An improved wind quality control for the China-France Oceanography Satellite (CFOSAT) scatterometer

Quality control(QC)is an essential procedure in scatterometer wind retrieval,which is used to distinguish good-quality data from poor-quality wind vector cells(WVCs)for the sake of wind applications.The current wind processor of the China-France Oceanography Satellite(CFOSAT)scatterometer(CSCAT)adopts a maximum likelihood estimator(MLE)-based QC method to filter WVCs affected by geophysical noise,such as rainfall and wind variability.As the first Ku-band rotating fan-beam scatterometer,CSCAT can acquire up to 16 observations over a single WVC,giving abundant information with diverse incidence/azimuth angles,as such its MLE statistical characteristics may be different from the previous scatterometers.In this study,several QC indicators,including MLE,its spatially averaged value(MLE_(m)),and the singularity exponents(SE),are analyzed using the collocated Global Precipitation Mission rainfall data as well as buoy data,to compare their sensitivity to rainfall and wind quality.The results show that wind error characteristics of CSCAT under different QC methods are similar to those of other Ku-band scatterometers,i.e.,SE is more suitable than other parameters for the wind QC at outer-swath and nadir regions,while MLE_(m) is the best QC indicator for the sweet region WVCs.Specifically,SE is much more favorable than others at high wind speeds.By combining different indicators,an improved QC method is developed for CSCAT.The validation with the collocated buoy data shows that it accepts more WVCs,and in turn,improves the quality control of CSCAT wind data.

Investigating the occurrence and predictability of pitch angle scattering events at ADITYA-Upgrade tokamak with the electron cyclotron emission radiometer

This paper describes the experimental analysis and preliminary investigation of the predictability of pitch angle scattering(PAS) events through the electron cyclotron emission(ECE)radiometer signals at the ADITYA-Upgrade(ADITYA-U) tokamak. For low-density discharges at ADITYA-U, a sudden abnormal rise is observed in the ECE signature while other plasma parameters are unchanged. Investigations are done to understand this abrupt rise that is expected to occur due to PAS. The rise time is as fast as 100 μs with a single step and/or multiple step rise in ECE radiometer measurements. This event is known to limit the on-axis energy of runaway electrons. Being a repetitive event, the conditions of its repetitive occurrence can be investigated, thereby exploring the possibility of it being triggered and surveyed as an alternate runaway electron mitigation plan. Functional parameterization of such events with other discharge parameters is obtained and the possibility to trigger these events is discussed.PREDICT code is used to investigate the possible interpretations for the PAS occurrence through modeling and supporting the ECE observations. The trigger values so obtained experimentally are set as input criteria for PAS occurrence. Preliminary modeling investigations provide reliable consistency with the findings.

System for Control, Data Collection and Processing in 8 mm Portable Microwave Radiometer-Scatterometer

In this paper we describe a system used to control,collect and process data in an 8 mm portable microwave radiometer scatterometer .We focus on hardware and software design of the system based on a PIC16F874 chip. The system has been successfully used in an 8 mm portable microwave radiometer scatterometer. Compared with other similar systems, the system modularization, miniaturization and intelligentization are improved so as to meet portable instrument requirements.

Validation and accuracy analysis of wind products from scatterometer onboard the HY-2B satellite

The Chinese marine dynamic environment satellite HY-2B was launched in October 2018 and carries a Ku-band scatterometer.This paper focuses on the accuracies of HY-2B scatterometer wind data during the period from November 2018 to May 2021.The HY-2B wind data are validated against global moored buoys operated by the U.S.National Data Buoy Center and Tropical Atmosphere Ocean,numerical model data by the National Centers for Environmental Prediction,and the Advanced Scatterometer data issued by the Remote Sensing System.The results showed that the wind speeds and directions observed by the HY-2B scatterometer agree well with these buoy wind measurements.The root-mean-squared errors(RMSEs)of the HY-2B wind speed and direction are 0.74 m/s and 11.74°,respectively.For low wind speeds(less than 5 m/s),the standard deviation of the HY-2B-derived wind direction is higher than 20°,which implies that the HY-2B wind direction for low wind speeds is less accurate than that for moderate to high wind speed ranges.The RMSE of the HY-2B wind speed is slightly larger in high latitude oceans(60°–90°S and 60°–90°N)than in low latitude regions.Furthermore,the dependence of the residuals on the cross-track location of wind vector cells and the stability of the HY-2B scatterometer wind products are discussed.The wind stability assessment results indicate that a clear yearly oscillation is observed for the HY-2B wind speed bias which is due to seasonal weather variations.In general,the accuracy of HY-2B winds meets the operational precision requirement and is consistent with other wind data.

