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David L. Williamson
and
Clive Temperton

Abstract

In Part II of this paper, we describe the nonlinear normal mode initialization applied to the ECMWF multilevel global grid-point model and show that the procedure is highly successful in eliminating spurious high-frequency oscillations from forecasts made by the model. We determine the number of vertical modes that can be included in the procedure and demonstrate insensitivity to minor changes in the definitions of the modes. Attempts to include physical parameterizations within the initialization procedure are described as are the problems which arise with such attempts. It is shown that adiabatic nonlinear initialization is adequate to eliminate high-frequency gravity mode oscillations from a forecast by a model which includes non-adiabatic processes.

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David L. Williamson
and
Robert E. Dickinson

Abstract

A procedure is developed for expanding grid-point data into the normal modes of the linearized NCAR GCM. The approach assumes small-amplitude perturbations about a state of rest and involves separation of variables to give vertical and latitudinal structure equations for each longitudinal wavenumber. As an example of the procedure, 30 days of GCM model simulation data are expanded into the normal modes. It is concluded that the time and space computational modes regarded as noise have amplitudes at least an order of magnitude smaller than the dominant Rossby waves. Except for the Kelvin modes, the model gravity waves have magnitudes no larger than the noise level. The largeness of the Kelvin modes suggests that they may be an important part of the model tropical climatology.

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Roger Daley
,
Joseph Tribbia
, and
David L. Williamson

Abstract

Recent experimental results indicate that there are serious problems in forecasting planetary scales of motion. In contrast with predictability theory which suggests that the planetary scales are the most predictable, forecast experiments indicate that the long waves are predicted less accurately than the synoptic scales.

The present work suggests that one of the causes of model long wave error is the spurious excitation of transient external large-scale Rossby modes. It was found that these modes can be excited by the imposition of an equatorial wall, or by the use of unsuitable data in the tropics. Paradoxically, the imposition of a wall north of the equator may tend to suppress these spurious Rossby modes. The excited external Rossby modes are relatively fast-moving and can have a substantial negative impact on midlatitude forecast skill after only 24 h of integration.

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David L. Williamson
,
David H. Bromwich
, and
Ren-Yow Tzeng

Abstract

No abstract available

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David L. Williamson
,
Jerry G. Olson
, and
Christiane Jablonowski

Abstract

Two flaws in the semi-Lagrangian algorithm originally implemented as an optional dynamical core in the NCAR Community Atmosphere Model (CAM3.1) are exposed by steady-state and baroclinic instability test cases. Remedies are demonstrated and have been incorporated in the dynamical core. One consequence of the first flaw is an erroneous damping of the speed of a zonally uniform zonal wind undergoing advection by a zonally uniform zonal flow field. It results from projecting the transported vector wind expressed in unit vectors at the arrival point to the surface of the sphere and is eliminated by rotating the vector to be parallel to the surface. The second flaw is the formulation of an a posteriori energy fixer that, although small, systematically affects the temperature field and leads to an incorrect evolution of the growing baroclinic wave. That fixer restores the total energy at each time step by changing the provisional forecast temperature proportionally to the magnitude of the temperature change at that time step. Two other fixers are introduced that do not exhibit the flaw. One changes the provisional temperature everywhere by an additive constant, and the other changes it proportionally by a multiplicative constant.

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David L. Williamson
,
Jerry G. Olson
, and
Byron A. Boville

Abstract

At the modest vertical resolutions typical of climate models, simulations produced by models based on semi-Lagrangian approximations tend to develop a colder tropical tropopause than matching simulations from models with Eulerian approximations, all other components of the model being the same. The authors examine the source of this relative cold bias in the context of the NCAR CCM3 and show that it is primarily due to insufficient vertical resolution in the standard 18-level model, which has 3-km spacing near the tropopause. The difference is first diagnosed with the Held and Suarez idealized forcing to eliminate the complex radiative–convective feedback that affects the tropopause formation in the complete model. In the Held and Suarez case, the tropical simulations converge as the vertical grid layers are halved to produce 36 layers and halved again to produce 72 layers. The semi-Lagrangian approximations require extra resolution above the original 18 to capture the converged tropical tropopause. The Eulerian approximations also need the increased resolution to capture the single-level tropopause implied by the 36- and 72-level simulations, although with 18 layers it does not produce a colder tropopause, just a thicker multilevel tropopause. The authors establish a minimal grid of around 25 levels needed to capture the structure of the converged simulation with the Held and Suarez forcing. The additional resolution is added between 200 and 50 mb, giving a grid spacing of about 1.3 km near the tropopause. With this grid the semi-Lagrangian and Eulerian approximations also create the same tropical structure in the complete model. With both approximations the convective parameterization is better behaved with the extra upper-tropospheric resolution. A benefit to both approximations of the additional vertical resolution is a reduction of the tropical temperature bias compared to the NCEP reanalysis. The authors also show that the Eulerian approximations are prone to stationary grid-scale noise if the vertical grid is not carefully defined. The semi-Lagrangian shows no indication of stationary vertical-grid-scale noise. In addition, the Eulerian simulation exhibits significantly greater transient vertical-grid-scale noise than the semi-Lagrangian.

