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Calibration for the Solar Reflective Bands of Medium Resolution Spectral Imager Onboard FY-3A Xiuqing Hu,Ling Sun,Jingjng Liu,Lei Ding,Xianghua Wang,Yuan Li,Yong Zhang,Na Xu,and Lin Chen

Abstract—The Medium Resolution Spectral Imager(MERSI) is a key instrument onboard Fengyun-3(FY-3),the second gen-eration of polar-orbiting meteorological satellites in China.This paper summarizes the knowledge of MERSI instrument in terms of sensor design,calibration algorithm,prelaunch and on-orbit characterization,and performance verification.The calibration monitoring of its reflective solar bands(RSBs)is primarily con-ducted using a visible onboard calibrator and found that it has a significant degradation on the order of10%in its shorter RSB bands(<500nm),with the largest in band8of about20%during the past two years.However,the performance at longer wavelength bands is relatively stable with a change of less than5%.It is shown that the postlaunch calibration of the two short-wavelength in-frared bands has frequentfluctuations because of random jumps in their electronic gains.These results are consistently verified by two kinds of vicarious calibration(VC)methods:China Ra-diometric Calibration Sites VC and intercalibration using Terra/ Moderate Resolution Imaging Spectroradiometer over Dunhuang desert.The overall uncertainty in the MERSI top-of-atmosphere radiance or reflectance is less than5%.These results provide the important reference and evaluation for the update of the FY-3A/ MERSI calibration coefficients.

Index Terms—Degradation rate,instrument monitoring, Medium Resolution Spectral Imager(MERSI),solar reflective band calibration,vicarious calibration(VC).


T HE SOLAR energy reflected from the Earth contains valuable information on its ecological,hydrological,and meteorological conditions.In1990s,NASA began its Earth Ob-serving System(EOS)to observe both reflected and thermally emitted radiation from the Earth’s atmosphere from ultraviolet to microwave wavelengths[1]–[3].One of the EOS instru-

Manuscript received November1,2011;revised March30,2012and June12,2012;accepted August4,2012.Date of publication November12, 2012;date of current version November22,2012.This work was supported in part by the Chinese Ministry of Science and Technology(MOST)through Projects2010CB951600and2010CB950802,by MOST through Project863 (ID2007AA12Z145),by the Ministry of Finance(ID GYHY200906036) through the Society Welfare Project(Meteorology),and International Science &Technology Cooperation Program of China(2010DFA21140).

X.Hu is with the National Satellite Meteorological Center,China Meteoro-logical Administration,Beijing100081,China(e-mail:[email protected]). L.Sun,J.Liu,Y.Li,Y.Zhang,N.Xu,and L.Chen are with the National Satellite Meteorological Center,China Meteorological Administration,Beijing 100081,China(e-mail:[email protected];[email protected];[email protected] gov.cn;[email protected];[email protected];[email protected]). L.Ding and X.Wang are with Shanghai Institute of Technical Physics, Chinese Academy of Sciences,Shanghai200083,China(e-mail:[email protected] sitp.ac.cn;[email protected]).

Color versions of one or more of thefigures in this paper are available online at http://ieeexplore.ieee.org.

Digital Object Identifier10.1109/TGRS.2012.2214226ments is the Moderate Resolution Imaging Spectroradiometer (MODIS)which has36spectral bands with nadir geometric instantaneousfields of view of250,500,and1000m[4]–[6].It inherited from the Advanced Very High Resolution Radiometer (A VHRR)and the High Resolution Infrared Sounder unit on-board the National Oceanic and Atmospheric Administration’s satellite the Nimbus-7Coastal Zone Color Scanner,SeaStar-SeaWiFS,and the Landsat Thematic Mapper.Other similar international instruments developed by some space agencies include the Global Imager onboard the Advanced Earth Ob-serving Satellite II which was launched on December14,2002 [7]–[10]and the Medium Resolution Imaging Spectrometer instrument on ENVISAT which was launched on March1,2002 [11],[12].China began independently with her own meteoro-logical satellite program in the1980s whose initial activities are with Fengyun-1series satellites,which carried itsfirst generation A VHRR-like sensor—Multispectral Visible Infrared Scanning Radiometer(MVISR).The Medium Resolution Spec-tral Imager(MERSI)is the latest generation imager onboard Fengyun-3(FY-3),the second generation of polar-orbiting me-teorological satellites in China.

