WorldWideScience

Sample records for sources readily assimilated

  1. Open source data assimilation framework for hydrological modeling

    Science.gov (United States)

    Ridler, Marc; Hummel, Stef; van Velzen, Nils; Katrine Falk, Anne; Madsen, Henrik

    2013-04-01

    An open-source data assimilation framework is proposed for hydrological modeling. Data assimilation (DA) in hydrodynamic and hydrological forecasting systems has great potential to improve predictions and improve model result. The basic principle is to incorporate measurement information into a model with the aim to improve model results by error minimization. Great strides have been made to assimilate traditional in-situ measurements such as discharge, soil moisture, hydraulic head and snowpack into hydrologic models. More recently, remotely sensed data retrievals of soil moisture, snow water equivalent or snow cover area, surface water elevation, terrestrial water storage and land surface temperature have been successfully assimilated in hydrological models. The assimilation algorithms have become increasingly sophisticated to manage measurement and model bias, non-linear systems, data sparsity (time & space) and undetermined system uncertainty. It is therefore useful to use a pre-existing DA toolbox such as OpenDA. OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement DA and calibration for arbitrary numerical models. The basic design philosophy of OpenDA is to breakdown DA into a set of building blocks programmed in object oriented languages. To implement DA, a model must interact with OpenDA to create model instances, propagate the model, get/set variables (or parameters) and free the model once DA is completed. An open-source interface for hydrological models exists capable of all these tasks: OpenMI. OpenMI is an open source standard interface already adopted by key hydrological model providers. It defines a universal approach to interact with hydrological models during simulation to exchange data during runtime, thus facilitating the interactions between models and data sources. The interface is flexible enough so that models can interact even if the model is coded in a different language, represent

  2. How exogenous nitric oxide regulates nitrogen assimilation in wheat seedlings under different nitrogen sources and levels.

    Science.gov (United States)

    Balotf, Sadegh; Islam, Shahidul; Kavoosi, Gholamreza; Kholdebarin, Bahman; Juhasz, Angela; Ma, Wujun

    2018-01-01

    Nitrogen (N) is one of the most important nutrients for plants and nitric oxide (NO) as a signaling plant growth regulator involved in nitrogen assimilation. Understanding the influence of exogenous NO on nitrogen metabolism at the gene expression and enzyme activity levels under different sources of nitrogen is vitally important for increasing nitrogen use efficiency (NUE). This study investigated the expression of key genes and enzymes in relation to nitrogen assimilation in two Australian wheat cultivars, a popular high NUE cv. Spitfire and a normal NUE cv. Westonia, under different combinations of nitrogen and sodium nitroprusside (SNP) as the NO donor. Application of NO increased the gene expressions and activities of nitrogen assimilation pathway enzymes in both cultivars at low levels of nitrogen. At high nitrogen supplies, the expressions and activities of N assimilation genes increased in response to exogenous NO only in cv. Spitfire but not in cv. Westonia. Exogenous NO caused an increase in leaf NO content at low N supplies in both cultivars, while under high nitrogen treatments, cv. Spitfire showed an increase under ammonium nitrate (NH4NO3) treatment but cv. Westonia was not affected. N assimilation gene expression and enzyme activity showed a clear relationship between exogenous NO, N concentration and N forms in primary plant nitrogen assimilation. Results reveal the possible role of NO and different nitrogen sources on nitrogen assimilation in Triticum aestivum plants.

  3. The composition of readily available carbon sources produced by fermentation of fish faeces is affected by dietary protein:energy ratios

    DEFF Research Database (Denmark)

    Letelier-Gordo, Carlos Octavio; Larsen, Bodil Katrine; Dalsgaard, Johanne

    2017-01-01

    , 17, 19, 21 and 23 g/MJ) to rainbow trout (Oncorhynchus mykiss) on the production of volatile fatty acids (VFAs) and ethanol during 7 days fermentation of the produced fish faeces. The total yields of VFAs and ethanol obtained (expressed as chemical oxygen demand (COD)) ranged between 0.21–0.24 g...... of acetic and valeric acid. Changing the diet composition thus affects the composition of readily available carbon that can be derived from the faeces. This can be applied to enhance on-farm single sludge denitrification and reduce the need for adding external carbon sources such as e.g. methanol....

  4. Chemical Source Inversion using Assimilated Constituent Observations in an Idealized Two-dimensional System

    Science.gov (United States)

    Tangborn, Andrew; Cooper, Robert; Pawson, Steven; Sun, Zhibin

    2009-01-01

    We present a source inversion technique for chemical constituents that uses assimilated constituent observations rather than directly using the observations. The method is tested with a simple model problem, which is a two-dimensional Fourier-Galerkin transport model combined with a Kalman filter for data assimilation. Inversion is carried out using a Green's function method and observations are simulated from a true state with added Gaussian noise. The forecast state uses the same spectral spectral model, but differs by an unbiased Gaussian model error, and emissions models with constant errors. The numerical experiments employ both simulated in situ and satellite observation networks. Source inversion was carried out by either direct use of synthetically generated observations with added noise, or by first assimilating the observations and using the analyses to extract observations. We have conducted 20 identical twin experiments for each set of source and observation configurations, and find that in the limiting cases of a very few localized observations, or an extremely large observation network there is little advantage to carrying out assimilation first. However, in intermediate observation densities, there decreases in source inversion error standard deviation using the Kalman filter algorithm followed by Green's function inversion by 50% to 95%.

  5. Ensemble-based data assimilation and optimal sensor placement for scalar source reconstruction

    Science.gov (United States)

    Mons, Vincent; Wang, Qi; Zaki, Tamer

    2017-11-01

    Reconstructing the characteristics of a scalar source from limited remote measurements in a turbulent flow is a problem of great interest for environmental monitoring, and is challenging due to several aspects. Firstly, the numerical estimation of the scalar dispersion in a turbulent flow requires significant computational resources. Secondly, in actual practice, only a limited number of observations are available, which generally makes the corresponding inverse problem ill-posed. Ensemble-based variational data assimilation techniques are adopted to solve the problem of scalar source localization in a turbulent channel flow at Reτ = 180 . This approach combines the components of variational data assimilation and ensemble Kalman filtering, and inherits the robustness from the former and the ease of implementation from the latter. An ensemble-based methodology for optimal sensor placement is also proposed in order to improve the condition of the inverse problem, which enhances the performances of the data assimilation scheme. This work has been partially funded by the Office of Naval Research (Grant N00014-16-1-2542) and by the National Science Foundation (Grant 1461870).

  6. Biomass burning source characterization requirements in air quality models with and without data assimilation: challenges and opportunities

    Science.gov (United States)

    Hyer, E. J.; Zhang, J. L.; Reid, J. S.; Curtis, C. A.; Westphal, D. L.

    2007-12-01

    Quantitative models of the transport and evolution of atmospheric pollution have graduated from the laboratory to become a part of the operational activity of forecast centers. Scientists studying the composition and variability of the atmosphere put great efforts into developing methods for accurately specifying sources of pollution, including natural and anthropogenic biomass burning. These methods must be adapted for use in operational contexts, which impose additional strictures on input data and methods. First, only input data sources available in near real-time are suitable for use in operational applications. Second, operational applications must make use of redundant data sources whenever possible. This is a shift in philosophy: in a research context, the most accurate and complete data set will be used, whereas in an operational context, the system must be designed with maximum redundancy. The goal in an operational context is to produce, to the extent possible, consistent and timely output, given sometimes inconsistent inputs. The Naval Aerosol Analysis and Prediction System (NAAPS), a global operational aerosol analysis and forecast system, recently began incorporating assimilation of satellite-derived aerosol optical depth. Assimilation of satellite AOD retrievals has dramatically improved aerosol analyses and forecasts from this system. The use of aerosol data assimilation also changes the strategy for improving the smoke source function. The absolute magnitude of emissions events can be refined through feedback from the data assimilation system, both in real- time operations and in post-processing analysis of data assimilation results. In terms of the aerosol source functions, the largest gains in model performance are now to be gained by reducing data latency and minimizing missed detections. In this presentation, recent model development work on the Fire Locating and Monitoring of Burning Emissions (FLAMBE) system that provides smoke aerosol

  7. A high performance, cost-effective, open-source microscope for scanning two-photon microscopy that is modular and readily adaptable.

    Directory of Open Access Journals (Sweden)

    David G Rosenegger

    Full Text Available Two-photon laser scanning microscopy has revolutionized the ability to delineate cellular and physiological function in acutely isolated tissue and in vivo. However, there exist barriers for many laboratories to acquire two-photon microscopes. Additionally, if owned, typical systems are difficult to modify to rapidly evolving methodologies. A potential solution to these problems is to enable scientists to build their own high-performance and adaptable system by overcoming a resource insufficiency. Here we present a detailed hardware resource and protocol for building an upright, highly modular and adaptable two-photon laser scanning fluorescence microscope that can be used for in vitro or in vivo applications. The microscope is comprised of high-end componentry on a skeleton of off-the-shelf compatible opto-mechanical parts. The dedicated design enabled imaging depths close to 1 mm into mouse brain tissue and a signal-to-noise ratio that exceeded all commercial two-photon systems tested. In addition to a detailed parts list, instructions for assembly, testing and troubleshooting, our plan includes complete three dimensional computer models that greatly reduce the knowledge base required for the non-expert user. This open-source resource lowers barriers in order to equip more laboratories with high-performance two-photon imaging and to help progress our understanding of the cellular and physiological function of living systems.

  8. A High Performance, Cost-Effective, Open-Source Microscope for Scanning Two-Photon Microscopy that Is Modular and Readily Adaptable

    Science.gov (United States)

    Rosenegger, David G.; Tran, Cam Ha T.; LeDue, Jeffery; Zhou, Ning; Gordon, Grant R.

    2014-01-01

    Two-photon laser scanning microscopy has revolutionized the ability to delineate cellular and physiological function in acutely isolated tissue and in vivo. However, there exist barriers for many laboratories to acquire two-photon microscopes. Additionally, if owned, typical systems are difficult to modify to rapidly evolving methodologies. A potential solution to these problems is to enable scientists to build their own high-performance and adaptable system by overcoming a resource insufficiency. Here we present a detailed hardware resource and protocol for building an upright, highly modular and adaptable two-photon laser scanning fluorescence microscope that can be used for in vitro or in vivo applications. The microscope is comprised of high-end componentry on a skeleton of off-the-shelf compatible opto-mechanical parts. The dedicated design enabled imaging depths close to 1 mm into mouse brain tissue and a signal-to-noise ratio that exceeded all commercial two-photon systems tested. In addition to a detailed parts list, instructions for assembly, testing and troubleshooting, our plan includes complete three dimensional computer models that greatly reduce the knowledge base required for the non-expert user. This open-source resource lowers barriers in order to equip more laboratories with high-performance two-photon imaging and to help progress our understanding of the cellular and physiological function of living systems. PMID:25333934

  9. Nitrogen-source preference in blueberry (Vaccinium sp.): Enhanced shoot nitrogen assimilation in response to direct supply of nitrate.

    Science.gov (United States)

    Alt, Douglas S; Doyle, John W; Malladi, Anish

    2017-09-01

    Blueberry (Vaccinium sp.) is thought to display a preference for the ammonium (NH 4 + ) form over the nitrate (NO 3 - ) form of inorganic nitrogen (N). This N-source preference has been associated with a generally low capacity to assimilate the NO 3 - form of N, especially within the shoot tissues. Nitrate assimilation is mediated by nitrate reductase (NR), a rate limiting enzyme that converts NO 3 - to nitrite (NO 2 - ). We investigated potential limitations of NO 3 - assimilation in two blueberry species, rabbiteye (Vaccinium ashei) and southern highbush (Vaccinium corymbosum) by supplying NO 3 - to the roots, leaf surface, or through the cut stem. Both species displayed relatively low but similar root uptake rates for both forms of inorganic N. Nitrate uptake through the roots transiently increased NR activity by up to 3.3-fold and root NR gene expression by up to 4-fold. However, supplying NO 3 - to the roots did not increase its transport in the xylem, nor did it increase NR activity in the leaves, indicating that the acquired N was largely assimilated or stored within the roots. Foliar application of NO 3 - increased leaf NR activity by up to 3.5-fold, but did not alter NO 3 - metabolism-related gene expression, suggesting that blueberries are capable of post translational regulation of NR activity in the shoots. Additionally, supplying NO 3 - to the cut ends of stems resulted in around a 5-fold increase in NR activity, a 10-fold increase in NR transcript accumulation, and up to a 195-fold increase in transcript accumulation of NITRITE REDUCTASE (NiR1) which codes for the enzyme catalyzing the conversion of NO 2 - to NH 4 + . These data indicate that blueberry shoots are capable of assimilating NO 3 - when it is directly supplied to these tissues. Together, these data suggest that limitations in the uptake and translocation of NO 3 - to the shoots may limit overall NO 3 - assimilation capacity in blueberry. Copyright © 2017 Elsevier GmbH. All rights reserved.

  10. The Ability to Assimilate Technology as a Source of Competitive Advantage of Financial Companies in Poland

    Directory of Open Access Journals (Sweden)

    Glabiszewski Waldemar

    2016-12-01

    Full Text Available This article is empirical in nature and attempts to assess the impact of ability to assimilate newly acquired technologies by financial companies operating in Poland gaining market competitive advantages. The outcome of the research conducted proved the existence of this relationship and found it be strong. This means that the development of these abilities within the absorptive potential of financial companies should trigger a significant increase in the market competitive advantages held by them. The strong impact was identified both in the total of the analyzed personnel and general-organizational components of the assimilation abilities. As regards elementary components of the analyzed potential, the obtained results are definitely more diverse.

  11. The Ability to Assimilate Technology as a Source of Competitive Advantage of Financial Companies in Poland

    OpenAIRE

    Glabiszewski Waldemar; Zastempowski Maciej

    2016-01-01

    This article is empirical in nature and attempts to assess the impact of ability to assimilate newly acquired technologies by financial companies operating in Poland gaining market competitive advantages. The outcome of the research conducted proved the existence of this relationship and found it be strong. This means that the development of these abilities within the absorptive potential of financial companies should trigger a significant increase in the market competitive advantages held by...

  12. Effects of source and sink manipulation on distribution of 14C-assimilate and endogenous hormone contents of high-yield cotton in Xinjiang

    International Nuclear Information System (INIS)

    Luo Honghai; Zhao Ruihai; Li Junhua; Zhang Yali; Zhang Wangfeng

    2011-01-01

    Effects of leaf-cutting and bud-thinning treatment on partitioning of 14 C-assimilate and endogenous hormone contents of source leaf (respective axial leaf and sympodian leaf) during flowering and boll-setting stage in high-yield cotton were studied by using Gossipium hirsutum L. cv. Xinluzao 132 as plant material. Results showed that bud-thinning reduced the peak value of indole-3-acetic acid (IAA) delayed the accumulation of isopenteny ladenime and its riboside (iP + iPA), and decreased the contents of abscisic acid (ABA) zeatin and its riboside (Z + ZR) of source leaf. Thus, the export and partitioning of percentage of 14 C-assimilate in boll was significantly decreased at full bolling and boll opening stages. As a result, both of boll weight and yield in bud-thinning were significantly lower than control. Leaf-cutting significantly improved the content of cytokinins (CTKs) and the distributive percentage of 14 C-assimilates in boll. Furthermore, when leaves were cut 1/4 at anthesis, no differences were found in number of bolls per plant, boll weight and yield compared with control. These results suggested that regulating source-sink relation with key practices of cultivation would be of great importance to super-high and stable yield of cotton, as it would affect the changes of endogenous hormone levels and regulate the distribution of 14 C-assimilate between source and sink. (authors)

  13. Data assimilation and source term estimation during the early phase of a nuclear accident

    Energy Technology Data Exchange (ETDEWEB)

    Golubenkov, A.; Borodin, R. [SPA Typhoon, Emergency Centre (Russian Federation); Sohier, A.; Rojas Palma, C. [Centre de l`Etude de l`Energie Nucleaire, Mol (Belgium)

    1996-02-01

    The mathematical/physical base of possible methods to model the source term during an accidental release of radionuclides is discussed. Knowledge of the source term is important in view of optimizing urgent countermeasures to the population. In most cases however, it will be impossible to assess directly the release dynamics. Therefore methods are under development in which the source term is modelled, based on the comparison of off-site monitoring data and model predictions using an atmospheric dispersion model. The degree of agreement between the measured and calculated characteristics of the radioactive contamination of the air and the ground surface is an important criterion in this process. Due to the inherent complexity, some geometrical transformations taking space-time discrepancies between observed and modelled contamination fields are defined before the source term is adapted. This work describes the developed algorithms which are also tested against data from some tracer experiments performed in the past. This method is also used to reconstruct the dynamics of the Chernobyl source term. Finally this report presents a concept of software to reconstruct a multi-isotopic source term in real-time.

  14. Data assimilation and source term estimation during the early phase of a nuclear accident

    International Nuclear Information System (INIS)

    Golubenkov, A.; Borodin, R.; Sohier, A.; Rojas Palma, C.

    1996-02-01

    The mathematical/physical base of possible methods to model the source term during an accidental release of radionuclides is discussed. Knowledge of the source term is important in view of optimizing urgent countermeasures to the population. In most cases however, it will be impossible to assess directly the release dynamics. Therefore methods are under development in which the source term is modelled, based on the comparison of off-site monitoring data and model predictions using an atmospheric dispersion model. The degree of agreement between the measured and calculated characteristics of the radioactive contamination of the air and the ground surface is an important criterion in this process. Due to the inherent complexity, some geometrical transformations taking space-time discrepancies between observed and modelled contamination fields are defined before the source term is adapted. This work describes the developed algorithms which are also tested against data from some tracer experiments performed in the past. This method is also used to reconstruct the dynamics of the Chernobyl source term. Finally this report presents a concept of software to reconstruct a multi-isotopic source term in real-time

  15. Tsunami Simulation Method Assimilating Ocean Bottom Pressure Data Near a Tsunami Source Region

    Science.gov (United States)

    Tanioka, Yuichiro

    2018-02-01

    A new method was developed to reproduce the tsunami height distribution in and around the source area, at a certain time, from a large number of ocean bottom pressure sensors, without information on an earthquake source. A dense cabled observation network called S-NET, which consists of 150 ocean bottom pressure sensors, was installed recently along a wide portion of the seafloor off Kanto, Tohoku, and Hokkaido in Japan. However, in the source area, the ocean bottom pressure sensors cannot observe directly an initial ocean surface displacement. Therefore, we developed the new method. The method was tested and functioned well for a synthetic tsunami from a simple rectangular fault with an ocean bottom pressure sensor network using 10 arc-min, or 20 km, intervals. For a test case that is more realistic, ocean bottom pressure sensors with 15 arc-min intervals along the north-south direction and sensors with 30 arc-min intervals along the east-west direction were used. In the test case, the method also functioned well enough to reproduce the tsunami height field in general. These results indicated that the method could be used for tsunami early warning by estimating the tsunami height field just after a great earthquake without the need for earthquake source information.

  16. Linkage of the Nit1C gene cluster to bacterial cyanide assimilation as a nitrogen source.

    Science.gov (United States)

    Jones, Lauren B; Ghosh, Pallab; Lee, Jung-Hyun; Chou, Chia-Ni; Kunz, Daniel A

    2018-05-21

    A genetic linkage between a conserved gene cluster (Nit1C) and the ability of bacteria to utilize cyanide as the sole nitrogen source was demonstrated for nine different bacterial species. These included three strains whose cyanide nutritional ability has formerly been documented (Pseudomonas fluorescens Pf11764, Pseudomonas putida BCN3 and Klebsiella pneumoniae BCN33), and six not previously known to have this ability [Burkholderia (Paraburkholderia) xenovorans LB400, Paraburkholderia phymatum STM815, Paraburkholderia phytofirmans PsJN, Cupriavidus (Ralstonia) eutropha H16, Gluconoacetobacter diazotrophicus PA1 5 and Methylobacterium extorquens AM1]. For all bacteria, growth on or exposure to cyanide led to the induction of the canonical nitrilase (NitC) linked to the gene cluster, and in the case of Pf11764 in particular, transcript levels of cluster genes (nitBCDEFGH) were raised, and a nitC knock-out mutant failed to grow. Further studies demonstrated that the highly conserved nitB gene product was also significantly elevated. Collectively, these findings provide strong evidence for a genetic linkage between Nit1C and bacterial growth on cyanide, supporting use of the term cyanotrophy in describing what may represent a new nutritional paradigm in microbiology. A broader search of Nit1C genes in presently available genomes revealed its presence in 270 different bacteria, all contained within the domain Bacteria, including Gram-positive Firmicutes and Actinobacteria, and Gram-negative Proteobacteria and Cyanobacteria. Absence of the cluster in the Archaea is congruent with events that may have led to the inception of Nit1C occurring coincidentally with the first appearance of cyanogenic species on Earth, dating back 400-500 million years.

  17. Repository of not readily available documents for project W-320

    Energy Technology Data Exchange (ETDEWEB)

    Conner, J.C.

    1997-04-18

    The purpose of this document is to provide a readily available source of the technical reports needed for the development of the safety documentation provided for the waste retrieval sluicing system (WRSS), designed to remove the radioactive and chemical sludge from tank 241-C-106, and transport that material to double-shell tank 241-AY-102 via a new, temporary, shielded, encased transfer line.

  18. Repository of not readily available documents for project W-320

    International Nuclear Information System (INIS)

    Conner, J.C.

    1997-01-01

    The purpose of this document is to provide a readily available source of the technical reports needed for the development of the safety documentation provided for the waste retrieval sluicing system (WRSS), designed to remove the radioactive and chemical sludge from tank 241-C-106, and transport that material to double-shell tank 241-AY-102 via a new, temporary, shielded, encased transfer line

  19. Evaluating model performance of an ensemble-based chemical data assimilation system during INTEX-B field mission

    Directory of Open Access Journals (Sweden)

    A. F. Arellano Jr.

    2007-11-01

    Full Text Available We present a global chemical data assimilation system using a global atmosphere model, the Community Atmosphere Model (CAM3 with simplified chemistry and the Data Assimilation Research Testbed (DART assimilation package. DART is a community software facility for assimilation studies using the ensemble Kalman filter approach. Here, we apply the assimilation system to constrain global tropospheric carbon monoxide (CO by assimilating meteorological observations of temperature and horizontal wind velocity and satellite CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT satellite instrument. We verify the system performance using independent CO observations taken on board the NSF/NCAR C-130 and NASA DC-8 aircrafts during the April 2006 part of the Intercontinental Chemical Transport Experiment (INTEX-B. Our evaluations show that MOPITT data assimilation provides significant improvements in terms of capturing the observed CO variability relative to no MOPITT assimilation (i.e. the correlation improves from 0.62 to 0.71, significant at 99% confidence. The assimilation provides evidence of median CO loading of about 150 ppbv at 700 hPa over the NE Pacific during April 2006. This is marginally higher than the modeled CO with no MOPITT assimilation (~140 ppbv. Our ensemble-based estimates of model uncertainty also show model overprediction over the source region (i.e. China and underprediction over the NE Pacific, suggesting model errors that cannot be readily explained by emissions alone. These results have important implications for improving regional chemical forecasts and for inverse modeling of CO sources and further demonstrate the utility of the assimilation system in comparing non-coincident measurements, e.g. comparing satellite retrievals of CO with in-situ aircraft measurements.

  20. A new framework for modeling urban land expansion in peri-urban area by combining multi-source datasets and data assimilation

    Science.gov (United States)

    Zhang, Z.; Xiao, R.; Li, X.

    2015-12-01

    Peri-urban area is a new type region under the impacts of both rural Industrialization and the radiation of metropolitan during rapid urbanization. Due to its complex natural and social characteristics and unique development patterns, many problems such as environmental pollution and land use waste emerged, which became an urgent issue to be addressed. Study area in this paper covers three typical peri-urban districts (Pudong, Fengxian and Jinshan), which around the Shanghai inner city. By coupling cellular automata and multi-agent system model as the basic tools, this research focus on modelling the urban land expansion and driving mechanism in peri-urban area. The big data is aslo combined with the Bayesian maximum entropy method (BME) for spatiotemporal prediction of multi-source data, which expand the dataset of urban expansion models. Data assimilation method is used to optimize the parameters of the coupling model and minimize the uncertainty of observations, improving the precision of future simulation in peri-urban area. By setting quantitative parameters, the coupling model can effectively improve the simulation of the process of urban land expansion under different policies and management schemes, in order to provide scientificimplications for new urbanization strategy. In this research, we precise the urban land expansion simulation and prediction for peri-urban area, expand the scopes and selections of data acquisition measurements and methods, develop the new applications of the data assimilation method in geographical science, provide a new idea for understanding the inherent rules of urban land expansion, and give theoretical and practical support for the peri-urban area in urban planning and decision making.

  1. Oxidation and Assimilation of Carbohydrates by Micrococcus sodonensis1

    Science.gov (United States)

    Perry, Jerome J.; Evans, James B.

    1966-01-01

    Perry, Jerome J. (North Carolina State University, Raleigh), and James B. Evans. Oxidation and assimilation of carbohydrates by Micrococcus sodonensis. J. Bacteriol. 91:33–38. 1966.—Micrococcus sodonensis is a biotin-requiring strict aerobe that cannot utilize carbohydrates as sole sources of carbon and energy. However, addition of mannose, glucose, sucrose, or maltose to a medium on which the organism can grow resulted in an increase in total growth. M. sodonensis oxidized these sugars without induction, thus indicating the presence of constitutive enzymes for their transport, activation, and metabolism. Under appropriate nonproliferating cell conditions, glucose was readily incorporated into essential constituents of the cell. When glucose-1-C14 and glucose-6-C14 were oxidized by nonproliferating cells, the label was found in both the protein and nucleic acid fractions of the cell. The respiratory quotients of cells oxidizing glucose in saline and in phosphate buffer indicated assimilation of sugar carbon in buffer and virtually no assimilation in saline. The ability of M. sodonensis to completely oxidize glucose and to grow on intermediates of glucose oxidation but not on glucose suggests that glucose may suppress or repress some reaction(s) necessary for growth, and that growth substrates either derepress or circumvent this block. PMID:5903100

  2. Stable carbon isotope ratios: implications for the source of sediment carbon and for phytoplankton carbon assimilation in Lake Memphremagog, Quebec

    International Nuclear Information System (INIS)

    LaZerte, B.D.

