real time arctic sst retrieval from satellite ir data issues and solutions(?) pierre le borgne,...
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Real time Arctic SST retrieval from satellite IR data
issues and solutions(?)Pierre Le Borgne, Gérard Legendre, Anne Marsouin, Sonia Péré, Hervé Roquet
Centre de Météorologie Spatiale, Météo-France, Lannion, France
Earthtemp Arctic SST workshop 18-19 December, Exeter
Outline
METOP-A/AVHRR derived daytime SST in September 2013
-Data-METOP-A (daytime)-Atmospheric profile data set
-Validation results (5years)
-Regional algorithms
-Use of NWP outputs
-Conclusions
Earthtemp Arctic SST workshop 18-19 December, Exeter
Data : METOP-A SST
METOP-A:1km resolution SST, Global coverage since 2007
METOP SST (see http://www.osi-saf.org )– Cloud mask (Maia, L. Lavanant, MF/CMS)– Ice mask (Ice probability, S. Eastwood, met.no)– Cloud/ice control– Daytime algorithm
SST = a T11 + (b TCLI + c S) (T11 - T12) + d S + e
MDB: 5 year Matchups at full resolution;
buoy location in central pixel within 3 hrs
Earthtemp Arctic SST workshop 18-19 December, Exeter
DATA: ECMWF output derived BT simulations (CEP+)
ECMWF operational forecasts RTTOV version 10.2 applied onto each profiles BTs at 3.7, 10.8 and 12 m
Training dataset
60N
Earthtemp Arctic SST workshop 18-19 December, Exeter
Daytime « Arctic » validation results
Error vs clear sky coverage:Clouds induce negative errors(no evidence of ice related errors)
Error vs T11-T12
5 year MDB
All cov
n
QL
3-5
17405 0.05 0.66
Simulated Error vs T11-T12
Simul.CEP+
n
534 0.22 0.34
Earthtemp Arctic SST workshop 18-19 December, Exeter
Validation conclusions
Significant influence of cloud contamination – Improved cloud/ice detection effort: met.no
Errors determined by the shape of atmospheric profiles:
(ex: summer temperature inversion cases lead to large positive errors)
Errors well reproduced by simulations
Earthtemp Arctic SST workshop 18-19 December, Exeter
Solutions
1) Multisensor Bias corrections (Hoyer et al, 2013, RSE, in press)
AATSR and NAVOCEANO GAC data as reference
2) Regional algorithms
NLC SST = (a + b S) T11 + (c + d TCLI + e S) (T11 - T12) + f +g
S
CASSTA SST = (a + b S) T11 +c +d S
3) NWP derived correction methods
Earthtemp Arctic SST workshop 18-19 December, Exeter
Regional algorithms ?
5 Year MDB +Cloud filtering reinforced: cov> 0.8; QL 4-5
Three regimes?
Earthtemp Arctic SST workshop 18-19 December, Exeter
Regional algorithms
Regional algorithms applied on the 5 year MDB
6143 cases (cov>0.8)
QL 4-5
Operational
NLC
Simulation derived regional NLC
Optimal regional NLC
Optimal
CASSTA
(T10.8)
0.28 0.25 0. 0.
0.45 0.50 0.44 0.64
Simulation dataset (CEP+) not adequate to determineregional algorithms
T10.8 based algoNot convincing
Earthtemp Arctic SST workshop 18-19 December, Exeter
NLC vs CASSTA on MDB
T108-T120 max
0. 0.1 0.2 0.5
OptimalNLC
0.76 0.73 0.75 0.59
OptimalCASSTA
0.77 0.74 0.78 0.68
Residual standard deviation on MDB
Earthtemp Arctic SST workshop 18-19 December, Exeter
NWP derived methods
Simulations must be « exact »: they should produce the same BTs as would be observed, given a surface temperature and atmospheric profiles:
A BT simulation adjustment step is necessary
We need to compare observations and simulations
(in consistent conditions)
Earthtemp Arctic SST workshop 18-19 December, Exeter
Simulations too cold
Earthtemp Arctic SST workshop 18-19 December, Exeter
Low wind zones: DW!
Earthtemp Arctic SST workshop 18-19 December, Exeter
OSTIA and DW in the Arctic?
Filter: 7 ms-1?
June 2012 June 2013June 2011
Earthtemp Arctic SST workshop 18-19 December, Exeter
Relative number of clear sky cases with wind > 7ms-1
July 2012
Earthtemp Arctic SST workshop 18-19 December, Exeter
Daytime prototype results in 2012 summer Arctic
June July August 2012, lat > 60°N
1070 cases Operational NLC
Operational NLC + bias correction
Optimal HL NLC
OSTIA
d -0.10 -0.13 -0.12 -0.31
s 0.60 0.55 0.52 0.37
Earthtemp Arctic SST workshop 18-19 December, Exeter
Trends with latitude
Operational NLC Operational NLC + bias correction
Optimal HL NLC OSTIA
Earthtemp Arctic SST workshop 18-19 December, Exeter
Operational SST retrieval methods in Arctic
Global daytime algorithm leads to SST overestimations by several tenths of K for T108-T120 below 0.5K
Regional algorithms may solve the problem, however simulation derived algorithms necessitate dedicated profile data sets
DW induced differences between OSTIA and observed SST make NWP derived simulation adjustments quite difficult in permanent daylight conditions
Drastic wind filtering (> 10ms-1) has lead to satisfactory results.
Earthtemp Arctic SST workshop 18-19 December, Exeter
Further work
CMS to write a paper on 5 (7) years of METOP-A Arctic results X(?) to build up a profile database adapted to Arctic studies CMS to prepare regional HL algorithms as a backup to simulation
derived BTs for METOP-B CMS & DMI to compare METOP biases (NWP derived vs Jacob’s
method) …….
Earthtemp Arctic SST workshop 18-19 December, Exeter
10.8 micron simulation error on the 1st of June 2012
Earthtemp Arctic SST workshop 18-19 December, Exeter
Summertime error origin
(see alsoLeBorgne et al, EUMETSAT Oslo 2011)
0.5<T11-T12 <0.7
Air temp. dt/dq
0.5<T11-T12 <0.7
Normal case=0.04, =0.16
0.<T11-T12 <0.3
Air temp.dt/dq
0.<T11-T12 <0.3
Summer ArcticCase=0.55, =0.21
Earthtemp Arctic SST workshop 18-19 December, Exeter
Trends with T108-T120
Operational NLCOperational NLC + bias correction
Optimal HL NLC
Earthtemp Arctic SST workshop 18-19 December, Exeter
Earthtemp Arctic SST workshop 18-19 December, Exeter
Anomalies in Sept 2013
METOP-A/AVHRR derived daytime SST in September 2013