Retrieval-Augmented Generation (RAG) enhances the answering capabilities of large language models (LLMs) by leveraging knowledge retrieved from external corpora, significantly mitigating hallucination issues in LLMs. RAG systems have been widely applied across various domains. However, existing RAG systems often rely on LLMs and retrievers trained on general-purpose datasets, which perform poorly when dealing with domain-specific tasks. Furthermore, current RAG bench-mark datasets fail to cover all domains, posing challenges in evaluating RAG systems’ performance in specific domains. To address these limitations, we propose a challenging domain-specific datasets generation method for RAG benchmarking (RAGCDs). This method automatically generates domain-specific RAG benchmark datasets with retrieval challenges and answering difficulties based on any given corpus. The generated datasets enable rigorous evaluation of the performance of RAG systems in specific domains. We detail the process of constructing domain-specific benchmark datasets using RAGCDs and select corpora from two distinct fields, X-ray Photoelectron Spectroscopy (XPS) and medical research papers, to create the CDs-xps and CDs-medical datasets. This demonstrates the generality of our method. Our experiments validate that the RAGCDs-generated datasets exhibit exceptional quality. In terms of retrieval, the datasets pose challenges comparable to those of specialized retrieval benchmarks. Regarding answering difficulty, even the most advanced LLMs struggle significantly, achieving a score ratio of only 0.391 and 0.471 in the absence of retrieval support. We hope that RAGCDs will effectively promote the development and optimization of RAG systems tailored for specific domains. Implementation and data are available at https://github.com/xiaowuxiaowu1/RAGCDs.

Ocean currents and winds are crucial parameters to understand ocean-atmosphere interactions, while the simultaneous retrievals using Doppler scatterometry can provide direct observational support. To obtain high-quality airborne Doppler scatterometer wind and current products, accurate estimation of the observed backscatter coefficient and reliable wind field inversion are essential. Based on the Ocean Surface Current Observation Mission (OSCOM) airborne experiment data collected using a Ka-band rotating pencil-beam Doppler scatterometer, we propose two different calibration methods for the backscatter coefficient to account for the larger-than-expected azimuthal modulation of the backscatter signal, as predicted by consolidated Geophysical Model Functions (GMFs) used in Ka-band scatterometry. Both methods are based on the numerical ocean calibration (NOC) approach, which is in turn based on the estimation of the mean backscatter differences between real measurements and simulated ones with the use of the GMF and reference winds. The first method employs an azimuth-dependent calibration, which can be implemented using either an overall ratio or a ratio per flight leg. The second method involves modifying the GMF to match the observed azimuthal modulation, with options for one or two GMF coefficient adjustments. The retrieved wind speeds range from 4 to 7 m/s, with wind directions around 155°. In comparison with collocated ECMWF winds, the wind speed biases of different methods are all lower than 1.2 m/s, and the wind direction standard deviations (SD) are lower than 9.3 °. The azimuth-dependent calibration method yields smaller wind speed biases but larger wind direction SDs compared to the modified GMF method. The azimuth-dependent calibration using leg-dependent ratios leads to the closest retrieved wind speeds and directions to ECMWF. The calibration methods proposed in this study provide data support for future simultaneous retrieval studies of ocean winds and currents. Additionally, these methods can be applied to other airborne Doppler scatterometer experiments.

Accurate sea level pressure (SLP) data are critical for the forecasting and monitoring of tropical cyclones (TCs). Previous studies have explored SLP retrieval for TCs using passive microwave observations in a single oxygen band (60 or 118 GHz). Leveraging the Fengyun-3 (FY-3) satellite’s capability to simultaneously observe radiation in both 60 and 118 GHz bands, this study proposes a neural network-based algorithm to retrieve TC SLP fields from combined observations of brightness temperature (TB) and warm TB anomalies in both frequency bands. Application studies were carried out using the joint observations from the Microwave Temperature Sounder-2 (MWTS-2) and Microwave Humidity Sounder-2 (MWHS-2) onboard the FY-3D satellite. Optimal frequency channels for the SLP retrieval were selected based on an information content analysis. SLP retrievals within the TC core regions (within a 2° radius from the centers) were compared with SLP data from the Global Data Assimilation System Final Analysis (GDAS/FNL). The results showed root mean square errors (RMSEs) of 2.78 hPa for tropical depressions and storms, 4.23 hPa for hurricanes or typhoons, and 6.15 hPa for major hurricanes or severe typhoons. Retrievals were also compared within situobservations, and the corresponding RMSEs were 3.82, 4.86, and 5.14 hPa, respectively. Furthermore, comparative experiments between the new algorithm and the previous algorithm that used only observations from a single oxygen band demonstrated that the new algorithm provides more comprehensive SLP information and achieves higher accuracy.

Ice sheet internal temperature profile plays a key role in the study of ice sheet thermodynamics and ice sheet mass balance. Wideband radiometric remote sensing measurement has been demonstrated to be an effective approach for estimating the ice sheet internal temperature profile. In this study, we make model analysis of the sensitivity of emission observation on different frequency channel to ice sheet internal temperature at different depth, aiming at assessing the value of each channel in deriving ice sheet internal temperature profile. As the emission contribution depth profile can give insight into the emission compositions and emission sensitivity to the ice sheet internal properties at different depth, this study analyses the impact on ice sheet emission contribution depth profile due to the uncertainties of ice sheet temperature profile based on Comprehensive Layer Emission Model (CLEM). The correlation of different frequency channel are further discussed. The analysis results give guidance to construct retrieval approach for better extraction and utilization of the information on ice sheet internal temperature profile providing by the wideband emission observation.

This article is the preliminary results of the in-cloud wind observation of an airborne Doppler scatterometer. This experiment took place on the Qinghai-Tibet Plateau in 2022 and it’s the first time to carry wind observation experiment in this place. During the process procedure, the dual-PRF process was used to extend the max unambiguous velocity, and the VVP method was used to invert the three-dimensional wind. The result provides a 40-second observation of the in-cloud wind, which indicates that the in-cloud wind in the plateau area can be detected through an airborne scatterometer.

Satellite-derived, coincident ocean surface winds and currents are of great importance to enhance our understanding of air-sea interactions. The data from a flight campaign, carrying a Ka-band rotating pencil-beam Doppler scatterometer (i.e., the so-called OSCOM prototype), are exploited in this work. In particular, data calibration and wind/current retrievals are performed. The Normalized Radar Cross-Sections (NRCS, σ0) or backscatter measurements are calibrated using two different methods to account for the larger than expected (by consolidated Geophysical Model Functions or GMFs used in Ka-band scatterometry) azimuthal modulation of the backscatter signal. Both methods are based on the so-called target or numerical ocean calibration (NOC). The first method consists of applying an azimuth-dependent calibration, while the second is based on a modification of the GMF to match the observed modulation after calibration. The retrieved wind speeds range from 3 to 6 m/s, and the wind directions are around 155°. The standard deviations for wind speed and direction against ECMWF winds are lower than 0.9 m/s and 9°. The winds derived using azimuth-dependent calibration present lower wind speed bias and larger wind direction standard deviation with respect to the modified GMF calibration.

The hostile environment and thick sulfuric acid clouds make it difficult to measure the Venusian lower and middle atmosphere. The Venus Volcano Imaging and Climate Explorer (VOICE), which is an orbiting mission, has planned to exploring the thermal structure and composition of the Venusian lower and middle atmosphere by the Microwave Radiometric Sounder (MWRS). This study presents a forward- and inversion- model for the Venusian lower and middle atmosphere at microwave and submillimeter wavelengths, which is developed to simulate the nadir and limb sounding from the MWRS. Important properties of the model with respect to the Venusian atmosphere are its inclusion of molecular thermal movement and collisions induced spectral lines broadening as well as the effects of refraction on the signal propagation in the atmosphere. The model also has potential applications for definition studies for future downward-looking and limb-looking sensors dedicated to Venus exploration.

The Doppler spectrum of a Doppler scatterometer signal is determined by the relative motion between the scatterometer and the ocean surface, including ocean surface motion and platform motion. It is also determined by the modulation from the backscattering coefficient. Estimating the Doppler centroid is an important issue for the application of a spaceborne Doppler scatterometer in ocean surface current retrieval. In this study, we use an echoed signal simulation model to analyze the Doppler spectrum with different incidence angle. Our results show that the satellite velocity and the backscattering coefficient modulation are the main influencing factors that affect the shape of the Doppler spectrum. With the increase of incidence angle, the radial platform velocity increases, and the modulation from the backscattering coefficient decreases. At 52° incidence angle, the Doppler spectrum is closest to the Gaussian distribution, which is suitable for Doppler scatterometer.

