Cross-calibration of brightness temperature obtained by FY-3B/MWRI using Aqua/AMSR-E data for snow depth retrieval in the Arctic

This study cross-calibrated the brightness temperatures observed in the Arctic by using the FY-3B/MWRI L1 and the Aqua/AMSR-E L2A.The monthly parameters of the cross-calibration were determined and evaluated using robust linear regression.The snow depth in case of seasonal ice was calculated by using parameters of the crosscalibration of data from the MWRI Tb.The correlation coefficients of the H/V polarization among all channels Tb of the two sensors were higher than 0.97.The parameters of the monthly cross-calibration were useful for the snow depth retrieval using the MWRI.Data from the MWRI Tb were cross-calibrated to the AMSR-E baseline.Biases in the data of the two sensors were optimized to approximately 0 K through the cross-calibration,the standard deviations decreased significantly in the range of 1.32 K to 2.57 K,and the correlation coefficients were as high as 99%.An analysis of the statistical distributions of the histograms before and after cross-calibration indicated that the FY-3B/MWRI Tb data had been well calibrated.Furthermore,the results of the cross-calibration were evaluated by data on the daily average Tb at 18.7 GHz,23.8 GHz,and 36.5 GHz(V polarization),and at 89 GHz(H/V polarization),and were applied to the snow depths retrieval in the Arctic.The parameters of monthly cross-calibration were found to be effective in terms of correcting the daily average Tb.The results of the snow depths were compared with those of the calibrated MWRI and AMSR-E products.Biases of 0.18 cm to 0.38 cm were observed in the monthly snow depths,with the standard deviations ranging from 4.19 cm to 4.80 cm.

Trends of sea surface wind energy over the South China Sea

Studies on climate change typically consider temperature and precipitation over extended periods but less so the wind. We used the Cross-Calibrated Multi-Platform (CCMP) 24-year wind fi eld data set to investigate the trends of wind energy over the South China Sea during 1988-2011. The results reveal a clear trend of increase in wind power density for each of three base statistics (i.e., mean, 90 th percentile and 99 th percentile) in all seasons and for annual means. The trends of wind power density showed obvious temporal and spatial variations. The magnitude of the trends was greatest in winter, intermediate in spring, and smallest in summer and autumn. A greater trend of increase was found in the northern areas of the South China Sea than in southern parts. The magnitude of the annual and seasonal trends over the South China Sea was larger in extreme high events (i.e., 90 th and 99 th percentiles) compared to the mean conditions. Sea surface temperature showed a negative correlation with the variability of wind power density over the majority of the South China Sea in all seasons and annual means, except for winter (41.7%).

Numerical simulation and preliminary analysis on ocean waves during Typhoon Nesat in South China Sea and adjacent areas

Using the wave model WAVEWATCH III(WW3), we simulated the generation and propagation of typhoon waves in the South China Sea and adjacent areas during the passage of typhoon Nesat(2011). In the domain 100°–145°E and 0°–35°N, the model was forced by the cross-calibrated multi-platform(CCMP) wind fi elds of September 15 to October 5, 2011. We then validated the simulation results against wave radar data observed from an oil platform and altimeter data from the Jason-2 satellite. The simulated waves were characterized by fi ve points along track using the Spectrum Integration Method(SIM) and the Spectrum Partitioning Method(SPM), by which wind sea and swell components of the 1D and 2D wave spectra are separated. There was reasonable agreement between the model results and observations, although the WW3 wave model may underestimate swell wave height. Signifi cant wave heights are large along the typhoon track and are noticeably greater on the right of the track than on the left. Swells from the east are largely unable to enter the South China Sea because of the obstruction due to the Philippine Islands. During the initial stage and later period of the typhoon, swells at the fi ve points were generated by the propagation of waves that were created by typhoons Haitang and Nalgae. Of the two methods, the 2D SPM method is more accurate than the 1D SIM which overestimates the separation frequency under low winds, but the SIM method is more convenient because it does not require wind speed and wave direction. When the typhoon left the area, the wind sea fractions decreased rapidly. Under similar wind conditions, the points located in the South China Sea are affected less than those points situated in the open sea because of the infl uence of the complex internal topography of the South China Sea. The results reveal the characteristic wind sea and swell features of the South China Sea and adjacent areas in response to typhoon Nesat, and provide a reference for swell forecasting and offshore structural designs.

