Impact of Assimilation of Radiosonde and UAV Observations from the Southern Ocean in the Polar WRF Model

Weather forecasting in the Southern Ocean and Antarctica is a challenge above all due to the rarity of observations to be assimilated in numerical weather prediction(NWP)models.As observations are expensive and logistically challenging,it is important to evaluate the benefit that additional observations could bring to NWP.Atmospheric soundings applying unmanned aerial vehicles(UAVs)have a large potential to supplement conventional radiosonde sounding observations.Here,we applied UAV and radiosonde sounding observations from an RV Polarstern cruise in the ice-covered Weddell Sea in austral winter 2013 to evaluate the impact of their assimilation in the Polar version of the Weather Research and Forecasting(Polar WRF)model.Our experiments revealed small to moderate impacts of radiosonde and UAV data assimilation.In any case,the assimilation of sounding data from both radiosondes and UAVs improved the analyses of air temperature,wind speed,and humidity at the observation site for most of the time.Further,the impact on the results of 5-day-long Polar WRF experiments was often felt over distances of at least 300 km from the observation site.All experiments succeeded in capturing the main features of the evolution of near-surface variables,but the effects of data assimilation varied between different cases.Due to the limited vertical extent of the UAV observations,the impact of their assimilation was limited to the lowermost 1?2-km layer,and assimilation of radiosonde data was more beneficial for modeled sea level pressure and near-surface wind speed.

Assimilation of Sea Surface Temperature in a Global Hybrid Coordinate Ocean Model

The Hybrid Coordinate Ocean Model(HYCOM) uses different vertical coordinate choices in different regions. In HYCOM, the prognostic variables include not only the seawater temperature, salinity and current fields, but also the layer thickness. All prognostic variables are usually adjusted in the assimilation when multivariate data assimilation methods are used to assimilate sea surface temperature(SST). This paper investigates the effects of SST assimilation in a global HYCOM model using the Ensemble Optimal Interpolation multivariate assimilation method. Three assimilation experiments are conducted from 2006–08. In the first experiment, all model variables are adjusted during the assimilation process. In the other two experiments, the temperature alone is adjusted in the entire water column and in the mixed layer. For comparison, a control experiment without assimilation is also conducted. The three assimilation experiments yield notable SST improvements over the results of the control experiment. Additionally, the experiments in which all variables are adjusted and the temperature alone in all model layers is adjusted, produce significant negative effects on the subsurface temperature. Also, they yield negative effects on the subsurface salinity because it is associated with temperature and layer thickness. The experiment adjusting the temperature alone in the mixed layer yields positive effects and outperforms the other experiments. The heat content in the upper 300 m and 300–700 m layers further suggests that it yields the best performance among the experiments.

Petrogenesis of Quebrada de la Mina and Altar North porphyries (Cordillera of San Juan, Argentina): Crustal assimilation and metallogenic implications

