Buoy perspective of a high-resolution global ocean vector wind analysis constructed from passive radiometers and active scatterometers (1987–present)

Author Posting. © American Geophysical Union, 2012. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 117 (2012): C11013, doi:10.1029/2012JC008069.The study used 126 buoy time series as a benchmark to evaluate a satellite-based daily, 0.25-degree gridded global ocean surface vector wind analysis developed by the Objectively Analyzed airs-sea Fluxes (OAFlux) project. The OAFlux winds were produced from synthesizing wind speed and direction retrievals from 12 sensors acquired during the satellite era from July 1987 onward. The 12 sensors included scatterometers (QuikSCAT and ASCAT), passive microwave radiometers (AMSRE, SSMI and SSMIS series), and the passive polarimetric microwave radiometer from WindSat. Accuracy and consistency of the OAFlux time series are the key issues examined here. A total of 168,836 daily buoy measurements were assembled from 126 buoys, including both active and archive sites deployed during 1988–2010. With 106 buoys from the tropical array network, the buoy winds are a good reference for wind speeds in low and mid-range. The buoy comparison shows that OAFlux wind speed has a mean difference of −0.13 ms−1 and an RMS difference of 0.71 ms−1, and wind direction has a mean difference of −0.55 degree and an RMS difference of 17 degrees. Vector correlation of OAFlux and buoy winds is of 0.9 and higher over almost all the sites. Influence of surface currents on the OAFlux/buoy mean difference pattern is displayed in the tropical Pacific, with higher (lower) OAFlux wind speed in regions where wind and current have the opposite (same) sign. Improved representation of daily wind variability by the OAFlux synthesis is suggested, and a decadal signal in global wind speed is evident.The authors are grateful for the support of the NASA Ocean Vector Wind Science Team (OVWST) under grant NNA10AO86G during the five-year development of the OAFlux wind synthesis products. Support from the NOAA Office of Climate Observation (OCO) under grant NA09OAR4320129 in establishing and maintaining the buoy validation database for surface fluxes is gratefully acknowledged.2013-05-1

Insights on the OAFlux ocean surface vector wind analysis merged from scatterometers and passive microwave radiometers (1987 onward)

Author Posting. © American Geophysical Union, 2014. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 119 (2014): 5244–5269, doi:10.1002/2013JC009648.A high-resolution global daily analysis of ocean surface vector winds (1987 onward) was developed by the Objectively Analyzed air-sea Fluxes (OAFlux) project. This study addressed the issues related to the development of the time series through objective synthesis of 12 satellite sensors (two scatterometers and 10 passive microwave radiometers) using a least-variance linear statistical estimation. The issues include the rationale that supports the multisensor synthesis, the methodology and strategy that were developed, the challenges that were encountered, and the comparison of the synthesized daily mean fields with reference to scatterometers and atmospheric reanalyses. The synthesis was established on the bases that the low and moderate winds (<15 m s−1) constitute 98% of global daily wind fields, and they are the range of winds that are retrieved with best quality and consistency by both scatterometers and radiometers. Yet, challenges are presented in situations of synoptic weather systems due mainly to three factors: (i) the lack of radiometer retrievals in rain conditions, (ii) the inability to fill in the data voids caused by eliminating rain-flagged QuikSCAT wind vector cells, and (iii) the persistent differences between QuikSCAT and ASCAT high winds. The study showed that the daily mean surface winds can be confidently constructed from merging scatterometers with radiometers over the global oceans, except for the regions influenced by synoptic weather storms. The uncertainties in present scatterometer and radiometer observations under high winds and rain conditions lead to uncertainties in the synthesized synoptic structures.The project is sponsored by the NASA Ocean Vector Wind Science Team (OVWST) activities under grant NNA10AO86G.2015-02-1

Azimuthal Dependence of GNSS‐R Scattering Cross‐Section in Hurricanes

Global Navigation Satellite System‐Reflectometry (GNSS‐R) measurements of the ocean surface are sensitive to roughness scales ranging from a few cms to several kms. Inside a hurricane the surface roughness changes drastically due to varying sea age and fetch length conditions and complex wave‐wave interactions caused by its cyclonic rotation and translational motion. As a result, the relationship between the surface roughness at different scale sizes becomes azimuthally dependent, as does the relationship between scattering cross‐section and wind speed as represented by a Geophysical Model Function (GMF). In this work, the impact of this azimuthal variation on the scattering cross‐section is assessed. An empirical GMF is constructed using measurements by the NASA CYclone GNSS (CYGNSS) matched to HWRF reanalysis surface winds for 19 hurricanes in 2017 and 2018. The analysis reveals a 2–8% variation in scattering cross‐section due to azimuthal location, and the magnitude of the azimuthal dependence is found to grow with wind speed.Plain Language SummaryGlobal Navigation Satellite System‐Reflectometry (GNSS‐R) is a technique of studying reflected GPS signals to extract useful information about the surface. CYGNSS is the first of its kind GNSS‐R constellation mission selected by NASAs earth venture program. The goal of the mission is to understand inner core processes in hurricanes by making accurate surface wind speed measurements there. Wind speed at the surface is determined using a GMF that maps the reflection measurement to a wind speed. Due to the complex nature of sea state and wave interactions inside a hurricane, measured scattering cross‐section depends on the azimuthal location of the measurement inside the hurricane system. A modified GMF is proposed here that accounts for the azimuthal dependence. The model is developed by matching up CYGNSS measurements to hurricane winds estimated by the NOAA HWRF model for 19 hurricanes during 2017 and 2018. The new GMF accounts for a 2–8% variation in the measurements due to azimuthal location which increases with wind speed.Key PointsAzimuthal variations of GNSS‐R scattering cross‐section in hurricanes are modeled with sinusoidal harmonicsThe azimuthal harmonics explain 2–8% of the overall variation in scattering cross‐sectionThe magnitude of the azimuthal harmonics increases with increasing wind speedPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156153/2/jgrc24060.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156153/1/jgrc24060_am.pd

