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George J. Boer

Abstract

Long time-scale teleconnection patterns, with common features in both the northern Atlantic and Pacific regions, are identified. The teleconnection patterns arise in an investigation of the internally generated variability in a multimodel ensemble of coupled climate model control simulations. The large amount of data involved offers statistical robustness and the benefits of combining results across models. Maxima of decadal potential predictability identify regions where long time-scale variability is an appreciable fraction of the total variability and serve as index regions for the teleconnection analysis. Annual, 5-yr, and decadal mean temperatures over these Atlantic and Pacific index regions are correlated with corresponding temperatures and precipitation rates over the globe. The resulting teleconnection patterns are reasonably similar despite the different long time-scale variability mechanisms thought to exist in the two ocean basins. Although lacking statistical robustness, some aspects of the temperature teleconnection patterns are obtained based on the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) dataset. The similarity of the teleconnection patterns in the two northern ocean regions suggests that common variability mechanisms may be involved.

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Mark Holzer and George J. Boer

Abstract

Atmospheric “transport climate” characterizes how trace gases are distributed by and within the atmosphere, on average, as a consequence of the interaction of atmospheric flow with tracer sources and sinks. The change in transport climate under global warming is investigated using passive tracers. Experiments with constant localized surfaces sources, pulsed sources, and pulsed boundary conditions are analyzed using a Green-function approach in conjunction with a climatological budget calculation.

Under climate warming, interhemispheric exchange times, mixing times, and mean transit times all increase by about 10%. The main transport pathway between the hemispheres via the “tracer fountain” at the ITCZ is suppressed. Generally less vigorous flow manifests itself in higher tracer burdens in the source hemisphere and in downwind plumes of enhanced mixing ratio close to the sources; these increases are also about 10%. Resolved advection and subgrid transport do not cooperate for all sources in enhancing the near-source mixing ratio. The warmer climate has a reduced cross-tropopause gradient, primarily due to a slightly higher tropopause, which results in a reduction of about 25% in the average tropospheric tracer mixing ratio, and a corresponding enhancement in the stratosphere. A global variance budget shows increased mean and transient tracer variance due to increased generation from strengthened mean gradients near the source and weakened eddy and subgrid transport.

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Markus Stowasser, Kevin Hamilton, and George J. Boer

Abstract

The climatic response to a 5% increase in solar constant is analyzed in three coupled global ocean–atmosphere general circulation models, the NCAR Climate System Model version 1 (CSM1), the Community Climate System Model version 2 (CCSM2), and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled General Circulation Model version 3 (CGCM3). For this simple perturbation the quantitative values of the radiative climate forcing at the top of the atmosphere can be determined very accurately simply from a knowledge of the shortwave fluxes in the control run. The climate sensitivity and the geographical pattern of climate feedbacks, and of the shortwave, longwave, clear-sky, and cloud components in each model, are diagnosed as the climate evolves. After a period of adjustment of a few years, both the magnitude and pattern of the feedbacks become reasonably stable with time, implying that they may be accurately determined from relatively short integrations.

The global-mean forcing at the top of the atmosphere due to the solar constant change is almost identical in the three models. The exact value of the forcing in each case is compared with that inferred by regressing annual-mean top-of-the-atmosphere radiative imbalance against mean surface temperature change. This regression approach yields a value close to the directly diagnosed forcing for the CCCma model, but a value only within about 25% of the directly diagnosed forcing for the two NCAR models. These results indicate that this regression approach may have some practical limitation in its application, at least for some models.

The global climate sensitivities differ among the models by almost a factor of 2, and, despite an overall apparent similarity, the spatial patterns of the climate feedbacks are only modestly correlated among the three models. An exception is the clear-sky shortwave feedback, which agrees well in both magnitude and spatial pattern among the models. The biggest discrepancies are in the shortwave cloud feedback, particularly in the tropical and subtropical regions where it is strongly negative in the NCAR models but weakly positive in the CCCma model. Almost all of the difference in the global-mean total feedback (and climate sensitivity) among the models is attributable to the shortwave cloud feedback component.

All three models exhibit a region of positive feedback in the equatorial Pacific, which is surrounded by broad areas of negative feedback. These positive feedback regions appear to be associated with a local maximum of the surface warming. However, the models differ in the zonal structure of this surface warming, which ranges from a mean El Niño–like warming in the eastern Pacific in the CCCma model to a far-western Pacific maximum of warming in the NCAR CCSM2 model. A separate simulation with the CCSM2 model, in which these tropical Pacific zonal gradients of surface warming are artificially suppressed, shows no region of positive radiative feedback in the tropical Pacific. However, the global-mean feedback is only modestly changed in this constrained run, suggesting that the processes that produce the positive feedback in the tropical Pacific region may not contribute importantly to global-mean feedback and climate sensitivity.

