Climate Attribution, Detection, and Future Projections: Key Concepts in Climate Science

Fingerprinting

Using theory to predict signatures/fingerprints we should see for various climate drivers and examining observations to confirm/deny hypothesis.

Empirical / Statistical Analysis

Using math model with observations to estimate response to various climate forcings; easiest to implement but can miss factors.

Climate Modelling

Natural only vs natural + anthropogenic model runs; allows comparison between human and natural effects.

Rising tropopause

Pattern consistent with greenhouse gases, sun, volcanoes.

Land warming faster than oceans

Consistent with greenhouse gases and sun.

Carbon dioxide (CO₂)

By far the largest contributor, causing about +2.3 W/m² of forcing since preindustrial times.

Other well-mixed greenhouse gases

CH₄, N₂O, halogens also add warming, totaling roughly +1.2 W/m² combined.

Positive bars

Energy gain = warming influence.

Aerosols

Tiny airborne particles that create negative forcing by reflecting sunlight and increasing cloud brightness.

Negative bars

Energy loss = cooling influence.

Total effective radiative forcing

When all are combined, it is positive, meaning the Earth's energy balance is tilted toward warming.

Main driver of warming

CO₂ and other greenhouse gases.

Partial offset

Aerosols and albedo changes (cooling).

Total Anthropogenic bar

Shows that human-caused forcing is overwhelmingly responsible for modern climate change, adding roughly +3 W/m² of warming influence.

General Circulation Models (GCM)

Uses equations to stimulate energy, fluid and mass exchanges and interactions throughout earth systems.

GCMs

Analogous to long-term weather models; months to years to run.

Modern GCMs

Adjusted to better match complex physics of the atmosphere.

Boundary conditions in GCM

GCMs require boundary conditions and run without changes until they are stable.

Ensemble of models

Modelling groups do the same scenarios with their models to produce an ensemble of models.

Best estimate of warming since 1850

100% of warming is due to human activity (+1.3ºC).

Human emissions of aerosols

Mask some of the effects of GHG warming.

Climate Sensitivity

Measure tells us how sensitive climate is to a change in radiative forcing.

Higher Sensitivity

Means more change in climate.

Lower Sensitivity

Means less change in climate.

Global Temperature Response

Usually expressed as response to a change in radiative forcing.

IPCC

Presents climate sensitivity as response to a doubling of preindustrial GHG forcing (about +3.6 w/m2).

Transient Climate Response (TCR)

Measure of the shorter-term response to a change in radiative forcing, only includes faster climate feedbacks.

TCR Calculation

Originally calculated as change in global temperature for a 20-year period at doubling of GHG forcing.

Recent TCR Studies

Calculate it by dividing the observed change in global temperature by change in total radiative forcing over the same period.

TCR Range

IPCC AR5 gives a likely TCR range of ~0.27ºC to ~0.69ºC per w/m2.

Earth's Energy Imbalance

Measured as 0.99 W/m2.

Effective Radiating Temperature

Temperature at which a system radiates away as much energy as it receives.

Equilibrium

Energy in = energy out.

Enhanced Greenhouse Effect

Energy imbalance: less energy leaves than enters.

Global Temperature Change

Global temperature change so far is about 1.3ºC.

Committed Warming

Our TCR estimate is 0.55, therefore ~0.55ºC of warming has already been committed.

Ongoing Increase in Radiative Forcing

About +0.57 per decade.

Paris Agreement

Holding the increase in the global average temperature to well below 2ºC above pre-industrial levels.

Unavoidable Warming

Some additional warming (~0.5°C) is effectively unavoidable.

Total Warming Plausibility

Meaning ~1.8°C total is very plausible even under strong mitigation.

Temporary Overshoot

Holding to 1.5°C now likely requires temporary overshoot and large-scale carbon removal later in the century.

Zero Emission Commitment (ZEC)

Refers to how much warming we are 'committed to' after we reach net zero emissions.

Warming follows cumulative CO₂

Rising emissions lead to both CO₂ and temperature increases.

Temperature plateaus

Occurs when emissions stop (ZEC phase), CO₂ stabilizes, and ocean feedbacks balance.

Long term warming

Slight drift up or down depending on model; warming is effectively locked in for centuries.

