High-resolution CO2 flux inversion model for regional study in Siberia

GRENE北極気候変動研究事業研究成果報告会日時：2016年3月4日（金）　14：30-16：30 (Core time 14：.30-15：40)会場：国立国語研究所　2Fホワイ

Simulation of CO2 and CH4 seasonal cycles in Siberia

第6回極域科学シンポジウム分野横断セッション：[IA] 急変する北極気候システム及びその全球的な影響の総合的解明―GRENE北極気候変動研究事業研究成果報告2015―11月19日（木）　国立極地研究所 2階 大会議

The Open-Source Data Inventory for Anthropogenic Carbon Dioxide (CO2), Version 2016 (ODIAC2016): A Global, Monthly Fossil-Fuel CO2 Gridded Emission Data Product for Tracer Transport Simulations and Surface Flux Inversions

The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a global high-spatial resolution gridded emission data product that distributes carbon dioxide (CO2) emissions from fossil fuel combustion. The emission spatial distributions are estimated at a 1x1 km spatial resolution over land using power plant profiles (emission intensity and geographical location) and satellite-observed nighttime lights. This paper describes the year 2016 version of the ODIAC emission data product (ODIAC2016) and presents analyses that help guiding data users, especially for atmospheric CO2 tracer transport simulations and flux inversion analysis. Since the original publication in 2011, we have made modifications to our emission modeling framework in order to deliver a comprehensive global gridded emission data product. Major changes from the 2011 publication are 1) the use of emissions estimates made by the Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory (ORNL) by fuel type (solid, liquid, gas, cement manufacturing, gas flaring and international aviation and marine bunkers), 2) the use of multiple spatial emission proxies by fuel type such as nightlight data specific to gas flaring and ship/aircraft fleet tracks and 3) the inclusion of emission temporal variations. Using global fuel consumption data, we extrapolated the CDIAC emissions estimates for the recent years and produced the ODIAC2016 emission data product that covers 2000-2015. Our emission data can be viewed as an extended version of CDIAC gridded emission data product, which should allow data users to impose global fossil fuel emissions in more comprehensive manner than original CDIAC product. Our new emission modeling framework allows us to produce future versions of ODIAC emission data product with a timely update. Such capability has become more significant given the CDIAC/ORNL's shutdown. ODIAC data product could play an important role to support carbon cycle science, especially modeling studies with space-based CO2 data collected near real time by ongoing carbon observing missions such as Japanese Greenhouse Observing SATellite (GOSAT), NASA's Orbiting Carbon Observatory 2 (OCO-2) and upcoming future missions. The ODIAC emission data product including the latest version of the ODIAC emission data (ODIAC2017, 2000-2016), is distributed from http://db.cger.nies.go.jp/dataset/ODIAC/ with a DOI

Исследование углекислого газа и метана в глобальном и региональном (Сибирь) масштабах: обзор

Статья на рус. яз. с.

Simulating CO 2 profiles using NIES TM and comparison with HIAPER Pole-to-Pole Observations

We present a study on validation of the National Institute for Environmental Studies Transport Model (NIES TM) by comparing to observed vertical profiles of atmospheric CO2. The model uses a hybrid sigma-isentropic (σ–θ) vertical coordinate that employs both terrain-following and isentropic parts switched smoothly in the stratosphere. The model transport is driven by reanalyzed meteorological fields and designed to simulate seasonal and diurnal cycles, synoptic variations, and spatial distributions of atmospheric chemical constituents in the troposphere. The model simulations were run for biosphere, fossil fuel, air–ocean exchange, biomass burning and inverse correction fluxes of carbon dioxide (CO2) by GOSAT Level 4 product. We compared the NIES TM simulated fluxes with data from the HIAPER Pole-to-Pole Observations (HIPPO) Merged 10 s Meteorology, Atmospheric Chemistry, and Aerosol Data, including HIPPO-1, HIPPO-2 and HIPPO-3 from 128.0° E to −84.0° W, and 87.0° N to −67.2° S

Global Lagrangian atmospheric dispersion model

The Global Lagrangian Atmospheric Dispersion Model (GLADIM) is described. GLADIM is based on the global trajectory model, which had been developed earlier and uses fields of weather parameters from different atmospheric reanalysis centers for calculations of trajectories of air mass that include trace gases. GLADIM includes the parameterization of turbulent diffusion and allows the forward calculation of concentrations of atmospheric tracers at nodes of a global regular grid when a source is specified. Thus, GLADIM can be used for the forward simulation of pollutant propagation (volcanic ash, radionuclides, and so on). Working in the reverse direction, GLADIM allows the detection of remote sources that mainly contribute to the tracer concentration at an observation point. This property of Lagrangian models is widely used for data analysis and the reverse modeling of emission sources of a pollutant specified. In this work we describe the model and some results of its validation through a comparison with results of a similar model and observation data

Mapping of West Siberian taiga wetland complexes using Landsat imagery: implications for methane emissions

High latitude wetlands are important for understanding climate change risks because these environments sink carbon and emit methane. Fine scale heterogeneity of wetland landscapes pose challenges for producing the greenhouse gas flux inventories based on point observations. To reduce uncertainties at the regional scale, we mapped wetlands and water bodies in the taiga zone of West Siberia on a scene-by-scene basis using a supervised classification of Landsat imagery. The training dataset was based on high-resolution images and field data that were collected at 28 test areas. Classification scheme was aimed at methane inventory applications and included 7 wetland ecosystem types composing 9 wetland complexes in different proportions. Accuracy assessment based on 1082 validation polygons of 10 × 10 pixels indicated an overall map accuracy of 79 %. The total area of the wetlands and water bodies was estimated to be 52.4 Mha or 4-12 % of the global wetland area. Ridge-hollow complexes prevail in WS's taiga, occupying 33 % of the domain, followed by forested bogs or "ryams" (23 %), ridge-hollow-lake complexes (16 %), open fens (8 %), palsa complexes (7 %), open bogs (5 %), patterned fens (4 %), and swamps (4 %). Various oligotrophic environments are dominant among the wetland ecosystems, while fens cover only 14 % of the area. Because of the significant update in the wetland ecosystem coverage, a considerable revaluation of the total CH4 emissions from the entire region is expected. A new Landsat-based map of WS's taiga wetlands provides a benchmark for validation of coarse-resolution global land cover products and wetland datasets in high latitudes