Chapter 6: Modeling the Atmosphere-Ocean System -So far in this class, we ve mostly discussed conceptual models models that qualitatively describe the system example: Daisyworld examined stable and unstable equilibrium points from such models, we can understand how a system operates, but not quantitatively so We really need physically-based mathematically models to do this (i.e. to determine how much the Earth will warm during this century due to greenhouse-gas forcing and other forcings)
Linking Different Feedback Processes and Other Physical Mechanisms Together -So far, we ve discussed many important feedbacks in this class (i.e. ice-albedo, greenhouse effect, IR Flux/Temperature, Sea- Ice, various cloud feedbacks, Water Vapor) and important properties of atmosphere-ocean transport -And, though these are important, they still do not give us anywhere of a complete picture of the climate system -We ve talked about them more as though they operate independently of each other -In fact, such feedbacks and other processes that affect weather and climate are really coupled (linked) together, making the Earth-climate system a very complicated one
Modeling Climate Do all climate models attempt to simulate all possible physics of the Earth systems (i.e. cryosphere, biosphere, atmosphere, oceans)? The short answer is NO : all model simulations (even those done with the most detailed models) are simplifications of the real world Some models simulate more processes than others Three important model types: 1. Radiative-convective models (RCMs) 2. Energy Balance Models (EBMs) 3. General Circulation Models (GCMs)
Radiative-Convective Models (RCMs) Simplest of the three climate models One-dimensional model that predicts the global mean temperature based on radiative fluxes and parameterized convection averaged throughout the globe Advantages: Can assess the quantitative importance of the cumulative greenhouse effect or of isolating the importance of each greenhouse gas (i.e. how much warming does doubling CO 2 cause?) Quick to run and straightforward to interpret (not too computationally expensive Disadvantages: Only get a 1-D picture of the atmosphere (i.e. regional responses to increasing greenhouse gases are not resolved) Many feedbacks and physics are not simulated
RCM 20 th Century Surface Temperature Change With Various Mixed Layer Depths 0.90 0.80 *Changing mixed layer depth has only a marginal impact on final results Surface Temperature Change (K) 0.70 0.60 0.50 0.40 0.30 0.20 0.10 *Mean Calculated 20 th Century DT 40% higher than observed results, as RCM only simulates positive GHG DF d=100m d=50m d=5m 0.00 1900 1920 1940 1960 1980 2000 Year
IPCC Observed Temperature Anomaly (As Adapted from Fig. 2 of IPCC Technical Summary) Thus, the RCM simulated the past century climate fairly well, despite not including the radiative impact of aerosols
3.5 RCM Calculated Temperature Changes With IPCC Concentrations. 3 Surface Temperature Change (K) 2.5 2 1.5 1 0.5 A1F1 B1 A1P 0 2000 2020 2040 2060 2080 2100 Year
How does this compare to more sophisticated, 3-D climate models? -The 2001 Intergovernmental Panel on Climate Change (IPCC) report had a range of 21 st century surface temperature increases of 1.3 C to 5.7 C -So, at least these RCM runs fell within the range of what more complicated models project!
Comparison of RCM Calculated Results Versus IPCC Results Emissions Scenario High (DT) SFC Low (DT) SFC Mean (DT) SFC IPCC A1F1 5.7 3.2 4.3 RCM A1F1 3.3 IPCC B1 2.6 1.3 1.8 RCM B1 1.3 *As this RCM has a fairly low sensitivity, these low values are somewhat expected *Inclusion of radiative forcing due to aerosols & other constituents would also be necessary to better explain differences
Energy Balance Models (EBMs) 2-dimensional models that usually split world the up into latitudinal (i.e. 10 N-20 N) bands Can examine more feedbacks than with RCMs (i.e. cloud feedbacks and ice-albedo feedback as a function of latitude can be examined) Cannot be used to make very detailed predictions about future climate change, as atmospheric winds/waves (i.e. those discussed in Chapter 4) can not be resolved with only 2 dimensions
Three-Dimensional Climate Models General Circulation Models (GCMs) designed to simulate all the important large-scale atmospheric motions Types: 1. Atmospheric GCMs (AGCMs), 2. Ocean GCMs (OGCMs), and the 3. Atmospheric and Ocean GCMs - AOGCMs The text calls AOGCMS Global Climate Models (GCMs), but this convention is not standard! Suffice it to say that GCMs normally mean General Circulation Models!
