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All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Model Simulations of CO2 Transport Using Assimilated Meteorological Fields

The numerical simulation of CO2 transport (and other tracers such as CO, CH4, and biomass burning tracers) in the atmosphere is required to determine the fate of anthropogenic source gases. Estimation of the CO2 exchange between the ocean surface, the terrestrial biosphere, and the atmosphere is of first-order importance to understanding the global carbon cycle and the processes that are most crucial in determining the atmospheric CO2 concentration. Forward transport simulations have been conducted using two-dimensional, time-dependent grids of average surface fluxes (from TRANSCOM) and three-dimensional wind data from a prototype data assimilation system (FV-DAS) run by the Goddard Data Assimilation Office. The objective is to better understand the contribution of meteorological variability to changes in CO2 and other constituents, By accurately accounting for meteorological variability, through use of assimilated winds, we hope to better characterize the distribution of surface sources and sinks (and chemistry where applicable). With assimilated meteorology such chemistry/transport runs provide the basic framework to analyze existing (and proposed) measurement data on a point-by-point, real-time basis. We compare with measured CO2 concentration gradients on a daily, seasonal, regional, and interhemispheric basis to examine the consistency of sources, sinks, and transport formulation. We will also examine the inter-annual variability of atmospheric CO2 due to atmospheric circulation changes using longer runs with assimilated winds.

Kaea, S. R.↗
NASA NTRS1998

Assessment of Anthropogenic and Climatic Impacts on the Global Carbon Cycle Using a 3-D Model Constrained by Isotopic Carbon Measurements and Remote Sensing of Vegetation

Our original proposal called for improved modeling of the terrestrial biospheric carbon cycle, specifically using biome-specific process models to account for both the energy and water budgets of plant growth, to facilitate investigations into recent changes in global atmospheric CO2 abundance and regional distribution. The carbon fluxes predicted by these models were to be incorporated into a global model of CO2 transport to establish large-scale regional fluxes of CO2 to and from the terrestrial biosphere subject to constraints imposed by direct measurements of atmospheric CO2 and its 13C/12C isotopic ratio. Our work was coordinated with a NASA project (NASA NAGW-3151) at the University of Montana under the direction of Steven Running, and was partially funded by the Electric Power Research Institute. The primary objective of this project was to develop and test the Biome-BGC model, a global biological process model with a daily time step which simulates the water, energy and carbon budgets of plant growth. The primary product, the unique global gridded daily land temperature, and the precipitation data set which was used to drive the process model is described. The Biome-BGC model was tested by comparison with a simpler biological model driven by satellite-derived (NDVI) Normalized Difference Vegetation Index and (PAR) Photosynthetically Active Radiation data and by comparison with atmospheric CO2 observations. The simple NDVI model is also described. To facilitate the comparison with atmospheric CO2 observations, a three-dimensional atmospheric transport model was used to produce predictions of atmospheric CO2 variations given CO2 fluxes owing to (NPP) Net Primary Productivity and heterotrophic respiration that were produced by the Biome-BGC model and by the NDVI model. The transport model that we used in this project, and errors associated with transport simulations, were characterized by a comparison of 12 transport models.

Keeling, Charles D.↗
NASA NTRS2018

Impacts of Land Carbon Flux Variability on Variations in Atmospheric CO2

To better understand the role of atmospheric CO2 in the global carbon cycle, it is important to understand the factors that control its variability in time and space. Here we investigate these factors using a coupled land-atmosphere modeling system (the NASA GEOS-5 model) fitted with land carbon physics and atmospheric CO2 transport. To separate the influences of land carbon flux variability and atmospheric transport variability on the variability of CO2 concentrations, we conducted two carbon-fitted GEOS-5 AGCM simulations run in replay mode (a technique that guides the model's weather to match that of the MERRA-2 reanalysis): (i) a control simulation of 15-year carbon cycle dynamics and climate, and (ii) a simulation in which the climatological seasonal cycles of net biosphere production (NBP), as determined from diagnostics produced in the control experiment, are applied at the surface to the atmosphere instead. The impact of land flux variability on atmospheric CO2 variability is then isolated by subtracting the variability inherent in the second simulation (as induced, e.g., by strong El Nino conditions) from that in the control. These results are also presented in the context of supplemental simulations that have examined the impact of imposed drought in a free running AGCM simulation on carbon fluxes and atmospheric CO2 variability.

