Tropical Pacific Ocean Research Articles

Retraction Note: Tropical coastal climate change based on image defogging algorithm and swimming rehabilitation training

This paper first designs and implements an image defogging algorithm based on FPGA. The hardware design mainly includes SDRAM control module, SD card control module, data transmission control module, and convolution neural network calculation module. The SDRAM control module controls the working state of SDRAM; the SD card control module controls the working state of SD card; the data transmission control module controls the data transmission of reading and writing SDRAM; and the convolution neural network module is responsible for the image defogging algorithm. Based on this point, this paper uses the medium complex ocean atmosphere combination model to estimate the SST diversity and climate characteristics of the tropical coastal Pacific and Atlantic Ocean in recent years, and studies and analyzes the influencing factors of the prediction. The atmospheric part of the coupled model is the global atmospheric circulation model CCM3, and the oceanic part is a simplified gravity model of Zebiak Cane type. In addition, an air filter is added to the coupled model to test the impact of natural noise during broadcasting. Finally, the article investigated the positive effect of swimming rehabilitation training on chronic neck pain symptoms of office workers; Objectives were to study the effect of various swimming rehabilitation trainings on neck pain of office workers and investigate the effect of different swimming rehabilitation training cycles on chronic neck pain symptoms of office workers. Objective was to provide a theoretical basis for the development of exercise rehabilitation plan to improve the chronic pain symptoms of office workers. The results showed that breaststroke training and freestyle training were effective in treating neck pain of office workers. In this paper, the application of adaptive image defogging algorithm and the correction of coastal climate change in the rehabilitation training research has promoted the healthy development and progress of swimming rehabilitation training.

New insights into the trophic ecology of the scalloped hammerhead shark, Sphyrna lewini, in the eastern tropical Pacific Ocean

New insights into the trophic ecology of the scalloped hammerhead shark, Sphyrna lewini, in the eastern tropical Pacific Ocean

Regional Characteristics of Variability in the Northern Hemisphere Wintertime Polar Front Jet and Subtropical Jet in Observations and CMIP6 Models

AbstractVariability in the position and strength of the subtropical jet (STJ) and polar front jet (PFJ) streams has important implications for global and regional climate. Previous studies have related the position and strength of the STJ to tropical thermodynamic processes, whereas the position and strength of the PFJ are more associated with midlatitude eddies. These conclusions have largely resulted from studies using idealized models. In this study, ERA‐Interim reanalysis and CMIP6 global climate models are used to examine month‐to‐month and interannual variability of the wintertime Northern Hemisphere (NH) STJ and PFJ. This study particularly focuses on the regional characteristics of the jet variability, extending previous studies on zonal‐mean jet streams. Consistent with idealized modeling studies, a close relationship is found between tropical outgoing longwave radiation (OLR) and the STJ and between midlatitude lower tropospheric temperature gradients and the PFJ. Variations of both jets are also linked to well‐known teleconnection patterns. Variations in tropical convection over the Pacific Ocean are associated with variations of the NH STJ at most longitudes, with different phases of the El Niño–Southern Oscillation (ENSO) associated with the shift and strengthening of the STJ in different regions. CMIP6 models generally capture these relationships, but the models’ tropical convection is often displaced westward when compared to observations, reflecting a climatological bias in OLR in the western tropical Pacific Ocean in many models. The displaced tropical convection in models excites different paths of Rossby wave propagation, resulting in different ENSO teleconnections on the STJ over North America and Europe.

