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Peter S. Ray, Alan Robinson, and Ying Lin

Abstract

During the Taiwan Area Mesoscale Experiment (TAMEX), three Doppler radars complemented enhanced surface and upper-air observations. The focus of the experiment was to better understand the interaction of the terrain with precipitation systems in the production of the important heavy rainfall. The intensive operational period (IOP) number 8 extended from 1400 IST (local standard time) 7 June 1987 until 0800 LST 9 June 1987. During this time, a mesoscale convective system (MCS) formed in the Straits of Taiwan and moved inland. It was interrogated by many observing instruments, including three Doppler radars, over a 6-h period. During this time the front moved through the radar network. The front was shallow and the precipitation widespread, both ahead of and behind the front. The front was only 1.6-km deep over a distance of 100 km.

Using velocity-azimuth display (VAD) data, a portion of the frontogenetic function was computed during the times the front was in the vicinity of the radar. The increase in both convergence and deformation contributed to large values of the frontogenetic function.

Dynamic retrieval was also attempted on the data during the time when the front was most favorably located for analysis. The results are very similar to what has been observed both for tropical squall lines and for midlatitude squall lines.

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Yuh-Lang Lin, Nicholas C. Witcraft, and Ying-Hwa Kuo

Abstract

In this study, the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) was used to simulate Supertyphoon Bilis (in 2000) and Typhoon Toraji (in 2001) in order to investigate the dynamics of track deflection caused by the Central Mountain Range (CMR) of Taiwan. The MM5 predicted the track of each storm reasonably well. Bilis was stronger and had a relatively faster forward motion, which helped make the track continuous as it crossed the CMR. The use of a “bogus” vortex in the initialization process helped produce a storm closer to the observed strength. Bilis is a classic example of a typhoon crossing Taiwan with a continuous track. For comparison, Typhoon Toraji, a typical typhoon having a discontinuous track, was also studied. Toraji was weaker and had a relatively slower forward speed, which prevented the original low center from crossing over the CMR and forced more air parcels to go around the northern tip of the CMR. As a result, it produced a vortex and a secondary low center on the lee. Potential vorticity banners on the north side of the CMR acted to organize the secondary low and the lee vortex. With time, the low-level circulation extended into the upper levels, completing the formation of the secondary center. Remnants of the initial center crossed over the CMR and were entrained into the secondary center. Nondimensional control parameters for track continuity and deflection from idealized studies are calculated for Bilis and Toraji. The results are consistent with the theory proposed in Lin et al. For tropical cyclones (TCs) approaching Taiwan from the southeast, the conceptual model proposed by Lin et al. for continuous and discontinuous tracks was applied. For continuous tracks over the CMR, the blocking effect on the outer circulation of the vortex is weak and the vorticity advection around the northern tip is strong due to an intense TC. Weak TCs tend to be totally blocked by the CMR.

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Ying Lin, Peter S. Ray, and Kenneth W. Johnson

Abstract

A method is developed to initialize convective storm simulations with Doppler radar-derived fields. Input fields for initialization include velocity, rainwater derived from radar reflectivity, and pressure and temperature fields obtained through thermodynamic retrieval. A procedure has been developed to fill in missing wind data, followed by a variational adjustment to the filled wind field to minimize “shocks” that would otherwise cause the simulated fields to deteriorate rapidly.

A series of experiments using data from a simulated storm establishes the feasibility of the initialization method. Multiple-Doppler radar observations from the 20 May 1977 Del City tornadic storm are used for the initialization experiments. Simulation results are shown and compared to observations taken at a later time. The simulated storm shows good agreement with the subsequent observations, though the simulated storm appears to be evolving faster than observed. Possible reasons for the discrepancies are discussed.

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Chuan-Chi Tu, Yi-Leng Chen, Shu-Ya Chen, Ying-Hwa Kuo, and Pay-Liam Lin

Abstract

A cycling run, which began 36 h before the model forecast, was employed to assimilate special Terrain-influenced Monsoon Rainfall Experiment (TiMREX) soundings, Global Telecommunications System (GTS) data, and Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) global positioning system (GPS) radio occultation (RO) refractivity profiles to improve the model initial conditions provided by the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) to study a coastal, heavy rainfall event over southwestern Taiwan during 15–16 June 2008. The 36-h cycling run with data assimilation (DA_ALL_DATA run) has a positive impact on the depiction of subsynoptic flow in the model initial conditions at 1200 UTC 15 June, including the warm moist tongue and southwesterly monsoon flow over the open ocean. Furthermore, the cold pool caused by the evaporative cooling of antecedent rains and orographic blocking over southwestern Taiwan are better resolved in the nested high-resolution domain in the DA_ALL_DATA run as compared to the initial conditions provided by the NCEP GFS. As a result, the heavy rainfall along the southwestern coast and afternoon localized heavy rainfall over northern Taiwan are better predicted in the DA_ALL_DATA run.

