scholarly journals Assimilation of Himawari-8 imager radiance data with the WRF-3DVAR system for the prediction of Typhoon Soudelor

2021 ◽  
Vol 21 (5) ◽  
pp. 1569-1582
Author(s):  
Feifei Shen ◽  
Aiqing Shu ◽  
Hong Li ◽  
Dongmei Xu ◽  
Jinzhong Min
Keyword(s):  
Data Assimilation ◽  
Inner Core ◽  
Surface Wind ◽  
Three Dimensional ◽  
Background Field ◽  
Japan Meteorological Agency ◽  
The Pacific ◽  
Geostationary Meteorological Satellite ◽  
Typhoon Season ◽  
Radiance Data

Abstract. Himawari-8 is a next-generation geostationary meteorological satellite launched by the Japan Meteorological Agency. It carries the Advanced Himawari Imager (AHI) on board, which can continuously monitor high-impact weather events with high frequency in space and time. The assimilation of AHI radiance data was implemented with the three-dimensional variational data assimilation system (3DVAR) of the Weather Research and Forecasting Model for the analysis and prediction of Typhoon Soudelor (2015) in the Pacific typhoon season. The effective assimilation of AHI radiance data in improving the forecast of the tropical cyclone during its rapid intensification has been realized. The results show that, after assimilating the AHI radiance data under clear-sky conditions, the typhoon position in the background field of the model was effectively corrected compared with the control experiment without AHI radiance data assimilation. It is found that the assimilation of AHI radiance data is able to improve the analyses of the water vapor and wind in a typhoon's inner-core region. The analyses and forecasts of the minimum sea level pressure, the maximum surface wind, and the track of the typhoon are further improved.

scholarly journals Assimilation of Himawari-8 Imager Radiance Data with the WRF-3DVAR system for the prediction of Typhoon Soulder

2020 ◽  
Author(s):  
Dongmei Xu ◽  
Aiqing Shu ◽  
Zhankui Zhang
Keyword(s):  
Inner Core ◽  
Surface Wind ◽  
Three Dimensional ◽  
Surface Wind Speed ◽  
Background Field ◽  
Japan Meteorological Agency ◽  
Near Surface ◽  
Frequency Space ◽  
Geostationary Meteorological Satellite ◽  
Typhoon Season

Abstract. Himawari-8 is a new generation geostationary meteorological satellite launched by Japan Meteorological Agency (JMA). It carries the Advanced Himawari imager (AHI) onboard, which can continuously monitor high-impact weather events with high frequency space and time. The assimilation of AHI was implemented with the framework of the mesoscale numerical model WRF and its three-dimensional variational assimilation system (3DVAR) for the analysis and prediction of typhoon Soudelor in the Pacific Typhoon season in 2015. The effective assimilation of AHI Imager data in tropical cyclone with rapid intensify development has been realized. The results show that after assimilating the AHI imager data under clear sky conditions, the typhoon position in the background field in the model is effectively corrected compared with the control experiment without AHI data. It is found that assimilation of AHI imager data is able to improve the analyses of the water vapor and wind in typhoon inner-core region. The analyses and forecast of the typhoon minimum sea level pressure, the maximum near-surface wind speed, and the typhoon track are further improved．

scholarly journals Evaluation of the Simulation of Typhoon Lekima (2019) Based on Different Physical Parameterization Schemes and FY-3D Satellite’s MWHS-2 Data Assimilation

2021 ◽  
Vol 13 (22) ◽  
pp. 4556
Author(s):  
Dongmei Xu ◽  
Xuewei Zhang ◽  
Hong Li ◽  
Haiying Wu ◽  
Feifei Shen ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Three Dimensional ◽  
Wrf Model ◽  
Background Field ◽  
Weather Research And Forecasting ◽  
Initial Field ◽  
Parameterization Schemes ◽  
Microwave Humidity Sounder ◽  
Radiance Data ◽  
Physical Parameterization

