Climate Variability and Teleconnections

Impacts of El Niño and La Niña to intensify as Climate warms

When an El Niño or its opposite, La Niña, forms in the future, it's likely to cause more intense impacts over many land regions — amplifying changes to temperature, precipitation, and wildfire risk — due to the warming climate. These are the findings of a new study led by J. Fasullo (NCAR) in collaboration with NCAR scientist B. Otto-Bliesner and S. Stevenson at UCSB.

The researchers found, for example, that the increased wildfire danger in the southwestern United States associated with La Niña events would become more acute. Conversely, the cooler and wetter weather in the same region associated with El Niño events would likely become even cooler and even wetter in the future, enhancing associated flood risks.

Fasullo, J.T., B.L. Otto-Bliesner and S. Stevenson, ENSO’s changing influence on temperature, precipitation, and wildfire in a warming climate, Geophys. Res. Lett., 2018


Uncertainty in ENSO teleconnections to the Northern Hemisphere

Application of random sampling techniques to composite differences between 18 El Niño and 14 La Niña events observed since 1920 reveals considerable uncertainty in both the pattern and amplitude of the Northern Hemisphere extratropical winter sea level pressure (SLP) response to ENSO. While the SLP responses over the North Pacific and North America are robust to sampling variability, their magnitudes can vary by a factor of 2; other regions, such as the Arctic, North Atlantic, and Europe are less robust in their SLP patterns, amplitudes, and statistical significance. The uncertainties on the observed ENSO composite are shown to arise mainly from atmospheric internal variability as opposed to ENSO diversity. These observational findings pose considerable challenges for the evaluation of ENSO teleconnections in models. An approach is proposed that incorporates both pattern and amplitude uncertainty in the observational target, allowing for discrimination between true model biases in the forced ENSO response and apparent model biases that arise from limited sampling of non-ENSO-related internal variability. Large initial-condition coupled model ensembles with realistic tropical Pacific sea surface temperature anomaly evolution during 1920–2013 show similar levels of uncertainty in their ENSO teleconnections as found in observations. Because the set of ENSO events in each of the model composites is the same (and identical to that in observations), these uncertainties are entirely attributable to sampling fluctuations arising from internal variability, which is shown to originate from atmospheric processes. The initial-condition model ensembles thus inform the interpretation of the single observed ENSO composite and vice versa.

Deser, C., I. R. Simpson, K. A. McKinnon and A. S. Phillips, 2017: The Northern Hemisphere extra-tropical atmospheric circulation response to ENSO: How well do we know it and how do we evaluate models accordingly? J. Climate, 30, 5059-5082, Doi: 10.1175/JCLI-D-16-0844.1
Deser, C., I. R. Simpson, A. S. Phillips and K. A. McKinnon, 2018: How well do we know ENSO's climate impacts over North America, and how do we evaluate models accordingly? J. Climate, 30, 4991-5014, Doi: 10.1175/JCLI-D-17-0783.1


Internal variability and regional climate trends in an Observational Large Ensemble

Recent observed climate trends result from a combination of external radiative forcing and internally-generated variability. In order to better contextualize these trends and forecast future ones, it is necessary to properly model the spatio-temporal properties of the internal variability. Here, a statistical model is developed for terrestrial temperature and precipitation, and global sea level pressure, based upon monthly gridded observational datasets that span 1921- 2014. The model is used to generate a synthetic ensemble, each member of which has a unique sequence of internal variability but with similar statistical properties as the observational record. This synthetic ensemble is combined with estimates of the externally-forced response from climate models to produce an Observational Large Ensemble (OBS-LE). The 1000 members of the OBS-LE display considerable diversity in their 50-year regional climate trends, indicative of the importance of internal variability on multidecadal timescales. For example, unforced atmospheric circulation trends associated with the Northern Annular Mode can induce winter temperature trends over Eurasia that are comparable in magnitude to the forced trend over the past 50 years. Similarly, the contribution of internal variability to winter precipitation trends is large across most of the globe, leading to substantial regional uncertainties in the amplitude and, in some cases, sign of the 50-year trend. The OBS-LE provides a real-world counterpart to initial-condition model ensembles. The approach could be expanded to using paleo-proxy data to simulate longer-term variability.

