Observing and Predicting the 2015/16 El Niño

Michelle L. L'Heureux, Ken Takahashi, Andrew B. Watkins, Anthony G. Barnston, Emily J. Becker, Tom E. Di Liberto, Felicity Gamble, Jon Gottschalck, Michael S. Halpert, Boyin Huang, Kobi Mosquera-Vásquez, Andrew T. Wittenberg
2017 Bulletin of The American Meteorological Society - (BAMS)  
The El Niño of 2015-16 was among the strongest El Niño events observed since 1950, and took place almost two decades after the previous major event in 1997-98. Here, perspectives of the event are shared by scientists from three national meteorological or climate services that issue regular operational updates on the status and prediction of the El Niño-Southern Oscillation (ENSO). Public advisories on the unfolding El Niño were issued in the first half of 2015. This was followed by significant
more » ... wed by significant growth in sea surface temperature (SST) anomalies, a peak during November 2015 -January 2016, subsequent decay, and its demise during May 2016. The lifecycle and magnitude of the 2015-16 El Niño was well predicted by most models used by national meteorological services, in contrast to the generally over-exuberant model predictions made the previous year. The evolution of multiple atmospheric and oceanic measures demonstrates the rich complexity of ENSO, as a coupled ocean-atmosphere phenomenon with pronounced global impacts. While some aspects of the 2015-16 El Niño rivaled the events of 1982-83 and 1997-98, we show that it also differed in unique and important ways, with implications for the study and evaluation of past and future ENSO events. Unlike previous major El Niños, remarkably above-average SST anomalies occurred in the western and central equatorial Pacific, but were milder near the coast of South America. While operational ENSO systems have progressed markedly over the past several decades, the 2015-16 El Niño highlights several challenges that will continue to test both the research and operational forecast communities. CAPSULE SUMMARY: The El Niño of 2015-16 rivaled the major El Niño events of 1982-83 55 and 1997-98, showcasing advancements in operational observing and prediction systems, while 56 offering challenges for the future. 57 1. Introduction 58 The 2015-16 El Niño was likely the most widely anticipated El Niño-Southern Oscillation 59 (ENSO) event ever, and it was preceded by nearly four decades of advancements in observing 60 and prediction systems. Unlike the previous major El Niño event of 1997-98 (e.g., McPhaden 61 1999), the most recent El Niño was embedded within the fabric of the Internet and social media, 62 with arguably more frequent updates and pathways to convey information than ever before. By 63 mid-2015, operational forecast centers around the world were nearly unanimous: El Niño was 64 very likely to be strong, with the potential of rivaling previous major El Niño events in 1982-83 65 and 1997-98. Given the widespread coverage of these ENSO outlooks and the comparisons made 66 to other similarly strong El Niño events, there was considerable concern about significant global 67 impacts. While the El Niño phenomenon itself was well predicted in 2015-16, climate impacts 68 near El Niño's peak matched historical patterns in some areas (e.g., Ropelewski and Halpert 1987; 69 Halpert and Ropelewski 1992), but in other regions, additional climate factors clearly played a 70 role. 71 Because the ENSO cycle, with its warm (El Niño) and cool (La Niña) phases, is a leading source 72 of seasonal climate variability and predictability, it is closely monitored by many national and in-73 ternational organizations. The authorship on this paper is composed of individuals associated with 74 three national-level assessments on ENSO from the National Oceanic and Atmospheric Adminis-75 tration (NOAA) in the United States, the Bureau of Meteorology (BoM) in Australia, and one of 76 the agencies that comprises the Multisectoral Committee of the National Study of El Niño (EN-77 3 FEN) in Peru. All provide operational, or regularly updated, ENSO assessments, in part because 78 these countries are known to have climates -and indeed economies and societies -significantly 79 influenced by ENSO. These three agencies also happen to be geographically complementary, span-80 ning the Pacific Ocean basin. They go beyond the automatic generation of observational and model 81 output to provide summary level information of the progress of ENSO and its forecast, which is 82 aimed at a diverse set of users among the general public, whose knowledge ranges from technically 83 savvy to novice. 