Takashi Maki

TransCom 3 inversion intercomparison: Impact of transport model errors on the interannual variability of regional CO2 fluxes, 1988–2003

Monthly CO2 fluxes are estimated across 1988–2003 for 22 emission regions using data from 78 CO2 measurement sites. The same inversion (method, priors, data) is performed with 13 different atmospheric transport models, and the spread in the results is taken as a measure of transport model error. Interannual variability (IAV) in the winds is not modeled, so any IAV in the measurements is attributed to IAV in the fluxes. When both this transport error and the random estimation errors are considered, the flux IAV obtained is statistically significant at P ≤ 0.05 when the fluxes are grouped into land and ocean components for three broad latitude bands, but is much less so when grouped into continents and basins. The transport errors have the largest impact in the extratropical northern latitudes. A third of the 22 emission regions have significant IAV, including the Tropical East Pacific (with physically plausible uptake/release across the 1997–2000 El Nino/La Nina) and Tropical Asia (with strong release in 1997/1998 coinciding with large-scale fires there). Most of the global IAV is attributed robustly to the tropical/southern land biosphere, including both the large release during the 1997/1998 El Nino and the post-Pinatubo uptake.

Transcom 3 inversion intercomparison: Model mean results for the estimation of seasonal carbon sources and sinks

[1] The TransCom 3 experiment was begun to explore the estimation of carbon sources and sinks via the inversion of simulated tracer transport. We build upon previous TransCom work by presenting the seasonal inverse results which provide estimates of carbon flux for 11 land and 11 ocean regions using 12 atmospheric transport models. The monthly fluxes represent the mean seasonal cycle for the 1992 to 1996 time period. The spread among the model results is larger than the average of their estimated flux uncertainty in the northern extratropics and vice versa in the tropical regions. In the northern land regions, the model spread is largest during the growing season. Compared to a seasonally balanced biosphere prior flux generated by the CASA model, we find significant changes to the carbon exchange in the European region with greater growing season net uptake which persists into the fall months. Both Boreal North America and Boreal Asia show lessened net uptake at the onset of the growing season with Boreal Asia also exhibiting greater peak growing season net uptake. Temperate Asia shows a dramatic springward shift in the peak timing of growing season net uptake relative to the neutral CASA flux while Temperate North America exhibits a broad flattening of the seasonal cycle. In most of the ocean regions, the inverse fluxes exhibit much greater seasonality than that implied by the DpCO2 derived fluxes though this may be due, in part, to misallocation of adjacent land flux. In the Southern Ocean, the austral spring and fall exhibits much less carbon uptake than implied by DpCO2 derived fluxes. Sensitivity testing indicates that the inverse estimates are not overly influenced by the prior flux choices. Considerable agreement exists between the model mean, annual mean results of this study and that of the previously published TransCom annual mean inversion. The differences that do exist are in poorly constrained regions and tend to exhibit compensatory fluxes in order to match the global mass constraint. The differences between the estimated fluxes and the prior model over the northern land regions could be due to the prior model respiration response to temperature. Significant phase differences, such as that in the Temperate Asia region, may be due to the limited observations for that region. Finally, differences in the boreal land regions between the prior model and the estimated fluxes may be a reflection of the timing of spring thaw and an imbalance in respiration versus photosynthesis. INDEX TERMS: 0322 Atmospheric Composition and Structure: Constituent sources and sinks; 1615 Global Change: Biogeochemical processes (4805); 0315 Atmospheric Composition and Structure: Biosphere/atmosphere interactions; KEYWORDS: carbon transport, inversion

TransCom model simulations of hourly atmospheric CO2: Analysis of synoptic-scale variations for the period 2002-2003

