Abstract

A nonhydrostatic extension to the Pennsylvania State University-NCAR Mesoscale Model is presented. This new version employs reference pressure as the basis for a terrain-following vertical coordinate and the fully compressible system of equations. In combination with the existing initialization techniques and physics of the current hydrostatic model, this provides a model capable of real-data simulations on any scale, limited only by data resolution and quality and by computer resources.

The model uses pressure perturbation and temperature as prognostic variables as well as a B-grid staggering in contrast to most current nonhydrostatic models. The compressible equations are solved with a split-time- step approach where sound waves are treated semi-implicitly on the shorter step. Numerical techniques and finite differencing are described.

Two-dimensional tests of flow over a bell-shaped hill on a range of scales were carded out with the hydrostatic and nonhydrostatic models to contrast the two and to verify the dynamics of the new version.

Several three-dimensional real-data simulations show the potential use of grid-nesting applications whereby the model is initialized from a coarser hydrostatic or nonhydrostatic model output by interpolation to a smaller grid area of typically between two and four times finer resolution. This approach is illustrated by a simulation of a cold front within a developing midlatitude cyclone, and a comparison of the front to observations of similar features.

The cold-frontal boundary was sharply defined at low levels and consisted of narrow linear updraft cores. At 2–4-km altitude this structure gave way to a more diffuse boundary with apparent mixing. Mechanisms are presented to explain these features in terms of inertial and shearing instability. Convection embedded in the frontal band formed a prefrontal line at later stages.

Finally, sensitivity studies showed that the frontal band owed its narrowness to the concentrating effect of latent heating. The frontal ascending branch was supplied by a strong easterly ageostrophic flow in the warm sector.

Abstract

A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea.

The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are:

1. Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil component. The heating is initiated by a thermodynamic adjustment that takes place after the air leaves the updrafts and is associated with the difference between water and ice saturation.

2. Melting and evaporation contribute to a 1ocalized mesoscale subsidence in a 50 km region to the rear of the moving convective area. The cooling associated with this almost cancels the cumulus heating in the lower to midtroposphere.

3. Radiative heating was found to be the main ascent-forcing influence at high levels occupied by the widespread cirrus outflow. Additionally, radiative clear-air cooling helped the convection by continuously destabilizing the troposphere and countering the warming effect of convective updrafts.

4. The overall structure and development of the system were well simulated, particularly the growth near the coast, and the propagation and decay in the cooler boundary layer further off-shore, but the rainfall may have been underestimated because of the two-dimensional assumptions of the model.

Abstract

A number of short-term numerical experiments conducted by the Penn State–NCAR fifth-generation Mesoscale Model (MM5) coupled with an advanced land surface model, alongside the simulations coupled with a simple slab model, are verified with observations. For clear sky day cases, the MM5 model gives reasonable estimates of radiation forcing at the surface with solar radiation being slightly overestimated probably due to the lack of aerosol treatment in the current MM5 radiation scheme. The improvements in the calculation of surface latent and sensible heat fluxes with the new land surface model (LSM) are very apparent, and more importantly, the new LSM captures the correct Bowen ratio. Evaporation obtained from the simple slab model is significantly lower than observations. Having time-varying soil moisture is important for capturing even short-term evolution of evaporation. Due to the more reasonable diurnal cycle of surface heat fluxes in the MM5–LSM, its near-surface temperature and humidity are closer to the FIFE observations. In particular, the MM5–slab model has a systematic warm bias in 2-m temperature. Both the slab model and the new LSM were coupled with the nonlocal Medium-Range Forecast model PBL parameterization scheme and they reproduced the depth of the morning surface inversion in the stable boundary layer well. The observed mixed layer in the late morning deepens faster than both models, despite the fact that both models have high bias in surface sensible heat fluxes. Presumably, such a rapid development of convective mixed layer is due to some effects induced by small-scale heterogeneity or large-scale advection that the MM5 failed to capture. Both surface models reasonably reproduce the daytime convective PBL growth and, in general, the temperature difference between the two models and observations is less than 2°. The simulations of two rainfall events are not conclusive. Both models produce a good forecast of rainfall for 24 June 1997 and have similar problems for the event of 4 July 1997, although the simulations with the new LSM have slightly improved results in some 3-h rainfall accumulations. It seems that the new LSM does not have unexpected influences in situations for which the land surface processes are secondary, but that it may have subtle, though complex, effects on the model behavior because of heterogeneity introduced by soil moisture, vegetation effects, and soil type, which are all lacking in the slab model.