A Roughness Correction for Aquarius Ocean Brightness Temperature Using the CONAE MicroWave Radiometer

Aquarius/SAC-D is a joint NASA/CONAE (Argentine Space Agency) Earth Sciences satellite mission to measure global sea surface salinity (SSS), using an L-band radiometer that measures ocean brightness temperature (Tb). The application of L-band radiometry to retrieve SSS is a difficult task, and therefore, precise Tb corrections are necessary to obtain accurate measurements. One of the major error sources is the effect of ocean roughness that warms the ocean Tb. The Aquarius (AQ) instrument (L-band radiometer/scatterometer) baseline approach uses the radar scatterometer to provide this ocean roughness correction, through the correlation of radar backscatter with the excess ocean emissivity. In contrast, this dissertation develops an ocean roughness correction for AQ measurements using the MicroWave Radiometer (MWR) instrument Tb measurements at Ka-band to remove the errors that are caused by ocean wind speed and direction. The new ocean emissivity radiative transfer model was tuned using one year (2012) of on-orbit combined data from the MWR and the AQ instruments that are collocated in space and time. The roughness correction in this paper is a theoretical Radiative Transfer Model (RTM) driven by numerical weather forecast model surface winds, combined with ancillary satellite data from WindSat and SSMIS, and environmental parameters from NCEP. This RTM provides an alternative approach for estimating the scatterometer-derived roughness correction, which is independent. The theoretical basis of the algorithm is described and results are compared with the AQ baseline scatterometer method. Also results are presented for a comparison of AQ SSS retrievals using both roughness corrections

Theoretical modeling of dual-frequency scatterometer response: improving ocean wind and rainfall effects

Ocean surface wind is a key parameter of the Earth’s climate system. Occurring at the interface between the ocean and the atmosphere, ocean winds modulate fluxes of heat, moisture and gas exchanges. They reflect the lower branch of the atmospheric circulation and represent a major driver of the ocean circulation. Studying the long-term trends and variability of the ocean surface winds is of key importance in our effort to understand the Earth’s climate system and the causes of its changes. More than three decades of surface wind data are available from spaceborne scatterometer/radiometer missions and there is an ongoing effort to inter-calibrate all these measurements with the aim of building a complete and continuous picture of the ocean wind variability. Currently, spaceborne scatterometer wind retrievals are obtained by inversion algorithms of empirical Geophysical Model Functions (GMFs), which represent the relationship between ocean surface backscattering coefficient and the wind parameters. However, by being measurement-dependent, the GMFs are sensor-specific and, in addition, they may be not properly defined in all weather conditions. This may reduce the accuracy of the wind retrievals in presence of rain and it may also lead to inconsistencies amongst winds retrieved by different sensors. Theoretical models of ocean backscatter have the big potential of providing a more general and understandable relation between the measured microwave backscatter and the surface wind field than empirical models. Therefore, the goal of our research is to understand and address the limitations of the theoretical modeling, in order to propose a new strategy towards the definition of a unified theoretical model able to account for the effects of both wind and rain. In this work, it is described our approach to improve the theoretical modeling of the ocean response, starting from the Ku-band (13.4 GHz) frequency and then broadening the analysis at C-band (5.3 GHz) frequency. This research has revealed the need for new understanding of the frequency-dependent modeling of the surface backscatter in response to the wind-forced surface wave spectrum. Moreover, our ocean wave spectrum modification introduced to include the influences of the surface rain, allows the interpretation/investigation of the scatterometer observations in terms not only of the surface winds but also of the surface rain, defining an additional step needed to improve the wind retrievals algorithms as well as the possibility to jointly estimate wind and rain from scatterometer observations