Lee, Eunjee↗
NASA NTRS2010

The Use of a Pseudo Noise Code for DIAL Lidar

Retrievals of CO2 profiles within the planetary boundary layer (PBL) are required to understand CO2 transport over regional scales and for validating the future space borne CO2 remote sensing instrument, such as the CO2 Laser Sounder, for the ASCENDS mission, We report the use of a return-to-zero (RZ) pseudo noise (PN) code modulation technique for making range resolved measurements of CO2 within the PBL using commercial, off-the-shelf, components. Conventional, range resolved, measurements require laser pulse widths that are s#rorter than the desired spatial resolution and have pulse spacing such that returns from only a single pulse are observed by the receiver at one time (for the PBL pulse separations must be greater than approximately 2000m). This imposes a serious limitation when using available fiber lasers because of the resulting low duty cycle (less than 0.001) and consequent low average laser output power. RZ PN code modulation enables a fiber laser to operate at much higher duty cycles (approaching 0.1) thereby more effectively utilizing the amplifier's output. This results in an increase in received counts by approximately two orders of magnitude. The approach involves employing two, back to back, CW fiber amplifiers seeded at the appropriate on and offline CO2 wavelengths (approximately 1572 nm) using distributed feedback diode lasers modulated by a PN code at rates significantly above 1 megahertz. An assessment of the technique, discussions of measurement precision and error sources as well as preliminary data will be presented.

Burris, John F.↗
NASA NTRS1988

A study of carbon monoxide distribution determinations for a global transport model

The primary objective of this grant was to further the development of a global transport/chemistry model that simulates the physico-chemical behavior of methane and carbon monoxide in the troposphere. The computer simulation model is designed to analyze the processes that occur as methane and carbon monoxide are transported from their respective sources to their ultimate fate, e.g., final conversion to CO2, transport to the stratosphere, deposition at ground level, etc.

Peters, Leonard K.↗
NASA NTRS2010

Comparing Global Atmospheric CO2 Flux and Transport Models with Remote Sensing (and Other) Observations

We report recent progress derived from comparison of global CO2 flux and transport models with new remote sensing and other sources of CO2 data including those from satellite. The overall objective of this activity is to improve the process models that represent our understanding of the workings of the atmospheric carbon cycle. Model estimates of CO2 surface flux and atmospheric transport processes are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, to provide the basic framework for carbon data assimilation, and ultimately for future projections of carbon-climate interactions. Models can also be used to test consistency within and between CO2 data sets under varying geophysical states. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 2000 through 2009. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at 1x1 degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-3), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to remote sensing observations from TCCON, GOSAT, and AIRS as well as relevant in situ observations. Examples of the influence of key process representations are shown from both forward and inverse model comparisons. We find that the model can resolve much of the synoptic, seasonal, and interannual variability in the observations, although reasons for persistent discrepancies in northern hemisphere vegetation uptake are examined. At this time, we do not find any serious shortcomings in the model transport representation, but this is still the subject of close scrutiny. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in CO2 fluxes and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.

