Numerical modelling of possible catastrophic climate changes E.V. Volodin, N. A. Diansky, V.Ya. Galin, V.P. Dymnikov, V.N. Lykossov Institute of Numerical.

Slides:



Advertisements
Similar presentations
Michael B. McElroy ACS August 23rd, 2010.
Advertisements

Framtidens Östersjön – resultat från oceanografisk modellering Markus Meier SMHI, Norrköping
1 Trend and Year-to-year Variability of Land-Surface Air Temperature and Land-only Precipitation Simulated by the JMA AGCM By Shoji KUSUNOKI, Keiichi MATSUMARU,
Climate change in centuries in observational and model data Evgeny Volodin, Institute of Numerical Mathematics RAS, Moscow, Russia.
International Conference on Environmental Observations, Modeling and Information Systems ENVIROMIS July 2004, Tomsk, Russia International Conference.
Scaling Laws, Scale Invariance, and Climate Prediction
Climate models in (palaeo-) climatic research How can we use climate models as tools for hypothesis testing in (palaeo-) climatic research and how can.
Sensitivity of the climate system to small perturbations of external forcing V.P. Dymnikov, E.M. Volodin, V.Ya. Galin, A.S. Gritsoun, A.V. Glazunov, N.A.
Climate Change and Malaysia
DARGAN M. W. FRIERSON DEPARTMENT OF ATMOSPHERIC SCIENCES DAY 16: 05/20/2010 ATM S 111, Global Warming: Understanding the Forecast.
Climate modeling Current state of climate knowledge – What does the historical data (temperature, CO 2, etc) tell us – What are trends in the current observational.
Earth Systems Science Chapter 6 I. Modeling the Atmosphere-Ocean System 1.Statistical vs physical models; analytical vs numerical models; equilibrium vs.
Outline Further Reading: Detailed Notes Posted on Class Web Sites Natural Environments: The Atmosphere GG 101 – Spring 2005 Boston University Myneni L31:
Consequences of Global climate Change. Impact of Global Warming Sea level rising Altered precipitation pattern Change in soil moisture content Increase.
Liu, J. et al., PNAS, 2012 World Weather Open Science Conference, Montreal, Canada, August 17, 2014 Jiping Liu University at Albany, State University of.
May 2007 vegetation Kevin E Trenberth NCAR Kevin E Trenberth NCAR Weather and climate in the 21 st Century: What do we know? What don’t we know?
Climate and Food Security Thank you to the Yaqui Valley and Indonesian Food Security Teams at Stanford 1.Seasonal Climate Forecasts 2.Natural cycles of.
Arctic Climate Variability in the Context of Global Change Ola M. Johannessen, Lennart Bengtsson, Leonid Bobylev, Svetlana I. Kuzmina, Elena Shalina.
Climate change in Italy An assessment by data and re-analysis models Raffaele Salerno, Mario Giuliacci e Laura Bertolani Mountain Witnesses of Global.
Rising Temperatures. Various Temperature Reconstructions from
Hal Gordon CSIRO Atmospheric Research, Aspendale, Australia CSIRO Mk3 Climate Model: Tropical Aspects.
The Future of Arctic Sea Ice Authors: Wieslaw Maslowski, Jaclyn Clement Kinney, Matthew Higgins, and Andrew Roberts Brian Rosa – Atmospheric Sciences.
Simulation of the second half of the 20th Century using the MGO AGCM P.V. Sporyshev, V.P. Meleshko, T.V. Pavlova Voeikov Main Geophysical Observatory,
Helgi Björnsson, Institute of Earth Sciences, University of Iceland, Reykjavik, Iceland Contribution of Icelandic ice caps to sea level rise: trends and.
Apresentação de Resultados do IPCC AR4 WG1 Jose A. Marengo CPTEC/INPE.
Outline Further Reading: Detailed Notes Posted on Class Web Sites Natural Environments: The Atmosphere GE 101 – Spring 2007 Boston University Myneni L30:
Atlantic Multidecadal Variability and Its Climate Impacts in CMIP3 Models and Observations Mingfang Ting With Yochanan Kushnir, Richard Seager, Cuihua.
Climate Change: From Global Predictions to Local Action Mathematical Sciences Research Institute April
Climate Change Science -- the Present Stuart Godfrey (retired CSIRO Oceanographer) What is it like being a Greenhouse climate scientist? Perth, WA river.
Modern Climate Change Darryn Waugh OES Summer Course, July 2015.
