scholarly journals Investigating Alaskan methane and carbon dioxide fluxes using measurements from the CARVE tower

2015 ◽  
Vol 15 (23) ◽  
pp. 34871-34911 ◽  
Author(s):  
A. Karion ◽  
C. Sweeney ◽  
J. B. Miller ◽  
A. E. Andrews ◽  
R. Commane ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Transport Model ◽  
Carbon Sources ◽  
Wrf Model ◽  
Surface Fluxes ◽  
Carbon Dioxide Fluxes ◽  
Near Surface ◽  
Annual Carbon ◽  
Northern High Latitude ◽  
Carbon Dioxide Co2

Abstract. Northern high-latitude carbon sources and sinks, including those resulting from degrading permafrost, are thought to be sensitive to the rapidly warming climate. Because the near-surface atmosphere integrates surface fluxes over large (~ 500–1000 km) scales, atmospheric monitoring of carbon dioxide (CO2) and methane (CH4) mole fractions in the daytime mixed layer is a promising method for detecting change in the carbon cycle throughout boreal Alaska. Here we use CO2 and CH4 measurements from a NOAA tower 17 km north of Fairbanks AK, established as part of NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE), to investigate regional fluxes of CO2 and CH4 for 2012–2014. CARVE was designed to use aircraft and surface observations to better understand and quantify the sensitivity of Alaskan carbon fluxes to climate variability. We use high-resolution meteorological fields from the Polar Weather Research and Forecasting (WRF) model coupled with the Stochastic Time-Inverted Lagrangian Transport model (hereafter, WRF-STILT), along with the Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM), to investigate fluxes of CO2 in boreal Alaska using the tower observations, which are sensitive to large areas of central Alaska. We show that simulated PolarVPRM/WRF-STILT CO2 mole fractions show remarkably good agreement with tower observations, suggesting that the WRF-STILT model represents the meteorology of the region quite well, and that the PolarVPRM flux magnitudes and spatial distribution are consistent with CO2 mole fractions observed at the CARVE tower. CO2 signals at the tower are larger than predicted, with significant respiration occurring in the fall that is not captured by PolarVPRM. Using the WRF-STILT model, we find that average CH4 fluxes in boreal Alaska are somewhat lower than flux estimates by Chang et al. (2014) over all of Alaska for May–September 2012; we also find emissions persist during some wintertime periods, augmenting those observed during the summer and fall. The presence of significant fall and winter CO2 and CH4 fluxes underscores the need for year-round in-situ observations to quantify changes in boreal Alaskan annual carbon balance.

scholarly journals Investigating Alaskan methane and carbon dioxide fluxes using measurements from the CARVE tower

2016 ◽  
Vol 16 (8) ◽  
pp. 5383-5398 ◽  
Author(s):  
Anna Karion ◽  
Colm Sweeney ◽  
John B. Miller ◽  
Arlyn E. Andrews ◽  
Roisin Commane ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Transport Model ◽  
Carbon Sources ◽  
Wrf Model ◽  
Surface Fluxes ◽  
Carbon Dioxide Fluxes ◽  
Near Surface ◽  
Northern High Latitude ◽  
Carbon Dioxide Co2 ◽  
Good Agreement

Abstract. Northern high-latitude carbon sources and sinks, including those resulting from degrading permafrost, are thought to be sensitive to the rapidly warming climate. Because the near-surface atmosphere integrates surface fluxes over large ( ∼  500–1000 km) scales, atmospheric monitoring of carbon dioxide (CO2) and methane (CH4) mole fractions in the daytime mixed layer is a promising method for detecting change in the carbon cycle throughout boreal Alaska. Here we use CO2 and CH4 measurements from a NOAA tower 17 km north of Fairbanks, AK, established as part of NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE), to investigate regional fluxes of CO2 and CH4 for 2012–2014. CARVE was designed to use aircraft and surface observations to better understand and quantify the sensitivity of Alaskan carbon fluxes to climate variability. We use high-resolution meteorological fields from the Polar Weather Research and Forecasting (WRF) model coupled with the Stochastic Time-Inverted Lagrangian Transport model (hereafter, WRF-STILT), along with the Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM), to investigate fluxes of CO2 in boreal Alaska using the tower observations, which are sensitive to large areas of central Alaska. We show that simulated PolarVPRM–WRF-STILT CO2 mole fractions show remarkably good agreement with tower observations, suggesting that the WRF-STILT model represents the meteorology of the region quite well, and that the PolarVPRM flux magnitudes and spatial distribution are generally consistent with CO2 mole fractions observed at the CARVE tower. One exception to this good agreement is that during the fall of all 3 years, PolarVPRM cannot reproduce the observed CO2 respiration. Using the WRF-STILT model, we find that average CH4 fluxes in boreal Alaska are somewhat lower than flux estimates by Chang et al. (2014) over all of Alaska for May–September 2012; we also find that enhancements appear to persist during some wintertime periods, augmenting those observed during the summer and fall. The possibility of significant fall and winter CO2 and CH4 fluxes underscores the need for year-round in situ observations to quantify changes in boreal Alaskan annual carbon balance.

