Reinitiation of the Boreal Summer Intraseasonal Oscillation in the Tropical Indian Ocean*

2005 ◽  
Vol 18 (18) ◽  
pp. 3777-3795 ◽  
Author(s):  
Xian-An Jiang ◽  
Tim Li
Keyword(s):  
Indian Ocean ◽  
General Circulation ◽  
Intraseasonal Oscillation ◽  
Circulation Model ◽  
Equatorial Indian Ocean ◽  
Specific Humidity ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Boreal Summer Intraseasonal Oscillation ◽  
Temperature Advection

Abstract The characteristic features of the boreal summer intraseasonal oscillation (BSISO) during its reinitiation period are studied using NCEP–NCAR reanalysis. Based on these observations and with the aid of an anomalous atmospheric general circulation model (AGCM), a possible mechanism responsible for the BSISO reinitiation is elucidated. The western equatorial Indian Ocean along the eastern African coast tends to be a key region for the phase transition of the BSISO from an enhanced to suppressed convective phase, or vise versa. The major precursory feature associated with reinitiation of suppressed convection is found in the divergence and reduced specific humidity in the boundary layer. Numerical experiments indicate that the low-level divergence is caused by the cold horizontal temperature advection and associated adiabatic warming (descending motion) in situ. The summer mean state is found to be important for the cold horizontal temperature advection through the modulation of a Gill-type response to an intraseasonal oscillation (ISO) heating in the eastern equatorial Indian Ocean. The results in this study suggest a self-sustained paradigm in the Indian Ocean for the BSISO; that is, the BSISO could be a basinwide phenomenon instead of a global circumstance system as hypothesized for the boreal winter ISO (i.e., the Madden–Julian oscillation).

scholarly journals Boreal summer intraseasonal oscillation in a superparameterized general circulation model: effects of air–sea coupling and ocean mean state

2020 ◽  
Vol 13 (11) ◽  
pp. 5191-5209
Author(s):  
Yingxia Gao ◽  
Nicholas P. Klingaman ◽  
Charlotte A. DeMott ◽  
Pang-Chi Hsu
Keyword(s):  
General Circulation ◽  
Intraseasonal Oscillation ◽  
Phase Relationship ◽  
Circulation Model ◽  
Atmospheric Model ◽  
Boreal Summer ◽  
Coupled Models ◽  
Boreal Summer Intraseasonal Oscillation ◽  
Taylor Diagram ◽  
Mean State

Abstract. The effect of air–sea coupling on simulated boreal summer intraseasonal oscillation (BSISO) is examined using atmosphere–ocean-mixed-layer coupled (SPCAM3-KPP, referred to as SPK throughout) and uncoupled configurations of the superparameterized (SP) Community Atmospheric Model, version 3 (SPCAM3, referred to as SPA throughout). The coupled configuration is constrained to either observed ocean mean state or the mean state from the SP coupled configuration with a dynamic ocean (SPCCSM3), to understand the effect of mean-state biases on the BSISO. All configurations overestimate summer mean subtropical rainfall and its intraseasonal variance. All configurations simulate realistic BSISO northward propagation over the Indian Ocean and western Pacific, in common with other SP configurations. Prescribing the 31 d smoothed sea surface temperature (SST) from the SPK simulation in SPA worsens the overestimated BSISO variance. In both coupled models, the phase relationship between intraseasonal rainfall and SST is well captured. This suggests that air–sea coupling improves the amplitude of simulated BSISO and contributes to the propagation of convection. Constraining SPK to the SPCCSM3 mean state also reduces the overestimated BSISO variability but weakens BSISO propagation. Using the SPCCSM3 mean state also introduces a 1-month delay to the BSISO seasonal cycle compared to SPK with the observed ocean mean state, which matches well with observation. Based on a Taylor diagram, both air–sea coupling and SPCCSM3 mean-state SST biases generally lead to higher simulated BSISO fidelity, largely due to their abilities to suppress the overestimated subtropical BSISO variance.

scholarly journals Dominant Interannual Covariations of the East Asian–Australian Land Precipitation during Boreal Winter

2019 ◽  
Vol 32 (11) ◽  
pp. 3279-3296 ◽  
Author(s):  
Lin Liu ◽  
Jianping Guo ◽  
Wen Chen ◽  
Renguang Wu ◽  
Lin Wang ◽  
...  
Keyword(s):  
Indian Ocean ◽  
General Circulation ◽  
Southern Oscillation ◽  
East Asian ◽  
Circulation Model ◽  
Boreal Winter ◽  
Dipole Structure ◽  
Second Mode ◽  
Precipitation Anomalies ◽  
Sst Anomalies

