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.

Abstract

Regional climate, anomalies associated with year-to-year changes in the tropospheric zonal-mean zonal wind (ū) are examined. This study focuses on the wintertime Northern Hemisphere extratropics and compares seasonal mean anomalies associated with ū to those associated with the El Niño–Southern Oscillation during the 1947–94 period.

Dynamical model experiments indicate that a single zonal index, characterized by out-of-phase ū anomalies at 35° and 55°N, is of primary importance for zonal flow/stationary wave interactions in the Northern Hemisphere extratropies. Such fluctuations in the zonal-mean zonal flow are shown to occur independently of tropical SST variability, consistent with earlier studies. Dynamical model experiments and regression analyses of the historical data indicate that such a zonal index explains a significant fraction of the wintertime stationary wave variability in several regions. The principal centers of action reside within wave trains over the North Pacific–North American region and the North Atlantic–Eurdsian region where locally 30%–40% of the eddy height variability is explained by the zonal index. Only over the North Pacific does the stationary wave signal related to ENSO appreciably exceed that associated with the zonal index. The surface climate associated with the zonal index is described by a wavenumber 1 pattern, which has out-of-phase temperature anomalies between Eurasia and North America and amplitudes considerably larger than those experienced during ENSO.

The analysis offers a physical basis for understanding extratropical seasonal climate anomalies as a simple linear combination of teleconnection patterns associated with ū states and ENSO states. The utility of such an approach is illustrated for several cases of hitherto unexplained observed extreme climate anomalies during northern winter. It is also shown that a significant fraction of the interannual variability in some regions cannot he explained by either a zonal index or ENSO.

A further important feature of the zonal index in the 1947–94 period is the recurrence of anomalies over multiyear periods. Such behavior has important implications for decadal climate variations, examples of which are given for secular changes after 1976.

Abstract

The atmospheric response to the evolution of global sea surface temperatures (SSTS) from 1985 to 1987 is studied using the NCAR Community Climate Model (CCM1). Five separate 2-year integrations are performed, and results are presented for the ensemble-averaged response during the pre-El Niño 1985/86 winter and the mature El Niño 1986/87 winter.

No skill is found in CCM1's simulation for 1985/86. The simulation for the following winter, when tropical Pacific SST anomalies approached 2°C, is more successful. A large-amplitude wave train extends poleward and eastward from the location of anomalous central Pacific convection in CCM1, although the model's wave train is shifted 30° too far east compared to observations.

A linear barotropic stationary wave model is used to diagnose CCM1's response during 1986/87. The eastward-shifted PNA response is easily excited by a dipole pattern of upper-level forcing with convergence over the western tropical Pacific and divergence over the central tropical Pacific. In contrast, the observed anomaly pattern during 1986/87 is most ettectively forced by anomalous subtropical convergence over the central Pacific. Zonally asymmetric features of CCM1's climate drift, in particular the pattern of zonal wind biases over the tropical and midialitude North Pacific, are shown to account for these different sensitivities.

Abstract

Whether distinct wintertime U.S. climate conditions exist for central-Pacific (CP) versus eastern-Pacific (EP) El Niño events is explored using atmospheric and coupled ocean–atmospheric models. Results using the former agree with most prior studies indicating different U.S. temperature and precipitation patterns associated with El Niño flavors. Causes are traced to equatorial rainfall sensitivity to both magnitudes and spatial patterns of sea surface temperatures (SSTs) distinguishing CP and EP cases. Warmer east equatorial Pacific Ocean SSTs during EP than CP events, specifically for strong EP cases, are responsible for greater east equatorial Pacific rainfall, which displaces tropospheric circulation anomalies eastward over the Pacific–North American region. Weak-amplitude EP cases and all CP events since 1980 fail to excite east equatorial Pacific rainfall, thus not initiating the dynamical chain of effects characterizing strong EP cases. Over the contiguous United States, the difference in tropospheric circulations between strong EP and CP events describes a cyclonic pattern that renders the former colder and wetter. Regional signals include notably colder western and warmer eastern U.S. surface temperatures during EP versus CP events, and higher southwestern and southeastern U.S. precipitation during EP events. We demonstrate the important result—new to studies of observed El Niño flavor impacts—that coupled models largely reproduce the sensitivities of atmospheric models. Confirmed hereby is the realism of prior estimates of El Niño flavor impacts that relied on atmospheric models alone. We further examine predictability of El Niño flavors using coupled forecasts, demonstrating that SST distinctions between CP and EP events and their diverse U.S. wintertime impacts are predictable at least a season in advance.