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Brian Medeiros
,
David L. Williamson
,
Cécile Hannay
, and
Jerry G. Olson

Abstract

Forecasts of October 2006 are used to investigate southeast Pacific stratocumulus in the Community Atmosphere Model, versions 4 and 5 (CAM4 and CAM5). Both models quickly develop biases similar to their climatic biases, suggesting that parameterized physics are the root of the climate errors. An extensive cloud deck is produced in CAM4, but the cloud structure is unrealistic because the boundary layer is too shallow and moist. The boundary layer structure is improved in CAM5, but during the daytime the boundary layer decouples from the cloud layer, causing the cloud layer to break up and transition toward a more trade wind cumulus structure in the afternoon. The cloud liquid water budget shows how different parameterizations contribute to maintaining these different expressions of stratocumulus. Sensitivity experiments help elucidate the origins of the errors. The importance of the diurnal cycle of these clouds for climate simulations is emphasized.

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David L. Williamson
,
Ronald M. Errico
, and
Roger Daley

Abstract

We illustrate systematic oscillations of the global average temperature in forecasts produced by the NCAR Community Climate Model (CCM). These oscillations are not simple linear oscillations associated with normal modes calculated about a state of rest Rather they result from an interaction between zonal-average gravity modes and zonal-average Rossby modes. Their amplitudes are related to the difference between the initial conditions and the model's average climate.

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David L. Williamson
,
Roger Daley
, and
Thomas W. Schlatter

Abstract

The relative importance of various sources of imbalance in analyses produced by multivariate optimal interpolation is determined. The experimental design uses the shallow-water equations and nonlinear normal mode initialization to define the correct balanced reference atmospheric state and thus restricts this study to horizontal aspects of the problem. The experiments show that the analysis procedure itself introduces systematic imbalances in lows due to the use of the geostrophic relationship to determine the height–wind covariances from the height–height covariances. Random observational errors introduce imbalances but not out of proportion to the observational errors themselves. Data-void areas are responsible for a region of imbalance with width approximately equal to the maximum radius of influence of the analysis on the data-void side of the data-void/data-rich boundary. Model errors in the form of equivalent depth errors do not introduce large imbalances.

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Scott N. Williamson
,
David S. Hik
,
John A. Gamon
,
Jeffrey L. Kavanaugh
, and
Saewan Koh

Abstract

Environment Canada meteorological station hourly sampled air temperatures T air at four stations in the southwest Yukon were used to identify cloud contamination in the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra clear-sky daytime land surface temperature (LST) and emissivity daily level-3 global 1-km grid product (MOD11A1, Collection 5) that is not flagged by the MODIS quality algorithm as contaminated. The additional cloud masking used qualitative ground-based sky condition observations, collected at two of the four stations, and coincident MODIS quality flag information. The results indicate that air temperature observed at a variety of discrete spatial locations having different land cover is highly correlated with MODIS LST collected at 1-km grid spacing. Quadratic relationships between LST and air temperature, constrained by ground observations of “clear” sky conditions, show less variability than relationships found under “mainly clear” and “mostly cloudy” sky conditions, and the more clouds observed in the sky coincides with a decreasing y intercept. Analysis of MODIS LST and its associated quality flags show a cold bias (<0°C) in the assignment of the ≤3-K-average LST error, indicating MODIS LST has a maximum average error of ≤2 K over a warm surface (>0°C). Analysis of two observation stations shows that unidentified clouds in MODIS LST are between 13% and 17%, a result that agrees well with previous studies. Analysis of daytime values is important because many processes are dependent on daylight and maximum temperature. The daytime clear-sky LST–T air relationship observed for the good-quality confirmed cloud-free-sky MODIS LST quality flag can be used to discriminate cloud-contaminated grid cells beyond the standard MODIS cloud mask.

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