Hiatus and decadal prediction research using MIROC climate model

Similar documents
Decadal predictions using the higher resolution HiGEM climate model Len Shaffrey, National Centre for Atmospheric Science, University of Reading

ENSO: Recent Evolution, Current Status and Predictions. Update prepared by: Climate Prediction Center / NCEP 29 June 2015

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 9 May 2011

A Project to Create Bias-Corrected Marine Climate Observations from ICOADS

Decadal/Interdecadal variations in ENSO predictability in a hybrid coupled model from

Performance Metrics for Climate Models: WDAC advancements towards routine modeling benchmarks

Present trends and climate change projections for the Mediterranean region

IGAD CLIMATE PREDICTION AND APPLICATION CENTRE

The role of forcings in 20 th century North Atlan6c- Mediterranean decadal variability

Observed Cloud Cover Trends and Global Climate Change. Joel Norris Scripps Institution of Oceanography

THE CURIOUS CASE OF THE PLIOCENE CLIMATE. Chris Brierley, Alexey Fedorov and Zhonghui Lui

Cloud-SST feedback in southeastern tropical Atlantic anomalous events

Monsoon Variability and Extreme Weather Events

The IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation

Baudouin Raoult, Iryna Rozum, Dick Dee

A Comparison of the Atmospheric Response to ENSO in Coupled and Uncoupled Model Simulations

Examining the Recent Pause in Global Warming

SPOOKIE: The Selected Process On/Off Klima Intercomparison Experiment

How To Predict Climate Change

Breeding and predictability in coupled Lorenz models. E. Kalnay, M. Peña, S.-C. Yang and M. Cai

The ozone hole indirect effect: Cloud-radiative anomalies accompanying the poleward shift of the eddy-driven jet in the Southern Hemisphere

On the relation between albedo, cloud fraction and aerosol optical depth in climate models and satellite observations

Lecture 4: Pressure and Wind

Discriminating robust and non-robust atmospheric circulation responses to global warming

Future Projections of Precipitation Characteristics in East Asia Simulated by the MRI CGCM2

The impact of parametrized convection on cloud feedback.

SST-Forced Atmospheric Variability in an Atmospheric General Circulation Model

Improving Hydrological Predictions

A review of the fall/winter 2000/01 and comparison with

Guy Carpenter Asia-Pacific Climate Impact Centre, School of energy and Environment, City University of Hong Kong

Development of an Integrated Data Product for Hawaii Climate

Coupling between subtropical cloud feedback and the local hydrological cycle in a climate model

Scholar: Elaina R. Barta. NOAA Mission Goal: Climate Adaptation and Mitigation

Structural Uncertainty of the CHAMP Climate Record from Different Data Centers

Item 4.1: Atmospheric Observation Panel for Climate Recent climatic events, observing-system changes and report from 17 th Session of AOPC

The retrospective prediction of ENSO from by a hybrid coupled. model (II) Interdecadal and decadal variations in predictability

Decadal Variability: ERBS, ISCCP, Surface Cloud Observer, and Ocean Heat Storage

Group Session 1-3 Rain and Cloud Observations

A process oriented descrip-on of oceanic clouds derived from A- train observa-ons, for climate model evalua-on

Radiative effects of clouds, ice sheet and sea ice in the Antarctic

Selected Ac)vi)es Overseen by the WDAC

The Influence of the Mean State on the Annual Cycle and ENSO Variability: A Sensitivity Experiment of a Coupled GCM

Ocean and climate research at KNMI. Andreas Sterl KNMI

Data Assimilation and Operational Oceanography: The Mercator experience

South Africa. General Climate. UNDP Climate Change Country Profiles. A. Karmalkar 1, C. McSweeney 1, M. New 1,2 and G. Lizcano 1

NOTES AND CORRESPONDENCE

Huai-Min Zhang & NOAAGlobalTemp Team

The impact of window size on AMV

CGC1D1: Interactions in the Physical Environment Factors that Affect Climate

Near Real Time Blended Surface Winds

Analysis of Climatic and Environmental Changes Using CLEARS Web-GIS Information-Computational System: Siberia Case Study

Queensland rainfall past, present and future

Extraseasonal ensemble numerical predictions of winter climate over China

5 day Training on Climate Change and Adaptation

Performance of current GCMs in high latitudes in the context of global climate change and variability studies

A decadal solar effect in the tropics in July August

Titelmasterformat durch Klicken. bearbeiten

Extra-Tropical Cyclones in a Warming Climate:

Clouds, Circulation, and Climate Sensitivity

Temporal variation in snow cover over sea ice in Antarctica using AMSR-E data product

Projecting climate change in Australia s marine environment Kathleen McInnes

Climate Change Long Term Trends and their Implications for Emergency Management August 2011

Enfermedad de las Manchas Blancas (EMB) White Spot Disease (WSD) Actualización del diagnóstico ambiental Octubre Perspectivas al 2011

Multi-decadal modulations in the Aleutian-Icelandic Low seesaw and the axial symmetry of the Arctic Oscillation

Seasonal & Daily Temperatures. Seasons & Sun's Distance. Solstice & Equinox. Seasons & Solar Intensity

