FY-3C/MERSI has some remarkable improvements compared to the previous MERSIs including better spectral response function (SRF) consistency of different detectors within one band, increasing the capability of lunar observation by space view (SV) and the improvement of radiometric response stability of solar bands. During the In-orbit verification (IOV) commissioning phase, early results that indicate the MERSI representative performance were derived, including the signal noise ratio (SNR), dynamic range, MTF, B2B registration, calibration bias and instrument stability. The SNRs at the solar bands (Bands 1–4 and 6-20) was largely beyond the specifications except for two NIR bands. The in-flight calibration and verification for these bands are also heavily relied on the vicarious techniques such as China radiometric calibration sites(CRCS), cross-calibration, lunar calibration, DCC calibration, stability monitoring using Pseudo Invariant Calibration Sites (PICS) and multi-site radiance simulation. This paper will give the results of the above several calibration methods and monitoring the instrument degradation in early on-orbit time.
Medium Resolution Spectral Imager (MERSI) is a keystone instrument onboard Fengyun-3 (FY-3), the second generation of polar-orbiting meteorological satellites in China. The first unit still in operation is FY-3A which was launched on May 27, 2008 in a sun-synchronous morning orbit with a local equator-crossing time of 10:30 AM in descending node. The second unit still in operation is FY-3B which was launched on November 5, 2010, in an afternoon orbit with an equator-crossing time of 1:30 PM in ascending node. FY-3 MERSI provides global coverage on top-of-atmosphere (TOA) radiances used for a broad range of scientific studies of the Earth’s system. Nineteen of the 20 MERSI spectral bands are reflective solar bands (RSBs) from 412 NM to 2130 nm, which cannot be absolutely calibrated onboard. The long-term on-orbit response changes of FY-3A/B MERSI are relatively large at visible bands. A multisite calibration tracking method has been developed to monitor the RSB radiometric response variation, revealing that the overall degradation for 412 nm of FY-3A MERSI is about 43% until June 2014. A daily calibration updating model is developed to recalibrate FY-3A/B MERSI, and the data quality is monitored using SNO targets against Aqua MODIS. This paper demonstrates the radiometric performance of FY-3A/B MERSI RSBs after recalibration accounting for the temporal variation of radiometric response. The recalibrated MERSI shows good agreement with MODIS. For FY-3B MERSI band 1 (470nm), the overall percentage difference (Mean±Std) is within 4%.
With the stable increase of carbon dioxide (CO<sub>2</sub>) concentrations, space based measurements of CO<sup>2</sup>
concentration in lower atmosphere by reflected sunlight in near infrared band has become a hot
research topic at present. Recently, the instruments sensitive to total CO<sub>2 </sub>column data in near-surface
have become available through the SCIAMACHY instrument on ENVISAT and TANSO-FTS on
GOSAT. The developing hyper spectral CO<sub>2</sub> detector in China carried by TANSAT will be launched
in late 2015. Hyper spectral CO<sub>2 </sub>detector is designed to provide global measurements of CO<sub>2</sub> in
lower troposphere. It employs high resolution spectra of reflected sunlight taken simultaneously in
near-infrared CO2 (1.61μm and 2.06μm) and O2 (0.76μm) bands.
Associating climate change with the observation requirements of carbon sources and sinks, the
feasibility of making CO2 column concentration measurements with high-resolution and
high-precision is studied by high resolution atmosphere radiation transfer model. The effects of key
specifications of the hyper spectral CO<sub>2 </sub>detector such as spectral resolution, sampling ratio and
sign-to-noise ratio (SNR) on CO<sub>2 </sub>detection are analyzed combining the scientific requirements of
CO<sub>2 </sub>measurements of China.
The typical characteristics of hyper spectral CO2 detector on TANSAT are grating spectrometer
and array-based detector. To achieve the column averaged atmospheric CO2 dry air mole fraction
(XCO<sub>2</sub>) precision requirements of 1×10<sup>-6</sup>-4×10<sup>-6</sup>, hyper spectral CO<sub>2</sub> detector should provide high
resolution at first to resolve CO<sub>2</sub> absorption lines from continuous spectra of reflected sunlight.
