The Role of the Terrestrial Biosphere in the Global Carbon Cycle - - PowerPoint PPT Presentation

The Role of the Terrestrial Biosphere in the Global Carbon Cycle

Peter Rayner June 18, 2015

Overall Outline

◮ The Role of the Terrestrial Biosphere in the Global

Carbon Cycle;

◮ Modelling the Terrestrial Biosphere; ◮ Climate/carbon-cycle Feedbacks.

Outline of this Lecture

◮ A brief tour of atmospheric CO2; ◮ The Global Carbon Budget ◮ Means, variability and trends: An evolving story. ◮ Simple diagnostics and what they can tell us;

Long Time-scale: CO2 from Vostok Core

• 5•105 -4•105 -3•105 -2•105 -1•105

year 180 200 220 240 260 280 300 CO2 concentration (ppmv) ◮ Measurements of air

bubbles trapped in long ice core

◮ Highly smoothed; ◮ Show large

variability but almost always below an equilibrium around 280 ppm;

◮ Play amplifying role

in glaciation cycles.

Millennial time-scale, CO2 from Law Dome

1000 1200 1400 1600 1800 2000 year 270 280 290 300 310 320 330 CO2 concentration (ppm)

◮ Higher

accumulation core so less time but multi-decadal resolution;

◮ Relative stability

before industrialization then rapid growth;

◮ Can learn a bit from

the relationships between CO2 and climate wiggles.

Atmospheric CO2

1960 1970 1980 1990 2000 2010 year 320 330 340 350 360 370 380 390 400 ppm

◮ Measurements

started by Dave Keeling at Mauna Loa (Hawaii), 1957;

◮ Globally

representative;

◮ Inexorable rise, even

acceleration.

Network of Measurements

◮ Network started out to test whether Keeling’s

measurements were globally representative so sampled “clean air”;

◮ Now used to detect regional or local sources and sinks; ◮ Network growing explosively with recent drop in fixed and

running cost;

◮ Now supplemented by satellites and airborne

measurements.

A More Global Picture

◮ Time-latitude plot

• f atmospheric CO2;

◮ Called the Flying

Carpet;

◮ Shows north-south

gradient, larger seasonal cycle in northern hemisphere and interannual variability;

Global Carbon Budget

1960 1970 1980 1990 2000 2010 year 6 4 2 2 4 6 8 10 flux(pgCy)

growth = fos+luc−ocean−terrestr

◮ Growth is derivative of

concentration (very well known);

◮ Fossil from economic

statistics;

◮ Land use controversial,

either on-ground or satellite-based;

◮ Ocean mixture of models

and proxy measurements;

◮ Terrestrial is the residual; ◮ 2011 largest uptake yet

seen.

So What Causes the Increase?

1980 1985 1990 1995 year

• 60
• 50
• 40
• 30
• 20
• 10

delta O2

Trend of atmospheric oxygen from Cape Grim, indicates imbalance

• f oxidation over

reduction. Langenfelds 1999. Trends in radiocarbon, Stuiver and Quay, 1981.

How do we Infer Terrestrial Flux?

Bottom Up

◮ Measure or model fluxes

at points;

◮ Points are almost

independent;

◮ Sum modelled points or

extrapolate measurements;

◮ Always involves a model; ◮ Works best at small

scales. Top Down

◮ Measure quantities which

integrate the results of all fluxes e.g. CO2 and its isotopes, COS, O2;

◮ Work backwards from

space-time gradients to infer variations in fluxes;

◮ “Working backwards”

(inversion) introduces its

• wn errors;

◮ Works best at larte scales; ◮ There is a gap between

• ptimal scales for each.

A More Global Picture

◮ Time-latitude plot

• f atmospheric CO2;

◮ Called the Flying

Carpet;

◮ Shows north-south

gradient, larger seasonal cycle in northern hemisphere and interannual variability;

Discovery of the Terrestrial Sink

growth = fos + luc − ocean − terrestr

◮ 1980s we could measure growth and estimate fos and

• cean;

◮ They didn’t balance, there was an extra sink; ◮ Much argument: Perhaps ocean was wrong or perhaps

terrestr played a role, if so what and where?

◮ Still sometimes called the “missing sink” although we

found it decades ago.

Atmospheric Inversions in One Slide

◮ Use concentration measurements and atmospheric flow to

back calculate surface sources/sinks (fluxes);

◮ Start with first guess of fluxes; ◮ Insert into atmospheric model and compare

concentrations with observed;

◮ Statistical techniques optimally adjust fluxes to improve

match to concentration observations;

◮ Use prior constraint to include a priori information.

Large-scale Gradients

a: Meridional gradient of obser- vational CO2 values and the un- certainty assigned to them in the inversion. b: Model mean con- centrations for the sum of the three background fluxes minus the observational CO2 values (cir- cles) and the model mean con- centrations after inverting for re- gional fluxes minus the observa- tional CO2 values (X’s). More up- take in the north and less uptake in south.

atmospheric Evidence of Terrestrial Variability

Global Carbon Budget

1960 1970 1980 1990 2000 2010 year 6 4 2 2 4 6 8 10 flux(pgCy)

growth = fos+luc−ocean−terrestr

◮ Growth is derivative of

concentration (very well known);

◮ Fossil from economic

statistics;

◮ Land use controversial,

either on-ground or satellite-based;

◮ Ocean mixture of models

and proxy measurements;

◮ Terrestrial is the residual; ◮ 2011 largest uptake yet

seen.

