Tazu Saeki

Continuous measurements of methane from a tower network over Siberia

We have been conducting continuous measurements of Methane (sCH4) concentration from an expanding network of towers (JR-STATION: Japan–Russia Siberian Tall Tower Inland Observation Network) located in taiga, steppe and wetland biomes of Siberia since 2004. High daytime means (>2000 ppb) observed simultaneously at several towers during winter, together with in situ weather data and NCEP/NCAR reanalysis data, indicate that high pressure systems caused CH4 accumulation at subcontinental scale due to the widespread formation of an inversion layer. Daytime means sometimes exceeded 2000 ppb, particularly in the summer of 2007 when temperature and precipitation rates were anomalously high over West Siberia, which implies that CH4 emission from wetlands were exceptionally high in 2007. Many hot spots detected by MODIS in the summer of 2007 illustrate that the contribution of biomass burning also cannot be neglected. Daytime mean CH4 concentrations from the Siberian tower sites were generally higher than CH4 values reported at NOAA coastal sites in the same latitudinal zone, and the difference in concentrations between two sets of sites was reproduced with a coupled Eulerian–Lagrangian transport model. Simulations of emissions from different CH4 sources suggested that the major contributor to variation switched from wetlands during summer to fossil fuel during winter.

Top–down assessment of the Asian carbon budget since the mid 1990s

Increasing atmospheric carbon dioxide (CO2) is the principal driver of anthropogenic climate change. Asia is an important region for the global carbon budget, with 4 of the worlds 10 largest national emitters of CO2. Using an ensemble of seven atmospheric inverse systems, we estimated land biosphere fluxes (natural, land-use change and fires) based on atmospheric observations of CO2 concentration. The Asian land biosphere was a net sink of −0.46 (−0.70–0.24) PgC per year (median and range) for 1996–2012 and was mostly located in East Asia, while in South and Southeast Asia the land biosphere was close to carbon neutral. In East Asia, the annual CO2 sink increased between 1996–2001 and 2008–2012 by 0.56 (0.30–0.81) PgC, accounting for ∼35% of the increase in the global land biosphere sink. Uncertainty in the fossil fuel emissions contributes significantly (32%) to the uncertainty in land biosphere sink change.

Concentration variations of tropospheric nitrous oxide over Japan

Aircraft measurements of the tropospheric N2O concentration were made over Japan during the period from October 1991 to June 1999. The observed values of the N2O concentration showed clear evidence of the secular increase, with mean rates of 0.50 to 0.64 ppbv/yr for selected height intervals of 0–2, 2–4, 4–6, 6–8 km and 8 km-tropopause. Although the seasonality of the N2O concentration was hardly observable throughout the troposphere, interannual variations with periods of about 2 years were clearly found. The average N2O concentrations over the observation period for the above 5 height intervals were almost identical with each other, showing no appreciable vertical gradient of the concentration. This suggests that N2O emissions from the ground surface around Japan are very weak and the emitted N2O is mixed well in the troposphere.

Inter‐annual variability of the atmospheric carbon dioxide concentrations as simulated with global terrestrial biosphere models and an atmospheric transport model

Seasonal and inter-annual variations of atmospheric CO2 for the period from 1961 to 1997 have been simulated using a global tracer transport model driven by a new version of the Biome BioGeochemical Cycle model (Biome-BGC). Biome-BGC was forced by daily temperature and precipitation from the NCEP reanalysis dataset, and the calculated monthly-averaged CO2 fluxes were used as input to the global transport model. Results from an inter-comparison with the Carnegie—Ames—Stanford Approach model (CASA) and the Simulation model of Carbon cYCle in Land Ecosystems (Sim-CYCLE) model are also reported. The phase of the seasonal cycle in the Northern Hemisphere was reproduced generally well by Biome-BGC, although the amplitude was smaller compared to the observations and to the other biosphere models. The CO2 time series simulated by Biome-BGC were compared to the global CO2concentration anomalies from the observations at Mauna Loa and the South Pole. The modeled concentration anomalies matched the phase of the inter-annual variations in the atmospheric CO2 observations; however, the modeled amplitude was lower than the observed value in several cases. The result suggests that a significant part of the inter-annual variability in the global carbon cycle can be accounted for by the terrestrial biosphere models. Simulations performed with another climate-based model, Sim-CYCLE, produced a larger amplitude of inter-annual variability in atmospheric CO2, making the amplitude closer to the observed range, but with a more visible phase mismatch in a number of time periods. This may indicate the need to increase the Biome-BGC model sensitivity to seasonal and inter-annual changes in temperature and precipitation.

