Technical note: A high-resolution inverse modelling technique for estimating surface CO₂ fluxes based on the NIES-TM–FLEXPART coupled transport model and its adjoint

We developed a high-resolution surface flux inversion system based on the global Eulerian–Lagrangian coupled tracer transport model composed of the National Institute for Environmental Studies (NIES) transport model (TM; collectively NIES-TM) and the FLEXible PARTicle dispersion model (FLEXPART). The inversion system is named NTFVAR (NIES-TM–FLEXPART-variational) as it applies a variational optimization to estimate surface fluxes. We tested the system by estimating optimized corrections to natural surface CO2 fluxes to achieve the best fit to atmospheric CO2 data collected by the global in situ network as a necessary step towards the capability of estimating anthropogenic CO2 emissions. We employed the Lagrangian particle dispersion model (LPDM) FLEXPART to calculate surface flux footprints of CO2 observations at a spatial resolution of 0.1∘×0.1∘. The LPDM is coupled with a global atmospheric tracer transport model (NIES-TM). Our inversion technique uses an adjoint of the coupled transport model in an iterative optimization procedure. The flux error covariance operator was implemented via implicit diffusion. Biweekly flux corrections to prior flux fields were estimated for the years 2010–2012 from in situ CO2 data included in the Observation Package (ObsPack) data set. High-resolution prior flux fields were prepared using the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) for fossil fuel combustion, the Global Fire Assimilation System (GFAS) for biomass burning, the Vegetation Integrative SImulator for Trace gases (VISIT) model for terrestrial biosphere exchange, and the Ocean Tracer Transport Model (OTTM) for oceanic exchange. The terrestrial biospheric flux field was constructed using a vegetation mosaic map and a separate simulation of CO2 fluxes at a daily time step by the VISIT model for each vegetation type. The prior flux uncertainty for the terrestrial biosphere was scaled proportionally to the monthly mean gross primary production (GPP) by the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD17 product. The inverse system calculates flux corrections to the prior fluxes in the form of a relatively smooth field multiplied by high-resolution patterns of the prior flux uncertainties for land and ocean, following the coastlines and fine-scale vegetation productivity gradients. The resulting flux estimates improved the fit to the observations taken at continuous observation sites, reproducing both the seasonal and short-term concentration variabilities including high CO2 concentration events associated with anthropogenic emissions. The use of a high-resolution atmospheric transport in global CO2 flux inversions has the advantage of better resolving the transported mixed signals from the anthropogenic and biospheric sources in densely populated continental regions. Thus, it has the potential to achieve better separation between fluxes from terrestrial ecosystems and strong localized sources, such as anthropogenic emissions and forest fires. Further improvements in the modelling system are needed as our posterior fit was better than that of the National Oceanic and Atmospheric Administration (NOAA)'s CarbonTracker for only a fraction of the monitoring sites, i.e. mostly at coastal and island locations where background and local flux signals are mixed.

Technical note: A high-resolution inverse modelling technique for estimating surface CO₂ fluxes based on the NIES-TM – FLEXPART coupled transport model and its adjoint

We developed a high-resolution surface flux inversion system based on the global Lagrangian–Eulerian coupled tracer transport model composed of National Institute for Environmental Studies Transport Model (NIES-TM) and FLEXible PARTicle dispersion model (FLEXPART). The inversion system is named NTFVAR (NIES-TM-FLEXPART-variational) as it applies variational optimisation to estimate surface fluxes. We tested the system by estimating optimized corrections to natural surface CO2 fluxes to achieve best fit to atmospheric CO2 data collected by the global in-situ network, as a necessary step towards capability of estimating anthropogenic CO2 emissions. We employ the Lagrangian particle dispersion model (LPDM) FLEXPART to calculate the surface flux footprints of CO2 observations at a 0.1° × 0.1° spatial resolution. The LPDM is coupled to a global atmospheric tracer transport model (NIES-TM). Our inversion technique uses an adjoint of the coupled transport model in an iterative optimization procedure. The flux error covariance operator is being implemented via implicit diffusion. Biweekly flux corrections to prior flux fields were estimated for the years 2010–2012 from in-situ CO2 data included in the Observation Package (ObsPack) dataset. High-resolution prior flux fields were prepared using Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) for fossil fuel combustion, Global Fire Assimilation System (GFAS) for biomass burning, the Vegetation Integrative SImulator for Trace gases (VISIT) model for terrestrial biosphere exchange and Ocean Tracer Transport Model (OTTM) for oceanic exchange. The terrestrial biospheric flux field was constructed using a vegetation mosaic map and separate simulation of CO2 fluxes at daily time step by the VISIT model for each vegetation type. The prior flux uncertainty for terrestrial biosphere was scaled proportionally to the monthly mean Gross Primary Production (GPP) by the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD17 product. The inverse system calculates flux corrections to the prior fluxes in the form of a relatively smooth field multiplied by high-resolution patterns of the prior flux uncertainties for land and ocean, following the coastlines and vegetation productivity gradients. The resulting flux estimates improve fit to the observations at continuous observations sites, reproducing both the seasonal variation and short-term concentration variability, including high CO2 concentration events associated with anthropogenic emissions. The use of high-resolution atmospheric transport in global CO2 flux inversion has the advantage of better resolving the transport from the mix of the anthropogenic and biospheric sources in densely populated continental regions and shows potential for better separation between fluxes from terrestrial ecosystems and strong localised sources such as anthropogenic emissions and forest fires. Further improvements in the modelling system are needed as the posterior fit is better than that by the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker only for a fraction of the monitoring sites, mostly at coastal and island locations experiencing mix of background and local flux signals.

