Dmitry Belikov

Influence of differences in current GOSAT XCO2 retrievals on surface flux estimation

We investigated differences in the five currently-available datasets of column-integrated CO2 concentrations (XCO2) retrieved from spectral soundings collected by Greenhouse gases Observing SATellite (GOSAT) and assessed their impact on regional CO2 flux estimates. We did so by estimating the fluxes from each of the five XCO2 datasets combined with surface-based CO2 data, using a single inversion system. The five XCO2 datasets are available in raw and bias-corrected versions, and we found that the bias corrections diminish the range of the five coincident values by ~30% on average. The departures of the five individual inversion results (annual-mean regional fluxes based on XCO2-surface combined data) from the surface-data-only results were close to one another in some terrestrial regions where spatial coverage by each XCO2 dataset was similar. The mean of the five annual global land uptakes was 1.7 ± 0.3 GtC yr−1, and they were all smaller than the value estimated from the surface-based data alone.

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.

Simultaneous retrieval of atmospheric CO2 and light path modification from space-based spectroscopic observations of greenhouse gases: methodology and application to GOSAT measurements over TCCON sites

This paper presents an improved photon path length probability density function method that permits simultaneous retrievals of column-average greenhouse gas mole fractions and light path modifications through the atmosphere when processing high-resolution radiance spectra acquired from space. We primarily describe the methodology and retrieval setup and then apply them to the processing of spectra measured by the Greenhouse gases Observing SATellite (GOSAT). We have demonstrated substantial improvements of the data processing with simultaneous carbon dioxide and light path retrievals and reasonable agreement of the satellite-based retrievals against ground-based Fourier transform spectrometer measurements provided by the Total Carbon Column Observing Network (TCCON).

Inter-annual variability of summertime CO2 exchange in Northern Eurasia inferred from GOSAT XCO2

Northern Eurasia is one of the largest terrestrial carbon reservoirs on the Earths surface. However, since the coverage of surface CO2 observations is still limited, the response to the climate variability remains uncertain. We estimated monthly CO2 fluxes for three sub-regions in Northern Eurasia (north of ~60?N), Northeastern Europe, Western Siberia and Eastern Siberia, using CO2 retrievals from the Japanese Greenhouse Gases Observing SATellite (GOSAT). The variations of estimated CO2 fluxes were examined in terms of the regional climate variability, for the three consecutive growing seasons of 2009?2011. The CO2 fluxes estimated using GOSAT data are highly correlated with the surface temperature anomalies in July and August (r?>?0.8) while no correlation is found in the CO2 fluxes estimated only using surface observations. The estimated fluxes from GOSAT data exhibit high negative correlations with one-month lagged positive precipitation anomalies in late summer (r?>??0.7) through surface temperature and the Normalized Difference Vegetation Index (NDVI). The results indicate that GOSAT data reflects the changes in terrestrial biospheric processes responding to climate anomalies. In 2010, a large part of Eurasia experienced an extremely hot and dry summer, while cold and wet weather conditions were recorded in Western Siberia. The CO2 fluxes estimated from GOSAT data showed a reduction of net CO2 uptake in Northeastern Europe and Eastern Siberia, but the enhancement of net CO2 uptake in Western Siberia. These opposite sub-regional flux anomalies can be explained by the different climate anomalies on a sub-regional scale in Northern Eurasia. Thus, this study demonstrates that space-based observations by GOSAT compensate for the lack of ground-based observational coverage so as to better capture the inter-annually varying atmosphere-terrestrial biosphere CO2 exchange on a regional scale.

