The challenges of climate change Lecture 3 – Forcings and Feedback

Outline of course Do we understand the science behind climate change? Historical climate Basics of climate science Modeling the climate Understanding the uncertainty What are the implications of climate change? Biological/environmental implications Economic political implications What human actions can be taken to address climate change? Individual action Political action Technology Economic action Sources of inertia

A greenhouse Energy in = Energy out Energy in = 2 Energy out E ½ E Greenhouse gas E E ½ E in-coming Re-radiated E Earth Surface

Radiative forcing Imbalance in incoming and outgoing radiation Top of troposphere 240 240 240 236 240 240 (W/m2) Pre-industrial CO2 = 280 ppm, now = 400 ppm x2 CO2 T=15 oC T=15 oC T=15+1.5 oC Earth surface Radiative forcing arises from all greenhouse gases, and can be assessed via global warming potential

Land Use

Aerosol forcing Aerosols are particulate matter in the atmosphere – natural (e.g. volcanoes, ice, sand) and anthropogenic (carbon etc). Can create two types of forcing (not feedback). DIRECT Global dimming (negative, 2 W/m2) INDIRECT Changes in cloud chemistry, albedo and lifetime (negative 1.5 W/m2)

Climate Sensitivity Change in temperature for a given radiative forcing G0= Change in temperature / Change in forcing = 0.27 oC/W/m2

Feedback Change Positive Negative Change Positive Negative Note: Feedback can be unstable

Daisyworld

Daisyworld Black daisies like it cool

Daisyworld Black daisies like it cool White daisies like the heat

Daisyworld Black daisies like it cool White daisies like the heat At early times the star is faint (like the sun)

Daisyworld Black daisies like it cool White daisies like the heat At early times the star is faint (like the sun) Black daisies dominate, albedo is low, and temperature rises.

Daisyworld Black daisies like it cool White daisies like the heat At early times the star is faint (like the sun) Black daisies dominate, albedo is low, and temperature rises. White daisies begin to grow, albedo rises

Daisyworld Black daisies like it cool White daisies like the heat At early times the star is faint (like the sun) Black daisies dominate, albedo is low, and temperature rises. White daisies begin to grow, albedo rises. As planet gets much hotter, white daisies dominate.

Daisyworld No daisies With daisies Temperature Time

Ca 6m sleq possibly vulnerable Ca 70m sleq total Ca 6m sleq possibly vulnerable Flemming et al. 1998

Blackbody feedback Peak proportional to Temperature Energy out proportional to T4 Note: T in Kelvin

Blackbody feedback Constant heat input (e.g. boiling a pan of water) Negative feedback Temperature Time Higher temperatures => Greater energy loss (T4)

Water Vapour Feedback Water vapour is dominant greenhouse gas Increased water vapour increases absorption in IR Causes additional increases in temperature Water saturation (mid troposphere) <-Simulation Observed->

Clouds? Complex and controversial Clouds are white, they reflect sunlight (negative feedback) Clouds have high humidity, so lots of water vapour (positive feedback) Probably a negative feedback, but level of scientific understanding still poor (but improving, see IPCC AR5).

Figure TS.5 Radiative Forcings IPCC AR4 2007

IPCC AR5 2013

“Real” Climate Sensitivity No feedback With feedback

Radiative forcing Imbalance in incoming and outgoing radiation Top of troposphere 240 240 240 236 240 240 240 240 With feedback x2 CO2 T=15 oC T=15 oC T=15+1.2 oC T=15+2.5 oC Earth surface Pre-industrial CO2 = 280 ppm, now = 400 ppm

The scary stuff – non-linear feedback Shutting down of the North Atlantic Thermohaline circulation North atlantic surface temperature salinity

Ocean Circulations

The younger dryas

Avoiding “non-linear” events The risk of irreversible change increases with temperature rises Vulnerability of ice sheets increases Larger degree of permafrost melting Breakdown of biomass in rainforests Smaller rises minimize this risk, 2 degrees is thought to be reasonable (450 ppm CO2) but there is still much uncertainty (week 4).

Conclusions Detailed measurements enable the degree of imbalance between incoming and outgoing radiation from various physical processes to be calculated as a radiative forcing Anthropogenic changes are amplified by feedbacks, which makes climate twice as sensitive to changes as might otherwise be expected. Potential for major, and irreversible (on the short term) changes exist.

The challenges of climate change Lecture 4 – Modeling the Climate

Weather is not climate Daily Express 2013 Daily Express (yesterday)

Ocean Atmosphere General Circulation Models (OAGCM) AIM: To enable projections of future climate

What’s in a model Basic physics Conservation laws Equations of state Transport of energy via convection/radiation Moist processes (evaporation/condensation etc) Geography/resolution Ab initio Parameterization

State of art ca 1997 Major Volcanos -> Major volcanic eruptions are a visible and predictable perturbation on the climate.

