lec 23: Modelling Climate Change

Question 1

predictive models

Answer 1

complex math-based computer programs which use past and present conditions to determine likely future conditions

predictive models are the most common models we use in climate science

Question 2

rational behind all these type of models

Answer 2

• what has happened in the past and is currently happening
• and why/how it happened
• will probably remain true for future events

system will remain similar over the time periods covered in the predictive model

Question 3

General Circulation Model (GCM)

Answer 3

utilizes mathematical models to simulate the circulation of energy and/or mass within and between the atmosphere and ocean

GCMs are incredibly complex and involve data collected by thousands of individuals over long time scales
(average model contains enough code for - 18 000 printed pages of text

output often in the petabytes of data (1 petabyte = 1024 TB)

requires very high computing power (this can sometime be a common limiting factor)

Question 4

variables included in GCMs

Answer 4

air temperature
vapour pressure
solar radiation
air pressure
albedo and more

mainly physics based energy and mass fluxes

Question 5

applying GCM to the terrestrial surface

Answer 5

land and atmosphere area is divided equally into a grid (divisions extend into the atmosphere)

The GCM will simulate climatic conditions per unit of area

Question 6

why are most GCMs very broad in scale -> 100 km2 grid size

Answer 6

they are designed to give averages for the planet, not details on a specific area

Question 7

what is the limitation to the global scale being useful for global predictions?

Answer 7

it misses potentially important local trends (i.e global warming trend in the oceans since 1970, but some areas have experienced a (yet unexplained) cooling trend)

Question 8

downscaling

Answer 8

global-scale data can be converted to local-scale data (downscaling)

Regional climate models (RCMs)

mathematical models used to convert data calibrated for global regions to apply to small-scale, local topography

note that this does not mean that the local models are more accurate
(simply that the data is now calibrated over a smaller geographic area)

Question 9

RCMs

Answer 9

RCMs are often how we make predictions about the impacts of climate change on the scale of a country or smaller

RCM-> not generating new data, changing the scale of existing data to a smaller unit area

Question 10

each grid is run as a separate simulation

Answer 10

decreasing grid size drastically increases the number of grids which must be simulated

Question 11

computing power limitation

Answer 11

computing power currently limits the total area that we can downscale

at one point, downscalling creates too many grids to simulate with current computing power

(downscaled maps are only of small regions, not the entire planet)

Question 12

uncertainty

Answer 12

all predictive models include some elements of uncertainty

uncertainty:
- the parts of a model for which we have insufficient data

• uncertainly can be known or unknown

known= we know we do not have the data
unknown= we don’t even realize we are missing the data MUCH more problematic

Question 13

common sources of uncertainty

Answer 13

frequently not possible to know all variables that should be part of a model

even if you know all the variables, can be difficult to determine how important each is

some sources of data do not stay the same over the time periods of the study (violate an assumption of predictive models)

Question 14

impact of uncertainty

Answer 14

greater degree of uncertainty = less accurate model

uncertainty in a model is acceptable (not a flaw)

but its important to know (or at least have an idea) of where your model has greater uncertainty (often we visually display our uncertainties in our projections )

Question 15

uncertainty in current GCMs

Answer 15

we have drastically decreased uncertainty in our GCMs over time (from the first models in the 1970 to today)

most uncertainties has been decreased by adding new global systems to our model (or better understanding known systems)

Question 16

current GCMs

Answer 16

most recent GCMs incorporate biogeochemical cycles
(transfer of chemicals between abiotic and biotic reservoirs)

new class of GCMs are called Earth System Models (ESMs)

Question 17

Intergrates assessment models (IAMs)

Answer 17

the final addition to GCMs has been the integration of predictions based on human activities

Question 18

Representative concentration pathway (RCP) projections

Answer 18

IAMs are responsible for the type of global temperature projections published by the IPCC

RCP models represent different projections for global climate change based on different future projections for CO2 emissions

Question 19

RCP 1.9

Answer 19

limits global warming to below 1.5C

not considered likely by most
often not even found in IPCC graphs anymore

Question 20

RCP 2.6

Answer 20

CO2 emissions starts declining by 2020 and go to 0 by 2100

currently considered the best case scenario

1.5-2C at 2100

Question 21

RCP 4.5

Answer 21

CO2 emissions peak in 2045 with peak oil
believed to be most likely with no mitigation efforts

2.5-3C at 2100

Question 22

RCP 8.5

Answer 22

CO2 emissions do not peak before 2100

business as usual scenario
5C by 2100

Question 23

reducing the scale of GCMs over time

Answer 23

greater computing power , more data

deceasing scale from 500 - 250km
requires 10X increase in computing power

Question 24

how to check your model to see if it’s accurate?

Answer 24

Hindcasting

Question 25

hindcasting

Answer 25

1. Using past environmental (pre-1850) conditions to calibrate a model
2. test your calibrated model to see if it can accurately “predict” current (2024) conditions (for a model calibrated with past data -> current conditions represent the future)
3. If your model can accurately “predict” conditions in 2024 (then will likely be accurate in predicting conditions past 2024 (in the future!))

Question 26

global systems poorly understood or still inherently difficult to model in the GCM framework

Answer 26

clouds
snow and ice formation in the atmosphere
jet stream
unpredictable rare events (major volcanic eruptions …)

Question 27

Clouds

Answer 27

cover 2/3 of the planet surface at any one time (but individual clouds can form and break down within minutes

depending on the location of the cloud (globally and within the atmosphere) (can either warm or cool the planet)

no relevant historical data on cloud formation to calibrate models (no proxy data and few historical direct observations)

cloud formation (condensation) and breakdown (evaporation n or precipitation) are frequently short term and localized events. Cannot be captured at the scale of most GCMs and even most RCMs

smallest RCMs are still -15km long (clouds are much smaller than. 15km some as small as 1km)

to attempt to model cloud systems , musts parameterized the dynamics of cloud formation and breakdown

Question 28

Parametrize

Answer 28

Average a variable over a large area as accurately as possible (use that average as a best estimate for a smaller area)

ex: rate of cloud formation averaged across 4 grids: average of 0.375 applied to all 4 grids

Question 29

convective-permitting models

Answer 29

simulate on an exceptionally small scale
few km wide

small enough to model most known models of cloud formation without the need for parameterization

currently very limited in scope
smaller scale produces MANY more grids to analyse than a larger scale
currently only available at the regional or country scale

better understanding of cloud formation
more accurate modelling of extreme rainfall events
more accurate modelling of changes in precipitation rates

Question 30

accuracy of GCMs

Answer 30

models are continuously updated as :
- we obtain more data concerning anthropocentric activities
- we gain a better understanding of global systems
- computing power improves

we have been modelling climate with a focus on anthropocentric activity since 1970s

modern 21st century models have minimized uncertainty as much as possible
(but are they really accurate?)

Question 31

are they accurate?

Answer 31

recent studies examining future predictions from older models (even as far back as the 1970s models)

vast majority have proven to have accurately predicted current global temperatures

older models were created with much less computing power and much less data
in some cases calculations were still conducted with punch cards