Abstract

Atmospheric circulation changes during boreal winter of the second half of the twentieth century exhibit a trend toward the positive polarity of both the Northern Hemisphere annular mode (NAM) and the Southern Hemisphere annular mode (SAM). This has occurred in concert with other trends in the climate system, most notably a warming of the Indian Ocean. This study explores whether the tropical Indian Ocean warming played a role in forcing these annular trends. Five different atmospheric general circulation models (AGCMs) are forced with an idealized, transient warming of Indian Ocean sea surface temperature anomalies (SSTA); the results of this indicate that the warming contributed to the annular trend in the NH but offset the annular trend in SH. The latter result implies that the Indian Ocean warming may have partly cancelled the influence of the stratospheric ozone depletion over the southern polar area, which itself forced a trend toward the positive phase of the SAM. Diagnosis of the physical mechanisms for the annular responses indicates that the direct impact of the diabatic heating induced by the Indian Ocean warming does not account for the annular response in the extratropics. Instead, interactions between the forced stationary wave anomalies and transient eddies is key for the formation of annular structures.

Abstract

Forced atmospheric teleconnections during 1979–2014 are examined using a 50-member ensemble of atmospheric general circulation model (AGCM) simulations subjected to observed variations in sea surface temperatures (SSTs), sea ice, and carbon dioxide. Three primary modes of forced variability are identified using empirical orthogonal function (EOF) analysis of the ensemble mean wintertime extratropical Northern Hemisphere 500-hPa heights. The principal component time series of the first and second modes are highly correlated with Niño-3.4 and trans-Niño (TNI) SST indices, respectively, indicating mostly tropical sources. Their impacts are largely confined to the Pacific–North American (PNA) sector. The leading mode describes the canonical atmospheric teleconnection associated with El Niño–Southern Oscillation (ENSO) resembling the tropical/Northern Hemisphere pattern. The second mode describes a wave train resembling the classic PNA pattern resulting from atmospheric sensitivity to ENSO asymmetry and from sensitivity to a tropical precursor SST for ENSO development. The third mode is characterized by a hemisphere-scale increasing trend in heights. Based on a comparison with 50-member coupled ocean–atmosphere model simulations, it is argued that this mode is strongly related to radiatively forced climate change, while the other two forced teleconnections are principally related to internal coupled variability. A trend in the leading forced mode is related to ENSO-like decadal variability and dominates the overall observed 500-hPa height trend since 1979. These model results indicate that the trend in the first mode is due to internal variability rather than external radiative forcing.

The Seasonal Diagnostics Consortium of the Applied Research Centers is engaging in a real-time activity to detect and understand the role of sea surface temperature (SST) anomalies in observed climate anomalies. The activity is aimed to improve practices in seasonal climate forecasting by fully harvesting the accumulated research evidence of the climate's sensitivity to ocean forcing. The approach, in the first phase of the activity, involves performing ensembles of atmospheric general circulation models (AGCMs) at several institutions, using the most recently observed global SST anomalies as prescribed forcings. The runs are routinely updated each month as the latest SST observations become available, adding to the archive of historical simulations spanning the last half-century.

The SST-forced signal in the seasonal mean climate is detected through the agreement among ensemble mean anomalies drawn from the simulations of the various AGCMs. The consortium activity also compares the dynamically forced signals with those estimated empirically, based on the observational archive. A comparison of the coordinated simulations with the observed climate anomalies is then made for two principal reasons: 1) to offer an attribution for the ocean's role in the origin of the observed seasonal climate anomalies, and 2) to determine the causes for success or failure of operational seasonal climate predictions, whose tools may be either mainly dynamically or empirically derived. It is expected that routine climate diagnostics and attribution efforts for climate anomalies will help further develop the knowledge base for improving the practice of seasonal climate predictions, and advance understanding of global climate on seasonal to decadal time scales.

