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Starley L. Thompson
and
David Pollard

Abstract

The present-day climatology of a global climate model (GENESIS Version 1.02) is described. The model includes a land-surface transfer component (LSX) that accounts for the physical effects of vegetation. The atmospheric general circulation model is derived from the NCAR CCM1 and modified to include semi-Lagrangian transport of water vapor, subgrid plume convection, PBL mixing, a more complex cloud scheme, and a diurnal cycle. The surface models consist of LSX; multilayer models of soil, snow, and sea ice; sea ice dynamics; and a slab mixed layer ocean. Brief descriptions of the current model components are included in an appendix. GENESIS is an ongoing project to develop an earth system model prototype for global change research. The Version 1.02 climate model has already proved useful in paleoclimate studies.

Results of present-day simulations are described using an atmospheric spectral resolution of RIS (∼4.5° lat×7.5° long) and a surface-model resolution of 2°×2°. In general the quality of the simulations is comparable to that of previous coarse-grid models with predicted sea-surface temperatures. Most of the errors are attributed to coarse atmospheric resolution, inaccurate cloud parameterization, large ocean roughness length, and lack of ocean dynamics.

The results are compared with those using a simplified bucket-soil model and crude parameterizations of surface albedo and roughness. Although quite similar results are obtained on global scales, significant regional differences including surface warming and drying occur in some regions of Amazonia and northern midlatitude continental interiors.

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Starley L. Thompson
and
David Pollard

Abstract

The sensitivity of the equilibrium climate to doubled atmospheric CO2 is investigated using the GENESIS global climate model version 1.02. The atmospheric general circulation model is a heavily modified version of the NCAR CCM1 and is coupled to a multicanopy land-surface model (LSX); multilayer models of soil, snow, and sea ice; and a slab ocean mixed layer. Features that are relatively new in CO2 sensitivity studies include explicit subgrid convective plumes, PBL mixing, a diurnal cycle, a complex land-surface model, sea ice dynamics and semi-Lagrangian transport of water vapor.

The global annual surface-air warming in the model is 2.1°C, with global precipitation increasing by 3.3%. Over most land areas, most of the changes in precipitation are insignificant at the 5% level compared to interannual variability. Decreases in soil moisture in summer are not as large as in most previous models and only occur poleward of ∼55°N in Siberia, northern Canada, and Alaska. Sea ice area in September recedes by 62% in the Arctic and by 43% in the Antarctic. The area of Northern Hemispheric permafrost decreases by 48%, while the total area of Northern Hemispheric snowcover in January decreases by only 13%.

The effects of several modifications to the model physics are described. Replacing LSX and the multilayer soil with a single-layer bucket model causes little change to CO2 sensitivities on global scales, and the regions of summer drying in northern high latitudes are reproduced, although with somewhat greater amplitude. Compared to convective adjustment, penetrative plume convection increases the tropical Hadley Cell response but decreases the global warming slightly by 0.1° to 0.30°, contrary to several previous GCM studies in which penetrative convection was associated with greater CO2 warming. Similarly, the use of a cruder parameterization for cloud amount changes the local patterns of cloud response but has slight effect on the global warming. The authors discuss implications of the greater global warming (3.2°C) found in an earlier version of the model and suggest that it was due to more detailed interactions that no longer occur in the current version.

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Natalya Gomez
,
Konstantin Latychev
, and
David Pollard

Abstract

A gravitationally self-consistent, global sea level model with 3D viscoelastic Earth structure is interactively coupled to a 3D dynamic ice sheet model, and the coupled model is applied to simulate the evolution of ice cover, sea level changes, and solid Earth deformation over the last deglaciation, from 40 ka to the modern. The results show that incorporating lateral variations in Earth’s structure across Antarctica yields local differences in the modeled ice history and introduces significant uncertainty in estimates of both relative sea level change and modern crustal motions through the last deglaciation. An analysis indicates that the contribution of glacial isostatic adjustment to modern records of sea level change and solid Earth deformation in regions of Antarctica underlain by low mantle viscosity may be more sensitive to ice loading during the late Holocene than across the last deglaciation.

