Requirements for monitoring methane from space:

What would we need to separate processes?

Julia Marshall, Tonatiuh Nuñez Ramirez The Climate Needs Space, Toulouse, 10-11 October, 2017

Max Planck Institutefor Biogeochemistry

The importance of methane

• second-most important greenhouse gas that is modified by human activities

IPCC, AR5, 2013

The importance of methane

• second-most important greenhouse gas that is modified by human activities

IPCC, AR5, 2013

Similar to the problem of CO2 in some ways…

• also tackled by top-down or inverse modelling

• also involves combined signals of anthropogenic and biogenic fluxes

• also requires a challengingly high measurement precision and accuracy

GHG-CCI URD v2.1, Buchwitz et al., 2016

Current measurement requirements

GHG-CCI URD v2.1, Buchwitz et al., 2016

Current measurement requirements

1 ppm/~400 ppm = .25%

GHG-CCI URD v2.1, Buchwitz et al., 2016

Current measurement requirements

1 ppm/~400 ppm = .25%

9 ppb/~1800 ppb = .5%

GHG-CCI URD v2.1, Buchwitz et al., 2016

Current measurement requirements

1 ppm/~400 ppm = .25%

9 ppb/~1800 ppb = .5%

0.2 ppm/~400 ppm = .05%

GHG-CCI URD v2.1, Buchwitz et al., 2016

Current measurement requirements

1 ppm/~400 ppm = .25%

9 ppb/~1800 ppb = .5%

0.2 ppm/~400 ppm = .05%

1 ppb/~1800 ppb ≈ .05%

Current measurement requirements

• 10 ppb “required measurement uncertainty” (2-σ value)

• 7 ppb/decade stability requirement

High precision requirements are a function of the small gradients we are after

In all cases:

• truly random error (noise) can be dealt with

• systematic errors (bias) result in erroneous flux estimation

In all cases:

• truly random error (noise) can be dealt with

• systematic errors (bias) result in erroneous flux estimation

Requirement: Very low bias, reasonable precision

Difference to CO2: Significant uncertainties in all contributing processes

• generally easier to solve for the total CH4 budget, and divide into processes based on bottom-up share per pixel

• separating the processes directly introduces more unknowns, and requires more constraints

from synthesis of Saunois et al., ESSD, 2016

Another difference to CO2: Enigmatic recent changes in the growth rate

Another difference to CO2: Enigmatic recent changes in the growth rate

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Another difference to CO2: Enigmatic recent changes in the growth rate

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Another difference to CO2: Enigmatic recent changes in the growth rate

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!!!

Separation of processes• we have information on the spatial distribution of

processes based on our bottom-up inventories and process models

Saunois et al., 2016

The (somewhat) current observation network●

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●●●●●●●● ●●●●●●●●Aircraft CARIBIC CONTRAIL GOSAT Ground station Ship transect Total Column UCI network

Requirement: Well-calibrated long-term surface measurements of methane

Satellite measurements of methane with sensitivity in the lower troposphere up to now:

• SCIAMACHY on Envisat (2002-2012, sensor degradation after 2005)

• TANSO-FTS on GOSAT (2009-present

A note about thermal infrared sounders:

• AIRS, IASI, and TES offer long records with good spatial coverage

• the sensitivity of the thermal infrared sounders to the upper troposphere limits their application in flux inversion

Worden et al., AMT, 2015

SCIAMACHY: SCanning Imaging Absorption Spectrometer for Atmospheric CHartographY

• despite poor precision, systematic errors, and sensor degradation, it provided new insight into methane fluxes (e.g. Bergamaschi et al., 2009 and 2013; Bousquet et al., 2011; Houweling et al., 2014)

• could detect hotspot emission regions with sufficient averaging…

data from 2004, 0.5˚ binning, Buchwitz et al., ACP, 2017

GOSAT offers better precision, but poorer coverage

GOSAT offers better precision, but poorer coverage

“full physics” retrieval has lots of gaps in regions with

high cloud cover, aerosol load, andsolar zenith angles

GOSAT offers better precision, but poorer coverage

so-called “proxy” retrieval solves for the ratio of XCH4:XCO2, and

multiplies it by a (better known) modelled XCO2 value

“full physics” retrieval has lots of gaps in regions with

high cloud cover, aerosol load, andsolar zenith angles

Sentinel-5P (launching on Friday!) will provide a huge increase in coverage

being encapsulated into its fairings on October 3, 2017(Credits: ESA–Stephane Corvaja, 2017)

Sentinel-5P

• 7 km x 7 km spatial resolution (compare to 30 km x 60 km for SCIAMACHY, 10 km diameter for GOSAT)

• 2600 km swath

• daily global coverage (minus the clouds…)

• also measuring CO, O3, NO2, SO2 (but not CO2)

What this means for a simulated 500 kTCH4 point source:

courtesy H. Bovensmann, IUP-Bremen

What this means for a simulated 500 kTCH4 point source:

courtesy H. Bovensmann, IUP-Bremen

Requirement: High spatial resolution for detection of spatial patterns of fluxes

Difficulties can still arise when fluxes are co-located

Other tracers provide us with information about these processes:

Ethane, C2H6

• most abundant atmospheric hydrocarbon after methane

• primary sources are fossil fuels, biomass burning, and biofuels

Simpson et al., Nature, 2012

What ethane tells us• comparison of

short-lived ethane to methane growth rate suggests at least 30-70% of the slow-down was due to reduced fugitive emissions

