Determining Tropical Cyclone Surface Wind Speed Structure and Intensity with the CYGNSS Satellite Constellation

Abstract

The Cyclone Global Navigation Satellite System (CYGNSS) consists of a constellation of eight microsatellites that provide observations of surface wind speed in all precipitating conditions. A method for estimating tropical cyclone (TC) metrics—maximum surface wind speed VMAX, radius of maximum surface wind speed RMAX, and wind radii (R64, R50, and R34)—from CYGNSS observations is developed and tested using simulated CYGNSS observations with realistic measurement errors. Using two inputs, 1) CYGNSS observations and 2) the storm center location, estimates of TC metrics are possible through the use of a parametric wind model algorithm that effectively interpolates between the available observations as a constraint on the assumed wind speed distribution. This methodology has a promising performance as evaluated from the simulations presented. In particular, after quality-control filters based on sampling properties are applied to the population of test cases, the standard deviation of retrieval error for VMAX is 4.3 m s−1 (where 1 m s−1 = 1.94 kt), for RMAX is 17.4 km, for R64 is 16.8 km, for R50 is 21.6 km, and for R34 is 41.3 km (where 1 km = 0.54 n mi). These TC data products will be available for the 2017 Atlantic Ocean hurricane season using on-orbit CYGNSS observations, but near-real-time operations are the subject of future work. Future work will also include calibration and validation of the algorithm once real CYGNSS data are available.

A Preliminary Impact Study of CYGNSS Ocean Surface Wind Speeds on Numerical Simulations of Hurricanes

“…Compared with most space‐based measurements that use backscattered microwave radar pulses (e.g., QuikSCAT and ASCAT), GPS signals are in an L band frequency and are largely unaffected by precipitation. Therefore, CYGNSS‐derived OSWS are available in a TC inner‐core region and provide high temporal resolution and spatial coverage under all precipitating conditions and over the full dynamic range of wind speeds experienced in a TC (Morris & Ruf, ; Ruf et al, ). Before its launch, a variety of observing system simulation experiments (e.g., Annane et al, ; Leidner et al, ; McNoldy et al, ; Zhang et al, ) suggested that assimilation of CYGNSS OSWS would have positive impacts on short‐range hurricane forecasts of both track and intensity with the Hurricane Weather Research and Forecasting (HWRF) model.…”

“…This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. and provide high temporal resolution and spatial coverage under all precipitating conditions and over the full dynamic range of wind speeds experienced in a TC (Morris & Ruf, 2017;Ruf et al, 2016). Before its launch, a variety of observing system simulation experiments (e.g., Annane et al, 2018;Leidner et al, 2018;McNoldy et al, 2017;Zhang et al, 2017) suggested that assimilation of CYGNSS OSWS would have positive impacts on short-range hurricane forecasts of both track and intensity with the Hurricane Weather Research and Forecasting (HWRF) model.…”

A Study on Assimilation of CYGNSS Wind Speed Data for Tropical Convection during 2018 January MJO

“…In this study, a few quality control steps were applied to the Level 2 CYGNSS data v2.1. Data with the range corrected gain below 3 and the zenith sun angle lower than zero were removed to Previous studies found that CYGNSS measurements during TC overpasses can help in finding the correct center location, estimating the intensity, and constructing the wind distribution within the TC [40,47,48]. Hoover et al [46] also showed that synthetic CYGNSS data may be used to monitor westerly wind burst (WWB) events during MJO events.…”

Retrieval of Ocean Wind Speed Using Super-Resolution Delay-Doppler Maps

“…Since scattered signals are relatively weak, a one-second long integration period is required, especially for spaceborne missions [13][14][15]. Currently, the National Aeronautics and Space Administration (NASA) Cyclone GNSS (CYGNSS) mission collects global surface wind field information to help predict the dynamics of hurricanes [16]. The CYGNSS is composed of eight micro-satellites.…”