How will the earth’s temperature change?

Let’s start with what we know. We know that … The global climate has changed in the past. There are natural and (more recently) anthropogenic reasons for change. Humans are changing the environment with increasing GHG concentrations and land use change. The global mean temperature has increased about 1°F (0.6°C) over the last century. We have good climate data for the past 150 years.

Let’s start with what we know. We know that … We have good proxy climate data for the last hundreds of thousands of years. We can simulate the atmosphere well enough for weather forecasts. We understand the basic processes and principle equations in the climate system. We have the computing power to simulate the climate future.

Climate Models 101 3/22/10 > What is a GCM? global climate model general circulation model > History of GCM’s and how they work > Types of GCM’s

Why are Climate Models Important? Simulations Running scenarios that you cannot test in the real world - Doubling of current CO2 levels Sensitivity testing … the what if questions What would happen if all the sea ice in the Arctic melted? What if there were more aerosols in the atmosphere? What if the ocean-atmosphere heat exchange in the North Atlantic slowed? Guidance Ability to provide some outlook on what the future will hold

How do you model something so complex? The earth climate system atmosphere processes land processes Interactions Feedbacks ocean processes snow/ice processes

How do you model something so complex? Start out simple. Start from what we know.

Weather Forecast Models give rise to Climate Prediction Models

Pre-History of Global Climate Models: Bjerknes Vilhelm Bjerknes (1862-1951) proposed the procedure known as numerical weather prediction. He developed a set of equations to predict large scale motion. He used graphical methods on weather maps to solve these equations. These methods were used into the 1950’s, but it was not very successful due to: a) lack of observations and b) calculation time http://www-groups.dcs.st-and.ac.uk/~history/PictDisplay/Bjerknes_Vilhelm.html

Early Weather Maps (1900) http://docs.lib.noaa.gov/rescue/dwm/data_rescue_daily_weather_maps.html

Pre-History of Global Climate Models: Richardson Lewis Richardson developed first Numerical Weather Prediction system. Divided space into grid and simplified the equations. An 8-hr weather forecast took 6 weeks! Plus the forecast was a bust. Envisioned Forecast Factory, 64,000 ‘computers’ (people with mechanical calculators) with a central leader coordinating by using a beam of light. Only in the 1940’s did this become reality with the advent of digital computers. http://www.maths.tcd.ie/~plynch/Publications/Woolly_art_figs/View_Figs.html http://www-groups.dcs.st-and.ac.uk/~history/PictDisplay/Richardson.html

Mid-Century Weather Maps http://docs.lib.noaa.gov/rescue/dwm/data_rescue_daily_weather_maps.html

Early modelling efforts - weather forecasting Use of mathematical models to predict the atmosphere Simulates physics and dynamics of atmosphere Non-linear equations solved for increments of time Based on meteorological observations (initialization) Various scales of models (regional, global) Early days of NWP Present day technology

Early modelling efforts - climate prediction Use of mathematical models to predict the atmosphere Simulates physics and dynamics of atmosphere Non-linear equations solved for increments of time Assume a radiative equilibrium of earth (1-a)S0r2 = 4r2 T4 incoming solar = outgoing thermal

(1-a)S0r2 = 4r2 T4 + atmosphere Simple climate models One-dimensional models - radiative-convective model incoming solar = outgoing thermal (1-a)S0r2 = 4r2 T4 + atmosphere

(1-a)S0r2 = 4r2 T4 + atmosphere + advection Simple climate models Three-dimensional models - radiative-convective model with horizontal transport incoming solar = outgoing thermal (1-a)S0r2 = 4r2 T4 + atmosphere + advection

Complex climate models: equations Solving physics equations: East-West Wind North-South Wind Temperature Moisture Pressure

Complex climate models: 3 components atmosphere ocean land

Complex climate models: coupling atmosphere ocean land

Complex climate models: parameterizations atmosphere clouds land type ice ocean land

Complex climate models: solving the equations T is a function of time time temperature How do we solve this in time? Temperature

Complex climate models: solving the equations What are the coordinates? Computation time goes up as resolution increases. [Washington & Parkinson, 1986]

Complex climate models: solving the equations Use pressure coordinates, not altitude. Help deal with terrain.

Complex climate models: solving the equations

Who runs these models? By the 1960’s, separate groups evolved to build primitive equation GCMs independently. GFDL Geophysical Fluid Dynamics Laboratory UCLA Univ of California, Los Angeles Livermore Lawrence Livermore National Laboratory NCAR National Center for Atmospheric Research UKMO United Kingdom Meteorological Office

Who runs these models now? • European Center (Reading, UK) (1970’s built from scratch) • Max Planck Institute (Hamburg, Germany) • NASA Goddard Laboratory for Atmospheric Sciences • Colorado State University • Oregon State University • National Meteorological Centre (Australia)

Who runs these models? [http://www.aip.org/history/sloan/gcm/famtree.html]

Computational Demands for GCMs GCMs demand enormous computational power. The first GCMs => 24 hours of computer time for 1 day By mid-1970s, ~ 12 hours per simulated year For a typical run of 20 simulated years, a GCM still required as much as 10days of expensive supercomputer time. Trade-off between resolution and time Because of these computational needs, weather and climate modeling groups were among the earliest major users of supercomputers.

Simulating the Climate System: Climate Models Use of mathematical models to predict the atmosphere Simulates physics and dynamics of atmosphere Non-linear equations solved for increments of time model calculations input (data) output (prediction)

Simulating the Climate System: Climate Models model calculations input (data) output (prediction) station many stations gridded dataset Factors: grid and model resolution missing / bad data

Simulating the Climate System: Climate Models model calculations input (data) output (prediction) East-West Wind land ocean atmosphere Moisture Temperature Pressure North-South Wind

Simulating the Climate System: Climate Models model calculations input (data) output (prediction) different models have different resolutions assumptions physics schemes biases drawbacks strengths Parameterizations for: clouds topography ocean-atmos. interaction sea ice

Simulating the Climate System: Climate Models model calculations input (data) output (prediction) Models are run for various time and space scales: Space Time global short-term regional long-term

Climate Predictions - short term 1-month temperature and precipitation outlook http://www.cpc.noaa.gov/

Climate Predictions - short term 3-month temperature and precipitation outlook http://www.cpc.noaa.gov/

Climate Predictions - regional

Climate Predictions - global

Climate Models Grew from weather forecast models Solve physical equations on a 3-dimensional space - the more grids, the more time it takes Are run by several different agencies Have their strengths and weaknesses Are good to find out answers to the “What if … ?” question