Structure of GCMs Surface of globe is divided up into latitude-longitude cells, and the atmosphere above each cell is divided into atmospheric layers Each 3-D box represents a portion of atmosphere defined by latitude, longitude, and height Each box can exchange energy with the boxes above or below (of which there are six adjacent boxes east/west, north/south, and up/down) At the surface, geography and surface features are taken into account (i.e. vegetation type (bare soil, forests, grasslands), mountains, ocean) NOTE THIS IS COMPLICATED!!!
A Flow Chart of Some of the Processes that GCMs simulate Solar radiation enters grid box from the top of atmosphere In each grid box, some radiation is transmitted, some is reflected, and some is absorbed Through the atmosphere, the fate of the LW radiation is determined by clouds, water vapor, and other greenhouse gases At the surface, some SW radiation is absorbed or reflected, and LW radiation is emitted (depending on the temperature Changes in density from box to box allows both horizontal and vertical motions to develop, carrying energy, mass, and momentum Depending on temperature and humidity, water vapor in boxes may condense to form clouds
Surface Characteristics Each box at the surface can be over ocean or land, and if over land, vegetative cover is considered, as is elevation Soil is divided into layers (and this determines the water/heat transfer) Vegetative covers determines surface albedo, surface roughness (how rough the surface is affects the friction, and thus the wind, near the surface) OCEAN -ocean circulation simulations are as detailed as atmospheric circulation simulations in GCMs -energy, mass, and momentum are exchanged at the ocean surface -changes in density, salinity, and temperature affects ocean circulations (think of the Thermohaline Circulation)
How many calculations are involved in GCMs? Let s say the horizontal resolution is 2.5 latitude by 2.5 longitude Æthis represents 20,000 cells And, there atmosphere is divided into 20 layersæthis makes 20,000 x 20 = 400,000 grid boxes! 6,000 of the surface boxes are over land, and these boxes also include a 5-layer soil model (another 30,000 set of calculations!) Remember that much is going on in each box, and that boxes can exchange heat, radiation, moisture, and wind with each other
Temporal Resolution The temporal resolution depends on the spatial resolution higher spatial resolution means higher temporal resolution is necessary The spatial resolution of most GCMs requires that they be updated every 10 to 30 minutes! What does this all mean? Thus, millions of calculations must be made each day GCMs usually simulate at least the past 100 years of climate and project at least 100 years into the future World s most powerful parallel processors might take 50 days to make a single model run with a GCM!
Timeline of Evolution of GCMs World War I through 1920s 1940s-1950s Late 1950s-1960s Since 1970s Lewis Fry Richardson solved the basic atmospheric equations of motion Emergence of electronic computers; used primarily for numerical weather forecasts Weather prediction models were transformed to climate prediction models GCMs have become increasingly more complex with time present-day GCMs simulate many components of the climate system (atmosphere, ocean/sea-ice, vegetative cover, aerosols, chemistry, etc.)
Experiments done with GCMs A. Equilibrum Climate Change Experiments 1. Some radiative forcing is given (i.e. changing the amount of CO 2 ), and then the model is run until it reaches equilibrium 2. Early GCMs (1970s):looked at effect of 4xCO 2 a. calculated global surface warming of 4 C b. assumed constant cloud cover 3. Later GCM equilibrium climate change studies examined the effect of doubling CO 2 with variable cloud cover a. calculated warming of about 4 C warming b. demonstrates the importance of clouds (there was an increase in high-level cirrus clouds) WHY WOULD AN INCREASE IN HIGH-LEVEL CIRRUS CLOUDS AMPLIFY WARMING?
B. Transient Climate Experiments _More recent (1980s through the present) _Assessment of how climate actually changes with time _Begin with simulating present or past climate, and then letting the GCM run for either tens to hundreds of years _For future climate, greenhouse gas concentrations need to be projected -Need to make projections of future socioeconomic states -Technology advancements are also considered
Examples of Emissions Scenarios
GCM Resolution Issues _GCMs are generally good representations of the basic principles of physics that govern climate _Resolution: Grid size and model time step _But, what about processes that occur on smaller spatial scales than can be resolved with models? 1. Typical area of grid box: 62500 km 2 2. But many things occur on much smaller scales 3. Solution: parameterize smaller-scale features, so that we have relations between two variables (i.e. clouds usually are generated as a function of relative humidity)
Are the Model Results Usable? _Despite resolution issues and other sources of uncertainty, all GCMs agree with the general characteristics of climate change in the 21 st century: 1. All models indicate warming (but there is a range of the magnitude of warming) 2. All models indicate more warming over the high latitudes and over continental regions _All models do a decent job of simulating past (~1850) through today _Results are normally applicable on sub-continental scales (i.e. western Europe)
Top: Only greenhouse gas forcing Bottom: Greenhouse + Aerosol Forcing Why do the model runs with aerosol forcing show less projected warming?