Comparison between Infrared and Microwave Radiometers for Retrieving Sea Surface Temperature

The basic principles of sea surface temperature （SST） remote sensing using infrared and microwave radiometers are introduced, and the differences between two sensors for retrieving sea surface temperature are investigated. The ground resolution, atmospheric effect, sea surface wind, skin depth and so on have important influence on precision of sea surface temperature retrieved by two sensors. The better understanding of the advantage and disadvantage of sea surface temperature detected by infrared and microwave radiometers would help us to imply SST remote sensing data more effectively and correctly.

Neural network wind retrieval from ERS-1/2 scatterometer data

A neural network methodology is presented to retrieve wind vectors from ERS - 1/2 scatterometer data. The wind directional ambiguities are eliminated by a circular median filter algorithm. All data come from ERS - 1/2 scatterometer data collocated pairs with CMCD4 vector. Comparing the results with CMCD4 and ECMWF wind vector,they agree well, which indicates that it is possible to extract wind vector from the ERS-1/2 scatterometer with the neural network method.

Astudyofanewretrievalalgorithmformeasurementofoceanicwindvectorsfieldusingsatellitemicrowavescatterometer

The Seasat-A satellite scatterometer(SASS) demonstrated very successfully that scatterometers can makeaccurate synoptic measurements of surface wind vectors field over the ocean. The technology is based on the sensitivityof microwave radar back scatter to the ocean waves in centimeter scale created by the action of the surface wind. More-over, the back scatter is anisotropic, therefore, wind speed and direction can be derived from radar measurements attwo or more different azimuths. Owing to the nonlinear nature of scatter model function and the existence of variousnoise sources in the measurements, the retrieval wind results consist of as many as four wind directions. A new algo-rithm is proposed to recover ocean wind field from the SASS normalized cross-section measurement in this paper. Comparison with those estimated from the SASS surface wind analysed by Peteherych et al . (1984) and other referencesshow agreement largely in the wind direction and more exactly in the wind speed.

Sea ice extent retrieval with HY-2A scatterometer data and its assessment

A sea ice extent retrieval algorithm over the polar area based on scatterometer data of HY-2A satellite has been established. Four parameters are used for distinguishing between sea ice and ocean with Fisher＇s linear discriminant analysis method. The method is used to generate polar sea ice extent maps of the Arctic and Antarctic regions of the full 2013-2014 from the scatterometer aboard HY-2A （HY-2A-SCAT） backscatter data. The time series of the ice mapped imagery shows ice edge evolution and indicates a similar seasonal change trend with total ice area from DMSP-F17 Special Sensor Microwave Imager/Sounder （SSMIS） sea ice concentration data. For both hemispheres, the HY-2A-SCAT extent correlates very well with SSMIS 15% extent for the whole year period. Compared with Synthetic Aperture Radar （SAR） imagery, the HY-2A-SCAT ice extent shows good correlation with the Sentinel-1 SAR ice edge. Over some ice edge area, the difference is very evident because sea ice edges can be very dynamic and move several kilometers in a single day.

