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

Abstract

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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Christopher J. Paciorek
,
James S. Risbey
,
Valérie Ventura
, and
Richard D. Rosen

Abstract

The National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis is used to estimate time trends of, and analyze the relationships among, six indices of cyclone activity or forcing for the winters of 1949–99, over the region 20°–70°N. The indices are Eady growth rate and temperature variance, both at 500 hPa; surface meridional temperature gradient; the 95th percentile of near-surface wind speed; and counts of cyclones and intense cyclones. With multiple indices, one can examine different aspects of storm activity and forcing and assess the robustness of the results to various definitions of a cyclone index. Results are reported both as averages over broad spatial regions and at the resolution of the NCEP–NCAR reanalysis grid, for which the false discovery rate methodology is used to assess statistical significance.

The Eady growth rate, temperature variance, and extreme wind indices are reasonably well correlated over the two major storm track regions of the Northern Hemisphere as well as over northern North America and Eurasia, but weakly correlated elsewhere. These indices show moderately strong correlations with each of the two cyclone count indices over much of the storm tracks when the count indices are offset 7.5° to the north.

Regional averages over the Atlantic, the Pacific, and Eurasia show either no long-term change or a decrease in the total number of cyclones; however, all regions show an increase in intense cyclones. The Eady growth rate, temperature variance, and wind indices generally increase in these regions. On a finer spatial scale, these three indices increase significantly over the storm tracks and parts of Eurasia. The intense cyclone count index also increases locally, but insignificantly, over the storm tracks. The wind and intense cyclone indices suggest an increase in impacts from cyclones, primarily over the oceans.

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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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Terence J. O’Kane
,
Dougal T. Squire
,
Paul A. Sandery
,
Vassili Kitsios
,
Richard J. Matear
,
Thomas S. Moore
,
James S. Risbey
, and
Ian G. Watterson

Abstract

Recent studies have shown that regardless of model configuration, skill in predicting El Niño–Southern Oscillation (ENSO), in terms of target month and forecast lead time, remains largely dependent on the temporal characteristics of the boreal spring predictability barrier. Continuing the 2019 study by O’Kane et al., we compare multiyear ensemble ENSO forecasts from the Climate Analysis Forecast Ensemble (CAFE) to ensemble forecasts from state-of-the-art dynamical coupled models in the North American Multimodel Ensemble (NMME) project. The CAFE initial perturbations are targeted such that they are specific to tropical Pacific thermocline variability. With respect to individual NMME forecasts and multimodel ensemble averages, the CAFE forecasts reveal improvements in skill when predicting ENSO at lead times greater than 6 months, in particular when predictability is most strongly limited by the boreal spring barrier. Initial forecast perturbations generated exclusively as disturbances in the equatorial Pacific thermocline are shown to improve the forecast skill at longer lead times in terms of anomaly correlation and the random walk sign test. Our results indicate that augmenting current initialization methods with initial perturbations targeting instabilities specific to the tropical Pacific thermocline may improve long-range ENSO prediction.

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Carly R. Tozer
,
James S. Risbey
,
Didier P. Monselesan
,
Dougal T. Squire
,
Matthew A. Chamberlain
,
Richard J. Matear
, and
Tilo Ziehn

Abstract

We assess the representation of multiday temperature and rainfall extremes in southeast Australia in three coupled general circulation models (GCMs) of varying resolution. We evaluate the statistics of the modeled extremes in terms of their frequency, duration, and magnitude compared to observations, and the model representation of the midtropospheric circulation (synoptic and large scale) associated with the extremes. We find that the models capture the statistics of observed heatwaves reasonably well, though some models are “too wet” to adequately capture the observed duration of dry spells but not always wet enough to capture the magnitude of extreme wet events. Despite the inability of the models to simulate all extreme event statistics, the process evaluation indicates that the onset and decay of the observed synoptic structures are well simulated in the models, including for wet and dry extremes. We also show that the large-scale wave train structures associated with the observed extremes are reasonably well simulated by the models although their broader onset and decay is not always captured in the models. The results presented here provide some context for, and confidence in, the use of the coupled GCMs in climate prediction and projection studies for regional extremes.

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Michael R. Grose
,
James S. Risbey
,
Aurel F. Moise
,
Stacey Osbrough
,
Craig Heady
,
Louise Wilson
, and
Tim Erwin

Abstract

Atmospheric circulation change is likely to be the dominant driver of multidecadal rainfall trends in the midlatitudes with climate change this century. This study examines circulation features relevant to southern Australian rainfall in January and July and explores emergent constraints suggested by the intermodel spread and their impact on the resulting rainfall projection in the CMIP5 ensemble. The authors find relationships between models’ bias and projected change for four features in July, each with suggestions for constraining forced change. The features are the strength of the subtropical jet over Australia, the frequency of blocked days in eastern Australia, the longitude of the peak blocking frequency east of Australia, and the latitude of the storm track within the polar front branch of the split jet. Rejecting models where the bias suggests either the direction or magnitude of change in the features is implausible produces a constraint on the projected rainfall reduction for southern Australia. For RCP8.5 by the end of the century the constrained projections are for a reduction of at least 5% in July (with models showing increase or little change being rejected). Rejecting these models in the January projections, with the assumption the bias affects the entire simulation, leads to a rejection of wet and dry outliers.

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Caroline C. Ummenhofer
,
Alexander Sen Gupta
,
Peter R. Briggs
,
Matthew H. England
,
Peter C. McIntosh
,
Gary A. Meyers
,
Michael J. Pook
,
Michael R. Raupach
, and
James S. Risbey
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Caroline C. Ummenhofer
,
Alexander Sen Gupta
,
Peter R. Briggs
,
Matthew H. England
,
Peter C. McIntosh
,
Gary A. Meyers
,
Michael J. Pook
,
Michael R. Raupach
, and
James S. Risbey

Abstract

The relative influences of Indian and Pacific Ocean modes of variability on Australian rainfall and soil moisture are investigated for seasonal, interannual, and decadal time scales. For the period 1900–2006, observations, reanalysis products, and hindcasts of soil moisture during the cool season (June–October) are used to assess the impacts of El Niño–Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD) on southeastern Australia and the Murray–Darling Basin, two regions that have recently suffered severe droughts. A distinct asymmetry is found in the impacts of the opposite phases of both ENSO and IOD on Australian rainfall and soil moisture. There are significant differences between the dominant drivers of drought at interannual and decadal time scales. On interannual time scales, both ENSO and the IOD modify southeastern Australian soil moisture, with the driest (wettest) conditions over the southeast and more broadly over large parts of Australia occurring during years when an El Niño and a positive IOD event (La Niña and a negative IOD event) co-occur. The atmospheric circulation associated with these responses is discussed. Lower-frequency variability over southeastern Australia, however, including multiyear drought periods, seems to be more robustly related to Indian Ocean temperatures than Pacific conditions. The frequencies of both positive and negative IOD events are significantly different during periods of prolonged drought compared to extended periods of “normal” rainfall. In contrast, the frequency of ENSO events remains largely unchanged during prolonged dry and wet periods. For the Murray–Darling Basin, there appears to be a significant influence by La Niña and both positive and negative IOD events. In particular, La Niña plays a much more prominent role than for more southern regions, especially on interannual time scales and during prolonged wet periods. For prolonged dry (wet) periods, positive IOD events also occur in unusually high (low) numbers.

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