We investigate the geology of Altar North(Cu-Au) and Quebrada de la Mina(Au) porphyry deposits located in San Juan Province(Argentina), close to the large Altar porphyry copper deposit(995 Mt,0.35% Cu, 0.083 g/t Au), to present constraints on the magmatic processes that occurred in the parental magma chambers of these magmatic-hydrothermal systems. Altar North deposit comprises a plagioclase-amphibole-phyric dacite intrusion(Altar North barren porphyry) and a plagioclaseamphibole-biotite-phyric dacite stock(Altar North mineralized porphyry, 11.98 ± 0.19 Ma). In Quebrada de la Mina, a plagioclase-amphibole-biotite-quartz-phyric dacite stock(QDM porphyry,11.91±0.33 Ma) crops out. High Sr/Y ratios(92-142) and amphibole compositions of Altar North barren and QDM porphyries reflect high magmatic oxidation states(fO_2= NNO+1.1 to+1.6) and high fH_2O conditions in their magmas. Zones and rims enriched in anorthite(An_(37-48))), SrO(0.22-0.33 wt.%)and FeO(0.21-0.37 wt.%) in plagioclase phenocrysts are evidences of magmatic recharge processes in the magma chambers. Altar North and Quebrada de la Mina intrusions have relatively homogeneous isotopic compositions(^(87)Sr/^(86)Sr_(t)= 0.70450-0.70466, ε_(ND)(t) = +0.2 to +1.2) consistent with mixed mantle and crust contributions in their magmas. Higher Pb isotopes ratios(^(207)Pb/^(204)Pb=15.6276-15.6294) of these intrusions compared to other porphyries of the district, reflect an increase in the assimilation of high radiogenic Pb components in the magmas. Ages of zircon xenocrysts(297,210,204,69 Ma) revealed that the magmas have experienced assimilation of Miocene, Cretaceous, Triassic and Carboniferous crustal rocks.Fluids that precipitated sulfides in the Altar deposit may have remobilized Pb from the host rocks, as indicated by the ore minerals being more radiogenic(207Pb/204 Pb = 15.6243-15.6269) than their host intrusions. Au/Cu ratio in Altar porphyries(average Au/Cu ratio of 0.14 ×10^(-4)by weight in Altar Central)is higher than in the giant Miocene porphyry deposits located to the south: Los Pelambres, Rio Blanco and Los Bronces(Chile) and Pachon(Argentina). We suggest that the increase in Au content in the porphyries of this region could be linked to the assimilation of high radiogenic Pb components in the magmas within these long-lived maturation systems.

Analysis of influence of observation operator on sequential data assimilation through soil temperature simulation with common land model

An observation operator is a bridge linking the system state vector and observations in a data assimilation system. Despite its importance, the degree to which an observation operator influences the performance of data assimilation methods is still poorly understood. This study aimed to analyze the influences of linear and nonlinear observation operators on the sequential data assimilation through soil temperature simulation using the unscented particle filter(UPF) and the common land model. The linear observation operator between unprocessed simulations and observations was first established. To improve the correlation between simulations and observations, both were processed based on a series of equations. This processing essentially resulted in a nonlinear observation operator. The linear and nonlinear observation operators were then used along with the UPF in three assimilation experiments: an hourly in situ soil surface temperature assimilation, a daily in situ soil surface temperature assimilation, and a moderate resolution imaging spectroradiometer(MODIS) land surface temperature(LST) assimilation. The results show that the filter improved the soil temperature simulation significantly with the linear and nonlinear observation operators. The nonlinear observation operator improved the UPF's performance more significantly for the hourly and daily in situ observation assimilations than the linear observation operator did, while the situation was opposite for the MODIS LST assimilation. Because of the high assimilation frequency and data quality, the simulation accuracy was significantly improved in all soil layers for hourly in situ soil surface temperature assimilation, while the significant improvements of the simulation accuracy were limited to the lower soil layers for the assimilation experiments with low assimilation frequency or low data quality.

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.

Involvement of sulfur assimilation in the low β subunit content of soybean seed storage protein revealed by comparative transcriptome analysis

The β subunit of soybean [Glycine max (L.) Merr.] seed storage protein is of great significance in sulfur-containing amino acid balance and soybean processing properties. The objective of this study was to elucidate the relationship between the β subunit and sulfur-containing amino acid composition, and the potential regulatory mechanism. The β subunit was independently accumulated in comparison with other major subunits (α/α′, acidic, basic, and A3) during seed filling, and a low level of β subunit content (BSC) was formed during the accumulation process. In low-BSC mature seeds, crude protein, oil content, and fatty acid composition were not changed, but sulfur-containing amino acids (Cys + Met) in the low- BSC seeds increased significantly (by 31.5%), suggesting that an internal regulatory mechanism within seed might be responsible for the rebalance of seed protein composition and that sulfur assimilation might be deeply involved in β subunit accumulation. Transcriptomic analysis revealed that genes involved in anabolism of cysteine, methionine, and glutathione were up-regulated but those involved in the catabolism of these compounds were down-regulated, suggesting a relationship between the elevation of methionine and glutathione and low BSC. Our study sheds light on seed composition in low BSC lines and on the potential molecular regulatory mechanism of β subunit accumulation, broadening our understanding of soybean seed protein synthesis and its regulation.

