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.

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.

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.

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%.

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.

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.

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%).

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.