中心波长/μm | 光谱区间/μm | SNR/NEdT |
0.630 | 0.580~0.68 | 9 @ 0.5%反照率 |
0.862 | 0.725~1.00 | 9 @ 0.5%反照率 |
1.610 | 1.58~1.64 | 20 @ 0.5%反照率 |
3.740 | 3.55~3.93 | 0.12 K @ 300 K |
10.80 | 10.3~11.3 | 0.12 K @ 300 K |
12.00 | 11.5~12.5 | 0.12 K @ 300 K |
Citation: | Yang Zhongdong, Liu Jian. A review of visible infrared imaging radiometer on meteorological satellite. J Appl Meteor Sci, 2016, 27(5): 592-603. DOI: 10.11898/1001-7313.20160508. |
Table 1 The spectral and radiometric characterization of AVHRR/3
中心波长/μm | 光谱区间/μm | SNR/NEdT |
0.630 | 0.580~0.68 | 9 @ 0.5%反照率 |
0.862 | 0.725~1.00 | 9 @ 0.5%反照率 |
1.610 | 1.58~1.64 | 20 @ 0.5%反照率 |
3.740 | 3.55~3.93 | 0.12 K @ 300 K |
10.80 | 10.3~11.3 | 0.12 K @ 300 K |
12.00 | 11.5~12.5 | 0.12 K @ 300 K |
Table 2 The spectral and radiometric characterization of IMAGER
中心波长/μm | 光谱区间/μm | SNR/NEdT |
0.65 | 0.55~0.75 | 250 @ 100%反照率 |
3.90 | 3.80~4.00 | 0.11 K @ 300 K |
6.55 | 5.80~7.30 | 0.14 K @ 300 K |
10.70 | 10.2~11.2 | 0.09 K @ 300 K |
13.35 | 13.0~13.7 | 0.70 K @ 300 K |
Table 3 The spectral and radiometric characterization of MODIS (from reference [56])
主要用途 | 波段 | 波段范围* | 光谱辐射/ (W·m-2·sr-1·μm-1) |
SNR/NEdT/K |
陆地/云/边界层气溶胶 | 1 | 620~670 | 21.8 | 128 |
2 | 841~876 | 24.7 | 201 | |
陆地/云/气溶胶特性 | 3 | 459~479 | 35.3 | 243 |
4 | 545~565 | 29.0 | 228 | |
5 | 1230~1250 | 5.4 | 74 | |
6 | 1628~1652 | 7.3 | 275 | |
7 | 2105~2155 | 1.0 | 110 | |
海洋水色/浮游生物/ 生物地球化学 |
8 | 405~420 | 44.9 | 880 |
9 | 438~448 | 41.9 | 838 | |
10 | 483~493 | 32.1 | 802 | |
11 | 526~536 | 27.9 | 754 | |
12 | 546~556 | 21.0 | 750 | |
13 | 662~672 | 9.5 | 910 | |
14 | 673~683 | 8.7 | 1087 | |
15 | 743~753 | 10.2 | 586 | |
16 | 862~877 | 6.2 | 516 | |
大气水汽 | 17 | 890~920 | 10.0 | 167 |
18 | 931~941 | 3.6 | 57 | |
19 | 915~965 | 15.0 | 250 | |
地表/云温度 | 20 | 3.660~3.840 | 0.45(300 K) | 0.05 |
21 | 3.929~3.989 | 2.38(335 K) | 2.00 | |
22 | 3.929~3.989 | 0.67(300 K) | 0.07 | |
23 | 4.020~4.080 | 0.79(300 K) | 0.07 | |
大气温度 | 24 | 4.433~4.498 | 0.17(250 K) | 0.25 |
25 | 4.482~4.549 | 0.59(275 K) | 0.25 | |
卷云水汽 | 26 | 1.360~1.390 | 6.00 | 150(SNR) |
27 | 6.535~6.895 | 1.16(240 K) | 0.25 | |
28 | 7.175~7.475 | 2.18(250 K) | 0.25 | |
云特征 | 29 | 8.400~8.700 | 9.58(300 K) | 0.05 |
臭氧 | 30 | 9.580~9.880 | 3.69(250 K) | 0.25 |
