scholarly journals Predictable and Unpredictable Aspects of U.S. West Coast Rainfall and El Niño: Understanding the 2015/16 Event

2019 ◽  
Vol 32 (10) ◽  
pp. 2843-2868 ◽  
Author(s):  
Benjamin A. Cash ◽  
Natalie J. Burls

AbstractCalifornia experienced record-setting drought from 2012 to 2017. Based on both seasonal forecast models and historical associations, there was widespread expectation that the major El Niño event of 2015/16 would result in increased winter-season precipitation and break the drought. However, the 2015/16 winter rainy season ultimately resulted in slightly below-average precipitation and the drought continued. In this work we analyze data from both observations and seasonal forecasts made as part of the North American Multi-Model Ensemble (NMME) to better understand the general relationship between El Niño and U.S. West Coast rainfall, focusing on Southern California (SOCAL) rainfall, Pacific Northwest (PNW) rainfall, and the 2015/16 event. We find that while there is a statistically significant positive correlation between El Niño events and the SOCAL and PNW rainfall anomalies, this relationship explains at most one-third of the observed variance. Examination of hindcasts from the NMME demonstrates that the models are capable of accurately reproducing this observed correlation between tropical Pacific sea surface temperatures and California rainfall when information from the individual ensemble members is retained. However, focusing on the multimodel ensemble mean, which deliberately reduces the influence of unpredicted variability, drastically overestimates the strength of this relationship. Our analysis demonstrates that much of the winter rainfall variability along the U.S. West Coast is dominated by unpredicted variations in the 200-hPa height field and that this same unpredicted variability was largely responsible for the unexpectedly dry conditions in 2015/16.

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 886
Author(s):  
Abdul Azim Amirudin ◽  
Ester Salimun ◽  
Fredolin Tangang ◽  
Liew Juneng ◽  
Muhamad Zuhairi

This study investigates the individual and combined impacts of El Niño and the positive Indian Ocean Dipole (IOD) on the Southeast Asia (SEA) rainfall variability. Using composite and partial correlation techniques, it is shown that both inter-annual events have individually distinct impacts on the SEA rainfall anomaly distribution. The results showed that the impacts of the co-occurrence of El Niño and IOD events are significant compared to the individual effects of pure El Niño or pure IOD. During June-July-August and September-October-November, the individual impacts of the pure El Niño and IOD events are similar but less significant. Both events caused negative impacts over the southern part of SEA during June-July-August (JJA) and propagated northeastward/eastward during September-October-November (SON). Thus, there are significant negative impacts over the southern part of SEA during the co-occurrence of both events. The differential impacts on the anomalous rainfall patterns are due to the changes in the sea surface temperature (SST) surrounding the region. Additionally, the differences are also related to the anomalous regional atmospheric circulations that interact with the regional SST. The anomalous Walker circulation that connects the Indian Ocean and tropical Pacific Ocean also plays a significant role in determining the regional anomalous rainfall patterns.


2006 ◽  
Vol 19 (21) ◽  
pp. 5624-5636 ◽  
Author(s):  
Lisa Goddard ◽  
Arun Kumar ◽  
Martin P. Hoerling ◽  
Anthony G. Barnston

Abstract The eastern United States experienced an unusually cold winter season during the 2002/03 El Niño event. The U.S. seasonal forecasts did not suggest an enhanced likelihood for below-normal temperatures over the eastern United States in that season. A postmortem analysis examining the observed temperatures and the associated forecast is motivated by two fundamental questions: what are these temperature anomalies attributable to, and to what extent were these temperature anomalies predictable? The results suggest that the extreme seasonal temperatures experienced in the eastern United States during December–February (DJF) 2002/03 can be attributed to a combination of several constructively interfering factors that include El Niño conditions in the tropical Pacific, a persistent positive Pacific–North American (PNA) mode, a persistent negative North Atlantic Oscillation (NAO) mode, and persistent snow cover over the northeastern United States. According to the simulations and predictions from several dynamical atmospheric models, which were not rigorously included in the U.S. forecast, much of the observed temperature pattern was potentially predictable.