Application of Tikhonov regularization method to wind retrieval from scatterometer data Ⅱ: cyclone wind retrieval with consideration of rain

According to the conclusion of the simulation experiments in paper I, the Tikhonov regularization method is applied to cyclone wind retrieval with a rain-effect-considering geophysical model function （called CMF＋Rain）. The CMF＋Rain model which is based on the NASA scatterometer-2 （NSCAT2） GMF is presented to compensate for the effects of rain on cyclone wind retrieval. With the multiple solution scheme （MSS）, the noise of wind retrieval is effectively suppressed, but the influence of the background increases. It will cause a large wind direction error in ambiguity removal when the background error is large. However, this can be mitigated by the new ambiguity removal method of Tikhonov regularization as proved in the simulation experiments. A case study on an extratropical cyclone of hurricane observed with SeaWinds at 25-km resolution shows that the retrieved wind speed for areas with rain is in better agreement with that derived from the best track analysis for the GMF＋Rain model, but the wind direction obtained with the two-dimensional variational （2DVAR） ambiguity removal is incorrect. The new method of Tikhonov regularization effectively improves the performance of wind direction ambiguity removal through choosing appropriate regularization parameters and the retrieved wind speed is almost the same as that obtained from the 2DVAR.

An assessment of arctic sea ice concentration retrieval based on “HY-2” scanning radiometer data using field observations during CHINARE-2012 and other satellite instruments

A retrieval algorithm of arctic sea ice concentration （SIC） based on the brightness temperature data of “HY-2” scanning microwave radiometer has been constructed. The tie points of the brightness temperature were selected based on the statistical analysis of a polarization gradient ratio and a spectral gradient ratio over open water （OW）, first-year ice （FYI）, and multiyear ice （MYI） in arctic. The thresholds from two weather filters were used to reduce atmospheric effects over the open ocean. SIC retrievals from the “HY-2” radiom-eter data for idealized OW, FYI, and MYI agreed well with theoretical values. The 2012 annual SIC was calcu-lated and compared with two reference operational products from the National Snow and Ice Data Center （NSIDC） and the University of Bremen. The total ice-covered area yielded by the “HY-2” SIC was consistent with the results from the reference products. The assessment of SIC with the aerial photography from the fifth Chinese national arctic research expedition （CHINARE） and six synthetic aperture radar （SAR） images from the National Ice Service was carried out. The “HY-2” SIC product was 16% higher than the values de-rived from the aerial photography in the central arctic. The root-mean-square （RMS） values of SIC between “HY-2” and SAR were comparable with those between the reference products and SAR, varying from 8.57% to 12.34%. The “HY-2” SIC is a promising product that can be used for operational services.

The study on an Antarctic sea ice identification algorithm of the HY-2A microwave scatterometer data

An Antarctic sea ice identification algorithm on the HY-2A scatterometer（HSCAT） employs backscattering coefficient（σ0） and active polarization ratio（APR） for a preliminary sea ice identification.Then standard deviation（STD） filtering and space filtering are carried out.Finally,it is used to identify sea ice.A process uses a σ0,STD threshold and an APR as sea ice indicators.The sea ice identification results are verified using the sea ice distribution data of the ASMR2 released by the National Snow and Ice Data Center as a reference.The results show very good consistence of sea ice development trends,seasonal changes,area distribution,and sea ice edge distribution of the sea ice identification results obtained by this algorithm relative to the ASMR2 sea ice results.The accuracy of a sea ice coverage is 90.8% versus the ASMR2 sea ice results.This indicates that this algorithm is reliable.

Assessment of the initial sea surface temperature product of the scanning microwave radiometer aboard on HY-2 satellite

HY-2 satellite is the first satellite for dynamic environmental parameters measurement of China,which was launched on 16th August 2011.A scanning microwave radiometer（RM） is carried for sea surface temperature（SST）,sea surface wind speed,columnar water vapor and columnar cloud liquid water detection.In this paper,the initial SST product of RM was validated with in-situ data of National Data of Buoy Center（NDBC） mooring and Argo buoy.The validation results indicate the accuracy of RM SST is better than 1.7 C.The comparison of RM SST and WindSat SST shows the former is warmer than the latter at high sea surface wind speed and the difference between these SSTs is depend on the sea surface wind speed.Then,the relationship between the errors of RM SST and sea surface wind speed was analyzed using NDBC mooring measurements.Based on the results of assessment and errors analysis,the suggestions of taking account of the affection of sea surface wind speed and using sea surface wind speed and direction derived from the microwave scatteromter aboard on HY-2 for SST product calibration were given for retrieval algorithm improvement.