地表/云温度 | 31 | 10.780~11.280 | 9.55(300 K) | 0.05 |
32 | 11.770~12.270 | 8.94(300 K) | 0.05 | |
云顶高度 | 33 | 13.185~13.485 | 4.52(260 K) | 0.25 |
34 | 13.485~13.785 | 3.76(250 K) | 0.25 | |
35 | 13.785~14.085 | 3.11(240 K) | 0.25 | |
36 | 14.085~14.385 | 2.08(220 K) | 0.35 | |
注:*波段1~19光谱单位:nm; 波段20~36光谱单位:μm。 |
Table 4 The main characterizations and usages of 3MI (from reference [64])
3MI | 中心波 长/μm |
光谱带 宽/nm |
SNR@xx.x/ (W·m-2·sr-1·μm-1) |
极化 | 主要用途 |
可见光近红外谱段 | 0.410 | 20 | 100 @ 35.4 | Y | 吸收气溶胶,火山灰云 |
0.443 | 20 | 100 @ 48.9 | Y | 吸收气溶胶 | |
0.490 | 20 | 100 @ 55.6 | Y | 气溶胶,地表反照率,云反射率,光学厚度 | |
0.555 | 20 | 100 @ 55.2 | Y | 地表反照率 | |
0.670 | 20 | 100 @ 44.1 | Y | 气溶胶光学特性 | |
0.754 | 20 | 200 @ 36.6 | N | 云,气溶胶高度 | |
0.763 | 10 | 200 @ 36.1 | N | 云,气溶胶高度 | |
0.865 | 40 | 100 @ 28.2 | Y | 植被,气溶胶,云,地表特征 | |
0.910 | 20 | 200 @ 25.2 | N | 水汽,大气校正 | |
短波红外谱段 | 0.910 | 20 | 200 @ 25.2 | N | 水汽,大气校正 |
1.370 | 40 | 100 @ 10.7 | Y | 卷云,水汽图像 | |
1.650 | 40 | 100 @ 6.8 | Y | 气溶胶反演中的地表特性 | |
2.130 | 40 | 100 @ 2.9 | Y | 气溶胶反演中的地表特性,云微物理 |
[1] |
Wikipedia.Television Infrared Observation Satellite.Wikipedia, 2016.
|
[2] |
WMO.WMO OSCAR.List of all Instruments.2015.
|
[3] |
Rao P K, Holmes S J, Anderson R K, 等编. 许健民, 方宗义, 徐建平, 等译. 气象卫星——系统、资料及其在环境中的应用. 北京: 气象出版社, 1994.
|
[4] |
Schmidt M, King E A, McVicar T R.A method for operational calibration of AVHRR reflective time series data.Remote Sens Environ, 2008, 112(3):1117-1129. doi: 10.1016/j.rse.2007.07.015
|
[5] |
Trishchenko A P, Li Z.A method for the correction of AVHRR onboard IR calibration in the event of short-term radiative contamination.Int J Remote Sens, 2001, 22(17):3619-3624. doi: 10.1080/01431160152609362
|
[6] |
Mittaz J, Harris A.A physical method for the calibration of the AVHRR/3 thermal IR channels.Part Ⅱ:An in-orbit comparison of the AVHRR longwave thermal IR channels on board metop-A with IASI.J Atmos Ocean Technol, 2011, 28(9):1072-1087. doi: 10.1175/2011JTECHA1517.1
|
[7] |
Raja M, Wu X Q, Yu F F.Extended Inter-comparison of collocated MetOp-A AVHRR-IASI brightness temperature data and its implication for AVHRR calibration.Atmospheric and Environmental Remote Sensing Data Processing and Utilization Ⅵ:Readiness for GEOSS Ⅳ, 2010, 781107, doi: 10.1117/12.861265.
