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James S. Risbey and Milind Kandlikar

The problem of detection of climate change and attribution of causes of change has been formalized as a series of discrete probability judgements in an expert elicitation protocol. Here results are presented from the protocol for 19 experts, highlighting areas of convergence and divergence among experts. There is broad agreement among the experts that the global mean surface air temperature, vertical pattern of temperature change, geographical pattern of temperature change, and changes in diurnal temperature are the important lines of evidence for climate change detection and attribution. For the global mean and vertical pattern lines of evidence, the majority of experts (90%) reject the null hypothesis (no climate change) at the 5% significance level, thereby lending strong support to detection of climate change. For these lines of evidence the median probability of detection at the 5% significance level across experts exceeds 0.9. For the geographical pattern and diurnal cycle lines of evidence, there is far less agreement and fewer than half the experts support detection at even the 10% level of significance. On attribution there is a broad consensus that greenhouse forcing is responsible for about half the warming in global mean temperature in the past century. This result is fairly robust to uncertainties assessed in the relevant forcings by this set of experts. For the other lines of evidence, greenhouse forcing makes smaller fractional contributions with more spread among expert assessments. The near consensus of the experts on detection of climate change and attribution to greenhouse gases rests on the evidence of change in global mean surface air temperature. For the other lines of evidence, there is either significant expert disagreement on detection (the geographical pattern and diurnal cycle), or attribution of change is predominantly to causes other than greenhouse gas forcing (the vertical pattern).

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James S. Risbey and Peter H. Stone

Abstract

Data on zonally averaged atmospheric angular momentum and high cloud cover percent are analyzed for the periods April–October 1979 and November 1982–October 1983. The dominant periodicity in both momentum and cloud datasets was the so called “30–60 day atmospheric oscillation” in tropical and subtropical belts. In lag correlations between high cloud belts, both the periodicity and a latitudinally varying correlation structure were evident. In the 1979 period (Northern Hemisphere summer) the cloud-cloud correlations had nodes near 17°S, 5°N, 24°N and 36°N, i.e., anomalously high/low zonal mean convection between 5 and 24°N coincided with anomalously low/high zonal mean convection between 17°S and 5°N, and between 24 and 36°N. In April–October 1983, a similar periodicity and phase structure were present, but not as well defined. The principal node in the northern Hemisphere summer, near 5°N, appears to lie between the belt of maximum cloud cover for the period (which is between 5 and 9°N) and the equator. In an analysis of the period November 1982–April 1983 (Southern Hemisphere summer), the principal node was located in the Southern Hemisphere. Lag correlations between high cloud belts and momentum belts showed strong correlations with the 30–60 day oscillation present. Anomalously high/low zonal mean high cloudiness in the tropics is accompanied by anomalously high/low zonal mean momentum in the tropics, with the latter anomalies subsequently propagating into midlatitudes.

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James S. Risbey and Peter H. Stone

Abstract

The Sacramento Basin is used as the focus for a case study testing whether general circulation models (GCMS) are capable of simulating the large-scale and synoptic-scale processes important in studies of regional water resources. Output from a variety of GCMs developed at GISS and NCAR were examined, but only results from Community Climate Model (CCM) simulations are presented since they are typical. The stationary waves, jet streams, and storm tracks in the North Pacific-North America region in the CCM simulators show major differences from the observations, both in the mean and in their interannual variations. In addition, although the stationary wave and jet stream patterns associated with individual storms in the basin exhibit robust differences from mean fields in the observations, these differences are not captured in the models. Consequently, the larger-scale fields necessary for driving nested models and impact models for the basin, or for western North America in general, are problematic in these models.

The model deficiencies persist at resolutions as high as T106. Also, the use of time series of observed ocean boundary conditions does little to improve model deficiencies. Consequently, the deficiencies in the model large-scale circulation features can be attributed to the model subgrid-scale parameterizations, underscoring the need to improve model parameterizations.

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Stephan Lewandowsky, James S. Risbey, and Naomi Oreskes

Abstract

There has been much recent published research about a putative “pause” or “hiatus” in global warming. We show that there are frequent fluctuations in the rate of warming around a longer-term warming trend, and that there is no evidence that identifies the recent period as unique or particularly unusual. In confirmation, we show that the notion of a pause in warming is considered to be misleading in a blind expert test. Nonetheless, the most recent fluctuation about the longer-term trend has been regarded by many as an explanatory challenge that climate science must resolve. This departs from long-standing practice, insofar as scientists have long recognized that the climate fluctuates, that linear increases in CO2 do not produce linear trends in global warming, and that 15-yr (or shorter) periods are not diagnostic of long-term trends. We suggest that the repetition of the “warming has paused” message by contrarians was adopted by the scientific community in its problem-solving and answer-seeking role and has led to undue focus on, and mislabeling of, a recent fluctuation. We present an alternative framing that could have avoided inadvertently reinforcing a misleading claim.