In this study, the case of super typhoon Lekima, which landed in Jiangsu and Zhejiang Province on 4 August 2019, is numerically simulated. Based on the Weather Research and Forecasting (WRF) model, the sensitivity experiments are carried out with different combinations of physical parameterization schemes. The results show that microphysical schemes have obvious impacts on the simulation of the typhoon’s track, while the intensity of the simulated typhoon is more sensitive to surface physical schemes. Based on the results of the typhoon’s track and intensity simulation, one parameterization scheme was further selected to provide the background field for the following data assimilation experiments. Using the three-dimensional variational (3DVar) data assimilation method, the Microwave Humidity Sounder-2 (MWHS-2) radiance data onboard the Fengyun-3D satellite (FY-3D) were assimilated for this case. It was found that the assimilation of the FY-3D MWHS-2 radiance data was able to optimize the initial field of the numerical model in terms of the model variables, especially for the humidity. Finally, by the inspection of the typhoon’s track and intensity forecast, it was found that the assimilation of FY-3D MWHS-2 radiance data improved the skill of the prediction for both the typhoon’s track and intensity.

scholarly journals Storm-Centered Ensemble Data Assimilation for Tropical Cyclones

2014 ◽  
Vol 142 (6) ◽  
pp. 2309-2320 ◽  
Author(s):  
Erika L. Navarro ◽  
Gregory J. Hakim
Keyword(s):  
Data Assimilation ◽  
Large Scale ◽  
Inner Core ◽  
Three Dimensional ◽  
Water Model ◽  
Ensemble Data Assimilation ◽  
Ensemble Data ◽  
Relative Coordinates ◽  
Order Of Magnitude ◽  
Storm Dynamics

Abstract A significant challenge for tropical cyclone ensemble data assimilation is that storm-scale observations tend to make analyses that are more asymmetric than the prior forecasts. Compromised structure and intensity, such as an increase of amplitude across the azimuthal Fourier spectrum, are a routine property of ensemble-based analyses, even with accurate position observations and frequent assimilation. Storm dynamics in subsequent forecasts evolve these states toward axisymmetry, creating difficulty in distinguishing between model-induced and actual storm asymmetries for predictability studies and forecasting. To address this issue, a novel algorithm using a storm-centered approach is proposed. The method is designed for use with existing ensemble filters with little or no modification, facilitating its adoption and maintenance. The algorithm consists of 1) an analysis of the environment using conventional coordinates, 2) a storm-centered analysis using storm-relative coordinates, and 3) a merged analysis that combines the large-scale and storm-scale fields together at an updated storm location. This algorithm is evaluated in two sets of observing system simulation experiments (OSSEs): first, no-cycling tests of the update step for idealized three-dimensional storms in radiative–convective equilibrium; second, full cycling tests of data assimilation applied to a shallow-water model for a field of interacting vortices. Results are compared against a control experiment based on a conventional ensemble Kalman filter (EnKF) scheme as well as an alternative EnKF scheme proposed by Lawson and Hansen. The storm-relative method yields vortices that are more symmetric and exhibit finer inner-core structure than either approach, with errors reduced by an order of magnitude over a control case with prior spread consistent with the National Hurricane Center (NHC)’s mean 5-yr forecast track error at 12 h. Azimuthal Fourier error spectra exhibit much-reduced noise associated with data assimilation as compared to both the control and the Lawson and Hansen approach. An assessment of free-surface height tendency of model forecasts after the merge step reveals a balanced trend between the storm-centered and conventional approaches, with storm-centered values more closely resembling the reference state.