Seasonal-To-Interannual Variability of Sea-Surface Temperatures in The Inter-Americas Seas: Pattern-Dependent Biases in The Regional Ocean Modeling System

The Inter-Americas Seas (IAS), involving the Gulf of Mexico, the Caribbean and a section of the eastern tropical Pacific Ocean bordering Central America, Colombia and Ecuador, exhibits very active ocean-land-atmosphere interactions that impact socio-economic activities within and beyond the region, and that are still not well understood or represented in state-of-the-art models. On seasonal-to-interannual timescales, the main source of variability of this geographical area is related to interactions between the Pacific and the Atlantic oceans, involving to anomalous sea-surface temperature (SST) patterns like El Niño-Southern Oscillation (ENSO), and regional features in the Caribbean linked to the bi-modal seasonality of the Caribbean Low-Level Jet. This study investigates seasonal-to-interannual IAS surface-temperature anomalies in observations, and their representation in am eddy-permitting, 1/9o-resolution simulation using the Regional Ocean Modeling System (ROMS), interannually-forced by the Climate Forecast System Reanalysis. Here, rather than analyzing model biases locally (i.e., gridbox-by-gridbox), a non-local SST pattern-based diagnostic was conducted via a principal component analysis. The approach allowed to identify magnitude, variance and spatial systematic errors in SST patterns related to the Western Hemisphere Warm Pool, ENSO, the Inter-American Seas Dipole, and several other variability modes. These biases are mainly related to errors in surface heat fluxes, misrepresentation of air-sea interactions impacting surface latent cooling in the Caribbean, and too strong sub-surface thermal stratification, mostly off the coast of Ecuador and northern Peru.

Spatial and temporal dynamics of SAR11 marine bacteria across a nearshore to offshore transect in the tropical Pacific Ocean.

Surveys of microbial communities across transitions coupled with contextual measures of the environment provide a useful approach to dissect the factors determining distributions of microorganisms across ecological niches. Here, monthly time-series samples of surface seawater along a transect spanning the nearshore coastal environment within Kāneʻohe Bay on the island of Oʻahu, Hawaiʻi, and the adjacent offshore environment were collected to investigate the diversity and abundance of SAR11 marine bacteria (order Pelagibacterales) over a 2-year time period. Using 16S ribosomal RNA gene amplicon sequencing, the spatiotemporal distributions of major SAR11 subclades and exact amplicon sequence variants (ASVs) were evaluated. Seven of eight SAR11 subclades detected in this study showed distinct subclade distributions across the coastal to offshore environments. The SAR11 community was dominated by seven (of 106 total) SAR11 ASVs that made up an average of 77% of total SAR11. These seven ASVs spanned five different SAR11 subclades (Ia, Ib, IIa, IV, and Va), and were recovered from all samples collected from either the coastal environment, the offshore, or both. SAR11 ASVs were more often restricted spatially to coastal or offshore environments (64 of 106 ASVs) than they were shared among coastal, transition, and offshore environments (39 of 106 ASVs). Overall, offshore SAR11 communities contained a higher diversity of SAR11 ASVs than their nearshore counterparts, with the highest diversity within the little-studied subclade IIa. This study reveals ecological differentiation of SAR11 marine bacteria across a short physiochemical gradient, further increasing our understanding of how SAR11 genetic diversity partitions into distinct ecological units.

Sample size requirements for genetic studies on yellowfin tuna.

In population genetics, the amount of information for an analytical task is governed by the number of individuals sampled and the amount of genetic information measured on each of those individuals. In this work, we assessed the numbers of individual yellowfin tuna (Thunnus albacares) and genetic markers required for ocean-basin scale inferences. We assessed this for three distinct data analysis tasks that are often employed: testing for differences between genetic profiles; stock delineation, and; assignment of individuals to stocks. For all analytical tasks, we used real (not simulated) data from four sampling locations that span the tropical Pacific Ocean. Whilst spatially separated, the genetic differences between the sampling sites were not substantial, a maximum of approximately Fst = 0.02, which is quite typical of large pelagic fish. We repeatedly sub-sampled the data, mimicking a new survey, and performed the analyses. False positive rates were also assessed by re-sampling and randomly assigning fish to groups. Varying the sample sizes indicated that some analytical tasks, namely profile testing, required relatively few individuals per sampling location (n ≳ 10) and single nucleotide polymorphisms (SNPs, m ≳ 256). Stock delineation required more individuals per sampling location (n ≳ 25). Assignment of fish to sampling locations required substantially more individuals, more in fact than we had available (n > 50), although this sample size could be reduced to n ≳ 30 when individual fish were assumed to belong to one of the groups sampled. With these results, designers of molecular ecological surveys for yellowfin tuna, and users of information from them, can assess whether the information content is adequate for the required inferential task.

