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Wei Huang, J.-W. Bao, Xu Zhang, and Baode Chen

ABSTRACT

The authors coarse-grained and analyzed the output from a large-eddy simulation (LES) of an idealized extratropical supercell storm using the Weather Research and Forecasting (WRF) Model with various horizontal resolutions (200 m, 400 m, 1 km, and 3 km). The coarse-grained physical properties of the simulated convection were compared with explicit WRF simulations of the same storm at the same resolution of coarse-graining. The differences between the explicit simulations and the coarse-grained LES output increased as the horizontal grid spacing in the explicit simulation coarsened. The vertical transport of the moist static energy and total hydrometeor mixing ratio in the explicit simulations converged to the LES solution at the 200-m grid spacing. Based on the analysis of the coarse-grained subgrid vertical flux of the moist static energy, the authors confirmed that the nondimensional subgrid vertical flux of the moist static energy varied with the subgrid fractional cloudiness according to a function of fractional cloudiness, regardless of the box size. The subgrid mass flux could not account for most of the total subgrid vertical flux of the moist static energy because the eddy-transport component associated with the internal structural inhomogeneity of convective clouds was of a comparable magnitude. This study highlights the ongoing challenge in developing scale-aware parameterizations of subgrid convection.

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Chaing Chen, Wei-Kuo Tao, Pay-Liam Lin, George S. Lai, S-F. Tseng, and Tai-Chi Chen Wang

Abstract

During the period of 21–25 June 1991, a mei-yu front, observed by the post–Taiwan Area Mesoscale Experiment, produced heavy precipitation along the western side of the Central Mountain Range of Taiwan. Several oceanic mesoscale convective systems were also generated in an area extending from Taiwan to Hong Kong. Numerical experiments using the Penn State–NCAR MM5 mesoscale model were used to understand the intensification of the low-level jet (LLJ). These processes include thermal wind adjustment and convective, inertial, and conditional symmetric instabilities.

Three particular circulations are important in the development of the mei-yu front. First, there is a northward branch of the circulation that develops across the upper-level jet and is mainly caused by the thermal wind adjustment as air parcels enter an upper-level jet streak. The upper-level divergence associated with this branch of the circulation triggers convection.

Second, the southward branch of the circulation, with its rising motion in the frontal region and equatorward sinking motion, is driven by frontal vertical deep convection. The return flow of this circulation at low levels can produce an LLJ through geostrophic adjustment. The intensification of the LLJ is sensitive to the presence of convection.

Third, there is a circulation that develops from low to middle levels that has a slantwise rising and sinking motion in the pre- and postfrontal regions, respectively. From an absolute momentum surface analysis, this slantwise circulation is maintained by conditionally symmetric instability located at low levels ahead of the front. The presence of both the LLJ and moisture is an essential ingredient in fostering this conditionally symmetric unstable environment.

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Yu-Chieng Liou, Jian-Luen Chiou, Wei-Hao Chen, and Hsin-Yu Yu

Abstract

This research combines an advanced multiple-Doppler radar synthesis technique with the thermodynamic retrieval method, originally proposed by Gal-Chen, and a moisture/temperature adjustment scheme, and formulates a sequential procedure. The focus is on applying this procedure to improve the model quantitative precipitation nowcasting (QPN) skill in the convective scale up to 3 hours. A series of (observing system simulation experiment) OSSE-type tests and a real case study are conducted to investigate the performance of this algorithm under different conditions.

It is shown that by using the retrieved three-dimensional wind, thermodynamic, and microphysical parameters to reinitialize a fine-resolution numerical model, its QPN skill can be significantly improved. Since the Gal-Chen method requires the horizontal average properties of the weather system at each altitude, utilization of in situ radiosonde(s) to obtain this additional information for the retrieval is tested. When sounding data are not available, it is demonstrated that using the model results to replace the role played by observing devices is also a feasible choice. The moisture field is obtained through a simple, but effective, adjusting scheme and is found to be beneficial to the rainfall forecast within the first hour after the reinitialization of the model.

Since this algorithm retrieves the unobserved state variables instantaneously from the wind measurements and directly uses them to reinitialize the model, fewer radar data and a shorter model spinup time are needed to correct the rainfall forecasts, in comparison with other data assimilation techniques such as four-dimensional variational data assimilation (4DVAR) or ensemble Kalman filter (EnKF) methods.

