DOI: 10.5194/hess-20-3263-2016
Scopus记录号: 2-s2.0-84982171425
论文题名: Cloud tolerance of remote-sensing technologies to measure land surface temperature
作者: Holmes T ; R ; H ; , Hain C ; R ; , Anderson M ; C ; , Crow W ; T
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2016
卷: 20, 期: 8 起始页码: 3263
结束页码: 3275
语种: 英语
Scopus关键词: Geostationary satellites
; Orbits
; Remote sensing
; Surface measurement
; Surface properties
; Conventional methods
; Diurnal temperature cycles
; Land surface temperature
; Passive microwaves
; Polar-orbiting satellites
; Remote sensing technology
; Satellite retrieval
; Stable performance
; Atmospheric temperature
; clear sky
; cloud
; cloud cover
; land surface
; microwave imagery
; performance assessment
; remote sensing
; satellite
; surface temperature
英文摘要: Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive-microwave (MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25° resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR-based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications. © 2016 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78763
Appears in Collections: 气候变化事实与影响
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作者单位: Hydrology and Remote Sensing Lab., USDA-ARS, Beltsville, MD, United States; Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, United States; Earth Science Interdisciplinary Center, University of Maryland, College Park, MD, United States
Recommended Citation:
Holmes T,R,H,et al. Cloud tolerance of remote-sensing technologies to measure land surface temperature[J]. Hydrology and Earth System Sciences,2016-01-01,20(8)