Statistical and machine learning methods applied to the prediction of different tropical rainfall types

Predicting rain from large-scale environmental variables remains a challenging problem for climate models and it is unclear how well numerical methods can predict the true characteristics of rainfall without smaller (storm) scale information. This study explores the ability of three statistical and machine learning methods to predict 3-hourly rain occurrence and intensity at 0.5° resolution over the tropical Pacific Ocean using rain observations the Global Precipitation Measurement (GPM) satellite radar and large-scale environmental profiles of temperature and moisture from the MERRA-2 reanalysis. We also separated the rain into different types (deep convective, stratiform, and shallow convective) because of their varying kinematic and thermodynamic structures that might respond to the large-scale environment in different ways. Our expectation was that the popular machine learning methods (i.e., the neural network and random forest) would outperform a standard statistical method (a generalized linear model) because of their more flexible structures, especially in predicting the highly skewed distribution of rain rates for each rain type. However, none of the methods obviously distinguish themselves from one another and each method still has issues with predicting rain too often and not fully capturing the high end of the rain rate distributions, both of which are common problems in climate models. One implication of this study is that machine learning tools must be carefully assessed and are not necessarily applicable to solving all big data problems. Another implication is that traditional climate model approaches are not sufficient to predict extreme rain events and that other avenues need to be pursued.

PREFACE

The seasonal atmospheric condition over the Maritime Continent is mainly driven by the Asian-Australian Monsoon. Precipitation over the Maritime Continent is highly influenced by the intra-seasonal Madden-Julian Oscillation (MJO), also highly affected by the El-Nino Southern Oscillation (ENSO) and Indian Ocean Dipole Mode (IOD). At an interannual time scale the Maritime Continent is also crossed by Indonesia Through Flow (ITF), as the artery connecting Tropical Pacific and Indian Oceans, and acting as a crucial link of the ocean general circulation that affects not only properties of these two oceans but also global climate.This complex mixture of land and sea interaction, with various atmospheric and oceanic phenomena within, makes the Maritime Continent as a unique, enigmatic and challenging area for scientific endeavor on tropical meteorology and atmospheric sciences. Various observations and research have been coordinated, campaigned, and conducted to better understand the atmospheric and oceanic condition over the tropics, especially the Maritime Continent.Many scientific discoveries have been found to enrich the knowledge of atmospheric science on the tropics, from the International Winter Monsoon Experiment in 1978, TOGA COARE in 1993, HARIMAU that ended in 2010, to CINDY/DYNAMO in 2011. The recent Year of Maritime Continent (YMC) during 2017 - 2020 aimed to improve understanding and prediction local multi-scale variability of the Maritime Continent weather-climate system and its global impact through observations and modelling exercises, was the state-of-art for such coordinated research on the tropics. As a part of YMC program, BMKG will also be involved in Measurements and Modelling of the Indonesian Throughflow International Experiment (MINTIE) which is collaborative research among countries including Indonesia BMKG and being led by Columbia University during 2019 – 2024.LIST OF Committee, Steering Committee, Organizing Committee Leader, Leader, Secretariat & Public Relations, Treasure, Event are available in this pdf.