The Impact of Multisatellite Data on the Initialization and Simulation of Hurricane Lili’s (2002) Rapid Weakening Phase

2007 ◽  
Vol 135 (2) ◽  
pp. 526-548 ◽  
Author(s):  
Xiaoyan Zhang ◽  
Qingnong Xiao ◽  
Patrick J. Fitzpatrick
Keyword(s):  
Data Assimilation ◽  
Satellite Data ◽  
Inner Core ◽  
Surface Wind ◽  
Storm Track ◽  
Outer Core ◽  
Intensity Change ◽  
Track Forecast ◽  
Surface Winds ◽  
The Impact

Abstract Numerical experiments have been conducted to examine the impact of multisatellite data on the initialization and forecast of the rapid weakening of Hurricane Lili (in 2002) from 0000 UTC to landfall in Louisiana on 1300 UTC 3 October 2002. Fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) 4DVAR sensitivity runs were conducted separately with QuikSCAT surface winds, the Geostationary Operational Environmental Satellite-8 (GOES-8) cloud drift–water vapor winds, and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) temperature–dewpoint sounding data to investigate their individual impact on storm track and intensity. The results were compared against a simulation initialized from a Global Forecast System background interpolated to the MM5 grid. Assimilating QuikSCAT surface wind data improves the analyzed outer-core surface winds, as well as the inner-core low-level temperature and moisture fields. Substantial adjustments of winds are noted on the periphery of the hurricane by assimilating GOES-8 satellite-derived upper-level winds. Both track forecasts initialized at 1200 UTC 2 October 2002 with four-dimensional variational data assimilation (4DVAR) of QuikSCAT and GOES-8 show improvement compared to those initialized with the model background. Assimilating Aqua MODIS sounding data improves the outer-core thermodynamic features. The Aqua MODIS data has a slight impact on the track forecast, but more importantly shows evidence of impacting the model intensity predicting by retarding the incorrect prediction of intensification. All three experiments also show that bogusing of an inner-core wind vortex is required to depict the storm’s initial intensity. To properly investigate Lili’s weakening, data assimilation experiments that incorporate bogusing vortex, QuikSCAT winds, GOES-8 winds, and Aqua MODIS sounding data were performed. The 4DVAR satellite-bogus data assimilation is conducted in two consecutive 6-h windows preceding Lili’s weakening. Comparisons of the results between the experiments with and without satellite data indicated that the satellite data, particularly the Aqua MODIS sounding information, makes an immediate impact on the hurricane intensity change beyond normal bogusing procedures. The track forecast with the satellite data is also more accurate than just using bogusing alone. This study suggests that dry air intrusion played an important role in Lili’s rapid weakening. It also demonstrates the potential benefit of using satellite data in a 4DVAR context—particularly high-resolution soundings—on unusual cases like Hurricane Lili.

Evaluations of BDA Scheme Using the Advanced Research WRF (ARW) Model

2009 ◽  
Vol 48 (3) ◽  
pp. 680-689 ◽  
Author(s):  
Qingnong Xiao ◽  
Liqiang Chen ◽  
Xiaoyan Zhang
Keyword(s):  
Data Assimilation ◽  
Surface Wind ◽  
Three Dimensional ◽  
Ocean Basin ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Sea Level Pressure ◽  
Noticeable Improvement ◽  
Arw Model ◽  
Definition Of

Abstract A tropical cyclone bogus data assimilation (BDA) scheme is built in the Weather Research and Forecasting three-dimensional variational data assimilation system (WRF 3D-VAR). Experiments were conducted (21 experiments with BDA in parallel with another 21 without BDA) to assess its impacts on the predictions of seven Atlantic Ocean basin hurricanes observed in 2004 (Charley, Frances, Ivan, and Jeanne) and in 2005 (Katrina, Rita, and Wilma). In addition, its performance was compared with the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane initialization scheme in a case study of Hurricane Humberto (2007). It is indicated that hurricane initialization with the BDA technique can improve the forecast skills of track and intensity in the Advanced Research WRF (ARW). Among the three hurricane verification parameters [track, central sea level pressure (CSLP), and maximum surface wind (MSW)], BDA improves CSLP the most. The improvement of MSW is also considerable. The track has the smallest, but still noticeable, improvement. With WRF 3D-VAR, the initial vortex produced by BDA is balanced with the dynamical and statistical balance in the 3D-VAR system. It has great potential for improving the hurricane intensity forecast. The case study on Hurricane Humberto (2007) shows that BDA performs better than the GFDL bogus scheme in the ARW forecast for the case. Better definition of the initial vortex is the main reason for the advanced skill in hurricane track and intensity forecasting in this case.

