Decadal predictability and near-term climate change experiments with HiGEM Len Shaffrey, NCAS – Climate University of Reading Thanks to: Doug Smith, Rowan.

Slides:



Advertisements
Similar presentations
Jennifer Catto Supervisors: Len Shaffrey – NCAS Climate and Kevin Hodges - ESSC The Representation of Extratropical Cyclones in HiGEM.
Advertisements

NCAS-Climate: Carries out research into climate change and variability, motivated by the need to understand how the climate system will evolve over the.
The effect of doubled CO 2 and model basic state biases on the monsoon- ENSO system: the mean response and interannual variability Andrew Turner, Pete.
© Crown copyright Met Office The Met Office high resolution seasonal prediction system Anca Brookshaw – Monthly to Decadal Variability and Prediction,
Seasonal to decadal prediction of the Arctic Oscillation D. Smith, A. Scaife, A. Arribas, E. Blockley, A. Brookshaw, R.T. Clark, N. Dunstone, R. Eade,
Mark Cane Lamont-Doherty Earth Observatory of Columbia University El Niño and the Southern Oscillation (ENSO): An Introduction.
ENSO-Monsoon relationships in current and future climates Andrew Turner, Pete Inness and Julia Slingo The University of Reading Department of Meteorology.
© Crown copyright Met Office Decadal Climate Prediction Doug Smith, Nick Dunstone, Rosie Eade, Leon Hermanson, Adam Scaife.
Simulation of the Global ENSO-Tropical Cyclone Teleconnection by a High-Resolution Coupled GCM Ray Bell, Kevin Hodges, Pier Luigi Vidale, Jane Strachan.
Indian Monsoon, Indian Ocean dipoles and ENSO Pascal Terray LOCEAN/IPSL, France Fabrice Chauvin CNRM/Météo-France, France Sébastien Dominiak LOCEAN/IPSL,
Jon Robson (Uni. Reading) Rowan Sutton (Uni. Reading) and Doug Smith (UK Met Office) Analysis of a decadal prediction system:
The Potential for Skill across the range of the Seamless-Weather Climate Prediction Problem Brian Hoskins Grantham Institute for Climate Change, Imperial.
UCSB Climate Research Meeting Dept. of Geography ICESS- UCSB October 16, 2009 Earth Space Research Group Climate Variations and Impacts: Monthly Discussion.
A comparison of North Atlantic storms in HiGEM, HadGEM and ERA-40 Jennifer Catto – University of Reading Supervisors: Len Shaffrey Warwick Norton Acknowledgement:
THORPEX-Pacific Workshop Kauai, Hawaii Polar Meteorology Group, Byrd Polar Research Center, The Ohio State University, Columbus, Ohio David H. Bromwich.
Jennifer Catto Supervisors: Len Shaffrey – NCAS Climate and Kevin Hodges - ESSC The Representation of Extratropical Cyclones in HiGEM.
Jennifer Catto Supervisors: Len Shaffrey and Kevin Hodges Extra-tropical cyclones in HiGEM.
UCSB Climate Research Meeting Dept. of Geography ICESS- UCSB October 16, 2009 Earth Space Research Group Climate Variations and Impacts: Monthly Discussion.
Modes of Pacific Climate Variability: ENSO and the PDO Michael Alexander Earth System Research Lab michael.alexander/publications/
Extreme Events and Climate Variability. Issues: Scientists are telling us that global warming means more extreme weather. Every year we seem to experience.
Seasonal outlook of the East Asian Summer in 2015 Motoaki Takekawa Tokyo Climate Center Japan Meteorological Agency May th FOCRAII 1.
© Crown copyright Met Office CLIVAR Climate of the 20 th Century Project Adam Scaife, Chris Folland, Jim Kinter, David Fereday January 2009.
High Resolution Climate Modelling in NERC (and the Met Office) Len Shaffrey, University of Reading Thanks to: Pier Luigi Vidale, Jane Strachan, Dave Stevens,
Issues in Ocean-Atmosphere-Land-Ice Coupling Ocean Integration in Earth System Prediction Capability Data Assimilation University of Maryland September.
Inter-annual to decadal climate prediction Mojib Latif, Leibniz Institute of Marine Sciences at Kiel University.
Monsoon Intraseasonal-Interannual Variability and Prediction Harry Hendon BMRC (also CLIVAR AAMP) Acknowledge contributions: Oscar Alves, Eunpa Lim, Guomin.
The role of the basic state in the ENSO-monsoon relationship and implications for predictability Andrew Turner, Pete Inness, Julia Slingo.
ENSO Variability in SODA: SULAGNA RAY BENJAMIN GIESE TEXAS A&M UNIVERSITY WCRP 2010, Paris, Nov
© Crown copyright Met Office Decadal predictions of the Atlantic ocean and hurricane numbers Doug Smith, Nick Dunstone, Rosie Eade, David Fereday, James.
C20C Workshop, ICTP Trieste 2004 The impact of stratospheric ozone depletion and CO 2 on tropical cyclone behaviour in the Australian region Syktus J.
Regional Air-Sea Interactions in Eastern Pacific 6th International RSM Workshop Palisades, New York July 11-15, th International RSM Workshop Palisades,
