Doppler Radar Data Research Articles

An Efficient Dual-Resolution Approach for Ensemble Data Assimilation and Tests with Simulated Doppler Radar Data

Abstract A new efficient dual-resolution (DR) data assimilation algorithm is developed based on the ensemble Kalman filter (EnKF) method and tested using simulated radar radial velocity data for a supercell storm. Radar observations are assimilated on both high-resolution and lower-resolution grids using the EnKF algorithm with flow-dependent background error covariances estimated from the lower-resolution ensemble. It is shown that the flow-dependent and dynamically evolved background error covariances thus estimated are effective in producing quality analyses on the high-resolution grid. The DR method has the advantage of being able to significantly reduce the computational cost of the EnKF analysis. In the system, the lower-resolution ensemble provides the flow-dependent background error covariance, while the single-high-resolution forecast and analysis provides the benefit of higher resolution, which is important for resolving the internal structures of thunderstorms. The relative smoothness of the covariance obtained from the lower 4-km-resolution ensemble does not appear to significantly degrade the quality of analysis. This is because the cross covariance among different variables is of first-order importance for “retrieving” unobserved variables from the radar radial velocity data. For the DR analysis, an ensemble size of 40 appears to be a reasonable choice with the use of a 4-km horizontal resolution in the ensemble and a 1-km resolution in the high-resolution analysis. Several sensitivity tests show that the DR EnKF system is quite robust to different observation errors. A 4-km thinned data resolution is a compromise that is acceptable under the constraint of real-time applications. A data density of 8 km leads to a significant degradation in the analysis.

Doppler Radar Data Assimilation in KMA's Operational Forecasting

Doppler Radar Data Assimilation in KMA's Operational Forecasting

A DESIGN OF FOUR DIMENSIONAL DATA ASSIMILATION OF DOPPLER RADAR DATA USING AN ENSEMBLE KALMAN FILTER

A Doppler radar data assimilation system based on an ensemble Kalman filter (EnKF) method is developed. The system employs a meso-scale hydrostatic model, which includes the conceptual model of the efficiency of the water vapor conversion. A case of the rainfall occurred in Kinki region in 2003 is chosen as an application. Radial velocity and reflectivity observed by Miyama Doppler radar and Jogamori conventional radar are assimilated. The rainfall predicted by our developed system is compared with the prediction results of the four dimensional variational method (4D-VAR) and those of the conditional Kalman filter method. It is demonstrated that our system has equal accuracy to the 4D-VAR method. Also by the comparison of the EnKF method and the conditional Kalman filter method, it is made clear that the spatial correlation in error cannot be ignored.

Urban effects and summer thunderstorms in a tropical cyclone affected situation over Guangzhou city

With data mainly from Guangzhou mesonet Automatic Weather Stations (AWS), Guangzhou Doppler Radar and satellite TBB data, characteristics and evolution of the urban heat island (UHI) over Guangzhou City were analyzed in a tropical cyclone affected situation for early August 2005. In particular, two thunderstorms occurring during this period respectively at the night of 4 August and in the afternoon of 7 August were investigated to study the relationships between the development of thunderstorms and the UHI. Results showed that two thunderstorms were associated with the UHI effects. UHI induced local air convergence and initiated the thunderstorm convections. Both cases showed a general agreement in time and space for the locations of maximum UHI, convergence, convection, and precipitation. Convection was found to be more favorable to developing in time periods and locations with stronger intensity of UHI. Analysis also showed that, due to the urban effects, both thunderstorms got strengthened when moving over Guangzhou City, with maximum radar echoes observed right over the urban area and precipitation located within the city. All these features reveal that two thunderstorms were urban-induced storms.

The Three-Dimensional Structure and Kinematics of Drizzling Stratocumulus

Abstract Drizzling marine stratocumulus are examined using observations from the 2001 East Pacific Investigation of Climate Stratocumulus (EPIC Sc) field experiment. This study uses a unique combination of satellite and shipborne Doppler radar data including both horizontal and vertical cross sections through drizzle cells. Stratocumulus cloud structure was classified as closed cellular, open cellular, or unclassifiable using infrared satellite images. Distributions of drizzle cell structure, size, and intensity are similar among the cloud-structure categories, though the open-cellular distributions are shifted toward higher values. Stronger and larger drizzle cells preferentially occur when the cloud field is broken (open-cellular and unclassifiable categories). Satellite observations of cloud structure may be useful to indicate the most likely distribution of rain rates associated with a set of scenes, but infrared data alone are not sufficient to develop routine precipitation retrievals for marine stratocumulus. Individual drizzle cells about 2–20 km across usually showed precipitation growth within the cloud layer and evaporation below, divergence near echo top, and convergence below cloud base. Diverging flow near the surface was also observed beneath heavily precipitating drizzle cells. As the cloud field transitioned from a closed to an open-cellular cloud structure, shipborne radar revealed prolific development of small drizzle cells (<10 km2) that exceeded by over 5 times the number of total cells in either the preceding closed-cellular or following open-cellular periods. Peak area-average rain rates lagged by a few hours the peak in total number of drizzle cells. Based on observations from EPIC Sc, the highest stratocumulus rain rates are more likely to occur near the boundary between closed and open-cellular cloud structures.

