29 May 2009GHRSST User's Symp - SQUAM1 The SST Quality Monitor (SQUAM) 1 st GHRSST Int’l User’s Symposium May 2009, Santa Rosa, CA Alexander “Sasha” Ignatov*, Prasanjit Dash*, John Sapper**, and Yury Kihai* NOAA/NESDIS *Center for Satellite Applications & Research (STAR) **Office of Satellite Data Processing & Distribution (OSDPD)

29 May 2009GHRSST User's Symp - SQUAM2 NESDIS Operational AVHRR SST Products and SQUAM Objectives  Heritage Main Unit Task (MUT) present (McClain et al., 1985; Walton et al., 1998).  New Advanced Clear-Sky Processor for Oceans (ACSPO) -May 2008 – present SST Quality Monitor (SQUAM) Evaluate MUT and ACSPO SST products in near-real time for self-, cross-platform and cross-product consistency Identify product anomalies & help diagnose their causes (e.g., sensor malfunction, cloud mask, or SST algorithm)

29 May 2009GHRSST User's Symp - SQUAM3 Native pixel resolution 8 km 6.6×10 4 SST pixels 8.3% ocean covered at 1day×0.3 o resolution Native pixel resolution 4 km 2.1 × 10 6 SST pixels (MUT × 30) 32.7% ocean covered at 1day × 0.3 o resolution AVHRR SST MetOp-A GAC, 3 January 2008 (Daytime) Heritage MUT SST product ACSPO SST product ACSPO is superior to MUT in coverage. But how to evaluate SST performance? SST imagery is often inspected visually for quality and artifacts. However, large-scale SST background dominates and it’s not easy to discern “signal” from “noise”.

29 May 2009GHRSST User's Symp - SQUAM4 Heritage MUT SST product Mapping deviations from a global reference field (e.g., Reynolds daily 0.25°) reveals artifacts in the product (e.g., cold stripes at AVHRR swath edges). Removing large-scale SST background (daily Reynolds) emphasizes ‘noise’ ACSPO SST product

29 May 2009GHRSST User's Symp - SQUAM5 Quantitatively, satellite SSTs are validated against in situ SSTs However, in situ SSTs have limitations  They are sparse and geographically biased (cover retrieval domain not fully and non-uniformly)  Have non-uniform and suboptimal quality (often comparable to or worse than satellite SSTs)  Not available in near real time in sufficient numbers to cover the full geographical domain and retrieval space

29 May 2009GHRSST User's Symp - SQUAM6 Try using global reference fields for quantitative evaluation of satellite SST..  Satellite & reference SSTs are subject to near-Gaussian errors T SAT = T TRUE + ε SAT ; ε SAT = N(μ sat,σ sat 2 ) T REF = T TRUE + ε REF ; ε REF = N(μ ref,σ ref 2 ) where μ’s and σ’s are global mean and standard deviations of ε‘s  The residual is distributed near-normally ΔT = T SAT - T REF = ε SAT - ε REF ; ε ΔT = N(μ ΔT,σ ΔT 2 ) where μ ΔT = μ sat - μ ref ; σ ΔT 2 = σ sat 2 + σ ref 2 (if ε SAT and ε REF are independent)  If T REF = T in situ, then it is customary validation. If (μ ref, σ ref ) are comparable to (μ in situ, σ in situ ), and if ε SAT and ε REF are not too strongly correlated, then T REF can be used to monitor T SAT  All current T REF (Reynolds, OSTIA, RTG, ODYSSEA) do not resolve diurnal cycle

29 May 2009GHRSST User's Symp - SQUAM7 Global Histograms of T SAT - T REF ( Nighttime MUT)

29 May 2009GHRSST User's Symp - SQUAM8 Histogram of SST residual Reference SST: In situ 30 days of data: ~6,500 match-ups with in situ SST Median = K; Robust Standard Deviation = 0.27 K

29 May 2009GHRSST User's Symp - SQUAM9 8 days of data: ~483,500 match-ups with OSTIA SST Median = 0.00 K; Robust Standard Deviation = 0.30 K Histogram of SST residual Reference SST: OSTIA

29 May 2009GHRSST User's Symp - SQUAM10 8 days of data: ~483,700 match-ups with daily Reynolds SST Median = K; Robust Standard Deviation = 0.42 K Histogram of SST residual Reference SST: Daily Reynolds

