Diversity of ENSO Events Unified by Convective Threshold Sea Surface Temperature: A Nonlinear ENSO Index

Williams, Ian N.; Patricola, Christina M.

doi:10.1029/2018gl079203

Cited by 88 publications

(110 citation statements)

References 55 publications

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“…By contrast, in the instrumental data, the Niño 3 region shows the strongest relationship with SWNA among the various tropical Pacific indices. The longitudinally dependent relationship between the tropical Pacific and SWNA supports the idea that the eastward extent of convection plays an important role in determining extratropical impacts of El Niño-Southern Oscillation events, and predetermined regional "boxes" (e.g., the Nino3 or Nino3.4 indices) may be insufficient to adequately represent the continuum of variability in the tropical Pacific (Williams & Patricola, 2018).…”

Section: Teleconnection Patterns During Wet and Dry Years In Swna In supporting

confidence: 64%

“…While the Niño3.4 index can broadly illustrate the state of the tropical Pacific during SWNA droughts, the previous analysis does not fully encompass potential impacts from other parts of the tropical Pacific or other ocean regions (e.g., McCabe et al, ; Seager et al, ; Ashok et al, ; Weng et al, ; Coats, Smerdon, et al, ; Coats et al, ; Williams & Patricola, ). Specifically, recent work has suggested that multiple remote factors, other than the tropical Pacific, may lead to persistent high pressure over the North Pacific and unusually dry conditions in SWNA (e.g., Teng & Branstator, ; Swain et al, ).…”

Section: Resultsmentioning

confidence: 99%

“…We also compare the Niño3.4 index to the TNA (5-24°N, 58-15°W) as well as a central Pacific El Niño index. There are multiple El Niño definitions that can produce different associated index time series (e.g., Ashok et al, 2007;Ren & Jin, 2011;Takahashi et al, 2011;Trenberth & Stepaniak, 2001;Williams & Patricola, 2018;Yeh et al, 2009). Here we use the Niño3.4 index and the El Niño Modoki Index (EMI), as the EMI captures the second leading pattern of equatorial Pacific SST anomalies (e.g., Ashok et al, 2007;Ren & Jin, 2011).…”

Section: Climate Model Datamentioning

confidence: 99%

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Ocean‐Atmosphere Trajectories of Extended Drought in Southwestern North America

Parsons

Coats

2019

JGR Atmospheres

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Multiyear droughts are a common occurrence in southwestern North America (SWNA), but it is unclear what causes these persistent dry periods. The ocean‐atmosphere conditions coinciding with droughts have traditionally been studied using correlation and composite methods, which suggest that cool conditions in the tropical Pacific are associated with SWNA droughts and warm conditions are associated with wet periods in SWNA. Nevertheless, the extent to which multiyear droughts are truly consistent with this paradigm remains unknown. This is, in part, because the temporal trajectory of ocean‐atmosphere conditions during these dry periods have not been sufficiently characterized. Here we examine the continuum of ocean‐atmosphere trajectories before, during, and after multiyear droughts in SWNA using observation‐based data and an ensemble of climate model simulations from the Community Earth System Model. An examination of sea surface temperature patterns at the beginning, middle, and end of SWNA droughts shows that an El Niño event tends to precede SWNA droughts, a cool tropical Pacific occurs during droughts, and central Pacific El Niño events end droughts. However, moderate El Niño events can occur in the middle of persistent droughts, so a warm tropical Pacific does not always end these dry periods. These findings are important for drought predictability and emphasize the need to improve simulations of the magnitude, life cycle, and frequency of occurrence of El Niño events.

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Section: Teleconnection Patterns During Wet and Dry Years In Swna In supporting

confidence: 64%

Section: Resultsmentioning

confidence: 99%

Section: Climate Model Datamentioning

confidence: 99%

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Ocean‐Atmosphere Trajectories of Extended Drought in Southwestern North America

Parsons

Coats

2019

JGR Atmospheres

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“…), and the resultant patterns can be dependent on the technique employed. A tailor-made climate index was developed for this study, largely due to a desire to preserve nonlinearity in the climate system and retain more information than off-the-shelf univariate indices provide (Williams & Patricola, 2018). The technique employed is a WT-based framework which has been used to explore climate variability in many of the physical processes relevant to coastal erosion and flooding extremes (e.g., .…”