    1983-01-01

    The stable carbon isotope (SCI) ratio of the sediment of Lake Memphremagog, Quebec is compared with that ot terrestrial sources and the phytoplankton to determine the relative proportion of allochthonous carbon incorporated into the sediments. Approximately 40-50% of the organic carbon in the main basins' pelagic sediment was terrestrial in origin, whereas up to 100% was terrestrial in littoral areas. The SCI method of determining the organic carbon source of sediments appears more reliable than the C/N method. A comparison of the SCI fractionation of the phytoplankton with laboratory cultures under different degrees of carbon limitation indicates that the phytoplankton of Lake Memphremagog are not carbon limited and fix carbon primarily by the C 3 pathway

  3. Assessing the Hydrologic Performance of the EPA's Nonpoint Source Water Quality Assessment Decision Support Tool Using North American Land Data Assimilation System (Products)

    Science.gov (United States)

    Lee, S.; Ni-Meister, W.; Toll, D.; Nigro, J.; Guiterrez-Magness, A.; Engman, T.

    2010-01-01

    The accuracy of streamflow predictions in the EPA's BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. The North American Land Data Assimilation System (NLDAS) data with high spatial and temporal resolutions provide an alternative to the NOAA National Climatic Data Center (NCDC)'s station data. This study assessed the improvement of streamflow prediction of the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS using the NLDAS 118 degree hourly precipitation and evapotranspiration estimates in seven watersheds of the Chesapeake Bay region. Our results demonstrated consistent improvements of daily streamflow predictions in five of the seven watersheds when NLDAS precipitation and evapotranspiration data was incorporated into BASINS. The improvement of using the NLDAS data is significant when watershed's meteorological station is either far away or not in a similar climatic region. When the station is nearby, using the NLDAS data produces similar results. The correlation coefficients of the analyses using the NLDAS data were greater than 0.8, the Nash-Sutcliffe (NS) model fit efficiency greater than 0.6, and the error in the water balance was less than 5%. Our analyses also showed that the streamflow improvements were mainly contributed by the NLDAS's precipitation data and that the improvement from using NLDAS's evapotranspiration data was not significant; partially due to the constraints of current BASINS-HSPF settings. However, NLDAS's evapotranspiration data did improve the baseflow prediction. This study demonstrates the NLDAS data has the potential to improve stream flow predictions, thus aid the water quality assessment in the EPA nonpoint water quality assessment decision tool.

  4. HL-60 differentiating activity and flavonoid content of the readily extractable fraction prepared from citrus juices.

    Science.gov (United States)

    Kawaii, S; Tomono, Y; Katase, E; Ogawa, K; Yano, M

    1999-01-01

    Citrus plants are rich sources of various bioactive flavonoids. To eliminate masking effects caused by hesperidin, naringin, and neoeriocitrin, the abundant flavonoid glycosides which make up 90% of the conventionally prepared sample, the readily extractable fraction from Citrus juice was prepared by adsorbing on HP-20 resin and eluting with EtOH and acetone from the resin and was subjected to HL-60 differentiation assay and quantitative analysis of major flavonoids. Screening of 34 Citrus juices indicated that King (C. nobilis) had a potent activity for inducing differentiation of HL-60, and the active principles were isolated and identified as four polymethoxylated flavonoids, namely, nobiletin, 3,3',4',5,6,7, 8-heptamethoxyflavone, natsudaidain, and tangeretin. HPLC analysis of the readily extractable fraction also indicated that King contained high amounts of these polymethoxylated flavonoids among the Citrus juices examined. Principal component and cluster analyses of the readily extractable flavonoids indicated peculiarities of King and Bergamot.

  5. Data Assimilation in Integrated and Distributed Hydrological Models

    DEFF Research Database (Denmark)

    Zhang, Donghua

    processes and provide simulations in refined temporal and spatial resolutions. Recent developments in measurement and sensor technologies have significantly improved the coverage, quality, frequency and diversity of hydrological observations. Data assimilation provides a great potential in relation...... point of view, different assimilation methodologies and techniques have been developed or customized to better serve hydrological assimilation. From the application point of view, real data and real-world complex catchments are used with the focus of investigating the models’ improvements with data...... a variety of model uncertainty sources and scales. Next the groundwater head assimilation experiment was tested in a much more complex catchment with assimilation of biased real observations. In such cases, the bias-aware assimilation method significantly outperforms the standard assimilation method...

  6. Methodological Developments in Geophysical Assimilation Modeling

    Science.gov (United States)

    Christakos, George

    2005-06-01

    This work presents recent methodological developments in geophysical assimilation research. We revisit the meaning of the term "solution" of a mathematical model representing a geophysical system, and we examine its operational formulations. We argue that an assimilation solution based on epistemic cognition (which assumes that the model describes incomplete knowledge about nature and focuses on conceptual mechanisms of scientific thinking) could lead to more realistic representations of the geophysical situation than a conventional ontologic assimilation solution (which assumes that the model describes nature as is and focuses on form manipulations). Conceptually, the two approaches are fundamentally different. Unlike the reasoning structure of conventional assimilation modeling that is based mainly on ad hoc technical schemes, the epistemic cognition approach is based on teleologic criteria and stochastic adaptation principles. In this way some key ideas are introduced that could open new areas of geophysical assimilation to detailed understanding in an integrated manner. A knowledge synthesis framework can provide the rational means for assimilating a variety of knowledge bases (general and site specific) that are relevant to the geophysical system of interest. Epistemic cognition-based assimilation techniques can produce a realistic representation of the geophysical system, provide a rigorous assessment of the uncertainty sources, and generate informative predictions across space-time. The mathematics of epistemic assimilation involves a powerful and versatile spatiotemporal random field theory that imposes no restriction on the shape of the probability distributions or the form of the predictors (non-Gaussian distributions, multiple-point statistics, and nonlinear models are automatically incorporated) and accounts rigorously for the uncertainty features of the geophysical system. In the epistemic cognition context the assimilation concept may be used to

  7. Regional Ocean Data Assimilation

    KAUST Repository

    Edwards, Christopher A.; Moore, Andrew M.; Hoteit, Ibrahim; Cornuelle, Bruce D.

    2015-01-01

    This article reviews the past 15 years of developments in regional ocean data assimilation. A variety of scientific, management, and safety-related objectives motivate marine scientists to characterize many ocean environments, including coastal

  8. A simple lightning assimilation technique for improving ...

    Science.gov (United States)

    Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain-Fritsch (KF) convective scheme to improve retrospective simulations using the Weather Research and Forecasting (WRF) model. The assimilation method has a straightforward approach: force KF deep convection where lightning is observed and, optionally, suppress deep convection where lightning is absent. WRF simulations were made with and without lightning assimilation over the continental United States for July 2012, July 2013, and January 2013. The simulations were evaluated against NCEP stage-IV precipitation data and MADIS near-surface meteorological observations. In general, the use of lightning assimilation considerably improves the simulation of summertime rainfall. For example, the July 2012 monthly averaged bias of 6 h accumulated rainfall is reduced from 0.54 to 0.07 mm and the spatial correlation is increased from 0.21 to 0.43 when lightning assimilation is used. Statistical measures of near-surface meteorological variables also are improved. Consistent improvements also are seen for the July 2013 case. These results suggest that this lightning assimilation technique has the potential to substantially improve simulation of warm-season rainfall in retrospective WRF applications. The

  9. Variable temperature effects on release rates of readily soluble nuclides

    International Nuclear Information System (INIS)

    Kim, C.-L.; Light, W.B.; Lee, W.W.-L.; Chambre, P.L.; Pigford, T.H.

    1988-09-01

    In this paper we study the effect of temperature on the release rate of readily soluble nuclides, as affected by a time-temperature dependent diffusion coefficient. In this analysis ground water fills the voids in the waste package at t = 0 and one percent of the inventories of cesium and iodine are immediately dissolved into the void water. Mass transfer resistance of partly failed container and cladding is conservatively neglected. The nuclides move through the void space into the surrounding rock under a concentration gradient. We use an analytic solution to compute the nuclide concentration in the gap or void, and the mass flux rate into the porous rock. 8 refs., 4 figs

  10. Arsenic readily released to pore waters from buried mill tailings

    Energy Technology Data Exchange (ETDEWEB)

    Mahoney, John [Hydrologic Consultants, Inc., 143 Union Blvd., Suite 525, Lakewood, CO 80228 (United States)]. E-mail: jmahoney@hcico.com; Langmuir, Donald [Hydrochem Systems Corp., P.O. Box 17090, Golden, CO 80402 (United States); Gosselin, Neil [Department of Chemistry and Biochemistry, University of Regina, 3737 Wascana Way, Regina, SK, S4S 0A2 (Canada); Rowson, John [COGEMA Resources, Inc., P.O. Box 9204, Saskatoon, SK, S7K 3X5 (Canada)

    2005-05-15

    At the McClean Lake Operation in the Athabasca Basin of northern Saskatchewan, the untreated acid raffinate solutions associated with U mill tailings contain up to 700 mg/L dissolved As. To reduce the concentration of As and other contaminants in acid tailing slurries at the JEB mill at McClean Lake, ferric sulfate may be added to the acid raffinates to assure that their molar Fe/As ratio equals or exceeds 3. Tailings slurries are then neutralized with lime to pH 4, and subsequently to pH 7-8. The neutralized tailings contain minerals from the original ore, which are chiefly quartz, illite, kaolinite and chlorite, and precipitated (secondary) minerals that include gypsum, scorodite, annabergite, hydrobasaluminite and ferrihydrite. Most of the As is associated with the secondary arsenate minerals, scorodite and annabergite. However, a few percent is adsorbed and/or co-precipitated, mainly by ferrihydrite. Of major concern to provincial and federal regulators is the risk that significant amounts of As might be released from the tailings to pore waters after their subaqueous disposal in the tailings management facility. A laboratory study was performed to address this issue, measuring readily desorbed As using a method known as equilibrium partitioning in closed systems (EPICS). The EPICS method was selected because it employs a leaching solution that, except for its As concentration, is identical in composition to the neutralized raffinate in contact with the tailings. Laboratory experiments and modeling results demonstrated that the As that could be readily released to pore waters is about 0.2% of the total As in the tailings. Long-term, such releases may contribute no more than a few mg/L of dissolved As to tailings pore waters.

  11. Arsenic readily released to pore waters from buried mill tailings

    International Nuclear Information System (INIS)

    Mahoney, John; Langmuir, Donald; Gosselin, Neil; Rowson, John

    2005-01-01

    At the McClean Lake Operation in the Athabasca Basin of northern Saskatchewan, the untreated acid raffinate solutions associated with U mill tailings contain up to 700 mg/L dissolved As. To reduce the concentration of As and other contaminants in acid tailing slurries at the JEB mill at McClean Lake, ferric sulfate may be added to the acid raffinates to assure that their molar Fe/As ratio equals or exceeds 3. Tailings slurries are then neutralized with lime to pH 4, and subsequently to pH 7-8. The neutralized tailings contain minerals from the original ore, which are chiefly quartz, illite, kaolinite and chlorite, and precipitated (secondary) minerals that include gypsum, scorodite, annabergite, hydrobasaluminite and ferrihydrite. Most of the As is associated with the secondary arsenate minerals, scorodite and annabergite. However, a few percent is adsorbed and/or co-precipitated, mainly by ferrihydrite. Of major concern to provincial and federal regulators is the risk that significant amounts of As might be released from the tailings to pore waters after their subaqueous disposal in the tailings management facility. A laboratory study was performed to address this issue, measuring readily desorbed As using a method known as equilibrium partitioning in closed systems (EPICS). The EPICS method was selected because it employs a leaching solution that, except for its As concentration, is identical in composition to the neutralized raffinate in contact with the tailings. Laboratory experiments and modeling results demonstrated that the As that could be readily released to pore waters is about 0.2% of the total As in the tailings. Long-term, such releases may contribute no more than a few mg/L of dissolved As to tailings pore waters

  12. Land Surface Data Assimilation

    Science.gov (United States)

    Houser, P. R.

    2012-12-01

    Information about land surface water, energy and carbon conditions is of critical importance to real-world applications such as agricultural production, water resource management, flood prediction, water supply, weather and climate forecasting, and environmental preservation. While ground-based observational networks are improving, the only practical way to observe these land surface states on continental to global scales is via satellites. Remote sensing can make spatially comprehensive measurements of various components of the terrestrial system, but it cannot provide information on the entire system (e.g. evaporation), and the observations represent only an instant in time. Land surface process models may be used to predict temporal and spatial terrestrial dynamics, but these predictions are often poor, due to model initialization, parameter and forcing, and physics errors. Therefore, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses) to provide a superior terrestrial state estimate. This is the goal of land surface data assimilation. Data Assimilation combines observations into a dynamical model, using the model's equations to provide time continuity and coupling between the estimated fields. Land surface data assimilation aims to utilize both our land surface process knowledge, as embodied in a land surface model, and information that can be gained from observations. Both model predictions and observations are imperfect and we wish to use both synergistically to obtain a more accurate result. Moreover, both contain different kinds of information, that when used together, provide an accuracy level that cannot be obtained individually. Model biases can be mitigated using a complementary calibration and parameterization process. Limited point measurements are often used to calibrate the model(s) and validate the assimilation results. This presentation will provide a brief background on land

  13. Binding Isotherms and Time Courses Readily from Magnetic Resonance.

    Science.gov (United States)

    Xu, Jia; Van Doren, Steven R

    2016-08-16

    Evidence is presented that binding isotherms, simple or biphasic, can be extracted directly from noninterpreted, complex 2D NMR spectra using principal component analysis (PCA) to reveal the largest trend(s) across the series. This approach renders peak picking unnecessary for tracking population changes. In 1:1 binding, the first principal component captures the binding isotherm from NMR-detected titrations in fast, slow, and even intermediate and mixed exchange regimes, as illustrated for phospholigand associations with proteins. Although the sigmoidal shifts and line broadening of intermediate exchange distorts binding isotherms constructed conventionally, applying PCA directly to these spectra along with Pareto scaling overcomes the distortion. Applying PCA to time-domain NMR data also yields binding isotherms from titrations in fast or slow exchange. The algorithm readily extracts from magnetic resonance imaging movie time courses such as breathing and heart rate in chest imaging. Similarly, two-step binding processes detected by NMR are easily captured by principal components 1 and 2. PCA obviates the customary focus on specific peaks or regions of images. Applying it directly to a series of complex data will easily delineate binding isotherms, equilibrium shifts, and time courses of reactions or fluctuations.

  14. Podiatry Ankle Duplex Scan: Readily Learned and Accurate in Diabetes.

    Science.gov (United States)

    Normahani, Pasha; Powezka, Katarzyna; Aslam, Mohammed; Standfield, Nigel J; Jaffer, Usman

    2018-03-01

    We aimed to train podiatrists to perform a focused duplex ultrasound scan (DUS) of the tibial vessels at the ankle in diabetic patients; podiatry ankle (PodAnk) duplex scan. Thirteen podiatrists underwent an intensive 3-hour long simulation training session. Participants were then assessed performing bilateral PodAnk duplex scans of 3 diabetic patients with peripheral arterial disease. Participants were assessed using the duplex ultrasound objective structured assessment of technical skills (DUOSATS) tool and an "Imaging Score". A total of 156 vessel assessments were performed. All patients had abnormal waveforms with a loss of triphasic flow. Loss of triphasic flow was accurately detected in 145 (92.9%) vessels; the correct waveform was identified in 139 (89.1%) cases. Participants achieved excellent DUOSATS scores (median 24 [interquartile range: 23-25], max attainable score of 26) as well as "Imaging Scores" (8 [8-8], max attainable score of 8) indicating proficiency in technical skills. The mean time taken for each bilateral ankle assessment was 20.4 minutes (standard deviation ±6.7). We have demonstrated that a focused DUS for the purpose of vascular assessment of the diabetic foot is readily learned using intensive simulation training.

  15. Displacement data assimilation

    Energy Technology Data Exchange (ETDEWEB)

    Rosenthal, W. Steven [Pacific Northwest Laboratory, Richland, WA 99354 (United States); Venkataramani, Shankar [Department of Mathematics and Program in Applied Mathematics, University of Arizona, Tucson, AZ 85721 (United States); Mariano, Arthur J. [Rosenstiel School of Marine & Atmospheric Science, University of Miami, Miami, FL 33149 (United States); Restrepo, Juan M., E-mail: restrepo@math.oregonstate.edu [Department of Mathematics, Oregon State University, Corvallis, OR 97331 (United States)

    2017-02-01

    We show that modifying a Bayesian data assimilation scheme by incorporating kinematically-consistent displacement corrections produces a scheme that is demonstrably better at estimating partially observed state vectors in a setting where feature information is important. While the displacement transformation is generic, here we implement it within an ensemble Kalman Filter framework and demonstrate its effectiveness in tracking stochastically perturbed vortices.

  16. A simple lightning assimilation technique for improving retrospective WRF simulations.

    Science.gov (United States)

    Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain-F...

  17. Atmospheric H2S and SO2 as sulfur sources for Brassica juncea and Brassica rapa: Regulation of sulfur uptake and assimilation

    NARCIS (Netherlands)

    Aghajanzadeh, T.; Hawkesford, M.J.; De Kok, L.J.

    2016-01-01

    Brassica juncea and Brassica rapa were able to utilize foliarly absorbed H2S and SO2 as sulfur source for growth and resulted in a decreased sink capacity of the shoot for sulfur supplied by the root and subsequently in a partial decrease in sulfate uptake capacity of the roots. Sulfate-deprived

  18. Data assimilation of CALIPSO aerosol observations

    Directory of Open Access Journals (Sweden)

    T. T. Sekiyama

    2010-01-01

    Full Text Available We have developed an advanced data assimilation system for a global aerosol model with a four-dimensional ensemble Kalman filter in which the Level 1B data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO were successfully assimilated for the first time, to the best of the authors' knowledge. A one-month data assimilation cycle experiment for dust, sulfate, and sea-salt aerosols was performed in May 2007. The results were validated via two independent observations: 1 the ground-based lidar network in East Asia, managed by the National Institute for Environmental Studies of Japan, and 2 weather reports of aeolian dust events in Japan. Detailed four-dimensional structures of aerosol outflows from source regions over oceans and continents for various particle types and sizes were well reproduced. The intensity of dust emission at each grid point was also corrected by this data assimilation system. These results are valuable for the comprehensive analysis of aerosol behavior as well as aerosol forecasting.

  19. Spatial Assimilation in Denmark?

    DEFF Research Database (Denmark)

    Andersen, Hans Skifter

    2010-01-01

    market and discrimination, which limits the housing possibilities for ethnic minorities. Another explanation could be that immigrants for different reasons choose to settle in so-called ethnic enclaves where they can find an ethnic social network, which can support them in their new country....... In traditional research literature about immigration it has been shown that for many immigrants living in enclaves has been a temporary situation. The 'spatial assimilation theory' says that this situation ends when the family has become more integrated in the new society and then moves to other parts...

  20. Regional Ocean Data Assimilation

    KAUST Repository

    Edwards, Christopher A.

    2015-01-03

    This article reviews the past 15 years of developments in regional ocean data assimilation. A variety of scientific, management, and safety-related objectives motivate marine scientists to characterize many ocean environments, including coastal regions. As in weather prediction, the accurate representation of physical, chemical, and/or biological properties in the ocean is challenging. Models and observations alone provide imperfect representations of the ocean state, but together they can offer improved estimates. Variational and sequential methods are among the most widely used in regional ocean systems, and there have been exciting recent advances in ensemble and four-dimensional variational approaches. These techniques are increasingly being tested and adapted for biogeochemical applications.

  1. Regulation of nitrogen uptake and assimilation: Effects of nitrogen source and root-zone and aerial environment on growth and productivity of soybean

    Science.gov (United States)

    Raper, C. David, Jr.

    1994-01-01

    The interdependence of root and shoot growth produces a functional equilibrium as described in quantitative terms by numerous authors. It was noted that bean seedlings grown in a constant environment tended to have a constant distribution pattern of dry matter between roots and leaves characteristic of the set of environmental conditions. Disturbing equilibrium resulted in a change in relative growth of roots and leaves until the original ratio was restored. To define a physiological basis for regulation of nitrogen uptake within the balance between root and shoot activities, the authors combined a partioning scheme and a utilization priority assumption in which: (1) all carbon enters the plant through photosynthesis in leaves and all nitrogen enters the plant through active uptake by roots, (2) nitrogen uptake by roots and secretion into the xylem for transport to the shoots are active processes, (3) availability of exogenous nitrogen determines concentration of soluble carbohydrates within the roots, (4) leaves are a source and a sink for carbohydrates, and (5) the requirement for nitrogen by leaf growth is proportionally greater during initiation and early expansion than during later expansion.

  2. Improving operational flood forecasting through data assimilation

    Science.gov (United States)

    Rakovec, Oldrich; Weerts, Albrecht; Uijlenhoet, Remko; Hazenberg, Pieter; Torfs, Paul

    2010-05-01

    Accurate flood forecasts have been a challenging topic in hydrology for decades. Uncertainty in hydrological forecasts is due to errors in initial state (e.g. forcing errors in historical mode), errors in model structure and parameters and last but not least the errors in model forcings (weather forecasts) during the forecast mode. More accurate flood forecasts can be obtained through data assimilation by merging observations with model simulations. This enables to identify the sources of uncertainties in the flood forecasting system. Our aim is to assess the different sources of error that affect the initial state and to investigate how they propagate through hydrological models with different levels of spatial variation, starting from lumped models. The knowledge thus obtained can then be used in a data assimilation scheme to improve the flood forecasts. This study presents the first results of this framework and focuses on quantifying precipitation errors and its effect on discharge simulations within the Ourthe catchment (1600 km2), which is situated in the Belgian Ardennes and is one of the larger subbasins of the Meuse River. Inside the catchment, hourly rain gauge information from 10 different locations is available over a period of 15 years. Based on these time series, the bootstrap method has been applied to generate precipitation ensembles. These were then used to simulate the catchment's discharges at the outlet. The corresponding streamflow ensembles were further assimilated with observed river discharges to update the model states of lumped hydrological models (R-PDM, HBV) through Residual Resampling. This particle filtering technique is a sequential data assimilation method and takes no prior assumption of the probability density function for the model states, which in contrast to the Ensemble Kalman filter does not have to be Gaussian. Our further research will be aimed at quantifying and reducing the sources of uncertainty that affect the initial

  3. Nonlinear data assimilation

    CERN Document Server

    Van Leeuwen, Peter Jan; Reich, Sebastian

    2015-01-01

    This book contains two review articles on nonlinear data assimilation that deal with closely related topics but were written and can be read independently. Both contributions focus on so-called particle filters. The first contribution by Jan van Leeuwen focuses on the potential of proposal densities. It discusses the issues with present-day particle filters and explorers new ideas for proposal densities to solve them, converging to particle filters that work well in systems of any dimension, closing the contribution with a high-dimensional example. The second contribution by Cheng and Reich discusses a unified framework for ensemble-transform particle filters. This allows one to bridge successful ensemble Kalman filters with fully nonlinear particle filters, and allows a proper introduction of localization in particle filters, which has been lacking up to now.

  4. Assimilation of Aircraft Observations in High-Resolution Mesoscale Modeling

    Directory of Open Access Journals (Sweden)

    Brian P. Reen

    2018-01-01

    Full Text Available Aircraft-based observations are a promising source of above-surface observations for assimilation into mesoscale model simulations. The Tropospheric Airborne Meteorological Data Reporting (TAMDAR observations have potential advantages over some other aircraft observations including the presence of water vapor observations. The impact of assimilating TAMDAR observations via observation nudging in 1 km horizontal grid spacing Weather Research and Forecasting model simulations is evaluated using five cases centered over California. Overall, the impact of assimilating the observations is mixed, with the layer with the greatest benefit being above the surface in the lowest 1000 m above ground level and the variable showing the most consistent benefit being temperature. Varying the nudging configuration demonstrates the sensitivity of the results to details of the assimilation, but does not clearly demonstrate the superiority of a specific configuration.

  5. Global Data Assimilation System (GDAS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Data Assimilation System (GDAS) is the system used by the Global Forecast System (GFS) model to place observations into a gridded model space for the...

  6. Data assimilation in hydrological modelling

    DEFF Research Database (Denmark)

    Drecourt, Jean-Philippe

    Data assimilation is an invaluable tool in hydrological modelling as it allows to efficiently combine scarce data with a numerical model to obtain improved model predictions. In addition, data assimilation also provides an uncertainty analysis of the predictions made by the hydrological model....... In this thesis, the Kalman filter is used for data assimilation with a focus on groundwater modelling. However the developed techniques are general and can be applied also in other modelling domains. Modelling involves conceptualization of the processes of Nature. Data assimilation provides a way to deal...... with model non-linearities and biased errors. A literature review analyzes the most popular techniques and their application in hydrological modelling. Since bias is an important problem in groundwater modelling, two bias aware Kalman filters have been implemented and compared using an artificial test case...

  7. Data Assimilation in Marine Models

    DEFF Research Database (Denmark)

    Frydendall, Jan

    maximum likelihood framework. These issues are discussed in paper B. The third part of the thesis falls a bit out of the above context is work published in papers C, F. In the first paper, a simple data assimilation scheme was investigated to examine the potential benefits of incorporating a data......This thesis consists of six research papers published or submitted for publication in the period 2006-2009 together with a summary report. The main topics of this thesis are nonlinear data assimilation techniques and estimation in dynamical models. The focus has been on the nonlinear filtering...... techniques for large scale geophysical numerical models and making them feasible to work with in the data assimilation framework. The filtering techniques investigated are all Monte Carlo simulation based. Some very nice features that can be exploited in the Monte Carlo based data assimilation framework from...

  8. 26 CFR 1.453-3 - Purchaser evidences of indebtedness payable on demand or readily tradable.

