Sea ice thickness is highly predictable in the central Arctic mainly due to persistence and in the Labrador Sea due to dynamics. Surface salinity is highly predictable in the Arctic Ocean, northern North Atlantic and North Pacific for several years in advance. We compare the results to the predictability due to persistence and show the importance of dynamical processes for the predictability.     

Global and regional variability in a coupled AOGCM

 The variability of near surface temperature on global and regional spatial scales and interannual time scales from a 1000 year control integration of the Hadley Centre coupled model (HADCM2-CTL) are compared with the observational record of surface temperature. The model succeeds in reproducing the observed patterns of natural variability, with high variability over the northern continents and low variability over much of the tropics. The model global mean variability has similar strength to observed global mean variability on time scales less than 20 years. The warming seen in the historical record is outside the range of natural variability as simulated in HADCM2-CTL. The model has El-Ni?o/Southern Oscillation (ENSO)-like behaviour with a central Pacific, peak to peak, strength of approximately 3 K. Changes in near surface temperature in the central Pacific are strongly correlated with changes in near surface temperature over most of the tropics, large regions of the extra-tropics and changes in tropical ocean upper 250 m heat content. Tropospheric temperature changes and tropical surface pressure changes are also strongly correlated with changes in the central Pacific surface temperature. Oceanic regions show significant departures from an AR1 or first order Markov behaviour in the Northwest Atlantic, Northwest Pacific and Arctic oceans. The Northwest Atlantic region has large amounts of variability over periods greater than 50 years. This variability is associated with a jump in the strength of North Atlantic meridional stream function. The spectra of the Western European and Continental US land regions are not significantly different from an AR1 process. The flow through the Drake Passage has an interannual standard deviation of approximately 2.5 Sv with significant departures from an AR1 process at time scales greater than 40 years. Winter northern hemispheric 500 hPa geopotential height shows some evidence of multiple regimes but no year to year persistence of these regimes. Received: 31 January 1996/Accepted: 22 July 1996     

The annual cycle and the predictability of the tropical coupled ocean-atmosphere system

Summary Using large-scale circulation statistics from the Pacific Ocean basin, predictability of the coupled ocean-atmosphere system on interannual time scales is found both to be limited in extent and to possess a strong annual cycle. Irrespective of when lagged correlations are commenced, correlations decrease rapidly through the boreal spring, indicating an inherent predictability limitation for large scale coupled oceanicatmospheric processes such as El Niño. Long term prediction experiments using numerical coupled-models show that the models are excellent facsimiles of the real system. They, too, encounter the predictability barrier and exhibit a substantial decrease in observation-prediction correlation across the boreal spring. Thus, a predictive system based solely on the interactive physics of the Pacific Basin appears limited to a maximum of less than one year and a minimum of only one or two months.Two hypotheses are made to explain the existence of the predictability barrier. First, it is argued that the tropical coupled system is at its frailest state during the boreal spring and that the signal-to-noise ratio is weakest. In such a system, maximum random error growth may occur as the atmosphere and the ocean become temporally detached and wander onto different climate trajectories. A series of 144 preliminary Monte Carlo experiments were conducted with a coupled ocean-atmosphere model to test the hypothesis. Irrespective of when the experiments were commenced, error growth was maximized at the same time of the year. The second hypothesis suggests that the near-equatorial circulation is perturbed at the time of its weakest state by external influences such as the monsoon and that the climate wanderings are nudged deterministically. There is observational and theoretical evidence to support the hypothesis. Observations suggest that anomalous monsoons impart basin-wide coherent alterations of the wind stress field in the Pacific Ocean. Experiments with a coupled ocean-atmosphere model show that the period of an ENSO event is altered substantially by an anomalous monsoon. Given that there appear to be precursors to anomalous monsoons, it is suggested that there may be ways to avoid the predictability barrier and thus extend prediction of the entire system.Finally, noting that the two hypotheses are not mutually exclusive, they are combined to form a unified theory. As the asymmetric monsoonal and the symmetric near-equatorial heating are in approximate quadrature, it is argued that the monsoons influence the Walker circulation during the boreal spring. However, during the boreal fall and early winter the near-equatorial heating variability dominates the winter monsoon.With 18 Figures     