AbstractThe present study applies the empirical orthogonal function (EOF) method to investigate the interannual covariations of East Asian–Australian land precipitation (EAALP) during boreal winter based on observational and reanalysis datasets. The first mode of EAALP variations is characterized by opposite-sign anomalies between East Asia (EA) and Australia (AUS). The second mode features an anomaly pattern over EA similar to the first mode, but with a southwest–northeast dipole structure over AUS. El Niño–Southern Oscillation (ENSO) is found to be a primary factor in modulating the interannual variations of land precipitation over EA and western AUS. By comparison, the Indian Ocean subtropical dipole mode (IOSD) plays an important role in the formation of precipitation anomalies over northeastern AUS, mainly through a zonal vertical circulation spanning from the southern Indian Ocean (SIO) to northern AUS. In addition, the ENSO-independent cold sea surface temperature (SST) anomalies in the western North Pacific (WNP) impact the formation of the second mode. Using the atmospheric general circulation model ECHAM5, three 40-yr numerical simulation experiments differing in specified SST forcings verify the impacts of the IOSD and WNP SST anomalies. Further composite analyses indicate that the dominant patterns of EAALP variability are largely determined by the out-of-phase and in-phase combinations of ENSO and IOSD. These results suggest that in addition to ENSO, IOSD should be considered as another crucial factor influencing the EAALP variability during the boreal winter, which has large implications for improved prediction of EAALP land precipitation on the interannual time scale.

scholarly journals Impacts of atmospheric and oceanic initial conditions on boreal summer intraseasonal oscillation forecast in the BCC model

2020 ◽  
Vol 142 (1-2) ◽  
pp. 393-406
Author(s):  
Zhongkai Bo ◽  
Xiangwen Liu ◽  
Weizong Gu ◽  
Anning Huang ◽  
Yongjie Fang ◽  
...  
Keyword(s):  
Indian Ocean ◽  
North Pacific ◽  
Western North Pacific ◽  
Initial Conditions ◽  
Intraseasonal Oscillation ◽  
Tropical Indian Ocean ◽  
Boreal Summer ◽  
Model Errors ◽  
Maritime Continent ◽  
Boreal Summer Intraseasonal Oscillation

Abstract In this paper, we evaluate the capability of the Beijing Climate Center Climate System Model (BCC-CSM) in simulating and forecasting the boreal summer intraseasonal oscillation (BSISO), using its simulation and sub-seasonal to seasonal (S2S) hindcast results. Results show that the model can generally simulate the spatial structure of the BSISO, but give relatively weaker strength, shorter period, and faster transition of BSISO phases when compared with the observations. This partially limits the model’s capability in forecasting the BSISO, with a useful skill of only 9 days. Two sets of hindcast experiments with improved atmospheric and atmosphere/ocean initial conditions (referred to as EXP1 and EXP2, respectively) are conducted to improve the BSISO forecast. The BSISO forecast skill is increased by 2 days with the optimization of atmospheric initial conditions only (EXP1), and is further increased by 1 day with the optimization of both atmospheric and oceanic initial conditions (EXP2). These changes lead to a final skill of 12 days, which is comparable to the skills of most models participated in the S2S Prediction Project. In EXP1 and EXP2, the BSISO forecast skills are improved for most initial phases, especially phases 1 and 2, denoting a better description for BSISO propagation from the tropical Indian Ocean to the western North Pacific. However, the skill is considerably low and insensitive to initial conditions for initial phase 6 and target phase 3, corresponding to the BSISO convection’s active-to-break transition over the western North Pacific and BSISO convection’s break-to-active transition over the tropical Indian Ocean and Maritime Continent. This prediction barrier also exists in many forecast models of the S2S Prediction Project. Our hindcast experiments with different initial conditions indicate that the remarkable model errors over the Maritime Continent and subtropical western North Pacific may largely account for the prediction barrier.

