Construction and Application of a Regional Kilometer-Scale Carbon Source and Sink Assimilation Inversion System(CCMVS-R)

CO_(2)is one of the most important greenhouse gases(GHGs)in the earth’s atmosphere.Since the industrial era,anthropogenic activities have emitted excessive quantities of GHGs into the atmosphere,resulting in climate warming since the 1950s and leading to an increased frequency of extreme weather and climate events.In 2020,China committed to striving for carbon neutrality by 2060.This commitment and China’s consequent actions will result in significant changes in global and regional anthropogenic carbon emissions and therefore require timely,comprehensive,and objective monitoring and verification support(MVS)systems.The MVS approach relies on the top-down assimilation and inversion of atmospheric CO_(2)concentrations,as recommended by the Intergovernmental Panel on Climate Change(IPCC)Inventory Guidelines in 2019.However,the regional high-resolution assimilation and inversion method is still in its initial stage of development.Here,we have constructed an inverse system for carbon sources and sinks at the kilometer level by coupling proper orthogonal decomposition(POD)with four-dimensional variational(4DVar)data assimilation based on the weather research and forecasting-greenhouse gas(WRF-GHG)model.Our China Carbon Monito ring and Verification Support at the Regional level(CCMVS-R)system can continuously assimilate information on atmospheric CO_(2)and other related information and realize the inversion of regional and local anthropogenic carbon emissions and natural terrestrial ecosystem carbon exchange.Atmospheric CO_(2)data were collected from six ground-based monito ring sites in Shanxi Province,China to verify the inversion effect of regio nal anthropogenic carbon emissions by setting ideal and real experiments using a two-layer nesting method(at 27 and 9 km).The uncertainty of the simulated atmospheric CO_(2)decreased significantly,with a root-mean-square error of CO_(2)concentration values between the ideal value and the simulated after assimilation was close to 0.The total anthropogenic carbon emissions in Shanxi Province in 2019 from the assimilated inversions were approximately 28.6%(17%-38%)higher than the mean of five emission inventories using the bottomup method,showing that the top-down CCMVS-R system can obtain more comprehensive information on anthropogenic carbon emissions.

Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI 3DVar, EnKF, and Hybrid En3DVar for the Analysis and Short-Term Forecast of a Supercell Storm Case

Capabilities to assimilate Geostationary Operational Environmental Satellite “R-series ”(GOES-R) Geostationary Lightning Mapper(GLM) flash extent density(FED) data within the operational Gridpoint Statistical Interpolation ensemble Kalman filter(GSI-EnKF) framework were previously developed and tested with a mesoscale convective system(MCS) case. In this study, such capabilities are further developed to assimilate GOES GLM FED data within the GSI ensemble-variational(EnVar) hybrid data assimilation(DA) framework. The results of assimilating the GLM FED data using 3DVar, and pure En3DVar(PEn3DVar, using 100% ensemble covariance and no static covariance) are compared with those of EnKF/DfEnKF for a supercell storm case. The focus of this study is to validate the correctness and evaluate the performance of the new implementation rather than comparing the performance of FED DA among different DA schemes. Only the results of 3DVar and pEn3DVar are examined and compared with EnKF/DfEnKF. Assimilation of a single FED observation shows that the magnitude and horizontal extent of the analysis increments from PEn3DVar are generally larger than from EnKF, which is mainly caused by using different localization strategies in EnFK/DfEnKF and PEn3DVar as well as the integration limits of the graupel mass in the observation operator. Overall, the forecast performance of PEn3DVar is comparable to EnKF/DfEnKF, suggesting correct implementation.