    Science.gov (United States)

    2010-04-01

    ... obligation (determined by taking into account all relevant factors, including proper discount to reflect the... demand or readily tradable. 1.453-3 Section 1.453-3 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT... Income Included § 1.453-3 Purchaser evidences of indebtedness payable on demand or readily tradable. (a...

  9. Effective Assimilation of Global Precipitation

    Science.gov (United States)

    Lien, G.; Kalnay, E.; Miyoshi, T.; Huffman, G. J.

    2012-12-01

    Assimilating precipitation observations by modifying the moisture and sometimes temperature profiles has been shown successful in forcing the model precipitation to be close to the observed precipitation, but only while the assimilation is taking place. After the forecast start, the model tends to "forget" the assimilation changes and lose their extra skill after few forecast hours. This suggests that this approach is not an efficient way to modify the potential vorticity field, since this is the variable that the model would remember. In this study, the ensemble Kalman filter (EnKF) method is used to effectively change the potential vorticity field by allowing ensemble members with better precipitation to receive higher weights. In addition to using an EnKF, two other changes in the precipitation assimilation process are proposed to solve the problems related to the highly non-Gaussian nature of the precipitation variable: a) transform precipitation into a Gaussian distribution based on its climatological distribution, and b) only assimilate precipitation at the location where some ensemble members have positive precipitation. The idea is first tested by the observing system simulation experiments (OSSEs) using SPEEDY, a simplified but realistic general circulation model. When the global precipitation is assimilated in addition to conventional rawinsonde observations, both the analyses and the medium range forecasts are significantly improved as compared to only having rawinsonde observations. The improvement is much reduced when only modifying the moisture field with the same approach, which shows the importance of the error covariance between precipitation and all other model variables. The effect of precipitation assimilation is larger in the Southern Hemisphere than that in the Northern Hemisphere because the Northern Hemisphere analyses are already accurate as a result of denser rawinsonde stations. Assimilation of precipitation using a more comprehensive

  10. The effect of acetylcholine on 14C-assimilates translocation of Isatis tinctoria L

    International Nuclear Information System (INIS)

    Yang Chongjun; Tang Feiyu; Zhang Ping; Guo Yuhai

    2004-01-01

    The effects of acetylcholine on 14 C-assimilates translocation are studied with source-channel-sink of Isatis tinctoria L. The experiments show that 0.01 mmol/L treatments of acetylcholine on the phloem, can improve the output of 14 C-assimilates in leaves indicating that acetylcholine enhances the activity of phloem transport. (authors)

  11. Nitrogen assimilation in denitrifier Bacillus azotoformans LMG 9581T.

    Science.gov (United States)

    Sun, Yihua; De Vos, Paul; Willems, Anne

    2017-12-01

    Until recently, it has not been generally known that some bacteria can contain the gene inventory for both denitrification and dissimilatory nitrate (NO 3 - )/nitrite (NO 2 - ) reduction to ammonium (NH 4 + ) (DNRA). Detailed studies of these microorganisms could shed light on the differentiating environmental drivers of both processes without interference of organism-specific variation. Genome analysis of Bacillus azotoformans LMG 9581 T shows a remarkable redundancy of dissimilatory nitrogen reduction, with multiple copies of each denitrification gene as well as DNRA genes nrfAH, but a reduced capacity for nitrogen assimilation, with no nas operon nor amtB gene. Here, we explored nitrogen assimilation in detail using growth experiments in media with different organic and inorganic nitrogen sources at different concentrations. Monitoring of growth, NO 3 - NO 2 - , NH 4 + concentration and N 2 O production revealed that B. azotoformans LMG 9581 T could not grow with NH 4 + as sole nitrogen source and confirmed the hypothesis of reduced nitrogen assimilation pathways. However, NH 4 + could be assimilated and contributed up to 50% of biomass if yeast extract was also provided. NH 4 + also had a significant but concentration-dependent influence on growth rate. The mechanisms behind these observations remain to be resolved but hypotheses for this deficiency in nitrogen assimilation are discussed. In addition, in all growth conditions tested a denitrification phenotype was observed, with all supplied NO 3 - converted to nitrous oxide (N 2 O).

  12. Effects of water stress on the distribution of 14C-assimilates in young apple trees (mauls pumila mill.)

    International Nuclear Information System (INIS)

    Dong Jiankang; Deng Ximin; Zeng Xiang

    1994-01-01

    Young apple trees were treated by water stress and 14 CO 2 was fed to leaves. Distribution of assimilates in source and sink organs was determined. The results show that plant water deficit increased the proportion of 14 C-assimilates remained in source leaves, and decreased the proportion of 13 C-assimilates exported into the developing fruits. Water stress also significantly decreased the photosynthetic rate of leaves and the growth rate of plants

  13. Sucrose assimilation and the role of sucrose transporters in plant ...

    African Journals Online (AJOL)

    STORAGESEVER

    2008-12-29

    Dec 29, 2008 ... African Journal of Biotechnology Vol. 7 (25), pp. ... Review. Sucrose assimilation and the role of sucrose transporters in plant wound response. Omodele ... Key words: Sucrose transporters, Plasma membrane, carbohydrate, sieve element, source-sink. ... pathogens (Paul et al., 2000) and results in a severe.

  14. Assimilation of Long-Range Lightning Data over the Pacific

    Science.gov (United States)

    2011-09-30

    convective rainfall analyses over the Pacific, and (iii) to improve marine prediction of cyclogenesis of both tropical and extratropical cyclones through...data over the North Pacific Ocean, refine the relationships between lightning and storm hydrometeor characteristics, and assimilate lightning...unresolved storm -scale areas of deep convection over the data-sparse open oceans. Diabatic heating sources, especially latent heat release in deep

  15. Data Assimilation for Applied Meteorology

    Science.gov (United States)

    Haupt, S. E.

    2012-12-01

    Although atmospheric models provide a best estimate of the future state of the atmosphere, due to sensitivity to initial condition, it is difficult to predict the precise future state. For applied problems, however, users often depend on having accurate knowledge of that future state. To improve prediction of a particular realization of an evolving flow field requires knowledge of the current state of that field and assimilation of local observations into the model. This talk will consider how dynamic assimilation can help address the concerns of users of atmospheric forecasts. First, we will look at the value of assimilation for the renewable energy industry. If the industry decision makers can have confidence in the wind and solar power forecasts, they can build their power allocations around the expected renewable resource, saving money for the ratepayers as well as reducing carbon emissions. We will assess the value to that industry of assimilating local real-time observations into the model forecasts and the value that is provided. The value of the forecasts with assimilation is important on both short (several hour) to medium range (within two days). A second application will be atmospheric transport and dispersion problems. In particular, we will look at assimilation of concentration data into a prediction model. An interesting aspect of this problem is that the dynamics are a one-way coupled system, with the fluid dynamic equations affecting the concentration equation, but not vice versa. So when the observations are of the concentration, one must infer the fluid dynamics. This one-way coupled system presents a challenge: one must first infer the changes in the flow field from observations of the contaminant, then assimilate that to recover both the advecting flow and information on the subgrid processes that provide the mixing. To accomplish such assimilation requires a robust method to match the observed contaminant field to that modeled. One approach is

  16. Bayesian Modeling of the Assimilative Capacity Component of Stream Nutrient Export

    Science.gov (United States)

    Implementing stream restoration techniques and best management practices to reduce nonpoint source nutrients implies enhancement of the assimilative capacity for the stream system. In this paper, a Bayesian method for evaluating this component of a TMDL load capacity is developed...

  17. Process antecedents of challenging, under-cover and readily-adopted innovations.

    Science.gov (United States)

    Adams, Richard; Tranfield, David; Denyer, David

    2013-01-01

    The purpose of the study is to test the utility of a taxonomy of innovation based on perceived characteristics in the context of healthcare by exploring the extent to which discrete innovation types could be distinguished from each other in terms of process antecedents. A qualitative approach was adopted to explore the process antecedents of nine exemplar cases of "challenging", "under-cover" and "readily-adopted" healthcare innovations. Data were collected by semi-structured interview and from secondary sources, and content analysed according to a theoretically informed framework of innovation process. Cluster analysis was applied to determine whether innovation types could be distinguished on the basis of process characteristics. The findings provide moderate support for the proposition that innovations differentiated on the basis of the way they are perceived by potential users exhibit different process characteristics. Innovations exhibiting characteristics previously believed negatively to impact adoption may be successfully adopted but by a different configuration of processes than by innovations exhibiting a different set of characteristics. The findings must be treated with caution because the sample consists of self-selected cases of successful innovation and is limited by sample size. Nevertheless, the study sheds new light on important process differences in healthcare innovation. The paper offers a heuristic device to aid clinicians and managers to better understand the relatively novel task of promoting and managing innovation in healthcare. The paper advances the argument that there is under-exploited opportunity for cross-disciplinary organisational learning for innovation management in the NHS. If efficiency and quality improvement targets are to be met through a strategy of encouraging innovation, it may be advantageous for clinicians and managers to reflect on what this study found mostly to be absent from the processes of the innovations studied

  18. Rapid Production of a Porous Cellulose Acetate Membrane for Water Filtration Using Readily Available Chemicals

    Science.gov (United States)

    Kaiser, Adrian; Stark, Wendelin J.; Grass, Robert N.

    2017-01-01

    A chemistry laboratory experiment using everyday items and readily available chemicals is described to introduce advanced high school students and undergraduate college students to porous polymer membranes. In a three-step manufacturing process, a membrane is produced at room temperature. The filtration principle of the membrane is then…

  19. Assimilate partitioning during reproductive growth

    International Nuclear Information System (INIS)

    Finazzo, S.F.; Davenport, T.L.

    1987-01-01

    Leaves having various phyllotactic relationships to fruitlets were labeled for 1 hour with 10/sub r/Ci of 14 CO 2 . Fruitlets were also labeled. Fruitlets did fix 14 CO 2 . Translocation of radioactivity from the peel into the fruit occurred slowly and to a limited extent. No evidence of translocation out of the fruitlets was observed. Assimilate partitioning in avocado was strongly influenced by phyllotaxy. If a fruit and the labeled leaf had the same phyllotaxy then greater than 95% of the radiolabel was present in this fruit. When the fruit did not have the same phyllotaxy as the labeled leaf, the radiolabel distribution was skewed with 70% of the label going to a single adjacent position. Avocado fruitlets exhibit uniform labeling throughout a particular tissue. In avocado, assimilates preferentially move from leaves to fruits with the same phyllotaxy

  20. Ocean Data Assimilation in the Gulf of Mexico Using 3D VAR Approach - Preliminary Results

    Science.gov (United States)

    Paturi, S.; Garraffo, Z. D.; Cummings, J. A.; Rivin, I.; Mehra, A.; Kim, H. C.

    2016-12-01

    Approaches to ocean data assimilation vary widely, both in terms of the sophistication of the method and the observations assimilated.A three-dimensional variational (3DVAR) data assimilation system, part of the Navy Coupled Ocean Data Assimilation (NCODA) system developed at Navy Research Laboratory (NRL), is used for assimilating Sea Surface Temperature (SST) and Sea Surface Height (SSH) in the Gulf of Mexico (GoM). The NCODA 3DVAR produces simultaneous analyses of temperature, salinity, and vector velocity and uses all possible sources of ocean data observations.The Hybrid Coordinate Ocean Model (HYCOM) is used for the simulations, at 1/25o grid resolution for July 2011 period. After successful implementation of NCODA 3DVAR in the GoM, the system will be extended to the global ocean with the intent of making it operational.

  1. Effects of inorganic nitrogen sources on the production of PP-V [(10Z)-12-carboxyl-monascorubramine] and the Expression of the nitrate assimilation gene cluster by Penicillium sp. AZ.

    Science.gov (United States)

    Arai, Teppei; Umemura, Sara; Ota, Tamaki; Ogihara, Jun; Kato, Jun; Kasumi, Takafumi

    2012-01-01

    A fungal strain, Penicillium sp. AZ, produced the azaphilone Monascus pigment homolog when cultured in a medium composed of soluble starch, ammonium nitrate, yeast extract, and citrate buffer, pH 5.0. One of the typical features of violet pigment PP-V [(10Z)-12-carboxyl-monascorubramine] is that pyranoid oxygen is replaced with nitrogen. In this study, we found that ammonia and nitrate nitrogen are available for PP-V biosynthesis, and that ammonia nitrogen was much more effective than nitrate nitrogen. Further, we isolated nitrate assimilation gene cluster, niaD, niiA, and crnA, and analyzed the expression of these genes. The expression levels of all these genes increased with sodium nitrate addition to the culture medium. The results obtained here strongly suggest that Penicillium sp. AZ produced PP-V using nitrate in the form of ammonium reduced from nitrate through a bioprocess assimilatory reaction.

  2. Assimilation of LAI time-series in crop production models

    Science.gov (United States)

    Kooistra, Lammert; Rijk, Bert; Nannes, Louis

    2014-05-01

    Agriculture is worldwide a large consumer of freshwater, nutrients and land. Spatial explicit agricultural management activities (e.g., fertilization, irrigation) could significantly improve efficiency in resource use. In previous studies and operational applications, remote sensing has shown to be a powerful method for spatio-temporal monitoring of actual crop status. As a next step, yield forecasting by assimilating remote sensing based plant variables in crop production models would improve agricultural decision support both at the farm and field level. In this study we investigated the potential of remote sensing based Leaf Area Index (LAI) time-series assimilated in the crop production model LINTUL to improve yield forecasting at field level. The effect of assimilation method and amount of assimilated observations was evaluated. The LINTUL-3 crop production model was calibrated and validated for a potato crop on two experimental fields in the south of the Netherlands. A range of data sources (e.g., in-situ soil moisture and weather sensors, destructive crop measurements) was used for calibration of the model for the experimental field in 2010. LAI from cropscan field radiometer measurements and actual LAI measured with the LAI-2000 instrument were used as input for the LAI time-series. The LAI time-series were assimilated in the LINTUL model and validated for a second experimental field on which potatoes were grown in 2011. Yield in 2011 was simulated with an R2 of 0.82 when compared with field measured yield. Furthermore, we analysed the potential of assimilation of LAI into the LINTUL-3 model through the 'updating' assimilation technique. The deviation between measured and simulated yield decreased from 9371 kg/ha to 8729 kg/ha when assimilating weekly LAI measurements in the LINTUL model over the season of 2011. LINTUL-3 furthermore shows the main growth reducing factors, which are useful for farm decision support. The combination of crop models and sensor

  3. The Impact of Readily Detected- and Underlying Attributes on Social Integration in Cross-Cultural Settings

    OpenAIRE

    Peltokorpi, Vesa

    2003-01-01

    The benefits and drawbacks of homogeneity and heterogeneity have been debated at length. Whereas some researchers assert that heterogeneity is beneficial for groups that are engaged in complex problem solving, the other researchers emphasize the potential costs associated with diversity. The inconsistency is a result of the incomplete measurement of diversity and focus one or two types of diversity. Most research concentrates on the readily detected/visible characteristics, making the assumpt...

  4. Conditions for successful data assimilation

    Science.gov (United States)

    Morzfeld, M.; Chorin, A. J.

    2013-12-01

    Many applications in science and engineering require that the predictions of uncertain models be updated by information from a stream of noisy data. The model and the data jointly define a conditional probability density function (pdf), which contains all the information one has about the process of interest and various numerical methods can be used to study and approximate this pdf, e.g. the Kalman filter, variational methods or particle filters. Given a model and data, each of these algorithms will produce a result. We are interested in the conditions under which this result is reasonable, i.e. consistent with the real-life situation one is modeling. In particular, we show, using idealized models, that numerical data assimilation is feasible in principle only if a suitably defined effective dimension of the problem is not excessive. This effective dimension depends on the noise in the model and the data, and in physically reasonable problems it can be moderate even when the number of variables is huge. In particular, we find that the effective dimension being moderate induces a balance condition between the noises in the model and the data; this balance condition is often satisfied in realistic applications or else the noise levels are excessive and drown the underlying signal. We also study the effects of the effective dimension on particle filters in two instances, one in which the importance function is based on the model alone, and one in which it is based on both the model and the data. We have three main conclusions: (1) the stability (i.e., non-collapse of weights) in particle filtering depends on the effective dimension of the problem. Particle filters can work well if the effective dimension is moderate even if the true dimension is large (which we expect to happen often in practice). (2) A suitable choice of importance function is essential, or else particle filtering fails even when data assimilation is feasible in principle with a sequential algorithm

  5. Assimilate partitioning in avocado, Persea americana

    Energy Technology Data Exchange (ETDEWEB)

    Finazzo, S.; Davenport, T.L.

    1986-04-01

    Assimilate partitioning is being studied in avocado, Persea americana cv. Millborrow in relation to fruit set. Single leaves on girdled branches of 10 year old trees were radiolabeled for 1 hr with 13..mu..Ci of /sup 14/CO/sub 2/. The source leaves were sampled during the experiment to measure translocation rates. At harvest the sink tissues were dissected and the incorporated radioactivity was measured. The translocation of /sup 14/C-labelled compounds to other leaves was minimal. Incorporation of label into fruitlets varied with the tissue and the stage of development. Sink (fruitlets) nearest to the labelled leaf and sharing the same phyllotaxy incorporated the most /sup 14/C. Source leaves for single non-abscising fruitlets retained 3X more /sup 14/C-labelled compounds than did source leaves for 2 or more fruitlets at 31 hrs. post-labelling. Export of label decreased appreciably when fruitlets abscised. If fruitlets abscised within 4 days of labeling then the translocation pattern was similar to the pattern for single fruitlets. If the fruitlet abscised later, the translocation pattern was intermediate between the single and double fruitlet pattern.

  6. Assimilate partitioning in avocado, Persea americana

    International Nuclear Information System (INIS)

    Finazzo, S.; Davenport, T.L.

    1986-01-01

    Assimilate partitioning is being studied in avocado, Persea americana cv. Millborrow in relation to fruit set. Single leaves on girdled branches of 10 year old trees were radiolabeled for 1 hr with 13μCi of 14 CO 2 . The source leaves were sampled during the experiment to measure translocation rates. At harvest the sink tissues were dissected and the incorporated radioactivity was measured. The translocation of 14 C-labelled compounds to other leaves was minimal. Incorporation of label into fruitlets varied with the tissue and the stage of development. Sink (fruitlets) nearest to the labelled leaf and sharing the same phyllotaxy incorporated the most 14 C. Source leaves for single non-abscising fruitlets retained 3X more 14 C-labelled compounds than did source leaves for 2 or more fruitlets at 31 hrs. post-labelling. Export of label decreased appreciably when fruitlets abscised. If fruitlets abscised within 4 days of labeling then the translocation pattern was similar to the pattern for single fruitlets. If the fruitlet abscised later, the translocation pattern was intermediate between the single and double fruitlet pattern

  7. You are not always what we think you eat: selective assimilation across multiple whole-stream isotopic tracer studies

    Science.gov (United States)

    W. K. Dodds; S. M. Collins; S. K. Hamilton; J. L. Tank; S. Johnson; J. R. Webster; K. S. Simon; M. R. Whiles; H. M. Rantala; W. H. McDowell; S. D. Peterson; T. Riis; C. L. Crenshaw; S. A. Thomas; P. B. Kristensen; B. M. Cheever; A. S. Flecker; N. A. Griffiths; T. Crowl; E. J. Rosi-Marshall; R. El-Sabaawi; E. Martí

    2014-01-01

    Analyses of 21 15N stable isotope tracer experiments, designed to examine food web dynamics in streams around the world, indicated that the isotopic composition of food resources assimilated by primary consumers (mostly invertebrates) poorly reflected the presumed food sources. Modeling indicated that consumers assimilated only 33–50% of the N...

  8. Snow multivariable data assimilation for hydrological predictions in mountain areas

    Science.gov (United States)

    Piazzi, Gaia; Campo, Lorenzo; Gabellani, Simone; Rudari, Roberto; Castelli, Fabio; Cremonese, Edoardo; Morra di Cella, Umberto; Stevenin, Hervé; Ratto, Sara Maria

    2016-04-01

    The seasonal presence of snow on alpine catchments strongly impacts both surface energy balance and water resource. Thus, the knowledge of the snowpack dynamics is of critical importance for several applications, such as water resource management, floods prediction and hydroelectric power production. Several independent data sources provide information about snowpack state: ground-based measurements, satellite data and physical models. Although all these data types are reliable, each of them is affected by specific flaws and errors (respectively dependency on local conditions, sensor biases and limitations, initialization and poor quality forcing data). Moreover, there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine observational and modeled information to obtain the most likely estimate of snowpack state. Indeed, by combining all the available sources of information, the implementation of DA schemes can quantify and reduce the uncertainties of the estimations. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model, strengthened by a robust multivariable data assimilation algorithm. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of an Ensemble Kalman Filter (EnKF) scheme enables to assimilate simultaneously ground

  9. Data Assimilation - Advances and Applications

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Brian J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2014-07-30

    This presentation provides an overview of data assimilation (model calibration) for complex computer experiments. Calibration refers to the process of probabilistically constraining uncertain physics/engineering model inputs to be consistent with observed experimental data. An initial probability distribution for these parameters is updated using the experimental information. Utilization of surrogate models and empirical adjustment for model form error in code calibration form the basis for the statistical methodology considered. The role of probabilistic code calibration in supporting code validation is discussed. Incorporation of model form uncertainty in rigorous uncertainty quantification (UQ) analyses is also addressed. Design criteria used within a batch sequential design algorithm are introduced for efficiently achieving predictive maturity and improved code calibration. Predictive maturity refers to obtaining stable predictive inference with calibrated computer codes. These approaches allow for augmentation of initial experiment designs for collecting new physical data. A standard framework for data assimilation is presented and techniques for updating the posterior distribution of the state variables based on particle filtering and the ensemble Kalman filter are introduced.

  10. Data assimilation with inequality constraints

    Science.gov (United States)

    Thacker, W. C.

    If values of variables in a numerical model are limited to specified ranges, these restrictions should be enforced when data are assimilated. The simplest option is to assimilate without regard for constraints and then to correct any violations without worrying about additional corrections implied by correlated errors. This paper addresses the incorporation of inequality constraints into the standard variational framework of optimal interpolation with emphasis on our limited knowledge of the underlying probability distributions. Simple examples involving only two or three variables are used to illustrate graphically how active constraints can be treated as error-free data when background errors obey a truncated multi-normal distribution. Using Lagrange multipliers, the formalism is expanded to encompass the active constraints. Two algorithms are presented, both relying on a solution ignoring the inequality constraints to discover violations to be enforced. While explicitly enforcing a subset can, via correlations, correct the others, pragmatism based on our poor knowledge of the underlying probability distributions suggests the expedient of enforcing them all explicitly to avoid the computationally expensive task of determining the minimum active set. If additional violations are encountered with these solutions, the process can be repeated. Simple examples are used to illustrate the algorithms and to examine the nature of the corrections implied by correlated errors.

  11. Impact of uncertainty description on assimilating hydraulic head in the MIKE SHE distributed hydrological model

    DEFF Research Database (Denmark)

    Zhang, Donghua; Madsen, Henrik; Ridler, Marc E.

    2015-01-01

    The ensemble Kalman filter (EnKF) is a popular data assimilation (DA) technique that has been extensively used in environmental sciences for combining complementary information from model predictions and observations. One of the major challenges in EnKF applications is the description of model un...... with respect to performance and sensitivity. Results show that inappropriate definition of model uncertainty can greatly degrade the assimilation performance, and an appropriate combination of different model uncertainty sources is advised....

  12. Quantification of birefringence readily measures the level of muscle damage in zebrafish

    Energy Technology Data Exchange (ETDEWEB)

    Berger, Joachim, E-mail: Joachim.Berger@Monash.edu [Australian Regenerative Medicine Institute, EMBL Australia, Monash University, Clayton (Australia); Sztal, Tamar; Currie, Peter D. [Australian Regenerative Medicine Institute, EMBL Australia, Monash University, Clayton (Australia)

    2012-07-13

    Highlights: Black-Right-Pointing-Pointer Report of an unbiased quantification of the birefringence of muscle of fish larvae. Black-Right-Pointing-Pointer Quantification method readily identifies level of overall muscle damage. Black-Right-Pointing-Pointer Compare zebrafish muscle mutants for level of phenotype severity. Black-Right-Pointing-Pointer Proposed tool to survey treatments that aim to ameliorate muscular dystrophy. -- Abstract: Muscular dystrophies are a group of genetic disorders that progressively weaken and degenerate muscle. Many zebrafish models for human muscular dystrophies have been generated and analysed, including dystrophin-deficient zebrafish mutants dmd that model Duchenne Muscular Dystrophy. Under polarised light the zebrafish muscle can be detected as a bright area in an otherwise dark background. This light effect, called birefringence, results from the diffraction of polarised light through the pseudo-crystalline array of the muscle sarcomeres. Muscle damage, as seen in zebrafish models for muscular dystrophies, can readily be detected by a reduction in the birefringence. Therefore, birefringence is a very sensitive indicator of overall muscle integrity within larval zebrafish. Unbiased documentation of the birefringence followed by densitometric measurement enables the quantification of the birefringence of zebrafish larvae. Thereby, the overall level of muscle integrity can be detected, allowing the identification and categorisation of zebrafish muscle mutants. In addition, we propose that the establish protocol can be used to analyse treatments aimed at ameliorating dystrophic zebrafish models.

  13. Long-term culture of astrocytes attenuates the readily releasable pool of synaptic vesicles.

    Directory of Open Access Journals (Sweden)

    Hiroyuki Kawano

    Full Text Available The astrocyte is a major glial cell type of the brain, and plays key roles in the formation, maturation, stabilization and elimination of synapses. Thus, changes in astrocyte condition and age can influence information processing at synapses. However, whether and how aging astrocytes affect synaptic function and maturation have not yet been thoroughly investigated. Here, we show the effects of prolonged culture on the ability of astrocytes to induce synapse formation and to modify synaptic transmission, using cultured autaptic neurons. By 9 weeks in culture, astrocytes derived from the mouse cerebral cortex demonstrated increases in β-galactosidase activity and glial fibrillary acidic protein (GFAP expression, both of which are characteristic of aging and glial activation in vitro. Autaptic hippocampal neurons plated on these aging astrocytes showed a smaller amount of evoked release of the excitatory neurotransmitter glutamate, and a lower frequency of miniature release of glutamate, both of which were attributable to a reduction in the pool of readily releasable synaptic vesicles. Other features of synaptogenesis and synaptic transmission were retained, for example the ability to induce structural synapses, the presynaptic release probability, the fraction of functional presynaptic nerve terminals, and the ability to recruit functional AMPA and NMDA glutamate receptors to synapses. Thus the presence of aging astrocytes affects the efficiency of synaptic transmission. Given that the pool of readily releasable vesicles is also small at immature synapses, our results are consistent with astrocytic aging leading to retarded synapse maturation.

