development of new sses for aatsr l2p

Medspiration/Globcolour, NIVA, Oslo, 20th November 2007

Development of New SSES for AATSR L2P

Gary Corlett

AATSR Validation Scientist


Content

Reminder of current SSES scheme SSTs from AATSR What affects the quality of AATSR SSTs? An alternate scheme using view differences Examples Analysis of GHRSST-PP MDB Future work Summary & Conclusions


Revised (Realistic) Content

Reminder of current SSES scheme SSTs from AATSR What affects the quality of AATSR SSTs? An alternate scheme using view differences Examples Analysis of GHRSST-PP MDB Future work Summary & Conclusions


What Affects AATSR Data Quality?


What Affects the Quality of AATSR SSTs? For December 2005 coefficients

• D2-D3 bias (the latitude dependent correction) owing to limited number of channels

• Small residual bias (~ 0.15 K at T < 280 K) most likely due to temperature dependent emissivity

• These issues are being addressed in (A)RC project• Suspected 12 μm calibration error

• In process of analysing flight-spare FPA• Clouds and aerosols (claerosols)

• AATSR cloud screening is over-zealous– AATSR is designed for climate SSTs– Much better during day owing to 1.6 µm channel– Observable edge effects at night

• Dual-view corrects for tropospheric aerosol– But not quite!– Being addressed in (A)RC project

• Relative alignment of nadir and forward views• New results suggest systematic offset• Currently being investigated by AATSR QWG


Suspected 12 μm Error: Implication for SSTs

Calibration offset seen between AATSR and ATSR-2 12 μm clear-sky SEA BTs• ATS_MET_2P and AT2_MET_2P products analysed• Validation results suggest AATSR is incorrect• Results in increase in latitude dependent D2-D3 bias

Effect on current D3 SSTs is ~ + 0.05 K

Effect on current D2 SSTs is ~ - 0.04 K


Distribution of M-AERI Matchups

Matchups

• Day; Overpass ± 60 min; 1x1 Block

LEGEND

All +ve D-N-ve D-N

• Bi-modal distribution of differences

• 1 distribution due to -ve dual-nadir SST differences

• 1 distribution due to +ve dual-nadir SST differences


Nov 2003

July 2003

The Affect of Saharan Dust on AATSR SSTs (30’)


Caribbean SST differences for ‘clean months’ – November to March

Data is derived from 30’ product

Threshold =

+0.26 K

Threshold =

-0.03 K

Day

D2-N2

Night

D3-N3


Day

D2-N2

Night

D3-N3 Threshold =

+0.26 K

Threshold =

+0.25 K

Caribbean SST differences for ‘clean months’ – November to March

Data is derived from 1-km product


Pacific Ocean – ‘clean’ months


BT


Schematic of BT Effects


Relative alignment of forward and nadir views (1)

Nadir View 3.7 micron Forward View 3.7 micron


Relative alignment of forward and nadir views (2)

Forward minus Nadir View 3.7 micron Forward minus Nadir View 3.7 micron with shift


Basis of New SSES Scheme


Requirements for AATSR SSES

Need, per pixel:• Bias

• Retrieval bias, or• Bias to a common standard – GHRSST match-up database

• Standard deviation• What exactly is a single pixel standard deviation?

• Quality flag• Scale of 1-5 agreed in Melbourne

– 1: Cloudy– 2: Bad– 3: Acceptable (defined by provider)– 4: Good– 5: Excellent


Updated QF Scheme – Theoretical Thresholds


Updated QF Scheme – Experimental Thresholds

T2U = + 0.04 ± 0.09 °C T2L = - 1.53 ± 0.09 °C T3U = +0.51 ± 0.07 °C T3L = -0.51 ± 0.07 °C


Updated PCF Scheme - Stratification

Stratification

If 2-channel Retrieval If 3-channel Retrieval

TL2 < D-N < TU2 TL3 < D-N < TU3

D-N < TL2 D-N < TL3

D-N > TU2 D-N > TU3


Potential SSES Scheme: Summary Effect of clouds and aerosols can be accounted for using D-N SST

differences• Should get well-defined normal distribution

• Can set thresholds to remove data not in normal distribution

Suspected alignment error between forward and nadir views will contribute to D-N differences• Significant positive edge structures still seen after view-difference shift• D-N test is designed for current AATSR data• Will need revising if and when relative alignment is corrected

