QUALITY INFORMATION DOCUMENT For OSI TAC SST products , 007, 008

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1 QUALITY INFORMATION DOCUMENT For OSI TAC SST products , 007, 008 Issue: 1.5 Contributors: Jacob L. HOYER (DMI), Hanne HEIBERG (met.no), Jean-Francois PIOLLÉ (IFREMER), Bruce Hackett (MET Norway) Approval Date by Quality Assurance Review Group : under review

2 CHANGE RECORD Issue Date Description of Change Author Validated By /01/13 All First draft version for OSI TAC V3 SST products Hervé ROQUET Lars-Anders BREIVIK /01/13 IV. 4 Updated statistics for the SST analysis over the Baltic Sea (product ) Hervé ROQUET Lars-Anders BREIVIK /02/13 All Update to include multisensor SST product over European Seas (product ) Hervé ROQUET Lars-Anders BREIVIK /03/2013 II.2, V SST inland water upgrade Ed BLOCKLEY Lars-Anders BREIVIK /08/2013 II.3 Added paragraph with comment on compensating missing ice data along the coast Hanne Heiberg /01/2014 I.1, IV. 1, IV. 2 V.2 Updated with MED and BS L4 data Added Summary of the impact of the changes in High Resolution SST analysis over the Mediterranean ( a) Andrea PISANO Bruno BUONGIORNO NARDELLI 1.3 May all Remove info about product and , 006, 012 and 013 already covered in other QUIDs Change format to fit CMEMS graphical rules L. Crosnier EU Copernicus Marine Service Public Page 2/ 11

3 1.4 01/09/2015 all Remove info about product a,b which is now found in separate QUIDs. Update satellite info /01/2016 All Complete CMEMS rebranding. Update statistics and processing description for Ifremer product Bruce Hackett, Cristina Luis, Jacob Høyer. J.-F. Piollé J.-F. Piollé, Bruce Hackett EU Copernicus Marine Service Public Page 3/ 11

4 TABLE OF CONTENTS I Executive summary... 5 I.1 Products covered by this document... 5 I.2 Summary of results... 5 I.3 Estimated Accuracy Numbers... 6 II Production Subsystem description... 7 II.1.1 Processing chain at DMI and MET Norway... 7 II.1.2 Processing chain at IFREMER... 8 III Validation framework... 9 IV Validation results IV.1 High Resolution SST analysis over the Baltic Sea ( ) IV.2 High Resolution SST analysis over the Arctic Ocean ( ) IV.3 High Resolution SST analysis over the Northwest European Shelves ( ) EU Copernicus Marine Service Public Page 4/ 11

5 I EXECUTIVE SUMMARY I.1 Products covered by this document The CMEMS OSI TAC (Ocean and Sea Ice Thematic Assembly Centre) SST products covered by this document are : Product Name SST_BAL_SST_L4_NRT_007_b SST_ARC_SST_L4_NRT_008_b SST_NWS_SST_L4_NRT_003 Production Unit DMI (Copenhagen) MET Norway (Oslo) IFREMER (Brest) The SST_BAL_SST_L4_NRT_007_b and SST_ARC_SST_L4_NRT_OBSERVATIONS_ 010_008_b products are daily analyses of the night time SST at high resolution, covering the Baltic Sea (0.02 x 0.02 ) and the extended Arctic region 60 N (0.03 x 0.03 ). The analyses are based on the same algorithm. It uses various satellite SST level 2 data as input, which have passed a significant number of quality controls, and which are bias corrected. Then they are interpolated onto the analysis grid through an optimal interpolation scheme. The SST_NWS_SST_L4_NRT_003 is a multi-sensor level 4 analysis, covering the Northwest European Shelves at 0.02 horizontal resolution. It results from the merging of various satellite SST level 2 data, which have passed a significant number of quality controls, and which have been inter-calibrated through an inter-sensor bias correction procedure, using a median field generated from a set of best quality sensors, to provide an estimate of the night time SST based on original SST observations. I.2 Summary of results When compared to in-situ SST measurements, the SST products documented here show rather consistent difference statistics. The regional SST analyses over the Arctic Ocean show results (mean difference : K, difference standard deviation : 0.63 K) which are slightly worse than the ones over the Baltic Sea (mean difference : K, difference standard deviation : 0.44 K). One important contributing factor is certainly the lower quality of input satellite SST measurements in the Arctic area, were problems like cloud screening (especially during winter time) and atmospheric correction are very challenging for SST retrieval from satellite measurements. EU Copernicus Marine Service Public Page 5/ 11

6 I.3 Estimated Accuracy Numbers Product Name Mean difference RMS difference (K) (K) SST_BAL_SST_L4_NRT_007_b SST_ARC_SST_L4_NRT_008_b SST_NWS_SST_L4_NRT_ EU Copernicus Marine Service Public Page 6/ 11

