ALBERT

Description: Equatorial Pacific sea surface temperature (SST) anomalies in the Center for Ocean–Land–Atmosphere Studies (COLA) interactive ensemble coupled general circulation model show near-annual variability as well as biennial El Niño–Southern Oscillation (ENSO) variability. There are two types of near-annual modes: a westward propagating mode and a stationary mode. For the westward propagating near-annual mode, warm SST anomalies are generated in the eastern equatorial Pacific in boreal spring and propagate westward in boreal summer. Consistent westward propagation is seen in precipitation, surface wind, and ocean current. For the stationary near-annual mode, warm SST anomalies develop near the date line in boreal winter and decay locally in boreal spring. Westward propagation of warm SST anomalies also appears in the developing year of the biennial ENSO mode. However, warm SST anomalies for the westward propagating near-annual mode occur about two months earlier than those for the biennial ENSO mode and are quickly replaced by cold SST anomalies, whereas warm SST anomalies for the biennial ENSO mode only experience moderate weakening. Anomalous zonal advection contributes to the generation and westward propagation of warm SST anomalies for both the westward propagating near-annual mode and the biennial ENSO mode. However, the role of mean upwelling is markedly different. The mean upwelling term contributes to the generation of warm SST anomalies for the biennial ENSO mode, but is mainly a damping term for the westward propagating near-annual mode. The development of warm SST anomalies for the stationary near-annual mode is partially due to anomalous zonal advection and upwelling, similar to the amplification of warm SST anomalies in the equatorial central Pacific for the biennial ENSO mode. The mean upwelling term is negative in the eastern equatorial Pacific for the stationary near-annual mode, which is opposite to the ENSO mode. The development of cold SST anomalies in the aftermath of warm SST anomalies for the westward propagating near-annual mode is coupled to large easterly wind anomalies, which occur between the warm and cold SST anomalies. The easterly anomalies contribute to the cold SST anomalies through anomalous zonal, meridional, and vertical advection and surface evaporation. The cold SST anomalies, in turn, enhance the easterly anomalies through a Rossby-wave-type response. The above processes are most effective during boreal spring when the mean near-surface-layer ocean temperature gradient is the largest. It is suggested that the westward propagating near-annual mode is related to air–sea interaction processes that are limited to the near-surface layers.

Description: Simulations of regional monsoon regimes, including the Indian, Australian, West African, South American, and North American monsoons, are described for the T85 version of the Community Climate System Model version 3 (CCSM3) and compared to observations and Atmospheric Model Intercomparison Project (AMIP)-type SST-forced simulations with the Community Atmospheric Model version 3 (CAM3) at T42 and T85. There are notable improvements in the regional aspects of the precipitation simulations in going to the higher-resolution T85 compared to T42 where topography is important (e.g., Ethiopian Highlands, South American Andes, and Tibetan Plateau). For the T85 coupled version of CCSM3, systematic SST errors are associated with regional precipitation errors in the monsoon regimes of South America and West Africa, though some aspects of the monsoon simulations, particularly in Asia, improve in the coupled model compared to the SST-forced simulations. There is very little realistic intraseasonal monsoon variability in the CCSM3 consistent with earlier versions of the model. Teleconnections to the tropical Pacific are well simulated for the South Asian monsoon.

Description: The impact of coupled air–sea feedbacks on the simulation of tropical intraseasonal variability is investigated in this study using the National Centers for Environmental Prediction Climate Forecast System. The simulation of tropical intraseasonal variability in a freely coupled simulation is compared with two simulations of the atmospheric component of the model. In one experiment, the uncoupled model is forced with the daily sea surface temperature (SST) from the coupled run. In the other, the uncoupled model is forced with climatological SST from the coupled run. Results indicate that the overall intraseasonal variability of precipitation is reduced in the coupled simulation compared to the uncoupled simulation forced by daily SST. Additionally, air–sea coupling is responsible for differences in the simulation of the tropical intraseasonal oscillation between the coupled and uncoupled models, specifically in terms of organization and propagation in the western Pacific. The differences between the coupled and uncoupled simulations are due to the fact that the relationships between precipitation and SST and latent heat flux and SST are much stronger in the coupled model than in the uncoupled model. Additionally, these relationships are delayed by about 5 days in the uncoupled model compared to the coupled model. As demonstrated by the uncoupled simulation forced with climatological SST, some of the intraseasonal oscillation can be simulated by internal atmospheric dynamics. However, the intraseasonally varying SST appears to be important to the amplitude and propagation of the oscillation beyond the Maritime Continent.

Description: This study investigates whether air–sea interactions contribute to differences in the predictability of the boreal winter tropical intraseasonal oscillation (TISO) using the NCEP operational climate model. A series of coupled and uncoupled, “perfect” model predictability experiments are performed for 10 strong model intraseasonal events. The uncoupled experiments are forced by prescribed SST containing different types of variability. These experiments are specifically designed to be directly comparable to actual forecasts. Predictability estimates are calculated using three metrics, including one that does not require the use of time filtering. The estimates are compared between these experiments to determine the impact of coupled air–sea interactions on the predictability of the tropical intraseasonal oscillation and the sensitivity of the potential predictability estimates to the different SST forcings. Results from all three metrics are surprisingly similar. They indicate that predictability estimates are longest for precipitation and outgoing longwave radiation (OLR) when the ensemble mean from the coupled model is used. Most importantly, the experiments that contain intraseasonally varying SST consistently predict the control events better than those that do not for precipitation, OLR, 200-hPa zonal wind, and 850-hPa zonal wind after the first 10 days. The uncoupled model is able to predict the TISO with similar skill to that of the coupled model, provided that an SST forecast that includes these intraseasonal variations is used to force the model. This indicates that the intraseasonally varying SSTs are a key factor for increased predictability and presumably better prediction of the TISO.