A preliminary assessment of the sea surface wind speed production of HY-2 scanning microwave radiometer

A scanning microwave radiometer（RM） was launched on August 16,2011,on board HY-2 satellite.The six-month long global sea surface wind speeds observed by the HY-2 scanning microwave radiometer are preliminarily validated using in-situ measurements and WindSat observations,respectively,from January to June 2012.The wind speed root-mean-square（RMS） difference of the comparisons with in-situ data is 1.89 m/s for the measurements of NDBC and 1.72 m/s for the recent four-month data measured by PY30-1 oil platform,respectively.On a global scale,the wind speeds of HY-2 RM are compared with the sea surface wind speeds derived from WindSat,the RMS difference of 1.85 m/s for HY-2 RM collocated observations data set is calculated in the same period as above.With analyzing the global map of a mean difference between HY-2 RM and WindSat,it appears that the bias of the sea surface wind speed is obviously higher in the inshore regions.In the open sea,there is a relatively higher positive bias in the mid-latitude regions due to the overestimation of wind speed observations,while the wind speeds are underestimated in the Southern Ocean by HY-2 RM relative to WindSat observations.

Application of Spectral Angle Mapper Classification to Discriminate Hydrothermal Alteration in Southwest Birjand, Iran, Using Advanced Spaceborne Thermal Emission and Reflection Radiometer Image Processing

The purpose of this study is to evaluate the Spectral Angle Mapper （SAM） classification method for determining the optimum threshold （maximum spectral angle） to unveil the hydrothermal mineral assemblages related to mineral deposits. The study area indicates good potential for Cu-Au porphyry, epithermal gold deposits and hydrothermal alteration well developed in arid and semiarid climates, which makes this region significant for Advanced Spaceborne Thermal Emission and Reflection Radiometer （ASTER） image processing analysis. Given that achieving an acceptable mineral mapping requires knowing the alteration patterns, petrochemistry and petrogenesis of the igneous rocks while considering the effect of weathering, overprinting of supergene alteration, overprinting of hypogene alteration and host rock spectral mixing, SAM classification was implemented for argillic, sericitic, propylitic, alunitization, silicification and iron oxide zones of six previously known mineral deposits： Maherabad, a Cu-Au porphyry system; Sheikhabad, an upper part of Cu-Au porphyry system; Khoonik, an Intrusion related Au system; Barmazid, a low sulfidation epithermal system; Khopik, a Cu-Au porphyry system; and Hanish, an epithermal Au system. Thus, the investigation showed that although the whole alteration zones are affected by mixing, it is also possible to produce a favorable hydrothermal mineral map by such complementary data as petrology, petrochemistry and alteration patterns.

Validation and intercomparison of HY-2A/MetOp-A/Oceansat-2 scatterometer wind products

Sea surface winds are of great significance in scientific research. In the last few years,three series of scatterometers were launched to measure these winds,including the Advanced Scatterometer(ASCAT) aboard Meteorological Operational Satellite A(Met Op-A) and Met Op-B,Oceansat-2 Scatterometer(OSCAT),and HY-2A Scatterometer(HY-2A SCAT). Based on buoy wind data,validation and intercomparison of these scatterometers were performed. Scatterometer-derived wind and buoy wind data were collected only if the spatial difference was less than 0.1 degree and temporal difference less than 5 min. After discarding wind direction data outside five times the standard deviation,ASCAT wind products showed high accuracy in both wind speed and direction,with root-mean-square error(RMSE) 0.86 m/s and 17.97 degrees,respectively. HY-2A SCAT nearly meets the mission requirement,with RMSE for wind speed 1.23 m/s and 22.85 degrees for wind direction. OSCAT had poor performance when compared with the others. RMSE for wind speed was 1.54 m/s and 39.86 degrees for wind direction,which greatly exceeds the mission requirement of 20 degrees. In addition,the RMSE for wind direction shows a high-low pattern on buoy wind speed. However,a wind speed range from 14 to 15 m/s was found to be abnormal,and the reason remains unclear. There was no systematic dependency of both wind speed and direction residuals on buoy wind speed and cross-track location of the wind vector cells across the entire range. No seasonal variation was found for any scatterometer.

