H compset experiments Robert Osinski, Wieslaw Maslowski, Jaromir Jakacki, Jackie Clemant- Kinney, Andrew Roberts RASM workshop, NPS, May 2012.

Slides:



Advertisements
Similar presentations
Coupled Arctic Regional Atmosphere-Ocean-Sea Ice Model Minwei Qian and Colin Jones.
Advertisements

Basics of numerical oceanic and coupled modelling Antonio Navarra Istituto Nazionale di Geofisica e Vulcanologia Italy Simon Mason Scripps Institution.
EGU 2007, CR140 Dan Lunt Introduction. GCM and ice sheet simulations. Conclusions. Other mechanisms for inception. Future plans. The closure of the Panama.
Service Assessment Criteria re-structuring Market needs Re-structuring approach Consequences and Affected documents Sponsored by Performed by.
Computation of High-Resolution Global Ocean Model using Earth Simulator By Norikazu Nakashiki (CRIEPI) Yoshikatsu Yoshida (CRIEPI) Takaki Tsubono (CRIEPI)
A thermodynamic model for estimating sea and lake ice thickness with optical satellite data Student presentation for GGS656 Sanmei Li April 17, 2012.
Coupled versus uncoupled radiation and microphysicsMicrophysics droplet concentration 5. Conclusions The sea ice state simulated in RASM is sensitive to.
High-Resolution Land Use Data in WPS/WRF for Urban Regions
Climate change in centuries in observational and model data Evgeny Volodin, Institute of Numerical Mathematics RAS, Moscow, Russia.
Sea Ice Thermodynamics and ITD considerations Marika Holland NCAR.
Daniela Flocco, Daniel Feltham, David Schr  eder Centre for Polar Observation and Modelling University College London.
CORE-II HYCOM Science application and test cases
John J. Cassano, Matthew Higgins, Alice DuVivier University of Colorado Wieslaw Maslowski, William Gutowski, Dennis Lettenmaier, Andrew Roberts.
Progress toward a HIM-based IPCC-class Coupled Climate Model Robert Hallberg NOAA Geophysical Fluid Dynamics Laboratory With contributions from A. Gnanadesikan,
Bridging the Gap between idealized and realistic numerical river plume simulations Robert Hetland Texas A&M University.
A comparison of North Atlantic storms in HiGEM, HadGEM and ERA-40 Jennifer Catto – University of Reading Supervisors: Len Shaffrey Warwick Norton Acknowledgement:
Regional Arctic Climate System Model (RACM) – Project Overview Participants: Wieslaw Maslowski(PI)- Naval Postgraduate School John Cassano (co-PI)- University.
Sea-ice & the cryosphere
The first 2 terms on the RHS are nonlinear terms in the bias. The group labeled THF are transient heat advection bias. Q^ is the bias in diabatic heating.
The Role of Surface Freshwater Flux Boundary Conditions in Arctic Ocean/Sea-Ice Models EGU General Assembly, Nice, April 2004 Matthias Prange and Rüdiger.
Challenges in Modeling Global Sea Ice in a Changing Environment Marika M Holland National Center for Atmospheric Research Marika M Holland National Center.
Toward Advanced Understanding and Prediction of Arctic Climate Change Wieslaw Maslowski Naval Postgraduate School 34th Annual Climate Diagnostics and Prediction.
© Crown copyright Met Office UK report for GOVST Matt Martin GOVST-V, Beijing, October 2014.
The Louvain-la-Neuve sea ice model : current status and ongoing developments T. Fichefet, Y. Aksenov, S. Bouillon, A. de Montety, L. Girard, H. Goosse,
The Future of Arctic Sea Ice Authors: Wieslaw Maslowski, Jaclyn Clement Kinney, Matthew Higgins, and Andrew Roberts Brian Rosa – Atmospheric Sciences.
Numerical International Polar Year Andrey Proshutinsky and AOMIP group, Woods Hole Oceanographic Institution NOAA Arctic Science Priorities Workshop, February.
Climate 2010 Gary Strand High Performance Network Planning Workshop.
Sea Ice Deformation Studies and Model Development
SMHI in the Arctic Lars Axell Oceanographic Research Unit Swedish Meteorological and Hydrological Institute.
Opening and closing of the Storfjorden polynya. Coastal Polynya Skogseth (2003), PhD thesis Storfjorden is estimated to supply 5-10% of the newly formed.
6-month Plan: May-Oct 2013 RASM 5 th Workshop Seattle 04/13 red == high priority tasks.
WP5: Integration & Validation IFREMER, NERSC, NIERSC, ODL, NAVTOR, NERC.
Comparison of Different Approaches NCAR Earth System Laboratory National Center for Atmospheric Research NCAR is Sponsored by NSF and this work is partially.
Lessons learned from building and managing the Community Climate System Model David Bailey PCWG liaison (NCAR) Marika Holland PCWG co-chair (NCAR) Elizabeth.
Global, Basin and Shelf Ocean Applications of OPA An Inter-Agency Canadian Initiative EC-DFO-DND + Universities + Mercator-Ocean  CONCEPTS -- Canadian.