scholarly journals Technical note: A geostatistical fixed-lag Kalman smoother for atmospheric inversions

2008 ◽  
Vol 8 (2) ◽  
pp. 7755-7779
Author(s):  
A. M. Michalak
Keyword(s):  
Carbon Dioxide ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Temporal Correlation ◽  
Technical Note ◽  
Surface Fluxes ◽  
Carbon Dioxide Fluxes ◽  
Kalman Smoother ◽  
Geostatistical Approach ◽  
Flux Estimation

Abstract. Inverse modeling methods are now commonly used for estimating surface fluxes of carbon dioxide, using atmospheric mass fraction measurements combined with a numerical atmospheric transport model. The geostatistical approach to flux estimation takes advantage of the spatial and/or temporal correlation in fluxes and does not require prior flux estimates. In this work, a geostatistical implementation of a fixed-lag Kalman smoother is developed to improve the computational efficiency of the inverse problem. This method makes it feasible to perform multi-year inversions, at fine resolutions, and with large amounts of data. The new method is applied to the recovery of global gridscale carbon dioxide fluxes for 1997 to 2001 using pseudodata representative of a subset of the NOAA-ESRL Cooperative Air Sampling Network.

scholarly journals Technical Note: Adapting a fixed-lag Kalman smoother to a geostatistical atmospheric inversion framework

2008 ◽  
Vol 8 (22) ◽  
pp. 6789-6799 ◽  
Author(s):  
A. M. Michalak
Keyword(s):  
Carbon Dioxide ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Temporal Correlation ◽  
Technical Note ◽  
Surface Fluxes ◽  
Computationally Efficient ◽  
Carbon Dioxide Fluxes ◽  
Kalman Smoother ◽  
Geostatistical Approach

Abstract. Inverse modeling methods are now commonly used for estimating surface fluxes of carbon dioxide, using atmospheric mass fraction measurements combined with a numerical atmospheric transport model. The geostatistical approach to flux estimation takes advantage of the spatial and/or temporal correlation in fluxes and does not require prior flux estimates. In this work, a previously-developed, computationally-efficient, fixed-lag Kalman smoother is adapted for application with a geostatistical approach to atmospheric inversions. This method makes it feasible to perform multi-year geostatistical inversions, at fine resolutions, and with large amounts of data. The new method is applied to the recovery of global gridscale carbon dioxide fluxes for 1997 to 2001 using pseudodata representative of a subset of the NOAA-ESRL Cooperative Air Sampling Network.

scholarly journals Carbon balance of South Asia constrained by passenger aircraft CO<sub>2</sub> measurements

2011 ◽  
Vol 11 (2) ◽  
pp. 5379-5405 ◽  
Author(s):  
P. K. Patra ◽  
Y. Niwa ◽  
T. J. Schuck ◽  
C. A. M. Brenninkmeijer ◽  
T. Machida ◽  
...  
Keyword(s):  
South Asia ◽  
Transport Model ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Ecosystem Model ◽  
Terrestrial Ecosystem Model ◽  
Terra Incognita ◽  
Annual Carbon ◽  
Carbon Dioxide Co2 ◽  
Passenger Aircraft

Abstract. Quantifying the fluxes of carbon dioxide (CO2) between the atmosphere and terrestrial ecosystems in all their diversity, across the continents, is important and urgent for implementing effective mitigating policies. Whereas much is known for Europe and North America for instance, in comparison, South Asia, with 1.6 billion inhabitants and considerable CO2 fluxes, remained terra incognita in this respect. We use regional measurements of atmospheric CO2 aboard a Lufthansa passenger aircraft between Frankfurt (Germany) and Chennai (India) at cruise altitude, in addition to the existing network sites for 2008, to estimate monthly fluxes for 64-regions using Bayesian inversion and transport model simulations. The applicability of the model's transport parameterization is confirmed using SF6, CH4 and N2O simulations for the CARIBIC datasets. The annual carbon flux obtained by including the aircraft data is twice as large as the fluxes simulated by a terrestrial ecosystem model that was applied to prescribe the fluxes used in the inversions. It is shown that South Asia sequestered carbon at a rate of 0.37±0.20 Pg C yr−1 (1Pg C = 1015 g of carbon in CO2) for the years 2007 and 2008. The seasonality and the strength of the calculated monthly fluxes are successfully validated using independent measurements of vertical CO2 profiles over Delhi and spatial variations at cruising altitude over Asia aboard Japan Airlines passenger aircraft.

