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The weak monsoon rainfall simulation in the CMIP6 models calls for further process understanding about the Indian summer monsoon (ISM), especially the intraseasonal variabilities. Here, the remote forcing from the Southern Hemisphere on the Indian summer monsoon is examined. Over the southeastern Indian Ocean (SEIO), intraseasonal warm SST anomalies can induce low-level southeasterly wind anomalies and accelerate the background southeasterly wind. According to the mechanism of Wind-Evaporation-SST (WES) feedback, the wind acceleration gives rise to the positive anomalies of surface latent heat flux (LHF). The intraseasonal wind anomalies propagate equatorward along with the background southeasterlies; the positive LHF increases the moist static energy over the equator. As a result, deep convections are reinforced over tropics, which strengthen the northward-propagating monsoon intraseasonal oscillations. During boreal summer, the northward intraseasonal oscillation prompts enhanced rainfall events over the monsoon region. Current results indicate the inter-hemispheric impacts as an inevitable contributor to the heavy precipitation during ISM in the Northern Hemisphere. In CMIP6, the models with better SST simulations over SEIO can have stronger equatorial rainfall and more realistic northward propagation. The unsatisfactory simulations of CMIP6 are associated with the defective ocean-atmosphere interaction over SEIO, and one clue is the feeble variances of intraseasonal oceanic signals over SEIO, which is far from the observation. This research offers a new perspective on the chronic dry monsoon bias in the Northern Hemisphere; the cross-equatorial process and the bias of intraseasonal oceanic variation over SEIO deserve further attention in the coupled models.

The generation and propagation of internal tides in the Andaman Sea are investigated using a three-dimensional high-resolution numerical model. Three categories of experiments, including driving the model with four main semidiurnal tides (M2, S2, N2, and K2), four main diurnal tides (K1, O1, P1, and Q1), and eight main tides (M2, S2, N2, K2, K1, O1, P1, and Q1), are designed to examine the effects of barotropic tides. The results show that the semidiurnal internal tides are dominant in the Andaman Sea, and the inclusion of diurnal barotropic tides negligibly modulates this result. That is partly due to the strength of the diurnal barotropic tides is generally one order smaller than that of the semidiurnal barotropic tides in this region. The sensitivity experiments put this on a firmer footing. In terms of the internal tidal energy, the experiments driven by the diurnal barotropic tides are three orders and one order smaller than those driven by the semidiurnal barotropic tides, respectively, during the spring and neap tides. In addition, the experiments result in total barotropic-to-baroclinic energy conversion rates over the Andaman Sea 29.15 GW (driven by the eight tides), 29.24 GW (driven by the four semidiurnal tides), and 0.05 GW (driven by the fourdiurnal tides) in the spring tidal period and 3.08 GW, 2.56 GW, and 0.31 GW in the neap tidal period, respectively. Four potential generation regions of internal tides are found, three of which are in the Andaman and Nicobar Islands and one in the northeastern Andaman Sea.

The Seychelles-Chagos Thermocline Ridge (SCTR, 5°S-10°S, 50°E-80°E) is a unique open-ocean upwelling region in the southwestern Indian Ocean. Due to the negative wind stress curl between the equatorial westerlies and southeasterly trade winds, SCTR is known as a strong upwelling region with high biological productivity, providing a primary fishing zone for the surrounding countries. Given its importance in shaping the variability of the Indian Ocean climate by understanding the sea-air interaction and its dynamics, the simulation of SCTR is evaluated using outputs from the Coupled Model Intercomparison Project Phase Sixth (CMIP6). Compared to observations, 23 out of 27 CMIP6 models tend to simulate considerably deeper SCTR thermocline depth (defined as the 20°C isotherm depth (D20))- a common bias in climate models. The deep bias is related to the easterly wind bias in the equatorial to southern Indian Ocean, which is prominent in boreal summer and fall. This easterly wind bias produces a weak annual mean Ekman pumping, especially in the boreal fall. Throughout the year, the observed Ekman pumping is positive and is driven by two components: the curl term, is associated with the wind stress curl, leads to upwelling during boreal summer to fall; the beta term, is linked to planetary beta and zonal wind stress, contributes to downwelling during boreal spring to fall. However, the easterly wind bias in the CMIP6 increases both the positive curl and negative beta terms. The beta term bias offsets the curl term bias and reduces the upwelling velocity. Furthermore, the easterly wind bias is likely caused by the reduced east-west sea surface temperature (SST) difference associated with a pronounced warm bias in the western equatorial Indian Ocean, accompanied by the east-west mean sea level pressure gradient over the Indian Ocean. Furthermore, this study finds local wind-induced Ekman pumping to be a more dominant factor in thermocline depth bias than Rossby waves,

Most climate forecast agencies failed to make successful predictions of the strong 2020/2021 La Niña event before May 2020. The western equatorial Pacific warm water volume (WWV) before the 2020 spring failed to predict this La Niña event because of the near neutral state of the equatorial Pacific Ocean in the year before. A strong Indian Ocean Dipole (IOD) event took place in the fall of 2019, which is used as a precursor for the La Niña prediction in this study. We used observational data to construct the precursory relationship between negative sea level anomalies (SLA) in the southeastern tropical Indian Ocean (SETIO) in boreal fall and negative Niño 3.4 sea surface temperature anomalies index one year later. The application of the above relation to the prediction of the 2020/2021 La Niña was a great success. The dynamics behind are the Indo-Pacific "oceanic channel" connection via the Indian Ocean Kelvin wave propagation through the Indonesian seas, with the atmospheric bridge playing a secondary role. The high predictability of La Niña across the spring barrier if a positive IOD should occur in the previous year suggests that the negative SETIO SLA in fall is a much better and longer predictor for this type of La Niña prediction than the WWV. In comparison, positive SETIO SLA lead either El Niño or La Niña by one year, suggesting uncertainty of El Niño predictions.