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Climate models typically have a cold sea surface temperature (SST) bias for the Arabian Sea, which regulates the Indian monsoon system as a water vapor source. Since the SST for the Arabian Sea is critical for the Indian monsoon, a better understanding of the processes that affect the SST is required. In this study, the effects of mesoscale oceanic variability on simulations of the Arabian Sea SST and Indian summer monsoon precipitation were investigated based on a comparison of climate model experiments in which non-eddying and eddy-permitting ocean components are coupled. In the eddy-permitting model, warm water advection driven by mesoscale variability near the Gulf of Aden and the Gulf of Oman increases the SST in the western Arabian Sea. Lateral eddy heat transport enhances warm water outflows to the Arabian Sea and suppresses surface water cooling by coastal upwelling during the southwestern monsoon season. Furthermore, a sensitivity experiment shows the primary importance of resolving oceanic mesoscale eddies and the secondary importance of resolving the Persian Gulf and Red Sea for the Arabian Sea SST. Also, the summer monsoonal precipitation decreases (increases) over the southeastern Arabian Sea (western and northern India) in the eddy-permitting model due to enhancement of wind convergence in the lower troposphere. Atmospheric general circulation model experiments indicate that the precipitation difference is partly caused by SST changes over the western Arabian Sea. The findings imply that the ocean resolution of climate models is a key factor in efficiently simulating the Indian monsoon.

A simple air–sea coupled model for wind–evaporation–sea surface temperature (SST), wind-induced turbulence–mixed layer (ML)–SST, and wind–evaporation–ML–SST feedback is extended to unitedly represent the precipitation anomaly associated with moisture convergence and the ML depth (MLD) anomaly due to freshwater-induced buoyancy flux. An eigenanalysis reveals the presence of yet another feedback accompanying a cross-equatorial SST gradient. The feedback operates as follows: A cross-equatorial SST gradient anomaly forces surface wind anomalies to blow toward the warmer hemisphere, causing low-level convergence (divergence) and hence a positive (negative) precipitation anomaly in the warmer (cooler) hemisphere. The positive (negative) precipitation anomaly stratifies (destabilizes) the near-surface ocean and results in a shallower (deeper) ML, which enhances (reduces) the warming by climatological shortwave radiation, and thus provides positive feedback to the initial SST gradient anomaly. The strength of this feedback is similar to the three known feedbacks in terms of stability. Sensitivity experiments with the coupled general circulation model MIROC6 reveal that the precipitation-induced buoyancy flux anomaly accounts for up to ∼14% of the Atlantic meridional mode (AMM) amplitude in boreal spring through affecting the MLD anomaly in the deep tropics, which is consistent with the simple model results, supporting the existence of the feedback. In contrast, the evaporation-induced buoyancy anomaly contributes only marginally to the MLD and thus the SST anomalies. The ML temperature budget from MIROC6 confirms that sensitivity changes of the ML to the warming by climatological shortwave radiation due to the MLD anomaly are important in generating the SST anomalies associated with the AMM, which is consistent with previous observational studies. Significance Statement It is known that year-to-year variations in the sea surface north–south temperature gradient in the tropical Atlantic can affect the climate in both surrounding and remote regions. In this study, we used theoretical and state-of-the-art climate models to investigate a tropical air–sea coupled process and establish its contribution to the Atlantic climate variability. As a result, we identified a previously unknown process contributing to north–south gradient variations in which the atmosphere and ocean interact to enhance the initial variation, thus forming a positive feedback loop. In particular, precipitation and near-surface ocean state changes were determined to be essential. This feedback process accounts for up to 14% of the north–south temperature gradient variations in the tropical Atlantic during the boreal spring.