  14. Amphetamine Elicits Opposing Actions on Readily Releasable and Reserve Pools for Dopamine

    Science.gov (United States)

    Covey, Dan P.; Juliano, Steven A.; Garris, Paul A.

    2013-01-01

    Amphetamine, a highly addictive drug with therapeutic efficacy, exerts paradoxical effects on the fundamental communication modes employed by dopamine neurons in modulating behavior. While amphetamine elevates tonic dopamine signaling by depleting vesicular stores and driving non-exocytotic release through reverse transport, this psychostimulant also activates phasic dopamine signaling by up-regulating vesicular dopamine release. We hypothesized that these seemingly incongruent effects arise from amphetamine depleting the reserve pool and enhancing the readily releasable pool. This novel hypothesis was tested using in vivo voltammetry and stimulus trains of varying duration to access different vesicular stores. We show that amphetamine actions are stimulus dependent in the dorsal striatum. Specifically, amphetamine up-regulated vesicular dopamine release elicited by a short-duration train, which interrogates the readily releasable pool, but depleted release elicited by a long-duration train, which interrogates the reserve pool. These opposing actions of vesicular dopamine release were associated with concurrent increases in tonic and phasic dopamine responses. A link between vesicular depletion and tonic signaling was supported by results obtained for amphetamine in the ventral striatum and cocaine in both striatal sub-regions, which demonstrated augmented vesicular release and phasic signals only. We submit that amphetamine differentially targeting dopamine stores reconciles the paradoxical activation of tonic and phasic dopamine signaling. Overall, these results further highlight the unique and region-distinct cellular mechanisms of amphetamine and may have important implications for its addictive and therapeutic properties. PMID:23671560

  15. Temperature sensitivity of soil respiration is dependent on readily decomposable C substrate concentration

    Science.gov (United States)

    Larionova, A. A.; Yevdokimov, I. V.; Bykhovets, S. S.

    2007-06-01

    Temperature acclimation of soil organic matter (SOM) decomposition is one of the major uncertainties in predicting soil CO2 efflux by the increase in global mean temperature. A reasonable explanation for an apparent acclimation proposed by Davidson and colleagues (2006) based on Michaelis-Menten kinetics suggests that temperature sensitivity decreases when both maximal activity of respiratory enzymes (Vmax) and half- saturation constant (Ks) cancel each other upon temperature increase. We tested the hypothesis of the canceling effect by the mathematical simulation of the data obtained in the incubation experiments with forest and arable soils. Our data confirm the hypothesis and suggest that concentration of readily decomposable C substrate as glucose equivalent is an important factor controlling temperature sensitivity. The highest temperature sensitivity was observed when C substrate concentration was much lower than Ks. Increase of substrate content to the half-saturation constant resulted in temperature acclimation associated with the canceling effect. Addition of the substrate to the level providing respiration at a maximal rate Vmax leads to the acclimation of the whole microbial community as such. However, growing microbial biomass was more sensitive to the temperature alterations. This study improves our understanding of the instability of temperature sensitivity of soil respiration under field conditions, explaining this phenomenon by changes in concentration of readily decomposable C substrate. It is worth noting that this pattern works regardless of the origin of C substrate: production by SOM decomposition, release into the soil by rhizodeposition, litter fall or drying-rewetting events.

  16. Temperature response of soil respiration is dependent on concentration of readily decomposable C

    Science.gov (United States)

    Larionova, A. A.; Yevdokimov, I. V.; Bykhovets, S. S.

    2007-12-01

    Temperature acclimation of soil organic matter (SOM) decomposition is one of the major uncertainties in predicting soil CO2 efflux associated with the increase in global mean temperature. A reasonable explanation for an apparent acclimation proposed by Davidson and colleagues (2006) based on Michaelis-Menten kinetics suggests that temperature sensitivity decreases when both maximal activity of respiratory enzymes (Vmax) and half-saturation constant (Ks) cancel each other upon temperature increase. We tested the hypothesis of the canceling effect by the mathematical simulation of data obtained in incubation experiments with forest and arable soils. Our data support the hypothesis and suggest that concentration of readily decomposable C substrate (as glucose equivalents) and temperature dependent substrate release are the important factors controlling temperature sensitivity of soil respiration. The highest temperature sensitivity of soil respiration was observed when substrate release was temperature dependent and C substrate concentration was much lower than Ks. Increase of substrate content to the half-saturation constant by glucose addition resulted in temperature acclimation associated with the canceling effect. Addition of the substrate to the level providing respiration at a maximal rate Vmax leads to the acclimation of the whole microbial community as such. However, growing microbial biomass was more sensitive to the temperature alterations. This study improves our understanding of the instability of temperature sensitivity of soil respiration under field conditions, attributing this phenomenon to changes in concentration of readily decomposable C substrate.

  17. Quantification of birefringence readily measures the level of muscle damage in zebrafish

    International Nuclear Information System (INIS)

    Berger, Joachim; Sztal, Tamar; Currie, Peter D.

    2012-01-01

    Highlights: ► Report of an unbiased quantification of the birefringence of muscle of fish larvae. ► Quantification method readily identifies level of overall muscle damage. ► Compare zebrafish muscle mutants for level of phenotype severity. ► Proposed tool to survey treatments that aim to ameliorate muscular dystrophy. -- Abstract: Muscular dystrophies are a group of genetic disorders that progressively weaken and degenerate muscle. Many zebrafish models for human muscular dystrophies have been generated and analysed, including dystrophin-deficient zebrafish mutants dmd that model Duchenne Muscular Dystrophy. Under polarised light the zebrafish muscle can be detected as a bright area in an otherwise dark background. This light effect, called birefringence, results from the diffraction of polarised light through the pseudo-crystalline array of the muscle sarcomeres. Muscle damage, as seen in zebrafish models for muscular dystrophies, can readily be detected by a reduction in the birefringence. Therefore, birefringence is a very sensitive indicator of overall muscle integrity within larval zebrafish. Unbiased documentation of the birefringence followed by densitometric measurement enables the quantification of the birefringence of zebrafish larvae. Thereby, the overall level of muscle integrity can be detected, allowing the identification and categorisation of zebrafish muscle mutants. In addition, we propose that the establish protocol can be used to analyse treatments aimed at ameliorating dystrophic zebrafish models.

  18. Application of Observed Precipitation in NCEP Global and Regional Data Assimilation Systems, Including Reanalysis and Land Data Assimilation

    Science.gov (United States)

    Mitchell, K. E.

    2006-12-01

    The Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) applies several different analyses of observed precipitation in both the data assimilation and validation components of NCEP's global and regional numerical weather and climate prediction/analysis systems (including in NCEP global and regional reanalysis). This invited talk will survey these data assimilation and validation applications and methodologies, as well as the temporal frequency, spatial domains, spatial resolution, data sources, data density and data quality control in the precipitation analyses that are applied. Some of the precipitation analyses applied by EMC are produced by NCEP's Climate Prediction Center (CPC), while others are produced by the River Forecast Centers (RFCs) of the National Weather Service (NWS), or by automated algorithms of the NWS WSR-88D Radar Product Generator (RPG). Depending on the specific type of application in data assimilation or model forecast validation, the temporal resolution of the precipitation analyses may be hourly, daily, or pentad (5-day) and the domain may be global, continental U.S. (CONUS), or Mexico. The data sources for precipitation include ground-based gauge observations, radar-based estimates, and satellite-based estimates. The precipitation analyses over the CONUS are analyses of either hourly, daily or monthly totals of precipitation, and they are of two distinct types: gauge-only or primarily radar-estimated. The gauge-only CONUS analysis of daily precipitation utilizes an orographic-adjustment technique (based on the well-known PRISM precipitation climatology of Oregon State University) developed by the NWS Office of Hydrologic Development (OHD). The primary NCEP global precipitation analysis is the pentad CPC Merged Analysis of Precipitation (CMAP), which blends both gauge observations and satellite estimates. The presentation will include a brief comparison between the CMAP analysis and other global

  19. Sources

    International Nuclear Information System (INIS)

    Duffy, L.P.

    1991-01-01

    This paper discusses the sources of radiation in the narrow perspective of radioactivity and the even narrow perspective of those sources that concern environmental management and restoration activities at DOE facilities, as well as a few related sources. Sources of irritation, Sources of inflammatory jingoism, and Sources of information. First, the sources of irritation fall into three categories: No reliable scientific ombudsman to speak without bias and prejudice for the public good, Technical jargon with unclear definitions exists within the radioactive nomenclature, and Scientific community keeps a low-profile with regard to public information. The next area of personal concern are the sources of inflammation. This include such things as: Plutonium being described as the most dangerous substance known to man, The amount of plutonium required to make a bomb, Talk of transuranic waste containing plutonium and its health affects, TMI-2 and Chernobyl being described as Siamese twins, Inadequate information on low-level disposal sites and current regulatory requirements under 10 CFR 61, Enhanced engineered waste disposal not being presented to the public accurately. Numerous sources of disinformation regarding low level radiation high-level radiation, Elusive nature of the scientific community, The Federal and State Health Agencies resources to address comparative risk, and Regulatory agencies speaking out without the support of the scientific community

  20. Covariance Function for Nearshore Wave Assimilation Systems

    Science.gov (United States)

    2018-01-30

    which is applicable for any spectral wave model. The four dimensional variational (4DVar) assimilation methods are based on the mathematical ...covariance can be modeled by a parameterized Gaussian function, for nearshore wave assimilation applications , the covariance function depends primarily on...SPECTRAL ACTION DENSITY, RESPECTIVELY. ............................ 5 FIGURE 2. TOP ROW: STATISTICAL ANALYSIS OF THE WAVE-FIELD PROPERTIES AT THE

  1. Data assimilation a mathematical introduction

    CERN Document Server

    Law, Kody; Zygalakis, Konstantinos

    2015-01-01

    This book provides a systematic treatment of the mathematical underpinnings of work in data assimilation, covering both theoretical and computational approaches. Specifically the authors develop a unified mathematical framework in which a Bayesian formulation of the problem provides the bedrock for the derivation, development and analysis of algorithms; the many examples used in the text, together with the algorithms which are introduced and discussed, are all illustrated by the MATLAB software detailed in the book and made freely available online. The book is organized into nine chapters: the first contains a brief introduction to the mathematical tools around which the material is organized; the next four are concerned with discrete time dynamical systems and discrete time data; the last four are concerned with continuous time dynamical systems and continuous time data and are organized analogously to the corresponding discrete time chapters. This book is aimed at mathematical researchers interested in a sy...

  2. Effective assimilation of global precipitation: simulation experiments

    Directory of Open Access Journals (Sweden)

    Guo-Yuan Lien

    2013-07-01

    Full Text Available Past attempts to assimilate precipitation by nudging or variational methods have succeeded in forcing the model precipitation to be close to the observed values. However, the model forecasts tend to lose their additional skill after a few forecast hours. In this study, a local ensemble transform Kalman filter (LETKF is used to effectively assimilate precipitation by allowing ensemble members with better precipitation to receive higher weights in the analysis. In addition, two other changes in the precipitation assimilation process are found to alleviate the problems related to the non-Gaussianity of the precipitation variable: (a transform the precipitation variable into a Gaussian distribution based on its climatological distribution (an approach that could also be used in the assimilation of other non-Gaussian observations and (b only assimilate precipitation at the location where at least some ensemble members have precipitation. Unlike many current approaches, both positive and zero rain observations are assimilated effectively. Observing system simulation experiments (OSSEs are conducted using the Simplified Parametrisations, primitivE-Equation DYnamics (SPEEDY model, a simplified but realistic general circulation model. When uniformly and globally distributed observations of precipitation are assimilated in addition to rawinsonde observations, both the analyses and the medium-range forecasts of all model variables, including precipitation, are significantly improved as compared to only assimilating rawinsonde observations. The effect of precipitation assimilation on the analyses is retained on the medium-range forecasts and is larger in the Southern Hemisphere (SH than that in the Northern Hemisphere (NH because the NH analyses are already made more accurate by the denser rawinsonde stations. These improvements are much reduced when only the moisture field is modified by the precipitation observations. Both the Gaussian transformation and

  3. Readily releasable pool of synaptic vesicles measured at single synaptic contacts.

    Science.gov (United States)

    Trigo, Federico F; Sakaba, Takeshi; Ogden, David; Marty, Alain

    2012-10-30

    To distinguish between different models of vesicular release in brain synapses, it is necessary to know the number of vesicles of transmitter that can be released immediately at individual synapses by a high-calcium stimulus, the readily releasable pool (RRP). We used direct stimulation by calcium uncaging at identified, single-site inhibitory synapses to investigate the statistics of vesicular release and the size of the RRP. Vesicular release, detected as quantal responses in the postsynaptic neuron, showed an unexpected stochastic variation in the number of quanta from stimulus to stimulus at high intracellular calcium, with a mean of 1.9 per stimulus and a maximum of three or four. The results provide direct measurement of the RRP at single synaptic sites. They are consistent with models in which release proceeds from a small number of vesicle docking sites with an average occupancy around 0.7.

  4. The non-steroidal anti-inflammatory drug diclofenac is readily biodegradable in agricultural soils

    International Nuclear Information System (INIS)

    Al-Rajab, Abdul Jabbar; Sabourin, Lyne; Lapen, David R.; Topp, Edward

    2010-01-01

    Diclofenac, 2-[2-[(2,6-dichlorophenyl)amino]phenyl]acetic acid, is an important non-steroidal anti-inflammatory drug widely used for human and animals to reduce inflammation and pain. Diclofenac could potentially reach agricultural lands through the application of municipal biosolids or wastewater, and in the absence of any environmental fate data, we evaluated its persistence in agricultural soils incubated in the laboratory. 14 C-Diclofenac was rapidly mineralized without a lag when added to soils varying widely in texture (sandy loam, loam, clay loam). Over a range of temperature and moisture conditions extractable 14 C-diclofenac residues decreased with half lives < 5 days. No extractable transformation products were detectable by HPLC. Diclofenac mineralization in the loam soil was abolished by heat sterilization. Addition of biosolids to sterile or non-sterile soil did not accelerate the dissipation of diclofenac. These findings indicate that diclofenac is readily biodegradable in agricultural soils.

  5. The non-steroidal anti-inflammatory drug diclofenac is readily biodegradable in agricultural soils

    Energy Technology Data Exchange (ETDEWEB)

    Al-Rajab, Abdul Jabbar; Sabourin, Lyne [Agriculture and Agri-Food Canada, London, ON, Canada N5V 4T3 (Canada); Lapen, David R. [Agriculture and Agri-Food Canada, Ottawa ON, Canada K1A 0C6 (Canada); Topp, Edward, E-mail: ed.topp@agr.gc.ca [Agriculture and Agri-Food Canada, London, ON, Canada N5V 4T3 (Canada)

    2010-12-01

    Diclofenac, 2-[2-[(2,6-dichlorophenyl)amino]phenyl]acetic acid, is an important non-steroidal anti-inflammatory drug widely used for human and animals to reduce inflammation and pain. Diclofenac could potentially reach agricultural lands through the application of municipal biosolids or wastewater, and in the absence of any environmental fate data, we evaluated its persistence in agricultural soils incubated in the laboratory. {sup 14}C-Diclofenac was rapidly mineralized without a lag when added to soils varying widely in texture (sandy loam, loam, clay loam). Over a range of temperature and moisture conditions extractable {sup 14}C-diclofenac residues decreased with half lives < 5 days. No extractable transformation products were detectable by HPLC. Diclofenac mineralization in the loam soil was abolished by heat sterilization. Addition of biosolids to sterile or non-sterile soil did not accelerate the dissipation of diclofenac. These findings indicate that diclofenac is readily biodegradable in agricultural soils.

  6. Temperature response of soil respiration is dependent on concentration of readily decomposable C

    Directory of Open Access Journals (Sweden)

    A. A. Larionova

    2007-12-01

    Full Text Available Temperature acclimation of soil organic matter (SOM decomposition is one of the major uncertainties in predicting soil CO2 efflux associated with the increase in global mean temperature. A reasonable explanation for an apparent acclimation proposed by Davidson and colleagues (2006 based on Michaelis-Menten kinetics suggests that temperature sensitivity decreases when both maximal activity of respiratory enzymes (Vmax and half-saturation constant (Ks cancel each other upon temperature increase. We tested the hypothesis of the canceling effect by the mathematical simulation of data obtained in incubation experiments with forest and arable soils. Our data support the hypothesis and suggest that concentration of readily decomposable C substrate (as glucose equivalents and temperature dependent substrate release are the important factors controlling temperature sensitivity of soil respiration. The highest temperature sensitivity of soil respiration was observed when substrate release was temperature dependent and C substrate concentration was much lower than Ks. Increase of substrate content to the half-saturation constant by glucose addition resulted in temperature acclimation associated with the canceling effect. Addition of the substrate to the level providing respiration at a maximal rate Vmax leads to the acclimation of the whole microbial community as such. However, growing microbial biomass was more sensitive to the temperature alterations. This study improves our understanding of the instability of temperature sensitivity of soil respiration under field conditions, attributing this phenomenon to changes in concentration of readily decomposable C substrate.

  7. sources

    Directory of Open Access Journals (Sweden)

    Shu-Yin Chiang

    2002-01-01

    Full Text Available In this paper, we study the simplified models of the ATM (Asynchronous Transfer Mode multiplexer network with Bernoulli random traffic sources. Based on the model, the performance measures are analyzed by the different output service schemes.

  8. Advanced Data Assimilation for Geosciences : Lecture Notes of the Les Houches School of Physics

    CERN Document Server

    Bocquet, Marc; Cosme, Emmanuel; Cugliandolo, Leticia F

    2014-01-01

    This book gathers notes from lectures and seminars given during a three-week school on theoretical and applied data assimilation held in Les Houches in 2012. Data assimilation aims at determining as accurately as possible the state of a dynamical system by combining heterogeneous sources of information in an optimal way. Generally speaking, the mathematical methods of data assimilation describe algorithms for forming optimal combinations of observations of a system, a numerical model that describes its evolution, and appropriate prior information. Data assimilation has a long history of application to high-dimensional geophysical systems dating back to the 1960s, with application to the estimation of initial conditions for weather forecasts. It has become a major component of numerical forecasting systems in geophysics, and an intensive field of research, with numerous additional applications in oceanography and atmospheric chemistry, with extensions to other geophysical sciences. The physical complexity and ...

  9. Skill Assessment in Ocean Biological Data Assimilation

    Science.gov (United States)

    Gregg, Watson W.; Friedrichs, Marjorie A. M.; Robinson, Allan R.; Rose, Kenneth A.; Schlitzer, Reiner; Thompson, Keith R.; Doney, Scott C.

    2008-01-01

    There is growing recognition that rigorous skill assessment is required to understand the ability of ocean biological models to represent ocean processes and distributions. Statistical analysis of model results with observations represents the most quantitative form of skill assessment, and this principle serves as well for data assimilation models. However, skill assessment for data assimilation requires special consideration. This is because there are three sets of information in the free-run model, data, and the assimilation model, which uses Data assimilation information from both the flee-run model and the data. Intercom parison of results among the three sets of information is important and useful for assessment, but is not conclusive since the three information sets are intertwined. An independent data set is necessary for an objective determination. Other useful measures of ocean biological data assimilation assessment include responses of unassimilated variables to the data assimilation, performance outside the prescribed region/time of interest, forecasting, and trend analysis. Examples of each approach from the literature are provided. A comprehensive list of ocean biological data assimilation and their applications of skill assessment, in both ecosystem/biogeochemical and fisheries efforts, is summarized.

  10. You are not always what we think you eat. Selective assimilation across multiple whole-stream isotopic tracer studies

    International Nuclear Information System (INIS)

    Dodds, W. K.; Collins, S. M.; Hamilton, S. K.; Johnson, S.; Webster, J. R.; Simon, K. S.; Whiles, M. R.; Rantala, H. M.; McDowell, W. H.; Peterson, S. D.; Riis, T.; Crenshaw, C. L.; Thomas, S. A.; Kristensen, P. B.; Cheever, B. M.; Flecker, A. S.; Griffiths, N. A.; Crowl, T.; Rosi-Marshall, E. J.; El-Sabaawi, R.; Marti, E.

    2014-01-01

    Analyses of 21 15 N stable isotope tracer experiments, designed to examine food web dynamics in streams around the world, indicated that the isotopic composition of food resources assimilated by primary consumers (mostly invertebrates) poorly reflected the presumed food sources. Modeling indicated that consumers assimilated only 33-50% of the N available in sampled food sources such as decomposing leaves, epilithon, and fine particulate detritus over feeding periods of weeks or more. Thus, common methods of sampling food sources consumed by animals in streams do not sufficiently reflect the pool of N they assimilate. Lastly, Isotope tracer studies, combined with modeling and food separation techniques, can improve estimation of N pools in food sources that are assimilated by consumers

  11. Multisensor on-the-go mapping of readily dispersible clay, particle size and soil organic matter

    Science.gov (United States)

    Debaene, Guillaume; Niedźwiecki, Jacek; Papierowska, Ewa

    2016-04-01

    Particle size fractions affect strongly the physical and chemical properties of soil. Readily dispersible clay (RDC) is the part of the clay fraction in soils that is easily or potentially dispersible in water when small amounts of mechanical energy are applied to soil. The amount of RDC in the soil is of significant importance for agriculture and environment because clay dispersion is a cause of poor soil stability in water which in turn contributes to soil erodibility, mud flows, and cementation. To obtain a detailed map of soil texture, many samples are needed. Moreover, RDC determination is time consuming. The use of a mobile visible and near-infrared (VIS-NIR) platform is proposed here to map those soil properties and obtain the first detailed map of RDC at field level. Soil properties prediction was based on calibration model developed with 10 representative samples selected by a fuzzy logic algorithm. Calibration samples were analysed for soil texture (clay, silt and sand), RDC and soil organic carbon (SOC) using conventional wet chemistry analysis. Moreover, the Veris mobile sensor platform is also collecting electrical conductivity (EC) data (deep and shallow), and soil temperature. These auxiliary data were combined with VIS-NIR measurement (data fusion) to improve prediction results. EC maps were also produced to help understanding RDC data. The resulting maps were visually compared with an orthophotography of the field taken at the beginning of the plant growing season. Models were developed with partial least square regression (PLSR) and support vector machine regression (SVMR). There were no significant differences between calibration using PLSR or SVMR. Nevertheless, the best models were obtained with PLSR and standard normal variate (SNV) pretreatment and the fusion with deep EC data (e.g. for RDC and clay content: RMSECV = 0,35% and R2 = 0,71; RMSECV = 0,32% and R2 = 0,73 respectively). The best models were used to predict soil properties from the

  12. Data Assimilation with Optimal Maps

    Science.gov (United States)

    El Moselhy, T.; Marzouk, Y.

    2012-12-01

    Tarek El Moselhy and Youssef Marzouk Massachusetts Institute of Technology We present a new approach to Bayesian inference that entirely avoids Markov chain simulation and sequential importance resampling, by constructing a map that pushes forward the prior measure to the posterior measure. Existence and uniqueness of a suitable measure-preserving map is established by formulating the problem in the context of optimal transport theory. The map is written as a multivariate polynomial expansion and computed efficiently through the solution of a stochastic optimization problem. While our previous work [1] focused on static Bayesian inference problems, we now extend the map-based approach to sequential data assimilation, i.e., nonlinear filtering and smoothing. One scheme involves pushing forward a fixed reference measure to each filtered state distribution, while an alternative scheme computes maps that push forward the filtering distribution from one stage to the other. We compare the performance of these schemes and extend the former to problems of smoothing, using a map implementation of the forward-backward smoothing formula. Advantages of a map-based representation of the filtering and smoothing distributions include analytical expressions for posterior moments and the ability to generate arbitrary numbers of independent uniformly-weighted posterior samples without additional evaluations of the dynamical model. Perhaps the main advantage, however, is that the map approach inherently avoids issues of sample impoverishment, since it explicitly represents the posterior as the pushforward of a reference measure, rather than with a particular set of samples. The computational complexity of our algorithm is comparable to state-of-the-art particle filters. Moreover, the accuracy of the approach is controlled via the convergence criterion of the underlying optimization problem. We demonstrate the efficiency and accuracy of the map approach via data assimilation in

  13. Enhancement of methyl tert-butyl ether degradation by the addition of readily metabolizable organic substrates

    International Nuclear Information System (INIS)

    Chen Dongzhi; Chen Jianmeng; Zhong Weihong

    2009-01-01

    Supplements with readily metabolizable organic substrates were investigated to increase the biomass and enhance degradation of methyl tert-butyl ether (MTBE) due to the low biomass yield of MTBE which has been one of the factors for low-rate MTBE degradation. The influence of various organic substrates on the rate of aerobic degradation of methyl tert-butyl ether (MTBE) by Methylibium petroleiphilum PM1 was investigated, and only yeast extract (YE), beef extract and tryptone exhibited stimulatory effect. With the concentration of each substrate being 100 mg/L, the average MTBE removal rate could increase to 1.29, 1.20 and 1.04 mg/(L h), respectively, in comparison with 0.71 mg/(L h) when carried out in medium without addition. The stimulatory effects of YE addition, as well as induction period required by MTBE degradation, varied dramatically with the storage conditions, pre-culture medium and concentrations of the inoculums. The extent of stimulatory effects of YE might be closely related to the proportion of induction period in the total time of MTBE-degradation. The removal efficiency increased from about 50% to 90.5% with the addition of YE in a packed-bed reactor loaded with calcium alginate immobilized cells.

