scholarly journals Characteristics of Himawari-8 Rapid Scan Atmospheric Motion Vectors Utilized in Mesoscale Data Assimilation

2018 ◽  
Vol 96B (0) ◽  
pp. 111-131 ◽  
Author(s):  
Michiko OTSUKA ◽  
Hiromu SEKO ◽  
Kazuki SHIMOJI ◽  
Koji YAMASHITA
Keyword(s):  
Data Assimilation ◽  
Motion Vectors ◽  
Rapid Scan ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors

scholarly journals Impact of Four-Dimensional Variational Data Assimilation of Atmospheric Motion Vectors on Tropical Cyclone Track Forecasts

2006 ◽  
Vol 21 (4) ◽  
pp. 663-669 ◽  
Author(s):  
Dongliang Wang ◽  
Xudong Liang ◽  
Yihong Duan ◽  
Johnny C. L. Chan
Keyword(s):  
Tropical Cyclone ◽  
Data Assimilation ◽  
Mesoscale Model ◽  
State University ◽  
Motion Vectors ◽  
Geostationary Meteorological Satellite ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors ◽  
Data Assimilation Technique ◽  
The Impact

Abstract The fifth-generation Pennsylvania State University–National Center for Atmospheric Research nonhydrostatic Mesoscale Model is employed to evaluate the impact of the Geostationary Meteorological Satellite-5 water vapor and infrared atmospheric motion vectors (AMVs), incorporated with the four-dimensional variational (4DVAR) data assimilation technique, on tropical cyclone (TC) track predictions. Twenty-two cases from eight different TCs over the western North Pacific in 2002 have been examined. The 4DVAR assimilation of these satellite-derived wind observations leads to appreciable improvements in the track forecasts, with average reductions in track error of ∼5% at 12 h, 12% at 24 h, 10% at 36 h, and 7% at 48 h. Preliminary results suggest that the improvement depends on the quantity of the AMV data available for assimilation.

Characteristics of Fengyun-4A Satellite Atmospheric Motion Vectors and Their Impacts on Data Assimilation

2020 ◽  
Vol 37 (11) ◽  
pp. 1222-1238
Author(s):  
Yaodeng Chen ◽  
Jie Shen ◽  
Shuiyong Fan ◽  
Deming Meng ◽  
Cheng Wang
Keyword(s):  
Data Assimilation ◽  
Motion Vectors ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors

scholarly journals Assimilation of Himawari-8 Rapid-Scan Atmospheric Motion Vectors on Tropical Cyclone in HWRF System

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 601
Author(s):  
Masahiro Sawada ◽  
Zaizhong Ma ◽  
Avichal Mehra ◽  
Vijay Tallapragada ◽  
Ryo Oyama ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Lead Time ◽  
Forecast Skill ◽  
Track Forecast ◽  
Motion Vectors ◽  
Substantial Impact ◽  
Rapid Scan ◽  
Forecast Lead Time ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors

This study investigates the assimilation impact of rapid-scan (RS) atmospheric motion vectors (AMVs) derived from the geostationary satellite Himawari-8 on tropical cyclone (TC) forecasts. Forecast experiments for three TCs in 2016 in the western North Pacific basin are performed using the National Centers for Environmental Prediction (NCEP) operational Hurricane Weather Research and Forecasting Model (HWRF). An ensemble-variational hybrid data assimilation system is used as an initialization. The results show that the assimilation of RS-AMVs can improve the track forecast skill, while the weak bias or slow intensification bias increases at the shorter forecast lead time. A vortex initialization in HWRF has a substantial impact on TC structure, but it has neutral impacts on the track and intensity forecasts. A thinning of AMVs mitigates the weak bias caused by RS-AMV assimilation, resulting in the reduction of intensity error. However, it degrades the track forecast skill for a longer lead time. A decomposition of the TC steering flows demonstrated that the change in TC-induced flow was a primary factor for reducing the track forecast error, and the change in environmental flow has less impact on the track forecast. The investigation of the structural change from the assimilation of RS-AMV revealed that the following two factors are likely related to the intensity forecast degradation: (1) an increase of inertial stability outside the radius of maximum wind (RMW), which weakens the boundary layer inflow; and (2) a drying around and outside the RMW.

scholarly journals Impact of Enhanced Atmospheric Motion Vectors on HWRF Hurricane Analyses and Forecasts with Different Data Assimilation Configurations

2018 ◽  
Vol 146 (5) ◽  
pp. 1549-1569 ◽  
Author(s):  
Shixuan Zhang ◽  
Zhaoxia Pu ◽  
Christopher Velden
Keyword(s):  
Data Assimilation ◽  
Inner Core ◽  
Core Region ◽  
Intensity Change ◽  
Motion Vectors ◽  
Processing Strategies ◽  
Negative Effect ◽  
Atmospheric Motion ◽  
Environmental Prediction ◽  
Atmospheric Motion Vectors