Reported radiometric measurements indicate that incoherent and coherent radiative transfer processes characterize the microwave emission features of layered irregular and inhomogeneous medium. In order to develop a forward emission model to be capable of considering the medium and boundary scattering and coherent boundary interaction that may exist in general layered medium, in this article, we present a comprehensive layer emission model (CLEM) based on the scattering operator formulation. We introduce wave-based coherent multiple reflection operators to account for coherent boundary interaction and first integrate them with the intensity-based multiple scattering processes, allowing the comprehensive description of rough boundary scattering, volume scattering, medium/boundary interaction, and coherent boundary interaction in the framework of CLEM. Simulations and analyses for ice- and snow-covered ground cases are conducted based on CLEM to evaluate the coherent boundary interaction and different impacting factors. Validation on CLEM is conducted with emission observations of snow-covered terrain in campaign Nordic Snow Radar Experiment (NoSREx) 2010–2013 during dry snow period and time-series emission observations of frozen soil during freezing and thawing processes. CLEM simulation results show a good agreement with measurements. For NoSREx, root-mean-square errors (RMSEs) at L- to Ka-band are below 5.5 K for both polarizations, which are of different levels of promotion compared with the incoherent model simulations, especially for horizontal polarization at L- and X-band. Application to frozen soil case illustrates the capability of CLEM to explain coherent oscillation feature with impact from incoherent scattering effect.

Combined use of active and passive remote sensing can provide complementary information to simultaneously characterize the internal structure and internal physical properties of ice sheet. Well constraints of layering structure and density variation are the precondition to retrieve ice sheet internal temperature profile using radiometric measurements. This paper makes further improvement to the combined active and passive remote sensing approach presented in our previous preliminary study, mainly in density variation profile characterization, emission modeling, and density variation estimation method. In the combined approach, ice-penetrating radar-echo profile is used to estimate the ice sheet density variation, correcting the input density parameter for ice sheet emission model when interpretating the ice sheet emission observations. Validation of the improved combined approach is conducted with SMOS data and radar profiles collected by CReSIS around several ice core sites in Greenland. Evaluation of availability and advantage of the improved combined approach is performed based on the results.

The China-France Oceanography Satellite (CFOSAT) scatterometer (CSCAT) is a rotating range-gated fan-beam scatterometer which is designed to measure the normalized radar backscatter. Because of its high spatial sampling density, CSCAT data is suited for land and ice applications facilitated by resolution enhancement algorithms. Generally, such algorithms require accurate knowledge of the spatial response function (SRF) for the individual measurement. Standard CSCAT L1B products include the locations of the backscatter measurements, but not the SRF. In the paper, the mathematical expression of CSCAT slice SRF is derived, and the shape of the SRF is investigated. It has been found that the SRF can be approximated as a binary function that is 1 inside the −3dB contour of the SRF and 0 outside. The shapes of CSCAT SRF varies with antenna rotation angle and orbit position.

Polar sea ice extent is a key component to a number of global geophysical processes. The unique capability and long record of scatterometer data provide a useful tool for polar sea ice extent retrieval. The Ku-band dual-polarized rotating fan-beam scatterometer onboard the China-France Oceanography Satellite (CFOSAT) launched in 2018 is a good candidate to continue the scatterometer sea ice extent data set of KNMI and OSI SAF. The paper utilizes the Bayesian methodology for sea ice extent retrieval of the CFOSAT scatterometer (CSCAT) data and evaluate the sea ice extent derived from the ice-masked imagery against the Special Sensor Microwave Imager/Sounder (SSMI/S) data set and Advanced Microwave Scanning Radiometer2 (AMSR2) data set during 2019. The results suggest CSCAT sea ice extent correlates well with the AMSR2 over sea ice concentrations (SIC) 25% for Antarctic, but different seasonally dependent correlations for Arctic.

Ocean surface current system contains multi-scales, including large-scale geostrophic current, basin-wide gyres, and ageostrophic currents, such as Ekman currents, Stokes, tides, etc. Understanding the full ocean surface current system requires measuring the total ocean surface current vector at multi-scales. Today's satellite observations cannot directly measure the total ocean surface current vector with global coverage, even though the large-scale geostrophic current can be derived from spaceborne altimetry based on the geostrophic balance assumption. This study uses the most recent 5-year GDP (Global Drifter Program) drifter data to derive near-surface ocean current velocity. After correcting the wind-induced slippage contribution from drifter observations, GDP drifter-derived ocean current velocity is compared with the existing commonly-used ocean current datasets, i.e., OSCAR (Ocean Surface Currents Analyses Real-time) and AVISO (Archiving Validation and Interpolation of Satellite Oceanographic Data) geostrophic current datasets. There are discrepancies among these three datasets, and the significant discrepancies are evident, especially around the equator regions since the geostrophic assumption is not valid at the equator. Our results indicate that the existing ocean current datasets cannot fully resolve the variability of total ocean surface current. A clear solution is to measure the global total ocean surface current vector, which is highly desirable.

Previous studies used 50-60 GHz or 118 GHz passive microwave measurements separately for surface pressure retrieval. To improve the retrieval accuracy, a joint retrieval method is proposed in this study to use the 50-60 GHz and 118 GHz passive microwave measurements simultaneously for surface pressure retrieval over oceans. Based on information content analysis and footprint matching, collocated passive observations of the two bands are obtained, and then are used to establish back-propagation neural network retrieval models. Using the 50-60 GHz passive observations of Microwave Temperature Sounder-II (MWTS-II) onboard the Fengyun-3D (FY-3D) satellite and the 118.75 GHz observations of the Microwave Humidity and Temperature Sounder (MWHTS) onboard the FY-3D satellite, joint retrieval experiments are completed. Experimental results show that when using the 50-60 GHz and 118.75 GHz oxygen absorption band together for surface pressure measurements, more surface pressure information and better retrieval accuracy can be obtained than using them separately.

In tropical regions, Ku-band scatterometer observations are affected by heavy rain, and affected data are labeled in the quality control (QC) step during wind product generation. This is achieved by setting thresholds for QC indicators. Among the applied indicators, it has been shown that$J_{\mathrm {oss}}$can be beneficially applied for reducing the false alarm rate (FAR) for Ku-band observations for data sets collocated to C-band observations. In this letter, the FAR reduction method based on$J_{\mathrm {oss}}$is further generalized to be tested without collocated C-band observations, which extension is subsequently applied to the CSCAT wind products. Results prove the effectiveness of the FAR reduction method without C-band collocations for Ku-band scatterometers. Verification with rain rates from the Global Precipitation Mission (GPM) proves the capability of the recruited data set to benefit nowcasting applications. Moreover, the results of this research indicate the consistency of products in rainy conditions for the new rotating-fan-beam CSCAT and the existing rotating-pencil-beam Ku-band scatterometers. Further research would be to analyze detailed rain effects in different rain development stages in a wind vector cell (WVC) for tropical regions.

The second-generation Microwave Humidity Sounder (MWHS-2) onboard Fengyun (FY)-3C has a data quality comparable to that of counterpart microwave moisture sounders. However, channels 13 and 14 have large biases that are negatively correlated with the instrument temperature and prevent the operational assimilation of the data of these two channels. To better understand the biases of channels 13 and 14, the correlation of the observation minus simulation data (O–B bias) of different channels with the instrument temperature and other factors is investigated for FY-3C MWHS-2 in this article. A sensitivity analysis using a gradient boosting decision tree indicates that the instrument temperature and scan position are the two dominant factors, with total bias-contribution scores exceeding 0.8 for both channels 13 and 14. This conclusion is verified through further analysis of the bias distributions for the scan position, scene brightness temperature, and ascending/descending orbits. Using 12-week data recorded in 2016, the correlations of the O–B bias with the scan position and instrument temperature are specifically investigated and a correction algorithm is formulated, with which data for 2016 and 2017 are corrected. The corrected data in both channels have smaller, more stable biases, and are less affected by the instrument temperatures and scan position. The bias contributions associated with these two factors should thus be further studied.

The Doppler shift of microwave radar signal is determined by the relative motion between radar and ocean surface, including contributions from the movement of the radar platform and the wind-wave-induced motion (phase velocity of the resonant Bragg waves and orbital motions of ocean waves that are longer than the Bragg waves) in addition to the ocean surface current. One of the main challenges in ocean surface current retrieval is the accurate estimation of the wind-wave-induced Doppler shift, which needs to be accurately removed from the total Doppler shift to determine the surface current. In this study, we investigate the effects of different wave directional spectra on estimates of the wind-wave-induced Doppler shift using a modulation transfer function (MTF)-based and time-independent Doppler model. Our results show that the wind-wave-induced Doppler shift estimates are highly dependent on the selection of wave spectra and the directional spreading function. This study also confirms the importance of ocean wave spectra parameterization on Doppler estimation of the ocean current. We find that Apel’s spectra model is a more consistent fit to the observations, but the optimal spreading function is wind-speed-dependent.