scholarly journals Seasonal Variations of Volcanic Ash and Aerosol Emissions around Sakurajima Detected by Two Lidars

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 326
Author(s):  
Atsushi Shimizu ◽  
Masato Iguchi ◽  
Haruhisa Nakamichi
Keyword(s):  
Particle Size ◽  
Extinction Coefficient ◽  
Volcanic Ash ◽  
Surface Wind ◽  
Three Dimensional ◽  
Japan Meteorological Agency ◽  
Extinction Coefficients ◽  
Ash Fall ◽  
Dimensional Distribution ◽  
Aerosol Emissions

Two polarization-sensitive lidars were operated continuously to monitor the three-dimensional distribution of small volcanic ash particles around Sakurajima volcano, Kagoshima, Japan. Here, we estimated monthly averaged extinction coefficients of particles between the lidar equipment and the vent and compared our results with monthly records of volcanic activity reported by the Japan Meteorological Agency, namely the numbers of eruptions and explosions, the density of ash fall, and the number of days on which ash fall was observed at the Kagoshima observatory. Elevated extinction coefficients were observed when the surface wind direction was toward the lidar. Peaks in extinction coefficient did not always coincide with peaks in ash fall density, and these differences likely indicate differences in particle size.

scholarly journals Application of ATOVS Radiance with ARW WRF/GSI Data Assimilation System in the Prediction of Hurricane Katrina

2009 ◽  
Vol 3 (1) ◽  
pp. 13-28 ◽  
Author(s):  
J. Xu ◽  
S. Rugg ◽  
M. Horner ◽  
L. Byerle
Keyword(s):  
Data Assimilation ◽  
Hurricane Katrina ◽  
Three Dimensional ◽  
Wrf Model ◽  
Vortex Center ◽  
Atmospheric Flow ◽  
Infrared Observation ◽  
Westward Movement ◽  
Radiance Data ◽  
The Impact

In this study, we evaluated the impact of directly assimilating radiance on Hurricane Katrina forecasts over the Gulf of Mexico in the southeastern United States in August 2005. The ATOVS (i.e., The Advanced Television and Infrared Observation Satellite (TIROS)-N Operational Vertical Sounder) radiance data, the Gridpoint Statistical Interpolation (GSI) three-dimensional variational analysis (3DVAR) system, and the Advanced Research WRF (ARW WRF) model were employed. The results in a series of experiments show that after radiance data assimilation, the intensity and structure of initial fields including atmospheric flow, temperature and moisture have been modified somehow, especially with instruments using microwave bands such as AMSU-A/B. An anomalous southward pressure gradient has been added behind the hurricane center, which made the easterly flow go through the initial vortex center, accelerating westward movement of the hurricane. All data assimilation experiments obtain a similar forecast for the hurricane track before 36 h of model integration. After 36 h, the hurricane tracks in AMSU-A/B experiments are closer to the best track, but the tracks in HIRS3 and control experiments have a bigger error. However, we note that the improvement is limited, all assimilation experiments did not properly depict the deepening of the hurricane center around 1800 UTC 28 August.

scholarly journals Effects of Clear-Sky Assimilation of GPM Microwave Imager on the Analysis and Forecast of Typhoon “Chan-Hom”

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2674
Author(s):  
Dongmei Xu ◽  
Aiqing Shu ◽  
Feifei Shen
Keyword(s):  
Three Dimensional ◽  
Maximum Error ◽  
Background Information ◽  
Track Forecast ◽  
Clear Sky ◽  
Warm Core ◽  
Microwave Imager ◽  
Typhoon Season ◽  
The One ◽  
Radiance Data

The module of assimilating a new GMI (GPM Microwave Imager) satellite detector was built in the framework of the Weather Research and Forecasting Model (WRF) and its three-dimensional variational (3DVar) data assimilation system (WRFDA). Typhoon “Chan-Hom” in the 2015 Pacific typhoon season was selected to verify the effectivity of the GMI clear-sky assimilation. The results show that, after assimilating the GMI radiance data, the background information in the model is modified positively when compared with the experiment without any assimilation and the one with assimilation of the conventional data. The obvious warm core structure of the typhoon, the modified geopotential height field, and the intensified circulation of the typhoon are favorable for the northwest twist of the typhoon, thus contributing to a better track forecast with a maximum error below 160 km in the 48-h deterministic forecast.

