scholarly journals Constraining estimates of terrestrial carbon uptake: new opportunities using long‐term satellite observations and data assimilation

2019 ◽  
Vol 225 (1) ◽  
pp. 105-112 ◽  
Author(s):  
William K. Smith ◽  
Andrew M. Fox ◽  
Natasha MacBean ◽  
David J. P. Moore ◽  
Nicholas C. Parazoo
Keyword(s):  
Data Assimilation ◽  
Satellite Observations ◽  
Carbon Uptake ◽  
Terrestrial Carbon

scholarly journals On the application and interpretation of Keeling plots in paleo climate research – deciphering δ<sup>13</sup>C of atmospheric CO<sub>2</sub> measured in ice cores

2006 ◽  
Vol 3 (4) ◽  
pp. 539-556 ◽  
Author(s):  
P. Köhler ◽  
H. Fischer ◽  
J. Schmitt ◽  
G. Munhoven
Keyword(s):  
Carbon Cycle ◽  
Ice Cores ◽  
Global Carbon Cycle ◽  
Isotopic Signature ◽  
Carbon Uptake ◽  
Terrestrial Carbon ◽  
Keeling Plot ◽  
Long Term Changes ◽  
Global Carbon

Abstract. The Keeling plot analysis is an interpretation method widely used in terrestrial carbon cycle research to quantify exchange processes of carbon between terrestrial reservoirs and the atmosphere. Here, we analyse measured data sets and artificial time series of the partial pressure of atmospheric carbon dioxide (pCO2) and of δ13C of CO2 over industrial and glacial/interglacial time scales and investigate to what extent the Keeling plot methodology can be applied to longer time scales. The artificial time series are simulation results of the global carbon cycle box model BICYCLE. The signals recorded in ice cores caused by abrupt terrestrial carbon uptake or release loose information due to air mixing in the firn before bubble enclosure and limited sampling frequency. Carbon uptake by the ocean cannot longer be neglected for less abrupt changes as occurring during glacial cycles. We introduce an equation for the calculation of long-term changes in the isotopic signature of atmospheric CO2 caused by an injection of terrestrial carbon to the atmosphere, in which the ocean is introduced as third reservoir. This is a paleo extension of the two reservoir mass balance equations of the Keeling plot approach. It gives an explanation for the bias between the isotopic signature of the terrestrial release and the signature deduced with the Keeling plot approach for long-term processes, in which the oceanic reservoir cannot be neglected. These deduced isotopic signatures are similar (−8.6‰) for steady state analyses of long-term changes in the terrestrial and marine biosphere which both perturb the atmospheric carbon reservoir. They are more positive than the δ13C signals of the sources, e.g. the terrestrial carbon pools themselves (−25‰). A distinction of specific processes acting on the global carbon cycle from the Keeling plot approach is not straightforward. In general, processes related to biogenic fixation or release of carbon have lower y-intercepts in the Keeling plot than changes in physical processes, however in many case they are indistinguishable (e.g. ocean circulation from biogenic carbon fixation).

scholarly journals Large influence of soil moisture on long-term terrestrial carbon uptake

Nature ◽  
2019 ◽  
Vol 565 (7740) ◽  
pp. 476-479 ◽  
Author(s):  
Julia K. Green ◽  
Sonia I. Seneviratne ◽  
Alexis M. Berg ◽  
Kirsten L. Findell ◽  
Stefan Hagemann ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Carbon Uptake ◽  
Terrestrial Carbon ◽  
Large Influence

scholarly journals Connecting Satellite Observations with Water Cycle Variables Through Land Data Assimilation: Examples Using the NASA GEOS-5 LDAS

2013 ◽  
Vol 35 (3) ◽  
pp. 577-606 ◽  
Author(s):  
Rolf H. Reichle ◽  
Gabriëlle J. M. De Lannoy ◽  
Barton A. Forman ◽  
Clara S. Draper ◽  
Qing Liu
Keyword(s):  
Data Assimilation ◽  
Water Cycle ◽  
Satellite Observations ◽  
Land Data Assimilation

scholarly journals Reviews and syntheses: Flying the satellite into your model: on the role of observation operators in constraining models of the Earth system and the carbon cycle