|
[8] |
Rossow W B, Garder L C.Validation of ISCCP cloud detections.J Climate, 1993, 6(12):2370-2393. doi: 10.1175/1520-0442(1993)006<2370:VOICD>2.0.CO;2
|
[9] |
Rossow W B, Schiffer R A.ISCCP cloud data products.Bull Am Meteor Soc, 1991, 72(1):2-20. doi: 10.1175/1520-0477(1991)072<0002:ICDP>2.0.CO;2
|
[10] |
Seze G, Rossow W B.Time-cumulated visible and infrared radiance histograms used as descriptors of surface and cloud variations.Int J Remote Sens, 1991, 12(5):877-920. doi: 10.1080/01431169108929702
|
[11] |
Rossow W B.Measuring cloud properties from space:A review.J Climate, 1989, 2(3):201-213. doi: 10.1175/1520-0442(1989)002<0201:MCPFSA>2.0.CO;2
|
[12] |
Rossow W, Mosher F.ISCCP cloud algorithm intercomparison.J Climate Appl Meteor, 1985, 24(9):877-903. doi: 10.1175/1520-0450(1985)024<0887:ICAI>2.0.CO;2
|
[13] |
Saunders R W, Kriebel K T.An improved method for detecting clear sky and cloudy radiances from AVHRR data.Int J Remote Sens, 1988, 9(1):123-150. doi: 10.1080/01431168808954841
|
[14] |
Stowe L L, Davis P, McClain E P.Evaluating the CLAVR (clouds from AVHRR) phase I-cloud cover experimental product.Adv Space Res, 1995, 16(10):21-24. doi: 10.1016/0273-1177(95)00374-N
|
[15] |
Stowe L L, Vemury S K, Rao A V.AVHRR clear sky radiation data sets at NOAA/NESDIS.Adv Space Res, 1994, 14(1):113-116. doi: 10.1016/0273-1177(94)90358-1
|
[16] |
Stowe L L, Davis P A, Mcclain E P.Scientific basis and initial evaluation of the CLAVR-1 global clear/cloud classification algorithm for the advanced very high resolution radiometer.J Atmos Ocean Technol, 1999, 16(6):656-681. doi: 10.1175/1520-0426(1999)016<0656:SBAIEO>2.0.CO;2
|
[17] |
Heidinger A K.CLAVR-x Cloud Mask Algorithm Theoretical Basis Document (ATBD), NOAA/NESDIS/Office of Research and Applications, Washington, DC, USA, 2004.
|
[18] |
Vemury S, Stowe L L, Anne V R.AVHRR pixel level clear-sky classification using dynamic threshold (CLAVR-3).J Atmos Ocean Technol, 2001, 18(2):169-186. doi: 10.1175/1520-0426(2001)018<0169:APLCSC>2.0.CO;2
|
[19] |
Gao B C, Goetz A F H, Wiscombe W J.Cirrus cloud detection from airborne imaging spectrometer data using the 1.38 micron water vapor band.Geophys Res Lett, 1993, 20(4):301-304. doi: 10.1029/93GL00106
|
[20] |
Baum B A, Wielicki B A.Cirrus cloud retrieval using infrared sounding data:Multilevel cloud errors.J Appl Meteorol, 1994, 33(1):107-117. doi: 10.1175/1520-0450(1994)033<0107:CCRUIS>2.0.CO;2
|
[21] |
Nakajima T, King M D.Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements.Part Ⅰ:Theory.Journal of the Atmospheric Sciences, 1990, 47(15):1878-1893. doi: 10.1175/1520-0469(1990)047<1878:DOTOTA>2.0.CO;2
|
[22] |
Ou S C, Liou K N, Takano Y, et al.Remote sounding of cirrus cloud optical depths and ice crystal sizes from AVHRR data:Verification using FIRE Ⅱ IFO measurements.J Atmos Sci, 1995, 52(23):4143-4158. doi: 10.1175/1520-0469(1995)052<4143:RSOCCO>2.0.CO;2
|
[23] |
