Cross-platform calibration of SMMR, SSM/I and AMSR-E passive microwave brightness temperature

被引:10
|
作者
Dai, Liyun [1 ]
Che, Tao [1 ]
机构
[1] Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Peoples R China
关键词
Brightness temperature; Passive microwave; Cross-platform calibration; diurnal cycle of temperature; SMMR; SSM/I; TIME-SERIES; ANTARCTICA; MELT; SOIL; F11;
D O I
10.1117/12.873150
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The long time series of passive microwave satellite data (SMMR, SSM/I and AMSR-E) have provided important information about the earth surface science and climate research in the past three decades. Due to the update of satellite-based radiometers and their platforms, some systematic parameters are different, and there are biases among brightness temperature in different periods, which lead to inaccuracy of some parameters' retrieval. In order to obtain consistent brightness temperature datasets, and provide convenience for the researchers using these data, it is necessary to calibrate the brightness temperature from different sensors. Considering the difference between the variance of brightness temperature from different sensors on cold and warm region at the cross time, this paper analyzed the brightness temperature on the cold and warm region respectively. On the cold region, because the diurnal temperature variation is very small, the influence on brightness temperature caused by difference of the satellites overpass time during the overlap period can be ignored. The brightness temperature data at 18GHz and 37GHz channels of Nimbus-7 and 19GHz, 37GHz channels of DMSP on the Antarctic or the Greenland glacier during the overlap period were analyzed. On the warm region, due to the reason that the daily variance of temperature contributes a lot to the difference of brightness temperature from different sensors during the overlap period, the diurnal cycle of surface temperature on the Sahara desert region was analyzed, and base on it, the influence of temperature to brightness temperature was eliminated. Finally, considering the two regions, the cross coefficients of calibration were estimated.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] INTERCALIBRATION OF AMSR-E AND WINDSAT BRIGHTNESS TEMPERATURE MEASUREMENTS OVER LAND SCENES
    Meissner, Thomas
    Wentz, Frank
    2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, : 3218 - 3219
  • [22] DEVELOPMENT OF PASSIVE MICROWAVE RETRIEVAL ALGORITHM FOR ESTIMATION OF SURFACE SOIL TEMPERATURE FROM AMSR-E DATA
    Han, Menglei
    Lu, Hui
    Yang, Kun
    2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 1671 - 1674
  • [23] An algorithm for retrieving soil moisture from AMSR-E passive microwave data
    Mao K.
    Hu D.
    Huang J.
    Zhang W.
    Zhang L.
    Zou J.
    Tang H.
    Gaojishu Tongxin/Chinese High Technology Letters, 2010, 20 (06): : 651 - 659
  • [24] LAND SURFACE-TEMPERATURE DERIVED FROM THE SSM/I PASSIVE MICROWAVE BRIGHTNESS TEMPERATURES
    MCFARLAND, MJ
    MILLER, RL
    NEALE, CMU
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1990, 28 (05): : 839 - 845
  • [25] Comparison of AMSR-E and SSM/I snow parameter retrievals over the Ob river basin
    Mognard, NM
    Grippa, M
    LeToan, T
    Kelly, REJ
    Chang, ATC
    Josberger, EG
    IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET, 2004, : 3713 - 3713
  • [26] Validation of microwave emission models by simulating AMSR-E brightness temperature data from ground-based observations
    Kontu, Anna
    Pulliainen, Jouni
    Heikkinen, Pauli
    Suokanerva, Hanne
    Takala, Matias
    IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 1440 - 1443
  • [27] An Updated Geophysical Model for AMSR-E and SSMIS Brightness Temperature Simulations over Oceans
    Zabolotskikh, Elizaveta
    Mitnik, Leonid
    Chapron, Bertrand
    REMOTE SENSING, 2014, 6 (03) : 2317 - 2342
  • [28] A neural-network technique for retrieving land surface temperature from AMSR-E passive microwave data
    Mao, Kebiao
    Shi, Jiancheng
    Tang, Huajun
    Guo, Ying
    Qiu, Yubao
    Li, Liying
    IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 4422 - +
  • [29] A NEURAL NETWORK BASED METHOD FOR LAND SURFACE TEMPERATURE RETRIEVAL FROM AMSR-E PASSIVE MICROWAVE DATA
    Gao, Caixia
    Jiang, Xiaoguang
    Qian, Yonggang
    Qiu, Shi
    Ma, Lingling
    Li, Zhao-liang
    2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2013, : 469 - 472
  • [30] Spring thaw classification based on AMSR-E brightness temperature in the central Tibetan Plateau
    Tang, Yi
    Zhang, Wenjiang
    Liu, Li
    Li, Guicai
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2019, 40 (17) : 6542 - 6552