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Starley L. Thompson
and
David Pollard

Abstract

As anthropogenic greenhouse warming occurs in the next century, changes in the mass balances of Greenland and Antarctica will probably accelerate and may have significant effects on global sea level. Recent trends and possible future changes in these mass balances have received considerable attention in the glaciological literature, but until recently relatively few general circulation modeling (GCM) studies have focused on the problem. However, there are two significant problems in using GCMs to predict mass balance distributions on ice sheets: (i) the relatively coarse GCM horizontal resolution truncates the topography of the ice-sheet flanks and smaller ice sheets such as Greenland, and (ii) the snow and ice physics in most GCMs does not include ice-sheet-specific processes such as the refreezing of meltwater.

Two techniques are described that attack these problems, involving (i) an elevation-based correction to the surface meteorology and (ii) a simple a posteriori correction for the refreezing of meltwater following Pfeffer et al Using these techniques in a new version 2 of the Global Environmental and Ecological Simulation of Interactive Systems global climate model, the authors present global climate and ice-sheet mass-balance results from two equilibrated runs for present and doubled atmospheric CO2. This GCM is well suited for ice-sheet mass-balance studies because (a) the surface can be represented at a finer resolution (2° lat × 2° long) than the atmospheric GCM, (b) the two correction techniques are included as part of the model, and (c) the model’s mass balances for present-day Greenland and Antarctica are realistic.

When atmospheric CO2 is doubled, the net annual surface mass balance decreases on Greenland from +13 to −12 cm yr−1 and increases on Antarctica from +18 to +21 cm yr−1. The corresponding changes in the ice-sheet contributions to global sea level are +1.2 and −1.3 mm yr−1, respectively, yielding a combined contribution of −0.1 mm yr−1. That would be a very minor component of the total sea level rise of ∼5 mm yr−1 expected in the next century, mainly from thermal expansion of the oceans and melting of smaller glaciers. However, biases in the GCM climate suggest a range of uncertainty in the ice-sheet contribution from about −2 to +1 mm yr−1.

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Samuel Levis
,
Jonathan A. Foley
, and
David Pollard

Abstract

Changes in vegetation cover are known to influence the climate system by modifying the radiative, momentum, and hydrologic balance of the land surface. To explore the interactions between terrestrial vegetation and the atmosphere for doubled atmospheric CO2 concentrations, the newly developed fully coupled GENESIS–IBIS climate–vegetation model is used. The simulated climatic response to the radiative and physiological effects of elevated CO2 concentrations, as well as to ensuing simulated shifts in global vegetation patterns is investigated.

The radiative effects of elevated CO2 concentrations raise temperatures and intensify the hydrologic cycle on the global scale. In response, soil moisture increases in the mid- and high latitudes by 4% and 5%, respectively. Tropical soil moisture, however, decreases by 5% due to a decrease in precipitation minus evapotranspiration.

The direct, physiological response of plants to elevated CO2 generally acts to weaken the earth’s hydrologic cycle by lowering transpiration rates across the globe. Lowering transpiration alone would tend to enhance soil moisture. However, reduced recirculation of water in the atmosphere, which lowers precipitation, leads to more arid conditions overall (simulated global soil moisture decreases by 1%), particularly in the Tropics and midlatitudes.

Allowing structural changes in the vegetation cover (in response to changes in climate and CO2 concentrations) overrides the direct physiological effects of CO2 on vegetation in many regions. For example, increased simulated forest cover in the Tropics enhances canopy evapotranspiration overall, offsetting the decreased transpiration due to lower leaf conductance. As a result of increased circulation of moisture through the hydrologic cycle, precipitation increases and soil moisture returns to the value simulated with just the radiative effects of elevated CO2. However, in the highly continental midlatitudes, changes in vegetation cover cause soil moisture to decline by an additional 2%. Here, precipitation does not respond sufficiently to increased plant-water uptake, due to a limited source of external moisture into the region.

These results illustrate that vegetation feedbacks may operate differently according to regional characteristics of the climate and vegetation cover. In particular, it is found that CO2 fertilization can cause either an increase or a decrease in available soil moisture, depending on the associated changes in vegetation cover and the ability of the regional climate to recirculate water vapor. This is in direct contrast to the view that CO2 fertilization will enhance soil moisture and runoff across the globe: a view that neglects changes in vegetation structure and local climatic feedbacks.