Global mapping of greenhouse gases retrieved from GOSAT Level 2 products by using a kriging method

Because a synoptic overview facilitates understanding of the temporal and spatial changes in the global distribution of greenhouse gases, we developed a statistical spatial estimation method using kriging. Level 3 (L3) data products for the Greenhouse Gases Observing Satellite (GOSAT) Thermal And Near infrared Sensor for Carbon Observation (TANSO) Fourier Transform Spectrometer (FTS) Short Wave Infrared (SWIR) were generated from column-averaged, dry-air mole fractions of carbon dioxide (XCO2) and methane (XCH4) TANSO-FTS SWIR Level 2 (L2) products using this method. Although there have been some reports on the use of kriging for analysing GOSAT products, the kriging method used in this research was specifically adapted to the statistical characteristics of GOSAT L2 products. In the context of using data for atmospheric research, spatially interpolated data (GOSAT L3 products) cannot be more accurate than model-simulated global distributions of gas concentrations (GOSAT Level 4B (L4B) products), which are generated using an atmospheric tracer transport model. However, the L3 product takes much less time to generate than the L4B. It would take about a year to produce the L4B after generation of an L2 product. The great advantage of the L3 product is that it gives a comprehensive and reasonable monthly global distribution of gas concentrations with little delay. The L3 product using the kriging method can be generated on a monthly basis by estimating global semi-variogram curves from the L2 products for each month and interpolating spatially within a region with a radius of 1000 km from existing L2 data locations. The main purpose of this paper is to describe the methodology and characteristics of kriging used to generate the GOSAT L3 product, not for strictly scientific use of the estimated values, but for a reasonable global map of gas concentrations derived statistically from the sparsely observed L2 products within a short time frame. The characteristics of this method are compared to XCO2 products simulated with an atmospheric tracer transport model. The results show that the method proposed in this study is of practical use for generating L3 products from L2 products.

Variations of stratospheric trace gases measured using a balloon-borne cryogenic sampler

Abstract For a better understanding of the cycles of atmospheric trace gases, we have continued to systematically collect air samples in the stratosphere over Japan since 1985, using a balloon-borne cryogenic sampler. The collection of the stratospheric air samples was also made twice over the Scandinavian Peninsula in 1997 and once over Japanese Antarctic station, Syowa in 1998. The air samples collected were analyzed not only for the concentrations of CO2, CH4, N2O and various halocarbons but also for their isotopic ratios. These measurements revealed that, in general, the concentrations of all gas components decreased and their isotopic ratios increased with increasing height, due to influence of atmospheric transport and photochemical destruction in the stratosphere. However, detailed inspection of the results indicated that the observed vertical profiles of the respective components were quantitatively different, depending on location and time. Stratospheric CO2 over Japan showed the secular increase with an average rate of 1.4 ppmv/year for the period 1985–1999.

Temporal variations of atmospheric carbon dioxide in the southernmost part of Japan

We present analysis of the temporal variation of atmospheric CO2 in the subtropical region of East Asia, obtained aboard a ferry between Ishigaki Island and Hateruma Island, Japan for the period June 1993–April 2005. The annual mean CO2 concentration increases from 360.1 ppmv in 1994 to 378.4 ppmv in 2004, showing an average growth rate of 1.8 ppmv yr-1. The growth rate shows interannual variations with high values duringENSOevents. The average seasonal CO2 cycle reaches the maximum in early April and the minimum in mid-September, with a peak-to-peak amplitude of 8.5 ppmv. Numerical simulations using a three-dimensional atmospheric transport model show interannual variations of the CO2 growth rate similar to the observation, but the amplitude of the seasonal cycle is larger, with maximum concentration appearing earlier than the observation by 1 month. Low CO2 values observed during the spring of 1998 are likely associated with the 1997/1998 ENSO event. A backward trajectory analysis suggests that they were due to changes in atmospheric transport whereby maritime air masses from the Pacific Ocean dominated over polluted air masses from the Asian Continent. Extreme values (either high or low) of CO2 are also occasionally observed. A comparison of backward trajectories of air parcels with CO2 concentration fields calculated using the atmospheric transport model shows that these unusual CO2 concentrations result from the transport of air affected not only by anthropogenic CO2 emissions but also by terrestrial biospheric activities mainly in China.