Research Needs for Decadal to Centennial Climate Prediction: From observations to modelling Julia Slingo, Met Office, Exeter, UK & V. Ramaswamy. GFDL,
A new approach to reproduce the 20 th century ENSO variability in an OAGCM Mathieu Joly ( Météo-France / CNRM ) PhD-Thesis Director: S. Janicot ( IPSL.
© Crown copyright Met Office The stratosphere and Seasonal to Decadal Prediction Adam Scaife, Sarah Ineson, Jeff Knight and Andrew Marshall January 2009.
3. Products of the EPS for three-month outlook 1) Outline of the EPS 2) Examples of products 3) Performance of the system.
Page 1© Crown copyright 2004 The Hadley Centre The forcing of sea ice characteristics by the NAO in HadGEM1 UK Sea Ice Workshop, 9 September 2005 Chris.
The evolution of climate modeling Kevin Hennessy on behalf of CSIRO & the Bureau of Meteorology Tuesday 30 th September 2003 Canberra Short course & Climate.
Oceanic forcing of Sahel rainfall on interannual to interdecadal time scales A. Giannini (IRI) R. Saravanan (NCAR) and P. Chang (Texas A&M) IRI for climate.
2010/ 11/ 16 Speaker/ Pei-Ning Kirsten Feng Advisor/ Yu-Heng Tseng
Beyond CMIP5 Decadal Predictions and the role of aerosols in the warming slowdown Doug Smith, Martin Andrews, Ben Booth, Nick Dunstone, Rosie Eade, Leon.
Modes of variability and teleconnections: Part II Hai Lin Meteorological Research Division, Environment Canada Advanced School and Workshop on S2S ICTP,
Coupled and Uncoupled Model Simulation of the Global ENSO-TC Teleconnection Ray Bell With thanks to Kevin Hodges, Pier Luigi Vidale, Jane Strachan and.
© Crown copyright Met Office Strategy for Seasonal Prediction Development: UKMO and WGSIP activities Adam Scaife Head Monthly to Decadal Prediction Met.
ECMWF Training course 26/4/2006 DRD meeting, 2 July 2004 Frederic Vitart 1 Predictability on the Monthly Timescale Frederic Vitart ECMWF, Reading, UK.
RT5, WP5.2 : Evaluation of processes and phenomena Objectives : Analyse the capability of the models to reproduce and predict the major modes of variations.
Page 1© Crown copyright 2004 The Uses of Marine Surface Data in Climate Research David Parker, Hadley Centre, Met Office MARCDAT-2, Met Office, Exeter,
MICHAEL A. ALEXANDER, ILEANA BLADE, MATTHEW NEWMAN, JOHN R. LANZANTE AND NGAR-CHEUNG LAU, JAMES D. SCOTT Mike Groenke (Atmospheric Sciences Major)
© Crown copyright Met Office Predictability and systematic error growth in Met Office MJO predictions Ann Shelly, Nick Savage & Sean Milton, UK Met Office.
VOCALS-UK Len Shaffrey and Thomas Toniazzo Walker Institute, University of Reading John Constable ‘Cloud Study’ 1822.
Jennifer Catto Supervisors: Len Shaffrey and Kevin Hodges Extra-tropical cyclones and Storm Tracks.
To clarify, coordinate and synthesize research devoted to achieve a better understanding of ENSO diversity, including: surface and sub-surface characteristics,
Matthew J. Hoffman CEAFM/Burgers Symposium May 8, 2009 Johns Hopkins University Courtesy NOAA/AVHRR Courtesy NASA Earth Observatory.
The HiGEM Weather Paper Len Shaffrey NCAS-Climate, Department of Meterology, University of Reading.
ESSL Holland, CCSM Workshop 0606 Predicting the Earth System Across Scales: Both Ways Summary:Rationale Approach and Current Focus Improved Simulation.
P.L. Vidale*, M. Roberts +, L. Shaffrey*, W. Norton and J. Slingo * A. Clayton, M.-E. Demory, J. Donners, I. Stevens, D. Stevens *NCAS-Climate, Walker.
Improved blocking at 25km resolution? Reinhard Schiemann 1,2, Marie-Estelle Demory 1, Mio Matsueda 3, Matthew Mizielinski 2, Malcolm Roberts 2, Len Shaffrey.
M. Roberts, P. L. Vidale, D. Stevens, Ian Stevens, Len Shaffrey, UJCC team with help from many others at Met Office and NCAS-Climate and CCSR/NIES/FRCGC.
Seasonal and decadal prediction. Ocean Assimilation and Reanalysis for Climate Research Head of Group : Keith Haines Maria Valdivieso da Costa (NCEO)
Seasonal Forecast of Antarctic Sea Ice
HiGEM A national UK programme in ‘Grand Challenge’ high resolution modelling of the global environment between NERC and the Hadley Centre.
Oliver Elison Timm ATM 306 Fall 2016
Climate and Global Dynamics Laboratory, NCAR
Andrew Turner, Pete Inness, Julia Slingo
Air-Sea Interactions The atmosphere and ocean form a coupled system, exchanging heat, momentum and water at the interface. Emmanuel, K. A. 1986: An air-sea.
Course Evaluation Now online You should have gotten an with link.
Course Evaluation Now online You should have gotten an with link.
Mark A. Bourassa and Qi Shi
Course Evaluation Now online You should have gotten an with link.
Prospects for Wintertime European Seasonal Prediction
Case Studies in Decadal Climate Predictability
Presentation transcript:

Decadal predictability and near-term climate change experiments with HiGEM Len Shaffrey, NCAS – Climate University of Reading Thanks to: Doug Smith, Rowan Sutton, Pier-Luigi Vidale, Ed Hawkins, Dave Stevens

HiGEM is a partnership between the UK academic community and the Met Office to develop a 'high' resolution atmosphere ocean coupled climate model. HiGEM is based on the Met Office coupled climate model, HadGEM1, but with increased horizontal resolution. HiGEM Snapshot of the HiGEM Model In the atmosphere the horizontal resolution is increased to 1.25 degrees longitude by 0.83 degrees latitude (~90km). The parametrisations remain largely the same as in HadGEM1, including the simple interactive aerosol scheme. In the ocean the horizontal resolution is 1/3 by 1/3 degree globally.

Centennial length control integrations of HiGEM have been completed on two computing platforms, the HPCx in the UK and the Earth Simulator in Japan. Some marked improvements Blocking in the Northern Hemisphere Position of the Gulf Stream Representation of the MJO Warm SST biases in the marine stratocumulus regions Some things don't improve Indian monsoon Some Tropical precipitation biases HiGEM

El Nino DJF Sea Surface Temperature composites from HadISST2, HadGEM1.2 and HiGEM1.2. Units K The warming of the Tropical Pacific during an El Nino event is well captured in HiGEM. Observations (HadISST2) HiGEM HadGEM1 ENSO in HiGEM and HadGEM1

Just completed porting HiGEM to a third computing platform (HECToR) On 128 processors the integration speed is 0.75 model years/day, but the model doesn't scale well past this. The plan is to be involved in the decadal predictability experiment, preferably using anomaly assimilation (some variation of DePreSys, Smith et al 2007) Computing resources and people are constraints to producing the forecasts but, since anomaly assimilation requires a series of long integrations to produce the initial conditions and HiGEM is slow, the biggest constraint might be time.....so we've already started working on the anomaly assimilation runs. Another possible constraint might be data volume and data handling. Already using the COSP simulator (offline) No aquaplanet version planned (at the moment) HiGEM

Normalised Nino3 SST Power Spectra for HadISST, HadGEM1.1 and HiGEM1.1 Both the spatial and temporal characteristics of ENSO, and its remote teleconnections, are better simulated in HiGEM relative to HadGEM Why does the ENSO improve in HiGEM? El Nino in HiGEM

Tropical Instability Waves in the Tropical Pacific Ocean are shear instabilities that grow in the equatorial current-counter current system –They propagate slowly westwards (~0.5ms -1 ) Tropical Instability Waves Instantaneous SST from HiGEM Instantaneous SSTs in the Tropical Pacific Ocean (Chelton et al. 2001)

Understanding the value of resolution HiGEM being used to inform seasonal forecasting development in the Met Office (PACE - Sarah Keeley) Idealised climate change experiments underway Future Directions Decadal forecasting? How to initialise the ocean? Model development - a high resolution version of HadGEM3? From Smith et al. (2008) The ORCA2 grid - no North Pole!

HiGEMERA-40 Will increasing the resolution of climate models allow us to better represent weather? Composite structures of the 50 most extreme wintertime Northern Hemisphere storms in ERA-40 and HiGEM. Colours – windspeed, Black lines – 1000hPa isobars, Red lines – 850hPa to 500hPa temperature thickness Courtesy of Jen Catto

El Nino DJF precipitation composites from CMAP, HadGEM1.2 and HiGEM1.2. Units mm/day. CMAP HiGEM1.2 HadGEM1.2 El Nino in HiGEM

El Nino DJF mslp composites from ERA40, HadGEM1.2 and HiGEM1.2. Units hPa. ERA-40 HiGEM1.2 HadGEM1.2 El Nino in HiGEM

Tropical Instability Waves in the Tropical Pacific Ocean are shear instabilities that grow in the equatorial current-counter current system –They propagate slowly westwards (~0.5ms -1 ) –Satellite data shows the coupling between the SST fronts associated with the TIWs and the atmosphere Tropical Instability Waves Instantaneous surface wind stress divergence from QuikSCAT winds Instantaneous SSTs in the Tropical Pacific Ocean (Chelton et al 2001)

Instantaneous Sea Surface Temperatures (contours) and surface windstress divergence (colours) HadGEM Tropical Instability Waves in HiGEM HiGEM How important is the small-scale coupling between ocean and the atmosphere in Tropical Instability Waves for the climate and its variability?