  14. A natural and readily available crowding agent: NMR studies of proteins in hen egg white.

    Science.gov (United States)

    Martorell, Gabriel; Adrover, Miquel; Kelly, Geoff; Temussi, Piero Andrea; Pastore, Annalisa

    2011-05-01

    In vitro studies of biological macromolecules are usually performed in dilute, buffered solutions containing one or just a few different biological macromolecules. Under these conditions, the interactions among molecules are diffusion limited. On the contrary, in living systems, macromolecules of a given type are surrounded by many others, at very high total concentrations. In the last few years, there has been an increasing effort to study biological macromolecules directly in natural crowded environments, as in intact bacterial cells or by mimicking natural crowding by adding proteins, polysaccharides, or even synthetic polymers. Here, we propose the use of hen egg white (HEW) as a simple natural medium, with all features of the media of crowded cells, that could be used by any researcher without difficulty and inexpensively. We present a study of the stability and dynamics behavior of model proteins in HEW, chosen as a prototypical, readily accessible natural medium that can mimic cytosol. We show that two typical globular proteins, dissolved in HEW, give NMR spectra very similar to those obtained in dilute buffers, although dynamic parameters are clearly affected by the crowded medium. The thermal stability of one of these proteins, measured in a range comprising both heat and cold denaturation, is also similar to that in buffer. Our data open new possibilities to the study of proteins in natural crowded media. Copyright © 2010 Wiley-Liss, Inc.

  15. Immigrants' continuing bonds with their native culture: assimilation analysis of three interviews.

    Science.gov (United States)

    Henry, Hani M; Stiles, William B; Biran, Mia W; Mosher, James K; Brinegar, Meredith Glick; Banerjee, Prashant

    2009-06-01

    Three case studies of immigrants to the US from China, Iraq, and Mexico were used to build a theory of acculturation in immigrants by integrating the continuing bonds model, which describes mourning in bereavement with the assimilation model, which describes psychological change in psychotherapy. Participants were interviewed about the loss of their native culture and their life in the US. One participant had not fully assimilated the loss of her native culture, but used her continuing bonds with her culture as a source of solace. Another participant used his continuing bonds with his culture as a source of solace, but these bonds had become a source of conflict with the host culture. The third participant had largely assimilated the loss of his native culture such that the voices of this culture were linked via meaning bridges with the voices of the host culture, and the continuing bonds were resources that helped him in his land of immigration.

  16. The importance of peers: assimilation patterns among second-generation Turkish immigrants in Western Europe

    NARCIS (Netherlands)

    Ali, S.; Fokkema, C.M.

    2011-01-01

    The two dominant approaches to immigrant assimilation, segmented assimilation and "new" assimilation theories, have been successful at reporting and analyzing between-group differences in assimilation patterns. However, studies of assimilation generally do not address differences at the individual

  17. Assimilative and non-assimilative color spreading in the watercolor configuration

    Directory of Open Access Journals (Sweden)

    Eiji eKimura

    2014-09-01

    Full Text Available A colored line flanking a darker contour will appear to spread its color onto an area enclosed by the line (watercolor effect. The watercolor effect has been characterized as an assimilative effect, but non-assimilative color spreading has also been demonstrated in the same spatial configuration; e.g., when a black inner contour (IC is paired with a blue outer contour (OC, yellow color spreading can be observed. To elucidate visual mechanisms underlying these different color spreading effects, this study investigated the effects of luminance ratio between the double contours on the induced color by systematically manipulating the IC and OC luminances (Experiment 1 as well as the background luminance (Experiment 2. The results showed that the luminance conditions suitable for assimilative and non-assimilative color spreading were nearly opposite. When the Weber contrast of the IC to the background luminances (IC contrast was smaller than that of the OC (OC contrast, the induced color became similar to the IC color (assimilative spreading. In contrast, when the OC contrast was smaller than or equal to the IC contrast, the induced color became yellow (non-assimilative spreading. Extending these findings, Experiment 3 showed that bilateral color spreading, e.g., assimilative spreading on one side and non-assimilative spreading on the other side, can also be observed in the watercolor configuration. These results suggest that the assimilative and non-assimilative spreading were mediated by different visual mechanisms. The properties of the assimilative spreading are consistent with the model proposed to account for neon color spreading [Grossberg, S. & Mingolla, E. (1985 Percept. Psychophys., 38, 141-171] and extended for the watercolor effect [Pinna, B., & Grossberg, S. (2005 J. Opt. Soc. Am. A, 22, 2207-2221]. However, the present results suggest that additional mechanisms are needed to account for the non-assimilative color spreading.

  18. Assimilative and non-assimilative color spreading in the watercolor configuration.

    Science.gov (United States)

    Kimura, Eiji; Kuroki, Mikako

    2014-01-01

    A colored line flanking a darker contour will appear to spread its color onto an area enclosed by the line (watercolor effect). The watercolor effect has been characterized as an assimilative effect, but non-assimilative color spreading has also been demonstrated in the same spatial configuration; e.g., when a black inner contour (IC) is paired with a blue outer contour (OC), yellow color spreading can be observed. To elucidate visual mechanisms underlying these different color spreading effects, this study investigated the effects of luminance ratio between the double contours on the induced color by systematically manipulating the IC and the OC luminance (Experiment 1) as well as the background luminance (Experiment 2). The results showed that the luminance conditions suitable for assimilative and non-assimilative color spreading were nearly opposite. When the Weber contrast of the IC to the background luminance (IC contrast) was smaller in size than that of the OC (OC contrast), the induced color became similar to the IC color (assimilative spreading). In contrast, when the OC contrast was smaller than or equal to the IC contrast, the induced color became yellow (non-assimilative spreading). Extending these findings, Experiment 3 showed that bilateral color spreading, i.e., assimilative spreading on one side and non-assimilative spreading on the other side, can also be observed in the watercolor configuration. These results suggest that the assimilative and the non-assimilative spreading were mediated by different visual mechanisms. The properties of the assimilative spreading are consistent with the model proposed to account for neon color spreading (Grossberg and Mingolla, 1985) and extended for the watercolor effect (Pinna and Grossberg, 2005). However, the present results suggest that additional mechanisms are needed to account for the non-assimilative color spreading.

  19. Error Covariance Estimation of Mesoscale Data Assimilation

    National Research Council Canada - National Science Library

    Xu, Qin

    2005-01-01

    The goal of this project is to explore and develop new methods of error covariance estimation that will provide necessary statistical descriptions of prediction and observation errors for mesoscale data assimilation...

  20. ERP ASSIMILATION: AN END-USER APPROACH

    Directory of Open Access Journals (Sweden)

    Hurbean Luminita

    2013-07-01

    The paper discusses the ERP adoption based on the IT assimilation theory. The ERP lifecycle is associated with the IT assimilation steps. We propose a distribution of these steps along the lifecycle. Derived from the findings in the reviewed literature we will focus the cultural factors, in particular those related to the end-users (determined as a major impact factor in our previous study: Negovan et al., 2011. Our empirical study is centred on the end-users perspective and it tries to determine if and how their behaviour affects the achievement of the ERP assimilation steps. The paper reasons that organizations that understand the IT assimilation steps correlated to the ERP implementation critical factors are more likely to implement and use ERP successfully.

  1. Comparison between assimilated and non-assimilated experiments of the MACCii global reanalysis near surface ozone

    Science.gov (United States)

    Tsikerdekis, Athanasios; Katragou, Eleni; Zanis, Prodromos; Melas, Dimitrios; Eskes, Henk; Flemming, Johannes; Huijnen, Vincent; Inness, Antje; Kapsomenakis, Ioannis; Schultz, Martin; Stein, Olaf; Zerefos, Christos

    2014-05-01

    In this work we evaluate near surface ozone concentrations of the MACCii global reanalysis using measurements from the EMEP and AIRBASE database. The eight-year long reanalysis of atmospheric composition data covering the period 2003-2010 was constructed as part of the FP7-funded Monitoring Atmospheric Composition and Climate project by assimilating satellite data into a global model and data assimilation system (Inness et al., 2013). The study mainly focuses in the differences between the assimilated and the non-assimilated experiments and aims to identify and quantify any improvements achieved by adding data assimilation to the system. Results are analyzed in eight European sub-regions and region-specific Taylor plots illustrate the evaluation and the overall predictive skill of each experiment. The diurnal and annual cycles of near surface ozone are evaluated for both experiments. Furthermore ozone exposure indices for crop growth (AOT40), human health (SOMO35) and the number of days that 8-hour ozone averages exceeded 60ppb and 90ppb have been calculated for each station based on both observed and simulated data. Results indicate mostly improvement of the assimilated experiment with respect to the high near surface ozone concentrations, the diurnal cycle and range and the bias in comparison to the non-assimilated experiment. The limitations of the comparison between assimilated and non-assimilated experiments for near surface ozone are also discussed.

  2. Assimilation of Baba and Nyonya in Malaysia

    OpenAIRE

    Razaleigh Muhamat Kawangit

    2015-01-01

    This research set outs to explore the exact level of the social aspect of assimilation between Baba and Nyonya and their Malay counterparts in Malaysia. It was sure that assimilation in social aspect is a dilemma which Baba and Nyonya face when they interact with Malays as a dominant ethnic group. It suggests that when the process of interaction, their behavior changes in line with the identity of the Malays. This is because the majority influenced the minority in the Malaysian context. Whils...

  3. Computational methods for data evaluation and assimilation

    CERN Document Server

    Cacuci, Dan Gabriel

    2013-01-01

    Data evaluation and data combination require the use of a wide range of probability theory concepts and tools, from deductive statistics mainly concerning frequencies and sample tallies to inductive inference for assimilating non-frequency data and a priori knowledge. Computational Methods for Data Evaluation and Assimilation presents interdisciplinary methods for integrating experimental and computational information. This self-contained book shows how the methods can be applied in many scientific and engineering areas. After presenting the fundamentals underlying the evaluation of experiment

  4. Temporal Reference, Attentional Modulation, and Crossmodal Assimilation

    Directory of Open Access Journals (Sweden)

    Yingqi Wan

    2018-06-01

    Full Text Available Crossmodal assimilation effect refers to the prominent phenomenon by which ensemble mean extracted from a sequence of task-irrelevant distractor events, such as auditory intervals, assimilates/biases the perception (such as visual interval of the subsequent task-relevant target events in another sensory modality. In current experiments, using visual Ternus display, we examined the roles of temporal reference, materialized as the time information accumulated before the onset of target event, as well as the attentional modulation in crossmodal temporal interaction. Specifically, we examined how the global time interval, the mean auditory inter-intervals and the last interval in the auditory sequence assimilate and bias the subsequent percept of visual Ternus motion (element motion vs. group motion. We demonstrated that both the ensemble (geometric mean and the last interval in the auditory sequence contribute to bias the percept of visual motion. Longer mean (or last interval elicited more reports of group motion, whereas the shorter mean (or last auditory intervals gave rise to more dominant percept of element motion. Importantly, observers have shown dynamic adaptation to the temporal reference of crossmodal assimilation: when the target visual Ternus stimuli were separated by a long gap interval after the preceding sound sequence, the assimilation effect by ensemble mean was reduced. Our findings suggested that crossmodal assimilation relies on a suitable temporal reference on adaptation level, and revealed a general temporal perceptual grouping principle underlying complex audio-visual interactions in everyday dynamic situations.

  5. Data Assimilation: Making Sense of Earth Observation

    Directory of Open Access Journals (Sweden)

    William Albert Lahoz

    2014-05-01

    Full Text Available Climate change, air quality and environmental degradation are important societal challenges for the 21st Century. These challenges require an intelligent response from society, which in turn requires access to information about the Earth System. This information comes from observations and prior knowledge, the latter typically embodied in a model describing relationships between variables of the Earth System. Data assimilation provides an objective methodology to combine observational and model information to provide an estimate of the most likely state and its uncertainty for the whole Earth System. This approach adds value to the observations – by filling in the spatio-temporal gaps in observations; and to the model – by constraining it with the observations. In this review paper we motivate data assimilation as a methodology to fill in the gaps in observational information; illustrate the data assimilation approach with examples that span a broad range of features of the Earth System (atmosphere, including chemistry; ocean; land surface; and discuss the outlook for data assimilation, including the novel application of data assimilation ideas to observational information obtained using Citizen Science. Ultimately, a strong motivation of data assimilation is the many benefits it provides to users. These include: providing the initial state for weather and air quality forecasts; providing analyses and reanalyses for studying the Earth System; evaluating observations, instruments and models; assessing the relative value of elements of the Global Observing System (GOS; and assessing the added value of future additions to the GOS.

  6. Readily Identifiable Risk Factors of Nursing Home Residents' Oral Hygiene: Dementia, Hospice, and Length of Stay.

    Science.gov (United States)

    Zimmerman, Sheryl; Austin, Sophie; Cohen, Lauren; Reed, David; Poole, Patricia; Ward, Kimberly; Sloane, Philip D

    2017-11-01

    The poor oral hygiene of nursing home (NH) residents is a matter of increasing concern, especially because of its relationship with pneumonia and other health events. Because details and related risk factors in this area are scant and providers need to be able to easily identify those residents at most risk, this study comprehensively examined the plaque, gingival, and denture status of NH residents, as well as readily available correlates of those indicators of oral hygiene, including items from the Minimum Data Set (MDS). Oral hygiene assessment and chart abstract conducted on a cross-section of NH residents. NHs in North Carolina (N = 14). NH residents (N = 506). Descriptive data from the MDS and assessments using three standardized measures: the Plaque Index for Long-Term Care (PI-LTC), the Gingival Index for Long-Term Care (GI-LTC), and the Denture Plaque Index (DPI). Oral hygiene scores averaged 1.7 (of 3) for the PI-LTC, 1.5 (of 4) for the GI-LTC, and 2.2 (of 4) for the DPI. Factors most strongly associated with poor oral hygiene scores included having dementia, being on hospice care, and longer stay. MDS ratings of gingivitis differed significantly from oral hygiene assessments. The findings identify resident subgroups at especially high risk of poor oral health who can be targeted in quality improvement efforts related to oral hygiene; they also indicate need to improve the accuracy of how MDS items are completed. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

  7. Use of Readily Accessible Inflammatory Markers to Predict Diabetic Kidney Disease

    Directory of Open Access Journals (Sweden)

    Lauren Winter

    2018-05-01

    Full Text Available Diabetic kidney disease is a common complication of type 1 and type 2 diabetes and is the primary cause of end-stage renal disease in developed countries. Early detection of diabetic kidney disease will facilitate early intervention aimed at reducing the rate of progression to end-stage renal disease. Diabetic kidney disease has been traditionally classified based on the presence of albuminuria. More recently estimated glomerular filtration rate has also been incorporated into the staging of diabetic kidney disease. While albuminuric diabetic kidney disease is well described, the phenotype of non-albuminuric diabetic kidney disease is now widely accepted. An association between markers of inflammation and diabetic kidney disease has previously been demonstrated. Effector molecules of the innate immune system including C-reactive protein, interleukin-6, and tumor necrosis factor-α are increased in patients with diabetic kidney disease. Furthermore, renal infiltration of neutrophils, macrophages, and lymphocytes are observed in renal biopsies of patients with diabetic kidney disease. Similarly high serum neutrophil and low serum lymphocyte counts have been shown to be associated with diabetic kidney disease. The neutrophil–lymphocyte ratio is considered a robust measure of systemic inflammation and is associated with the presence of inflammatory conditions including the metabolic syndrome and insulin resistance. Cross-sectional studies have demonstrated a link between high levels of the above inflammatory biomarkers and diabetic kidney disease. Further longitudinal studies will be required to determine if these readily available inflammatory biomarkers can accurately predict the presence and prognosis of diabetic kidney disease, above and beyond albuminuria, and estimated glomerular filtration rate.

  8. Effect of readily available water deficit in soil on maize yield and evapotranspiration

    Directory of Open Access Journals (Sweden)

    Pejić Borivoj

    2010-01-01

    Full Text Available An investigation was carried out at Rimski Šančevi experiment field of Institute of Field and Vegetable Crops, Novi Sad on calcareous chernozem soil on the loess terrace, in the period 2000-2007, and included irrigated variant (T1 and non-irrigated i.e. control variant (T0. NS-640, maize hybrid from the FAO maturity group 600, was analyzed. Readily available soil water deficit (RASWD in the layer of 60 cm in the course of growing season and actual evapotranspiration (ETa were calculated by the water balance method. Water consumption for potential evapotranspiration (ETm in individual months and the growing season were calculated by the bioclimatic procedure, using hydrophytothermic indexes. The correlation analysis revealed highly significant dependences of maize yield (Y on RASWD (r = -0.941 and the amount of precipitation (P in August (r = 0.931. Statistically significant dependence was also found between Y and RASWD (r = -0.765 and P (r = 0.768 in July and August. The obtained results indicate that maize production in Vojvodina under the rainfed conditions is unreliable, and that it is correlated with weather conditions, especially with the amount and distribution of precipitation. The statistically significant correlation obtained between Y and ETa (r = 0.755 confirms that water supply is the basic prerequisite which allows the other production factors to be realized. Significantly higher maize yields in the T1 variant (13.517 t ha-1 in relation to the T0 variant (11.210 t ha-1 indicate clearly that under the climatic conditions of Vojvodina high and stable yields of maize can be achieved only in irrigation. .

  9. Virtual screening using combinatorial cyclic peptide libraries reveals protein interfaces readily targetable by cyclic peptides.

    Science.gov (United States)

    Duffy, Fergal J; O'Donovan, Darragh; Devocelle, Marc; Moran, Niamh; O'Connell, David J; Shields, Denis C

    2015-03-23

    Protein-protein and protein-peptide interactions are responsible for the vast majority of biological functions in vivo, but targeting these interactions with small molecules has historically been difficult. What is required are efficient combined computational and experimental screening methods to choose among a number of potential protein interfaces worthy of targeting lead macrocyclic compounds for further investigation. To achieve this, we have generated combinatorial 3D virtual libraries of short disulfide-bonded peptides and compared them to pharmacophore models of important protein-protein and protein-peptide structures, including short linear motifs (SLiMs), protein-binding peptides, and turn structures at protein-protein interfaces, built from 3D models available in the Protein Data Bank. We prepared a total of 372 reference pharmacophores, which were matched against 108,659 multiconformer cyclic peptides. After normalization to exclude nonspecific cyclic peptides, the top hits notably are enriched for mimetics of turn structures, including a turn at the interaction surface of human α thrombin, and also feature several protein-binding peptides. The top cyclic peptide hits also cover the critical "hot spot" interaction sites predicted from the interaction crystal structure. We have validated our method by testing cyclic peptides predicted to inhibit thrombin, a key protein in the blood coagulation pathway of important therapeutic interest, identifying a cyclic peptide inhibitor with lead-like activity. We conclude that protein interfaces most readily targetable by cyclic peptides and related macrocyclic drugs may be identified computationally among a set of candidate interfaces, accelerating the choice of interfaces against which lead compounds may be screened.

  10. Estimation of readily-available phosphate in some English Lake District woodland soils

    International Nuclear Information System (INIS)

    Harrison, A.F.

    1975-01-01

    Four chemical extraction methods (2.5 percent acetic acid, Olsen, Truog and Egner) and 5 isotope dilution methods involving short exchange periods (1 inverse dilution, 2 carrier-free and 2 using phosphate carrier) were investigatd for reliability in measurement of readily-available phosphate in widely differing soils from some non-fertilized semi-natural Lake District woodlands. Correlation coefficients between values produced and phosphate uptake during a two-month period from 16 soils (pH range 3.85 to 7.85) by Urtica dioica L., a phosphate-sensitive plant, differed markedly. They were negative for all the extraction procedures, varying from r = -0.079 for the Truog method to -0.518 for the Olsen method. The isotope dilution methods, with the exception of one, all gave positive correlation coefficients, varying from r = -0.676 for the carrier-free method of Talibudeen to r = 0.798 for a modified Amer carrier method. When combined by multiple regression analysis, the results of the isotope dilution methods accounted for 86.4 percent of the variation in phosphate-uptake by the nettle plants, whereas the results of the four extraction methods accounted for only 32.2 percent. Multiple regression analysis of the data showed that there were strong and different interactions between all methods investigated and soil properties, particularly soil pH, organic matter content, extractable iron, C/P and C/N. This clearly indicates that methods must be evaluated for each series of soils to be compared. (author)

  11. Ensemble Kalman Filter data assimilation and storm surge experiments of tropical cyclone Nargis

    Directory of Open Access Journals (Sweden)

    Le Duc

    2015-07-01

    Full Text Available Data assimilation experiments on Myanmar tropical cyclone (TC, Nargis, using the Local Ensemble Transform Kalman Filter (LETKF method and the Japan Meteorological Agency (JMA non-hydrostatic model (NHM were performed to examine the impact of LETKF on analysis performance in real cases. Although the LETKF control experiment using NHM as its driving model (NHM–LETKF produced a weak vortex, the subsequent 3-day forecast predicted Nargis’ track and intensity better than downscaling from JMA's global analysis. Some strategies to further improve the final analysis were considered. They were sea surface temperature (SST perturbations and assimilation of TC advisories. To address SST uncertainty, SST analyses issued by operational forecast centres were used in the assimilation window. The use of a fixed source of SST analysis for each ensemble member was more effective in practice. SST perturbations were found to have slightly positive impact on the track forecasts. Assimilation of TC advisories could have a positive impact with a reasonable choice of its free parameters. However, the TC track forecasts exhibited northward displacements, when the observation error of intensities was underestimated in assimilation of TC advisories. The use of assimilation of TC advisories was considered in the final NHM–LETKF by choosing an appropriate set of free parameters. The extended forecast based on the final analysis provided meteorological forcings for a storm surge simulation using the Princeton Ocean Model. Probabilistic forecasts of the water levels at Irrawaddy and Yangon significantly improved the results in the previous studies.

  12. Simultaneous Radar and Satellite Data Storm-Scale Assimilation Using an Ensemble Kalman Filter Approach for 24 May 2011

    Science.gov (United States)

    Jones, Thomas A.; Stensrud, David; Wicker, Louis; Minnis, Patrick; Palikonda, Rabindra

    2015-01-01

    Assimilating high-resolution radar reflectivity and radial velocity into convection-permitting numerical weather prediction models has proven to be an important tool for improving forecast skill of convection. The use of satellite data for the application is much less well understood, only recently receiving significant attention. Since both radar and satellite data provide independent information, combing these two sources of data in a robust manner potentially represents the future of high-resolution data assimilation. This research combines Geostationary Operational Environmental Satellite 13 (GOES-13) cloud water path (CWP) retrievals with Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity and radial velocity to examine the impacts of assimilating each for a severe weather event occurring in Oklahoma on 24 May 2011. Data are assimilated into a 3-km model using an ensemble adjustment Kalman filter approach with 36 members over a 2-h assimilation window between 1800 and 2000 UTC. Forecasts are then generated for 90 min at 5-min intervals starting at 1930 and 2000 UTC. Results show that both satellite and radar data are able to initiate convection, but that assimilating both spins up a storm much faster. Assimilating CWP also performs well at suppressing spurious precipitation and cloud cover in the model as well as capturing the anvil characteristics of developed storms. Radar data are most effective at resolving the 3D characteristics of the core convection. Assimilating both satellite and radar data generally resulted in the best model analysis and most skillful forecast for this event.

  13. Mapping Surface Heat Fluxes by Assimilating SMAP Soil Moisture and GOES Land Surface Temperature Data

    Science.gov (United States)

    Lu, Yang; Steele-Dunne, Susan C.; Farhadi, Leila; van de Giesen, Nick

    2017-12-01

    Surface heat fluxes play a crucial role in the surface energy and water balance. In situ measurements are costly and difficult, and large-scale flux mapping is hindered by surface heterogeneity. Previous studies have demonstrated that surface heat fluxes can be estimated by assimilating land surface temperature (LST) and soil moisture to determine two key parameters: a neutral bulk heat transfer coefficient (CHN) and an evaporative fraction (EF). Here a methodology is proposed to estimate surface heat fluxes by assimilating Soil Moisture Active Passive (SMAP) soil moisture data and Geostationary Operational Environmental Satellite (GOES) LST data into a dual-source (DS) model using a hybrid particle assimilation strategy. SMAP soil moisture data are assimilated using a particle filter (PF), and GOES LST data are assimilated using an adaptive particle batch smoother (APBS) to account for the large gap in the spatial and temporal resolution. The methodology is implemented in an area in the U.S. Southern Great Plains. Assessment against in situ observations suggests that soil moisture and LST estimates are in better agreement with observations after assimilation. The RMSD for 30 min (daytime) flux estimates is reduced by 6.3% (8.7%) and 31.6% (37%) for H and LE on average. Comparison against a LST-only and a soil moisture-only assimilation case suggests that despite the coarse resolution, assimilating SMAP soil moisture data is not only beneficial but also crucial for successful and robust flux estimation, particularly when the uncertainties in the model estimates are large.

