Abstract

A series of 5-day forecasts for both winter and summer initial conditions have been performed using a fairly high resolution version (0.9375° latitude–longitude grid with 28 vertical levels) of a gridpoint semi-Lagrangian global forecast model with second-order semi-implicit off-centering and a time step of 1800 s. Most of the physics included in the model are taken from the NCEP operational MRF model. The forecasts are evaluated by comparing the anomaly correlations computed using the NCEP operational global analyses with those for the operational MRF forecasts. It is found that the skill scores of the semi-Lagrangian model are fairly close to those of the operational MRF model despite the handicap of not having its own analyses forecast cycle. The forecasts are also used to get an estimate of the climate drift of the model. It is found that the drift is similar to but somewhat larger than that for the NCEP MRF model.

In the second part of the paper, a spatially averaged Eulerian treatment of orography is incorporated into the semi-Lagrangian model and its performance is compared against its semi-Lagrangian counterpart. Eight 5-day forecasts are made, four with the Eulerian treatment of orography and four with the semi-Lagrangian treatment, for both first-order and second-order off-centering and with time steps of 1800 and 2700 s, respectively. It is found that the spatially averaged Eulerian representation of orography has superior mass conservation but has slightly more noise at upper levels over the Himalayas. It is also found that first-order off-centering with ϵ = 0.1 gives as good a forecast as the second-order off-centering. Increasing the time step from 1800 to 2700 s is associated with some damping of the fields.

Abstract

We have investigated baroclinic instability with cumulus heating using a vertically discrete, linearized, quasi-geostrophic model on a β-plane. Two formulations of cumulus heating were used. The first formulation (η-model) rests on the assumption that heating at all levels is proportional to the vertical p-velocity at the top of the lowest model layer. The second formulation (AS-model) follows the cumulus parameterization proposed by Arakawa and Schubert.

We present results for basic states with a constant temperature lapse rate and zonal flows linear in pressure. With both formulations, we found the Green modes for easterly shears destabilized by cumulus heating. We discuss the mechanism of this destabilization along with the vertical structure and energetics of the perturbations.

We extended the analyses for basic zonal flows similar to those observed during the Indian summer monsoon season, with the AS-model. The wavelength, phase speed, growth rate and vertical structure corresponding to a peak growth rate are very similar to some of the observed monsoon depressions. This similarity indicates that baroclinic instability with cumulus heating can be responsible for the development of monsoon depressions.

Abstract

Two vertically discrete systems, one based on the “Charney-Phillips grid” and the other on the “Lorenz grid,” are compared in view of the quasi-geostrophic potential vorticity equation and baroclinic instability.

It is shown that with the Charney-Phillips grid, the standard grid for the quasi-geostrophic system of equations, one can easily maintain important dynamical constraints on quasi-geostrophic flow, such as the conservation of quasi-geostrophic potential vorticity through horizontal advection and resulting integral constraints. With the Lorenz grid, however, in which horizontal velocity and (potential) temperature are carried at same levels, it is not straightforward even to define quasi-geostrophic potential vorticity. Moreover, due to an extra degree of freedom in potential temperature, the Lorenz grid can falsely satisfy the necessary condition for baroclinic instability near the lower and upper boundaries. In fact, eigenvalue solutions of the linear quasi-geostrophic equations show the existence of spuriously amplifying modes with short wavelengths, one trapped near the lower boundary and the other near the upper boundary. The former grows more rapidly then the latter when static stability increases with height. In a model discretized both in vertical and horizontal, the spurious amplification appears with high horizontal resolution unless vertical resolution is very high.

The existence of the spurious amplification of short waves in a nonlinear primitive equation model is also confirmed. Here the amplification also influences longer waves though nonlinearity and upper level presumably through vertical propagation of gravity waves.

It is shown that the spurious amplification can be removed at its origin by introducing additional terms in the thermodynamic equations for the bottom and top layers, which effectively eliminate the possibility of falsely satisfying the necessary condition for baroclinic instability.

Abstract

An efficient, direct, second-order solver for the discrete solution of a class of two-dimensional separable elliptic equations on the sphere (which generally arise in implicit and semi-implicit atmospheric models) is presented. The method involves a Fourier transformation in longitude and a direct solution of the resulting coupled second-order finite-difference equations in latitude. The solver is made efficient by vectorizing over longitudinal wave-number and by using a vectorized fast Fourier transform routine. It is evaluated using a prescribed solution method and compared with a multigrid solver and the standard direct solver from FISHPAK.

