Shuyan Lang

The Feasibility of Ocean Surface Current Measurement Using Pencil-Beam Rotating Scatterometer

Ocean current is highly related to the interaction between ocean and atmosphere. By measuring the speed and direction of the ocean current from space, we can investigate the ocean- atmosphere interaction on a global scale. The ocean-atmosphere interaction helps to maintain the balance that is essential for planet habitability. However, the conventional scatterometer is unable to measure the ocean current vector. To achieve this, a potentially feasible approach is to use a bigger antenna, a higher PRF, and measure the interferometric phase of two successive echoes. This paper derives four decorrelation factors, and provides the phase error model first. Then, an end-to-end simulation model is established, and it is used to analyze the feasibility of ocean surface current measurement from space. Based on the simulation model, the system parameters are optimized. The simulation results show that the current speed standard deviation (Std), which means the measurement accuracy, in along-track and cross-track direction is smaller than 0.1 m/s when the wind speed is larger than 4 m/s. The swath can be used for current vector inversion that is greater than 70% when the wind speed is larger than 7 m/s. Meanwhile, Kpc of the modified scatterometer is computed and the results show that Kpc is better than the traditional pencil-beam rotating scatterometer when the wind speed is larger than 6 m/s.

Airborne experiments validating the spaceborne RFSCAT on CFOSAT

Airborne experiments were carried out to validate the spaceborne scatterometer. Airborne scatterometer use all the instruments of the spaceborne scatterometer to validate the system design and reliability, except the power amplifier and the antenna. The software of the scatterometer is redesigned due to the observation geometry of airborne platform. The wind retrieval results are compared with the HY-2A scatterometer and the real time wind vector measured on the ship at the center of testing region.

Ocean Surface Current Inversion Method for a Doppler Scatterometer

The ocean surface current is a very important parameter of ocean dynamic environment. It is connected to global climate change, marine environment forecasting, marine navigation, engineering security, and so on. The observation and prediction of ocean surface current have attracted more and more concern. Doppler Scatterometer (DopScat) is a new type of radar for ocean surface wind and current field remote sensing. The ocean surface current inversion method of DopScat impacts the measurement accuracy directly. In this paper, we establish the simulation model of a DopScat and provide the radial velocity error model. The numerical ocean surface Doppler spectrum model is also introduced and validated with the empirical geophysical model function in C-band (CDOP). The suitable ocean wave elevation spectrum and directional distribution function are selected. What is more, this paper establishes the maximum likelihood estimation (MLE) method to retrieve the ocean surface current and wind simultaneously. The retrieval accuracy for different positions in cross track, different wind speeds, and different current speeds are analyzed. At last, the global ocean current field is observed by DopScat and the ocean current is retrieved. In our simulation, the orbit parameters and observation geometry of DopScat are the same as that of HY-2A scatterometer. The retrieval results show that global current speed standard deviation can be smaller than 0.18 m/s for five days and

The ocean surface current inversion mehtod of Doppler scatterometer

0.5 {^{\circ }} \times 0.5 {^{\circ }}

Wind speed retrieving for combined observations of scatterometer and radiometer onboard HY-2A for typhoons using neural network

grid average.

On the improvement of the HY-2A scatterometer wind quality control

Ocean surface current is a very important parameter of ocean dynamic environment. The observation and prediction of ocean surface current has attracted more and more concern. Doppler Scatterometer (DopScat) is a new type of radar for ocean surface wind and current field remote sensing. The ocean surface current inversion method of DopScat impacts the measurement accuracy directly. In this paper, we establishes the Maximum Likelihood Estimation(MLE) method to retrieve the ocean surface current and wind simultaneously. The retrieval accuracy for different position in cross-track, wind speed, and current speed are analyzed. The retrieval results show that the RMS of inversion current speed and direction can be smaller than 0.18m/s and 25°respectively, for medium wind speed condition. This is submitted for the special session of “New Developments of Chinese Oceanographic and Meteorological Satellites”.

Wind field retrieving under rainy condition from combined observations of scatterometer and radiometer onboard HY-2A

In typhoon conditions, air-sea interactions are fierce, the wind speeds are quite high and usually tangled with complex rains. Under such circumstances, the combined observations of scatterometer and radiometer would be able to provide good information although traditional wind filed retrieving methods for them, i.e. MLE based on GMF (Geographical Modelling Function) for scatterometer and RTM(Radiative Transfer Method) which are originated from low or median wind conditions will not be applicable. In this paper, a neural network was employed to combine the observations of the two sensors onboard HY-2A satellite: radiometer (HRAD) and scatterometer (HSCAT) to achieve wind speed retrieving under typhoon conditions. The network was trained by GRAPS (global/regional assimilation and prediction system) data used as true values of wind speeds in typhoons. The established network was verified by data excluded from training data set. Results show that the wind speeds obtained from the network are better than the products of HY-2A compared to GRAPS data. The research of this paper has provided a clue of retrieving typhoon wind speeds for HY-2A products and for the data processing of coming HY satellite series, though further work on wind direction obtain, data comparison between different kinds of assimilation and perdition systems and the test of this method on other scatterometer and radiometer data are to be done in the near future.

Data and processing of RFSCAT onboard CFOSAT

This paper reviews several wind quality-sensitive parameters derived from HY-2A scatterometer data, such as the wind-inversion residual (or Maximum Likelihood Estimator, MLE) and its spatially averaged value, and the singularity exponent (SE) derived from an image processing technique, called singularity analysis. Their sensitivity to data quality is evaluated using the collocated European Centre for Medium-range Weather Forecasting (ECMWF) model output and satellite radiometer rain data. It shows that SE is the best quality indicator, followed by the spatially averaged MLE and the conventional MLE. A set of MLE and SE thresholds are derived from the sensitivity analysis in order to optimize the quality control (QC) for the HY-2A scatterometer.

Sea surface wind speed inversion using low incident NRCS

The wind fields retrieved by scatterometers from GMF (Geographical Modelling Function) would be invalidated under rainy conditions, due to scattering and attenuation effects of rain drops. The scatterometer (HSCAT) and the scanning microwave radiometer (RM) onboard HY-2A can give observations over sea surface at the same time. In this paper, firstly, data of HSCAT and RM onboard HY-2A observing rainy ocean surface were selected as experiment data, with corresponding buoy wind fields. Secondly, an artificial neural network was established for wind fields retrieval under rain conditions, which was tested by other data sets.

A study on wind vector retrieval algorithm for rotating fan-beam scatterometer

The Rotating fan-beam scatterometer (RFSCAT) onboard the Chinese-French Oceanography Satellite (CFOSAT) is a novel kind of scatterometer whose performance had been preliminarily verified by airborne campaign. In this paper the whole data processing chain that can achieve wind field derivation from original data set transmitted from the scatterometer had been proposed with definition of corresponding data levels that would be applied for RFSCAT in the CFOSAT mission. The pre-processing part in the processing chain was validated for it was derived from the same system verified by the airborne campaign. While for the post-processing prime algorithms, validity was concluded from processing some of the data gained in that experiment as well. Further researches needed had been explored as well.