A decadal inversion of CO2 using the Global Eulerian–Lagrangian Coupled Atmospheric model (GELCA): sensitivity to the ground-based observation network

Abstract We present an assimilation system for atmospheric carbon dioxide (CO2) using a Global Eulerian–Lagrangian Coupled Atmospheric model (GELCA), and demonstrate its capability to capture the observed atmospheric CO2 mixing ratios and to estimate CO2 fluxes. With the efficient data handling scheme in GELCA, our system assimilates non-smoothed CO2 data from observational data products such as the Observation Package (ObsPack) data products as constraints on surface fluxes. We conducted sensitivity tests to examine the impact of the site selections and the prior uncertainty settings of observation on the inversion results. For these sensitivity tests, we made five different site/data selections from the ObsPack product. In all cases, the time series of the global net CO2 flux to the atmosphere stayed close to values calculated from the growth rate of the observed global mean atmospheric CO2 mixing ratio. At regional scales, estimated seasonal CO2 fluxes were altered, depending on the CO2 data selected for assimilation. Uncertainty reductions were determined at the regional scale and compared among cases. As measures of the model–data mismatch, we used the model–data bias, root-mean-square error, and the linear correlation. For most observation sites, the model–data mismatch was reasonably small. Regarding regional flux estimates, tropical Asia was one of the regions that showed a significant impact from the observation network settings. We found that the surface fluxes in tropical Asia were the most sensitive to the use of aircraft measurements over the Pacific, and the seasonal cycle agreed better with the results of bottom-up studies when the aircraft measurements were assimilated. These results confirm the importance of these aircraft observations, especially for constraining surface fluxes in the tropics.

Retrievals of atmospheric CO2, CH4 and optical path modifications from the GOSAT observations

We present satellite-based data of the column-averaged dry air mole fraction of atmospheric carbon dioxide (XCO2) and methane (XCH4), which were derived from the radiance spectra measured by Greenhouse gases Observing SATellite (GOSAT). We have applied new version of the Photon path-length Probability Density Function (PPDF)-based algorithm to estimate XCO2 and PPDF parameters. These parameters serve to allow for optical path modification due to atmospheric light scattering and they are retrieved simultaneously with CO2 concentration using radiance spectra from all available GOSAT short wave infrared (SWIR) bands (oxygen A-band, 1.6-μm, and 2.0-μm CO2 absorption bands). For the methane abundance, retrieved from 1.67-μm absorption band, we applied optical path correction based on PPDF parameters from 1.6-μm CO2 absorption band. Similarly to widely used CO2-proxy technique, this correction assumes identical light path modifications in 1.67-μm and 1.6-μm bands. This approach is believed to offer some advantages over the proxy technique since it does not use any prior assumptions on carbon dioxide concentrations. Both carbon dioxide and methane GOSAT retrievals were validated using ground-based Fourier Transform Spectrometer (FTS) measurements provided by the Total Carbon Column Observing Network (TCCON). For XCO2 retrievals we found subppm station-to-station bias (GOSAT versus TCCON); single-scan precision of mostly below 2 ppm (0.5%); and correlation coefficient for the Northern Hemisphere TCCON stations above 0.8. For XCH4 retrievals over TCCON sites we found single-scan precision below 1 % and correlation coefficient above 0.8.

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.

Simulation of Doppler lidar measurements using the WRF and Yamada-Mellor models

In this paper the numerical simulation results of mean wind velocity vector and its measurement error for VAD technique using Weather Research and Forecasting Model (WRF) and Yamada-Mellor models are presented. The numerical model takes into account the non-Gaussian and nonstationary characteristics of the Doppler lidar signal. The numerical simulation results were compared with CASES-99 experimental data from balloon sonde (GLASS) and the Doppler Lidar. It shows that results of numerical simulation by WRF and Yamada-Mellor models agree well with experimental data for potential temperature. Yamada-Mellor model describes the nocturnal low-level jet only up to 100 m and above the fit is fairly bad. But WRF model allows us to have a good comparison for all levels. In case of the strong turbulence the value of measurement error can greatly surpass the value 0.5 m/s; therefore it does not satisfy World Meteorological Organization (WMO) requirements for wind. For the high spatial resolution we cannot get the required accuracy.

Letter tot the editor: 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.

Iconic CO2 Time Series at Risk - eScholarship

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.