Model sensitivity tests are also performed to diagnose the effects of terrain and rain-evaporative cooling on the intensity and depth of the cold pool and degree of orographic blocking on the southwesterly flow over southwestern Taiwan. It is apparent that including rain-evaporative cooling from antecedent rains and orographic effects in the model initial conditions are important to account for the predicted rainfall distribution of this coastal rainfall event.

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Juanzhen Sun, Ying Zhang, Junmei Ban, Jing-Shan Hong, and Chung-Yi Lin

Abstract

Radar and surface rainfall observations are two sources of operational data crucial for heavy rainfall prediction. Their individual values on improving convective forecasting through data assimilation have been examined in the past using convection-permitting numerical models. However, the benefit of their simultaneous assimilations has not yet been evaluated. The objective of this study is to demonstrate that, using a 4D-Var data assimilation system with a microphysical scheme, these two data sources can be assimilated simultaneously and the combined assimilation of radar data and estimated rainfall data from radar reflectivity and surface network can lead to improved short-term heavy rainfall prediction. In our study, a combined data assimilation experiment is compared with a rainfall-only and a radar-only (with or without reflectivity) experiments for a heavy rainfall event occurring in Taiwan during the passage of a mei-yu system. These experiments are conducted by applying the Weather Research and Forecasting (WRF) 4D-Var data assimilation system with a 20-min time window aiming to improve 6-h convective heavy rainfall prediction. Our results indicate that the rainfall data assimilation contributes significantly to the analyses of humidity and temperature whereas the radar data assimilation plays a crucial role in wind analysis, and further, combining the two data sources results in reasonable analyses of all three fields by eliminating large, unphysical analysis increments from the experiments of assimilating individual data only. The results also show that the combined assimilation improves forecasts of heavy rainfall location and intensity of 6-h accumulated rainfall for the case studied.

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Na Wei, Ying Li, Da-Lin Zhang, Zi Mai, and Shi-Qi Yang

Abstract

The geographical and temporal characteristics of upper-tropospheric cold low (UTCL) and their relationship to tropical cyclone (TC) track and intensity change over the western North Pacific (WNP) during 2000–12 are examined using the TC best track and global meteorological reanalysis data. An analysis of the two datasets shows that 73% of 346 TCs coexist with 345 UTCLs, and 21% of the latter coexist with TCs within an initial cutoff distance of 15°. By selecting those coexisted systems within this distance, the possible influences of UTCL on TC track and intensity change are found, depending on their relative distance and on the sectors of UTCLs where TCs are located. Results show that the impact of UTCLs on TC directional changes are statistically insignificant when averaged within the 15° radius. However, left-turning TCs within 5° distance from the UTCL center exhibit large deviated directional changes from the WNP climatology, due to the presence of highly frequent abrupt left turnings in the eastern semicircle of UTCL. The abrupt turnings of TCs are often accompanied by their slow-down movements. Results also show that TCs seem more (less) prone to intensify at early (late) development stages when interacting with UTCLs compared to the WNP climatology. Intensifying (weakening) TCs are more distributed in the southern (northern) sectors of UTCLs, with less hostile conditions for weakening within 9°–13° radial range. In addition, rapid intensifying TCs take place in the south-southwest and east-southeast sectors of UTCLs, whereas rapid weakening cases appear in the western semicircle of UTCLs due to their frequent proximity to mainland coastal regions.