Kawa, S. R.↗
NASA NTRS2016

Advanced Supported Liquid Membranes for Carbon Dioxide Control in Cabin Applications

The development of new, robust, life support systems is critical to NASA's continued progress in space exploration. One vital function is maintaining the carbon dioxide (CO2) concentration in the cabin at levels that do not impair the health or performance of the crew. The CO2 removal assembly (CDRA) is the current CO2 control technology on-board the International Space Station (ISS). Although the CDRA has met the needs of the ISS to date, the repeated cycling of the molecular sieve sorbent causes it to break down into small particles that clog filters or generate dust in the cabin. This reduces reliability and increases maintenance requirements. Another approach that has potential advantages over the current system is a membrane that separates CO2 from air. In this approach, cabin air contacts one side of the membrane while other side of the membrane is maintained at low pressure to create a driving force for CO2 transport across the membrane. In this application, the primary power requirement is for the pump that creates the low pressure and then pumps the CO2 to the oxygen recovery system. For such a membrane to be practical, it must have high CO2 permeation rate and excellent selectivity for CO2 over air. Unfortunately, conventional gas separation membranes do not have adequate CO2 permeability and selectivity to meet the needs of this application. However, the required performance could be obtained with a supported liquid membrane (SLM), which consists of a microporous material filled with a liquid that selectively reacts with CO2 over air. In a recently completed Phase II SBIR project, Reaction Systems, Inc. fabricated an SLM that is very close to meeting permeability and selectivity objectives for use in the advanced space suit portable life support system. This paper describes work carried out to evaluate its potential for use in spacecraft cabin application.

Wickham, David T.↗
NASA NTRS2016

Advanced Supported Liquid Membranes for Carbon Dioxide Control in Cabin Applications

The development of new, robust, life support systems is critical to NASA's continued progress in space exploration. One vital function is maintaining the carbon dioxide (CO2) concentration in the cabin at levels that do not impair the health or performance of the crew. The carbon dioxide removal assembly (CDRA) is the current CO2 control technology on-board the International Space Station (ISS). Although the CDRA has met the needs of the ISS to date, the repeated cycling of the molecular sieve sorbent causes it to break down into small particles that clog filters or generate dust in the cabin. This reduces reliability and increases maintenance requirements. Another approach that has potential advantages over the current system is a membrane that separates CO2 from air. In this approach, cabin air contacts one side of the membrane while other side of the membrane is maintained at low pressure to create a driving force for CO2 transport across the membrane. In this application, the primary power requirement is for the pump that creates the low pressure and then pumps the CO2 to the oxygen recovery system. For such a membrane to be practical, it must have high CO2 permeation rate and excellent selectivity for CO2 over air. Unfortunately, conventional gas separation membranes do not have adequate CO2 permeability and selectivity to meet the needs of this application. However, the required performance could be obtained with a supported liquid membrane (SLM), which consists of a microporous material filled with a liquid that selectively reacts with CO2 over air. In a recently completed Phase II SBIR project, Reaction Systems, Inc. fabricated an SLM that is very close to meeting permeability and selectivity objectives for use in the Portable Life Support System (PLSS). This paper describes work carried out to evaluate its potential for use in the cabin.

Wickham, David T.↗
NASA NTRS2011

CFD Ventilation Study for the Human Powered Centrifuge at the International Space Station

The Human Powered Centrifuge (HPC) is a hyper gravity facility that will be installed on board the International Space Station (ISS) to enable crew exercises under the artificial gravity conditions. The HPC equipment includes a bicycle for long-term exercises of a crewmember that provides power for rotation of HPC at a speed of 30 rpm. The crewmember exercising vigorously on the centrifuge generates the amount of carbon dioxide of several times higher than a crewmember in ordinary conditions. The goal of the study is to analyze the airflow and carbon dioxide distribution within Pressurized Multipurpose Module (PMM) cabin. The 3D computational model included PMM cabin. The full unsteady formulation was used for airflow and CO2 transport modeling with the so-called sliding mesh concept is considered in the rotating reference frame while the rest of the cabin volume is considered in the stationary reference frame. The localized effects of carbon dioxide dispersion are examined. Strong influence of the rotating HPC equipment on the CO2 distribution is detected and discussed.

