Investigations into the development of a satellite-based aerosol climate data record using ATSR-2, AATSR and AVHRR data over north-eastern China from 1987 to 2012
<p>Satellites provide information on the temporal and spatial distributions of aerosols on regional and global scales. With the same method applied to a single sensor all over the world, a consistent data set is to be expected. However, the application of different retrieval algorithms to the...
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2019-07-01
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English |
format |
Article |
sources |
DOAJ |
author |
Y. Che Y. Che J. Guang G. de Leeuw G. de Leeuw Y. Xue L. Sun H. Che |
spellingShingle |
Y. Che Y. Che J. Guang G. de Leeuw G. de Leeuw Y. Xue L. Sun H. Che Investigations into the development of a satellite-based aerosol climate data record using ATSR-2, AATSR and AVHRR data over north-eastern China from 1987 to 2012 Atmospheric Measurement Techniques |
author_facet |
Y. Che Y. Che J. Guang G. de Leeuw G. de Leeuw Y. Xue L. Sun H. Che |
author_sort |
Y. Che |
title |
Investigations into the development of a satellite-based aerosol climate data record using ATSR-2, AATSR and AVHRR data over north-eastern China from 1987 to 2012 |
title_short |
Investigations into the development of a satellite-based aerosol climate data record using ATSR-2, AATSR and AVHRR data over north-eastern China from 1987 to 2012 |
title_full |
Investigations into the development of a satellite-based aerosol climate data record using ATSR-2, AATSR and AVHRR data over north-eastern China from 1987 to 2012 |
title_fullStr |
Investigations into the development of a satellite-based aerosol climate data record using ATSR-2, AATSR and AVHRR data over north-eastern China from 1987 to 2012 |
title_full_unstemmed |
Investigations into the development of a satellite-based aerosol climate data record using ATSR-2, AATSR and AVHRR data over north-eastern China from 1987 to 2012 |
title_sort |
investigations into the development of a satellite-based aerosol climate data record using atsr-2, aatsr and avhrr data over north-eastern china from 1987 to 2012 |
publisher |
Copernicus Publications |
series |
Atmospheric Measurement Techniques |
issn |
1867-1381 1867-8548 |
publishDate |
2019-07-01 |
description |
<p>Satellites provide information on the temporal and spatial
distributions of aerosols on regional and global scales. With the same
method applied to a single sensor all over the world, a consistent data set
is to be expected. However, the application of different retrieval
algorithms to the same sensor and the use of a series of different sensors
may lead to substantial differences, and no single sensor or algorithm is
better than any other everywhere and at all times. For the production of
long-term climate data records, the use of multiple sensors cannot be
avoided. The Along Track Scanning Radiometer (ATSR-2) and the Advanced ATSR
(AATSR) aerosol optical depth (AOD) data sets have been used to provide a
global AOD data record over land and ocean of 17 years (1995–2012), which is
planned to be extended with AOD retrieved from a similar sensor. To
investigate the possibility of extending the ATSR data record to earlier years,
the use of an AOD data set from the Advanced Very High Resolution Radiometer
(AVHRR) is investigated. AOD data sets used in this study were retrieved
from the ATSR sensors using the ATSR Dual View algorithm ADV version 2.31, developed
by Finnish Meteorological Institute (FMI), and from the AVHRR sensors using
the aerosol optical depth over land (ADL) algorithm developed by RADI/CAS. Together, these data sets cover a
multi-decadal period (1987–2012). The study area includes two contrasting
areas, both in regards to aerosol content and composition and surface
properties, i.e. a region over north-eastern China, encompassing a highly
populated urban/industrialized area (Beijing–Tianjin–Hebei) and a sparsely
populated mountainous area.</p>
<p>Ground-based AOD observations available from ground-based sun photometer AOD
data in AERONET and CARSNET are used as a reference, together with broadband
extinction method (BEM) data at Beijing to cover the time before sun
photometer observations became available in the early 2000s. In addition,
MODIS-Terra C6.1 AOD data are used as a reference data set over the wide area
where no ground-based data are available. All satellite data over the study
area were validated against the reference data, showing the qualification of
MODIS for comparison with ATSR and AVHRR. The comparison with MODIS shows
that AVHRR performs better than ATSR in the north of the study area
(40<span class="inline-formula"><sup>∘</sup></span> N), whereas further south ATSR provides better results. The
validation against sun photometer AOD shows that both AVHRR and ATSR
underestimate the AOD, with ATSR<span id="page4092"/> failing to provide reliable results in the
wintertime. This is likely due to the highly reflecting surface in the dry
season, when AVHRR-retrieved AOD traces both MODIS and reference AOD data
well. However, AVHRR does not provide AOD larger than about 0.6 and hence is
not reliable when high AOD values have been observed over the last decade.
