Proceedings from the Princeton Ocean Model (POM) Users Meeting
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remote sensing Article Impact of Enhanced Wave-Induced Mixing on the Ocean Upper Mixed Layer during Typhoon Nepartak in a Regional Model of the Northwest Pacific Ocean Chengcheng Yu 1 , Yongzeng Yang 2,3,4, Xunqiang Yin 2,3,4,*, Meng Sun 2,3,4 and Yongfang Shi 2,3,4 1 Ocean College, Zhejiang University, Zhoushan 316000, China; [email protected] 2 First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China; yangyz@fio.org.cn (Y.Y.); sunm@fio.org.cn (M.S.); shiyf@fio.org.cn (Y.S.) 3 Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology, Qingdao 266071, China 4 Key Laboratory of Marine Science and Numerical Modeling (MASNUM), Ministry of Natural Resources, Qingdao 266061, China * Correspondence: yinxq@fio.org.cn Received: 30 July 2020; Accepted: 27 August 2020; Published: 30 August 2020 Abstract: To investigate the effect of wave-induced mixing on the upper ocean structure, especially under typhoon conditions, an ocean-wave coupled model is used in this study. Two physical processes, wave-induced turbulence mixing and wave transport flux residue, are introduced. We select tropical cyclone (TC) Nepartak in the Northwest Pacific ocean as a TC example. The results show that during the TC period, the wave-induced turbulence mixing effectively increases the cooling area and cooling amplitude of the sea surface temperature (SST). The wave transport flux residue plays a positive role in reproducing the distribution of the SST cooling area. From the intercomparisons among experiments, it is also found that the wave-induced turbulence mixing has an important effect on the formation of mixed layer depth (MLD). -
Ocean Circulation Models and Modeling
2512-5 Fundamentals of Ocean Climate Modelling at Global and Regional Scales (Hyderabad - India) 5 - 14 August 2013 Ocean Circulation Models and Modeling GRIFFIES Stephen Princeton University U.S. Department of Commerce N.O.A.A., Geophysical Fluid Dynamics Laboratory, 201 Forrestal Road, Forrestal Campus P.O. Box 308, 08542-6649 Princeton NJ U.S.A. 5.1: Ocean Circulation Models and Modeling Stephen.Griffi[email protected] NOAA/Geophysical Fluid Dynamics Laboratory Princeton, USA [email protected] Laboratoire de Physique des Oceans,´ LPO Brest, France Draft from May 24, 2013 1 5.1.1. Scope of this chapter 2 We focus in this chapter on numerical models used to understand and predict large- 3 scale ocean circulation, such as the circulation comprising basin and global scales. It 4 is organized according to two themes, which we consider the “pillars” of numerical 5 oceanography. The first addresses physical and numerical topics forming a foundation 6 for ocean models. We focus here on the science of ocean models, in which we ask 7 questions about fundamental processes and develop the mathematical equations for 8 ocean thermo-hydrodynamics. We also touch upon various methods used to represent 9 the continuum ocean fluid with a discrete computer model, raising such topics as the 10 finite volume formulation of the ocean equations; the choice for vertical coordinate; 11 the complementary issues related to horizontal gridding; and the pervasive questions 12 of subgrid scale parameterizations. The second theme of this chapter concerns the 13 applications of ocean models, in particular how to design an experiment and how to 14 analyze results. -
Evaluation of the Harmful Algal Bloom Mapping System (Habmaps) and Bulletin
Evaluation of the Harmful Algal Bloom Mapping System (HABMapS) and Bulletin Earth Science Applications Directorate Coastal Management Team John C. Stennis Space Center, Mississippi National Aeronautics and Space Administration John C. Stennis Space Center SSC, Mississippi 39529–6000 June 2004 Acknowledgments This work was directed by the NASA Earth Science Applications Directorate at the John C. Stennis Space Center, Mississippi. Participation in this work by Lockheed Martin Space Operations – Stennis Programs was supported under contract number NAS 13-650. Earth Science Applications Directorate Coastal Management Team John C. Stennis Space