An operational analysis system for the global diurnal cycle of sea surface temperature: implementation and validation

2017 ◽  
Vol 143 (705) ◽  
pp. 1787-1803 ◽  
Author(s):  
J. While ◽  
C. Mao ◽  
M. J. Martin ◽  
J. Roberts-Jones ◽  
P. A. Sykes ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Diurnal Cycle ◽  
Sea Surface ◽  
Operational Analysis ◽  
Analysis System

scholarly journals Estimating Sea Surface Temperature Measurement Methods Using Characteristic Differences in the Diurnal Cycle

2018 ◽  
Vol 45 (1) ◽  
pp. 363-371 ◽  
Author(s):  
G. Carella ◽  
J. J. Kennedy ◽  
D. I. Berry ◽  
S. Hirahara ◽  
C. J. Merchant ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Temperature Measurement ◽  
Diurnal Cycle ◽  
Measurement Methods ◽  
Sea Surface ◽  
Surface Temperature Measurement

scholarly journals Modeling the Near‐Surface Diurnal Cycle of Sea Surface Temperature in the Mediterranean Sea

2019 ◽  
Vol 124 (1) ◽  
pp. 171-183 ◽  
Author(s):  
S. Pimentel ◽  
W.‐H. Tse ◽  
H. Xu ◽  
D. Denaxa ◽  
E. Jansen ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mediterranean Sea ◽  
Diurnal Cycle ◽  
Sea Surface ◽  
Near Surface ◽  
The Mediterranean

Evaluation of the in situ Sea Surface Temperature Quality Control in the NOAA in situ SST Quality Monitor (iQuam) System

2021 ◽  
Author(s):  
Haifeng Zhang ◽  
Alexander Ignatov ◽  
Dean Hinshaw
Keyword(s):  
Quality Control ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Diurnal Cycle ◽  
Critical Role ◽  
Sea Surface ◽  
Multiple Sources ◽  
Ocean Data Assimilation ◽  
Satellite Sst

AbstractIn situ sea surface temperature (SST) measurements play a critical role in the calibration/validation (Cal/Val) of satellite SST retrievals and ocean data assimilation. However, their quality is not always optimal, and proper quality control (QC) is required before they can be used with confidence. The in situ SST Quality Monitor (iQuam) system was established at the National Oceanic and Atmospheric Administration (NOAA) in 2009, initially to support the Cal/Val of NOAA satellite SST products. It collects in situ SST data from multiple sources, performs uniform QC, monitors the QC’ed data online, and distributes it to users. In this study, the iQuam QC is compared with other QC methods available in some of the in situ data ingested in iQuam. Overall, the iQuam QC performs well on daily-to-monthly time scales over most global oceans and under a wide variety of environmental conditions. However, it may be less accurate in the daytime a when pronounced diurnal cycle is present, and in dynamic regions, due to the strong reliance on the “reference SST check”, which employs daily low-resolution level 4 (L4) analyses with no diurnal cycle resolved. The iQuam “performance history check”, applied to all in situ platforms, is an effective alternative to the customary “black/gray” lists, available only for some platforms (e.g., drifters and Argo floats). In the future, iQuam QC will be upgraded (e.g., using improved reference field(s), with enhanced temporal and spatial resolutions). More comparisons with external QC methods will be performed to learn and employ the best QC practices.

scholarly journals Coupled Impacts of the Diurnal Cycle of Sea Surface Temperature on the Madden–Julian Oscillation

2014 ◽  
Vol 27 (22) ◽  
pp. 8422-8443 ◽  
Author(s):  
Hyodae Seo ◽  
Aneesh C. Subramanian ◽  
Arthur J. Miller ◽  
Nicholas R. Cavanaugh
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Diurnal Cycle ◽  
Atmospheric Model ◽  
Sea Surface ◽  
Madden Julian Oscillation ◽  
Sst Variability ◽  
Budget Analysis ◽  
Diurnal Sst Variation

Abstract This study quantifies, from a systematic set of regional ocean–atmosphere coupled model simulations employing various coupling intervals, the effect of subdaily sea surface temperature (SST) variability on the onset and intensity of Madden–Julian oscillation (MJO) convection in the Indian Ocean. The primary effect of diurnal SST variation (dSST) is to raise time-mean SST and latent heat flux (LH) prior to deep convection. Diurnal SST variation also strengthens the diurnal moistening of the troposphere by collocating the diurnal peak in LH with those of SST. Both effects enhance the convection such that the total precipitation amount scales quasi-linearly with preconvection dSST and time-mean SST. A column-integrated moist static energy (MSE) budget analysis confirms the critical role of diurnal SST variability in the buildup of column MSE and the strength of MJO convection via stronger time-mean LH and diurnal moistening. Two complementary atmosphere-only simulations further elucidate the role of SST conditions in the predictive skill of MJO. The atmospheric model forced with the persistent initial SST, lacking enhanced preconvection warming and moistening, produces a weaker and delayed convection than the diurnally coupled run. The atmospheric model with prescribed daily-mean SST from the coupled run, while eliminating the delayed peak, continues to exhibit weaker convection due to the lack of strong moistening on a diurnal basis. The fact that time-evolving SST with a diurnal cycle strongly influences the onset and intensity of MJO convection is consistent with previous studies that identified an improved representation of diurnal SST as a potential source of MJO predictability.

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