Statistical Analysis and Prediction of KwaZulu-Natal Climate

Summary. Climatic fluctuations in KwaZulu-Natal, southeastern South Africa, are analysed using statistical techniques. Moist easterly winds sweep in from the Indian Ocean during all seasons except winter, producing a balance between evaporative losses and precipitation. The seasonal cycle is unimodal with a peak of rainfall and temperature in the summer months (December to February) with a 1–2 month lag for streamflow and vegetation growth. Rainfall and temperature departures in recent decades exhibit a 3 year cycle and a 3–6 month persistence of cool/wet or warm/dry phases. The predictability of summer rainfall, temperature, crop yield, inflow to dams and malaria incidence is explored. Multivariate linear regression models with lead-times of one season account for two-thirds of the variance in most cases. Climatic signals which enable predictability include winds over the tropical east Atlantic and north Indian Ocean. El Ni?o signals from tropical Pacific sea surface temperatures and the Southern Oscillation Index are also important predictors for KwaZulu-Natal’s climate. These relationships suggest that local circulation responses to large scale tropical-polar temperature gradients govern climatic fluctuations over KwaZulu-Natal. Received August 27, 1997. Revised November 10, 1997     

Interpretation of interbasin exchange in an isopycnal ocean model

 This work concerns an analysis of inter-basin and inter-layer exchanges in the component ocean part of the coupled ECHAM4/OPYC3 general circulation model, aimed at documenting the simulation of North Atlantic Deep Water (NADW) and related thermohaline circulations in the Indian and Pacific Oceans. The modeled NADW is formed mainly in the Greenland– Iceland–Norwegian Seas through a composite effect of deep convection and downward cross-isopycnal transport. The modeled deep-layer outflow of NADW can reach 16 Sv near 30 °S in the South Atlantic, with the corresponding upper-layer return flow mainly coming from the “cold water path” through Drake Passage. Less than 4 Sv of the Agulhas “leakage” water contributes to the replacement of NADW along the “warm water path”. In the South Atlantic Ocean, the model shows that some intermediate isopycnal layers with potential densities ranging between 27.0 and 27.5 are the major water source that compensate the NADW return flow and enhance the Circumpolar Deep Water (CDW) flowing from the Atlantic into Indian Ocean. The modeled thermohaline circulations in the Indian and Pacific Oceans indicate that the Indian Ocean may play the major role in converting deep water into intermediate water. About 16 Sv of the CDW-originating deep water enters the Indian Ocean northward of 31 °S, of which more than 13 Sv “upwell” mainly near the continental boundaries of Africa, South Asia and Australia through inter-layer exchanges and return to the Antarctic Circumpolar Current (ACC) as intermediate-layer water. As a contrast, only 4 Sv of Pacific intermediate water is connected to “upwelling” flow southward across 31 °S while the magnitude of northward deep flow across 31 °S in the Pacific Ocean is significantly greater than that in the Indian Ocean. The model suggests that a large portion of the deep waters entering the Pacific Ocean (about 14 Sv) “upwells” continually into some upper layers through the thermocline, and becomes the source of the Indonesian throughflow. Uncertainties in these results may be related to the incomplete adjustment of the model’s isopycnal layers and the sensitivity of the Indonesian throughflow to the model’s geography and topography. Received: 12 August 1997/Accepted: 12 March 1998     

The structure of low frequency phenomena in the tropics and its interaction with the extratropics

