{"count":88296,"next":"https://catalogue.ceda.ac.uk/api/v3/onlineresources/?format=json&limit=100&offset=88000","previous":"https://catalogue.ceda.ac.uk/api/v3/onlineresources/?format=json&limit=100&offset=87800","results":[{"ob_id":96144,"function":"externalCitation","linkage":"https://doi.org/10.1029/2025jd046173","name":"Wang, Y., Luo, H., Nie, Y., Xiu, Y., Liu, J., & Yang, Q. (2026). Limitations and Potential in Subseasonal Prediction of Antarctic Sea Ice Thickness for Thin Ice Regimes. Journal of Geophysical Research: Atmospheres, 131(6). Portico. https://doi.org/10.1029/2025jd046173","relatedTo":{"ob_id":25871,"uuid":"48fc3d1e8ada405c8486ada522dae9e8","short_code":"ob"}},{"ob_id":96145,"function":"externalCitation","linkage":"https://doi.org/10.1038/s41597-025-06390-x","name":"Ma, Z., Yang, Q., Xu, Y., Shi, W., Dong, X., Shi, Q., Luo, H., Liu, J., Uotila, P., & Nie, Y. (2025). Reconstruction of Antarctic sea ice thickness from sparse satellite laser altimetry data via deep learning. Scientific Data, 13(1). https://doi.org/10.1038/s41597-025-06390-x","relatedTo":{"ob_id":25872,"uuid":"ff79d140824f42dd92b204b4f1e9e7c2","short_code":"ob"}},{"ob_id":96146,"function":"externalCitation","linkage":"https://doi.org/10.1029/2025jd046173","name":"Wang, Y., Luo, H., Nie, Y., Xiu, Y., Liu, J., & Yang, Q. (2026). Limitations and Potential in Subseasonal Prediction of Antarctic Sea Ice Thickness for Thin Ice Regimes. Journal of Geophysical Research: Atmospheres, 131(6). Portico. https://doi.org/10.1029/2025jd046173","relatedTo":{"ob_id":25872,"uuid":"ff79d140824f42dd92b204b4f1e9e7c2","short_code":"ob"}},{"ob_id":96147,"function":"externalCitation","linkage":"https://doi.org/10.3390/f15101814","name":"Chi, Y., Wang, C., Chen, Z., & Xu, S. (2024). TCSNet: A New Individual Tree Crown Segmentation Network from Unmanned Aerial Vehicle Images. Forests, 15(10), 1814. https://doi.org/10.3390/f15101814","relatedTo":{"ob_id":38111,"uuid":"dd4d20c8626f4b9d99bc14358b1b50fe","short_code":"ob"}},{"ob_id":96148,"function":"externalCitation","linkage":"https://doi.org/10.1111/gcb.17493","name":"Jackson, T. D., Fischer, F. J., Vincent, G., Gorgens, E. B., Keller, M., Chave, J., Jucker, T., & Coomes, D. A. (2024). Tall Bornean forests experience higher canopy disturbance rates than those in the eastern Amazon or Guiana shield. Global Change Biology, 30(9). Portico. https://doi.org/10.1111/gcb.17493","relatedTo":{"ob_id":38111,"uuid":"dd4d20c8626f4b9d99bc14358b1b50fe","short_code":"ob"}},{"ob_id":96149,"function":"externalCitation","linkage":"https://doi.org/10.1038/s43247-025-02236-x","name":"Wang, X., Bai, Y., Jiang, S., Li, K., Li, Z., Liu, H., Wang, L., Wang, Y., Dong, L., Liang, C., & Zhang, J. (2025). Community-level foliar stable carbon isotope is dominantly influenced by leaf functional traits in dry Inner Mongolia steppes. Communications Earth & Environment, 6(1). https://doi.org/10.1038/s43247-025-02236-x","relatedTo":{"ob_id":30210,"uuid":"0683e320d8634a37aa1d9ef62dd41a0d","short_code":"coll"}},{"ob_id":96150,"function":"externalCitation","linkage":"https://doi.org/10.1029/2021gl095232","name":"Stone, K. A., Solomon, S., Kinnison, D. E., & Mills, M. J. (2021). On Recent Large Antarctic Ozone Holes and Ozone Recovery Metrics. Geophysical Research Letters, 48(22). Portico. https://doi.org/10.1029/2021gl095232","relatedTo":{"ob_id":13703,"uuid":"a8a7e52b299a46c9b09d8e56b283d385","short_code":"ob"}},{"ob_id":96151,"function":"externalCitation","linkage":"https://doi.org/10.1029/2024ef005013","name":"Tanguy, R., Bartsch, A., Nitze, I., Irrgang, A., Petzold, P., Widhalm, B., von Baeckmann, C., Boike, J., Martin, J., Efimova, A., Vieira, G., Whalen, D., Heim, B., Wieczorek, M., & Grosse, G. (2024). Pan‐Arctic Assessment of Coastal Settlements and Infrastructure Vulnerable to Coastal Erosion, Sea‐Level Rise, and Permafrost Thaw. Earth’s Future, 12(12). Portico. https://doi.org/10.1029/2024ef005013","relatedTo":{"ob_id":32619,"uuid":"b25d4a6174de4ac78000d034f500a268","short_code":"ob"}},{"ob_id":96152,"function":"externalCitation","linkage":"https://doi.org/10.5194/essd-17-1731-2025","name":"Zou, D., Zhao, L., Hu, G., Du, E., Liu, G., Wang, C., & Li, W. (2025). Permafrost temperature baseline at 15 m depth on the Qinghai–Tibetan Plateau (2010–2019). Earth System Science Data, 17(4), 1731–1742. https://doi.org/10.5194/essd-17-1731-2025","relatedTo":{"ob_id":32619,"uuid":"b25d4a6174de4ac78000d034f500a268","short_code":"ob"}},{"ob_id":96153,"function":"externalCitation","linkage":"https://doi.org/10.1038/s43247-024-01883-w","name":"Gartler, S., Scheer, J., Meyer, A., Abass, K., Bartsch, A., Doloisio, N., Falardeau, J., Hugelius, G., Irrgang, A., Haukur Ingimundarson, J., Jungsberg, L., Lantuit, H., Nymand Larsen, J., Lodi, R., Martin, V. S., Mercer, L., Nielsen, D., Overduin, P., Povoroznyuk, O., et al. (2025). A transdisciplinary, comparative analysis reveals key risks from Arctic permafrost thaw. Communications Earth & Environment, 6(1). https://doi.org/10.1038/s43247-024-01883-w","relatedTo":{"ob_id":32619,"uuid":"b25d4a6174de4ac78000d034f500a268","short_code":"ob"}},{"ob_id":96154,"function":"externalCitation","linkage":"https://doi.org/10.21203/rs.3.rs-459269/v1","name":"Vazquez, R., Parras-Berrocal, I., Cabos, W., Sein, D. V., Mañanes, R., & Izquierdo, A. (2021). Assessment of The Canary Current Upwelling System In A Regionally Coupled Climate Model. https://doi.org/10.21203/rs.3.rs-459269/v1","relatedTo":{"ob_id":27447,"uuid":"aced40d7cb964f23a0fd3e85772f2d48","short_code":"ob"}},{"ob_id":96155,"function":"externalCitation","linkage":"https://doi.org/10.1016/j.dsr2.2025.105483","name":"Flügel, R., Herbette, S., Treguier, A.