Deep learning to estimate ocean subsurface salinity structure in the Indian Ocean using satellite observations

Accurately estimating the ocean subsurface salinity structure(OSSS)is crucial for understanding ocean dynamics and predicting climate variations.We present a convolutional neural network(CNN)model to estimate the OSSS in the Indian Ocean using satellite data and Argo observations.We evaluated the performance of the CNN model in terms of its vertical and spatial distribution,as well as seasonal variation of OSSS estimation.Results demonstrate that the CNN model accurately estimates the most significant salinity features in the Indian Ocean using sea surface data with no significant differences from Argo-derived OSSS.However,the estimation accuracy of the CNN model varies with depth,with the most challenging depth being approximately 70 m,corresponding to the halocline layer.Validations of the CNN model’s accuracy in estimating OSSS in the Indian Ocean are also conducted by comparing Argo observations and CNN model estimations along two selected sections and four selected boxes.The results show that the CNN model effectively captures the seasonal variability of salinity,demonstrating its high performance in salinity estimation using sea surface data.Our analysis reveals that sea surface salinity has the strongest correlation with OSSS in shallow layers,while sea surface height anomaly plays a more significant role in deeper layers.These preliminary results provide valuable insights into the feasibility of estimating OSSS using satellite observations and have implications for studying upper ocean dynamics using machine learning techniques.

Distribution and influencing factors of microeukaryote in different water layers of the southwestern Indian Ocean Ridge

Microeukaryotes play a vital role in shaping marine ecosystems,especially in marine productivity,the microbial food web,and carbon cycle.The Indian Ocean is one of the largest oligotrophic areas in the world,but little is known about the biodiversity of microeukaryotes in the area.The community composition and geographical distribution of microeukaryotes collected from the surface(SUR)and deep chlorophyll maximum(DCM)layers in the southwestern Indian Ocean were studied using high-throughput sequencing of the 18S rRNA gene.The metagenomic data helped quantify the impact of environmental factors on microeukaryotic communities.The relative abundance of different taxa groups exhibited distinct patterns between SUR and DCM layers,except for the most dominant Dinoflagellata that accounted for more than 40.6%abundance in each sample.Radiolaria was much more abundant in the nutrient-rich DCM layer than the SUR layer.The community similarity of microeukaryotes decreased with increasing of geographic distance,whereas the temperature and inorganic nitrogen were the most important environmental parameters to community structure.Abundant communities were more influenced by dispersal limitations and rare communities were more responsive to environmental factors.Correlation network analyses revealed strong biotic interactions indicative of parasitism,predation and competition,and their contribution to microeukaryotic population in diverse environments.Overall,this study provided insights into the biodiversity of microeukaryotes by characterizing the differences between water layers and identifying the driving factors in the ocean.

Environmental characteristics of trace metals in seawater from the Ninety East Ridge in the Indian Ocean

The Ninety East Ridge in the Indian Ocean has complex and unique characteristics.The concentrations and distribution characteristics of 10 trace metals(V,Cr,Mn,Fe,Co,Ni,Cu,Cd,Pb,and U)in seawater from the Ninety East Ridge in the Indian Ocean were investigated.Results show that the average concentrations of different trace metals in all the collected seawater samples were 1.134μg/L for V,0.158μg/L for Cr,0.489μg/L for Mn,0.427μg/L for Fe,0.011μg/L for Co,0.395μg/L for Ni,0.403μg/L for Cu,0.097μg/L for Cd,0.139μg/L for Pb,and 3.470μg/L for U.Differences in the horizontal and vertical distributions of all measured trace metals were revealed,and the occurrence of high concentrations was nonuniform.In addition,the significant differences in the concentration distribution of different trace metals in seawater on both sides of the Ninety East Ridge present regional segmentation in the area for various trace metals in deep sea water.This study provided basic data for future investigations on the environmental and ecological impact of trace metals in the Indian Ocean and the potential water mass transport mechanism.