7 II PRODUCTION SUBSYSTEM DESCRIPTION II.1.1 Processing chain at DMI and MET Norway Figure II.3.1 Schematic diagram of the operational processing chain at DMI and MET Norway The Operational Sea surface Temperature and Ice Analysis (DMIOI) system is run daily in the operational suite at DMI and MET Norway. Figure III.2.1 shows the different steps for the creation of the daily SST analyses (level 4 products) covering the Baltic Sea and the Arctic Ocean. For the Baltic Sea, the following satellite SST level 2 data are collected for input to the DMIOI algorithm: infra-red data from the AVHRR instruments on board NOAA and MetOp-A satellites, from SEVIRI on board the MSG satellite and from VIIRS onboard the Suomi-NPP. The data are collected in near real-time from various satellite SST producers (NASA, NOAA, EUMETSAT SAF on Ocean and Sea Ice, ESA) in GHRSST L2P format. The analysis is using high resolution (1 km) sea ice concentration products over the Baltic Sea from the CMEMS OSI TAC, and for operational validation in situ SST measurements from drifting buoys, obtained from the CMEMS In Situ Thematic Assembly Centre (INS TAC). For the Arctic Ocean, the same SST level 2 data are collected for input, except from the SEVIRI instrument. The EUMETSAT OSI-SAF sea ice mask is used (since the sea-ice concentration product with 1 km resolution from the OSI TAC does not cover the Arctic Ocean). A derivative of the CMEMS EU Copernicus Marine Service Public Page 7/ 11

8 INS TAC product from drifting buoys, INSITU_GLO_TS_NRT_OBSERVATION_013_001_a, is used for operational validation. The ice edge and ice concentration data cover the sea area outside a fixed distance from the coastline. This fixed distance is chosen in accordance with the size of the footprint of the satellite sensor, because it cannot detect ice properly due to possible land contamination. To compensate for the missing ice close to land, the ice area is grown 5 pixels if there is land within a radius of 5 pixels from an ice pixel. Sometimes, (more often in summer than winter), the ice field may contain false ice pixels. If close to land, the false ice pixel is also grown as a side-effect. This typically shows up as sudden small ice covered area(s) close to land that slowly disappears within in few days. This is a consequence of improving missing ice and is judged to be a net benefit. II.1.2 Processing chain at IFREMER Figure II.5.1 Schematic diagram of the operational processing chain at IFREMER Figure II.4.1 shows the different steps for the processing of SST products at IFREMER. In the current configuration of the chain, a selection of GHRSST L2P products is used as to build the reference for the bias correction of the other SST sources. More details on each processing step can be found in the corresponding Product User Manual. EU Copernicus Marine Service Public Page 8/ 11

9 III VALIDATION FRAMEWORK The baseline for the validation of SST products is to use drifting buoy measurements only, as recommended currently by the GHRSST group on satellite SST validation (STVAL). Mean and standard deviation of the departures from drifting buoy SST measurements are computed over pre-defined geographical areas (Figure IV.1.1). Various quality check procedures are applied on drifting buoy measurements by SST Production Units to discard suspect data, using gross error checks and/or blacklists made available by various centres. Figure III.1.1 : Geographical areas defined for the computation of validation statistics. However, for some SST products, the use of drifting buoy measurements has limitations which can affect negatively the significance of these statistics : - in some parts of the global ocean and in some regional seas, the number of drifting buoy measurements is very low (ex : Mediterranean Sea, Baltic Sea), and even sometimes equal to zero (ex : Black Sea). In these cases, additional statistics can be computed using other data sources (moored buoys, ARGOS floats, AATSR ) - some of the SST products make use of drifting buoy measurements (ex : OSTIA analysis), which cannot be considered as independent validation data anymore. This issue can be circumvented in some cases by computing background ( = analysis from the previous day in the OSTIA case) departure statistics, or by using other data sources which are not used in the processing (ex : ARGOS floats) EU Copernicus Marine Service Public Page 9/ 11

10 IV VALIDATION RESULTS IV.1 High Resolution SST analysis over the Baltic Sea ( ) Product Name start date end date sel. area parameter value SST_BAL_SST_L4_NRT _007_b T00: T00:00 bal mean SST_BAL_SST_L4_NRT _007_b T00: T00:00 bal stddev SST_BAL_SST_L4_NRT _007_b T00: T00:00 bal nbsamples 8577 Table V.4.1 Mean (K), standard deviation (K), and number of match-ups for differences between High Resolution Baltic Sea SST analysis and in-situ SST measurements provided by IN-Situ TAC. The statistics were computed over the Baltic Sea area from to IV.2 High Resolution SST analysis over the Arctic Ocean ( ) Product Name start date end date sel. area parameter value SST_ARC_SST_L4_NRT _008_b T00: T00:00 arc mean SST_ARC_SST_L4_NRT _008_b T00: T00:00 arc stddev 0.63 SST_ARC_SST_L4_NRT _008_b T00: T00:00 arc nbsamples Table V.5.1 Mean (K), standard deviation (K), and number of match-ups for differences between High Resolution Arctic Ocean SST analysis and in-situ SST measurements provided by IN-Situ TAC. The statistics were computed over the Arctic Ocean (subarea defined in Figure IV.1.1) from to EU Copernicus Marine Service Public Page 10/ 11

11 IV.3 High Resolution SST analysis over the Northwest European Shelves ( ) Product Name start date end date sel. area parameter value SST_NWS_SST_L4_NR T_OBSERVATIONS_01 0_ T00: T00:00 nwe mean SST_NWS_SST_L4_NR T_OBSERVATIONS_01 0_ T00: T00:00 nwe stddev SST_NWS_SST_L4_NR T_OBSERVATIONS_01 0_ T00: T00:00 nwe nbsamples Table V.5.1 Mean (K), standard deviation (K), and number of match-ups for differences between High Resolution Northwest European Shelves SST analysis and in-situ SST measurements provided by IN- Situ TAC. The statistics were computed from to EU Copernicus Marine Service Public Page 11/ 11