-M., Waldman, R., & Roberts, M. (2025). Spatial variation of future trends in Atlantic upwelling cells from two CMIP6 models. Deep Sea Research Part II: Topical Studies in Oceanography, 221, 105483. https://doi.org/10.1016/j.dsr2.2025.105483","relatedTo":{"ob_id":27447,"uuid":"aced40d7cb964f23a0fd3e85772f2d48","short_code":"ob"}},{"ob_id":96156,"function":"externalCitation","linkage":"https://doi.org/10.1038/s41598-020-64785-9","name":"Bulgin, C. E., Merchant, C. J., & Ferreira, D. (2020). Tendencies, variability and persistence of sea surface temperature anomalies. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-64785-9","relatedTo":{"ob_id":27447,"uuid":"aced40d7cb964f23a0fd3e85772f2d48","short_code":"ob"}},{"ob_id":96157,"function":"externalCitation","linkage":"https://doi.org/10.1029/2021jd035968","name":"Meroni, A. N., Desbiolles, F., & Pasquero, C. (2022). Introducing New Metrics for the Atmospheric Pressure Adjustment to Thermal Structures at the Ocean Surface. Journal of Geophysical Research: Atmospheres, 127(16). Portico. https://doi.org/10.1029/2021jd035968","relatedTo":{"ob_id":27447,"uuid":"aced40d7cb964f23a0fd3e85772f2d48","short_code":"ob"}},{"ob_id":96158,"function":"externalCitation","linkage":"https://doi.org/10.1002/gdj3.94","name":"Williams, S. D. P., & Berry, D. I. (2020). ACSIS Atlantic Ocean medium resolution SST dataset: Reconstructed 5‐day, ½‐degree, Atlantic Ocean SST (1950‐2014). Geoscience Data Journal, 7(2), 135–148. Portico. https://doi.org/10.1002/gdj3.94","relatedTo":{"ob_id":27447,"uuid":"aced40d7cb964f23a0fd3e85772f2d48","short_code":"ob"}},{"ob_id":96159,"function":"externalCitation","linkage":"https://doi.org/10.1038/s43247-025-02728-w","name":"Gall, S. S., Harwood, T., Obersteiner, M., & Hall, J. W. (2025). Strategic land reallocation enhances carbon sequestration and biodiversity protection without compromising agricultural productivity in Great Britain. Communications Earth & Environment, 6(1). https://doi.org/10.1038/s43247-025-02728-w","relatedTo":{"ob_id":37212,"uuid":"bbca3267dc7d4219af484976734c9527","short_code":"ob"}},{"ob_id":96160,"function":"externalCitation","linkage":"https://doi.org/10.17028/rd.lboro.28704884","name":"Hodgkins, R. (2025). Loughborough University East Midlands campus meteorological data, 2008-2021 [Data set]. Loughborough University. https://doi.org/10.17028/RD.LBORO.28704884","relatedTo":{"ob_id":37212,"uuid":"bbca3267dc7d4219af484976734c9527","short_code":"ob"}},{"ob_id":96161,"function":"externalCitation","linkage":"https://doi.org/10.1101/2025.11.10.687559","name":"Seaton, F. (2025). jsdmstan: An R package for fitting joint species distribution models in Stan. https://doi.org/10.1101/2025.11.10.687559","relatedTo":{"ob_id":37212,"uuid":"bbca3267dc7d4219af484976734c9527","short_code":"ob"}},{"ob_id":96162,"function":"externalCitation","linkage":"https://doi.org/10.21203/rs.3.rs-6091509/v1","name":"Gall, S., Harwood, T., Obersteiner, M., & Hall, J. (2025). Mapping the option space for carbon sequestration, food and biodiversity in Great Britain. https://doi.org/10.21203/rs.3.rs-6091509/v1","relatedTo":{"ob_id":37212,"uuid":"bbca3267dc7d4219af484976734c9527","short_code":"ob"}},{"ob_id":96163,"function":"externalCitation","linkage":"https://doi.org/10.1111/ele.70131","name":"Cunningham, C. A., Beale, C. M., Bowler, D. E., Pocock, M. J. O., Hutchinson, R., White, P. C. L., Hunt, M., Maskell, L., & Hill, J. K. (2025). Connectivity Benefits Most Woodland Invertebrate Species but Only in Landscapes With Low Woodland Cover. Ecology Letters, 28(5). Portico. https://doi.org/10.1111/ele.70131","relatedTo":{"ob_id":37212,"uuid":"bbca3267dc7d4219af484976734c9527","short_code":"ob"}},{"ob_id":96164,"function":"externalCitation","linkage":"https://doi.org/10.1098/rspb.2025.0554","name":"Seaton, F., Wood, C., Hornigold, K., Kirby, K., Nichols, C., Jam, D., Dear, E., Kimberley, A., & Smart, S. (2025). The increasing role of tree disease and decreasing influence of anthropogenic management over 50 years of woodland dynamics. Proceedings of the Royal Society B: Biological Sciences, 292(2048). https://doi.org/10.1098/rspb.2025.0554","relatedTo":{"ob_id":37212,"uuid":"bbca3267dc7d4219af484976734c9527","short_code":"ob"}},{"ob_id":96165,"function":"externalCitation","linkage":"https://doi.org/10.5194/acp-25-3841-2025","name":"Choudhury, G., Block, K., Haghighatnasab, M., Quaas, J., Goren, T., & Tesche, M. (2025). Pristine oceans are a significant source of uncertainty in quantifying global cloud condensation nuclei. Atmospheric Chemistry and Physics, 25(6), 3841–3856. https://doi.org/10.5194/acp-25-3841-2025","relatedTo":{"ob_id":37566,"uuid":"864a46cc65054008857ee5bb772a2a2b","short_code":"ob"}},{"ob_id":96166,"function":"externalCitation","linkage":"https://doi.org/10.1029/2024jd041918","name":"He, X., Lu, C., Liu, Y., Zhu, Y., Peng, Y., Zhu, L., Xu, X., Luo, S., Wang, H., Li, T., Li, J., Wang, H., Gao, S., & Lin, Y. (2025). Implementation and Evaluation of Physics‐Driven Dynamic Entrainment‐Mixing Parameterization in a Climate Model and Its Impact on Low‐Cloud Simulation. Journal of Geophysical Research: Atmospheres, 130(6). Portico. https://doi.org/10.1029/2024jd041918","relatedTo":{"ob_id":37566,"uuid":"864a46cc65054008857ee5bb772a2a2b","short_code":"ob"}},{"ob_id":96167,"function":"externalCitation","linkage":"https://doi.org/10.1029/2021ef002035","name":"Zhang, Y., Ciais, P., Boucher, O., Maignan, F., Bastos, A., Goll, D., Lurton, T., Viovy, N., Bellouin, N., & Li, L. (2021). Disentangling the Impacts of Anthropogenic Aerosols on Terrestrial Carbon Cycle During 1850–2014. Earth’s Future, 9(7). Portico. https://doi.org/10.1029/2021ef002035","relatedTo":{"ob_id":26978,"uuid":"13f3635174794bb98cf8ac4b0ee8f4ed","short_code":"ob"}},{"ob_id":96168,"function":"externalCitation","linkage":"https://doi.org/10.1080/07055900.2025.2540430","name":"Deepak, R. S. N., Seiler, C., & Monahan, A. H. (2025). Global Sensitivity Analysis of the Future Land Carbon Sink. Atmosphere-Ocean, 63(5), 299–317. https://doi.org/10.1080/07055900.2025.2540430","relatedTo":{"ob_id":26978,"uuid":"13f3635174794bb98cf8ac4b0ee8f4ed","short_code":"ob"}},{"ob_id":96169,"function":"externalCitation","linkage":"https://doi.org/10.3389/frsen.2025.1724950","name":"Wan, L., Ciais, P., de Truchis, A., Sean, E., Fischer, F. J., Purnell, D., Belouze, G., Fayad, I., Schwartz, M., Xu, Y., Su, Y., Réjou-Méchain, M., Barbier, N., Tresson, P., Bastin, J.