Son, Chang H.↗
NASA NTRS2012

Computational Fluid Dynamics Ventilation Study for the Human Powered Centrifuge at the International Space Station

The Human Powered Centrifuge (HPC) is a facility that is planned to be installed on board the International Space Station (ISS) to enable crew exercises under the artificial gravity conditions. The HPC equipment includes a "bicycle" for long-term exercises of a crewmember that provides power for rotation of HPC at a speed of 30 rpm. The crewmember exercising vigorously on the centrifuge generates the amount of carbon dioxide of about two times higher than a crewmember in ordinary conditions. The goal of the study is to analyze the airflow and carbon dioxide distribution within Pressurized Multipurpose Module (PMM) cabin when HPC is operating. A full unsteady formulation is used for airflow and CO2 transport CFD-based modeling with the so-called sliding mesh concept when the HPC equipment with the adjacent Bay 4 cabin volume is considered in the rotating reference frame while the rest of the cabin volume is considered in the stationary reference frame. The rotating part of the computational domain includes also a human body model. Localized effects of carbon dioxide dispersion are examined. Strong influence of the rotating HPC equipment on the CO2 distribution detected is discussed.

Son, Chang H.↗
NASA NTRS2012

Monitoring Ocean CO2 Fluxes from Space: GOSAT and OCO-2

The ocean is a major component of the global carbon cycle, emitting over 330 billion tons of carbon dioxide (CO2) into the atmosphere each year, or about 10 times that emitted fossil fuel combustion and all other human activities [1, 2]. The ocean reabsorbs a comparable amount of CO2 each year, along with ~25% of the CO2 emitted by these human activities. The nature and geographic distribution of the processes controlling these ocean CO2 fluxes are still poorly constrained by observations. A better understanding of these processes is essential to predict how this important CO2 sink may evolve as the climate changes.While in situ measurements of ocean CO2 fluxes can be very precise, the sampling density is far too sparse to quantify ocean CO2 sources and sinks over much of the globe. One way to improve the spatial resolution, coverage, and sampling frequency is to make observations of the column averaged CO2 dry air mole fraction, XCO2, from space [4, 5, 6]. Such measurements could provide global coverage at high resolution (< 100 km) on monthly time scales. High precision (< 1 part per million, ppm) is essential to resolve the small, near-surface CO2 variations associated with ocean fluxes and to better constrain the CO2 transport over the ocean. The Japanese Greenhouse gases Observing Satellite (GOSAT) and the NASA Orbiting Carbon Observatory (OCO) were first two space based sensors designed specifically for this task. GOSAT was successfully launched on January 23, 2009, and has been returning measurements of XCO2 since April 2009. The OCO mission was lost in February 2009, when its launch vehicle malfunctioned and failed to reach orbit. In early 2010, NASA authorized a re-flight of OCO, called OCO-2, which is currently under development.

GOSAT↗
NASA NTRS2007

Progress in Modeling Global Atmospheric CO2 Fluxes and Transport: Results from Simulations with Diurnal Fluxes

Progress in better determining CO2 sources and sinks will almost certainly rely on utilization of more extensive and intensive CO2 and related observations including those from satellite remote sensing. Use of advanced data requires improved modeling and analysis capability. Under NASA Carbon Cycle Science support we seek to develop and integrate improved formulations for 1) atmospheric transport, 2) terrestrial uptake and release, 3) biomass and 4) fossil fuel burning, and 5) observational data analysis including inverse calculations. The transport modeling is based on meteorological data assimilation analysis from the Goddard Modeling and Assimilation Office. Use of assimilated met data enables model comparison to CO2 and other observations across a wide range of scales of variability. In this presentation we focus on the short end of the temporal variability spectrum: hourly to synoptic to seasonal. Using CO2 fluxes at varying temporal resolution from the SIB 2 and CASA biosphere models, we examine the model's ability to simulate CO2 variability in comparison to observations at different times, locations, and altitudes. We find that the model can resolve much of the variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The influence of key process representations is inferred. The high degree of fidelity in these simulations leads us to anticipate incorporation of realtime, highly resolved observations into a multiscale carbon cycle analysis system that will begin to bridge the gap between top-down and bottom-up flux estimation, which is a primary focus of NACP.

