Group for High Resolution Sea Surface Temperature (GHRSST) analysis fields inter-comparisons-Part 2: Near real time web-based level 4 SST Quality Monitor (L4-SQUAM)
|Copyright||2012 Elsevier Ltd. All rights reserved|
|Author(s)||Dash Prasanjit1, 1, 2, 2, Ignatov Alexander1, 1, Martin Matthew3, 3, Donlon Craig4, 4, Brasnett Bruce5, 5, Reynolds Richard W.6, 6, Banzon Viva7, 7, Beggs Helen8, 8, Cayula Jean-Francois9, 9, Chao Yi10, 10, Grumbine Robert11, 11, Maturi Eileen1, 1, Harris Andy1, 1, 12, 12, Mittaz Jonathan1, 1, 12, 12, Sapper John13, 13, Chin Toshio M.14, 14, Vazquez-Cuervo Jorge14, 14, Armstrong Edward M.14, 14, Gentemann Chelle, Cummings James15, 15, Piolle Jean-Francois16, 16, Autret Emmanuelle16, 16, Roberts-Jones Jonah3, 3, Ishizaki Shiro17, 17, Hoyer Jacob L.18, 18, Poulter Dave19, 19|
|Affiliation(s)||1 : Ctr Satellite Applicat & Res STAR, NOAA NESDIS, Camp Springs, MD USA.
2 : Colorado State Univ, CIRA, Ft Collins, CO 80523 USA.
3 : Met Off, Exeter, Devon, England.
4 : ESA ESTEC, Earth Observat Miss Sci Div, NL-2201 AZ Noordwijk, Netherlands.
5 : Canadian Meteorol Ctr, Dorval, PQ, Canada.
6 : Inst Climate & Satellites CICS, NOAA Cooperat, Asheville, NC USA.
7 : NCDC, NOAA, Asheville, NC USA.
8 : Ctr Australian Weather & Climate Res, Bur Meteorol, Melbourne, Vic, Australia.
9 : QinctiQ N Amer, Technol Solut Grp, Stennis Space Ctr, MS 39522 USA.
10 : Remote Sensing Solut Inc, Pasadena, CA USA.
11 : NOAA NWS NCEP, Camp Springs, MD USA.
12 : Univ Maryland, CICS, College Pk, MD 20742 USA.
13 : OSPO, NOAA NESDIS, Camp Springs, MD USA.
14 : JPL Caltech, Pasadena, CA USA.
15 : USN, Res Lab, Monterey, CA USA.
16 : CERSAT, IFREMER, Spatial Oceanog Lab, Brest, France.
17 : Japan Meteorol Agcy, Tokyo, Japan.
18 : Danish Meteorol Inst, Copenhagen, Denmark.
19 : Natl Oceanog Ctr, Southampton SO14 3ZH, Hants, England.
|Source||Deep-sea Research Part Ii-topical Studies In Oceanography (0967-0645) (Pergamon-elsevier Science Ltd), 2012-11 , Vol. 77-80 , P. 31-43|
|WOS© Times Cited||22|
|Keyword(s)||Sea surface temperature, Intercomparison, Climate data, Sea ice, Data centers|
|Abstract||There are a growing number of level 4 (L4; gap-free gridded) sea surface temperature (SST) products generated by blending SST data from various sources which are available for use in a wide variety of operational and scientific applications. In most cases, each product has been developed for a specific user community with specific requirements guiding the design of the product. Consequently differences between products are implicit. In addition, anomalous atmospheric conditions, satellite operations and production anomalies may occur which can introduce additional differences. This paper describes a new web-based system called the L4 SST Quality Monitor (L4-SQUAM) developed to monitor the quality of L4 SST products. L4-SQUAM intercompares thirteen L4 products with 1-day latency in an operational environment serving the needs of both L4 SST product users and producers. Relative differences between products are computed and visualized using maps, histograms, time series plots and Hovmoller diagrams, for all combinations of products. In addition, products are compared to quality controlled in situ SST data (available from the in situ SST Quality Monitor, iQUAM, companion system) in a consistent manner. A full history of products statistics is retained in L4-SQUAM for time series analysis. L4-SQUAM complements the two other Group for High Resolution SST (GHRSST) tools, the GHRSST Multi Product Ensemble (GMPE) and the High Resolution Diagnostic Data Set (HRDDS) systems, documented in part 1 of this paper and elsewhere, respectively. Our results reveal significant differences between SST products in coastal and open ocean areas. Differences of > 2 degrees C are often observed at high latitudes partly due to different treatment of the sea-ice transition zone. Thus when an ice flag is available, the intercomparisons are performed in two ways: including and excluding ice-flagged grid points. Such differences are significant and call for a community effort to understand their root cause and ensure consistency between SST products. Future work focuses on including the remaining daily L4 SST products, accommodating for newer L4 SSTs which resolve the diurnal variability and evaluating retrospectively regenerated L4 SSTs to support satellite data reprocessing efforts aimed at generating improved SST Climate Data Records. (c) 2012 Elsevier Ltd. All rights reserved.|