The structure of planetary scale low frequency phenomena in the tropics is studied, and an attempt is made to de-termine its influence and interactions with phenomena at higher latitudes.In the tropics, it is found that the majority of the variance in the zonal wind structure is made up in wave num-bers 1 and 2. During warm events in the Pacific Ocean, when the Southern Oscillation Index is negative, almost all of the variance resides in the gravest mode which undergoes a 40o eastward phase shift. Meanwhile, the second logitudinal mode almost disappears. On the other hand, the meridional wind field possesses maximum amplitude at higher wave numbers. However, near the equator, the amplitude is small with extreme values occurring in the subtropics. The difference in scale and the location of extrema of the meridional and zonal wind components indicate that the tropical atmosphere is responding to two different driving mechanisms,Correlation analyses between variations of the zonal wind at reference points along the equator with variations of component elsewhere show that there are strong logitudinal connections. The strongest correlations between the tropics and higher latitudes exist in the region of the equatorial westerlies. In fact, stronger correlations occur between variations in U anywhere along the equator and the middle latitudes to the north and south of the equatorial wester-lies than to the latitudes immediately to the north and south of the reference points. We interpret this “remote” corre-lation pattern as indicating a two-stage teleconnection process which emphasizes the importance of the equatorial tropical westerlies of the Pacific Ocean as a “corridor” of communication between the low and high latitudes. The regionality of the correlations confirms, to some extent, recent theoretical development regarding trapped equatorial modes. Finally, time lagged correlations from plus and minus six months between variations of U and OLR indicate that the interactions between the extratropics and low latitudes possess an organized sequence. The extratropical in-fluence appears to propagate into the tropics followed by an eastward propagation along the equator. Finally, a propagation from the tropics to the extratropics in the upper troposphere occurs in the eastern Pacific Ocean. The time-lagged correlation sequence does not appear to be symmetric about the equator.     

A Regression-based Assessment of the Predictability of New Zealand Climate Anomalies

Summary Estimates of the predictability of New Zealand monthly and seasonal temperature and rainfall anomalies are calculated using a cross-validated linear regression procedure. Predictors are indices of the large scale circulation, sea-surface temperatures, the Southern Oscillation Index and persistence. Statistical significance is estimated through a series of Monte Carlo trials. No significant forecast relationships are found for rainfall anomalies at either the monthly or seasonal time scale. Temperature forecasts are however considered to exhibit significant skill, with variance reductions of the order of 10–20% in independent trials. Temperature anomalies are most skilfully predicted over the North Island, and skill is greatest in Spring and Summer in most areas. At the monthly time scale, predictors local to the New Zealand region account for most of the forecast skill, while at the seasonal time scale, skill depends strongly upon “remote” predictors defined over regions of the southern hemisphere distant from New Zealand. Indices of meridional flow over the Tasman Sea/New Zealand region are found to be useful predictors, especially for monthly forecasts, perhaps as a proxy for atmospherically-forced sea surface temperature anomalies. Sea surface temperature anomalies to the west of New Zealand and in the tropical Indian Ocean are also useful, especially for seasonal predictions. Forecast skill is more reliably estimated at the monthly time scale than at the seasonal time scale, as a result of the larger sample size of monthly mean data. While long-term mean levels of skill may be estimated reliably over the whole data set, statistically significant decadal-scale variations are found in the predictability of temperature anomalies. Therefore, even if long-term forecast skill levels are reliably estimated, it may be impossible to predict the short-term skill of operational seasonal climate forecasts. Implications for operational climate predictions in mid-latitudes are discussed. Received July 18, 1997 Revised April 2, 1998     

Decadal predictability and prediction skill of sea surface temperatures in the South Pacific region

The South Pacific Ocean is a key driver of climate variability within the Southern Hemisphere at different time scales. Previous studies have characterized the main mode of interannual sea surface temperature (SST) variability in that region as a dipolar pattern of SST anomalies that cover subtropical and extratropical latitudes (the South Pacific Ocean Dipole, or SPOD), which is related to precipitation and temperature anomalies over several regions throughout the Southern Hemisphere. Using that relationship and the reported low predictive skill of precipitation anomalies over the Southern Hemisphere, this work explores the predictability and prediction skill of the SPOD in near-term climate hindcasts using a set of state-of-the-art forecast systems. Results show that predictability greatly benefits from initializing the hindcasts beyond the prescribed radiative forcing, and is modulated by known modes of climate variability, namely El Niño-Southern Oscillation and the Interdecadal Pacific Oscillation. Furthermore, the models are capable of simulating the spatial pattern of the observed SPOD even without initialization, which suggests that the key dynamical processes are properly represented. However, the hindcast of the actual phase of the mode is only achieved when the forecast systems are initialized, pointing at SPOD variability to not be radiatively forced but probably internally generated. The comparison with the performance of an empirical prediction based on persistence suggests that initialization may provide skillful information for SST anomalies, outperforming damping processes, up to 2–3 years into the future.     