Radiometric Characteristics of the Landsat Collection 1 Dataset

This study evaluates the long-term radiometric performance of the USGS new released Landsat Collection 1 archive, including the absolute calibration of each Landsat sensor as well as the relative cross-calibration among the four most popular Landsat sensors. A total of 920 Landsat Collection 1 scenes were evaluated against the corresponding Pre-Collection images over a Pseudo-Invariant Site, Railroad Valley Playa Nevada, United States (RVPN). The radiometric performance of the six Landsat solar reflective bands, in terms of both Digital Numbers (DNs) and at-sensor Top of Atmosphere (TOA) reflectance, on the sensor cross-calibration was examined. Results show that absolute radiometric calibration at DNs level was applied to the Landsat-4 and -5 TM (L4 TM and L5 TM) by –1.119% to 0.126%. For L4 TM and L5 TM, the cross-calibration decreased the radiometric measurement level by rescaling at-sensor radiance to DN values. The radiometric changes, –0.77% for L4 TM, 0.95% for L5 TM, –0.26% for L7 ETM+, and –0.01% for L8 OLI, were detected during the cross-calibration stage of converting DNs into TOA reflectance. This study has also indicated that the long-term radiometric performance for the Landsat Collection 1 archive is promising. Supports of these conclusions were demonstrated through the time-series analysis based on the Landsat Collection 1 image stack. Nevertheless, the radiometric changes across the four Landsat sensors raised concerns of the previous Landsat Pre-Collection based results. We suggest that Landsat users should pay attention to differences in results from Pre-Collection and Collection 1 time-series data sets.

Radiometric cross-calibration of the CBERS-02 CCD camera with the TERRA MODIS

For the application of the CCD camera, the most important payload on CBERS-02, the key is to provide long-term stable radiometric calibration coefficients. Although the vicarious calibration had been proved successful, it had its limitations such as test site requirement and unsuitable for historical data. Cross-calibration is one of the alternative methods, but it needs synchro surface spectrum to achieve spectral band matching factors. Our effort is to probe the influences on these factors. Simulations with a lot of surface spectrum showed that the factors changed with the viewing geometry, atmospheric condition and surface targets. However, simulating with the same viewing geometry and atmospheric condition, the spectral band matching factors of the same or similar surface targets’ spectrum acquired from different dates and different places would like to be consistent to each other within 1%―5%. Thus, the synchro measurement data can be substituted by the same or similar target from other source. Based on this method, using the MODIS as the reference, the cross-calibration was performed for CCD camera. The research demonstrated that the traditional method with single calibration site was inappropriate for CCD camera, since the offsets for its four spectral bands were not zeros. With four calibration sites, these offsets were obtained. And the camera was detected to degrade with dates based on four times of cross-calibrations.

The improvement of cross-calibration of IIM data and band selection for FeO inversion

Chang’E-1(CE-1)Interference Imaging Spectrometer(IIM)dataset suffers from the weak response in the near infrared(NIR)bands,which are the important wavelength for retrieving the minerals and elements of the Moon.In this paper,the cross-calibration was implemented to the IIM hyperspectral data for improving the weak response in NIR bands.The results show that the cross-calibrated IIM spectra were consistent to the Earth-based telescopic spectra,which suggests that the cross-calibration yields acceptable results.For further validating the influence of the cross-calibration on the FeO inversion and searching the optimal bands to retrieve lunar FeO contents,four band selection schemes were designed to retrieve FeO using the original and cross-calibrated IIM spectra.By comparing the distribution patterns and histograms of the IIM derived FeO contents with the Clementine derived FeO,the IIM 891 nm band after cross-calibration showed a higher accuracy in the FeO inversion,hence most useful for lunar FeO inversion.

