Optimization of wind field retrieval procedures

IEEE Geoscience and Remote Sensing Letters, 2008

A new efficient algorithm for retrieving wind-vector solutions from scatterometers is developed based on a criterion of minimum normalized standard deviation (NSD) of wind speed derived from backscatter measurements using a geophysical model function (GMF). Its performance has been evaluated through simulations using QSCAT-1 GMF and the QuikSCAT observational geometry. The present algorithm, named the NSD algorithm, is found to be computationally more efficient (two to three times) besides being at par with the maximum-likelihood estimator (MLE) algorithm in terms of retrieval skill, retrieval errors, and distribution of solutions, on the basis of simulations as well as comparison of limited QuikSCAT-data-derived winds with National Centers for Environmental Prediction and European Centre for Medium-Range Weather Forecasts model winds. Simulation results and analysis of sample QuikSCAT data are presented.

IEEE Transactions on Geoscience and Remote Sensing, 2000

This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.

Natural Hazards and Earth System Science, 2006

Although methods of using multiple Doppler radars to study wind fields have long been proposed, and many research studies have been made, very few operational radar operators adopt methods which require the use of specific scanning strategies to allow the extraction of wind information. Here we report a collaborative study on dual-Doppler radars based on two Doppler radars in the Po valley, Italy. Unusually, the radars are only about 90 km apart, though operated by the same authority. The wind field syntheses are carried out on a 30 km by 30 km region where the two radars have overlapping scan coverage. An iterative method based on the linear wind model and the equation of mass continuity is used to construct the wind fields. The methodology has been validated by two different methods. The first method is to reconstruct the radial wind observed by each radar, and the second method is calculating and comparing the along-track component with that derived from the observations. Both two comparisons show good agreement with the original data.

This paper represents a consensus on the state-of-the-art in wind retrieval using synthetic aperture radar (SAR), after the SEASAR 2012 workshop "Advances in SAR Oceanography" hosted by the European Space Agency (ESA) and the Norwegian Space Centre in Tromsø, Norway 18–22 June 2012. We document the recent advances of the methodologies, which are capitalizing on the improved capabilities of the modern generation of SAR sensors providing Doppler grid and multi-polarizations. The many applications of SAR wind retrieval have also benefitted from on the improved availability of wide swath modes (~500 km) with excellent coverage, giving much better overview of regional and mesoscale wind features. The accuracy of offshore wind retrieval is robust and generally in the order of 1.5 m/s in speed and 20° in direction, whereas the new methodologies steadily improve the performance for the more challenging conditions near cyclones and complex coastal topography.

2001

A dealiasing technique for radar Doppler velocities based on a variational technique is proposed. The Doppler velocity image is dealiased region-wise by forcing continuity and overall agreement with a mean wind estimate. The latter constraint reduces the propagation of errors in space. The method estimates the quality of the dealiased regions by using the residual between calculated Nyquist numbers and their applied integer values. This dealiasing technique corrects the Doppler velocity images for use in a wind field retrieval under different meteorological situations. The wind field can be retrieved from Doppler radar observations using the technique by Protat and Zawadzki (1999). This technique assimilates a model wind field to the radar observations but uses physical constraints and movement estimators to retrieve the missing (not measured) wind components. This thesis compares two concepts to eliminate spurious vectors when retrieving the wind field from Doppler observations. The first method is based on smoothing the radar data. The second method uses a smoothness constraint as part of the wind field model. Second order spatial derivatives of the wind field product are minimized. Two-and three-dimensional wind fields are retrieved from simulated radar observations, using different noise filtering techniques. The smoothness constraint eliminates spurious vectors more efficiently while reliably retrieving the wind field. Smoothing the radar data unintentionally dampens the characteristic wind variation. Applying the smoothness constraint is indispensable for the retrieval of the vertical wind velocity. It is recommended in general. The proposed methods are implemented to investigate the dynamics of the winter storm Lothar on 26 December 1999. Severe damage happened in northern Switzerland around noon when a narrow cold-frontal rainband (NCFR) passed. The variational dealiasing is successfully applied to the images of the ETH radar. The threedimensional wind field is retrieved using the described noise filtering configuration. Analyzing the dynamics of the NCFR reveals that-atypically for this meteorological system-the strongest winds are at the trailing edge of the rainband and collocated with the core regions of the NCFR. This explains the bands observed in the forest damvii Die variationelle Entfaltungstechnik und der Algorithmus zur Herleitung des Windfelds von Protat and Zawadzki (1999) wurden verwendet, um in einer Testplattform an der ETH das Windfeld vom Schweizer Radarnetzwerk operationell herzuleiten. Die Methode zur Herleitung des Windfelds ist angepasst für die Anwendung in der Schweiz, indem eine neue untere Randbedingung die Topographie berücksichtigt, und indem die Elemente für die Herleitung von einem und mehreren Radar(s) kombiniert sind. Experimente werden mit archivierten sowie Echtzeit-Beobachtungen durchgeführt. x

Recently, there has been an increase in use of Unmanned Aerial Systems (UASs) as platforms for conducting fundamental and applied research in the lower atmosphere due to their relatively low cost and ability to collect samples with high spatial and temporal resolution. Concurrent with this development comes the need for accurate instrumentation and measurement methods suitable for small meteorological UASs. Moreover, the instrumentation to be integrated into such platforms must be small and lightweight. Whereas thermodynamic variables can be easily measured using well aspirated sensors onboard, it is much more challenging to accurately measure the wind with a UAS. Several algorithms have been developed that incorporate GPS observations as a means of estimating the horizontal wind vector, with each algorithm exhibiting its own particular strengths and weaknesses. In the present study, the performance of three such GPS-based wind-retrieval algorithms has been investigated and compared with wind estimates from rawinsonde and sodar observations. Each of the algorithms considered agreed well with the wind measurements from sounding and sodar data. Through the integration of UAS-retrieved profiles of thermodynamic and kinematic parameters, one can investigate the static and dynamic stability of the atmosphere and relate them to the state of the boundary layer across a variety of times and locations, which might be difficult to access using conventional instrumentation.