12 μm calibration error will contribute to D-N differences• D-N test is designed for current AATSR data• Will need revising if and when 12 μm calibration error is corrected


Examples


Example 1

AATSR Orbit: ATS_NR__2PNPDE20060516_012117_000049912047_00403_22000_0504.N1

Area of interest: 102 ºE to 118 ºE by 12 ºS to 4 ºS Day time descending node The day time example demonstrates the over-zealous

cloud-screening, as the updated PCF mask is mainly indicating good data, while the larger-scale bad data is most likely affected by aerosol rather than cloud. The data are for 16th May 2006 over Indonesia, and it is noted that the volcano Mount Merapi, in central Java, was fairly active during May 2006.


Comparison of N1 and L2P SSTs


L2P Quality Control


N1 D-N & New QF


Change in QF


Summary of Main Changes Due to New Scheme

Large number of pixels classified as QF 2 and QF 3 data are now classed as QF 5• Little change for QF 4 and QF 5 (except night time)

A lot of pixels identified as bad (QF 2) by new scheme was previously classed as QF 3


Analysis of GHRSST-PP MDB


Definitions of SST D

epth

10m

1 mm

1 m

10 m

(a) Night time situation, light windAATSR 3 channel

-0.3 -0.2 -0.1 0.0

SSTskin – SST10m (K)

Dep

th

10m

1 mm

1 m

10 m

SSTskin – SST10m (K)

0 0.5 1.0 1.5 2.0 2.5 3.0

Infrared sensors (T ~10s)

Contact thermometersShips/Buoys (T ~minutes)

(b) Day time situation, strong solar radiation and light winds

AATSR 2-channel


Location of GHRSST-PP Match-ups (1)


Location of GHRSST-PP Match-ups (2)

Drifting Buoys

Others


Example: Day time “Good” data low wind speed


Example: Night time “high” data low wind speed


Statistics from GHRSST-PP MDB Analysis

StratificationStatistics

Number Bias sigma

2-channel, B, L 10762 +0.024 0.41

2-channel, B, H 14345 -0.001 0.35

2-channel, A, L 443 -3.895 3.24

2-channel, A, H 447 -2.230 2.19

2-channel, C, L 419 +0.531 0.66

2-channel, C, H 642 +0.487 0.66

3-channel, B, L 12013 -0.170 0.36

3-channel, B, H 15158 -0.083 0.35

3-channel, A, L 358 -0.901 0.54

3-channel, A, H 348 -0.790 0.52

3-channel, C, L 910 +0.381 0.39

3-channel, C, H 1394 +0.446 0.35

A: Data below lower thresholdB: Data within upper and lower thresholdsC: Data above upper threshold


New Confidence Values and Statistics

Stratification Case Summary of criteria Bias St. Dev. Confidence Value

Case 1: 2-channel, Middle D-N, Low wind +0.179 0.38 5

Case 2: 2-channel, Middle D-N, High wind +0.179 0.38 5

Case 3: 2-channel, Low D-N, Low wind -2.719 2.88 2

Case 4: 2-channel, Low D-N, High wind -2.719 2.88 2

Case 5: 2-channel, High D-N, Low wind +0.674 0.66 3 (or 4)

Case 6: 2-channel, High D-N, High wind +0.674 0.66 3 (or 4)

Case 7: 3-channel, Middle D-N, Low wind +0.000 0.36 5

Case 8: 3-channel, Middle D-N, High wind +0.087 0.35 5

Case 9: 3-channel, Low D-N, Low wind -0.731 0.54 4 (or 3)

Case 10: 3-channel, Low D-N, High wind -0.620 0.52 4 (or 3)

Case 11: 3-channel, High D-N, Low wind +0.551 0.39 5

Case 12: 3-channel, High D-N, High wind +0.616 0.35 5

Biases have been converted to skin biases by adding 0.17 K


Summary & Conclusions (1)