Microwave emission from layered inhomogeneous medium is affected by both incoherent scattering and coherent interaction within the layer. Reported emission observations of snow-covered surface and ice sheet indicate that effects of layer boundary interference are more prominent at low frequencies. This paper presents a comprehensive layer emission model (CLEM) for layered inhomogeneous medium that fully accounts for incoherent scattering and coherent boundary interactions within the layer. The CLEM model is based on scattering operator (matrix doubling) formulation, which provides the basic framework for integrating rough boundary scattering, volume scattering, and coherent multiple reflections at layer boundaries. Coherent boundary interactions are accounted for through novel integrated wave- and intensity-based layer scattering operators. Initial model validation using published Elbara-II data and SodRad data shows good agreement between CLEM predictions and measured results.

Decades of ocean surface vector wind (OSVW) data acquired from space-based radar scatterometry have been providing short and long-term researches and applications information about ocean surfaces. The main objective of the project, stands and metrics of ocean surface vector wind by space-borne microwave remote sensing, of W orking Group on Calibration and Validation of the Committee on Earth Observation Satellites (CEOS WGCV), is to develop the standard and guideline for the requirement, procedure, processing and assessment for the space borne radar scatterometer measurement calibration, wind retrieval approaches, wind data validation and assessment for OSVW, which will be used to assure the consistency of the data quality of these satellites and instruments are the prerequisite for related scientific researches and applications. This synthesizes calibration, standardized practices of retrieval approaches for ocean surface winds, development of guidelines/standards of validation of ocean surface winds, and identifying and organizing collocation related data. This presentation will provide an overview of the proj ect and the recent progresses.

Polar sea ice is an important and sensitive indicator of climate change. The scatterometer onboard the China-France Oceanography Satellite (CFOSAT) is a Ku-band rotating fan-beam scatterometer with dual polarization capability and dedicated to the measurement of sea surface wind vectors. Because of the wide swath, it is also a good candidate for sea ice detection in the polar regions. The paper explorers a Bayesian sea ice detection method for the CFOSAT scatterometer. The performance of the approach is analyzed and validated against coincident sea ice concentration product of Special Sensor Microwave/Imager (SSMI). The results shows that the sea ice detection approach is feasible and effective. The resulting agreement between the sea ice maps of the CFOSAT scatterometer and sea ice concentration of SSMI is high.

Respecting the low measurement resolution of scatterometer, the adaption of the linear deconvolution processing for scatterometer is investigated to improve its spatial resolution. Based on the linear deconvolution processing, a specific form of averaging window of the resolution enhanced solution is derived. A quantitative evaluation of resolution enhancement and noise amplification of the reconstruction is conducted. The results show that some specific resolution and noise amplification solution can be obtained by tradeoff parameter selection. Based on the linear deconvolution processing, the resolution enhancement of scatterometer data can be analyzed quantitatively.

With the advent of the golden era of scatterometry, with seven scatterometers currently operating in orbit and a few others to be launched in the near future, a wide variety of scientific and operational applications will certainly benefit from consolidated wind retrieval procedures. In particular, an important component of the scatterometer wind processing is the quality control (QC) procedure. Over the last two decades, several QC indicators have been developed for C-band and Ku-band scatterometers, and used in the operational generation of sea surface wind products. Such indicators mostly aim at identifying and filtering retrieved wind quality degradation due to high wind variability and/or rain contamination effects. As such, the different QC indicators may be applied for different oceanographic and meteorological applications. The methods will be presented at the conference to motivate a discussion on their application-dependent use and come up with a consolidated view from the different user communities.

Uncertainties in wind inversion from scatterometer observations are contributed by system and geophysical noise. In practice, both can be quantified by the indicators applied in the quality control (QC) procedures during wind processing. In this research, the underlying principles of three reported indicators, MLE, SE and Joss, are discussed for CSCAT. In the observation scenes of this Ku-band scatterometer, one of the major reasons for geophysical noise are rain clouds, which are analyzed specifically with respect to those indicators. Finally, examples for super typhoon Lekima, followed by Krosa in 2019, are discussed. We confirm that the MLE and Jossindicators are relatively independent from each other, and show different features in rain screening. The combined application of them would result in a better result of rain labelling. Another conclusion derived from this research is that SE and Jossare similar indicators of spatial heterogeneity in scatterometer wind fields, but that the wind speed depression measured by Joss is a more unique indicator of rain than SE. This research contributes to improving the quality of wind retrieval from scatterometers.

An airborne validation experiment using a pencil-beam Doppler scatterometer was carried out in south of Yangjiang River, Guangdong Province, China. Its purpose is to validate the feasibility of spaceborne Doppler scatterometers and simultaneous observations of ocean wind and currents. This study presents the pencil-beam airborne Doppler scatterometer system, and its data processing algorithm. To investigate the accuracy of measured ocean wind and currents in the airborne campaign, we made a comparison with other datasets. The results show that 1) The speed error of wind is 1.2m/s, and wind direction error is around 13.19°. 2) The current speed error is better than 0.15 m/s, the current speed is better than 15 degree.

Wideband radiometric measurements can be used to retrieve the internal temperature of ice sheet [1]. However, emission from ice sheet is affected by many factors including layering structure, density profile and grain size distribution. These factors are not well constrained due to the lack of ice sheet characterization data, and thus severely limit the ability to retrieve ice internal temperature profile using radiometric measurements. This paper presents a combined active and passive remote sensing approach, in which ice-penetrating radar provides information that constraint the ice sheet parameters, to improve estimation of ice internal temperature profile using radiometric measurements. In this study, radar reflectivity measurements are used for estimating ice density variations, which are input parameters for the ice sheet emission model. Model analysis of emission from ice layer with internal temperature and structural profiles, and comparison with SMOS data are conducted to assess the viability of the combined approach.

Ocean surface current is an important variable for ocean dynamics, and it plays a key role in air-sea interactions, with gradients of currents creating much strong air-sea coupling. However, retrieving the magnitude of the surface current is still challenging, with accurate wind-wave induced Doppler shift estimates being the main challenge for separating ocean surface current from the total ocean Doppler shift. This separation requires information on wind vectors, wave spectra and forward models to be able to simulate the radar response to the ocean surface. In this study, we investigate the effects of different wave spectra on estimates of wind-wave induced Doppler shift based on a numerical Doppler model. Simulation results show that, this quantity is dependent on the wave spectra. We support the selection of the Apel spectrum by comparing empirical models at C and Ka-band (CDOP and KaDOP). The study also highlights the important effects of wave spectra selection in future satellite Doppler measurements of ocean surface currents, a variable considered important by the National Acadamies.

Space-borne Doppler scatterometer is a new and promising sensor for wide-swath, high-accuracy, and simultaneous measurements of ocean surface current and wind vector. Doppler shift of ocean surface backscattering is determined by the relative motion between the sensor and ocean surface, it includes contributions from ocean surface current, wind-wave, and satellite motion. Accurate Doppler shift due to ocean surface current is estimated by removing the wind-wave and satellite motion effects. Satellite motion contribution can be accurately estimated from the satellite attitude motion of spacecraft. The main challenge for ocean surface current retrieval is uncertainty/error in the estimation of wind-wave induced Doppler shift. In this study, effects of wind estimation errors on surface current retrieval are evaluated through the Doppler scatterometer system simulations. Simulation results show that (1) surface current retrieval is affected more by estimation error in wind direction than in wind speed; and (2) wind estimation errors have larger effect on retrieval accuracy of ocean surface current direction than that of surface current speed.

Space-borne scatterometer observations are well-known ocean surface wind remote sensing instruments, they usually work at C- or Ku-band. Particularly in tropical regions, their observations are affected by rain. Rain-affected data are labeled in a quality control (QC) step during wind product generation. This is achieved by setting threshold of QC indicators. Among the applied QC indicators, a new one namely Joss proposed by Xu & Stoffelen in 2019, is characterized by a higher probability of detection (POD) of rain events. Joss particularly reduces the false alarm rate (FAR) for Ku-band observations during the rain screening as tested with reference to C-band observations., However, it is not possible in tropical regions for the Ku-band rotating fan-beam scatterometer onboard the Chinese-French Oceanographic SATellite (CFOSAT), to obtain C-band collocations with time differences less than 30 min. In our research, first, based on the results of the existing FAR reduction method, collocated C-and Ku- band observations are further investigated. Then the method is generalized, without the assistance of collocated C-band observations. Finally, application to wind product FAR reduction of CSCAT is presented. Results prove the effectiveness of the theory of this paper. Rain references are provided by products from the Global Precipitation Mission (GPM). Further research would be analysis on detailed rain effects to Ku-band scatterometers in different rain processes in tropical and sub-tropical regions to improve the established method.