Observation of Low-Level Jets in the Eastern Tropical Indian Ocean Based on Shipborne Coherent Doppler Lidar

In contrast to the Pacific and Atlantic Oceans,the Indian Ocean has lacked in-situ observations of wind profiles over open sea areas for decades.In 2021,a shipborne coherent Doppler lidar(CDL)was used to observe in-situ wind profiles in the eastern tropical Indian Ocean.This equipment successfully captured low-level jets(LLJs)in the region,and their characteristics were thoroughly analyzed.Results reveal that the observed wind speed of LLJs in the eastern Indian Ocean ranges from 6 m s^(-1) to 10 m s^(-1) during the boreal winter and spring seasons,showing a height range of 0.6 to 1 km and two peak times at 0800 and 2000 UTC.This wind shear is weaker than that in land or offshore areas,ranging from 0 s^(-1) to 0.006 s^(-1).Moreover,the accuracy of the CDL data is compared to that of ERA5 data in the study area.The results indicate that the zonal wind from ERA5 data significantly deviated from the CDL measurement data,and the overall ERA5 data are substantially weaker than the in-situ observations.Notably,ERA5 underestimates northwestward LLJs.

Synergistic Impacts of Indian Ocean SST and Indo-China Peninsula Soil Moisture on the 2020 Record-breaking Mei-yu

The Yangtze River basin(YRB)experienced a record-breaking mei-yu season in June‒July 2020.This unique long-lasting extreme event and its origin have attracted considerable attention.Previous studies have suggested that the Indian Ocean(IO)SST forcing and soil moisture anomaly over the Indochina Peninsula(ICP)were responsible for this unexpected event.However,the relative contributions of IO SST and ICP soil moisture to the 2020 mei-yu rainfall event,especially their linkage with atmospheric circulation changes,remain unclear.By using observations and numerical simulations,this study examines the synergistic impacts of IO SST and ICP soil moisture on the extreme mei-yu in 2020.Results show that the prolonged dry soil moisture led to a warmer surface over the ICP in May under strong IO SST backgrounds.The intensification of the warm condition further magnified the land thermal effects,which in turn facilitated the westward extension of the western North Pacific subtropical high(WNPSH)in June‒July.The intensified WNPSH amplified the water vapor convergence and ascending motion over the YRB,thereby contributing to the 2020 mei-yu.In contrast,the land thermal anomalies diminish during normal IO SST backgrounds due to the limited persistence of soil moisture.The roles of IO SST and ICP soil moisture are verified and quantified using the Community Earth System Model.Their synergistic impacts yield a notable 32%increase in YRB precipitation.Our findings provide evidence for the combined influences of IO SST forcing and ICP soil moisture variability on the occurrence of the 2020 super mei-yu.

Corrections of shipboard GPS radiosonde soundings and applications on historical records in the eastern tropical Indian Ocean and South China Sea

Shipboard radiosonde soundings are important for detecting and quantifying the multiscale variability of atmosphere-ocean interactions associated with mass exchanges.This study evaluated the accuracies of shipboard Global Positioning System(GPS)soundings in the eastern tropical Indian Ocean and South China Sea through a simultaneous balloon-borne inter-comparison of different radiosonde types.Our results indicate that the temperature and relative humidity(RH)measurements of GPS-TanKong(GPS-TK)radiosonde(used at most stations before 2012)have larger biases than those of ChangFeng-06-A(CF-06-A)radiosonde(widely used in current observation)when compared to reference data from Vaisala RS92-SGP radiosonde,with a warm bias of 5℃and dry bias of 10%during daytimes,and a cooling bias of-0.8℃and a moist bias of 6%during nighttime.These systematic biases are primarily attributed to the radiation effects and altitude deviation.An empirical correction algorithm was developed to retrieve the atmospheric temperature and RH profiles.The corrected profiles agree well with that of RS92-SGP,except for uncertainties of CF-06-A in the stratosphere.These correction algorithms were applied to the GPS-TK historical sounding records,reducing biases in the corrected temperature and RH profiles when compared to radio occultation data.The correction of GPS-TK historical records illustrated an improvement in capturing the marine atmospheric structure,with more accurate atmospheric boundary layer height,convective available potential energy,and convective inhibition in the tropical ocean.This study contributes significantly to improving the quality of GPS radiosonde soundings and promotes the sharing of observation in the eastern tropical Indian Ocean and South China Sea.