The influence of the tropical Atlantic on El Niño–Southern Oscillation (ENSO) is examined using sensitivity experiments with the SINTEX-F general circulation model with prescribed sea surface temperature (SST) distributions based on observations for the period 1982–2018. In the control experiment (CTRL) observed SSTs are prescribed over the global oceans; in the sensitivity experiment observed SSTs are prescribed in the tropical Atlantic only, while in other regions the climatological annual cycle is prescribed. A composite analysis of the model output suggests that cold SST events in the northern tropical Atlantic during boreal spring are associated with near-surface wind changes over the equatorial and subtropical Pacific that are conducive to the development of El Niño, consistent with previous studies. The amplitude of these changes, however, is at most 20% of those observed during typical El Niño events. Likewise, warm events in the equatorial Atlantic produce only about 10% of the wind changes seen in the western equatorial Pacific during the developing phase of typical La Niña events. Similar results are obtained from a partial regression analysis performed on an ensemble of atmosphere-only simulations from phase 6 of the Atmospheric Model Intercomparison Project (AMIP) although the equatorial Atlantic influence is stronger in AMIP. Further analysis of the AMIP models indicates that model biases do not have a major impact on the Atlantic-to-Pacific influence. Overall, the results suggest that the tropical Atlantic has a rather weak influence on ENSO development and mostly acts to modulate ongoing events rather than initiate them.

The ocean–atmosphere feedback associated with the thermodynamic coupling among wind speed, evaporation, and sea surface temperature (SST), called the wind–evaporation–SST (WES) feedback, contributes to the cross-equatorial SST gradient over the tropical oceans. By conducting an eigenanalyses of simple linear air–sea coupled models, it is shown that two additional feedback processes are present when the variable oceanic mixed layer depth (MLD) is considered. The horizontal structures of the leading modes are similar to the WES mode, which shows a meridional dipole in the SST anomalies straddling the equator with cross-equatorial wind anomalies that represent the weakening/strengthening of the trade winds over the warm/cool SST anomalies. The coupling of the variable MLD with winds and SST more than doubles the growth rate of the WES mode and enhances the equatorward propagation of the coupled disturbances. The identified feedbacks operate as follows: The weaker winds associated with warm SST anomalies shoal the mixed layer through suppressed turbulent mixing, which causes the mixed layer to be more sensitive to the climatological shortwave radiation and amplifies the initial positive SST anomalies. Likewise, deepening of the mixed layer due to stronger winds acts to maintain the negative SST anomaly on the other side of the dipole. The MLD anomalies can also be generated by the buoyancy flux anomaly related to the wind-induced latent heat flux anomaly. The antiphase relationship between the SST and MLD anomalies seen in the simple model bears some resemblance to that which is observed in the observations and a state-of-the-art coupled model during the Atlantic meridional mode.

The present paper presents results of seasonal‐to‐decadal climate predictions based on a coupled climate model called the Model for Interdisciplinary Research on Climate version 6 (MIROC6) contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). MIROC6 is initialized every year for 1960–2018 by assimilating observed ocean temperature and salinity anomalies and full fields of sea ice concentration and by prescribing atmospheric initial states from reanalysis data. The impacts of updating the system on prediction skill are then evaluated by comparing hindcast experiments between the MIROC6 prediction system and a previous system based on MIROC version 5 (MIROC5). Skill of seasonal prediction is overall improved in association with representation and initialization of El Niño/Southern Oscillation (ENSO), the Quasi‐Biennial Oscillation (QBO), and the Northern Hemisphere sea ice concentration in MIROC6. In particular, the QBO is skillfully predicted up to 3 years ahead with a maximum anomaly correlation exceeding r = 0.8. The prediction skill for the North Atlantic Oscillation in winter is also enhanced, but the prediction still suffers from model's inherent errors. On decadal timescales, MIROC6 has a larger fraction of areas of the globe with better surface temperature skill at all lead times than MIROC5, and it has predictive skill in the annual‐mean sea surface temperature (SST) in the North Atlantic and the Pacific. In particular, MIROC6 hindcasts at 2–5 years lead time are able to capture the spatial structure of SST changes in the North Pacific and the eastern tropical Pacific associated with the 1970s regime shift better than MIROC5 hindcasts.

Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis. Fil: Merryfield, William J.. Canadian Centre For Climate Modelling And Analysis; Canadá Fil: Baehr, Johanna. Universitat Hamburg; Alemania Fil: Batté, Lauriane. Centre National de Recherches Météorologiques; Francia Fil: Becker, Emily J.. No especifíca; Fil: Butler, Amy H.. State University of Colorado at Boulder; Estados Unidos Fil: Coelho, Caio A.S.. Instituto Nacional de Pesquisas Espaciais; Brasil Fil: Danabasoglu, Gokhan. National Center for Atmospheric Research; Estados Unidos Fil: Dirmeyer, Paul A.. No especifíca; Fil: Doblasreyes, Francisco. No especifíca; Fil: Domeisen, Daniela I.V.. No especifíca; Fil: Ferranti, Laura. No especifíca; Fil: Ilynia, Tatiana. No especifíca; Fil: Kumar, Arun. No especifíca; Fil: Müller, Wolfgang A.. No especifíca; Fil: Rixen, Michel. World Meteorological Organization; Estados Unidos Fil: Robertson, Andrew W.. International Research Institute For Climate And Society; Estados Unidos Fil: Smith, Doug M.. No especifíca; Fil: Takaya, Yuhei. Japan Meteorological Agency; Japón Fil: Tuma, Matthias. World Meteorological Organization; Estados Unidos Fil: Vitart, Frederic. No especifíca; Fil: White, Christopher J.. University of Strathclyde; Reino Unido Fil: Alvarez, Mariano Sebastián. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Ardilouze, Constantin. No especifíca; Fil: Attard, Hannah. No especifíca; Fil: Baggett, Cory. State University of Colorado - Fort Collins; Estados Unidos Fil: Balmaseda, Magdalena A.. No especifíca; Fil: Beraki, Asmerom F.. University Of Pretoria; Sudáfrica Fil: Bhattacharjee, Partha S.. National Oceanic And Atmospheric Administration; Estados Unidos Fil: Bilbao, Roberto. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; España Fil: De Andrade, Felipe M.. University of Reading; Reino Unido Fil: DeFlorio, Michael J.. No especifíca; Fil: Díaz, Leandro Baltasar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Ehsan, Muhammad Azhar. The Abdus Salam. International Centre for Theoretical Physics; Italia. The Abdus Salam; Italia Fil: Fragkoulidis, Georgios. Johannes Gutenberg Universitat Mainz; Alemania Fil: Grainger, Sam. No especifíca; Fil: Green, Benjamin W.. State University of Colorado at Boulder; Estados Unidos Fil: Hell, Momme C.. No especifíca; Fil: Infanti, Johnna M.. National Oceanic And Atmospheric Administration; Estados Unidos Fil: Isensee, Katharina. No especifíca; Fil: Kataoka, Takahito. No especifíca; Fil: Kirtman, Ben P.. No especifíca; Fil: Klingaman, Nicholas P.. University of Reading; Reino Unido Fil: Lee, June Yi. Pusan National University; Corea del Sur Fil: Mayer, Kirsten. State University of Colorado at Boulder; Estados Unidos Fil: McKay, Roseanna. Monash University; Australia Fil: Mecking, Jennifer V.. University of Southampton; Reino Unido Fil: Miller, Douglas E.. University of Illinois. Urbana - Champaign; Estados Unidos Fil: Neddermann, Nele. No especifíca; Fil: Ng, Ching Ho Justin. University of Princeton; Estados Unidos Fil: Ossó, Albert. University of Graz; Austria Fil: Pankatz, Klaus. Max Planck Institute For Meteorology; Estados Unidos Fil: Peatman, Simon. No especifíca; Fil: Pegion, Kathy. George Mason University; Estados Unidos Fil: Perlwitz, Judith. State University of Colorado at Boulder; Estados Unidos Fil: Recalde Coronel, G. Cristina. Escuela Superior Politecnica del Litoral ; Ecuador Fil: Reintges, Annika. Geomar-Helmholtz Centre for Ocean Research Kiel; Alemania Fil: Renkl, Christoph. Dalhousie University Halifax; Canadá Fil: Solaraju-Murali, Balakrishnan. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; España Fil: Spring, Aaron. No especifíca; Fil: Stan, Cristiana. George Mason University; Estados Unidos Fil: Sun, Y. Qiang. University of Princeton; Estados Unidos Fil: Tozer, Carly R.. No especifíca; Fil: Vigaud, Nicolas. No especifíca; Fil: Woolnough, Steven. University of Reading; Reino Unido Fil: Yeager, Stephen. National Center for Atmospheric Research; Estados Unidos