Scatterometers provide consistent observations of ocean surface wind with reliable quality. In tropical regions, Quality Control (QC) rejects observations effected by rain clouds to guarantee the quality of wind products obtained with references to Geophysical Model Functions (GMFs). GMFs map scatterometer observed normalized radar cross-sections (NRCS) to wind fields without considering rain effects. The rejected groups have information of both rains and winds, and can be utilized for quantitative modelling of rain effects. Wind scatterometers usually operate at C-or Ku-band, they are affected differently by rain clouds due to differences in sensing wavelengths. Collocated observations with both frequencies would enable quantitative evaluation of rain effects. This study exploits these collocated C- and Ku-band measurements and seeks to ultimately develop a method for improving surface wind retrieval using a rain-cloud correction factor, with the preliminary model outline proposed. A vector radiative transfer based layer scattering model for rain clouds above ocean surface that accounts for scattering and attenuation effects of rain column and sea surface roughness will be used in quantitative analysis of rain cloud effects on surface wind retrieval at C- and Ku-band. Rain drop size distribution (DSD) and surface modifications from rains under different wind speed are considered in the model. For rain-free condition, a modified IEM surface scattering model is utilized in the quantitative analysis. Model validation and evaluation of the proposed correction factor are conducted using collocated data obtained from existing C- and Ku-band scatterometer observations, with time lag less than 5 minutes and spatial difference less than 25 km, and references to rain rates from the Meteosat Second Generation (MSG) Satellite.

This paper makes a comparison of the retrieval of sea level pressure using 50-60 GHz and 118.75 GHz passive microwave observations. The 50-60 GHz passive observations of the Microwave Temperature Sounder-II (MWTS-II) and 118.75 GHz observations of the Microwave Humidity and Temperature Sounder (MWHTS) onboard the Chinese Fengyun-3D (FY-3D) meteorological satellite were used to carry out the comparison. Based on neural network-based retrieval algorithm, sea surface atmospheric pressure retrieval models for MWTS-II and MWHTS were established, respectively. Passive microwave observations from January 2018 to October 2019 and the corresponding Global Data Assimilation System (GDAS) Final (FNL) analysis data were used to develop and test the retrieval models. Results show that the accuracy of sea surface atmospheric pressure from MWTS-II retrieval is similar to that of the MWHTS retrieval for both usual weather conditions and tropical cyclone (TC) conditions. This provides a reference for high spatial resolution surface pressure observations by passive microwave instruments from low orbit satellites and high temporal resolution observations from geostationary orbit in the future.

The first rotating fan beam scatterometer onboard China-France Oceanography Satellite (CFOSAT) was successfully launched on October 29, 2018. CFOSAT SCATterometer (CSCAT) is dedicated to the monitoring of sea surface wind vectors but also provides valuable data for the applications over land and Polar Regions. This article provides an overview of the relevant procedures of CSCAT data processing, including onboard signal processing and operational ground processing. Then a post-launch analysis is carried out to evaluate the first results of CSCAT L1 and L2 products. It shows that the CSCAT instrument is generally stable in terms of noise measurements and internal calibration, unless there is any important change in the system configuration. Specifically, the CSCAT backscatter (σθ) precision and wind quality are studied using a set of collocated ancillary data. The σθprecision degrades as wind speed decreases, and it is relatively low at high incidence angles (e.g., θ >46°). In particular, backscatter estimation of the horizontally polarized beam should be further improved by correcting the noise subtraction factor. The retrieved CSCAT winds are in good agreement with the European Centre for Medium Range Weather Forecasts (ECMWF) winds, the Advanced Scatterometer (ASCAT) winds, as well as the buoy winds. However, due to unresolved calibration and interbeam consistency problems, the wind quality degrades remarkably for the out-swath and the nadir-region wind vector cells, implying that the σθcalibration should be improved in the future updates.

After the launching of CFOSAT (China-France Oceanography Satellite), calibrations of the SCAT (scatterometer onboard the CFOSAT) are carried out to modify the bias of the observed NRCS (normalized radar cross section). In this paper, some preliminary calibration results of CFOSAT SCAT are presented, including both internal calibration onboard the CFOSAT and external calibration on the ground. First, the onboard calibration signals and noise signals are analyzed to ensure the SCAT works in a steady status. Then, calibrations on NRCS are carried out by using the SCAT data from Amazon rainforest area. Furthermore, Calibrations using transponders will be carried out at Inner-Mongolian. Preliminary calibration results show that the NRCS of CFOSAT SCAT are compliable with the NRCS of NSCAT.

The scatterometer (SCAT) onboard the China-France Oceanography Satellite (CFOSAT) is the first rotating fan-beam scatterometer (RFSCAT) in space for global ocean surface vector wind measurement. After the CFOSAT launched in Oct. 29, 2018, the main performances of the CFOSAT scatterometer (CFOSCAT) are being tested in orbit. In this paper, the preliminary data processing results of CFOSCAT are presented, including the calibration signal analyses, system noise analyses, normalized radar cross section (NRCS) processing results and wind retrieval results. The results show that CFOSCAT works properly in orbit, the main system specifications of scatterometer system satisfies the design. Preliminary results also validates the wind retrieval performance.

The sea surface winds from the CFOSAT scatterometer (CFOSCAT) are retrieved using the maximum likelihood estimator, and the inversion residual is used to sort the good-quality winds from the poor-quality ones. A two-dimensional variational analysis ambiguity removal (2DVAR) scheme is then applied over the CFOSCAT swath such that a unique wind field is selected from the available local scatterometer wind vector ambiguities. The preliminary results of CFOSCAT Level 2 (L2) processing show that the retrieved wind speed is overestimated under low-wind conditions (w15 m/s). Moreover, the inversion residual for the sweet swath (where there are more than 10 views) is generally higher than that for the nadir/outer swath. These imply that observations with different geometries (views) at the same WVC are inconsistent with respect to the geophysical model function, and thus a comprehensive calibration is highly demanded. A more detailed assessment of the CFOSCAT wind quality will be carried out after calibration and validation campaign.

The simultaneous measurements of ocean surface current and wind have attracted considerable interest. Since they are closely coupled at sea surface, wind errors (speed and direction) have a transfer effect on current retrieval. In this paper we investigate the effects of wind transfer error on current retrieval for a Doppler scattterometer. We analyze current retrieved errors in different cross-track distances, and find the best current retrieval position is at sweet spot (i.e., mid-swath). For a single measurement in a current resolution cell of 10km, if no wind errors in 7m/s wind speed, at sweet spot current retrieved errors are around 0.25m/s and 30°, respectively. However, with wind errors existing, current retrieved errors are 0.33m/s and 41°. For comparisons, the results show that wind errors degrade current retrieval performances. Additionally, we also analyze current retrieved errors in different wind and current conditions, the results show that, wind direction error has a larger effect on current retrieval compared with wind speed error, and current direction error is more susceptible to wind errors. Our results indicate that, a simultaneous and accurate wind measurement is critically needed to accurately mitigate its effect on current retrieval.

The RFSCAT(Rotating Fan-beam SCATterometer) is one of the two payloads of CFOSAT, the China-France Oceanography Satellite. It is a radar scatterometer designed to measure the electromagnetic backscatter from wind roughened ocean surface. The operating frequency of the scatterometer is 13.256GHz (Ku-band) and has a swath about 1,000 kilometers. The CFOSAT scatterometer data level-1 processing is the key step to obtain the high-quality sigma0s, and is the guarantee of obtaining high quality wind fields. In this paper, the CFOSAT scatterometer data pre-processing system and level-1 data processing algorithm and level-1 processor operation procedures is introduced. On the other hand, the in-orbit test preliminary results of the CFOSAT scatterometer data level-1 processor is introduced and analyzed.