Nakajima T Y, Nakajma T.Wide-area determination of cloud microphysical properties from NOAA AVHRR measurements for FIRE and ASTEX Regions.J Atmos Sci, 1995, 52(23):4043-4059. doi: 10.1175/1520-0469(1995)052<4043:WADOCM>2.0.CO;2
|
[24] |
Ackerman S A, Moeller C C, Strabala K I, et al.Retrieval of effective microphysical properties of clouds:A wave cloud case study.Geophys Res Lett, 1998, 25(8):1121. doi: 10.1029/98GL00042
|
[25] |
Baum B A, Yang P, Nasiri S, et al.Bulk scattering properties for the remote sensing of ice clouds.Part Ⅲ:High-resolution spectral models from 100 to 3250 cm-1.J Appl Meteorol Climatol, 2007, 46(4):423-434. doi: 10.1175/JAM2473.1
|
[26] |
Baum B A, Yang P, Heymsfield A J, et al.Bulk scattering properties for the remote sensing of ice clouds.Part Ⅱ:Narrowband models.J Appl Meteorol, 2005, 44(12):1896-1911. doi: 10.1175/JAM2309.1
|
[27] |
Baum B A, Heymsfield A J, Yang P, et al.Bulk scattering properties for the remote sensing of ice clouds.Part Ⅰ:Microphysical data and models.J Appl Meteorol, 2005, 44(12):1885-1895. doi: 10.1175/JAM2308.1
|
[28] |
Ou S C, Liou K N, Caudill T R.Remote sounding of multilayer cirrus cloud systems using AVHRR data collected during FIRE-Ⅱ-IFO.J Appl Meteorol, 1998, 37(3):241-254. doi: 10.1175/1520-0450-37.3.241
|
[29] |
Kawamoto K, Nakajima T.A global determination of cloud microphysics with AVHRR remote sensing.J Climate, 2001, 14(9):2054-2068. doi: 10.1175/1520-0442(2001)014<2054:AGDOCM>2.0.CO;2
|
[30] |
赵凤生, 丁强, 孙同明, 等.利用NOAA-AVHRR观测数据反演云辐射特性的一种迭代方法.气象学报, 2002, 60(5):594-601. doi: 10.11676/qxxb2002.070
|
[31] |
Liu Jian, Dong Chaohua.Using satellite data to analyze properties of cloud particles size on the top of cloud.J Infrared Millim Waves, 2002, 21(2):4-8. http://www.oalib.com/paper/1597681
|
[32] |
Liu Jian, Zhu Yuanjing, Zhao Bolin, et al.Appl ication study on detecting multilayer cloud's properties by satellite data.J Infrared Millim Waves, 2004, 23(6):408-412. https://www.researchgate.net/publication/287026472_Application_study_on_detecting_multilayer_cloud's_properties_by_satellite_data
|
[33] |
刘健.FY-2云检测中动态阈值提取技术改进方法研究.红外与毫米波学报, 2010, 29(4):288-292. http://www.cnki.com.cn/Article/CJFDTOTAL-HWYH201004012.htm
|
[34] |
傅云飞.利用卫星双光谱反射率算法反演的云参数及其应用.气象学报, 2014, 72(5):1039-1053. doi: 10.11676/qxxb2014.087
|
[35] |
McClain E P, Pichel W G, Walton C C, et al.Multi-channel improvements to satellite-derived global sea surface temperatures.Adv Space Res, 1982, 2(6):43-47. http://citeseerx.ist.psu.edu/showciting?cid=1905732
|
[36] |
McClain E P, Pichel W G, Walton C C.Comparative performance of AVHRR-based multichannel sea surface temperatures.J Geophys Res Ocean, 1985, 90(C6):11587-11601. doi: 10.1029/JC090iC06p11587
|
[37] |
Walton C C.Nonlinear multichannel algorithms for estimating sea surface temperature with AVHRR satellite sata.J Appl Meteorol, 1988, 27(2):115-124. doi: 10.1175/1520-0450(1988)027<0115:NMAFES>2.0.CO;2
|
[38] |