-F., Bogaert, J., Vander Linden, A., Plumacker, A., Angoboy Ilondea, B., et al. (2025). Satellite-based mapping of annual canopy height and aboveground biomass in African dense forests. Frontiers in Remote Sensing, 6. https://doi.org/10.3389/frsen.2025.1724950","relatedTo":{"ob_id":43090,"uuid":"bf535053562141c6bb7ad831f5998d77","short_code":"ob"}},{"ob_id":96170,"function":"externalCitation","linkage":"https://doi.org/10.1038/s41467-025-59999-2","name":"Li, X., Ciais, P., Fensholt, R., Chave, J., Sitch, S., Canadell, J. G., Brandt, M., Fan, L., Xiao, X., Tao, S., Wang, H., Albergel, C., Yang, H., Frappart, F., Wang, M., Bastos, A., Maisongrande, P., Qin, Y., Xing, Z., et al. (2025). Large live biomass carbon losses from droughts in the northern temperate ecosystems during 2016-2022. Nature Communications, 16(1). https://doi.org/10.1038/s41467-025-59999-2","relatedTo":{"ob_id":43090,"uuid":"bf535053562141c6bb7ad831f5998d77","short_code":"ob"}},{"ob_id":96171,"function":"externalCitation","linkage":"50|dedup_wf_002::47a152068713fb3d27afb9024aead1e1","name":"Murillo Gallego, Macarena (2025). Valoración del proceso de cuantificación de carbono del sistema BASOKO en ecosistemas forestales del País Vasco. Recolector de Ciencia Abierta, RECOLECTA.","relatedTo":{"ob_id":43090,"uuid":"bf535053562141c6bb7ad831f5998d77","short_code":"ob"}},{"ob_id":96172,"function":"externalCitation","linkage":"https://doi.org/10.1016/j.oneear.2025.101392","name":"Ganzenmüller, R., Obermeier, W. A., Bultan, S., Spawn-Lee, S. A., Zabel, F., & Pongratz, J. (2025). Humans have depleted global terrestrial carbon stocks by a quarter. One Earth, 8(8), 101392. https://doi.org/10.1016/j.oneear.2025.101392","relatedTo":{"ob_id":43090,"uuid":"bf535053562141c6bb7ad831f5998d77","short_code":"ob"}},{"ob_id":96173,"function":"externalCitation","linkage":"https://doi.org/10.3897/oneeco.10.e135722","name":"Sarmiento, R., Abella, P., Handayan, S. M., Madelo, J., Mercado, J., & Palaso, R. (2025). Potential impacts of industrial tree plantation encroachment on tree species diversity and carbon storage in the riparian zones of Andanan Watershed Forest Reserve, Philippines. One Ecosystem, 10. https://doi.org/10.3897/oneeco.10.e135722","relatedTo":{"ob_id":43090,"uuid":"bf535053562141c6bb7ad831f5998d77","short_code":"ob"}},{"ob_id":96174,"function":"externalCitation","linkage":"https://doi.org/10.5194/tc-20-3299-2026","name":"Browne, P., de Boisseson, E., Keeley, S., Pelletier, C., & Zuo, H. (2026). Sea ice data assimilation in ORAS6. The Cryosphere, 20(6), 3299–3311. https://doi.org/10.5194/tc-20-3299-2026","relatedTo":{"ob_id":43483,"uuid":"8978580336864f6d8282656d58771b32","short_code":"ob"}},{"ob_id":96175,"function":"externalCitation","linkage":"https://doi.org/10.5194/essd-18-2891-2026","name":"Tellefsen, E. H., Tonboe, R. T., & Kolbe, W. M. (2026). Mapping sea ice concentration using Nimbus-5 ESMR and local dynamical tie points. Earth System Science Data, 18(4), 2891–2906. https://doi.org/10.5194/essd-18-2891-2026","relatedTo":{"ob_id":43483,"uuid":"8978580336864f6d8282656d58771b32","short_code":"ob"}},{"ob_id":96176,"function":"externalCitation","linkage":"https://doi.org/10.1088/2515-7620/ae6d8d","name":"Prajapati, J., Athul, C. R., Rajiv, V. V., Baduru, B., Hennath PH, F., Daiya, V., Paul, B., & Paul, A. (2026). A machine learning framework for sea surface salinity prediction at short time scales. Environmental Research Communications, 8(5), 55044. https://doi.org/10.1088/2515-7620/ae6d8d","relatedTo":{"ob_id":43292,"uuid":"7294d93479654c139770f13fae4142d1","short_code":"coll"}},{"ob_id":96177,"function":"externalCitation","linkage":"50|od______2386::bed34e52a5caa03ade36bf2feab9ff57","name":"(2024). Linking observations and modelling to advance our understanding of spatio-temporal variations in structure and productivity of Arctic protist plankton. OceanRep.","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96178,"function":"externalCitation","linkage":"https://doi.org/10.1098/rsos.221421","name":"Wilkie Johnston, L., Bergami, E., Rowlands, E., & Manno, C. (2023). Organic or junk food? Microplastic contamination in Antarctic krill and salps. Royal Society Open Science, 10(3). https://doi.org/10.1098/rsos.221421","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96179,"function":"externalCitation","linkage":"https://doi.org/10.1016/j.scitotenv.2024.172431","name":"Krawczyk, D. W., Vonnahme, T., Burmeister, A. D., Maier, S. R., Blicher, M. E., Meire, L., & Nygaard, R. (2024). Arctic puzzle: Pioneering a northern shrimp (Pandalus borealis) habitat model in Disko Bay, West Greenland. Science of the Total Environment, 929, 172431. https://doi.org/10.1016/j.scitotenv.2024.172431","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96180,"function":"externalCitation","linkage":"50|od_______660::5afd67654e87f2f36d8600d3ffd9b8b9","name":"Lampe, Vanessa (2024). Linking observations and modelling to advance our understanding of spatio-temporal variations in structure and productivity of Arctic protist plankton. MACAU: Open Access Repository of Kiel University.","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96181,"function":"externalCitation","linkage":"https://doi.org/10.5194/os-18-1419-2022","name":"Lima, M. M., Gouveia, C. M., & Trigo, R. M. (2022). Upper-ocean response to the passage of tropical cyclones in the Azores region. Ocean Science, 18(5), 1419–1430. https://doi.org/10.5194/os-18-1419-2022","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96182,"function":"externalCitation","linkage":"https://doi.org/10.5194/essd-17-1959-2025","name":"Nicholson, S.