Center, Mississippi Leland Estep, Lockheed Martin Space Operations – Stennis Programs Gregory Terrie, Lockheed Martin Space Operations – Stennis Programs Eurico D'Sa, Lockheed Martin Space Operations – Stennis Programs Mary Pagnutti, Lockheed Martin Space Operations – Stennis Programs Callie Hall, NASA Earth Science Applications Directorate Vicki Zanoni, NASA Earth Science Applications Directorate The use of trademarks or names of manufacturers is for accurate reporting only and does not constitute an official endorsement, either expressed or implied, of such products or manufacturers by the National Aeronautics and Space Administration. Earth Science Applications Directorate Coastal Management Team Table of Contents Executive Summary...................................................................................................................................... v 1.0 Introduction............................................................................................................................................ -
(CCRUN) Phase II
Supporting Regional Implementation of Integrated Climate Resilience Consortium for Climate Risk in the Urban Northeast (CCRUN) Phase II Research Highlights, September 1, 2015 – May 31, 2016 Boston New York City Philadelphia CCRUN’s Mission CCRUN conducts stakeholder-driven research that reduces climate- related vulnerability and advances opportunities for adaptation in the urban Northeast September 2015 – May 2016 | 1 The CCRUN Team Lead Investigators, Sectors, and Cross-Cutting Themes: Radley Horton (CU), Patrick Kinney (CU), Franco Montalto (Drexel), Richard Palmer (UMass), Philip Orton (Stevens), William Solecki (CUNY) Program Manager: Daniel Bader (CU) Investigators: Sandra Baptista (CU), Alan Blumberg (Stevens), Robert Chen (CU), Nickitas Georgas (Stevens), Vivien Gornitz (CU), Patrick Gurian (Drexel), Yochanan Kushnir (CU), Kytt MacManus (CU), Malgosia Madajewicz (CU) Research & Support Staff: Jim Carcone (CU), Annie Gerard (CU), Merlie Hansen (CU), Valentina Mara (CU), Reza Marsooli (Stevens), Dara Mendeloff (CU), Danielle Peters (CU), John Scialdone (CU), Justin Schulte (Stevens), Raquel Sousa (Drexel), David Strom (CU), Sri Vinay (CU), Ziwen Yu (Drexel) Graduate Students and Post-docs: Roham Bakhtyar (Stevens), Grace Cambareri (UMass), Ethan Coffel (CU), Leslie DeCristofaro (UMass), Erin Friedman (CUNY), Stephanie Miller (Drexel), Jennifer Nguyen (CU), Ashlinn Quinn (CU), Lauren Smalls-Mantey (Drexel), Kate Weinberger (CU), Sarah Whateley (UMass) Research Affiliates: Susana Adamo (CU), Mark Arend (CCNY), James Booth (CCNY), Arthur -
Committee I.1: Environment 3
18th International Ship and Offshore Structures Congress (ISSC 2012) - W. Fricke, R. Bronsart (Eds.) c 2012 Schiffbautechnische Gesellschaft, Hamburg, ISBN 978-3-87700-131-f5,8g i Proceedings to be purchased at http://www.stg-online.org/publikationen.html i i i 18th INTERNATIONAL SHIP AND OFFSHORE STRUCTURES CONGRESS 09-13 SEPTEMBER 2012 I S S C ROSTOCK, GERMANY 2 0 1 2 VOLUME 1 COMMITTEE I.1 ENVIRONMENT COMMITTEE MANDATE Concern for descriptions of the ocean environment, especially with respect to wave, current and wind, in deep and shallow waters, and ice, as a basis for the determination of environmental loads for structural design. Attention shall be given to statistical description of these and other related phenomena relevant to the safe design and operation of ships and offshore structures. The committee is encouraged to cooperate with the corresponding ITTC committee. COMMITTEE MEMBERS Chairman: Elzbieta M. Bitner-Gregersen Subrata K. Bhattacharya Ioannis K. Chatjigeorgiou Ian Eames Kathrin Ellermann Kevin Ewans Greg Hermanski Michael C. Johnson Ning Ma Christophe Maisondieu Alexander Nilva Igor Rychlik Takuji Waseda KEYWORDS Environment, ocean, wind, wave, current, sea level, ice, deep water, shallow water, data source, modelling, climate change, data access, design condition, operational condition, uncertainty. 1 i i i i 18th International Ship and Offshore Structures Congress (ISSC 2012) - W. Fricke, R. Bronsart (Eds.) c 2012 Schiffbautechnische Gesellschaft, Hamburg, ISBN 978-3-87700-131-f5,8g i Proceedings to be purchased at http://www.stg-online.org/publikationen.html i i i i i i i 18th International Ship and Offshore Structures Congress (ISSC 2012) - W. -