Abstract

The atmospheric response to a midlatitude SST anomaly in the North Pacific and its dependence on background flow are examined in a GCM. Experiments are conducted using the same warm SST anomalies but two different model states: perpetual January and perpetual February. The atmospheric responses to the SST anomalies are statistically significant in both January and February but are completely different. The anomalous circulation in January is characterized by a trough decaying with height immediately downstream of the SST anomalies. In February, the anomalous circulation is dominated by a downstream ridge growing with height. The patterns of the anomalous heights in the two months are nearly orthogonal.

Vorticity and thermodynamic budgets are diagnosed to illustrate how the anomalous circulations are maintained. Over the SST anomalies, low-level convergence and ascent are observed in both months. In January the anomalous convergence is balanced by a residual due primarily to the forcing by submonthly transients. In February the convergence is balanced by the advection of planetary vorticity. Analysis of the thermodynamic budget indicates that the intensity of the mean meridional wind downstream of the SST anomalies plays a critical role in determining the nature of the responses in the two months. The “warm SST-ridge” type of response is favored when the background meridional flow is relatively weak. These results demonstrate that the atmospheric response to a midlatitude SST anomaly is strongly dependent on the background flow.

Abstract

For the case of probabilistic seasonal forecasts verified by the rank probability skill score, the dependence of the expected value of seasonal forecast skill on a hypothesized perfect atmospheric general circulation model’s ensemble size is examined. This score evaluates the distributional features of the forecast as well as its central tendency. The context of the verification is that of interannual variability of the extratropical climate anomalies forced by sea surface temperatures in the tropical Pacific associated with ENSO. It is argued that because of the atmospheric internal variability, the seasonal predictability is inherently limited, and that this upper limit in the average skill is the one that can be achieved using infinite ensemble size. Next, for different assumptions of signal-to-noise ratios, the ensemble size required to deliver average predictive skill close to inherent skill is evaluated.

Results indicate that for signal-to-noise ratios of magnitudes close to 0.5, the typical ensemble size currently used for the seasonal prediction efforts (i.e., 10–20 members), is sufficient to ensure average skill close to what is expected based on infinite ensemble size. For smaller standardized seasonal mean atmospheric anomalies, the ensemble size required to obtain predictive skill close to the inherent limit increases dramatically. But for these cases the expected skill itself is very low and the use of larger ensemble size has to be judged against the marginal level of prediction skill. Further, for small signal-to-noise ratios, forecasting the climatological distribution becomes nearly as effective as accurately defining the slight deviations from climatology.

Abstract

Dynamical methods are used to investigate atmospheric teleconnections associated with extreme seasonal precipitation anomalies over the central United States during April–June. The importance of sea surface temperature (SST) anomalies in forcing atmospheric teleconnections is specifically addressed through analyses of atmospheric general circulation model (GCM) simulations forced with the monthly varying SSTs of the years 1950–98. The results from three different models, each run in ensemble mode, are compared with observations of extreme April–June precipitation events in the central United States during the last half of the twentieth century.

Analysis of GCM simulations of April–June 1988 indicates that the atmospheric circulation anomalies associated with the 1988 drought were not forced by SST anomalies and that the coexistence of central U.S. drought and La Niña during that spring was coincidental. Likewise, composite analysis reveals no SST forcing for the teleconnections associated with extreme dry spring seasons over the central United States during the last half of the twentieth century in either observations or GCMs. Nonetheless, this characteristic teleconnection pattern of the composite analysis resembles the circulation anomalies of 1988. The results imply that such drought events and the teleconnections related with them have little SST-based predictability.

A somewhat different conclusion is drawn regarding the role of tropical SSTs in the occurrence of extreme wet spring seasons over the central United States. Simulations of the 1993 flood period exhibit skill in reproducing the seasonal circulation anomalies over the Pacific–North American region, and the ensemble mean precipitation anomalies in one GCM nearly replicate the observed strength and distribution of positive rainfall anomalies over the United States. Further composite analysis of extreme wet spring seasons over the last half of the twentieth century confirms the impression gathered from the 1993 case study, with observations and all three GCMs possessing positive tropical east Pacific SST anomalies in conjunction with extreme wet spring seasons over the central United States. Some SST-based potential predictability of extreme wet springs over the central United States consequently exists.