Cross-calibration on the electromagnetic field detection payloads of the China Seismo-Electromagnetic Satellite

The China Seismo-Electromagnetic Satellite(CSES)deploys three payloads to detect the electromagnetic environment in the ionosphere.The tri-axial fluxgate magnetometers(FGM),as part of the high precision magnetometer(HPM),measures the Earth magnetic vector field in a frequency range from direct current(DC)to 15 Hz.The tri-axial search coil magnetometer(SCM)detects the alternating current(AC)related magnetic field in a frequency range from several Hz to 20 k Hz,and the electric field detector(EFD)measures the spatial electric field in a broad frequency band from DC to 3.5 MHz.This work mainly crosscalibrates the consistency of these three payloads in their overlapped detection frequency range and firstly evaluates CSES’s timing system and the sampling time differences between EFD and SCM.A sampling time synchronization method for EFD and SCM waveform data is put forward.The consistency between FGM and SCM in the ultra-low-frequency(ULF)range is validated by using the magnetic torque(MT)signal as a reference.A natural quasiperiodic electromagnetic wave event verifies SCM and EFD’s consistency in extremely low-frequency and very low-frequency(ELF/VLF)bands.This cross-calibration work is helpful to upgrade the data quality of CSES and brings valuable insights to similar electromagnetic detection solutions by low earth orbit satellites.

Cross-calibration of high energetic particles data——A case study between FY-3B and NOAA-17

Cross-calibration of high energetic particle data is a primary requirement for the availability of multi-instrument, multi-spacecraft data. II also can provide a method to verify relative reliability of data from single satellite measurement. This pa- per presents a case study of energetic particles data cross-calibration between FY-3B and NOAA-17. A generally good agree- ment is acquired in the flux values and distribution trend of 2.5-6.9 MeV protons and 0.3-1.1 MeV electrons between FY-3B and NOAA-17 satellites. It suggests that the data observed by FY-3B is properly cross-calibrated. We can also confirm that energetic particles data observed by FY-3B satellite is available.

Water target based cross-calibration of CBERS-02 CCD camera with MODIS data

In order to make quantitative watercolor sensing with China-Brazil Earth Resources Satellite (CBERS-02) CCD camera, the MODIS data with higher accuracy is used to cross-calibrate the CCD camera over water targets. In homogeneous clear water area, two pairs of images obtained over the same area on the same day by the two sensors are selected. The top-of-atmosphere (TOA) radiances of the multispectral bands of CCD are calculated with the water and aerosol parameters from MODIS based on a water-atmosphere radiative transfer algorithm. The stripes in CCD image that caused by unequal response of the CCD array detectors are firstly removed before making the cross-calibration. The same part of CCD detectors is selected for the calibrations in the two images to eliminate the residual error of destriping and uniformity correction for the focus plane irradiance. It is shown that the calibration results from two different images are consistent. The error of this method is about 5%.

A twin-channel difference model for cross-calibration of thermal infrared band

Based on the conduction and transformation of the thermal infrared radiative transfer equation of water target,a twinchannel difference model(DM) was proposed to improve the calibration precision by conquering the limitation that the atmospheric condition when image is acquiring cannot be truly obtained in the traditional radiometric simulation calibration method.The analysis of surface,atmosphere and top-of-atmosphere(TOA) radiative energy decomposition demonstrated that the apparent TOA radiance of the uncalibrated channel is the differential combination of two reference channels.The DM avoids impacts from atmospheric temperature and density.The only impact is from water vapor(WV) content.Based on the fitting error analysis of 742 mid-latitude atmospheric profiles(column WV content:0-5×10 3 atm cm) selected from TIGR database,the DM is insensitive to WV content.The maximum error is less than 0.2 K when the view zenith angels(VZAs) of reference channels and uncalibrated channel are less than 30.The error becomes 0.3 K when VZAs range from 30 to 40 and 0.6 K when VZAs are in 40-50.Because the uncertainty increases when VZAs are larger than 50,the best range of VZAs is 30-50.The vicarious calibration results at Lake Qinghai field indicated that the calibration precision of the DM cross-calibration by using MODIS bands 31 and 32 as reference channels to calibrate IRS band 08 is similar to that of vicarious calibration.Therefore,the DM is a reliable alternative tool for sensor on-orbit calibration and validation with high precision and frequency.

