monitoring aerosols in china with aatsr anu-maija sundström 2 gerrit de leeuw 1 pekka kolmonen 1,...

16
Monitoring aerosols in Monitoring aerosols in China with AATSR China with AATSR Anu-Maija Sundström Anu-Maija Sundström 2 Gerrit de Leeuw Gerrit de Leeuw 1 Pekka Kolmonen Pekka Kolmonen 1 , and Larisa , and Larisa Sogacheva Sogacheva 1 AMFIC. 24.6.2009, Barcelona AMFIC. 24.6.2009, Barcelona 1: Finnish Meteorological 1: Finnish Meteorological Institute Institute 2: University of Helsinki 2: University of Helsinki

Upload: ethan-hill

Post on 05-Jan-2016

213 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

Monitoring aerosols in Monitoring aerosols in China with AATSRChina with AATSR

Anu-Maija SundströmAnu-Maija Sundström22

Gerrit de LeeuwGerrit de Leeuw11

Pekka KolmonenPekka Kolmonen11, and Larisa , and Larisa SogachevaSogacheva11

AMFIC. 24.6.2009, BarcelonaAMFIC. 24.6.2009, Barcelona

1: Finnish Meteorological Institute1: Finnish Meteorological Institute

2: University of Helsinki2: University of Helsinki

Page 2: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

Presentation outlinePresentation outline

A short overview of the current AATSR aerosol algorithm over land

Comparison with the AERONET data

Datasets and the Web page

Page 3: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

The AATSR Dual View The AATSR Dual View (ADV) algorithm(ADV) algorithm Used to monitor aerosol optical

properties over land The algorithm exploits the AATSR

measurements made in two viewing angles (nadir and 55° forward ) to exclude the surface contribution from the measured TOA-reflectance.

Over ocean a single view algorithm is used

The retrieved parameters include aerosol optical depth at 555, 659, and 1600 nm wave lengths, mixing ratio and Ångström coefficient at 1x1 km2 resolution.

55

Page 4: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

New implementations Modified linear-mixing

method After Abdou et al.,

1997 To reduce the AOD

overestimation by AATSR

Interpolation between the AOD levels

Several new aerosol models

Based on AERONET observations (Dubovik et (Dubovik et al. 2002, Levy et al. 2007)al. 2002, Levy et al. 2007)

Current status of the ADV algorithm

Page 5: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

Aerosol modelsAerosol models

Fine mode models (reff ~ 0.1 µm)

• Sulphate type aerosol• Industrial pollution• Dirty pollution

Coarse mode models (reff ~1 µm)

• Neutral • Mineral type aerosol

• In each retrieval two aerosol model are mixed• The best mixture for each case (pixel) is found by the least squares method in the iteration procedure.

Page 6: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

Comparison with the AERONET Comparison with the AERONET measurementsmeasurements

The goal is to find the most plausible aerosol models for large dataset processing.

Available AERONET stations are centered either around Beijing or Shanghai area.

large interesting areas remain still uncovered.

Studied months (Mar.-Nov. 2008) are selected by the availability of the AERONET-data.

Beijing, XiangHe, Xin-glong

Hefei, NUIST, Shouxian, Qiandaohu, LA-TM, Hangzhou, and Ningbo

Page 7: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

1.5 and 2.0 level AERONET-data is used The monthly number of collocated AATSR and AERONET observations can

vary a lot.

Since the retrieved AODs can vary depending on which aerosol models are used, the AATSR retrievals for each AERONET station are done with all the possible combinations of the five models.

Page 8: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

On average the best agreement with the AERONET AOD at the Beijing area was obtained with the combination of industrial or dirty pollution and neutral coarse model aerosol.

During the summer months the mixing ratio for fine particles was about 100%

the best agreement was obtained with a mixture of sulphate and dirty or best agreement was obtained with a mixture of sulphate and dirty or industrial pollution.industrial pollution.

To some degree the best aerosol model combinations depended on the location (urban, rural) and season and/or the origin of the airflow.

AOD 555nm 7.3.2009 Note different scales

Page 9: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

At Shanghai area the fine mode fraction was near 100% most of the time with the exception of the summer months.

During the summer months, the industrial pollution combined with the neutral coarse model was mainly the optimal combination.

Hangzhou City 20.5.2008

Qiandaohu 20.5.2008

AOD 555 nm 20.5.2008

Page 10: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

The AATSR ADV retrieval algorithm works for a wide range of AODs and for different aerosol types.

Page 11: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

Dust and smog episodes has been shown to be extremely difficult cases for the different satellite algorithms, also for the AATSR ADV.