Compared to a variety of simulated spectral resolutions, the spectral resolution of hyper spectral CO<sub>2</sub>
detector on TANSAT can resolve CO<sub>2</sub> spectral features and maintain the moderate radiance
sensitivity. Since small size array detector-based instruments may suffer from undersampling of the
spectra, the influences of spectral undersampling to CO<sub>2 </sub>absorption spectra are studied, the results
indicate that sampling ratio should exceed 2 pixels/FWHM to ensure the accuracy of CO<sub>2 </sub>spectrum.
Signal-to-noise ratio is one of the most important parameters of hyper spectral CO<sub>2</sub> detectors to
ensure the reliability of CO<sub>2 </sub>signal. SNR requirements of CO<sub>2</sub> detector to different detection
precisions are explored based on the radiance sensitivity factors. The results show that it is difficult
to achieve the SNR to detect 1×10<sup>-6</sup>-4×10<sup>-6 </sup>CO2 concentration change in the boundary layer by solar
shortwave infrared passive remote sensing, limited by the instrument development at present.
However, the instrument SNR to detect 1% change in the CO<sub>2</sub> column concentration is attainable.
The results of this study are not only conductive to universal applications and guides on developing
grating spectrometer, but also helpful to have a better understanding of the complexity of CO<sub>2</sub>
The global carbon dioxide observation satellite (TanSat) mission of China is introduced. Two instruments carried by
TanSat including carbon dioxide (CO2) spectrometer with high spectral resolution, termed the TanSat CO2 Spectrometer
(TSCS), and the Cloud and Aerosol Polarize Instrument (CAPI) will make global measurements of atmospheric CO2 with
the high precision of 1% and resolution of 1 km approximately. In this paper, we aim at quantifying the error associated
with aerosol and albedo over China utilizing the new designed parameters of TanSat. Firstly, the latest specifications of
TSCS are analyzed through the observing simulations as well as the retrieval experiments over some areas in China, where
space-based measurements of CO<sub>2</sub> confront the huge challenge induced by atmospheric aerosols which optical depth can
ascend up to more than 1 at wavelengths of 550 nm at certain atmospheric conditions. MODIS aerosol and albedo products
are used in the synthetic measurements. The impacts of both aerosol scattering and surface albedo on CO2 retrieval
accuracy are investigated by applying different retrieval implementation. The errors are estimated for nadir observation
over land with typical solar zenith angle 30° and 60°. Comparisons amongst the three approaches suggest that correctly
treatment of aerosol scattering is necessary to account for the impacts of multiple scattering in order to meet the
requirement of TanSat mission. The development of retrieval algorithm will be continued to the launch of TanSat in late
This paper addresses the issue on airborne image positioning model and its application in FY-3A experiment. First, the FY-3A Medium Resolution Spectral Imager (MERSI)'s viewing vector is derived from MERSI's imaging pattern. Then, the image positioning model is analyzed mathematically in detail which is based on Earth-aircraft geometry. The model parameters are mainly determined by both the sensor - aircraft alignment and the onboard discrete measurements of the positioning and orientation. Flight trials are flown at an altitude of 8300 m over the Qinghai Lake China. It is shown that the image positioning accuracy (about 1~4 pixels) is better than previous methods (more than 7 pixels, [G. J. Jedlovec et al. NASA Technical Memorandum TM - 100352 (1989) and D. P. Roy et al. Int. J. Rem. Sens. 18(9), 1865 - 1887 (1997)]). It is also shown that the model has the potential to hold the image positioning errors within one pixel. The model can operate automatically, and does not need ground control points data. Since our algorithm get the image positioning results through an observation geometric perspective which is in computing the point at which the sensor viewing vector intersects the earth surface, our algorithm assumes the airborne data are from the plain area.
MODIS measurements contain the striping signals in the longwave infrared bands because MODIS is a multi-detector sensor. We describe a wavelet method for recovery of MODIS data from its stripe signals. Our work is organized into four broad sections. Section 1 will introduce wavelet shrinkage method for de-noising noisy data, compare the character of the wavelet method and the FFT method in de-noising processing. The objective of section 2 is to find out the scale of MODIS stripe by the wavelet analysis for MODIS stripe data using continuous wavelet transforms. Section 3 analyses Stripe data pattern for the MODIS level 1B stripe data, present the wavelet shrinkage method for MODIS level 1B data. Section 4 will provide a comparing for MODIS cloud product and atmospheric profile product between the original data and de-striped data.
We can find that there’s been an improvement in MODIS cloud product and atmospheric profile product after de-striping. And we can get more understanding for the stripe regular pattern.