MAVT Summary Session 4: AATSR SST and LST Validation. Gary Corlett. MAVT-2006 ESRIN March

Transcription

1 MAVT Summary Session 4: AATSR SST and LST Validation Gary Corlett 1

2 AATSR SST Validation AATSR is required to measure global SST values to within 0.3 K (1 σ) in single point coincidences and over 0.5º (30 ) x 0.5 º (30 ) averages ATS_NR 2P Gridded 1km by 1km global product Against in situ radiometer measurements Against in situ buoy measurements ATS_AR 2P Spatially averaged products at various resolutions (30 ; 10 ; 50 km; 17 km) Against in situ buoy measurements Against other satellite sensor measurement Two types of validation How accurate is AATSR? What is the accuracy of the data? The validation uses truly independent data sets - there is no tuning to in situ The validation uses the operational AATSR data there is no post-processing 2

3 From: Ian Barton Conclusions - Accuracy of AATSR Skin SST products Bias (K) Bias (K) * Std. Devn. (K) Bias (K)** AATSR SST SST SST SST AATSR SST validation against Bulk SST (Perth ferry) SST SST * Bias for 2005 coefficients ** 2005 coeffs + skin-effect of 0.17 K 3

4 From: Craig Donlon D3 N3 D2 N2 Validation of AATSR: Robust reproducible procedure-based validation AATSR is performing exceptionally well 4

5 From: Tim Nightingale (Newcastle) Hanstholm # Bergen ########################################################################################################################################################################################################################################################################################################################### Oslo ############# # Hirtshals ###################################### Kirkenes Color Festival: Oslo Hirtshals Operative since August 2001 EU-project FerryBox and DISMAR Data used in REVAMP project Used for algal monitoring, satellite validation and phytoplankton studies Fjord Norway: Bergen Hanstholm In operation since May 2005 Used for algal monitoring Fjord Norway: Bergen Newcastle Started November 2005 Hurtigruten: Bergen Kirkenes MS Trollfjord operated by NIVA InteReg project NorSEN Algal monitoring 5

6 From: John Remedios M-AERI (EotS) Results Jan 2003 Dec 2005 Dual Nadir Match-ups N Bias (K) St. Dev. (K) N Bias (K) St. Dev. (K) All match-ups 2-channel All match-ups 3-channel Normal D-N 2-channel Normal D-N 3-channel High D-N 2-channel High D-N 3-channel Matchups: Overpass ± 120 min; 1x1 Block 6

7 From: Thomas Blackmore AATSR compared to buoy SSTs AATSR SST buoy SST Means for 2 complete years 1 Aug Jul 2005: Agreement within ± 0.3 K SKIN All: 0.02 K (σ = 0.29 K) Night: 0.05 K (σ = 0.26 K) Day: K (σ = 0.33 K) BULK All: 0.18 K (σ = 0.29 K) Night: 0.21 K (σ = 0.24 K) Day: 0.15 K (σ = 0.33 K) 7

8 From: Thomas Blackmore Buoy Match-ups New Coefficients New coefficients used in the skin SST calculations for AATSR were made operational by ESA on 07/12/2005. D2 day, D3 night Buoy match-up statistics from 07/12/05 to 18/02/06: (5120 match-ups) Mean St. Dev. New coefficient dual-view SST Old coefficient dual-view SST

9 From: Thomas Blackmore Errors calculated from 3-point analysis Calculated error for each observation type: AATSR bulk D3 SST = 0.13K Buoy SST = 0.21K AMSR-E SST = 0.43K Similar trends are seen when in Northern and Southern hemisphere match-ups individually, using moored and drifting buoys individually, and using a 1-hour cutoff instead of 3 hours: 0.13K <= error in AATSR SST <= 0.16K 0.20K <= error in buoy SST <= 0.22K 0.4K <= error in AMSR-E SST <= 0.49K 9

10 SST Validation Issues Cloud and aerosol contamination Use of the D-N test for improved data quality Affect on the climate SST? Most data presented were comparisons to pre-launch coefficients Updated coefficients now available (07/12/2005) Removes D2/D3 bias (offset latitudinal correction now available) Do not have a well defined error budget Adopt GHRSST-PP SSES 10

11 The AATSR LST Product First LST product from the ATSR mission Algorithm developed by Fred Prata and Andrew Birks Operational since March 2004 (prototype available prior to this date) Available since start of mission through reprocessing Provides 1x1 km gridded LST over the entire globe Spatially averaged under consideration Target accuracy of 2.5 K in day (better results obtained at night, 1.0 K)* Land surface is classified into 14 biomes * Prata, A. J., 2000, Land Surface Temperature Measurement from Space: AATSR Algorithm Theoretical Basis Document, ESA/CSIRO Publication 11

