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Song-You Hong and Eugenia Kalnay

Abstract

This study presents results from mechanistic experiments to clarify the origin and maintenance of the Oklahoma–Texas (OK–TX) drought of the 1998 summer, using the National Centers for Environmental Prediction (NCEP) global and regional models. In association with this unprecedented drought, three major mechanisms that can produce extended atmospheric anomalies have been identified: (i) sea surface temperature (SST) anomalies, (ii) soil moisture anomalies, and (iii) atmospheric initial conditions favorable to such a climate extreme even in the absence of surface forcing (i.e., internal forcing).

The authors found that the SST anomalies during April–May 1998 established the large-scale conditions for the drought. However, the warm El Niño–Southern Oscillation (ENSO) SST anomalies over the central and eastern tropical Pacific alone did not play a major role in initiating the drought. The internal structure of atmospheric conditions played as significant a role as the SST anomalies over the globe. In June 1998, soil moisture anomalies started to play an important role in maintaining the drought, and the regional positive feedback associated with lower evaporation/lower precipitation explained most of the water deficit in July. After July, synoptic-scale disturbances overwhelmed the impact of dry soil moisture near the Gulf of Mexico states where above-normal precipitation occurred, but the regional feedback was still prominent over the OK–TX region, where the drought persisted until early October.

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Song-You Hong and Jimy Dudhia

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Song-You Hong and Ants Leetmaa

Abstract

In this study, the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) has been evaluated as a means of enhancing the depiction of regional details beyond that which is capable in low-resolution global models. Three-month-long simulations driven by the NCEP–National Center for Atmospheric Research 40-yr reanalysis data are conducted with a horizontal resolution of about 50 km over the United States, for the two winters and summers. The selected winter cases are December–February (DJF) 1991/92 (warm eastern Pacific SST anomalies) and DJF 1992/93 (normal eastern Pacific SST anomalies). Summer cases are May–July (MJJ) 1988 (a drought in the Great Plains) and MJJ 1993 (a flooding).

Overall, the results from the model are very satisfactory in terms of the precipitation distribution for different seasons as well as the representation of large-scale features. Evaluation of simulated large-scale features reveals that the model does not exhibit a discernible synoptic-scale drift during the 3-month integration period, irrespective of the seasons. Surprisingly, the model simulation is found to correct some biases in the large-scale fields that exist in the reanalysis data. This bias reduction is attributed to the improved depiction of physical processes within the RSM. This finding indicates that one should take special care in the interpretation and validation of simulated results against the analyzed data.

Evaluation of the RSM simulated precipitation for the winter and summer cases generally agrees with results obtained from previous studies. For instance, the skill for simulated precipitation in the winter cases exceeds that of the summer cases by a factor of 2. Comparison of simulated precipitation with observations reveals the 3-month-long RSM simulated precipitation to be more skillful than that obtained from the reanalysis data (the 6-h forecast from the data assimilation system). In addition to seasonal variations in precipitation, daily variation in the simulated precipitation is quite good. However, detailed analysis points to the need for further RSM development, particularly in physics. In the summer cases the grid-resolvable precipitation physics simulate excessive precipitation over the northern United States. A more serious problem is found in the diurnal cycle of the simulation precipitation, in that the model initiates convection too early. Despite these deficiencies, it is concluded that the NCEP RSM is a very useful tool for regional climate studies.

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Young-Hwa Byun and Song-You Hong

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This study describes a revised approach for the subgrid-scale convective properties of a moist convection scheme in a global model and evaluates its effects on a simulated model climate. The subgrid-scale convective processes tested in this study comprise three components: 1) the random selection of cloud top, 2) the inclusion of convective momentum transport, and 3) a revised large-scale destabilization effect considering synoptic-scale forcing in the cumulus convection scheme of the National Centers for Environmental Prediction medium-range forecast model. Each component in the scheme has been evaluated within a single-column model (SCM) framework forced by the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment data. The impact of the changes in the scheme on seasonal predictions has been examined for the boreal summers of 1996, 1997, and 1999. In the SCM simulations, an experiment that includes all the modifications reproduces the typical convective heating and drying feature. The simulated surface rainfall is in good agreement with the observed precipitation. Random selection of the cloud top effectively moistens and cools the upper troposphere, and it induces drying and warming below the cloud-top level due to the cloud–radiation feedback. However, the two other components in the revised scheme do not play a significant role in the SCM simulations. On the other hand, the role of each modification component in the scheme is significant in the ensemble seasonal simulations. The random selection process of the cloud top preferentially plays an important role in the adjustment of the thermodynamic profile in a manner similar to that in the SCM framework. The inclusion of convective momentum transport in the scheme weakens the meridional circulation. The revised large-scale destabilization process plays an important role in the modulation of the meridional circulation when this process is combined with other processes; on the other hand, this process does not induce significant changes in large-scale fields by itself. Consequently, the experiment that involves all the modifications shows a significant improvement in the seasonal precipitation, thereby highlighting the importance of nonlinear interaction between the physical processes in the model and the simulated climate.

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Song-You Hong and Hua-Lu Pan

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In this paper, the incorporation of a simple atmospheric boundary layer diffusion scheme into the NCEP Medium-Range Forecast Model is described. A boundary layer diffusion package based on the Troen and Mahrt nonlocal diffusion concept has been tested for possible operational implementation. The results from this approach are compared with those from the local diffusion approach, which is the current operational scheme, and verified against FIFE observations during 9–10 August 1987. The comparisons between local and nonlocal approaches are extended to the forecast for a heavy rain case of 15–17 May 1995. The sensitivity of both the boundary layer development and the precipitation forecast to the tuning parameters in the nonlocal diffusion scheme is also investigated. Special attention is given to the interaction of boundary layer processes with precipitation physics. Some results of parallel runs during August 1995 are also presented.

