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Jiandong Gong
,
Lei Lei Wang
, and
Qin Xu

Abstract

A three-step method is developed for Doppler radar velocity dealiasing. First, the modified velocity azimuth display (VAD) method of Tabary et al. is adopted and applied to raw (aliased) velocity data to estimate horizontal vector velocities averaged on selected circles of radar scans. These velocities are used as preliminary references to detect and pre-dealiase or flag (if not correctable) possible alias errors. Then, the traditional VAD method is applied to the pre-dealiased velocity data to produce refined reference velocities to further detect and dealiase or flag alias errors in the second step. After these two steps, flagged data points are confined in small areas (often associated with strong shear and/or convergence flows), so the dealiased velocities along the boundary of each small area provide reliable starting points for the continuity check in the third step. The two-dimensional continuity check can start from any and every boundary point and proceed inward until all the flagged data are checked within each small area. The method is tested with Doppler radar data collected during the 3 May 1999 Oklahoma tornado outbreak—a difficult case for dealiasing. The results show that the method is efficient and effective even in the areas of mesocyclones.

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Lihong Zhang
,
Jiandong Gong
, and
Ruichun Wang

Abstract

Observation impact studies have received increasing amounts of research attention. The impacts of observations on numerical weather prediction (NWP) are highly dependent on assimilation algorithm, prediction system, and observation source. Therefore, the major NWP centers worldwide have each developed their own diagnostic techniques to assess observation impacts. However, similar diagnostic techniques have not yet been developed in China. In this study, a diagnostic technique was exploited with the randomized perturbation method in the Global/Regional Assimilation and Prediction System (GRAPES) 3DVAR system, and then applied to evaluate observation impacts for various regions of the world. It was found that a reasonable and stable estimation could be obtained when the number of perturbations was greater than 15. Because of differences in observations in the Northern and Southern Hemispheres, refractivity data from GNSS radio occultation (GNSS-RO), satellite radiance, and atmospheric motion vector data had more impact in the Southern Hemisphere than in the Northern Hemisphere. However, radiosonde data, aircraft, and surface data were more important in the Northern Hemisphere. Low-impact observation points were located in data-rich areas, whereas high-impact observation points were located in data-poor areas. In the equatorial region, the contributions of observations to the analysis were smaller than those in the nonequatorial regions because of the lack of proper mass–wind balance relationship. Radiosondes contributed the largest impact in China and its surrounding regions, with contributions of radiosondes and GNSS-RO data exceeding 60% of the total contributions, except for wind speed below 700 hPa.

Open access
Jidong Gao
,
Kelvin K. Droegemeier
,
Jiandong Gong
, and
Qin Xu

The velocity–azimuth display (VAD) technique was designed to estimate the areal mean vertical profile of the horizontal wind above a ground-based Doppler radar. The method uses radial velocity observations under the assumption of a linear wind field, though it encounters difficulty when the observations are contaminated by velocity ambiguities, large noise, and when viable data exist only over a restricted azimuthal range. The method suggested in this paper uses gradients of radial velocity, rather than only the velocity itself, to derive wind profiles and thus is termed the gradient velocity–azimuth display (GVAD) technique.

Both the VAD and GVAD methods are tested first on simulated data to examine their sensitivity to different type of errors in radial velocity. The retrieved mean wind profiles are shown to be insensitive to random errors in radial velocity, even at large amplitude. However, the VAD method is very sensitive to systematic errors caused by velocity ambiguities. The experiments indicate that if only 3% of a full-volume scan of radial wind data is contaminated by aliasing errors, the relative rms error in the mean wind profile retrieved by VAD can reach 50%. In contrast, GVAD is very robust to such errors.

Application of GVAD to Weather Surveillance Radar-1988 Doppler (WSR-88D) data collected during the 3 May 1999 tornado outbreak show that it has the ability to obtain accurate wind profiles even when the observations contain large errors caused by velocity ambiguities and random noise.

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Yihong Duan
,
Jiandong Gong
,
Jun Du
,
Martin Charron
,
Jing Chen
,
Guo Deng
,
Geoff DiMego
,
Masahiro Hara
,
Masaru Kunii
,
Xiaoli Li
,
Yinglin Li
,
Kazuo Saito
,
Hiromu Seko
,
Yong Wang
, and
Christoph Wittmann

The Beijing 2008 Olympics Research and Development Project (B08RDP), initiated in 2004 under the World Meteorological Organization (WMO) World Weather Research Programme (WWRP), undertook the research and development of mesoscale ensemble prediction systems (MEPSs) and their application to weather forecast support during the Beijing Olympic Games. Six MEPSs from six countries, representing the state-of-the-art regional EPSs with near-real-time capabilities and emphasizing on the 6–36-h forecast lead times, participated in the project.

The background, objectives, and implementation of B08RDP, as well as the six MEPSs, are reviewed. The accomplishments are summarized, which include 1) providing value-added service to the Olympic Games, 2) advancing MEPS-related research, 3) accelerating the transition from research to operations, and 4) training forecasters in utilizing forecast uncertainty products. The B08RDP has fulfilled its research (MEPS development) and demonstration (value-added service) purposes. The research conducted covers the areas of verification, examining the value of MEPS relative to other numerical weather prediction (NWP) systems, combining multimodel or multicenter ensembles, bias correction, ensemble perturbations [initial condition (IC), lateral boundary condition (LBC), land surface IC, and model physics], downscaling, forecast applications, data assimilation, and storm-scale ensemble modeling. Seven scientific issues important to MEPS have been identified. It is recognized that the daily use of forecast uncertainty information by forecasters remains a challenge. Development of forecaster-friendly products and training activities should be a long-term effort and needs to be continuously enhanced.

The B08RDP dataset is also a valuable asset to the research community. The experience gained in international collaboration, organization, and implementation of a multination regional EPS for a common goal and to address common scientific issues can be shared by the ongoing projects The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble—Limited Area Models (TIGGE-LAM) and North American Ensemble Forecast System—Limited Area Models (NAEFS-LAM).

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