Contrasting physical mechanisms of yellowfin tuna fluctuations between the western and eastern Indian Ocean

As an economically critical pelagic migratory species,yellowfin tuna(Thunnus albacores,YFT)is very sensible to physical and environmental conditions,such as sea surface temperature(SST),ocean heat content(OHC),and the mixed layer depth(MLD).We investigated the impact of SST,OHC,and MLD on fluctuations of YFT catch in the western/eastern Indian Ocean using the long time series of 63-year environmental and YFT datasets.We found that the impact of SST on YFT was heavily overestimated in the past,and MLD plays a more critical role in the YFT catch fluctuation.When the MLD deepens(>34.8 m),SST was more influential in predicting the catches of YFT than OHC in the western Indian Ocean,and OHC was more critical to YFT than SST in the eastern Indian Ocean.However,when the MLD shallows(<34.8 m),MLD was more vital to predict the catch per unit effort(CPUE)of YFT than SST/OHC in the western.After 2000,there was an asynchronous pattern of YFT CPUE induced by higher frequency variations and ocean hiatus of SST/OHC signals in the western and eastern Indian Oceans basins.The impact of the subsurface hiatus may induce the decrease of YFT in the eastern Indian Ocean.The above findings clarified a non-stationary relationship between the environmental factors and catches of YFT and provided new insights into variations in YFT abundance.

Accuracy assessment of global vertical displacement loading tide models for the equatorial and Indian Ocean

The three-dimensional displacements caused by ocean loading effects are significant enough to impact spatial geodetic measurements on sub-daily or longer timescales,particularly in the vertical direction.Currently,most tide models incorporate the distribution of vertical displacement loading tides;however,their accuracy has not been assessed for the equatorial and Indian Ocean regions.Global Positioning System(GPS)observations provide high-precision data on sea-level changes,enabling the assessment of the accuracy and reliability of vertical displacement tide models.However,because the tidal period of the K_(2) constituent is almost identical to the orbital period of GPS constellations,the estimation of the K_(2) tidal constituent from GPS observations is not satisfactory.In this study,the principle of smoothness is employed to correct the systematic error in K_(2) estimates in GPS observations through quadratic fitting.Using the adjusted harmonic constants from 31 GPS stations for the equatorial and Indian Ocean,the accuracy of eight major constituents from five global vertical displacement tide models(FES2014,EOT11a,GOT4.10c,GOT4.8,and NAO.99b)is evaluated for the equatorial and Indian Ocean.The results indicate that the EOT11a and FES2014 models exhibit higher accuracy in the vertical displacement tide models for the equatorial and Indian Ocean,with root sum squares errors of 2.29 mm and 2.34 mm,res-pectively.Furthermore,a brief analysis of the vertical displacement tide distribution characteristics of the eight major constituents for the equatorial and Indian Ocean was conducted using the EOT11a model.

Characteristics and triggering mechanisms of early negative Indian Ocean Dipole

Negative Indian Ocean Dipole(nIOD)can exert great impacts on global climate and can also strongly influence the climate in China.Early nIOD is a major type of nIOD,which can induce more pronounced climate anomalies in summer than La Niña-related nIOD.However,the characteristics and triggering mechanisms of early nIOD are unclear.Our results based on reanalysis datasets indicate that the early nIOD and La Niña-related nIOD are the two major types of nIOD,and the former accounts for over one third of all the nIOD events in the past six decades.These two types of nIODs are similar in their intensities,but are different in their spatial patterns and seasonal cycles.The early nIOD,which develops in spring and peaks in summer,is one season earlier than the La Niña-related nIOD.The spatial pattern of the wind anomaly associated with early nIOD exhibits a winter monsoon-like pattern,with strong westerly anomalies in the equatorial Indian Ocean and eastly anomalies in the northern Indian Ocean.Opposite to the triggering mechanism of early positve IOD,the early nIOD is induced by delayed Indian summer monsoon onset.The results of this study are helpful for improving the prediction skill of IOD and its climate impacts.

