NWP Ocean Calibration for the CFOSAT wind scatterometer and wind retrieval evaluation

The National Aeronautics and Space Administration (NASA) Cyclone Global Navigation Satellite System (CyGNSS) mission was launched in December 2016, which can remotely sense sea surface wind with a relatively high spatio-temporal resolution for tracking tropical cyclones. In recent years, with the gradual development of the geophysical model function (GMF) for CyGNSS wind retrieval, different versions of CyGNSS Level 2 products have been released and their performance has gradually improved. This paper presents a comprehensive evaluation of CyGNSS wind product v1.1 produced by the National Oceanic and Atmospheric Administration (NOAA). The Cross-Calibrated Multi-Platform (CCMP) analysis wind (v02.0 and v02.1 near real time) products produced by Remote Sensing Systems (RSS) were used as the reference. Data pairs between the NOAA CyGNSS and RSS CCMP products were processed and evaluated by the bias and standard deviation SD. The CyGNSS dataset covers the period between May 2017 and December 2020. The statistical comparisons show that the bias and SD of CyGNSS relative to CCMP-nonzero collocations when the flag of CCMP winds is nonzero are –0.05 m/s and 1.19 m/s, respectively. The probability density function (PDF) of the CyGNSS winds coincides with that of CCMP-nonzero. Furthermore, the average monthly bias and SD show that CyGNSS wind is consistent and reliable generally. We found that negative deviation mainly appears at high latitudes in both hemispheres. Positive deviation appears in the China Sea, the Arabian Sea, and the west of Africa and South America. Spatial–temporal analysis demonstrates the geographical anomalies in the bias and SD of the CyGNSS winds, confirming that the wind speed bias shows a temporal dependency. The verification and comparison show that the remotely sensed wind speed measurements from NOAA CyGNSS wind product v1.1 are in good agreement with CCMP winds.

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Wind Speed Retrieval from Simulated RADARSAT Constellation Mission Compact Polarimetry SAR Data for Marine Application

Remote Sensing ◽

10.3390/rs11141682 ◽

2019 ◽

Vol 11 (14) ◽

pp. 1682 ◽

Cited By ~ 1

Author(s):

Torsten Geldsetzer ◽

Shahid K. Khurshid ◽

Kerri Warner ◽

Filipe Botelho ◽

Dean Flett

Keyword(s):

Wind Speed ◽

Low Noise ◽

Quality Data ◽

Band Model ◽

Data Set ◽

Wind Retrieval ◽

Wind Speeds ◽

Geophysical Model ◽

The Right ◽

Quality Threshold

RADARSAT Constellation Mission (RCM) compact polarimetry (CP) data were simulated using 504 RADARSAT-2 quad-pol SAR images. These images were used to samples CP data in three RCM modes to build a data set with co-located ocean wind vector observations from in situ buoys on the West and East coasts of Canada. Wind speeds up to 18 m/s were included. CP and linear polarization parameters were related to the C-band model (CMOD) geophysical model functions CMOD-IFR2 and CMOD5n. These were evaluated for their wind retrieval potential in each RCM mode. The CP parameter Conformity was investigated to establish a data-quality threshold (>0.2), to ensure high-quality data for model validation. An accuracy analysis shows that the first Stokes vector (SV0) and the right-transmit vertical-receive backscatter (RV) parameters were as good as the VV backscatter with CMOD inversion. SV0 produced wind speed retrieval accuracies between 2.13 m/s and 2.22 m/s, depending on the RCM mode. The RCM Medium Resolution 50 m mode produced the best results. The Low Resolution 100 m and Low Noise modes provided similar results. The efficacy of SV0 and RV imparts confidence in the continuity of robust wind speed retrieval with RCM CP data. Three image-based case studies illustrate the potential for the application of CP parameters and RCM modes in operational wind retrieval systems. The results of this study provide guidance to direct research objectives once RCM is launched. The results also provide guidance for operational RCM data implementation in Canada’s National SAR winds system, which provides near-real-time wind speed estimates to operational marine forecasters and meteorologists within Environment and Climate Change Canada.

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Retrieval of three-dimensional wind fields from Doppler radar data using an efficient two-step approach

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-3-4459-2010 ◽

2010 ◽

Vol 3 (5) ◽

pp. 4459-4495 ◽

Cited By ~ 1

Author(s):

C. López Carrillo ◽

D. J. Raymond

Keyword(s):

Variational Approach ◽

Continuity Equation ◽

Doppler Radar ◽

Three Dimensional ◽

Relevant Information ◽

Radar Data ◽

Wind Fields ◽

Wind Retrieval ◽

Complex Sampling ◽

Doppler Radar Data

Abstract. In this work, we describe an efficient approach for wind retrieval from dual Doppler radar data. The approach produces a gridded field that not only satisfies the observations, but also satisfies the anelastic mass continuity equation. The method is based on the so-called three-dimensional variational approach to the retrieval of wind fields from radar data. The novelty consists in separating the task into steps that reduce the amount of data processed by the global minimization algorithm, while keeping the most relevant information from the radar observations. The method is flexible enough to incorporate observations from several radars, accommodate complex sampling geometries, and readily include dropsonde or sounding observations in the analysis. We demonstrate the usefulness of our method by analyzing a real case with data collected during the TPARC/TCS-08 field campaign.

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Water-Surface Wind Retrieval Using Airborne Radar Altimeter

Foundations for Innovative Application of Airborne Radars - SpringerBriefs in Earth Sciences ◽

10.1007/978-3-319-00621-5_6 ◽

2013 ◽

pp. 65-85

Author(s):

Alexey Nekrasov

Keyword(s):

Water Surface ◽

Surface Wind ◽

Airborne Radar ◽

Radar Altimeter ◽

Wind Retrieval

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Vertical Vortex Development in Hurricane Michael (2018) during Rapid Intensification

Monthly Weather Review ◽

10.1175/mwr-d-21-0098.1 ◽

2021 ◽

Author(s):

Alexander J. DesRosiers ◽

Michael M. Bell ◽

Ting-Yu Cha

Keyword(s):

Inner Core ◽

Doppler Radar ◽

Three Dimensional ◽

Vertical Gradient ◽

Machine Learning Techniques ◽

Rapid Intensification ◽

Wind Retrieval ◽

Retrieval Technique ◽

Budget Analysis ◽

Tangential Wind

AbstractThe landfall of Hurricane Michael (2018) at category 5 intensity occurred after rapid intensification (RI) spanning much of the storm’s lifetime. Four Hurricane Hunter aircraft missions observed the RI period with tail Doppler radar (TDR). Data from each of the 14 aircraft passes through the storm were quality controlled via a combination of interactive and machine learning techniques. TDR data from each pass were synthesized using the SAMURAI variational wind retrieval technique to yield three-dimensional kinematic fields of the storm to examine inner core processes during RI. Vorticity and angular momentum increased and concentrated in the eyewall region. A vorticity budget analysis indicates the tendencies became more axisymmetric over time. In this study we focus in particular on how the eyewall vorticity tower builds vertically into the upper levels. Horizontal vorticity associated with the vertical gradient of tangential wind was tilted into the vertical by the eyewall updraft to yield a positive vertical vorticity tendency inward atop the existing vorticity tower, that is further developed locally upward and outward along the sloped eyewall through advection and stretching. Observed maintenance of thermal wind balance from a thermodynamic retrieval shows evidence of a strengthening warm core, which aided in lowering surface pressure and further contributed to the efficient intensification in the latter stages of this RI event.

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