-A., Ryan-Keogh, T. J., Thomalla, S. J., Chang, N., & Smith, M. E. (2025). Satellite-derived global-ocean phytoplankton phenology indices. Earth System Science Data, 17(5), 1959–1975. https://doi.org/10.5194/essd-17-1959-2025","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96183,"function":"externalCitation","linkage":"https://doi.org/10.1007/s12040-025-02645-8","name":"Jadhav, S. J., Shafeeque, M., Arun, V. S., Vishnu, N. N. S., & Smitha, B. R. (2025). Phenology of coastal upwelling in the Southeastern Arabian Sea: Insights from in-situ and satellite observations. Journal of Earth System Science, 134(3). https://doi.org/10.1007/s12040-025-02645-8","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96184,"function":"externalCitation","linkage":"https://doi.org/10.1029/2024jc021670","name":"Jardine, J. E., Holt, J., Wakelin, S. L., Katavouta, A., & Partridge, D. (2025). An Asymmetric Change in Circulation and Nitrate Transports in the Bay of Bengal. Journal of Geophysical Research: Oceans, 130(2). Portico. https://doi.org/10.1029/2024jc021670","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96185,"function":"externalCitation","linkage":"https://doi.org/10.3389/fmars.2024.1309050","name":"Kong, C. E., Sathyendranath, S., Jackson, T., Stramski, D., Brewin, R. J. W., Kulk, G., Jönsson, B. F., Loisel, H., Galí, M., & Le, C. (2024). Comparison of ocean-colour algorithms for particulate organic carbon in global ocean. Frontiers in Marine Science, 11. https://doi.org/10.3389/fmars.2024.1309050","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96186,"function":"externalCitation","linkage":"https://doi.org/10.22541/essoar.174585012.27386970/v2","name":"Chen, Y., Partridge, D., & Nerger, L. (2025). Effects of assimilating phytoplankton carbon in marine ecosystem modelling. https://doi.org/10.22541/essoar.174585012.27386970/v2","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96187,"function":"externalCitation","linkage":"https://doi.org/10.5194/acp-24-12595-2024","name":"Boyer, M., Aliaga, D., Quéléver, L. L. J., Bucci, S., Angot, H., Dada, L., Heutte, B., Beck, L., Duetsch, M., Stohl, A., Beck, I., Laurila, T., Sarnela, N., Thakur, R. C., Miljevic, B., Kulmala, M., Petäjä, T., Sipilä, M., Schmale, J., & Jokinen, T. (2024). The annual cycle and sources of relevant aerosol precursor vapors in the central Arctic during the MOSAiC expedition. Atmospheric Chemistry and Physics, 24(22), 12595–12621. https://doi.org/10.5194/acp-24-12595-2024","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96188,"function":"externalCitation","linkage":"https://doi.org/10.5194/gmd-16-6875-2023","name":"Yumruktepe, V. Ç., Mousing, E. A., Tjiputra, J., & Samuelsen, A. (2023). An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas. Geoscientific Model Development, 16(22), 6875–6897. https://doi.org/10.5194/gmd-16-6875-2023","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96189,"function":"externalCitation","linkage":"https://doi.org/10.1038/s43247-025-02302-4","name":"Park, H.-J., An, S.-I., Park, J.-H., Yang, Y.-M., & Kim, S.-K. (2025). Sub-seasonal impact of El Niño–Southern Oscillation on development of the Indian Ocean Dipole. Communications Earth & Environment, 6(1). https://doi.org/10.1038/s43247-025-02302-4","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96190,"function":"externalCitation","linkage":"https://doi.org/10.1016/j.rse.2024.114487","name":"Sun, X., Brewin, R. J. W., Sathyendranath, S., Dall’Olmo, G., Antoine, D., Barlow, R., Bracher, A., Kheireddine, M., Li, M., Raitsos, D. E., Shen, F., Tilstone, G. H., & Vellucci, V. (2025). Coupling ecological concepts with an ocean-colour model: Parameterisation and forward modelling. Remote Sensing of Environment, 316, 114487. https://doi.org/10.1016/j.rse.2024.114487","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96191,"function":"externalCitation","linkage":"https://doi.org/10.3390/su17062556","name":"Corridore, M., de Jesús Crespo, R., Valladares-Castellanos, M., & Douthat, T. (2025). From the Mountains to the Beach: Water Purification Ecosystem Services and Recreational Beach Use in Puerto Rico. Sustainability, 17(6), 2556. https://doi.org/10.3390/su17062556","relatedTo":{"ob_id":32135,"uuid":"1dbe7a109c0244aaad713e078fd3059a","short_code":"coll"}},{"ob_id":96192,"function":"externalCitation","linkage":"https://doi.org/10.1038/s41612-025-00945-w","name":"Kim, H.-J., Kim, J.-S., Ham, Y.-G., Park, J.-H., Milodowski, D., Aragão, L. E. O. C., & Williams, M. (2025). Anomalous temperature in North Tropical Atlantic linked to Brazilian Cerrado fires. Npj Climate and Atmospheric Science, 8(1). https://doi.org/10.1038/s41612-025-00945-w","relatedTo":{"ob_id":31986,"uuid":"62866635ab074e07b93f17fbf87a2c1a","short_code":"ob"}},{"ob_id":96193,"function":"externalCitation","linkage":"https://doi.org/10.1088/2752-5295/ae4920","name":"Patel, T. D., Nguvava, M., & Odoulami, R. C. (2026). Projected temperature and precipitation extremes over Tanzania under stratospheric SO₂ injection. Environmental Research: Climate, 5(2), 25016. https://doi.org/10.1088/2752-5295/ae4920","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96194,"function":"externalCitation","linkage":"https://doi.org/10.1038/s41598-025-25396-4","name":"Akhtar, T., Mushtaq, H., & Hashmi, M. Z.