greenhouse gas observations from space: why and how? - home - earth … · 2014-09-10 · michael...

Michael Buchwitz Institute of Environmental Physics (IUP)

ESA Earth Observation Summer School, ESRIN, 4-14 August 2014

Greenhouse gas observations from space: Why and how?

1 www.iup.uni-bremen.de

Greenhouse gas observations from space 1. Why and how ?

2. Results from ESA‘s GHG-CCI project

3. Proposed future mission CarbonSat

Overview Talks 1 - 3

2

Greenhouse gas observations from space: Why and how?

• Why ?

• … including at least a little bit of the most relevant background information …

• How ?

• From satellite radiances -> atmospheric GHG concentrations -> GHG surface fluxes (sources & sinks)

Overview Talk 1

3

Why ?

Greenhouse gas observations from space

4

„System Earth“

Source: http://energy.lbl.gov/AQ/smenon/images/earth_system.jpg (via IPCC)

Large and increasing human influences We are living in a new geological epoch (TBC), the

„Anthropocene“ (Crutzen, 2000)

A complex system with many positive and negative feedback cycles.

Outgoing long-wave radiation

Incoming solar radation

5

http://energy.lbl.gov/AQ/smenon/images/earth_system.jpg

http://energy.lbl.gov/AQ/smenon/images/earth_system.jpg

Greenhouse Effect

6 Trenberth, K. E., J. T. Fasullo, and J. Kiehl, 2009: Earth's global energy budget. Bull. Amer. Meteor. Soc., 90, No. 3, 311-324, doi: 10.1175/2008BAMS2634.1.

http://www.bis.gov.uk/go-science/climatescience/greenhouse-effect

1370 W/m2

340 W/m2 100 W/m2 240 W/m2

„Solar constant“

Climate Change: Observations

7

Source: IPCC 2013, AR5, Approved „Summary for Policy Makers“

Mean temperature increase (1880-2012): 0.85 [0.65 to 1.06] °C

Radiative Forcing

8 Source: IPCC 2013, AR5, Approved „Summary for Policy Makers“ 2.3 W/m2 [1.1-3.3] corresponds to

observed 0.85 oC [0.65-1.06]

Solar energy input and long-wave outgoing radiation

9

O3

CO2

H2O

Wavelength in 10-6 meter = µm

0.5 x10-6 meter

= 500 nm

15 x10-6 meter

= 15 µm

Solar Input Heat Output

Doubling CO2: Radiative transfer simulations

10

Source: pload.wikimedia.org/wikipedia/commons/9/9c/ModtranRadiativeForcingDoubleCO2.png

15 µm CO2 Band

Transparent „window“ to space

9.6 µm O3 H2O, CH4, …

H2O, …

+270C

-530C

Rule of thumb (neglecting feedbacks): ΔF = 5.3 ln(CO2-ratio=2) = 3.7 -> 3.7/3 = ~1.2 K = ΔT

260 K

240 K

S 240

L 236

CO2 x2

Ts = 15oC

S 240

L 240

Ts = 15oC

Climate sensitivity: Temperature change for doubling CO2:

Doubling?: Pre-industrial = 280 ppm x2 -> 560 ppm 400 ppm reached in May 2013 (= maximum of seasonal cycle, not yearly average)

„2 degree goal“: ~450 ppm should not be exceeded (Controversial !?: e.g. Hansen argues for < 350 ppm) 11

S 240

L 240

CO2 x2

Ts = 15+1.2 oC

S 240

L 240

CO2 x2 With feedbacks: H2O, íce-albedo,

clouds, ocean, …, ???

Ts = 15+(1.5-4.5) oC

(AR5 likely range equilibrium clim.sensit.) Houghton, 2004

Kohlenstoffkreislauf

12

GtC GtC/yr

Earth‘s breathing

13

Courtesy: D. Crisp (NASA/JPL), GEO-X Meeting, Geneva, 13 Januar 2014

Atmospheric CO2 2002 -2008

Carbon cycle: Sources and sinks

Emissions Atmospheric

growth

Ocean sink

Land sink

Le Quere et al., 2013

NOAA/Scripps CO2 Time series

15

Charles Keeling, 1958

Oil crisis 1973

El Nino 1997

Pinatubo 1992

The more accurate and the longer the observational time series, the more we can learn from analyzing the observations …

Observed Emissions and Emissions Scenarios

Emissions are on track for 3.2–5.4ºC “likely” increase in temperature above pre-industrial Large and sustained mitigation is required to keep below 2ºC

Linear interpolation is used between individual data points Source: Peters et al. 2012a; CDIAC Data; Global Carbon Project 2013

Emissions from fossil fuels and cement

16

RCP: Represenative Concentration Pathway; 8.5: RF(2100) = 8.5 W/m2

http://cdiac.ornl.gov/trends/emis/meth_reg.html

http://www.globalcarbonproject.org

Why bother ? Just a few degrees more !

