Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns
The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exi...
Main Authors: | , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2018-02-01
|
Series: | Atmospheric Chemistry and Physics |
Online Access: | https://www.atmos-chem-phys.net/18/1573/2018/acp-18-1573-2018.pdf |
id |
doaj-54f9e172e64f4141a64995955bf99cff |
---|---|
record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
G. de Leeuw L. Sogacheva E. Rodriguez K. Kourtidis A. K. Georgoulias G. Alexandri V. Amiridis E. Proestakis E. Proestakis E. Marinou Y. Xue R. van der A |
spellingShingle |
G. de Leeuw L. Sogacheva E. Rodriguez K. Kourtidis A. K. Georgoulias G. Alexandri V. Amiridis E. Proestakis E. Proestakis E. Marinou Y. Xue R. van der A Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns Atmospheric Chemistry and Physics |
author_facet |
G. de Leeuw L. Sogacheva E. Rodriguez K. Kourtidis A. K. Georgoulias G. Alexandri V. Amiridis E. Proestakis E. Proestakis E. Marinou Y. Xue R. van der A |
author_sort |
G. de Leeuw |
title |
Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns |
title_short |
Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns |
title_full |
Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns |
title_fullStr |
Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns |
title_full_unstemmed |
Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns |
title_sort |
two decades of satellite observations of aod over mainland china using atsr-2, aatsr and modis/terra: data set evaluation and large-scale patterns |
publisher |
Copernicus Publications |
series |
Atmospheric Chemistry and Physics |
issn |
1680-7316 1680-7324 |
publishDate |
2018-02-01 |
description |
The retrieval of aerosol properties from satellite observations
provides their spatial distribution over a wide area in cloud-free
conditions. As such, they complement ground-based measurements by providing
information over sparsely instrumented areas, albeit that significant
differences may exist in both the type of information obtained and the
temporal information from satellite and ground-based observations. In this
paper, information from different types of satellite-based instruments is
used to provide a 3-D climatology of aerosol properties over mainland China,
i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol
Lidar with Orthogonal Polarization (CALIOP), a lidar flying
aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation
(CALIPSO) satellite and the column-integrated extinction (aerosol optical depth – AOD)
available from three radiometers: the European Space Agency (ESA)'s Along-Track
Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to
as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995–2015. AOD
data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS
Collection 6 (C6) the AOD data set is used that was obtained from merging the
AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further
referred to as the DTDB merged AOD product. These data sets are
validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data
as reference. The results show that, over China, ATSR slightly underestimates
the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is
overall lower than that from MODIS, and the difference increases with
increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD
data sets is better than the other one everywhere. However, ATSR ADV has
limitations over bright surfaces which the MODIS DB was designed for. To
allow for comparison of MODIS C6 results with previous analyses where MODIS
Collection 5.1 (C5.1) data were used, also the difference between the C6 and
C5.1 merged DTDB data sets from MODIS/Terra over China is briefly discussed.
<br><br>
The AOD data sets show strong seasonal differences and the seasonal features
vary with latitude and longitude across China. Two-decadal AOD time series,
averaged over all of mainland China, are presented and briefly discussed.
Using the 17 years of ATSR data as the basis and MODIS/Terra to follow
the temporal evolution in recent years when the environmental satellite Envisat was lost requires a
comparison of the data sets for the overlapping period to show their
complementarity. ATSR precedes the MODIS time series between 1995 and 2000
and shows a distinct increase in the AOD over this period. The two data
series show similar variations during the overlapping period between 2000 and
2011, with minima and maxima in the same years. MODIS extends this time
series beyond the end of the Envisat period in 2012, showing decreasing AOD. |
url |
https://www.atmos-chem-phys.net/18/1573/2018/acp-18-1573-2018.pdf |
work_keys_str_mv |
AT gdeleeuw twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns AT lsogacheva twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns AT erodriguez twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns AT kkourtidis twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns AT akgeorgoulias twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns AT galexandri twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns AT vamiridis twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns AT eproestakis twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns AT eproestakis twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns AT emarinou twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns AT yxue twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns AT rvandera twodecadesofsatelliteobservationsofaodovermainlandchinausingatsr2aatsrandmodisterradatasetevaluationandlargescalepatterns |
_version_ |
1725184640252116992 |
spelling |
doaj-54f9e172e64f4141a64995955bf99cff2020-11-25T01:08:03ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242018-02-01181573159210.5194/acp-18-1573-2018Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patternsG. de Leeuw0L. Sogacheva1E. Rodriguez2K. Kourtidis3A. K. Georgoulias4G. Alexandri5V. Amiridis6E. Proestakis7E. Proestakis8E. Marinou9Y. Xue10R. van der A11Finnish Meteorological Institute (FMI), Climate Research Unit, Helsinki, FinlandFinnish Meteorological Institute (FMI), Climate Research Unit, Helsinki, FinlandFinnish Meteorological Institute (FMI), Climate Research Unit, Helsinki, FinlandLaboratory of Atmospheric Pollution and Pollution Control Engineering of Atmospheric Pollutants, Department of Environmental Engineering, Democritus University of Thrace, Xanthi, GreeceLaboratory of Atmospheric Pollution and Pollution Control Engineering of Atmospheric Pollutants, Department of Environmental Engineering, Democritus University of Thrace, Xanthi, GreeceLaboratory of Atmospheric Pollution and Pollution Control Engineering of Atmospheric Pollutants, Department of Environmental Engineering, Democritus University of Thrace, Xanthi, GreeceNational Observatory Athens (NOA), Athens, GreeceNational Observatory Athens (NOA), Athens, GreeceLaboratory of Atmospheric Physics, Department of Physics, University of Patras, Patras, GreeceNational Observatory Athens (NOA), Athens, GreeceDepartment of Electronics, Computing and Mathematics, College of Engineering and Technology, University of Derby, Derby, UKRoyal Netherlands Meteorological Institute (KNMI), De Bilt, the NetherlandsThe retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a lidar flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the column-integrated extinction (aerosol optical depth – AOD) available from three radiometers: the European Space Agency (ESA)'s Along-Track Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995–2015. AOD data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS Collection 6 (C6) the AOD data set is used that was obtained from merging the AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further referred to as the DTDB merged AOD product. These data sets are validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data as reference. The results show that, over China, ATSR slightly underestimates the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is overall lower than that from MODIS, and the difference increases with increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces which the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 merged DTDB data sets from MODIS/Terra over China is briefly discussed. <br><br> The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over all of mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when the environmental satellite Envisat was lost requires a comparison of the data sets for the overlapping period to show their complementarity. ATSR precedes the MODIS time series between 1995 and 2000 and shows a distinct increase in the AOD over this period. The two data series show similar variations during the overlapping period between 2000 and 2011, with minima and maxima in the same years. MODIS extends this time series beyond the end of the Envisat period in 2012, showing decreasing AOD.https://www.atmos-chem-phys.net/18/1573/2018/acp-18-1573-2018.pdf |