Collatz, G. James↗
NASA NTRS2007

Evaluating the Capacity of Global CO2 Flux and Atmospheric Transport Models to Incorporate New Satellite Observations

As we enter the new era of satellite remote sensing for CO2 and other carbon cyclerelated quantities, advanced modeling and analysis capabilities are required to fully capitalize on the new observations. Model estimates of CO2 surface flux and atmospheric transport are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, and ultimately for future projections of carbon-climate interactions. For application to current, planned, and future remotely sensed CO2 data, it is desirable that these models are accurate and unbiased at time scales from less than daily to multi-annual and at spatial scales from several kilometers or finer to global. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 1998 through 2006. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at lxi degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-2), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to in situ observations at sites in Northern mid latitudes and the continental tropics. The influence of key process representations is inferred. We find that the model can resolve much of the hourly to synoptic variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The seasonal cycle and its interannual variations generally respond adequately, but discrepancies in the tropics suggest the need for a refinement of the soil moisture dependence of the respiration flux in CASA. Examples and inferences for interpretation of satellite data will be discussed. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in the terrestrial CO2 sink and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.

Kawa, S. R.↗
NASA NTRS2006

A Test of Sensitivity to Convective Transport in a Global Atmospheric CO2 Simulation

Two approximations to convective transport have been implemented in an offline chemistry transport model (CTM) to explore the impact on calculated atmospheric CO2 distributions. GlobalCO2 in the year 2000 is simulated using theCTM driven by assimilated meteorological fields from the NASA s Goddard Earth Observation System Data Assimilation System, Version 4 (GEOS-4). The model simulates atmospheric CO2 by adopting the same CO2 emission inventory and dynamical modules as described in Kawa et al. (convective transport scheme denoted as Conv1). Conv1 approximates the convective transport by using the bulk convective mass fluxes to redistribute trace gases. The alternate approximation, Conv2, partitions fluxes into updraft and downdraft, as well as into entrainment and detrainment, and has potential to yield a more realistic simulation of vertical redistribution through deep convection. Replacing Conv1 by Conv2 results in an overestimate of CO2 over biospheric sink regions. The largest discrepancies result in a CO2 difference of about 7.8 ppm in the July NH boreal forest, which is about 30% of the CO2 seasonality for that area. These differences are compared to those produced by emission scenario variations constrained by the framework of Intergovernmental Panel on Climate Change (IPCC) to account for possible land use change and residual terrestrial CO2 sink. It is shown that the overestimated CO2 driven by Conv2 can be offset by introducing these supplemental emissions.

Bian, H.↗
NASA NTRS2011

Forward Modeling of Atmospheric Carbon Dioxide in GEOS-5: Uncertainties Related to Surface Fluxes and Sub-Grid Transport

Forward GEOS-5 AGCM simulations of CO2, with transport constrained by analyzed meteorology for 2009-2010, are examined. The CO2 distributions are evaluated using AIRS upper tropospheric CO2 and ACOS-GOSAT total column CO2 observations. Different combinations of surface C02 fluxes are used to generate ensembles of runs that span some uncertainty in surface emissions and uptake. The fluxes are specified in GEOS-5 from different inventories (fossil and biofuel), different data-constrained estimates of land biological emissions, and different data-constrained ocean-biology estimates. One set of fluxes is based on the established "Transcom" database and others are constructed using contemporary satellite observations to constrain land and ocean process models. Likewise, different approximations to sub-grid transport are employed, to construct an ensemble of CO2 distributions related to transport variability. This work is part of NASA's "Carbon Monitoring System Flux Pilot Project,"

Pawson, Steven↗
NASA NTRS2019

Quantifying Contributions of Land Carbon Fluxes Variability and Atmospheric Transport Variability to Atmospheric CO2 Variability

