大気水圏科学(A)
セッション小記号大気水圏科学複合領域・一般(CG)
セッションIDA-CG32
タイトル和文Global Carbon Cycle Observation and Analysis
英文Global Carbon Cycle Observation and Analysis
タイトル短縮名和文Global Carbon Cycle Observation and Analysis
英文Global Carbon Cycle Analysis
代表コンビーナ 氏名和文市井 和仁
英文Kazuhito Ichii
所属和文千葉大学
英文Chiba University
共同コンビーナ 1氏名和文Patra Prabir
英文Prabir Patra
所属和文Research Institute for Global Change, JAMSTEC
英文Research Institute for Global Change, JAMSTEC
共同コンビーナ 2氏名和文Forrest M. Hoffman
英文Forrest M. Hoffman
所属和文Oak Ridge National Laboratory
英文Oak Ridge National Laboratory
共同コンビーナ 3氏名和文Makoto Saito
英文Makoto Saito
所属和文National Institute of Environmental Studies
英文National Institute of Environmental Studies
発表言語E
スコープ和文The landmark Paris Agreement under the United Nations Framework Convention on Climate Change (UNFCCC) aims at reduction of greenhouse gases (GHGs) emission to keep the global warming below 2 degC. As per the agreement the nationally determined commitments (NDCs) and their progresses should be carefully monitored and verified by international bodies. The emission verification will be based on observation of the time evolution of greenhouse gases and model-based estimations of emissions from time to time.

In recent years, the number of observations and new techniques to monitor GHGs budget have been increasing. The improvements includes observational platforms for monitoring atmospheric GHGs, national or regional emission inventories, top-down models (e.g. atmospheric inverse models), and bottom-up models (e.g. process-based models). However, due to uncertainties in modeling and sparse observation network, high uncertainty exists in GHGs sources/sinks estimations at global and regional scales. These uncertainties lead to large variations in future projection of GHG budgets and climate changes.

The purpose of the session is to discuss state-of-the-art techniques for estimations of GHGs (e.g. CO2, CH4, N2O) budget at global and regional scales. The topic includes natural and anthropogenic processes, various methodologies (e.g. in-situ observation, aircraft monitoring, remote sensing, modeling), and various targets (e.g. atmosphere, terrestrial, and ocean), various spatial and temporal coverage (e.g. regional to global scales and past-present-future). Improved estimates of emissions from land use change, forest fires, and other anthropogenic sources (urban developments and thermal power station etc.) are also of interest. We also welcome discussions for designs and plans for future studies targeting city and country scale emission estimations using sophisticated modeling tools.
英文The landmark Paris Agreement under the United Nations Framework Convention on Climate Change (UNFCCC) aims at reduction of greenhouse gases (GHGs) emission to keep the global warming below 2 degC. As per the agreement the nationally determined commitments (NDCs) and their progresses should be carefully monitored and verified by international bodies. The emission verification will be based on observation of the time evolution of greenhouse gases and model-based estimations of emissions from time to time.

In recent years, the number of observations and new techniques to monitor GHGs budget have been increasing. The improvements includes observational platforms for monitoring atmospheric GHGs, national or regional emission inventories, top-down models (e.g. atmospheric inverse models), and bottom-up models (e.g. process-based models). However, due to uncertainties in modeling and sparse observation network, high uncertainty exists in GHGs sources/sinks estimations at global and regional scales. These uncertainties lead to large variations in future projection of GHG budgets and climate changes.

The purpose of the session is to discuss state-of-the-art techniques for estimations of GHGs (e.g. CO2, CH4, N2O) budget at global and regional scales. The topic includes natural and anthropogenic processes, various methodologies (e.g. in-situ observation, aircraft monitoring, remote sensing, modeling), and various targets (e.g. atmosphere, terrestrial, and ocean), various spatial and temporal coverage (e.g. regional to global scales and past-present-future). Improved estimates of emissions from land use change, forest fires, and other anthropogenic sources (urban developments and thermal power station etc.) are also of interest. We also welcome discussions for designs and plans for future studies targeting city and country scale emission estimations using sophisticated modeling tools.
発表方法口頭および（または）ポスターセッション
招待講演Tomohiro Oda
時間講演番号タイトル発表者予稿原稿
口頭発表 5月28日 PM1
13:45 - 14:00ACG32-01A high-resolution fossil fuel CO2 emission gridded dataset for tracer transport simulations and flux inversions: An overview, evaluations, applications and future perspectivesTomohiro Oda予稿
14:00 - 14:15ACG32-02グローバル二酸化炭素排出インベントリーの不確実性の低減に向けて叢 日超予稿
14:15 - 14:30ACG32-03Evaluation of MIROC4-ACTM reanalysis of GHGs concentrations using aircraftJagat Bisht予稿
14:30 - 14:45ACG32-04Carbon flux estimation using NICAM-TM 4D-Var and GOSAT data towards GOSAT-2 Level 4 product佐伯 田鶴予稿
14:45 - 15:00ACG32-05Attribution of the ambiguity in methane’s growth rate shifts during 1988-2016.Naveen Chandra予稿
15:00 - 15:15ACG32-06Ocean uptake and land use change emissions suppressed atmospheric CO2 growth in the 2015/16 El Niño近藤 雅征予稿
口頭発表 5月28日 PM2
15:30 - 15:45ACG32-07Observing vegetation seasonal dynamics in Japan with Himawari-8 hypertemporal dataTomoaki Miura予稿
15:45 - 16:00ACG32-08Carbon and Water Fluxes at High spatial Resolutions through Down-ScalingJiquan Chen予稿
16:00 - 16:15ACG32-09Connecting Satellite Based Spectral Modelling Approach and Forest Inventory to Model Biomass and Carbon Stocks in Natural and Planted Forest over part of Semi-arid zone, IndiaSWATI UNIYAL予稿
16:15 - 16:30ACG32-10Allocation of forest net primary production varies by forest age and air temperatureXiang Song予稿
16:30 - 16:45ACG32-11Analyzing Model Biases in Terrestrial Carbon Cycle Submodels in Earth System Models and Offline Models市井 和仁予稿
16:45 - 17:00ACG32-12Assessing terrestrial biogeochemical feedbacks in a strategically geoengineered climateForrest M. Hoffman予稿
講演番号タイトル発表者予稿原稿
ポスター発表 5月28日 AM2
ACG32-P01Regional budgets of 3 major greenhouse gases using inverse modelling of atmospheric dataPatra Prabir予稿
ACG32-P02Analysis of hot summer in 2018村上 和隆予稿
ACG32-P03Updated Data-Driven GPP and NEE Estimation Using Machine Learning Algorithms with Remote Sensing and Flux DataZhiyan Liu予稿
ACG32-P04Response of a Bornean Rainforest to the Climatic Changes imposed by ENSO during 2009-2016Julie Karine Michelon予稿
ACG32-P05モンゴルの草原域におけるCO2フラックスのモニタリングと評価王 勤学予稿
ACG32-P06Data-driven monitoring of terrestrial carbon cycle in MongoliaZAYA MART予稿