NOC GNSS-R Global Ocean Wind Speed and Sea-Ice Products Using Data from the TechDemoSat-1 Mission

2020 ◽  
Author(s):  
Giuseppe Foti ◽  
Matthew Lee Hammond ◽  
Christine Gommenginger ◽  
Meric Srokosz ◽  
Martin Unwin ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Global Ocean ◽  
Using Data ◽  
Ocean Wind

NOC GNSS-R Global Ocean Wind Speed and Sea-Ice Products

2020 ◽  
Author(s):  
Matthew Hammond ◽  
Giuseppe Foti ◽  
Christine Gommenginger ◽  
Meric Srokosz ◽  
Martin Unwin ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Global Ocean ◽  
Retrieval Algorithm ◽  
Navigation Satellite ◽  
Validation Data ◽  
Global Navigation ◽  
Ice Detection ◽  
Global Navigation Satellite ◽  
Ocean Wind

<p>Global Navigation Satellite System-Reflectometry (GNSS-R) is an innovative and rapidly developing approach to Earth Observation that makes use of signals of opportunity from Global Navigation Satellite Systems, which have been reflected off the Earth’s surface. Using GNSS-R data collected by the UK TechDemoSat-1 (TDS-1) between 2014 and 2018, the National Oceanography Centre (NOC) has developed a GNSS-R wind speed retrieval algorithm called the Calibrated Bistatic Radar Equation (C-BRE), which now features updated data quality control mechanisms including flagging of radio frequency interference (RFI) and sea-ice detection based on the GNSS-R waveform. Here we present an assessment of the performance of the latest NOC GNSS-R ocean wind speed and sea-ice products (NOC C-BRE v1.0) using validation data from the ECMWF ERA-5 re-analysis model output. Results show the capability of spaceborne GNSS-R sensors for accurate wind speed retrieval and sea-ice detection. Additionally, ground-processed Galileo returns collected by TDS-1 are examined and the geophysical sensitivity of reflected Galileo data to surface parameters is investigated. Preliminary results demonstrate the feasibility of spaceborne GNSS-R instruments receiving a combination of GNSS signals transmitted by multiple navigation systems, which offers the opportunity for frequent, high-quality ocean wind and sea-ice retrievals at low relative cost. Other advancements in GNSS-R technology are represented by future mission concepts such as HydroGNSS, a proposed ESA Scout mission opportunity by SSTL offering support for enhanced retrieval capabilities exploiting dual polarisation, dual frequency, and coherent reflected signal reception.</p>

GNSS reflectometry global ocean wind speed using deep learning: Development and assessment of CyGNSSnet

2022 ◽  
Vol 269 ◽  
pp. 112801
Author(s):  
Milad Asgarimehr ◽  
Caroline Arnold ◽  
Tobias Weigel ◽  
Chris Ruf ◽  
Jens Wickert
Keyword(s):  
Deep Learning ◽  
Wind Speed ◽  
Global Ocean ◽  
Gnss Reflectometry ◽  
Learning Development ◽  
Ocean Wind

Calibration and Cross Validation of Global Ocean Wind Speed Based on Scatterometer Observations

2020 ◽  
Vol 37 (2) ◽  
pp. 279-297 ◽  
Author(s):  
Agustinus Ribal ◽  
Ian R. Young
Keyword(s):  
Wind Speed ◽  
Cross Validation ◽  
Regression Line ◽  
Total Duration ◽  
Global Ocean ◽  
High Wind ◽  
Wind Speeds ◽  
Buoy Data ◽  
Ocean Wind

AbstractGlobal ocean wind speed observed from seven different scatterometers, namely, ERS-1, ERS-2, QuikSCAT, MetOp-A, OceanSat-2, MetOp-B, and Rapid Scatterometer (RapidScat) were calibrated against National Data Buoy Center (NDBC) data to form a consistent long-term database of wind speed and direction. Each scatterometer was calibrated independently against NDBC buoy data and then cross validation between scatterometers was performed. The total duration of all scatterometer data is approximately 27 years, from 1992 until 2018. For calibration purposes, only buoys that are greater than 50 km offshore were used. Moreover, only scatterometer data within 50 km of the buoy and for which the overpass occurred within 30 min of the buoy recording data were considered as a “matchup.” To carry out the calibration, reduced major axis (RMA) regression has been applied where the regression minimizes the size of the triangle formed by the vertical and horizontal offsets of the data point from the regression line and the line itself. Differences between scatterometer and buoy data as a function of time were investigated for long-term stability. In addition, cross validation between scatterometers and independent altimeters was also performed for consistency. The performance of the scatterometers at high wind speeds was examined against buoy and platform measurements using quantile–quantile (Q–Q) plots. Where necessary, corrections were applied to ensure scatterometer data agreed with the in situ wind speed for high wind speeds. The resulting combined dataset is believed to be unique, representing the first long-duration multimission scatterometer dataset consistently calibrated, validated and quality controlled.