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Juanzhen Sun, Hongli Wang, Wenxue Tong, Ying Zhang, Chung-Yi Lin, and Dongmei Xu

Abstract

The momentum variables of streamfunction and velocity potential are used as control variables in a number of operational variational data assimilation systems. However, in this study it is shown that, for limited-area high-resolution data assimilation, the momentum control variables ψ and χ (ψχ) pose potential difficulties in background error modeling and, hence, may result in degraded analysis and forecast when compared with the direct use of x and y components of wind (UV). In this study, the characteristics of the modeled background error statistics, derived from an ensemble generated from Weather Research and Forecasting (WRF) Model real-time forecasts of two summer months, are first compared between the two control variable options. Assimilation and forecast experiments are then conducted with both options for seven convective events in a domain that encompasses the Rocky Mountain Front Range using the three-dimensional variational data assimilation (3DVar) system of the WRF Model. The impacts of the two control variable options are compared in terms of their skills in short-term qualitative precipitation forecasts. Further analysis is performed for one case to examine the impacts when radar observations are included in the 3DVar assimilation. The main findings are as follows: 1) the background error modeling used in WRF 3DVar with the control variables ψχ increases the length scale and decreases the variance for u and υ, which causes negative impact on the analysis of the velocity field and on precipitation prediction; 2) the UV-based 3DVar allows closer fits to radar wind observations; and 3) the use of UV control variables improves the 0–12-h precipitation prediction.

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David H. Bromwich, Andrew J. Monaghan, Jordan G. Powers, John J. Cassano, He-Lin Wei, Ying-Hwa Kuo, and Andrea Pellegrini

Abstract

To support the forecasting needs of the United States Antarctic Program at McMurdo, Antarctica, a special numerical weather prediction program, the Antarctic Mesoscale Prediction System (AMPS), was established for the 2000–01 field season. AMPS employs the Polar MM5, a version of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) that has physics modifications for polar environments. This study assesses the performance of AMPS in forecasting an event of mesoscale cyclogenesis in the western Ross Sea during 13–17 January 2001. Observations indicate the presence of a complex trough having two primary mesoscale lows that merge to the east of Ross Island shortly after 0700 UTC 15 January. In contrast, AMPS predicts one primary mesoscale low throughout the event, incorrectly placing it until the 1800 UTC 15 January forecast, when the observed system carries a prominent signature in the initialization. The model reproduces the evolution of upper-level conditions in agreement with the observations and shows skill in resolving many small-scale surface features common to the region (i.e., katabatic winds; lows and highs induced by wind/topography). The AMPS forecasts can rely heavily on the representation of surface lows and upper-level forcing in the first-guess fields derived from NCEP's Aviation Model (AVN). Furthermore, even with relatively high spatial resolution, mesoscale models face observation-related limitations on performance that can be particularly acute in Antarctica.

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Guo-Yuan Lien, Chung-Han Lin, Zih-Mao Huang, Wen-Hsin Teng, Jen-Her Chen, Ching-Chieh Lin, Hsu-Hui Ho, Jyun-Ying Huang, Jing-Shan Hong, Chia-Ping Cheng, and Ching-Yuang Huang

Abstract

The FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) Radio Occultation (RO) satellite constellation was launched in June 2019 as a successor of the FORMOSAT-3/COSMIC mission. The Central Weather Bureau (CWB) of Taiwan has received FORMOSAT-7/COSMIC-2 GNSS RO data in real time from the Taiwan Analysis Center for COSMIC. With the global numerical prediction system at CWB, a parallel semioperational experiment assimilating the FORMOSAT-7/COSMIC-2 bending angle data with all other operational observation data has been conducted to evaluate the impact of the FORMOSAT-7/COSMIC-2 data. The first seven-month results show that the quality of the early FORMOSAT-7/COSMIC-2 data has been satisfactory for assimilation. Consistent and significant positive impacts on global forecast skills have been observed since the start of the parallel experiment, with the most significant impact found in the tropical region, reflecting the low-inclination orbital design of the satellites. The impact of the FORMOSAT-7/COSMIC-2 RO data is also estimated using the ensemble forecast sensitivity to observation impact (EFSOI) method, showing an average positive impact per observation similar to other existing GNSS RO datasets, while the total impact is impressive by virtue of its large amount. Sensitivity experiments suggest that the quality control processes built in the Gridpoint Statistical Interpolation (GSI) system for RO data work well to achieve a positive impact by the low-level FORMOSAT-7/COSMIC-2 RO data, while more effort on observation error tuning should be focused to obtain an optimal assimilation performance. This study demonstrates the usefulness of the FORMOSAT-7/COSMIC-2 RO data in global numerical weather prediction during the calibration/validation period and leads to the operational use of the data at CWB.

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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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