Integrated Observation and Analysis System for Monitoring
Anthropogenic and Natural Greenhouse Gas Sources and Sinks

Nobuko Saigusa

National Institute for Environmental Studies, Japan

Pictures and figures by courtesy ofMeteorological Agency (JMA) andJapan Aerospace Exploration Agency (JAXA)
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Concepts
To provide data and knowledge to stakeholders in time with
the Global Stocktake Process under the Paris Agreement
To provide additional sources of data and information that can
support estimating the impacts of mitigation actions
Relevant Japanese institutions and agencies for GHG observation
and analysis will cooperate to improve up-to-date analysis systems
and data coverage particularly in Asia–Oceania for better
estimation of the distribution of anthropogenic and natural sinks
and sources with sufficient accuracy
2Methods
1. Top-down analysis
2. Flux upscaling
3. GHG Inventory
Improve their accuracy by identifying the cause ofdiscrepancy
Provide global gridded GHG sink/source data tocontribute to the Global Stocktake under the Paris
Agreement by FY2021 and publish synthesis reportby FY2022 (tentative)
Estimate long-term anthropogenic and natural
GHG budgets with high spatio-temporalresolution by FY 2023 (tentative)⇒Assess the past socio-economic
scenarios used
Forin the climate models⇒Predict the effects of climate change mitigation
measures in the near future3

Progress in top-down analysis

4Data:GOSAT Data Archive Service (GDAS)
https://data2.gosat.nies.go.jp/index_en.html
GOSAT-2 Product Archivehttps://prdct.gosat-2.nies.go.jp/en/index.html

Satellite-based Monitoring

Whole-atmosphere monthly mean CO2 and CH4
concentrations based on GOSAT observations

CO2CH4Comparison of methane columnaveraged dry-air mole fraction (XCH4)
between GOSAT and GOSAT-2 dataacquired on the same day.

XCH4

Global distribution of methane column-averaged
dry-air mole fraction (XCH4) retrieved by theproxy-method from FTS-2 data acquired fromMarch 5 to April 3, 2019.

XCO

Global distribution of carbon monoxide columnaveraged dry-air mole fraction (XCO) retrieved by
the proxy method from the FTS-2 data acquired
from March 5 to April 3, 2019.

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Airborne-based Monitoring
CONTRAIL（Comprehensive Observation Network for TRace gases by AIrLiner）
Powerful high-precision data for verifying
models and satellite observations

Height [km]Vertical distribution of CO2 concentration and its seasonal change
Delhi, India
Tokyo (Narita), JapanMonth
Uptake from winter crops← Flight paths and the number ofvertical profile observations of CME

MonthUmezawa et al. GRL (2016)
Umezawa et al. ACP (2018)

Data: Atmospheric CO2 mole fraction data of CONTRAIL-CME:
http://www.nies.go.jp/doi/10.17595/20180208.001-e.html

6Data Integration and Inverse Model Estimation for
GHG Sources and Sinks
NICAM-TM 4D-Var

NICAM-TM (Nonhydrostatic ICOsahedral AtmosphericModel-based Transport Model)

Niwa et al. (2017a,b)

Results of the preliminary experiments
for the detection of large-scale forest fires

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Data Integration and Inverse Model Estimation ofGHG Sources and Sinks
CO2 concentration distribution at 10 km (250 hPa)estimated using NICAM-TM and CONTRAIL flight data

Southeast Asia for Oct 2015
Inversion analysis with CONTRAIL data improved thereliability of the results. Strong sources, likely related tobiomass burning, and also some sinks, were retrieved.

Slide provided by Niwa Ysinksource

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Bottom-up GHG Inventory

9Methane budget of East Asia, 1990–2015:
A bottom-up evaluation
Itoh et al. (2019)

Aggregated CH4budget (2000–2012).

Time seriesof the CH4budget inEast Asia(1990-2015)10

Emissions of nitrous oxide (N2O) from soil surfaces
and their historical changes in East Asia
Itoh et al. (2018)
Emissions ofN2O in East
Asia (2000–2009)
simulated with
the VISIT
model.
Interannual
variability of total
N2O emissions inEast Asia
simulated with
the VISIT model.

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Progress in both top-down and bottom-up approaches
for terrestrial CO2 budgetTerrestrial CO2 budget
estimations was much
improved byreconciling top-down
and bottom-up
approaches.
Kondo, Patra, et al.
(2019) Global Change
Biology (in press)

Collaboration Among Japanese Agencies and Institutions
to Contribute to the Global Stocktake (tentative)
Expected Product/Data
2019

2020
Paris Agreement

Global GHG sources and sinks

2021
2022
Provide Gridded Data & Synthesis

GHG emission from Cities and Countries

2023★GST 1

2024

2025

2026
2027
Provide Gridded Data & Synthesis

2028
★GST2

Global Stocktake

International research
projects:
WCRP, Future Earth,
TranCom, SOCAT, FLUXNET,…..

GAW
WDCGG
IG33IS

Data

WG Climate
GHG TT

Data and knowledge

Japan Platform
Data: Atmospheric GHGs & SLCPs, ocean/terrestrial surface fluxes, GHG inventories
Observation platforms: Satellites, aircraft, ships, ground stations, …
Analysis systems: Inverse models, flux upscaling, bottom-up inventories, …
Global GHG sinks
and sources

JMA
MOE

NIES
GHG Inventory Office

City-scale andNational emissions

JAMSTEC

Universities

JAXA
MEXT

Other countries’ efforts
City-scale andnationalemissions

EU

Global GHGemission

City-scale andnationalemissions

US

Global GHGemission…

Discussion needed: Inter-comparison of global datasets?
 Separation of anthropogenic andnatural emissions?
 Possibilities of near-future prediction 13

Summary Japanese institutions and agencies for GHG observation andanalysis cooperate to improve up-to-date analysis systems anddata coverage globally and in Asia–Oceania for better
estimation of the distribution of anthropogenic and naturalsinks and sources with sufficient accuracy
 International cooperation is essential to improve reliability inthe global datasets (anthropogenic and natural sinks and sources) Technological development is still required for- separation of anthropogenic and natural emission- near-future prediction of impacts of mitigation actions

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