Climate models – prediction and projection Nils Gunnar Kvamstø Geophysical Department University of Bergen

Climate models Best tool for projections The best tool for attribution of observed climate change Potential for realistic regional and local projections The reality of global warming is based on much more than climate model results

Climate model results used for Local climate change Mitigation studies, e.g. emissions corresponding to two degrees GW Effects of climate change (e.g. extinction, food supply, climate refugees, water management, economy)

Vilhelm Bjerknes – proposed weather prediction models in 1904 Doctor deg Ass. Prof. in mechanics Stockholm 1893 Prof. Stockholm 1895 Kristiania 1907 Leipzig 1912 Bergen 1917 Oslo 1926 Painting: Rolv Groven

Bjerknes’ vision on scientific weather forecasting

1. The state of the atmosphere must be known for a specific time (from observations) 2. Then future states might be computed from conservation laws for mass, energy and momentum Bjerknes’ vision

Numerical methods: Finite differences Spectral methods Model equations One set of prognostic variables in each grid box

Parametrisation of sub-grid scale processes Resolved topography Sub-grid topography

Sub-grid processes for parameterisation Sub-grid processes are prameterized, often as a function of grid-point values. Horizontal derivatives are not involved => Easier to parallellize these computations.

1. State at a specific time S 0 (wind, temperature, pressure, humidity clouds) determined from observations. 2. Future stated by solving (non-linear) conservation laws: Numerical Weather Prediction Models

Lorenz attractor (analogy to weather behaviour) Ed Lorenz ( ) Predictability for weather forecasting y x

Limitation in predictability of the weather score predictability (days) Theoretical limit Today’s limit Tomorrow’s limit Limit for useable prediction

Predictability for climate change different from that of weather forecasting Weather forecasting: predictability of first kind (the actual weather) Prediction of climate change: predictability of second kind (statistical properties of the weather over several years) Actual weather models determines: present limits for weather prediction Actual climate models determine: present ability to predict climate change

Source: IPCC AR4 WG1 Increase in complexity of climate models FAR: First Assessment Report (IPCC 1990) SAR: Second Assessment report (IPCC 1996) TAR: Third Assessment Report (IPCC 2001)

CLM CAM CICE HAMOCC MICOM Atmospheric chemistry Components in blue communicate trough a coupling component. Components in red are subroutines of blue components. River routing NorESM framework and model components

Computer platforms Shared memoryDistributed memory Combination memory network node gridur/embla (2002), 2 nodes, = 896 cores, 1.0 Tflop njord (2006), 62 nodes x 16 cores = 992 cores, 7.5 Tflop stallo (2007), 704 nodes x 8 cores = 5632 cores, 60 Tflop hexagon (2008), 1388 nodes x 4 cores = 5552 cores, 50 Tflop

Dipole grid (default CCSM)Tripole grid Specs Bergen Climate Model Res atmosphere (1.9x 2.5 deg 20 layers) 96*172*20 Res ocean: (1deg, 20 layers) 180*360*90 90 procs Hexagon 6.7 yr/d Output 6h, d, mon -> 5Tb per 100 years

Emission scenarios from IPCC, includes also air pollution giving aerosols ppm EXPERIMENT TYPES

Projections of global temperature change Norges mål:2 grader IPCC

IPCC 2007

Changes in precipitation (percent) by the end of the century Winter Summer

Conclusions Climate models solve well known physical equations from hour to hour, from day to day, from year to year Climate models have no tuning to fit observations Climate models simulate the observed global warming during the latest decades Best tool for future projections and attribution of sources for climate change Decadal prediction with models a large research area Climate drift a problem Next generation models will include the carbon cycle Feed-back from clouds and effects of aerosols a notorious problem

Questions Why are there 'wiggles' in the output? What is tuning? What is robust in a climate projection and how can I tell? Are the models complete? That is, do they contain all the processes we know about? Do models have global warming built in? What is the difference between a physical model and a statistical model?