* This essay stems from international conferences on subseasonal to seasonal and seasonal to decadal prediction jointly convened by WWRP and WCRP in September 2018 in Boulder, Colorado: (www.wcrp-climate.org/s2s-s2d-2018-home). Adapted from “Current and Emerging Developments in Subseasonal to Decadal Prediction,”. Published Online in BAMS, June 2020. For the full, citable article, see DOI:10.1175 /BAMS-D-19-0037.1. © Copyright 2020 American Meteorological Society (AMS). For permission to reuse any portion of this Work, please contact permissions@ametsoc.org. Any use of material in this Work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act (17 U.S. Code § 107) or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC § 108) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a website or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. All AMS journals and monograph publications are registered with the Copyright Clearance Center (https://www.copyright.com). Additional details are provided in the AMS Copyright Policy statement, available on the AMS website (https://www.ametsoc.org/PUBSCopyrightPolicy). Tremendous recent progress in climate prediction on subseasonal to decadal time scales has been enabled by better observations, data assimilation, and models originating from the weather prediction and climate simulation communities together with ever-increasing computational power. World Climate Research Program (WCRP) efforts led initially to predictions one to two seasons ahead becoming part of the WMO operational infrastructure. More recently, a joint World Weather Research Program (WWRP) and WCRP Subseasonal to Seasonal Prediction Project has started tackling the weather–climate gap (from two weeks to a season). The NOAA-led Subseasonal Experiment project has similar aims. New frontiers have been enabled by Earth system models that represent the carbon and other biogeochemical cycles in addition to the physical climate system. As a result, skillful multiyear prediction is likely achievable for biogeochemical and ecological Earth system components. The ultimate collective subseasonal to seasonal (S2S; 2 weeks to season) and seasonal to decadal (S2D) endeavor is to improve the prediction of the spatial–temporal continuum connecting weather to climate through a coordinated, seamless, and integrated Earth system approach. The S2S and S2D communities share common scientific and technical challenges. This essay* synthesizes those commonalities across time scales and Earth system components, and from basic research to operational delivery. Peer Reviewed Article signat per 65 autors/es: William J. Merryfield, Johanna Baehr, Lauriane Batté, Emily J. Becker, Amy H. Butler, Caio A. S. Coelho, Gokhan Danabasoglu, Paul A. Dirmeyer, Francisco J. Doblas-Reyes, Daniela I. V. Domeisen, Laura Ferranti, Tatiana Ilynia, Arun Kumar, Wolfgang A. Müller, Michel Rixen, Andrew W. Robertson, Doug M. Smith, Yuhei Takaya, Matthias Tuma, Frederic Vitart, Christopher J. White, Mariano S. Alvarez, Constantin Ardilouze, Hannah Attard, Cory Baggett, Magdalena A. Balmaseda, Asmerom F. Beraki, Partha S. Bhattacharjee, Roberto Bilbao, Felipe M. de Andrade, Michael J. DeFlorio, Leandro B. Díaz, Muhammad Azhar Ehsan, Georgios Fragkoulidis, Sam Grainger, Benjamin W. Green, Momme C. Hell, Johnna M. Infanti, Katharina Isensee, Takahito Kataoka, Ben P. Kirtman, Nicholas P. Klingaman, June-Yi Lee, Kirsten Mayer, Roseanna McKay, Jennifer V. Mecking, Douglas E. Miller, Nele Neddermann, Ching Ho Justin Ng, Albert Ossó, Klaus Pankatz, Simon Peatman, Kathy Pegion, Judith Perlwitz, G. Cristina Recalde-Coronel, Annika Reintges, Christoph Renkl, Balakrishnan Solaraju-Murali, Aaron Spring, Cristiana Stan, Y. Qiang Sun, Carly R. Tozer, Nicolas Vigaud, Steven Woolnough, and Stephen Yeager.

