Article
Ecology
Kathryn Wheeler, Michael C. Dietze
Summary: Monitoring leaf phenology can track the impact of climate change and seasonal variations on organisms and ecosystems. Ground networks provide high temporal resolution phenological information, while satellite data is used for broader measurements of phenology.
Article
Geography, Physical
Zhenwei Zhang, Qingyun Du
Summary: This study developed estimation schemes for mapping hourly SAT over a large-scale region by blending LST datasets from two-satellite system. The model scheme with reanalysis variables and HOD achieved the highest performance with a mean RMSE of 1.9 K, indicating the importance of including these variables in the modeling process.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Zhenwei Zhang, Yanzhi Liang, Guangxia Zhang, Chen Liang
Summary: In this study, hourly estimation models for surface air temperature (SAT) based on land surface temperature (LST) derived from FY-4A, the first geostationary satellite in China's new-generation meteorological observation mission, were developed and cross-validated using random forest. Incorporating time and location variables into the hourly models significantly improves predictive performance. The best-performing model with an average RMSE of 2.22 K was used to reconstruct hourly maps of SAT. This study has general implications for large-scale estimation of hourly SAT based on geostationary LST datasets.
Article
Environmental Sciences
Zhi Huang, Jianyu Hu, Weian Shi
Summary: This study used satellite data to map and quantitatively analyze coastal upwelling along the Taiwan east coast during the summer monsoon season, showing evidence of seasonal upwelling influenced by southwest/south winds. The results indicate three broad upwelling centers in the north, central, and south, with the northern center having the longest upwelling season lasting from May to September, and larger extents between June and August during the peak of the summer monsoon.
Article
Meteorology & Atmospheric Sciences
Shanshan Yu, Li Li, Biao Cao, Hailong Zhang, Lin Zhu, Xiaozhou Xin, Qinhuo Liu
Summary: This study developed clear-sky and all-sky algorithms for estimating surface downward longwave radiation (SDLR), incorporating high-resolution satellite data. The proposed algorithms showed good performance in estimating SDLR under clear-sky conditions and provided more accurate and detailed results compared to single algorithms and ERA5 data.
ATMOSPHERIC RESEARCH
(2022)
Article
Environmental Sciences
Peiyang Cheng, Arastoo Pour-Biazar, Andrew Tyler White, Richard T. McNider
Summary: Clouds play a crucial role in the Earth's climate system, affecting physical and chemical processes in the atmosphere. Cloud assimilation was used to improve cloud placement within the WRF model and enhance air quality predictions. The study showed that cloud assimilation corrected surface solar radiation, adjusted biogenic emissions, and improved the prediction of surface ozone concentration, especially in the southeast U.S. region.
ATMOSPHERIC ENVIRONMENT
(2022)
Article
Environmental Sciences
Yating Ouyang, Yuhong Zhang, Jianwei Chi, Qiwei Sun, Yan Du
Summary: Satellite measurements have greatly improved sea surface salinity (SSS) observations, but deviations still exist compared to in-situ measurements. These deviations are related to environmental factors such as sea surface temperature (SST), precipitation, and wind speed. Deviations are largest in middle and high latitudes, where the SST is colder. Heavy rainfall and strong westerly winds also contribute to larger deviations. In tropical convergence zones, large deviations are mainly caused by heavy rainfall and result in significant freshening. The Level 2 SSS measurements show stronger biases related to rainfall compared to Level 3. Surface freshening is more apparent in low wind speed scenarios.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Meteorology & Atmospheric Sciences
Yoonjin Lee, Christian D. Kummerow, Imme Ebert-Uphoff
Summary: Accurately detecting convective regions is crucial for initializing short-term precipitation forecast models. This study demonstrates that utilizing high spatial and temporal resolution data from GOES-16, artificial intelligence neural network models can effectively identify convective clouds with low false alarm rates and high probability of detection.
ATMOSPHERIC MEASUREMENT TECHNIQUES
(2021)
Article
Geochemistry & Geophysics
Lirong Ding, Ji Zhou, Zhao-Liang Li, Xinming Zhu, Jin Ma, Ziwei Wang, Wei Wang, Wenbin Tang
Summary: This study proposes a method for estimating hourly all-weather land surface temperature in the Tibetan Plateau. By fusing reanalysis data from the China Land Surface Data Assimilation System and thermal infrared data from the Chinese Fengyun-4A geostationary satellite, the proposed method can estimate the temperature without relying on data after the target moment. Validation results demonstrate the good accuracy of the method, which can improve temperature estimation.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Cheng-Chien Liu
Summary: This article discusses the development of a satellite image-matching system (SIMS) that can detect and track ocean surface features from GOCI data, thereby gaining a better understanding of ocean surface currents.
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
(2021)
Article
Geochemistry & Geophysics
Xiaolei Yu, Shuangling Chen, Fei Chai
Summary: The study developed a stacking random forest (SRF) model for estimating sea surface nitrate in the central and southern sections of the California Current System. The model showed high accuracy and robustness, suggesting it could serve as a reliable approach for other regions once in situ SSN data are available for model calibration.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Yeji Shin, Juhyun Lee, Jungho Im, Seongmun Sim
Summary: In this study, a geostationary-satellite-based approach for estimating the center of tropical cyclones (TCs) is proposed. The approach utilizes a score matrix (SCM) and an enhanced logarithmic spiral band (LSB) to determine an accurate TC center. The experimental results show that the proposed method outperforms existing approaches, particularly in detecting strong TCs.
Article
Geochemistry & Geophysics
Chong Wang, Gang Zheng, Xiaofeng Li, Qing Xu, Bin Liu, Jun Zhang
Summary: In this study, a set of deep convolutional neural networks (CNNs) were designed to estimate the intensity of tropical cyclones (TCs) over the Northwest Pacific Ocean from satellite data. The study showed that the selection of different infrared (IR) channels had a significant impact on the performance of the TC intensity estimate. The CNN models demonstrated good accuracy and stability in estimating TC intensity.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Jorge Vazquez-Cuervo, Sandra L. Castro, Michael Steele, Chelle Gentemann, Jose Gomez-Valdes, Wenqing Tang
Summary: There is a high demand for complete satellite SST maps of the Arctic regions to monitor environmental changes. Although there are many L4 SST products to choose from, constant changes in satellite-based products make periodic validations necessary. This study compares eight L4 products with saildrone data and evaluates their accuracy and spatial variability. The NOAA/NCEI DOISST and the RSS MWOI SSTs consistently show better relative accuracy, while the UK Met Office OSTIA product outperforms others in reproducing fine-scale features. The high-resolution coverage of current satellite infrared technology is too sparse for high-resolution L4 SST products in high latitudinal regions.
Article
Geochemistry & Geophysics
Hua Li, Ruibo Li, Hao Tu, Biao Cao, Fangjian Liu, Zunjian Bian, Tian Hu, Yongming Du, Lin Sun, Qinhuo Liu
Summary: This article proposes an operational split-window algorithm for generating long-term global land surface temperature products using Chinese Fengyun-3 series satellite data. The algorithm involves steps such as recalibrating brightness temperatures, estimating daily dynamic emissivity maps, and simulating split-window algorithm coefficients. The results show that the proposed algorithm has reasonable accuracy for producing land surface temperature products.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Meteorology & Atmospheric Sciences
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
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
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.
Article
Environmental Sciences
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
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.
Article
Environmental Sciences
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
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.
Article
Environmental Sciences
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
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
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
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
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)