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Sukyoung Lee
,
Steven Feldstein
,
David Pollard
, and
Tim White

Abstract

Viable explanations for equable climates of the Cretaceous and early Cenozoic (from about 145 to 50 million years ago), especially for the above-freezing temperatures detected for high-latitude continental winters, have been a long-standing challenge. In this study, the authors suggest that enhanced and localized tropical convection, associated with a strengthened paleo–warm pool, may contribute toward high-latitude warming through the excitation of poleward-propagating Rossby waves. This warming takes place through the poleward heat flux and an overturning circulation that accompany the Rossby waves. This mechanism is tested with an atmosphere–mixed layer ocean general circulation model (GCM) by imposing idealized localized heating and compensating cooling, a heating structure that mimics the effect of warm-pool convective heating.

The localized tropical heating is indeed found to contribute to a warming of the Arctic during the winter. Within the range of 0–150 W m−2 for the heating intensity, the average rate for the zonal mean Arctic surface warming is 0.8°C per (10 W m−2) increase in the heating for the runs with an atmospheric CO2 level of 4 × PAL (Preindustrial Atmospheric Level, 1 PAL = 280 ppmv), the Cretaceous and early Cenozoic values considered for this study. This rate of warming for the Arctic is lower in model runs with 1 × PAL CO2, which show an increase of 0.3°C per (10 W m−2). Further increase of the heating intensity beyond 150 W m−2 produces little change in the Arctic surface air temperature. This saturation behavior is interpreted as being a result of nonlinear wave–wave interaction, which leads to equatorward wave refraction.

Under the 4 × PAL CO2 level, raising the heating from 120 W m−2 (estimated warm-pool convective heating value for the present-day climate) to 150 and 180 W m −2 (estimated values for the Cretaceous and early Cenozoic) produces a warming of 4°–8°C over northern Siberia and the adjacent Arctic Ocean. Relative to the warming caused by a quadrupling of CO2 alone, this temperature increase accounts for about 30% of the warming over this region. The possible influence of warm-pool convective heating on the present-day Arctic is also discussed.

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Ming Chen
,
David Pollard
, and
Eric J. Barron

Abstract

A regional coupled soil–vegetation–atmosphere model is used to study changes and interactions between climate and the ecosystem in East Asia due to increased atmospheric CO2. The largest simulated climate changes are due to the radiative influence of CO2, modified slightly by vegetation feedbacks. Annual precipitation increases by about 20% in coastal areas of northern China and in central China, but only by 8% in southern China. The strongest warming of up to 4°C occurs in summer in northern China. Generally, the climate tends to be warmer and wetter under doubled CO2 except for inland areas of northern China, where it becomes warmer and drier. Most of the changes discussed in this paper are associated with changes in the East Asian monsoon, which is intensified under doubled CO2.

The largest changes and feedbacks between vegetation and climate occur in northern China. In some coastal and central areas around 40°N, temperate deciduous forests expand northward, replacing grassland due to warmer and wetter climate. Evergreen taiga retreats in the coastal northeast, causing extra cooling feedback due to less snow masking. The largest changes occur in extensive inland regions northward of 40°N, where deserts and shrub land expand due to warmer and drier conditions, and water supply is a critical factor for vegetation. These northern inland ecosystems experience considerable degradation and desertification, indicating a marked sensitivity and vulnerability to climatic change.

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Gordon B. Bonan
,
David Pollard
, and
Starley L. Thompson

Abstract

The statistical representation of multiple land surfaces within a grid cell has received attention as a means to parameterize the nonlinear effects of subgrid-scale heterogeneity on land-atmosphere energy exchange. However, previous analyses have not identified the critical land-surface parameters to which energy exchanges are sensitive; the appropriate number of within-grid-cell classes for a particular parameter, or the effects of interactions among several parameters on the nonlinearity of energy exchanges. The analyses reported here used a land-surface scheme for climate models to examine the effects of subgrid variability in leaf area index, minimum and maximum stomatal resistances, and soil moisture on grid-scale fluxes. Comparisons between energy fluxes obtained using parameter values for the average of 100 subgrid points and the average fluxes for the 100 subgrid points showed minor differences for emitted infrared radiation and reflected solar radiation, but large differences for sensible heat and evapotranspiration. Leaf area index was the most important parameter; stomatal resistances were only important on wet soils. Interactions among parameters increased the nonlinearity of land-atmosphere energy exchange. When considered separately, six to ten values of each parameter greatly reduced the deviation between the two flux estimates. However, this approach became cumbersome when all four parameters varied independently. These analyses suggest that the debate over how to best parameterize the nonlinear effects of subgrid-scale heterogeneity on land-atmosphere interactions will continue.