Section: A1 Weather-type Classifications and Chronologymentioning

confidence: 99%

Time‐Varying Emulator for Short and Long‐Term Analysis of Coastal Flood Hazard Potential

et al. 2019

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Rising seas coupled with ever increasing coastal populations present the potential for significant social and economic loss in the 21st century. Relatively short records of the full multidimensional space contributing to total water level coastal flooding events (astronomic tides, sea level anomalies, storm surges, wave run-up, etc.) result in historical observations of only a small fraction of the possible range of conditions that could produce severe flooding. The Time-varying Emulator for Short-and Long-Term analysis of coastal flood hazard potential is presented here as a methodology capable of producing new iterations of the sea-state parameters associated with the present-day Pacific Ocean climate to simulate many synthetic extreme compound events. The emulator utilizes weather typing of fundamental climate drivers (sea surface temperatures, sea level pressures, etc.) to reduce complexity and produces new daily synoptic weather chronologies with an auto-regressive logistic model accounting for conditional dependencies on the El Niño Southern Oscillation, the Madden-Julian Oscillation, seasonality, and the prior two days of weather progression. Joint probabilities of sea-state parameters unique to simulated weather patterns are used to create new time series of the hypothetical components contributing to synthetic total water levels (swells from multiple directions coupled with water levels due to wind setup, temperature anomalies, and tides). The Time-varying Emulator for Short-and Long-Term analysis of coastal flood hazard potential reveals the importance of considering the multivariate nature of extreme coastal flooding, while progressing the ability to incorporate large-scale climate variability into site specific studies assessing hazards within the context of predicted climate change in the 21st century.Plain Language Summary Predicting extreme coastal flooding is a present-day societal need and will only become more relevant as mean water levels increase due to sea level rise. However, the number of processes contributing to such events is too high for relatively short observational records to have measured all of the constructive combinations of waves, surge, wind, and sea level anomalies. We present a framework designed to create hypothetical combinations of relevant flood hazard potential processes by simulating the climate and weather patterns that drive coastal flooding. Including large-scale oceanic and atmospheric patterns as the drivers of coastal hazards reveals the climate a coastal community is most vulnerable to, which will be increasingly more important to understand as the climate changes during the 21st century.

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“…Johnson and Xie et al (2010) used this property to explain that the "threshold" for deep atmospheric convection will increase at the same rate as the tropical mean SST in response to anthropogenic climate change. RSST has to date mostly been used in the global warming context, for instance, to understand the spatial patterns of changes in tropical cyclones (as aforementioned), in the hydrological cycle (e.g., Xie et al, 2010), and to define ENSO events (Williams & Patricola, 2018) and their convective signature (Johnson & Kosaka, 2016) in a warming world. RSST also allows isolating the ENSO and IOD signals in the context of global cooling induced by tropical explosive volcanic eruptions (Izumo et al, 2018;Khodri et al, 2017).…”

Section: 1029/2019gl086182mentioning

confidence: 99%

Relevance of Relative Sea Surface Temperature for Tropical Rainfall Interannual Variability

Izumo

Vialard

Lengaigne

et al. 2020

Geophysical Research Letters

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The coupling between sea surface temperature (SST) anomalies and rainfall is an important driver of tropical climate variability. Observations however reveal inconsistencies, such as decreased convective rainfall in regions with positive SST anomalies in the tropical Indian and Atlantic Oceans during and after El Niño–Southern Oscillation (ENSO) events. The upper troposphere warms during El Niño events, stabilizing the atmosphere. SST anomalies only account for the influence of the surface. Using theoretical arguments, we show that relative SST (RSST; defined as SST minus its tropical mean) anomalies, by also accounting for the influence of upper tropospheric temperature anomalies on gross moist stability, explain tropical convection interannual variations better than SST anomalies in observations and climate models. This relation further improves when RSST anomalies are weighted by the precipitation climatology to account for low and high‐precipitation regimes. Using RSST is thus essential to understand El Niño–Southern Oscillation teleconnections and interactions between modes of tropical climate variability.

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Diversity of ENSO Events Unified by Convective Threshold Sea Surface Temperature: A Nonlinear ENSO Index

Cited by 88 publications

References 55 publications

Ocean‐Atmosphere Trajectories of Extended Drought in Southwestern North America

Ocean‐Atmosphere Trajectories of Extended Drought in Southwestern North America

Time‐Varying Emulator for Short and Long‐Term Analysis of Coastal Flood Hazard Potential

Relevance of Relative Sea Surface Temperature for Tropical Rainfall Interannual Variability

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