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Xia X, Che H, Shi H, Chen H, Zhang X, Wang P, Goloub P, Holben B. Advances in sunphotometer-measured aerosol optical properties and related topics in China: Impetus and perspectives. ATMOSPHERIC RESEARCH 2021; 249:105286. [PMID: 33012934 PMCID: PMC7518977 DOI: 10.1016/j.atmosres.2020.105286] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2020] [Revised: 09/21/2020] [Accepted: 09/21/2020] [Indexed: 06/02/2023]
Abstract
Aerosol is a critical trace component of the atmosphere. Many processes in the Earth's climate system are intimately related to aerosols via their direct and indirect radiative effects. Aerosol effects are not limited to these climatic aspects, however. They are also closely related to human health, photosynthesis, new energy, etc., which makes aerosol a central focus in many research fields. A fundamental requirement for improving our understanding of the diverse aerosol effects is to accumulate high-quality aerosol data by various measurement techniques. Sunphotometer remote sensing is one of the techniques that has been playing an increasingly important role in characterizing aerosols across the world. Much progress has been made on this aspect in China during the past decade, which is the work reviewed in this paper. Three sunphotometer networks have been established to provide high-quality observations of long-term aerosol optical properties across the country. Using this valuable dataset, our understanding of spatiotemporal variability and long-term trends of aerosol optical properties has been much improved. The radiative effects of aerosols both at the bottom and at the top of the atmosphere are comprehensively assessed. Substantial warming of the atmosphere by aerosol absorption is revealed. The long-range transport of dust from the Taklimakan Desert in Northwest China and anthropogenic aerosols from South Asia to the Tibetan Plateau is characterized based on ground-based and satellite remote sensing as well as model simulations. Effective methods to estimate chemical compositions from sunphotometer aerosol products are developed. Dozens of satellite and model aerosol products are validated, shedding new light on how to improve these products. These advances improve our understanding of the critical role played by aerosols in both the climate and environment. Finally, a perspective on future research is presented.
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Affiliation(s)
- Xiangao Xia
- LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huizheng Che
- State Key Laboratory of Severe Weather (LASW) and Key Laboratory of Atmospheric Chemistry (LAC), Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Hongrong Shi
- LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Hongbin Chen
- LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoye Zhang
- State Key Laboratory of Severe Weather (LASW) and Key Laboratory of Atmospheric Chemistry (LAC), Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Pucai Wang
- LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Phillipe Goloub
- Univ. Lille, CNRS, UMR 8518 - LOA - Laboratoire d'Optique Atmosphérique, F-59000 Lille, France
| | - Brent Holben
- Biospheric Sciences Branch, Code 923, NASA/Goddard Space Flight Center, Greenbelt, MD, USA
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The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future. REMOTE SENSING 2020. [DOI: 10.3390/rs12182900] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The Dark Target aerosol algorithm was developed to exploit the information content available from the observations of Moderate-Resolution Imaging Spectroradiometers (MODIS), to better characterize the global aerosol system. The algorithm is based on measurements of the light scattered by aerosols toward a space-borne sensor against the backdrop of relatively dark Earth scenes, thus giving rise to the name “Dark Target”. Development required nearly a decade of research that included application of MODIS airborne simulators to provide test beds for proto-algorithms and analysis of existing data to form realistic assumptions to constrain surface reflectance and aerosol optical properties. This research in itself played a significant role in expanding our understanding of aerosol properties, even before Terra MODIS launch. Contributing to that understanding were the observations and retrievals of the growing Aerosol Robotic Network (AERONET) of sun-sky radiometers, which has walked hand-in-hand with MODIS and the development of other aerosol algorithms, providing validation of the satellite-retrieved products after launch. The MODIS Dark Target products prompted advances in Earth science and applications across subdisciplines such as climate, transport of aerosols, air quality, and data assimilation systems. Then, as the Terra and Aqua MODIS sensors aged, the challenge was to monitor the effects of calibration drifts on the aerosol products and to differentiate physical trends in the aerosol system from artefacts introduced by instrument characterization. Our intention is to continue to adapt and apply the well-vetted Dark Target algorithms to new instruments, including both polar-orbiting and geosynchronous sensors. The goal is to produce an uninterrupted time series of an aerosol climate data record that begins at the dawn of the 21st century and continues indefinitely into the future.
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Validation of MODIS C6.1 and MERRA-2 AOD Using AERONET Observations: A Comparative Study over Turkey. ATMOSPHERE 2020. [DOI: 10.3390/atmos11090905] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This study validated MODIS (Moderate Resolution Imaging Spectroradiometer) of the National Aeronautics and Space Agency, USA, Aqua and Terra Collection 6.1, and MERRA-2 (Modern-ERA Retrospective Analysis for Research and Application) Version 2 of aerosol optical depth (AOD) at 550 nm against AERONET (Aerosol Robotic Network) ground-based sunphotometer observations over Turkey. AERONET AOD data were collected from three sites during the period between 2013 and 2017. Regression analysis showed that overall, seasonally and daily statistics of MODIS are better than MERRA-2 by the mean of coefficient of determination (R2), mean absolute error (MAE), and relative root mean square deviation (RMSDrel). MODIS combined Terra/Aqua AOD and MERRA-2 AOD corresponding to morning and noon hours resulted in better results than individual sub datasets. A clear annual cycle in AOD was detected by the three platforms. However, overall, MODIS and MERRA-2 tend to overestimate and underestimate AOD, respectively, in comparison with AERONET. MODIS showed higher efficiency in detecting extreme events than MERRA-2. There was no clear relation found between the accuracy in MODIS/MERRA-2 AOD and surface relative humidity (RH).
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