Correlation of Rainfall Anomalies in Rwanda from September to December (SOND) with Indian Ocean Dipole (IOD) and El Nino Southern Oscillation (ENSO) Events

Understanding the relationship between rainfall anomalies and large-scale systems is critical for driving adaptation and mitigation strategies in socioeconomic sectors. This study therefore aims primarily to investigate the correlation between rainfall anomalies in Rwanda during the months of September to December (SOND) with the occurrences of Indian Ocean Dipole (IOD) and El Nino Southern Oscillation (ENSO) events. The study is useful for early warning and forecasting of negative effects associated with extreme rainfall anomalies across the country, using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), the National Centers for Environmental Prediction (NCEP) National Center for Atmospheric Research (NCAR) reanalysis sea surface temperature and ERA5 reanalysis datasets, during the period of 1983-2021. Both empirical orthogonal function (EOF), correlation analysis and composite analysis were used to delineate variability, relationship and the related atmospheric circulation between Rwanda seasonal rainfall September to December (SOND) with Indian Ocean Dipole (IOD) and El-Nino Southern Oscillation (ENSO). The results for Empirical Orthogonal Function (EOF) for the reconstructed rainfall data set showed three modes. EOF-1, EOF-2 and EOF-3 with their total variance of 63.6%, 16.5% and 4.8%, Indian ocean dipole (IOD) events resulted to a strong positive correlation of rainfall anomalies and Dipole model index (DMI) (r = 0.42, p value = 0.001, DF = 37) significant at 95% confidence level. The composite analysis for the reanalysis dataset was carried out to show the circulation patterns during four different events correlated with September to December seasonal rainfall in Rwanda using T-test at 95% confidence level. Wind anomaly revealed that there was a convergence of south westerly winds and easterly wind over the study area during positive Indian Ocean Diploe (PIOD) and PIOD with El Nino concurrence event years. The finding of this study will contribute to the enhancement of SOND seasonal rainfall forecasting and the reduction of vulnerability during IOD (ENSO) event years.

The Relationship between Extreme Precipitation Events in East Africa during the Short Rainy Season and Indian Ocean Sea Surface Temperature

The East African short rainy season (October-November-December) is one of the major flood seasons in the East African region. The amount of rainfall during the short rainy season is closely related to the lives of the people and the socio-economic development of the area. By using precipitation data and sea surface temperature data, this study reveals the spatial and temporal variation patterns of extreme precipitation during the East African short rainy season. Key findings include significant rainfall variability, with Tanzania experiencing the highest amounts in December due to the southward shift of the Intertropical Convergence Zone (ITCZ), while other regions receive less than 100 mm. Extreme rainfall events (90th percentiles) are evenly distributed, averaging 2 to 10 days annually. Historical data shows maximum seasonal rainfall often peaks at 15 mm, with frequent occurrences of daily rainfall exceeding 10 mm during OND. Additionally, a positive correlation (0.48) between OND precipitation extremes and Indian Ocean Dipole (IOD) anomalies is statistically significant. These findings highlight the climatic variability and potential trends in extreme rainfall events in East Africa, providing valuable insights for regional climate adaptation strategies.

Variations of the Precipitation over the Three-River Headwaters Region Affected by the North Atlantic and Indian Ocean