Abstract The impacts of enhanced satellite-derived atmospheric motion vectors (AMVs) on the numerical prediction of intensity changes during Hurricanes Gonzalo (2014) and Joaquin (2015) are examined. Enhanced AMVs benefit from special data-processing strategies and are examined for impact on model forecasts via assimilation experiments by employing the National Centers for Environmental Prediction (NCEP) operational Hurricane Weather Research and Forecasting (HWRF) Model using a Gridpoint Statistical Interpolation analysis system (GSI)-based ensemble–variational hybrid system. Two different data assimilation (DA) configurations, one with and one without the use of vortex initialization (VI), are compared. It is found that the assimilation of enhanced AMVs can improve the HWRF track and intensity forecasts of Gonzalo and Joaquin during their intensity change phases. The degree of data impact depends on the DA configuration used. Overall, assimilation of enhanced AMVs in the innermost domain (e.g., storm inner-core region and its immediate vicinity) outperforms other DA configurations, both with and without VI, as it results in better track and intensity forecasts. Compared to the experiment with VI, assimilation of enhanced AMVs without VI reveals more notable data impact on the forecasts of Hurricane Gonzalo, as the VI before DA alters the first guess and reduces the actual number of AMV observations assimilated into the DA system. Even with VI, assimilation of enhanced AMVs in the inner-core region can at least partially mitigate the negative effect of VI on the intensity forecast of Hurricane Gonzalo and alleviate the unrealistic vortex weakening in the simulation by removing unrealistic outflow structure and unfavorable thermodynamic conditions, thus leading to improved intensity forecasts.

scholarly journals Assimilation Experiments of MTSAT Rapid Scan Atmospheric Motion Vectors on a Heavy Rainfall Event

2015 ◽  
Vol 93 (4) ◽  
pp. 459-475 ◽  
Author(s):  
Michiko OTSUKA ◽  
Masaru KUNII ◽  
Hiromu SEKO ◽  
Kazuki SHIMOJI ◽  
Masahiro HAYASHI ◽  
...  
Keyword(s):  
Heavy Rainfall ◽  
Rainfall Event ◽  
Heavy Rainfall Event ◽  
Motion Vectors ◽  
Rapid Scan ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors

scholarly journals Impact of local data assimilation on tropical cyclone predictions over the Bay of Bengal using the ARW model

2015 ◽  
Vol 33 (7) ◽  
pp. 805-828 ◽  
Author(s):  
M. M. Greeshma ◽  
C. V. Srinivas ◽  
V. Yesubabu ◽  
C. V. Naidu ◽  
R. Baskaran ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Data Assimilation ◽  
Bay Of Bengal ◽  
Weather Research And Forecasting ◽  
Motion Vectors ◽  
Arw Model ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors ◽  
Radiance Data ◽  
Weather Research

Abstract. The tropical cyclone (TC) track and intensity predictions over Bay of Bengal (BOB) using the Advanced Research Weather Research and Forecasting (ARW) model are evaluated for a number of data assimilation experiments using various types of data. Eight cyclones that made landfall along the east coast of India during 2008–2013 were simulated. Numerical experiments included a control run (CTL) using the National Centers for Environmental Prediction (NCEP) 3-hourly 0.5 × 0.5° resolution Global Forecasting System (GFS) analysis as the initial condition, and a series of cycling mode variational assimilation experiments with Weather Research and Forecasting (WRF) data assimilation (WRFDA) system using NCEP global PrepBUFR observations (VARPREP), Atmospheric Motion Vectors (VARAMV), Advanced Microwave Sounding Unit (AMSU) A and B radiances (VARRAD) and a combination of PrepBUFR and RAD (VARPREP+RAD). The impact of different observations is investigated in detail in a case of the strongest TC, Phailin, for intensity, track and structure parameters, and finally also on a larger set of cyclones. The results show that the assimilation of AMSU radiances and Atmospheric Motion Vectors (AMV) improved the intensity and track predictions to a certain extent and the use of operationally available NCEP PrepBUFR data which contains both conventional and satellite observations produced larger impacts leading to improvements in track and intensity forecasts. The forecast improvements are found to be associated with changes in pressure, wind, temperature and humidity distributions in the initial conditions after data assimilation. The assimilation of mass (radiance) and wind (AMV) data showed different impacts. While the motion vectors mainly influenced the track predictions, the radiance data merely influenced forecast intensity. Of various experiments, the VARPREP produced the largest impact with mean errors (India Meteorological Department (IMD) observations less the model values) of 78, 129, 166, 210 km in the vector track position, 10.3, 5.8, 4.8, 9.0 hPa deeper than IMD data in central sea level pressure (CSLP) and 10.8, 3.9, −0.2, 2.3 m s−1 stronger than IMD data in maximum surface winds (MSW) for 24, 48, 72, 96 h forecasts respectively. An improvement of about 3–36 % in track, 6–63 % in CSLP, 26–103 % in MSW and 11–223 % in the radius of maximum winds in 24–96 h lead time forecasts are found with VARPREP over CTL, suggesting the advantages of assimilation of operationally available PrepBUFR data for cyclone predictions. The better predictions with PrepBUFR could be due to quality-controlled observations in addition to containing different types of data (conventional, satellite) covering an effectively larger area. The performance degradation of VARPREP+RAD with the assimilation of all available observations over the domain after 72 h could be due to poor area coverage and bias in the radiance data.

Retrieval and Application of Rapid-Scan Atmospheric Motion Vectors Using an Infrared Channel of the INSAT-3DR Satellite

2021 ◽  
Author(s):  
Dineshkumar K. Sankhala ◽  
Prashant Kumar ◽  
Sanjib K. Deb ◽  
Neeru Jaiswal ◽  
C. M. Kishtawal ◽  
...  
Keyword(s):  
Motion Vectors ◽  
Rapid Scan ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors ◽  
Infrared Channel
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