Projecting changes in climate and sea level Thomas Stocker Climate and Environmental Physics, Physics Institute, University of Bern Jonathan Gregory Walker.
Status of the Sea Ice Model Testing of CICE4.0 in the coupled model context is underway Includes numerous SE improvements, improved ridging formulation,
Studies of IGBP-related subjects in Northern Eurasia at the Laboratory of Climatology, Institute of Geography, Russian Academy of Sciences Andrey B.Shmakin.
(Mt/Ag/EnSc/EnSt 404/504 - Global Change) Climate Models (from IPCC WG-I, Chapter 10) Projected Future Changes Primary Source: IPCC WG-I Chapter 10 - Global.
The dynamic-thermodynamic sea ice module in the Bergen Climate Model Helge Drange and Mats Bentsen Nansen Environmental and Remote Sensing Center Bjerknes.
Correlation of temperature with solar activity (SSN) Alexey Poyda and Mikhail Zhizhin Geophysical Center & Space Research Institute, Russian Academy of.
Sahel Climate Change in the IPCC AR4 models Michela Biasutti in collaboration with : Alessandra Giannini, Adam Sobel, Isaac.
The European Heat Wave of 2003: A Modeling Study Using the NSIPP-1 AGCM. Global Modeling and Assimilation Office, NASA/GSFC Philip Pegion (1), Siegfried.
Mechanisms of drought in present and future climate Gerald A. Meehl and Aixue Hu.
The evolution of climate modeling Kevin Hennessy on behalf of CSIRO & the Bureau of Meteorology Tuesday 30 th September 2003 Canberra Short course & Climate.
The GEOS-5 AOGCM List of co-authors Yury Vikhliaev Max Suarez Michele Rienecker Jelena Marshak, Bin Zhao, Robin Kovack, Yehui Chang, Jossy Jacob, Larry.
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.
PAPER REVIEW R Kirsten Feng. Impact of global warming on the East Asian winter monsoon revealed by nine coupled atmosphere-ocean GCMs Masatake.
© Crown copyright Met Office Uncertainties in the Development of Climate Scenarios Climate Data Analysis for Crop Modelling workshop Kasetsart University,
Climate Variability and Basin Scale Forcing over the North Atlantic Jim Hurrell Climate and Global Dynamics Division National Center for Atmospheric Research.
Future Projections of Precipitation Characteristics in Asia.
Earth system model of INM RAS Volodin E.M., Galin V.Ya., Diansly N.A., Gusev A.V., Smyshlyaev S.P., Yakovlev N.G. Institute of Numerical Mathematics RAS.
Chapter 6 Future climate changes Climate system dynamics and modelling Hugues Goosse.
Schematic framework of anthropogenic climate change drivers, impacts and responses to climate change, and their linkages (IPCC, 2007).
Climate Change & The Probability of Extreme Events Brian Hoskins Royal Society Research Professor & Professor of Meteorology University of Reading Department.
1 Zhou Tianjun and Rucong Yu, 2006, Twentieth Century Surface Air Temperature over China and the Globe Simulated by Coupled Climate Models, Journal of.
El Niño / Southern Oscillation
Global Impacts and Consequences of Climate Change
Climate Change Climate change scenarios of the
North American Regional Climate Change Assessment Program
Modeling the Atmos.-Ocean System
Global mean temperatures are rising faster with time Warmest 12 years:
20th Century Sahel Rainfall Variability in IPCC Model Simulations and Future Projection Mingfang Ting With Yochanan Kushnir, Richard Seager, Cuihua Li,
1 GFDL-NOAA, 2 Princeton University, 3 BSC, 4 Cerfacs, 5 UCAR
Globale Mitteltemperatur
Observed climatological annual mean SST and, over land, surface
Globale Mitteltemperatur
Decadal prediction in the Pacific
Schematic framework of anthropogenic climate change drivers, impacts and responses to climate change, and their linkages (IPCC, 2007).
Korea Ocean Research & Development Institute, Ansan, Republic of Korea
Anthropogener Klimawandel: Projektionen
Inez Fung University of California, Berkeley April 2007
Fig. 1 a) All-India Summer (JJAS) Monsoon rainfall anomalies (% of mean) during The 31-yr sliding mean of the anomalies is shown in.
Globale Mitteltemperatur
Presentation transcript:

Numerical modelling of possible catastrophic climate changes E.V. Volodin, N. A. Diansky, V.Ya. Galin, V.P. Dymnikov, V.N. Lykossov Institute of Numerical Mathematics (INM) Russian Academy of Sciences, Moscow Corresponding

COUPLED ATMOSPHERE-OCEAN GSM (INMCM3.0) AGCM Finite difference model has spatial resolution of 5° in longitude and 4° in latitude and 21 levels in sigma-coordinates from the surface up to 10 hPa. In radiation absorption of water vapour, clouds, CO2, O3, CH4, N2O, O2 and aerosol are taken into account. Solar spectrum is divided by 18 intervals, while infrared spectrum is divided by 10 intervals. Deep convection, orographic and non-orographic gravity wave drag are considered in the model. Soil and vegetation processes are taken into account. Non-flux-adjusted coupling OGCM: Global ocean σ-model with resolution is 2.5°x2°x33 including sea ice thermodynamics. Coupling includes interactive river runoff. Global ocean general circulation model as ocean component of the climate system model: characteristics of global ocean circulation simulated in experiments under IPCC scenarios.

The results of the experiments carried out according to IPCC scenario. (Also presented in the IPCC Fourth Assessment Report) IPCC scenario of time evolution of CO2, CH4, N2O, SOL,VLC

Model climate in 20th century. Meridional heat transport averaged for Mean sea level evolution Global temperature anomaly in , 10-yr moving average (thick line is observations, thin line is model)

The first SVD modes of SLP (top) and SST (bottom) in the North Atlantic region in winter for the model (left) and observations (right) for Model climate in 20th century.

Model climate in 20th century: El-Nino reproducing. Power spectra of SST anomaly in Nino 3 region (5°N–5°S,150°W–90°W) Root mean square (RMS) of SST anomaly for INMCM3.0.

Multi-model mean of annual mean surface warming (surface air temperature, in °C) for the A1B scenario 2080–2099. Stippling denotes where the multi-model ensemble mean exceeds the intermodel standard deviation. INMCM3.0 annual mean surface warming (surface air temperature, in °C) for the A1B scenario 2080–2099. Climate changes according IPCC scenario A1B:

ΔT ( )– ( ) DEC-FEB JUN-AUG

Time series of globally averaged (left) surface warming (surface air temperature, in °C) and (right) precipitation (in %) from the various IPCC models for the scenarios (top) A2, (middle) A1B and (bottom) B1 scenario. Values are annual means, relative to the 1980–1999 average from the corresponding 20th century simulations, with any linear trends in the corresponding control run simulations removed. Shown in black are the multi-model (ensemble) mean series. Climate changes according IPCC scenarios:

Projected global average sea level rise (m) due to thermal expansion during the 21st century relative to 2000 under SRES scenarios a) A1B, b) A2 and c) B1. Climate changes according IPCC scenarios:

September arctic sea ice area (10 6 km 2 ) in control run (blue), 20c3m(green), B1 (yellow), A1B (orange) and A2 (red)

ΔT DJF ( )- ( ) ALL MONTHS WARM MONTHS COLD MONTHS

ΔT JJA ALL MONTHS WARM MONTHS COLD MONTHS

ΔP/P MAY-SEP ALL MONTHS WET MONTHS DRY MONTHS

Change of vegetation period length (top) and number of frost days (bottom) ( ) – ( ) A1B

Change of maximum dry period, days (top) and number of days with P>10 mm ( ) – ( ) A1B.

PERMAFROST B A2