SST CCI Phase-II

ESA Climate Change Initiative Phase-II

Sea Surface Temperature (SST)

www.esa-sst-cci.org

The CDR from SST CCI Chris Merchant University of Reading

SST CCI Phase-II

R&D Passive Microwave Sensors

35 year uncertainty-quantified SST CDR Integrated, consistent L2, L3 & L4

SST CCI Phase-II

New EO science in SST CCI Phase 2 § Known techniques cannot deliver SST CDR

requirements § New EO science required to

•  Harmonise and stabilise AVHRRs/ATSR1 pre-1996 –  Mutual bias correction across constellation –  Instrument calibration modelling (essential work at L1b)

•  Link AATSR to SLSTR via AVHRR-A/IASI •  Achieve IR SST targets for noise and bias

–  Smooth-atmosphere retrieval to reduce noise –  Retrieval and cloud detection in presence of stratospheric aerosol

§ Fundamental work on new MW subskin-SST •  in context of IR-dominated CDR

SST CCI Phase-II

Passive Microwave SST §  Can PMW SST be used to

enhance the SST CDR? •  Enhanced frequency of

observation (at lower resolution) in cloudy areas

•  Could damage observational stability of CDR relative to IR-only

§  Optimal estimation for AMSR-2 SST developed

•  Information content analysis completed, to prioritise channels

•  Significant BT-related and wind-stress related biases

Page 4 21 September 2015 PM5 - Met Office

6.9V Brightness Temperature / K

Est

imat

ed O

bs –

Sim

Bia

s / K

SST CCI Phase-II

Initial PMW SST validation results

21 July 2015 GHRSST XVI Page 5

JAXA RSS CCI Matching Good Buoys 305 161 305 161 305 161 Mean Error / K 0.03 -0.04 -0.14 Robust SD / K 0.40 0.38 0.38

SS

T AM

SR –

SS

T in

situ

/ K

NWP wind speed / m/s

Wind-stress dependence of emissivity around 7 GHz is not well understood

SST CCI Phase-II

Less noisy IR SST §  For climate record, priority is to

•  minimise biases •  maximise sensitivity to true SST

(minimise prior influence)

§  Users also like data that isn’t noisy

•  but obvious low-noise retrieval increase bias and prior influence

§  Experimental reprocessing introduced “smooth-atmosphere” retrievals

•  the SST fields are not merely smoothed, even if it looks like it

•  bias and sensitivity are unchanged

Page 6 21 September 2015 PM5 - Met Office

Low bias, normal noise

Low bias, low noise

SST CCI Phase-II

Stratospheric aerosol events

7

0 0.3 Infra-red optical depth, Pinatubo aerosol

Causes bias in IR SST Good solution exists for ATSR: “aerosol robust” retrieval coeffs

El Chichon (1982) Pinatubo (1991)

SST CCI Phase-II

El Chichon and AVHRRs §  Tougher to get a good solution for

AVHRRs •  Single view => good knowledge

of spectral impact more crucial •  Fundamentally not enough

information in 2 or 3 channels => prior IR AOD

§  Derived using HIRS data a prior IR AOD for El Chichon event

§  Will use this in extension to the optimal estimation scheme presently used

§  Crucial step in extending CDR back to 1981

Page 8 21 September 2015 PM5 - Met Office

FromMerchantetal.,2013communitypaperandroadmap:h"p://www.geosci-instrum-method-data-syst.net/2/305/2013/gi-2-305-2013.html

H2020 project EUSTACE Aim: to understand, parameterise and exploit relationships between satellite (skin) and meteorological air temperature, for global historical analysis

•  SST CCI data will be exploited for air temperature analysis

•  Key benefit: uncertainty information

EUSTACEhasreceivedfundingfromtheEuropeanUnionHorizon2020Research

andInnovaJonprogramme,underGrantAgreementnumber640171

HadISST2.2 switch to SST CCI •  Key benefit of SST CCI: improved AVHRR products •  HadISST1 paper ~3000 citations

HadISST.2.1.0.0 ERSSTv3b Kaplan COBE HadISST1

SST CCI Phase-II

Conclusions

§  Building an integrated “operations-ready” system (presented on Day 1)

§  Many innovations to improve the scientific quality of the CDR in progress, and to deal with challenges of early sensors

§  Key to wider user adoption and application will be combination of •  reputation -- trust in the quality •  1981 to recent •  ongoing extension of CDR in time

Page 11 21 September 2015 PM5 - Met Office