  14. Application of Bred Vectors To Data Assimilation

    Science.gov (United States)

    Corazza, M.; Kalnay, E.; Patil, Dj

    subspace. The presence of low-dimensional regions in the perturbations of the basic flow has important implications for data assimilation. At any given time, there is a difference between the true atmospheric state and the model forecast. Assuming that model er- rors are not the dominant source of errors, in a region of low BV-dimensionality the difference between the true state and the forecast should lie substantially in the low dimensional unstable subspace of the few bred vectors that contribute most strongly to the low BV-dimension. This information should yield a substantial improvement in the forecast: the data assimilation algorithm should correct the model state by moving it closer to the observations along the unstable subspace, since this is where the true state most likely lies. Preliminary experiments have been conducted with the quasi-geostrophic data assim- ilation system testing whether it is possible to add "errors of the day" based on bred vectors to the standard (constant) 3D-Var background error covariance in order to capture these important errors. The results are extremely encouraging, indicating a significant reduction (about 40%) in the analysis errors at a very low computational cost. References: 2 Corazza, M., E. Kalnay, DJ Patil, R. Morss, M Cai, I. Szunyogh, BR Hunt, E Ott and JA Yorke, 2001: Use of the breeding technique to estimate the structure of the analysis "errors of the day". Submitted to Nonlinear Processes in Geophysics. Hamill, T.M., Snyder, C., and Morss, R.E., 2000: A Comparison of Probabilistic Fore- casts from Bred, Singular-Vector and Perturbed Observation Ensembles, Mon. Wea. Rev., 128, 1835­1851. Kalnay, E., and Z. Toth, 1994: Removing growing errors in the analysis cycle. Preprints of the Tenth Conference on Numerical Weather Prediction, Amer. Meteor. Soc., 1994, 212-215. Morss, R. E., 1999: Adaptive observations: Idealized sampling strategies for improv- ing numerical weather prediction. PHD thesis, Massachussetts Institute

  15. Variational data assimilation schemes for transport and transformation models of atmospheric chemistry

    Science.gov (United States)

    Penenko, Alexey; Penenko, Vladimir; Tsvetova, Elena; Antokhin, Pavel

    2016-04-01

    The work is devoted to data assimilation algorithm for atmospheric chemistry transport and transformation models. In the work a control function is introduced into the model source term (emission rate) to provide flexibility to adjust to data. This function is evaluated as the constrained minimum of the target functional combining a control function norm with a norm of the misfit between measured data and its model-simulated analog. Transport and transformation processes model is acting as a constraint. The constrained minimization problem is solved with Euler-Lagrange variational principle [1] which allows reducing it to a system of direct, adjoint and control function estimate relations. This provides a physically-plausible structure of the resulting analysis without model error covariance matrices that are sought within conventional approaches to data assimilation. High dimensionality of the atmospheric chemistry models and a real-time mode of operation demand for computational efficiency of the data assimilation algorithms. Computational issues with complicated models can be solved by using a splitting technique. Within this approach a complex model is split to a set of relatively independent simpler models equipped with a coupling procedure. In a fine-grained approach data assimilation is carried out quasi-independently on the separate splitting stages with shared measurement data [2]. In integrated schemes data assimilation is carried out with respect to the split model as a whole. We compare the two approaches both theoretically and numerically. Data assimilation on the transport stage is carried out with a direct algorithm without iterations. Different algorithms to assimilate data on nonlinear transformation stage are compared. In the work we compare data assimilation results for both artificial and real measurement data. With these data we study the impact of transformation processes and data assimilation to the performance of the modeling system [3]. The

  16. LEAP into the Pfizer Global Virtual Library (PGVL) space: creation of readily synthesizable design ideas automatically.

    Science.gov (United States)

    Hu, Qiyue; Peng, Zhengwei; Kostrowicki, Jaroslav; Kuki, Atsuo

    2011-01-01

    Pfizer Global Virtual Library (PGVL) of 10(13) readily synthesizable molecules offers a tremendous opportunity for lead optimization and scaffold hopping in drug discovery projects. However, mining into a chemical space of this size presents a challenge for the concomitant design informatics due to the fact that standard molecular similarity searches against a collection of explicit molecules cannot be utilized, since no chemical information system could create and manage more than 10(8) explicit molecules. Nevertheless, by accepting a tolerable level of false negatives in search results, we were able to bypass the need for full 10(13) enumeration and enabled the efficient similarity search and retrieval into this huge chemical space for practical usage by medicinal chemists. In this report, two search methods (LEAP1 and LEAP2) are presented. The first method uses PGVL reaction knowledge to disassemble the incoming search query molecule into a set of reactants and then uses reactant-level similarities into actual available starting materials to focus on a much smaller sub-region of the full virtual library compound space. This sub-region is then explicitly enumerated and searched via a standard similarity method using the original query molecule. The second method uses a fuzzy mapping onto candidate reactions and does not require exact disassembly of the incoming query molecule. Instead Basis Products (or capped reactants) are mapped into the query molecule and the resultant asymmetric similarity scores are used to prioritize the corresponding reactions and reactant sets. All sets of Basis Products are inherently indexed to specific reactions and specific starting materials. This again allows focusing on a much smaller sub-region for explicit enumeration and subsequent standard product-level similarity search. A set of validation studies were conducted. The results have shown that the level of false negatives for the disassembly-based method is acceptable when the

  17. Predicting extreme rainfall events over Jeddah, Saudi Arabia: Impact of data assimilation with conventional and satellite observations

    KAUST Repository

    Viswanadhapalli, Yesubabu

    2015-08-20

    The impact of variational data assimilation for predicting two heavy rainfall events that caused devastating floods in Jeddah, Saudi Arabia is studied using the Weather Research and Forecasting (WRF) model. On 25 November 2009 and 26 January 2011, the city was deluged with more than double the annual rainfall amount caused by convective storms. We used a high resolution, two-way nested domain WRF model to simulate the two rainfall episodes. Simulations include control runs initialized with National Center for Environmental Prediction (NCEP) Global Forecasting System (GFS) data and 3-Dimensional Variational (3DVAR) data assimilation experiments conducted by assimilating NCEP prepbufr and radiance observations. Observations from Automated Weather Stations (AWS), synoptic charts, radar reflectivity and satellite pictures from the Presidency of Meteorology and Environment (PME), Jeddah, Saudi Arabia are used to assess the forecasting results. To evaluate the impact of the different assimilated observational datasets on the simulation of the major flooding event of 2009, we conducted 3DVAR experiments assimilating individual sources and a combination of all data sets. Results suggest that while the control run had a tendency to predict the storm earlier than observed, the assimilation of profile observations greatly improved the model\\'s thermodynamic structure and lead to better representation of simulated rainfall both in timing and amount. The experiment with assimilation of all available observations compared best with observed rainfall in terms of timing of the storm and rainfall distribution, demonstrating the importance of assimilating different types of observations. Retrospective experiments with and without data assimilation, for three different model lead times (48, 72 and 96-h), were performed to examine the skill of WRF model to predict the heavy rainfall events. Quantitative rainfall analysis of these simulations suggests that 48-h lead time runs with

  18. Coupled assimilation for an intermediated coupled ENSO prediction model

    Science.gov (United States)

    Zheng, Fei; Zhu, Jiang

    2010-10-01

    The value of coupled assimilation is discussed using an intermediate coupled model in which the wind stress is the only atmospheric state which is slavery to model sea surface temperature (SST). In the coupled assimilation analysis, based on the coupled wind-ocean state covariance calculated from the coupled state ensemble, the ocean state is adjusted by assimilating wind data using the ensemble Kalman filter. As revealed by a series of assimilation experiments using simulated observations, the coupled assimilation of wind observations yields better results than the assimilation of SST observations. Specifically, the coupled assimilation of wind observations can help to improve the accuracy of the surface and subsurface currents because the correlation between the wind and ocean currents is stronger than that between SST and ocean currents in the equatorial Pacific. Thus, the coupled assimilation of wind data can decrease the initial condition errors in the surface/subsurface currents that can significantly contribute to SST forecast errors. The value of the coupled assimilation of wind observations is further demonstrated by comparing the prediction skills of three 12-year (1997-2008) hindcast experiments initialized by the ocean-only assimilation scheme that assimilates SST observations, the coupled assimilation scheme that assimilates wind observations, and a nudging scheme that nudges the observed wind stress data, respectively. The prediction skills of two assimilation schemes are significantly better than those of the nudging scheme. The prediction skills of assimilating wind observations are better than assimilating SST observations. Assimilating wind observations for the 2007/2008 La Niña event triggers better predictions, while assimilating SST observations fails to provide an early warning for that event.

  19. Model Uncertainty Quantification Methods In Data Assimilation

    Science.gov (United States)

    Pathiraja, S. D.; Marshall, L. A.; Sharma, A.; Moradkhani, H.

    2017-12-01

    Data Assimilation involves utilising observations to improve model predictions in a seamless and statistically optimal fashion. Its applications are wide-ranging; from improving weather forecasts to tracking targets such as in the Apollo 11 mission. The use of Data Assimilation methods in high dimensional complex geophysical systems is an active area of research, where there exists many opportunities to enhance existing methodologies. One of the central challenges is in model uncertainty quantification; the outcome of any Data Assimilation study is strongly dependent on the uncertainties assigned to both observations and models. I focus on developing improved model uncertainty quantification methods that are applicable to challenging real world scenarios. These include developing methods for cases where the system states are only partially observed, where there is little prior knowledge of the model errors, and where the model error statistics are likely to be highly non-Gaussian.

  20. Data assimilation the ensemble Kalman filter

    CERN Document Server

    Evensen, Geir

    2007-01-01

    Data Assimilation comprehensively covers data assimilation and inverse methods, including both traditional state estimation and parameter estimation. This text and reference focuses on various popular data assimilation methods, such as weak and strong constraint variational methods and ensemble filters and smoothers. It is demonstrated how the different methods can be derived from a common theoretical basis, as well as how they differ and/or are related to each other, and which properties characterize them, using several examples. Rather than emphasize a particular discipline such as oceanography or meteorology, it presents the mathematical framework and derivations in a way which is common for any discipline where dynamics is merged with measurements. The mathematics level is modest, although it requires knowledge of basic spatial statistics, Bayesian statistics, and calculus of variations. Readers will also appreciate the introduction to the mathematical methods used and detailed derivations, which should b...

  1. Comparative Study on Assimilating Remote Sensing High Frequency Radar Surface Currents at an Atlantic Marine Renewable Energy Test Site

    OpenAIRE

    Lei Ren; Michael Hartnett

    2017-01-01

    A variety of data assimilation approaches have been applied to enhance modelling capability and accuracy using observations from different sources. The algorithms have varying degrees of complexity of implementation, and they improve model results with varying degrees of success. Very little work has been carried out on comparing the implementation of different data assimilation algorithms using High Frequency radar (HFR) data into models of complex inshore waters strongly influenced by both ...

  2. Scalable and balanced dynamic hybrid data assimilation

    Science.gov (United States)

    Kauranne, Tuomo; Amour, Idrissa; Gunia, Martin; Kallio, Kari; Lepistö, Ahti; Koponen, Sampsa

    2017-04-01

    Scalability of complex weather forecasting suites is dependent on the technical tools available for implementing highly parallel computational kernels, but to an equally large extent also on the dependence patterns between various components of the suite, such as observation processing, data assimilation and the forecast model. Scalability is a particular challenge for 4D variational assimilation methods that necessarily couple the forecast model into the assimilation process and subject this combination to an inherently serial quasi-Newton minimization process. Ensemble based assimilation methods are naturally more parallel, but large models force ensemble sizes to be small and that results in poor assimilation accuracy, somewhat akin to shooting with a shotgun in a million-dimensional space. The Variational Ensemble Kalman Filter (VEnKF) is an ensemble method that can attain the accuracy of 4D variational data assimilation with a small ensemble size. It achieves this by processing a Gaussian approximation of the current error covariance distribution, instead of a set of ensemble members, analogously to the Extended Kalman Filter EKF. Ensemble members are re-sampled every time a new set of observations is processed from a new approximation of that Gaussian distribution which makes VEnKF a dynamic assimilation method. After this a smoothing step is applied that turns VEnKF into a dynamic Variational Ensemble Kalman Smoother VEnKS. In this smoothing step, the same process is iterated with frequent re-sampling of the ensemble but now using past iterations as surrogate observations until the end result is a smooth and balanced model trajectory. In principle, VEnKF could suffer from similar scalability issues as 4D-Var. However, this can be avoided by isolating the forecast model completely from the minimization process by implementing the latter as a wrapper code whose only link to the model is calling for many parallel and totally independent model runs, all of them

  3. Employment assimilation of immigrants in the Netherlands: Catching up and the irrelevance of education

    NARCIS (Netherlands)

    Zorlu, A.; Hartog, J.

    2008-01-01

    Using two Dutch labour force surveys, employment assimilation of immigrants is examined. We observe marked differences between immigrants by source country. Non-western immigrants never reach parity with native Dutch. Even second generation immigrants never fully catch up. Caribbean immigrants, who

  4. Employment assimilation of immigrants in the Netherlands: catching up and the irrelevance of education

    NARCIS (Netherlands)

    Zorlu, A.; Hartog, J.

    2008-01-01

    Using two Dutch labour force surveys, employment assimilation of immigrants is examined. We observe marked differences between immigrants by source country. Non-western immigrants never reach parity with native Dutch. Even second generation immigrants never fully catch up. Caribbean immigrants, who

  5. HippDB: a database of readily targeted helical protein-protein interactions.

    Science.gov (United States)

    Bergey, Christina M; Watkins, Andrew M; Arora, Paramjit S

    2013-11-01

    HippDB catalogs every protein-protein interaction whose structure is available in the Protein Data Bank and which exhibits one or more helices at the interface. The Web site accepts queries on variables such as helix length and sequence, and it provides computational alanine scanning and change in solvent-accessible surface area values for every interfacial residue. HippDB is intended to serve as a starting point for structure-based small molecule and peptidomimetic drug development. HippDB is freely available on the web at http://www.nyu.edu/projects/arora/hippdb. The Web site is implemented in PHP, MySQL and Apache. Source code freely available for download at http://code.google.com/p/helidb, implemented in Perl and supported on Linux. arora@nyu.edu.

  6. Information-Based Analysis of Data Assimilation (Invited)

    Science.gov (United States)

    Nearing, G. S.; Gupta, H. V.; Crow, W. T.; Gong, W.

    2013-12-01

    Data assimilation is defined as the Bayesian conditioning of uncertain model simulations on observations for the purpose of reducing uncertainty about model states. Practical data assimilation methods make the application of Bayes' law tractable either by employing assumptions about the prior, posterior and likelihood distributions (e.g., the Kalman family of filters) or by using resampling methods (e.g., bootstrap filter). We propose to quantify the efficiency of these approximations in an OSSE setting using information theory and, in an OSSE or real-world validation setting, to measure the amount - and more importantly, the quality - of information extracted from observations during data assimilation. To analyze DA assumptions, uncertainty is quantified as the Shannon-type entropy of a discretized probability distribution. The maximum amount of information that can be extracted from observations about model states is the mutual information between states and observations, which is equal to the reduction in entropy in our estimate of the state due to Bayesian filtering. The difference between this potential and the actual reduction in entropy due to Kalman (or other type of) filtering measures the inefficiency of the filter assumptions. Residual uncertainty in DA posterior state estimates can be attributed to three sources: (i) non-injectivity of the observation operator, (ii) noise in the observations, and (iii) filter approximations. The contribution of each of these sources is measurable in an OSSE setting. The amount of information extracted from observations by data assimilation (or system identification, including parameter estimation) can also be measured by Shannon's theory. Since practical filters are approximations of Bayes' law, it is important to know whether the information that is extracted form observations by a filter is reliable. We define information as either good or bad, and propose to measure these two types of information using partial

  7. Assimilation, partitioning, and nonstructural carbohydrates in sweet compared with grain sorghum

    International Nuclear Information System (INIS)

    Vietor, D.M.; Miller, F.R.

    1990-01-01

    Nonstructural carbohydrate concentrations in stems are greater for sweet than grain sorghums [Sorghum bicolor (L.) Moench]. Knowledge of plant characteristics associated with high nonstructural carbohydrates in sweet sorghum will air efforts to increase nonstructural carbohydrates in grain sorghum stems. This study tested the hypothesis that variation of CO 2 assimilation rate, leaf area, branching at upper nodes, and partitioning of 14 C-labeled assimilate to main stems are associated with variation of stem nonstructural carbohydrates. A sweet (Atlas X Rio) and a grain (ATx623 X RTx5388) hybrid, stages near and after physiological maturity, and defoliation and gibberellic acid (GA 3 ) treatments provided sources of variation for study. Concentrations of nonstructural carbohydrates in lower and upper stems of the sweet hybrid were 1.4 and 2.7 times higher, respectively, than for the grain hybrid, after physiological maturity. Variation in branching, including 14 C-assimilate partitioning to branches, was not consistently associated with hybrid differences in stem nonstructural carbohydrates. Increased recovery (twofold) of 14 C-assimilate in roots and labeled leaves corresponded with lower percentages of 14 C-assimilate and lower concentrations of nonstructural carbohydrates in stems of the grain hybrid. Leaf areas and leaf CO 2 exchange rate were twice as great for the sweet hybrid. Although defoliation of the sweet hybrid minimized leaf area differences between hybrids, the sweet hybrid accumulated twice as much nonstructural carbohydrates in branches after physiological maturity. Greater potentials for CO 2 assimilation and for 14 C-assimilate accumulation in mature stem tissue were associated with higher levels of stem nonstructural carbohydrates in the sweet compared with the grain hybrid

  8. The Assimilation of Diazotroph-Derived Nitrogen by Scleractinian Corals Depends on Their Metabolic Status

    Directory of Open Access Journals (Sweden)

    Vanessa N. Bednarz

    2017-01-01

    Full Text Available Tropical corals are associated with a diverse community of dinitrogen (N2-fixing prokaryotes (diazotrophs providing the coral an additional source of bioavailable nitrogen (N in oligotrophic waters. The overall activity of these diazotrophs changes depending on the current environmental conditions, but to what extent it affects the assimilation of diazotroph-derived N (DDN by corals is still unknown. Here, in a series of 15N2 tracer experiments, we directly quantified DDN assimilation by scleractinian corals from the Red Sea exposed to different environmental conditions. We show that DDN assimilation strongly varied with the corals’ metabolic status or with phosphate availability in the water. The very autotrophic shallow-water (~5 m corals showed low or no DDN assimilation, which significantly increased under elevated phosphate availability (3 µM. Corals that depended more on heterotrophy (i.e., bleached and deep-water [~45 m] corals assimilated significantly more DDN, which contributed up to 15% of the corals’ N demand (compared to 1% in shallow corals. Furthermore, we demonstrate that a substantial part of the DDN assimilated by deep corals was likely obtained from heterotrophic feeding on fixed N compounds and/or diazotrophic cells in the mucus. Conversely, in shallow corals, the net release of mucus, rich in organic carbon compounds, likely enhanced diazotroph abundance and activity and thereby the release of fixed N to the pelagic and benthic reef community. Overall, our results suggest that DDN assimilation by corals varies according to the environmental conditions and is likely linked to the capacity of the coral to acquire nutrients from seawater.

  9. Photophysics of BODIPY Dyes as Readily-Designable Photosensitisers in Light-Driven Proton Reduction

    Directory of Open Access Journals (Sweden)

    Laura Dura

    2017-04-01

    Full Text Available A series of boron dipyrromethene (BODIPY dyes was tested as photosensitisers for light-driven hydrogen evolution in combination with the complex [Pd(PPh3Cl2]2 as a source for catalytically-active Pd nanoparticles and triethylamine as a sacrificial electron donor. In line with earlier reports, halogenated dyes showed significantly higher hydrogen production activity. All BODIPYs were fully characterised using stationary absorption and emission spectroscopy. Time-resolved spectroscopic investigations on meso-mesityl substituted compounds revealed that reduction of the photo-excited BODIPY by the sacrificial agent occurs from an excited singlet state, while, in halogenated species, long-lived triplet states are present, determining electron transfer processes from the sacrificial agent. Quantum chemical calculations performed at the time-dependent density functional level of theory indicate that the differences in the photocatalytic performance of the present series of dyes can be correlated to the varying efficiency of intersystem crossing in non-halogenated and halogenated species and not to alterations in the energy levels introduced upon substitution.

  10. Hydrologic Remote Sensing and Land Surface Data Assimilation

    Directory of Open Access Journals (Sweden)

    Hamid Moradkhani

    2008-05-01

    Full Text Available Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface–atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF and Particle filter (PF, for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law and could be a strong alternative to EnKF which is subject to some

  11. Hydrologic Remote Sensing and Land Surface Data Assimilation.

    Science.gov (United States)

    Moradkhani, Hamid

    2008-05-06

    Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear

  12. Differentiation between Trichophyton mentagrophytes and T. rubrum by sorbitol assimilation.

    OpenAIRE

    Rezusta, A; Rubio, M C; Alejandre, M C

    1991-01-01

    Trichophyton rubrum was easily differentiated from T. mentagrophytes by its ability to assimilate sorbitol with an API 20C AUX strip. One hundred percent of 36 T. rubrum strains and none of 147 T. mentagrophytes strains assimilated sorbitol.

  13. Assimilation of Doppler weather radar observations in a mesoscale ...

    Indian Academy of Sciences (India)

    Research (PSU–NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation ... investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present ...... Results presented in this paper are based on.

  14. Dioxin and phthalate uptake and assimilation by the green mussel Perna viridis

    International Nuclear Information System (INIS)

    Wang, Wen-Xiong; Zhang, Qiong

    2013-01-01

    In this study, the aqueous uptake and dietary assimilation (trophic transfer) of two endocrine disrupting compounds (dioxin and phathalic acid) in the green mussel Perna viridis were quantified. During short-term exposure period, dioxin rapidly sorbed onto phytoplankton and its accumulation was much higher than that of phthalate. The uptake of these two compounds by the mussels increased with increasing temperature and salinity (for dioxin only). The dietary assimilation of the two contaminants was rather modest (10–64% for dioxin and 20–47% for phthalate), and was greatly dependent on the food species and concentration. Interestingly, dietary assimilation increased with increasing diatom food concentration. Gut passage time was partially responsible for the variable dietary assimilation. Given the high dissolved uptake rate and the modest dietary assimilation, aqueous exposure was predicted to be the dominant bioaccumulation source for both dioxin and phthalate in the green mussels under most conditions. -- Capsule: Aqueous uptake was the predominant pathway for dioxin and phthalate accumulation in marine green mussels

  15. Development of a data assimilation algorithm

    DEFF Research Database (Denmark)

    Thomsen, Per Grove; Zlatev, Zahari

    2008-01-01

    It is important to incorporate all available observations when large-scale mathematical models arising in different fields of science and engineering are used to study various physical and chemical processes. Variational data assimilation techniques can be used in the attempts to utilize efficien......It is important to incorporate all available observations when large-scale mathematical models arising in different fields of science and engineering are used to study various physical and chemical processes. Variational data assimilation techniques can be used in the attempts to utilize...... assimilation technique is applied. Therefore, it is important to study the interplay between the three components of the variational data assimilation techniques as well as to apply powerful parallel computers in the computations. Some results obtained in the search for a good combination of numerical methods...... computers, Mathematics and Computers in Simulation, 65 (2004) 557–577, Z. Zlatev, Computer Treatment of Large Air Pollution Models, Kluwer Academic Publishers, Dordrecht, Boston, London, 1995]. The ideas are rather general and can easily be applied in connection with other mathematical models....

  16. Nitrogen assimilation in soybean nodules, 1

    International Nuclear Information System (INIS)

    Ohyama, Takuji; Kumazawa, Kikuo

    1980-01-01

    In order to elucidate the pathways to assimilate the ammonia produced by N 2 -fixation in soybean nodules, 15 N-labeled compounds were administered to intact nodules or nodule slices pretreated with various inhibitors of nitrogen assimilation. After exposure to 15 N 2 , 15 N-incorporation into various nitrogenous compounds was investigated in attached nodules injected with methionine sulfoximine (MSX) or azaserine (AS). MSX treatment increased the 15 N content of ammonia more than 6 times, however, depressed 15 N content of most of amides and amino acids. AS treatment enhanced 15 N content of amido-N of glutamine as well as ammonia, but decreased amino-N of glutamine and most of amino acids. Experiments with nodule slices pretreated with MSX or AS solution and then fed with 15 N-labeled ammonia or amido- 15 N of glutamine showed the same trends. Aminooxyacetate inhibited nitrogen flow from glutamic acid to other amino acids. These results strongly indicate that the ammonia produced by N 2 -fixation is assimilated by GS/GOGAT system to glutamic acid and then transaminated to various amino acids in situ. 15 N-incorporation patterns in nodule slices fed with 15 N-labeled ammonia, hydroxylamine, nitrite were similar, but nitrate seemed to be reduced in a definite compartment and assimilated similarly as in intact nodules fed with 15 N 2 (author)

  17. Data assimilation for air quality models

    DEFF Research Database (Denmark)

    Silver, Jeremy David

    2014-01-01

    -dimensional optimal interpolation procedure (OI), an Ensemble Kalman Filter (EnKF), and a three-dimensional variational scheme (3D-var). The three assimilation procedures are described and tested. A multi-faceted approach is taken for the verification, using independent measurements from surface air-quality...

  18. Data ingestion and assimilation in ionospheric models

    Czech Academy of Sciences Publication Activity Database

    Burešová, Dalia; Nava, B.; Galkin, I.; Angling, M.; Stankov, S. M.; Coisson, P.

    2009-01-01

    Roč. 52, 3/4 (2009), s. 235-253 ISSN 1593-5213 R&D Projects: GA ČR GA205/08/1356; GA MŠk OC 091 Institutional research plan: CEZ:AV0Z30420517 Keywords : ionosphere * models * data assimilation * data ingestion Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.548, year: 2009

  19. A study on assimilating potential vorticity data

    Science.gov (United States)

    Li, Yong; Ménard, Richard; Riishøjgaard, Lars Peter; Cohn, Stephen E.; Rood, Richard B.

    1998-08-01

    The correlation that exists between the potential vorticity (PV) field and the distribution of chemical tracers such as ozone suggests the possibility of using tracer observations as proxy PV data in atmospheric data assimilation systems. Especially in the stratosphere, there are plentiful tracer observations but a general lack of reliable wind observations, and the correlation is most pronounced. The issue investigated in this study is how model dynamics would respond to the assimilation of PV data. First, numerical experiments of identical-twin type were conducted with a simple univariate nuding algorithm and a global shallow water model based on PV and divergence (PV-D model). All model fields are successfully reconstructed through the insertion of complete PV data alone if an appropriate value for the nudging coefficient is used. A simple linear analysis suggests that slow modes are recovered rapidly, at a rate nearly independent of spatial scale. In a more realistic experiment, appropriately scaled total ozone data from the NIMBUS-7 TOMS instrument were assimilated as proxy PV data into the PV-D model over a 10-day period. The resulting model PV field matches the observed total ozone field relatively well on large spatial scales, and the PV, geopotential and divergence fields are dynamically consistent. These results indicate the potential usefulness that tracer observations, as proxy PV data, may offer in a data assimilation system.

  20. OLYMPUS DISS - A Readily Implemented Geographic Data and Information Sharing System

    Science.gov (United States)

    Necsoiu, D. M.; Winfrey, B.; Murphy, K.; McKague, H. L.

