Adjoint of the Global Eulerian Lagrangian Coupled Atmospheric transport model (A-GELCA v1.0): development and validation

Abstract. We present the development of the Adjoint of the Global Eulerian–Lagrangian Coupled Atmospheric (A-GELCA) model that consists of the National Institute for Environmental Studies (NIES) model as an Eulerian three-dimensional transport model (TM), and FLEXPART (FLEXible PARTicle dispersion model) as the Lagrangian plume diffusion model (LPDM). The tangent and adjoint components of the Eulerian model were constructed directly from the original NIES TM code using an automatic differentiation tool known as TAF (Transformation of Algorithms in Fortran; http://www.FastOpt.com), with additional manual pre- and post-processing aimed at improving the performance of the computing, including MPI (Message Passing Interface). As results, the adjoint of Eulerian model is discrete. Construction of the adjoint of the Lagrangian component did not require any code modification, as LPDMs are able to track a significant number of particles back in time and thereby calculate the sensitivity of observations to the neighboring emissions areas. Eulerian and Lagrangian adjoint components were coupled at the time boundary in the global domain.The results are verified using a series of test experiments. The forward simulation shown the coupled model is effective in reproducing the seasonal cycle and short-term variability of CO2 even in the case of multiple limiting factors, such as high uncertainty of fluxes and the low resolution of the Eulerian model. The adjoint model demonstrates the high accuracy compared to direct forward sensitivity calculations and fast performance. The developed adjoint of the coupled model combines the flux conservation and stability of an Eulerian discrete adjoint formulation with the flexibility, accuracy, and high resolution of a Lagrangian backward trajectory formulation. </jats:p

Global Lagrangian atmospheric dispersion model

The Global Lagrangian Atmospheric Dispersion Model (GLADIM) is described. GLADIM is based on the global trajectory model, which had been developed earlier and uses fields of weather parameters from different atmospheric reanalysis centers for calculations of trajectories of air mass that include trace gases. GLADIM includes the parameterization of turbulent diffusion and allows the forward calculation of concentrations of atmospheric tracers at nodes of a global regular grid when a source is specified. Thus, GLADIM can be used for the forward simulation of pollutant propagation (volcanic ash, radionuclides, and so on). Working in the reverse direction, GLADIM allows the detection of remote sources that mainly contribute to the tracer concentration at an observation point. This property of Lagrangian models is widely used for data analysis and the reverse modeling of emission sources of a pollutant specified. In this work we describe the model and some results of its validation through a comparison with results of a similar model and observation data

Adjoint of the global Eulerian-Lagrangian coupled atmospheric transport model (A-GELCA v1.0): development and validation

We present the development of the Adjoint of the Global Eulerian–Lagrangian Coupled Atmospheric (A-GELCA) model that consists of the National Institute for Environmental Studies (NIES) model as an Eulerian three-dimensional transport model (TM), and FLEXPART (FLEXible PARTicle dispersion model) as the Lagrangian Particle Dispersion Model (LPDM). The forward tangent linear and adjoint components of the Eulerian model were constructed directly from the original NIES TM code using an automatic differentiation tool known as TAF (Transformation of Algorithms in Fortran; http://www.FastOpt.com), with additional manual pre- and post-processing aimed at improving transparency and clarity of the code and optimizing the performance of the computing, including MPI (Message Passing Interface). The Lagrangian component did not require any code modification, as LPDMs are self-adjoint and track a significant number of particles backward in time in order to calculate the sensitivity of the observations to the neighboring emission areas. The constructed Eulerian adjoint was coupled with the Lagrangian component at a time boundary in the global domain. The simulations presented in this work were performed using the A-GELCA model in forward and adjoint modes. The forward simulation shows that the coupled model improves reproduction of the seasonal cycle and short-term variability of CO2. Mean bias and standard deviation for five of the six Siberian sites considered decrease roughly by 1 ppm when using the coupled model. The adjoint of the Eulerian model was shown, through several numerical tests, to be very accurate (within machine epsilon with mismatch around to ±6 e−14) compared to direct forward sensitivity calculations. The developed adjoint of the coupled model combines the flux conservation and stability of an Eulerian discrete adjoint formulation with the flexibility, accuracy, and high resolution of a Lagrangian backward trajectory formulation. A-GELCA will be incorporated into a variational inversion system designed to optimize surface fluxes of greenhouse gases