MERSI and Visible InfRared Radiometer(VIRR)are two major multispectral imaging instruments onboard FY-3satellite in China[13].The VIRR is inherited from MVISR of thefirst generation of China’s polar-orbiting meteorological satellite (FY-1)and has one band different from MVISR.MERSI is a completely new sensor and will be further enhanced in the fourth satellite in FY-3series,which includes more bands at the infrared region,higher detection sensitivity,and higher calibration accuracy.It will also cover the function of VIRR, which will be eliminated in the fourth FY-3satellite.Thefirst MERSI was launched on May27,2008,onboard the FY-3A satellite.It is operated in a sun-synchronous morning orbit with a local equator-crossing time of10:30A.M.in descending node. The second MERSI was launched on November5,2010,on-board the FY-3B satellite in an afternoon orbit with an equator-crossing time of1:30P.M.in ascending node.MERSI was designed and developed based on the requirements of Chinese user and science community to provide continuous global data for the studies of both short-and long-term changes in the Earth system.Its spectral bands and spatial resolutions were selected in order to continue and enhance the observations of previous sensors such as FY-1C/1D MVISR and FY-3VIRR.There are approximately20science data products generated from the observations of all the MERSI instruments[13].With China’s morning and afternoon satellites,two MERSI instruments have greatly enhanced the ability to monitor global environment and climate changes.


To ensure the quality of the data products,both MERSIs have

undergone extensive prelaunch calibration and characterization, including various tests at the component level,subsystem level, and thermal vacuum(TV)system level.In orbit,the instrument is calibrated and characterized using its onboard calibrators:a visible(VIS)onboard calibrator(VOC),space view(SV)and a v-groovedflat panel blackbody(BB)[14]–[16].In addition to this,several vicarious calibration(VC)methods are used to monitor the instrument stability and degradation on orbit.For earlier operational instrument A VHRR,several VCs were used and kept frequently updated using the reflectance information over the Libyan desert,cloud[17]–[24]and intercalibration with EOS/MODIS[25],[26]since it did not have an onboard calibration(OBC)device.The desert VC assumes a stable bidirectional reflectance distribution function(BRDF)at the calibration sites withoutfield campaign measurement which may not be valid due to cloud and water vapor variability in the regions[18]–[22].The VC method using natural earth target withfield measurement wasfirst developed by the Remote Sensing Group at The University of Arizona[27]in1980s.A similar method based on China Radiometric Calibration Sites (CRCS)–Dunhuang site has been adopted into the baseline approach for the Chinese Fengyun series satellites since the late of1990s[28]–[30].For MODIS,an onboard solar diffuser (SD)with an SD stability monitor was deployed for calibrating its solar bands[31],[32].MODIS has also been scheduled for periodical lunar observations to track the calibration stability of its reflective solar bands through spacecraft roll maneuvers [33].It has been demonstrated that MODIS meets the absolute calibration accuracy requirement of2%in reflectance[34], [35]and therefore has become the common reference instru-ment for intercalibration with other instruments.MERSI relies on simultaneous nadir observations(SNOs)and desert-based intercalibration using MODIS as the calibration reference to verify the CRCS calibration[25],[26].The dedicated lunar observations by SeaWiFS can achieve a stable VIS channel calibration and got calibration stability better than0.07%for six years after launch[36]–[39]through rigorous calibration efforts.However,it is difficult for MERSI to conduct this kind of lunar observation maneuver and is expected to realize this method in future satellite designs.

This paper is organized as follows.The next section describes the MERSI instrument.Section III describes the MERSI cali-bration algorithm.In Section IV,the prelaunch calibration and characterization of MERSI are presented.In Section V,three methods are presented for monitoring the in-flight calibration performance,and an integrated result analysis is provided.The last section is the conclusion.


The MERSI was manufactured by Shanghai Institute of Technical Physics(SITP),Chinese Academy of Sciences[16]. Thefirst MERSI(MERSI-1)onboard the three FY-3satellites has20spectral bands,of which19are the solar reflective bands covering the wavelength range from0.4to2.1μm and only one is the thermal emissive band covering10–12.5μm.Fig.1 shows the MERSI observation sketch of each scanning of Earth





Fig.2.Real instrument photograph of two MERSI modules.(1)Left is the VOC seeing from the front.(2)Right is the instrument main optical–mechanical component.

utilize p-i-n photovoltaic silicon diodes.The SWIR has photo-voltaic HgCdTe detectors,and LWIR bands use photoconduc-tive HgCdTe.

The design of the MERSI includes two VIS OBC compo-nents:the VOC and the SV .The SV provides the dark signal.The VOC is the first onboard VIS calibration prototype device for Fengyun series sensors [15].Fig.4shows the VOC con-figuration.It is composed of three main optical components:a 6-cm-diameter integrating minisphere,a beam expanding sys-tem,and trap standard detectors.There are two halogen–tungsten lamps in the minisphere.The sunlight is congregated and imported into the minisphere by an incident light cone.The beam expanding system includes a flat mirror and a parabola which enable the small beam output from minisphere to fill a large entrance aperture of MERSI.The output light from mini-sphere is reflected by the flat mirror and then collimated by the overfilled parabola to create a quasi-Gaussian beam.This beam is the MERSI calibration beam.The trap standard detectors stow the edge of the exit of VOC,including the four silicon de-tectors with the same filter designs as some bands of the MERSI (470,550,650,and 865nm)and one panchromatic detector with no filter.The VOC is mounted on the side of the main in-strument,allowing the scanner to view the exit of VOC,and can observe sun signal when the satellite passes over the South Pole.

