Model Mean State Research Articles

On the dependence of ENSO simulation on the coupled model mean state

Systematic model error remains a difficult problem for seasonal forecasting and climate predictions. An error in the mean state could affect the variability of the system. In this paper, we investigate the impact of the mean state on the properties of ENSO. A set of coupled decadal integrations have been conducted, where the mean state and its seasonal cycle have been modified by applying flux correction to the momentum-flux and a combination of heat and momentum fluxes. It is shown that correcting the mean state and the seasonal cycle improves the amplitude of SST inter-annual variability and also the penetration of the ENSO signal into the troposphere and the spatial distribution of the ENSO teleconnections are improved. An analysis of a multivariate PDF of ENSO shows clearly that the flux correction affects the mean, variance, skewness and tails of the distribution. The changes in the tails of the distribution are particularly noticeable in the case of precipitation, showing that without the flux correction the model is unable to reproduce the frequency of large events. For the inter-annual variability the momentum-flux correction alone has a large impact, while the additional heat-flux correction is important for the teleconnections. These results suggest that the current forecasts practices of removing the forecast bias a-posteriori or anomaly initialisation are by no means optimal, since they can not deal with the strong nonlinear interactions. A consequence of the results presented here is that the predictability on annual time-ranges could be higher than currently achieved. Whether or not the correction of the model mean state by some sort of flux correction leads to better forecasts needs to be addressed. In any case, flux correction may be a powerful tool for diagnosing coupled model errors and predictability studies.

The East Asia-western North Pacific boreal summer intraseasonal oscillation simulated in GAMIL 1.1.1

We evaluate the performance of GAMIL1.1.1 in a 27-year forced simulation of the summer intraseasonal oscillation (ISO) over East Asia (EA)-western North Pacific (WNP). The assessment is based on two measures: climatological ISO (CISO) and transient ISO (TISO). CISO is the ISO component that is phase-locked to the annual cycle and describes seasonal march. TISO is the ISO component that varies year by year. The model reasonably captures many observed features of the ISO, including the stepwise northward advance of the rain belt of CISO, the dominant periodicities of TISO in both the South China Sea-Philippine Sea (SCS-PS) and the Yangtze River Basin (YRB), the northward propagation of 30–50-day TISO and the westward propagation of the 12–25-day TISO mode over the SCS-PS, and the zonal propagating features of three major TISO modes over the YRB. However, the model has notable deficiencies. These include the early onset of the South China Sea monsoon associated with CISO, too fast northward propagation of CISO from 20°N to 40°N and the absence of the CISO signal south of 10°N, the deficient eastward propagation of the 30–50-day TISO mode and the absence of a southward propagation in the YRB TISO modes. The authors found that the deficiencies in the ISO simulation are closely related to the model’s biases in the mean states, suggesting that the improvement of the model mean state is crucial for realistic simulation of the intraseasonal variation.

Vertical structure variability in a seasonal simulation of a medium-resolution regional model of the Eastern South Pacific

A seasonal simulation from a medium-resolution ocean general circulation mode (OGCM) is used to investigate the vertical structure variability of the Southeast Pacific (SEP). The focus is on the extra-tropical Rossby wave (ETRW) variability and associated forcing mechanism. Some aspects of the model mean state are validated from available observations, which justifies a vertical mode decomposition of the model variability. The analysis of the baroclinic mode contributions to sea level indicates that the gravest mode is dominant over most of the domain at all frequencies. Annual variability is on average twice as large as the semi-annual variability which is confined near the coast for all the modes. The first baroclinic mode contribution to the annual cycle exhibits a clear westward propagation north of the critical latitude. The higher-order modes only contribute near the coast where they are associated with vertically propagating energy. The residual variability, which is the energy at all timescales other than annual and semi-annual periods peaks offshore between ∼20°S and ∼30°S for all baroclinic modes. The third baroclinic mode also exhibits a relative maximum variability off the coast of Peru south of the critical latitude of the annual cycle (∼13°S), where the Peru–Chile Undercurrent is the most intense. Sensitivity experiments to the atmospheric and boundary forcing suggest that the residual variability results from the non-linear interaction between annual Rossby waves and the mean flow, while the annual ETRWs in the model result from the summed-contribution from both the local wind stress and remote equatorial forcing. Overall the study extends the classical analysis of sea level variability in the SEP based on linear theory, and suggests that the peculiarities of the baroclinic modes need to be taken into account for interpreting the sea level variability and understanding its connection with the equatorial variability.