A Spatially Dependent Nudging Method and Its Application to a Global Tide Assimilation

Tides represent a crucial dynamic process in the ocean and play a vital role in both marine and atmospheric studies,thus,accurate simulation of tidal processes is of the utmost importance in tidal circulation models.Bazed on the sequential data assimilation method and the concept of the Kalman gain matrix,this paper proposes a new nudging method with spatially dependent coefficients for tidal assimilation.The spatial-dependent nudging method not only retains the advantages of the traditional nudging method but also facilitates the direct determination of a more reasonable spatial distribution of nudging coefficients.Utilizing the M_(2)tidal constituent(the main lunar semidiurnal tide)as an illustration,we conducted assimilation experiments of sea-level data to the barotropic circulation and tide model to assess the global harmonic constants of the M_(2)constituent.The results demonstrate that the spatial-dependent nudging method successfully mitigates deviations of tidal phase lag.Following assimilation using the new method,the deviations of the M_(2)tidal amplitude and phase lag can be reduced by 47%and 18%compared to the traditional nudging method,respectively,while the respective values for the non-assimilated case are as much as 9%and 11%.We also applied the S-nudging method to realistic tidal simulations and noted a significantly enhanced effectiveness relative to traditional methods,making it highly valuable for modeling oceanic tidal circulations.

The effect of glutathione on glucosinolate biosynthesis through the sulfur assimilation pathway in pakchoi associated with the growth conditions

Glucosinolates(GSLs) are a group of nitrogen-and sulfur-containing secondary metabolites, synthesized primarily in members of the Brassicaceae family, that play an important role in food flavor, plant antimicrobial activity, resistance to insect attack, stress tolerance, and human anti-cancer effects. As a sulfur-containing compound, glutathione has a strong connection with GSLs biosynthesis as a sulfur donor or redox system, and exists in reduced(glutathione;GSH) and oxidized(glutathione disulfide;GSSG) forms. However, the mechanism of GSH regulating GSLs biosynthesis remainds unclear. Hence, the exogenous therapy to pakchoi under normal growth condition and sulfur deficiency condition were conducted in this work to explore the relevant mechanism. The results showed that exogenous application of buthionine sulfoximine, an inhibitor of GSH synthesis, decreased the transcript levels of GSLs synthesis-related genes and transcription factors, as well as sulfur assimilation-related genes under the normal growth condition. Application of exogenous GSH inhibited the expression of GSLs synthesis-and sulfur assimilation-related genes under the normal condition, while the GSLs biosynthesis and the sulfur assimilation pathway were activated by exogenous application of GSH when the content of GSH in vivo of plants decreased owing to sulfur deficiency. Moreover,exogenous application of GSSG increased the transcript levels of GSLs synthesis-and sulfur assimilation-related genes under the normal growth condition and under sulfur deficiency. The present work provides new insights into the molecular mechanisms of GSLs biosynthesis underlying glutathione regulation.

Optimal Assimilation of Microwave Upper-Level Sounding Data in CMA-GFS

Various approaches have been proposed to minimize the upper-level systematic biases in global numerical weather prediction(NWP)models by using satellite upper-air sounding channels as anchors.However,since the China Meteorological Administration Global Forecast System(CMA-GFS)has a model top near 0.1 hPa(60 km),the upper-level temperature bias may exceed 4 K near 1 hPa and further extend to 5 hPa.In this study,channels 12–14 of the Advanced Microwave Sounding Unit A(AMSU-A)onboard five satellites of NOAA and METOP,whose weighting function peaks range from 10 to 2 hPa are all used as anchor observations in CMA-GFS.It is shown that the new“Anchor”approach can effectively reduce the biases near the model top and their downward propagation in three-month assimilation cycles.The bias growth rate of simulated upper-level channel observations is reduced to±0.001 K d^(–1),compared to–0.03 K d^(–1)derived from the current dynamic correction scheme.The relatively stable bias significantly improves the upper-level analysis field and leads to better global medium-range forecasts up to 10 days with significant reductions in the temperature and geopotential forecast error above 10 hPa.

