Satellite radiance data assimilation for binary tropical cyclone cases over the western <scp>N</scp>orth <scp>P</scp>acific

Choi, Yonghan; Cha, Dong‐Hyun; Lee, Myong‐In; Kim, Joowan; Jin, Chun‐Sil; Park, Sang Hun; Joh, Min Su

doi:10.1002/2016ms000826

Cited by 19 publications

(9 citation statements)

References 66 publications

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“…We suspect that changes in DA-IMERG are sufficiently effective not only in improving the accuracy of the WRF model but also advancing the detection capability of heavy rainfall events. These results are almost consistent with the results from Choi et al [46], who also points to assimilating observation data for improved track and intensity forecasts of TC rainfall.…”

Section: Discussionsupporting

confidence: 91%

Data Assimilation of High-Resolution Satellite Rainfall Product Improves Rainfall Simulation Associated with Landfalling Tropical Cyclones in the Yangtze River Delta

Wang

Yang

et al. 2020

Remote Sensing

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Floods caused by heavy rainfall events associated with landfalling tropical cyclones (TCs) represent a major risk for the Yangtze River Delta (YRD) region of China. Accurate extreme precipitation forecasting, at long lead times, is crucial for the improvement of flood prevention and warning. However, accurate prediction of timing, location, and intensity of the heavy rainfall events is a major challenge for the Numerical Weather Prediction (NWP). In this study, high-resolution satellite precipitation products like Global Precipitation Measurement (GPM) are evaluated at the hourly timescale, and the optimal Integrated Multi-satellite Retrievals for GPM (IMERG) precipitation product is selected and applied to directly assimilate into the Weather Research and Forecasting (WRF) model via the four-dimensional variational (4D-Var) method. The TC Jondari and Rumbia events of August 2018 are evaluated to analyze the performance of the WRF model with the 4D-Var method assimilated IMERG precipitation product (DA-IMERG) and the conventional observation (DA-CONV) for real-time heavy rainfall forecasting. The results indicate that (1) IMERG precipitation products were larger and wetter than the observed precipitation values over YRD. By comparison, the performance of “late” run precipitation product (IMERG-L) was the closest to the observation data with lower deviation and higher detection capability; (2) DA-IMERG experiment substantially affected the magnitude of the WRF model primary variables, which changed the precipitation pattern of the TC heavy rain. (3) DA-IMERG experiment further improved the forecast of heavy rainbands and relatively reduced erroneous detection rate than CTL and DA-CONV experiments at the grid scale. Meanwhile, the DA-IMERG experiment has a better fractions skill score (FSS) value (especially in the threshold of 10 mm/h) than DA-CONV for TC Jondari and Rumbia at the spatial scale, while it shows a lower performance than CTL and DA-CONV experiments when the threshold is lower than the 5 mm/h for the TC Rumbia.

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Section: Discussionsupporting

confidence: 91%

Data Assimilation of High-Resolution Satellite Rainfall Product Improves Rainfall Simulation Associated with Landfalling Tropical Cyclones in the Yangtze River Delta

Wang

Yang

et al. 2020

Remote Sensing

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“…Figure 4 also shows the distribution of GTS observation data at the simulated domain at 00:00 UTC on 2 August 2015. It is proved that raw radiance observations thinned to a grid with 2-6 times the model grid resolution are able to remove the potential error correlations between adjacent observations (Schwartz et al, 2012;Xu et al, 2015;Choi et al, 2017). Hence, 20 km is chosen for thinning of AHI radiance data.…”

Section: Experimental Designmentioning

confidence: 99%

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

Shen

Shu

et al. 2021

Nat. Hazards Earth Syst. Sci.

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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.

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“…In the 2000s, numerous researchers conducted studies on multiple-typhoon interactions using numerical models (Khain et al, 2000;Yang et al, 2008;Wu et al, 2012;Jang and Chun, 2015;Choi et al, 2017). For example, Khain et al (2000) investigated the motion and evolution of binary tropical cyclone using a coupled tropical cyclone-ocean movable nested grid model.…”

Section: Introductionmentioning

confidence: 99%

Numerical Analysis of the Effect of Binary Typhoons on Ocean Surface Waves in Waters Surrounding Taiwan

et al. 2021

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The ocean surface waves during Super Typhoons Maria (2018), Lekima (2019), and Meranti (2016) were reproduced using hybrid typhoon winds and a fully coupled wave-tide-circulation modeling system (SCHISM-WWM-III). The hindcasted significant wave heights are in good agreement with the along-track significant wave heights measured by the altimeters aboard the SARAL (Satellite with ARgos and ALtiKa) and Jason-2 satellites. Two numerical experiments pairing Super Typhoons Maria (2018) and Meranti (2016) and Super Typhoons Lekima (2019) and Meranti (2016) were conducted to analyze the storm wave characteristics of binary and individual typhoons. Four points located near the tracks of the three super typhoons were selected to elucidate the effects of binary typhoons on ocean surface waves. The comparisons indicate that binary typhoons not only cause an increase in the significant wave height simulations at four selected pints but also result in increases in the one-dimensional wave energy and two-dimensional directional wave spectra. Our results also reveal that the effects of binary typhoons on ocean surface waves are more significant at the periphery of the typhoon than near the center of the typhoon. The interactions between waves generated by Super Typhoons Maria (2018) and Meranti (2016) or Super Typhoons Lekima (2019) and Meranti (2016) might be diminished by Taiwan Island even if the separation distance between two typhoons is <700 km.

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Satellite radiance data assimilation for binary tropical cyclone cases over the western North Pacific

Cited by 19 publications

References 66 publications

Data Assimilation of High-Resolution Satellite Rainfall Product Improves Rainfall Simulation Associated with Landfalling Tropical Cyclones in the Yangtze River Delta

Data Assimilation of High-Resolution Satellite Rainfall Product Improves Rainfall Simulation Associated with Landfalling Tropical Cyclones in the Yangtze River Delta

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

Numerical Analysis of the Effect of Binary Typhoons on Ocean Surface Waves in Waters Surrounding Taiwan

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