Simpson et al., Nature, 2012

What ethane tells us

• ground-based total- column measurements from northern hemisphere and southern hemisphere suggest increase after 2007 was largely due to fossil fuel emissions increase

Hausmann et al., ACP, 2016

Other tracers provide us with further information about these processes:

stable isotopologue δ13CH4

• expresses ratio of 13C/12C-ratio in atmospheric CH4 in δ-notation relative to VPDB-standard

• different source types have distinct signatures

• there is significant uncertainty on these signatures, however

Schwietzke et al., Nature, 2016

Other tracers provide us with further information about these processes:

stable isotopologue δ13CH4

• expresses ratio of 13C/12C-ratio in atmospheric CH4 in δ-notation relative to VPDB-standard

• different source types have distinct signatures

• there is significant uncertainty on these signatures, however

Schwietzke et al., Nature, 2016

very depleted microbial signature

• one interpretation of these data (in a one-box model) suggests that the recent increase is driven by (depleted) microbial sources

• this is attributed to agriculture

Schaefer et al., Science, 2016

Nisbet et al., GBC, 2016

• the same data were simultaneously published as being indicative of climate-related increases in tropical wetland emissions

• a cow’s stomach is a bit like a wetland, isotopically speaking

• while others argue for a redistribution of the budget, and a decrease in fossil sources along with a microbial increase, contrary to the ethane data

Schwietzke et al., Nature, 2016

Ideally these pieces of information could be combined to provide a consistent answer…

Why is this so unclear?

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• these supporting measurements are sparse, especially in the tropics

• uncertainties on the regional distribution of source signatures remains

δ13CH4

C2H6

Why is this so unclear?

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• these supporting measurements are sparse, especially in the tropics

• uncertainties on the regional distribution of source signatures remains

δ13CH4

C2H6

Requirement: globally distributed sampling of related tracers

But also methane measurements are sparse in some regions

• persistent tropical clouds make satellite measurements difficult during much of the year

• requirement of sunlight limits high latitude measurements seasonally

• here an active lidar sensor (like MERLIN) with a footprint of only ~100 m and its own radiation source can provide much-needed low-bias data

Unknowns in the Arctic: wetland emissions during the zero curtain (and beyond)

Mastepanov et al., Nature, 2008

MERLIN: Polar-orbiting active sensor will offer data at all latitudes over the whole year

Ehret et al., Remote Sensing, 2017 (accepted)

Satellite/Instrument XCO2 XCH4 IFOV ‘12 ‘13 ‘14 ‘15 ‘16 ‘17 ‘18 ‘19 ‘20 ‘21 ‘22 ‘23 ‘24 ‘25

Envisat/SCIAMACHY ✓ ✓ 30 km x 60 km

GOSAT/TANSO-FTS ✓ ✓ 10.5 km (D)

OCO-2 ✓ 1.25 km x 2.26 km

TanSat ✓ 1 km x 2 km

Sentinel-5P/TROPOMI ✓ 7 km x 7 km

Gao Fen-5 ✓ ✓ 10 km (D)

GOSAT-2/TANSO-FTS ✓ ✓ 9.7 km (D)

FengYun-3D ✓ ✓ 10 km (D)

OCO-3 ✓ ~2 km x 2 km

MicroCarb ✓ 4.5 km x 9 km

MERLIN ✓ 100 m x ~50 km

Sentinel-5 (a, b, c) ✓ ✓ 7 km x 7 km

GeoCARB ✓ ✓ ~10 km x 10 km

Sentinel-7 ✓ ✓ ~2 km x 2 km

year

The future from space looks promising…

Satellite/Instrument XCO2 XCH4 IFOV ‘12 ‘13 ‘14 ‘15 ‘16 ‘17 ‘18 ‘19 ‘20 ‘21 ‘22 ‘23 ‘24 ‘25

Envisat/SCIAMACHY ✓ ✓ 30 km x 60 km

GOSAT/TANSO-FTS ✓ ✓ 10.5 km (D)

OCO-2 ✓ 1.25 km x 2.26 km

TanSat ✓ 1 km x 2 km

Sentinel-5P/TROPOMI ✓ 7 km x 7 km

Gao Fen-5 ✓ ✓ 10 km (D)

GOSAT-2/TANSO-FTS ✓ ✓ 9.7 km (D)

FengYun-3D ✓ ✓ 10 km (D)

OCO-3 ✓ ~2 km x 2 km

MicroCarb ✓ 4.5 km x 9 km

MERLIN ✓ 100 m x ~50 km

Sentinel-5 (a, b, c) ✓ ✓ 7 km x 7 km

GeoCARB ✓ ✓ ~10 km x 10 km

Sentinel-7 ✓ ✓ ~2 km x 2 km

year

The future from space looks promising…

Provided the following requirements are met:

• satellite data with low bias and reasonable precision

• maintenance of well-calibrated surface measurements

• high spatial resolution for imaging/separation of flux patterns

• active sensors for low bias coverage at high latitudes and in cloudy regions

• expansion of supplemental tracer measurements (ethane, isotopes)

• improvement of stratospheric representation in models

• a proxy for the hydroxy radical sink going forward( )