The ability to reliably estimate CO2 fluxes from current in situ atmospheric CO2 measurements and future satellite CO2 measurements is dependent on transport model performance at synoptic and shorter timescales. The TransCom continuous experiment was designed to evaluate the performance of forward transport model simulations at hourly, daily, and synoptic timescales, and we focus on the latter two in this paper. Twenty-five transport models or model variants submitted hourly time series of nine predetermined tracers (seven for CO2) at 280 locations. We extracted synoptic-scale variability from daily averaged CO2 time series using a digital filter and analyzed the results by comparing them to atmospheric measurements at 35 locations. The correlations between modeled and observed synoptic CO2 variabilities were almost always largest with zero time lag and statistically significant for most models and most locations. Generally, the model results using diurnally varying land fluxes were closer to the observations compared to those obtained using monthly mean or daily average fluxes, and winter was often better simulated than summer. Model results at higher spatial resolution compared better with observations, mostly because these models were able to sample closer to the measurement site location. The amplitude and correlation of model-data variability is strongly model and season dependent. Overall similarity in modeled synoptic CO2 variability suggests that the first-order transport mechanisms are fairly well parameterized in the models, and no clear distinction was found between the meteorological analyses in capturing the synoptic-scale dynamics.

TransCom model simulations of hourly atmospheric CO2 : experimental overview and diurnal cycle results for 2002

[1] A forward atmospheric transport modeling experiment has been coordinated by the TransCom group to investigate synoptic and diurnal variations in CO2. Model simulations were run for biospheric, fossil, and air-sea exchange of CO2 and for SF6 and radon for 2000-2003. Twenty-five models or model variants participated in the comparison. Hourly concentration time series were submitted for 280 sites along with vertical profiles, fluxes, and meteorological variables at 100 sites. The submitted results have been analyzed for diurnal variations and are compared with observed CO2 in 2002. Mean summer diurnal cycles vary widely in amplitude across models. The choice of sampling location and model level account for part of the spread suggesting that representation errors in these types of models are potentially large. Despite the model spread, most models simulate the relative variation in diurnal amplitude between sites reasonably well. The modeled diurnal amplitude only shows a weak relationship with vertical resolution across models; differences in near-surface transport simulation appear to play a major role. Examples are also presented where there is evidence that the models show useful skill in simulating seasonal and synoptic changes in diurnal amplitude.

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.

New technique to analyse global distributions of CO2 concentrations and fluxes from non-processed observational data

We have developed a new observational screening technique for inverse model. This technique was applied to our transport models with re-analysed meteorological data and the inverse model to estimate the global distribution of CO2 concentrations and fluxes. During the 1990s, we estimated a total CO2 uptake by the biosphere of 1.4–1.5 PgC yr-1 and a total CO2 uptake by the oceans of 1.7–1.8 PgC yr-1. The uncertainty of global CO2 flux estimation is about 0.3 PgC yr-1. We also obtained monthly surface CO2 concentrations in the marine boundary layer to precisions of 0.5–1.0 ppm. To utilize non-processed (statistical monthly mean) observational data in our analysis, we developed a quality control procedure for such observational data including a repetition of inversion. This technique is suitable for other inversion setups. Observational data by ships were placed into grids and used in our analysis to add to the available data from fixed stations. The estimated global distributions are updated and extended every year.

Aerosol data assimilation using data from Himawari-8, a next-generation geostationary meteorological satellite

Himawari-8, a next-generation geostationary meteorological satellite, was launched on 7 October 2014 and became operational on 7 July 2015. The advanced imager on board Himawari-8 is equipped with 16 observational bands (including three visible and three near-infrared bands) that enable retrieval of full-disk aerosol optical properties at 10 min intervals from geostationary (GEO) orbit. Here we show the first application of aerosol optical properties (AOPs) derived from Himawari-8 data to aerosol data assimilation. Validation of the assimilation experiment by comparison with independent observations demonstrated successful modeling of continental pollution that was not predicted by simulation without assimilation and reduced overestimates of dust front concentrations. These promising results suggest that AOPs derived from Himawari-8/9 and other planned GEO satellites will considerably improve forecasts of air quality, inverse modeling of emissions, and aerosol reanalysis through assimilation techniques.

