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Xin Lin, David A. Randall, and Laura D. Fowler

Abstract

The simulated diurnal cycle is in many ways an ideal test bed for new physical parameterizations. The purpose of this paper is to compare observations from the Tropical Rainfall Measurement Mission, the Earth Radiation Budget Experiment, the International Satellite Cloud Climatology Project, the Clouds and the Earth’s Radiant Energy System Experiment, and the Anglo-Brazilian Amazonian Climate Observation Study with the diurnal variability of the Amazonian hydrologic cycle and radiative energy budget as simulated by the Colorado State University general circulation model, and to evaluate improvements and deficiencies of the model physics. The model uses a prognostic cumulus kinetic energy (CKE) to relax the quasi-equilibrium closure of the Arakawa–Schubert cumulus parameterization. A parameter, α, is used to relate the CKE to the cumulus mass flux. This parameter is expected to vary with cloud depth, mean shear, and the level of convective activity, but up to now a single constant value for all cloud types has been used. The results of the present study show clearly that this approach cannot yield realistic simulations of both the diurnal cycle and the monthly mean climate state. Improved results are obtained using a version of the model in which α is permitted to vary with cloud depth.

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Todd D. Ringler, Ross P. Heikes, and David A. Randall

Abstract

This paper documents the development and testing of a new type of atmospheric dynamical core. The model solves the vorticity and divergence equations in place of the momentum equation. The model is discretized in the horizontal using a geodesic grid that is nearly uniform over the entire globe. The geodesic grid is formed by recursively bisecting the triangular faces of a regular icosahedron and projecting those new vertices onto the surface of the sphere. All of the analytic horizontal operators are reduced to line integrals, which are numerically evaluated with second-order accuracy. In the vertical direction the model can use a variety of coordinate systems, including a generalized sigma coordinate that is attached to the top of the boundary layer. Terms related to gravity wave propagation are isolated and an efficient semi-implicit time-stepping scheme is implemented. Since this model combines many of the positive attributes of both spectral models and conventional finite-difference models into a single dynamical core, it represents a distinctively new approach to modeling the atmosphere’s general circulation.

The model is tested using the idealized forcing proposed by Held and Suarez. Results are presented for simulations using 2562 polygons (approximately 4.5° × 4.5°) and using 10 242 polygons (approximately 2.25° × 2.25°). The results are compared to those obtained with spectral model simulations truncated at T30 and T63. In terms of first and second moments of state variables such as the zonal wind, meridional wind, and temperature, the geodesic grid model results using 2562 polygons are comparable to those of a spectral model truncated at slightly less than T30, while a simulation with 10 242 polygons is comparable to a spectral model simulation truncated at slightly less than T63.

In order to further demonstrate the viability of this modeling approach, preliminary results obtained from a full-physics general circulation model that uses this dynamical core are presented. The dominant features of the DJF climate are captured in the full-physics simulation.

In terms of computational efficiency, the geodesic grid model is somewhat slower than the spectral model used for comparison. Model timings completed on an SGI Origin 2000 indicate that the geodesic grid model with 10 242 polygons is 20% slower than the spectral model truncated at T63. The geodesic grid model is more competitive at higher resolution than at lower resolution, so further optimization and future trends toward higher resolution should benefit the geodesic grid model.

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Bruce A. Wielicki, Robert D. Cess, Michael D. King, David A. Randall, and Edwin F. Harrison

The role of clouds in modifying the earth's radiation balance is well recognized as a key uncertainty in predicting any potential future climate change. This statement is true whether the climate change of interest is caused by changing emissions of greenhouse gases and sulfates, deforestation, ozone depletion, volcanic eruptions, or changes in the solar constant. This paper presents an overview of the role of the National Aeronautics and Space Administration's Earth Observing System (EOS) satellite data in understanding the role of clouds in the global climate system. The paper gives a brief summary of the cloud/radiation problem, and discusses the critical observations needed to support further investigations. The planned EOS data products are summarized, including the critical advances over current satellite cloud and radiation budget data. Key advances include simultaneous observation of radiation budget and cloud properties, additional information on cloud particle size and phase, improved detection of thin clouds and multilayer cloud systems, greatly reduced ambiguity in partially cloud-filled satellite fields of view, improved calibration and stability of satellite-observed radiances, and improved estimates of radiative fluxes at the top of the atmosphere, at the surface, and at levels within the atmosphere. Outstanding sampling and remote sensing issues that affect data quality are also discussed. Finally, the EOS data are placed in the context of other satellite observations as well as the critical surface, field experiment, and laboratory data needed to address the role of clouds in the climate system. It is concluded that the EOS data are a necessary but insufficient condition for solution of the scientific cloud/radiation issues. A balanced approach of satellite, field, and laboratory data will be required. These combined data can span the necessary spatial scales of global, regional, cloud cell, and cloud particle physics (i.e., from 108 to 10−7 m).

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David A. Randall, Anthony D. Del Genio, Leo J. Donner, William D. Collins, and Stephen A. Klein
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Charlotte A. DeMott, Cristiana Stan, David A. Randall, and Mark D. Branson

Abstract

The interaction of ocean coupling and model physics in the simulation of the intraseasonal oscillation (ISO) is explored with three general circulation models: the Community Atmospheric Model, versions 3 and 4 (CAM3 and CAM4), and the superparameterized CAM3 (SPCAM3). Each is integrated coupled to an ocean model, and as an atmosphere-only model using sea surface temperatures (SSTs) from the coupled SPCAM3, which simulates a realistic ISO. For each model, the ISO is best simulated with coupling. For each SST boundary condition, the ISO is best simulated in SPCAM3.