Abrupt changes as indicators of decadal climate variability

 A statistical test has revealed that abrupt regional climate changes are produced in a coupled atmosphere-ocean general circulation model. Abrupt changes are detected over much of the globe although the occurrence frequency is small over the continents. Over the tropical Pacific Ocean and northern Pacific Ocean, surface air temperature (SAT) and sea level pressure (SLP) shift rapidly on decadal time scales. The regional climate changes presented here have been classified into three types. The first type consists of statistically significant shifts in SLP and statistically significant shifts in SAT which are of opposite sign, and which are reinforced through a positive feedback between the atmosphere and the ocean. The second type is for those occurrences where changes are of the same sign. The third type includes those with a significant shift in only one meteorological element. The second and third types are generally generated by changes in air pressure and wind fields induced by changes of the first type. For example, when SLP increases and sea surface temperature (SST) decreases abruptly in the tropical Pacific Ocean, it triggers abrupt regional changes in middle and high latitudes. The abrupt changes in the model climate have characteristics which are very similar to those of observed rapid shifts. Thus, it is concluded that abrupt changes are a predominant part of regional climate change on decadal time scales. Received: 11 February 1999 / Accepted: 18 May 2000     

Predictability of SST forced climate signals in two atmospheric general circulation models

 The predictability of atmospheric responses to global sea surface temperature (SST) anomalies is evaluated using ensemble simulations of two general circulation models (GCMs): the GENESIS version 1.5 (GEN) and the ECMWF cycle 36 (ECM). The integrations incorporate observed SST variations but start from different initial land and atmospheric states. Five GEN 1980–1992 and six ECM 1980–1988 realizations are compared with observations to distinguish predictable SST forced climate signals from internal variability. To facilitate the study, correlation analysis and significance evaluation techniques are developed on the basis of time series permutations. It is found that the annual mean global area with realistic signals is variable dependent and ranges from 3 to 20% in GEN and 6 to 28% in ECM. More than 95% of these signal areas occur between 35 °S–35 °N. Due to the existence of model biases, robust responses, which are independent of initial condition, are identified over broader areas. Both GCMs demonstrate that the sensitivity to initial conditions decreases and the predictability of SST forced responses increases, in order, from 850 hPa zonal wind, outgoing longwave radiation, 200 hPa zonal wind, sea-level pressure to 500 hPa height. The predictable signals are concentrated in the tropical and subtropical Pacific Ocean and are identified with typical El Ni?o/ Southern Oscillation phenomena that occur in response to SST and diabatic heating anomalies over the equatorial central Pacific. ECM is less sensitive to initial conditions and better predicts SST forced climate changes. This results from (1) a more realistic basic climatology, especially of the upper-level wind circulation, that produces more realistic interactions between the mean flow, stationary waves and tropical forcing; (2) a more vigorous hydrologic cycle that amplifies the tropical forcing signals, which can exceed internal variability and be more efficiently transported from the forcing region. Differences between the models and observations are identified. For GEN during El Ni?o, the convection does not carry energy to a sufficiently high altitude, while the spread of the tropospheric warming along the equator is slower and the anomaly magnitude smaller than observed. This impacts model ability to simulate realistic responses over Eurasia and the Indian Ocean. Similar biases exist in the ECM responses. In addition, the relationships between upper and lower tropospheric wind responses to SST forcing are not well reproduced by either model. The identification of these model biases leads to the conclusion that improvements in convective heat and momentum transport parametrizations and basic climate simulations could substantially increase predictive skill. Received: 25 April 1996 / Accepted: 9 December 1996     

Intercomparison of the seasonal cycle of tropical surface stress in 17 AMIP atmospheric general circulation models