2020 ◽  
Vol 148 (5) ◽  
pp. 1861-1875
Author(s):  
Andrew W. Robertson ◽  
Nicolas Vigaud ◽  
Jing Yuan ◽  
Michael K. Tippett

Abstract Large-scale atmospheric circulation regime structures are used to diagnose subseasonal forecasts of wintertime geopotential height fields over the North American sector, from the NCEP CFSv2 model. Four large-scale daily circulation regimes derived from reanalysis 500-hPa geopotential height data using K-means clustering are used as a low-dimensional basis for diagnosing the model’s forecasts up to 45 days ahead. On average, hindcast skill in regime space is found to be limited to 10–15 days ahead, in terms of anomaly correlation of 5-day averages of regime counts, over the 1999–2010 period. However, skill up to 30 days ahead is identified in individual winters, and intraseasonal episodes of high skill are identified using a forecast-evolution graphical tool. A striking vacillation between the West Coast and Pacific ridge patterns during December–January 2008/09 is shown to be predicted 20–25 days in advance, illustrating the possibility to identify “forecasts of opportunity” when subseasonal forecast skill is much higher than the average. The forecast-evolution tool also provides insight into the poor seasonal forecasts of California precipitation by operational centers during the 2015/16 El Niño winter. The Pacific trough regime is shown to be greatly overpredicted beyond 1–2 weeks in advance during the 2015/16 winter, with weather-scale features dominating the forecast evolution at shorter lead times. A similar though less extreme situation took place during the weaker El Niño of 2009/10, with the Pacific trough overforecast at S2S lead times.


2010 ◽  
Vol 23 (11) ◽  
pp. 2902-2915 ◽  
Author(s):  
Xuebin Zhang ◽  
Jiafeng Wang ◽  
Francis W. Zwiers ◽  
Pavel Ya Groisman

Abstract The generalized extreme value (GEV) distribution is fitted to winter season daily maximum precipitation over North America, with indices representing El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the North Atlantic Oscillation (NAO) as predictors. It was found that ENSO and PDO have spatially consistent and statistically significant influences on extreme precipitation, while the influence of NAO is regional and is not field significant. The spatial pattern of extreme precipitation response to large-scale climate variability is similar to that of total precipitation but somewhat weaker in terms of statistical significance. An El Niño condition or high phase of PDO corresponds to a substantially increased likelihood of extreme precipitation over a vast region of southern North America but a decreased likelihood of extreme precipitation in the north, especially in the Great Plains and Canadian prairies and the Great Lakes/Ohio River valley.


2021 ◽  
Author(s):  
Erik W Kolstad ◽  
David MacLeod

Abstract The East African ‘short rains’ in October–December (OND) exhibit large interannual variability. Drought and flooding are not unusual, and long-range rainfall forecasts can guide planning and preparedness. Although seasonal forecasts based on dynamical models are making inroads, statistical models based on sea surface temperature (SST) precursors are still widely used. It is important to better understand the sources of skill of statistical models and why they sometimes fail. Here, we define a linear regression model, where the August states of El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) predict about 40% of the short rains variability in 1950–2020. The forecast errors are traced back to the initial SSTs: toowet (too-dry) forecasts are linked linearly to positive (negative) initial ENSO and IOD states in August. The link to the initial IOD state is mediated by IOD between August and OND, highlighting a physical mechanism for prediction busts. We also identify asymmetry and nonlinearity: when ENSO and/or the IOD are positive in August, the range and variance of OND forecast errors are larger than when the SST indices are negative. Upfront adjustments of predictions conditional on initial SSTs would have helped in some years with large forecast busts, such as the dry 1987 season during a major El Niño, for which the model erroneously predicts copious rainfall, but it would have exacerbated the forecast performance in the wet 2019 season, when the IOD was strongly positive and the model predicts too-dry conditions.


2017 ◽  
Vol 18 (1) ◽  
pp. 177-186 ◽  
Author(s):  
N. Wanders ◽  
A. Bachas ◽  
X. G. He ◽  
H. Huang ◽  
A. Koppa ◽  
...  