RGB-composite BT 11 microns - BT12 microns

The dense dust plume over Beijing (Mar 2008) was almost completely missed by the algorithm. We are testing alternative methods for detecting dust.

For the smog episodes, the best agreement was obtained with dirty pollution and sulphate aerosol. The AATSR AOD pattern is correctly retrieved but the absolute values remain underestimated.

Page 12: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

Based on the results from collocated AATSR-AERONET comparisons, the combination of industrial pollution – neutral coarse mode aerosol was selected to the larger dataset processing.

Page 13: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

Datasets and Web-pageDatasets and Web-page

AATSR retrievals over China are produced for Mar-Nov 2008 (dataset 1.0) Figures: AOD at 555 nm with 1x1 km2

resolution Retrievals for specific AERONET stations as

a 25 km x 25 km spatial averages.

Web page: http://AATSRaerosol.fmi.fiWeb page: http://AATSRaerosol.fmi.fi

Page 14: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:
Page 15: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

First 13 letters in the file name refer to the AATSR aerosol modelContents: Aeronet sitename, Year, Month, Day, Hour, Minute AOD 555 nm, std AOD555, AOD 659 nm, std AOD659, AOD 1600 nm, std AOD1600,mixratio1 and std mixratio1

AATSR data is being collected from 25x25 km2 AOD distributions.AATSR data point has to be closer than 12.5 km to an Aeronet site to be accepted.

Hangzhou_City 2008 8 14 1 24 0.97303 0.13738 0.67139 0.10494 0.07817 0.03798 0.98758 0.01763Hangzhou_City 2008 8 17 1 30 2.33027 0.67590 1.62357 0.50255 0.18589 0.09586 1.00000 0.00000Hangzhou_City 2008 8 27 1 16 0.78876 0.10022 0.54880 0.06865 0.07022 0.02553 0.97778 0.02473 Hefei 2008 8 4 1 38 1.91194 0.43644 1.31999 0.31326 0.14173 0.05517 1.00000 0.00000 Hefei 2008 8 7 1 44 0.53526 0.16173 0.38287 0.12164 0.08605 0.05814 0.98791 0.02038 Hefei 2008 8 23 1 40 1.59965 0.39220 1.09671 0.26171 0.11173 0.03512 1.00000 0.00000 Hefei 2008 8 26 1 46 0.87338 0.13547 0.61559 0.09554 0.10290 0.04321 0.99303 0.01642 LA-TM 2008 8 11 1 18 0.76750 0.40893 0.52600 0.27898 0.05500 0.02947 0.99681 0.01034 LA-TM 2008 8 14 1 24 1.87328 0.69644 1.30007 0.51758 0.13592 0.08705 0.99534 0.00857 LA-TM 2008 8 17 1 30 3.31376 0.45795 2.51738 0.43524 0.40932 0.14193 1.00000 0.00000 LA-TM 2008 8 20 1 35 1.33437 0.78271 0.93298 0.56789 0.13090 0.09137 0.96171 0.04904 Ningbo 2008 8 8 1 13 0.92328 0.37913 0.63798 0.25727 0.08072 0.03460 0.99595 0.00956 Ningbo 2008 8 14 1 24 1.43649 0.15718 0.98724 0.11467 0.10280 0.02894 0.99560 0.00839 Ningbo 2008 8 27 1 16 0.47284 0.04367 0.32331 0.02847 0.03300 0.01033 0.98576 0.02296 Ningbo 2008 8 30 1 21 2.23475 0.60355 1.52544 0.40969 0.13498 0.03032 1.00000 0.00000 Qiandaohu 2008 8 4 1 38 0.60112 0.21101 0.44109 0.17315 0.13379 0.11936 0.88380 0.08165 Qiandaohu 2008 8 20 1 35 0.73438 0.18651 0.54564 0.15619 0.17629 0.11825 0.92748

Page 16: Monitoring aerosols in China with AATSR Anu-Maija Sundström 2 Gerrit de Leeuw 1 Pekka Kolmonen 1, and Larisa Sogacheva 1 AMFIC. 24.6.2009, Barcelona 1:

ConclusionsConclusions The AATSR ADV- algorithm is able to retrieve AODs

over China in highly different situations. Anthropogenic fine mode aerosol components dominate the ADV

retrieval. Smog and dust cases are difficult as for all satellite instruments, and

lead to underestimation of AATSR AOD.

Dataset 1.0 is available at the web-page Figures of the AOD pattern at 555 nm at 1x1

km2 resolution Data for specific AERONET stations.

The dataset is updated regularly Article submitted to Remote Sensing of Environment,

AATSR Special Issue