The Orbiting Carbon Observatory (OCO-2) tracks 2-3 peta-gram increase in carbon release to the atmosphere during the 2014-2016 El Niño

The powerful El Niño event of 2015–2016 – the third most intense since the 1950s – has exerted a large impact on the Earth’s natural climate system. The column-averaged CO2 dry-air mole fraction (XCO2) observations from satellites and ground-based networks are analyzed together with in situ observations for the period of September 2014 to October 2016. From the differences between satellite (OCO-2) observations and simulations using an atmospheric chemistry-transport model, we estimate that, relative to the mean annual fluxes for 2014, the most recent El Niño has contributed to an excess CO2 emission from the Earth’s surface (land + ocean) to the atmosphere in the range of 2.4 ± 0.2 PgC (1 Pg = 1015 g) over the period of July 2015 to June 2016. The excess CO2 flux is resulted primarily from reduction in vegetation uptake due to drought, and to a lesser degree from increased biomass burning. It is about the half of the CO2 flux anomaly (range: 4.4–6.7 PgC) estimated for the 1997/1998 El Niño. The annual total sink is estimated to be 3.9 ± 0.2 PgC for the assumed fossil fuel emission of 10.1 PgC. The major uncertainty in attribution arise from error in anthropogenic emission trends, satellite data and atmospheric transport.

Estimation of regional surface CO2 fluxes with GOSAT observations using two inverse modeling approaches

Inverse estimation of surface C02 fluxes is performed with atmospheric transport model using ground-based and GOSAT observations. The NIES-retrieved C02 column mixing (Xc02) and column averaging kernel are provided by GOSAT Level 2 product v. 2.0 and PPDF-DOAS method. Monthly mean C02 fluxes for 64 regions are estimated together with a global mean offset between GOSAT data and ground-based data. We used the fixed-lag Kalman filter to infer monthly fluxes for 42 sub-continental terrestrial regions and 22 oceanic basins. We estimate fluxes and compare results obtained by two inverse modeling approaches. In basic approach adopted in GOSAT Level4 product v. 2.01, we use aggregation of the GOSAT observations into monthly mean over 5x5 degree grids, fluxes are estimated independently for each region, and NIES atmospheric transport model is used for forward simulation. In the alternative method, the model-observation misfit is estimated for each observation separately and fluxes are spatially correlated using EOF analysis of the simulated flux variability similar to geostatistical approach, while transport simulation is enhanced by coupling with a Lagrangian transport model Flexpart. Both methods use using the same set of prior fluxes and region maps. Daily net ecosystem exchange (NEE) is predicted by the Vegetation Integrative Simulator for Trace gases (VISIT) optimized to match seasonal cycle of the atmospheric C02 . Monthly ocean-atmosphere C02 fluxes are produced with an ocean pC02 data assimilation system. Biomass burning fluxes were provided by the Global Fire Emissions Database (GFED); and monthly fossil fuel C02 emissions are estimated with ODIAC inventory. The results of analyzing one year of the GOSAT data suggest that when both GOSAT and ground-based data are used together, fluxes in tropical and other remote regions with lower associated uncertainties are obtained than in the analysis using only ground-based data. With version 2.0 of L2 Xc02 the fluxes appear reasonable for many regions and seasons, however there is a need for improving the L2 bias correction, data filtering and the inverse modeling method to reduce estimated flux anomalies visible in some areas. We also observe that application of spatial flux correlations with EOF based approach reduces flux anomalies.

Land use change and El Niño-Southern Oscillation drive decadal carbon balance shifts in Southeast Asia

An integrated understanding of the biogeochemical consequences of climate extremes and land use changes is needed to constrain land-surface feedbacks to atmospheric CO2 from associated climate change. Past assessments of the global carbon balance have shown particularly high uncertainty in Southeast Asia. Here, we use a combination of model ensembles to show that intensified land use change made Southeast Asia a strong source of CO2 from the 1980s to 1990s, whereas the region was close to carbon neutral in the 2000s due to an enhanced CO2 fertilization effect and absence of moderate-to-strong El Niño events. Our findings suggest that despite ongoing deforestation, CO2 emissions were substantially decreased during the 2000s, largely owing to milder climate that restores photosynthetic capacity and suppresses peat and deforestation fire emissions. The occurrence of strong El Niño events after 2009 suggests that the region has returned to conditions of increased vulnerability of carbon stocks.The carbon balance in Southeast Asia is highly uncertain. Here, the authors show that land use changes and occurrence of strong El Niño control decadal shifts in the carbon balance of this region.