Bridging element-free Galerkin and pluri-Gaussian simulation for geological uncertainty estimation in an ensemble smoother data assimilation framework

The facies distribution of a reservoir is one of the biggest concerns for geologists,geophysicists,reservoir modelers,and reservoir engineers due to its high importance in the setting of any reliable decisionmaking/optimization of field development planning.The approach for parameterizing the facies distribution as a random variable comes naturally through using the probability fields.Since the prior probability fields of facies come either from a seismic inversion or from other sources of geologic information,they are not conditioned to the data observed from the cores extracted from the wells.This paper presents a regularized element-free Galerkin(R-EFG)method for conditioning facies probability fields to facies observation.The conditioned probability fields respect all the conditions of the probability theory(i.e.all the values are between 0 and 1,and the sum of all fields is a uniform field of 1).This property achieves by an optimization procedure under equality and inequality constraints with the gradient projection method.The conditioned probability fields are further used as the input in the adaptive pluri-Gaussian simulation(APS)methodology and coupled with the ensemble smoother with multiple data assimilation(ES-MDA)for estimation and uncertainty quantification of the facies distribution.The history-matching of the facies models shows a good estimation and uncertainty quantification of facies distribution,a good data match and prediction capabilities.

Application of the finite analytic numerical method to a flowdependent variational data assimilation

An anisotropic diffusion filter can be used to model a flow-dependent background error covariance matrix,which can be achieved by solving the advection-diffusion equation.Because of the directionality of the advection term,the discrete method needs to be chosen very carefully.The finite analytic method is an alternative scheme to solve the advection-diffusion equation.As a combination of analytical and numerical methods,it not only has high calculation accuracy but also holds the characteristic of the auto upwind.To demonstrate its ability,the one-dimensional steady and unsteady advection-diffusion equation numerical examples are respectively solved by the finite analytic method.The more widely used upwind difference method is used as a control approach.The result indicates that the finite analytic method has higher accuracy than the upwind difference method.For the two-dimensional case,the finite analytic method still has a better performance.In the three-dimensional variational assimilation experiment,the finite analytic method can effectively improve analysis field accuracy,and its effect is significantly better than the upwind difference and the central difference method.Moreover,it is still a more effective solution method in the strong flow region where the advective-diffusion filter performs most prominently.

Progress and future prospects of decadal prediction and data assimilation:A review

年代际预测,也称为“近期气候预测”,旨在预测未来1-10年内的气候变化,是气候预测和气候变化研究领域的一个新关注点.它位于季节至年际预测和长期气候变化预测之间,结合了初值问题和外部强迫问题的两个方面.年代际预测的核心技术在于用于模式初始化的同化方法的准确性和效率,其目标是为模式提供准确的初始条件,其中包含观测到的气候系统内部变率,年代际预测的初始化通常涉及在耦合框架内同化海洋观测,其中观测到的信号通过耦合过程传递到其他分量,如大气和海冰.然而,最近的研究越来越关注在海洋-大气耦合模式中探索耦合数据同化(CDA),有人认为CDA有潜力显著提高年代际预测技巧.本文综合评述了该领域的三个方面的研究现状:初始化方法,年代际气候预测的可预测性和预测技巧,以及年代际预测的未来发展和挑战.

SAR Data Assimilation for Crop Biomass Simulation Based on Crop Growth Model

Biomass from SAR data was assimilated into crop growth model to describe relationship between crop biomass and crop growth time to improve estimation accuracy of biomass. In addition, inverse model was established in order to estimate biomass according to relationship between biomass and backscattering coefficients from SAR data. Based on cost function, parameters of growth model were optimized as per conjugate gradient method, minimizing the differences between estimated biomass and inversion values from SAR data. The results indicated that the simulated biomass using the revised growth model with SAR data was consistent with the measured one in time distribution and even higher in accuracy than that without SAR data. Hence, the key parameters of crop growth model could be revised by real-time growth information from SAR data and accuracy of the simulated biomass could be improved accordingly.