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Sukyoung Lee
,
Tingting Gong
,
Nathaniel Johnson
,
Steven B. Feldstein
, and
David Pollard

Abstract

This study presents mechanisms for the polar amplification of surface air temperature that occurred in the Northern Hemisphere (NH) between the periods of 1958–77 (P1) and 1982–2001 (P2). Using European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) reanalysis data, it is found that over the ice-covered Arctic Ocean, the winter surface warming arises from dynamic warming (stationary eddy heat flux and adiabatic warming). Over the ice-free Arctic Ocean between the Greenland and the Barents Seas, downward infrared radiative (IR) flux is found to dominate the warming.

To investigate whether the difference in the flow between P1 and P2 is due to changes in the frequency of occurrence of a small number of teleconnection patterns, a coupled self-organizing map (SOM) analysis of the 250-hPa streamfunction and tropical convective precipitation is performed. The latter field was specified to lead the former by 5 days. The results of the analysis showed that the P2 − P1 trend arises from a decrease in the frequency of negative phase PNA-like and circumglobal streamfunction patterns and a corresponding increase in the frequency of positive PNA-like and circumglobal streamfunction patterns. The occurrence of the two strong 1982–83 and 1997–98 El Niño events also contributes toward this trend. The corresponding trend in the convective precipitation is from below average to above average values in the tropical Indo-western Pacific region. Each of the above patterns was found to have an e-folding time scale from 6 to 8 days, which implies that the P2 − P1 trend can be understood as arising from the change in the frequency of occurrence of teleconnection patterns that fluctuate on intraseasonal time scales.

The link between intraseasonal and interannual variability was further examined by linearly regressing various quantities against trend patterns with interannual variability subtracted. It was found that enhanced convective precipitation is followed 3–6 days later by the occurrence of the P2 − P1 circulation trend pattern, and then 1–2 days later by the corresponding trend pattern in the downward IR flux. This finding suggests that an increased frequency of the above sequence of events, which occurs on intraseasonal time scales, can account for the NH winter polar amplification of the surface air temperature via increased dynamic warming and downward IR flux.

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James Foster
,
Glen Liston
,
Randy Koster
,
Richard Essery
,
Helga Behr
,
Lydia Dumenil
,
Diana Verseghy
,
Starly Thompson
,
David Pollard
, and
Judah Cohen

Abstract

Confirmation of the ability of general circulation models (GCMs) to accurately represent snow cover and snow mass distributions is vital for climate studies. There must be a high degree of confidence that what is being predicted by the models is reliable, since realistic results cannot be assured unless they are tested against results from observed data or other available datasets. In this study, snow output from seven GCMs and passive-microwave snow data derived from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) are intercompared. National Oceanic and Atmospheric Administration satellite data are used as the standard of reference for snow extent observations and the U.S. Air Force snow depth climatology is used as the standard for snow mass. The reliability of the SMMR snow data needs to be verified, as well, because currently this is the only available dataset that allows for yearly and monthly variations in snow depth. [The GCMs employed in this investigation are the United Kingdom Meteorological Office, Hadley Centre GCM, the Max Planck Institute for Meteorology/University of Hamburg (ECHAM) GCM, the Canadian Climate Centre GCM, the National Center for Atmospheric Research (GENESIS) GCM, the Goddard Institute for Space Studies GCM, the Goddard Laboratory for Atmospheres GCM and the Goddard Coupled Climate Dynamics Group (AIRES) GCM.] Data for both North America and Eurasia are examined in an effort to assess the magnitude of spatial and temporal variations that exist between the standards of reference, the models, and the passive microwave data. Results indicate that both the models and SMMR represent seasonal and year-to-year snow distributions fairly well. The passive microwave data and several of the models, however, consistently underestimate snow mass, but other models overestimate the mass of snow on the ground. The models do a better job simulating winter and summer snow conditions than in the transition months. In general, the underestimation by SMMR is caused by absorption of microwave energy by vegetation. For the GCMs, differences between observed snow conditions can be ascribed to inaccuracies in simulating surface air temperatures and precipitation fields, especially during the spring and fall.

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