The light source from the internal lamps or exterior sun-light is collected and uniformed by the integrating minisphere and then collimated into parallel lights by a beam expanding system.The parallel lights from the expanding system fill the entrance aperture of MERSI and are viewed at each scan line.However,VOC readings are essentially zero except when the lamps are turned on or the sun enters the light cone.The VOC is used to monitor the system radiometric response changes which arise either from the MERSI degradation or a change in the output of VOC.Therefore,the output of VOC must be independently monitored.This is the task of the trap detectors which are directly traceable to the radiance output of the VOC.The full-aperture onboard BB is a V-groove design that have been black anodized to provide a high effective emissivity.In addition to the BB,the scan mirror views space each scan line,thereby enabling a two-point radiometric calibration of the thermal band every scan.


For a spaceborne observation,the apparent reflectance at the top of atmosphere (TOA)of an Earth scene ρtoa at wavelength can be determined with

ρtoa =π·L toa / μ·E 0

D 2ES (1)where L toa is the scene radiance measured by each MERSI

solar reflective band,μis the cosine of the solar zenith angle θs ,E 0is the in-band solar irradiance at a distance of 1AU,and D ES is the Earth–Sun distance in astronomical units.The scene radiance (in units of W ·m −2·sr −1·qμm −1)is given by

L toa =(DN −DN 0)·k (t )


where DN is the MERSI signal and DN 0is the signal in the dark.For each MERSI scan,DN 0is measured as the telescope views the black interior of the instrument,and k (t )is the radiance calibration coefficient at time t .There are two possible approaches to handle the variation of the instrument


2012 Fig.3.Instrument optical design sketch map of MERSI main optical–mechanical module.(a)Interior optical configuration of MERSI and light passing.

(b)Detector layout of each band in the focal


Fig.4.Schematic of the MERSI VIS onboard calibrator.The left is the vertical section sketch map.The calibrator is composed of the motherboard, the light cone congregation system,minisphere,plane mirror,parabolic lens, and trap detectors.The MERSI will scan the radiance from parabolic lens.The right is front seeing and also faces to the scanner of MERSI.

calibration with time:Thefirst one is to frequently update the calibration coefficients,and the second one is to simulate their evolution with time using several calibration results.The former method is to use the coefficient calculated from the prelaunch calibration or the instantaneous gain coefficients derived from the onboard radiometric calibration.This method may lead to afluctuation of the calibration coefficient k because of the uncertainty in the instantaneous data.The MERSI operational calibration is based on the simulated evolution of calibration coefficient with time using previous historical calibration coef-ficients.In the modeling,the sensor degradation and a reference gain(e.g.,the gain coefficient valid for a reference time)are modeled for a given set of instantaneous gain coefficients and a mathematical representation of the gain variation with time.

Usually,the optical component is known to degrade ex-ponentially in the space environment[38].The radiometric calibration model for MERSI is designed to incorporate the prelaunch laboratory/outdoor solar calibration of the instrument with on-orbit changes over time as follows:

k(t)=k(t0)·F d(t−t0)




where k(t0)is the calibration coefficient at time t0and F d(t−t0)is the degradation rate function of the MERSI radiometric sensitivity.k(g)is the prelaunch calibration coefficient(in W·m−2·sr−1μm−1·DN−1),g is the electronic gain,α(t0)is a vi-carious correction(dimensionless)to the prelaunch calibration on thefirst day of on-orbit operations(t0),and the coefficients B0(dimensionless),B1(in day−1),and B2(in day−2)are used to calculate the change in radiometric sensitivity for the band at a given number of days(t−t0)after the start of operations. These B coefficients are determined from a series absolute


calibration coefficients(CRCS VCs)or relative calibration trend(VOC monitoring and others)during one period(more than six months).For MERSI,thefirst starting date of t0is the day of thefirst Earth image,which occurred on June4,2008,for FY-3A and November12,2010,for FY-3B.The k(g)·α(t0)is the initial absolute calibration coefficient at t0.The calibration coefficient is relatively adjusted based on(3)gradually after t0. The k(g)·α(t0)may be changed at some time in the future when wefind that the initial absolute calibration coefficient exists with apparent bias at historical t0.When the new initial absolute calibration coefficient is updated,t0is also changed into new corresponding starting date.The determination of the vicarious correction is based on the CRCSfield campaign [29],[30].The radiometric changes in the instrument on orbit seem to be adequately modeled by the B0,B1,and B2terms in(3)only for a specific period.For this reason,α(t0)will change with the different time period and is dependent on time because of the change of the MERSI radiometric sensitivity with time period.Strictly speaking,the changes in the radio-metric sensitivity for each band are not tracked in orbit using single quadratic curves shown in(3).The actual curves are the combination of linear and quadratic curves pieced together. In addition,this kind of modeling may not work due to the instrument setting change and anomalies.The MERSI on-orbit calibration relies on monitoring of VOC minisphere aging and instrument degradation and is verified by the CRCS VCs and the cross-calibration with MODIS.Level1(L1)data users of MERSI do not need to care about which calibration method is applied and will directly use thefinal calibration coefficient in the L1hierarchical data format granulefile for the conversion from digital numbers(DNs)into apparent reflectance.