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Hyeyum Hailey Shin and Song-You Hong

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Parameterization of the unresolved vertical transport in the planetary boundary layer (PBL) is one of the key physics algorithms in atmospheric models. This study attempts to represent the subgrid-scale (SGS) turbulent transport in convective boundary layers (CBLs) at gray-zone resolutions by investigating the effects of grid-size dependency in the vertical heat transport parameterization for CBL simulations. The SGS transport profile is parameterized based on the 2013 conceptual derivation by Shin and Hong. First, nonlocal transport via strong updrafts and local transport via the remaining small-scale eddies are separately calculated. Second, the SGS nonlocal transport is formulated by multiplying a grid-size dependency function with the total nonlocal transport profile fit to the large-eddy simulation (LES) output. Finally, the SGS local transport is formulated by multiplying a grid-size dependency function with the total local transport profile, which is calculated using an eddy-diffusivity formula. The new algorithm is evaluated against the LES output and compared with a conventional nonlocal PBL parameterization.

For ideal CBL cases, by considering the scale dependency in the parameterized vertical heat transport, improvements over the conventional nonlocal K-profile model appear in mean profiles, resolved and SGS vertical transport profiles with their grid-size dependency, and the energy spectrum. Real-case simulations for convective rolls show that the simulated roll structures are more robust with stronger intensity when the new algorithm is used.

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Song-You Hong, Yign Noh, and Jimy Dudhia

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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.

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So-Young Kim and Song-You Hong

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The source and sink terms of microphysical processes vary nonlinearly with cloud condensate amount. Therefore, partial cloudiness is one of the important factors to be considered in a cloud microphysics scheme given that in-cloud condensate amount depends on the cloud fraction of the grid box. An alternative concept to represent the partial cloudiness effect on the microphysical processes of a bulk microphysics scheme is proposed. Based on the statistical relationship between cloud condensate and cloudiness, all hydrometeors in the microphysical processes are treated after converting them to in-cloud values by dividing the amount by estimated cloudiness and multiplying it after the computation of all microphysics terms. The underlying assumption is that all the microphysical processes occur in a cloudy part of the grid box. In a 2D idealized storm case, the Weather Research and Forecasting (WRF) single-moment 5-class (WSM5) microphysics scheme with the proposed approach increases the amount of snow and rain through enhanced autoconversion/accretion and increases precipitation reaching the surface.

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Hann-Ming Henry Juang and Song-You Hong

Abstract

A semi-Lagrangian advection scheme is developed for falling hydrometeors in hopes of replacing the conventional Eulerian scheme that has been widely used in the cloud microphysics scheme of numerical atmospheric models. This semi-Lagrangian scheme uses a forward advection method to determine the advection path with or without iteration, and advected mass in a two-time-level algorithm with mass conservation. Monotonicity is considered in mass-conserving interpolation between Lagrangian grids and model Eulerian grids, thus making it a positive definite advection scheme. For mass-conserving interpolation between the two grid systems, the piecewise constant method (PCM), piecewise linear method (PLM), and piecewise parabolic method (PPM) are proposed. The falling velocity at the bottom cell edge is modified to avoid unphysical deformation by scanning from the top layer to the bottom of the model, which enables the use of a large time step with reasonable accuracy. The scheme is implemented and tested in the Weather Research and Forecasting (WRF) Single-Moment 3-Class Microphysics Scheme (WSM3).

In a theoretical test bed with constant terminal velocity, the proposed semi-Lagrangian algorithm shows that the higher-order interpolation scheme produces less diffusive features at maximal precipitation. Results from another idealized test bed with mass-weighted terminal velocity demonstrate that the accuracy of the proposed scheme is still satisfactory even with a time step of 120 s when the mean terminal velocity averaged at the departure and arrival points is employed. A two-dimensional (2D) squall-line test using the WSM3 scheme shows that the control run with the Eulerian advection scheme and the semi-Lagrangian run with the PCM method reveal similar results, whereas behaviors using the PLM and PPM are similar with higher-resolution features, such as mammatus-like clouds.

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Hyeyum Hailey Shin and Song-You Hong

Abstract

The gray zone of a physical process in numerical models is defined as the range of model resolution in which the process is partly resolved by model dynamics and partly parameterized. In this study, the authors examine the grid-size dependencies of resolved and parameterized vertical transports in convective boundary layers (CBLs) for horizontal grid scales including the gray zone. To assess how stability alters the dependencies on grid size, four CBLs with different surface heating and geostrophic winds are considered. For this purpose, reference data for grid-scale (GS) and subgrid-scale (SGS) fields are constructed for 50–4000-m mesh sizes by filtering 25-m large-eddy simulation (LES) data.

As relative importance of shear increases, the ratio of resolved turbulent kinetic energy increases for a given grid spacing. Vertical transports of potential temperature, momentum, and a bottom-up diffusion passive scalar behave in a similar fashion. The effects of stability are related to the horizontal scale of coherent large-eddy structures that change in the different stability. The subgrid-scale vertical transport of heat and the bottom-up scalar are divided into a nonlocal mixing owing to the coherent structures and remaining local mixing. The separate treatment of the nonlocal and local transports shows that the grid-size dependency of the SGS nonlocal flux and its sensitivity to stability predominantly determine the dependency of total (nonlocal plus local) SGS transport.

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