Cadmium Effects on Enzymes of Ammonia Assimilation in Excised Etiolated Maize Leaf Segments during Greening: A Mechanistic Approach

Supply of CdCl2 in the presence of NH4NO3 to excised etiolated maize leaf segments during greening decreased the glutamine synthetase and nicotinamide adenine dinucleotide reduced (NADH) dependent glutamate synthase activities, while the ferredoxin (Fd) dependent glutamate synthase and glutamate dehydrogenase activities were increased. Inclusion of inorganic nitrogen, metabolites and the inhibitor influenced the effect of Cd on glutamine synthetase activity. The % inhibition of activity caused by Cd was higher with NO3<sup style='margin-left:-6px;'>- but lower with NH4<sup style='margin-left:-6px;'>+. Glutamine, 2-oxoglutarate, glutathione and sucrose decreased the % inhibition by Cd with the more prominent effect with glutamine and sucrose. Methionine sulfoximine exerted a more prominent effect for + Cd enzyme at lower concentration. The results indicate the involvement of reciprocal effects of Cd on glutamine synthetase and glutamate dehydrogenase activities and also on NADH- and Fd-glutamate synthase activities. For the inhibitory effect of Cd on glutamine synthetase activity, NH4<sup style='margin-left:-6px;'>+, glutamine, 2-oxoglutarate, glutathione and sucrose exerted a protective effect with the sucrose being most effective.

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.

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.

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.

FY-3A SATELLITE MICROWAVE DATA ASSIMILATION EXPERIMENTS IN TROPICAL CYCLONE FORECAST

China's new generation of polar-orbiting meteorological satellite FY-3A was successfully launched on May 26,2008,carrying microwave sounding devices which had similar performance to ATOVS of NOAA series.In order to study the application of microwave sounding data in numerical prediction of typhoons and to improve typhoon forecasting,we assimilated data directly for numerical forecasting of the track and intensity of the 2009 typhoon Morakot(0908)based on the WRF-3DVar system.Results showed that the initial fields of the numerical model due to direct assimilation of FY-3A microwave sounding data was improved much more than that due to assimilation of conventional observations alone,and the improvement was especially significant over the ocean,which is always without conventional observations.The model initial fields were more reasonable in reflecting the initial situation of typhoon circulation as well as temperature and humidity conditions,and typhoon central position at sea was also adjusted.Through direct 3DVar assimilation of FY-3A microwave data,the regional mesoscale model improves the forecasting of typhoon track.Therefore,the FY-3A microwave data could efficiently improve the numerical prediction of typhoons.

A STUDY ON SATELLITE DATA ASSIMILATION WITH DIFFERENT ATOVS IN TYPHOON NUMERICAL EXPERIMENTS

Based on the newly developed Weather Research and Forecasting model(WRF)and its three-dimensional variational data assimilation(3DVAR)system,this study constructed twelve experiments to explore the impact of direct assimilation of different ATOVS radiance on the intensity and track simulation of super-typhoon Fanapi(2010)using a data assimilation cycle method.The result indicates that the assimilation of ATOVS radiance could improve typhoon intensity effectively.The average bias of the central sea level pressure(CSLP)drops to 18 hPa,compared to 42 hPa in the experiment without data assimilation.However,the influence due to different radiance data is not significant,which is less than 6hPa on average,implying limited improvement from sole assimilation of ATOVS radiance.The track issue is studied in the following steps.First,the radiance from the same sensor of different satellites could produce different effect.For the AMSU-A,NOAA-15 and NOAA-18,they produce equivalent improvement,whereas NOAA-16 produces slightly poor effect.And for the AMSU-B,NOAA-15 and NOAA-16,they produce equivalent and more positive effect than that provided by the AMSU-A.Second,the assimilation radiance from different sensors of the identical satellites could also produce different effect.The assimilation of AMSU-B produces the largest improvement,while the ameliorating effect of HIRS/3assimilation is inferior to that of AMSU-B assimilation,while the AMSU-A assimilation exhibits the poorest improvement.Moreover,the simultaneous assimilation of different radiance could not produce further improvement.Finally,the experiments of simultaneous assimilation radiance from multiple satellites indicate that such assimilation may lead to negative effect due to accumulative bias when adding various radiance data into the data assimilation system.Thus the assimilation of ATOVS radiance from a single satellite may perform better than that from two or three satellites.