Regional Arctic Climate System Model (RACM) – Project Overview Participants: Wieslaw Maslowski (PI)- Naval Postgraduate School John Cassano (co-PI)- University.
ROMS in Alaska Waters Kate Hedstrom, ARSC/UAF Enrique Curchitser, IMCS/Rutgers August, 2007.
The dynamic-thermodynamic sea ice module in the Bergen Climate Model Helge Drange and Mats Bentsen Nansen Environmental and Remote Sensing Center Bjerknes.
Relationship between interannual variations in the Length of Day (LOD) and ENSO C. Endler, P. Névir, G.C. Leckebusch, U. Ulbrich and E. Lehmann Contact:
“Very high resolution global ocean and Arctic ocean-ice models being developed for climate study” by Albert Semtner Extremely high resolution is required.
Mixed Layer Ocean Model: Model Physics and Climate
Autonomous Polar Atmospheric Observations John J. Cassano University of Colorado.
Arctic Minimum 2007 A Climate Model Perspective What makes these two special? Do models ever have 1 year decline as great as observed from September 2006.
Advances in Lake-Effect Process Prediction within NOAA’s Climate Forecast System for North America: A Project Progress Report Jiming Jin and Shaobo Zhang.
Current state of ECHAM5/NEMO coupled model Wonsun Park, Noel Keenlyside, Mojib Latif (IFM-GEOMAR) René Redler (NEC C&C Research Laboratories) DRAKKAR meeting.
Ocean Climate Simulations with Uncoupled HYCOM and Fully Coupled CCSM3/HYCOM Jianjun Yin and Eric Chassignet Center for Ocean-Atmospheric Prediction Studies.
Of what use is a statistician in climate modeling? Peter Guttorp University of Washington Norwegian Computing Center
Assessment of the ECCO2 optimized solution in the Arctic An T. Nguyen, R. Kwok, D. Menemenlis JPL/Caltech ECCO-2 Team Meeting, MIT Sep 23-24, 2008.
Presented by LCF Climate Science Computational End Station James B. White III (Trey) Scientific Computing National Center for Computational Sciences Oak.
Publications An intro RASM paper (BAMS/EGU/J. Clim) – Model description (components, coupler, challenges resolved/outstanding, community effort) – Best/typical.
Validation of ORCA05 regional configuration of the Arctic North Atlantic Christophe HERBAUT and Marie-Noëlle HOUSSAIS Charles DELTEL LOCEAN, Université.
Atmospheric Circulation Response to Future Arctic Sea Ice Loss Clara Deser, Michael Alexander and Robert Tomas.
THEME#4: Are predicted changes in the arctic system detectable? OAII Focus on: Detecting Change(s) in the Arctic System - Ocean (heat, salt/freshwater,
CT2 : Assessing sources of uncertainty in ocean analysis and forecasts We consider the structural sources of uncertainty generic to all practical forecasting.
Tropical Atlantic SST in coupled models; sensitivity to vertical mixing Wilco Hazeleger Rein Haarsma KNMI Oceanographic Research The Netherlands.
15 Annual AOMIP Meeting. WHOI, 1- 4 November 2011 Numerical modeling of the Atlantic Water distribution in the upper Arctic Ocean: Sensitivity studies.
HIRLAM coupled to the ocean wave model WAM. Verification and improvements in forecast skill. Morten Ødegaard Køltzow, Øyvind Sætra and Ana Carrasco. The.
Coupled HYCOM in CESM and ESPC Alexandra Bozec, Eric P. Chassignet.
Toward improved understanding of mass and property fluxes through Bering Strait Jaclyn Clement Kinney 1, Wieslaw Maslowski 1, Mike Steele 2, Jinlun Zhang.
A BOUT MY THESIS 2010/03/02 Pei-Yu Chueh. M OTIVATION An Inconvenient Truth: The temperature was determined by the concentrations of carbon dioxide. (Al.
Indian Institute of Tropical Meteorology (IITM) Suryachandra A. Rao Colloborators: Hemant, Subodh, Samir, Ashish & Kiran Dynamical Seasonal Prediction.
Modeling Seasonal to Decadal Climate Variability using the Regional Arctic System Model W. Maslowski 1 and the RASM Team (25+ researchers from 10 institutions)
A Fully Coupled GCM Study of a "Geoengineered World"
Preliminary Results from the Global Ocean Simulations with the Baringer-Price-Yang Marginal Sea Boundary Condition Model Wanli Wu, William Large and Gokhan.
A sensitivity study of the sea ice simulation in the global coupled climate model, HadGEM3 Jamie Rae, Helene Hewitt, Ann Keen, Jeff Ridley, John Edwards,
A Comparison of Profiling Float and XBT Representations of Upper Layer Temperature Structure of the Northwestern Subtropical North Atlantic Robert L.
The Role of Inter-ocean Exchanges on Long-term Variability of the Northward Heat Transport in the South Atlantic Shenfu Dong CIMAS/UM and NOAA/AOML S.
A Model View of Arctic Sea Ice During Summer 2007 and Beyond
POPCICE - numerical experiments.
Fig. 2. Annual sea ice extent (107 km2) cycle for all 30 ensemble members. Each panel shows the five orbital simulations with the same pCO2 and minimum.
Presentation transcript:

H compset experiments Robert Osinski, Wieslaw Maslowski, Jaromir Jakacki, Jackie Clemant- Kinney, Andrew Roberts RASM workshop, NPS, May 2012

Channel problem

Volume transport through the channel

Scalability of H compset

Timing profile

Experiments H_NC2_AL0_ST0_CP0_D0_T0 Inter-annually varying forcing (IAF), as developed by Large and Yeager (2008) at NCAR: CORE2 Ice albedo Ice mechanical redistribution (sea ice strength) Coupling – especially how the momentum flux is transfer from atmosphere to the sea ice Ocean dynamics Time steps in both ice and ocean models

30-year long runs Five 30-year tests are finished and another three are currently running. H_NC2_AL0_ST0_CP0_D0_T0 – Control run All default values; albedo type= constant H_NC2_AL1_ST0_CP0_D0_T0 Albedo type = default (ahmax = 0.5m) - albedo is constant above this thickness H_NC2_AL2_ST0_CP0_D0_T0 Albedo type = default (ahmax = 0.5m) - albedo is constant above this thickness ; shortwave='dEdd H_NC2_AL3_ST1_CP0_D0_T0 Albedo type = default (ahmax = 0.3m) - albedo is constant above this thickness ; Cf=5.6 H_NC2_AL4_ST1_CP0_D0_T0 Albedo type = default (ahmax = 0.1m) - albedo is constant above this thickness ; shortwave=default; Cf=5.6

AL0 and AL1 All default values; albedo type= constant; albedo type = default (ahmax = 0.5m)

AL1 and AL2 albedo type = default (ahmax = 0.5m); Albedo type = default (ahmax = 0.5m) ; shortwave='dEdd

AL1 and AL2 albedo type = default (ahmax = 0.5m); Albedo type = default (ahmax = 0.5m) ; shortwave='dEdd

AL3 Albedo type = default (ahmax = 0.3m) - albedo is constant above this thickness ; Cf=5.6

AL0, AL1 and AL4 albedo type= constant; albedo type = default (ahmax = 0.5m); Albedo type = default (ahmax = 0.1m) ; shortwave='default, Cf=5.6

Al1 and AL4 albedo type = default (ahmax = 0.5m); Albedo type = default (ahmax = 0.1m) ; shortwave='default, Cf=5.6

Some conclusions Default values of the model settings give not enough sea ice in the results ice extent minima was reproduced correctly with H_NC2_AL1_ST0_CP0_D0_T0 experiment. We still have not get the proper sea ice thickness distribution. The default ahmax=0.5 m is probably too high; some more tests are needed e.g. with R_ice : tuning parameter for sea ice albedo from Delta-Eddington shortwave.

Plan for the next six months: Include the volume transport from Atlantic to Pacific side in fully coupled case. Include and test 2km resolution version of the RASM with at least H comset. Performed more tuning tests to get acceptable results. Compare tuning results with measurement at least with RGPS measurements.

AL3 Albedo type = default (ahmax = 0.3m) - albedo is constant above this thickness ; shortwave='dEdd; Cf=5.6