The SST Quality Monitor (SQUAM)

被引:71
作者
Dash, Prasanjit [1 ,2 ]
Ignatov, Alexander
Kihai, Yury [3 ]
Sapper, John [4 ]
机构
[1] NOAA, CSU, CIRA Res Scientist 2, NESDIS,STAR,WWB,Ctr Satellite Applicat & Res, Camp Springs, MD 20746 USA
[2] Colorado State Univ, Cooperat Inst Res Atmospheres, Ft Collins, CO 80523 USA
[3] Perot Syst Govt Serv, Fairfax, VA USA
[4] NOAA, NESDIS, Off Satellite Data Proc & Distribut, Camp Springs, MD USA
关键词
SEA-SURFACE TEMPERATURE; EMITTED RADIANCE INTERFEROMETER; HIGH-RESOLUTION; IN-SITU; REAL-TIME; SATELLITE; ACCURACY; CALIBRATION; RETRIEVALS; CHANNELS;
D O I
10.1175/2010JTECHO756.1
中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
The National Environmental Satellite, Data, and Information Service (NESDIS) has been operationally generating sea surface temperature (SST) products (T-S) from the Advanced Very High Resolution Radiometers (AVHRR) onboard NOAA and MetOp-A satellites since the early 1980s. Customarily, T-S 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 (T-R) and performs statistical analyses of the differences Delta T-S = T-S - T-R. The results are posted online in NRT. The T-S 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 T-R 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 Delta T-S 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 T-S checks are performed to identify retrieval artifacts by plotting Delta T-S versus observational parameters. Cross-platform T-S biases are evaluated using double differences, and cross-L4 T-R differences are assessed using Hovmoller 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.
引用
收藏
页码:1899 / 1917
页数:19
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