Studies of Variational Assimilation for the Inversion of the Coupled Air-sea Model

For the prediction of ENSO, the accuracy of the model including the parameters, initial value and others of the model is important, which can be retrieved by the variational data assimilation methods developed in recent years. However, when the nonlinearity of the model is quite strong, the effect of the improvement made by the 4-D variational data assimilation may be poor due to the bad approximation of the tangent linear model to the original model. So in the paper the ideas in the optimal control is introduced to improve the effect of 4-DVAR in the inversion of the parameters of a nonlinear dynamic ENSO model. The results indicate that when the terminal controlling term is added to the cost functional of 4DVAR, which originated from the optimal control, the effect of the inversion may be largely improved comparing to the traditional 4DVAR, as can be especially obvious from the phase orbit of the model variables. The results in the paper also suggest that the method of 4DVAR in combination with optimal control cannot only reduce the error resulting from the inaccuracy of the model parameters but also can correct the parameters itself. This gives a good method in modifying the model and improving the quality of prediction of ENSO.

Simulating leaf net CO_2 assimilation rate of C_3 & C_4 plants and its response to environmental factors

Basic structure and algorithm of leaf mechanism photosynthesis model were described in first part of this study based on former researcher results. Then, considering some environmental factors influencing on leaf photosynthesis, three numerical sensitivity experiments were carried out. We simulated the sing le leaf net CO2 assimilation, which acts as a function of different light, carbo n dioxide and temperature conditions. The relationships between leaf net photosy nthetic rate of C3 and C4 plant with CO2 concentration intercellular, leaf tempe rature, and photosynthetic active radiation (PAR) were presented, respectively. The results show the numerical experiment may indicate the main characteristic o f plant photosynthesis in C3 and C4 plant, and further can be used to integrate with the regional climate model and act as land surface process scheme, and bett er understand the interaction between vegetation and atmosphere.

STUDY ON THE ADJOINT METHOD IN DATA ASSIMILATION AND THE RELATED PROBLEMS

It is not reasonable that one can only use the adjoint of model in data assimilation. The simulated numerical experiment shows that for the tidal model, the result of the adjoint of equation is almost the same as that of the adjoint of model: the averaged absolute difference of the amplitude between observations and simulation is less than 5.0 cm and that of the phase-lag is less than 5.0°. The results are both in good agreement with the observed M2 tide in the Bohai Sea and the Yellow Sea. For comparison, the traditional methods also have been used to simulate M2 tide in the Bohai Sea and the Yellow Sea. The initial guess values of the boundary conditions are given first, and then are adjusted to acquire the simulated results that are as close as possible to the observations. As the boundary conditions contain 72 values, which should be adjusted and how to adjust them can only be partially solved by adjusting them many times. The satisfied results are hard to acquire even gigantic efforts are done. Here, the automation of the treatment of the open boundary conditions is realized. The method is unique and superior to the traditional methods. It is emphasized that if the adjoint of equation is used, tedious and complicated mathematical deduction can be avoided. Therefore the adjoint of equation should attract much attention.

Simulating leaf net CO2 assimilation rate of C3 & C4 plants and its response to environmental factors

Basic structure and algorithm of leaf mechanism photosynthesis model were described in first part of this study based on former researcher results. Then, considering some environmental factors influencing on leaf photosynthesis, three numerical sensitivity experiments were carried out. We simulated the sing le leaf net CO2 assimilation, which acts as a function of different light, carbo n dioxide and temperature conditions. The relationships between leaf net photosy nthetic rate of C3 and C4 plant with CO2 concentration intercellular, leaf tempe rature, and photosynthetic active radiation (PAR) were presented, respectively. The results show the numerical experiment may indicate the main characteristic o f plant photosynthesis in C3 and C4 plant, and further can be used to integrate with the regional climate model and act as land surface process scheme, and bett er understand the interaction between vegetation and atmosphere.

