Bias-correcting carbon fluxes derived from land-surface satellite data for retrospective and near-real-time assimilation systems
Brad Weir,Brad Weir,Lesley Ott,G. J. Collatz,Stephan R. Kawa,Benjamin Poulter,Abhishek Chatterjee,Abhishek Chatterjee,Tomohiro Oda,Tomohiro Oda,Steven Pawson +10 more
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TLDR
In this article, the authors describe techniques for bias-correcting surface fluxes derived from satellite observations of the Earth's surface to be consistent with constraints from inventories and in situ CO2 datasets.Abstract:
. The ability to monitor and understand natural and anthropogenic variability in
atmospheric carbon dioxide ( CO2 ) is a growing need of many stakeholders across the world. Systems that assimilate satellite observations, given their
short latency and dense spatial coverage, into high-resolution global models are valuable, if not essential, tools for addressing this need. A notable drawback of modern assimilation systems is the long latency of many vital input datasets; for example, inventories, in situ measurements, and reprocessed remote-sensing data can trail the current date by months to years. This paper describes techniques for bias-correcting surface fluxes derived from satellite
observations of the Earth's surface to be consistent with constraints from
inventories and in situ CO2 datasets. The techniques are applicable in both short-term forecasts and retrospective simulations, thus taking advantage of the coverage and short latency of satellite data while reproducing the major features of long-term inventory and in situ records. Our approach begins with
a standard collection of diagnostic fluxes which incorporate a variety of
remote-sensing driver data, viz. vegetation indices, fire radiative power, and nighttime lights. We then apply an empirical sink so that global budgets of the diagnostic fluxes match given atmospheric and oceanic growth rates for each year. This step removes coherent, systematic flux errors that produce biases in CO2 which mask the signals an assimilation system hopes to capture. Depending on the simulation mode, the empirical sink uses different choices of atmospheric growth rates: estimates based on observations in retrospective mode
and projections based on seasonal forecasts of sea surface temperature in
forecasting mode. The retrospective fluxes, when used in simulations with
NASA's Goddard Earth Observing System (GEOS), reproduce marine boundary layer
measurements with comparable skill to those using fluxes from a modern
inversion system. The forecasted fluxes show promising accuracy in their
application to the analysis of changes in the carbon cycle as they occur.read more
Citations
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Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations
Abstract: We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5 degrees x 0.5 degrees spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 +/- 7 J x 10(18) yr(-1)), H (164 +/- 15 J x 10(18) yr(-1)), and GPP (119 +/- 6 Pg C yr(-1)) were similar to independent estimates. Our global TER estimate (96 +/- 6 Pg C yr(-1)) was likely underestimated by 5-10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.
The Orbiting Carbon Observatory (OCO) Mission
TL;DR: This article collected the first space-based measurements of atmospheric CO2 with the precision, resolution, and coverage needed to characterize its sources and sinks on regional scales and quantify their variability over the seasonal cycle.
Posted Content
The declining uptake rate of atmospheric CO2 by land and ocean sinks
Michael R. Raupach,Manuel Gloor,Jorge L. Sarmiento,Josep G. Canadell,Thomas L. Frölicher,Thomas Gasser,Richard A. Houghton,C. Le Quere,Cathy M. Trudinger +8 more
TL;DR: In this paper, the authors show that the CO 2 sink rate (kS) of land and ocean CO2 sinks declined by a factor of about 1/3 between 1959-2012, implying that CO2 sink increased more slowly than excess CO2.
Journal Article
Response of the Amazon carbon balance to the 2010 drought derived with CarbonTracker South America
Ingrid T. van der Laan-Luijkx,Ivar R. van der Velde,Maarten Krol,Luciana V. Gatti,John B. Miller,John B. Miller,Manuel Gloor,Thijs T. van Leeuwen,Johannes W. Kaiser,Christine Wiedinmyer,Sourish Basu,Sourish Basu,Cathy Clerbaux,Wouter Peters +13 more
TL;DR: In this article, the results from the CarbonTracker South America data assimilation system suggest that carbon uptake by vegetation was indeed reduced in 2010, but that the magnitude of the decrease strongly depends on the estimated 2010 and 2011 biomass burning emissions.