Abstract

A simple implementation of the Arakawa and Schubert (1974) cumulus parameterization is presented. The major simplification made is to “relax”the state toward equilibrium each time the parameterization is invoked, rather than requiring that the final state be balanced, as in the original Arakawa-Schubert implementation. This relaxed Arakawa-Schubert (RAS) scheme is evaluated in off-line tests using the Global Atmospheric Research Programme (GARP) Atlantic Tropical Experiment (GATE) Phase III data. The results show that RAS is equivalent to the standard implementation of Arakawa-Schubert but is more economical and simpler to code. RAS also avoids the ill-posed problem that occurs in Arakawa-Schubert as a result of having to solve for a balanced state.

Abstract

This study describes and demonstrates a new method for identifying deficiencies in how cloud processes are represented in large-scale models. Kilometer-scale-resolving cloud radar observations and cloud-resolving model (CRM) simulations were used to evaluate the representation of cirrus clouds in the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model for a 29-day period during June and July 1997 at the Atmospheric Radiation Measurement Program site in Oklahoma.

To produce kilometer-scale cirrus statistics from the SCM results, synthetic subgrid-scale (SGS) cloud fields were generated using the SCM’s cloud fraction and hydrometeor content profiles, and the SCM’s cloud overlap and horizontal inhomogeneity assumptions. Three sets of SCM synthetic SGS cloud fields were analyzed. Two NOSNOW sets were produced in which clouds did not include snow; one set used random overlap, the other, maximum/random. In the SNOW set, clouds included snow and random overlap was used. The three sets were sampled in the same way as the cloud-radar-detected cloud fields and the CRM-simulated cloud fields.

The mean cirrus cloud occurrence frequency for the SCM NOSNOW cloud fields agrees with the observed value as well as the CRM’s does, while that for SCM SNOW cloud fields is only half that observed. In most aspects, the SCM’s cirrus properties differ significantly from the cloud radar’s and the CRM’s, which generally agree.

In comparison, there are too many physically thin SCM NOSNOW cirrus layers (most occupy only a single model layer) and too many physically thick SCM SNOW cirrus layers (most are thicker than 4 km). For the optically thin subset of cirrus layers, 1) the mean, mode, and median ice water path, and layer-mean ice water content (IWC) values for the SCM are significantly larger than the observed and CRM values; 2) the SCM layer-mean IWCs decrease with cloud physical thickness, opposite to the observations and CRM results; and 3) the range of layer-mean effective radii in the SCM thin cirrus is too narrow.

Abstract

The atmospheric response to a sea surface temperature anomaly over the equatorial eastern Pacific Ocean (SSTA) is investigated using the UCLA General Circulation Model. The SSTA used is an idealization of that compiled by Rasmusson and Carpenter for the mature phase of El Niño. Two simulations over seasons, one without and the other with the SSTA, are performed and their results are compared for the Northern Hemisphere winter season.

In the tropics the SSTA enhances precipitation over the central and eastern equatorial Pacific, while it decreases precipitation over the adjacent regions. The anomalous precipitation is predominantly balanced by the anomalous moisture flux convergence, which has comparable magnitude in the planetary boundary layer (PBL), and in the free atmosphere with quite different geographical distribution. This suggests that the anomalous precipitation, and hence the anomalous tropical cumulus heating, cannot be related exclusively to either flow anomalies in the PBL or in the free atmosphere.

In the midlatitudes, it is found that the SSTA results in a more zonal flow over the Pacific with an intensification of the upper-tropospheric westerlies. Associated with this intensification, synoptic-scale transient baroclinic waves become more active. This is consistent with interannual differences in observed spectral distributions of transients for five winters, two of which were El Niño winters. Geographically, the increase in baroclinic wave activity occurs in a zonal bell extending from the northeastern Pacific to the northern Atlantic.

Abstract

General circulation model (GCM) simulations of low-frequency variability with time scales of 20 to 70 days are analyzed for the Pacific sector during boreal winter. The GCM's leading mode in the upper-tropospheric zonal wind is associated with fluctuations of the East Asian jet; this mode resembles, in both structure and amplitude, the Pacific/North American (PNA) pattern found in the observations on these time scales.