The raw imagery of MERSI displays an apparent detector-to-detector striping due to the different response function from the multidetectors and also has banding stripes generated in the consecutive scanning by two different sides of the K-mirror. In order to improve the appearance of the MERSI image and to simplify the radiometric calibration only on the bands rather than on the detector,the destripe processing of raw data is conducted before the radiometric calibration.Usually,there are three major approaches developed for removing the detector-to-detector stripes and mirror-side stripes(banding)in satellite images.Thefirst one is to construct afilter for removing the stripe noise at a given frequency[40],[41].The second approach is to use the wavelet analysis which has been recently applied to remove stripe noise[42].The third approach is to examine the distribution of DNs for each sensor and adjusts this distribution to one reference distribution[43].Thefirst two methods are difficult to be performed in the operational processing.Thus,the empirical distribution function(EDF) matching algorithm is applied to the data preprocessing system (DP2S)of MERSI.The EDF-matching algorithm assumes that,within a large scene,the distribution of the intensity of the Earth radiation incident on each detector will be similar[44]. Global MERSI data during the several days(usually ten days) are used to generate the cumulative distribution function via the offline analysis.The histogram matching maps the EDF of each detector to one reference EDF for one band.A normalization lookup table is created for each detector to map every DNx to a referenced DNx’.We make statistic of the lookup table offline every day and analyze its change.The lookup table will be updated when wefind that it has more than5%change and the image striping is heavily increased by eye looking.Generally, it is updated every three months.

The objective of detector equalization,or“relative”radio-metric calibration,is to reduce striping effects by establishing a reference,based on a single detector,and then shifting and scal-ing the detector responses to match the reference detector.After the image striping normalization,the radiometric calibration is simplified into the band level of MERSI.After the detector equalization,we do not need to worry about the complicated multidetector and banding issue,and the calibration can just be conducted as the band-based.The aforementioned destripe processing is done during the L1data generation,and the L1 data users do not need to apply this processing by themselves. IV.P RELAUNCH C HARACTERIZATION AND C ALIBRATION

A comprehensive testing program was executed on the MERSIflight model(FM)by SITP before it was launched[16]. These tests had two purposes.Thefirst was to demonstrate com-pliance with the owner’s performance required specifications. The second,and perhaps the most important purpose,was to supply the extensive characterization data needed to convert the digital output from the MERSI to geometrically located calibrated radiance.The tests conduct characterization of the instrument’s physical and performance parameters,including spatial,spectral,radiometric,and stray light response.The TV and ambient tests are performed,and more than1T

B of data is obtained from the FM.The summary below is the best estimate at this time of the instrument performance.Updates may be made as more information,and improved algorithms are developed.Prelaunch characterization provides an initial set of parameters which serves as a reference for monitoring the in-orbit performance and/or in-orbit calibration as well as an initial function to be used for data processing to basic physical values.

A.Spectral Characterization

The relative spectral response(SRF)function was acquired in two different environments.Solar reflective bands were ac-quired in a clean room,and thermal emissive band was acquired during the TV system level testing.The SRFs in the VIS to NIR spectral bands are shown in Fig.5from the prelaunch measurement.The second and third columns of Table II gave the center wavelength and the bandwidth in required specifi-cation which are defined as the midpoint and the wavelength range.The MERSI out-of-band response was characterized us-ing broadbandfilters as well as scanning the double monochro-mator across the out-of-band spectral region over which each detector responds.The out-of-band response is defined as the ratio of the integrated response outside the1%of peak response points(upper and lower)to the integrated response inside the 1%response points.Preliminary results of FY-3A MERSI show an excellent out-of-band rejection with no major anomalies other than band8.


Fig.5.FY-3B/MERSI VIS and NIR SRF profiles acquired at system level dur-ing the prelaunch characterization testing at nominal instrument temperature.



Fig.6.Photograph of the prelaunch outdoor SRBC for FY-3A/MERSI at

Dali in December 2006.The MERSI measurements at the nadir to a serial of different level reference panels were conducted when the solar light illuminated the panels and was baffled.There are 16difference level panels in each measurement,and this took about 15min and was set at 15-min interval.The total measurements were conducted more than 30times from Beijing time 8:00A .M .to 5:00P .M .

into several radiance levels,and MERSI signal response for them was acquired.The resulting instrument response was then fit to a second-order polynomial to obtain the instrument response function and evaluate the nonlinear characteristics.To evaluate the nonlinear characteristics,we analyzed the significance of the quadratic term eval-uated with the relation between the radiances and DNs based on data in the laboratory SIS and TV testing of the instrument radiometric response.C.Prelaunch Outdoor SRBC Calibration

