Abstract

The relative roles of direct atmospheric radiative forcing (due to observed changes in well-mixed greenhouse gases, tropospheric and stratospheric ozone, sulfate and volcanic aerosols, and solar output) and observed sea surface temperature (SST) forcing of global December–February atmospheric circulation trends during the second half of the twentieth century are investigated by means of experiments with an atmospheric general circulation model, Community Atmospheric Model, version 3 (CAM3). The model experiments are conducted by specifying the observed time-varying SSTs and atmospheric radiative quantities individually and in combination. This approach allows the authors to isolate the direct impact of each type of forcing agent as well as to evaluate their combined effect and the degree to which their impacts are additive. CAM3 realistically simulates the global patterns of sea level pressure and 500-hPa geopotential height trends when both forcings are specified. SST forcing and direct atmospheric radiative forcing drive distinctive circulation responses that contribute about equally to the global pattern of circulation trends. These distinctive circulation responses are approximately additive and partially offsetting. Atmospheric radiative changes directly drive the strengthening and poleward shift of the midlatitude westerly winds in the Southern Hemisphere (and to a lesser extent may contribute to those over the Atlantic–Eurasian sector in the Northern Hemisphere), whereas SST trends (specifically those in the tropics) are responsible for the intensification of the Aleutian low and weakening of the tropical Walker circulation. Discrepancies between the atmospheric circulation trends simulated by CAM3 and Community Climate System Model, version 3 (CCSM3), a coupled model driven by the same atmospheric radiative forcing as CAM3, are traced to differences in their tropical SST trends: in particular, a 60% weaker warming of the tropical Indo-Pacific in the CCSM3 ensemble mean than in nature.

Abstract

This study examines the contribution of tropical sea surface temperature (SST) forcing to the 1976/77 climate transition of the winter atmospheric circulation over the North Pacific using a combined observational and modeling approach. The National Center for Atmospheric Research (NCAR) Community Atmospheric Model version 3 (CAM3) simulates approximately 75% of the observed 4-hPa deepening of the wintertime Aleutian low from 1950–76 to 1977–2000 when forced with the observed evolution of tropical SSTs in a 10-member ensemble average. This response is driven by precipitation increases over the western half of the equatorial Pacific Ocean. In contrast, the NCAR Community Climate Model version 3 (CCM3), the predecessor to CAM3, simulates no significant change in the strength of the Aleutian low when forced with the same tropical SSTs in a 12-member ensemble average. The lack of response in CCM3 is traced to an erroneously large precipitation increase over the tropical Indian Ocean whose dynamical impact is to weaken the Aleutian low; this, when combined with the response to rainfall increases over the western and central equatorial Pacific, results in near-zero net change in the strength of the Aleutian low. The observed distribution of tropical precipitation anomalies associated with the 1976/77 transition, estimated from a combination of direct measurements at land stations and indirect information from surface marine cloudiness and wind divergence fields, supports the models’ simulated rainfall increases over the western half of the Pacific but not the magnitude of CCM3’s rainfall increase over the Indian Ocean.

Abstract

This study elucidates the physical mechanisms underlying internal and forced components of winter surface air temperature (SAT) trends over North America during the past 50 years (1963–2012) using a combined observational and modeling framework. The modeling framework consists of 30 simulations with the Community Earth System Model (CESM) at 1° latitude–longitude resolution, each of which is subject to an identical scenario of historical radiative forcing but starts from a slightly different atmospheric state. Hence, any spread within the ensemble results from unpredictable internal variability superimposed upon the forced climate change signal. Constructed atmospheric circulation analogs are used to estimate the dynamical contribution to forced and internal components of SAT trends: thermodynamic contributions are obtained as a residual. Internal circulation trends are estimated to account for approximately one-third of the observed wintertime warming trend over North America and more than half locally over parts of Canada and the United States. Removing the effects of internal atmospheric circulation variability narrows the spread of SAT trends within the CESM ensemble and brings the observed trends closer to the model’s radiatively forced response. In addition, removing internal dynamics approximately doubles the signal-to-noise ratio of the simulated SAT trends and substantially advances the “time of emergence” of the forced component of SAT anomalies. The methodological framework proposed here provides a general template for improving physical understanding and interpretation of observed and simulated climate trends worldwide and may help to reconcile the diversity of SAT trends across the models from phase 5 of the Coupled Model Intercomparison Project (CMIP5).

