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Despite decades of efforts and improvements in the representation of processes as well as in model resolution, current global climate models still suffer from a set of important, systematic biases in sea surface temperature (SST), not much different from the previous generation of climate models. Many studies have looked at errors in the wind field, cloud representation or oceanic upwelling in coupled models to explain the SST errors. In this paper we highlight the relationship between latent heat flux (LH) biases in forced atmospheric simulations and the SST biases models develop in coupled mode, at the scale of the entire intertropical domain. By analyzing 22 pairs of forced atmospheric and coupled ocean-atmosphere simulations from the CMIP5 database, we show a systematic, negative correlation between the spatial patterns of these two biases. This link between forced and coupled bias patterns is also confirmed by two sets of dedicated sensitivity experiments with the IPSL-CM5A-LR model. The analysis of the sources of the atmospheric LH bias pattern reveals that the near-surface wind speed bias dominates the zonal structure of the LH bias and that the near-surface relative humidity dominates the east-west contrasts. [ABSTRACT FROM AUTHOR]

This paper aims at identifying oceanic regions outside the tropical Pacific, which may influence the El Niño Southern Oscillation (ENSO) through interannual modulation of equatorial Pacific winds. An Atmospheric General Circulation Model (AGCM) 7-members ensemble experiment forced by climatological sea surface temperature (hereafter, SST) in the tropical Pacific Ocean and observed interannually varying SST elsewhere produces ensemble-mean equatorial zonal wind stress interannual anomalies (ZWSA) over the equatorial Pacific. These ZWSA are largest during boreal winter in the western Pacific, and induce a ~0.5 °C response in the central Pacific during the following spring in a simple ocean model, that weakly but significantly correlates with the following ENSO peak amplitude. When correlated with global SST, the residual western equatorial Pacific ZWSA yield SST patterns that are reminiscent of ENSO teleconnections in the Indian, North and South Pacific, and Atlantic Oceans. We further design 20-members ensemble sensitivity experiments forced by typical SST patterns of the main climate modes for each of these regions, in order to identify regions that influence equatorial Pacific ZWSA most. In our experiments, only the Indian Ocean Basin-wide SST warming in late boreal winter produces a statistically significant ZWSA in the western equatorial Pacific, resulting in a weak but significant ~0.35 °C SST response in the central Pacific (i.e. ~35 % of the observed standard deviation) during the following spring, the season when the Bjerkness coupled feedback is particularly efficient. This paper hence agrees with previous studies, which suggest that ENSO-induced basin-wide SST signals in the Indian Ocean may contribute to the phase transition of ENSO. Our results suggest that studies exploring external influences on ENSO should adopt a global approach rather than focus on a specific region. Designing coupled model simulations would also allow investigating air-sea interactions-mediated teleconnection mechanisms, which we can't reproduce in our forced AGCM framework. [ABSTRACT FROM AUTHOR]

In this study, the data from three long-term observation stations, Aburatsu, Xiamen, and Hong Kong, which are located on the northwest Pacific Ocean coast, were analyzed to estimate the 100-year annual maximum water levels. The performances of four common frequency analysis methods, namely the Gumbel, Weibull, GEV, and GPD distributions, were evaluated. It is found that the GEV model performs best among these four distribution models in Hong Kong and Aburatsu, whereas the Gumbel distribution is the best at the Xiamen station. It is also found that the GEV model generally performs better than the Gumbel model in regard to the mean high correlation coefficient and the mean minimum root-mean-square error. Moreover, in this study, the r-largest value model was used to study temporal trends in the 50-year annual maximum water levels on the northwest Pacific coast over the past fifty years using the observation data of Hong Kong, Xiamen, and Aburatsu. The results show that there are two temporal features in the 50-year return levels at all three stations, with the first being an overall increasing trend over the whole period and the other being an oscillatory trend over the period of observation. The relationships between the temporal trends and the Pacific Decadal Oscillation (PDO), sea level rise, and change of typhoons were also analyzed in this paper. It is found that when the PDO index is shifted to be 4 years in advance, a significantly negative correlation will occur between the PDO index and the 50-year return levels. However, sea level rise and changes of typhoons cause the overall increase over the entire period. [ABSTRACT FROM AUTHOR]

