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 CO 2 ; ◮ The Global Carbon Budget ◮ Means, variability and trends: An evolving story. ◮ Simple diagnostics and what they can tell us;

Long Time-scale: CO 2 from Vostok Core 300 ◮ Measurements of air 280 bubbles trapped in CO2 concentration (ppmv) long ice core 260 ◮ Highly smoothed; ◮ Show large 240 variability but 220 almost always below an equilibrium 200 around 280 ppm; ◮ Play amplifying role 180 -5•10 5 -4•10 5 -3•10 5 -2•10 5 -1•10 5 0 in glaciation cycles. year

Millennial time-scale, CO 2 from Law Dome ◮ Higher 330 accumulation core so less time but 320 CO2 concentration (ppm) multi-decadal 310 resolution; ◮ Relative stability 300 before 290 industrialization then rapid growth; 280 ◮ Can learn a bit from 270 the relationships 1000 1200 1400 1600 1800 2000 year between CO 2 and climate wiggles.

Atmospheric CO 2 400 390 ◮ Measurements 380 started by Dave Keeling at Mauna 370 Loa (Hawaii), 1957; 360 ppm ◮ Globally 350 representative; 340 ◮ Inexorable rise, even 330 acceleration. 320 1960 1970 1980 1990 2000 2010 year

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 of atmospheric CO 2 ; ◮ Called the Flying Carpet; ◮ Shows north-south gradient, larger seasonal cycle in northern hemisphere and interannual variability;

Global Carbon Budget ◮ Growth is derivative of concentration (very well known); 10 ◮ Fossil from economic 8 6 statistics; 4 ◮ Land use controversial, flux(pgCy) 2 either on-ground or 0 satellite-based; 2 ◮ Ocean mixture of models 4 6 and proxy measurements; 1960 1970 1980 1990 2000 2010 year growth = fos + luc − ocean − terrestr ◮ Terrestrial is the residual ; ◮ 2011 largest uptake yet seen.

So What Causes the Increase? 0 -10 -20 delta O2 -30 -40 -50 -60 1980 1985 1990 1995 year Trends in radiocarbon, Stuiver Trend of and Quay, 1981. atmospheric oxygen from Cape Grim, indicates imbalance of oxidation over reduction. Langenfelds 1999.

How do we Infer Terrestrial Flux? Top Down Bottom Up ◮ Measure quantities which integrate the results of all ◮ Measure or model fluxes fluxes e.g. CO 2 and its at points; isotopes, COS, O 2 ; ◮ Points are almost ◮ Work backwards from independent; space-time gradients to ◮ Sum modelled points or infer variations in fluxes; extrapolate ◮ “Working backwards” measurements; (inversion) introduces its ◮ Always involves a model; own errors; ◮ Works best at small ◮ Works best at larte scales; scales. ◮ There is a gap between optimal scales for each.

A More Global Picture ◮ Time-latitude plot of atmospheric CO 2 ; ◮ 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 ocean ; ◮ 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 ◮ Growth is derivative of concentration (very well known); 10 ◮ Fossil from economic 8 6 statistics; 4 ◮ Land use controversial, flux(pgCy) 2 either on-ground or 0 satellite-based; 2 ◮ Ocean mixture of models 4 6 and proxy measurements; 1960 1970 1980 1990 2000 2010 year growth = fos + luc − ocean − terrestr ◮ Terrestrial is the residual ; ◮ 2011 largest uptake yet seen.

Global Growth Rates 10 8 6 PgC/y 4 2 0 1960 1970 1980 1990 2000 2010 year 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; 5 ◮ Airborne fraction model ∂ c 4 ∂ t = α A ◮ 1st-order response model 3 PgC/y ocean + terrestrial = 2 β ( c − c 0 ) ◮ A total anthropogenic flux 1 (fossil + landuse) 0 1960 1970 1980 1990 2000 2010 year ◮ Equivalent if anthropogenic Fit of both models, solid line is flux described by single observed growth rate, dotted is exponential; airborne fraction model and ◮ Can fit either model with dashed is first-order. simple statistics, including uncertainty.

Residual Growth Rates 3 2 ◮ Philosophical preference for 1st-order; 1 PgC/y ◮ 0th order does as well; 0 ◮ Amplitude of residuals 1 roughly doubles over 2 period; 3 1960 1970 1980 1990 2000 2010 year ◮ No evidence of long-term Residuals (GCP − model) departure from linearity; from both growth-rate models.

The Pause 10 3 2 8 1 6 PgC/y PgC/y 0 4 1 2 2 0 3 1960 1970 1980 1990 2000 2010 1960 1970 1980 1990 2000 2010 year year Anthropogenic inputs (red) Residuals (GCP − model) and atmospheric growth from both growth-rate rate (black) from www. models. globalcarbonproject. org 2013. Anthropogenic inputs include both fossil and land-use.

Do we have an increasing response? 3 ◮ Mean of residuals after 2 2002 is significantly 1 negative; PgC/y 0 ◮ Fitted trend after 2002 is significantly negative 1 (< 5% probability by 2 accident); 3 1960 1970 1980 1990 2000 2010 year ◮ Note that 2011 does Residuals (GCP − model) not stand out as from both growth-rate anomaly. models.

Comparing observed and Inverted Growth Rates 0 1 ◮ Good agreement for 2 both short and flux(gtC/y) long-term 3 variability; 4 5 ◮ Necessary but not 6 sufficient condition 1995 2000 2005 2010 year for good regional Net uptake from GCP (black) and fits. from the inversion (blue). Means over the period have been adjusted to be equal.

Regional Land and Ocean Uptakes 4 4 4 3 3 3 2 2 2 1 1 1 pgC/yr pgC/yr pgC/yr 0 0 0 1 1 1 2 2 2 3 3 3 1995 2000 2005 2010 1995 2000 2005 2010 1995 2000 2005 2010 year year year 4 4 4 3 3 3 2 2 2 1 1 1 pgC/yr pgC/yr pgC/yr 0 0 0 1 1 1 2 2 2 3 3 3 1995 2000 2005 2010 1995 2000 2005 2010 1995 2000 2005 2010 year year year

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 0.005 0.012 0.016 0.031 LPJ Northern − 0.010 0.020 − 0.014 0.055 Inverse tropical − 0.013 0.008 − 0.002 0.021 LPJ Tropics 0.020 0.055 0.038 0.140 southern land 0.010 0.007 0.014 0.017 LPJ South − 0.004 0.020 0.027 0.055