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Michael J. Pook, James S. Risbey, and Peter C. McIntosh

Abstract

Synoptic weather systems form an important part of the physical link between remote large-scale climate drivers and regional rainfall. A synoptic climatology of daily rainfall events is developed for the Central Wheatbelt of southwestern Australia over the April–October growing season for the years 1965–2009. The climatology reveals that frontal systems contribute approximately one-half of the rainfall in the growing season while cutoff lows contribute about a third. The ratio of frontal rainfall to cutoff rainfall varies throughout the growing season. Cutoff lows contribute over 40% of rainfall in the austral autumn and spring, but this falls to about 20% in August when frontal rainfall climbs to more than 60%. The number of cutoff lows varies markedly from one growing season to another, but does not exhibit a significant long-term trend. The mean rainfall per cutoff system is also highly variable, but has gradually declined over the analysis period, particularly in the past decade. The decline in rainfall per frontal system is less significant. Cutoff low rainfall has contributed more strongly in percentage terms to the recent decline in rainfall in the Central Wheatbelt than the frontal component and accounts for more than half of the overall trend. Atmospheric blocking is highly correlated with rainfall in the region where cutoff low rainfall makes its highest proportional contribution. Hence, the decline in rain from cutoff low systems is likely to have been associated with changes in blocking and the factors controlling blocking in the region.

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Valérie Ventura, Christopher J. Paciorek, and James S. Risbey

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The analysis of climatological data often involves statistical significance testing at many locations. While the field significance approach determines if a field as a whole is significant, a multiple testing procedure determines which particular tests are significant. Many such procedures are available, most of which control, for every test, the probability of detecting significance that does not really exist. The aim of this paper is to introduce the novel “false discovery rate” approach, which controls the false rejections in a more meaningful way. Specifically, it controls a priori the expected proportion of falsely rejected tests out of all rejected tests; additionally, the test results are more easily interpretable. The paper also investigates the best way to apply a false discovery rate (FDR) approach to spatially correlated data, which are common in climatology. The most straightforward method for controlling the FDR makes an assumption of independence between tests, while other FDR-controlling methods make less stringent assumptions. In a simulation study involving data with correlation structure similar to that of a real climatological dataset, the simple FDR method does control the proportion of falsely rejected hypotheses despite the violation of assumptions, while a more complicated method involves more computation with little gain in detecting alternative hypotheses. A very general method that makes no assumptions controls the proportion of falsely rejected hypotheses but at the cost of detecting few alternative hypotheses. Despite its unrealistic assumption, based on the simulation results, the authors suggest the use of the straightforward FDR-controlling method and provide a simple modification that increases the power to detect alternative hypotheses.

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Terence J. O’Kane, Didier P. Monselesan, and James S. Risbey

Abstract

The authors undertake a multiscale spectral reexamination of the variability of the Pacific–South American (PSA) pattern and the mechanisms by which this variability occurs. Time scales from synoptic to interannual are investigated, focusing on the means by which tropical variability is communicated to the midlatitudes and on in situ forcing within the midlatitude waveguides. Particular interest is paid to what fraction of the total variability associated with the PSA, occurring on interannual time scales, is attributable to tropical forcing relative to that occurring on synoptic and intraseasonal time scales via internal waveguide dynamics. In general, it is found that the eastward-propagating wave train pattern typically associated with the PSA manifests across time scales from synoptic to interannual, with the majority of the variability occurring on synoptic-to-intraseasonal time scales largely independent of tropical convection. It is found that the small fraction of the total variance with a tropical signal occurs via the zonal component of the thermal wind modulating both the subtropical and polar jets. The respective roles of the Hadley circulation and stationary Rossby wave sources are also examined. Further, a PSA-like mode is identified in terms of the slow components of higher-order modes of tropospheric geopotential height. This study reestablishes the multiscale nonlinear nature of the PSA modes arising largely as a manifestation of internal midlatitude waveguide dynamics and local disturbances.