Abstract

The Madden–Julian oscillation (MJO) is an important source of predictability. The boreal 2004/05 winter is used as a case study to conduct predictability experiments with the Weather Research and Forecasting (WRF) Model. That winter season was characterized by an MJO event, weak El Niño, strong North Atlantic Oscillation, and extremely wet conditions over the contiguous United States (CONUS). The issues investigated are as follows: 1) growth of forecast errors in the tropics relative to the extratropics, 2) propagation of forecast errors from the tropics to the extratropics, 3) forecast error growth on spatial scales associated with MJO and non-MJO variability, and 4) the relative importance of MJO and non-MJO tropical variability on predictability of precipitation over CONUS.

Root-mean-square errors in forecasts of normalized eddy kinetic energy (NEKE) (200 hPa) show that errors in initial conditions in the tropics grow faster than in the extratropics. Potential predictability extends out to about 4 days in the tropics and 9 days in the extratropics. Forecast errors in the tropics quickly propagate to the extratropics, as demonstrated by experiments in which initial conditions are only perturbed in the tropics. Forecast errors in NEKE (200 hPa) on scales related to the MJO grow slower than in non-MJO variability over localized areas in the tropics and short lead times. Potential predictability of precipitation extends to 1–5 days over most of CONUS but to longer leads (7–12 days) over regions with orographic precipitation in California. Errors in initial conditions on small scales relative to the MJO quickly grow, propagate to the extratropics, and degrade forecast skill of precipitation.

Abstract

This paper addresses and documents a number of issues related to the implementation of an advanced land surface–hydrology model in the Penn State–NCAR fifth-generation Mesoscale Model (MM5). The concept adopted here is that the land surface model should be able to provide not only reasonable diurnal variations of surface heat fluxes as surface boundary conditions for coupled models, but also correct seasonal evolutions of soil moisture in the context of a long-term data assimilation system. In a similar way to that in which the modified Oregon State University land surface model (LSM) has been used in the NCEP global and regional forecast models, it is implemented in MM5 to facilitate the initialization of soil moisture. Also, 1-km resolution vegetation and soil texture maps are introduced in the coupled MM5–LSM system to help identify vegetation/water/soil characteristics at fine scales and capture the feedback of these land surface forcings. A monthly varying climatological 0.15° × 0.15° green vegetation fraction is utilized to represent the annual control of vegetation on the surface evaporation. Specification of various vegetation and soil parameters is discussed, and the available water capacity in the LSM is extended to account for subgrid-scale heterogeneity. The coupling of the LSM to MM5 is also sensitive to the treatment of the surface layer, especially the calculation of the roughness length for heat/moisture. Including the effect of the molecular sublayer can improve the simulation of surface heat flux. It is shown that the soil thermal and hydraulic conductivities and the surface energy balance are very sensitive to soil moisture changes. Hence, it is necessary to establish an appropriate soil moisture data assimilation system to improve the soil moisture initialization at fine scales.

Abstract

A nonhydrostatic numerical mesoscale model has been applied to the study of an Oklahoma squall line with initial conditions taken from the Oklahoma–Kansas Preliminary Regional Experiment for STORM-Central (PRE-STORM) data for 7 May 1985. The model reproduced features typical of organized propagating convection occurring during spring and summer in this region, namely a squall line/mesoscale convective system containing strong right-flank convection resembling many documented cases. The alignment and motion of the system change during its development and are determined by the ambient wind at three levels, the steering level of the mature cells, the level of free convection, and the surface layer. Three persistent right-flank cells had a characteristic rightward propagation relative to the mean wind shear vector. Their propagation occurred through successive mergers of cells that had formed at a downdraft outflow convergence front and were similar to the flanking line often seen to the south of strong updraft cores.

The three-dimensional flow structure of the right-flank cells was found to center on a distinct dynamical pressure pattern that itself resulted from the interaction of the midlevel relative flow with the cyclonic vorticity in the updrafts. This low pressure on the updraft's flank extended down to low levels where it was partly responsible for directing the southward surge of downdraft air causing the convergence and flanking line. Other types of supercell propagation are speculated upon in relation to this characteristic dynamical pressure effect evident in the simulation in the neighborhood of cyclonic updrafts.

The updraft cyclonic vorticity was found to strongly influence the domain-scale circulation, particularly in the upper troposphere where it counteracted the anticyclonic production due to divergence and the Coriolis acceleration, leaving net cyclonic vorticity throughout most of the troposphere on a scale of 200 km.