Description: Decadal variations in the amplitude of El Niño and the Southern Oscillation have been the subject of great interest in the literature for the past decade. One theory suggests that ENSO is best described as a stable system driven by linear dynamics and that stochastic atmospheric forcing is responsible for the development and modulation of ENSO on interannual as well as decadal time scales. Another theory suggests that ENSO is driven by strong nonlinear coupled feedbacks between the ocean and atmosphere and low frequency changes in ENSO amplitude are driven by decadal changes in the tropical Pacific mean state. Unfortunately, the observed record is too short to collect reliable statistics for such low frequency behavior. A hybrid coupled model composed of a simple statistical atmosphere coupled to the Poseidon isopycnal ocean model has been developed for the study of ENSO decadal variability. The model simulates realistic ENSO variability on interannual and decadal time scales with negligible climate drift over 1000 years. Through analysis and experimentation the authors show that low frequency changes in the atmospheric “weather noise” drive changes in the tropical Pacific mean state leading to changes in the amplitude of ENSO on decadal time scales. Additional model simulations suggest that, while predictability is limited by the presence of atmospheric noise, there are extended periods when the coupled instability, strengthened by changes in the mean state, is insensitive to noise on interannual time scales. The relationship between decadal modulation of ENSO and mean state changes resides somewhere between the linear damped stochastically forced theory and the strongly unstable theory. Unlike the strongly unstable system, changes in ENSO amplitude on longer time scales are determined by the stochastic forcing. The stochastic forcing is not necessary in this model to sustain ENSO; however, its presence is crucial for low frequency changes in the mean state of the tropical Pacific. The strong relationship between the mean state and ENSO amplitude modulation in the model is in opposition to the linear damped stochastically forced theory. The fact that changes in the tropical Pacific mean state lead directly to changes in ENSO amplitude and predictability has positive implications for predictability.

Description: The present study documents the influence of El Niño and La Niña events on the spread and predictability of rainfall, surface pressure, and 500-hPa geopotential height, and contrasts the relative contribution of signal and noise changes to the predictability change based on a long-term integration of an interactive ensemble coupled general circulation model. It is found that the pattern of the El Niño–Southern Oscillation (ENSO)-induced noise change for rainfall follows closely that of the corresponding signal change in most of the tropical regions. The noise for tropical Pacific surface pressure is larger (smaller) in regions of lower (higher) mean pressure. The ENSO-induced noise change for 500-hPa height displays smaller spatial scales compared to and has no systematic relationship with the signal change. The predictability for tropical rainfall and surface pressure displays obvious contrasts between the summer and winter over the Bay of Bengal, the western North Pacific, and the tropical southwestern Indian Ocean. The predictability for tropical 500-hPa height is higher in boreal summer than in boreal winter. In the equatorial central Pacific, the predictability for rainfall is much higher in La Niña years than in El Niño years. This occurs because of a larger percent reduction in the amplitude of noise compared to the percent decrease in the magnitude of signal from El Niño to La Niña years. A consistent change is seen in the predictability for surface pressure near the date line. In the western North and South Pacific, the predictability for boreal winter rainfall is higher in El Niño years than in La Niña years. This is mainly due to a stronger signal in El Niño years compared to La Niña years. The predictability for 500-hPa height increases over most of the Tropics in El Niño years. Over western tropical Pacific–Australia and East Asia, the predictability for boreal winter surface pressure and 500-hPa height is higher in El Niño years than in La Niña years. The predictability change for 500-hPa height is primarily due to the signal change.

Description: The biennial variability is a large component of year-to-year variations in the Indian summer monsoon (ISM). Previous studies have shown that El Niño–Southern Oscillation (ENSO) plays an important role in the biennial variability of the ISM. The present study investigates the role of the Indian Ocean in the biennial transition of the ISM when the Pacific ENSO is absent. The influence of the Indian and Pacific Oceans on the biennial transition between the ISM and the Australian summer monsoon (ASM) is also examined. Controlled numerical experiments with a coupled general circulation model (CGCM) are used to address the above two issues. The CGCM captures the in-phase ISM to ASM transition (i.e., a wet ISM followed by a wet ASM or a dry ISM followed by a dry ASM) and the out-of-phase ASM to ISM transition (i.e., a wet ASM followed by a dry ISM or a dry ASM followed by a wet ISM). These transitions are more frequent than the out-of-phase ISM to ASM transition and the in-phase ASM to ISM transition in the coupled model, consistent with observations. The results of controlled coupled model experiments indicate that both the Indian and Pacific Ocean air–sea coupling are important for properly simulating the biennial transition between the ISM and ASM in the CGCM. The biennial transition of the ISM can occur through local air–sea interactions in the north Indian Ocean when the Pacific ENSO is suppressed. The local sea surface temperature (SST) anomalies induce the Indian monsoon transition through low-level moisture convergence. Surface evaporation anomalies, which are largely controlled by surface wind speed changes, play an important role for SST changes. Different from local air–sea interaction mechanisms proposed in previous studies, the atmospheric feedback is not strong enough to reverse the SST anomalies immediately at the end of the monsoon season. Instead, the reversal of the SST anomalies is accomplished in the spring of the following year, which in turn leads to the Indian monsoon transition.