2017 ◽  
Vol 14 (9) ◽  
pp. 2343-2357 ◽  
Author(s):  
Thomas Kaminski ◽  
Pierre-Philippe Mathieu
Keyword(s):  
Data Assimilation ◽  
Carbon Cycle ◽  
Automatic Differentiation ◽  
Satellite Observations ◽  
Spectral Radiance ◽  
Special Focus ◽  
Earth System ◽  
The Earth ◽  
Retrieval Scheme

Abstract. The vehicles that fly the satellite into a model of the Earth system are observation operators. They provide the link between the quantities simulated by the model and the quantities observed from space, either directly (spectral radiance) or indirectly estimated through a retrieval scheme (biogeophysical variables). By doing so, observation operators enable modellers to properly compare, evaluate, and constrain their models with the model analogue of the satellite observations. This paper provides the formalism and a few examples of how observation operators can be used in combination with data assimilation techniques to better ingest satellite products in a manner consistent with the dynamics of the Earth system expressed by models. It describes commonalities and potential synergies between assimilation and classical retrievals. This paper explains how the combination of observation operators and their derivatives (linearizations) form powerful research tools. It introduces a technique called automatic differentiation that greatly simplifies both the development and the maintenance of code for the evaluation of derivatives. Throughout this paper, a special focus lies on applications to the carbon cycle.

scholarly journals Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

2017 ◽  
Author(s):  
Marko Scholze ◽  
Michael Buchwitz ◽  
Wouter Dorigo ◽  
Luis Guanter ◽  
Shaun Quegan
Keyword(s):  
Data Assimilation ◽  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Full Description ◽  
Model Data ◽  
Terrestrial Carbon ◽  
Carbon Cycle Model ◽  
Terrestrial Carbon Cycle ◽  
Uncertainty Estimates ◽  
Global Carbon

Abstract. The global carbon cycle is an important component of the Earth system and it interacts with the hydrological, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification 5 of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by model-data fusion or data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation, and systematic and 10 well error-characterized observations relevant to the carbon cycle. Relevant observations for assimilation include various in-situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model 15 benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current 20 observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al. (2005) emphasising the rapid advance in relevant space-based observations.

scholarly journals NH<sub>3</sub> emissions from large point sources derived from CrIS and IASI satellite observations

2019 ◽  
Vol 19 (19) ◽  
pp. 12261-12293 ◽  
Author(s):  
Enrico Dammers ◽  
Chris A. McLinden ◽  
Debora Griffin ◽  
Mark W. Shephard ◽  
Shelley Van Der Graaf ◽  
...  
Keyword(s):  
Human Health ◽  
Reactive Nitrogen Species ◽  
Point Sources ◽  
Satellite Observations ◽  
Atmospheric Sounding ◽  
Order Of Magnitude ◽  
Short And Long Term ◽  
Current Emission ◽  
Cross Track

Abstract. Ammonia (NH3) is an essential reactive nitrogen species in the biosphere and through its use in agriculture in the form of fertilizer (important for sustaining humankind). The current emission levels, however, are up to 4 times higher than in the previous century and continue to grow with uncertain consequences to human health and the environment. While NH3 at its current levels is a hazard to environmental and human health, the atmospheric budget is still highly uncertain, which is a product of an overall lack of measurements. The capability to measure NH3 with satellites has opened up new ways to study the atmospheric NH3 budget. In this study, we present the first estimates of NH3 emissions, lifetimes and plume widths from large (>∼5 kt yr−1) agricultural and industrial point sources from Cross-track Infrared Sounder (CrIS) satellite observations across the globe with a consistent methodology. The same methodology is also applied to the Infrared Atmospheric Sounding Interferometer (IASI) (A and B) satellite observations, and we show that the satellites typically provide comparable results that are within the uncertainty of the estimates. The computed NH3 lifetime for large point sources is on average 2.35±1.16 h. For the 249 sources with emission levels detectable by the CrIS satellite, there are currently 55 locations missing (or underestimated by more than an order of magnitude) from the current Hemispheric Transport Atmospheric Pollution version 2 (HTAPv2) emission inventory and only 72 locations with emissions within a factor of 2 compared to the inventories. The CrIS emission estimates give a total of 5622 kt yr−1, for the sources analyzed in this study, which is around a factor of ∼2.5 higher than the emissions reported in HTAPv2. Furthermore, the study shows that it is possible to accurately detect short- and long-term changes in emissions, demonstrating the possibility of using satellite-observed NH3 to constrain emission inventories.

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