Atmospheric and Forest Decoupling of Passive Microwave Brightness Temperature Observations Over Snow-Covered Terrain in North America

被引:12
|
作者
Xue, Yuan [1 ]
Forman, Barton A. [1 ]
机构
[1] Univ Maryland, Dept Civil & Environm Engn, College Pk, MD 20742 USA
关键词
AMSR-E; atmosphere; brightness temperature; forest; LAI; microwave; passive; snow; LEAF-AREA INDEX; WATER EQUIVALENT; IN-SITU; SEASONAL SNOW; SOIL-MOISTURE; DEPTH-HOAR; REMOTE; MODEL; LAND; RETRIEVALS;
D O I
10.1109/JSTARS.2016.2614158
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This study addresses two significant sources of uncertainty prevalent in snow water equivalent (SWE) retrievals derived from advanced microwave scanning radiometer (AMSR-E) passive microwave (PMW) brightness temperature (Tb) observations at 18.7 and 36.5 GHz. Namely, atmospheric and overlying forest effects are decoupled from the original AMSR-E PMW Tb observations using relatively simple, physically based radiative transfer models. Comparisons against independent Tb measurements collected during airborne PMWTb surveys highlight the effectiveness of the proposed AMSR-E atmospheric decoupling procedure. The atmospheric contribution to Tb ranges from 1 to 3 K depending on the frequency and polarization measured as well as meteorologic conditions at the time of AMSR-E overpass. It is further shown that forest decoupling should be conducted as a function of both land cover type and snow cover class. The exponential decay relationship between the forest structure parameter, namely, MODIS-derived leaf area index (LAI) and forest transmissivity, is fitted across snow-covered terrain in North America. The fitted exponential function can be utilized during forest decoupling activities for evergreen needle-leaved forest and woody savanna regions, but remains uncertain in other forest types due to a sparsity of snow-covered areas. By removing forest-related Tb contributions from the original AMSR-E observations, the results suggest that Tb spectral difference between 18.7 and 36.5 GHz, in general, increases across thinly vegetated to heavily vegetated regions, which can be beneficial when applied to traditional SWE retrieval algorithms.
引用
收藏
页码:3172 / 3189
页数:18
相关论文
共 33 条
  • [1] A review of passive microwave observations of snow-covered areas over complex Arctic terrain
    Alimasi, Nuerasimuguli
    [J]. BULLETIN OF GLACIOLOGICAL RESEARCH, 2018, 36 : 1 - 13
  • [2] The HUT brightness temperature model for snow-covered terrain
    Hallikainen, M
    Pulliainen, J
    Kurvonen, L
    Grandell, J
    [J]. IGARSS '97 - 1997 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS I-IV: REMOTE SENSING - A SCIENTIFIC VISION FOR SUSTAINABLE DEVELOPMENT, 1997, : 622 - 624
  • [3] Estimating Passive Microwave Brightness Temperature Over Snow-Covered Land in North America Using a Land Surface Model and an Artificial Neural Network
    Forman, Barton A.
    Reichle, Rolf H.
    Derksen, Chris
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2014, 52 (01): : 235 - 248
  • [4] Investigation of passive microwave signatures over snow-covered forest areas
    Kruopis, N
    Koskinen, J
    Praks, J
    Arslan, AN
    Alasalmi, H
    Hallikainen, M
    [J]. IGARSS '98 - 1998 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS 1-5: SENSING AND MANAGING THE ENVIRONMENT, 1998, : 1544 - 1546
  • [5] Passive Microwave Brightness Temperature Scaling Over Snow Covered Boreal Forest and Tundra
    Derksen, Chris
    Strapp, J. Walter
    Walker, Anne
    [J]. 2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, 2006, : 3762 - 3765
  • [6] Analyzing Machine Learning Predictions of Passive Microwave Brightness Temperature Spectral Difference Over Snow-Covered Terrain in High Mountain Asia
    Ahmad, Jawairia A.
    Forman, Barton A.
    Kwon, Yonghwan
    [J]. FRONTIERS IN EARTH SCIENCE, 2019, 7
  • [7] Comparison of passive microwave brightness temperature prediction sensitivities over snow-covered land in North America using machine learning algorithms and the Advanced Microwave Scanning Radiometer
    Xue, Yuan
    Forman, Barton A.
    [J]. REMOTE SENSING OF ENVIRONMENT, 2015, 170 : 153 - 165
  • [8] Passive microwave measurements of snow-covered forest areas in EMAC'95
    Kruopis, N
    Praks, J
    Arslan, AN
    Alasalmi, HM
    Koskinen, JT
    Hallikainen, MT
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1999, 37 (06): : 2699 - 2705
  • [9] Machine learning predictions of passive microwave brightness temperature over snow-covered land using the special sensor microwave imager (SSM/I)
    Forman, Barton A.
    Xue, Yuan
    [J]. PHYSICAL GEOGRAPHY, 2017, 38 (02) : 176 - 196
  • [10] Observation and Modeling of the Microwave Brightness Temperature of Snow-Covered Frozen Lakes and Wetlands
    Kontu, Anna
    Lemmetyinen, Juha
    Pulliainen, Jouni
    Seppanen, Jaakko
    Hallikainen, Martti T.
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2014, 52 (06): : 3275 - 3288