Arctic SST retrieval in the CCI project

Owen EmburyChris Merchant

University of Reading

SST CCI Phase 1

• Combine ATSR accuracy with AVHRR coverage• Optimal Estimation (OE) retrieval– Cross referenced to ARC SST

• Diurnal variability adjustment– Report SSTs at standard depth and time of day

• Uncertainty estimation• Product specification– NetCDF 4 with classic data model– GDS2.0 compliant

SST CCI Phase 1• Long-term (Aug 1991 – Dec 2010)– ATSR

• OE retrieval• Bayesian cloud screening• L3U (0.05°)

– AVHRR GAC• OE retrieval• CLAVR-X cloud screening• Ice detection• L2P

– SSTskin at time of observation– SST0.2m at 10:30 local time

• Adjusted to nearest am/pm

Bayesian Cloud Detection

• Use RTTOV to simulate expected observations from ECMWF NWP

• Calculate P(obs | clear) from obs-sim differences• Get P(obs | cloud) from empirical lookup table• Use Bayes to get P(clear | obs, nwp)• P(obs | clear) is dominant factor– ECMWF NWP– RTTOV forward model– Prior error assumptions

• Prior SST error is location dependent (0.5 to 1.8 K)

Bayesian Cloud Detection• Can consider the current system as Bayesian “clear-sky”

detection• Problem detecting conditions which look like clear-sky in

infrared– Seaice– Fog

• Potential improvements– Add fog / seaice as extra classes for detection

• Needs software refactoring– Use visible channels

• Not done yet due to ARC software heritage (ARC needed method applicable to ATSR1)

• Daytime only– Review prior SST error assumption in Arctic areas

OE SST retrieval

• MAP formulation with prior SST error of 5 K– Reduces influence of prior on retrieval

• QC check on χ2 to remove bad retrievals– Calculation of χ2 similar to P(obs | clear) in

Bayesian cloud detection

• QC check to remove SSTs < 271.35 K– Not applied in pre-release data

Comparison with other datasets

• Compare 5 day composite images– Pathfinder v5.2– ARC v1.1.1– AMSR-E v7– OSTIA– CCI

• AVHRR L2P• ATSR L3U

• Show with OSISAF sea ice concentration– 15% and 85% contour lines

2008Norwegian and Greenland Seas

2010Norwegian and Greenland Seas

2008Ice melt in Beaufort Sea and outflow from Mackenzie river

2010Ice melt in Beaufort Sea and outflow from Mackenzie river

Summary

• AVHRR– CCI generally has better coverage than Pathfinder– Pathfinder less likely to reject extreme warm SSTs in

Mackenzie outflow• ATSR– CCI and ARC consistent in images shown

• CCI-ARC differences exist but << 1 K

• Large temperature anomalies can be problematic for Phase 1 CCI– Both SST retrieval and Bayesian cloud screening used

ECMWF-interim SST (OSTIA) as prior

SST CCI Phase 1• Demonstration (two 3 month periods)

– AATSR L2P (1km)• OE retrieval• Bayesian cloud screening

– Metop-A AVHRR L3C (0.05°)• Meteo France retrieval• Meteo France cloud screening

– SEVIRI L3C (0.05°)• Meteo France retrieval• Meteo France cloud screening

– AMSR-E L2P (0.25°)• RSS retrieval

– TMI L2P (0.25°)• RSS retrieval

Known bugs in pre-release data

• Two biggest issues caused by “minor” bugs• No data after midnight– Unsigned int bug in pre-processing code– Last orbit in day cut off at mid-night– Regular gaps in ATSR data

• Missing data flagged as quality_level 5– QC based on cloud mask and uncertainty information– OE retrieval can produce SST < 271.15 K– SST-CCI product can not store SST values < 271.15 K