The North American Multi‐Model Ensemble (NMME) has become integral scientific infrastructure in subseasonal and seasonal climate prediction, advancing applied prediction and scientific understanding ...of the mechanisms and predictability of short‐term climate. The NMME was designed to evolve as old models were retired and new models joined the ensemble. This study examines the assumption that prediction skill will increase as the system evolves, focusing on 2 m temperature, precipitation rate, and sea surface temperature prediction. The common period of 1982–2010 is studied for four configurations of the NMME, approximately representing the operational model suites of 2011, 2012, 2014–2018, and 2019–present. Substantial improvement in temperature prediction over both land and ocean is observed, with little change in global precipitation prediction. Sea surface temperature prediction at longer leads has improved over much of the globe, with the notable exception of the central‐eastern tropical Pacific, where prediction skill has declined.
Plain Language Summary
Predicting the climate more than a few weeks in advance requires forecasters to bet on more than one computer model, similar to the method of diversifying an investment portfolio. Many earlier studies have shown that the combination of predictions generated by different computer models, known as a multi‐model ensemble, almost always achieves better forecast skill than using a single model alone. The North American Multi‐Model Ensemble (NMME), a subseasonal and seasonal prediction system combining individual North American state‐of‐the‐art climate prediction models, has become an integral part of subseasonal and seasonal research and applications. The NMME has continually evolved, as newer models replace older ones; it is assumed that this evolution will produce more skillful predictions over time. But, until now, this assumption has not been tested. We examine the skill of NMME predictions in four different model combinations, including the oldest configuration, two transitional suites, and the operational configuration as of early 2020. Temperature prediction over both land and ocean has improved noticeably through the exchange of older models for newer ones, but precipitation prediction has not substantially improved. Overcoming the difficulty in precipitation prediction may require higher‐resolution climate models in the NMME.
Key Points
NMME seasonal temperature prediction has improved as new models have replaced old ones
Both land and ocean temperature prediction have improved at short and longer leads over most of the globe with newer model combinations
Precipitation prediction has not noticeably improved
There is a continually increasing demand for near‐term (i.e., lead times up to a couple of decades) climate information. This demand is partly driven by the need to have robust forecasts and is ...partly driven by the need to assess how much of the ongoing climate change is due to natural variability and how much is due to anthropogenic increases in greenhouse gases or other external factors. Here we discuss results from a set of state‐of‐the‐art climate model experiments in comparison with observational estimates that show that an assessment of predictability requires models that capture the variability of major oceanic fronts, which are, at best, poorly resolved and may even be absent in the near‐term prediction of Intergovernmental Panel on Climate Change class models. This is the first time that air‐sea interactions associated with resolved Gulf Stream sea surface temperature have been identified in the context of a state‐of‐the‐art global coupled climate model with inferred near‐term predictability.
Key Points
Ocean dynamics play a key role in decadal climate variability once air‐sea interactions associated with ocean fronts and eddies are resolved
IPCC class climate models have limited ability to capture decadal variability in the North Atlantic due to relatively low ocean resolution
This study examines how semi‐stochastic Westerly Wind Bursts (WWBs) affect El Niño Southern Oscillation (ENSO) predictability. An ensemble ENSO prediction experiment is presented in which the ...Community Climate System Model version 3 (CCSM3) and CCSM3 with a state‐dependent WWB parameterization are used as both “truth” and as predictor systems. Inclusion of WWBs has little effect on ENSO predictability if the “truth” lacks WWBs. If the “truth” includes WWBs, the limit of ENSO predictability is larger for a forecast system that captures the correct statistics of WWBs. Predictability drops considerably if a forecast system that lacks WWB events is used to predict a “truth” that includes WWBs. At longer lead times, predictability is more dependent on the dynamical properties of the truth; that is, the importance of capturing the WWB statistics becomes less important and the statistics (e.g., signal‐to‐noise ratio) of the truth determine the limit of predictability. At short leads, ENSO predictability depends on the prediction system and the “truth.” ENSO prediction skill is model and phase dependent. Predictability of extreme warm events remains a challenge as the number of ensemble members required to capture these events is on the order of 100 members. Finally, we examine real ENSO predictions with and without the WWB parameterization. It is found that including WWBs in the prediction system significantly increases ENSO prediction skill compared with a prediction system that lacks WWBs. Also, it is found that the so‐called forecast spring prediction barrier is, at least partially, caused by the lack of WWB representation in the forecast system.
