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Alexis Berg, Benjamin R. Lintner, Kirsten L. Findell, Sergey Malyshev, Paul C. Loikith, and Pierre Gentine

Abstract

Understanding how different physical processes can shape the probability distribution function (PDF) of surface temperature, in particular the tails of the distribution, is essential for the attribution and projection of future extreme temperature events. In this study, the contribution of soil moisture–atmosphere interactions to surface temperature PDFs is investigated. Soil moisture represents a key variable in the coupling of the land and atmosphere, since it controls the partitioning of available energy between sensible and latent heat flux at the surface. Consequently, soil moisture variability driven by the atmosphere may feed back onto the near-surface climate—in particular, temperature. In this study, two simulations of the current-generation Geophysical Fluid Dynamics Laboratory (GFDL) Earth System Model, with and without interactive soil moisture, are analyzed in order to assess how soil moisture dynamics impact the simulated climate. Comparison of these simulations shows that soil moisture dynamics enhance both temperature mean and variance over regional “hotspots” of land–atmosphere coupling. Moreover, higher-order distribution moments, such as skewness and kurtosis, are also significantly impacted, suggesting an asymmetric impact on the positive and negative extremes of the temperature PDF. Such changes are interpreted in the context of altered distributions of the surface turbulent and radiative fluxes. That the moments of the temperature distribution may respond differentially to soil moisture dynamics underscores the importance of analyzing moments beyond the mean and variance to characterize fully the interplay of soil moisture and near-surface temperature. In addition, it is shown that soil moisture dynamics impacts daily temperature variability at different time scales over different regions in the model.

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Zachary Naiman, Paul J. Goodman, John P. Krasting, Sergey L. Malyshev, Joellen L. Russell, Ronald J. Stouffer, and Andrew T. Wittenberg

Abstract

Two state-of-the-art Earth system models (ESMs) were used in an idealized experiment to explore the role of mountains in shaping Earth’s climate system. Similar to previous studies, removing mountains from both ESMs results in the winds becoming more zonal and weaker Indian and Asian monsoon circulations. However, there are also broad changes to the Walker circulation and El Niño–Southern Oscillation (ENSO). Without orography, convection moves across the entire equatorial Indo-Pacific basin on interannual time scales. ENSO has a stronger amplitude, lower frequency, and increased regularity. A wider equatorial wind zone and changes to equatorial wind stress curl result in a colder cold tongue and a steeper equatorial thermocline across the Pacific basin during La Niña years. Anomalies associated with ENSO warm events are larger without mountains and have greater impact on the mean tropical climate than when mountains are present. Without mountains, the centennial-mean Pacific Walker circulation weakens in both models by approximately 45%, but the strength of the mean Hadley circulation changes by less than 2%. Changes in the Walker circulation in these experiments can be explained by the large spatial excursions of atmospheric deep convection on interannual time scales. These results suggest that mountains are an important control on the large-scale tropical circulation, impacting ENSO dynamics and the Walker circulation, but have little impact on the strength of the Hadley circulation.

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John P. Krasting, Ronald J. Stouffer, Stephen M. Griffies, Robert W. Hallberg, Sergey L. Malyshev, Bonita L. Samuels, and Lori T. Sentman

Abstract

Oceanic heat uptake (OHU) is a significant source of uncertainty in both the transient and equilibrium responses to increasing the planetary radiative forcing. OHU differs among climate models and is related in part to their representation of vertical and lateral mixing. This study examines the role of ocean model formulation—specifically the choice of the vertical coordinate and the strength of the background diapycnal diffusivity K d—in the millennial-scale near-equilibrium climate response to a quadrupling of atmospheric CO2. Using two fully coupled Earth system models (ESMs) with nearly identical atmosphere, land, sea ice, and biogeochemical components, it is possible to independently configure their ocean model components with different formulations and produce similar near-equilibrium climate responses. The SST responses are similar between the two models (r 2 = 0.75, global average ~4.3°C) despite their initial preindustrial climate mean states differing by 0.4°C globally. The surface and interior responses of temperature and salinity are also similar between the two models. However, the Atlantic meridional overturning circulation (AMOC) responses are different between the two models, and the associated differences in ventilation and deep-water formation have an impact on the accumulation of dissolved inorganic carbon in the ocean interior. A parameter sensitivity analysis demonstrates that increasing the amount of K d produces very different near-equilibrium climate responses within a given model. These results suggest that the impact of the ocean vertical coordinate on the climate response is small relative to the representation of subgrid-scale mixing.