MERSI cannot provide an absolute calibration reference on orbit since the uncertainty of the prelaunch calibration and the transfer to orbit is not known.The first calibration coefficients are based on the measurements of a uniform integrating sphere source with several output levels scanned by MERSI in the laboratory.The laboratory calibration also gives the primary dynamic range at all bands,and it is adjusted based on the out-door solar calibration characterization procedure.A preflight solar-radiation-based calibration (SRBC)which is similar to the SeaWiFS method [36],[37]was made for the MERSI in Dali,China,by the instrument manufacturer (see Fig.6).For the SRBC measurements,the sun is the source of irradiance,and MERSI viewed the solar irradiance reflected from a set of the 16reference Spectralon panels with different reflective levels (from 5%to 99%)on each panel.Combined with digital counts from the instrument during these panel measurements,the calibration coefficients for the MERSI bands were determined.From (2),the calibration coefficient of the MERSI can be calculated by

k (g )=

L (λ)(DN −DN 0)


HU et al.:CALIBRATION FOR THE SOLAR REFLECTIVE BANDS OF MERSI ONBOARD FY-3A4921 where L(λ)is the averaged radiance at the MERSI bands

viewing the reference panels









where R(λ)is the SRF of the MERSI band,λ1andλ2are the beginning and the end wavelength of the SRF,and L(λ)is the solar reflective spectral radiance from the panel given by







where E0(λ)is the TOA solar irradiance,D2is the Earth–Sun distance in astronomical units,F(θi,λ)is the bidirectional reflectance factor of the reference panel with a solar zenith angle ofθi,and T(λ)is the transmittance of the direct solar beam by the atmosphere(dimensionless).A combination of (4)–(6)can allow for solving k and yield
















In order to calibrate MERSI via a set of the reference panels using the solar source,the sensor and the electronic module have to be taken outside.The MERSI instrument vendor SITP claimed that this ground measurement was done to check the appropriate gain settings in the laboratory using the true solar irradiance.The calibration also required the measurements using a CE318sun photometer to determine the transmittances of principal atmospheric constituents.Fig.7shows the at-mosphere transmittance results from the interpolation of the sun-photometer measurement combined with the MODTRAN model[45]and the Langley plot[46],[47]using the MERSI measurements of all the reference panels.Fig.8shows a radiometric calibration regression plot of the eighth band of FY-3A MERSI.The SRBC calibration line is close to linear. The primary uncertainties in the outdoor measurements are the transmission of the atmosphere and the reflectance of the reference panels.The SRBC provided values of the coefficient k(g),which can be compared with the preflight integrating sphere absolute radiance calibration from the laboratory.There are some risks and disadvantages associated with the solar-based method of calibrating a sensor.The instrument optical components can be contaminated when they are exposed to the environment.Clear sky conditions are required with a very low aerosol loading in which that the atmospheric transmittance measurements can be made very accurately.

Finally,this outdoor SRBC calibration needs to be trans-ferred to the orbit.The VOC provides the transfer bridge through the next two steps.Thefirst step is that outdoor SRBC calibration standard is transferred to the VOC radiance

output Fig.7.Atmospheric transmittances during the prelaunch outdoor calibration experiment in Dali on December24,2006.The red star symbols give the results that are derived from the Langley plot using the MERSI measurements of all the reference panels.The curve gives the calculated atmospheric transmittance spectrum based the atmospheric attenuation measurement from the sun pho-tometer combined with the MODTRAN radiative transfer


Fig.8.Prelaunch calibration regression plot between the input radiance and the DN of the band8of FY-3A MERSI based on the outdoor SRBC calibration measurement conducted in Dali in December2006.

when its internal lamps turn on before the launch.The following step is conducted just after the launch when we assume that the radiance output of the VOC with turning on the lamps is not changed.The initial change of response of MERSI to the VOC after launch is used to tune the calibration coefficient from outdoor SRBC calibration before launch.

So,the most important thing is to require an estimate of the relative change in MERSI response to the VOC with turning on the lamps at the prelaunch and itsfirst VOC measurements on orbit.These results of the preflight calibration and characteriza-tion of MERSI in laboratory and outdoor provide the nominal calibration coefficient with the above tuning and provide the







4923 Fig.9.FY-3A MERSI radiometric response degradation derived from the VOC observation monitoring from July1,2008to July17,2011.(a)MERSI VOC’s output normalized radiance when the interior lamps are turned on is monitored byfive trap detectors at the wavelength of the panchromatic and470,550,650,and 865nm.(b)Derived response degradation of MERSI17solar reflective bands from MERSI outputs of scanning VOC at different dates when the interior lamps are turned on.

