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Chris Mutlow (1) , Gary Corlett (2) and Dave Smith (1) Earth Observation and Atmospheric Science Division, Rutherford Appleton Laboratory (2) Earth Observation Science, University of Leicester. The AATSR sensor and its in-flight performance. - PowerPoint PPT Presentation
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The AATSR sensor and its in-flight performance
Chris Mutlow(1), Gary Corlett(2) and Dave Smith(1)
(1) Earth Observation and Atmospheric Science Division,Rutherford Appleton Laboratory
(2) Earth Observation Science, University of Leicester
2
The Along Track Scanning Radiometer (ATSR) Programme
Primary objective to measure Sea Surface Temperature (SST) with an accuracy of 0.3 K (±1σ limit)
Thermal and visible data for atmospheric and land studies (e.g. temperature, vegetation, aerosols, clouds)
Provision of a long-term dataset for global climate change studies
ATSR-1 (ERS-1) 09/1991 - 03/00
ATSR-2 (ERS-2) 04/95 – Still working
AATSR (Envisat) 03/02 - Operational
3
ATSR Programme Timeline
AATSR
ATSR-2
ATSR Development AIT Operations Extended Life
Start
1984
Calibration
Summer 1989
Launch
17 July 1991ERS-1 Fails
10-March-2000
Nominal
Operations End
June 1996
Start
1990Calibration
Christmas 1992
Launch
27 April 1995
2005?
2010 ?Launch June 2001
Calibration
Christmas 1997
& 1998
Start
1994
4
Long Term (A)ATSR Data Record
14 year record of ATSR infrared data from 1991 when ATSR-1 was launched until today
This provides a traceable global SST record from 1991 to today
Sensors cross-calibrated
10 year record of visible data available from the launch of ATSR-2 in 1995 until today
Calibrated using on-board VISCAL systems
Reprocessing is underway to put ATSR-1 and ATSR-2 data into a common AATSR “Envisat-style” format
See Matt Pritchard’s talk on Tuesday
5
What is (A)ATSR?
Imaging infrared and visible radiometer on ENVISAT
Similar channels to AVHRR & MODIS.
Dual view (nadir and 55° to nadir)
Along-track scanning, two views of same scene at different angles, for better atmospheric correction
On-board calibration
2 on-board black bodies for IR calibration
VISCAL unit for visible channel calibration (see first talk after coffee break)
500 km swath
1 km IFOV at nadir
Stirling Cycle Coolers, cooling low noise detectors to 80K, for optimum signal-to-noise ratios
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Nominal Channel Centre
Primary Application
0.55 m Chlorophyll
0.66 m Vegetation
0.87 m Vegetation
1.6 m Cloud Clearing
3.7 m SST Retrieval
10.8 m SST/LST Retrieval
12.0 m SST/LST Retrieval
(A)ATSR Spectral Channels
Red: ATSR-1,-2 and AATSR have these channels
Blue: Only ATSR-2 and AATSR have these channels
7
Data Products from AATSR
Operational
Brightness temperatures and reflectances
Sea Surface Temperature (SST)
Land Surface Temperature (LST)
New product for AATSR
NDVI
Under development
Cloud parameters
Aerosol optical properties
8
Nadir View
Along-Track View
Hot Blackbody Cold Blackbody
VISCAL
Scan Direction
Both blackbodies viewedevery scan.
AATSR On-board Calibration System
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Blackbody Crossover Test
Test performed over 17th-19th May
All commands executed successfully
Data to be analysed-XBB
Hot BB
+XBB
Cold BB
11µm BB counts
BB temperatures
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Scan Mechanism Trends
11
NET Trend
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Cooler performance (1)
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Cooler Performance (2)
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FPA Temperatures
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Visible Channel Signals
16
Contamination
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Dynamic Range and Digitisation
Periodically (nominally every 6 Months) data are processed for one orbit.
