4.3 Article

Sea Surface Temperature Estimation from the Geostationary Operational Environmental Satellite-12 (GOES-12)

期刊

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/2008JTECHO596.1

关键词

-

资金

  1. NERC [NE/D001129/1] Funding Source: UKRI
  2. Natural Environment Research Council [NE/D001129/1] Funding Source: researchfish

向作者/读者索取更多资源

This paper describes the techniques used to obtain sea surface temperature (SST) retrievals from the Geostationary Operational Environmental Satellite 12 (GOES-12) at the National Oceanic and Atmospheric Administration's Office of Satellite Data Processing and Distribution. Previous SST retrieval techniques relying on channels at 11 and 12 mm are not applicable because GOES-12 lacks the latter channel. Cloud detection is performed using a Bayesian method exploiting fast-forward modeling of prior clear-sky radiances using numerical weather predictions. The basic retrieval algorithm used at nighttime is based on a linear combination of brightness temperatures at 3.9 and 11 mu m. In comparison with traditional split window SSTs (using 11- and 12-mu m channels), simulations show that this combination has maximum scatter when observing drier colder scenes, with a comparable overall performance. For daytime retrieval, the same algorithm is applied after estimating and removing the contribution to brightness temperature in the 3.9-mu m channel from solar irradiance. The correction is based on radiative transfer simulations and comprises a parameterization for atmospheric scattering and a calculation of ocean surface reflected radiance. Potential use of the 13-mu m channel for SST is shown in a simulation study: in conjunction with the 3.9-mu m channel, it can reduce the retrieval error by 30%. Some validation results are shown while a companion paper by Maturi et al. shows a detailed analysis of the validation results for the operational algorithms described in this present article.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.3
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Meteorology & Atmospheric Sciences

Sea Surface Temperature Intercomparison in the Framework of the Copernicus Climate Change Service (C3S)

Chunxue Yang, Francesca Elisa Leonelli, Salvatore Marullo, Vincenzo Artale, Helen Beggs, Bruno Buongiorno Nardelli, Toshio M. Chin, Vincenzo De Toma, Simon Good, Boyin Huang, Christopher J. Merchant, Toshiyuki Sakurai, Rosalia Santoleri, Jorge Vazquez-Cuervo, Huai-Min Zhang, Andrea Pisano

Summary: The study compared eight global sea surface temperature (SST) products and found consistent spatial patterns with main differences in specific regions. Linear trends showed a significant warming trend in global SST from 2012 to 2018, with the Pacific Ocean basin being the main contributor.

JOURNAL OF CLIMATE (2021)

Article Meteorology & Atmospheric Sciences

GLOBAL CLIMATE

R. J. H. Dunn, F. Aldred, N. Gobron, J. B. Miller, K. M. Willett, M. Ades, Robert Adler, Richard, P. Allan, Rob Allan, J. Anderson, Anthony Arguez, C. Arosio, John A. Augustine, C. Azorin-Molina, J. Barichivich, H. E. Beck, Andreas Becker, Nicolas Bellouin, Angela Benedetti, David I. Berry, Stephen Blenkinsop, Olivier Bock, X. Bodin, Michael G. Bosilovich, Olivier Boucher, S. A. Buehler, B. Calmettes, Laura Carrea, Laura Castia, Hanne H. Christiansen, John R. Christy, E. -S. Chung, Melanie Coldewey-Egbers, Owen R. Cooper, Richard C. Cornes, Curt Covey, J. -F. Cretaux, M. Crotwell, Sean M. Davis, Richard A. M. De Jeu, Doug Degenstein, R. Delaloye, Larry Di Girolamo, Markus G. Donat, Wouter A. Dorigo, Imke Durre, Geoff S. Dutton, Gregory Duveiller, James W. Elkins, Vitali E. Fioletov, Johannes Flemming, Michael J. Foster, Stacey M. Frith, Lucien Froidevaux, J. Garforth, Matthew Gentry, S. K. Gupta, S. Hahn, Leopold Haimberger, Brad D. Hall, Ian Harris, D. L. Hemming, M. Hirschi, Shu-pen (Ben) Ho, F. Hrbacek, Daan Hubert, Dale F. Hurst, Antje Inness, K. Isaksen, Viju O. John, Philip D. Jones, Robert Junod, J. W. Kaiser, V. Kaufmann, A. Kellerer-Pirklbauer, Elizabeth C. Kent, R. Kidd, Hyungjun Kim, Z. Kipling, A. Koppa, B. M. Kraemer, D. P. Kratz, Xin Lan, Kathleen O. Lantz, D. Lavers, Norman G. Loeb, Diego Loyola, R. Madelon, Michael Mayer, M. F. McCabe, Tim R. McVicar, Carl A. Mears, Christopher J. Merchant, Diego G. Miralles, L. Moesinger, Stephen A. Montzka, Colin Morice, L. Mosinger, Jens Muhle, Julien P. Nicolas, Jeannette Noetzli, Ben Noll, J. O'Keefe, Tim J. Osborn, T. Park, A. J. Pasik, C. Pellet, Maury S. Pelto, S. E. Perkins-Kirkpatrick, G. Petron, Coda Phillips, S. Po-Chedley, L. Polvani, W. Preimesberger, D. G. Rains, W. J. Randel, Nick A. Rayner, Samuel Remy, L. Ricciardulli, A. D. Richardson, David A. Robinson, Matthew Rodell, N. J. Rodriguez-Fernandez, K. H. Rosenlof, C. Roth, A. Rozanov, T. Rutishauser, Ahira Sanchez-Lugo, P. Sawaengphokhai, T. Scanlon, Verena Schenzinger, R. W. Schlegel, S. Sharma, Lei Shi, Adrian J. Simmons, Carolina Siso, Sharon L. Smith, B. J. Soden, Viktoria Sofieva, T. H. Sparks, Paul W. Stackhouse, Wolfgang Steinbrecht, Martin Stengel, Dimitri A. Streletskiy, Sunny Sun-Mack, P. Tans, S. J. Thackeray, E. Thibert, D. Tokuda, Kleareti Tourpali, Mari R. Tye, Ronald van der A, Robin van der Schalie, Gerard van der Schrier, M. van der Vliet, Guido R. van der Werf, A. Vance, Jean-Paul Vernier, Isaac J. Vimont, Holger Vomel, Russell S. Vose, Ray Wang, Markus Weber, David Wiese, Anne C. Wilber, Jeanette D. Wild, Takmeng Wong, R. Iestyn Woolway, Xinjia Zhou, Xungang Yin, Guangyu Zhao, Lin Zhao, Jerry R. Ziemke, Markus Ziese, R. M. Zotta

BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY (2021)

Article Environmental Sciences

Bayesian Cloud Detection over Land for Climate Data Records

Claire E. Bulgin, Owen Embury, Ross I. Maidment, Christopher J. Merchant

Summary: Cloud detection is crucial in generating land surface temperature climate data records. This study presents a sensor-independent Bayesian cloud detection algorithm and demonstrates its effectiveness in producing accurate records. The algorithm is tested on multiple instruments and shows consistent performance, ensuring observation stability over time.

REMOTE SENSING (2022)

Article Environmental Sciences

Space-based Earth observation in support of the UNFCCC Paris Agreement

Michaela Hegglin, Ana Bastos, Heinrich Bovensmann, Michael Buchwitz, Dominic Fawcett, Darren Ghent, Gemma Kulk, Shubha Sathyendranath, Theodore G. Shepherd, Shaun Quegan, Regine Roethlisberger, Stephen Briggs, Carlo Buontempo, Anny Cazenave, Emilio Chuvieco, Philippe Ciais, David Crisp, Richard Engelen, Suvarna Fadnavis, Martin Herold, Martin Horwath, Oskar Jonsson, Gabriel Kpaka, Christopher J. Merchant, Christian Mielke, Thomas Nagler, Frank Paul, Thomas Popp, Tristan Quaife, Nick A. Rayner, Colas Robert, Marc Schroder, Stephen Sitch, Sara Venturini, Robin van der Schalie, Mendy van der Vliet, Jean-Pierre Wigneron, R. Iestyn Woolway

Summary: Space-based Earth observation plays a crucial role in monitoring and quantifying climate system changes, and is essential for effective policy making and measuring progress towards the goals of the Paris Agreement. However, the best approach for translating observation data into actionable information is still unclear.

FRONTIERS IN ENVIRONMENTAL SCIENCE (2022)

Article Multidisciplinary Sciences

Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies

Laura Carrea, Jean-Francois Cretaux, Xiaohan Liu, Yuhao Wu, Beatriz Calmettes, Claude R. Duguay, Christopher J. Merchant, Nick Selmes, Stefan G. H. Simis, Mark Warren, Herve Yesou, Dagmar Mueller, Dalin Jiang, Owen Embury, Muriel Berge-Nguyen, Clement Albergel

Summary: This dataset presents a consistent collection of satellite observations for lake surface water temperature, ice cover, water-leaving reflectance, water level, and extent. The observations span from 1992 to 2020 and cover over 2000 large lakes, representing a significant portion of global freshwater surface. The dataset, validated against in situ measurements, provides the most complete and consistent satellite observations of the Lakes Essential Climate Variable (ECV) available.

SCIENTIFIC DATA (2023)

Article Environmental Sciences

Dynamic sea-level changes and potential implications for storm surges in the UK: a storylines perspective

Claire E. Bulgin, Jennifer Mecking, Ben J. Harvey, Svetlana Jevrejeva, Niall F. McCarroll, Christopher J. Merchant, Bablu Sinha

Summary: Global sea-level rise from a warming climate increases flood risk from storm surges in coastal and low-lying areas. This study uses satellite observations and model projections to identify the drivers of dynamic sea-level changes over the UK shelf seas. The findings suggest that a northward shift in the atmospheric jet stream and a weakening of the Atlantic meridional overturning circulation are key factors influencing local sea-level variability.