Key Points
ENSO predictability is analyzedThe limit of ENSO predictability increases if the forecast system includes WWBsSpring prediction barrier is caused by the lack of WWBs in forecast systems
Although modeling and observational studies have highlighted a robust relationship between the Pacific meridional mode (PMM) and El Niño–Southern Oscillation (ENSO)—namely, that the PMM is often a ...precursor to El Niño events—it remains unclear if this relationship has any real predictive use. Bridging the gap between theory and practical application is essential, because the potential use of the PMM precursor as a supplemental tool for ENSO prediction has been implied but not yet implemented into a realistic forecast setting. In this paper, a suite of sea surface temperature hindcasts is utilized from the North American Multimodel Ensemble (NMME) prediction experiment between 1982 and 2010. The goal is first to assess the NMME’s ability to forecast the PMM precursor and second to examine the relationship between PMM and ENSO within a forecast framework. In terms of model performance, results are optimistic in that not only is PMM variability captured well by the multimodel ensemble mean, but it also appears as a precursor to ENSO events in the NMME. In forecast mode, positive PMM events predict eastern Pacific El Niño events in both observations and model forecasts with some skill, yet with less skill for central Pacific El Niño events. Conversely, negative PMM events poorly predict La Niña events in observations, yet the model forecasts fail to capture this observed representation. There proves to be considerable opportunity for improvement of the PMM–ENSO relationship in the forecast models; accordingly, the predictive use of PMM for certain types of ENSO events may also see improvement.
Simple dynamical models are used to understand fundamental processes of how ENSO modulates subseasonal teleconnections associated with tropical imprints of the MJO by stripping away complex ...phenomena. Both a dry linear baroclinic model and a dry nonlinear baroclinic model are employed to (1) assess how much of the MJO teleconnection pattern in a particular ENSO phase can be captured by linear and nonlinear dynamics and (2) analyze the role of the ENSO-modulated MJO forcing and base state in reproducing the teleconnection patterns. The modeling experiments reveal that linear dynamics are sufficient in capturing differences between the Northern Hemisphere teleconnections associated with the MJO during El Niño and La Niña. Nonlinear dynamics modestly capture more of the Northern Hemisphere MJO teleconnection pattern, particularly over North America, suggesting the teleconnection response over North America is more complex. The teleconnection patterns are sensitive to changes in both the ENSO background state and the domain of the monthly MJO-associated forcing. A Rossby wave source diagnosis is applied to further understand the underlying mechanisms. Further, a series of experiments swapping MJO forcings during El Niño events versus La Niña events with an ENSO-neutral base state and vice versa show that the MJO forcing has a larger influence over the teleconnection pattern than the base state. Therefore, the modulation of the MJO convection by ENSO dominates the ENSO-phase-dependent changes to the Northern Hemisphere teleconnection pattern. These modeling experiments highlight that MJO teleconnections must be considered in the context of the ongoing ENSO event.
Seasonal forecasts of summer continental United States (CONUS) rainfall have relatively low skill, partly due to a lack of consensus about its sources of predictability. The East Asian monsoon (EAM) ...can excite a cross-Pacific Rossby wave train, also known as the Asia–North America (ANA) teleconnection. In this study, we analyze the ANA teleconnection in observations and model simulations from the Community Atmospheric Model, version 5 (CAM5), comparing experiments with prescribed climatological SSTs and prescribed observed SSTs. Observations indicate a statistically significant relationship between a strong EAM and increased probability of positive precipitation anomalies over the US west coast and the Plains-Midwest. The ANA teleconnection and CONUS rainfall patterns are improved in the CAM5 experiment with prescribed observed SSTs, suggesting that SST variability is necessary to simulate this teleconnection over CONUS. We find distinct ANA patterns between ENSO phases, with the La Niña-related patterns in CAM5 disagreeing with observations. Using linear steady-state quasi-geostrophic theory, we conclude that incorrect EAM forcing location greatly contributed to CAM5 biases, and jet stream disparities explained the ENSO-related biases. Finally, we compared EAM forcing experiments with different mean states using a simple dry nonlinear atmospheric general circulation model. Overall, the ANA pattern over CONUS and its modulation by ENSO forcing are well described by dry dynamics on seasonal-to-interannual timescales, including the constructive (destructive) interference between El Niño (La Niña) modulation and the ANA patterns over CONUS.
Sea level rise (SLR) imposes an increasing flooding hazard on low-lying coastal communities due to higher exposure to high-tide conditions and storm surge. Additional coastal flooding hazard arises ...due to reduced effectiveness of gravity-based drainage systems to drain rainwater during heavy rain events. Over the past decade, several coastal communities along the US Atlantic coast have experienced an increasing rate of flooding events. In this study, we focus on the increasing flooding hazard in Miami Beach, Florida, which has caused severe property damage and significant disruptions to daily life. We evaluate the flooding frequency and its causes by analyzing tide and rain gauge records, media reports, insurance claims, and photo records from Miami Beach acquired during 1998–2013. Our analysis indicates that significant changes in flooding frequency occurred after 2006, in which rain-induced events increased by 33% and tide-induced events increased by more than 400%. We also analyzed tide gauge records from Southeast Florida and detected a decadal-scale accelerating rates of SLR. The average pre-2006 rate is 3 ± 2 mm/yr, similar to the global long-term rate of SLR, whereas after 2006 the average rate of SLR in Southeast Florida rose to 9 ± 4 mm/yr. Our results suggest that engineering solutions to SLR should rely on regional SLR rate projections and not only on the commonly used global SLR projections.
