Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1109/TGRS.2020.3036248 |
A Method for Deriving Relative Humidity From MODIS Data Under All-Sky Conditions | |
Liao, Qian-Yu; Leng, Pei; Li, Zhao-Liang; Ren, Chao; Sun, Ya-Yong; Gao, Mao-Fang; Duan, Si-Bo; Shang, Guo-Fei | |
通讯作者 | Leng, P (corresponding author), Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China. |
来源期刊 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
![]() |
ISSN | 0196-2892 |
EISSN | 1558-0644 |
出版年 | 2021 |
卷号 | 59期号:11页码:8992-9006 |
英文摘要 | Relative humidity (RH) is one of the key variables for understanding the water, energy, and carbon exchange between the Earth and the atmosphere. Traditional methods for deriving RH from remotely sensed data usually require ground meteorological observations or are limited to clear-sky conditions, thereby making it a significant challenge to obtain spatially complete RH under all-sky conditions, especially over the regions with sparse meteorological instruments for observation. To this end, a new approach for deriving all-sky RH entirely based on Moderate Resolution Imaging Spectroradiometer (MODIS) data was proposed in the present study. Two key assumptions in the approach under cloudy conditions are that the actual water vapor is linearly related to the total precipitable water vapor (PWV) and that air temperature is linearly related to land surface temperature (LST). Results from a total of 30 AmeriFlux stations proved the aforementioned assumptions based on MODIS data collected over a study period of three years from 2009 to 2011. For different aridity conditions, RH retrieval revealed reasonable accuracy with a root-mean-square error (RMSE) of approximately 15.3% over an arid and semiarid region, whereas a comparable RMSE of 17.0% was obtained over a humid area. Further results also indicated that the aforementioned linear relationships were generally temporally stable, thereby indicating that the proposed method can be used to obtain all-sky RH at a regional or global scale entirely based on MOD06_L2-derived LST and MOD05_L2-derived PWV data given that the assumed linear relationships can be easily determined by historical MOD07_L2-derived atmospheric profiles. |
英文关键词 | Clouds Land surface temperature Satellites MODIS Mathematical model Humidity Remote sensing All-sky atmospheric profile land surface temperature (LST) precipitable water vapor (PWV) relative humidity (RH) |
类型 | Article |
语种 | 英语 |
收录类别 | SCI-E |
WOS记录号 | WOS:000711850900010 |
WOS关键词 | VAPOR-PRESSURE DEFICIT ; MINIMUM AIR-TEMPERATURE ; NEAR-SURFACE AIR ; WATER-VAPOR ; CLIMATE VARIABILITY ; PRECIPITABLE WATER ; DAILY MAXIMUM ; EVAPOTRANSPIRATION ; MOISTURE ; TRENDS |
WOS类目 | Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
来源机构 | 中国科学院地理科学与资源研究所 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/368090 |
作者单位 | [Liao, Qian-Yu; Leng, Pei; Li, Zhao-Liang; Gao, Mao-Fang; Duan, Si-Bo] Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China; [Liao, Qian-Yu] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; [Ren, Chao] Guilin Univ Technol, Coll Geomat & Geoinformat, Guilin 530001, Peoples R China; [Sun, Ya-Yong] China Inst Water Resources & Hydropower Res, Beijing 100038, Peoples R China; [Shang, Guo-Fei] Hebei GEO Univ, Sch Land Resources & Urban Rural Planning, Shijiazhuang 050031, Hebei, Peoples R China |
推荐引用方式 GB/T 7714 | Liao, Qian-Yu,Leng, Pei,Li, Zhao-Liang,et al. A Method for Deriving Relative Humidity From MODIS Data Under All-Sky Conditions[J]. 中国科学院地理科学与资源研究所,2021,59(11):8992-9006. |
APA | Liao, Qian-Yu.,Leng, Pei.,Li, Zhao-Liang.,Ren, Chao.,Sun, Ya-Yong.,...&Shang, Guo-Fei.(2021).A Method for Deriving Relative Humidity From MODIS Data Under All-Sky Conditions.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,59(11),8992-9006. |
MLA | Liao, Qian-Yu,et al."A Method for Deriving Relative Humidity From MODIS Data Under All-Sky Conditions".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 59.11(2021):8992-9006. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。