Radar placement based on a geometric uncertainty multiplier reduction criterion

In this paper the problem of retrieving wind field information from Doppler radar data motivates the formulation of a method to design radar network configurations. The problem of estimating wind velocities from radar data is posed and used to construct a certain retrieval operator. This operator contains a factor that may be interpreted as an uncertainty multiplier. It depends on the geometry of the configuration of the radar network. The uncertainty multiplier is shown to vary continuously with perturbations of the network configuration. It is also shown to be a generalization of the Doppler angle condition used in meteorology. Numerical examples are presented to determine a network of five radars minimizing the uncertainty multiplier for the problem. Also, a configuration of sites is determined that maximizes the area of the Doppler region.

Depiction of complex airflow near Hong Kong International Airport using a Doppler LIDAR with a two-dimensional wind retrieval technique

The Hong Kong Observatory (HKO) operates a Doppler Light Detection And Ranging (LIDAR) system at the Hong Kong International Airport (HKIA) to monitor the airflow around the airport area. The LIDAR measures the radial component of the wind field. To better visualize the airflow, a variational method which has been successfully applied to Doppler Radar data is adopted in this study to retrieve the two-dimensional wind field based on the LIDAR measurements. The wind field so obtained is found to reveal many salient features of terrain-induced airflow disturbances at HKIA, such as mountain waves and vortices. Its application to the detection of low-level windshear is demonstrated through selected cases. With a simple extension of the variational method, dual-Doppler analysis is also carried out using the radial velocity data from both the LIDAR and a Terminal Doppler Weather Radar (TDWR) to retrieve the wind field at the airport area in a gust front event.

Multiple-Radar Data Assimilation and Short-Range Quantitative Precipitation Forecasting of a Squall Line Observed during IHOP_2002

Abstract The impact of multiple–Doppler radar data assimilation on quantitative precipitation forecasting (QPF) is examined in this study. The newly developed Weather Research and Forecasting (WRF) model Advanced Research WRF (ARW) and its three-dimensional variational data assimilation system (WRF 3DVAR) are used. In this study, multiple–Doppler radar data assimilation is applied in WRF 3DVAR cycling mode to initialize a squall-line convective system on 13 June 2002 during the International H2O Project (IHOP_2002) and the ARW QPF skills are evaluated for the case. Numerical experiments demonstrate that WRF 3DVAR can successfully assimilate Doppler radial velocity and reflectivity from multiple radar sites and extract useful information from the radar data to initiate the squall-line convective system. Assimilation of both radial velocity and reflectivity results in sound analyses that show adjustments in both the dynamical and thermodynamical fields that are consistent with the WRF 3DVAR balance constraint and background error correlation. The cycling of the Doppler radar data from the 12 radar sites at 2100 UTC 12 June and 0000 UTC 13 June produces a more detailed mesoscale structure of the squall-line convection in the model initial conditions at 0000 UTC 13 June. Evaluations of the ARW QPF skills with initialization via Doppler radar data assimilation demonstrate that the more radar data in the temporal and spatial dimensions are assimilated, the more positive is the impact on the QPF skill. Assimilation of both radial velocity and reflectivity has more positive impact on the QPF skill than does assimilation of either radial velocity or reflectivity only. The improvement of the QPF skill with multiple-radar data assimilation is more clearly observed in heavy rainfall than in light rainfall. In addition to the improvement of the QPF skill, the simulated structure of the squall line is also enhanced by the multiple–Doppler radar data assimilation in the WRF 3DVAR cycling experiment. The vertical airflow pattern shows typical characteristics of squall-line convection. The cold pool and its related squall-line convection triggering process are better initiated in the WRF 3DVAR analysis and simulated in the ARW forecast when multiple–Doppler radar data are assimilated.