Evaluation of model-data mismatch errors in the CarboScope-Regional Inversion System

<p>With an increasing network of atmospheric stations that produce a constant data stream, top-down inverse transport modelling of GHGs in a quasi-operational way becomes feasible. The CarboScope-Regional inversion system embeds the regional inversion, within a global inversion using the two-step approach. The regional inversion consists of Lagrangian mesoscale transport from STILT, prior fluxes from the diagnostic VPRM biosphere model, and anthropogenic emissions from a combination of EDGAR v4.3 with the annually updated BP statistical report. Regional ocean fluxes were derived from the CarboScope ocean flux product based on SOCATv2019 data. The inversion uses atmospheric observations from 44 stations to infer biosphere-atmosphere exchange. The regional domain covers most of Europe (33 – 73N, 15W – 35E) with a spatial resolution of 0.25 degree for fluxes and 0.5 degree for flux corrections inferred by the inversion (i.e. the state space).<br>One of the critical parameters is the assumed uncertainty of the observations, and the major contribution to this is the model-data mismatch error, or representation error. Within CarboScope-Regional, this model-data mismatch error is specified differently for different station types, such as tall towers, mountain or coastal stations, etc. To evaluate the validity and appropriateness of these assumed uncertainties, a leave-one-out cross-validation is applied for a single year, using all stations except one for the inversion, and comparing posterior concentrations predicted for the omitted station with the observed concentrations. Results of this cross-validation will be presented separately for the different station types, and will be used to evaluate the magnitude of the assumed model-data mismatch errors.</p>

Assessment of meander hydro-morphodynamics using modelling approaches in an amazonian river

<p>The Madre de Dios river basin belongs to the Amazon river basin, until the study area has an approximate area of ​​47070 km<sup>2</sup>. In recent years serious problems of lateral undermining are occurring on the right bank of the river, bringing with it problems in nearby towns and the layout of the interoceanic highway that connects to the country of Brazil. The case study is the Meander “La Pastora”, whose right margin is constituted by a compact clay material, which was affected by local undermining phenomena, also the approach of thalweg and sedimentation in the left margin was caused by causes of deforestation of the basin and increased solid contribution. Since 2015, measures have been built that have the function of mitigating erosion on the right bank and recovering the affected area. Using two-dimensional numerical modelling, ADCP/multibeam bathymetric surveys and limnimetric records, the hydrodynamic conditions and sediment transport will be evaluated by the hand of a results from physical modelling and inclusion of structural measures, estimating erosion and sedimentation areas that may have been in the meander. BASEMENT and IRIC NAYS2DH-FASTMECH models were used which simulated the flow conditions in different minimum and maximum hydrological scenarios compared with physical modelling results and field data, considering sediment flux corrections in curved channels with significant secondary flow motions and lateral erosion to precisely capture the complex flow field induced by channel curvature and riverbank gravitational effects.</p>

Carbon Exchange between the Atmosphere and a Subtropical Evergreen Mountain Forest in Taiwan

Tropical, temperate, and boreal forests are the subject of various eddy covariance studies, but less is known about the subtropical region. As there are large areas of subtropical forests in the East Asian monsoon region with possibly high carbon uptake, we used three years (2011–2013) of eddy covariance data to estimate the carbon balance of a subtropical mountain forest in Taiwan. Two techniques of flux partitioning are applied to evaluate ecosystem respiration, thoroughly evaluate the validity of the estimated fluxes, and arrive at an estimate of the yearly net ecosystem exchange (NEE). We found that advection is a strong player at our site. Further, when used alone, the nighttime flux correction with the so-called u∗ method (u∗ = friction velocity) cannot avoid underestimating the nighttime respiration. By using a two-technique method employing both nighttime and daytime parameterizations for flux corrections, we arrive at an estimate of the three-year mean NEE of −561 (±standard deviation 114) g·C·m−2·yr−1. The corrected flux estimate represents a rather large uptake of CO2 for this mountain cloud forest, but the value is in good agreement with the few existing comparable estimates for other subtropical forests.