-4oC

? +4oC

17

Ice & snow

Medieval warm period (Vikings in Greenland with cattle & sheep, etc.)

Major crop failures northern Europe, UK, …, „Great Famine“ ~1300

CO2 emissions -> Temperature change

Emitted until 2011: 531 (446-616) GtC

IPCC 2013, AR5 „Summary for Policy Makers“

18

Future: Large uncertainty, e.g., response

of terrestrial biosphere to changing climate ?

Natural CO2: Terrestrial C sinks

19

Houghton, Biologist, 2002: “Strangely, the difference between the net terrestrial sink and the emissions from land-use change suggests that there is a residual terrestrial sink, not well understood, that locked away as much as 3.0 PgC/yr during the last two decades. … The exact magnitude, location and cause of this residual terrestrial sink are uncertain, …”

Gurney et al., Nature, 2002

TransCom 3 regional CO2 flux inversions

Observartions: Very accurate but sparse

Information content sources & sinks (excluding fossil fluxes):

Large regions only (continents, ocean basins)

Large uncertainties (often +/- 100%)

Natural CO2 fluxes from in-situ (mostly surface) obs.

20

A priori land

Within model uncertainty

Inversions:

Left / right: different inversions

Mean flux x

Uncertainty reduction using satellite data - I

21

Rayner and O‘Brien, 2001

Natural CO2 fluxes from space?: • Yes ! If …

Precision < 2.5 ppm for monthly 8ox10o

Uncertainty reduction using satellite data - II

22

Hungershöfer et al., 2010

Weekly mean error reduction

Altitude sensitivity Prior uncertainty

Methane

23

Coal mining

Landfills

Termites

Wastewater

Wetlands Rice

Ruminants

Hydrates

Natural gas

Energy

Methane • Second most important

anthropogenic GHG (directly after CO2)

• Many anthropogenic and natural sources; large uncertainties

Kirschke et al., 2013

? ?

How will sources and sinks behave in a changing climate?

CO2 and CH4 sources and sinks: !! ??

25

Are the reported emissions correct?

How will today's CO2 sinks behave in a changing climate?

How will today's CH4 sources (e.g., wetlands) behave in a changing climate?

Will sinks turn into sources?

Will sources be amplified?

How much is emitted where, when and by what?

How much CO2 is absorbed by land and oceans? Where and when?

How strong are the various sources and sinks ?

Essential Climate Variable (ECV) Greenhouse Gases (GHG)

26

ECV GHG (GCOS-154*)): “Retrievals of greenhouse gases, such as CO2 and CH4, of sufficient quality to estimate regional sources and sinks.”

*) „SYSTEMATIC OBSERVATION REQUIREMENTS FOR SATELLITE-BASED DATA PRODUCTS FOR CLIMATE“

Reliable climate prediction requires a good understanding of the natural and anthropogenic (surface) sources and sinks of CO2 and CH4.

Important questions are, for example:

• Where are they ? • How strong are they ? • How do they respond to a changing climate ?

A better understanding requires appropriate global observations and (inverse) modelling.

CO2 and CH4 are the two most important anthropogenic greenhouse gases and increasing concentrations

result in global warming.

Observed and predicted temperature change (AR5)

Future?

Why ?

• The greenhouse gases (GHGs) carbon dioxide (CO2) and methane (CH4) are „Essential Climate Variables“ (ECVs)


27 (#) See Talk 2: GHG-CCI results

• Increasing atmospheric concentrations result in global warming

• Reliable prediction of the future climate of our planet requires a good understanding of their (variable) natural and anthropogenic sources and sinks

• Our understanding has large gaps and global satellite data help to improve our understanding, i.e., they help reducing uncertainties on GHG sources and sinks (#)

How ?