REGIONAL CLIMATE AND DOWNSCALING

2008 Global Surface Temperature in GISS Analysis

Distinctive climate signals in reanalysis of global ocean heat content

NOAA s National Climatic Data Center

Climate Extremes Research: Recent Findings and New Direc8ons

Addendum to the CMIP5 Experiment Design Document: A compendium of relevant s sent to the modeling groups

Improving Low-Cloud Simulation with an Upgraded Multiscale Modeling Framework

Comment on "Observational and model evidence for positive low-level cloud feedback"

Application of Numerical Weather Prediction Models for Drought Monitoring. Gregor Gregorič Jožef Roškar Environmental Agency of Slovenia

The Impact of Global Warming on Marine Boundary Layer Clouds over the Eastern Pacific A Regional Model Study

Temporal and spatial evolution of the Antarctic sea ice prior to the September 2012 record maximum extent

Can latent heat release have a negative effect on polar low intensity?

climate science A SHORT GUIDE TO This is a short summary of a detailed discussion of climate change science.

II. Related Activities

Developing Continuous SCM/CRM Forcing Using NWP Products Constrained by ARM Observations

TCC News 1 No. 33 Summer 2013

Roy W. Spencer 1. Search and Discovery Article # (2009) Posted September 8, Abstract

Comparison of the Vertical Velocity used to Calculate the Cloud Droplet Number Concentration in a Cloud-Resolving and a Global Climate Model

Ⅱ. Related Activities

Climate Change in Mexico implications for the insurance and reinsurance market

Climate Change in North Carolina

Fundamentals of Climate Change (PCC 587): Water Vapor

A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands

Dr. Gary S. E. Lagerloef Earth and Space Research, 1910 Fairview Ave E

Geography affects climate.

ICOADS: Data Characteristics and Future Directions

IMPACTS OF IN SITU AND ADDITIONAL SATELLITE DATA ON THE ACCURACY OF A SEA-SURFACE TEMPERATURE ANALYSIS FOR CLIMATE

Goal: Understand the conditions and causes of tropical cyclogenesis and cyclolysis

Physical properties of mesoscale high-level cloud systems in relation to their atmospheric environment deduced from Sounders

Tropical Stationary Wave Response to ENSO: Diabatic Heating Influence on the Indian summer monsoon

Impact of the Indian Ocean SST basin mode on the Asian summer monsoon

CFMIP-2 : Cloud Feedback Model Intercomparison Project Phase 2

A glance at compensating errors between low-level cloud fraction and cloud optical properties using satellite retrievals

Regional Climate Science for the Pacific John Clarke, Tim Erwin, Geoff Gooley & Kevin Hennessy

Transcription:

Hiatus and decadal prediction research using MIROC climate model Masahide Kimoto Atmosphere and Ocean Research Institute The University of Tokyo with special thanks to Masahiro Watanabe (AORI, Univ. Tokyo), Masayoshi Ishii (MRI/JMA) and Team SPAM

Intensified Pacific trades and heat uptake Pacemaker experiments using CGCM * Eastern Pacific cooling à hiatus (Kosaka and Xie 2013 Nature) * Intensified Pacific trades in the 2000s à hiatus w/ increasing ocean heat uptake (England et al. 2014 Nature CC) Model response to 1992-2011 wind trend England et al. (2014)

ParFal Wind Overriding historical experiments MIROC5.2 (T85L40) 5- member ensembles for 1958-2012 * PWO- Hist: Tropical (30S- 30N) τ anomaly replaced w/ JRA reanalysis * PWO- Nat: As in PWO- hist but with external forcing fixed at 1850 2001-2010 average: PWO- Hist ü 0.64±0.26 W/m 2 CERES ü 0.5±0.43 W/m 2 (Loeb et al. 2012 NGeo) ü 0.62±0.43 W/m 2 (Allan et al. 2014 GRL) Excess energy to the system à TOA radiafve imbalance PWO- Hist Watanabe et al. (2014)

ParFal Wind Overriding historical experiments MIROC5.2 (T85L40) 5- member ensembles for 1958-2012 * PWO- Hist: Tropical (30S- 30N) τ anomaly replaced with JRA55 reanalysis Reproducibility of the Pacific SST variability PWO- Hist SST, Mean ACC = 0.49 Nino3.4 SST anomaly ASYM- H PWO- Hist

Watanabe et al. (2014) Hiatus reproduced in MIROC5.2 Par6al wind overriding experiments Tropical ocean wind stress anomalies are sufficient to reproduce surface temperature anomaly pa_ern in the hiatus SAT change from 1990-1999 to 2001-2012 Observa`ons PWO- Hist

Hiatus reproduced in MIROC5.2 Par6al wind overriding experiments Decadal wind stress variability substan`ally contributes to the warming accelera`on in the 1980-90s and hiatus in the 2000s CMIP models Obs PWO- Hist (tropical τ anomaly replaced with reanalysis) PWO- Nat (PWO- Hist + external forcing fixed at 1850) Watanabe et al. (2014)

