scholarly journals ENSO modulation of tropical Indian Ocean subseasonal variability

2016 ◽  
Vol 43 (24) ◽  
pp. 12,634-12,642 ◽  
Author(s):  
Eunsil Jung ◽  
Ben P. Kirtman
Keyword(s):  
Indian Ocean ◽  
Tropical Indian Ocean ◽  
Subseasonal Variability ◽  
Enso Modulation

scholarly journals Observed subseasonal variability of heat flux and the SST response of the tropical Indian Ocean

2016 ◽  
Vol 121 (10) ◽  
pp. 7290-7307 ◽  
Author(s):  
Sindu Raj Parampil ◽  
G. N. Bharathraj ◽  
Matthew Harrison ◽  
Debasis Sengupta
Keyword(s):  
Heat Flux ◽  
Indian Ocean ◽  
Tropical Indian Ocean ◽  
Subseasonal Variability

scholarly journals Tropical modulation of East Asia air pollution

2020 ◽  
Author(s):  
Myung-Il Jung ◽  
Seok-Woo Son ◽  
Hyemi Kim ◽  
Deliang Chen
Keyword(s):  
Air Pollution ◽  
Indian Ocean ◽  
East Asia ◽  
Phase 1 ◽  
Primary Source ◽  
Tropical Indian Ocean ◽  
Tropical Convection ◽  
Pm10 Concentration ◽  
Subseasonal Variability ◽  
The Indian Ocean

Abstract Given the high population density and serious air pollution problems, understanding and predicting air pollution in East Asia are of great importance. Here, we show that the day-to-day variability of East Asia air pollution in winter is remotely controlled by the convection over the tropical Indian Ocean and western Pacific, the so-called Madden–Julian oscillation (MJO), through its extratropical teleconnections. In particular, the concentration of particulate matter with aerodynamic diameter less than 10 micron (PM10) becomes significantly high when the tropical convection is suppressed over the Indian Ocean (MJO phases 5–6). In contrast, PM10 concentration becomes significantly low when the convection is enhanced there (MJO phase 1–2). The station-averaged PM10 difference between the two MJO phases reaches up to 47% of the daily PM10 variability, indicating that the MJO is a primary source of wintertime subseasonal variability of East Asia PM10 concentration. We also show that PM10 anomaly typically lags the tropical convection by one to two weeks. This opens a new window of opportunity for subseasonal PM10 prediction in East Asia.

Vertical distribution of bigeye tuna Thunnus obesus in the tropical Indian Ocean

2013 ◽  
Vol 20 (3) ◽  
pp. 660-671 ◽  
Author(s):  
Xuezhong CHEN ◽  
Shenglong YANG ◽  
Yu Zhang ◽  
Wei FAN ◽  
Yumei WU
Keyword(s):  
Indian Ocean ◽  
Vertical Distribution ◽  
Tropical Indian Ocean ◽  
Bigeye Tuna ◽  
Thunnus Obesus

Interannual variability of the Tropical Indian Ocean mixed layer depth

2012 ◽  
Vol 40 (3-4) ◽  
pp. 743-759 ◽  
Author(s):  
M. G. Keerthi ◽  
M. Lengaigne ◽  
J. Vialard ◽  
C. de Boyer Montégut ◽  
P. M. Muraleedharan
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Tropical Indian Ocean ◽  
Ocean Mixed Layer ◽  
Layer Depth ◽  
Ocean Mixed Layer Depth

Assessment of mass-induced sea level variability in the Tropical Indian Ocean based on GRACE and altimeter observations

2021 ◽  
Vol 95 (2) ◽  
Author(s):  
Shiva Shankar Manche ◽  
Rabindra K. Nayak ◽  
Prakash Chandra Mohanty ◽  
M. V. R. Shesasai ◽  
V. K. Dadhwal
Keyword(s):  
Indian Ocean ◽  
Sea Level ◽  
Tropical Indian Ocean ◽  
Sea Level Variability

scholarly journals Seasonality and Dynamics of Atmospheric Teleconnection from the Tropical Indian Ocean and the Western Pacific to West Antarctica

