Field-of-view characteristics and resolution matching for the Global Precipitation Measurement (GPM) Microwave Imager (GMI)

被引:17
|
作者
Petty, GrantW. [1 ]
Bennartz, Ralf [2 ]
机构
[1] Univ Wisconsin, Atmospher & Ocean Sci, 1225 W Dayton St, Madison, WI 53706 USA
[2] Vanderbilt Univ, Earth & Environm Sci, Stevenson Ctr 5726, Nashville, TN 37240 USA
关键词
GROSS EARTH DATA; BRIGHTNESS TEMPERATURES; INSTRUMENT;
D O I
10.5194/amt-10-745-2017
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Representative parameters of the scan geometry are empirically determined for the Global Precipitation Measurement (GPM) Microwave Imager (GMI). Effective fields of view (EFOVs) are computed for the GMI's 13 channels, taking into account the blurring effect of the measurement interval on the instantaneous fields of view (IFOVs). Using a Backus-Gilbert procedure, coefficients are derived that yield an approximate spatial match between synthetic EFOVs of different channels, using the 18.7 GHz channels as a target and with due consideration of the tradeoff between the quality of the fit and noise amplification and edge effects. Modest improvement in resolution is achieved for the 10.65 GHz channels, albeit with slight '' ringing '' in the vicinity of coastlines and other sharp brightness temperature gradients. For all other channels, resolution is coarsened to approximate the 18.7 GHz EFOV. It is shown that the resolution matching procedure reduces nonlinear correlations between channels in the presence of coastlines as well as enables the more efficient separation of large brightness temperature variations due to coastlines from the much smaller variations due to other geophysical variables. As a byproduct of this work, we report accurate EFOV resolutions as well as a self-consistent set of parameters for modeling the scan geometry of the GMI.
引用
收藏
页码:745 / 758
页数:14
相关论文
共 29 条
  • [1] Global Precipitation Measurement (GPM) Microwave Imager (GMI) instrument
    Bidwell, Steven W.
    SENSORS, SYSTEMS, AND NEXT-GENERATION SATELLITES X, 2006, 6361
  • [2] The global precipitation measurement (GPM) microwave imager (GMI) instrument: Role, performance, and status
    Bidwell, SW
    Flaming, GM
    Durning, JF
    Smith, EA
    IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, 2005, : 83 - 86
  • [3] Global Precipitation Measurement (GPM) Microwave Imager (GMI) After Four Years On-orbit
    Draper, David
    Newell, David
    2018 IEEE 15TH SPECIALIST MEETING ON MICROWAVE RADIOMETRY AND REMOTE SENSING OF THE ENVIRONMENT (MICRORAD), 2018, : 10 - 13
  • [4] Global Precipitation Measurement (GPM) Microwave Imager (GMI) Pre-flight Noise Diode Calibration
    Draper, David
    Newell, David
    2014 13TH SPECIALIST MEETING ON MICROWAVE RADIOMETRY AND REMOTE SENSING OF THE ENVIRONMENT (MICRORAD), 2014, : 167 - 170
  • [5] The Global Precipitation Measurement (GPM) Microwave Imager (GMI): Instrument Overview and Early On-Orbit Performance
    Draper, David W.
    Newell, David A.
    Wentz, Frank J.
    Krimchansky, Sergey
    Skofronick-Jackson, Gail M.
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2015, 8 (07) : 3452 - 3462
  • [6] Assessing Calibration Stability Using the Global Precipitation Measurement (GPM) Microwave Imager (GMI) Noise Diodes
    Draper, David W.
    Newell, David A.
    McKague, Darren S.
    Piepmeier, Jeffrey R.
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2015, 8 (09) : 4239 - 4247
  • [7] Microphysical properties of frozen particles inferred from Global Precipitation Measurement (GPM) Microwave Imager (GMI) polarimetric measurements
    Gong, Jie
    Wu, Dong L.
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2017, 17 (04) : 2741 - 2757
  • [8] Global Precipitation Measurement Microwave Imager (GMI) On-orbit Calibration
    Draper, David
    Newell, David
    Wentz, Frank
    2016 14TH SPECIALIST MEETING ON MICROWAVE RADIOMETRY AND REMOTE SENSING OF THE ENVIRONMENT (MICRORAD), 2016, : 166 - 169
  • [9] A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements
    Das, Spandan
    Wang, Yiding
    Gong, Jie
    Ding, Leah
    Munchak, Stephen J.
    Wang, Chenxi
    Wu, Dong L.
    Liao, Liang
    Olson, William S.
    Barahona, Donifan O.
    REMOTE SENSING, 2022, 14 (15)
  • [10] Development of a high-resolution and omnidirectional field-of-view neutron imager
    Liu, Linkang
    Gong, Hui
    Yu, Zerui
    Fan, Peng
    Lyu, Zhenlei
    Xu, Tianpeng
    Han, Yeliang
    Liu, Yaqiang
    Ma, Tianyu
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 2024, 1061