Using the daily precipitation data from the global precipitation measurement(GPM)satellite and meteorological stations from 2001 to 2020,the present study has analyzed the seasonal and interannual spatial-temporal variations of the precipitation over the Three-River Headwaters region.The rainfall of the Three-River Headwaters region is verified to have obvious spatial-temporal variations and is mainly concentrated in summer.Then,the empirical orthogonal function(EOF)method is performed and reveals that the summer precipitation in the Three-River Headwaters region mainly shows three patterns,e.g.,the“north−south dipole pattern,”“northeast−southwest diploe pattern,”and“east−west dipole pattern,”among which the northeast−southwest diploe pattern has a strong correlation with the mid-latitude westerlies and summer monsoon.Further analysis reveals that the northeast-southwest diploe pattern of summer precipitation is significantly related to the tripolar sea surface temperature(SST)anomalies(SSTAs)of the North Atlantic Ocean in the preceding winter and the tropical Indian Ocean SSTAs in the simultaneous summer.In the preceding winter,a wave-like pattern zonally propagating along the mid-latitude westerlies is triggered downstream by the North Atlantic tripolar SSTAs.One of the cyclones generated by the wave-like pattern coincidentally locates in Northeastern China and forms a deep northeastern low system in summer.Moreover,the warming of the tropical Indian Ocean SSTAs in summer weakens the Walker circulation,which leads to the strengthening and westward extension of the Western Pacific subtropical high(WPSH).Northerly anomalies from the deep northeastern cyclonic anomalies and southwesterly anomalies from the enhancing WPSH exactly met at the eastern Three-River Headwaters region.Hence,more water vapor and ascending motion anomalies likely appear over the east part of the Three-River Headwaters region.Opposite anomalies cover the south-western Three-River Headwaters region and its surroundings.Then,the northeast-southwest reverse diploe pattern of the summer rainfall in the Three-River Headwaters region is directly produced.

Impact of Tropical Indian Ocean Temperature on the Ozone Layer in East Asia

Based on the reanalysis data of monthly mean sea surface temperature (SST) from British Hadley Center and ozone mass mixing ratio from National Aeronautics and Space Administration (NASA) during 1980-2015, two indexes IOBI and IODI of the main modes characterizing SST changes in the tropical Indian Ocean——Indian Ocean Basin (IOB) and Indian Ocean Dipole (IOD) were calculated firstly, and then the correlation of SST anomaly (SSTA) in the tropical Indian Ocean and ozone mass mixing ratio in the stratosphere over East Asia from 1980 to 2015 was analyzed. Besides, the impact of SST changes in the tropical Indian Ocean on the distribution of ozone layer in East Asia was discussed. The results show that SST changes in the tropical Indian Ocean had significant effects on stratospheric ozone distribution in East Asia, and it was consistent with the temporal changes of IOB and IOD. IOBI and IODI had a certain correlation with stratospheric ozone changes in East Asia, with a particularly significant correlation in the lower stratosphere (70 hPa) and middle stratosphere (40 hPa) especially during spring and autumn.

Study on the relationship between ENSO and tropical Indian Ocean temperature

The relationship between ENSO and Indian Ocean Dipole was discussed by using the data set of sea temperature from Scripps Institute of Oceanography, the air temperature at 1000hPa from the NCEP reanalysis data and the Nino3 index from the Climate Prediction Center （CPC） of U.S.A. during the period from 1955 to 2001. The results show that there exists a Dipole on the maximum temperature anomalous level （MTAL） in the Indian Ocean, which close relates to ENSO in the Pacific Ocean. During El Nino periods there are good relationships between ENSO and Indian Ocean Dipole which maximum correlation occurring when ENSO leads by one month, but in La Nina periods the relationship is not so good. The distribution of Dipole in Indian Ocean is from northeast to southwest, which one （west） pole in 65°E - 75°E, 6°S - 10°S and the other in 85°E - 95°E, 2°N - 6°N, which is different from that defined by Saij. The correlation coefficients of Nino3 index with temperature anomalies in the west/east poles on the MTAL are over 0.4 - 0.15, respectively. It is a main sea temperature system in the tropical Indian Ocean. However, in the surface layer from sea surface to the depth of 20 m - 30 m there is no such a dipole with opposite sea temperature anomalies in the NE and SW of tropical Indian Ocean. The SSTA in the NE might be influenced by the sensible exchange process because the evolution of sea and 1 000 hPa air temperature anomaly time series of the NE of tropical Indian Ocean is quite similar except those during 1962 - 1963 and 1986. The periods of Indian Ocean Dipole are shorter than that of ENSO, and about 1 to 6-year.

How does the Indian Ocean subtropical dipole trigger the tropical Indian Ocean dipole via the Mascarene high?

