Search Results

You are looking at 1 - 10 of 28 items for :

  • Author or Editor: Jimy Dudhia x
  • Monthly Weather Review x
  • All content x
Clear All Modify Search
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.

Full access
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.

Full access
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.

Full access
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.

Full access
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.

Full access
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.

Full access
Hyeyum Hailey Shin and Jimy Dudhia

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.

Full access
Steven M. Cavallo, Jimy Dudhia, and Chris Snyder

Abstract

An upper-level cold bias in potential temperature tendencies of 10 K day−1, strongest at the top of the model, is observed in Weather Research and Forecasting (WRF) model forecasts. The bias originates from the Rapid Radiative Transfer Model longwave radiation physics scheme and can be reduced substantially by 1) modifying the treatment within the scheme by adding a multilayer buffer between the model top and top of the atmosphere and 2) constraining stratospheric water vapor to remain within the estimated climatology in the stratosphere. These changes reduce the longwave heating rate bias at the model top to ±0.5 K day−1. Corresponding bias reductions are also seen, particularly near the tropopause.

Full access
Song-You Hong, Yign Noh, and Jimy Dudhia

Abstract

This paper proposes a revised vertical diffusion package with a nonlocal turbulent mixing coefficient in the planetary boundary layer (PBL). Based on the study of Noh et al. and accumulated results of the behavior of the Hong and Pan algorithm, a revised vertical diffusion algorithm that is suitable for weather forecasting and climate prediction models is developed. The major ingredient of the revision is the inclusion of an explicit treatment of entrainment processes at the top of the PBL. The new diffusion package is called the Yonsei University PBL (YSU PBL). In a one-dimensional offline test framework, the revised scheme is found to improve several features compared with the Hong and Pan implementation. The YSU PBL increases boundary layer mixing in the thermally induced free convection regime and decreases it in the mechanically induced forced convection regime, which alleviates the well-known problems in the Medium-Range Forecast (MRF) PBL. Excessive mixing in the mixed layer in the presence of strong winds is resolved. Overly rapid growth of the PBL in the case of the Hong and Pan is also rectified. The scheme has been successfully implemented in the Weather Research and Forecast model producing a more realistic structure of the PBL and its development. In a case study of a frontal tornado outbreak, it is found that some systematic biases of the large-scale features such as an afternoon cold bias at 850 hPa in the MRF PBL are resolved. Consequently, the new scheme does a better job in reproducing the convective inhibition. Because the convective inhibition is accurately predicted, widespread light precipitation ahead of a front, in the case of the MRF PBL, is reduced. In the frontal region, the YSU PBL scheme improves some characteristics, such as a double line of intense convection. This is because the boundary layer from the YSU PBL scheme remains less diluted by entrainment leaving more fuel for severe convection when the front triggers it.

Full access
Françoise Guichard, David B. Parsons, Jimy Dudhia, and James Bresch

Abstract

This study evaluates the predictions of radiative and cloud-related processes of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5). It is based on extensive comparison of three-dimensional forecast runs with local data from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site collected at the Central Facility in Lamont, Oklahoma, over a seasonal timescale. Time series are built from simulations performed every day from 15 April to 23 June 1998 with a 10-km horizontal resolution. For the one single column centered on this site, a reasonable agreement is found between observed and simulated precipitation and surface fields time series. Indeed, the model is able to reproduce the timing and vertical extent of most major cloudy events, as revealed by radiative flux measurements, radar, and lidar data. The model encounters more difficulty with the prediction of cirrus and shallow clouds whereas deeper and long-lasting systems are much better captured. Day-to-day fluctuations of surface radiative fluxes, mostly explained by cloud cover changes, are similar in simulations and observations. Nevertheless, systematic differences have been identified. The downward longwave flux is overestimated under moist clear sky conditions. It is shown that the bias disappears with more sophisticated parameterizations such as Rapid Radiative Transfer Model (RRTM) and Community Climate Model, version 2 (CCM2) radiation schemes. The radiative impact of aerosols, not taken into account by the model, explains some of the discrepancies found under clear sky conditions. The differences, small compared to the short timescale variability, can reach up to 30 W m−2 on a 24-h timescale.

Overall, these results contribute to strengthen confidence in the realism of mesoscale forecast simulations. They also point out model weaknesses that may affect regional climate simulations: representation of low clouds, cirrus, and aerosols. Yet, the results suggest that these finescale simulations are appropriate for investigating parameterizations of cloud microphysics and radiative properties, as cloud timing and vertical extension are both reasonably captured.

Full access