Terra and Aqua MODIS TEB intercomparison using Himawari-8/AHI as reference

被引:7
|
作者
Chang, Tiejun [1 ]
Xiong, Xiaoxiong [2 ]
Angal, Amit [1 ]
机构
[1] Sci Syst & Applicat Inc, Lanham, MD 20706 USA
[2] NASA, Sci & Explorat Directorate, GSFC, Greenbelt, MD USA
来源
JOURNAL OF APPLIED REMOTE SENSING | 2019年 / 13卷 / 01期
关键词
intercomparison; MODIS; TEB; radiometric calibration; Himawari-8; AHI; ON-ORBIT CALIBRATION; SURFACE-TEMPERATURE; LONG-TERM; LAND; PRODUCTS; EMISSIVITY; VIIRS;
D O I
10.1117/1.JRS.13.017501
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Intercomparison between the two MODIS instruments is very useful for both the instrument calibration and its uncertainty assessment. Terra and Aqua MODIS have almost identical relative spectral response, spatial resolution, and dynamic range for each band, so the site-dependent effect from spectral mismatch for their comparison is negligible. Major challenges in cross-sensor comparison of instruments on different satellites include differences in observation time and view angle over selected pseudoinvariant sites. The simultaneous nadir overpasses (SNO) between the two satellites are mostly applied for comparison and the scene under SNO varies. However, there is a dearth of SNO between the Terra and Aqua. This work focuses on an intercomparison method for MODIS thermal emissive bands using Himawari-8 Advanced Himawari Imager (AHI) as a reference. Eleven thermal emissive bands on MODIS are at least to some degree spectrally matched to the AHI bands. The sites selected for the comparison are an ocean area around the Himawari-8 suborbital point and the Strzelecki Desert located south of the Himawari-8 suborbital point. The time difference between the measurements from AHI and MODIS is <5 min. The comparison is performed using 2017 collection 6.1 L1B data for MODIS. The MODIS-AHI difference is corrected to remove the view angle dependence. The Terra-Aqua MODIS difference for the selected TEB is up to 0.6 K with the exception of band 30. Band 30 has the largest difference, which is site dependent, most likely due to a crosstalk effect. Over the ocean, the band 30 difference between the two MODIS instruments is around 1.75 K, while over the desert; the difference is around 0.68 K. The MODIS precision is also compared from the Gaussian regression of the double difference. Terra bands 27 to 30 have significant extra noise due to crosstalk effects on these bands. These Terra-Aqua comparison results are used for MODIS calibration assessments and are beneficial for future calibration algorithm improvement. The impact of daytime measurements and the scene dependence are also discussed. (C) 2019 Society of Photo-Optical Instrumentation Engineers (SPIE)
引用
收藏
页数:19
相关论文
共 50 条
  • [41] Evaluation of NDVI Estimation Considering Atmospheric and BRDF Correction through Himawari-8/AHI
    Noh-Hun Seong
    Daeseong Jung
    Jinsoo Kim
    Kyung-Soo Han
    Asia-Pacific Journal of Atmospheric Sciences, 2020, 56 : 265 - 274
  • [42] Himawari-8/AHI Aerosol Optical Depth Detection Based on Machine Learning Algorithm
    Chen, Yuanlin
    Fan, Meng
    Li, Mingyang
    Li, Zhongbin
    Tao, Jinhua
    Wang, Zhibao
    Chen, Liangfu
    REMOTE SENSING, 2022, 14 (13)
  • [43] Impact Assessment of Himawari-8 AHI Data Assimilation in NCEP GDAS/GFS with GSI
    Ma, Zaizhong
    Maddy, Eric S.
    Zhang, Banglin
    Zhu, Tong
    Boukabara, Sid Ahmed
    JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2017, 34 (04) : 797 - 815
  • [44] Evaluation of NDVI Estimation Considering Atmospheric and BRDF Correction through Himawari-8/AHI
    Seong, Noh-Hun
    Jung, Daeseong
    Kim, Jinsoo
    Han, Kyung-Soo
    ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES, 2020, 56 (02) : 265 - 274
  • [45] Comparison of FY-4A/AGRI SST with Himawari-8/AHI and In Situ SST
    Yang, Chang
    Guan, Lei
    Sun, Xiaohui
    REMOTE SENSING, 2023, 15 (17)
  • [46] Improved Himawari-8/AHI Radiance Data Assimilation With a Double Cloud Detection Scheme
    Li, Xin
    Zou, Xiaolei
    Zhuge, Xiaoyong
    Zeng, Mingjian
    Wang, Ning
    Tang, Fei
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2020, 125 (13)
  • [47] BIDIRECTIONAL REFLECTANCE MODELING OF THE GEOSTATIONARY SENSOR HIMAWARI-8/AHI USING A KERNEL-DRIVEN BRDF MODEL
    Matsuoka, M.
    Takagi, M.
    Akatsuka, S.
    Honda, R.
    Nonomura, A.
    Moriya, H.
    Yoshioka, H.
    XXIII ISPRS CONGRESS, COMMISSION VII, 2016, 3 (07): : 3 - 8
  • [48] Development of Fog Detection Algorithm during Nighttime Using Himawari-8/AHI Satellite and Ground Observation Data
    Kim, So-Hyeong
    Suh, Myoung-Seok
    Han, Ji-Hye
    ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES, 2019, 55 (03) : 337 - 350
  • [49] Precipitable water vapor estimation from Himawari-8/AHI observations using a stacking machine learning model
    Du, Zheng
    Yao, Yibin
    Zhang, Bao
    Zhao, Qingzhi
    ATMOSPHERIC RESEARCH, 2024, 301
  • [50] Estimation of Summer Air Temperature over China Using Himawari-8 AHI and Numerical Weather Prediction Data
    Liu, Hailei
    Zhou, Qi
    Zhang, Shenglan
    Deng, Xiaobo
    ADVANCES IN METEOROLOGY, 2019, 2019