THE INFLUENCE OF THE WIND SPEED PREDICTION ERROR ON THE SIZE OF THE STORAGE CONTROLLED OPERATION ZONE IN THE SYSTEM WITH THE WIND GENERATOR

2020 ◽  
Vol 2020 (57) ◽  
pp. 35-41
Author(s):  
K.S. Klen ◽  
◽  
M.K. Yaremenko ◽  
V.Ya. Zhuykov ◽  
◽  
...  
Keyword(s):  
Wind Speed ◽  
Prediction Error ◽  
Average Energy ◽  
Interpolation Formula ◽  
Wind Speed Prediction ◽  
Wind Generator ◽  
Prediction Horizon ◽  
Speed Prediction ◽  
Using Data ◽  
Predictor Corrector

The article analyzes the influence of wind speed prediction error on the size of the controlled operation zone of the storage. The equation for calculating the power at the output of the wind generator according to the known values of wind speed is given. It is shown that when the wind speed prediction error reaches a value of 20%, the controlled operation zone of the storage disappears. The necessity of comparing prediction methods with different data discreteness to ensure the minimum possible prediction error and determining the influence of data discreteness on the error is substantiated. The equations of the "predictor-corrector" scheme for the Adams, Heming, and Milne methods are given. Newton's second interpolation formula for interpolation/extrapolation is given at the end of the data table. The average relative error of MARE was used to assess the accuracy of the prediction. It is shown that the prediction error is smaller when using data with less discreteness. It is shown that when using the Adams method with a prediction horizon of up to 30 min, within ± 34% of the average energy value, the drive can be controlled or discharged in a controlled manner. References 13, figures 2, tables 3.

On the impact of sea ice in a global ocean circulation model

1997 ◽  
Vol 25 ◽  
pp. 111-115 ◽  
Author(s):  
Achim Stössel
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Ocean Circulation ◽  
General Circulation ◽  
Thermohaline Circulation ◽  
Circulation Model ◽  
Deep Ocean ◽  
Global Ocean ◽  
Convective Activity ◽  
The Impact

This paper investigates the long-term impact of sea ice on global climate using a global sea-ice–ocean general circulation model (OGCM). The sea-ice component involves state-of-the-art dynamics; the ocean component consists of a 3.5° × 3.5° × 11 layer primitive-equation model. Depending on the physical description of sea ice, significant changes are detected in the convective activity, in the hydrographic properties and in the thermohaline circulation of the ocean model. Most of these changes originate in the Southern Ocean, emphasizing the crucial role of sea ice in this marginally stably stratified region of the world's oceans. Specifically, if the effect of brine release is neglected, the deep layers of the Southern Ocean warm up considerably; this is associated with a weakening of the Southern Hemisphere overturning cell. The removal of the commonly used “salinity enhancement” leads to a similar effect. The deep-ocean salinity is almost unaffected in both experiments. Introducing explicit new-ice thickness growth in partially ice-covered gridcells leads to a substantial increase in convective activity, especially in the Southern Ocean, with a concomitant significant cooling and salinification of the deep ocean. Possible mechanisms for the resulting interactions between sea-ice processes and deep-ocean characteristics are suggested.

scholarly journals Using Eulerian and Lagrangian Approaches to Investigate Wind-Driven Changes in the Southern Ocean Abyssal Circulation

2013 ◽  
Vol 44 (2) ◽  
pp. 662-675 ◽  
Author(s):  
Paul Spence ◽  
Erik van Sebille ◽  
Oleg A. Saenko ◽  
Matthew H. England
Keyword(s):  
Southern Ocean ◽  
Wind Stress ◽  
Climate Model ◽  
Meridional Overturning Circulation ◽  
Global Ocean ◽  
Lagrangian Particle ◽  
Stress Changes ◽  
Abyssal Circulation ◽  
Flow Pathways ◽  
Ocean Wind