Comparison of sea surface wind field measured by HY-2A scatterometer and WindSat in global oceans

In this study, we present a comprehensive comparison of the sea surface wind ?eld measured by scatterometer(Ku-band scatterometer) aboard the Chinese HY-2 A satellite and the full-polarimetric radiometer WindSat aboard the Coriolis satellite. The two datasets cover a four-year period from October2011 to September 2015 in the global oceans. For the sea surface wind speed, the statistical comparison indicates good agreement between the HY-2 A scatterometer and WindSat with a bias of nearly 0 m/s and a root mean square error(RMSE) of 1.13 m/s. For the sea surface wind direction, a bias of 1.41° and an RMSE of 20.39° were achieved after excluding the data collocated with opposing directions. Furthermore,discrepancies in sea surface wind speed measured by the two sensors in the global oceans were investigated.It is found that the larger dif ferences mainly appear in the westerlies in the both hemispheres. Both the bias and RMSE show latitude dependence, i.e., they have signi?cant latitudinal ?uctuations.

Verification and recalibration of HY-2A microwave radiometer brightness temperature

HY-2A is the first one of the Chinese HY-2 ocean satellite series carrying a microwave radiometer(RM)to measure sea surface temperature,sea surface wind speed,atmospheric water vapor,cloud liquid water content,and rain rate.We verified the RM level 1B brightness temperature(T B)to retrieve environmental parameters.In the verification,TB that simulated using the ocean-atmosphere radiative transfer model(RTM)was used as a reference.The total bias and total standard deviation(SD)of the RM level 1B TB,with reference to the RTM simulation,ranged-20.6-4.38 K and 0.7-2.93 K,respectively.We found that both the total bias and the total SD depend on the frequency and polarization,although the values for ascending and descending passes are different.In addition,substantial seasonal variation of the bias was found at all channels.The verification results indicate the RM has some problems regarding calibration,e.g.,correction of antenna spillover and antenna physical emission,especially for the 18.7-GHz channel.Based on error analyses,a statistical recalibration algorithm was designed and recalibration was performed for the RM level 1B TB.Validation of the recalibrated TB indicated that the quality of the recalibrated RM level 1B TB was improved significantly.The bias of the recalibrated T B at all channels was reduced to<0.4 K,seasonal variation was almost eradicated,and SD was diminished(i.e.,the SD of the 18.7-GHz channel was reduced by more than 0.5K).

0-10 KM TEMPERATURE AND HUMIDITY PROFILES RETRIEVAL FROM GROUND-BASED MICROWAVE RADIOMETER

Deviation exists between measured and simulated microwave radiometer sounding data. The bias results in low-accuracy atmospheric temperature and humidity profiles simulated by Back Propagation artificial neural network models. This paper evaluated a retrieving atmospheric temperature and humidity profiles method by adopting an input data adjustment-based Back Propagation artificial neural networks model. First, the sounding data acquired at a Nanjing meteorological site in June 2014 were inputted into the Mono RTM Radiative transfer model to simulate atmospheric downwelling radiance at the 22 spectral channels from 22.234 GHz to 58.8 GHz, and we performed a comparison and analysis of the real observed data; an adjustment model for the measured microwave radiometer sounding data was built. Second, we simulated the sounding data of the 22 channels using the sounding data acquired at the site from 2011 to 2013. Based on the simulated rightness temperature data and the sounding data, BP neural network-based models were trained for the retrieval of atmospheric temperature, water vapor density and relative humidity profiles. Finally, we applied the adjustment model to the microwave radiometer sounding data collected in July 2014, generating the corrected data. After that, we inputted the corrected data into the BP neural network regression model to predict the atmospheric temperature, vapor density and relative humidity profile at 58 high levels from 0 to 10 km. We evaluated our model's effect by comparing its output with the real measured data and the microwave radiometer's own second-level product. The experiments showed that the inversion model improves atmospheric temperature and humidity profile retrieval accuracy; the atmospheric temperature RMS error is between 1 K and 2.0 K; the water vapor density's RMS error is between 0.2 g/m^3 and 1.93 g/m3; and the relative humidity's RMS error is between 2.5% and 18.6%.