    2002-12-01

    Electronic information technology has become a crucial component of business, government, and scientific organizations. In this technology era, many enterprises are moving away from the perception that information repositories are only a tool for decision-making. Instead, many organizations are learning that information systems, which are capable of organizing and following the interrelations between information and both the short-term and strategic organizational goals, are assets themselves, with inherent value. Olympus Data and Information Sharing System (DISS) is a system developed at the Center for Nuclear Waste Regulatory Analyses (CNWRA) to solve several difficult tasks associated with the management of geographical, geological and geophysical data. Three of the tasks were to (1) gather the large amount of heterogeneous information that has accumulated over the operational lifespan of CNWRA, (2) store the data in a central, knowledge-based, searchable database and (3) create quick, easy, convenient, and reliable access to that information. Faced with these difficult tasks CNWRA identified the requirements for designing such a system. Key design criteria were: (a) ability to ingest different data formats (i.e., raster, vector, and tabular data); (b) minimal expense using open-source and commercial off-the-shelf software; (c) seamless management of geospatial data, freeing up time for researchers to focus on analyses or algorithm development, rather than on time consuming format conversions; (d) controlled access; and (e) scalable architecture to meet new and continuing demands. Olympus DISS is a solution that can be easily adapted to small and mid-size enterprises dealing with heterogeneous geographic data. It uses established data standards, provides a flexible mechanism to build applications upon and output geographic data in multiple and clear ways. This abstract is an independent product of the CNWRA and does not necessarily reflect the views or

  1. Readily Available Sources of Long-Chain Omega-3 Oils: Is Farmed Australian Seafood a Better Source of the Good Oil than Wild-Caught Seafood?

    Directory of Open Access Journals (Sweden)

    Peter D. Nichols

    2014-03-01

    Full Text Available Seafood consumption enhances intake of omega-3 long-chain (≥C20 polyunsaturated fatty acids (termed LC omega-3 oils. Humans biosynthesize only small amounts of LC-omega-3, so they are considered semi-essential nutrients in our diet. Concern has been raised that farmed fish now contain lower LC omega-3 content than wild-harvested seafood due to the use of oil blending in diets fed to farmed fish. However, we observed that two major Australian farmed finfish species, Atlantic salmon (Salmo salar and barramundi (Lates calcifer, have higher oil and LC omega-3 content than the same or other species from the wild, and remain an excellent means to achieve substantial intake of LC omega-3 oils. Notwithstanding, LC omega-3 oil content has decreased in these two farmed species, due largely to replacing dietary fish oil with poultry oil. For Atlantic salmon, LC omega-3 content decreased ~30%–50% between 2002 and 2013, and the omega-3/omega-6 ratio also decreased (>5:1 to <1:1. Australian consumers increasingly seek their LC omega-3 from supplements, therefore a range of supplement products were compared. The development and future application of oilseeds containing LC omega-3 oils and their incorporation in aquafeeds would allow these health-benefitting oils to be maximized in farmed Australian seafood. Such advances can assist with preventative health care, fisheries management, aquaculture nutrition, an innovative feed/food industry and ultimately towards improved consumer health.

  2. Empowering Geoscience with Improved Data Assimilation Using the Data Assimilation Research Testbed "Manhattan" Release.

    Science.gov (United States)

    Raeder, K.; Hoar, T. J.; Anderson, J. L.; Collins, N.; Hendricks, J.; Kershaw, H.; Ha, S.; Snyder, C.; Skamarock, W. C.; Mizzi, A. P.; Liu, H.; Liu, J.; Pedatella, N. M.; Karspeck, A. R.; Karol, S. I.; Bitz, C. M.; Zhang, Y.

    2017-12-01

    The capabilities of the Data Assimilation Research Testbed (DART) at NCAR have been significantly expanded with the recent "Manhattan" release. DART is an ensemble Kalman filter based suite of tools, which enables researchers to use data assimilation (DA) without first becoming DA experts. Highlights: significant improvement in efficient ensemble DA for very large models on thousands of processors, direct read and write of model state files in parallel, more control of the DA output for finer-grained analysis, new model interfaces which are useful to a variety of geophysical researchers, new observation forward operators and the ability to use precomputed forward operators from the forecast model. The new model interfaces and example applications include the following: MPAS-A; Model for Prediction Across Scales - Atmosphere is a global, nonhydrostatic, variable-resolution mesh atmospheric model, which facilitates multi-scale analysis and forecasting. The absence of distinct subdomains eliminates problems associated with subdomain boundaries. It demonstrates the ability to consistently produce higher-quality analyses than coarse, uniform meshes do. WRF-Chem; Weather Research and Forecasting + (MOZART) Chemistry model assimilates observations from FRAPPÉ (Front Range Air Pollution and Photochemistry Experiment). WACCM-X; Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension assimilates observations of electron density to investigate sudden stratospheric warming. CESM (weakly) coupled assimilation; NCAR's Community Earth System Model is used for assimilation of atmospheric and oceanic observations into their respective components using coupled atmosphere+land+ocean+sea+ice forecasts. CESM2.0; Assimilation in the atmospheric component (CAM, WACCM) of the newly released version is supported. This version contains new and extensively updated components and software environment. CICE; Los Alamos sea ice model (in CESM) is used to assimilate

  3. An algorithm for variational data assimilation of contact concentration measurements for atmospheric chemistry models

    Science.gov (United States)

    Penenko, Alexey; Penenko, Vladimir

    2014-05-01

    Contact concentration measurement data assimilation problem is considered for convection-diffusion-reaction models originating from the atmospheric chemistry study. High dimensionality of models imposes strict requirements on the computational efficiency of the algorithms. Data assimilation is carried out within the variation approach on a single time step of the approximated model. A control function is introduced into the source term of the model to provide flexibility for data assimilation. This function is evaluated as the minimum of the target functional that connects its norm to a misfit between measured and model-simulated data. In the case mathematical model acts as a natural Tikhonov regularizer for the ill-posed measurement data inversion problem. This provides flow-dependent and physically-plausible structure of the resulting analysis and reduces a need to calculate model error covariance matrices that are sought within conventional approach to data assimilation. The advantage comes at the cost of the adjoint problem solution. This issue is solved within the frameworks of splitting-based realization of the basic convection-diffusion-reaction model. The model is split with respect to physical processes and spatial variables. A contact measurement data is assimilated on each one-dimensional convection-diffusion splitting stage. In this case a computationally-efficient direct scheme for both direct and adjoint problem solution can be constructed based on the matrix sweep method. Data assimilation (or regularization) parameter that regulates ratio between model and data in the resulting analysis is obtained with Morozov discrepancy principle. For the proper performance the algorithm takes measurement noise estimation. In the case of Gaussian errors the probability that the used Chi-squared-based estimate is the upper one acts as the assimilation parameter. A solution obtained can be used as the initial guess for data assimilation algorithms that assimilate

  4. Assimilation of Gridded GRACE Terrestrial Water Storage Estimates in the North American Land Data Assimilation System

    Science.gov (United States)

    Kumar, Sujay V.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.; Rodell, Matthew; Reichle, Rolf; Li, Bailing; Jasinski, Michael; Mocko, David; Getirana, Augusto; De Lannoy, Gabrielle; hide

    2016-01-01

    The objective of the North American Land Data Assimilation System (NLDAS) is to provide best available estimates of near-surface meteorological conditions and soil hydrological status for the continental United States. To support the ongoing efforts to develop data assimilation (DA) capabilities for NLDAS, the results of Gravity Recovery and Climate Experiment (GRACE) DA implemented in a manner consistent with NLDAS development are presented. Following previous work, GRACE terrestrial water storage (TWS) anomaly estimates are assimilated into the NASA Catchment land surface model using an ensemble smoother. In contrast to many earlier GRACE DA studies, a gridded GRACE TWS product is assimilated, spatially distributed GRACE error estimates are accounted for, and the impact that GRACE scaling factors have on assimilation is evaluated. Comparisons with quality-controlled in situ observations indicate that GRACE DA has a positive impact on the simulation of unconfined groundwater variability across the majority of the eastern United States and on the simulation of surface and root zone soil moisture across the country. Smaller improvements are seen in the simulation of snow depth, and the impact of GRACE DA on simulated river discharge and evapotranspiration is regionally variable. The use of GRACE scaling factors during assimilation improved DA results in the western United States but led to small degradations in the eastern United States. The study also found comparable performance between the use of gridded and basin averaged GRACE observations in assimilation. Finally, the evaluations presented in the paper indicate that GRACE DA can be helpful in improving the representation of droughts.

  5. Dark matter assimilation into the baryon asymmetry

    International Nuclear Information System (INIS)

    D'Eramo, Francesco; Fei, Lin; Thaler, Jesse

    2012-01-01

    Pure singlets are typically disfavored as dark matter candidates, since they generically have a thermal relic abundance larger than the observed value. In this paper, we propose a new dark matter mechanism called a ssimilation , which takes advantage of the baryon asymmetry of the universe to generate the correct relic abundance of singlet dark matter. Through assimilation, dark matter itself is efficiently destroyed, but dark matter number is stored in new quasi-stable heavy states which carry the baryon asymmetry. The subsequent annihilation and late-time decay of these heavy states yields (symmetric) dark matter as well as (asymmetric) standard model baryons. We study in detail the case of pure bino dark matter by augmenting the minimal supersymmetric standard model with vector-like chiral multiplets. In the parameter range where this mechanism is effective, the LHC can discover long-lived charged particles which were responsible for assimilating dark matter

  6. Data assimilation in integrated hydrological modelling

    DEFF Research Database (Denmark)

    Rasmussen, Jørn

    Integrated hydrological models are useful tools for water resource management and research, and advances in computational power and the advent of new observation types has resulted in the models generally becoming more complex and distributed. However, the models are often characterized by a high...... degree of parameterization which results in significant model uncertainty which cannot be reduced much due to observations often being scarce and often taking the form of point measurements. Data assimilation shows great promise for use in integrated hydrological models , as it allows for observations...... to be efficiently combined with models to improve model predictions, reduce uncertainty and estimate model parameters. In this thesis, a framework for assimilating multiple observation types and updating multiple components and parameters of a catchment scale integrated hydrological model is developed and tested...

  7. Probabilistic forecasting and Bayesian data assimilation

    CERN Document Server

    Reich, Sebastian

    2015-01-01

    In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in ap...

  8. Data assimilation techniques in modeling ocean processes

    Digital Repository Service at National Institute of Oceanography (India)

    Mahadevan, R.; Fernandes, A.A.; Naqvi, S.W.A.

    are usually called data analysis or assimilation. These homogeneous fields are prerequisites for various practical applications and theoretical studies. The fields produced by an analysi the one hand, they must be close to the observations.... The practical usefulness of variational methods for meteorological problems are pointed out very early by Sasaki (1955, 1958), but in spite of that these methods have not been fully utilized. Probably, the complex mathematical technicality of these methods...

  9. Preliminary studies on the evolution of carbon assimilation abilities within Mucorales.

    Science.gov (United States)

    Pawłowska, Julia; Aleksandrzak-Piekarczyk, Tamara; Banach, Agnieszka; Kiersztyn, Bartosz; Muszewska, Anna; Serewa, Lidia; Szatraj, Katarzyna; Wrzosek, Marta

    2016-05-01

    Representatives of Mucorales belong to one of the oldest lineages of terrestrial fungi. Although carbon is of fundamental importance for fungal growth and functioning, relatively little is known about enzymatic capacities of Mucorales. The evolutionary history and the variability of the capacity to metabolize different carbon sources among representatives of the order Mucorales was studied using Phenotypic Microarray Plates. The ability of 26 strains belonging to 23 nonpathogenic species of Mucorales to use 95 different carbon sources was tested. Intraspecies variability of carbon assimilation profiles was lower than interspecies variation for some selected strains. Although similarities between the phylogenetic tree and the dendrogram created from carbon source utilization data were observed, the ability of the various strains to use the analyzed substrates did not show a clear correlation with the evolutionary history of the group. Instead, carbon assimilation profiles are probably shaped by environmental conditions. Copyright © 2016 The British Mycological Society. Published by Elsevier Ltd. All rights reserved.

  10. Comparison of Sequential and Variational Data Assimilation

    Science.gov (United States)

    Alvarado Montero, Rodolfo; Schwanenberg, Dirk; Weerts, Albrecht

    2017-04-01

    Data assimilation is a valuable tool to improve model state estimates by combining measured observations with model simulations. It has recently gained significant attention due to its potential in using remote sensing products to improve operational hydrological forecasts and for reanalysis purposes. This has been supported by the application of sequential techniques such as the Ensemble Kalman Filter which require no additional features within the modeling process, i.e. it can use arbitrary black-box models. Alternatively, variational techniques rely on optimization algorithms to minimize a pre-defined objective function. This function describes the trade-off between the amount of noise introduced into the system and the mismatch between simulated and observed variables. While sequential techniques have been commonly applied to hydrological processes, variational techniques are seldom used. In our believe, this is mainly attributed to the required computation of first order sensitivities by algorithmic differentiation techniques and related model enhancements, but also to lack of comparison between both techniques. We contribute to filling this gap and present the results from the assimilation of streamflow data in two basins located in Germany and Canada. The assimilation introduces noise to precipitation and temperature to produce better initial estimates of an HBV model. The results are computed for a hindcast period and assessed using lead time performance metrics. The study concludes with a discussion of the main features of each technique and their advantages/disadvantages in hydrological applications.

  11. Data assimilation and model evaluation experiment datasets

    Science.gov (United States)

    Lai, Chung-Cheng A.; Qian, Wen; Glenn, Scott M.

    1994-01-01

    The Institute for Naval Oceanography, in cooperation with Naval Research Laboratories and universities, executed the Data Assimilation and Model Evaluation Experiment (DAMEE) for the Gulf Stream region during fiscal years 1991-1993. Enormous effort has gone into the preparation of several high-quality and consistent datasets for model initialization and verification. This paper describes the preparation process, the temporal and spatial scopes, the contents, the structure, etc., of these datasets. The goal of DAMEE and the need of data for the four phases of experiment are briefly stated. The preparation of DAMEE datasets consisted of a series of processes: (1) collection of observational data; (2) analysis and interpretation; (3) interpolation using the Optimum Thermal Interpolation System package; (4) quality control and re-analysis; and (5) data archiving and software documentation. The data products from these processes included a time series of 3D fields of temperature and salinity, 2D fields of surface dynamic height and mixed-layer depth, analysis of the Gulf Stream and rings system, and bathythermograph profiles. To date, these are the most detailed and high-quality data for mesoscale ocean modeling, data assimilation, and forecasting research. Feedback from ocean modeling groups who tested this data was incorporated into its refinement. Suggestions for DAMEE data usages include (1) ocean modeling and data assimilation studies, (2) diagnosis and theoretical studies, and (3) comparisons with locally detailed observations.

  12. Comparative Study on Assimilating Remote Sensing High Frequency Radar Surface Currents at an Atlantic Marine Renewable Energy Test Site

    Directory of Open Access Journals (Sweden)

    Lei Ren

    2017-12-01

    Full Text Available A variety of data assimilation approaches have been applied to enhance modelling capability and accuracy using observations from different sources. The algorithms have varying degrees of complexity of implementation, and they improve model results with varying degrees of success. Very little work has been carried out on comparing the implementation of different data assimilation algorithms using High Frequency radar (HFR data into models of complex inshore waters strongly influenced by both tides and wind dynamics, such as Galway Bay. This research entailed implementing four different data assimilation algorithms: Direct Insertion (DI, Optimal Interpolation (OI, Nudging and indirect data assimilation via correcting model forcing into a three-dimensional hydrodynamic model and carrying out detailed comparisons of model performances. This work will allow researchers to directly compare four of the most common data assimilation algorithms being used in operational coastal hydrodynamics. The suitability of practical data assimilation algorithms for hindcasting and forecasting in shallow coastal waters subjected to alternate wetting and drying using data collected from radars was assessed. Results indicated that a forecasting system of surface currents based on the three-dimensional model EFDC (Environmental Fluid Dynamics Code and the HFR data using a Nudging or DI algorithm was considered the most appropriate for Galway Bay. The largest averaged Data Assimilation Skill Score (DASS over the ≥6 h forecasting period from the best model NDA attained 26% and 31% for east–west and north–south surface velocity components respectively. Because of its ease of implementation and its accuracy, this data assimilation system can provide timely and useful information for various practical coastal hindcast and forecast operations.

  13. Scalar and Vector Spherical Harmonics for Assimilation of Global Datasets in the Ionosphere and Thermosphere

    Science.gov (United States)

    Miladinovich, D.; Datta-Barua, S.; Bust, G. S.; Ramirez, U.

    2017-12-01

    Understanding physical processes during storm time in the ionosphere-thermosphere (IT) system is limited, in part, due to the inability to obtain accurate estimates of IT states on a global scale. One reason for this inability is the sparsity of spatially distributed high quality data sets. Data assimilation is showing promise toward enabling global estimates by blending high quality observational data sets with established climate models. We are continuing development of an algorithm called Estimating Model Parameters for Ionospheric Reverse Engineering (EMPIRE) to enable assimilation of global datasets for storm time estimates of IT drivers. EMPIRE is a data assimilation algorithm that uses a Kalman filtering routine to ingest model and observational data. The EMPIRE algorithm is based on spherical harmonics which provide a spherically symmetric, smooth, continuous, and orthonormal set of basis functions suitable for a spherical domain such as Earth's IT region (200-600 km altitude). Once the basis function coefficients are determined, the newly fitted function represents the disagreement between observational measurements and models. We apply spherical harmonics to study the March 17, 2015 storm. Data sources include Fabry-Perot interferometer neutral wind measurements and global Ionospheric Data Assimilation 4 Dimensional (IDA4D) assimilated total electron content (TEC). Models include Weimer 2000 electric potential, International Geomagnetic Reference Field (IGRF) magnetic field, and Horizontal Wind Model 2014 (HWM14) neutral winds. We present the EMPIRE assimilation results of Earth's electric potential and thermospheric winds. We also compare EMPIRE storm time E cross B ion drift estimates to measured drifts produced from the Super Dual Auroral Radar Network (SuperDARN) and Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) measurement datasets. The analysis from these results will enable the generation of globally assimilated

  14. Antiproliferative effects of the readily extractable fractions prepared from various citrus juices on several cancer cell lines.

    Science.gov (United States)

    Kawaii, S; Tomono, Y; Katase, E; Ogawa, K; Yano, M

    1999-07-01

    To eliminate the masking effect by flavonoid glycosides, which comprise approximately 70% of conventionally prepared sample, the readily extractable fraction from Citrus juice, which was prepared by adsorbing on HP-20 resin and eluting with ethanol and acetone from the resin, was subjected to antiproliferative tests against several cancer cell lines. Screening of 34 Citrus juices indicated that King (Citrus nobilis) strongly inhibited proliferation of all cancer cell lines examined. Sweet lime and Kabuchi inhibited three of the four cancer cell lines. In contrast, these samples were substantially less cytotoxic toward normal human cell lines.

  15. The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance 2001-2015

    Science.gov (United States)

    van der Laan-Luijkx, Ingrid T.; van der Velde, Ivar R.; van der Veen, Emma; Tsuruta, Aki; Stanislawska, Karolina; Babenhauserheide, Arne; Zhang, Hui Fang; Liu, Yu; He, Wei; Chen, Huilin; Masarie, Kenneth A.; Krol, Maarten C.; Peters, Wouter

    2017-07-01

    Data assimilation systems are used increasingly to constrain the budgets of reactive and long-lived gases measured in the atmosphere. Each trace gas has its own lifetime, dominant sources and sinks, and observational network (from flask sampling and in situ measurements to space-based remote sensing) and therefore comes with its own optimal configuration of the data assimilation. The CarbonTracker Europe data assimilation system for CO2 estimates global carbon sources and sinks, and updates are released annually and used in carbon cycle studies. CarbonTracker Europe simulations are performed using the new modular implementation of the data assimilation system: the CarbonTracker Data Assimilation Shell (CTDAS). Here, we present and document this redesign of the data assimilation code that forms the heart of CarbonTracker, specifically meant to enable easy extension and modification of the data assimilation system. This paper also presents the setup of the latest version of CarbonTracker Europe (CTE2016), including the use of the gridded state vector, and shows the resulting carbon flux estimates. We present the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show that with equal fossil fuel emissions, 2015 has a higher atmospheric CO2 growth rate compared to 2014, due to reduced net land carbon uptake in later year. The European carbon sink is especially present in the forests, and the average net uptake over 2001-2015 was 0. 17 ± 0. 11 PgC yr-1 with reductions to zero during drought years. Finally, we also demonstrate the versatility of CTDAS by presenting an overview of the wide range of applications for which it has been used so far.

  16. Spatial dependence of color assimilation by the watercolor effect.

    Science.gov (United States)

    Devinck, Frédéric; Delahunt, Peter B; Hardy, Joseph L; Spillmann, Lothar; Werner, John S

    2006-01-01

    Color assimilation with bichromatic contours was quantified for spatial extents ranging from von Bezold-type color assimilation to the watercolor effect. The magnitude and direction of assimilative hue change was measured as a function of the width of a rectangular stimulus. Assimilation was quantified by hue cancellation. Large hue shifts were required to null the color of stimuli < or = 9.3 min of arc in width, with an exponential decrease for stimuli increasing up to 7.4 deg. When stimuli were viewed through an achromatizing lens, the magnitude of the assimilation effect was reduced for narrow stimuli, but not for wide ones. These results demonstrate that chromatic aberration may account, in part, for color assimilation over small, but not large, surface areas.

  17. Accelerating assimilation development for new observing systems using EFSO

    Science.gov (United States)

    Lien, Guo-Yuan; Hotta, Daisuke; Kalnay, Eugenia; Miyoshi, Takemasa; Chen, Tse-Chun

    2018-03-01

    To successfully assimilate data from a new observing system, it is necessary to develop appropriate data selection strategies, assimilating only the generally useful data. This development work is usually done by trial and error using observing system experiments (OSEs), which are very time and resource consuming. This study proposes a new, efficient methodology to accelerate the development using ensemble forecast sensitivity to observations (EFSO). First, non-cycled assimilation of the new observation data is conducted to compute EFSO diagnostics for each observation within a large sample. Second, the average EFSO conditionally sampled in terms of various factors is computed. Third, potential data selection criteria are designed based on the non-cycled EFSO statistics, and tested in cycled OSEs to verify the actual assimilation impact. The usefulness of this method is demonstrated with the assimilation of satellite precipitation data. It is shown that the EFSO-based method can efficiently suggest data selection criteria that significantly improve the assimilation results.

  18. Benefits and Pitfalls of GRACE Terrestrial Water Storage Data Assimilation

    Science.gov (United States)

    Girotto, Manuela

    2018-01-01

    Satellite observations of terrestrial water storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE) mission have a coarse resolution in time (monthly) and space (roughly 150,000 sq km at midlatitudes) and vertically integrate all water storage components over land, including soil moisture and groundwater. Nonetheless, data assimilation can be used to horizontally downscale and vertically partition GRACE-TWS observations. This presentation illustrates some of the benefits and drawbacks of assimilating TWS observations from GRACE into a land surface model over the continental United States and India. The assimilation scheme yields improved skill metrics for groundwater compared to the no-assimilation simulations. A smaller impact is seen for surface and root-zone soil moisture. Further, GRACE observes TWS depletion associated with anthropogenic groundwater extraction. Results from the assimilation emphasize the importance of representing anthropogenic processes in land surface modeling and data assimilation systems.

  19. Completing the Feedback Loop: The Impact of Chlorophyll Data Assimilation on the Ocean State

    Science.gov (United States)

    Borovikov, Anna; Keppenne, Christian; Kovach, Robin

    2015-01-01

    In anticipation of the integration of a full biochemical model into the next generation GMAO coupled system, an intermediate solution has been implemented to estimate the penetration depth (1Kd_PAR) of ocean radiation based on the chlorophyll concentration. The chlorophyll is modeled as a tracer with sources-sinks coming from the assimilation of MODIS chlorophyll data. Two experiments were conducted with the coupled ocean-atmosphere model. In the first, climatological values of Kpar were used. In the second, retrieved daily chlorophyll concentrations were assimilated and Kd_PAR was derived according to Morel et al (2007). No other data was assimilated to isolate the effects of the time-evolving chlorophyll field. The daily MODIS Kd_PAR product was used to validate the skill of the penetration depth estimation and the MERRA-OCEAN re-analysis was used as a benchmark to study the sensitivity of the upper ocean heat content and vertical temperature distribution to the chlorophyll input. In the experiment with daily chlorophyll data assimilation, the penetration depth was estimated more accurately, especially in the tropics. As a result, the temperature bias of the model was reduced. A notably robust albeit small (2-5 percent) improvement was found across the equatorial Pacific ocean, which is a critical region for seasonal to inter-annual prediction.

  20. Assimilative Modeling of Ionospheric Disturbances with FORMOSAT-3/COSMIC and Ground-Based GPS Measurements

    Directory of Open Access Journals (Sweden)

    Xiaoqing Pi

    2009-01-01

    Full Text Available The four-dimensional Global Assimilative Ionospheric Model (GAIM is applied to a study of ionospheric disturbances. The investigation is focused on disturbance features, particularly in the altitude and latitude dimensions, at low latitudes during a geomagnetic storm on 7 August 2006, under solar minimum conditions. The modeling of storm-time ionospheric state (electron density is conducted by assimilating an unprecedented volume of line-of-sight TEC data collected by the Global Positioning System (GPS occultation receivers on board six FORMOSAT-3/COSMIC satellites and geodetic-quality GPS receivers at two hundred globally-distributed ground tracking stations.With a band-limited Kalman filter technique to update the ionospheric state, the assimilative modeling reveals a pronounced enhancement in the equatorial anomaly in the East Asia sector during dusk and evening hours. The disturbance characteristics, obtained by comparing with the quiet conditions prior to the storm also modeled in this study through data assimilation, include lifted F layer and reduced electron density in the equatorial region, enhanced density at the magnetically conjugate anomaly latitudes, and tilted feature of density increase towards higher altitudes at lower latitudes. The characteristics are attributed to the enhanced plasma fountain effect driven by an enhanced eastward zonal electric field. These results enable us to distinguish the storm-time electric field perturbations clearly from other sources during the storm. The possible origins of electric field perturbations are also discussed, including penetration of the magnetospheric electric field and wind dynamo disturbances.