12 From: Lizzie Noyes AATSR LST Validation Results 12/03-12/05 Operational cloud screening Additional cloud screening Cloud screening by eye and 3σ filtering of differences Cloud Contamination Day (cloud-free): N = 50 Bias = 0.5 K StDev = 3.3 K Night (cloud-free): N = 44 Bias = 1.2 K StDev = 1.2 K Seasonal bias: warmer in summer colder in winter 12

13 From: Lizzie Noyes AATSR LST Auxiliary Data: Biome Map (1) Lake Tahoe is not currently classified as a lake! Lake Tahoe UMD Land Use Map (1 km resolution) Biome numbers are not equivalent! Operational AATSR LST Biome Map (0.5º resolution) 13

14 From: Lizzie Noyes AATSR LST Auxiliary Data: Biome Map (2) AATSR biome grid appears offset by approximately 1º longitude to the west. 14

15 From: Lizzie Noyes AATSR IFOV 15

16 From: Lizzie Noyes Results: AATSR (Surface) FOV Maximum difference observed between the two sets of LSTs is 0.7 K. Results for 12 pixels show that the true AATSR FOV may be an important consideration in some applications 16

17 From: Guillem Soria Validation of LST from Level 2 data and algorithms DAY/Cluster 14a 14b 17a 17b 17c 20 in situ Standard Bias deviation σ Level SW SW 6 + ε, W Comparison Ts(in situ) vs Ts(algorithms) RMSE Ts In situ (K) Level SW Ts Algorithms (K) 17

18 From: Cesar Coll AATSR LST product RAL processor Year Date (day/month) Ground LST (ºC) RAL LST (ºC) 10/ / / / / / Ground RAL LST (ºC) 05/ / / / / / / / / / / / / // / / / Average difference (ºC) -3.5 Standard deviation (ºC) 0.7 Range of differences (ºC): [ 4.8 ; 2.3] 18

19 From: Cesar Coll Validation of AATSR LST Year Date Ground LST AATSR LST (ºC) Ground-AATSR LST (ºC) (day/month) (ºC) Eq. (1) Eq. (2) Eq. (1) Eq. (2) 10/ / / / / / / / / / / / / / / / / / / // / / / Average difference (ºC) Standard deviation (ºC) Range of differences (ºC): [ 1.1 ; 1.0] [ 1.0 ; 1.0] 19

20 Summary SST AATSR NR D3 SSTs Warm bias of K (σ = 0.28 K) in the Caribbean Warm bias of K (σ = 0.24 K) in the Bay of Biscay Cool bias of 0.05 K (σ = 0.22 K) around Australia AATSR AR D3 SSTs Warm bias of K (σ = 0.24 K) globally Warm bias of K (σ = 0.24 K) in the Caribbean Warm bias of K (σ = 0.33 K) in the Bay of Biscay Difference between NR and AR in Caribbean is cloud contamination Strong spatial pattern in differences to buoys D2-D3 bias affects previous validation of D2 SSTs This bias is removed by the use of updated coefficients from 07/12/2005 Limited validation shows new coefficients give more accurate and precise products Benefits of long term validation data sets from the in situ buoy network and from the M-AERI and ISAR instruments are clear Incorrect conclusions on product accuracy would otherwise be drawn 20

21 Summary LST AATSR NR LSTs Day time warm bias of K (σ = 0.33 K) at the ARM-SGP site Night time warm bias of K (σ = 1.20 K) at the ARM-SGP site Cool bias of -3.5 (σ = 0.7 K) at Valencia for operational algorithm Cool bias of -0.1 (σ = 0.1 K) at Valencia for optimised algorithm Warm bias of (σ = 4.11 K) at Barrax for operational algorithm Warm bias of (σ = 1.36 K) at Barrax for optimised algorithm The 0.5º 0.5º resolution of land cover/vegetation fraction is too coarse to account for the heterogeneity of land surfaces. 21

22 Recommendations Long term autonomous in situ data are needed for both SST and LST validation More sites (particularly for LST) Apply current knowledge to ATSR-1 & ATSR-2 The seasonal bias in the AATSR LST data needs addressing Improvements to the current LST auxiliary data are desperately needed Resolution Ensuring all land is covered by these data (with no shift!) Using EO-GRID and BEAM for algorithm application, testing/optimisation Needs implementation of the prototype/operational processors The climate community needs ATSR-4! 22

23 AATSR Surface Temperatures over the UK and Northern France From Simon Good (UL) 23