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Viewing Geometries

Satellite Observation Geometries

Nadir Occultation Limb

SCIAMACHY, AIRS, IASI, TES, GOSAT, OCO-2, CarbonSat, A-SCOPE, MERLIN,

ASCENDS, …

SCIAMACHY,

MIPAS, …

SCIAMACHY, ACE-FTS, …

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Measurement Techniques

Measurement Techniques

Active

SCIAMACHY,

GOSAT, OCO-2, CarbonSat, …

TOVS, IMG, AIRS, IASI, TES,

MIPAS, …

A-SCOPE, MERLIN,

ASCENDS, …

Passive

Solar Thermal Laser

Reflected solar (NIR/SWIR) vs thermal (TIR) Thermal emission NIR absorption

Passive Active

Sensitive to mid/upper

troposphere

Sensitive (also) to near-surface

GHG concentration

variations ->

Important to get source/sink

info

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Note:

32

In the following I will focus on • nadir observations in the • solar spectral region using • passive satellite observations

GHG-CCI project www.esa-ghg-cci.org

SCIAMACHY/ENVISAT

Global satellite observations Global information on near-surface CO2 & CH4

TANSO/GOSAT

Upper layer CO2 & CH4

IASI, MIPAS, SCIA/occ, AIRS, ACE-FTS, …

Global observations

Calibrated radiances Calibration (L 0-1)

Reference observations Validation

Inverse modelling

(L 2-4)

Improved information on GHG sources & sinks

Atmospheric GHG distributions

Retrieval (L 1-2)

33

SCIAMACHY SCIAMACHY on ENVISAT SCIAMACHY Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY

Nadir mode: Swath width: 960 km XCO2 & XCH4 from 1.6 & 0.76 µm bands Horizontal resolution: 30 x 60 km2

Tropospheric data products from SCIAMACHY/nadir

... and more.

35

Greenhouse gases via SCIAMACHY/ENVISAT

36

CO2 CH4

XCO2 = CO2 column / Air column

37

H L

CO2

O2

XCO2

XCO2 := CO2 column-averaged dry air mixing ratio (mole fraction)

Buchwitz et al., ACP, 2005

+/- 10% +/- 1.5%

XCO2 ? Counting molecules …

38 XCO2 := CO2 column-averaged dry air mixing ratio (mole fraction)

O2 Vertical Column

Buchwitz et al., 2008

XCO2 = CO2-Column / Air-Column

CO2 Vertical Column

Measurement principle - I

39

Measurement principle - II

40

Measurement principle - III

41

Light path issues

From: SCIAMACHY – Monitoring the changing Earth‘s atmosphere

42

SCIAMACHY nadir spectrum

Buchwitz, 2000; Schneising et al., 2008, 2009

Radiative Transfer

44

e.g., plane-parallel RTE

Change of radiance I, dI, along path ds due to sources (+εS) and/or losses (-εI).

SCIA: IUP-UB retrieval algorithms

45

• XCO2 & XCH4 • Focus on speed and data

volume • Tabulated RT • Least squares fitting • References:

• Buchwitz et al., 2000, 2005 • Heymann et al., 2012 • Schneising et al., 2011, 2012, 2013

Details see ATBDs at http://www.esa-ghg-cci.org/

• XCO2 • Focus on accuracy and

precision • Online RT • Optimal estimation • References:

• Reuter et al., 2010, 2011

WFM-DOAS (WFMD) BESD

46

Measured radiation -> CO2 emissions

Measured Radiation

Atmospheric CO2 or CH4

CO2 or CH4 Emissions A

B

C

Forward- Models

Transport-Chemistry-Model

Radiative-Transfer-Model

Inversion-Models

„Inversion“

„Retrieval“ =

„Inversion“

47

Inversion ? • Different methods

• (Nearly all are) Based on „adjusting“ model parameters until model data „optimally“ agree with the observations

• Requires sufficiently accurate and fast forward models

• Often based on „Bayesian Inference“ or „Optimal Estimation“

Thomas Bayes [beɪz] (~1701 - 1761). • English statistician,

philosopher and Presbyterian minister.

• Bayes‘ Theorem: he suggested using this theorem to update beliefs considering new knowledge. http://en.wikipedia.org/

Bayes‘ Theorem

𝑃𝑃 𝑋𝑋 𝑌𝑌 = 𝑃𝑃 𝑌𝑌 𝑋𝑋 𝑃𝑃(𝑋𝑋)

𝑃𝑃(𝑌𝑌)

P(X = atmos.CO2 | Y = radiation) P(X = CO2 emission | Y = atmos.CO2)

To be minimized cost function (Optimal Estimation (Rodgers, 2000)): + Gaussian statistics

48

Illustration

Y Radiation

or atmospheric CO2, …

X Atmospheric CO2, or CO2 emission, …

xi

yj

P(X, Y)

P(Y) = Σi P(Y|Xi) x P(Xi)