AWribuFon of hiatus Wind stress variability responsible for the global- mean SAT change 10- member AMIP runs w/ and w/o anthropogenic warming (AMIP- Hist & AMIP- Nat) reveal the decadal τ variability is approximately independent of the global warming τ EOF1 reanalysis PC `meseries τ EOF1 AMIP- Hist Global- mean SAT AMIP- Hist AMIP- Nat Watanabe et al. (2014)

AWribuFon of hiatus Contribu6on of natural internal variability & external forced component to the global warming accelera6on & hiatus Substan`al contribu`on of the internal decadal varia`ons Frac`onal contribu`on decreases as rising signal of anthropogenic warming DecomposiFon of decadal- mean SAT changes PWO- Hist PWO- Nat diff. Decade ΔT INT ΔT INT /ΔT ALL 1980s +0.11K 47% 1990s +0.13K 38% 2000s - 0.11K 27% Watanabe et al. (2014)

AWribuFon of hiatus Dis6nct structure of ocean warming Zonal- mean temperature change from 1990-1999 to 2001-2012 Obs (Ishii) ΔT INT More heat uptake in the subtropics by the wind- driven circulafon ΔT ALL= PWO- Hist ΔT EXT More heat uptake in northern high laftudes (mostly North AtlanFc) Watanabe et al. (2014)

Seasonality in warming trends Surface air temperature anomaly [ ] Courtesy of Y Kamae p Hiatus seen year round over oceans p Hiatus only in DJF over land à What s happened in warm seasons?

A_ribu`on of increase in NH heat waves MIROC5- AGCM (T85L40) C20C Radia6ve forcing SST/sea ice Historical Historical PI fixed AMIP- Hist AMIP- Nst Natural* AMIP- Alf AMIP- Nat Contribu`on to heatwave frequency (25-50N) f = f ADIR + f ASST + f NAT Direct GHG SST increase Natural Var f ADIR f NAT f ASST Decadal 38% 43% 19% Long- term 40% 15% 45% Combined analysis of AMIP- type ensembles à Considerable contribu`on of direct radia`ve effect of GHGs to increasing heat wave frequency AMIP- Hist reproduces increasing f AMIP- Hist Kamae et al. (2014 GRL)

Summary p Coupled models can reproduce the hiatus well if the tropical Pacific is constrained with observafons p Natural decadal variability explains a significant fracfon of warming hiatus as well as accelerafon in the 1980-90s, but its contribufon has declined p Land surface shows a warming trend despite hiatus, due largely to direct effect by GHGs Watanabe et al. (2014)

Forced component in AMV? Watanabe et al. (2015) AMV index: Obs (top), MIROC5.2 (5 members) FULL(middle) & NOSO2 (bottom)

150-year reanalysis/reforecast of coupled ocean-atmosphere climate system? Prediction? Verification? Global mean surface temperature 1890-2010 (JMA) Spatial distribution? 1959年伊勢湾台風 Upper air? Subsurface? Causes for anomalous/extreme weather? Predictability? Surface Obs Upper- air Obs Ocean subsurface Obs Coupled atmosphere- ocean reanalysis Reanalysis/reforecast of historical climate data using a state-ofthe art coupled ocean-atmosphere climate model A 100yr-long, 3D reconstruction of atmosphere and oceans Promote studies of natural decadal variability Assessments of anomalous/extreme weather and their predictability Increased credibility of climate predictions, contributing to impact assessments The analysis system can serve as a research platform

150- yr Reanalysis CGCM Ensemble Run Computational Node Reformation Objective Analysis w/ EnKF Atmos. Obs. Quality Control Ocean Obs. Quality Control A new system configured specifically for long- term climate reanalysis Coupled Model + EnKF From 1850 to present Spec. (ver. 1) l LETKF (Hunt et al. 2007) l Loosely coupled A Trial l Assimila`on interval: 6 hours for Atmos. and 5 days for Ocean l Surface Pressure Data (ISPD v.3.2.8) l Typhoon bogus (IBTrACS v03r05) l SST: COBE- SST2 + SST perturba`ons l Gridded subsurface ocean T and S (Ishii and Kimoto 2009)

Z500 ACC 2005-2010 No Assym SLP Assym SST Assym SLP-SST Assym Z500 ACC 2005-2010

Time 500hPa Geopotential height at 12UTC, February 20 th, 2005 ERA-Interim EnKF Spread PaWern CorrelaFon Pa_ern CC aqer subtrac`ng zonal means Preliminary Run with MIROC3m (T42L20 AGCM and 1- deg OGCM)

Global Mean Surface Temperature over Land Shade: Spread

Monthly Mean Precipita`on July 2010 GPCP July 2010 GPCP EnKF EnKF July 2010 Internannual variability (1980-2010)

A trial of pre- 1950 ENSO PredicFons Bias Uncorrcted Bias Corrcted

Atmosphere and Ocean Data Rescue Recently processed SLP data (1890 1940; Kubota et al. JAMSTEC) Upper air observa`ons to be digi`zed ç Expected data distribu`on (red) of marine met. Obs. by the Japanese Imperial Navy (1903-1944, ~ 1 million) ParFcipaFng in and collaborafng with internafonal acfvifes: ACRE, ICOADS, ICA&D, IQuOD