Ningaloo Nino/Nina is the dominant climate mode in the southeastern Indian Ocean with its center of positive/negative sea surface temperature anomalies attached to Australia. Ningaloo Nino is the major cause of marine heatwaves in the region. Although oceanic variability in this region has long been considered mainly as a response to the El Nino-Southern Oscillation (ENSO), some recent studies have suggested the possible existence of local air-sea feedback processes. Using a state-of-the-art ocean-atmosphere coupled model that realistically simulates Ningaloo Nino/Nina, whether Ningaloo Nino/Nina can occur independently of ENSO is examined. Even in an experiment in which ENSO is suppressed by strongly nudging tropical Pacific sea surface temperatures toward the model climatology, Ningaloo Nino/Nina with a similar magnitude and seasonality still develops, likely through an air-sea interaction off Western Australia amplifying atmospheric stochastic forcing. This study is the first to show that Ningaloo Nino/Nina can develop even without ENSO. Plain Language Summary Ningaloo Nino/Nina is the major cause of extreme warming/cooling in the southeastern Indian Ocean in austral summer and affects the marine environment and precipitation over the Western Australia. Although it has long been considered that El Nino and La Nina in the Pacific drive ocean extreme events in this region, some recent studies have suggested a possibility that warming/cooling off Western Australia would add to itself by changing the atmospheric condition and creating further heating/cooling (i.e., positive air-sea feedback). Using climate model simulations, we show that, even without El Nino and La Nina, Ningaloo Nino/Nina with a similar magnitude occurs in summer, likely through the positive air-sea feedback off Western Australia amplifying atmospheric random forcing. This study is the first to show that Ningaloo Nino/Nina can develop even without El Nino and La Nina.

形態: カラー図版あり, Physical characteristics: Original contains color illustrations, 資料番号: PA1810045000

Using an ocean model, generation and decay mechanisms of warm/cool sea surface temperature anomalies (SSTAs) off Western Australia, or Ningaloo Nino/Nina, are investigated through the calculation of a mixed-layer temperature (MLT) balance taking the mixed-layer depth (MLD) variation into account. Since Ningaloo Nino/Nina develops owing to local air-sea interaction and/or remote forcing, events are classified into two cases based on alongshore wind anomalies and analyzed separately. It is revealed that the anomalous meridional advection associated with the stronger Leeuwin Current and the enhanced warming by the climatological shortwave radiation because of the shallower MLD generate warm SSTAs in the coastal region for both cases of Ningaloo Nino. On the other hand, the latent heat flux damps SSTAs only in a case without northerly alongshore wind anomalies. In the decay, larger sensible heat loss is important. Because of the reduced meridional temperature gradient, the meridional advection eventually damps SSTAs. The sensitivity change to the climatological shortwave radiation owing to MLD anomalies explains offshore MLT tendency anomalies for both cases throughout the events. The mechanisms for Ningaloo Nina are close to a mirror image of Ningaloo Nino, but differ in that the latent heat flux damps offshore SSTAs. The seasonal phase-locking nature of Ningaloo Nino/Nina is related to the seasonal variations of MLD and surface heat fluxes, which regulate the amplitude and sign of the sensitivity change to surface heat fluxes. It is also related to the seasonal variations of the Leeuwin Current and meridional temperature gradient through advection anomalies.

The ability of coupled general circulation models (CGCMs) to simulate a newly-discovered climate mode called Ningaloo Nino/Nina is examined using outputs from 17 CGCMs that participated in the Coupled Model Inter-comparison Project, phase 5. It is shown that 8 out of 17 models reproduce sea surface temperature (SST) anomalies associated with Ningaloo Nino/Nina with a pattern correlation coefficient of 0.7 or higher, but the location of peak SST anomalies is very different from the observation in 2 models. Also, fundamental features such as the seasonality and associated anomalous atmospheric circulation and precipitation are fairly well reproduced in most models, but the amplitude varies significantly among the models. The inter-model difference in the amplitude is found to be mainly due to that in the magnitude of remote influences from the El Nino-Southern Oscillation via oceanic and atmospheric teleconnections. On the other hand, the strength of local air-sea interaction does not contribute much to the inter-model difference. This study may pave the way for an improved representation of Ningaloo Nino/Nina in CGCMs.

