scholarly journals Impact of CYGNSS Ocean Surface Wind Speeds on Numerical Simulations of a Hurricane in Observing System Simulation Experiments

2017 ◽  
Vol 34 (2) ◽  
pp. 375-383 ◽  
Author(s):  
Shixuan Zhang ◽  
Zhaoxia Pu ◽  
Derek J. Posselt ◽  
Robert Atlas
Keyword(s):  
Numerical Simulations ◽  
Inner Core ◽  
System Simulation ◽  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Surface Fluxes ◽  
Hurricane Track ◽  
Ocean Surface Wind ◽  
The Impact

AbstractThe NASA Cyclone Global Navigation Satellite System (CYGNSS) was launched in late 2016. It will make available frequent ocean surface wind speed observations throughout the life cycle of tropical storms and hurricanes. In this study, the impact of CYGNSS ocean surface winds on numerical simulations of a hurricane case is assessed with a research version of the Hurricane Weather Research and Forecasting Model and a Gridpoint Statistical Interpolation analysis system in a regional observing system simulation experiment framework. Two different methods for reducing the CYGNSS data volume were tested: one in which the winds were thinned and one in which the winds were superobbed.The results suggest that assimilation of the CYGNSS winds has great potential to improve hurricane track and intensity simulations through improved representations of the surface wind fields, hurricane inner-core structures, and surface fluxes. The assimilation of the superobbed CYGNSS data seems to be more effective in improving hurricane track forecasts than thinning the data.

Impact of Assimilating CYGNSS Data on Tropical Cyclone Analyses and Forecasts in a Regional OSSE Framework

2017 ◽  
Vol 51 (1) ◽  
pp. 7-15 ◽  
Author(s):  
Brian McNoldy ◽  
Bachir Annane ◽  
Sharanya Majumdar ◽  
Javier Delgado ◽  
Lisa Bucci ◽  
...  
Keyword(s):  
Wind Speed ◽  
Large Scale ◽  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Satellite System ◽  
Directional Information ◽  
Wind Speed Data ◽  
Ocean Surface Wind ◽  
The Impact

AbstractThe impact of assimilating ocean surface wind observations from the Cyclone Global Navigation Satellite System (CYGNSS) is examined in a high-resolution Observing System Simulation Experiment (OSSE) framework for tropical cyclones (TCs). CYGNSS is a planned National Aeronautics and Space Administration constellation of microsatellites that utilizes existing GNSS satellites to retrieve surface wind speed. In the OSSE, CYGNSS wind speed data are simulated using output from a “nature run” as truth. In a case study using the regional Hurricane Weather Research and Forecasting modeling system and the Gridpoint Statistical Interpolation data assimilation scheme, analyses of TC position, structure, and intensity, together with large-scale variables, are improved due to the assimilation of the additional surface wind data. These results indicate the potential importance of CYGNSS ocean surface wind speed data and furthermore that the assimilation of directional information would add further value to TC analyses and forecasts.

Ocean surface wind speed retrieval from C-band quad-polarized SAR measurements at optimal spatial resolution

2020 ◽  
Vol 12 (2) ◽  
pp. 155-164
Author(s):  
He Fang ◽  
William Perrie ◽  
Gaofeng Fan ◽  
Tao Xie ◽  
Jingsong Yang
Keyword(s):  
Wind Speed ◽  
Spatial Resolution ◽  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Ocean Surface Wind

CYGNSS Observations and Analysis of Low-Latitude Extratropical Cyclones

2021 ◽  
Vol 60 (4) ◽  
pp. 527-541
Author(s):  
Juan A. Crespo ◽  
Catherine M. Naud ◽  
Derek J. Posselt
Keyword(s):  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Satellite System ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Surface Processes ◽  
Extratropical Cyclones ◽  
Low Latitude ◽  
Reanalysis Dataset

AbstractLatent and sensible heat fluxes over the oceans are believed to play an important role in the genesis and evolution of marine-based extratropical cyclones (ETCs) and affect rapid cyclogenesis. Observations of ocean surface heat fluxes are limited from existing in situ and remote sensing platforms, which may not offer sufficient spatial and temporal resolution. In addition, substantial precipitation frequently veils the ocean surface around ETCs, limiting the capacity of spaceborne instruments to observe the surface processes within maturing ETCs. Although designed as a tropics-focused mission, the Cyclone Global Navigation Satellite System (CYGNSS) can observe ocean surface wind speed and heat fluxes within a notable quantity of low-latitude extratropical fronts and cyclones. These observations can assist in understanding how surface processes may play a role in cyclogenesis and evolution. This paper illustrates CYGNSS’s capability to observe extratropical cyclones manifesting in various ocean basins throughout the globe and shows that the observations provide a robust sample of ETCs winds and surface fluxes, as compared with a reanalysis dataset.

scholarly journals Evaluation of the Ocean Surface Wind Speed Change following the Super Typhoon from Space-Borne GNSS-Reflectometry

2020 ◽  
Vol 12 (12) ◽  
pp. 2034 ◽  
Author(s):  
Hongsu Liu ◽  
Shuanggen Jin ◽  
Qingyun Yan
Keyword(s):  
Wind Speed ◽  
Correlation Coefficient ◽  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Wind Speeds ◽  
Mean Error ◽  
Super Typhoon ◽  
The Mean ◽  
Ocean Surface Wind

Ocean surface wind speed is an essential parameter for typhoon monitoring and forecasting. However, traditional satellite and buoy observations are difficult to monitor the typhoon due to high cost and low temporal-spatial resolution. With the development of spaceborne GNSS-R technology, the cyclone global navigation satellite system (CYGNSS) with eight satellites in low-earth orbit provides an opportunity to measure the ocean surface wind speed of typhoons. Though observations are made at the extremely efficient spatial and temporal resolution, its accuracy and reliability are unclear in an actual super typhoon case. In this study, the wind speed variations over the life cycle of the 2018 Typhoon Mangkhut from CYGNSS observations were evaluated and compared with European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-5 (ERA-5). The results show that the overall root-mean-square error (RMSE) of CYGNSS versus ECMWF was 4.12 m/s, the mean error was 1.36 m/s, and the correlation coefficient was 0.96. For wind speeds lower and greater than 15 m/s, the RMSE of CYGNSS versus ECMWF were 1.02 and 4.36 m/s, the mean errors were 0.05 and 1.61 m/s, the correlation coefficients were 0.91 and 0.90, and the average relative errors were 9.8% and 11.6%, respectively. When the typhoon reached a strong typhoon or super typhoon, the RMSE of CYGNSS with respect to ERA-5 from ECMWF was 5.07 m/s; the mean error was 3.57 m/s; the correlation coefficient was 0.52 and the average relative error was 11.0%. The CYGNSS estimation had higher precision for wind speeds below 15 m/s, but degraded when the wind speed was above 15 m/s.

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