Review on Mathematical Perspective for Data Assimilation Methods: Least Square Approach

Environmental systems including our atmosphere oceans, biological… etc. can be modeled by mathematical equations to estimate their states. These equations can be solved with numerical methods. Initial and boundary conditions are needed for such of these numerical methods. Predication and simulations for different case studies are major sources for the great importance of these models. Satellite data from different wide ranges of sensors provide observations that indicate system state. So both numerical models and satellite data provide estimation of system states, and between the different estimations it is required the best estimate for system state. Assimilation of observations in numerical weather models with data assimilation techniques provide an improved estimate of system states. In this work, highlights on the mathematical perspective for data assimilation methods are introduced. Least square estimation techniques are introduced because it is considered the basic mathematical building block for data assimilation methods. Stochastic version of least square is included to handle the error in both model and observation. Then the three and four dimensional variational assimilation 3dvar and 4dvar respectively will be handled. Kalman filters and its derivatives Extended, (KF, EKF, ENKF) and hybrid filters are introduced.

ANALYSIS OF THE EFFECT OF 3DVAR AND ENSRF DIRECT ASSIMILATION OF RADAR DATA ON THE FORECAST OF A HEAVY RAINFALL EVENT

The present study designs experiments on the direct assimilation of radial velocity and reflectivity data collected by an S-band Doppler weather radar(CINRAD WSR-98D) at the Hefei Station and the reanalysis data produced by the United States National Centers for Environmental Prediction using the Weather Research and Forecasting(WRF) model,the WRF model with a three-dimensional variational(3DVAR) data assimilation system and the WRF model with an ensemble square root filter(EnSRF) data assimilation system.In addition,the present study analyzes a Meiyu front heavy rainfall process that occurred in the Yangtze-Huaihe River Basin from July 4 to July 5,2003,through numerical simulation.The results show the following.(1) The assimilation of the radar radial velocity data can increase the perturbations in the low-altitude atmosphere over the heavy rainfall region,enhance the convective activities and reduce excessive simulated precipitation.(2) The 3DVAR assimilation method significantly adjusts the horizontal wind field.The assimilation of the reflectivity data improves the microphysical quantities and dynamic fields in the model.In addition,the assimilation of the radial velocity and reflectivity data can better adjust the wind fields and improve the intensity and location of the simulated radar echo bands.(3) The EnSRF assimilation method can assimilate more small-scale wind field information into the model.The assimilation of the reflectivity data alone can relatively accurately forecast the rainfall centers.In addition,the assimilation of the radial velocity and reflectivity data can improve the location of the simulated radar echo bands.(4) The use of the 3DVAR and EnSRF assimilation methods to assimilate the radar radial velocity and reflectivity data can improve the forecast of precipitation,rain-band areal coverage and the center location and intensity of precipitation.

Assimilation approach to measuring organizational change from pre- to post-intervention