A Theory of the Spring Persistence Barrier on ENSO. Part III: The Role of Tropical Pacific Ocean Heat Content

AbstractIn this paper, we investigate the relationship between upper ocean heat content (OHC) and El Niño–Southern Oscillation (ENSO) sea surface temperature (SST) anomalies mainly using the neutral recharge oscillator (NRO) model both analytically and numerically. Previous studies showed that spring OHC, which leads SST by 6–12 months, represents a major source of predictability for ENSO. It is suggested that this seasonality is caused by the seasonally varying growth rate in SST anomalies. Moreover, a shortened ENSO period will lead to a reduced SST predictability from OHC, with the most significant decrease occurring in the latter half of the calendar year. The cross-correlation relationship between OHC and ENSO SST anomalies is further identified in the damped and self-excited version of the recharge oscillator model. Finally, we suggest that the seasonal growth rate of ENSO anomalies is the cause of the seasonality in the effectiveness of OHC as a predictor in ENSO forecasting, particularly as it relates to the boreal spring persistence barrier and associated spring predictability barrier. We also explain the shorter lead time between spring OHC and ENSO SST anomalies after the turn of the twenty-first century in terms of the apparent higher frequency of the ENSO period.

Revisiting the Recharge and Discharge Processes for Different Flavors of El Niño

AbstractEl Niño‐related sea surface temperature (SST) anomalies over the tropical Pacific Ocean impact global climates, but these impacts differ substantially for conventional cold tongue El Niño (CT El Niño) and the central Pacific El Niño (CP El Niño) events. This study is motivated by the need for a better understanding of the recharge/discharge processes associated with these two different flavors of El Niño. Composite analysis based on improved CT and CP El Niño identification methods applied to the Simple Ocean Data Assimilation demonstrates that the recharge/discharge processes are active during CT El Niño events. In contrast, for CP El Niño events, the recharge/discharge processes do not play a significant role. Prior to a CT El Niño, warm water accumulates over the western Pacific due to off‐equatorial anticyclonic wind stress curl. The onset of a CT El Niño is closely associated with the formation of a cyclonic atmospheric circulation over the northwest Pacific in the winter and spring, which induces westerly wind anomalies in the equatorial western Pacific and initiates eastward warm water transport. This leads to peak warming in the eastern equatorial Pacific the following winter, followed by the poleward discharge of warm water. This quasi‐cyclical behavior provides a measure of predictability. In contrast, the CP El Niño events do not show a precursor subsurface warming signal along the tropical Pacific thermocline. Instead, modest warm SST anomalies appear in boreal summer and peak in the fall, with weak subsurface warming mainly in the fall during CP El Niños. Hence, CP El Niños are less predictable in terms of an equatorial thermocline precursor than CT El Niño events.

El Niño-Southern Oscillation and Indian Ocean Dipole Modes: Their Effects on South American Rainfall during Austral Spring

This paper examines the effects of the tropical Pacific Ocean (TPO) and Indian Ocean Dipole (IOD) modes in the interannual variations of austral spring rainfall over South America (SA). The TPO mode refers to the El Niño-Southern Oscillation (ENSO). The isolated effects between IOD and TPO were estimated, events were chosen from the residual TPO (R-TPO) or residual IOD (R-IOD), and the IOD (TPO) effects for the R-TPO (R-IOD) composites were removed from the variables. One relevant result was the nonlinear precipitation response to R-TPO and R-IOD. This feature was accentuated for the R-IOD composites. The positive R-IOD composite showed significant negative precipitation anomalies along equatorial SA east of 55° W and in subtropical western SA, and showed positive anomalies in northwestern SA and central Brazil. The negative R-IOD composite indicated significant positive precipitation anomalies in northwestern Amazon, central–eastern Brazil north of 20° S, and western subtropical SA, and negative anomalies were found in western SA south of 30° S. This nonlinearity was likely due to the distinct atmospheric circulation responses to the anomalous heating sources located in longitudinally distinct regions: the western tropical Indian Ocean and areas neighboring Indonesia. The results obtained in this study might be relevant for climate monitoring and modeling studies.