Coupling Ensemble Kalman Filter with Four-dimensional Variational Data Assimilation

This study examines the performance of coupling the deterministic four-dimensional variational assimilation system （4DVAR） with an ensemble Kalman filter （EnKF） to produce a superior hybrid approach for data assimilation. The coupled assimilation scheme （E4DVAR） benefits from using the state-dependent uncertainty provided by EnKF while taking advantage of 4DVAR in preventing filter divergence： the 4DVAR analysis produces posterior maximum likelihood solutions through minimization of a cost function about which the ensemble perturbations are transformed, and the resulting ensemble analysis can be propagated forward both for the next assimilation cycle and as a basis for ensemble forecasting. The feasibility and effectiveness of this coupled approach are demonstrated in an idealized model with simulated observations. It is found that the E4DVAR is capable of outperforming both 4DVAR and the EnKF under both perfect- and imperfect-model scenarios. The performance of the coupled scheme is also less sensitive to either the ensemble size or the assimilation window length than those for standard EnKF or 4DVAR implementations.

Assimilation of carbonate country rock by the parent magma of the Panzhihua Fe-Ti-V deposit(SW China):Evidence from stable isotopes

The Panzhihua intrusion in southwest China is part of the Emeishan Large Igneous Province and host of a large Fe-Ti-V ore deposit.During emplacement of the main intrusion,multiple generations of mafic dykes invaded carbonate wall rocks,producing a large contact aureole.We measured the oxygen-isotope composition of the intrusions,their constituent minerals,and samples of the country rock.Magnetite and plagioclase from Panzhihua intrusion haveδ18O values that are consistent with magmatic equilibrium, and formed from magmas withδ18O values that were 1-2‰higher than expected in a mantle-derived magma.The unmetamorphosed country rock has highδ18O values,ranging from 13.2‰（sandstone） to 24.6-28.6‰（dolomite）.The skarns and marbles from the aureole have lowerδ18O andδ13C values than their protolith suggesting interaction with fluids that were in exchange equilibrium with the adjacent mafic magmas and especially the numerous mafic dykes that intruded the aureole.This would explain the alteration ofδ18O of the dykes which have significantly higher values than expected for a mantle-derived magma.Depending on the exactδ18O values assumed for the magma and contaminant, the amount of assimilation required to produce the elevatedδ18O value of the Panzhihua intrusion was between 8 and 13.7 wt.%,assuming simple mixing.The exact mechanism of contamination is unclear but may involve a combination of assimilation of bulk country rock,mixing with a melt of the country rock and exchange with CO2-rich fluid derived from decarbonation of the marls and dolomites.These mechanisms,particularly the latter,were probably involved in the formation of the Fe-Ti-V ores.

Application of Direct Assimilation of ATOVS Microwave Radiances to Typhoon Track Prediction

In order to solve the difficult problem of typhoon track prediction due to the sparsity of conventional data over the tropical ocean, in this paper, the No. 0205 typhoon Rammasun of 4-6 July 2002 is studied and an experiment of the typhoon track prediction is made with the direct use of the Advanced TIROS-N Operational Vertical Sounder (ATOVS) microwave radiance data in three-dimensional variational data assimilation. The prediction result shows that the experiment with the ATOVS microwave radiance data can not only successfully predict the observed fact that typhoon Rammasun moves northward and turns right, but can also simulate the action of the fast movement of the typhoon, which cannot be simulated with only conventional radiosonde data. The skill of the typhoon track prediction with the ATOVS microwave radiance data is much better than that without the ATOVS data. The typhoon track prediction of the former scheme is consistent in time and in location with the observation. The direct assimilation of ATOVS microwave radiance data is an available way to solve the problem of the sparse observation data over the tropical ocean, and has great potential in being applied to typhoon track prediction.

Nitrate Effect on Rice Growth and Nitrogen Absorption and Assimilation at Different Growth Stages