AIM: To present a conceptual and measurement strategy that allows to objectively, sensitively evaluate intervention progress based on data of participants' perceptions of presenting problems.METHODS: We used as an example an organization development intervention at a United States Veterans Affairs medical center. Within a year, the intervention addressed the hospital's initially serious problems and multiple stakeholders(employees, management, union representatives) reported satisfaction with progress made. Traditional quantitative outcome measures, however, failed to capture the strong positive impact consistently reported by several types of stakeholders in qualitative interviews. To address the paradox, full interview data describing the medical center pre-and post- intervention were examined applying a validated theoretical framework from another discipline: Psychotherapy research. The Assimilation model is a clinical-developmental theory that describes empirically grounded change levels in problematic experiences, e.g., problems reported by participants. The model, measure Assimilation of Problematic Experiences Scale(APES), and rating procedure have been previously applied across various populations and problem types, mainly in clinical but also in non-clinical settings. We applied the APES to the transcribed qualitative data of intervention participants' interviews, using the method closely replicating prior assimilation research(the process whereby trained clinicians familiar with the Assimilation model work with full, transcribed interview data to assign the APES ratings). The APES ratings summarized levels of progress which was defined as participants' assimilation level of problematic experiences, and compared from pre- to post-intervention.RESULTS: The results were consistent with participants' own reported perceptions of the intervention impact. Increase in APES levels from pre- to post-intervention suggested improvement, missed in the previous quantitative measures(the Maslach Burnout Inventory and the Work Environment Scale). The progress specifically consisted of participants' moving from the APES stages where the problematic experience was avoided, to the APES stages where awareness and attention to the problems were steadily sustained, although the problems were not yet fully processed or resolved. These results explain why the conventional outcome measures failed to reflect the intervention progress; they narrowly defined progress as resolution of the presenting problems and alleviation of symptomatic distress. In the Assimilation model, this definition only applies to a sub-segment of the change continuum, specifically the latest APES stages. The model defines progress as change in psychological processes used in response to the problem, i.e., a growing ability to deal with problematic issues non-defensively, manifesteddifferently depending on APES stages. At early stages,progress is an increased ability to face the problem rather than turning away. At later APES stages, progress involves naming, understanding and successfully addressing the problem. The assimilation approach provides a broader developmental context compared to exclusively symptom, problem-, or behavior- focused approaches that typically inform outcome measurement in interpersonally based interventions. In our data, this made the difference between reflecting(APES) vs missing(Maslach Burnout Inventory, Work Environment Scale) the pre-post change that was strongly perceived by the intervention recipients.CONCLUSION: The results illustrated a working solution to the challenge of objectively evaluating progress in subjectively experienced problems. This approach informs measuring change in psychologically based interventions.

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.

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.

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.

Assimilation and Modernity——A Case Study of Abraham Cahan's “The Imported Bridegroom”

In the modern era, the Jewish-Americans were faced with challenges because of the assimilation and modernity environment in the US, and as a result, many of them were in a double bind—to be an assimilated American citizen or to be a traditional Jew. With his work"The Imported Bridegroom", Abraham Cahan contemplated on the subject of Jewish immigration and assimilation and he made a ground-breaking contribution to the establishment of American modernity. This paper intends to analyze Cahan's attitudes towards assimilation and modernity and how he builds up modernity for all of the Americans. Three characters in"The Imported Bridegroom", who stand for three prototypes of modern Jewish-Americans confronting the overwhelming flood of assimilation and the duty for retaining their traditions, will be analyzed. Through the composition of this work, Cahan tried to spread the Jewish culture on the one hand, and on the other, he warned the peripheral that it was difficult to be assimilated without disasters even if they had made contribution to the formation of modernity.

Preliminary Meteorological Results of a Four-Dimensional Data Assimilation Technique in Southern Italy

A four-dimensional data assimilation (FDDA) scheme based on a Newtonian relaxation (or “nudging”) was tested using observational asynoptic data collected at a coastal site in the Central Mediterranean peninsula of Calabria, southern Italy. The study is referred to an experimental campaign carried out in summer 2008. For this period a wind profiler, a sodar and two surface meteorological stations were considered. The collected measurements were used for the FDDA scheme, and the technique was incorporated into a tailored version of the Regional Atmospheric Modeling System (RAMS). All instruments are installed and operated routinely at the experimental field of the CRATI-ISAC/CNR located at 600 m from the Tyrrhenian coastline. Several simulations were performed, and the results show that the assimilation of wind and/or temperature data, both throughout the simulation time (continuous FDDA) and for a 12 h time window (forecasting configuration), produces improvements of the model performance. Considering a whole single day, improvements are sub-stantial in the case of continuous FDDA while they are smaller in the case of forecasting configuration. En-hancements, during the first six hours of each run, are generally higher. The resulting meteorological fields are finalised as input into air quality and agro-meteorological models, for short-term predictions of renew-able energy production forecast, and for atmospheric model initialization.