84 ENSO is a sprawling and multi-faceted coupled ocean-atmosphere climate phenomenon that 85 affects every country in a different manner. Table 1 summarizes the current El Niño definitions and 86 watch/alert/warning systems in association with the national-level ENSO updates. As in past years, 87 the timing of El Niño status updates and declarations varied during 2015-16 due to differences in 88 datasets and ENSO criteria and thresholds, which are governed by differing regional impacts. For 89 example, Peru issues forecasts for a "coastal El Niño" because the amount of coastal rainfall they 90 receive is very sensitive to how warm sea surface temperatures (SST) adjacent to South America 91 become (e.g., Takahashi 2004). Ultimately, though, every agency examines a broad range of 92 oceanic and atmospheric anomalies to inform their updates. Internationally, the Niño-3.4 SST 93 region (thin red box in Fig. 6, in the east-central equatorial Pacific Ocean, is perhaps the most 94 common measure of ENSO because this region is strongly coupled with the overlying atmosphere 95 (e.g., Barnston et al. 1997) and to global teleconnections. This index also tends to be the focus of 96 operational model displays. 97 These operational updates have evolved over past decades due to lessons learned from previous 98 ENSO events and user demands placed on them. The 2015-16 El Niño not only showcased the 99 latest generation of ENSO climate services, but this knowledge was disseminated and interpreted 100 across a wide variety of media platforms, ranging from traditional mainstream outlets to social 101 4 media -a vastly different communication environment compared to the last major El Niño event 102 of 1997-98. This came with its own set of advantages, such as exposure to far broader audiences, 103 and disadvantages, such as the sometimes-questionable interpretation of datasets and forecast out-104 looks, which differed from official assessments. While the ENSO assessments and dissemination 105 processes vary by national agency, the following sections summarizes our collective experience in 106 tracking the observational evolution, verifying the model forecasts, and documenting the global 107 climate anomalies associated with the historic 2015-16 El Niño. 108 2. Datasets and Methods 109 Since the major El Niño of 1997-98, many observational reconstructions and reanalysis datasets 110 have been created or improved. Unlike station-based data or point "in situ" observations (e.g. a 111 buoy), these gridded datasets are complete both spatially and temporally and, for the statistical 112 reconstructions of SST, extend as far back as the late 1800s. Several operationally oriented centers 113 update datasets in near real-time, which allows scientists to monitor the tropical Pacific. Given 114 the interest in the 2015-16 El Niño and its potential impacts, these real-time datasets were popular 115 with users, many of whom were interested in the strength of the event and its ranking relative to 116 past El Niño events. 117 Complicating this assessment, however, each center relies on a set of core observational datasets 118 for its ENSO updates, so the exact values for a given variable (e.g. Niño-3.4 SST) will vary de-119 pending which dataset is examined. These differences between datasets primarily arise due to 120 structural reasons, such as the choice of the dynamical model or the statistical method used to 121 infill between available observations. The disparities are particularly evident across the tropical 122 Pacific Ocean, which contains large regions that are not covered by point measurements (e.g. 123 buoys, ships). Many centers additionally rely on datasets that ingest not only buoy or ship data, 124 5 but also satellite information. However, the modern satellite record began in the late 1970s, which 125 prevents the use of these datasets for historical rankings going further back in time. Moreover, 126 satellite estimates have biases (due to issues like varying equatorial crossing times), which need to 127 be corrected by in situ surface observations, and these corrections can vary over time and space as 128 new satellites are incorporated (e.g., Huang et al. 2015a). Some datasets like the NOAA Extended 129 Reconstructed SST (ERSST) opt to not include satellite information in order to preserve the con-130 sistency, or homogeneity, of the record. But, for purposes outside of historical comparisons and 131 to provide more real-time ENSO updates, these satellite-based datasets are strongly relied upon 132 both to get an overall sense of the ENSO evolution and as the initial conditions for many forecast 133 models. 134
doi:10.1175/bams-d-16-0009.1 fatcat:bbds5ltgf5fcxjjmavnckm5pme