The China-France Oceanography Satellite (CFOSAT) to be launched in October 2018 will carry two innovative payloads, i.e., the surface wave investigation and monitoring instrument and the rotating fan-beam scatterometer [CFOSAT scatterometer (CFOSCAT)]. Both instruments, operated in Ku-band microwave frequency, are dedicated to the measurement of sea surface wave spectra and wind vectors, respectively. This paper provides an overview of the system definition and characteristics of the CFOSCAT instrument. A prelaunch analysis is carried out to estimate the scatterometer backscatter and wind quality based on the developed CFOSCAT simulator prototype. The overall simulation includes two parts: first, a forward model is developed to simulate the ocean backscatter signals, accounting for both instrument and geophysical noise. Second, a wind inversion processor is used to retrieve wind vectors from the outputs of the forward model. The benefits and challenges of the novel observing geometries are addressed in terms of the CFOSCAT wind retrieval. The simulations show that the backscatter accuracy and the retrieved wind quality of CFOSCAT are quite promising and meet the CFOSAT mission requirements.

The Ku-band rotating fan-beam scatterometer (RFSCAT) onboard the China-France Oceanography Satellite (CFOSAT) is dedicated to the measurement of sea surface wind vectors. The flight model of RFSCAT has been assembled and tested, and the data processing algorithms have been developed. This paper provides an overview of the design and characteristics of RFSCAT instrument, and then a prelaunch analysis is carried out to estimate the scatterometer backscatter and wind accuracy. The overall study includes two parts: first, a forward model is developed to simulate the ocean backscatter signals under certain wind conditions; second, a wind inversion processor is used to retrieve sea surface wind vectors from the outputs of the forward model. Simulations show that the backscatter accuracy and the retrieved wind quality of RFSCAT are quite promising and meet the scientific requirements of the mission.

Based on [1], a quantitative comparison of resolution enhancement performance for three deconvolution approaches (L2 norm, L1 norm and TV) to DPS scatterometer over nadir swath are made. The spatial resolution and reconstruction accuracy/precision properties of these methods are analyzed and compared. Results show that resolution enhancement is achieved by the price of decreased accuracy/precision of reconstructed backscatter, and the reconstructed backscatter becomes a more smoothed version of truth backscatter with decrease of spatial resolution.

Wind fields over ocean surface can be effectively retrieved by scatterometer measurements with GMFs (geophysical model functions) relating them and observing geometry with wind speeds. However, existed GMFs are not suitable for rainy conditions which require extra information for rain induced factors in observations that vary with rain conditions. The combined observations of scatterometer and radiometer are suitable for the problem. In this paper, this was realized by the method based on SVM (support vector machine) with kernel function established in this paper considering the form of existed GMFs. Experiments had been conducted over HY-2A scatterometer (HSCAT) and radiometer (HRAD) who give observations at almost the same time and operation frequencies suitable for this problem. The training progress was achieved by taken Windsat wind fields as true values. The method had been verified by comparison made between the wind fields retrieved with that of Buoy data. Discussion were made for further researches exploring the underlying physical progress of the SVM established.

The scatterometer (SCAT) onboard China France Oceanography Satellite (CFOSAT) will be the first scanning scatterometer with rotating fan-beams. Wind retrieving methods for existed scatterometers, which are with rotating pencil beams or fixed fan beams, are needed to be modified considering efficiency in information extraction from the numerous observations acquired in this working mode. This was achieved in the research of this paper by applying Principle Component Analysis (PCA) method. Firstly, vectors for applying PCA are composed in two different ways for analysis of the effectiveness of information extraction for the SCAT data and for wind retrieving respectively. Then the description of simulated SCAT data considering observing geometry and SCAT working mode was given. Then experiments of PCA based wind retrieving method was carried out with conclusion that it was effective in information extraction for preparing data sets for wind retrieving. Finally, further research has been discussed.

The paper investigates the retrieval of typhoon and hurricane surface barometric pressure by passive measurements. The SVR based retrieval algorithm is presented and the passive microwave measurements from the SNPP/ATMS are used for the algorithm training and verification. The assessment of the retrieval performance is done by comparing the case-by-case retrievals with dropsonde measurements and tropical cyclone best track data. The validation results show that the established retrieval algorithm can estimate typhoon and hurricane surface barometric pressure with the accuracy better than 8hpa. As a preliminary conclusion, this method can provide some important sea surface barometric pressure information for typhoon and hurricane structure and dynamic characteristics analysis and offers a new idea for the study of typhoon and hurricane from microwave radiometer data.

Water Cycle Observation Mission (WCOM) is a mission dedicated to synergetic observations of global water cycle parameters, with emphasis on soil moisture, ocean surface salinity, snow water equivalent and frozen/thaw. WCOM implements its observation requirements by measurement of microwave emission/scattering of both the frequencies sensitive to the key parameters and also the auxiliary frequencies providing necessary atmospheric and surface roughness corrections. In order to satisfy this measurement requirements, WCOM is equipped with payloads with combination of active and passive microwave sounding capabilities of frequency from L-band to W-band. Dual Frequency Polarized Scatterometer (DFPSCAT) is one of the three payloads onboard the satellite of Water Cycle Observation Mission (WCOM). DFPSCAT is an X/Ku band rotating pencil beam scatterometer with 2-5 km resolution and 1000km swath for mapping of snow water equivalent (SWE) and freeze-thaw process. DFPSCAT achieves fine resolution by linear frequency modulation pulse compression along the elevation direction, and by unfocused synthetic aperture processing (a technique where the Doppler effect is exploited to synthesize a longer aperture to achieve an improved resolution), as well as super-resolution reconstruction by oversampling in the direction of the azimuth. Based on the payloads of WCOM mission, especially with X/Ku scatterometer and L/Ku/Ka radiometer active/passive observations, there are obvious advantages in snow water equivalent retrieval. The atmospheric correction of active and passive data should be performed before the retrieval. The estimation of SWE mainly rely on the high resolution X and Ku band scatterometer, and combined active/passive retrieval can provide more reliable SWE product. The retrieval method of SWE from X/Ku scatterometer is described, and combined active/passive retrieval is also briefly described.

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”.

Dual-Frequency Polarized Scatterometer (DPS) is a new system utilizing Doppler Beam Sharpening (DBS) technology for resolution enhancement. Respecting the low azimuth resolution over nadir swath, the Backus-Gilbert method is investigated to improve the resolution. According to the precision definition of scatterometer measurement, a Backus-Gilbert method for scatterometer is derived. Using the method, the tradeoff of resolution and precision of resolution-enhanced backscatter (normalized radar cross section, σ0) is established in a quantitative manner. The results show that resolution enhancement is achieved by the price of greatly decreased precision of reconstructed backscatter.

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.

The paper investigates the retrieval of sea surface barometric pressure under clear sky by passive measurements. Several linear and nonlinear statistical algorithms are presented and the passive microwave measurements from the Advanced Technology Microwave Sounder (ATMS) on S-NPP satellite are used for the algorithm training and verification. The retrieval are assessed by evaluation of root mean square error (RMSE), with comparison with the reanalysis data of European Centre for Medium-Range Weather Forecasts (ECMWF). The validated results show that Support Vector Regression (SVR) has the best performance and the corresponding RMSE of sea surface pressure is 1.53mb. The accuracy is comparable with the other traditional in-situ methods, and satisfy the requirements for meteorological applications.

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$0.5 {^{\circ }} \times 0.5 {^{\circ }}$grid average.

Earth observation satellites play a critical role in providing information for understanding the global water cycle, which dominates the Earth-climate system. However, limitations in observations will restrict our current ability to reduce the uncertainties in the information used to make decisions regarding to water use and management. Under the support of “Strategic Priority Research Program for Space Sciences” of the Chinese Academy of Sciences, a new satellite concept of global Water Cycle Observation Mission (WCOM) is proposed, aiming to provide higher accuracy and consistent measurements of key elements of water cycle from space, including soil moisture, ocean salinity, freeze-thaw, snow water equivalent and etc. The expected more consistent and accurate datasets would be used to refine existing long-time series of satellite measurements, to constrain hydrological model projections and to detect the trends necessary for global change studies. The WCOM is expected to be implemented during the 13thfive-year-plan period (2016–2020).

Water Cycle Observation Mission (WCOM) is a mission dedicated to synergetic observations of global water cycle parameters, with emphasis on soil moisture, ocean surface salinity, snow water equivalent and frozen/thaw. WCOM implements its observation requirements by measurement of microwave emission/scattering of both the frequencies sensitive to the key parameters and also the auxiliary frequencies providing necessary atmospheric and surface roughness corrections. In order to satisfy this measurement requirements, WCOM is equipped with payloads with combination of active and passive microwave sounding capabilities of frequency from L-band to W-band. In addition to the multiple frequency requirement, the requirement for spatial resolutions and swath width leads to large aperture antennas and scanning of antenna beams, the accommodation of the three payloads becomes the major challenge for the design of the WCOM satellite. In order to satisfy the temporal resolution requirement, the design of data downlink and ground segment are also discussed. In this presentation, a preliminary design for WCOM satellite is provided, some technical issues need further investigation are also discussed.