Radiometric Cross-Calibration for Multiple Sensors with the Moon as an Intermediate Reference

The instrument cross-calibration is an effective way to assess the quality of satellite data. In this study, a new method is proposed to cross-calibrate the sensors among satellite instruments by using a RObotic Lunar Observatory(ROLO) model and Apollo sample reflectance in reflective solar bands(RSBs). The ROLO model acts as a transfer radiometer to bridge between the instruments. The reflective spectrum of the Apollo sample is used to compensate for the difference in the instrument's relative spectral responses(RSRs). In addition, the double ratio between the observed lunar irradiance and the simulated lunar irradiance is used to reduce the difference in instrument lunar viewing and illumining geometry. This approach is applied to the Moderate Resolution Imaging Spectroradiometer(MODIS), the Sea-Viewing Wide Field-of-View Sensor(Sea Wi FS), and the Advanced Land Imager(ALI) on board three satellites, respectively. The mean difference between MODIS and Sea Wi FS is less than 3.14%, and the difference between MODIS and ALI is less than 4.75%. These results indicate that the proposed cross-calibration method not only compensates for the RSR mismatches but also reduces the differences in lunar observation geometry. Thus,radiance calibration of any satellite instrument can be validated with a reference instrument bridged by the moon.

On joint analysing XMM-NuSTAR spectra of active galactic nuclei

A recently released XMM-Newton note revealed a significant calibration issue between nuclear spectroscopic telescope array(NuSTAR)and XMM-Newton European Photon Imaging Camera(EPIC)and provided an empirical correction to the EPIC effective area.To quantify the bias caused by the calibration issue in the joint analysis of XMM-NuSTAR spectra and verify the effectiveness of the correction,in this work,we perform joint-fitting of the NuSTAR and EPIC-pn spectra for a large sample of 104 observation pairs of 44 X-ray bright active galactic nuclei(AGN).The spectra were extracted after requiring perfect simultaneity between the XMM-Newton and NuSTAR exposures(merging good time intervals(GTIs)from two missions)to avoid bias due to the rapid spectral variability of the AGN.Before the correction,the EPIC-pn spectra are systematically harder than the corresponding NuSTAR spectra by■subsequently yielding significantly underestimated cutoff energy E_(cut)and the strength of reflection component R when performing joint-fitting.We confirm that the correction is highly effective and can commendably erase the discrepancy in best-fitΓ,E_(cut),and R.We thus urge the community to apply the correction when joint-fitting XMM-NuSTAR spectra,but note that the correction is limited to 3–12 keV and therefore not applicable when the soft X-ray band data are included.Besides,we show that as merging GTIs from two missions would cause severe loss of NuSTAR net exposure time,in many cases,joint-fitting yields no advantage compared with utilizing NuSTAR data alone.Finally,We present a technical note on filtering periods of high background flares for XMM-Newton EPIC-pn exposures in the small window(SW)mode.

Verification of Fengyun-3D MWTS and MWHS Calibration Accuracy Using GPS Radio Occultation Data

The newly launched Fengyun-3D(FY-3D)satellite carries microwave temperature sounder(MWTS)and microwave humidity sounder(MWHS),providing the global atmospheric temperature and humidity measurements.It is important to assess the in orbit performance of MWTS and MWHS and understand their calibration accuracy before using them in numerical weather prediction and many other applications such as hurricane monitoring.This study aims at quantifying the biases of MWTS and MWHS observations relative to the simulations from the collocated Global Positioning System(GPS)radio occultation(RO)data.Using the collocated FY-3C Global Navigation Satellite System Occultation Sounder(GNOS)RO data under clear-sky conditions as inputs to Community Radiative Transfer Model(CRTM),brightness temperatures and viewing angles are simulated for the upper level sounding channels of MWTS and MWHS.In order to obtain O–B statistics under clear sky conditions,a cloud detection algorithm is developed by using the two MWTS channels with frequencies at 50.3 and 51.76 GHz and the two MWHS channels with frequencies centered at 89 and 150 GHz.The analysis shows that for the upper air sounding channels,the mean biases of the MWTS observations relative to the GPS RO simulations are negative for channels 5–9,with absolute values<1 K,and positive for channels 4 and 10,with values<0.5 K.For the MWHS observations,the mean biases in brightness temperature are negative for channels 2–6,with absolute values<2.6 K and relatively small standard deviations.The mean biases are also negative for channels 11–13,with absolute values<1.3 K,but with relatively large standard deviations.The biases of both MWTS and MWHS show scan-angle dependence and are asymmetrical across the scan line.The biases for the upper air MWTS and MWHS sounding channels are larger than those previously derived for the Advanced Technology Microwave Sounder.