The variation in the Indian Ocean is investigated using Hadley center sea surface temperature（SST） data during the period 1958–2010.All the first empirical orthogonal function（EOF） modes of the SST anomalies（SSTA） in different domains represent the basin-wide warming and are closely related to the Pacific El Ni o– Southern Oscillation（ENSO） phenomenon.Further examination suggests that the impact of ENSO on the tropical Indian Ocean is stronger than that on the southern Indian Ocean.The second EOF modes in different domains show different features.It shows a clear east-west SSTA dipole pattern in the tropical Indian Ocean（Indian Ocean dipole,IOD）,and a southwest-northeast SSTA dipole in the southern Indian Ocean（Indian Ocean subtropical dipole,IOSD）.It is further revealed that the IOSD is also the main structure of the second EOF mode on the whole basin-scale,in which the IOD pattern does not appear.A correlation analysis indicates that an IOSD event observed during the austral summer is highly correlated to the IOD event peaking about 9 months later.One of the possible physical mechanisms underlying this highly significant statistical relationship is proposed.The IOSD and the IOD can occur in sequence with the help of the Mascarene high.The SSTA in the southwestern Indian Ocean persists for several seasons after the mature phase of the IOSD event,likely due to the positive wind–evaporation–SST feedback mechanism.The Mascarene high will be weakened or intensified by this SSTA,which can affect the atmosphere in the tropical region by teleconnection.The pressure gradient between the Mascarene high and the monsoon trough in the tropical Indian Ocean increases（decreases）.Hence,an anticyclone（cyclone） circulation appears over the Arabian Sea-India continent.The easterly or westerly anomalies appear in the equatorial Indian Ocean,inducing the onset stage of the IOD.This study shows that the SSTA associated with the IOSD can lead to the onset of IOD with the aid of atmosphere circulation and also explains why some IOD events in the tropical tend to be followed by IOSD in the southern Indian Ocean.

The Positive Indian Ocean Dipole–like Response in the Tropical Indian Ocean to Global Warming

Climate models project a positive Indian Ocean Dipole （plOD）-like SST response in the tropical Indian Ocean to global warming, By employing the Community Earth System Model and applying an overriding technique to its ocean component （version 2 of the Parallel Ocean Program）, this study investigates the similarities and differences of the formation mechanisms for the changes in the tropical Indian Ocean during the plOD versus global warming. Results show that their formation processes and related seasonality are quite similar; in particular, wind-thermocline-SST feedback is the leading mechanism in producing the anomalous cooling over the eastern tropics in both cases. Some differences are also fbund, including the fact that the cooling effect of the vertical advection over the eastern tropical Indian Ocean is dominated by the anomalous vertical velocity during the plOD but by the anomalous upper-ocean stratification under global warming. These findings are lhrther examined through an analysis of the mixed layer heat budget.

Diffusion Characteristics of Swells in the North Indian Ocean

Research on the diffusion characteristics of swells contributes positively to wave energy forecasting, swell monitoring, and early warning. In this work, the South Indian Ocean westerly index(SIWI) and Indian Ocean swell diffusion effect index(IOSDEI) are defined on the basis of the 45-year(September 1957–August 2002) ERA-40 wave reanalysis data from the European Centre for Medium-Range Weather Forecasts(ECMWF) to analyze the impact of the South Indian Ocean westerlies on the propagation of swell acreage. The following results were obtained: 1) The South Indian Ocean swell mainly propagates from southwest to northeast. The swell also spreads to the Arabian Sea upon reaching low-latitude waters. The 2.0-meter contour of the swell can reach northward to Sri Lankan waters. 2) The size of the IOSDEI is determined by the SIWI strength. The IOSDEI requires approximately 2–3.5 days to fully respond to the SIWI. The correlations between SIWI and IOSDEI show obvious seasonal differences, with the highest correlations found in December–January–February(DJF) and the lowest correlations observed in June–July–August(JJA). 3) The SIWI and IOSDEI have a common period of approximately 1 week in JJA and DJF. The SIWI leads by approximately 2–3 days in this common period.