Recently, there has been an increase in use of Unmanned Aerial Systems (UASs) as platforms for conducting fundamental and applied research in the lower atmosphere due to their relatively low cost and ability to collect samples with high spatial and temporal resolution. Concurrent with this development comes the need for accurate instrumentation and measurement methods suitable for small meteorological UASs. Moreover, the instrumentation to be integrated into such platforms must be small and lightweight. Whereas thermodynamic variables can be easily measured using wellaspirated sensors onboard, it is much more challenging to accurately measure the wind with a UAS. Several algorithms have been developed that incorporate GPS observations as a means of estimating the horizontal wind vector, with each algorithm exhibiting its own particular strengths and weaknesses. In the present study, the performance of three such GPS-based wind-retrieval algorithms has been investigated and compared with wind estimates from rawinsonde and sodar observations. Each of the algorithms considered agreed well with the wind measurements from sounding and sodar data. Through the integration of UAS-retrieved profiles of thermodynamic and kinematic parameters, one can investigate the static and dynamic stability of the atmosphere and relate them to the state of the boundary layer across a variety of times and locations, which might be difficult to access using conventional instrumentation.

Advances in Atmospheric Sciences, 2005

A variational method is developed to retrieve winds in the first step and then thermodynamic fields in the second step from Doppler radar observations. In the first step, wind fields are retrieved at two time levels: the beginning and ending times of the data assimilation period, simultaneously from two successive volume scans by using the weak form constraints provided by the mass continuity and vorticity equations. As the retrieved wind fields are expressed by Legendre polynomial expansions at the beginning and ending times, the time tendency term in the vorticity equation can be conveniently formulated, and the retrieved winds can be compared with the radar observed radial winds in the cost function at the precise time and position of each radar beam. In the second step, the perturbation pressure and temperature fields at the middle time are then derived from the retrieved wind fields and the velocity time tendency by using the weak form constraints provided by the three momentum equations. The merits of the new method are demonstrated by numerical experiments with simulated radar observations and compared with the traditional least squares methods which consider neither the precise observation times and positions nor the velocity time tendency. The new method is also applied to real radar data for a heavy rainfall event during the 2001 Meiyu season in China.

IEEE Transactions on Geoscience and Remote Sensing, 2006

The Naval Research Laboratory WindSat polarimetric radiometer was launched on January 6, 2003 and is the first fully polarimetric radiometer to be flown in space. WindSat has three fully polarimetric channels at 10.7, 18.7, and 37.0 GHz and vertically and horizontally polarized channels at 6.8 and 23.8 GHz. A first-generation wind vector retrieval algorithm for the WindSat polarimetric radiometer is developed in this study. An atmospheric clearing algorithm is used to estimate the surface emissivity from the measured WindSat brightness temperature at each channel. A specular correction factor is introduced in the radiative transfer equation to account for excess reflected atmospheric brightness, compared to the specular assumption, as a function wind speed. An empirical geophysical model function relating the surface emissivity to the wind vector is derived using coincident QuikSCAT scatterometer wind vector measurements. The confidence in the derived harmonics for the polarimetric channels is high and should be considered suitable to validate analytical surface scattering models for polarized ocean surface emission. The performance of the retrieval algorithm is assessed with comparisons to Global Data Assimilation System (GDAS) wind vector outputs. The root mean square (RMS) uncertainty of the closest wind direction ambiguity is less than 20 for wind speeds greater than 6 m/s and less than 15 at 10 m/s and greater. The retrieval skill, the percentage of retrievals in which the first-rank solution is the closest to the GDAS reference, is 75% at 7 m/s and 85% or higher above 10 m/s. The wind speed is retrieved with an RMS uncertainty of 1.5 m/s.

Journal of Geophysical Research, 2010

A method for improving scatterometer wind retrievals based on the mesoscale and synoptic-scale structure of the flow field is presented and evaluated. The large-scale structure of the flow is inferred from the sea-level pressure (SLP) field derived from the scatterometer winds using a planetary boundary layer model. The wind vectors derived from this SLP field can be used to either (1) inform the ambiguity selection, (2) correct the direction of the scatterometer wind vectors, in all cases or above a certain threshold, or (3) replace the scatterometer winds. The methodology is demonstrated with QuikSCAT (QS) scatterometer wind vectors. The new wind vector set is evaluated statistically by comparison with buoy measurements, with numerical weather prediction model analyses, and by spectral analysis. It is found that the new wind vectors are particularly valuable at nadir and in rain-contaminated areas, and that their spectral behavior is closer to a power law than are the uncorrected QS winds.