Abstract This study uses a global ocean eddy-permitting climate model to explore the export of abyssal water from the Southern Ocean and its sensitivity to projected twenty-first-century poleward-intensifying Southern Ocean wind stress. The abyssal flow pathways and transport are investigated using a combination of Lagrangian and Eulerian techniques. In an Eulerian format, the equator- and poleward flows within similar abyssal density classes are increased by the wind stress changes, making it difficult to explicitly diagnose changes in the abyssal export in a meridional overturning circulation framework. Lagrangian particle analyses are used to identify the major export pathways of Southern Ocean abyssal waters and reveal an increase in the number of particles exported to the subtropics from source regions around Antarctica in response to the wind forcing. Both the Lagrangian particle and Eulerian analyses identify transients as playing a key role in the abyssal export of water from the Southern Ocean. Wind-driven modifications to the potential energy component of the vorticity balance in the abyss are also found to impact the Southern Ocean barotropic circulation.

Oceanic eddy signature on SAR-derived sea ice drift and vorticity

2021 ◽  
Author(s):  
Angelina Cassianides ◽  
Camillie Lique ◽  
Anton Korosov
Keyword(s):  
Sea Ice ◽  
Surface Current ◽  
Satellite Observation ◽  
The Arctic ◽  
Global Ocean ◽  
Sar Images ◽  
Surface Ocean ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Oceanic Eddy

<p>In the global ocean, mesoscale eddies are routinely observed from satellite observation. In the Arctic Ocean, however, their observation is impeded by the presence of sea ice, although there is a growing recognition that eddy may be important for the evolution of the sea ice cover. In this talk, we will present a new method of surface ocean eddy detection based on their signature in sea ice vorticity retrieved from Synthetic Aperture Radar (SAR) images. A combination of Feature Tracking and Pattern Matching algorithm is used to compute the sea ice drift from pairs of SAR images. We will mostly focus on the case of one eddy in October 2017 in the marginal ice zone of the Canadian Basin, which was sampled by mooring observations, allowing a detailed description of its characteristics. Although the eddy could not be identified by visual inspection of the SAR images, its signature is revealed as a dipole anomaly in sea ice vorticity, which suggests that the eddy is a dipole composed of a cyclone and an anticyclone, with a horizontal scale of 80-100 km and persisted over a week. We will also discuss the relative contributions of the wind and the surface current to the sea ice vorticity. We anticipate that the robustness of our method will allow us to detect more eddies as more SAR observations become available in the future.</p>

scholarly journals Modeling the effect of Ross Ice Shelf melting on the Southern Ocean in quasi-equilibrium

2018 ◽  
Vol 12 (9) ◽  
pp. 3033-3044 ◽  
Author(s):  
Xiying Liu
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Ross Sea ◽  
Global Ocean ◽  
Freshwater Flux ◽  
Quasi Equilibrium ◽  
Ice Shelf ◽  
Sea Ice Concentration ◽  
Ross Ice Shelf ◽  
Ice Concentration

Abstract. To study the influence of basal melting of the Ross Ice Shelf (BMRIS) on the Southern Ocean (ocean southward of 35∘ S) in quasi-equilibrium, numerical experiments with and without the BMRIS effect were performed using a global ocean–sea ice–ice shelf coupled model. In both experiments, the model started from a state of quasi-equilibrium ocean and was integrated for 500 years forced by CORE (Coordinated Ocean-ice Reference Experiment) normal-year atmospheric fields. The simulation results of the last 100 years were analyzed. The melt rate averaged over the entire Ross Ice Shelf is 0.25 m a−1, which is associated with a freshwater flux of 3.15 mSv (1 mSv = 103 m3 s−1). The extra freshwater flux decreases the salinity in the region from 1500 m depth to the sea floor in the southern Pacific and Indian oceans, with a maximum difference of nearly 0.005 PSU in the Pacific Ocean. Conversely, the effect of concurrent heat flux is mainly confined to the middle depth layer (approximately 1500 to 3000 m). The decreased density due to the BMRIS effect, together with the influence of ocean topography, creates local differences in circulation in the Ross Sea and nearby waters. Through advection by the Antarctic Circumpolar Current, the flux difference from BMRIS gives rise to an increase of sea ice thickness and sea ice concentration in the Ross Sea adjacent to the coast and ocean water to the east. Warm advection and accumulation of warm water associated with differences in local circulation decrease sea ice concentration on the margins of sea ice cover adjacent to open water in the Ross Sea in September. The decreased water density weakens the subpolar cell as well as the lower cell in the global residual meridional overturning circulation (MOC). Moreover, we observe accompanying reduced southward meridional heat transport at most latitudes of the Southern Ocean.

Sign in / Sign up

Export Citation Format

Share Document