or irradiance cannot be measured exactly.However,it is a rela-tively stable source and monitored by trap detectors.So,VOC can be used to monitor the response relative change of MERSI. Fig.9shows the MERSI radiometric response degradation from VOC during three years from July1,2008,to July15,2011. The degradation of interior lamp illumination was detected by the trap detectors.Fig.9(a)shows the radiance output of the MERSI VOC when the interior lamps turn on at different dates.In order to compare with other VC calibrations at the same beginning,the normalized time point is set on July1, 2008,because thefirst VC calibration was conducted nearly in September2008.Since July1,2008,the lamp illumination in VOC has more than5%degradation in all spectral bands and the instrument has more than10%degradation for the wavelength less than550nm.After deducting the VOC output source change from MERSI scanning VOC signal,the response degradation rate of all MERSI SRB bands was derived,as shown in Fig.9(b).It is found that the response degradation is more than10%at bands1(470nm),8(412nm),9(443nm), 10(490nm),and11(520nm)since its launch.The greatest degradation is at band8(412nm),which is nearly20%during three years.Two green bands(550and565nm)and one NIR band(1030nm)have a degradation of more than5%.These bands in NIR region between650and980nm are stable with less than5%degradation during three years.It is interesting to see that some bands at the NIR region have a slight re-sponse increase of less than5%.The response degradation is different in different time intervals.This implies that the tem-poral change of the MERSI instrument response is nonlinear with time.There is a quick degradation rate in thefirst year, and then,the rate is decreasing after one year and sometime shows a littlefluctuation.

Except for the VOC viewing,MERSI also scans the deep space(SV)and BB and gets the signal counts,called DN sv and DN bb.These observation signals are suggested by the Coordination Group for Meteorological Satellites[50]to be used to monitor the instrument operational status and the radio-metric performance change in orbit.Fig.10shows the anomaly jump of SV signal of MERSI bands6and7at the same time when the electric gain jump appears.These jumps are also reflected in the brightness jump of EV raw images(not shown). TIR band5appears with the same situation(not shown).The calibration slopes of bands6and7derived from VCs show the consistent jump simultaneously with the DN sv random jump. The instrument vendor explained that it was induced by the electronic gain anomaly jump of MERSI NIR and IR bands because these bands are susceptible to contamination by extra electrons produced by high-energy protons from the natural en-vironment hitting the detector.IR band5can be calibrated using BB and SV observations at real time.However,the calibration algorithm of bands6and band7is not based on(3)and has to be adjusted for the calibration coefficient using the electronic gain state from the telemetry data at any time.There are eight electric gain levels(1.0,1.1,1.2,1.3,1.43,1.57,1.7,and1.87) set by the vendor before it was launched,and the calibration coefficient can be adjusted based on the ratio of DN sv to DN sv0 (lowest SV counts when its electric gain was equal to1.0). C.Intercalibration Based on Dunhuang Desert

An intercalibration method was proposed by Liu et al.[51] for solar reflective bands.Essentially,the Terra/MODIS data were used as a reference sensor because of its excellent calibra-tion accuracy[34],[35]and local overpassing time similar to FY-3A.From July2008to the end of2010,clear sky measure-ments over the Gobi Desert Dunhuang site were coincidently obtained from Terra/MODIS and MERSI in the same day.Us-ing the6S radiative transfer model[52],the MODIS reflectance measured at the TOA is converted into surface reflectance. They were corrected to the viewing geometry of the MERSI using the BRDF measured on the ground.The BRDF-corrected surface reflectance data were interpolated with a spline func-tion to obtain a continuous surface reflectance spectrum under the assumption of smooth reflectance spectrum of the desert


2012 Fig.10.Signal trend of SV(DN sv)of FY-3A MERSI bands6,7,and8from July2008to December2010.The points in thefigure are the average of one 5granule data at one invariant Earth observation location.DN sv of band6and that of band7have a frequent unusualfluctuation during the two years while that of band8has the relatively simple change trend.

[30],[51].With the MERSI SRF,the BRDF-modified and interpolated spectral reflectance was further converted to TOA values from the6S radiative transfer model[52]and the same atmospheric conditions used for MODIS.Using the observa-tions of dark space from MERSI as another calibration point, the sensor gains of all solar reflective bands were computed for all the matched data.

It can be found that the short-wavelength bands’response gain(1/Scale)has obviously degraded throughout the two years (shown in Table IV).If we assume that this kind of degradation is nearly linear,but not supported by the VOC results,the linear regression of scale reveals the degradation of the instruments, and thefluctuation of scale around the linear regression line (standard deviationσ)reveals the uncertainty of the calibration [30].As for the water vapor absorption bands(bands17,18,and 19),the uncertainty of the desert intercalibration method is too high to be accepted.Bands8and9have the same degradations as those from other methods.Bands1,2,10,and11have medium degradations.The rest bands have a near stable gain with a degradation of less than2%.


The major MERSI elements have been working well after it was activated on June3,2008.The scan mirror,focal plane electronics,and the calibration and characterization devices discussed previously are functioning normally.The door for the radiative cooler was opened and operating properly.Un-fortunately,the K-mirror of FY-3A MERSI which removes the rotation of the image from the scan of the telescope stopped working after two days and led to the rotation of the image. Under this situation,a software module in DP2S was devel-oped immediately for derotation of the image based on the image rotation mechanism.The latest preprocessing software for MERSI L1product generation wasfinalized in the FY-3A DP2S in late September2008.Since then,the MERSI L1data are stable and used for MERSI product generation.The beta version of products was available at the end of2008.