The effect of nitrate （NO3^-） on rice （Oryza sativa L.） growth as well as N absorption and assimilation during different growth stages was examined using three typical rice cultivars. Dry weight, yield, N uptake, nitrate reductase activity （NRA） in leaves, and glutamine synthetase activity （GSA） in roots and leaves during their entire growth periods, as well as the kinetic parameters of ammonium （NH4^＋） uptake at the seedling stage, were measured with solution culture experiments. Results indicated that addition of NH4^＋-N and NO3^-N at a ratio of 75：25 （NH4^＋＋NO3^- treatment） when compared with that of NH4^＋-N alone （NH4^＋ treatment） increased the dry weight of ‘Nanguang＇ cultivar by 30% and ‘Yunjing 38＇ cultivar by 31%, and also increased their grain yield by 21% and 17%, respectively. For the four growth stages, the total N accumulation in plants increased by an average of 36% for ‘Nanguang＇ and 31% for ‘Yunjing 38＇, whereas the increasing effect of NO3^- in the ‘4007＇ cultivar was only found at the seedling stage, in the NH4^＋＋NO3^- treatment compared to the NH4^＋ treatment, NRA in the leaves increased by 2.09 folds, and GSA increased by 92% in the roots and 52% in the leaves of the three cultivars. NO3^- supply increased the maximum uptake rate （Vmax） in the ‘Nanguang＇ and ‘Yunjing 38＇ cultivars, reflecting that the NO3^- itself, not the increasing N concentration, increased the uptake rate of NH4^＋ by rice. There was no effect on the apparent Michaelis-Menten constant （Kin） of the three cultivars. Thus, some replacement of NH4^＋ with NO3^-could greatly improve the growth of rice plants, mainly on account of the increased uptake of NH4^＋ promoted by NO3^-, and future studies should focus on the molecular mechanism of the increased uptake of NH4^＋ by NO3^-.

Assimilation and Simulation of Typhoon Rusa (2002) Using the WRF System

Using the recently developed Weather Research and Forecasting (WRF) 3DVAR and the WRF model, numerical experiments are conducted for the initialization and simulation of typhoon Rusa (2002). The observational data used in the WRF 3DVAR are conventional Global Telecommunications System (GTS) data and Korean Automatic Weather Station (AWS) surface observations. The Background Error Statistics (BES) via the National Meteorological Center (NMC) method has two different resolutions, that is, a 210-km horizontal grid space from the NCEP global model and a 10-km horizontal resolution from Korean operational forecasts. To improve the performance of the WRF simulation initialized from the WRF 3DVAR analyses, the scale-lengths used in the horizontal background error covariances via recursive filter are tuned in terms of the WRF 3DVAR control variables, streamfunction, velocity potential, unbalanced pressure and specific humidity. The experiments with respect to different background error statistics and different observational data indicate that the subsequent 24-h the WRF model forecasts of typhoon Rusa's track and precipitation are significantly impacted upon the initial fields. Assimilation of the AWS data with the tuned background error statistics obtains improved predictions of the typhoon track and its precipitation.

Transport of Nitrogen Assimilation in Xylem Vessels of Green Tea Plants Fed with NH_4-N and NO_3-N

An experiment was carried out to study the transport process of nitrogen （N） assimilation from tea roots by monitoring the dynamic composition of N compounds in xylem sap after 15^N-NO3 and 15^N-NH4 were fed to the root of tea plants （Camellia sinensis L.）. Results showed that the main amino acids were glutamine, theanine, axginine, asparic acid and glutamic acid, which accounted for 49%, 17%, 8%, 7%, and 4%, respectively, of the total amino acids in the xylem sap. After the tea plants were fed with 15^N-NO3 and 15^N-NH4 for 48 h, the amount of total amino acids in xylem sap significantly increased and those fed with 15^N-NH4 had higher increment than those with 15^N-NOa. Two hours after 15^N- NO3 and 15^N-NH4 were fed, 15N abundance in glutamine, asparagine, glutamic acid, alanine, and arginine were detected and increased quickly over time. This indicated that it took less than 2 h for NO3-N and NH4-N to be absorbed by tea roots, incorporated into the above amino acids and transported to the xylem sap. Rapid increase in 15^N-NO3 in the xylem sap of tea plants fed with 15^N-NO3 indicated that nitrate could be directly transported to the xylem sap. Glutamine, theanine, and alanine were the main amino acids transported in xylem sap of tea plants fed with both 15^N-NO3 and 15^N-NH4.