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 849
Author(s):  
Hyun-Ju Lee ◽  
Emilia-Kyung Jin
Keyword(s):  
Indian Ocean ◽  
Rossby Wave ◽  
Tropical Indian Ocean ◽  
Western Pacific ◽  
Tropical Region ◽  
Formation Mechanisms ◽  
West Antarctica ◽  
Background Flow ◽  
The Impact ◽  
The Western Pacific

The global impact of the tropical Indian Ocean and the Western Pacific (IOWP) is expected to increase in the future because this area has been continuously warming due to global warming; however, the impact of the IOWP forcing on West Antarctica has not been clearly revealed. Recently, ice loss in West Antarctica has been accelerated due to the basal melting of ice shelves. This study examines the characteristics and formation mechanisms of the teleconnection between the IOWP and West Antarctica for each season using the Rossby wave theory. To explicitly understand the role of the background flow in the teleconnection process, we conduct linear baroclinic model (LBM) simulations in which the background flow is initialized differently depending on the season. During JJA/SON, the barotropic Rossby wave generated by the IOWP forcing propagates into the Southern Hemisphere through the climatological northerly wind and arrives in West Antarctica; meanwhile, during DJF/MAM, the wave can hardly penetrate the tropical region. This indicates that during the Austral winter and spring, the IOWP forcing and IOWP-region variabilities such as the Indian Ocean Dipole (IOD) and Indian Ocean Basin (IOB) modes should paid more attention to in order to investigate the ice change in West Antarctica.

scholarly journals Sources of Tropical Subseasonal Skill in the CFSv2

2020 ◽  
Vol 148 (4) ◽  
pp. 1553-1565 ◽  
Author(s):  
Carl J. Schreck ◽  
Matthew A. Janiga ◽  
Stephen Baxter
Keyword(s):  
Indian Ocean ◽  
Low Frequency ◽  
Equatorial Pacific ◽  
Convectively Coupled Equatorial Waves ◽  
Subseasonal Variability ◽  
The Pacific ◽  
Fourier Filtering ◽  
The Indian Ocean ◽  
Rainfall Anomalies ◽  
Combined Data

Abstract This study applies Fourier filtering to a combination of rainfall estimates from TRMM and forecasts from the CFSv2. The combined data are filtered for low-frequency (LF, ≥120 days) variability, the MJO, and convectively coupled equatorial waves. The filtering provides insight into the sources of skill for the CFSv2. The LF filter, which encapsulates persistent anomalies generally corresponding with SSTs, has the largest contribution to forecast skill beyond week 2. Variability within the equatorial Pacific is dominated by its response to ENSO, such that both the unfiltered and the LF-filtered forecasts are skillful over the Pacific through the entire 45-day CFSv2 forecast. In fact, the LF forecasts in that region are more skillful than the unfiltered forecasts or any combination of the filters. Verifying filtered against unfiltered observations shows that subseasonal variability has very little opportunity to contribute to skill over the equatorial Pacific. Any subseasonal variability produced by the model is actually detracting from the skill there. The MJO primarily contributes to CFSv2 skill over the Indian Ocean, particularly during March–May and MJO phases 2–5. However, the model misses opportunities for the MJO to contribute to skill in other regions. Convectively coupled equatorial Rossby waves contribute to skill over the Indian Ocean during December–February and the Atlantic Ocean during September–November. Convectively coupled Kelvin waves show limited potential skill for predicting weekly averaged rainfall anomalies since they explain a relatively small percent of the observed variability.

scholarly journals Intrinsic precursors and timescale of the tropical Indian Ocean Dipole: insights from partially decoupled numerical experiment

2017 ◽  
Vol 51 (4) ◽  
pp. 1311-1332 ◽  
Author(s):  
Julien Crétat ◽  
Pascal Terray ◽  
Sébastien Masson ◽  
K. P. Sooraj
Keyword(s):  
Indian Ocean ◽  
Numerical Experiment ◽  
Indian Ocean Dipole ◽  
Tropical Indian Ocean

Interdecadal variability in the tropical Indian Ocean and its dynamic explanation

1999 ◽  
Vol 44 (17) ◽  
pp. 1620-1627 ◽  
Author(s):  
Dongxiao Wang ◽  
Guoxiong Wu ◽  
Jianjun Xu
Keyword(s):  
Indian Ocean ◽  
Tropical Indian Ocean ◽  
Interdecadal Variability
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