Circulation Patterns Linked to the Positive Sub-Tropical Indian Ocean Dipole

The positive phase of the subtropical Indian Ocean dipole(SIOD)is one of the climatic modes in the subtropical southern Indian Ocean that influences the austral summer inter-annual rainfall variability in parts of southern Africa.This paper examines austral summer rain-bearing circulation types(CTs)in Africa south of the equator that are related to the positive SIOD and the dynamics through which specific rainfall regions in southern Africa can be influenced by this relationship.Four austral summer rain-bearing CTs were obtained.Among the four CTs,the CT that featured(i)enhanced cyclonic activity in the southwest Indian Ocean;(ii)positive widespread rainfall anomaly in the southwest Indian Ocean;and(iii)low-level convergence of moisture fluxes from the tropical South Atlantic Ocean,tropical Indian Ocean,and the southwest Indian Ocean,over the south-central landmass of Africa,was found to be related to the positive SIOD climatic mode.The relationship also implies that positive SIOD can be expected to increase the amplitude and frequency of occurrence of the aforementioned CT.The linkage between the CT related to the positive SIOD and austral summer homogeneous regions of rainfall anomalies in Africa south of the equator showed that it is the principal CT that is related to the inter-annual rainfall variability of the south-central regions of Africa,where the SIOD is already known to significantly influence its rainfall variability.Hence,through the large-scale patterns of atmospheric circulation associated with the CT,the SIOD can influence the spatial distribution and intensity of rainfall over the preferred landmass through enhanced moisture convergence.

The Subsurface and Surface Indian Ocean Dipoles and Their Association with ENSO in CMIP6 models

This study assesses the reproducibility of 31 historical simulations from 1850 to 2014 in the Coupled Model Intercomparison Project phase 6(CMIP6) for the subsurface(Sub-IOD) and surface Indian Ocean Dipole(IOD) and their association with El Ni?o-Southern Oscillation(ENSO). Most CMIP6 models can reproduce the leading east-west dipole oscillation mode of heat content anomalies in the tropical Indian Ocean(TIO) but largely overestimate the amplitude and the dominant period of the Sub-IOD. Associated with the much steeper west-to-east thermocline tilt of the TIO, the vertical coupling between the Sub-IOD and IOD is overly strong in most CMIP6 models compared to that in the Ocean Reanalysis System 4(ORAS4). Related to this, most models also show a much tighter association of Sub-IOD and IOD events with the canonical ENSO than observations. This explains the more(less) regular Sub-IOD and IOD events in autumn in those models with stronger(weaker) surface-subsurface coupling in TIO. Though all model simulations feature a consistently low bias regarding the percentage of the winter–spring Sub-IOD events co-occurring with a Central Pacific(CP) ENSO, the linkage between a westward-centered CP-ENSO and the Sub-IOD that occurs in winter–spring, independent of the IOD, is well reproduced.

RELATIONSHIPS BETWEEN AUTUMN INDIAN OCEAN DIPOLE MODE AND THE STRENGTH OF SCS SUMMER MONSOON

Based on 1948 - 2004 monthly Reynolds Sea Surface Temperature （SST） and NCEP/NCAR atmospheric reanalysis data, the relationships between autumn Indian Ocean Dipole Mode （IODM） and the strength of South China Sea （SCS） Summer Monsoon are investigated through the EOF and smooth correlation methods. The results are as the following. （1） There are two dominant modes of autumn SSTA over the tropical Indian Ocean. They are the uniformly signed basin-wide mode （USBM） and Indian Ocean dipole mode （IODM）, respectively. The SSTA associated with USBM are prevailing deeadal to interdecadal variability characterized by a unanimous pattern, while the IODM mainly represents interannual variability of SSTA. （2） When positive （negative） IODM exists over the tropical Indian Ocean during the preceding fall, the SCS summer monsoon will be weak （strong）. The negative correlation between the interannual variability of IODM and that of SCS summer monsoon is significant during the warm phase of long-term trend but insignificant during the cool phase. （3） When the SCS summer monsoon is strong （weak）, the IODM will be in its positive （negative） phase during the following fall season. The positive correlation between the interannual variability of SCS summer monsoon and that of IODM is significant during both the warm and cool phase of the long-term trend, but insignificant during the transition between the two phases.