The SST Quality Monitor (SQUAM)Source: Journal of Atmospheric and Oceanic Technology:;2010:;volume( 027 ):;issue: 011::page 1899DOI: 10.1175/2010JTECHO756.1Publisher: American Meteorological Society
Abstract: The National Environmental Satellite, Data, and Information Service (NESDIS) has been operationally generating sea surface temperature (SST) products (TS) from the Advanced Very High Resolution Radiometers (AVHRR) onboard NOAA and MetOp-A satellites since the early 1980s. Customarily, TS are validated against in situ SSTs. However, in situ data are sparse and are not available globally in near?real time (NRT). This study describes a complementary SST Quality Monitor (SQUAM), which employs global level 4 (L4) SST fields as a reference standard (TR) and performs statistical analyses of the differences ?TS = TS ? TR. The results are posted online in NRT. The TS data that are analyzed are the heritage National Environmental Satellite, Data, and Information Service (NESDIS) SST products from NOAA-16, -17, -18, and -19 and MetOp-A from 2001 to the present. The TR fields include daily Reynolds, real-time global (RTG), Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA), and Ocean Data Analysis System for Marine Environment and Security for the European Area (MERSEA) (ODYSSEA) analyses. Using multiple fields facilitates the distinguishing of artifacts in satellite SSTs from those in the L4 products. Global distributions of ?TS are mapped and their histograms are analyzed for proximity to Gaussian shape. Outliers are handled using robust statistics, and the Gaussian parameters are trended in time to monitor SST products for stability and consistency. Additional TS checks are performed to identify retrieval artifacts by plotting ?TS versus observational parameters. Cross-platform TS biases are evaluated using double differences, and cross-L4 TR differences are assessed using Hovmöller diagrams. SQUAM results compare well with the customary in situ validation. All satellite products show a high degree of self- and cross-platform consistency, except for NOAA-16, which has flown close to the terminator in recent years and whose AVHRR is unstable.
|
Collections
Show full item record
contributor author | Dash, Prasanjit | |
contributor author | Ignatov, Alexander | |
contributor author | Kihai, Yury | |
contributor author | Sapper, John | |
date accessioned | 2017-06-09T16:37:32Z | |
date available | 2017-06-09T16:37:32Z | |
date copyright | 2010/11/01 | |
date issued | 2010 | |
identifier issn | 0739-0572 | |
identifier other | ams-71168.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4213030 | |
description abstract | The National Environmental Satellite, Data, and Information Service (NESDIS) has been operationally generating sea surface temperature (SST) products (TS) from the Advanced Very High Resolution Radiometers (AVHRR) onboard NOAA and MetOp-A satellites since the early 1980s. Customarily, TS are validated against in situ SSTs. However, in situ data are sparse and are not available globally in near?real time (NRT). This study describes a complementary SST Quality Monitor (SQUAM), which employs global level 4 (L4) SST fields as a reference standard (TR) and performs statistical analyses of the differences ?TS = TS ? TR. The results are posted online in NRT. The TS data that are analyzed are the heritage National Environmental Satellite, Data, and Information Service (NESDIS) SST products from NOAA-16, -17, -18, and -19 and MetOp-A from 2001 to the present. The TR fields include daily Reynolds, real-time global (RTG), Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA), and Ocean Data Analysis System for Marine Environment and Security for the European Area (MERSEA) (ODYSSEA) analyses. Using multiple fields facilitates the distinguishing of artifacts in satellite SSTs from those in the L4 products. Global distributions of ?TS are mapped and their histograms are analyzed for proximity to Gaussian shape. Outliers are handled using robust statistics, and the Gaussian parameters are trended in time to monitor SST products for stability and consistency. Additional TS checks are performed to identify retrieval artifacts by plotting ?TS versus observational parameters. Cross-platform TS biases are evaluated using double differences, and cross-L4 TR differences are assessed using Hovmöller diagrams. SQUAM results compare well with the customary in situ validation. All satellite products show a high degree of self- and cross-platform consistency, except for NOAA-16, which has flown close to the terminator in recent years and whose AVHRR is unstable. | |
publisher | American Meteorological Society | |
title | The SST Quality Monitor (SQUAM) | |
type | Journal Paper | |
journal volume | 27 | |
journal issue | 11 | |
journal title | Journal of Atmospheric and Oceanic Technology | |
identifier doi | 10.1175/2010JTECHO756.1 | |
journal fristpage | 1899 | |
journal lastpage | 1917 | |
tree | Journal of Atmospheric and Oceanic Technology:;2010:;volume( 027 ):;issue: 011 | |
contenttype | Fulltext |