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Jimy Dudhia

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.
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Jimy Dudhia

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.

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Fei Chen and Jimy Dudhia

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.

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Fei Chen and Jimy Dudhia

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.

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Charles Jones and Jimy Dudhia

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.

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David B. Parsons and Jimy Dudhia

Abstract

Time continuous data assimilation or four-dimensional data assimilation (FDDA) is a collection of techniques where observations are ingested into a numerical model during the simulation in order to produce a physically balanced estimate of the true state of the atmosphere. Application of FDDA to the mesoalpha and subalpha scales is relatively new. One of many strategies for undertaking FDDA on the mesoscale is to employ Newtonian relaxation on increasingly finer horizontal grids. Encouraging results were found using this technique by Kuo et al. on a 40-km grid and by Stauffer and Seaman in a nested model with a 10-km inner grid. In these studies, the model is nudged toward the observations through adding an extra term(s) based on the difference between observations and the model predictions to the model’s prognostic equation(s). Since the model must retain a balance, this adjustment is spread over relatively large spatial and long temporal scales, and the nudging term is also multiplied by a coefficient that keeps the adjustment relatively small. Despite the positive findings of past studies, a number of questions arise in the application of this technique to fine grids. One area yet to be tested is how nudging will behave on fine grids under conditions with sharp horizontal and temporal gradients. Little improvement or even degradation of the model by the nudging might be expected as the timescale of nudging is relatively slow compared to the rapid evolution of the atmosphere, and spreading the observations out in time and space may not be representative of the actual atmospheric conditions. Other questions include 1) how the behavior of nudging at these scales and in active convection depends on boundary conditions, network density, and areal extent; 2) how the results depend on variations in the nudging coefficients; and 3) how nudging compares to simple objective analysis of the observations. In this study, Newtonian relaxation is used in a moist, full physics, nonhydrostatic mesoscale model to conduct simulations with horizontal resolutions as fine as 5 km in environments with deep convection and in mountainous terrain. Observing system simulation experiments were designed to address the previously mentioned questions. The authors show that nudging on these scales and in these conditions tends not to produce any large degradations but instead leads to improvements in the simulations even with a small number of observing sites. In applying nudging to a limited mesoscale area, the authors found that the results were more favorable if the nudging was undertaken over larger regions, which supports the nested approach used by Stauffer and Seaman. Some negative aspects of nudging were also uncovered with locally high rms errors due to data representativity problems and predictability issues. The accuracy of objective analysis was also explored and discussed in the context of the Atmospheric Radiation Measurement (ARM) Program. In agreement with Mace and Ackerman, the errors associated with objective analysis can be too large for the goals of ARM. However, the authors also found that a method proposed by Mace and Ackerman to detect time periods where significant errors exist in the objective analysis was not valid for this case. Based on this work, the authors propose that for a modest network of observing sites FDDA has a number of advantages over objective analysis.

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Jimy Dudhia and James F. Bresch

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.

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Pedro A. Jiménez and Jimy Dudhia

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The Weather Research and Forecasting (WRF) model presents a high surface wind speed bias over plains and valleys that constitutes a limitation for the increasing use of the model for several applications. This study attempts to correct for this bias by parameterizing the effects that the unresolved topographic features exert over the momentum flux. The proposed parameterization is based on the concept of a momentum sink term and makes use of the standard deviation of the subgrid-scale orography as well as the Laplacian of the topographic field. Both the drag generated by the unresolved terrain and the possibility of an increase in the speed of the flow over the mountains and hills, where it is herein shown that WRF presents a low wind speed bias, are considered in the scheme. The surface wind simulation over a complex-terrain region that is located in the northeast of the Iberian Peninsula is improved with the inclusion of the new parameterization. In particular, the underestimation of the wind speed spatial variability resulting from the mentioned biases is corrected. The importance of selecting appropriate grid points to compare with observations is also examined. The wind speed from the nearest grid point is not always the most appropriate one for this comparison, nearby ones being more representative. The new scheme not only improves the climatological winds but also the intradiurnal variations at the mountains, over which the default WRF shows limitations in reproducing the observed wind behavior. Some advantages of the proposed formulation for wind-resource evaluation are also discussed.

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Steven P. Oncley and Jimy Dudhia

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.

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Pedro A. Jiménez and Jimy Dudhia

Abstract

The wind stress formulation in an atmospheric model over shallow waters is investigated using year-long observations of the wind profile within the first 100 m of the atmosphere and mesoscale simulations. The model experiments use a range of planetary boundary layer parameterizations to quantify the uncertainty related to the turbulent closure assumptions and thus to isolate the dominant influence of the surface roughness formulation. Results indicate that a positive wind speed bias exists when common open-ocean formulations for roughness are adopted for a region with a water depth of 30 m. Imposition of a wind stress formulation that is consistent with previous shallow-water estimates is necessary to reconcile model wind speeds with observations, providing modeling evidence that supports the increase of surface drag over shallow waters. The possibility of including water depth in the parameterization of roughness length is examined.

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