1. Intercalibration of AMSU-A,MHS and Update on mitigating loss of AATSR
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Intercalibration of AMSU-A,MHS and Update on mitigating loss of AATSR
Roger Saunders, Pete Francis, Tom Blackmore, Brett Candy, Viju John and Tim Hewison
Acknowledgements to EUMETSAT for supporting this work
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2. Goals of the project
Generation of Microwave Radiance Fundamental Climate Data Records (FCDR) from the upper tropospheric water vapour channels from AMSU-B, MHS and SSM/T-2 sensors from 1994 to 2014
Generation of the Infrared Radiance FCDR from the upper tropospheric water vapour channel on HIRS from 1979 to 2014
To compare IR and MW FCDRs with simulated radiances from CMIP5 climate models and reanalyses (e.g. ERA-Interim) to ascertain deficiencies in model hydrological cycle.
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3. Something good about orbit drift!
SNOs occur over all latitudes when Xing times are identical
John et al 2011

4. Inferring radiance biases (1) SNOs
For channel n on sensor 1 and
channel m on sensor 2 average over all
cloud-free ocean pixels within colocation area
DBTnm = mean{(yn – ym)}
1 to k coincident obs
k typically ~ 100
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5. Distribution of collocations SNOs at all latitudes
John et al 2011
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6. Radiance dependence of bias from global SNOs
N19-N18
MA-N17
MA-N17
SNO – Simultaneous nadir overpass
I take N19, MA, and N16 are primary satellites and N18, N17, and N15 as secondary satellites. “N” represent NOAA. “MA” represent MetOp-A
Bias is calculated as primary satellite minus secondary satellite.
Most of the channels show significant dependence of bias on radiance.
Black symbols show dependence of bias on radiance of primary satellite.
Red symbols show dependence of bias on radiance of secondary satellites.
N19 Channel 3 had very high radiometric noise during this time (~7K), that is the reason why it has very large radiance dependent bias.
More details in:
John, V. O., G. Holl, S. A. Buehler, B. Candy, R. W. Saunders, and D. E. Parker (Accepted with minor revision, 2011), Understanding inter-satellite biases of microwave humidity sounders using global SNOs, J. Geophys. Res..
N16-N15
John et al., (2012) Understanding inter-satellite biases of microwave humidity sounders using global simultaneous nadir overpasses, J. Geophys. Res.
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7. Scan dependent biases
John et al., (submitted), Monitoring scan asymmetry of microwave humidity sounding channels using simultaneous all angle collocations (SAACs), J. Geophys. Res.
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8. Correcting for Orbit drift
Equator Xing times of ascending nodes
Data from 5 satellites are used to construct diurnal cycle climatology
(31.25 N, 1.25 E)
Channel 1
NOAA-16 channel 1
Kottayil, John, and Buehler (Submitted) Correcting diurnal cycle aliasing in microwave humidity sounder measurements, J. Geophys. Res..
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9. Assessment of inter-calibration methods
NOAA-16 – NOAA-15
John et al., (submitted), Assessment of inter-calibration methods for microwave humidity sounders, J. Geophys. Res.
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10. Summary 1 SNOs used to characterise AMSU-B/MHS biases
Important to note biases change significantly with latitude so polar SNOs only tell part of story
Scan biases biases vary significantly from intrument to instrument
Diurnal changes can be modelled with the 5 NOAA/METOP satellites in orbit with different equator crossing times
Tropical ocean appears to be best region to monitor biases
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11. Calculation of radiance biases (2) NWP as transfer standard
For channel n
Sensor 1: DBT(n) = mean{yn - Hn(xi)}
i=1 to k obs
For channel m
Sensor 2: DBT(m) = mean{ym - Hm(xi)}
Assume same bias?
Compare DBT(n) with DBT(m)
(double difference)
xi atmospheric state vector for observation i
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12. AMSU-A on NOAA19 and METOP-A Chan 10 Stable but biases different for each instrument
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13. AMSU-A on NOAA19 and METOP-A Chan 8 NOAA-19 Not Stable!
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14. MHS on NOAA19 and METOP-A Chan 18 Stable but biases different for each instrument Note much higher NeDT for NOAA-19
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15. AATSR to SLSTR ? the bridge for climate quality SST
AATSR data ceased when the ENVISAT satellite failed in April 2012.
It provides the high quality SST data record and well calibrated radiances useful for GSICS
SLSTR is planned to be launched on Sentinel-3 in 2014?
How to bridge the gap?
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16. AATSR biases
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17. HIRS SEVIRI AATSR stats over ocean 2011
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18. HIRS SEVIRI AATSR
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19. IASI vs AATSR Can we use IASI to bridge the gap to SLSTR?
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20. IASI vs AATSR Can we use IASI to bridge the gap to SLSTR?
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21. IASI vs AATSR Can we use IASI to bridge the gap to SLSTR?
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22. Summary 2
With the failure of AATSR, METOP-A/B IASI is the best option for a stable radiometric reference in the AM orbit and AIRS in the PM orbit until Sentinel-3 is launched.
The AVHRR and MODIS imagers can be used to retrieve SST but the calibration is monitored with IASI or AIRS on the same platform.
A study with METOP during the overlap period with AATSR is planned
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23. Questions and answers
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