High-Resolution Radar Data Assimilation for Hurricane Isabel (2003) at Landfall

Zhao, Quan; Jin, Yi

doi:10.1175/2008bams2562.1

Cited by 56 publications

(50 citation statements)

References 27 publications

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“…1c, d), the first simulation starts at 03 UTC, 19 April 2008 and is run for three hours, and another data assimilation is made at 06 UTC, 19 April 2008, and model forecast is run since then. It could be seen that, for the cycling simulations (c) and (d) (being respectively the direct assimilation of radar velocity and reflectivity data through WRF 3DVAR, and the assimilation of radar-derived 2D winds only obtained by [5] in WRF 3DVAR), the surface wind magnitudes over Hong Kong are generally smaller (in the order of 17 m/s) than those without cycling, viz. (a) and (b) (being respectively without the use of radar data at all, and the assimilation of radar velocity and reflectivity data only at 06 UTC, 19 April 2008).…”

Section: Typhoon Neogurimentioning

confidence: 99%

“…For this purpose, the two-step variational method as described in [5] is employed. This two-step variational method calculates 2D wind field at different heights by minimization of a cost function that takes into account the difference between the observed and the analyzed radial velocity, conservation of reflectivity and continuity of the wind field.…”

Section: Assimilation Of Radar Datamentioning

confidence: 99%

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Improving Wind and Rain Simulations for Tropical Cyclones with the Assimilation of Doppler Radar Data

Cheung¹,

Chan²

2010

TOASCJ

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More accurate prediction of the strong winds and heavy rain associated with tropical cyclones using numerical weather prediction (NWP) models would be helpful in the provision of weather services for the public. In this paper, the impact of assimilating radar data in the simulation of Typhoon Neoguri and Severe Tropical Storm Kammuri in 2008 is studied using Weather Research and Forecasting (WRF) version 2.2 and WRF VAR version 2.1. Only the data from the radar at Tate's Cairn in Hong Kong are considered. Four experiments are conducted, namely, (a) simulation without radar data, (b) simulation with radar data assimilated at the initial time, (c) cycling simulation with the assimilation of radar data (Doppler velocity and reflectivity) directly assimilated, and (d) cycling simulation with the assimilation of 2D wind field retrieved from the Doppler velocity data from the radar. By comparing with actual observations of the surface wind distribution in Hong Kong and the actual radar reflectivity data, it turns out that both (c) and (d) outperform (a) and (b), and (c) and (d) show comparable skills. As a result, cycling simulation with the assimilation of weather radar data (even for a single radar) could improve the prediction of winds and rain bands associated with tropical cyclones.

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Section: Typhoon Neogurimentioning

confidence: 99%

Section: Assimilation Of Radar Datamentioning

confidence: 99%

Improving Wind and Rain Simulations for Tropical Cyclones with the Assimilation of Doppler Radar Data

Cheung¹,

Chan²

2010

TOASCJ

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“…Recent operations of Doppler radar have brought opportunities to sample the thermodynamics, microphysics and dynamic characteristics of TCs (Marks 2003). With data at high spatial and temporal resolution, airborne Doppler radar can reveal detailed structural features of the TCs, and studies have demonstrated that these radar data are useful in studying hurricanes (Xiao et al, 2007;Zhao et al, 2008;Zhao & Jin 2008, Pu et al, 2009b. With very high resolution (about 1-2 km in the horizontal and 0.5 km in the vertical direction), airborne Doppler radars mostly represent the wind, moisture, and hydrometeor structure within the hurricane eyewall.…”

Section: Impact Of Assimilation Of the Airborne Doppler Radar On Tc Fmentioning

confidence: 99%

“…Fortunately, the amount of available Doppler radar data and recent developments in radar data assimilation have brought hopes of improving TC inner-core thermodynamic and hydrometeor conditions. Several studies (Zhao et al, 2008;Zhao & Jin, 2008;Pu et al, 2009b) have proved that radar data assimilation resulted in a significant impact on TC track and intensity forecasting. From all the aformentioned studies, improved hurricane environmental conditions and the vortex initialization both play important roles in the accurate forecasting of hurricane rapid intensification and intensity changes.…”

Section: Introductionmentioning

confidence: 99%

Improving Hurricane Intensity Forecasting through Data Assimilation: Environmental Conditions Versus the Vortex Initialization

Pu¹

2011

Recent Hurricane Research - Climate, Dynamics, and Societal Impacts

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“…Zhao et al (2006) developed a three-and-half-dimensional variational data assimilation (3.5D-VAR) system for radar wind data to initialize the Navy's Coupled Ocean-Atmosphere Mesoscale Prediction System (COAMPS) model. Zhao and Jin (2008) improved the simulated hurricane intensity and structure by assimilating radar data into the COAMPS model using 3.5D-VAR. They revealed that the maximum of surface wind speed (5 m s -1 ) was increased in the first 5-h forecasts.…”

Section: Introductionmentioning

confidence: 99%

Effect of Doppler Radial Velocity Data Assimilation on the Simulation of a Typhoon Approaching Taiwan: A Case Study of Typhoon Aere (2004)

Lin¹,

Lin²,

Xiao³

et al. 2011

Terr. Atmos. Ocean. Sci.

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Compared to conventional data, radar observations have an advantage of high spatial and temporal resolutions, and Doppler radars are capable of capturing detailed characteristics of flow fields, including typhoon circulation. In this study, the possible improvement of short-term typhoon predictions near Taiwan, particularly with regard to related rainfall forecasts over the mountainous island, using Doppler radial wind observations is explored. The case of Typhoon Aere (2004) was chosen for study, and a series of experiments were carried out using the Penn State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model Version 5 (MM5) with its three-dimensional variational (3D-VAR) data assimilation system.The results show that once the Doppler radial velocities were assimilated into the model, the typhoon's circulation intensified within one hour. However, when Typhoon Aere approached from the east and only the western half of its core area could be observed by the radar, the assimilation caused the typhoon to deflect southward due to the incomplete and uneven data coverage. In another experiment in which Doppler radar data assimilation did not start until Typhoon Aere moved closer, such that its entire core region could be observed. A similar track deflection was avoided. Overall, the assimilation of Doppler radial velocity data reduced the intensity error (in wind speed) by about 25%. Furthermore, the improvements in location, intensity, and circulation structure of Typhoon Aere lead to better rainfall prediction over the island of Taiwan.

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High-Resolution Radar Data Assimilation for Hurricane Isabel (2003) at Landfall

Cited by 56 publications

References 27 publications

Improving Wind and Rain Simulations for Tropical Cyclones with the Assimilation of Doppler Radar Data

Improving Wind and Rain Simulations for Tropical Cyclones with the Assimilation of Doppler Radar Data

Improving Hurricane Intensity Forecasting through Data Assimilation: Environmental Conditions Versus the Vortex Initialization

Effect of Doppler Radial Velocity Data Assimilation on the Simulation of a Typhoon Approaching Taiwan: A Case Study of Typhoon Aere (2004)

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