The Tropical Ocean-Global Atmosphere (TOGA) program sought to determine the predictability of the coupled ocean-atmosphere system. The World Climate Research Programme's (WCRP) Global Ocean-Atmosphere-Land System (GOALS) program seeks to explore predictability of the global climate system through investigation of the major planetary heat sources and sinks, and interactions between them. The Asian-Australian monsoon system, which undergoes aperiodic and high amplitude variations on intraseasonal, annual, biennial and interannual timescales is a major focus of GOALS. Empirical seasonal forecasts of the monsoon have been made with moderate success for over 100 years. More recent modeling efforts have not been successful. Even simulation of the mean structure of the Asian monsoon has proven elusive and the observed ENSO-monsoon relationships has been difficult to replicate. Divergence in simulation skill occurs between integrations by different models or between members of ensembles of the same model. This degree of spread is surprising given the relative success of empirical forecast techniques. Two possible explanations are presented: difficulty in modeling the monsoon regions and nonlinear error growth due to regional hydrodynamical instabilities. It is argued that the reconciliation of these explanations is imperative for prediction of the monsoon to be improved. To this end, a thorough description of observed monsoon variability and the physical processes that are thought to be important is presented. Prospects of improving prediction and some strategies that may help achieve improvement are discussed.

/pdf/monsoons-processes-predictability-and-the-prospects-for-1auwiao0qt.pdf

Monsoons: Processes, predictability, and the prospects for prediction

[1] The analysis of univariate or multivariate time series provides crucial information to describe, understand, and predict climatic variability. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical field of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory. In this review we describe the connections between time series analysis and nonlinear dynamics, discuss signal-to-noise enhancement, and present some of the novel methods for spectral analysis. The various steps, as well as the advantages and disadvantages of these methods, are illustrated by their application to an important climatic time series, the Southern Oscillation Index. This index captures major features of interannual climate variability and is used extensively in its prediction. Regional and global sea surface temperature data sets are used to illustrate multivariate spectral methods. Open questions and further prospects conclude the review.

/pdf/advanced-spectral-methods-for-climatic-time-series-4hxv68i0r0.pdf

Advanced spectral methods for climatic time series

Analyses of 50-yr NCEP-NCAR reanalysis data reveal remarkably different interannual variability between the Indian summer monsoon (ISM) and western North Pacific summer monsoon (WNPSM) in their temporal- spatial structures, relationships to El Nino, and teleconnections with midlatitude circulations. Thus, two circulation indices are necessary, which measure the variability of the ISM and WNPSM, respectively. A weak WNPSM features suppressed convection along 108-208N and enhanced rainfall along the mei-yu/baiu front. So the WNPSM index also provides a measure for the east Asian summer monsoon. An anomalous WNPSM exhibits a prominent meridional coupling among the Australian high, cross-equatorial flows, WNP monsoon trough, WNP subtropical high, east Asian subtropical front, and Okhotsk high. The WNP monsoon has leading spectral peaks at 50 and 16 months, whereas the Indian monsoon displays a primary peak around 30 months. The WNPSM is weak during the decay of an El Nino, whereas the ISM tends to abate when an El Nino develops. Since the late 1970s, the WNPSM has become more variable, but its relationship with El Nino remained steady; in contrast, the ISM has become less variable and its linkage with El Nino has dramatically declined. These contrasting features are in part attributed to the differing processes of monsoon-ocean interaction. Also found is a teleconnection between a suppressed WNPSM and deficient summer rainfall over the Great Plains of the United States. This boreal summer teleconnection is forced by the heat source fluctuation associated with the WNPSM and appears to be established through excitation of Rossby wave trains and perturbation of the jet stream that further excites downstream optimum unstable modes.

/pdf/interannual-variability-of-the-asian-summer-monsoon-3p5a61esfd.pdf

Interannual Variability of the Asian Summer Monsoon: Contrasts between the Indian and the Western North Pacific–East Asian Monsoons*

Here we present a high-resolution marine sediment record from the El Nino region off the coast of Peru spanning the last 20,000 years. Sea surface temperature, photosynthetic pigments, and a lithic proxy for El Nino flood events on the continent are used as paleo–El Nino–Southern Oscillation proxy data. The onset of stronger El Nino activity in Peru started around 17,000 calibrated years before the present, which is later than modeling experiments show but contemporaneous with the Heinrich event 1. Maximum El Nino activity occurred during the early and late Holocene, especially during the second and third millennium B.P. The recurrence period of very strong El Nino events is 60–80 years. El Nino events were weak before and during the beginning of the Younger Dryas, during the middle of the Holocene, and during medieval times. The strength of El Nino flood events during the last millennium has positive and negative relationships to global and Northern Hemisphere temperature reconstructions.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2004PA001099

El Niño variability off Peru during the last 20,000 years

Critical reviews of forecasts of ENSO conditions, based on a set of 15 dynamical and statistical models, are given for the 1997—98 El Nino event and the initial stages of the 1998—99 La Nina. While many of the models forecasted some degree of warming one to two seasons prior to the onset of the El Nino in boreal spring of 1997, none predicted its strength until the event was already becoming very strong in late spring. Neither the dynamical nor the statistical models, as groups, performed significantly better than the other during this episode. The best performing statistical models and dynamical models forecast SST anomalies of about +1°C (vs 2.5°—3° observed) in the Nino 3.4 region prior to any observed positive anomalies. The most comprehensive dynamical models performed better than the simple dynamical models. Once the El Nino had developed in mid-1997, a larger set of models was able to forecast its peak in late 1997 and dissipation and reversal to cold conditions in late spring/early summer...