McKinnon, K. A and C. Deser, 2018: Internal variability and regional climate trends in an Observational Large Ensemble


Attributing the US Southwest’s recent shift into drier conditions

The U.S. Southwest has been getting drier and warmer over the last few decades. These changes fit the common narrative of what might be expected to happen in response to increasing greenhouse gas concentrations. However, natural variability of precipitation and temperature is known to be large in this region, making it difficult to clearly attribute the recent drying and warming to greenhouse gas forcing. Here we show that while the warming is largely due to greenhouse gas forcing, the drying is mostly due to internal climate variability. To date, only an insignificant drying remains after accounting for this internal climate variability. Unlike previous studies that relied exclusively on climate models, we are able to reach these conclusions based on a combination of observations, an empirical statistical method, and climate models.

Lehner, F., C. Deser, I. R. Simpson and L Terray, 2018: Attributing the US Southwest’s recent shift into drier conditions. Geophys. Res. Lett., 45, 6251-6261, Doi: 10.1029/2018GL078312


Modelled and observed multidecadal variability in the North Atlantic jet stream and its connection to Sea Surface Temperatures

Multidecadal variability in the North Atlantic jet stream in general circulation models (GCMs) is compared with that in reanalysis products of the twentieth century. It is found that almost all models exhibit multidecadal jet stream variability that is entirely consistent with the sampling of white noise year-to-year atmospheric fluctuations. In the observed record, the variability displays a pronounced seasonality within the winter months, with greatly enhanced variability toward the late winter. This late winter variability exceeds that found in any GCM and greatly exceeds expectations from the sampling of atmospheric noise, motivating the need for an underlying explanation. The potential roles of both external forcings and internal coupled ocean–atmosphere processes are considered. While the late winter variability is not found to be closely connected with external forcing, it is found to be strongly related to the internally generated component of Atlantic multidecadal variability (AMV) in sea surface temperatures (SSTs). In fact, consideration of the seasonality of the jet stream variability within the winter months reveals that the AMV is far more strongly connected to jet stream variability during March than the early winter months or the winter season as a whole. Reasoning is put forward for why this connection likely represents a driving of the jet stream variability by the SSTs, although the dynamics involved remain to be understood. This analysis reveals a fundamental mismatch between late winter jet stream variability in observations and GC

Simpson, I. R., C. Deser, K. A. McKinnon, and E. A. Barnes, 2018: Modelled and observed multidecadal variability in the North Atlantic jet stream and its connection to Sea Surface Temperatures. J. Climate, 8313-8338, Doi: 10.1175/JCLI-D-18-0168.1


Decadal variability

Decadal climate variability of sea surface temperature (SST) over the Pacific Ocean can be characterized by Interdecadal Pacific Oscillation (IPO) or Pacific Decadal Oscillation (PDO) based on Empirical Orthogonal Function (EOF) analysis. Although the procedures to derive the IPO and PDO indices differ in their regional focuses and filtering methods to remove interannual variability, IPO and PDO are highly correlated in time and are often used interchangeably. Studies have shown that the IPO/PDO play a vital role in modulating the pace of global warming. It is less clear, however, how externally-forced global warming may, in turn, affect IPO/PDO. One obstacle to revealing this effect is that the conventional definitions of IPO/PDO fail to account for the spatial heterogeneity of background warming trend, which causes IPO/PDO to be conflated with the warming trend, especially for the 21st century simulation when the forced change is likely to be more dominant. The large-ensemble simulation with Community Earth System Model version 1 (CESM1) is analyzed to show that a better practice of detrending prior to EOF analysis is to remove the “local and non-linear” trend, defined as the ensemble mean time series at each grid box (or simply as the quadratic fit of the local time series if such an ensemble is not available). The revised IPO/PDO index is purely indicative of internal decadal variability. In the 21st century warmer climate, IPO/PDO has a weaker amplitude in space, a higher frequency in time, and a muted impact on global and North American temperature and rainfall.

Xu, Y. and A. Hu, 2017: How would the 21st-century warming influence Pacific decadal variability and its connection to North American rainfall: assessment based on a revised procedure for IPO/PDO, J. Climate, Doi: 10.1175/JCLI-D-17-0319.1