In both the model and observations the PNA anomaly is characterized by 1) a linear balance in the upper-tropospheric vorticity budget with no significant Rossby wave source in the tropics, 2) a barotropic conversion of kinetic energy from the time mean Pacific jet, and 3) a north/south displacement of the Pacific storm track. In the GCM, the latter is associated with synoptic eddy heat flux and latent heat anomalies that appear to contribute to a strong lower-tropospheric source of wave activity over the North Pacific. This is in contrast to the observations, which show only a weak source of wave activity in this region.

The GCM produces 60% of the total observed Pacific sector low-frequency zonal wind variance. About one-third of the missing variability appears to be due to unrealistic simulations of the Madden-Julian oscillation; the remainder is characterized in the variance spectrum as a deficit in the overall level of “background” variability. The nature of this missing background variability is unclear.

Abstract

This study evaluates the performance of the National Centers for Environmental Prediction Global Forecast System (GFS) against observations made by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program at the southern Great Plains site for the years 2001–04. The spatial and temporal scales of the observations are examined to search for an optimum approach for comparing grid-mean model forecasts with single-point observations. A single-column model (SCM) based upon the GFS was also used to aid in understanding certain forecast errors. The investigation is focused on the surface energy fluxes and clouds. Results show that the overall performance of the GFS model has been improving, although certain forecast errors remain. The model overestimated the daily maximum latent heat flux by 76 W m⁻² and the daily maximum surface downward solar flux by 44 W m⁻², and underestimated the daily maximum sensible heat flux by 44 W m⁻². The model’s surface energy balance was reached by a cancellation of errors. For clouds, the GFS was able to capture the observed evolutions of cloud systems during major synoptic events. However, on average, the model largely underestimated cloud fraction in the lower and midtroposphere, especially for daytime nonprecipitating low clouds because shallow convection in the GFS does not produce clouds. Analyses of surface radiative fluxes revealed that the diurnal cycle of the model’s surface downward longwave flux (SDLW) was not in phase with that of the ARM-observed SDLW. SCM experiments showed that this error was caused by an inaccurate scaling factor, which was a function of ground skin temperature and was used to adjust the SDLW at each model time step to that computed by the model’s longwave radiative transfer routine once every 3 h. A method has been proposed to correct this error in the operational forecast model. It was also noticed that the SDLW biases changed from mostly negative in 2003 to slightly positive in 2004. This change was traced back to errors in the near-surface air temperature. In addition, the SDLW simulated with the newly implemented Rapid Radiative Transfer Model longwave routine in the GFS is usually 5–10 W m⁻² larger than that simulated with the previous routine. The forecasts of surface downward shortwave flux (SDSW) were relatively accurate under clear-sky conditions. The errors in SDSW were primarily caused by inaccurate forecasts of cloud properties. Results from this study can be used as guidance for the further development of the GFS.

Abstract

This work investigates the impact of tropical sea surface temperature (SST) biases on the Subseasonal to Seasonal Prediction project (S2S) precipitation forecast skill over the contiguous United States (CONUS) in the Unified Forecast System (UFS) coupled model Prototype 6. Boreal summer (June–September) and winter (December–March) for 2011–18 were analyzed. The impact of tropical west Pacific (WP) and tropical North Atlantic (TNA) warm SST biases is evaluated using multivariate linear regression analysis. A warm SST bias over the WP influences the CONUS precipitation remotely through a Rossby wave train in both seasons. During boreal winter, a warm SST bias over the TNA partly affects the magnitude of the North Atlantic subtropical high (NASH)’s center, which in the reforecasts is weaker than in reanalysis. The weaker NASH favors an enhanced moisture transport from the Gulf of Mexico, leading to increased precipitation over the Southeast United States. Compared to reanalysis, during boreal summer, the NASH’s center is also weaker and in addition, its position is displaced to the northeast. The displacement further affects the CONUS summer precipitation. The SST biases over the two tropical regions and their impacts become stronger as the forecast lead increases from week 1 to 4. These tropical biases explain up to 10% of the CONUS precipitation biases on the S2S time scale.