Plots produced showing:
Max, mins and means for each scan over the orbit to evaluate dynamic range
Histograms of nadir view pixel counts to check for any missing/preferred states
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Dynamic Range – IR Channels
Daytime Night-time
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Dynamic Range – Visible Channels
Daytime Night-time
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Digitisation States – IR channels
Rounding off at 1024, 2048, 3072Rounding off at 1024, 2048, 3072
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Digitisation States – Visible Channels
Rounding off at multiples of 1024
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IR Gain Offset Loop maintaining dynamic range of IR channels as expected
No saturation in visible channels – visible gains updated to maintain dynamic range.
Slight rounding off at 1024, 2048, 3072 counts – less than 1bit error (<20mK)
Dynamic Range & Digitisation Summary
23
Example Validation Results
ATS_NR__2P (SST & LST)
Gridded 1km by 1km global product
Against in-situ radiometric measurements
ATS_AR__2P (SST only)
Spatially averaged products at various resolutions (30´; 10´; 50 km; 17 km)
Against in-situ buoy measurements
Further talks on data quality throughout the workshop
24
M-AERI and ISAR (Dual SST)
M-AERI Results ISAR Results
N Bias St. Dev. % ±0.3 N Bias St. Dev. % ±0.3
All match-ups
Day87 +0.25 0.58 45.98 87 +0.49 0.44 37.93
All match-ups
Night261 +0.18 0.37 62.45 223 +0.18 0.35 49.76
‘Normal’ D-N
Day75 +0.15 0.53 53.33 84 +0.44 0.36 39.29
‘Normal’ D-N
Night229 +0.11 0.31 68.55 204 +0.14 0.32 53.92
‘High’ D-N
Day12 +0.90 0.50 0.00 3 +2.19 1.32 0.00
‘High’ D-N
Night30 +0.60 0.35 20.00 18 +0.70 0.23 5.55
From: Lizzie Noyes (University of Leicester), Werenfrid Wimmer (NOCS)
25
AATSR Compared to Buoy SST
From: Anne O’Carroll (Met Office)
Sat “bulk” SST
Sat “skin” SST
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Buoy Results 04/2003-03/2005 (Dual SST)
Match Up Skin results Bulk results
N Bias St. Dev. % ±0.3 N Bias St. Dev. % ±0.3
All match-ups Day
15011 -0.02 0.32 N/A 13440 +0.15 0.33 63.96
All match-ups Night
16124 +0.05 0.26 N/A 14527 +0.21 0.25 64.02
‘Normal’ D-N Day
14230 -0.03 0.31 N/A 12862 +0.14 0.31 65.23
‘Normal’ D-N Night
15593 +0.04 0.25 N/A 14402 +0.21 0.24 64.38
‘High’ D-N Day 741 +0.19 0.55 N/A 549 +0.35 0.61 37.52
‘High’ D-N Night 511 +0.31 0.33 N/A 115 +0.44 0.46 23.48
From: Anne O’Carroll (Met Office)
27
Summary of LST Validation Results
Biome Site Campaign Bias ± StDev
4 Finland Discrete -0.1 ± 1.0 K
6 Valencia Discrete + 2.7 ± 0.8 K(1)
7 Uardry Autonomous -0.2 ± 0.9 K
8 Thangoo Autonomous -4.1 ± 3.3 K(2)
11 Amburla Autonomous -1.1 ± 1.5 K
12 Morocco Discrete 0.61 ± 2.7 K
14 Lake Tahoe Autonomous -0.07 ± 0.22 K
From: Cesar Coll (University of Valencia), Jose Sobrino (University of Valencia), Fred Prata (CSIRO), Simon Hook (JPL)
(1) Vegetation cover not accounted for properly in the algorithm
(2) Actually a sea pixel to which LST retrieval has been applied in error
28
Summary and Conclusions
AATSR is the third in a series of sensors providing a long-term data set of global SST since 1991.
Visible channel data available from 1995
LST algorithm can be applied to data from 1991
The sensor is performing extremely well
Geophysical validation results provide evidence of excellent data quality from both the SST and LST operational algorithms
Minor algorithm improvements are currently being assessed
29
Acknowledgements
Co-authors Gary Corlett and Dave Smith for all their material
Defra, the UK Department of Environment, Food and Rural Affairs, who funded AATSR to support their programme of climate prediction and research, which in turn provides inputs to their policy-making processes
Funding agencies in Australia who made significant contributions
The European Space Agency