The Chinese and French Space Agencies are jointly preparing an innovative mission, CFOSAT (China France Oceanography Satellite) devoted to the monitoring of the ocean surface and its related science and applications. This paper gives an overview of the scientific objectives, the mission and instrument characteristics, the expected data products and their performance.

Dual-Frequency Polarized Scatterometer (DFPSCAT) is a new system utilizing Doppler beam sharpening (DBS) technology for azimuthal resolution enhancement. Considering the DBS technology is inapplicable for the middle areas of the swath, a theoretical framework of deconvolution signal processing is proposed to improve resolution. A deconvolution method of the nonlocally centralized sparse representation (NCSR) is adopted to verify its feasibility, and simulation results show that the deconvolution method have obviously better resolution enhancement and higher recovery accuracy than these of the classical scatterometer image reconstruction (SIR) method.

Polarimetric Microwave Imager (PMI) is planning as one of the main payload on WCOM satellite with the purposes of collecting the radiation from the Earth surface to retrieve the geophysical parameters of the land, ocean and atmosphere. PMI is passive microwave radiometer with frequencies of 6.8, 10.7, 18.7, 23.8, 37 .0 and 89GHz. The radiometers at 10.7, 18.7 and 37.0 GHz are full-polarized to measure four Stokes of the surface, whether from the ocean or the land. The other frequencies are traditional radiometer with vertical and horizontal channels. Since the third and the fourth Stokes parameter are sensitive to the orientation feature of the surface, they can be used to retrieve the wind vector, rain, snow cover, forest distribution and polar icecaps. Furthermore, with the higher resolutions at 37.0 and 89.0 GHz, the freeze-thaw on the land and rain on the ocean can be more accurately evaluated. In the paper, some primacy consideration and design on PMI are given for the application fulfilling the requirements of WCOM.

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.

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.

The MICAP(microwave imager combined active and passive), which has been selected to be a candidate payload for future Chinese ocean salinity mission, contains an L-band digital beam forming(DBF) scatterometer for the purpose of elimination of ocean surface roughness and wind retrieving. In this paper, data pre-processing flow for this scatterometer to obtain data ready for sea surface salinity and ocean surface wind retrieval was presented after corresponding data level definitions in this flow had been introduced. The processing flow was verified by processing data resulted from a data set simulated in a simple progress. Future work to perfect the pre-processing progress was also discussed.

The RFSCAT(Rotating Fan-beam SCATterometer) is one of the two payloads of CFOSAT, the China-France Oceanography Satellite. It is a radar scatterometer designed to measure the electromagnetic back-scatter from wind roughened ocean surface. The operating frequency of the scatterometer is 13.256GHz (Ku-band) and has a swath about 1,000 kilometers. In this paper, an end-to-end data simulation system of CFOSAT RFSCAT is developed for processing algorithm validation and performance analysis. Using the simulation system, the slice and WVC geometries are determined and the measurement performance is analyzed. Based on the simulated data, the wind is retrieved and the performance of wind retrieval is estimated. Meanwhile, according to the simulation and wind retrieval of CFOSAT RFSCAT, some considerations of the actual data processing are introduced.

The scatterometer onboard the China-France Oceanography Satellite (CFOSAT) will be the first rotating fan-beam scatterometer (RFSCAT) ever flown in space for global ocean vector wind measurement. The status and progress of the scatterometer will be presented, including the mission schedule, payload design and development, validation experiments. The internal calibration strategy, Doppler compensation method and onboard signal processing arithmetic are also reported.

Dual Frequency Polarized Scatterometer (DFPSCAT) is one of the three payloads onboard the satellite of Water Cycle Observation Mission (WCOM). DFPSCAT is an X/Ku band rotating pencil beam scatterometer with 2-5 km resolution and 1000km swath for mapping of snow water equivalent (SWE) and freeze-thaw process [1]. DFPSCAT achieves fine resolution by linear frequency modulation pulse compression along the elevation direction, and by unfocused synthetic aperture processing (a technique where the Doppler effect is exploited to synthesize a longer aperture to achieve an improved resolution), as well as super-resolution reconstruction by oversampling in the direction of the azimuth.

This letter presents an algorithm for retrieving soil moisture using only H-polarized multiangular brightness temperature at L-band. We developed a parameterized surface model based on a simple-empirical model, the Hpmodel, for this retrieval algorithm. By analyzing a simulated database using the advanced integral equation model (AIEM), it was found that the roughness variable Hhcan be parameterized as a function of an effective roughness parameter Sr = (kL· s)2-N(s/l)N. Influences of three surface roughness parameters (e.g., rms height, correlation length, and type of autocorrelation function) required to describe a rough surface on surface reflectivity were all considered in this parameterized model. Comparison with AIEM simulations over a wide range of soil conditions indicates a good performance of this model. Then, based on the ω - τ model, this algorithm is applied on refined SMOS H-polarized multiangular brightness temperature. Retrieved soil moisture in Africa exhibits reasonable patterns and temporal changes. Validation using in situ soil moisture from Little Washita watershed and Yanco over 2010-2011 showed fine accuracy with root-mean-square errors of 0.031 and 0.045 m3/m3 for two areas, respectively.

Ocean surface current is a very important parameter of ocean dynamic environment, which has been connected to global climate change, marine environment forecasting, marine navigation, engineering security and so on. Doppler scatterometer is a new type of scatterometer that can be used to measure ocean surface current as well as the ocean wind vector in space. The Doppler Scatterometer is based on a real aperture radar, which can achieve a very wide swath. It can provide the ocean surface current and wind vector information in a certain resolution and achieve global coverage quickly, which is very important for the marine environment forecasting and climate changes research.

Dual-Frequency Polarized Scatterometer (DFPSCAT) is a pencil-beam rotating scatterometer which is used to measure snow water equivalence (SWE). Respecting the low azimuth resolution of its forward-looking region, an adaptive regularization deconvolution super-resolution method, based on the scatterometer echo signal model, is proposed. Compared with the classical SIR and MAP algorithms, the proposed method can better reconstruct the original signal, and has less noise amplification. The algorithm processing accuracy with different Kpcis also studied, and the results show that when the value of Kpcis less than 0.1, nearly the entire restored data can satisfy the requirement of 0.5dB accuracy.

In order to satisfy a high resolution for the measurement of snow water equivalent, we use the system of using the dual frequency(X-band 9.6GHz and Ku-band 17GHz ) and full polarization. This paper discusses the various system options(scanning pencil-beam, high PRF, high SNR) and tradeoffs considered for improving the azimuth resolution of scatterometer are required.

The RFSCAT(Rotating Fan-beam SCATterometer) is one of the two payloads of CFOSAT, the China-France Oceanography Satellite. It is a radar scatterometer designed to measure the electromagnetic back-scatter from wind roughened ocean surface. The operating frequency of the scatterometer is 13.256GHz (Ku-band) and has a swath about 1,000 kilometers. In this paper, based on the characteristics of echo signal of RFSCAT, the on-board processing of RFSCAT signal is introduced. A Doppler pre-compensation LUT and A slice division LUT are developed, and the signal processing algorithms are validated and the wind retrieval performances of RFSCAT are analyzed based on the well-developed data simulation system of CFOSAT RFSCAT.

In order to measure the ocean surface current vector in a direct way, an interferometric method using pencil-beam scatterometer is proposed and the parameters of the traditional scatterometer are modified. What's more, the measurement principle and correlation model are introduced in this paper. The simulation results show that the Std of ocean surface current speed in both along-track and cross-track direction can be smaller than 10cm/s when the wind speed is larger than 4m/s. And the effective swath is greater than 445km when the wind speed is larger than 7m/s. The Kpcof the modified scatterometer is better than that of the tradition scatterometer.

WCOM, the Water Cycle Observation Mission, is proposed to improve the capability of synergetic observation of key water cycle variables. By developing innovative active-passive and multi-frequency combined sensors and retrieval models and techniques, the scientific objectives of this mission is to deepen the understanding on global water distribution, transportation and phase conversion by synergistic observations; and based on the improved model and data, to rebuilt long-term data series for revealing of the responses and feedbacks of water cycle to global changes.

Earth observation satellites play a critical role in providing information for understanding the global water cycle, which dominates the Earth-climate system. However, limitations in observations will restrict our current ability to reduce the uncertainties in the information used to make decisions regarding to water use and management. Under the support of “Strategic Priority Research Program for Space Sciences” of the Chinese Academy of Sciences, a new satellite concept of global Water Cycle Observation Mission (WCOM) is proposed, aiming to provide higher accuracy and consistent measurements of key elements of water cycle from space, including soil moisture, ocean salinity, freeze-thaw, snow water equivalent and etc. The expected more consistent and accurate datasets would be used to refine existing long-time series of satellite measurements, to constrain hydrological model projections and to detect the trends necessary for global change studies.