Review of Circulation Studies and Modeling in Casco Bay Asa 2011-32
REVIEW OF CIRCULATION STUDIES AND MODELING IN CASCO BAY ASA 2011-32 PREPARED FOR: Casco Bay Estuarine Partnership (CBEP) University of Southern Maine, Muskie School PO Box 9300 34 Bedford St 228B Wishcamper Center Portland, ME 04104-9300 PREPARED BY: Malcolm L. Spaulding Applied Science Associates 55 Village Square Drive South Kingstown, RI 02880 DATE SUBMITTED July 11, 2011 1 EXECUTIVE SUMMARY Applied Science Associates (ASA) was contracted by the Casco Bay Estuary Partnership (CBEP) to prepare a report reviewing the state of knowledge of circulation in Casco Bay, discussing relevant hydrodynamic modeling approaches and supporting observation programs. A summary of the final report of this study (the present document) was presented at a two day, Casco Bay Circulation Modeling Workshop held on May 18-19, 2011 at the Eastland Park Hotel, Portland, Maine. At the conclusion of the workshop a brief consensus summary was prepared and provided in this report. The review identified four efforts focused on modeling the circulation of Casco Bay and the adjacent shelf waters. These included the following: Pearce et al (1996) application of the NOAA Model for Estuarine and Coastal Circulation Assessment (MECCA) model (Hess, 1998) (funded by CBEP); True and Manning’s (undated) application of the unstructured grid Finite Volume Coastal Ocean Model (FVCOM) model (Chen et al, 2003); McCay et al (2008) application of ASA’s Boundary Fitted Hydrodynamic Model (BFHYRDO), and Xue and Du(2010) application of the Princeton Ocean Model (POM) (Mellor, 2004). All models were applied in a three dimensional mode and featured higher resolution of the inner bay than of the adjacent shelf. -
TR-2933 Street Scale Modeling of Storm Surge Inundation Along The
TR-2933 Street Scale Modeling of Storm Surge Inundation along the New Jersey Hudson River Waterfront Alan Blumberg, Thomas Herrington, Larry Yin, and Nickitas Georgas Davidson Laboratory Technical Report TR-2933 Stevens Institute of Technology Hoboken, NJ October 2014 1 TR-2933 Executive Summary A new, high-resolution, hydrodynamic model that encompasses the urban coastal waters and coastal flood plain of New Jersey along the Hudson River waterfront opposite New York City has been developed and validated. 3.1m model grid resolution combined with high-resolution LiDAR elevation datasets permit a street by street focus to inundation modeling. The waterfront inundation model (NJWIM) is a sECOM model application, nested into a larger New York Bight sECOM model (NYHOPS), itself nested to an even larger Northwest Atlantic sECOM model (SNAP). Robust wetting and drying of land in the model physics provides for the dynamic prediction of flood elevations and velocities across land features during inundation events. NJWIM was forced by water levels from the NYHOPS hindcast of Hurricane Sandy. The hindcast utilized Sandy over ocean wind field and atmospheric pressure data, offshore wave and tidal boundary forcing, atmospheric heat fluxes, and interior streamflow data. Validation against 56 water marks and 16 edgemarks provided via the USGS and through an extensive crowd sourcing effort consisting of photographs, videos and personal stories shows that the model is capable of computing overland water elevations quite accurately. The correlation coefficient (R2) between the water mark observations and the model results is 0.92. The standard deviation of the residual error is 0.07 m. The simulated water levels at 78% of the data measurement locations have less than 20% error. -
A Wetting and Drying Scheme for POM