The riddle of eastern tropical Pacific Ocean oxygen levels: the role of the supply by intermediate-depth waters

Abstract. Observed oxygen minimum zones (OMZs) in the tropical Pacific Ocean are located above intermediate-depth waters (IDWs), defined here as the 500–1500 m water layer. Typical climate models do not represent IDW properties well and are characterized by OMZs that are too deep-reaching. We analyze the role of the IDW in the misrepresentation of oxygen levels in a heterogeneous subset of ocean models characterized by a horizontal resolution ranging from 0.1 to 2.8∘. First, we show that forcing the extratropical boundaries (30∘ S and N) to observed oxygen values results in a significant increase in oxygen levels in the intermediate eastern tropical region. Second, we highlight the fact that the Equatorial Intermediate Current System (EICS) is a key feature connecting the western and eastern part of the basin. Typical climate models lack in representing crucial aspects of this supply at intermediate depth, as the EICS is basically absent in models characterized by a resolution lower than 0.25∘. These two aspects add up to a “cascade of biases” that hampers the correct representation of oxygen levels at intermediate depth in the eastern tropical Pacific Ocean and potentially future OMZ projections.

How Does El Niño Affect Predictability Barrier of Its Accompanied Positive Indian Ocean Dipole Event?

The effects of El Niño on the predictability of positive Indian Ocean dipole (pIOD) events are investigated by using the GFDL CM2p1 coupled model from the perspective of error growth. The results show that, under the influence of El Niño, the summer predictability barrier (SPB) for pIOD tends to intensify and the winter predictability barrier (WPB) is weakened. Since the reason for the weakening of WPB has been explained in a previous study, the present study attempts to explore why the SPB is enhanced. The results demonstrate that the initial sea temperature errors, which are most likely to induce SPB for pIOD with El Niño, possess patterns similar to those for pIOD without El Niño, whose dominant errors concentrate in the tropical Pacific Ocean (PO), with a pattern of negative SST errors occurring in the eastern and central PO and subsurface sea temperature errors being negative in the eastern PO and positive in the western PO. By tracking the development of such initial errors, it is found that the initial errors over PO lead to anomalous westerlies in the southeastern Indian Ocean (IO) through the effect of double-cell Walker circulation. Such westerly anomalies are inhibited by the strongest climatological easterly wind and the southeasterlies related to the pIOD event itself in summer, while they are enhanced by El Niño. This competing effect causes the intensified seasonal variation in latent heat flux, with much less loss in summer under the effect of El Niño. The greater suppression of the loss of latent heat flux favors the positive sea surface temperature (SST) errors developing much faster in the eastern Indian Ocean in summer, and eventually induces an enhanced SPB for pIOD due to El Niño.

Interaction between the Tropical Atlantic and Pacific Oceans on an Interannual Time Scale

ABSTRACT Based on the fifth-generation reanalysis of the European Centre for Medium-range Weather Forecasts (ECMWF), the Hadley Centre sea surface temperature (SST) data, and the Global Precipitation Climatology Project (GPCP) precipitation data, the interaction between the tropical Atlantic and Pacific Oceans on an interannual time scale is investigated using correlation, regression, and composite analyses, and the quantitative estimates of the relative and collective contribution of the tropical North Atlantic (NTA) and equatorial Atlantic (ETA) SST anomalies to the El Niño–Southern Oscillation (ENSO) are presented. An El Niño or La Niña event can cause a same-sign SST anomaly in the NTA in the following boreal spring, accounting for 33% of the interannual variability of the NTA SST. The NTA SST anomaly may excite a same-sign SST anomaly of the ETA in boreal summer with an ETA SST anomaly of 0.44°C per 1°C NTA SST anomaly. Moreover, an SST anomaly in the NTA and ETA can cause an opposite-sign SST anomaly in the equatorial Pacific during the following winter. The NTA SST anomaly influences the central equatorial Pacific with a Niño 3.4 SST anomaly of −0.85°C per 1°C NTA SST anomaly, while the ETA SST anomaly exerts an impact on the central-eastern equatorial Pacific with a Niño 3.4 SST anomaly of −1.85°C per 1°C ETA SST anomaly based on a multiple regression analysis. The composite analyses based on Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) hindcasts show that the ETA SST anomaly in summer acts as a primary contributor to the interaction between the tropical Atlantic and Pacific Oceans. The ETA impact can relay and amplify the NTA SST anomaly such that it affects the equatorial Pacific. The collective impact of spring NTA and summer ETA SST anomalies can explain 33% of the total variance of the winter Niño 3.4 index. This study deepens our understanding of the interannual interaction between the tropical Atlantic and Pacific Oceans and highlights the role of the tropical Atlantic Ocean, especially the ETA region, in the pan-tropical air–sea interaction.

