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We describe the development of the tangent linear (TL) and adjoint models of the MPAS-CO2 transport model, which is a global online chemical transport model developed upon the non-hydrostatic Model for Prediction Across Scales- Atmosphere (MPAS-A). The primary goal is to make the model system a valuable research tool for investigating atmospheric carbon transport and inverse modeling. First, we develop the TL code, encompassing all CO2 transport processes within the MPAS-CO2 forward model. Then, we construct the adjoint model using a combined strategy involving re-calculation and storage of the essential meteorological variables needed for CO2 transport. This strategy allows the adjoint model to undertake long-period integration with moderate memory demands. To ensure accuracy, the TL and adjoint models undergo vigorous verifications through a series of standard tests. The adjoint model, through backward-in-time integration, calculates the sensitivity of atmospheric CO2 observations to surface CO2 fluxes and the initial atmospheric CO2 mixing ratio. To demonstrate the utility of the newly-developed adjoint model, we conduct simulations for two types of atmospheric CO2 observations: tower-based in situ CO2 mixing ratio and satellite-derived column-averaged (XCO2 ). A comparison between the sensitivity to surface flux calculated by the MPAS-CO2 adjoint model with its counterpart from Carbon Tracker-Lagrange (CT-L) reveals spatial agreement but notable magnitude differences. These differences, particularly evident for XCO2, likely arise from differences in vertical mixing between the two systems. Moreover, this comparison highlights the substantial loss of information in the atmospheric CO2 observations due to CT-L's simulation length and spatial domain limitations. Furthermore, the adjoint sensitivity analysis demonstrates that the sensitivities to both surface flux and initial CO2 conditions spread out throughout the entire northern hemisphere within a month. MPAS-CO2 forward, TL, and adjoint models stand out for their calculation efficiency and variable-resolution capability, making them competitive in computational cost. In conclusion, the successful development of the MPAS-CO2 TL and adjoint models, and their integration into the MPAS-CO2 system, establish the possibility of using MPAS's unique features in atmospheric CO2 transport sensitivity studies and in inverse modeling with advanced methods such as variational data assimilation. [ABSTRACT FROM AUTHOR]

Quantifying the uncertainty of inversion-derived fluxes and attributing the uncertainty to errors in either flux or transport continue to be challenges in the characterization of surface sources and sinks of carbon dioxide (CO2). It is also not clear if fluxes inferred in a coarse-resolution global system will remain optimal in a higher-resolution modeling environment. 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 North American domain within the global model. We test the coupling by simulating Greenhouse gases Observing SATellite (GOSAT) column-averaged dry-air mole fractions (XCO2) over North American for 2010. We find mean model-model differences in summer of ~0.12ppm. 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 850hPa. The framework methods can be used to couple other global model inversion results to WRF for further study using different boundary layer and transport parameterizations. [ABSTRACT FROM AUTHOR]

Expanding urban populations and the significant contribution of cities to global fossil-fuel CO2 (CO2ff) emissions emphasize the necessity of achieving independent and accurate quantifications of the emissions from urban area. In this paper, we assess the utility of total column dry air CO2 mole fraction (XCO2) data retrieved from NASA's Orbiting Carbon Observatory 2 (OCO-2) observations to quantify CO2ff emissions from cities. Observing System Simulation Experiments (OSSEs) are implemented by forward modeling of meteorological fields and column XCO2. The impact of transport model errors on the inverse emissions estimates is examined for two "plume cities" (Riyadh, Cairo) and a "basin city" (Los Angeles metropolitan region, LA). The pseudo data experiments indicate convergence of emission uncertainties related to transport model errors with increasing amount of observations. The 1-σ uncertainty of emission estimates is constrained to approximately 15%/5% with about 10 pseudo tracks for plume city/basin city. The systematic wind speed biases in simulated wind fields for LA lead to overestimations in total CO2ff emission, which require data assimilation to improve high-resolution atmospheric transport. The contribution of biogenic fluxes gradients in urban and rural area of Pearl River Delta metropolitan region in China are examined by simulations with biospheric fluxes imposed by the Net Ecosystem Exchange (NEE) from multiple terrestrial biosphere models, which show about 24 ± 21% (1σ) and 19 ± 15% (1σ) contributions to the total XCO2 enhancements for the two cases examined. The representations of transport model errors for the emission optimization are examined for Riyadh, Cairo and LA ¬in real cases. The determination of background XCO2 is discussed for LA by using constant and simulated background with biospheric fluxes included, demonstrating the need of careful consideration of the variations in background XCO2 for identifying concentration enhancements due to fossil fuel emissions. [ABSTRACT FROM AUTHOR]

Megacities are major sources of anthropogenic fossil fuel CO2 (FFCO2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km² or more with complex topography and changing landscapes. We present a high-resolution land-atmosphere modelling system for urban CO2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO2 emission product, Hestia-LA, to simulate atmospheric CO2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimized errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May-June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the highresolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO2 emission products to evaluate the impact of the spatial resolution of the CO2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO2 concentrations. We find that high spatial resolution in the fossil fuel CO2 emissions is more important than in the atmospheric model to capture CO2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO2 emissions monitoring in the LA megacity requires FFCO2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates. [ABSTRACT FROM AUTHOR]

Large urban emissions of greenhouse gases result in large atmospheric enhancements relative to background that are easily measured. Using CO2 mole fractions and Δ14C and δ13C values of CO2 in the Los Angeles megacity observed in inland Pasadena (2006-2013) and coastal Palos Verdes peninsula (autumn 2009-2013), we have determined time series for CO2 contributions from fossil fuel combustion (Cff) for both sites and broken those down into contributions from petroleum and/or gasoline and natural gas burning for Pasadena. We find a 10% reduction in Pasadena Cff during the Great Recession of 2008-2010, which is consistent with the bottom-up inventory determined by the California Air Resources Board. The isotopic variations and total atmospheric CO2 from our observations are used to infer seasonality of natural gas and petroleum combustion. The trend of CO2 contributions to the atmosphere from natural gas combustion is out of phase with the seasonal cycle of total natural gas combustion seasonal patterns in bottom-up inventories but is consistent with the seasonality of natural gas usage by the area's electricity generating power plants. For petroleum, the inferred seasonality of CO2 contributions from burning petroleum is delayed by several months relative to usage indicated by statewide gasoline taxes. Using the high-resolution Hestia-LA data product to compare Cff from parts of the basin sampled by winds at different times of year, we find that variations in observed fossil fuel CO2 reflect seasonal variations in wind direction. The seasonality of the local CO2 excess from fossil fuel combustion along the coast, on Palos Verdes peninsula, is higher in autumn and winter than spring and summer, almost completely out of phase with that from Pasadena, also because of the annual variations of winds in the region. Variations in fossil fuel CO2 signals are consistent with sampling the bottom-up Hestia-LA fossil CO2 emissions product for sub-city source regions in the LA megacity domain when wind directions are considered. [ABSTRACT FROM AUTHOR]