Predictive Skill of Statistical and Dynamical Climate Models in SST Forecasts during the 1997-98 El Niño Episode and the 1998 La Niña Onset.

Evaluation of competing El Nino/Southern Oscillation (ENSO) theories requires one to identify separate spectral peaks in equatorial wind and sea-surface temperature (SST) time series. To sharpen this identification, we examine the seasonal-to-interannual variability of these fields by the data-adaptive method of multi-channel singular spectrum analysis (M-SSA). M-SSA is applied to the equatorial band (4°N-4°S), using 1950–1990 data from the Comprehensive Ocean and Atmosphere Data Set. Two major interannual oscillations are found in the equatorial SST and surface zonal wind fields, U. The main peak is centered at about 52-months; we refer to it as the quasi-quadrennial (QQ) mode. Quasi-biennial (QB) variability is split between two modes, with periods near 28 months and 24 months. A faster, 15-month oscillation has smaller amplitude. The QQ mode dominates the variance and has the most distinct spectral peak. In time-longitude reconstructions of this mode, the SST has the form of a standing oscillation in the eastern equatorial Pacific, while the U-field is dominated by a standing oscillation pattern in the western Pacific and exhibits also slight eastward propagation in the central and western Pacific. The locations of maximum anomalies in both QB modes are similar to those of the QQ mode. Slight westward migration in SST, across the eastern and central, and eastward propagation of U, across the western and central Pacific, are found. The significant wind anomaly covers a smaller region than for the QQ. The QQ and QB modes together represent the ENSO variability well and interfere constructively during major events. The sharper definition of the QQ spectral peak and its dominance are consistent with the “devil's staircase” interaction mechanism between the annual cycle and ENSO.

/pdf/quasi-quadrennial-and-quasi-biennial-variability-in-the-5eugyleh7r.pdf

Quasi-quadrennial and quasi-biennial variability in the equatorial Pacific

Historical extreme heatwaves struck the Yangtze River Valley (YRV) in the boreal summer of 2022, severely impacting agricultural production, electricity supply, and resident health in China. This study shows that extreme heatwaves recurred over the YRV with distinct subseasonal processes. In early summer, from 14 June to 18 July, two extreme heatwaves were embedded in a mid-latitude 10–25-day intraseasonal oscillation (ISO), and hot-and-wet anomalies persisted over the YRV. A self-sustaining mechanism between the “cold vortex” over Northeast China and the “heat dome” around the YRV maintained this bi-weekly ISO. It fueled the heatwaves by modulating the meridional advection of upper-tropospheric potential vorticity, which firstly warmed the air via adiabatic processes and then later by diabatic heating. In late summer, from 30 July to 29 August, a 30–50-day ISO impacted the heatwave and drought over the YRV. This ISO originated from monsoon convection in the tropics, which regulated the meridional monsoonal circulation and enhanced the heatwave by intensifying the descending air motion and adiabatic heating over the YRV. The alternation of the two ISOs accompanied the northward migration of the subtropical westerly jet over East Asia. The combination of the above-normal 10–25-day ISO and the moderate 30–50-day ISO led to the three consecutive extreme YRV heatwaves in 2022. 

Subseasonal processes of triple extreme heatwaves over the Yangtze River Valley in 2022

In 2023, the development of El Niño is poised to drive a global upsurge in surface air temperatures (SAT), potentially resulting in unprecedented warming worldwide. Nevertheless, the regional patterns of SAT anomalies remain diverse, obscuring where historical warming records may be surpassed in the forthcoming year. Our study underscores the significant influence of El Niño and the persistence of climate signals on the inter-annual variability of regional SAT, both in amplitude and spatial distribution. The likelihood of global mean SAT exceeding historical records, calculated from July 2023 to June 2024, is estimated at 90%, contingent upon annual-mean sea surface temperature anomalies in the eastern equatorial Pacific exceeding 0.6 °C. Regions particularly susceptible to recording record-high SAT include coastal and adjacent areas in Asia such as the Bay of Bengal and the South China Sea, as well as Alaska, the Caribbean Sea, and the Amazon. This impending warmth heightens the risk of year-round marine heatwaves and escalates the threat of wildfires and other negative consequences in Alaska and the Amazon basin, necessitating strategic mitigation measures to minimize potential worst-case impacts. 

Enhanced risk of record-breaking regional temperatures during the 2023–24 El Niño

The triple-dip La Niña in 2020–23 is characterized by persisting southeasterly wind anomalies over the tropical central and eastern Pacific. Our results show that the wind anomalies are associated with the anomalously negative phase of the first two leading modes of the annual cycle (antisymmetric and symmetric modes about the equator) of sea surface temperature (SST) in the tropical Pacific. The two modes account for 82.2% and 13.5% of the total variance, linking to the seasonal swing of SST between the northern and southern hemispheres and the temporal evolution of El Niño-Southern Oscillation, respectively. During 2020–23, the persistently and anomalously negative phase of the symmetric mode enhances easterly wind over the tropical central Pacific, while the antisymmetric mode strengthens the southeasterly wind over the tropical eastern Pacific. The anomalously negative phase of the antisymmetric mode is associated with the contrast of SST anomalies between the northern and southern hemispheres, which provided a favorable background for the triple-dip La Niña in 2020–23.

https://iopscience.iop.org/article/10.1088/1748-9326/ace274/pdf

Triple-dip La Niña in 2020–23: understanding the role of the annual cycle in tropical Pacific SST

Progress and Prospects of Research on Subseasonal to Seasonal Variability and Prediction of the East Asian Monsoon

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