Change in Temperature after Net Zero in Climate Models (ZEC)

Most models cluster near zero, meaning after CO₂ emissions stop, global temperature remains roughly stable for centuries.

Earth's Zero Emissions Commitment (ZEC)

Close to 0°C ± 0.2°C.

Modelled Carbon and Climate Forcing after net zero

CO₂ doesn't vanish quickly; it lingers for centuries, slowly decreasing even after emissions stop.

Radiative forcing

Falls slowly because CO₂ removal is slow, meaning the planet continues to absorb more energy than it emits for decades.

Natural processes and climate

Always influenced climate, but at much slower rates.

Modern warming spike

Steeper and faster than any comparable event in at least the last 10,000 years.

Equilibrium Climate Sensitivity

Change in global surface temperature that occurs once medium to long term feedback processes reach equilibrium.

IPCC AR5 ECS range

Gives likely ECS range of 1.5ºC to 4.5ºC for a doubling of GHG forcing.

Net zero commitment

One way of stimulating the future climate.

Standard emission scenarios via CMIP

Historical climate model runs can use observed GHG, aerosol concentrations.

Input scenarios

Consider predicted fossil fuel usage, mitigation strategies, and international cooperation.

RCP Model Scenarios

Only 4 RCP: 2.6, 4.5, 6.0, 8.5.

RCP numbers

Signify radiative forcing for this scenario.

RCP scenarios

Run to at least 2100 AD, ranging from negative emissions (2.6) to burning most fossil fuels (8.5).

Core idea of climate prediction

Predicting climate = (future forcing) + (estimate of sensitivity).

What controls emissions?

A question regarding the factors influencing emissions.

IPAT

I = P x A x T

I

GHG emissions

P

Population

A

Affluence (GDP per person)

T

GHG intensity (emissions per $GDP)

Split T

T = EI x CI

EI

Energy intensity = energy per $GDP (J/$)

CI

Carbon intensity = CO₂ per energy (CO₂/J)

GtC to GtCO₂ conversion

Multiply by 3.67 (44/12)

Population change since 1960

Population ↑ sharply (7.8B by mid-2020; +200k/day)

Affluence change since 1960

Affluence (GDP/person) ↑ (global growth)

EI change since 1960

EI ↓ (efficiency gains; structural shift to services; LEDs, etc.)

CI change since 1960

CI ↓ to ~2000 (coal → gas), ↑ in 2000s (coal surge in China), then ↓ in 2010s (gas displacing coal)

Net emissions change

Emissions ≈ tripled 1960→2018 because PPP and AAA rose faster than EI & CI fell

SSP1

Sustainability: greener, equitable, slower pop growth, fast CI drop

SSP2

Middle of the road: historical trends continue

SSP3

Regional rivalry: fragmented, slower tech, high CI, lower affluence, higher pop in poorer regions

SSP4

Inequality: divided world but rapid low-CI tech for elites

SSP5

Fossil-fueled development: rich & fast growth but fossil-heavy (high CI)

Radiative forcing suffix

Suffix = radiative forcing in 2100 (W/m²)

Common SSP scenarios

SSP1-26, SSP2-45, SSP3-70, SSP5-85 (≈ successors to RCP2.6, 4.5, 8.5)

CO₂ and forcing relationship

Feed scenarios into carbon-cycle models ⇒ CO₂ concentrations ⇒ radiative forcing

CO₂'s role in future forcing growth

CO₂ dominates future forcing growth due to long lifetime (centuries) and accumulation

Temperature projections near-term

Near-term similarity across scenarios until ~2040-2050 (CO₂ stock dominates)

2100 warming projections

SSP1-26: ~+2.0 °C (~+1 °C above 2010s), SSP2-45: mid-range, SSP3-70: higher, SSP5-85: ~+5.5 °C (~+4.5 °C above 2010s)

Irreversibility beyond 2100

Even if emissions stop abruptly, CO₂ declines slowly (centuries-millennia)

Temperature persistence

Temperatures remain elevated for ~≥1000 years due to persistent elevated CO₂, ocean heat capacity, slow feedbacks (ice sheets, etc.)

Weather predictability

Weather: initial-value problem (needs today's exact state) → predictability ~days

Climate predictability

Climate: boundary-value problem (needs forcing) → statistics predictable decades+