Current PCF scheme used in L2P applied to AATSR data is appropriate for nadir-only IR with poor cloud screening• Does not account for over-zealous operational AATSR cloud

screening• Does not account for impact of claerosols on forward view

Have developed improved quality flag for AATSR• Use D-N SST difference to identify retrievals affected by

claerosols• Threshold = mode + 3 * sigma

• Also stratification according to wind speed• Future scheme could take into account spatial and temporal

variation in SST retrievals


Summary & Conclusions (2) Issues

• Data classed as “others”• No day time wind speed dependence

• May imply no significant diurnal warming has started or diurnal warming cancels out cool-skin effect

• Night-time sub-skin correction• No current agreement on how to correct (consistently)

• Would only recommend QF 5 data if using AATSR as reference• Requires changes to L2P product

• Addition of nadir-only SST for each dual-view SST• Addition of flag to identify 3-channel retrievals


Acknowledgements

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

This work was funded by ESA (ESA-NOCS Contract: AO/1-4362/03/I-LG) and Defra (Space ConneXions Contract: 2004-03-001/CPEG10)


Current SSES Scheme


Current SSES scheme for AATSR L2P


AATSR SSTs


What is AATSR? 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

500 km swath 1 km IFOV at nadir

Stirling Cycle Coolers, cooling low noise detectors to 80K, for optimum signal-to-noise ratios


Nominal Channel Centre Primary Application

0.55 m Chlorophyll

0.66 m Vegetation Index

0.87 m Vegetation

1.6 m Cloud Clearing

3.7 m SST Retrieval

11 m SST/LST Retrieval

12 m SST/LST Retrieval

AATSR SST Retrievals Retrievals by radiative transfer

modelling Usually of the form:

where n is the number of channels

For AATSR we have 2 channels during day and 3 during night

• 3.7 µm not used during day owing to solar contamination

We have two views, so we have four SST retrievals in total

We also have two product formats

• 1-km gridded (swath)• Spatially –averaged (gridded)

Four Possible Retrievals:

Nadir 2-channel N2Nadir 3-channel N3Dual 2-channel D2Dual 3-channel D3

∑+n

nnBTaa1

0


Retrieval Coefficients: 1-km

Coefficient N2 N3 D2 D3

Constant -0.34 0.04 2.83 0.70

Nadir 3.7 µm - 1.08 - 2.51

Nadir 11 µm 3.42 0.65 5.42 0.63

Nadir 12 µm -2.42 -0.73 -3.08 -0.73

Forward 3.7 µm - - - -1.47

Forward 11 µm - - -3.20 -0.34

Forward 12 µm - - 1.84 0.40


Ongoing Work


Spatial Pattern of AR Differences to Buoys

Data from Anne O’Carroll (Met Office)


Further Refinement of SSES

The (A)ATSR L2P project is aiming to make a few further improvement to the SSES

The two main ones are

• To use high quality ICOADS in situ data

• Introduce spatial and temporal variation to bias and standard deviations


L2P Reformatting (2)

10 degree

20 degree

45 degree


L2P Reformatting (3)

10 degree

20 degree

45 degree


Example 2 AATSR Orbit:

ATS_NR__2PNPDE20060516_012117_000049912047_00403_22000_0504.N1

Area of interest: 70 ºW to 50 ºW by 25 ºN to 35 ºN Night time ascending node

The night time example in Section 5.1.2 clearly demonstrates the edge of pixel cloud contamination that affects AATSR data, and is clearly not picked up by the current PCF scheme. In addition, as for the day time data, there is no reason to suspect the rest of the SST data, which has been cloud screened twice and retrieved using two different SST retrievals. Therefore the data which passes the D-N test is set as good data and the PCF mask for these pixels is set to 5.


AATSR and ATSR-2 Simulated Bias: Centre of Swath

From Owen Embury (University of Edinburgh)


Compare AATSR and ATSR-2 BTs: Case 1

Nadir View Forward View

development of new sses for aatsr l2p

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