A hybrid coupled model (HCM) is constructed for El Niño-Southern Oscillation (ENSO)-related modeling studies over almost the entire Pacific basin. An ocean general circulation model is coupled to a statistical atmospheric model for interannual wind stress anomalies to represent their dominant coupling with sea surface temperatures. In addition, various relevant forcing and feedback processes exist in the region and can affect ENSO in a significant way; their effects are simply represented using historical data and are incorporated into the HCM, including stochastic forcing of atmospheric winds, and feedbacks associated with freshwater flux, ocean biology-induced heating (OBH), and tropical instability waves (TIWs). In addition to its computational efficiency, the advantages of making use of such an HCM enable these related forcing and feedback processes to be represented individually or collectively, allowing their modulating effects on ENSO to be examined in a clean and clear way. In this paper, examples are given to illustrate the ability of the HCM to depict the mean ocean state, the circulation pathways connecting the subtropics and tropics in the western Pacific, and interannual variability associated with ENSO. As satellite data are taken to parameterize processes that are not explicitly represented in the HCM, this work also demonstrates an innovative method of using remotely sensed data for climate modeling. Further model applications related with ENSO modulations by extratropical influences and by various forcings and feedbacks will be presented in Part II of this study. [ABSTRACT FROM AUTHOR]

Understanding of past climate variability on millennial to decadal scales are of primary importance in order to assess modern processes and predict future climatic events. Past history of Arctic climate changes is currently receiving increasing attention due to the recent phenomena of rapid sea-ice reduction. In this paper, we thoroughly reviewed the Holocene history of spatiotemporal climatic changes in the western Arctic region in order to better understand recent rapid environmental changes occurring in the Pacific sector of the Arctic, and further to discuss critical issues and new perspectives on the western Arctic in terms of paleoclimate researches. Records of temporal and spatial variations in sea-ice extents as well as marine and terrestrial paleoclimatic proxies show a strong asynchronicity between the western and eastern Arctic throughout the Holocene. The reason for this apparent contradiction across the Arctic may be linked to freshwater discharges over the Arctic shelves and the inflow of the Pacific freshwater into the western Arctic Ocean in coupled with a complex interaction between atmospheric and sea-ice dynamics. Special emphasis is placed on a tentative linkage of the late Holocene paleoclimatic events between the Arctic regions and the northwestern Pacific margin, highlighting the notion that climatic events of the northern Pacific Ocean is closely linked to the global climate system through hydrological dynamics in the western Arctic Ocean. [ABSTRACT FROM AUTHOR]

The seasonal cycle and interannual variability in the tropical oceans simulated by three versions of the Flexible Ocean-Atmosphere-Land System (FGOALS) model (FGOALS-g1.0, FGOALS-g2 and FGOALSs2), which have participated in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5), are presented in this paper. The seasonal cycle of SST in the tropical Pacific is realistically reproduced by FGOALS-g2 and FGOALSs2, while it is poorly simulated in FGOALS-g1.0. Three feedback mechanisms responsible for the SST annual cycle in the eastern Pacific are evaluated. The ocean-atmosphere dynamic feedback, which is successfully reproduced by both FGOALS-g2 and FGOALS-s2, plays a key role in determining the SST annual cycle, while the overestimated stratus cloud-SST feedback amplifies the annual cycle in FGOALS-s2. Because of the serious warm bias existing in FGOALS-g1.0, the ocean-atmosphere dynamic feedback is greatly underestimated in FGOALS-g1.0, in which the SST annual cycle is mainly driven by surface solar radiation. FGOALS-g1.0 simulates much stronger ENSO events than observed, whereas FGOALS-g2 and FGOALSs2 successfully simulate the observed ENSO amplitude and period and positive asymmetry, but with less strength. Further ENSO feedback analyses suggest that surface solar radiation feedback is principally responsible for the overestimated ENSO amplitude in FGOALS-g1.0. Both FGOALS-g1.0 and FGOALS-s2 can simulate two different types of El Ni-no events - with maximum SST anomalies in the eastern Pacific (EP) or in the central Pacific (CP) - but FGOALS-g2 is only able to simulate EP El Ni-no, because the negative cloud shortwave forcing feedback by FGOALS-g2 is much stronger than observed in the central Pacific. [ABSTRACT FROM AUTHOR]