Abstract

The ability of the Weather Research and Forecasting (WRF) model to reproduce the surface wind direction over complex terrain is examined. A simulation spanning a winter season at a high horizontal resolution of 2 km is compared with wind direction records from a surface observational network located in the northeastern Iberian Peninsula. A previous evaluation has shown the ability of WRF to reproduce the wind speed over the region once the effects of the subgrid-scale topography are parameterized. Hence, the current investigation complements the previous findings, providing information about the model's ability to reproduce the direction of the surface flow. The differences between the observations and the model are quantified in terms of scores explicitly designed to handle the circular nature of the wind direction. Results show that the differences depend on the wind speed. The larger the wind speed is, the smaller are the wind direction differences. Areas with more complex terrain show larger systematic differences between model and observations; in these areas, a statistical correction is shown to help. The importance of the grid point selected for the comparison with observations is also analyzed. A careful selection is relevant to reducing comparative problems over complex terrain.

Abstract

Planetary boundary layer (PBL) parameterizations in mesoscale models have been developed for horizontal resolutions that cannot resolve any turbulence in the PBL, and evaluation of these parameterizations has been focused on profiles of mean and parameterized flux. Meanwhile, the recent increase in computing power has been allowing numerical weather prediction (NWP) at horizontal grid spacings finer than 1 km, at which kilometer-scale large eddies in the convective PBL are partly resolvable. This study evaluates the performance of convective PBL parameterizations in the Weather Research and Forecasting (WRF) Model at subkilometer grid spacings. The evaluation focuses on resolved turbulence statistics, considering expectations for improvement in the resolved fields by using the fine meshes. The parameterizations include four nonlocal schemes—Yonsei University (YSU), asymmetric convective model 2 (ACM2), eddy diffusivity mass flux (EDMF), and total energy mass flux (TEMF)—and one local scheme, the Mellor–Yamada–Nakanishi–Niino (MYNN) level-2.5 model.

Key findings are as follows: 1) None of the PBL schemes is scale-aware. Instead, each has its own best performing resolution in parameterizing subgrid-scale (SGS) vertical transport and resolving eddies, and the resolution appears to be different between heat and momentum. 2) All the selected schemes reproduce total vertical heat transport well, as resolved transport compensates differences of the parameterized SGS transport from the reference SGS transport. This interaction between the resolved and SGS parts is not found in momentum. 3) Those schemes that more accurately reproduce one feature (e.g., thermodynamic transport, momentum transport, energy spectrum, or probability density function of resolved vertical velocity) do not necessarily perform well for other aspects.

Abstract

Direct observations of surface fluxes of momentum, sensible, and latent heat from towers and aircraft are compared to output from the NCAR-Penn State Mesoscale Model MM5. The model flux parameterization is seen to work well if appropriate values of the roughness length z ₀ and moisture availability parameter M are specified. Although the surface fluxes are quite sensitive to these parameters, as found by earlier investigators, it is not obvious how to select a value for M a priori. An initial estimate of M should take into account the rainfall and cloudiness history and probably other factors. Because temperature and humidity near the surface are quite sensitive to the fluxes, it is suggested that the difference between observed and calculated air temperatures could be used iteratively to guide the choice of M.

Abstract

A global version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (PSU–NCAR MM5) is described. The new model employs two polar stereographic projection domains centered on each pole. These domains interact at their equators, thereby eliminating the need for a lateral boundary condition file.

This paper describes the method, and contrasts this fully compressible nonhydrostatic Eulerian global model with other global models. There are potential advantages over spherical polar grids in the resolution distribution and the treatment of curvature forces near the poles. The model also selectively damps acoustic modes, which appears to have some benefits in real-data initialization. The split-explicit time steps are different from the semi-implicit schemes used in several global nonhydrostatic models, and this localized scheme avoids the need for global elliptic solvers, making it particularly adept for distributed-memory platforms and the use of composite meshes.

Tests of the model show that acoustic and gravity waves as well as advective features propagate across the equator without distortion. A trial 100-day perpetual January simulation shows realistic rain patterns as compared to climatology with no evidence of equatorial effects. Nesting is also available to focus on areas of interest, and this is demonstrated with a 72-h nested forecast over North America.

While the time step is shorter than that typically used in semi-Lagrangian global models with a comparable resolution, the model is efficient enough to have allowed the running of daily 120-km grid forecasts on nondedicated computers as small as four-processor workstations since October 1999. Results from this real-time application of the model to 5-day forecasts are shown, and demonstrate that the model performs well at this scale.

The model is consistent with the regular regional MM5 and shares dynamics and physics packages without modification. It can also make use of pre- and postprocessing packages developed for the MM5 system. This tight linkage between a regional and global model will have a clear benefit as future global models move toward higher resolutions. It allows current mesoscale numerical weather prediction research to directly feed into the next generation of global models.