Physical response of the coastal ocean to Hurricane Isabel near landfall

International audienceHurricane Isabel made landfall near Drum Inlet, North Carolina on 18 September 2003. In nearby Onslow Bay an array of 5 moorings captured the response of the coastal ocean to the passage of the storm by measuring currents, surface waves, bottom pressure, temperature and salinity. Temperatures across the continental shelf decreased by 1?3°C, consistent with a surface heat flux estimate of 750 W/m2. Salinity decreased at most mooring locations. A calculation at one of the moorings estimates rainfall of 11 cm and a net addition of fresh water at the surface of 8 cm. The low-pass current field shows a shelf-wide movement of water, first to the southwest, with an abrupt reversal to the northeast along the shelf after landfall. Close analysis of this reversal shows it to be a disturbance propagating offshore at a speed somewhat less than the local shallow water wave speed. The high-pass current field at one of the moorings shows a significant increase in kinetic energy at periods between 10 min and 2 h during the approach of the storm. This high-pass flow is isotropic and has a short (<5 m) vertical decorrelation scale. It appears to be closely associated with the winds, Finally we examined the surface wave field at one of the moorings. It shows the swell energy peaking well before the winds waves. At the height of the storm, as the winds rotated rapidly in the cyclonic sense, the wind wave direction rotated as well, with a lag of 45?90°

An Ocean Surface Wind Vector Model Function For A Spaceborne Microwave Radiometer And Its Application

Ocean surface wind vectors over the ocean present vital information for scientists and forecasters in their attempt to understand the Earth\u27s global weather and climate. As the demand for global wind velocity information has increased, the number of satellite missions that carry wind-measuring sensors has also increased; however, there are still not sufficient numbers of instruments in orbit today to fulfill the need for operational meteorological and scientific wind vector data. Over the last three decades operational measurements of global ocean wind speeds have been obtained from passive microwave radiometers. Also, vector ocean surface wind data were primarily obtained from several scatterometry missions that have flown since the early 1990\u27s. However, other than SeaSat-A in 1978, there has not been combined active and passive wind measurements on the same satellite until the launch of the second Advanced Earth Observing Satellite (ADEOS-II) in 2002. This mission has provided a unique data set of coincident measurements between the SeaWinds scatterometer and the Advanced Microwave Scanning Radiometer (AMSR). AMSR observes the vertical and horizontal brightness temperature (TB) at six frequency bands between 6.9 GHz and 89.0 GHz. Although these measurements contain some wind direction information, the overlying atmospheric influence can easily obscure this signal and make wind direction retrieval from passive microwave measurements very difficult. However, at radiometer frequencies between 10 and 37 GHz, a certain linear combination of vertical and horizontal brightness temperatures causes the atmospheric dependence to be nearly cancelled and surface parameters such as wind speed, wind direction and sea surface temperature to dominate the resulting signal. This brightness temperature combination may be expressed as ATBV-TBH, where A is a constant to be determined and the TBV and TBH are the brightness temperatures for the vertical and horizontal polarization respectively. In this dissertation, an empirical relationship between the AMSR\u27s ATBV-TBH and SeaWinds\u27 surface wind vector retrievals was established for three microwave frequencies: 10, 18 and 37 GHz. This newly developed model function for a passive microwave radiometer could provide the basis for wind vector retrievals either separately or in combination with scatterometer measurements

Satellite remote sensing of surface winds, waves, and currents: Where are we now?

This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields

Improving Sea-Surface Remote Sensing of Ocean Wind Vectors by Scatterometers

Though scatterometers have been used to sense global ocean surface wind vectors for over 40 years, there remain some significant shortcomings. The largest problems appear in retrieving the wind vector when the ocean is being driven by high wind speeds or when rain is present in the beam-illuminated volume. Geophysical model functions (GMFs) developed using data from high-wind events can improve retrievals at high wind speeds, but only if sufficient ground truth measurements exist in the scatterometer swath. Airborne scatterometers, such as the Imaging Wind and Rain Airborne Profiler (IWRAP) developed by the Microwave Remote Sensing Laboratory (MIRSL) at the University of Massachusetts Amherst (UMass), are well-suited for collecting such high-wind data, largely due to their abilities to reposition to areas of interest, sample the ocean surface on a small scale, and use complementary in-situ sensors. The IWRAP system is also able to investigate the effect of precipitation impact (the “splash effect”) on the sea surface normalized radar cross-section (NRCS), since it can discriminate between volume and surface effects of precipitation. This dissertation will improve upon the existing IWRAP GMF and quantify the effect of precipitation on wind vector retrievals. Additionally, IWRAP is used to observe the effects of Earth-incidence angle and polarization on the sea-surface radar backscatter, helping scatterometer GMFs to be applicable to other satellite sensors. IWRAP and collocated Stepped Frequency Microwave Radiometer (SFMR) data were gathered from 4 years of flight experiments. Using this data, the high-wind IWRAP GMF is extended to incidence angles near 22° at C- and Ku-band VV- and HH-polarization from 15 m s−1 to 45 m s−1. There is also a revision made to the higher harmonics of the GMF near 50° incidence, but the mean NRCS appears to be modeled appropriately. There is no splash effect observed in the mean NRCS or first harmonic at wind speeds from 15 m s−1 to 45 m s−1. The second harmonic shows some muted behavior in precipitation. Lastly, a wind speed dependence is observed in the VV/HH NRCS polarization ratio in both incidence angle and azimuth