In this paper, lead-time and spatial dependence in skill for prediction of monthly mean climate variability is analyzed. The analysis is based on a set of extensive hindcasts from the Climate Forecast System at the National Centers for Environmental Prediction. The skill characteristics of initialized predictions is also compared with the AMIP simulations forced with the observed sea surface temperature (SST) to quantify the role of initial versus boundary conditions in the prediction of monthly means. The analysis is for prediction of monthly mean SST, precipitation, and 200-hPa height. The results show a rapid decay in skill with lead time for the atmospheric variables in the extratropical latitudes. Further, after a lead-time of approximately 30-40 days, the skill of monthly mean prediction is essentially a boundary forced problem, with SST anomalies in the tropical central/eastern Pacific playing a dominant role. Because of the larger contribution from the atmospheric internal variability to monthly time-averages (compared to seasonal averages), skill for monthly mean prediction associated with boundary forcing is also lower. The analysis indicates that the prospects of skillful prediction of monthly means may remain a challenging problem, and may be limited by inherent limits in predictability. [ABSTRACT FROM AUTHOR]

Most of the annual rainfall over India occurs during the Southwest (June-September) and Northeast (October-December) monsoon periods. In March 2008, however, Southern peninsular India and Sri Lanka received the largest rainfall anomaly on record since 1979, with amplitude comparable to summer-monsoon interannual anomalies. This anomalous rainfall appeared to be modulated at intraseasonal timescale by the Madden Julian Oscillation, and was synchronous with a decaying La Niña event in the Pacific Ocean. Was this a coincidence or indicative of a teleconnection pattern? In this paper, we explore factors controlling rainfall over southern India and Sri Lanka between January and April, i.e. outside of the southwest and northeast monsoons. This period accounts for 20% of annual precipitation over Sri Lanka and 10% over the southern Indian states of Kerala and Tamil Nadu. Interannual variability is strong (about 40% of the January-April climatology). Intraseasonal rainfall anomalies over southern India and Sri Lanka are significantly associated with equatorial eastward propagation, characteristic of the Madden Julian Oscillation. At the interannual timescale, we find a clear connection with El Niño-Southern Oscillation (ENSO); with El Niños being associated with decreased rainfall (correlation of −0.46 significant at the 98% level). There is also a significant link with local SST anomalies over the Indian Ocean, and in particular with the inter-hemispheric sea surface temperature (SST) gradient over the Indian Ocean (with colder SST south of the equator being conducive to more rainfall, correlation of 0.55 significant at the 99% level). La Niñas/cold SSTs south of the equator tend to have a larger impact than El Niños. We discuss two possible mechanisms that could explain these statistical relationships: (1) subsidence over southern India remotely forced by Pacific SST anomalies; (2) impact of ENSO-forced regional Indian Ocean SST anomalies on convection. However, the length of the observational record does not allow distinguishing between these two mechanisms in a statistically significant manner. [ABSTRACT FROM AUTHOR]

Several studies show that the El Niño-Southern Oscillation (ENSO) is an important factor in determining interannual rainfall variability in South America. This signal is detected in the region including Northeastern Argentina, Uruguay and part of southern Brazil, in the form of excessive rains and big floods in the regional rivers. To check that this relationship was similar in the past the objectives of this paper were to construct a time series of large floods in the Paraná River region from documentary records, during the sixteenth to eighteenth centuries, and to evaluate the relationship between that historical record of extreme floods, the ENSO documentary evidence (Ortlieb, The Documented Historical Record of El Niño Events in Perú: An Update of the Quinn Record (Ortlieb, sixteenth through nineteenth centuries, Diaz and Markgraf, (eds.), El Niño and the southern oscillation. Multiscale variability and global and regional Impacts. Cambridge University Press, pp. 207-295, 2001; Quinn and Neal, The historical record of El Niño events, Bradley and Jones (eds.), Climate since a.d. 1500, Routledges, pp. 623-648, 1992) and the temperature index of the Pacific Ocean (Mann ME et al., Global temperature patterns in past centuries: an interactive presentation, IGBP pages/world data center for paleoclimatology data contribution series #2000-075. NOAA/NGDC Paleoclimatology Program, Boulder CO, USA, 2000). Considering that the period 1904-2000, where 11 out of 16 floods occurred during El Niño events, it can be concluded that the proportion of years with exceptional flow volume in the Paraná River in years with El Niño events in the seventeenth and eighteenth centuries was relatively lower than that of the twentieth century. The reason for this difference is discussed. [ABSTRACT FROM AUTHOR]