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William J. Merryfield and George J. Boer

Abstract

Variability of subtropical cell (STC) overturning in the upper Pacific Ocean is examined in a coupled climate model in light of large observed changes in STC transport. In a 1000-yr control run, modeled STC variations are smaller than observed, but correlate in a similar way with low-frequency ENSO-like variability. In model runs that include anthropogenically forced climate change, STC pycnocline transports decrease progressively under the influence of global warming, attaining reductions of 8% by 2000 and 46% by 2100. Although the former reduction is insufficient to fully account for the apparent observed decline in STC transport over recent decades, it does suggest that global warming may have contributed to the observed changes. Analysis of coupled model results shows that STC transports play a significant role in modulating tropical Pacific Ocean heat content, and that such changes are dominated by anomalous currents advecting mean temperature, rather than by advection of temperature anomalies by mean currents.

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Vivek K. Arora and George J. Boer

Abstract

Root distribution is treated as a static component in most current dynamic vegetation models (DVMs). While changes in leaf and stem biomass are reflected in leaf area index (LAI) and vegetation height via specific leaf area (SLA) and allometric relationships, most DVMs assume that changes in root biomass do not result in changes in the root distribution profile and rooting depth. That is, the fraction of roots in soil layers, which is used to estimate transpiration, is taken to be constant and independent of root biomass and/or vegetation age. A methodology for parameterizing root distribution as a function of root biomass is proposed for use in dynamic vegetation models. In this representation, root distribution and rooting depth evolve and increase as root biomass increases, as is expected intuitively and as is seen in observations. Root biomass data from temperate coniferous, tropical evergreen, and tundra sites show that the approach successfully represents, to the first order, the change of root distribution and rooting depth as a function of root biomass.

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Vivek K. Arora and George J. Boer

Abstract

The variance budget of land surface hydrological quantities is analyzed in the second Atmospheric Model Intercomparison Project (AMIP2) simulation made with the Canadian Centre for Climate Modelling and Analysis (CCCma) third-generation general circulation model (AGCM3). The land surface parameterization in this model is the comparatively sophisticated Canadian Land Surface Scheme (CLASS). Second-order statistics, namely variances and covariances, are evaluated, and simulated variances are compared with observationally based estimates. The soil moisture variance is related to second-order statistics of surface hydrological quantities. The persistence time scale of soil moisture anomalies is also evaluated.

Model values of precipitation and evapotranspiration variability compare reasonably well with observationally based and reanalysis estimates. Soil moisture variability is compared with that simulated by the Variable Infiltration Capacity-2 Layer (VIC-2L) hydrological model driven with observed meteorological data. An equation is developed linking the variances and covariances of precipitation, evapotranspiration, and runoff to soil moisture variance via a transfer function. The transfer function is connected to soil moisture persistence in terms of lagged autocorrelation. Soil moisture persistence time scales are shorter in the Tropics and longer at high latitudes as is consistent with the relationship between soil moisture persistence and the latitudinal structure of potential evaporation found in earlier studies. In the Tropics, although the persistence of soil moisture anomalies is short and values of the transfer function small, high values of soil moisture variance are obtained because of high precipitation variability. At high latitudes, by contrast, high soil moisture variability is obtained despite modest precipitation variability since the persistence time scale of soil moisture anomalies is long. Model evapotranspiration estimates show little variability and soil moisture variability is dominated by precipitation and runoff, which account for about 90% of the soil moisture variance over land surface areas.

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Vivek K. Arora and George J. Boer

Abstract

The global distribution of vegetation is broadly determined by climate, and where bioclimatic parameters are favorable for several plant functional types (PFTs), by the competition between them. Most current dynamic global vegetation models (DGVMs) do not, however, explicitly simulate inter-PFT competition and instead determine the existence and fractional coverage of PFTs based on quasi-equilibrium climate–vegetation relationships. When competition is explicitly simulated, versions of Lotka–Volterra (LV) equations developed in the context of interaction between animal species are almost always used. These equations may, however, exhibit unrealistic behavior in some cases and do not, for example, allow the coexistence of different PFTs in equilibrium situations. Coexistence may, however, be obtained by introducing features and mechanisms such as temporal environmental variation and disturbance, among others.

A generalized version of the competition equations is proposed that includes the LV equations as a special case, which successfully models competition for a range of climate and vegetation regimes and for which coexistence is a permissible equilibrium solution in the absence of additional mechanisms. The approach is tested for boreal forest, tropical forest, savanna, and temperate forest locations within the framework of the Canadian Terrestrial Ecosystem Model (CTEM) and successfully simulates the observed successional behavior and the observed near-equilibrium distribution of coexisting PFTs.