Ocean Modelling 9 (2005) 133–150 www.elsevier.com/locate/ocemod A wetting and drying scheme for POM Lie-Yauw Oey * Princeton University, AOS, Sayre Hall, Forrestal Campus, Princeton, NJ 08544, USA Received 7 May 2004; received in revised form 10 May 2004; accepted 3 June 2004 Available online 2 July 2004 Abstract In shallow-water models, wetting and drying (WAD) are determined by the total water depth D ¼ 0 for ‘dry’ and >0 for ‘wet’. Checks are applied to decide the fate of each cell during model integration. It is shown that with bottom friction values commonly used in coastal models, the shallow-water system may be cast into a Burger’s type equation for D. For flows dominated by D (i.e. jrDjjrHj, where Hðx; yÞ defines topography) a non-linear diffusion equation results, with an effective diffusivity that varies like D2, so that ‘dry’ cells are regions where ‘diffusion’ is very small. In this case, the system admits D ¼ 0 as part of its continuous solution and no checks are necessary. For general topography, and/or in the case of strong momentum advection, ‘wave-breaking’ solution (i.e. hydraulic jumps and/or bores) can develop. A WAD scheme is proposed and applied to the Princeton Ocean Model (POM). The scheme defines ‘dry’ cells as regions with a thin film of fluid O (cm). The primitive equations are solved in the thin film as well as in other regular wet cells. The scheme requires only flux-blocking conditions across cells’ interfaces when wet cells become dry, while ‘dry’ cells are temporarily dormant and are dynamically activated through mass and momentum conservation. -
Tsunami Inundation Simulation at the Yaene Port, Hachijo Island Due to Hypothetical South Sea of Japan Tsunami 일본남해의 가상지진에 의한 야에네항의 지진해일 범람시뮬레이션
한국해안․ 해양공학회 학술발표논문집 (2008) 2008년 9월 25일-9월 26일 제17권, pp. 88-91 Tsunami Inundation Simulation at the Yaene Port, Hachijo Island due to hypothetical South Sea of Japan Tsunami 일본남해의 가상지진에 의한 야에네항의 지진해일 범람시뮬레이션 Kyeong Ok Kim1, Tomoaki Komaguchi2, Takao Yamashita3 and Byung Ho Choi4 김경옥1, 駒口友章2, 山下隆男3, 최병호4 1. INTRODUCTION Earthquake. The return period is about 80 ~ 150 year, the theory of 200 year is exist also. The The 2004 Indian Ocean earthquake was an expected earthqake is the maximum magnitude of undersea (subduction) earthquake that occurred on 8.7, and it will be one of the strongest earthqake. December 26, 2004, and damaged near the This research simulated the hypothetical tsunami epicenter of the west coast of Sumatra, Indonesia expected in the South Sea of Japan, and its focused and the opposite side of Indian Ocean. The moment inundation to the Yaene Port, Hachijo Island magniude is estimated Mw=9.3 and it is almost (Fig.3) using 2-D mode of Princeton Ocean Model same as the 1960s in Chile and Alaska. Such (Mellor, 2003). earthquake was not expected on the seismology. The tectonic setting from the west-north of Japan to Ryukyu trench is very similar with the tectonic setting of Sumatra to Andaman Islands. relatively slow subduction is proceeded and a major slip fault is developed on islands in this region. And the half area has a back-arc basin with expanding axis. These affinity is not the evidence to cause similar massive earthquake, and the gigantic earthquake could not occur by the characteristic of these area in the traditional point of view. -
Indian Ocean SST Biases in a Flexible Regional Ocean Atmosphere Land
ATMOSPHERIC AND OCEANIC SCIENCE LETTERS, 2012, VOL. 5, NO. 4, 273−279 Indian Ocean SST Biases in a Flexible Regional Ocean Atmosphere Land System (FROALS) Model HAN Zhen-Yu1, 2, ZHOU Tian-Jun1, and ZOU Li-Wei1 1State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of At- mospheric Physics, Chinese Academy of Sciences, Beijing 100029, China 2Graduate University of the Chinese Academy of Sciences, Beijing 100049, China Received 23 March 2012; revised 19 April 2012; accepted 20 April 2012; published 16 July 2012 Abstract The authors examine the Indian Ocean sea interaction. Recent studies have shown that coupled re- surface temperature (SST) biases simulated by a Flexible gional climate models (CRCMs) generally improve the Regional Ocean Atmosphere Land System (FROALS) simulation (Seo et al., 2008; Ratnam et al., 2009). A model. The regional coupled model exhibits pronounced Flexible Regional Ocean Atmosphere Land System cold SST biases in a large portion of the Indian Ocean (FROALS) model was established at the State Key Labo- warm pool. Negative biases in the net surface heat fluxes ratory of Numerical Modeling for Atmospheric Sciences are evident in the model, leading to the cold biases of the and Geophysical Fluid Dynamics, Institute of Atmos- SST. Further analysis indicates that the negative biases in pheric Physics (LASG, IAP) (Zou and Zhou, 2011, 2012). the net surface heat fluxes are mainly contributed by the An evaluation of the model performance over the western biases of sensible heat and latent heat flux. Near-surface North Pacific found that the SST shows cold biases, meteorological variables that could contribute to the SST which partly stem from the overestimation of convection biases are also examined. -