-u.-R. (2025). Integrated use of meteorological and hydrological indices for drought early warning in the mountainous catchments of the Himalaya-Karakorum-Hindukush region. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-25396-4","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96195,"function":"externalCitation","linkage":"https://doi.org/10.1134/s1064229324601653","name":"Smirnova, M. A., Bardashov, D. R., Fil, P. P., Lozbenev, N. I., & Dobrokhotov, A. V. (2024). Seasonal and Multi-Year Dynamics of Soil Moisture in Gleyic Chernozems (the Oka–Don Lowland). Eurasian Soil Science, 57(10), 1601–1615. https://doi.org/10.1134/s1064229324601653","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96196,"function":"externalCitation","linkage":"https://doi.org/10.31223/x5sw3n","name":"Simpson, C., Hosking, J., Mitchell, D., Betts, R., & Shuckburgh, E. (2022). Regional disparities and seasonal differences in climate risk to rice labour. https://doi.org/10.31223/x5sw3n","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96197,"function":"externalCitation","linkage":"https://doi.org/10.1029/2025jd044821","name":"Zhang, Y., Wu, R., Zheng, X.-T., Mei, J., & Sun, L. (2026). Anthropogenic Forcings Intensify Droughts More Severely in Drylands than in Humid Regions. Journal of Geophysical Research: Atmospheres, 131(3). Portico. https://doi.org/10.1029/2025jd044821","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96198,"function":"externalCitation","linkage":"https://doi.org/10.1175/jcli-d-20-0169.1","name":"Jiang, J., Zhou, T., Wang, H., Qian, Y., Noone, D., & Man, W. (2020). Tracking Moisture Sources of Precipitation over Central Asia: A Study Based on the Water-Source-Tagging Method. Journal of Climate, 33(23), 10339–10355. https://doi.org/10.1175/jcli-d-20-0169.1","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96199,"function":"externalCitation","linkage":"https://doi.org/10.1016/j.heliyon.2023.e22345","name":"Chisanga, C. B., Nkonde, E., Phiri, E., Mubanga, K. H., & Lwando, C. (2023). Trend analysis of rainfall from 1981-2022 over Zambia. Heliyon, 9(11), e22345. https://doi.org/10.1016/j.heliyon.2023.e22345","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96200,"function":"externalCitation","linkage":"https://doi.org/10.1029/2025jd043887","name":"Zhang, Y., Wu, R., Zheng, X., Wang, Y., Cheng, S., & Wang, S. (2025). Anthropogenic Impacts on Asian Drought Trends: Distinct Effects of Greenhouse Gases and Aerosols. Journal of Geophysical Research: Atmospheres, 130(12). Portico. https://doi.org/10.1029/2025jd043887","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96201,"function":"externalCitation","linkage":"https://doi.org/10.21203/rs.3.rs-623790/v1","name":"Fahim, T. C., & Sikder, B. B. (2021). Exploring farmers’ perception on climate-induced events and adaptation practices to protect crop production and livestock farming in Haor area of northeastern Bangladesh. https://doi.org/10.21203/rs.3.rs-623790/v1","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96202,"function":"externalCitation","linkage":"https://doi.org/10.1007/s11600-025-01747-7","name":"Proutsos, N. D., Tigkas, D., & Stefanidis, S. P. (2025). Impact of hydrometeorological factors and extreme events on black pine forests growth in the Mediterranean. Acta Geophysica, 74(1). https://doi.org/10.1007/s11600-025-01747-7","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96203,"function":"externalCitation","linkage":"https://doi.org/10.1002/essoar.10504738.1","name":"Naimark, J. G., Fiore, A., Jin, X., Wang, Y., Klovenski, E., & Braneon, C. (2020). Evaluating Drought Responses of Surface Ozone Precursor Proxies: Variations with Land Cover Type, Precipitation, and Temperature. https://doi.org/10.1002/essoar.10504738.1","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96204,"function":"externalCitation","linkage":"https://doi.org/10.21203/rs.3.rs-1193877/v1","name":"Liu, D., & Fu, D. (2022). The Water Yield Pattern for Annual and Monthly Scales Through a Unifying Catchment Water Balance Model. https://doi.org/10.21203/rs.3.rs-1193877/v1","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96205,"function":"externalCitation","linkage":"https://doi.org/10.1029/2024gl112084","name":"Zhu, T., Zhou, Y., & Ju, W. (2025). Seasonal El Niño‐Southern Oscillation and Indian Ocean Dipole Dependencies of Methane Emissions From Wetlands. Geophysical Research Letters, 52(4). Portico. https://doi.org/10.1029/2024gl112084","relatedTo":{"ob_id":27493,"uuid":"10d3e3640f004c578403419aac167d82","short_code":"ob"}},{"ob_id":96206,"function":"externalCitation","linkage":"https://doi.org/10.1038/s41467-025-61930-8","name":"Luckeneder, S., Maus, V., Siqueira-Gay, J., Krisztin, T., & Kuhn, M. (2025). Forest loss and uncertain economic gains from industrial and garimpo mining in Brazilian municipalities. Nature Communications, 16(1). https://doi.org/10.1038/s41467-025-61930-8","relatedTo":{"ob_id":6679,"uuid":"ac4ecbd554d0dd52a9b575d9666dc42d","short_code":"ob"}},{"ob_id":96207,"function":"externalCitation","linkage":"https://doi.org/10.1038/s41598-026-41957-7","name":"Hu, B., Cutler, M. E. J., & Morel, A. C. (2026). Spatiotemporal dynamics of heat stress and cold stress on UK rapeseed cropping over 1961–2020. Scientific Reports, 16(1). https://doi.org/10.1038/s41598-026-41957-7","relatedTo":{"ob_id":40129,"uuid":"46f8c1377f8849eeb8570b8ac9b26d86","short_code":"ob"}},{"ob_id":96208,"function":"externalCitation","linkage":"https://doi.org/10.1080/02626667.2026.2622458","name":"Faulkner, D., McKenna, C., & Winder, A. (2026). Detection