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Chaing Chen, Craig H. Bishop, George S. Lai, and Wei-Kuo Tao

Abstract

A cold-frontal rainband, which occurred during the afternoon of 28 December 1988, is numerically simulated using the Penn State–NCAR three-dimensional MM5 modeling system. This case is characterized by a line of severe convection that has a gravity current–like structure along the leading edge of a strong surface cold front. The authors test whether this gravity current–like structure is associated with the cold-air outflow boundary generated by the evaporation of hydrometeors from the postfrontal precipitation system. It is found that the neglect of moist processes in the model did not significantly affect the gravity current–like structure of the front. PBL (planetary boundary layer) frictional processes, which produce cross-frontal low-level wind shear (u z), play an important role. The role of this cross-frontal low-level wind shear is to generate low-level convergence and to steepen the frontal slope. Thus, the observed intense NCFR (narrow cold-frontal rainband) is closely related to frictionally induced PBL processes.

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Shou-Jun Chen, Ying-Hwa Kuo, Wei Wang, Zu-Yu Tao, and Bo Cui

Abstract

On 12–13 June 1991, a series of convective rainstorms (defined as mesoscale precipitation systems with rainfall rates exceeding 10 mm h−1) developed successively along the Mei-Yu front. During this event, new rainstorms formed to the east of preceding storms at an interval of approximately 300–400 km. The successive development and eastward propagation of these rainstorms produced heavy rainfall over the Jiang-Huai Basin in eastern China, with a maximum 24-h accumulation of 234 mm. This study presents the results of a numerical simulation of this heavy rainfall event using the Penn State–NCAR Mesoscale Model Version 5 (MM5) with a horizontal resolution of 54 km.

Despite the relatively coarse horizontal resolution, the MM5, using a moist physics package comprising an explicit scheme and the Grell cumulus parameterization, simulated the successive development of the rainstorms. The simulated rainstorms compared favorably with the observed systems in terms of size and intensity. An additional sensitivity experiment showed that latent heat release is crucial for the development of the rainstorms, the mesoscale low-level jet, the mesolow, the rapid spinup of vorticity, and the Mei-Yu frontogenesis. Without latent heat release, the maximum vertical motion associated with the rainstorm is reduced from 70 to 6 cm s−1.

Additional model sensitivity experiments using the Kain–Fritsch cumulus parameterization with grid sizes of 54 and 18 km produced results very similar to the 54-km control experiment with the Grell scheme. This suggests that the simulation of Mei-Yu rainstorms, the mesoscale low-level jet, and the mesolow is not highly sensitive to convective parameterization and grid resolution. In all the full-physics experiments, the model rainfall was dominated by the resolvable-scale precipitation. This is attributed to the high relative humidity and low convective available potential energy environment in the vicinity of the Mei-Yu front.

The modeling results suggest that there is strong interaction and positive feedback between the convective rainstorms embedded within the Mei-Yu front and the Mei-Yu front itself. The front provides a favorable environment for such rainstorms to develop, and the rainstorms intensify the Mei-Yu front.

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Tae-Kwon Wee, Ying-Hwa Kuo, Dong-Kyou Lee, Zhiquan Liu, Wei Wang, and Shu-Ya Chen

Abstract

The authors have discovered two sizeable biases in the Weather Research and Forecasting (WRF) model: a negative bias in geopotential and a warm bias in temperature, appearing both in the initial condition and the forecast. The biases increase with height and thus manifest themselves at the upper part of the model domain. Both biases stem from a common root, which is that vertical structures of specific volume and potential temperature are convex functions. The geopotential bias is caused by the particular discrete hydrostatic equation used in WRF and is proportional to the square of the thickness of model layers. For the vertical levels used in this study, the bias far exceeds the gross 1-day forecast bias combining all other sources. The bias is fixed by revising the discrete hydrostatic equation. WRF interpolates potential temperature from the grids of an external dataset to the WRF grids in generating the initial condition. Associated with the Exner function, this leads to the marked bias in temperature. By interpolating temperature to the WRF grids and then computing potential temperature, the bias is removed. The bias corrections developed in this study are expected to reduce the disparity between the forecast and observations, and eventually to improve the quality of analysis and forecast in the subsequent data assimilation. The bias corrections might be especially beneficial to assimilating height-based observations (e.g., radio occultation data).