scholarly journals Atmospheric Simulations of Total Column CO2 Mole Fractions from Global to Mesoscale within the Carbon Monitoring System Flux Inversion Framework

Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 787 ◽  
Author(s):  
Martha P. Butler ◽  
Thomas Lauvaux ◽  
Sha Feng ◽  
Junjie Liu ◽  
Kevin W. Bowman ◽  
...  
Keyword(s):  
North America ◽  
Monitoring System ◽  
Atmospheric Transport ◽  
Regional Scale ◽  
Wrf Model ◽  
Horizontal Distribution ◽  
Surface Fluxes ◽  
Coupling Scheme ◽  
Northern Half ◽  
Carbon Dioxide Co2

Quantifying the uncertainty of inversion-derived CO2 surface fluxes and attributing the uncertainty to errors in either flux or atmospheric transport simulations continue to be challenges in the characterization of surface sources and sinks of carbon dioxide (CO2). Despite recent studies inferring fluxes while using higher-resolution modeling systems, the utility of regional-scale models remains unclear when compared to existing coarse-resolution global systems. Here, we present an off-line coupling of the mesoscale Weather Research and Forecasting (WRF) model to optimized biogenic CO2 fluxes and mole fractions from the global Carbon Monitoring System inversion system (CMS-Flux). The coupling framework consists of methods to constrain the mass of CO2 introduced into WRF, effectively nesting our regional domain covering most of North America (except the northern half of Canada) within the CMS global model. We test the coupling by simulating Greenhouse gases Observing SATellite (GOSAT) column-averaged dry-air mole fractions (XCO2) over North America for 2010. We find mean model-model differences in summer of ∼0.12 ppm, significantly lower than the original coupling scheme (from 0.5 to 1.5 ppm, depending on the boundary). While 85% of the XCO2 values are due to long-range transport from outside our North American domain, most of the model-model differences appear to be due to transport differences in the fraction of the troposphere below 850 hPa. Satellite data from GOSAT and tower and aircraft data are used to show that vertical transport above the Planetary Boundary Layer is responsible for significant model-model differences in the horizontal distribution of column XCO2 across North America.

scholarly journals Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions

2019 ◽  
Vol 19 (22) ◽  
pp. 14233-14251 ◽  
Author(s):  
Frédéric Chevallier ◽  
Marine Remaud ◽  
Christopher W. O'Dell ◽  
David Baker ◽  
Philippe Peylin ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Large Scale ◽  
Transport Model ◽  
Spatial Scales ◽  
Objective Evaluation ◽  
Annual Growth Rate ◽  
Surface Network ◽  
Carbon Dioxide Co2 ◽  
Aircraft Data ◽  
Atmospheric Inversions

Abstract. We study an ensemble of six multi-year global Bayesian carbon dioxide (CO2) atmospheric inversions that vary in terms of assimilated observations (either column retrievals from one of two satellites or surface air sample measurements) and transport model. The time series of inferred annual fluxes are first compared with each other at various spatial scales. We then objectively evaluate the small inversion ensemble based on a large dataset of accurate aircraft measurements in the free troposphere over the globe, which are independent of all assimilated data. The measured variables are connected with the inferred fluxes through mass-conserving transport in the global atmosphere and are part of the inversion results. Large-scale annual fluxes estimated from the bias-corrected land retrievals of the second Orbiting Carbon Observatory (OCO-2) differ greatly from the prior fluxes, but are similar to the fluxes estimated from the surface network within the uncertainty of these surface-based estimates. The OCO-2-based and surface-based inversions have similar performance when projected in the space of the aircraft data, but the relative strengths and weaknesses of the two flux estimates vary within the northern and tropical parts of the continents. The verification data also suggest that the more complex and more recent transport model does not improve the inversion skill. In contrast, the inversion using bias-corrected retrievals from the Greenhouse Gases Observing Satellite (GOSAT) or, to a larger extent, a non-Bayesian inversion that simply adjusts a recent bottom-up flux estimate with the annual growth rate diagnosed from marine surface measurements both estimate much different fluxes and fit the aircraft data less. Our study highlights a way to rate global atmospheric inversions. Without any general claim regarding the usefulness of all OCO-2 retrieval datasets vs. all GOSAT retrieval datasets, it still suggests that some satellite retrievals can now provide inversion results that are, despite their uncertainty, comparable with respect to credibility to traditional inversions using the accurate but sparse surface network and that are therefore complementary for studies of the global carbon budget.

scholarly journals Eddy covariance for quantifying trace gas fluxes from soils

SOIL ◽  
2015 ◽  
Vol 1 (1) ◽  
pp. 187-205 ◽  
Author(s):  
W. Eugster ◽  
L. Merbold
Keyword(s):  
Eddy Covariance ◽  
Surface Fluxes ◽  
Small Scale ◽  
Spatial Integration ◽  
Near Surface ◽  
Trace Gas Fluxes ◽  
Online Measurements ◽  
Flux Measurements ◽  
Primary Focus ◽  
Carbon Dioxide Co2