Much of the uncertainty in predicting variations in greenhouse gases originates in the complex dynamics of the land ecosystem and the atmosphere. To reduce the uncertainties, it is useful to decouple the contributions of land carbon fluxes and atmospheric transport to atmospheric carbon variability. Here we isolate these contributions using a version of the NASA GEOS model that couples carbon, energy and water cycles between the land and the atmosphere. Our current study is a follow-on to a preliminary analysis that suggested that an extreme event (e.g., imposed drought) in a free running AGCM simulation affects atmospheric CO2 more through its impact on atmospheric transport than through a modification of land carbon fluxes. In order to more carefully isolate the effects of the land carbon variability and atmospheric transport variability on atmospheric CO2 variability, we conducted two coupled-AGCM simulations in replay mode, a mode that forces the model's evolution of weather to match that of the MERRA-2 reanalysis. In the control simulation, the land carbon fluxes and the atmospheric CO2 concentrations, as well as the meteorology, are simulated over 2001-2015. We compute the climatological seasonal cycles of net land carbon production from this control simulation and then prescribe, in a second simulation, these climatological carbon fluxes to the atmosphere in the same replay mode. By comparing the atmospheric CO2 variability produced in the two simulations, we fully isolate the part of this variability associated with land surface fluxes. Relative contributions of land flux variability and atmospheric transport variability to CO2 variability are quantified both on a regional basis and as a function of height into the atmosphere to support interpretation of both ground-based and satellite observations.

Lee, Eunjee↗
NASA NTRS2002

Mass Conservation in a Chemical Transport Model and its Effect on CO2 and SF6 Simulations

Chemical transport models (CTMs) must conserve mass to be useful for applications involving assessment of the effect of various pollutants on the troposphere and stratosphere. Furthermore, calculations of the evolution of constituents such as SF6 are used to evaluate overall model transport, and interpretation of such simulations is clouded if mass conservation is not assured. For realistic simulations or predictions, it is crucial that constituents are not produced or lost by transport or other processes in the CTMs. Analysis of CO2 and SF6 experiments using a CTM shows that problems with mass conservation can seriously degrade the simulations. Failure to conserve mass results from inconsistency of the surface pressure tendency and the divergence of horizontal mass flux when the model is forced by assimilated meteorological data. We have developed an effective method to eliminate the inconsistency by modifying the divergent part of the wind field. The changes in the wind fields are quite small but the impact on mass conservation is large. Parameterizations of physical processes such as convection or turbulent transport can also affect mass conservation. The lack of conservation is small but accumulates when integrations are lengthy such as required for SF6. This lack of conservation is found using winds from either a GCM or from an assimilation system. A simple adjustment removes much of the inaccuracy in the convective parameterization. A CO2 simulation using assimilated winds from the most recent version of the Goddard Earth Observing System Data Assimilation System will be used to illustrate the impact of these transport improvements.

Zhu, Z.↗
NASA NTRS2012

New Approaches to Quantifying Transport Model Error in Atmospheric CO2 Simulations

In recent years, much progress has been made in observing CO2 distributions from space. However, the use of these observations to infer source/sink distributions in inversion studies continues to be complicated by difficulty in quantifying atmospheric transport model errors. We will present results from several different experiments designed to quantify different aspects of transport error using the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM). In the first set of experiments, an ensemble of simulations is constructed using perturbations to parameters in the model s moist physics and turbulence parameterizations that control sub-grid scale transport of trace gases. Analysis of the ensemble spread and scales of temporal and spatial variability among the simulations allows insight into how parameterized, small-scale transport processes influence simulated CO2 distributions. In the second set of experiments, atmospheric tracers representing model error are constructed using observation minus analysis statistics from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA). The goal of these simulations is to understand how errors in large scale dynamics are distributed, and how they propagate in space and time, affecting trace gas distributions. These simulations will also be compared to results from NASA's Carbon Monitoring System Flux Pilot Project that quantified the impact of uncertainty in satellite constrained CO2 flux estimates on atmospheric mixing ratios to assess the major factors governing uncertainty in global and regional trace gas distributions.

Ott, L.↗