Healing and Ritual Imagination in Chinese Medicine: The Multiple Interpretations of Zhuyou

In the Chinese medical corpus, ritual healing largely fell under the rubric of zhuyou 祝由 to uncover and expel the unknown, imperceptible, and occult causes of illness. Often dealing with uncertain or incurable cases, zhuyou remained at the cutting-edge of contemporary medicine. For a rising medical elite after the Northern Song, zhuyou was the branch of medicine to flexibly incorporate and critique the variety of ritual therapies into orthodox practice. Zhuyou employed prayer, incantations, talismans, gestures, and drugs in a nuanced clinical encounter to reveal the hidden root of disorder ranging from a blockage of qi, spirit possession, emotional imbalance, or loss of virtue. These rituals opened an imaginative space for therapeutic play where patients and healers could use spiritual proxies and props to address difficult emotions or issues that were often the hidden cause of affliction. The development of zhuyou also reflected the changing role of ritual in the history of Chinese medicine and the exchanges among physicians, Daoist priests, and other ritual healers. The significance of ritual in Chinese medical history has largely remained unclear as most editions of medical classics republished since the early twentieth century excise relevant chapters and zhuyou manuscripts, until recently, were uncatalogued

Study of the footprints of short-term variation in XCO₂ observed by TCCON sites using NIES and FLEXPART atmospheric transport models

The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier Transform Spectrometers (FTS) that record near-infrared (NIR) spectra of the Sun. From these spectra, accurate and precise observations of CO2 column-averaged dry-air mole fraction (denoted XCO2) are retrieved. TCCON FTS observations have previously been used to validate satellite estimations of XCO2; however, our knowledge of the short-term spatial and temporal variations in XCO2 surrounding the TCCON sites is limited. In this work, we use the National Institute for Environmental Studies (NIES) Eulerian three-dimensional transport model and the FLEXPART (FLEXible PARTicle) Lagrangian Particle Dispersion Model (LPDM) to determine the footprints of short-term variations in XCO2 observed by operational, past, future, and possible TCCON sites. We propose a footprint-based method for the colocation of satellite and TCCON XCO2 observations, and estimate the performance of the method using the NIES model and five GOSAT XCO2 product datasets. Comparison of the proposed approach with a standard geographic method shows higher number of colocation points and average bias reduction up to 0.15 ppm for a subset of 16 stations for the period from January 2010 to January 2014. Case studies of the Darwin and La Réunion sites reveal that when the footprint area is rather curved, non-uniform and significantly different from a geographical rectangular area, the differences between these approaches are more noticeable. This emphasizes that the colocation is sensitive to local meteorological conditions and flux distributions

Study of the footprints of short-term variation in XCO_2 observed by TCCON sites using NIES and FLEXPART atmospheric transport models