Evaluation of wind vectors observed by HY-2A scatterometer using ocean buoy observations,ASCAT measurements,and numerical model data

The first Chinese microwave ocean environment satellite HY-2A was launched successfully in August, 201 I. This study presents a quality assessment of HY-2A scatterometer （HYSCAT） data based on comparison with ocean buoy data, the Advanced Scatterometer （ASCAT） data, and numerical model data from the National Centers for Environmental Prediction （NCEP）. The in-situ observations include those from buoy arrays operated by the National Data Buoy Center （NDBC） and Tropical Atmosphere Ocean （TAO） project. Only buoys located offshore and in deep water were analyzed. The temporal and spatial collocation windows between HYSCAT data and buoy observations were 30 min and 25 km, respectively. The comparisons showed that the wind speeds and directions observed by HYSCAT agree well with the buoy data. The root-mean-squared errors （RMSEs） of wind speed and direction for the HYSCAT standard wind products are 1.90 m/s and 22.80°, respectively. For the HYSCAT-ASCAT comparison, the temporal and spatial differences were limited to 1 h and 25 km, respectively. This comparison yielded RMSEs of 1.68 m/s for wind speed and 19.1° for wind direction. We also compared HYSCAT winds with reanalysis data from NCEP. The results show that the RMSEs of wind speed and direction are 2.6 m/s and 26°, respectively. The global distribution of wind speed residuals （HYSCAT-NCEP） is also presented here for evaluation of the HYSCAT-retrieved wind field globally. Considering the large temporal and spatial differences of the collocated data, it is concluded that the HYSCAT-retrieved wind speed and direction met the mission requirements, which were 2 rn/s and 20° for wind speeds in the range 2-24 m/s. These encouraging assessment results show that the wind data obtained from HYSCAT will be useful for the scientific community.

The Performance of Dual-Frequency Polarimetric Scatterometer in Sea Surface Wind Retrieval

The wind retrieval performance of HY-2 A scanning scatterometer operating at Ku-band in HH and VV polarizations has been well evaluated in the wind speed range of 0–25 m s^-1.In order to obtain more accurate ocean wind field,a potential extension of dual-frequency(C-band and Ku-band)polarimetric measurements is investigated for both low and very high wind speeds,from 5 to 45 m s^-1.Based on the geophysical model functions of C-band and Ku-band,the simulation results show that the polarimetric measurements of Ku-band can improve the wind vector retrieval over the entire scatterometer swath,especially in nadir area,with the wind direction root-mean-square error(RMSE)less than 12?in the wind speed range of 5–25 m s^-1.Furthermore,the results also show that C-band cross-polarization plays a very important role in improving the wind speed retrieval,with the wind speed retrieval accuracy better than 2 m s^-1 for all wind conditions(0–45 m s^-1).For extreme winds,the C-band HH backscatter coefficients modeled by CMOD5.N(H)and the ocean co-polarization ratio model at large incidence are used to retrieve sea surface wind vector.This result reveals that there is a big decrease of wind direction retrieval RMSE for extreme wind fields,and the retrieved result of C-band HH polarization is nearly the same as that of C-band VV polarization for low-to-high wind speed(5–25 m s^-1).Thus,to improve the wind retrieval for all wind conditions,the dual-frequency polarimetric scatterometer with C-band and Ku-band horizontal polarization in inner beam,and C-band horizontal and Ku-band vertical polarization in outer beam,can be used to measure ocean winds.This study will contribute to the wind retrieval with merged satellites data and the future spaceborne scatterometer.