Walton C C, Pichel W G, Sapper J F, et al.The development and operational application of nonlinear algorithms for the measurement of sea surface temperatures with the NOAA polar-orbiting environmental satellites.J Geophys Res, 1998, 103(C12):27999. doi: 10.1029/98JC02370
|
[39] |
Kilpatrick K A, Podestá G P, Evans R.Overview of the NOAA/NASA advanced very high resolution radiometer pathfinder algorithm for sea surface temperature and associated matchup database.J Geophys Res, 2001, 106(C5):9179. doi: 10.1029/1999JC000065
|
[40] |
Geogdzhayev I V, Mishchenko M I, Rossow W B, et al.Global two-channel AVHRR retrievals of aerosol properties over the ocean for the period of NOAA-9 observations and preliminary retrievals using NOAA-7 and NOAA-11 data.J Atmos Sci, 2002, 59(3):262-278. doi: 10.1175/1520-0469(2002)059<0262:GTCARO>2.0.CO;2
|
[41] |
Mishchenko M I, Geogdzhayev I V, Liu L, et al.Aerosol retrievals from AVHRR radiances:Effects of particle nonsphericity and absorption and an updated long-term global climatology of aerosol properties.J Quant Spectrosc Radiat Transf, 2003, 79-80:953-972. doi: 10.1016/S0022-4073(02)00331-X
|
[42] |
Mishchenko M I, Liu L, Geogdzhayev I V, et al.Aerosol retrievals from channel-1 and-2 AVHRR radiances:Long-term trends updated and revisited.J Quant Spectrosc Radiat Transf, 2012, 113(15):1974-1980. doi: 10.1016/j.jqsrt.2012.05.006
|
[43] |
Dong C, Yang J, Zhang W, et al.An overview of new Chinese weather satellite FY-3A.Bull Am Meteorol Soc, 2009, 90(10):1531-1544. doi: 10.1175/2009BAMS2798.1
|
[44] |
Gao C, Zhao Y, Li C, et al.An investigation of a novel cross-calibration method of FY-3C/VIRR against NPP/VIIRS in the Dunhuang test site.Remote Sensing, 2016, 8(1):77-98. https://www.researchgate.net/publication/291527400_An_investigation_of_a_novel_cross-calibration_method_of_FY-3CVIRR_against_NPPVIIRS_in_the_Dunhuang_test_site
|
[45] |
Xu N, Chen L, Hu X, et al.Assessment and correction of on-orbit radiometric calibration for FY-3 VIRR thermal infrared channels.Remote Sens, 2014, 6(4):2884-2897. doi: 10.3390/rs6042884
|
[46] |
Yu F, Wu X.An integrated method to improve the GOES Imager visible radiometric calibration accuracy.Remote Sens Environ, 2015, 164:103-113. doi: 10.1016/j.rse.2015.04.003
|
[47] |
Wang L, Cao C, Goldberg M.Intercalibration of GOES-11 and GOES-12 water vapor channels with MetOp IASI hyperspectral measurements.J Atmos Ocean Technol, 2009, 26(9):1843-1855. doi: 10.1175/2009JTECHA1233.1
|
[48] |
Meng Z, Zhang Y.On the squall lines preceding landfalling tropical cyclones in China.Mon Wea Rev, 2012, 140:445-470. doi: 10.1175/MWR-D-10-05080.1
|
[49] |
Mecikalski J R, Bedka K M.Forecasting convective initiation by monitoring the evolution of moving cumulus in daytime GOES imagery.Mon Wea Rev, 2006, 134:49-78. doi: 10.1175/MWR3062.1
|
[50] |
Mecikalski J R, Bedka K M, Paech S J, et al.A statistical evaluation of GOES cloud-top properties for nowcasting convective initiation.Mon Wea Rev, 2008, 136:4899-4914. doi: 10.1175/2008MWR2352.1