 The mean state of the tropical atmosphere is important as the nature of the coupling between the ocean and the atmosphere depends nonlinearly on the basic state of the coupled system. The simulation of the annual cycle of the tropical surface wind stress by 17 atmospheric general circulation models (AGCMs) is examined and intercompared. The models considered were part of the Atmospheric Model Intercomparison Project (AMIP) and were integrated with observed sea surface temperature (SST) for the decade 1979–1988. Several measures have been devised to intercompare the performance of the 17 models on global tropical as well as regional scales. Within the limits of observational uncertainties, the models under examination simulate realistic tropical area-averaged zonal and meridional annual mean stresses. This is a noteworthy improvement over older generation low resolution models which were noted for their simulation of surface stresses considerably weaker than the observations. The models also simulate realistic magnitudes of the spatial distribution of the annual mean surface stress field and are seen to reproduce realistically its observed spatial pattern. Similar features are observed in the simulations of the annual variance field. The models perform well over almost all the tropical regions apart from a few. Of these, the simulations over Somali are interesting. Over this region, the models are seen to underestimate the annual mean zonal and meridional stresses. There is also wide variance between the different models in simulating these quantities. Large model-to-model variations were also seen in the simulations of the annual mean meridional stress field over equatorial Indian Ocean, south central Pacific, north east Pacific and equatorial eastern Pacific oceans. It is shown that the systematic errors in simulating the surface winds are related to the systematic errors in simulating the Inter-Tropical Convergence Zone (ITCZ) in its location and intensity. Weaker than observed annual mean southwesterlies simulated by most models over Somali is due to weaker than observed southwesterlies during the Northern Hemisphere summer. This is related to the weaker than observed land precipitation simulated by most models during the Northern Hemisphere summer. The diversity in simulation of the surface wind over Somali and equatorial Indian ocean is related to the diversity of AGCMs in simulating the precipitation zones in these regions. Received: 2 August 1996 / Accepted: 7 February 1997     

Climate predictability on interannual to decadal time scales: the initial value problem

Any initial value forecast of climate will be subject to errors originating from poorly known initial conditions, model imperfections, and by "chaos" in the sense that, even if the initial conditions were perfectly known, infinitesimal errors can amplify and spoil the forecast at some lead time. Here the latter source of error is examined using a "perfect model" approach whereby small perturbations are made to a coupled atmosphere-ocean general circulation model and the spread of nearby model trajectories, on time and space scales appropriate to seasonal-decadal climate variability, is measured to assess the lead time at which the error saturates. The study therefore represents an estimate of the upper limit of the predictability of climate (appropriate to the initial value problem) given a perfect model and near perfect knowledge of the initial conditions. It is found that, on average, surface air temperature anomalies are potentially predictable on seasonal to interannual time scales in the tropical regions and are potentially predictable on decadal time scales over the ocean in the North Atlantic. For mid-latitude surface air temperature anomalies over land, model trajectories rapidly diverge and there is little sign of any potential predictability on time scales greater than a season or so. For mean sea level pressure anomalies, there is potential predictability on seasonal time scales in the tropics, and for some global scale annual-decadal anomalies, although not those associated with the North Atlantic Oscillation. For precipitation, the only potential for predictability is for seasonal time anomalies associated with the El-Niño Southern Oscillation. For the majority of the highly populated regions of the world, climate predictability on interannual to decadal time scales based in the initial value approach is likely to be severely limited by chaotic error growth. It is found however that there can be cases in which the potential predictability can be higher than average indicating that there is perhaps some utility in making initial value forecasts of climate in those regions which show low predictability on average.     

Multiscale Oscillations of the Global Climate System as Revealed by Wavelet Transform of Observational Data Time Series

Summary  The surface air temperature time series of both hemispheres and the North Atlantic European area as well as the Southern Oscillation (SO) index time series were analysed using a wavelet transform technique. The values of the so-called singularity exponents of these series were estimated and compared with such estimations for some surrogate time series artificially created from the observed temperature series. It was concluded that the climate dynamics on interannual and interdecadal scales may be considered as a kind of classical Brownian motion although its consideration as a flicker-noise is also possible. The extracted temperature variations were shown to be closely coupled with the SO process. The wavelet-transformed SO series reveals itself as a whole self-similar “tree” the main branches of which are the appearances of the strongest El-Ninos of 1898 – 1899, 1941 – 1942, and 1982 – 1983. Similar “trees” can be seen in the wavelet-transformed temperature series. Thus, the extracted temperature variations were shown to be closely coupled with the SO process, and a decomposition of the current global climate dynamics into three climatic epochs (of about 40-year long) seems to be appropriate. Received May 4, 1998 Revised April 25, 1999     