and spatial modelling of trends in UK rainfall frequency. Hydrological Sciences Journal, 71(5), 974–988. https://doi.org/10.1080/02626667.2026.2622458","relatedTo":{"ob_id":40129,"uuid":"46f8c1377f8849eeb8570b8ac9b26d86","short_code":"ob"}},{"ob_id":96209,"function":"externalCitation","linkage":"https://doi.org/10.1175/jcli-d-15-0421.1","name":"Tietsche, S., Hawkins, E., & Day, J. J. (2015). Atmospheric and Oceanic Contributions to Irreducible Forecast Uncertainty of Arctic Surface Climate. Journal of Climate, 29(1), 331–346. https://doi.org/10.1175/jcli-d-15-0421.1","relatedTo":{"ob_id":11700,"uuid":"d330c7873c3f4880893bdedb547bea20","short_code":"coll"}},{"ob_id":96210,"function":"externalCitation","linkage":"https://doi.org/10.5194/acp-2016-172","name":"Bowdalo, D. R., Evans, M. J., & Sofen, E. D. (2016). Spectral analysis of atmospheric composition: application to surface ozone model-measurement comparisons. https://doi.org/10.5194/acp-2016-172","relatedTo":{"ob_id":12399,"uuid":"a3931d0dfcc243ab8d93603c8ee58811","short_code":"ob"}},{"ob_id":96211,"function":"externalCitation","linkage":"https://doi.org/10.5194/acp-16-8295-2016","name":"Bowdalo, D. R., Evans, M. J., & Sofen, E. D. (2016). Spectral analysis of atmospheric composition: application to surface ozone model–measurement comparisons. Atmospheric Chemistry and Physics, 16(13), 8295–8308. https://doi.org/10.5194/acp-16-8295-2016","relatedTo":{"ob_id":12399,"uuid":"a3931d0dfcc243ab8d93603c8ee58811","short_code":"ob"}},{"ob_id":96212,"function":"externalCitation","linkage":"https://doi.org/10.5194/acp-16-2323-2016","name":"Geddes, J. A., Heald, C. L., Silva, S. J., & Martin, R. V. (2016). Land cover change impacts on atmospheric chemistry: simulating projected large-scale tree mortality in the United States. Atmospheric Chemistry and Physics, 16(4), 2323–2340. https://doi.org/10.5194/acp-16-2323-2016","relatedTo":{"ob_id":12399,"uuid":"a3931d0dfcc243ab8d93603c8ee58811","short_code":"ob"}},{"ob_id":96213,"function":"externalCitation","linkage":"https://doi.org/10.5194/essd-8-41-2016","name":"Sofen, E. D., Bowdalo, D., Evans, M. J., Apadula, F., Bonasoni, P., Cupeiro, M., Ellul, R., Galbally, I. E., Girgzdiene, R., Luppo, S., Mimouni, M., Nahas, A. C., Saliba, M., & Tørseth, K. (2016). Gridded global surface ozone metrics for atmospheric chemistry model evaluation. Earth System Science Data, 8(1), 41–59. https://doi.org/10.5194/essd-8-41-2016","relatedTo":{"ob_id":12399,"uuid":"a3931d0dfcc243ab8d93603c8ee58811","short_code":"ob"}},{"ob_id":96214,"function":"externalCitation","linkage":"https://doi.org/10.5194/essd-8-41-2016","name":"Sofen, E. D., Bowdalo, D., Evans, M. J., Apadula, F., Bonasoni, P., Cupeiro, M., Ellul, R., Galbally, I. E., Girgzdiene, R., Luppo, S., Mimouni, M., Nahas, A. C., Saliba, M., & Tørseth, K. (2016). Gridded global surface ozone metrics for atmospheric chemistry model evaluation. Earth System Science Data, 8(1), 41–59. https://doi.org/10.5194/essd-8-41-2016","relatedTo":{"ob_id":13832,"uuid":"c0455ab814224a05ac74642d3d44b73e","short_code":"ob"}},{"ob_id":96215,"function":"externalCitation","linkage":"https://doi.org/10.3897/oneeco.9.e124989","name":"Nguyen, T. D. L., Tran, T., Dang, K. B., Do, T. T. T., Dong, H., Pham Thi Phuong, N., Hoang Thi, T., & Giang, T. L. (2024). A Bayesian Belief Network for assessing ecosystem services and socio-economic development in threatened estuarine regions. One Ecosystem, 9. https://doi.org/10.3897/oneeco.9.e124989","relatedTo":{"ob_id":34591,"uuid":"e1ff6e07cd624c59a7e7983ce60add44","short_code":"ob"}},{"ob_id":96216,"function":"externalCitation","linkage":"50|dedup_wf_002::f25e42ed7ef66e91fb0eab5aee1d6b49","name":"Hellwig, Niels (Dr.), Walz, Ariane (Prof. Dr.), Markovic, Danijela (2019). Climatic and socioeconomic effects on land cover changes across Europe. Publikationsserver der Universität Potsdam.","relatedTo":{"ob_id":25066,"uuid":"58a8802721c94c66ae45c3baa4d814d0","short_code":"ob"}},{"ob_id":96217,"function":"externalCitation","linkage":"https://doi.org/10.1175/jcli-d-18-0890.1","name":"Jiang, J., & Zhou, T. (2019). Global Monsoon Responses to Decadal Sea Surface Temperature Variations during the Twentieth Century: Evidence from AGCM Simulations. Journal of Climate, 32(22), 7675–7695. https://doi.org/10.1175/jcli-d-18-0890.1","relatedTo":{"ob_id":25066,"uuid":"58a8802721c94c66ae45c3baa4d814d0","short_code":"ob"}},{"ob_id":96218,"function":"externalCitation","linkage":"https://doi.org/10.1029/2024ef005013","name":"Tanguy, R., Bartsch, A., Nitze, I., Irrgang, A., Petzold, P., Widhalm, B., von Baeckmann, C., Boike, J., Martin, J., Efimova, A., Vieira, G., Whalen, D., Heim, B., Wieczorek, M., & Grosse, G. (2024). Pan‐Arctic Assessment of Coastal Settlements and Infrastructure Vulnerable to Coastal Erosion, Sea‐Level Rise, and Permafrost Thaw. Earth’s Future, 12(12). Portico. https://doi.org/10.1029/2024ef005013","relatedTo":{"ob_id":32612,"uuid":"67a3f8c8dc914ef99f7f08eb0d997e23","short_code":"ob"}},{"ob_id":96219,"function":"externalCitation","linkage":"https://doi.org/10.1007/s41748-024-00491-0","name":"Nadeem, I., Nakicenovic, N., Yaqub, A., Sakschewski, B., Loriani, S., Bala, G., Tharammal, T., & Zimm, C. (2024). Permafrost Thawing and Estimates of Vulnerable Carbon in the Northern High Latitude. Earth Systems and Environment, 9(2), 715–740. https://doi.org/10.1007/s41748-024-00491-0","relatedTo":{"ob_id":32612,"uuid":"67a3f8c8dc914ef99f7f08eb0d997e23","short_code":"ob"}},{"ob_id":96220,"function":"externalCitation","linkage":"https://doi.org/10.1029/2023gl108081","name":"Watts, J. D., Potter, S., Rogers, B. M., Virkkala, A.