Sorption-Caused Attenuation and Delay of Water Vapor Signals in Eddy-Covariance Sampling Tubes and Filters

Adsorption and desorption (together called sorption) processes in sampling tubes and filters of eddy-covariance stations cause attenuation and delay of water vapor signals, leading to an underestimation of water vapor fluxes by tens of percent. The aim of this work was (i) to quantify the effects on sorption in filters and tubes of humidity, flow rate, and dirtiness and (ii) to test a recently introduced sorption model that facilitates correction of fluxes. Laboratory measurements on the transport of water vapor pulses through tubes and filters were carried out, and eddy-covariance field measurements were also used. In the laboratory measurements, the effects of sorption processes were evident, and filters caused a similar attenuation and delay of the signal as tubes. Filters could have a larger impact than a long tube, whereas the flow rate had a much smaller impact on the flux loss than the sorption processes (Reynolds numbers 2120–3360). The sorption model represented well the water vapor pulses in a wide range of conditions. As for the field measurements, the transfer function (TF) derived from the sorption model represented well the observations. Fitting parameters were found to depend strongly on the relative humidity and correlate with the signal delay. Having a more complex shape, TF of the sorption model represented much better the measured TFs than, for example, a Lorentzian or adjusted Gaussian TF, leading on average to a 4% unit difference in the flux corrections. Use of this more complex TF is recommended and its implementation is assisted by the codes provided in appendix B.

The effect of hygroscopicity on eddy covariance estimates of sea-spray aerosol fluxes: a comparison of high-rate and bulk correction methods

The eddy covariance technique is the most direct of the methods that have been used to measure the flux of sea-spray aerosol between the ocean and atmosphere, but has been applied in only a handful of studies. However, unless the aerosol is dried before the eddy covariance measurements are made, the hygroscopic nature of sea-spray may combine with a relative humidity flux to result in a bias in the calculated aerosol flux. "Bulk" methods have been presented to account for this bias, however, they rely on assumptions of the shape of the aerosol spectra which may not be valid for near-surface measurements of sea-spray. Here we describe a method of correcting aerosol spectra for relative humidity induced size variations at the high frequency (10 Hz) measurement timescale, where counting statistics are poor and the spectral shape cannot be well represented by a simple power law. Such a correction allows the effects of hygroscopicity and relative humidity flux on the aerosol flux to be explicitly evaluated and compared to the bulk corrections, both in their original form and once reformulated to better represent the measured mean aerosol spectra. In general, the bulk corrections – particularly when reformulated for the measured mean aerosol spectra – perform relatively well, producing flux corrections of the right sign and approximate magnitude. However, there are times when the bulk methods either significantly over- or underestimate the required flux correction. We conclude that, where possible, relative humidity corrections should be made at the measurement frequency.

The effect of hygroscopicity on sea-spray aerosol fluxes: a comparison of high-rate and bulk correction methods

The eddy covariance technique is the most direct of the methods that have been used to measure the flux of sea-spray aerosol between the ocean and atmosphere, but has been applied in only a handful of studies. However, unless the aerosol is dried before the eddy covariance measurements are made, the hygroscopic nature of sea-spray may combine with a relative humidity flux to result in a bias in the calculated aerosol flux. "Bulk" methods have been presented to account for this bias, however they rely on assumptions of the shape of the aerosol spectra which may not be valid for near-surface measurements of sea-spray. Here we describe a method of correcting aerosol spectra for relative humidity induced size variations at the high frequency (10 Hz) measurement timescale, where counting statistics are poor and the spectral shape cannot be well represented by a simple power law. Such a correction allows the effects of hygroscopicity and relative humidity flux on the aerosol flux to be explicitly evaluated and compared to the bulk corrections, both in their original form and once reformulated to better represent the measured mean aerosol spectra. In general, the bulk corrections – particularly when reformulated for the measured mean aerosol spectra – perform relatively well, producing flux corrections of the right sign and approximate magnitude. However, there are times when the bulk methods either significantly over- or underestimate the required flux correction. We thus conclude that, where possible, relative humidity corrections should be made at the measurement frequency.