•Flooding frequency in Miami Beach increased significantly since 2006, mostly due to high tide events.•The average rate of sea level rise in Southeast Florida increased from 3 ± 2 mm/yr prior to 2006 to 9 ± 4 mm/yr after 2006.•Increasing sea level in the Miami area correlates with weakening of the entire Gulf Stream system (decrease in kinetic energy).•Engineering solutions to SLR should rely on regional sea level rise rate projections and not only on the commonly used global SLR projections.
This study investigates El Niño precursors in a high‐resolution version of CCSM3.5. First, using an Empirical Orthogonal Function analysis of all non‐ENSO tropical Pacific variability, we find that ...the Pacific Meridional Mode (PMM) acts as an ENSO trigger 7–9 months prior to large El Niño events in the model, which is consistent with previous model and observational studies. However, because not every PMM event triggers an ENSO event, we also find that PMM appears to be an effective trigger when the western‐to‐central Pacific is preconditioned (i.e., anomalously high sea surface heights or heat content). Second, this study looks at the contribution of western Pacific variability, namely westerly wind bursts (WWBs), as well as all other non‐ENSO variability in the tropical Pacific. We find that the relative importance of low‐frequency climate variability associated with PMM dominates over other non‐ENSO variability between 15°N and 15°S, including high‐frequency atmospheric variability and WWBs, in acting as a precursor to El Niño events.
Key Points
The dominant non‐ENSO variability in the tropical Pacific is PMM in a model
PMM is an effective ENSO trigger when the equatorial Pacific is preconditioned
Low frequency climate variability is the most important for the ENSO precursor
The relative influence of El Niño Southern Oscillation (ENSO) forced response versus internally generated atmospheric variability or noise on the upper tropospheric Pacific North American circulation ...is investigated. The analysis is performed on the boreal winter (December–January–February) 200 hPa circulation and the associated precipitation based on observational records and modeling experiments. The model experiment includes an ocean eddy-resolving coupled general circulation model (CGCM) and an atmospheric noise reduced ocean eddy-resolving CGCM. The noise reduction technique is the interactive ensemble approach, adopted to reduce the effects of internal atmospheric dynamics noise at the air-sea interface. Tropical rainfall anomalies associated with ENSO forces a teleconnection pattern that is a combination of the so-called Pacific North American (PNA) pattern, themed here as state-dependent atmospheric noise, and a pattern distinct from the PNA, themed here as ENSO-signal. The ENSO signal has a meridional structure in the streamfunction associated with significant poleward Rossby wave flux emanating from the eastern Pacific. Conversely, the PNA teleconnection pattern is zonally oriented, with most of the wave flux in the zonal direction from the Pacific towards North America. The mid-latitude ENSO forced response is asymmetric between warm and cold events. This asymmetry is strongly dependent on the amplitude of atmospheric noise. It is shown that the ENSO forced response is masked by atmospheric noise, with the latter being 3–10 times larger in amplitude. We show that the PNA pattern was positive during the 2015–2016 boreal winter and prevented the large 2015–2016 El Niño event from alleviating the persistent drought in the western US.
El Niño in a changing climate Yeh, Sang-Wook; Kug, Jong-Seong; Dewitte, Boris ...
Nature (London),
09/2009, Volume:
461, Issue:
7263
Journal Article
Peer reviewed
El Niño events, characterized by anomalous warming in the eastern equatorial Pacific Ocean, have global climatic teleconnections and are the most dominant feature of cyclic climate variability on ...subdecadal timescales. Understanding changes in the frequency or characteristics of El Niño events in a changing climate is therefore of broad scientific and socioeconomic interest. Recent studies show that the canonical El Niño has become less frequent and that a different kind of El Niño has become more common during the late twentieth century, in which warm sea surface temperatures (SSTs) in the central Pacific are flanked on the east and west by cooler SSTs. This type of El Niño, termed the central Pacific El Niño (CP-El Niño; also termed the dateline El Niño, El Niño Modoki or warm pool El Niño), differs from the canonical eastern Pacific El Niño (EP-El Niño) in both the location of maximum SST anomalies and tropical-midlatitude teleconnections. Here we show changes in the ratio of CP-El Niño to EP-El Niño under projected global warming scenarios from the Coupled Model Intercomparison Project phase 3 multi-model data set. Using calculations based on historical El Niño indices, we find that projections of anthropogenic climate change are associated with an increased frequency of the CP-El Niño compared to the EP-El Niño. When restricted to the six climate models with the best representation of the twentieth-century ratio of CP-El Niño to EP-El Niño, the occurrence ratio of CP-El Niño/EP-El Niño is projected to increase as much as five times under global warming. The change is related to a flattening of the thermocline in the equatorial Pacific.
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