|
[51] |
刘健, 蒋建莹.FY-2C高时间分辨率扫描数据在强对流云团监测中的应用研究.大气科学, 2013, 37(4):873-880. doi: 10.3878/j.issn.1006-9895.2012.12062
|
[52] |
Yang X, Fei J, Huang X, et al.Characteristics of mesoscale convective systems over China and its vicinity using geostationary satellite FY2.J Clim, 2015, 28(12):4890-4907. doi: 10.1175/JCLI-D-14-00491.1
|
[53] |
Xiong X, Sun J, Xie X, et al.On-orbit calibration and performance of Aqua MODIS reflective solar bands.IEEE Trans Geosci Remote Sens, 2010, 48(1):535-546. doi: 10.1109/TGRS.2009.2024307
|
[54] |
Xiong X, Chiang K, Sun J, et al.NASA EOS Terra and Aqua MODIS on-orbit performance.Adv Space Res, 2009, 43(3):413-422. doi: 10.1016/j.asr.2008.04.008
|
[55] |
Xiong X, Wu A, Cao C.On-orbit calibration and inter-comparison of Terra and Aqua MODIS surface temperature spectral bands.Int J Remote Sens, 2008, 29(17-18):5347-5359. doi: 10.1080/01431160802036300
|
[56] |
Maccherone B.MODIS Web. http://modis.gsfc.nasa.gov/data/dataprod, 2014.
|
[57] |
Yang Z, Lu N, Shi J, et al.Overview of FY-3 payload and ground application system.IEEE Trans Geosci Remote Sens, 2012, 50(12):4846-4853. doi: 10.1109/TGRS.2012.2197826
|
[58] |
Xu H, Xu N, Hu X.Inter-Calibration of Infrared Bands of FY-3C MERSI and VIRR Using Hyperspectral Sensor CrIS and IASI.Proc.SPIE 9264, Earth Observing Missions and Sensors:Development, Implementation, and Characterization Ⅲ, 92640B, 2014. https://www.researchgate.net/profile/Xiuqing_Hu/publication/290534157_Inter-calibration_of_infrared_bands_of_FY-3C_MERSI_and_VIRR_using_hyperspectral_sensor_CrIS_and_IASI/links/574cdac408ae061b3301e86c.pdf?inViewer=0&pdfJsDownload=0&origin=publication_detail
|
[59] |
Uprety S, Cao C.Suomi NPP VIIRS reflective solar band on-orbit radiometric stability and accuracy assessment using desert and Antarctica Dome C sites.Remote Sens Environ, 2015, 166:106-115. doi: 10.1016/j.rse.2015.05.021
|
[60] |
Cao C, Xiong J, Blonski S, et al.Suomi NPP VIIRS sensor data record verification, validation, and long-term performance monitoring.J Geophys Res Atmos, 2013, 118(20):11664-11678. doi: 10.1002/2013JD020418
|
[61] |
Okuyama A, Andou A, Date K, et al.Preliminary validation of Himawari-8/AHI navigation and calibration.SPIE, 2015, 9607:96072E. http://adsabs.harvard.edu/abs/2015SPIE.9607E..2EO
|
[62] |
Da C.Preliminary assessment of the advanced Himawari imager (AHI) measurement onboard Himawari-8 geostationary satellite.Remote Sens Lett, 2015, 6(8):637-646. doi: 10.1080/2150704X.2015.1066522
|
[63] |
Manolis I, Grabarnik S, Caron J, et al.The MetOp Second generation 3MI Instrument.Proc SPIE, 2013, 5:88890J. https://www.researchgate.net/publication/260967393_The_MetOp_Second_Generation_3MI_instrument
|
[64] |
Nazionale C, Aeronautica C, Pratica V, et al.METOP-SG 3MI (Multi-viewing Multi-channel Multi-polarization Imaging), a Powerful Observing Mission for Future Operational Applications.Daniele BIRON.EUMETSAT Meteorological Satellite Conference, Vienna, 2013.
|