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global-coupled-ocean-level1-product-userguide.pdf

Product user manual For Global Ocean level-1 data products from the Met Office Global Coupled Atmosphere-Land-Ocean-Ice system Contributors: J Roberts-Jones, M. Price, S. Moreton, R. King Date: December 2024 Ocean Products User Guide, Met Office Global Coupled Atmosphere-Land-Ocean-Ice system Date

typhoon_haiyan_(yolanda)_in_the_philippines_summary_for_scientists.pdf

) was the most severe tropical cyclone to ever make landfall in the Philippines (right - NASA satellite image on November 7 th 2013). Maximum wind speeds peaked at 88m/s (197mph) and a storm surge produced wave heights reaching 5-6m above normal in some regions of Leyte. Yolanda caused widespread

Abbreviations

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z A AC Altocumulus AD Aerodrome AGL Above ground level AIMMS Aircraft Integrated Meteorological Measurement System AMD Amend or amended AMSL Above mean sea level AOD Aerosol Optical Depth APR April AS Altostratus ASR Altimeter setting region ATD

metoffice_sipn_2014.pdf

, L. M. Mercado, S. Sitch, E. Blyth, O. Boucher, P. M. Cox, C. S. B. Grimmond, and R. J. Harding. The Joint UK Land Environment Simulator (JULES), model description part 1: Energy and water fluxes. Geoscientific Model Development, 4(3):677–699, 2011. doi: 10.5194/gmd-4-677-2011. URL http://www.geosci

L5_Kilpua_V2.pptx

- interaction region structure, leading shock - peak velocity, density, Alfvénicity of fast streams NOAA: warning when GOES electron fluxes at GEO exceed 10^3 e/(cm 2 s sr) Kilpua et al., GRL, 2015 Storm driver CME sheath CME ejecta + slow wind CME ejecta + fast wind interacKon region + faster

Joint Marine Modelling Programme (JMMP)

Office North-West European Shelf forecasting system. Ocean Sci.,15(4), https://doi.org/10.5194/os-15-1133-2019.   Graham, J. A., E. O’Dea, J. Holt, J. Polton, H.T. Hewitt, R. Furner, K. Guihou, A. Brereton, A. Arnold, S. Wakelin, J.M. Castillo Sanchez, C.G. Mayorga Adame (2018) AMM15: A new

steele_etal_2025_otc_s2.pdf

Offshore Technology Conference OTC-35733-MS A Spatiotemporal Machine Learning Framework for the Prediction of Metocean Conditions in the Gulf of Mexico: Application to Loop Current and Loop Current Eddy Forecasting E.C.C. Steele 1 , M.C.R. Juniper 1 , A.C. Pillai 2 , I.G.C. Ashton 2 , J. Chen 3 , S

353-369-94.fm

, 1047-1056, doi:10.1039/C4EM00650J. Cherchi, A., A. Alessandri, S. Masina, and A. Navarra, 2011: Effects of increased CO 2 levels on monsoon. Clim. Dynam., 37, 83-101, doi: 10.1007/s00382-010-0801-7. Climate Profile of India Report, 2010: Met Monograph No. Environment Meteorology-01/2010. [Available

ukcp18-guidance---how-to-use-joint-probability-plots.pdf

, Brown S, Calvert D, Clark RT, Eagle KE, Edwards T, Fosser G, Fung F, Gohar L, Good P, Gregory J, Harris GR, Howard T, Kaye N, Kendon EJ, Krijnen J, Maisey P, McDonald RE, McInnes RN, McSweeney CF, Mitchell JFB, Murphy JM, Palmer M, Roberts C, Rostron JW, Sexton DMH, Thornton HE, Tinker J, Tucker S

D2_2_Presentation Submission_SanchezRivas-Daniel

radar reflectivity and differential reflectivity data for rain attenuation: A self-consistent method with constraints. IEEE transactions on geoscience and remote sensing, 39(9), 1906-1915. Diederich, M., Ryzhkov, A., Simmer, C., Zhang, P., & Trömel, S. (2015). Use of Specific Attenuation

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