Climate Weather

State of the art ~today

State of the art ~today Models are highly advanced (e.g. GEOS-5) BUT still fail to match some detailed measurements ……These errors include: too strong surface wind stress in high latitudes; too strong cloud radiative forcing in low latitudes, and too weak cloud radiative forcing in high latitudes; errors in precipitation typical of most state-of-the-art climate models, e.g.,a strong double Inter-Tropical Convergence Zone (ITCZ). (Vikhliaev et al. GEOS-5) http://gmao.gsfc.nasa.gov/GEOS/geos5/geos5_research/CTB_seminar_11_2010.php

“Greenhouse gas forcing has very likely [90%] caused most “Warming of the climate is unequivocal”, “It is extremely likely that human influence has been the dominant cause of the observed warming” IPCC 2013 “Greenhouse gas forcing has very likely [90%] caused most of the observed global warming over the last 50 years.” IPCC 2007 ….likely [67%].. IPCC 2001 IPC 2007 Figure TS.23. (a) Global mean surface temperature anomalies relative to the period 1901 to 1950, as observed (black line) and as obtained from simulations with both anthropogenic and natural forcings. The thick red curve shows the multi-model ensemble mean and the thin lighter red curves show the individual simulations. Vertical grey lines indicate the timing of major volcanic events. (b) As in (a), except that the simulated global mean temperature anomalies are for natural forcings only. The thick blue curve shows the multi-model ensemble mean and the thin lighter blue curves show individual simulations. Each simulation was sampled so that coverage corresponds to that of the observations. {Figure 9.5}

Inevitable Problems of projection Even with a perfect model: Anthropogenic changes in future climate depend on human activity – need different scenarios (SRES) Some natural variations (e.g. volcanoes) are unpredicatable, so can’t be easily folded in.

Potentially soluble problems with projection Garbage in = Garbage out (GIGO) Real world is complex Geography Ocean cycles (El Nino etc) Real physics is complicated and not all well understood. Water Radiative transfer

Special Report on Emissions Scenarios B2 Population peaks mid century. A1: technology-led economy, F fossil fuels vs ( B “balanced” ) vs T non-fossil fuelled. B1: info & service economy; sustainability & global sol’ns. Population continues to increase. A2: very heterogeneous world (“business as usual”) B2: lower growth rate; emphasis on local solutions (smart but laissez-faire) not predictions, but a range of plausible assumptions

Figure TS.28 IPCC 2007: Scenario -> OAGCM -> Climate prediction

IPCC 2007

Figure TS.29. Decadal mean continental surface temperature anomalies (°C) in observations and simulations for the period 1906 to 2005 and in projections for 2001 to 2050. Anomalies are calculated from the 1901 to 1950 average. The black lines represent the observations and the pink and blue bands show simulated average temperature anomalies as in Figure TS.22 for the 20th century (i.e., pink includes anthropogenic and natural forcings and blue includes only natural forcings). The yellow shading represents the 5th to 95th percentile range of projected changes according to the SRES A1B emissions scenario. The green bar denotes the 5th to 95th percentile range of decadal mean anomalies from the 20th-century simulations with only natural forcings (i.e., a measure of the natural decadal variability). For the observed part of these graphs, the decadal averages are centred on calendar decade boundaries (i.e., the last point is at 2000 for 1996 to 2005), whereas for the future period they are centred on calendar decade mid-points (i.e., the first point is at 2005 for 2001 to 2010). To construct the ranges, all simulations from the set of models involved were considered independent realisations of the possible evolution of the climate given the forcings applied. This involved 58 simulations from 14 models for the red curve, 19 simulations from 5 models (a subset of the 14) for the blue curve and green bar and 47 simulations from 18 models for the yellow curve. {FAQ 9.2.1, Figure 1 and Box 11.1, Figure 1}

The last 20 years IPCC 2013

Hallmarks of real warming Carbon dioxide and other greenhouse gases can have their radiative forcing directly measured. Stratospheric cooling, more heat is being returned to Earth than escapes. The re-radiated IR emission has been directly observed. Models only re-create recent past temperature trends with the addition of anthropogenic forcing Nights are warming faster than days The ocean is warming from the top down

Not only global warming Sea level rises – loss of habitat, fish spawning grounds etc. CO2 absorbed in the ocean causes acidification More on implications next lecture.

Think about how you might now answer these critics Doubting voices Massive, non-anthropogenic climate change has occurred in the past, and will happen in the future. Human activity is dwarfed by natural processes which render the impact of e.g. fossil fuel burning on global climate negligible. Evidence for recent warming depends critically on the data and time range chosen. There is insufficient evidence to conclude that anthropogenic global warming is occurring. Think about how you might now answer these critics

Justifiable concerns? Statistical and systematic errors on direct measurement Baselines for temperature proxies Attribution Past performance is not a good guide to future return

Real data Measurements aren’t perfect………. Thermometers Statistical errors affect the accuracy to which the thermometer can be read – inevitable, and act in both directions. Systematic errors reflect additional sources of uncertainty, and often act in a single direction

Temperature proxies

Natural variability

Simple temperature records Strongly dependent on quality of data, and local effects (note the units of the x-axis are standard deviations, not degrees) http://www.giss.nasa.gov/research/briefs/hansen_17/dice.gif

IPCC approach Note that improved treatment of uncertainty is a “key goal” of AR5

Attribution A warming record does not attribute the cause