The resolution of the present spaceborne scatterometers are challenged by some applications like polar ice mapping and soil moisture mapping. In this paper, a new image reconstruction method is proposed to apply to the scatterometer image reconstruction for the rotating fan-beam spaceborne scatterometer (RFSCAT) called the total variation regularization. The simulation experiments show that the new method can improve the quality of the reconstructed image through both resolution enhancement and noise reduction at the same time.

The Normalized Radar Cross-Sections (NRCS,σ0) measured by spaceborne scatterometer are used to determine the near-surface wind field using the geophysical model functions (GMF). The accuracy of the retrieved wind field is a sensitive function of the radiometric accuracy of the σ0measurements. Therefore, in-orbit calibration is essential for the retrieval of optimum quality geophysical products. In this paper, the scatterometer onboard HY-2A satellite (HY-2 SCAT) is calibrated using Numerical Ocean Calibration (NOC) and its winds retrieval after calibration are validated by winds from global buoys and from the European Centre for Medium-Range Weather Foresting (ECMWF) Numerical Weather Prediction model (NWP). The standard deviations for wind speed and wind direction against buoy winds are better than 1.3 m/s and 15°, indicating that the HY-2 SCAT calibration has been successful and that HY-2 SCAT wind products after NOC are of high quality.

For the operational spaceborne scatterometers, there is no effective way to eliminate the influence of the rain. Echoes contaminated by the rain are discarded directly. In this paper, a special designed spaceborne scatterometer and its decoupling methods of echoes from sea surface and rain are introduced. The main steps of decoupling methods are as follows. First, the scatterometer system parameters are slightly adjusted to acquire both the rain and sea surface echoes simultaneously. Next, the data of the scatterometer are copied and processed separately, one copy for rain retrieving and the other copy for sea surface backscatter retrieving. Finally, the rain attenuations are compensate to modify the bottom rain rate and the sea surface backscatter energy.

Through the effective combination of polarization and interferometry information, PolInSAR can simultaneously measure the three-dimensional spatial structure and scattering properties of the illuminated target, it provides the possibility of extracting the high-precision digital elevation information and slight deformation information of observed object, so quantitative microwave remote sensing can be realized1. The construction, data processing technique and applied research of PolInSAR system have been the research hotspot of SAR at home and abroad. In this paper, a Ku-band polarimetric interferometric radar system is constructed, and in the recent airborne flight experiments, preliminary images of observed area with obvious polarimetric characteristic are acquired, which lays the foundation for further extracting the polarization and interferometry information.

With polarimetric techniques introduced into SAR interferometry, comprehensive information about vertical distribution and 2D distribution of scattering mechanisms with polarimetric characteristics can be achieved. As a result, polarization interferometric synthetic aperture radar can provide more accurate, rich data source for mapping, disaster monitoring, vegetation distribution, resource exploration etc. Ku-band Multifunction radar system built in the CAS key laboratory of microwave remote sensing provides a test bench for principle verification. In the recent airborne experiment, several system functions have been proved on this test bench. Effective data were obtained during experiments. Now, H and V channel data are imaging processed respectively using RD algorithm. From processed results, the polarization information of the target is obvious. Analyze the phase of each image of channel H and V.

Polarimetric backscatter measurements has potential benefits to improve wind retrieval performance [1]. It simultaneously measures co-polarized backscatter coefficient (σhh, σvv) and the correlation coefficient of the co- and cross-polarized component (σvhhh, σhvvv) of radar returns. A pre-processing design of spaceborne polarimetric scatterometer will be introduce in this paper considering to improve the resolution by range filtering [2]. A corresponding formulation for assessing the variance of the measurements due to fading and the thermal noise is presented considering the factors affecting the measurement accuracy.

Scatterometers are key instruments for remotely sensing of ocean surface winds. The Ku-band airborne full polarized scatterometer (AFPSCAT) of the Airborne Remote Sensing System (ARSS) was developed mainly for this application by the Key Laboratory of Microwave Remote Sensing in National Space Science Center of Chinese Academy of Sciences. Its rotating fan-beam antenna is unique among existed fully polarized scatterometers for remote sensing, which is a special type of scatterometer capable of collecting the co-polarized and cross-polarized backscattering as well as providing complex correlation of the scattering matrix. An initial test of this instrument and its potential for measuring wind field was done by flying with a plane over the Yellow Sea area in China. In this paper, the instrument was depicted, and then the experiment was described as well as data processing progress. Finally results were analyzed and conclusions were drawn that the instrument worked well for wind retrieving and further work needed to be done before its forward applications.

Rotating fan-beam scatterometer (RFSCAT) is a new kind of radar system designed to measure the normalized radar backscatter coefficients (σ°) to derive the near ocean surface wind vectors (OSWV). In this paper, some considerations about the in-orbit calibration of a Ku-band RFSCAT are presented. A simple method based on ground Calibration Ground Stations (CGS) is proposed and the method is verified by simulations. Spacecraft attitude errors are estimated and RFSCAT antenna gain pattern is able to be monitored using Calibration Ground Stations (CGS).

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.

In this paper, the status and progress of the scatterometer (SCAT) of the Chinese-French Oceanography Satellite (CFOSAT) will be reported. SCAT/CFOSAT will be the first rotating fan-beam scatterometer (RFSCAT) ever flown on a satellite for global ocean vector wind measurement. The mission schedule, some design and development status and simulation results of its performances will be presented. The considerations about the calibration of RFSCAT is also presented in this presentation.

The scatterometer can be significantly affected by rain, especially those operated on Ku-band. The effects are related to many parameters, such as rain rate and frequency. In this paper, a model which takes all the parameters into accounted is presented. The effects of all the parameters played on sea surface back scattering with precipitation are analyzed using this model. The analyzed results indicate that rain volume fraction and frequency are key factors, while influence of raindrop size polarization is less obvious.

Spaceborne wind scatterometers has been proved to be an efficient instrument for measurements of ocean surface winds. There have been some experiments show that the polarimetric scatterometer can significantly improve the measurement accuracy compared to the traditional co-polarized scatterometers [1]. In this paper, a Ku-band rotation pen-beam polarimetric scatterometer system simulation model is established and compared with co-polarized mode, further demonstrates that polarimetric scatterometer has better wind retrieval quality. Then discuss the factors affecting the performance of the polarimetric scatterometer.

The scatterometer of HY-2 satellite is a rotating pencil-beam radar. It has a one-meter dish reflector antenna with two beams, the outer beam is VV-polarized and the inner beam is HH-polarized. This paper provides the in-orbit processing and calibration results of HY-2 scatterometer. After analyzing the acquired data for natural targets from the Amazon Rainforest and the Sahara Desert, the in-orbit calibration algorithms are verified and the results are also presented.

An airborne multi-pencil beam rotating scatterometer is introduced in this paper. Multi-pencil beam scatterometer can obtain echoes of sea surface and precipitation simultaneously. When the radar system parameters and retrieving arithmetic are carefully designed, sea surface wind vector, three Domain wind vector above the sea and the vertical structure of the precipitation can be refined from the multi-angle echoes. In this paper, the key technologies, such as precipitation and sea surface decoupling arithmetic and pulse compression with low side lobe arithmetic are applied to obtain the wind vector and precipitation structure.

Rotating fan-beam scatterometer (RFSCAT) is a new kind of spaceborne scatterometer for ocean surface vector wind (OSVW) measurement. In this paper, some consideration about the calibration of a Ku-band RFSCAT is presented. Both internal calibration and external calibration are described. Preliminary analyses about the internal calibration precision and external calibration accuracy are presented. Based on the method of Long, et al, external calibration method for RFSCAT is proposed. Some simulation results for the external calibration with natural extended targets, such as Amazon forest, are presented.

In this paper, the status and progress of the scatterometer (SCAT) of the Chinese-French Oceanography Satellite (CFOSAT) will be reported. SCAT/CFOSAT will be the first rotating fan-beam scatterometer (RFSCAT) ever flown on a satellite for global ocean vector wind measurement. The mission schedule, some design and development status and simulation results of its performances will be presented. It is shown that the RFSCAT will have some advantages for wind vector retrieval for high wind speed situations.