Abstract. Soils are highly complex physical and biological systems, and hence measuring soil gas exchange fluxes with high accuracy and adequate spatial representativity remains a challenge. A technique which has become increasingly popular is the eddy covariance (EC) method. This method takes advantage of the fact that surface fluxes are mixed into the near-surface atmosphere via turbulence. As a consequence, measurements with an EC system can be done at some distance above the surface, providing accurate and spatially integrated flux density estimates. In this paper we provide a basic overview targeting scientists who are not familiar with the EC method. This review gives examples of successful deployments from a wide variety of ecosystems. The primary focus is on the three major greenhouse gases: carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Several limitations to the application of EC systems exist, requiring a careful experimental design, which we discuss in detail. Thereby we group these experiments into two main classes: (1) manipulative experiments, and (2) survey-type experiments. Recommendations and examples of successful studies using various approaches are given, including the combination of EC flux measurements with online measurements of stable isotopes. We conclude that EC should not be considered a substitute to traditional (e.g., chamber based) flux measurements but instead an addition to them. The greatest strength of EC measurements in soil science are (1) their uninterrupted continuous measurement of gas concentrations and fluxes that can also capture short-term bursts of fluxes that easily could be missed by other methods and (2) the spatial integration covering the ecosystem scale (several square meters to hectares), thereby integrating over small-scale heterogeneity in the soil.

scholarly journals Modeling the Evolution and Life Cycle of Stable Cold Pools

2016 ◽  
Vol 31 (6) ◽  
pp. 1753-1769 ◽  
Author(s):  
Travis H. Wilson ◽  
Robert G. Fovell
Keyword(s):  
Relative Humidity ◽  
Wrf Model ◽  
Central Valley ◽  
Surface Fluxes ◽  
Weather Research And Forecasting ◽  
Near Surface ◽  
Cold Pools ◽  
Drainage Flows ◽  
Forested Region ◽  
Dry Bias

Abstract Stable cold pools in California’s Central Valley (CV) are conducive to freezing temperatures, high relative humidity, and, in some cases, fog. In this study it will be shown that the Weather Research and Forecasting (WRF) Model as commonly configured cannot reproduce such conditions because of a persistent warm and dry bias near the surface. It was found that removing horizontal diffusion, which by default operates on model levels and thus up and down the valley’s sides, can reduce but not entirely fix the problem. Other improvements include enhancing the near-surface vertical resolution and the surface–air coupling, as both directly control the surface fluxes, especially evaporation. However, these alterations actually have the largest impact in the forested region surrounding the Central Valley, and influence the nighttime relative humidity in the CV only indirectly via nocturnal drainage flows. While it is not clear how realistic are the increased evaporation in the forest or the drainage flows, how and why these alterations result in significantly improved relative humidity reconstructions within the Central Valley are shown.

scholarly journals Eddy covariance for quantifying trace gas fluxes from soils

2014 ◽  
Vol 1 (1) ◽  
pp. 541-583 ◽  
Author(s):  
W. Eugster ◽  
L. Merbold
Keyword(s):  
Eddy Covariance ◽  
Surface Fluxes ◽  
Small Scale ◽  
Spatial Integration ◽  
Near Surface ◽  
Trace Gas Fluxes ◽  
Online Measurements ◽  
Flux Measurements ◽  
Primary Focus ◽  
Carbon Dioxide Co2

Abstract. Soils are highly complex physical and biological systems, and hence measuring soil gas exchange fluxes with high accuracy and adequate spatial representativity remains a challenge. A technique which has become increasingly popular is the eddy covariance (EC) method. This method takes advantage of the fact that surface fluxes are mixed into the near-surface atmosphere via turbulence. As a consequence, measurement with an EC system can be done at some distance above the surface, providing accurate and spatially integrated flux density estimates. In this paper we provide a basic overview targeting at scientists who are not familiar with the EC method. This reviews gives examples of successful deployments from a wide variety of ecosystems. The primary focus is on the three major greenhouse gases carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Several limitations to the application of EC systems exist, requiring a careful experimental design, which we discuss in detail. Thereby we group these experiments into two main classes: (1) manipulative experiments, and (2) survey-type experiments. Recommendations and examples of successful studies using various approaches, including the combination of EC flux measurements with online measurements of stable isotopes are given. We conclude that EC should not be considered a substitution of traditional flux measurements, but an addition to the latter. The greatest strength of EC measurements in soil science are (1) their uninterrupted continuous measurement of gas concentrations and fluxes that also can capture short-term bursts of fluxes that easily could be missed by other methods; and (2) the spatial integration covering the ecosystem scale (several m2 to ha), thereby integrating over small-scale heterogeneity in the soil.

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