The sixth version of the Model for Interdisciplinary Research on Climate (MIROC), called MIROC6, was cooperatively developed by a Japanese modeling community. In the present manuscript, simulated mean climate, internal climate variability, and climate sensitivity in MIROC6 are evaluated and briefly summarized in comparison with the previous version of our climate model (MIROC5) and observations. The results show that overall reproducibility of mean climate and internal climate variability in MIROC6 is better than that in MIROC5. The tropical climate systems (e.g., summertime precipitation in the western Pacific and the eastward propagating Madden-Julian Oscillation) and the mid-latitude atmospheric circulations (e.g., the westerlies, the polar night jet, and troposphere-stratosphere interactions) are significantly improved in MIROC6. These improvements can be attributed to the newly implemented parameterization for shallow convective processes and to the directly resolved stratosphere. While there are significant differences in climates and variabilities between the two models, the effective climate sensitivity of 2.5 K remains the same because the differences in radiative forcing and climate feedback tend to offset each other. With an aim towards contributing to the sixth phase of the Coupled Model Intercomparison Project, designated simulations tackling a wide range of climate science issues, as well as seasonal-to-decadal climate predictions and future climate projections, are currently ongoing using MIROC6.

A recently identified climate mode called Ningaloo Nino (Nina) is associated with positive (negative) sea surface temperature (SST) anomalies off the west coast of Australia and negative (positive) sea level pressure (SLP) anomalies in the overlying atmosphere. By conducting a series of numerical experiments with an atmospheric general circulation model, generation mechanisms of the atmospheric circulation anomalies accompanied by Ningaloo Nino/Nina are examined. Even when SST is allowed to vary interannually only in the eastern South Indian Ocean, negative (positive) SLP anomalies are formed off the west coast of Australia in Ningaloo Nino (Nina) years, supporting the existence of local ocean–atmosphere interaction. When the model is forced by SST anomalies outside of the eastern South Indian Ocean, negative (positive) SLP anomalies are also generated in Ningaloo Nino (Nina) years owing to a Matsuno–Gill type response to atmospheric convection anomalies in the tropical Pacific. It is found that the latter impact is stronger in the current atmospheric general circulation model. Regarding climatic impacts, it is shown that Ningaloo Nino (Nina) induces wet (dry) anomalies over the northwestern part of Australia even when SST anomalies outside of the eastern South Indian Ocean are excluded from the SST forcing.

Using both observational and reanalysis data, evolution processes of a regional climate phenomenon off Western Australia named recently “Ningaloo Nino (Nina)” are studied in detail. It is also shown that the Ningaloo Nino (Nina) has significant impacts on the precipitation over Australia. The Ningaloo Nino (Nina), which is associated with positive (negative) sea surface temperature (SST) anomalies and atmospheric anomalies off the western coast of Australia, peaks during austral summer and is classified into two types based on the difference in the evolution process. The first type called a locally amplified mode develops through an intrinsic unstable air–sea interaction off the western coast of Australia; an anomalous cyclone (anticyclone) generated by positive (negative) SST anomalies forces northerly (southerly) alongshore wind anomalies, which induce coastal downwelling (upwelling) anomalies, and enhance the positive (negative) SST anomalies further. The second type called a non-locally amplified mode is associated with coastally trapped waves originating in either the western tropical Pacific, mostly related to El Nino/Southern Oscillation, or the northern coast of Australia. Positive (negative) SST anomalies in both modes are associated with an anomalous low (high) off the western coast of Australia. The sea level pressure (SLP) anomalies in the locally amplified mode are regionally confined with a cell-like pattern and produce a sharp offshore pressure gradient along the western coast of Australia, whereas those in the non-locally amplified mode tend to show a zonally elongated pattern. The difference is found to be related to conditions of the continental SLP modulated by the Australian summer monsoon and/or the Southern Annular Mode.