During the in-orbit verification(IOV)phase,some key pa-rameters that measure the MERSI performance specification were derived,including the SNR,dynamic range,spatial res-olution and modulation transfer function,band-to-band reg-istration,the consistency of the multiple detector,instrument stability,and saturation restore function.The SNRs(charac-terized by noise equivalent reflectance NEΔρ)at the reflected solar radiation bands(bands1–4and6–20)meet the specifica-tions in most situations except for some detectors at band7,as shown in Fig.11.The solid bars show the instrument required specifications.The MERSI SNR is checked sometimes in orbit to make sure if the performance can meet the specifications or has some change.The on-orbit calibration and verification are also heavily relied on the vicarious techniques for solar bands because VOC cannot provide the absolute calibration. However,the VOC can monitor the relative change of radio-metric response of the MERSI SRB bands.Thefield campaign using the CRCS calibration sites for the historical instruments indicates that the absolute calibration accuracy is better than 5%[28],[48],which is less than the required7%specification of MERSI.This kind of VC becomes one of the most important methods for in-flight MERSI calibration check.

The CRCS calibration for FY-3A/MERSI was conducted for thefirst time in September2008using simultaneous satellite and ground measurements during its IOV[30].Fig.12com-pares the CRCS VC results with those from the prelaunch cali-bration and two kinds of intercalibration methods in September 2009.Except for Liu’s method[48]mentioned earlier,the intercalibration based on SNO method[26]was also conducted for the similar bands of Terra/MODIS.The intercomparison of most of bands from these three methods shows good agreement except for two NIR bands(15and18)with large atmospheric absorption.The reason for the inconsistency of SWIR bands (6and7)from these methods is the random jump in the MERSI electronic gain(explained earlier)during these observations. These in-flight calibration results verified the fact of large bias of the preflight calibration except for bands3,11,and14. The operational calibration coefficients at the MERSI band






Fig.11Noise equivalent reflectance (NE Δρ)of each detector of FY-3A MERSI solar reflective bands on orbit calculated using the SV data during the commissioning phase.Detectors 1–160on the x -axis are for bands 1–4,and each band has 40detectors.Detectors 161–310on the x -axis are for bands 6–20,and each band has ten detectors.The red lines are the required specification of NE Δρ,and the blue ones are the testing results on orbit during the commissioning phase in August 2008.

except for the atmospheric absorption bands were updated in December 2008using the VC results.

E.Result Analysis of Long-Term Calibration Monitoring The aforementioned three calibration methods are conducted independently for FY-3A MERSI at the same time after its launch.Finally,the results from all these methods are combined into an integrated calibration analysis system as the reference for the calibration update of MERSI.Fig.13shows the total degradation from these methods during a period of two years (from 2008to 2010).Although there are some differences in the values of degradation of the MERSI bands from differ-ent methods,the relative degradation trend is consistent.The



Fig.12.Comparison of the calibration slopes from three different calibration methods,including CRCS VC,cross-calibration based on Dunhuang site,and SNO cross-calibration for FY-3A/MERSI during the commissioning phase in September 2008.These two cross-calibrations were conducted with the Terra/MODIS.The blue one is VC using the Dunhuang site.The purple is the cross-calibration using Liu’s method on the Dunhuang site.The yellow one is the SNO cross-calibration.The red one is the preflight calibration result of this


Fig.13.Degradation rate (F d )comparison of solar reflective bands of FY-3A MERSI derived from three methods,including the VOC,CRCS,and intercali-bration between September 2008and August 2010.These relative degradations are all standing September 10,2008,as the beginning point.The blue bars are from the VOC results,the red ones from the CRCS calibration,and the green ones from intercalibration with MODIS.All the methods show the same degradation trend and have a good consistency except water absorption bands 17,18,and 19.Band 18appears to have significant difference of degradation from different methods.

degradations of most of the bands are less than 3%.The shorter wavelength bands (<500nm)have a large degradation,while the longer ones have a small degradation rate except bands 6,7,and 20.The largest degradation appears at band 8with more than 20%after two years.In the red and NIR bands (600–900nm),including bands 13,14,15,and 16,the calibra-tion coefficients are very stable with a decay rate of below 2%.Bands 3and 4show a slight radiometric response enhancement (the calibration coefficient slope becomes smaller).The gas absorption bands 17,18,and 19have a larger uncertainty in CRCS VC and desert intercalibration,but the VOC monitoring shows that their radiometric response is stable in the past.These bands need further verification by other methods.It is found that the degradation speed is not the same and nonlinear over time if we separate the two years of total degradation by year.Most of the bands have a larger degradation at the beginning of in-flight,and the speed of degradation decreases gradually with time.Based on these analysis and comparison,the calibration coefficients of the FY-3A MERSI have already been updated three times for these bands with more than 5%degradation rate since its launch.