Assimilation of Doppler weather radar observations in a mesoscale model for the prediction of rainfall associated with mesoscale convective systems

Obtaining an accurate initial state is recognized as one of the biggest challenges in accurate model prediction of convective events. This work is the first attempt in utilizing the India Meteorological Department (IMD) Doppler radar data in a numerical model for the prediction of mesoscale convective complexes around Chennai and Kolkata. Three strong convective events both over Chennai and Kolkata have been considered for the present study. The simulation experiments have been carried out using fifth-generation Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation approach is one of the most promising tools available for directly assimilating the mesoscale observations in order to improve the initial state. The horizontal wind derived from the DWR has been used alongwith other conventional and non-conventional data in the assimilation system. The preliminary results from the three dimensional variational (3DVAR) experiments are encouraging. The simulated rainfall has also been compared with that derived from the Tropical Rainfall Measuring Mission (TRMM) satellite. The encouraging result from this study can be the basis for further investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present study indicates that Doppler radar data assimilation improves the initial field and enhances the Quantitative Precipitation Forecasting (QPF) skill.

Impact of Doppler Radar Wind in Simulating the Intensity and Propagation of Rainbands Associated with Mesoscale Convective Complexes Using MM5-3DVAR System

Pre-monsoon rainfall around Kolkata (northeastern part of India) is mostly of convective origin as 80% of the seasonal rainfall is produced by Mesoscale Convective Systems (MCS). Accurate prediction of the intensity and structure of these convective cloud clusters becomes challenging, mostly because the convective clouds within these clusters are short lived and the inaccuracy in the models initial state to represent the mesoscale details of the true atmospheric state. Besides the role in observing the internal structure of the precipitating systems, Doppler Weather Radar (DWR) provides an important data source for mesoscale and microscale weather analysis and forecasting. An attempt has been made to initialize the storm-scale numerical model using retrieved wind fields from single Doppler radar. In the present study, Doppler wind velocities from the Kolkata Doppler weather radar are assimilated into a mesoscale model, MM5 model using the three-dimensional variational data assimilation (3DVAR) system for the prediction of intense convective events that occurred during 0600 UTC on 5 May and 0000 UTC on 7 May, 2005. In order to evaluate the impact of the DWR wind data in simulating these severe storms, three experiments were carried out. The results show that assimilation of Doppler radar wind data has a positive impact on the prediction of intensity, organization and propagation of rain bands associated with these mesoscale convective systems. The assimilation system has to be modified further to incorporate the radar reflectivity data so that simulation of the microphysical and thermodynamic structure of these convective storms can be improved.

A brief summary of Dr. G. V. Rao’s research interests

A brief summary of Dr. G. V. Rao's research interests is presented. Many of his earlier studies were in conjunction with the summer Monsoon Experiment of 1979 (MONEX-79). These included: 1) the structure of the Somali jet based on aerial observations; 2) sea-level air trajectories over the equatorial Indian Ocean; 3) structural features of the east African low-level flow; 4) effects of Indian Ocean surface temperature anomaly patterns on the summer monsoon circulations; 5) structures of the monsoon low-level flow over the Arabian Sea; 6) characteristics and momentum-flux budgets of the Arabian Sea convective bands; and 7) evaporation and precipitation over the Arabian Sea during the monsoon seasons. Dr. Rao's research efforts in recent years had focused on case studies of mesocyclones spawned by tropical cyclones (TCs) in Florida using Doppler radar data and a mesoscale numerical model. These included: 1) research on tornadic mesocyclones spawned by TC Earl in 1998; 2) documentation of subtle differences between tornadic and non-tornadic mesocyclones in TC Floyd in 1999; and 3) numerical simulation of the tornadic environment observed in peninsular Florida during TC Earl in 1998. Preliminary findings show that the supercells' cold pools interacted with an existing boundary resulting in increased baroclinicity and horizontal vorticity, and a maximization of the tornado production potential by the updrafts. The model successfully simulated the mesoscale features of the mesocyclones and the tornadic environment observed during TC Earl. A 24 h simulation of accumulated rainfall within the inner domain agreed well with the observed precipitation pattern over the region.