Sources of Subseasonal Skill and Predictability in Wintertime California Precipitation Forecasts

AbstractThe relation between the El Niño–Southern Oscillation (ENSO) and California precipitation has been studied extensively and plays a prominent role in seasonal forecasting. However, a wide range of precipitation outcomes on seasonal time scales are possible, even during extreme ENSO states. Here, we investigate prediction skill and its origins on subseasonal time scales. Model predictions of California precipitation are examined using Subseasonal Experiment (SubX) reforecasts for the period 1999–2016, focusing on those from the Flow-Following Icosahedral Model (FIM). Two potential sources of subseasonal predictability are examined: the tropical Pacific Ocean and upper-level zonal winds near California. In both observations and forecasts, the Niño-3.4 index exhibits a weak and insignificant relationship with daily to monthly averages of California precipitation. Likewise, model tropical sea surface temperature and outgoing longwave radiation show only minimal relations with California precipitation forecasts, providing no evidence that flavors of El Niño or tropical modes substantially contribute to the success or failure of subseasonal forecasts. On the other hand, an index for upper-level zonal winds is strongly correlated with precipitation in observations and forecasts, across averaging windows and lead times. The wind index is related to ENSO, but the correlation between the wind index and precipitation remains even after accounting for ENSO phase. Intriguingly, the Niño-3.4 index and California precipitation show a slight but robust negative statistical relation after accounting for the wind index.

Genesis of Easterly Waves over the Tropical Eastern Pacific and the Intra-Americas Sea

AbstractThis paper explores a new mechanism for in situ genesis of easterly waves (EWs) over the tropical eastern Pacific Ocean (EPAC). Using an idealized primitive equation model, it is shown that EWs can be triggered by finite-amplitude transient heating close to the midlevel jet at about 15°N over the EPAC and intra-Americas sea region. The atmospheric response to heating initiates EWs downstream, showing an EW structure within 4 days, with a wavelength and propagation speed of about 2000 km and 4.6 m s−1, respectively, resembling EWs described in the literature. The most sensitive location for EW initiation from finite-amplitude transient heating is located over the northern part of South America and extends to the EPAC. The closer the heating is to the jet, the bigger the response is. A stratiform heating profile is the most efficient at triggering EPAC EWs. Comparisons of simulated EWs over the EPAC and West Africa reveal similar structures but with a shorter wavelength and much weaker amplitudes over the EPAC. EPAC EWs are dominated by horizontal tilts against the shear on the equatorial side of the jet, consistent with barotropic growth, with weaker low-level amplitudes relative to those seen over West Africa. These differences arise from differences in the mean state EPAC having a shorter and weaker midlevel jet with less baroclinicity.