Using observation data and outputs from the “twentieth-century climate in coupled models” (20c3m) control runs of coupled general circulation models submitted to the Coupled Model Intercomparison Project, phase 3 (CMIP3), the ability of CMIP3 models to simulate the Indian Ocean subtropical dipole (IOSD) and its influence on the rainfall anomaly over the southern African region is investigated. Many models simulate the IOSD, but the location and shape of the sea surface temperature anomaly vary among models. This model bias is closely linked to the bias in simulating the anomalous strengthening and southward shift of the subtropical high. Almost all models fail to simulate the rainfall anomaly associated with the IOSD owing to the inaccurate simulation of the location of sea surface temperature and sea level pressure anomalies.

As climate change accelerates, societies and climate-sensitive socioeconomic sectors cannot continue to rely on the past as a guide to possible future climate hazards. Operational decadal predictions offer the potential to inform current adaptation and increase resilience by filling the important gap between seasonal forecasts and climate projections. The World Meteorological Organization (WMO) has recognized this and in 2017 established the WMO Lead Centre for Annual to Decadal Climate Predictions (shortened to “Lead Centre” below), which annually provides a large multimodel ensemble of predictions covering the next 5 years. This international collaboration produces a prediction that is more skillful and useful than any single center can achieve. One of the main outputs of the Lead Centre is the Global Annual to Decadal Climate Update (GADCU), a consensus forecast based on these predictions. This update includes maps showing key variables, discussion on forecast skill, and predictions of climate indices such as the global mean near-surface temperature and Atlantic multidecadal variability. it also estimates the probability of the global mean temperature exceeding 1.5°C above preindustrial levels for at least 1 year in the next 5 years, which helps policy-makers understand how closely the world is approaching this goal of the Paris Agreement. This paper, written by the authors of the GADCU, introduces the GADCU, presents its key outputs, and briefly discusses its role in providing vital climate information for society now and in the future. LH and AS were supported by the EUCP project funded by the European Commission’s Horizon 2020 programme, Grant Agreement 776613 and supported by the U.K.–China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. AS, DS, and MS were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. The EC-Earth simulations at SMHI were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at PDC and NSC and have been performed as part of the NordForsk-funded Nordic Centre of Excellence project (Award 76654) Arctic Climate Predictions: Pathways to Resilient, Sustainable Societies (ARCPATH). SY and TT were supported by the ARCPATH (NordForsk Award 76654) and the Danish state-funded National Centre for Climate Research [Nationalt Center for Klimaforskning (NCFK)]. SY was also partly supported by the EUCP project (Horizon 2020 Grant Agreement 776613). The EC-Earth simulations at BSC were performed using resources from the Red Española de Supercomputación. HP and WM received funding from the German Federal Ministry of Education and Research (BMBF) project MiKlip (FKZ 01LP1519A). Takahito Kataoka and Hiroaki Tatebe were supported by the Integrated Research Program for Advancing Climate Models (TOUGOU) Grant JPMXD0717935457 from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. MIROC simulations were performed on the Earth Simulator at JAMSTEC. NK, YW, FC, and IB were supported by the Trond Mohn Foundation (Grant BFS2018TMT01; Bjerknes Climate Prediction Unit). Peer Reviewed "Article signat per 45 autors/es: Leon Hermanson, Doug Smith, Melissa Seabrook, Roberto Bilbao, Francisco Doblas-Reyes, Etienne Tourigny, Vladimir Lapin, Viatcheslav V. Kharin, William J. Merryfield, Reinel Sospedra-Alfonso, Panos Athanasiadis, Dario Nicoli, Silvio Gualdi, Nick Dunstone, Rosie Eade, Adam Scaife, Mark Collier, Terence O’Kane, Vassili Kitsios, Paul Sandery, Klaus Pankatz, Barbara Früh, Holger Pohlmann, Wolfgang Müller, Takahito Kataoka, Hiroaki Tatebe, Masayoshi Ishii, Yukiko Imada, Tim Kruschke, Torben Koenigk, Mehdi Pasha Karami, Shuting Yang, Tian Tian, Liping Zhang, Tom Delworth, Xiaosong Yang, Fanrong Zeng, Yiguo Wang, François Counillon, Noel Keenlyside, Ingo Bethke, Judith Lean, Jürg Luterbacher, Rupa Kumar Kolli, and Arun Kumar"