FY-3A MERSI is the newest instrument in the Chinese me-teorological satellite history.The MERSI adopted a 45◦mirror scanning and unique derotation techniques with K-mirror when it can do cross-track scanning with multiple detectors.The MERSI has a high spectral and radiometric resolution and dual spatial resolution,within a global mission covering atmosphere,land surface,and ocean.

The VOC of the MERSI is the first time experimented onboard calibrator for VIS bands and provides a good tool for monitoring the relative degradation trend of radiometric sensi-tivity of solar reflective bands of the MERSI.The prelaunch characterization and calibration of this sensor show that it can meet the required specification and provided the important basic parameter for L1product generation and data application.The outdoor calibration using multiple-reference-panel-based solar source is a distinctive method and is proven to be a good reasonable calibration accuracy.The baseline calibra-tion approach has been conducted using the CRCS–Dunhuang site in the summer of every year since 2008.The frequent intercalibration with Terra/MODIS is also used to verify the aforementioned calibration and monitoring results.The reliable accuracy of intercomparison of these methods can reach a difference of less than 5%.The results from these three methods are relatively consistent for most of the MERSI bands except the bands with large atmospheric gas absorption.From the calibration monitoring during more than two years,the shorter wavelength bands (<500nm)of the FY-3A MERSI have a significant degradation performance of more than 10%,and the largest degradation in band 8is more than 20%.Seven bands (1,2,8,9,10,11,and 20)of the 19solar reflective bands have definitely more than 5%degradation in the past.All the calibra-tion methods show consistently that the calibration coefficients of the bands in the red and NIR bands (600–900nm),including bands 13,14,15and 16,almost have no change with a degra-dation rate of below 2%during the past two years.It is found that the speed of the degradation is not the same and nonlinear over time,and the degradation in the first year is much faster than that in the second year.The degradation information was provided to the instrument vendor for supporting instrument improvement in the future.

These methods of calibration monitoring and verification for the MERSI provide much important information to its product retrieval and quantitative application in the data user community.The lessons have been learned for the instrument maintenance and calibration coefficient update in orbit.The calibration results from them have already been used to update its operational calibration coefficients three times for these bands with more than 5%degradation rate since its launch.Further research studies are needed to improve the accuracy of calibration and clarify the calibration uncertainty.For these,more methods and further validation are used to pay attention to the MERSI calibration performance.More earth targets or celestial objects such as the African deserts [53],Greenland and Dome C snow [54],deep convective cloud [55],[56],and moon [57]are used to monitoring and evaluating the accuracy and consistency of the calibration for the MERSI.



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Xiuqing Hu received the B.S.degree in atmospheric

science from Nanjing University,Nanjing,China,

in1996,the M.S.degree in cartography and geo-

graphical information system from Beijing Normal

University,Beijing,China,in2004,and the Ph.D.

degree in quantitative remote sensing science from

the Institute of Remote Sensing Application,Chinese

Academy of Sciences,Beijing,in2012.

He was a Research Assistant in the National Satel-

lite Meteorological Center,China Meteorological

Administration(NSMC/CMA),Beijing,from1996 to2004and became an Associate Professor and the Chief of the CAL/V AL Branch,Satellite Meteorological Institute,NSMC/CMA,in2004.He has been a Professor of engineering since2010and has been the Instrument Scientist of MERSI onboard FY-3since2006.He is currently a Visiting Scientist and also a Contractor in NOAA/NESDIS/STAR as a Remote Sensing Senior Scientist with Earth Resources Technology Inc.His research interests include calibration and validation for optical sensors,the retrieval algorithm of aerosol/dust and water vapor,and the climate data record from environment satellite.

Prof.Hu is a member of WMO Sand and Dust Storm Warning Advisory and Assessment System(SDS-WAS)Regional Steering Group and a member of GSICS Research Working


Ling Sun received the Ph.D.degree in physical

oceanology from the Institute of Oceanology,Chi-

nese Academy of Sciences,Qingdao,China,in2005.

Since June2005,she has been with the National

Satellite Meteorological Center,China Meteorologi-

cal Administration,Beijing,China,where she was an

Associate Research Scientist.In the past few years,

she developed the ocean color and ocean aerosol

retrieval algorithms which have been operationally

used in FY-3A product generation.The majorfields

she is working on include the following:1)remote sensing of ocean color;2)satellite sensor calibration;and3)aerosol retrieval and validation.

Jingjng Liu,photograph and biography not available at the time of publication. Lei Ding,photograph and biography not available at the time of publication. Xianghua Wang,photograph and biography not available at the time of publication.

Yuan Li,photograph and biography not available at the time of publication. Yong Zhang,photograph and biography not available at the time of


Na Xu received the Ph.D.degree in atmospheric

physics and environment from the Chinese Academy

of Sciences,Beijing,China,in2010.Her thesis was

on the modification and application of an atmo-

spheric radiative transfer model.

She is currently a Research Assistant with the

National Satellite Meteorological Center,China Me-

teorological Administration,Beijing.She is working

on the vicarious calibration of FengYun satellite


Lin Chen,photograph and biography not available at the time of publication.





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