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Rui M. Ponte, Richard D. Rosen, and George J. Boer

Abstract

Anomalies in the angular momentum of the atmosphere (M) during the 1982-83 El Niño event and the torques responsible for these anomalies are investigated using output from the Canadian Climate Centre general circulation model. Model values of M during the year of the event are generally larger than those for the model climatology, thereby capturing the observed tendency toward higher values of M during El Niñto. Differences exist between the model and observations in the timing and amplitude of the largest anomalies, but these differences may he due to natural variability and not necessarily directly associated with the 1982-83 El Niño conditions.

In late September and October 1982, the model atmosphere acquires momentum more rapidly than usual, leading to the development of the largest deviations from mean conditions at the end of this period, mostly associated with strong westerly momentum signals centered at 25°N. Large, sustained positive anomalies in tangential stress torques over the northern tropics are the major mechanism responsible for the modeled increase in M, but mountain torque anomalies centered at 35°N are also important at the end of October. A secondary maximum in the departure from mean M values occurs in January 1983 and is related to a general strengthening of westerly momentum anomalies over the model's tropical and midlatitude regions. Both mountain and tangential stress torques are involved in this episode, but no particular mechanism or region dominates the anomalous exchange of momentum.

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William J. Merryfield, Woo-Sung Lee, George J. Boer, Viatcheslav V. Kharin, John F. Scinocca, Gregory M. Flato, R. S. Ajayamohan, John C. Fyfe, Youmin Tang, and Saroja Polavarapu

Abstract

The Canadian Seasonal to Interannual Prediction System (CanSIPS) became operational at Environment Canada's Canadian Meteorological Centre (CMC) in December 2011, replacing CMC's previous two-tier system. CanSIPS is a two-model forecasting system that combines ensemble forecasts from the Canadian Centre for Climate Modeling and Analysis (CCCma) Coupled Climate Model, versions 3 and 4 (CanCM3 and CanCM4, respectively). Mean climate as well as climate trends and variability in these models are evaluated in freely running historical simulations. Initial conditions for CanSIPS forecasts are obtained from an ensemble of coupled assimilation runs. These runs assimilate gridded atmospheric analyses by means of a procedure that resembles the incremental analysis update technique, but introduces only a fraction of the analysis increment in order that differences between ensemble members reflect the magnitude of observational uncertainties. The land surface is initialized through its response to the assimilative meteorology, whereas sea ice concentration and sea surface temperature are relaxed toward gridded observational values. The subsurface ocean is initialized through surface forcing provided by the assimilation run, together with an offline variational assimilation of gridded observational temperatures followed by an adjustment of the salinity field to preserve static stability. The performance of CanSIPS historical forecasts initialized every month over the period 1981–2010 is documented in a companion paper. The CanCM4 model and the initialization procedures developed for CanSIPS have been employed as well for decadal forecasts, including those contributing to phase 5 of the Coupled Model Intercomparison Project.

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Vivek K. Arora, George J. Boer, Pierre Friedlingstein, Michael Eby, Chris D. Jones, James R. Christian, Gordon Bonan, Laurent Bopp, Victor Brovkin, Patricia Cadule, Tomohiro Hajima, Tatiana Ilyina, Keith Lindsay, Jerry F. Tjiputra, and Tongwen Wu

Abstract

The magnitude and evolution of parameters that characterize feedbacks in the coupled carbon–climate system are compared across nine Earth system models (ESMs). The analysis is based on results from biogeochemically, radiatively, and fully coupled simulations in which CO2 increases at a rate of 1% yr−1. These simulations are part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). The CO2 fluxes between the atmosphere and underlying land and ocean respond to changes in atmospheric CO2 concentration and to changes in temperature and other climate variables. The carbon–concentration and carbon–climate feedback parameters characterize the response of the CO2 flux between the atmosphere and the underlying surface to these changes. Feedback parameters are calculated using two different approaches. The two approaches are equivalent and either may be used to calculate the contribution of the feedback terms to diagnosed cumulative emissions. The contribution of carbon–concentration feedback to diagnosed cumulative emissions that are consistent with the 1% increasing CO2 concentration scenario is about 4.5 times larger than the carbon–climate feedback. Differences in the modeled responses of the carbon budget to changes in CO2 and temperature are seen to be 3–4 times larger for the land components compared to the ocean components of participating models. The feedback parameters depend on the state of the system as well the forcing scenario but nevertheless provide insight into the behavior of the coupled carbon–climate system and a useful common framework for comparing models.

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