Impact of Westerly Wind Bursts on ENSO Based on a Hybrid Coupled Model: Part I – ENSO Simulation

ABSTRACT Westerly wind bursts (WWBs), usually occurring in the tropical Pacific region during the beginning and advancement of El Niño events, play a vital role in El Niño–Southern Oscillation (ENSO). In this study, we use a hybrid coupled model (HCM) for the tropical Pacific Ocean–atmosphere system to investigate the impact of WWBs on ENSO. To achieve this goal, we performed two experiments: first, the standard version of the HCM is integrated for years without prescribed WWBs events; and second, the WWBs are added to the HCM, which are constructed using observational data and WWB parameterization schemes. Results show that when WWBs are added to the HCM not only can a more realistic climatology of sea surface temperature (SST) in both spatial structure and temporal amplitudes be generated but also better ENSO features can be generated than with the HCM alone. The former is mainly reflected in the simulation of the SST seasonal cycle in the eastern Pacific and a reduction in the bias toward the cold tongue in the equatorial eastern Pacific, whereas the latter includes an improvement in a broad spectrum of ENSO features, such as ENSO amplitude, phase locking, asymmetry, and diversity. In particular, when WWBs are added to the HCM, the model can capture central Pacific ENSO events, which are absent in the original HCM. On the other hand, WWBs have little impact on cold events because very few WWBs occur during the cold phase of ENSO. Furthermore, the possible physical mechanisms responsible for these improvements as a result of adding WWBs are discussed.

Sea Level Seasonal, Interannual and Decadal Variability in the Tropical Pacific Ocean

The satellite altimeter data, temperature and salinity data, and 1.5-layer reduced gravity model are used to quantitatively evaluate the contributions of the steric effect and the dynamic process to sea level variations in the Tropical Pacific Ocean (TPO) on different time scales. Concurrently, it also analyses the influence of wind forcing over the different regions of the Pacific Ocean on the sea level variations in the TPO. Seasonal sea level variations in the TPO were the most important in the middle and eastern regions of the 5°–15°N latitude zone, explaining 40–60% of the monthly mean sea level variations. Both the steric effect and dynamic process jointly affected the seasonal sea level variations. Among them, the steric effect was dominant, contributing over 70% in most regions of the TPO, while the dynamic process primarily acted near the equator and southwest regions, contributing approximately 55–85%. At the same time, the seasonal dynamic sea level variations were caused by the combined actions of primarily local wind forcing, alongside subtropical north Pacific wind forcing. On the interannual to decadal time scale, the sea level interannual variations were significant in the northwestern, southwestern, and middle eastern regions of the TPO and explained 45–60% of the monthly mean sea level variations. The decadal sea level variations were the most intense in the eastern Philippine Sea, contributing 25–45% to the monthly mean sea level variations. The steric effect and the dynamic process can explain 100% of the interannual to decadal sea level variations. The contribution of the steric effect was generally high, accounting for more than 85% in the regions near the equator. The impact of the dynamic process was mainly concentrated in the northwest, northeast, and southern regions of the TPO, contributing approximately 55–80%. Local wind forcing is the leading role of interannual to decadal sea level variations. The combined actions of El Niño–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) can explain 90% of the interannual to decadal sea level variations in the northwestern and eastern of the TPO.

Predicting Interannual Variability in Sea Surface Height Along the West Coast of Australia Using a Simple Ocean Model

AbstractSea surface height (SSH) along the west coast of Australia is key to local climate and is strongly forced by remote surface wind variability related to El Niño Southern Oscillation (ENSO) in the tropical Pacific Ocean. This study provides a method to predict interannual variability in SSH along the west coast of Australia using a simple 1.5‐layer dynamical ocean model forced by a statistical atmospheric model for ENSO‐related winds. The model has realistic coastlines and is driven by reanalysis surface winds regressed onto an ENSO index. The model when run in hindcast mode to predict past variability can simulate tide gauge observations at Fremantle along the west coast of Australia up to 13 months in advance, which outperforms persistence. We conclude that this methodology can be useful as a baseline for gauging the performance of more sophisticated forecast models for predicting SSH variations along the west coast of Australia.

Tropical Climate Change Is a Puzzle—Could Aerosols Be a Piece?

The eastern tropical Pacific Ocean hasn’t warmed as much as climate change models projected. A new study shows that aerosols in the atmosphere could be responsible.