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George Tai-Jen Chen, Chung-Chieh Wang, and David Ta-Wei Lin

Abstract

The present study investigates the characteristics of low-level jets (LLJs) (≥12.5 m s−1) below 600 hPa over northern Taiwan in the mei-yu season and their relationship to heavy rainfall events (≥50 mm in 24 h) through the use of 12-h sounding data, weather maps at 850 and 700 hPa, and hourly rainfall data at six surface stations during the period of May–June 1985–94. All LLJs are classified based on their height, appearance (single jet or double jet), and movement (migratory and nonmigratory). The frequency, vertical structure, and spatial and temporal distribution of LLJs relative to the onset of heavy precipitation are discussed.

Results on the general characteristics of LLJs suggest that they occurred about 15% of the time in northern Taiwan, with a top speed below 40 m s−1. The level of maximum wind appeared mostly between 850 and 700 hPa, with highest frequency at 825–850 hPa. A single jet was observed more often (76%) than a double jet (24%), while in the latter case a barrier jet usually existed at 900–925 hPa as the lower branch.

Migratory and nonmigratory LLJs each constituted about half of all cases, and there existed no apparent relationship between their appearance and movement. Migratory LLJs tended to be larger in size, stronger over a thicker layer, more persistent, and were much more closely linked to heavy rainfall than nonmigratory jets. They often formed over southern China between 20° and 30°N and moved toward Taiwan presumably along with the mei-yu frontal system.

Before and near the onset of the more severe heavy rain events (≥100 mm in 24 h) in northern Taiwan, there was a 94% chance that an LLJ would be present over an adjacent region at 850 hPa, and 88% at 700 hPa, in agreement with earlier studies. Occurrence frequencies of LLJs for less severe events (50–100 mm in 24 h) were considerably lower, and the difference in accumulative rainfall amount was seemingly also affected by the morphology of the LLJs, including their strength, depth, elevation of maximum wind, persistence, proximity to northern Taiwan, source region of moisture, and their relative timing of arrival before rainfall. During the data period, about 40% of all migratory LLJs at 850 or 700 hPa passing over northern Taiwan were associated with heavy rainfall within the next 24 h. The figure, however, was much lower compared to earlier studies, and some possible reasons are offered to account for this deficit.

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Christopher Davis, Wei Wang, Shuyi S. Chen, Yongsheng Chen, Kristen Corbosiero, Mark DeMaria, Jimy Dudhia, Greg Holland, Joe Klemp, John Michalakes, Heather Reeves, Richard Rotunno, Chris Snyder, and Qingnong Xiao

Abstract

Real-time forecasts of five landfalling Atlantic hurricanes during 2005 using the Advanced Research Weather Research and Forecasting (WRF) (ARW) Model at grid spacings of 12 and 4 km revealed performance generally competitive with, and occasionally superior to, other operational forecasts for storm position and intensity. Recurring errors include 1) excessive intensification prior to landfall, 2) insufficient momentum exchange with the surface, and 3) inability to capture rapid intensification when observed. To address these errors several augmentations of the basic community model have been designed and tested as part of what is termed the Advanced Hurricane WRF (AHW) model. Based on sensitivity simulations of Katrina, the inner-core structure, particularly the size of the eye, was found to be sensitive to model resolution and surface momentum exchange. The forecast of rapid intensification and the structure of convective bands in Katrina were not significantly improved until the grid spacing approached 1 km. Coupling the atmospheric model to a columnar, mixed layer ocean model eliminated much of the erroneous intensification of Katrina prior to landfall noted in the real-time forecast.

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Xiang-Yu Huang, Qingnong Xiao, Dale M. Barker, Xin Zhang, John Michalakes, Wei Huang, Tom Henderson, John Bray, Yongsheng Chen, Zaizhong Ma, Jimy Dudhia, Yongrun Guo, Xiaoyan Zhang, Duk-Jin Won, Hui-Chuan Lin, and Ying-Hwa Kuo

Abstract

The Weather Research and Forecasting (WRF) model–based variational data assimilation system (WRF-Var) has been extended from three- to four-dimensional variational data assimilation (WRF 4D-Var) to meet the increasing demand for improving initial model states in multiscale numerical simulations and forecasts. The initial goals of this development include operational applications and support to the research community. The formulation of WRF 4D-Var is described in this paper. WRF 4D-Var uses the WRF model as a constraint to impose a dynamic balance on the assimilation. It is shown to implicitly evolve the background error covariance and to produce the flow-dependent nature of the analysis increments. Preliminary results from real-data 4D-Var experiments in a quasi-operational setting are presented and the potential of WRF 4D-Var in research and operational applications are demonstrated. A wider distribution of the system to the research community will further develop its capabilities and to encourage testing under different weather conditions and model configurations.

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