Near-surface vertical gradients of specific humidity, (temperature, ), explain ~20% (50%) of tropical Indian Ocean latent (sensible) heat flux variance, and somewhat less of west Pacific variance. In turn, local SST anomalies explain ~5% (25%) of variance in coupled simulations, and less in uncoupled simulations. Ergo, latent and sensible heat fluxes are strongly controlled by wind speed fluctuations, which are largest in the coupled simulations, and represent a remote response to coupling. The moisture budget reveals that wind variability in coupled simulations increases east-of-convection midtropospheric moistening via horizontal moisture advection, which influences the direction and duration of ISO propagation.

These results motivate a new conceptual model for the role of ocean feedbacks on the ISO. Indian Ocean surface fluxes help developing convection attain a magnitude capable of inducing the circulation anomalies necessary for downstream moistening and propagation. The “processing” of surface fluxes by model physics strongly influences the moistening details, leading to model-dependent responses to coupling.

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L. Bounoua, G. J. Collatz, S. O. Los, P. J. Sellers, D. A. Dazlich, C. J. Tucker, and D. A. Randall

Abstract

The sensitivity of global and regional climate to changes in vegetation density is investigated using a coupled biosphere–atmosphere model. The magnitude of the vegetation changes and their spatial distribution are based on natural decadal variability of the normalized difference vegetation index (NDVI). Different scenarios using maximum and minimum vegetation cover were derived from satellite records spanning the period 1982–90.

Albedo decreased in the northern latitudes and increased in the Tropics with increased NDVI. The increase in vegetation density revealed that the vegetation’s physiological response was constrained by the limits of the available water resources. The difference between the maximum and minimum vegetation scenarios resulted in a 46% increase in absorbed visible solar radiation and a similar increase in gross photosynthetic CO2 uptake on a global annual basis. This increase caused the canopy transpiration and interception fluxes to increase and reduced those from the soil. The redistribution of the surface energy fluxes substantially reduced the Bowen ratio during the growing season, resulting in cooler and moister near-surface climate, except when soil moisture was limiting.

Important effects of increased vegetation on climate are

  • a cooling of about 1.8 K in the northern latitudes during the growing season and a slight warming during the winter, which is primarily due to the masking of high albedo of snow by a denser canopy; and

  • a year-round cooling of 0.8 K in the Tropics.

These results suggest that increases in vegetation density could partially compensate for parallel increases in greenhouse warming. Increasing vegetation density globally caused both evapotranspiration and precipitation to increase. Evapotranspiration, however, increased more than precipitation, resulting in a global soil-water deficit of about 15%. A spectral analysis on the simulated results showed that changes in the state of vegetation could affect the low-frequency modes of the precipitation distribution and might reduce its low-frequency variability in the Tropics while increasing it in northern latitudes.

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C.-H. Moeng, P. P. Sullivan, M. F. Khairoutdinov, and D. A. Randall

Abstract

A large-domain large-eddy simulation of a tropical deep convection system is used as a benchmark to derive and test a mixed subgrid-scale (SGS) scheme for scalar and momentum fluxes in cloud-resolving models (CRMs). The benchmark simulation resolves a broad range of scales ranging from mesoscale organizations, through gravity waves and individual clouds, down to energy-containing turbulent eddies. A spectral analysis shows that the vertical-velocity kinetic energy peaks at scales from hundreds of meters in the lower cloud layer to several kilometers higher up; these scales are typical grid sizes of today’s CRMs. The analysis also shows that a significant portion of the scalar and momentum fluxes in the benchmark simulation are carried by motions smaller than several kilometers (i.e., smaller than a typical grid resolution of CRMs). The broad range of scales of the benchmark simulation is split into two components: filter scale (mimicking CRM resolvable scale) and subfilter scale (mimicking CRM SGS), using filter widths characteristic of a typical CRM grid spacing. The local relationship of the subfilter-scale fluxes to the filter-scale variables is examined. This leads to a mixed SGS scheme to represent the SGS fluxes of scalars and momentum in CRMs. A priori tests show that the mixed SGS scheme yields spatial distributions of subfilter-scale fluxes that correlate much better with those retrieved from the benchmark when compared with an eddy viscosity/diffusivity scheme that is commonly used in today’s CRMs.

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P.J. Sellers, D.A. Randall, G.J. Collatz, J.A. Berry, C.B. Field, D.A. Dazlich, C. Zhang, G.D. Collelo, and L. Bounoua

Abstract

The formulation of a revised land surface parameterization for use within atmospheric general circulation models (GCMs) is presented. The model (SiB2) incorporates several significant improvements over the first version of the Simple Biosphere model (SiB) described in Sellers et al. The improvements can be summarized as follows:

(i) incorporation of a realistic canopy photosynthesis–conductance model to describe the simultaneous transfer of CO2 and water vapor into and out of the vegetation, respectively;

(ii) use of satellite data, as described in a companion paper, Part II, to describe the vegetation phonology;

(iii) modification of the hydrological submodel to give better descriptions of baseflows and a more reliable calculation of interlayer exchanges within the soil profile;

(iv) incorporation of a “patchy” snowmelt treatment, which prevents rapid thermal and surface reflectance transitions when the area-averaged snow cover is low and decreasing.

To accommodate the changes in (i) and (ii) above, the original two-layer vegetation canopy structure of SiB2 has been reduced to a single layer in SiB2. The use of satellite data in SiB2 and the performance of SiB2 when coupled to a GCM are described in the two companion papers, Part II and III.

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D. A. Randall, J. A. Coakley Jr., C. W. Fairall, R. A. Kropfli, and D. H. Lenschow
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J. Teixeira, B. Stevens, C. S. Bretherton, R. Cederwall, J. D. Doyle, J. C . Golaz, A. A. M. Holtslag, S. A . Klein, J. K. Lundquist, D. A. Randall, A. P. Siebesma, and P. M. M. Soares
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