Lightning activity and precipitation structure of hailstorms

By using the cloud-to-ground (CG) lightning location data from the lightning detection network of Henan Province, surface Doppler radar data and standard orbit data of PR, TMI and LIS on TRMM satellite, the spatial and temporal characteristics of CG lightning flashes in 10 severe hailstorms are analyzed. The results show that the percentage of +CG lightning in these hailstorms is high with an average value of 45.5%. There is a distinct increase in CG flash rate during the rapid development stage of hailstorms. The hailstone falling corresponds to an active positive flash period, and the increase of +CG flash rate is generally accompanied with a decrease of −CG flash rate. The flash rate declines rapidly during the dissipating stage of hailstorms. The precipitation structure and lightning activity in two typical hailstorms are studied in detail. It is found that strong convective cells with reflectivity greater than 30dBZ mainly are situated in the front region of hailstorms, whereas the trailing stratiform region is in the rear part of the hailstorms. The maximum heights of echo top are higher than 14 km. Convective rain contributes much more rainfall to the total than stratiform rain, and the convective rain takes about 85% and 97% of the total in the two cases, respectively. Total lightning in the hailstorms is very active with the flash rate up to 183 fl/min and 55 fl/min, respectively. The results also indicate that most lightning flashes occurred in the echo region greater than 30 dBZ and its immediate periphery. The probability of lightning occurrence is 20 times higher in the convective region than in the stratiform region. The result suggests that the lightning information is helpful to the identification of convective rain region. The linear relationship between flash rate and ice water content is disclosed primarily.

A novel algorithm for automatic tropical cyclone eye fix using Doppler radar data

AbstractTropical cyclone (TC) is among the most destructive of weather phenomena. A key element in issuing early TC warnings is an accurate and timely knowledge of the location of the circulation centre, or ‘eye’, of the TC. However, TC radar eye fix is often carried out manually in practice, and results may vary among forecasters. In this paper, a novel motion field structure analysis method is described as an aid to locate TC eyes more accurately. The method is comprehensive, and can handle incomplete data and landfalling cases. Implemented on a standard desktop computer, an average error of 0.15 degrees in latitude/longitude on a Mercator Projection map for TCs that are completely inside the radar image is obtained. This is well within the relative errors given by different TC warning centres. The method provides an independent and objective source of information to assist forecasters to fix the TC centre. Copyright © 2007 Royal Meteorological Society

Ground-Based Velocity Track Display (GBVTD) Analysis of W-Band Doppler Radar Data in a Tornado near Stockton, Kansas, on 15 May 1999

Abstract On 15 May 1999, a storm intercept team from the University of Oklahoma collected high-resolution, W-band Doppler radar data in a tornado near Stockton, Kansas. Thirty-five sector scans were obtained over a period of approximately 10 min, capturing the tornado life cycle from just after tornadogenesis to the decay stage. A low-reflectivity “eye”—whose diameter fluctuated during the period of observation—was present in the reflectivity scans. A ground-based velocity track display (GBVTD) analysis of the W-band Doppler radar data of the Stockton tornado was conducted; results and interpretations are presented and discussed. It was found from the analysis that the axisymmetric component of the azimuthal wind profile of the tornado was suggestive of a Burgers–Rott vortex during the most intense phase of the life cycle of the tornado. The temporal evolution of the axisymmetric components of azimuthal and radial wind, as well as the wavenumber-1, -2, and -3 angular harmonics of the azimuthal wind, are also presented. A quasi-stationary wavenumber-2 feature of the azimuthal wind was analyzed from 25 of the 35 scans. It is shown, via simulated radar data collection in an idealized Burgers–Rott vortex, that this wavenumber-2 feature may be caused by the translational distortion of the vortex during the radar scans. From the GBVTD analysis, it can be seen that the maximum azimuthally averaged azimuthal wind speed increased while the radius of maximum wind (RMW) decreased slightly during the intensification phase of the Stockton tornado. In addition, the maximum azimuthally averaged azimuthal wind speed, the RMW, and the circulation about the vortex center all decreased simultaneously as the tornado decayed.

The Impact of Coastal Boundaries and Small Hills on the Precipitation Distribution across Southern Connecticut and Long Island, New York