In these cases, ATSR performs much better for AOD up to about 1.3.
AVHRR-retrieved AOD compares favourably with BEM AOD, except
for AOD higher than about 0.6. These comparisons lead to the conclusion that
AVHRR and ATSR AOD data records each have their strengths and weaknesses
that need to be accounted for when combining them in a single multi-decadal
climate data record.</p> |
url |
https://www.atmos-meas-tech.net/12/4091/2019/amt-12-4091-2019.pdf |
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doaj-381960561b294279bf44ba4133ceba502020-11-25T02:34:56ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482019-07-01124091411210.5194/amt-12-4091-2019Investigations into the development of a satellite-based aerosol climate data record using ATSR-2, AATSR and AVHRR data over north-eastern China from 1987 to 2012Y. Che0Y. Che1J. Guang2G. de Leeuw3G. de Leeuw4Y. Xue5L. Sun6H. Che7Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (RADI/CAS), Beijing 100094, ChinaUniversity of Chinese Academy of Sciences, Beijing, 100049, ChinaKey Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (RADI/CAS), Beijing 100094, ChinaFinnish Meteorological Institute, Climate Research Programme, P.O. Box 503, 00101 Helsinki, FinlandSchool of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaDepartment of Electronics, Computing and Mathematics, College of Engineering and Technology, University of Derby, Derby, DE22 1GB, UKKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites (LRCVES/CMA), National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, ChinaState Key Laboratory of Severe Weather and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China<p>Satellites provide information on the temporal and spatial distributions of aerosols on regional and global scales. With the same method applied to a single sensor all over the world, a consistent data set is to be expected. However, the application of different retrieval algorithms to the same sensor and the use of a series of different sensors may lead to substantial differences, and no single sensor or algorithm is better than any other everywhere and at all times. For the production of long-term climate data records, the use of multiple sensors cannot be avoided. The Along Track Scanning Radiometer (ATSR-2) and the Advanced ATSR (AATSR) aerosol optical depth (AOD) data sets have been used to provide a global AOD data record over land and ocean of 17 years (1995–2012), which is planned to be extended with AOD retrieved from a similar sensor. To investigate the possibility of extending the ATSR data record to earlier years, the use of an AOD data set from the Advanced Very High Resolution Radiometer (AVHRR) is investigated. AOD data sets used in this study were retrieved from the ATSR sensors using the ATSR Dual View algorithm ADV version 2.31, developed by Finnish Meteorological Institute (FMI), and from the AVHRR sensors using the aerosol optical depth over land (ADL) algorithm developed by RADI/CAS. Together, these data sets cover a multi-decadal period (1987–2012). The study area includes two contrasting areas, both in regards to aerosol content and composition and surface properties, i.e. a region over north-eastern China, encompassing a highly populated urban/industrialized area (Beijing–Tianjin–Hebei) and a sparsely populated mountainous area.</p> <p>Ground-based AOD observations available from ground-based sun photometer AOD data in AERONET and CARSNET are used as a reference, together with broadband extinction method (BEM) data at Beijing to cover the time before sun photometer observations became available in the early 2000s. In addition, MODIS-Terra C6.1 AOD data are used as a reference data set over the wide area where no ground-based data are available. All satellite data over the study area were validated against the reference data, showing the qualification of MODIS for comparison with ATSR and AVHRR. The comparison with MODIS shows that AVHRR performs better than ATSR in the north of the study area (40<span class="inline-formula"><sup>∘</sup></span> N), whereas further south ATSR provides better results. The validation against sun photometer AOD shows that both AVHRR and ATSR underestimate the AOD, with ATSR<span id="page4092"/> failing to provide reliable results in the wintertime. This is likely due to the highly reflecting surface in the dry season, when AVHRR-retrieved AOD traces both MODIS and reference AOD data well. However, AVHRR does not provide AOD larger than about 0.6 and hence is not reliable when high AOD values have been observed over the last decade. In these cases, ATSR performs much better for AOD up to about 1.3. AVHRR-retrieved AOD compares favourably with BEM AOD, except for AOD higher than about 0.6. These comparisons lead to the conclusion that AVHRR and ATSR AOD data records each have their strengths and weaknesses that need to be accounted for when combining them in a single multi-decadal climate data record.</p>https://www.atmos-meas-tech.net/12/4091/2019/amt-12-4091-2019.pdf |