当前位置： 首页»科研成果» 2013 Retrieval of aerosol optical depth and surface reflectance over land from NOAA AVHRR data 李英杰

 

Yingjie Li ^a,h,i, Yong Xue ^a,b, Gerrit de Leeuw ^c,d,e, Chi Li ^f,h, Leiku Yang ^g, Tingting Hou ^f,h, Farhi Marir ^b

^a State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101, China;

^b Faculty of Life Sciences and Computing, London Metropolitan University, London N7 8DB, UK;

^c Department of Physics, University of Helsinki, Helsinki, Finland;

^d Finnish Meteorological Institute, Climate Change Unit, Helsinki, Finland;

^e Netherlands Organisation for Applied Scientific Research TNO, Utrecht, The Netherlands;

^f Center for Earth Observation and Digital Earth of Chinese Academy of Sciences, Beijing 100094, China;

^g School of Geography, Beijing Normal University, Beijing 100875, China;

^h University of the Chinese Academy of Sciences, Beijing 100049, China;

ⁱ College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China.

 

ABSTRACT

An algorithm for the land aerosol and bidirectional reflectance inversion by times series technique (LABITS) is proposed and applied to data from the National Oceanic and Atmospheric Administration (NOAA) advanced very high resolution radiometer (AVHRR). The surface reflectance and aerosol optical depth are inverted from AVHRR Channel 1 data using a model for the earth-atmosphere system which couples an atmospheric radiative transfer model with the Ross–Thick–Li-sparse bidirectional reflectance factor (BRF) model. Basic assumptions are that the surface bidirectional reflective property does not vary over a 2–4 day periods and that the aerosol characteristics are uniform within a 0.1° × 0.1° window (approximately 10 km × 10 km). The LABITS algorithm is applied to data from AVHRR on the NOAA-15, NOAA-16, and NOAA-18 satellites over four distinct areas, namely, North America, Europe, the Sahara and India, to simultaneously retrieve the aerosol optical depth (AOD), BRF parameters and surface albedo. Preliminary results show that AOD and reflectance retrieved from the three different instruments are in good agreement and that LABITS provides good results over both bright surfaces, e.g. the Sahara, and dark surfaces, e.g. Europe. Evaluation of the AOD versus data from the Aerosol Robotic Network (AERONET) provides a correlation coefficient R2 of 0.88 and a root-mean-square error (RMSE) of approximately 0.07; and the uncertainty is approximately Δτ = ± 0.05 ± 0.20τ. Comparing our results with the moderate resolution imaging spectroradiometer (MODIS) AOD products, over many areas, provides biases in the range of ± 0.05. The surface albedo values calculated from the retrieved BRF parameters are similar to those provided by the MODIS albedo product (MCD43). The robustness and applicability of the LABITS algorithm are demonstrated with the retrieval of AOD over China during August 2008. Daily and monthly averaged results show good agreement with collocated AERONET observations and AQUA MODIS products (MYD04 and MYD08). The AOD uncertainty is estimated as Δτ = ± 0.05 ± 0.30τ. The preliminary analysis of time series over selected AERONET sites shows that the temporal variations of the AOD values retrieved by application of LABITS to AVHRR data are overall similar to temporal variations of AOD provided by the MODIS and AERONET. The algorithm has the potential to retrieve global AOD over land for long time series of NOAA AVHRR data going back to the 1980s, which are urgently needed for studies on aerosol climatology and global climate change.

 

KEY WORDS: AVHRR; Aerosol; Optical depth; Bidirectional reflectance; Albedo; Time series

 

PUBLISHED IN: REMOTE SENSING OF ENVIRONMENT, 2013, 133: 1-20.

 

SOURCE: http://www.sciencedirect.com/science/article/pii/S0034425713000382