Precursor Signals and Processes Associated with MJO Initiation over the Tropical Indian Ocean*

2013 ◽  
Vol 26 (1) ◽  
pp. 291-307 ◽  
Author(s):  
Chongbo Zhao ◽  
Tim Li ◽  
Tianjun Zhou
Keyword(s):  
Indian Ocean ◽  
Rossby Wave ◽  
Lower Troposphere ◽  
Equatorial Indian Ocean ◽  
Specific Humidity ◽  
Boreal Winter ◽  
Mean Flow ◽  
Wave Response ◽  
The Mean ◽  
Convection Initiation

Abstract The precursor signals of convection initiation associated with the Madden–Julian oscillation (MJO) in boreal winter were investigated through the diagnosis of the 40-yr ECMWF Re-Analysis (ERA-40) data for the period 1982–2001. The western equatorial Indian Ocean (WIO) is a key region of the MJO initiation. A marked increase of specific humidity and temperature in the lower troposphere appears 5–10 days prior to the convection initiation. The increased moisture and temperature cause a convectively more unstable stratification, leading to the onset of convection. A diagnosis of lower-tropospheric moisture (heat) budgets shows that the moisture (temperature) increase is caused primarily by the horizontal advection of the mean specific humidity (temperature) by the MJO flow. The anomalous flow is primarily determined by the downstream Rossby wave response to a preceding suppressed-phase MJO over the eastern Indian Ocean, whereas the upstream Kelvin wave response to the previous eastward-propagating convective-phase MJO is not critical. An idealized numerical experiment further supports this claim. The Southern Hemisphere (SH) midlatitude Rossby wave train and associated wave activity flux prior to the MJO initiation were diagnosed. It is found that SH midlatitude Rossby waves may contribute to MJO initiation over the western Indian Ocean through wave energy accumulation. Idealized numerical experiments confirm that SH midlatitude perturbations play an important role in affecting the MJO variance in the tropics. A barotropic energy conversion diagnosis indicates that there is continuous energy transfer from the mean flow to intraseasonal disturbances over the initiation region, which may help trigger MJO development.

The representation of the boreal summer intraseasonal oscillation in a global convection-permitting simulation

2021 ◽  
Author(s):  
Peter Willetts ◽  
Jennifer Fletcher ◽  
John Marsham
Keyword(s):  
Time Series ◽  
Spatial Scales ◽  
Rainfall Variability ◽  
Intraseasonal Oscillation ◽  
Equatorial Indian Ocean ◽  
Principal Component ◽  
Boreal Summer ◽  
Boreal Summer Intraseasonal Oscillation ◽  
Spatial And Temporal Scales ◽  
Major Mode

<p>The Boreal Summer Intraseasonal Oscillation (BSISO) is a major mode of intraseasonal variability in the Indian summer monsoon. The characteristic pattern includes northward/north-eastward propagating anomalies of convection and circulation over the Indian longitudes, and concurrent eastward propagating anomalies that move through the tropics from the equatorial Indian ocean. In the Indian monsoon region, the BSISO interacts with other processes to affect the rainfall variability on a range of spatial and temporal scales. Convection-permitting simulations are known to improve the representation of some of these smaller-scale processes, but until recently, it has not been feasible to use convection-permitting simulations to model the entire BSISO because of the temporal and spatial scales on which it occurs. Here we assess how well a global multi-year convection-permitting simulation with a coarse grid-spacing of ~10km at the equator models the BSISO. Using Empirical Orthogonal Function (EOF) analysis, we show that overall, the convection-permitting simulation does not give a substantially better representation of the BSISO, when compared with a simulation which parametrises convection. In the observations, the first two EOF eigenvectors and their Principal Component (PC) time series describe the BSISO. The characteristic northwest-to-southeast slope of the observed EOF 1 and 2 patterns is not captured in the parametrised simulation but is better captured in the convection-permitting simulation. However, the convection-permitting simulation does not capture the observed relationship between the PC1 and PC2 time series that describe the strength and phase of the BSISO. The observed pattern is of a fairly constant phase difference between the PC1 and PC2 time series, but in the convection-permitting simulation, there are periods of both negative and positive phase differences. Our results demonstrate that the BSISO is very sensitive to the representation of convection and future higher resolution runs will provide useful routes for understanding scale interactions in the BSISO.</p>

scholarly journals Bomb 14C in the Indian Ocean Measured by Accelerator Mass Spectrometry: Oceanographic Implications

Radiocarbon ◽  
1989 ◽  
Vol 31 (03) ◽  
pp. 510-522 ◽  
Author(s):  
Edouard Bard ◽  
Maurice Arnold ◽  
J R Toggweiler ◽  
Pierre Maurice ◽  
Jean-Claude Duplessy
Keyword(s):  
Mass Spectrometry ◽  
Indian Ocean ◽  
General Circulation ◽  
Circulation Model ◽  
Equatorial Indian Ocean ◽  
Equatorial Zone ◽  
Mode Water ◽  
Indonesian Archipelago ◽  
The Pacific ◽  
The Indian Ocean

