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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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)

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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)

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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

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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

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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