Disruptive Climate, Disruptive Technologies
EBC and Sustainable Solutions Lab at UMass Boston Climate Adaptation Forum Disruptive Climate, Disruptive Technologies Friday, June 7, 2019 University of Massachusetts Club | Boston Save the Date! September 20, 2019 Climate Adaptation Forum: Public Health EBC & Sustainable Solutions Lab at UMass Boston – Quarterly Climate Adaptation Forum EBC Contact: Jackson Bailey, [email protected] | SSL Contact: Rebecca Herst, [email protected] www.climateadaptationforum.org AGENDA 8:00 a.m. Welcome • David Cash, Ph.D., Forum Organizer Dean, John W. McCormack Graduate School of Policy and Global Studies University of Massachusetts Boston 8:05 a.m. Forum Introduction & Overview • Kelly Knee, Forum Co-Chair Executive Director – Ocean Science, RPS Group 8:10 a.m. Lightning Round of Disruptive Technologies Biobot • Mariana Matus, Co-Founder & CEO, Biobot Emerald Tutu • Gabriel Cira, Architect, Very Flat • Nicholas Lutsko, Postdoctoral Associate, MIT Green Stream Technologies • Karen Lindquist, Chief Operating Officer, Green Stream Technologies ISeeChange • Julia Kumari Drapkin, CEO and Founder, ISeeChange Risk Map • Mayank Ojha, Research Associate, Urban Risk Lab, MIT Upstream Tech • Marshall Moutenot, Managing Director, Upstream Tech WAVE of Change • Valentina Sumini, Postdoctoral Associate, MIT MediaLab • Alpha Yacob, Ph.D. Candidate, MIT 9:00 a.m. Keynote Presentation: Building a Resilient Tomorrow: Will Tech Get Us There? • Alice Hill, Research Fellow, Hoover Institution, Stanford University 9:30 a.m. Networking Break 10:00 a.m. Rhode Island’s Coastal Hazard Application Viewer • Teresa Crean, Coastal Research Associate Community Planning and Coastal Resilience University of Rhode Island Coastal Resources Center 10:05 a.m. Scenario Base Permitting and the Use of the Environmental Risk Index • Grover Fugate, Executive Director Rhode Island Coastal Resources Management Council 10:20 a.m. -
HWRF Ocean: the Princeton Ocean Model Isaac Ginis Graduate School
Ready for Stormy Weather? Isaac Ginis Graduate School of Oceanography University of Rhode Island HWRF Ocean: The Princeton Ocean Model Isaac Ginis Graduate School of Oceanography University of Rhode Island HWRF Tutorial NCWCP, College Park, MD 23-25 January 2018 1 1 Why Couple a 3-D Ocean Model to a Hurricane Model? To create accurate SST during hurricane model integration Evaporation (moisture flux) from sea surface provides heat energy to drive a hurricane Available energy decreases if storm-core SST decreases Uncoupled hurricane models with static SST neglect SST cooling during integration à high intensity bias One-dimensional (vertical-only) ocean models neglect upwelling and horizontal advection, both of which can impact SST during integration 2 Early history of Princeton Ocean Model Three-dimensional, primitive equation, numerical ocean model (commonly known as POM) Originally developed by Alan Blumberg and George Mellor in the late 1970’s Initially used for coastal ocean circulation applications Open to the community during the 1990s and 2000s https://en.wikipedia.org/wiki/Princeton_ocean_model 3 Developing POM for Tropical Cyclones Available POM code version transferred to University of Rhode Island (URI) in 1994 POM code changes made at URI specifically to address ocean response to hurricane wind forcing This POM version coupled to GFDL hurricane model at URI Coupled GFDL/POM model operational at NWS in 2001 Additional POM upgrades made at URI during 2000’s (e.g. initialization) and implemented in operational GFDL/POM