Abstract Dry conditions in 2013–16 in much of the western United States were responsible for severe drought and led to an exceptional fire season in the Pacific Northwest in 2015. Winter 2015/16 was forecasted to relieve drought in the southern portion of the region as a result of increased precipitation due to a very strong El Niño signal. A student forecasting challenge is summarized in which forecasts of winter hydroclimate across the western United States were made on 1 January 2016 for the winter hydroclimate using several dynamical and statistical forecast methods. They show that the precipitation forecasts had a large spread and none were skillful, while anomalously high observed temperatures were forecasted with a higher skill and precision. The poor forecast performance, particularly for precipitation, is traceable to high uncertainty in the North American Multi-Model Ensemble (NMME) forecast, which appears to be related to the inability of the models to predict an atmospheric blocking pattern over the region. It is found that strong El Niño sensitivities in dynamical models resulted in an overprediction of precipitation in the southern part of the domain. The results suggest the need for a more detailed attribution study of the anomalous meteorological patterns of the 2015/16 El Niño event compared to previous major events.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Wenjun Zhang ◽  
Feng Jiang ◽  
Malte F. Stuecker ◽  
Fei-Fei Jin ◽  
Axel Timmermann

AbstractThe El Niño-Southern Oscillation (ENSO), the primary driver of year-to-year global climate variability, is known to influence the North Tropical Atlantic (NTA) sea surface temperature (SST), especially during boreal spring season. Focusing on statistical lead-lag relationships, previous studies have proposed that interannual NTA SST variability can also feed back on ENSO in a predictable manner. However, these studies did not properly account for ENSO’s autocorrelation and the fact that the SST in the Atlantic and Pacific, as well as their interaction are seasonally modulated. This can lead to misinterpretations of causality and the spurious identification of Atlantic precursors for ENSO. Revisiting this issue under consideration of seasonality, time-varying ENSO frequency, and greenhouse warming, we demonstrate that the cross-correlation characteristics between NTA SST and ENSO, are consistent with a one-way Pacific to Atlantic forcing, even though the interpretation of lead-lag relationships may suggest otherwise.


2021 ◽  
Vol 9 (4) ◽  
pp. 377
Author(s):  
Dong Eun Lee ◽  
Jaehee Kim ◽  
Yujin Heo ◽  
Hyunjin Kang ◽  
Eun Young Lee

The impact of climatic variability in atmospheric conditions on coastal environments accompanies adjustments in both the frequency and intensity of coastal storm surge events. The top winter season daily maximum sea level height events at 20 tidal stations around South Korea were examined to assess such impact of winter extratropical cyclone variability. As the investigation focusses on the most extreme sea level events, the impact of climate change is found to be invisible. It is revealed that the measures of extreme sea level events—frequency and intensity—do not correlate with the local sea surface temperature anomalies. Meanwhile, the frequency of winter extreme events exhibits a clear association with the concurrent climatic indices. It was determined that the annual frequency of the all-time top 5% winter daily maximum sea level events significantly and positively correlates with the NINO3.4 and Pacific Decadal Oscillation (PDO) indices at the majority of the 20 tidal stations. Hence, this indicates an increase in extreme event frequency and intensity, despite localized temperature cooling. This contradicts the expectation of increases in local extreme sea level events due to thermal expansion and global climate change. During El Nino, it is suggested that northward shifts of winter storm tracks associated with El Nino occur, disturbing the sea level around Korea more often. The current dominance of interannual storm track shifts, due to climate variability, over the impact of slow rise on the winter extreme sea level events, implies that coastal extreme sea level events will change through changes in the mechanical drivers rather than thermal expansion. The major storm tracks are predicted to continue shifting northward. The winter extreme sea level events in the midlatitude coastal region might not go through a monotonic change. They are expected to occur more often and more intensively in the near future, but might not continue doing so when northward shifting storm tracks move away from the marginal seas around Korea, as is predicted by the end of the century.


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