Abstract The modification of precipitation by the coastal land areas of Long Island (LI), New York, and southern Connecticut (CT) is examined for an extratropical cyclone over the northeast United States on 1 December 2004, which produced strong southerly flow (15–30 m s−1) below 900 mb and heavy precipitation over LI. The differential surface roughness at the coast and the hills of LI (30–80 m) and southern CT (100–250 m) enhanced the surface precipitation by 30%–50% over these regions compared with the nearby water region of LI Sound. The three-dimensional precipitation structures are shown using composite Weather Surveillance Radar-1988 Doppler radar data interpolated to a Cartesian grid, which is compared with a 4-km simulation using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). As the low-level stratification and flow increased at low levels, the MM5 produced a terrain-forced gravity wave over LI and CT upward through 6 km MSL. Precipitation enhancement (2–3 dBZ) occurred from the surface upward to around the freezing level (3 km MSL) across central LI and southern CT, while there was a localized precipitation minimum over LI Sound. A factor separation on a few sensitivity MM5 runs was performed to isolate the impact of small hills and differential friction across the LI coastline. Both the hills and frictional effects have similar contributions to the total precipitation enhancement and the vertical circulations below 3 km. The hills of LI enhanced the gravity wave circulations slightly more than the differential friction above 3 km, while there was little flow and precipitation interaction between the hills and differential friction. A sensitivity simulation without an ice/snow cloud above 3 km MSL revealed that the seeder-feeder process enhanced surface precipitation by about a factor of 4.

Multiresolution Ensemble Forecasts of an Observed Tornadic Thunderstorm System. Part II: Storm-Scale Experiments

Abstract In Part I, the authors used a full physics, nonhydrostatic numerical model with horizontal grid spacing of 24 km and nested grids of 6- and 3-km spacing to generate the ensemble forecasts of an observed tornadic thunderstorm complex. The principal goal was to quantify the value added by fine grid spacing, as well as the assimilation of Doppler radar data, in both probabilistic and deterministic frameworks. The present paper focuses exclusively on 3-km horizontal grid spacing ensembles and the associated impacts on the forecast quality of temporal forecast sequencing, the construction of initial perturbations, and data assimilation. As in Part I, the authors employ a modified form of the scaled lagged average forecasting technique and use Stage IV accumulated precipitation estimates for verification. The ensemble mean and spread of accumulated precipitation are found to be similar in structure, mimicking their behavior in global models. Both the assimilation of Doppler radar data and the use of shorter (1–2 versus 3–5 h) forecast lead times improve ensemble precipitation forecasts. However, even at longer lead times and in certain situations without assimilated radar data, the ensembles are able to capture storm-scale features when the associated control forecast in a deterministic framework fails to do so. This indicates the potential value added by ensembles although this single case is not sufficient for drawing general conclusions. The creation of initial perturbations using forecasts of the same grid spacing shows no significant improvement over simply extracting perturbations from forecasts made at coarser spacing and interpolating them to finer grids. However, forecast quality is somewhat dependent upon perturbation amplitude, with smaller scaling values leading to significant underdispersion. Traditional forecast skill scores show somewhat contradictory results for accumulated precipitation, with the equitable threat score most consistent with qualitative performance.

Impact of Configurations of Rapid Intermittent Assimilation of WSR-88D Radar Data for the 8 May 2003 Oklahoma City Tornadic Thunderstorm Case

Abstract Various configurations of the intermittent data assimilation procedure for Level-II Weather Surveillance Radar-1988 Doppler radar data are examined for the analysis and prediction of a tornadic thunderstorm that occurred on 8 May 2003 near Oklahoma City, Oklahoma. Several tornadoes were produced by this thunderstorm, causing extensive damages in the south Oklahoma City area. Within the rapidly cycled assimilation system, the Advanced Regional Prediction System three-dimensional variational data assimilation (ARPS 3DVAR) is employed to analyze conventional and radar radial velocity data, while the ARPS complex cloud analysis procedure is used to analyze cloud and hydrometeor fields and adjust in-cloud temperature and moisture fields based on reflectivity observations and the preliminary analysis of the atmosphere. Forecasts for up to 2.5 h are made from the assimilated initial conditions. Two one-way nested grids at 9- and 3-km grid spacings are employed although the assimilation configuration experiments are conducted for the 3-km grid only while keeping the 9-km grid configuration the same. Data from the Oklahoma City radar are used. Different combinations of the assimilation frequency, in-cloud temperature adjustment schemes, and the length and coverage of the assimilation window are tested, and the results are discussed with respect to the length and evolution stage of the thunderstorm life cycle. It is found that even though the general assimilation method remains the same, the assimilation settings can significantly impact the results of assimilation and the subsequent forecast. For this case, a 1-h-long assimilation window covering the entire initial stage of the storm together with a 10-min spinup period before storm initiation works best. Assimilation frequency and in-cloud temperature adjustment scheme should be set carefully to add suitable amounts of potential energy during assimilation. High assimilation frequency does not necessarily lead to a better result because of the significant adjustment during the initial forecast period. When a short assimilation window is used, covering the later part of the initial stage of storm and using a high assimilation frequency and a temperature adjustment scheme based on latent heat release can quickly build up the storm and produce a reasonable analysis and forecast. The results also show that when the data from a single Doppler radar are assimilated with properly chosen assimilation configurations, the model is able to predict the evolution of the 8 May 2003 Oklahoma City tornadic thunderstorm well for up to 2.5 h. The implications of the choices of assimilation settings for real-time applications are discussed.