-M., Fiske, G., Arndt, K. A., Burrell, A., Butler, K., Gerlt, B., Grayson, J., Shestakova, T. A., Du, J., Kim, Y., Parmentier, F.-J. W., & Natali, S. M. (2025). Regional Hotspots of Change in Northern High Latitudes Informed by Observations From Space. Geophysical Research Letters, 52(2). Portico. https://doi.org/10.1029/2023gl108081","relatedTo":{"ob_id":32612,"uuid":"67a3f8c8dc914ef99f7f08eb0d997e23","short_code":"ob"}},{"ob_id":96221,"function":"externalCitation","linkage":"https://doi.org/10.1088/1748-9326/ad0f73","name":"Liu, Z., Kimball, J. S., Ballantyne, A., Watts, J. D., Natali, S. M., Rogers, B. M., Yi, Y., Klene, A. E., Moghaddam, M., Du, J., & Zona, D. (2023). Widespread deepening of the active layer in northern permafrost regions from 2003 to 2020. Environmental Research Letters, 19(1), 14020. https://doi.org/10.1088/1748-9326/ad0f73","relatedTo":{"ob_id":32612,"uuid":"67a3f8c8dc914ef99f7f08eb0d997e23","short_code":"ob"}},{"ob_id":96222,"function":"externalCitation","linkage":"https://doi.org/10.1088/1748-9326/ae358e","name":"Berry, B., Guimond, J. A., Stolle, J., & Kurylyk, B. L. (2026). Classifying pan-Arctic supra-permafrost aquifer function under present and projected conditions. Environmental Research Letters, 21(2), 24017. https://doi.org/10.1088/1748-9326/ae358e","relatedTo":{"ob_id":32612,"uuid":"67a3f8c8dc914ef99f7f08eb0d997e23","short_code":"ob"}},{"ob_id":96223,"function":"externalCitation","linkage":"https://doi.org/10.1016/j.ocecoaman.2021.105713","name":"Mutia, D., Carpenter, S., Jacobs, Z., Jebri, F., Kamau, J., Kelly, S. J., Kimeli, A., Langat, P. K., Makori, A., Nencioli, F., Painter, S. C., Popova, E., Raitsos, D., & Roberts, M. (2021). Productivity driven by Tana river discharge is spatially limited in Kenyan coastal waters. Ocean & Coastal Management, 211, 105713. https://doi.org/10.1016/j.ocecoaman.2021.105713","relatedTo":{"ob_id":25390,"uuid":"9c334fbe6d424a708cf3c4cf0c6a53f5","short_code":"coll"}},{"ob_id":96224,"function":"externalCitation","linkage":"https://doi.org/10.1080/01431161.2021.1899329","name":"Shafeeque, M., Balchand, A. N., Shah, P., George, G., B. R., S., Varghese, E., Joseph, A. K., Sathyendranath, S., & Platt, T. (2021). Spatio-temporal variability of chlorophyll-a in response to coastal upwelling and mesoscale eddies in the South Eastern Arabian Sea. International Journal of Remote Sensing, 42(13), 4836–4863. https://doi.org/10.1080/01431161.2021.1899329","relatedTo":{"ob_id":25390,"uuid":"9c334fbe6d424a708cf3c4cf0c6a53f5","short_code":"coll"}},{"ob_id":96225,"function":"externalCitation","linkage":"https://doi.org/10.1029/2025pa005175","name":"Wu, J., Han, Z., Fan, G., Sun, W., Zhao, J., Zhang, H., Nihashi, S., Yang, B., Jin, H., Chen, J., & Pan, J. (2026). Ballast Effect on the Export of Sea‐Ice Biomarker IPSO₂₅ in Prydz Bay, Antarctica. Paleoceanography and Paleoclimatology, 41(2). Portico. https://doi.org/10.1029/2025pa005175","relatedTo":{"ob_id":25390,"uuid":"9c334fbe6d424a708cf3c4cf0c6a53f5","short_code":"coll"}},{"ob_id":96226,"function":"externalCitation","linkage":"https://doi.org/10.5194/os-17-1141-2021","name":"Wang, B., Fennel, K., & Yu, L. (2021). Can assimilation of satellite observations improve subsurface biological properties in a numerical model? A case study for the Gulf of Mexico. Ocean Science, 17(4), 1141–1156. https://doi.org/10.5194/os-17-1141-2021","relatedTo":{"ob_id":25390,"uuid":"9c334fbe6d424a708cf3c4cf0c6a53f5","short_code":"coll"}},{"ob_id":96227,"function":"externalCitation","linkage":"https://doi.org/10.5194/bg-2020-152","name":"Ford, D. (2020). Assimilating synthetic Biogeochemical-Argo and ocean colour observations into a global ocean model to inform observing system design. https://doi.org/10.5194/bg-2020-152","relatedTo":{"ob_id":25390,"uuid":"9c334fbe6d424a708cf3c4cf0c6a53f5","short_code":"coll"}},{"ob_id":96228,"function":"externalCitation","linkage":"https://doi.org/10.22541/essoar.175372306.62137124/v1","name":"Kwatra, S., Lengaigne, M., Suresh, I., Dutheil, C., & Vialard, J. (2025). Stratification and Wind Changes Shape Future Indian Ocean Chlorophyll. https://doi.org/10.22541/essoar.175372306.62137124/v1","relatedTo":{"ob_id":25390,"uuid":"9c334fbe6d424a708cf3c4cf0c6a53f5","short_code":"coll"}},{"ob_id":96229,"function":"externalCitation","linkage":"https://doi.org/10.1016/j.ejrh.2024.101672","name":"Lu, T., Zhang, W., Abel, C., Horion, S., Brandt, M., Huang, K., & Fensholt, R. (2024). Changes in vegetation-water response in the Sahel-Sudan during recent decades. Journal of Hydrology: Regional Studies, 52, 101672. https://doi.org/10.1016/j.ejrh.2024.101672","relatedTo":{"ob_id":27622,"uuid":"bbdfd09a04304158b366777eba0d2aeb","short_code":"ob"}},{"ob_id":96230,"function":"externalCitation","linkage":"https://doi.org/10.3390/jmse8121039","name":"Timmermans, B., Shaw, A., & Gommenginger, C. (2020). Reliability of Extreme Significant Wave Height Estimation from Satellite Altimetry and In Situ Measurements in the Coastal Zone. Journal of Marine Science and Engineering, 8(12), 1039. https://doi.org/10.3390/jmse8121039","relatedTo":{"ob_id":30003,"uuid":"f91cd3ee7b6243d5b7d41b9beaf397e1","short_code":"ob"}},{"ob_id":96231,"function":"externalCitation","linkage":"https://doi.org/10.5194/gmd-16-2515-2023","name":"Valiente, N. G., Saulter, A., Gomez, B., Bunney, C., Li, J.