Impact of Assimilating Himawari‐8‐Derived Layered Precipitable Water With Varying Cumulus and Microphysics Parameterization Schemes on the Simulation of Typhoon Hato

Lu, Jiazheng; Feng, Tao; Li, Jun; Cai, Zelin; Xu, Xunjian; Li, Li; Li, Jinlong

doi:10.1029/2018jd029364

Cited by 29 publications

(16 citation statements)

References 79 publications

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“…The increasing PWV and decreasing pressure in Figure 10 indicated that the closer to the interior area of the typhoon, the higher the PWV and the lower the pressure, compared with their counterparts in the periphery of the typhoon. These results were consistent with many typhoon cases [3,42,43].…”

Section: Relationship Between Variations In Pwv and Atmospheric Paramsupporting

confidence: 91%

“…This is why many national central and local meteorological departments have paid great attention to typhoon forecasting [2]. A TC often carries a large amount of water vapor as it arrives in an area, thus the measurements of the spatio-temporal variations in water vapor may be used to predict the movement, intensity, and precipitation of the TC [3,4].…”

Section: Introductionmentioning

confidence: 99%

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Real-Time GNSS-Derived PWV for Typhoon Characterizations: A Case Study for Super Typhoon Mangkhut in Hong Kong

Zhang

et al. 2019

Remote Sensing

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Typhoons can be serious natural disasters for the sustainability and development of society. The development of a typhoon usually involves a pre-existing weather disturbance, warm tropical oceans, and a large amount of moisture. This implies that a large variation in the atmospheric water vapor over the path of a typhoon can be used to study the characteristics of the typhoon. This is the reason that the variation in precipitable water vapor (PWV) is often used to capture the signature of a typhoon in meteorology. This study investigates the usability of real-time PWV retrieved from global navigation satellite systems (GNSS) for typhoons’ characterizations, and especially, the following aspects were investigated: (1) The correlation between PWV and atmospheric parameters including pressure, temperature, precipitation, and wind speed; (2) water vapor transportation during a typhoon period; and (3) the correlation between the movement of a typhoon and the transportation of water vapor. The case study selected for this research was Super Typhoon Mangkhut that occurred in mid-September 2018 in Hong Kong. The PWV time series were obtained from a conversion of GNSS-derived zenith total delays (ZTDs) using observations at 10 stations selected from the Hong Kong GNSS continuously operating reference stations (CORS) network, which are also located along the path of the typhoon. The Bernese GNSS Software (ver. 5.2) was used to obtain the ZTDs; and the root mean square (RMS) of the differences between the GNSS-ZTDs and International GNSS Service post-processed ZTDs time series was less than 8 mm. The RMS of the differences between the GNSS-PWVs (i.e., the ZTDs converted PWVs) and radiosonde-derived PWVs (RS-PWVs) time series was less than 2 mm. The changes in PWV reflect the variation in wind speed during the typhoon period to a certain degree, and their correlation coefficient was 0.76, meaning a significant positive correlation. In addition, a new approach was proposed to estimate the direction and speed of a typhoon’s movement using the time difference of PWV arrival at different sites. The direction and speed estimated agreed well with the ones published by the China Meteorological Administration. These results suggest that GNSS-derived PWV has a great potential for the monitoring and even prediction of typhoon events, especially for near real-time warnings.

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Section: Relationship Between Variations In Pwv and Atmospheric Paramsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Real-Time GNSS-Derived PWV for Typhoon Characterizations: A Case Study for Super Typhoon Mangkhut in Hong Kong

Zhang

et al. 2019

Remote Sensing

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“…Comparisons between IR band radiance assimilation and LPW assimilation show overall similar or comparable impact on precipitation forecasts, but LPW assimilation provides better impact over land than that of radiance assimilation. Lu et al () also found that LPW assimilation reduces the 0‐ to 72hr (hour) average TC track error by better adjusting the atmospheric circulation fields, regardless which microphysical scheme and cumulus parameterization are used. They also found that LPW assimilation improves the TC intensity prediction due to accurate adjustment to the latent heat release process, the heavy precipitation forecasts are more sensitive to microphysical schemes selection, however, after LPW assimilation, the equitable threat scores from different schemes become similar and all forecast skills are increased.…”

Section: Applicationsmentioning

confidence: 99%

Legacy Atmospheric Profiles and Derived Products From GOES‐16: Validation and Applications

Schmit

Lee

et al. 2019

Earth and Space Science

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The Geostationary Operational Environmental Satellite‐R (GOES‐R) series started a new era for the U.S. geostationary satellite observing system. The Advanced Baseline Imager (ABI) onboard the GOES‐R series has fine temporal (30 s to 10 min) and spatial resolutions (0.5–2 km), and 16 spectral bands. However, due to the lack of an infrared sounder, the ABI is used to continue the legacy atmospheric profile (LAP) products that the previous GOES Sounder has, including the legacy atmospheric moisture profile, legacy atmospheric temperature profile, total precipitable water, layered precipitable water, and derived atmospheric stability indices. The ABI LAP retrieval algorithms have been developed under the GOES‐R series Algorithm Working Group (AWG) program funded by the GOES‐R Program Office. The LAP products from GOES‐16 have been operational and validated with a series of reference data sets including radiosonde observations, the Global Positioning System from SuomiNet, the Advanced Microwave Scanning Radiometer 2 total precipitable water measurements, as well as global operational analysis from National Oceanic and Atmospheric Administration and European Centre for Medium‐Range Weather Forecasts models, for almost a year (from 2017 to 2018) to assure the data quality for applications. In addition, the LAP products have been successfully demonstrated at the Hazardous Weather Testbed experiments in the summer of 2017 and the spring of 2018. Both validation results and Hazardous Weather Testbed demonstrations indicate that the GOES‐R series LAP products meet the product requirements and provide added value over NWP short‐range forecasts, especially for middle‐upper tropospheric moisture, in situation awareness and nowcasting.

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“…Currently, our state-of-the-art General Circulation Models (GCM) use Numerical Weather Prediction (NWP) to predict TCs and study their formation, development, and dissipation [4]. However, most GCM simulations present coarse horizontal resolutions (~0.1 • ).…”

Section: Introductionmentioning

confidence: 99%

“…Among the various NWP models, WRF, as one of the most popular mesoscale numerical weather predictions models, has been widely used to forecast and study TCs due to a flexible and computationally efficient platform for operational forecasting [6,7]. Nevertheless, TC's intense rainfall is time-dependent and spatially complex, therefore, the accuracy of TC precipitation prediction remains a challenge [4]. Additionally, uncertainty remains in optimal microphysics schemes and initializations, which contribute to inaccurate simulations.…”

Section: Introductionmentioning

confidence: 99%

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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Impact of Assimilating Himawari‐8‐Derived Layered Precipitable Water With Varying Cumulus and Microphysics Parameterization Schemes on the Simulation of Typhoon Hato

Cited by 29 publications

References 79 publications

Real-Time GNSS-Derived PWV for Typhoon Characterizations: A Case Study for Super Typhoon Mangkhut in Hong Kong

Real-Time GNSS-Derived PWV for Typhoon Characterizations: A Case Study for Super Typhoon Mangkhut in Hong Kong

Legacy Atmospheric Profiles and Derived Products From GOES‐16: Validation and Applications

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

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