The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier transform spectrometers (FTSs) that record near-infrared (NIR) spectra of the sun. From these spectra, accurate and precise observations of CO_2 column-averaged dry-air mole fractions (denoted XCO_2) are retrieved. TCCON FTS observations have previously been used to validate satellite estimations of XCO_2; however, our knowledge of the short-term spatial and temporal variations in XCO_2 surrounding the TCCON sites is limited. In this work, we use the National Institute for Environmental Studies (NIES) Eulerian three-dimensional transport model and the FLEXPART (FLEXible PARTicle dispersion model) Lagrangian particle dispersion model (LPDM) to determine the footprints of short-term variations in XCO_2 observed by operational, past, future and possible TCCON sites. We propose a footprint-based method for the collocation of satellite and TCCON XCO_2 observations and estimate the performance of the method using the NIES model and five GOSAT (Greenhouse Gases Observing Satellite) XCO_2 product data sets. Comparison of the proposed approach with a standard geographic method shows a higher number of collocation points and an average bias reduction up to 0.15 ppm for a subset of 16 stations for the period from January 2010 to January 2014. Case studies of the Darwin and Reunion Island sites reveal that when the footprint area is rather curved, non-uniform and significantly different from a geographical rectangular area, the differences between these approaches are more noticeable. This emphasises that the collocation is sensitive to local meteorological conditions and flux distributions

Testiranje pokrivenog kamatnog pariteta: slučaj HRK/EUR

Cilj ovog rada je uspostaviti vezu između terminske premije/diskonta i kamatnog diferencijala koristeći model pokrivenog kamatnog pariteta (CIRP). Model je izgrađen na pretpostavkama visoke mobilnosti kapitala, savršene supstitucije valuta i odsutnosti transakcijskih troškova. Postojanje pokrivenog kamatnog pariteta testirano je na podacima tečaja eura i kune za Hrvatsku u 2010. godini. Rezultati su potvrdili skoro savršeno važenje pokrivenog kamatnog pariteta u kratkom roku koristeći referentne kamatnjake ZIBOR i EURIBOR kao i odgovarajuće vrijednosti spot i forward HRK/EUR tečaja odgovarajuće ročnosti od 1, 3, 6, 9 i 12 mjeseci. Ekonometrijski test je proveden kako bi se procijenio nagib linije pokrivenog kamatnog pariteta. Rezultati su pokazali kako je empirijska vrijednost nagiba linije kamatnog pariteta gotovo identična očekivanoj vrijednosti koristeći teorijski model pokrivenog kamatnog pariteta. Zbog relativno uske zone kamatnog pariteta kratkoročne mogućnosti arbitraže su minimizirane kao i vjerojatnost ostvarenja nerizičnog profita

Global Lagrangian atmospheric dispersion model

The Global Lagrangian Atmospheric Dispersion Model (GLADIM) is described. GLADIM is based on the global trajectory model, which had been developed earlier and uses fields of weather parameters from different atmospheric reanalysis centers for calculations of trajectories of air mass that include trace gases. GLADIM includes the parameterization of turbulent diffusion and allows the forward calculation of concentrations of atmospheric tracers at nodes of a global regular grid when a source is specified. Thus, GLADIM can be used for the forward simulation of pollutant propagation (volcanic ash, radionuclides, and so on). Working in the reverse direction, GLADIM allows the detection of remote sources that mainly contribute to the tracer concentration at an observation point. This property of Lagrangian models is widely used for data analysis and the reverse modeling of emission sources of a pollutant specified. In this work we describe the model and some results of its validation through a comparison with results of a similar model and observation data

Comparing GOSAT observations of localized CO2 enhancements by large emitters with inventory-based estimates

We employed an atmospheric transport model to attribute column-averaged CO2 mixing ratios (XCO2) observed by Greenhouse gases Observing SATellite (GOSAT) to emissions due to large sources such as megacities and power plants. XCO2 enhancements estimated from observations were compared to model simulations implemented at the spatial resolution of the satellite observation footprint (0.1° × 0.1°). We found that the simulated XCO2 enhancements agree with the observed over several continental regions across the globe, for example, for North America with an observation to simulation ratio of 1.05 ± 0.38 (p < 0.1), but with a larger ratio over East Asia (1.22 ± 0.32; p < 0.05). The obtained observation-model discrepancy (22%) for East Asia is comparable to the uncertainties in Chinese emission inventories (~15%) suggested by recent reports. Our results suggest that by increasing the number of observations around emission sources, satellite instruments like GOSAT can provide a tool for detecting biases in reported emission inventories