𝑃𝑃 𝑋𝑋 = 𝑥𝑥𝑖𝑖 𝑌𝑌 = 𝑦𝑦𝑗𝑗 = 𝑃𝑃 𝑌𝑌 = 𝑦𝑦𝑗𝑗 𝑋𝑋 = 𝑥𝑥𝑖𝑖 𝑃𝑃(𝑋𝑋 = 𝑥𝑥𝑖𝑖)∑ 𝑃𝑃 𝑌𝑌 = 𝑦𝑦𝑗𝑗 𝑋𝑋 = 𝑥𝑥𝑖𝑖 𝑃𝑃(𝑋𝑋 = 𝑥𝑥𝑖𝑖)𝑖𝑖

P(X)

P(Y)

49

Does God exist ?

http://www.colorado.edu/philosophy/vstenger/Briefs/Bayes.pdf

http://www.colorado.edu/philosophy/vstenger/Briefs/Bayes.pdf

50

Bayesian inference: Example: Monty Hall problem 1 2 3

3 closed doors

1 car 2 goats

p(C=1) = 1/3

A priori probabilities to win the car: p(C=i): p(C=1) = 1/3 p(C=2) = 1/3 p(C=3) = 1/3

What is the probability to win the car ?

Choose one of the doors. If you pick the right one, the car is yours.

51


p(C=1) = p(stay) = 1/3

52


p(C=1) = p(stay) = 1/3

I will now open one of the two remainig doors

53


p(C=1) = p(stay) = 1/3

p(C=2) = p(switch) = ???

stay or switch ?

Stay or switch ?

54


p(C=1) = p(stay) = 1/3

p(C=2 | ???) =

55


p(C=1) = p(stay) = 1/3

p(C=2 | D=3) = p(D=3 | C=2) x p(C=2)

p(D=3 | C=1) x p(C=1) + p(D=3 | C=2) x p(C=2) + p(D=3 | C=3) x p(C=3)

1/3

What is the probability that the car is behind door 2 (C=2) given that door 3 (D=3) has been opended

A priori probability

Probability that door 3 has been opended (D=3) given that the car is behind door 2 (C=2)

1.0

0.5 x 1/3 0.0 x 1/3 1.0 x 1/3 + +

56


p(C=1) = p(stay) = 1/3

p(switch) = 2/3

So you better switch as this doubles your chance to win the car.

Except if you want a goat …

Retrieval: Optimal Estimation (Rodgers, 2000)

57

CarbonSat: BESD/C algorithm

58

Via pre-processing: Surface albedo

VCF / SIF @ 755 nm Cirrus Optical Depth (COD)

SCIAMACHY / BESD: Example fit

Reuter et al., JGR 2011 59

Jacobian matrix (K): Example

Details: Buchwitz et al., AMT, 2013

Col

umns

of K

Wavelength 60



Col

umns

of K

Wavelength 61

Zoom into Vegetation Chlorophyll / Solar Induced Fluorescence (VCF / SIF) Jacobian: Spectral region with clear solar Fraunhofer lines for accurate VCF / SIF retrieval



Col

umns

of K

Wavelength 62

Zoom into Spectral Squeeze Jacobian



Col

umns

of K

Wavelength 63

Zoom into Water Vapor Jacobian



Col

umns

of K

Wavelength 64

Zoom into Albedo NIR Jacobian

One could say much more …

Retrieval algorithms: • DOAS (WFM-DOAS, IMAP-DOAS, …), …

• Full Physics (FP) versus Proxy (PR), …

Modelling & inverse modelling: • … Other topics: • …

65

Satellite XCO2 retrieval algorithms … From „First ever“ to „recent“



Bovensmann et al., 2010

O‘Dell et al., 2012

Butz et al., 2011

Reuter et al., 2010, 2011

Oshchepkov et al., 2008

Schneising et al., 2011, 2012, 2013, 2014 WFMD

WFMD

Remote-C

WFMD

ACOS

BESD

BESD/C

PPDF

BESD/C


Reuter et al., 2013 EMMA

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Satellite XCH4 retrieval algorithms …



Bovensmann et al., 2010

Butz et al., 2011

Schneising et al., 2011, 2012 WFMD

WFMD

Remote-C

WFMD BESD/C

Frankenberg et al., 2005 IMAP Parker et al., 2011

Schepers et al., 2012

UoL-FP/PR

Remote-C

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From „First ever“ to „recent“

Many thanks for your attention !

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greenhouse gas observations from space: why and how? - home - earth … · 2014-09-10 · michael...

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