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P. C. D. Milly, Sergey L. Malyshev, Elena Shevliakova, Krista A. Dunne, Kirsten L. Findell, Tom Gleeson, Zhi Liang, Peter Phillipps, Ronald J. Stouffer, and Sean Swenson

Abstract

LM3 is a new model of terrestrial water, energy, and carbon, intended for use in global hydrologic analyses and as a component of earth-system and physical-climate models. It is designed to improve upon the performance and to extend the scope of the predecessor Land Dynamics (LaD) and LM3V models by better quantifying the physical controls of climate and biogeochemistry and by relating more directly to components of the global water system that touch human concerns. LM3 includes multilayer representations of temperature, liquid water content, and ice content of both snowpack and macroporous soil–bedrock; topography-based description of saturated area and groundwater discharge; and transport of runoff to the ocean via a global river and lake network. Sensible heat transport by water mass is accounted throughout for a complete energy balance. Carbon and vegetation dynamics and biophysics are represented as in LM3V. In numerical experiments, LM3 avoids some of the limitations of the LaD model and provides qualitatively (though not always quantitatively) reasonable estimates, from a global perspective, of observed spatial and/or temporal variations of vegetation density, albedo, streamflow, water-table depth, permafrost, and lake levels. Amplitude and phase of annual cycle of total water storage are simulated well. Realism of modeled lake levels varies widely. The water table tends to be consistently too shallow in humid regions. Biophysical properties have an artificial stepwise spatial structure, and equilibrium vegetation is sensitive to initial conditions. Explicit resolution of thick (>100 m) unsaturated zones and permafrost is possible, but only at the cost of long (≫300 yr) model spinup times.

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John P. Dunne, Jasmin G. John, Alistair J. Adcroft, Stephen M. Griffies, Robert W. Hallberg, Elena Shevliakova, Ronald J. Stouffer, William Cooke, Krista A. Dunne, Matthew J. Harrison, John P. Krasting, Sergey L. Malyshev, P. C. D. Milly, Peter J. Phillipps, Lori T. Sentman, Bonita L. Samuels, Michael J. Spelman, Michael Winton, Andrew T. Wittenberg, and Niki Zadeh

Abstract

The physical climate formulation and simulation characteristics of two new global coupled carbon–climate Earth System Models, ESM2M and ESM2G, are described. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory’s previous Climate Model version 2.1 (CM2.1) while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4p1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in El Niño–Southern Oscillation being overly strong in ESM2M and overly weak in ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to total heat content variability given its lack of long-term drift, gyre circulation, and ventilation in the North Pacific, tropical Atlantic, and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to surface circulation given its superior surface temperature, salinity, and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. The overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon–climate models.

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Zhichang Guo, Paul A. Dirmeyer, Randal D. Koster, Y. C. Sud, Gordon Bonan, Keith W. Oleson, Edmond Chan, Diana Verseghy, Peter Cox, C. T. Gordon, J. L. McGregor, Shinjiro Kanae, Eva Kowalczyk, David Lawrence, Ping Liu, David Mocko, Cheng-Hsuan Lu, Ken Mitchell, Sergey Malyshev, Bryant McAvaney, Taikan Oki, Tomohito Yamada, Andrew Pitman, Christopher M. Taylor, Ratko Vasic, and Yongkang Xue

Abstract

The 12 weather and climate models participating in the Global Land–Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land–atmosphere coupling and some intriguing commonalities. In this paper, the causes of variations in coupling strength—both the geographic variations within a given model and the model-to-model differences—are addressed. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage—an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first-stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation–precipitation connection, however, also play a key role.

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John P. Dunne, Jasmin G. John, Elena Shevliakova, Ronald J. Stouffer, John P. Krasting, Sergey L. Malyshev, P. C. D. Milly, Lori T. Sentman, Alistair J. Adcroft, William Cooke, Krista A. Dunne, Stephen M. Griffies, Robert W. Hallberg, Matthew J. Harrison, Hiram Levy, Andrew T. Wittenberg, Peter J. Phillips, and Niki Zadeh

Abstract

The authors describe carbon system formulation and simulation characteristics of two new global coupled carbon–climate Earth System Models (ESM), ESM2M and ESM2G. These models demonstrate good climate fidelity as described in part I of this study while incorporating explicit and consistent carbon dynamics. The two models differ almost exclusively in the physical ocean component; ESM2M uses the Modular Ocean Model version 4.1 with vertical pressure layers, whereas ESM2G uses generalized ocean layer dynamics with a bulk mixed layer and interior isopycnal layers. On land, both ESMs include a revised land model to simulate competitive vegetation distributions and functioning, including carbon cycling among vegetation, soil, and atmosphere. In the ocean, both models include new biogeochemical algorithms including phytoplankton functional group dynamics with flexible stoichiometry. Preindustrial simulations are spun up to give stable, realistic carbon cycle means and variability. Significant differences in simulation characteristics of these two models are described. Because of differences in oceanic ventilation rates, ESM2M has a stronger biological carbon pump but weaker northward implied atmospheric CO2 transport than ESM2G. The major advantages of ESM2G over ESM2M are improved representation of surface chlorophyll in the Atlantic and Indian Oceans and thermocline nutrients and oxygen in the North Pacific. Improved tree mortality parameters in ESM2G produced more realistic carbon accumulation in vegetation pools. The major advantages of ESM2M over ESM2G are reduced nutrient and oxygen biases in the southern and tropical oceans.