Single-Doppler Retrieval of the Three-Dimensional Wind in a Deep Convective System Based on an Optimal Moving Frame of Reference

A single-Doppler radar velocity retrieval method, based on an optimally determined moving frame of reference, is developed. This method enables the recovery of the complete three-dimensional wind field using reflectivity, and radial wind observations, detected by a single Doppler radar over multiple volume scans. This method first computes a set of optimal moving speeds (U, V, W), which can be functions of the height. It is considered optimal in the sense that when a reference frame is traveling at this speed, as much of the radar reflectivity, interpolated onto this frame can be conserved as possible. The perturbation velocities (u′, v′, w′) are then solved simultaneously, with respect to the moving speeds, by minimizing a cost function through the three-dimensional variational (3D-Var) approach. This cost function consists of a set of weak constraints, mainly the equation for radar reflectivity conservation, the continuity equation, the geometric relationship between the radar-observed radial wind and the Cartesian winds, and a smoothness filter. Finally, by adding the optimal moving speed to the perturbation velocities, a complete three-dimensional wind field is obtained.The performance of this method is tested under different scenarios, including cases with deep convections, embedded in an environment without mean wind, with constant mean wind, with vertical wind shear of the horizontal mean wind, and with differences in the radar observational time at each grid point within one volume scan are considered.This method is demonstrated to be feasible by applying it to recover the three-dimensional wind structure of a subtropical squall line from Doppler radar data, collected during the 1987 Taiwan Area Mesoscale Experiment (TAMEX).

Doppler Radar Observation of a Tornado Generated Over the Japan Sea Coast during a Cold Air Outbreak

On January 18, 2001, a tornado formed over the Japan Sea near the Mikuni Town on the Hokuriku Coast of Japan. The “Mikuni Tornado” formed within a winter thundercloud, during a period of a cold air-outbreak, and heavy snowfall. The detailed structure of the tornado funnel cloud, and misocyclone with in the cloud are revealed from photographs, videotape, Doppler radar data, and the GPS sonde data. The tornado was generated 3 km offshore, close to the radar site. The tornado formed at the edge of a developing cell, had a single funnel, and was accompanied by a misocyclone near the cloud base; the position of the misocyclone corresponded well with a funnel cloud. The misocyclone had a diameter of 400-800 m and vorticity of 10−1 s−1, and coincided with the tornado funnel vortex in the cloud base. The funnel cloud had diameters of 150 m at the cloud base and 30 m near the surface, and a vorticity of 100 s−1. Although the funnel diameter at the cloud base changed remarkably during the life cycle of the tornado, the diameter near the surface remained largely unchanged. The funnel cloud began to dissipate after landing. The maximum wind speed of the tornado vortex is estimated to have been approximately 30 ms−1 (F0-scale), and the lifetime of the funnel cloud was 7 minutes. No damage or strong winds were recorded at the coastal radar site, which was located about 1 km from the tornado. The environmental feature that generated the Mikuni Tornado was vertical wind shear of the sub-cloud layer (3.5 × 10−2 s−1). The tornado was a non-supercell type tornado that formed under the uniform winter monsoon. This result indicates that small-scale snowclouds can produce tornadoes during periods of cold air outbreaks.

An Approach of Radar Reflectivity Data Assimilation and Its Assessment with the Inland QPF of Typhoon Rusa (2002) at Landfall

Abstract A radar reflectivity data assimilation scheme was developed within the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) three-dimensional variational data assimilation (3DVAR) system. The model total water mixing ratio was used as a control variable. A warm-rain process, its linear, and its adjoint were incorporated into the system to partition the moisture and hydrometeor increments. The observation operator for radar reflectivity was developed and incorporated into the 3DVAR. With a single reflectivity observation, the multivariate structures of the analysis increments that included cloud water and rainwater mixing ratio increments were examined. Using the onshore Doppler radar data from Jindo, South Korea, the capability of the radar reflectivity assimilation for the landfalling Typhoon Rusa (2002) was assessed. Verifications of inland quantitative precipitation forecasting (QPF) of Typhoon Rusa (2002) showed positive impacts of assimilating radar reflectivity data on the short-range QPF.