Assimilation of SSM/I Radiances in the NCEP Global Data Assimilation System

2006 ◽  
Vol 134 (9) ◽  
pp. 2612-2631 ◽  
Author(s):  
Kozo Okamoto ◽  
John C. Derber
Keyword(s):  
Wind Speed ◽  
Data Assimilation ◽  
Bias Correction ◽  
Surface Wind ◽  
Radiative Transfer Model ◽  
Average Error ◽  
Transfer Model ◽  
The Tropics ◽  
Radiance Data ◽  
Global Data

Abstract A technique for the assimilation of Special Sensor Microwave Imager (SSM/I) data in the National Centers for Environmental Prediction (NCEP) global data assimilation and forecast system is described. Because the radiative transfer model used does not yet allow for cloud/rain effects, it is crucial to properly identify and exclude (or correct) cloud/rain-contaminated radiances using quality control (QC) and bias correction procedures. The assimilation technique is unique in that both procedures take into account the effect of the liquid cloud on the difference between observed and simulated brightness temperature for each SSM/I channel. The estimate of the total column cloud liquid water from observed radiances is used in a frequency-dependent cloud detection component of the QC and as a predictor in the bias correction algorithm. Also, a microwave emissivity Jacobian model with respect to wind speed is developed for oceanic radiances. It was found that the surface wind information in the radiance data can be extracted through the emissivity model Jacobian rather than producing and including a separate SSM/I wind speed retrieval. A two-month-long data assimilation experiment from July to August 2004 using NCEP’s Gridpoint Statistical Interpolation analysis system and the NCEP operational forecast model was performed. In general, the assimilation of SSM/I radiance has a significant positive impact on the analyses and forecasts. Moisture is added in the Northern Hemisphere and Tropics and is slightly reduced in the Southern Hemisphere. The moisture added appears to be slightly excessive in the Tropics verified against rawinsonde observations. Nevertheless, the assimilation of SSM/I radiance data reduces model spinup of precipitation and substantially improves the dynamic fields, especially in measures of the vector wind error at 200 hPa in the Tropics. In terms of hurricane tracks, SSM/I radiance assimilation produces more cases with smaller errors and reduces the average error. No disruption of the Hadley circulation is found from the introduction of the SSM/I radiance data.

Improving numerical simulation of typhoon LEKIMA(2019) through assimilating ATMS radiance data

2020 ◽  
Author(s):  
Lei Zhang ◽  
Baode Chen
Keyword(s):  
Numerical Simulation ◽  
Data Assimilation ◽  
Inner Core ◽  
Weather Prediction ◽  
Advanced Technology ◽  
Limited Area ◽  
Numerical Weather ◽  
Satellite Radiance Data ◽  
Radiance Data ◽  
The Impact

<p>Lacking of high-resolution observations over oceans is one of the major problems for the numerical simulation of the tropical cyclones (TC), especially for the tropical cyclone inner-core structure’s simulation. Satellite observations plays an important role in improving the forecast skills of numerical weather prediction (NWP) systems. Many studies have suggested that the assimilation of satellite radiance data can substantially improve the numerical weather forecast skills for global model. However, the performance of satellite radiance data assimilation in limited-area modeling systems is still controversial.</p><p>This study attempts to investigate the impact of assimilation of the Advanced Technology Microwave Sounder (ATMS) satellite radiances data and its role to improve the model initial condition and forecast of typhoon LEKIMA(2019) using a regional mesoscale model. In this study, detailed analysis of the data impact will be presented, also the results from different data assimilation methods and different data usage schemes will be discussed.</p>

Sign in / Sign up

Export Citation Format

Share Document