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Thomas L. Delworth, Anthony J. Broccoli, Anthony Rosati, Ronald J. Stouffer, V. Balaji, John A. Beesley, William F. Cooke, Keith W. Dixon, John Dunne, K. A. Dunne, Jeffrey W. Durachta, Kirsten L. Findell, Paul Ginoux, Anand Gnanadesikan, C. T. Gordon, Stephen M. Griffies, Rich Gudgel, Matthew J. Harrison, Isaac M. Held, Richard S. Hemler, Larry W. Horowitz, Stephen A. Klein, Thomas R. Knutson, Paul J. Kushner, Amy R. Langenhorst, Hyun-Chul Lee, Shian-Jiann Lin, Jian Lu, Sergey L. Malyshev, P. C. D. Milly, V. Ramaswamy, Joellen Russell, M. Daniel Schwarzkopf, Elena Shevliakova, Joseph J. Sirutis, Michael J. Spelman, William F. Stern, Michael Winton, Andrew T. Wittenberg, Bruce Wyman, Fanrong Zeng, and Rong Zhang

Abstract

The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved.

Two versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2° latitude × 2.5° longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1° in latitude and longitude, with meridional resolution equatorward of 30° becoming progressively finer, such that the meridional resolution is 1/3° at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments.

The control simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and the land model, both of which act to increase the net surface shortwave radiation in CM2.1, thereby reducing an overall cold bias present in CM2.0; and 3) a reduction of ocean lateral viscosity in the extratropics in CM2.1, which reduces sea ice biases in the North Atlantic.

Both models have been used to conduct a suite of climate change simulations for the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment report and are able to simulate the main features of the observed warming of the twentieth century. The climate sensitivities of the CM2.0 and CM2.1 models are 2.9 and 3.4 K, respectively. These sensitivities are defined by coupling the atmospheric components of CM2.0 and CM2.1 to a slab ocean model and allowing the model to come into equilibrium with a doubling of atmospheric CO2. The output from a suite of integrations conducted with these models is freely available online (see http://nomads.gfdl.noaa.gov/).

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Leo J. Donner, Bruce L. Wyman, Richard S. Hemler, Larry W. Horowitz, Yi Ming, Ming Zhao, Jean-Christophe Golaz, Paul Ginoux, S.-J. Lin, M. Daniel Schwarzkopf, John Austin, Ghassan Alaka, William F. Cooke, Thomas L. Delworth, Stuart M. Freidenreich, C. T. Gordon, Stephen M. Griffies, Isaac M. Held, William J. Hurlin, Stephen A. Klein, Thomas R. Knutson, Amy R. Langenhorst, Hyun-Chul Lee, Yanluan Lin, Brian I. Magi, Sergey L. Malyshev, P. C. D. Milly, Vaishali Naik, Mary J. Nath, Robert Pincus, Jeffrey J. Ploshay, V. Ramaswamy, Charles J. Seman, Elena Shevliakova, Joseph J. Sirutis, William F. Stern, Ronald J. Stouffer, R. John Wilson, Michael Winton, Andrew T. Wittenberg, and Fanrong Zeng

Abstract

The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for the atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol–cloud interactions, chemistry–climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical system component of earth system models and models for decadal prediction in the near-term future—for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud droplet activation by aerosols, subgrid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with ecosystem dynamics and hydrology. Its horizontal resolution is approximately 200 km, and its vertical resolution ranges approximately from 70 m near the earth’s surface to 1 to 1.5 km near the tropopause and 3 to 4 km in much of the stratosphere. Most basic circulation features in AM3 are simulated as realistically, or more so, as in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks remains problematic, as in AM2. The most intense 0.2% of precipitation rates occur less frequently in AM3 than observed. The last two decades of the twentieth century warm in CM3 by 0.32°C relative to 1881–1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of 0.56° and 0.52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol–cloud interactions, and its warming by the late twentieth century is somewhat less realistic than in CM2.1, which warmed 0.66°C but did not include aerosol–cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud–aerosol interactions to limit greenhouse gas warming.

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