Abstract

This study examines the tropical linkages to interdecadal climate fluctuations over the North Pacific during boreal winter through a comprehensive and physically based analysis of a wide variety of observational datasets spanning the twentieth century. Simple difference maps between epochs of high sea level pressure over the North Pacific (1900–24 and 1947–76) and epochs of low pressure (1925–46 and 1977–97) are presented for numerous climate variables throughout the tropical Indo-Pacific region, including rainfall, cloudiness, sea surface temperature (SST), and sea level pressure. The results support the notion that the Tropics play a key role in North Pacific interdecadal climate variability. In particular, SST anomalies in the tropical Indian Ocean and southeast Pacific Ocean, rainfall and cloudiness anomalies in the vicinity of the South Pacific convergence zone, stratus clouds in the eastern tropical Pacific, and sea level pressure differences between the tropical southeast Pacific and Indian Oceans all exhibit prominent interdecadal fluctuations that are coherent with those in sea level pressure over the North Pacific. The spatial patterns of the interdecadal tropical climate anomalies are compared with those associated with ENSO, a predominantly interannual phenomenon; in general, the two are similar with some differences in relative spatial emphasis. Finally, a published 194-yr coral record in the western tropical Indian Ocean is shown to compare favorably with the twentieth-century instrumental records, indicating the potential for extending knowledge of tropical interdecadal climate variability to earlier time periods.

Abstract

Simulations of the El Niño–Southern Oscillation (ENSO) phenomenon and tropical Atlantic climate variability in the newest version of the Community Climate System Model [version 3 (CCSM3)] are examined in comparison with observations and previous versions of the model. The analyses are based upon multicentury control integrations of CCSM3 at two different horizontal resolutions (T42 and T85) under present-day CO₂ concentrations. Complementary uncoupled integrations with the atmosphere and ocean component models forced by observed time-varying boundary conditions allow an assessment of the impact of air–sea coupling upon the simulated characteristics of ENSO and tropical Atlantic variability.

The amplitude and zonal extent of equatorial Pacific sea surface temperature variability associated with ENSO is well simulated in CCSM3 at both resolutions and represents an improvement relative to previous versions of the model. However, the period of ENSO remains too short (2–2.5 yr in CCSM3 compared to 2.5–8 yr in observations), and the sea surface temperature, wind stress, precipitation, and thermocline depth responses are too narrowly confined about the equator. The latter shortcoming is partially overcome in the atmosphere-only and ocean-only simulations, indicating that coupling between the two model components is a contributing cause. The relationships among sea surface temperature, thermocline depth, and zonal wind stress anomalies are consistent with the delayed/recharge oscillator paradigms for ENSO. We speculate that the overly narrow meridional scale of CCSM3's ENSO simulation may contribute to its excessively high frequency. The amplitude and spatial pattern of the extratropical atmospheric circulation response to ENSO is generally well simulated in the T85 version of CCSM3, with realistic impacts upon surface air temperature and precipitation; the simulation is not as good at T42.

CCSM3's simulation of interannual climate variability in the tropical Atlantic sector, including variability intrinsic to the basin and that associated with the remote influence of ENSO, exhibits similarities and differences with observations. Specifically, the observed counterpart of El Niño in the equatorial Atlantic is absent from the coupled model at both horizontal resolutions (as it was in earlier versions of the coupled model), but there are realistic (although weaker than observed) SST anomalies in the northern and southern tropical Atlantic that affect the position of the local intertropical convergence zone, and the remote influence of ENSO is similar in strength to observations, although the spatial pattern is somewhat different.

Abstract

Internal variability in the climate system gives rise to large uncertainty in projections of future climate. The uncertainty in future climate due to internal climate variability can be estimated from large ensembles of climate change simulations in which the experiment setup is the same from one ensemble member to the next but for small perturbations in the initial atmospheric state. However, large ensembles are invariably computationally expensive and susceptible to model bias.