ENVIRONMENTAL RESEARCH LETTERS (2023)

Article Meteorology & Atmospheric Sciences

Benchmarking a two-way coupled coastal wave-current hydrodynamics model

Anastasia K. Fragkou, Christopher Old, Vengatesan Venugopal, Athanasios Angeloudis

Summary: In this study, a series of benchmark test cases were selected to evaluate and compare coupled model frameworks for wave-current interaction. Calibration uncertainties were identified and highlighted through comparing calibrated and default parameter settings. The calibrated model results showed good correlation with experimental and analytical data, as well as benchmarked predictions from other wave-current models.

OCEAN MODELLING (2023)

Article Environmental Sciences

Improving the combined use of reflectance and thermal channels for ocean and coastal cloud detection for the Sea and Land Surface Temperature Radiometer (SLSTR)

Claire E. Bulgin, Agnieszka Faulkner, Christopher J. Merchant, Gary K. Corlett, Niall McCarroll, Owen Embury, Edward Polehampton, Connor McGurk

Summary: This paper presents new approaches to utilizing reflectance imagery for sea surface temperature (SST) remote sensing and improving cloud detection in infrared images. By averaging and calculating the standard deviation of the nearest reflectance observations, the authors were able to enhance the discrimination of clouds in the infrared image. The results show significant improvements in coastal areas and around ocean fronts, leading to increased accuracy and coverage of SST measurements.

REMOTE SENSING OF ENVIRONMENT (2023)

Article Astronomy & Astrophysics

Inconsistent Coral Bleaching Risk Indicators Between Temperature Data Sources

V. H. F. Neo, J. Zinke, T. Fung, C. J. Merchant, K. J. A. Zawada, H. Krawczyk, J. M. Maina

Summary: Coral reefs are at risk of accelerated decline due to climate change-induced changes, and it is uncertain if the Sea Surface Temperature data used for coral reef studies are consistent among different data products. Understanding the consistency among different SST data sources can help improve monitoring and understanding of the impact of global warming on coral reefs. The study compares four types of SST data and highlights the need to compare existing indicators of thermal stress from different data sets. Rating: 8/10

EARTH AND SPACE SCIENCE (2023)

Article Geochemistry & Geophysics

Retrieval of Sea Surface Temperature From HY-1B COCTS

Mingkun Liu, Christopher J. Merchant, Owen Embury, Jianqiang Liu, Qingjun Song, Lei Guan

Summary: The Bayesian cloud detection and optimal estimation (OE) SST retrieval algorithm was applied to reprocess the Haiyang-1B (HY-1B) COCTS SST data. The results showed that this algorithm successfully improved the accuracy of COCTS SST and demonstrated the potential for developing SST products for operational HY-1 satellites: HY-1C and HY-1D.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2022)

Article Geosciences, Multidisciplinary

Global sea-level budget and ocean-mass budget, with a focus on advanced data products and uncertainty characterisation

Martin Horwath, Benjamin D. Gutknecht, Anny Cazenave, Hindumathi Kulaiappan Palanisamy, Florence Marti, Ben Marzeion, Frank Paul, Raymond Le Bris, Anna E. Hogg, Ines Otosaka, Andrew Shepherd, Petra Doell, Denise Caceres, Hannes Mueller Schmied, Johnny A. Johannessen, Jan Even Oie Nilsen, Roshin P. Raj, Rene Forsberg, Louise Sandberg Sorensen, Valentina R. Barletta, Sebastian B. Simonsen, Per Knudsen, Ole Baltazar Andersen, Heidi Ranndal, Stine K. Rose, Christopher J. Merchant, Claire R. Macintosh, Karina von Schuckmann, Kristin Novotny, Andreas Groh, Marco Restano, Jerome Benveniste

Summary: Studies on the global sea-level budget and ocean-mass budget are crucial for understanding the reliability of sea-level change and its contributors. In this study, datasets for the sea-level budget and ocean-mass budget were analyzed using a consistent framework of uncertainty characterization. The findings show that the sea-level rise trend aligns with the sum of the mass and steric components.

EARTH SYSTEM SCIENCE DATA (2022)

Article Environmental Sciences

Characterising industrial thermal plumes in coastal regions using 3-D numerical simulations

Agnieszka Faulkner, Claire E. Bulgin, Christopher J. Merchant

Summary: This study assesses the use of simulations and remotely sensed observations to characterize thermal plume behavior for a coastal power station, showing that simulated plume temperatures are higher than observed values, but the direction is consistent.

ENVIRONMENTAL RESEARCH COMMUNICATIONS (2021)

暂无数据