Quantifying the Multivariate ENSO Index (MEI) coupling to CO2 concentration and to the length of day variations

The El Niño Southern Oscillation (ENSO) is the Earth’s strongest climate fluctuation on inter-annual time scales and has global impacts although originating in the tropical Pacific. Many point indices have been developed to describe ENSO but the Multivariate ENSO Index (MEI) is considered as the most representative since it links six different meteorological parameters measured over the tropical Pacific. Extreme values of MEI are correlated to the extreme values of atmospheric CO₂ concentration rate variations and negatively correlated to equivalent scale extreme values of the length of day rate variation. We evaluate a first-order conversion function between MEI and the other two indexes using their annual rate of variation. The quantification of the strength of the coupling herein evaluated provides a quantitative measure to test the accuracy of theoretical model predictions. Our results further confirm the idea that the major local and global Earth–atmosphere system mechanisms are significantly coupled and synchronized to each other at multiple scales.     

Dynamics of the Indian monsoon and ENSO relationships in the SINTEX global coupled model

This paper uses recent gridded climatological data and a coupled general circulation model (GCM) simulation in order to assess the relationships between the interannual variability of the Indian summer monsoon (ISM) and the El Niño-Southern Oscillation (ENSO). The focus is on the dynamics of the ISM-ENSO relationships and the ability of the state-of-the-art coupled GCM to reproduce the complex lead-lag relationships between the ISM and the ENSO. The coupled GCM is successful in reproducing the ISM circulation and rainfall climatology in the Indian areas even though the entire ISM circulation is weaker relative to that observed. In both observations and in the simulation, the ISM rainfall anomalies are significantly associated with fluctuations of the Hadley circulation and the 200 hPa zonal wind anomalies over the Indian Ocean. A quasi-biennial time scale is found to structure the ISM dynamical and rainfall indices in both cases. Moreover, ISM indices have a similar interannual variability in the simulation and observations. The coupled model is less successful in simulating the annual cycle in the tropical Pacific. A major model bias is the eastward displacement of the western North Pacific inter-tropical convergence zone (ITCZ), near the dateline, during northern summer. This introduces a strong semiannual component in Pacific Walker circulation indices and central equatorial Pacific sea surface temperatures. Another weakness of the coupled model is a less-than-adequate simulation of the Southern Oscillation due to an erroneous eastward extension of the Southern Pacific convergence zone (SPCZ) year round. Despite these problems, the coupled model captures some aspects of the interannual variability in the tropical Pacific. ENSO events are phase-locked with the annual cycle as observed, but are of reduced amplitude relative to the observations. Wavelet analysis of the model Niño34 time series shows enhanced power in the 2–4 year band, as compared to the 2–8 year range for observations during the 1950–2000 period. The ISM circulation is weakened during ENSO years in both the simulation and the observations. However, the model fails to reproduce the lead-lag relationship between the ISM and Niño34 sea surface temperatures (SSTs). Furthermore, lag correlations show that the delayed response of the wind stress over the central Pacific to ISM variability is insignificant in the simulation. These features are mainly due to the unrealistic interannual variability simulated by the model in the western North Pacific. The amplitude and even the sign of the simulated surface and upper level wind anomalies in these areas are not consistent with observed patterns during weak/strong ISM years. The ISM and western North Pacific ITCZ fluctuate independently in the observations, while they are negatively and significantly correlated in the simulation. This isolates the Pacific Walker circulation from the ISM forcing. These systematic errors may also contribute to the reduced amplitude of ENSO variability in the coupled simulation. Most of the unrealistic features in simulating the Indo-Pacific interannual variability may be traced back to systematic errors in the base state of the coupled model.     