AMS 14C measurements on samples collected in the tropical-equatorial Indian Ocean during the INDIGO program (leg II, 1986) are presented and compared with β-counting results obtained under both INDIGO program and GEOSECS expedition in the Indian Ocean (1978). The most significant observation is a doubling of the bomb-14C inventory and mean penetration depth in the equatorial zone. Based on hydrologic considerations, two hypotheses can be proposed: 1) direct influx of Pacific mid-latitude waters through the Indonesian archipelago and 2) advection and/or mixing with Mode Water from the southern gyre of the Indian Ocean. Results obtained with a general circulation model of the ocean suggest that the influx from the Pacific is important in the upper 300m and that below 500m the bomb-14C budget is dominated by Mode Water advection.

scholarly journals Air, Sea, and Land Interactions of the Continental U.S. Hydroclimate

2009 ◽  
Vol 10 (2) ◽  
pp. 353-373 ◽  
Author(s):  
Vasubandhu Misra ◽  
P. A. Dirmeyer
Keyword(s):  
United States ◽  
General Circulation Model ◽  
General Circulation ◽  
Winter Season ◽  
Circulation Model ◽  
Moisture Flux ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Moisture Flux Convergence ◽  
The Mean

Abstract Multidecadal simulations over the continental United States by an atmospheric general circulation model coupled to an ocean general circulation model is compared with that forced by observed sea surface temperature (SST). The differences in the mean and the variability of precipitation are found to be larger in the boreal summer than in the winter. This is because the mean SST differences in the two simulations are qualitatively comparable between the two seasons. The analysis shows that, in the boreal summer season, differences in moisture flux convergence resulting from changes in the circulation between the two simulations initiate and sustain changes in precipitation between them. This difference in precipitation is, however, further augmented by the contributions from land surface evaporation, resulting in larger differences of precipitation between the two simulations. However, in the boreal winter season, despite differences in the moisture flux convergence between the two model integrations, the precipitation differences over the continental United States are insignificant. It is also shown that land–atmosphere feedback is comparatively much weaker in the boreal winter season.

scholarly journals Simulated Sea Surface Salinity Variability in the Tropical Indian Ocean

2010 ◽  
Vol 23 (24) ◽  
pp. 6542-6554 ◽  
Author(s):  
Rashmi Sharma ◽  
Neeraj Agarwal ◽  
Imran M. Momin ◽  
Sujit Basu ◽  
Vijay K. Agarwal
Keyword(s):  
Indian Ocean ◽  
Time Scales ◽  
General Circulation ◽  
Circulation Model ◽  
Equatorial Indian Ocean ◽  
Tropical Indian Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Salinity Variability

Abstract A long-period (15 yr) simulation of sea surface salinity (SSS) obtained from a hindcast run of an ocean general circulation model (OGCM) forced by the NCEP–NCAR daily reanalysis product is analyzed in the tropical Indian Ocean (TIO). The objective of the study is twofold: assess the capability of the model to provide realistic simulations of SSS and characterize the SSS variability in view of upcoming satellite salinity missions. Model fields are evaluated in terms of mean, standard deviation, and characteristic temporal scales of SSS variability. Results show that the standard deviations range from 0.2 to 1.5 psu, with larger values in regions with strong seasonal transitions of surface currents (south of India) and along the coast in the Bay of Bengal (strong Kelvin-wave-induced currents). Comparison of simulated SSS with collocated SSS measurements from the National Oceanographic Data Center and Argo floats resulted in a high correlation of 0.85 and a root-mean-square error (RMSE) of 0.4 psu. The correlations are quite high (>0.75) up to a depth of 300 m. Daily simulations of SSS compare well with a Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction (RAMA) buoy in the eastern equatorial Indian Ocean (1.5°S, 90°E) with an RMSE of 0.3 psu and a correlation better than 0.6. Model SSS compares well with observations at all time scales (intraseasonal, seasonal, and interannual). The decorrelation scales computed from model and buoy SSS suggest that the proposed 10-day sampling of future salinity sensors would be able to resolve much of the salinity variability at time scales longer than intraseasonal. This inference is significant in view of satellite salinity sensors, such as Soil Moisture and Ocean Salinity (SMOS) and Aquarius.

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