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Terence J. O’Kane, James S. Risbey, Christian Franzke, Illia Horenko, and Didier P. Monselesan

Abstract

Changes in the metastability of the Southern Hemisphere 500-hPa circulation are examined using both cluster analysis techniques and split-flow blocking indices. The cluster methodology is a purely data-driven approach for parameterization whereby a multiscale approximation to nonstationary dynamical processes is achieved through optimal sequences of locally stationary fast vector autoregressive factor (VARX) processes and some slow (or persistent) hidden process switching between them. Comparison is made with blocking indices commonly used in weather forecasting and climate analysis to identify dynamically relevant metastable regimes in the 500-hPa circulation in both reanalysis and Atmospheric Model Intercomparison Project (AMIP) datasets. The analysis characterizes the metastable regime in both reanalysis and model datasets prior to 1978 as positive and negative phases of a hemispheric midlatitude blocking state with the southern annular mode (SAM) associated with a transition state. Post-1978, the SAM emerges as a true metastable state replacing the negative phase of the hemispheric blocking pattern. The hidden state frequency of occurrences exhibits strong trends. The blocking pattern dominates in the early 1980s, and then gradually decreases. There is a corresponding increase in the SAM frequency of occurrence. This trend is largely evident in the reanalysis summer and spring but was not evident in the AMIP dataset. Further comparison with the split-flow blocking indices reveals a superficial correspondence between the cluster hidden state frequency of occurrences and split-flow indices. Examination of composite states shows that the blocking indices capture splitting of the zonal flow whereas the cluster composites reflect coherent block formation. Differences in blocking climatologies from the respective methods are discussed.

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James S. Risbey, Peter J. Lamb, Ron L. Miller, Michael C. Morgan, and Gerard H. Roe

Abstract

A set of regional climate scenarios is constructed for two study regions in North America using a combination of GCM output and synoptic–dynamical reasoning. The approach begins by describing the structure and components of a climate scenario and identifying the dynamical determinants of large-scale and regional climate. Expert judgement techniques are used to categorize the tendencies of these elements in response to increased greenhouse forcing in climate model studies. For many of the basic dynamical elements, tendencies are ambiguous, and changes in sign (magnitude, position) can usually be argued in either direction. A set of climate scenarios is produced for winter and summer, emphasizing the interrelationships among dynamical features, and adjusting GCM results on the basis of known deficiences in GCM simulations of the dynamical features. The scenarios are qualitative only, consistent with the level of precision afforded by the uncertainty in understanding of the dynamics, and in order to provide an outline of the reasoning and chain of contingencies on which the scenarios are based. The three winter scenarios outlined correspond roughly to a north–south displacement of the stationary wave pattern, to an increase in amplitude of the pattern, and to a shift in phase of the pattern. These scenarios illustrate that small changes in the dynamics can lead to large changes in regional climate in some regions, while other regions are apparently insensitive to some of the large changes in dynamics that can be plausibly hypothesized. The dynamics of summer regional climate changes are even more difficult to project, though thermodynamic considerations allow some more general conclusions to be reached in this season. Given present uncertainties it is difficult to constrain regional climate projections.

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Caroline C. Ummenhofer, Peter C. McIntosh, Michael J. Pook, and James S. Risbey

Abstract

Characteristics of atmospheric blocking in the Southern Hemisphere (SH) are explored in atmospheric general circulation model (AGCM) simulations with the Community Atmosphere Model, version 3, with a particular focus on the Australia–New Zealand sector. Preferred locations of blocking in SH observations and the associated seasonal cycle are well represented in the AGCM simulations, but the observed magnitude of blocking is underestimated throughout the year, particularly in late winter and spring. This is related to overly zonal flow due to an enhanced meridional pressure gradient in the model, which results in a decreased amplitude of the longwave trough/ridge pattern. A range of AGCM sensitivity experiments explores the effect on SH blocking of tropical heating, midlatitude sea surface temperatures, and land–sea temperature gradients created over the Australian continent during austral winter. The combined effects of tropical heating and extratropical temperature gradients are further explored in a configuration that is favorable for blocking in the Australia–New Zealand sector with warm SST anomalies to the north of Australia, cold to the southwest of Australia, warm to the southeast, and cool Australian land temperatures. The blocking-favorable configuration indicates a significant strengthening of the subtropical jet and a reduction in midlatitude flow, which results from changes in the thermal wind. While these overall changes in mean climate, predominantly forced by the tropical heating, enhance blocking activity, the magnitude of atmospheric blocking compared to observations is still underestimated. The blocking-unfavorable configuration with surface forcing anomalies of opposite sign results in a weakening subtropical jet, enhanced midlatitude flow, and significantly reduced blocking.

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