Tracer transport model at Japan meteorological agency and its application to the ETEX data

This paper describes the JMA tracer transport model and its sensitivity to model physics and initial conditions by using the ETEX data. Compared with observations, the model overestimates ground-level concentration in the early stage within about one day from the emission, possibly due to underestimation of vertical diffusion. In the early stage, the enhanced vertical diffusion effectively transports the tracer upward and decreases the ground-level concentration, while in the later stage, it enhances downward transports from the upper layer and increases the ground-level concentration. A conceptual model is given for understanding the vertical transport due to vertical diffusion. The horizontal diffusion introduced to the model has preferable impacts on forecasts especially in the early stage. Finally, we discuss the predictability of this model based on sensitivity to initial conditions of emission time and height.

Iconic CO2 Time Series at Risk

The steady rise in atmospheric long-lived greenhouse gas concentrations is the main driver of contemporary climate change. The Mauna Loa CO2 time series (1, 2), started by C. D. Keeling in 1958 and maintained today by the Scripps Institution of Oceanography and the Earth System Research Laboratory (ESRL) of NOAA, is iconic evidence of the effect of human-caused fossil fuel and land-use change emissions on the atmospheric increase of CO2. The continuity of such records depends critically on having stable funding, which is challenging to maintain in the context of 3- to 4-year research grant funding cycles (3), and is currently threatened by the financial crisis. The ESRL Global Monitoring Division maintains a network of about 100 surface and aircraft sites worldwide at which whole air samples are collected approximately every week for analysis of CO2, CH4, CO, halocarbons, and many other chemical species (4). This is complemented by high-frequency measurements at the Mauna Loa, Barrow, American Samoa, and South Pole observatories, and about 10 North American tall towers. The success of the NOAA program has inspired similar efforts in Europe (5), China (6), India (7), and Brazil (8), with the United Nations World Meteorological Organization providing guidance and precision requirements through the Global Atmosphere Watch program (9), but no funding. The data collected by NOAA and its worldwide partners have been used not only to demonstrate the unassailable rise of atmospheric greenhouse gas concentrations, but also to infer the magnitudes, locations, and times of surface-atmosphere exchange of those gases based on small concentration gradients between sites (10). Important findings from analysis of these records include the detection of a significant terrestrial carbon sink at northern mid-latitudes (11) and subsequent research aimed at identifying the mechanisms by which that sink must operate. Long-term, high-quality, atmospheric measurements are crucial for quantifying trends in greenhouse gas fluxes and attributing them to fossil fuel emissions, changes in land-use and management, or the response of natural land and ocean ecosystems to climate change and elevated CO2 concentrations. Greenhouse gas measurements along tall towers in the interior continents allow quantification of regional sources and sinks, which has a very high relevance for measuring the effectiveness of climate policy. NOAA ESRL provides measurements that are critical for the U.S. national security in that they provide independent verification and early warning of changing greenhouse gas emissions from countries involved in efforts to mitigate greenhouse gases. Dedicated carbon-observing satellites such as GOSAT and OCO-2 are needed to fill in the missing geographical information required for verification of carbon flux mitigation efforts. However, satellite retrievals do not yet provide sufficient information to deliver new constraints on surface fluxes, although quick progress is being made in this direction. In situ observations are crucial for anchoring space-borne measurements, for detecting potential biases of remote sensing techniques, and for providing continuity given the finite lifetime of satellites. Despite the growing importance of greenhouse gas observations to humanity, substantial budget cuts at NOAA have resulted in curtailment of our ability to observe and understand changes to the global carbon cycle. Already, a dozen surface flask-sampling sites have been removed from NOAAs operational network and aircraft profiling sites have been eliminated and reduced in frequency at the remaining NOAA sites. The planned growth in the tall tower program has stopped, and plans for closing some towers are being developed. The U.S. budget process in this election year, with the added risk of mandatory across-the-board cuts due to the 2011 Budget Control Act, foretells more bleak news for greenhouse gas monitoring at NOAA and could cause further retreat from the goal of recording ongoing changes in atmospheric composition. As scientists, we believe that preserving the continuity of these vital time series must remain a priority for U.S. carbon cycle research.

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.