A conceptual framework for time and space scale interactions in the climate system

 Interactions involving various time and space scales, both within the tropics and between the tropics and midlatitudes, are ubiquitous in the climate system. We propose a conceptual framework for understanding such interactions whereby longer time scales and larger space scales set the base state for processes on shorter time scales and smaller space scales, which in turn have an influence back on the longer time scales and larger space scales in a continuum of process-related interactions. Though not intended to be comprehensive, we do cite examples from the literature to provide evidence for the validity of this framework. Decadal time scale base states of the coupled climate system set the context for the manifestation of interannual time scales (El Nino/Southern Oscillation, ENSO and tropospheric biennial oscillation, TBO) which are influenced by and interact with the annual cycle and seasonal time scales. Those base states in turn influence the large-scale coupled processes involved with intraseasonal and submonthly time scales, tied to interactions within the tropics and extratropics, and tropical–midlatitude teleconnections. All of these set the base state for processes on the synoptic and mesoscale and regional/local space scales. Events at those relatively short time scales and small space scales may then affect the longer time scale and larger space scale processes in turn, reaching back out to submonthly, intraseasonal, seasonal, annual, TBO, ENSO and decadal. Global coupled models can capture some elements of the decadal, ENSO, TBO, annual and seasonal time scales with the associated global space scales. However, coupled models are less successful at simulating phenomena at subseasonal and shorter time scales with hemispheric and smaller space scales. In the context of the proposed conceptual framework, the synergistic interactions of the time and space scales suggest that a high priority must be placed on improved simulations of all of the time and space scales in the climate system. This is particularly important for the subseasonal time scales and hemispheric and smaller space scales, which are not well simulated at present, to improve the prospects of successfully forecasting phenomena beyond the synoptic scales. Received: 3 April 2000/ Accepted: 6 November 2000     

Impacts of shortwave radiation forcing on ENSO: a study with a coupled tropical ocean-atmosphere model

 We describe a coupled tropical ocean-atmosphere model that represents a new class of models that fill the gap between anomaly coupled models and fully coupled general circulation models. Both the atmosphere and ocean are described by two and half layer primitive equation models, which emphasize the physical processes in the oceanic mixed layer and atmospheric boundary layer. Ocean and atmosphere are coupled through both momentum and heat flux exchanges without explicit flux correction. The coupled model, driven by solar radiation, reproduces a realistic annual cycle and El Nino-Southern Oscillation (ENSO). In the presence of annual mean shortwave radiation forcing, the model exhibits an intrinsic mode of ENSO. The oscillation period depends on the mean forcing that determines the coupled mean state. A perpetual April (October) mean forcing prolongs (shortens) the oscillation period through weakening (enhancing) the mean upwelling and mean vertical temperature gradients. The annual cycle of the solar forcing is shown to have fundamental impacts on the behavior of ENSO cycles through establishing a coupled annual cycle that interacts with the ENSO mode. Due to the annual cycle solar forcing, the single spectral peak of the intrinsic ENSO mode becomes a double peak with a quasi-biennial and a low-frequency (4–5 years) component; the evolution of ENSO becomes phase-locked to the annual cycle; and the amplitude and frequency of ENSO become variable on an interdecadal time scale due to interactions of the mean state and the two ENSO components. The western Pacific monsoon (the annual shortwave radiation forcing in the western Pacific) is primarily responsible for the generation of the two ENSO components. The annual march of the eastern Pacific ITCZ tends to lock ENSO phases to the annual cycle. The model's deficiencies, limitations, and future work are also discussed. Received: 15 June 1999 / Accepted: 11 December 1999     

20世纪全球增暖最显著的区域

Having analyzed a global grid temperature anomaly data set and some sea level pressure data during the last century, we found the following facts. Firstly, the annual temperature change with a warming trend of about 0.6℃/100 years in the tropical area over Indian to the western Pacific Oceans was most closely correlated to the global mean change. Therefore, the temperature change in this area might serve as an indicator of global mean change at annual and longer time scales. Secondly, a cooling of about -0.3℃ / 100 years occurred over the northern Atlantic. Thirdly, a two-wave pattern of temperature change, warming over northern Asia and northwestern America and cooling over the northern Atlantic and the northern Pacific, occurred during the last half century linked to strengthening westerlies over the northern Atlantic and the weakening Siberian High. Fourthly, a remarkable seasonal difference occurred over the Eurasian continent, with cooling (warming) in winter (summer) during 1896-1945, and warming (cooling) in winter (summer) during 1946-1995. The corresponding variations of the North Atlantic Oscillation and the Southern Oscillation were also discussed.