-G., Palmer, T., & Pequignet, C. (2023). The Met Office operational wave forecasting system: the evolution of the regional and global models. Geoscientific Model Development, 16(9), 2515–2538. https://doi.org/10.5194/gmd-16-2515-2023","relatedTo":{"ob_id":30006,"uuid":"3ef6a5a66e9947d39b356251909dc12b","short_code":"ob"}},{"ob_id":96232,"function":"externalCitation","linkage":"https://doi.org/10.3390/jmse8121039","name":"Timmermans, B., Shaw, A., & Gommenginger, C. (2020). Reliability of Extreme Significant Wave Height Estimation from Satellite Altimetry and In Situ Measurements in the Coastal Zone. Journal of Marine Science and Engineering, 8(12), 1039. https://doi.org/10.3390/jmse8121039","relatedTo":{"ob_id":30013,"uuid":"47140d618dcc40309e1edbca7e773478","short_code":"ob"}},{"ob_id":96233,"function":"externalCitation","linkage":"https://doi.org/10.5194/tc-17-1431-2023","name":"Derksen, C., & Mudryk, L. (2023). Assessment of Arctic seasonal snow cover rates of change. The Cryosphere, 17(4), 1431–1443. https://doi.org/10.5194/tc-17-1431-2023","relatedTo":{"ob_id":29998,"uuid":"fa20aaa2060e40cabf5fedce7a9716d0","short_code":"ob"}},{"ob_id":96234,"function":"externalCitation","linkage":"https://doi.org/10.25972/opus-29194","name":"Üreyen, S. (2022). Multivariate Time Series for the Analysis of Land Surface Dynamics - Evaluating Trends and Drivers of Land Surface Variables for the Indo-Gangetic River Basins [Universität Würzburg]. https://doi.org/10.25972/OPUS-29194","relatedTo":{"ob_id":29998,"uuid":"fa20aaa2060e40cabf5fedce7a9716d0","short_code":"ob"}},{"ob_id":96235,"function":"externalCitation","linkage":"https://doi.org/10.1080/17538947.2025.2548008","name":"Peng, G., Liu, Y., Xiao, C., Du, W., & Xiao, C. (2025). A dynamic adaptive graph convolutional recurrent network model for efficient mid-short term prediction of global sea surface salinity. International Journal of Digital Earth, 18(1). https://doi.org/10.1080/17538947.2025.2548008","relatedTo":{"ob_id":32840,"uuid":"5920a2c77e3c45339477acd31ce62c3c","short_code":"coll"}},{"ob_id":96236,"function":"externalCitation","linkage":"https://doi.org/10.1029/2025jc022733","name":"Jarugula, S., Lee, T., Wang, O., & Fournier, S. (2025). Maritime Continent Water Cycle as a Key Forcing for Decadal Variation of Upper‐Ocean Salinity in the Southeast Indian Ocean. Journal of Geophysical Research: Oceans, 130(12). Portico. https://doi.org/10.1029/2025jc022733","relatedTo":{"ob_id":32840,"uuid":"5920a2c77e3c45339477acd31ce62c3c","short_code":"coll"}},{"ob_id":96237,"function":"externalCitation","linkage":"https://doi.org/10.1029/2024jc021039","name":"Lovecchio, E., Henson, S., Carvalho, F., Briggs, N., Hilder, H., Wolff, G. A., Giering, S. L. C., Cook, K., Baker, C. A., Fielding, S., Preece, C., & Stinchcombe, M. (2025). Mesopelagic Particle Layers in the Dynamic Hypoxic Northern Benguela Are Shaped by Zooplankton Activity. Journal of Geophysical Research: Oceans, 130(3). Portico. https://doi.org/10.1029/2024jc021039","relatedTo":{"ob_id":32840,"uuid":"5920a2c77e3c45339477acd31ce62c3c","short_code":"coll"}},{"ob_id":96238,"function":"externalCitation","linkage":"https://doi.org/10.1126/sciadv.adn9660","name":"Mellin, C., Brown, S., Cantin, N., Klein-Salas, E., Mouillot, D., Heron, S. F., & Fordham, D. A. (2024). Cumulative risk of future bleaching for the world’s coral reefs. Science Advances, 10(26). https://doi.org/10.1126/sciadv.adn9660","relatedTo":{"ob_id":27532,"uuid":"62c0f97b1eac4e0197a674870afe1ee6","short_code":"ob"}},{"ob_id":96239,"function":"externalCitation","linkage":"https://doi.org/10.1038/s41561-025-01762-9","name":"Bonino, G., McAdam, R., Athanasiadis, P., Cavicchia, L., Rodrigues, R. R., Scoccimarro, E., Tibaldi, S., & Masina, S. (2025). Mediterranean summer marine heatwaves triggered by weaker winds under subtropical ridges. Nature Geoscience, 18(9), 848–853. https://doi.org/10.1038/s41561-025-01762-9","relatedTo":{"ob_id":27532,"uuid":"62c0f97b1eac4e0197a674870afe1ee6","short_code":"ob"}},{"ob_id":96240,"function":"externalCitation","linkage":"https://doi.org/10.1175/jcli-d-19-0954.1","name":"Robertson, F. R., Roberts, J. B., Bosilovich, M. G., Bentamy, A., Clayson, C. A., Fennig, K., Schröder, M., Tomita, H., Compo, G. P., Gutenstein, M., Hersbach, H., Kobayashi, C., Ricciardulli, L., Sardeshmukh, P., & Slivinski, L. C. (2020). Uncertainties in Ocean Latent Heat Flux Variations over Recent Decades in Satellite-Based Estimates and Reduced Observation Reanalyses. Journal of Climate, 33(19), 8415–8437. https://doi.org/10.1175/jcli-d-19-0954.1","relatedTo":{"ob_id":27532,"uuid":"62c0f97b1eac4e0197a674870afe1ee6","short_code":"ob"}},{"ob_id":96241,"function":"externalCitation","linkage":"https://doi.org/10.1002/aqc.70124","name":"Cherbero, M., Teichert, N., De Oliveira, E., & Le Pichon, C. (2025). Coastal to Riverine Entry Timing During the Spawning Migration of the European Shads (Alosa spp.): Drivers and Phenological Trends for the French Atlantic Coast Populations. Aquatic Conservation: Marine and Freshwater Ecosystems, 35(4). Portico. https://doi.org/10.1002/aqc.70124","relatedTo":{"ob_id":27532,"uuid":"62c0f97b1eac4e0197a674870afe1ee6","short_code":"ob"}},{"ob_id":96242,"function":"externalCitation","linkage":"https://doi.org/10.5194/essd-2022-294","name":"Sims, R. P., Holding, T. M., Land, P. E., Piolle, J.-F., Green, H. L., & Shutler, J. D. (2022). OceanSODA-UNEXE: A multi-year gridded Amazon and Congo River outflow surface ocean carbonate system dataset. https://doi.org/10.5194/essd-2022-294","relatedTo":{"ob_id":27532,"uuid":"62c0f97b1eac4e0197a674870afe1ee6","short_code":"ob"}},{"ob_id":96243,"function":"externalCitation","linkage":"https://doi.org/10.3389/fmars.2023.1129295","name":"Wiberg, P. L. (2023). Temperature amplification and marine heatwave alteration in shallow coastal bays. Frontiers in Marine Science, 10. https://doi.org/10.3389/fmars.2023.1129295","relatedTo":{"ob_id":27532,"uuid":"62c0f97b1eac4e0197a674870afe1ee6","short_code":"ob"}}]}