Atmospheric simulations using a GCM with simplified physical parametrizations. I: model climatology and variability in multi-decadal experiments

This work describes the formulation and climatology of an atmospheric general circulation model (GCM) of intermediate complexity, based on a spectral primitive-equation dynamical core and a set of simplified physical parametrization schemes. The parametrization package has been specially designed to work in models with just a few vertical levels, and is based on the same physical principles adopted in the schemes of state-of-the art GCMs. The parametrized processes include large-scale condensation, convection, clouds, short-wave and long-wave radiation, surface fluxes and vertical diffusion. In the current configuration, the model (nicknamed SPEEDY, from Simplified Parametrizations, primitivE-Equation DYnamics") has five vertical levels and a spectral truncation at total wave number 30 (T30L5). The top vertical level (crudely) represents the stratosphere, the bottom one the planetary boundary layer. Computationally, SPEEDY requires (at least) one order of magnitude less CPU time than a state-of-the-art GCM at the same horizontal resolution, and is therefore suitable for studies of inter-decadal or inter-centennial variability. Statistics of the model mean state and variability are computed from an ensemble of 41-year simulations forced by observed sea-surface temperatures in the period 1952–1992. The model mean state is closer to the observed climatology during the (boreal) winter than during summer. In winter (i.e. December to February, DJF), the model underestimates the amplitude of the Northern Hemisphere stationary wave pattern, particularly in the European-Atlantic sector. Some aspects of the systematic error of SPEEDY are in fact typical of many GCMs, although the error amplitude is stronger than in state-of-the-art models. On the other hand, the global distribution of precipitation in DJF is quite realistic, and compares well with that of more complex GCMs. In summer (June to August), a strong negative bias in the mid-tropospheric temperature generates a Northern Hemisphere circulation with some springtime characteristics. In particular, the position of the Tropical Convergence Zone in the Indian Ocean remains too far south, leading to a deficient simulation of the monsoon circulation over South Asia. The simulated variability during the northern winter is reasonably realistic as far as the spatial distribution is concerned, although some underestimation in the intensity can be found, particularly in the low-frequency range and in the Atlantic sector. The atmospheric response to ENSO events is also weaker than observed, although the spatial patterns of the rainfall and geopotential response in the Pacific sector are in phase with their observed counterparts. In the Atlantic/Eurasian region, the spatial patterns associated with the interdecadal trends in the simulated and observed large-scale circulation show a clear positive correlation, consistent with the hypothesis of a positive ocean–atmosphere feedback on decadal time scales.

Oceanic Forcing of the Wintertime Low-Frequency Atmospheric Variability in the North Atlantic European Sector: A Study with the ARPEGE Model

Abstract The relationship between global sea surface temperatures (SSTs) and the North Atlantic–Europe (NAE) atmospheric circulation is investigated using an ensemble of eight simulations with the ARPEGE atmospheric global circulation model forced with prescribed SSTs over the 1948–97 period. The model mean state is first validated against NCEP reanalyses. The interannual SST-forced variability is then compared to the internal one using analysis of variance (ANOVA) techniques. Both components are maximum in winter over the Northern Hemisphere and the associated potential predictability shows weak but significant values located over the Icelandic low (IL) and the Azores high (AH). The North Atlantic oscillation (NAO) is found to be the leading internal variability mode over the NAE sector as shown by principal component analysis of a control simulation with climatological SSTs. The noise imprint dominates the forced response estimated from the ensemble mean. The latter is related first to the El Nino–South...

The tropical intraseasonal oscillation in a coupled ocean‐atmosphere general circulation model

In this study we report the simulation of the intraseasonal oscillation of the tropical atmosphere (TIO) in the coupled model GIOTTO. The model produces a zonal wave number one eastward propagating disturbance with a mean period of 42 days, which is in good agreement with the observed TIO periodicity. The simulated TIO, however, seems to be influenced by errors in the model mean state. In particular, the errors in the sea surface temperature of the tropical Pacific appear to have a significant impact on the oscillation, affecting its spatial distribution and producing an excess of TIO activity over the eastern Pacific. Despite of these shortcomings, the model seems to be able to reproduce some of the air‐sea interaction mechanisms which characterize the observed TIO.

Interannual Climate Simulation and Predictability in a Coupled TOGA GCM

Abstract A Pacific Ocean–global atmosphere general circulation model is used to simulate the climatic mean state and variability in the Tropics, up to interannual timescales. For this model no long-term trend in climate occurs, but there are systematic differences between the model mean state and observations: in particular, the east equatorial Pacific sea surface temperature is too high by several degrees. Along the equator the seasonal variability in sea surface temperature is good although some features of the seasonal cycle are unrealistic: for example, the east Pacific convergence zone crosses the equator twice a year, residing in the summer hemisphere. Despite some deficiencies in the simulation of the mean state, there is substantial interannual variability, with irregular oscillations dominated by a 2-yr cycle. A principal oscillation pattern analysis shows that the interannual anomalies are typically generated in the west Pacific and move eastward along the equator, with closely connected oceanic...