29 May 2009GHRSST User's Symp - SQUAM11  Global histograms of T SAT - T REF are close to Gaussian shape, against all other T REF including T in situ  Gaussian distribution is characterized by location and scale. Here, robust VAL statistics are used: Median and Robust Standard Deviation (RSD)  For some T REF ‘s (OSTIA), VAL statistics are closer to T in situ than for other T REF ‘s (Reynolds). This preliminary observation is further verified on time series. ** For more histograms (ACSPO vs. MUT, day and night, other platforms and reference SSTs), go to SQUAM page Preliminary observations from global histograms analyses

29 May 2009GHRSST User's Symp - SQUAM12 Nighttime Time Series Global Median Biases of (T SAT - T REF )

29 May 2009GHRSST User's Symp - SQUAM13 Global Median Biases T SAT – T in situ Each data point = 1 month match-up with in situ Median Bias from 0 to K except for N-16 (sensor problems) MetOp-A and N-17 fly close orbits but show a cross-platform bias of ~0.10 K

29 May 2009GHRSST User's Symp - SQUAM14 Each data point: 1 week match-up with OSTIA SST Patterns reproducible yet crispier (finer temporal resolution) NOAA-18 more consistent with NOAA-17 than in VAL OSTIA artifacts observed in early period ( ) Global Median Biases T SAT – T OSTIA

29 May 2009GHRSST User's Symp - SQUAM15 Each data point: 1 week match-up with Reynolds SST Patterns reproducible but noisier than wrt OSTIA N-18 is more consistent with N-17 than in Val against in situ Artifacts in Reynolds SST different from those in OSTIA Global Median Biases T SAT – T Reynolds

29 May 2009GHRSST User's Symp - SQUAM16  Number of match-ups: Two orders of magnitude larger against T REF than against T in situ  Major trends & anomalies in T SAT : Captured well in time series against all T REF but crisper than against T in situ  Noise: Some T REF (Reynolds) are “noisier” than others (OSTIA)  Artifacts: Different artifacts are seen in different T REF ** For more analyses (ACSPO vs. MUT, and other reference SSTs), go to SQUAM page Observations from time series of global median biases

29 May 2009GHRSST User's Symp - SQUAM17 Time Series Global RSDs of (T SAT - T REF )

29 May 2009GHRSST User's Symp - SQUAM18 Robust Standard Deviations T SAT – T in situ On average, Val against in situ SST shows RSD~0.3 K N-16: Anomalous noise in recent years (sensor problems) N-18 (flies ~2am) shows slightly better RSD that MetOp-A and N-17 (fly ~10 pm)

29 May 2009GHRSST User's Symp - SQUAM19 On average, RSD~ K N-16: the same anomalies as against in situ SST but crispier N-18: slightly better RSD than for MetOp-A and N-17, consistent with in situ Val Robust Standard Deviations T SAT – T OSTIA

29 May 2009GHRSST User's Symp - SQUAM20 Before Jan 2006: RSD~0.5 K After Jan 2006: RSD~0.4 K Change likely due to switch in Jan 2006 from Pathfinder to NAVOCEANO SEATEMP as input to Reynolds SST Robust Standard Deviations T SAT – T Reynolds

29 May 2009GHRSST User's Symp - SQUAM21  Global RSDs are slightly larger for T REF compared to T in situ  For some T REF (Reynolds) RSD is larger than for others (OSTIA)  Nevertheless, all RSDs accurately track performance of T SAT  Different artifacts are seen in different T REF ** For more analyses (ACSPO vs. MUT, and other reference SSTs), go to SQUAM page Observations from time series of global RSD’s

29 May 2009GHRSST User's Symp - SQUAM22  Validation against global reference fields is currently employed in SQUAM to monitor two NESDIS operational AVHRR SST products, in near-real time  It helps quickly uncover SST product anomalies and diagnose their root causes (SST algorithm, cloud mask, or sensor performance), and leads to corrections Summary and Future Work  Work is underway to reconcile AVHRR & reference SSTs -Improve AVHRR sensor calibration -Adjust T REF for diurnal cycle (e.g., Kennedy et al., 2007) -Improve SST product (cloud screening, SST algorithms) -Provide feedback to T REF producers Objective is to have a single “benchmark” SST in NPOESS era  Add NOAA-19 and eventually MetOp-B, -C and VIIRS to SQUAM  We are open to integration with GHRSST and collaboration (to test other satellite & reference SSTs, diurnal correction,..)

29 May 2009GHRSST User's Symp - SQUAM23  SQUAM page Real time maps, histograms, time series (including double differences), dependencies  CALVAL page Cal/Val of MUT and ACSPO data against in situ SST (currently, password protected but will be open in 2-3 months)  MICROS page (Monitoring of IR Clear-sky Radiances over Oceans for SST) Validation of SST Radiances against RTM calculations with Reynolds SST and NCEP GFS inputhttp:// NESDIS NRT SST analyses on the web