Journal ArticleDOI
Four years of global carbon cycle observed from the Orbiting Carbon Observatory 2 (OCO-2) version 9 and in situ data and comparison to OCO-2 version 7
Hélène E. Peiro,Sean Crowell,Andrew Schuh,David H. Baker,Christopher W. O'Dell,Andrew R. Jacobson,Frédéric Chevallier,Junjie Liu,Annmarie Eldering,David Crisp,Feng Deng,Brad Weir,Sourish Basu,Sajeev Philip,Ian Baker +14 more
TL;DR: In this paper , an ensemble of 10 atmospheric inversions all characterized by different transport models, data assimilation algorithms, and prior fluxes using first OCO-2 v7 in 2015-2016 and then OCO2 version 9 land observations for the longer period 2015-2018.
References
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Journal ArticleDOI
A Large and Persistent Carbon Sink in the World’s Forests
Yude Pan,Richard Birdsey,Jingyun Fang,Jingyun Fang,Richard A. Houghton,Pekka E. Kauppi,Werner A. Kurz,Oliver L. Phillips,Anatoly Shvidenko,Simon L. Lewis,Josep G. Canadell,Philippe Ciais,Robert B. Jackson,Stephen W. Pacala,A. David McGuire,Shilong Piao,Aapo Rautiainen,Stephen Sitch,Daniel J. Hayes +18 more
TL;DR: The total forest sink estimate is equivalent in magnitude to the terrestrial sink deduced from fossil fuel emissions and land-use change sources minus ocean and atmospheric sinks, with tropical estimates having the largest uncertainties.
Journal ArticleDOI
MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications
Michele M. Rienecker,Max J. Suarez,Ronald Gelaro,Ricardo Todling,Julio T. Bacmeister,Julio T. Bacmeister,Emily Liu,Emily Liu,Michael G. Bosilovich,Siegfried D. Schubert,Lawrence L. Takacs,Lawrence L. Takacs,Gi-Kong Kim,S. C. Bloom,S. C. Bloom,Junye Chen,Junye Chen,Douglas Collins,Douglas Collins,Austin Conaty,Austin Conaty,Arlindo da Silva,Wei Gu,Wei Gu,Joanna Joiner,Randal D. Koster,Robert A. Lucchesi,Robert A. Lucchesi,Andrea Molod,Andrea Molod,Tommy Owens,Tommy Owens,Steven Pawson,Philip Pegion,Philip Pegion,Christopher R. Redder,Christopher R. Redder,Rolf H. Reichle,Franklin R. Robertson,Albert G. Ruddick,Albert G. Ruddick,Meta Sienkiewicz,Meta Sienkiewicz,John S. Woollen +43 more
TL;DR: The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA's Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA's Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses as mentioned in this paper.
Journal ArticleDOI
The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)
Ronald Gelaro,Will McCarty,Max J. Suarez,Max J. Suarez,Ricardo Todling,Andrea Molod,Lawrence L. Takacs,Cynthia A. Randles,Cynthia A. Randles,Anton Darmenov,Michael G. Bosilovich,Rolf H. Reichle,Krzysztof Wargan,Lawrence Coy,Richard I. Cullather,Richard I. Cullather,Clara S. Draper,Clara S. Draper,Santha Akella,V. Buchard,V. Buchard,Austin Conaty,Arlindo da Silva,Wei Gu,Gi-Kong Kim,Randal D. Koster,Robert A. Lucchesi,Dagmar Merkova,J. E. Nielsen,Gary Partyka,Steven Pawson,William M. Putman,Michele M. Rienecker,Siegfried D. Schubert,Meta Sienkiewicz,Bin Zhao,Bin Zhao +36 more
TL;DR: An overview of the MERRA-2 system and various performance metrics is provided, including the assimilation of aerosol observations, several improvements to the representation of the stratosphere including ozone, and improved representations of cryospheric processes.
Supporting Online Material for A Large and Persistent Carbon Sink in the World's Forests
Yude Pan,Richard A. Birdsey,Jingyun Fang,Richard A. Houghton,Pekka E. Kauppi,Werner A. Kurz,Oliver L. Phillips,Anatoly Shvidenko,Simon L. Lewis,Philippe Ciais,Robert B. Jackson,Stephen W. Pacala,A. David McGuire,Shilong Piao,Aapo Rautiainen,Stephen Sitch,Daniel J. Hayes +16 more
Journal ArticleDOI
On the temperature dependence of soil respiration
Jon Lloyd,John Taylor +1 more
TL;DR: An empirical equation is presented which yields an unbiased estimator of respiration rates over a wide range of temperatures and provides representative estimates of the seasonal cycle of net ecosystem productivity and its effects on atmospheric CO 2.
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