Global Growth Rates

1960 1970 1980 1990 2000 2010 year 2 4 6 8 10 PgC/y

Anthropogenic inputs (red) and atmospheric growth rate (black) from www.globalcarbonproject.org 2013. Anthropogenic inputs include both fossil and land-use.

Two Models for Atmospheric Growth Rate

◮ Both go back to Dave

Keeling;

◮ Airborne fraction model ∂c ∂t = αA ◮ 1st-order response model

• cean + terrestrial =

β(c − c0)

◮ A total anthropogenic flux

(fossil + landuse)

◮ Equivalent if anthropogenic

flux described by single exponential;

◮ Can fit either model with

simple statistics, including uncertainty.

1960 1970 1980 1990 2000 2010 year 1 2 3 4 5 PgC/y

Fit of both models, solid line is

• bserved growth rate, dotted is

airborne fraction model and dashed is first-order.

Residual Growth Rates

1960 1970 1980 1990 2000 2010 year 3 2 1 1 2 3 PgC/y

Residuals (GCP − model) from both growth-rate models.

◮ Philosophical preference

for 1st-order;

◮ 0th order does as well; ◮ Amplitude of residuals

roughly doubles over period;

◮ No evidence of long-term

departure from linearity;

The Pause

1960 1970 1980 1990 2000 2010 year 2 4 6 8 10 PgC/y

Anthropogenic inputs (red) and atmospheric growth rate (black) from www. globalcarbonproject.

• rg 2013. Anthropogenic

inputs include both fossil and land-use.

1960 1970 1980 1990 2000 2010 year 3 2 1 1 2 3 PgC/y

Residuals (GCP − model) from both growth-rate models.

Do we have an increasing response?

1960 1970 1980 1990 2000 2010 year 3 2 1 1 2 3 PgC/y

Residuals (GCP − model) from both growth-rate models.

◮ Mean of residuals after

2002 is significantly negative;

◮ Fitted trend after 2002

is significantly negative (< 5% probability by accident);

◮ Note that 2011 does

not stand out as anomaly.

Comparing observed and Inverted Growth Rates

1995 2000 2005 2010 year 6 5 4 3 2 1 flux(gtC/y)

Net uptake from GCP (black) and from the inversion (blue). Means

• ver the period have been adjusted

to be equal.

◮ Good agreement for

both short and long-term variability;

◮ Necessary but not

sufficient condition for good regional fits.

Regional Land and Ocean Uptakes

1995 2000 2005 2010 year 3 2 1 1 2 3 4 pgC/yr 1995 2000 2005 2010 year 3 2 1 1 2 3 4 pgC/yr 1995 2000 2005 2010 year 3 2 1 1 2 3 4 pgC/yr 1995 2000 2005 2010 year 3 2 1 1 2 3 4 pgC/yr 1995 2000 2005 2010 year 3 2 1 1 2 3 4 pgC/yr 1995 2000 2005 2010 year 3 2 1 1 2 3 4 pgC/yr

Summarizing Regional First-order Responses

Flux 1992–2012 2002–2012 β(y−1) ±(yr−1) β(y−1) ±(y−1) northern land 0.016 0.005 0.031 0.012 northern ocean 0.002 0.002 0.001 0.005 tropical land −0.013 0.008 −0.002 0.021 tropical ocean 0.001 0.003 0.002 0.007 southern land 0.010 0.007 0.014 0.017 southern ocean 0.001 0.003 0.011 0.008

◮ Little response in ocean anywhere; ◮ Strong and increasing positive response in northern

hemisphere;

◮ Negative response in tropics but weakening; ◮ Tropics and southern hemisphere hard to distinguish (not

enough measurements);

◮ Tropical response dependent on trends in LUC.

More on the Northern Extratropics

Flux 1992–2012 2002–2012 β(y−1) ±(yr−1) β(y−1) ±(y−1) Northern GSNF 0.015 0.028 0.030 0.070 Northern QSNF −0.000 0.009 −0.002 0.024 Northern max 0.016 0.027 0.035 0.067

◮ Can divide annual cycle into uptake and eflux periods; ◮ GSNF = integrated uptake and QSNF = integrated eflux; ◮ See strong response in GSNF but not QSNF so increased

uptake not balanced by increased eflux;

◮ Increased GSNF similar to increased max uptake

suggesting strength rather than length of growing season.

So, can we Model Regional Response?

Flux 1992–2012 2002–2012 β(y−1) ±(yr−1) β(y−1) ±(y−1) Inverse northern 0.016 0.005 0.031 0.012 LPJ Northern −0.010 0.020 −0.014 0.055 Inverse tropical −0.013 0.008 −0.002 0.021 LPJ Tropics 0.038 0.020 0.140 0.055 southern land 0.010 0.007 0.014 0.017 LPJ South −0.004 0.020 0.027 0.055

Conclusions

◮ Atmospheric data shows that CO2 growth driven by fossil

fuel

◮ Atmospheric data suggests a large terrestrial sink,

probably in the northern extratropics and large interannual variability, mainly in the tropics;

◮ The sink appears to be increasing most likely due to

increased productivity in northern summers;

◮ Models seem to match the responses globally but not

with correct regional attribution.