Here the authors outline an alternative approach for assessing the role of internal variability in future climate based on a simple analytic model and the statistics of the unforced climate variability. The analytic model is derived from the standard error of the regression and assumes that the statistics of the internal variability are roughly Gaussian and stationary in time. When applied to the statistics of an unforced control simulation, the analytic model provides a remarkably robust estimate of the uncertainty in future climate indicated by a large ensemble of climate change simulations. To the extent that observations can be used to estimate the amplitude of internal climate variability, it is argued that the uncertainty in future climate trends due to internal variability can be robustly estimated from the statistics of the observed climate.

Abstract

This study highlights the relative importance of internally generated versus externally forced climate trends over the next 50 yr (2010–60) at local and regional scales over North America in two global coupled model ensembles. Both ensembles contain large numbers of integrations (17 and 40): each of which is subject to identical anthropogenic radiative forcing (e.g., greenhouse gas increase) but begins from a slightly different initial atmospheric state. Thus, the diversity of projected climate trends within each model ensemble is due solely to intrinsic, unpredictable variability of the climate system. Both model ensembles show that natural climate variability superimposed upon forced climate change will result in a range of possible future trends for surface air temperature and precipitation over the next 50 yr. Precipitation trends are particularly subject to uncertainty as a result of internal variability, with signal-to-noise ratios less than 2. Intrinsic atmospheric circulation variability is mainly responsible for the spread in future climate trends, imparting regional coherence to the internally driven air temperature and precipitation trends. The results underscore the importance of conducting a large number of climate change projections with a given model, as each realization will contain a different superposition of unforced and forced trends. Such initial-condition ensembles are also needed to determine the anthropogenic climate response at local and regional scales and provide a new perspective on how to usefully compare climate change projections across models.

abstract

The role of sampling variability in ENSO composites of winter surface air temperature and precipitation over North America during the period 1920–2013 is assessed for observations and ensembles of coupled model simulations in which sea surface temperature anomalies in the tropical eastern Pacific are nudged to those of the real world. The individual members of each model ensemble show a surprising amount of diversity in their ENSO composites, despite being constructed from the same observed set of 18 El Niño and 14 La Niña events. For a given model, this ensemble spread can only be due to sampling variability, that is, aliasing of internal variability that is unrelated to ENSO, which in turn is shown to arise from internal atmospheric dynamics rather than coupled ocean–atmosphere processes. Analogous ensemble spread is evident in 2000 synthetic ENSO composites based on observations using random sampling techniques. These synthetic composites provide information on the range of spatial patterns and amplitudes associated with imperfect estimation of the forced ENSO signal in the observational record. In some locations, the amplitude of the estimated ENSO signal can vary by more than a factor of two. This observational uncertainty necessitates an approach to model assessment that considers not only the model’s forced response to ENSO, given by its ensemble-mean ENSO composite, but also its representation of internal variability unrelated to ENSO. Such an approach is used to reveal fidelities and shortcomings in the Community Earth System Model, version 1.

Abstract

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.

Abstract

Reanalysis output for 1948–99 is used to evaluate the temporal distributions, the geographical origins, and the atmospheric teleconnections associated with major cold outbreaks affecting heavily populated areas of middle latitudes. The study focuses on three subregions of the United States and two subregions of Europe. The cold outbreaks affecting the United States are more extreme than those affecting Europe, in terms of both the regionally averaged and the local minimum air temperatures. There is no apparent trend toward fewer extreme cold events on either continent over the 1948–99 period, although a long station history suggests that such events may have been more frequent in the United States during the late 1800s and early 1900s. The trajectories of the coldest air masses are southward or southeastward over North America, but westward over Europe. Subsidence of several hundred millibars is typical of the trajectories of the coldest air to reach the surface in the affected regions. Sea level pressure anomalies evolve consistently with the trajectories over the 1–2 weeks prior to the extreme outbreaks, and precursors of the cold events are apparent in coherent antecedent anomaly patterns. Negative values of the North Atlantic oscillation index and positive anomalies of Arctic sea level pressure are features common to North American as well as European outbreaks. However, the strongest associated antecedent anomalies of sea level pressure are generally shifted geographically relative to the nodal locations of the North Atlantic and Arctic oscillations.