In this paper, a conceptual design for a dual-frequency Rotating Fanbeam SCATterometer (RFSCAT) to fly onboard the future satellite (e.g. FY-3) with altitude of 836km is studied. System configurations of the studied C- and Ku-band RFSCAT are introduced respectively. Then an end-to-end simulation process is adopted to analyze the backscatter measurement accuracy, ant to assess the wind retrieval quality of the proposed RFSCAT. For a wind vector cell with spatial resolution of 25 km, the communication noise ranges from 4% to 90% for the Ku-band measurement, and from 3% to 25% for the C-band one, depending on ocean surface wind speed. The simulation results indicate that the proposed system would promote the wind retrieval qualities significantly by combining the C- and Ku-band microwave measurement.

This paper introduces the design and simulation results of a Ku-band rotating fan-beam radar scatterometer for ocean surface wind vector measurement. It will be flown on a small satellite dedicated to provide data for investigation of the ocean wave and ocean surface wind vector interactions, along with another payload for measurement of directional ocean wave spectra by a real-aperture radar with multiple scanned pencil beams. Key issues about the design of a Ku-band rotating fan-beam radar scatterometer, and results of performance simulations are provided as well. The performance of the system is simulated by the absolute and relative specifications. For the absolute specifications, retrieval performances for both wind speed and wind direction are evaluated, with the maximum likelihood method being employed. For the relative specifications, the figures of merit (FOM) is simulated, for comparison with other Ku-band scatterometers and optimization of system parameters. Simulation results of both the σ° precision and wind retrieval accuracies for different wind speed from 4m/s to 24m/s will be provided, which shows that SCAT can satisfy the performance requirements within most part of the swath.

FY-3A (Feng Yun means wind and cloud in Chinese) meteorological satellite of China was successfully launched on May 27, 2008. MWHS (MicroWave Humidity Sounder) is a very important payload for measuring global atmospheric water vapour profiles. In this paper, the authors will describe the system configuration and parameters of MWHS. Moreover it gives the testing results in-orbit and comparing with AMSU-B which has been installed on NOAA-17.

This paper introduces an on-board signal processing subsystem of a spaceborne rotating fan-beam scatterometer in China. The subsystem processes returned signal after downconversion to intermediate frequency. To reduce the data stream downlinked from the satellite, the final data bins are summed into 34 energy slices, each with a range resolution of 10 km. Then a simulation process is adopted to analyze the Doppler effects due to the motion of the spacecraft, and to generate the Doppler compensation table and the bin summation table. This method is also used to analyze the measurement variance Kpcof each detected slice. Finally, the coefficients of the expression of Kpcare presented.

Spaceborne Rotating Fanbeam Scatterometer, RFSCAT, has a wider continuous swath that can provide a large number of independent samples of Sigma0 for wind speed and direction retrieving. But the large swath and footprint result in a wideband Doppler frequency shift. For a low earth orbiting satellite, the maxim Doppler bandwidth between forward and backward echoes will be about 500 KHz. Even in a single echo of RFSCAT, the Doppler bandwidth is about 90 KHz, while in a pencil beam scatterometer the Doppler bandwidth is almost a single tone. A method of Doppler frequency compensation both on center frequency of transmitted pulses and signal processing section of the echoes are carried out and evaluated.

In this paper, a simulation method is presented to analyze and to optimize the performance of a real aperture radar system for measuring oceanic directional wave spectra, taking into account of data processing parameters. The results show that spaceborne radar ocean wave spectrometer (SB-ROWS) can measure spectra of fully developed waves with significant wave heights (SWH) over approximately 2.0 meter and swell surface under low wind conditions. The minimum detectable wavelength in the study is about 40 m. The wavelength resolution for a wavelength of 200 m is better than 30 m, and the directional resolution after averaging is better than 20o.

A spaceborne Ku-band rotation fan-beam scatterometer (RFSCAT) for sea surface wind field measurement is introduced. The system will be operated in Ku-band frequency so that the dimension of its antenna can be shortened enough for a small satellite platform. Then a simulation method is adopted to analyze the performance of this system. The results show that the proposed scatterometer has a good performance in wind retrieval.

It is well known, that the backscattering radiometric accuracy of radar scatterometers for ocean surface wind and precipitation measurements is decided by the signal-to-noise ratio and number of independent samples for non-coherent average. For sea wind scatterometers and meteorological radars, pulse compression can be employed to improve the range resolution and increase the number of independent numbers. But for airborne and spaceborne scatterometers, the peak power of the transmitter and the pulse length are usually decided by the platform capability, orbit parameter and observation geometry. As a result, compromise and trade-off between the signal-to-noise ratio (SNR) for measurement of each resolution cell and the total number of independent samples of each pulse are usually required. In this paper, based on the radiometric accuracy model, an optimization scheme for design of the independent samples numbers and the corresponding system bandwidth are presented. Based on the presented optimization scheme, the bandwidth of a Ku-band rotating fan-beam radar scatterometer for sea surface wind measurement is design. Simulation validates the optimization and design results.

Pulse compression with very low sidelobes is one of challenges in the design of spaceborne weather radar. To detect the weak echoes of clouds occurring near the strong echoes of sea surface, sidelobe performance below -60db is needed in the pulse compression system. Based on the traditional ways of pulse compression, double Kaiser Windows are applied here for sidelobe suppression and the Peak Sidelobe Level (PSL) can reach -75db. To avoid power and SNR loss, the time domain Kaiser Window weighted on transmitter was replaced by the frequency domain window weighted on receiver equally. A real time signal processor and digital predistortion method based on successive overrelaxation (SOR) arithmetic is carried out. It can be used for verifying the arithmetic and modifying the nonlinear and noise character of the system.

The Ku-band scatterometer onboard HY-2 (SCAT/HY-2) is a pencil-beam radar employing pulse compression techniques to ensure number of the independent measurement samples and the resulted precision of the backscattering coefficient for each resolution cell. In this paper, the system specifications of SCAT/HY-2 are introduced. The signal processing scheme, including pulse compression, resolution cell regroup and the area weighted incoherent average of the backscattered power, is presented and analyzed. Based on the analysis of the resolution cell after pulse compression processing, the radiometric accuracy and surface resolution of the SCAT/HY-2 for all the azimuth angles will be simulated. Simulation and analysis results shows that SCAT/HY-2 can satisfy the specification requirements of HY-2 satellite.

Pulse compression techniques are very attractive in the development of new-generation spaceborne meteorological radars, because it has the advantages to reduce the transmit power requirements and improve the measurement precision by increasing incoherent average samples. Compared with TRMM, which employed a pulsed-CW signal, it is very important to analyze the effect of surface clutter from ranging sidelobes of the returned signal after pulse compression. In this paper, the effect of surface clutter with different antenna sidelobe levels and different ranging sidelobe levels are analyzed in details. Based on the analysis of surface clutter, the requirements for antenna sidelobe level and pulse compression range sidelobe level are proposed.

In order to achieve very low range side-lobe (<-75dB) for pulse compression of spaceborne meteorological radar, the spatial average technique is developed. This technique coherently averages, which corresponding windowed weighting in frequency domain, the scattered signals from several neighbored range resolution cells of higher resolution pulse compression measurements. Some considerations about the design of the basic higher resolution pulse compression are presented. Integral and peak side-lobe level characteristics are analyzed. Relationship between the new and other available techniques of very low side-lobe level pulse compression is also discussed.

This presentation describes some issues about the surface penetrating radar for lunar rover. The radar is proposed for the China's lunar landing program, which is to be conducted after the launch of the lunar satellite.

This presentation describes the specifications and parameters of the radar altimeter and scatterometer for China's Oceanic Dynamic Environment Mission (ODEM) (HY-2, Haiyang-2. "Haiyang" means ocean in Chinese). Some details about the design of these two instruments are also presented. The instrument on-board HY-2 includes a microwave imager (MWI), a dual-band radar altimeter (RA) and Ku-band radar scatterometer (SCAT).

We extend the multilevel fast multipole algorithm (MLFMA) to the case of electromagnetic scattering from an arbitrary number of dielectric and/or perfectly conducting targets in the presence of a half space. This multitarget MLFMA is implemented in an iterative fashion, in which the fields incident on and scattered from each target are updated sequentially by considering each target in isolation, with appropriate field updating to account for intertarget scattering. Each target is analyzed in parallel on a separate computer node, and intertarget interaction is addressed via message passaging between the processors. We also utilize the aforementioned iterative formulation employed for handling interactions between multiple targets to develop a new means of solving the MLFMA matrix equation for an isolated target. This new formulation generally results in significant acceleration in the analysis of scattering from single targets, thereby also accelerating the analysis of scattering from multiple targets (within the context of the iterative multitarget analysis developed).

A novel theorem on the wavelet transform and Hilbert transform (HT) is proposed and applied to extract the instantaneous parameters of energy-limited, real signals. Numerical simulations shows advantages of the presented method in both precision and antinoise performance.