  1. Testbed model and data assimilation for ARM

    International Nuclear Information System (INIS)

    Louis, J.F.

    1992-01-01

    The objectives of this contract are to further develop and test the ALFA (AER Local Forecast and Assimilation) model originally designed at AER for local weather prediction and apply it to three distinct but related purposes in connection with the Atmospheric Radiation Measurement (ARM) program: (a) to provide a testbed that simulates a global climate model in order to facilitate the development and testing of new cloud parametrizations and radiation models; (b) to assimilate the ARM data continuously at the scale of a climate model, using the adjoint method, thus providing the initial conditions and verification data for testing parameumtions; (c) to study the sensitivity of a radiation scheme to cloud parameters, again using the adjoint method, thus demonstrating the usefulness of the testbed model. The data assimilation will use a variational technique that minimizes the difference between the model results and the observation during the analysis period. The adjoint model is used to compute the gradient of a measure of the model errors with respect to nudging terms that are added to the equations to force the model output closer to the data. The radiation scheme that will be included in the basic ALFA model makes use of a gen two-stream approximation, and is designed for vertically inhonogeneous, multiple-scattering atmospheres. The sensitivity of this model to the definition of cloud parameters will be studied. The adjoint technique will also be used to compute the sensitivities. This project is designed to provide the Science Team members with the appropriate tools and modeling environment for proper testing and tuning of new radiation models and cloud parametrization schemes

  2. Variational data assimilation using targetted random walks

    KAUST Repository

    Cotter, S. L.

    2011-02-15

    The variational approach to data assimilation is a widely used methodology for both online prediction and for reanalysis. In either of these scenarios, it can be important to assess uncertainties in the assimilated state. Ideally, it is desirable to have complete information concerning the Bayesian posterior distribution for unknown state given data. We show that complete computational probing of this posterior distribution is now within the reach in the offline situation. We introduce a Markov chain-Monte Carlo (MCMC) method which enables us to directly sample from the Bayesian posterior distribution on the unknown functions of interest given observations. Since we are aware that these methods are currently too computationally expensive to consider using in an online filtering scenario, we frame this in the context of offline reanalysis. Using a simple random walk-type MCMC method, we are able to characterize the posterior distribution using only evaluations of the forward model of the problem, and of the model and data mismatch. No adjoint model is required for the method we use; however, more sophisticated MCMC methods are available which exploit derivative information. For simplicity of exposition, we consider the problem of assimilating data, either Eulerian or Lagrangian, into a low Reynolds number flow in a two-dimensional periodic geometry. We will show that in many cases it is possible to recover the initial condition and model error (which we describe as unknown forcing to the model) from data, and that with increasing amounts of informative data, the uncertainty in our estimations reduces. © 2011 John Wiley & Sons, Ltd.

  3. Nitrogen uptake and assimilation by corn roots

    International Nuclear Information System (INIS)

    Yoneyama, Tadakatsu; Akiyama, Yoko; Kumazawa, Kikuo

    1977-01-01

    The site of nitrogen uptake in the apical root zone of corn was experimentally investigated. Two experiments were performed. The one is to see the assimilation of nitrate and ammonium and the effects of low temperature on it. The 4-day-old roots were treated with 15 N-labelled inorganic nitrogen of 20 ppm N in 5 x 10 -4 M CaSO 4 solution at 30 deg. C and 0 deg. C. The other is to see the nitrogen uptake at apical root zone and the utilization of newly absorbed nitrogen at the root top. The 4-day-old roots were transferred into 5 x 10 -4 M CaSO 4 solution containing 15 N-labelled ammonium nitrate of 40 ppm N. As a result, the effect of low temperature on the nitrogen uptake appeared to be more drastic in the case of nitrate than ammonium. The 15 N content of amino acids indicates that ammonium is assimilated into amino acids even at 0 deg. C, but nitrate is not. The ammonium nitrogen seemed to be absorbed at both cell dividing and elongating zones. On the other hand, nitrate nitrogen seemed to be strongly absorbed at cell elongating zone. The nitrogen in the apical part may be supplied not only by direct absorption but also by translocation from the basal part. The clear difference was found in the utilization of nitrate and ammonium nitrogen at the root top when the root was elongating. This may be due to the difference of assimilation products of inorganic nitrogen. Newly absorbed ammonium nitrogen is more utilizable for the growth of root top than nitrate nitrogen. (Iwakiri, K.)

  4. Data assimilation strategies for volcano geodesy

    Science.gov (United States)

    Zhan, Yan; Gregg, Patricia M.

    2017-09-01

    Ground deformation observed using near-real time geodetic methods, such as InSAR and GPS, can provide critical information about the evolution of a magma chamber prior to volcanic eruption. Rapid advancement in numerical modeling capabilities has resulted in a number of finite element models targeted at better understanding the connection between surface uplift associated with magma chamber pressurization and the potential for volcanic eruption. Robust model-data fusion techniques are necessary to take full advantage of the numerical models and the volcano monitoring observations currently available. In this study, we develop a 3D data assimilation framework using the Ensemble Kalman Filter (EnKF) approach in order to combine geodetic observations of surface deformation with geodynamic models to investigate volcanic unrest. The EnKF sequential assimilation method utilizes disparate data sets as they become available to update geodynamic models of magma reservoir evolution. While the EnKF has been widely applied in hydrologic and climate modeling, the adaptation for volcano monitoring is in its initial stages. As such, our investigation focuses on conducting a series of sensitivity tests to optimize the EnKF for volcano applications and on developing specific strategies for assimilation of geodetic data. Our numerical experiments illustrate that the EnKF is able to adapt well to the spatial limitations posed by GPS data and the temporal limitations of InSAR, and that specific strategies can be adopted to enhance EnKF performance to improve model forecasts. Specifically, our numerical experiments indicate that: (1) incorporating additional iterations of the EnKF analysis step is more efficient than increasing the number of ensemble members; (2) the accuracy of the EnKF results are not affected by initial parameter assumptions; (3) GPS observations near the center of uplift improve the quality of model forecasts; (4) occasionally shifting continuous GPS stations to

  5. Data assimilation approaches in the EURANOS project

    DEFF Research Database (Denmark)

    Kaiser, J.C.; Gering, F.; Astrup, Poul

    2010-01-01

    -nuclides in urban areas the results of demonstration exercises are presented here. With the data assimilation module of the RIMPUFF dispersion code, predictions of the gamma dose rate are corrected with simulated readings of fixed detector stations. Using the DA capabilities of the IAMM package for mapping...... the radioactive contamination in inhabited areas, predictions of a large scale deposition model have been combined with hypothetical measurements on a local scale. In both examples the accuracy of the model predictions has been improved and the uncertainties have been reduced. © EDP Sciences, 2010...

  6. Improving carbon model phenology using data assimilation

    Science.gov (United States)

    Exrayat, Jean-François; Smallman, T. Luke; Bloom, A. Anthony; Williams, Mathew

    2015-04-01

    Carbon cycle dynamics is significantly impacted by ecosystem phenology, leading to substantial seasonal and inter-annual variation in the global carbon balance. Representing inter-annual variability is key for predicting the response of the terrestrial ecosystem to climate change and disturbance. Existing terrestrial ecosystem models (TEMs) often struggle to accurately simulate observed inter-annual variability. TEMs often use different phenological models based on plant functional type (PFT) assumptions. Moreover, due to a high level of computational overhead in TEMs they are unable to take advantage of globally available datasets to calibrate their models. Here we describe the novel CARbon DAta MOdel fraMework (CARDAMOM) for data assimilation. CARDAMOM is used to calibrate the Data Assimilation Linked Ecosystem Carbon version 2 (DALEC2) model using Bayes' Theorem within a Metropolis Hastings - Markov Chain Monte Carlo (MH-MCMC). CARDAMOM provides a framework which combines knowledge from observations, such as remotely sensed LAI, and heuristic information in the form of Ecological and Dynamical Constraints (EDCs). The EDCs are representative of real world processes and constrain parameter interdependencies and constrain carbon dynamics. We used CARDAMOM to bring together globally spanning datasets of LAI and the DALEC2 and DALEC2-GSI models. These analyses allow us to investigate the sensitivity ecosystem processes to the representation of phenology. DALEC2 uses an analytically solved model of phenology which is invariant between years. In contrast DALEC2-GSI uses a growing season index (GSI) calculated as a function of temperature, vapour pressure deficit (VPD) and photoperiod to calculate bud-burst and leaf senescence, allowing the model to simulate inter-annual variability in response to climate. Neither model makes any PFT assumptions about the phenological controls of a given ecosystem, allowing the data alone to determine the impact of the meteorological

  7. First assimilations of COSMIC radio occultation data into the Electron Density Assimilative Model (EDAM

    Directory of Open Access Journals (Sweden)

    M. J. Angling

    2008-02-01

    Full Text Available Ground based measurements of slant total electron content (TEC can be assimilated into ionospheric models to produce 3-D representations of ionospheric electron density. The Electron Density Assimilative Model (EDAM has been developed for this purpose. Previous tests using EDAM and ground based data have demonstrated that the information on the vertical structure of the ionosphere is limited in this type of data. The launch of the COSMIC satellite constellation provides the opportunity to use radio occultation data which has more vertical information. EDAM assimilations have been run for three time periods representing quiet, moderate and disturbed geomagnetic conditions. For each run, three data sets have been ingested – only ground based data, only COSMIC data and both ground based and COSMIC data. The results from this preliminary study show that both ground and space based data are capable of improving the representation of the vertical structure of the ionosphere. However, the analysis is limited by the incomplete deployment of the COSMIC constellation and the use of auto-scaled ionosonde data. The first of these can be addressed by repeating this type of study once full deployment has been achieved. The latter requires the manual scaling of ionosonde data; ideally an agreed data set would be scaled and made available to the community to facilitate comparative testing of assimilative models.

  8. Development of airborne remote sensing data assimilation system

    International Nuclear Information System (INIS)

    Gudu, B R; Bi, H Y; Wang, H Y; Qin, S X; Ma, J W

    2014-01-01

    In this paper, an airborne remote sensing data assimilation system for China Airborne Remote Sensing System is introduced. This data assimilation system is composed of a land surface model, data assimilation algorithms, observation data and fundamental parameters forcing the land surface model. In this data assimilation system, Variable Infiltration Capacity hydrologic model is selected as the land surface model, which also serves as the main framework of the system. Three-dimensional variation algorithm, four-dimensional variation algorithms, ensemble Kalman filter and Particle filter algorithms are integrated in this system. Observation data includes ground observations and remotely sensed data. The fundamental forcing parameters include soil parameters, vegetation parameters and the meteorological data

  9. Boundary Conditions, Data Assimilation, and Predictability in Coastal Ocean Models

    National Research Council Canada - National Science Library

    Samelson, Roger M; Allen, John S; Egbert, Gary D; Kindle, John C; Snyder, Chris

    2007-01-01

    ...: The specific objectives of this research are to determine the impact on coastal ocean circulation models of open ocean boundary conditions from Global Ocean Data Assimilation Experiment (GODAE...

  10. Assimilation of enterprise technology upgrades: a factor-based study

    Science.gov (United States)

    Claybaugh, Craig C.; Ramamurthy, Keshavamurthy; Haseman, William D.

    2017-02-01

    The purpose of this study is to gain a better understanding of the differences in the propensity of firms to initiate and commit to the assimilation of an enterprise technology upgrade. A research model is proposed that examines the influences that four technological and four organisational factors have on predicting assimilation of a technology upgrade. Results show that firms with a greater propensity to assimilate the new enterprise resource planning (ERP) version have a higher assessment of relative advantage, IS technical competence, and the strategic role of IS relative to those firms with a lower propensity to assimilate a new ERP version.

  11. Data assimilation and PWR primary measurement

    International Nuclear Information System (INIS)

    Mercier, Thibaud

    2015-01-01

    A Pressurized Water Reactor (PWR) Reactor Coolant System (RCS) is a highly complex physical process: heterogeneous power, flow and temperature distributions are difficult to be accurately measured, since instrumentations are limited in number, thus leading to the relevant safety and protection margins. EDF R and D is seeking to assess the potential benefits of applying Data Assimilation to a PWR's RCS (Reactor Coolant System) measurements, in order to improve the estimators for parameters of a reactor's operating setpoint, i.e. improving accuracy and reducing uncertainties and biases of measured RCS parameters. In this thesis, we define a 0D semi-empirical model for RCS, satisfying the description level usually chosen by plant operators, and construct a Monte-Carlo Method (inspired from Ensemble Methods) in order to use this model with Data Assimilation tools. We apply this method on simulated data in order to assess the reduction of uncertainties on key parameters: results are beyond expectations, however strong hypothesis are required, implying a careful preprocessing of input data. (author)

  12. Data Assimilation by delay-coordinate nudging

    Science.gov (United States)

    Pazo, Diego; Lopez, Juan Manuel; Carrassi, Alberto

    2016-04-01

    A new nudging method for data assimilation, delay-coordinate nudging, is presented. Delay-coordinate nudging makes explicit use of present and past observations in the formulation of the forcing driving the model evolution at each time-step. Numerical experiments with a low order chaotic system show that the new method systematically outperforms standard nudging in different model and observational scenarios, also when using an un-optimized formulation of the delay-nudging coefficients. A connection between the optimal delay and the dominant Lyapunov exponent of the dynamics is found based on heuristic arguments and is confirmed by the numerical results, providing a guideline for the practical implementation of the algorithm. Delay-coordinate nudging preserves the easiness of implementation, the intuitive functioning and the reduced computational cost of the standard nudging, making it a potential alternative especially in the field of seasonal-to-decadal predictions with large Earth system models that limit the use of more sophisticated data assimilation procedures.

  13. Turbulent viscosity optimized by data assimilation

    Directory of Open Access Journals (Sweden)

    Y. Leredde

    Full Text Available As an alternative approach to classical turbulence modelling using a first or second order closure, the data assimilation method of optimal control is applied to estimate a time and space-dependent turbulent viscosity in a three-dimensional oceanic circulation model. The optimal control method, described for a 3-D primitive equation model, involves the minimization of a cost function that quantifies the discrepancies between the simulations and the observations. An iterative algorithm is obtained via the adjoint model resolution. In a first experiment, a k + L model is used to simulate the one-dimensional development of inertial oscillations resulting from a wind stress at the sea surface and with the presence of a halocline. These results are used as synthetic observations to be assimilated. The turbulent viscosity is then recovered without the k + L closure, even with sparse and noisy observations. The problems of controllability and of the dimensions of the control are then discussed. A second experiment consists of a two-dimensional schematic simulation. A 2-D turbulent viscosity field is estimated from data on the initial and final states of a coastal upwelling event.

    Key words. Oceanography: general (numerical modelling · Oceanography: physical (turbulence · diffusion · and mixing processes

  14. Impact of Assimilation on Heavy Rainfall Simulations Using WRF Model: Sensitivity of Assimilation Results to Background Error Statistics

    Science.gov (United States)

    Rakesh, V.; Kantharao, B.

    2017-03-01

    Data assimilation is considered as one of the effective tools for improving forecast skill of mesoscale models. However, for optimum utilization and effective assimilation of observations, many factors need to be taken into account while designing data assimilation methodology. One of the critical components that determines the amount and propagation observation information into the analysis, is model background error statistics (BES). The objective of this study is to quantify how BES in data assimilation impacts on simulation of heavy rainfall events over a southern state in India, Karnataka. Simulations of 40 heavy rainfall events were carried out using Weather Research and Forecasting Model with and without data assimilation. The assimilation experiments were conducted using global and regional BES while the experiment with no assimilation was used as the baseline for assessing the impact of data assimilation. The simulated rainfall is verified against high-resolution rain-gage observations over Karnataka. Statistical evaluation using several accuracy and skill measures shows that data assimilation has improved the heavy rainfall simulation. Our results showed that the experiment using regional BES outperformed the one which used global BES. Critical thermo-dynamic variables conducive for heavy rainfall like convective available potential energy simulated using regional BES is more realistic compared to global BES. It is pointed out that these results have important practical implications in design of forecast platforms while decision-making during extreme weather events

  15. A Readily Accessible Class of Chiral Cp Ligands and their Application in RuII -Catalyzed Enantioselective Syntheses of Dihydrobenzoindoles.

    Science.gov (United States)

    Wang, Shou-Guo; Park, Sung Hwan; Cramer, Nicolai

    2018-05-04

    Chiral cyclopentadienyl (Cp x ) ligands have a large application potential in enantioselective transition-metal catalysis. However, the development of concise and practical routes to such ligands remains in its infancy. We present a convenient and efficient two-step synthesis of a novel class of chiral Cp x ligands with tunable steric properties that can be readily used for complexation, giving Cp x Rh I , Cp x Ir I , and Cp x Ru II complexes. The potential of this ligand class is demonstrated with the latter in the enantioselective cyclization of azabenzonorbornadienes with alkynes, affording dihydrobenzoindoles in up to 98:2 e.r., significantly outperforming existing binaphthyl-derived Cp x ligands. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Development of a software framework for data assimilation and its applications for streamflow forecasting in Japan

    Science.gov (United States)

    Noh, S. J.; Tachikawa, Y.; Shiiba, M.; Yorozu, K.; Kim, S.

    2012-04-01

    Data assimilation methods have received increased attention to accomplish uncertainty assessment and enhancement of forecasting capability in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modeling software are based on a deterministic approach. In this study, we developed a hydrological modeling framework for sequential data assimilation, so called MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modeling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. Sequential data assimilation based on the particle filters is available for any hydrologic models based on MPI-OHyMoS considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for short-term streamflow forecasting of several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and remotely-sensed rainfall data such as X-band or C-band radar is estimated and mitigated in the sequential data assimilation.

  17. Interaction of Sulfate Assimilation with Carbon and Nitrogen Metabolism in Lemna minor1

    Science.gov (United States)

    Kopriva, Stanislav; Suter, Marianne; von Ballmoos, Peter; Hesse, Holger; Krähenbühl, Urs; Rennenberg, Heinz; Brunold, Christian

    2002-01-01

    Cysteine synthesis from sulfide and O-acetyl-l-serine (OAS) is a reaction interconnecting sulfate, nitrogen, and carbon assimilation. Using Lemna minor, we analyzed the effects of omission of CO2 from the atmosphere and simultaneous application of alternative carbon sources on adenosine 5′-phosphosulfate reductase (APR) and nitrate reductase (NR), the key enzymes of sulfate and nitrate assimilation, respectively. Incubation in air without CO2 led to severe decrease in APR and NR activities and mRNA levels, but ribulose-1,5-bisphosphate carboxylase/oxygenase was not considerably affected. Simultaneous addition of sucrose (Suc) prevented the reduction in enzyme activities, but not in mRNA levels. OAS, a known regulator of sulfate assimilation, could also attenuate the effect of missing CO2 on APR, but did not affect NR. When the plants were subjected to normal air after a 24-h pretreatment in air without CO2, APR and NR activities and mRNA levels recovered within the next 24 h. The addition of Suc and glucose in air without CO2 also recovered both enzyme activities, with OAS again influenced only APR. 35SO42− feeding showed that treatment in air without CO2 severely inhibited sulfate uptake and the flux through sulfate assimilation. After a resupply of normal air or the addition of Suc, incorporation of 35S into proteins and glutathione greatly increased. OAS treatment resulted in high labeling of cysteine; the incorporation of 35S in proteins and glutathione was much less increased compared with treatment with normal air or Suc. These results corroborate the tight interconnection of sulfate, nitrate, and carbon assimilation. PMID:12428005

  18. Global NOx emission estimates derived from an assimilation of OMI tropospheric NO2 columns

    Directory of Open Access Journals (Sweden)

    K. Sudo

    2012-03-01

    Full Text Available A data assimilation system has been developed to estimate global nitrogen oxides (NOx emissions using OMI tropospheric NO2 columns (DOMINO product and a global chemical transport model (CTM, the Chemical Atmospheric GCM for Study of Atmospheric Environment and Radiative Forcing (CHASER. The data assimilation system, based on an ensemble Kalman filter approach, was applied to optimize daily NOx emissions with a horizontal resolution of 2.8° during the years 2005 and 2006. The background error covariance estimated from the ensemble CTM forecasts explicitly represents non-direct relationships between the emissions and tropospheric columns caused by atmospheric transport and chemical processes. In comparison to the a priori emissions based on bottom-up inventories, the optimized emissions were higher over eastern China, the eastern United States, southern Africa, and central-western Europe, suggesting that the anthropogenic emissions are mostly underestimated in the inventories. In addition, the seasonality of the estimated emissions differed from that of the a priori emission over several biomass burning regions, with a large increase over Southeast Asia in April and over South America in October. The data assimilation results were validated against independent data: SCIAMACHY tropospheric NO2 columns and vertical NO2 profiles obtained from aircraft and lidar measurements. The emission correction greatly improved the agreement between the simulated and observed NO2 fields; this implies that the data assimilation system efficiently derives NOx emissions from concentration observations. We also demonstrated that biases in the satellite retrieval and model settings used in the data assimilation largely affect the magnitude of estimated emissions. These dependences should be carefully considered for better understanding NOx sources from top-down approaches.

  19. Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

    Directory of Open Access Journals (Sweden)

    Tao Wang

    Full Text Available Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique improve the simulation accuracy of mean seasonal (October throughout May snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the

  20. Assimilation of flood extent data with 2D flood inundation models for localised intense rainfall events

    Science.gov (United States)

    Neal, J. C.; Wood, M.; Bermúdez, M.; Hostache, R.; Freer, J. E.; Bates, P. D.; Coxon, G.

    2017-12-01

    Remote sensing of flood inundation extent has long been a potential source of data for constraining and correcting simulations of floodplain inundation. Hydrodynamic models and the computing resources to run them have developed to the extent that simulation of flood inundation in two-dimensional space is now feasible over large river basins in near real-time. However, despite substantial evidence that there is useful information content within inundation extent data, even from low resolution SAR such as that gathered by Envisat ASAR in wide swath mode, making use of the information in a data assimilation system has proved difficult. He we review recent applications of the Ensemble Kalman Filter (EnKF) and Particle Filter for assimilating SAR data, with a focus on the River Severn UK and compare these with complementary research that has looked at the internal error sources and boundary condition errors using detailed terrestrial data that is not available in most locations. Previous applications of the EnKF to this reach have focused on upstream boundary conditions as the source of flow error, however this description of errors was too simplistic for the simulation of summer flood events where localised intense rainfall can be substantial. Therefore, we evaluate the introduction of uncertain lateral inflows to the ensemble. A further limitation of the existing EnKF based methods is the need to convert flood extent to water surface elevations by intersecting the shoreline location with a high quality digital elevation model (e.g. LiDAR). To simplify this data processing step, we evaluate a method to directly assimilate inundation extent as a EnKF model state rather than assimilating water heights, potentially allowing the scheme to be used where high-quality terrain data are sparse.

  1. Data assimilation in the decision support system RODOS

    DEFF Research Database (Denmark)

    Rojas-Palma, C.; Madsen, H.; Gering, F.

    2003-01-01

    . The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based on Kalman...

  2. Assimilation as Attraction: Computing Distance, Similarity, and Locality in Phonology

    Science.gov (United States)

    Wayment, Adam

    2009-01-01

    This dissertation explores similarity effects in assimilation, proposing an Attraction Framework to analyze cases of parasitic harmony where a trigger-target pair only results in harmony if the trigger and target agree on other features. Attraction provides a natural model of these effects by relating the pressure for assimilation to the…

  3. The dynamic radiation environment assimilation model (DREAM)

    International Nuclear Information System (INIS)

    Reeves, Geoffrey D.; Koller, Josef; Tokar, Robert L.; Chen, Yue; Henderson, Michael G.; Friedel, Reiner H.

    2010-01-01

    The Dynamic Radiation Environment Assimilation Model (DREAM) is a 3-year effort sponsored by the US Department of Energy to provide global, retrospective, or real-time specification of the natural and potential nuclear radiation environments. The DREAM model uses Kalman filtering techniques that combine the strengths of new physical models of the radiation belts with electron observations from long-term satellite systems such as GPS and geosynchronous systems. DREAM includes a physics model for the production and long-term evolution of artificial radiation belts from high altitude nuclear explosions. DREAM has been validated against satellites in arbitrary orbits and consistently produces more accurate results than existing models. Tools for user-specific applications and graphical displays are in beta testing and a real-time version of DREAM has been in continuous operation since November 2009.

  4. Transgenic plants that exhibit enhanced nitrogen assimilation

    Science.gov (United States)

    Coruzzi, Gloria M.; Brears, Timothy

    1999-01-01

    The present invention relates to a method for producing plants with improved agronomic and nutritional traits. Such traits include enhanced nitrogen assimilatory and utilization capacities, faster and more vigorous growth, greater vegetative and reproductive yields, and enriched or altered nitrogen content in vegetative and reproductive parts. More particularly, the invention relates to the engineering of plants modified to have altered expression of key enzymes in the nitrogen assimilation and utilization pathways. In one embodiment of the present invention, the desired altered expression is accomplished by engineering the plant for ectopic overexpression of one of more the native or modified nitrogen assimilatory enzymes. The invention also has a number of other embodiments, all of which are disclosed herein.

  5. Assimilating data into open ocean tidal models

    Science.gov (United States)

    Kivman, Gennady A.

    The problem of deriving tidal fields from observations by reason of incompleteness and imperfectness of every data set practically available has an infinitely large number of allowable solutions fitting the data within measurement errors and hence can be treated as ill-posed. Therefore, interpolating the data always relies on some a priori assumptions concerning the tides, which provide a rule of sampling or, in other words, a regularization of the ill-posed problem. Data assimilation procedures used in large scale tide modeling are viewed in a common mathematical framework as such regularizations. It is shown that they all (basis functions expansion, parameter estimation, nudging, objective analysis, general inversion, and extended general inversion), including those (objective analysis and general inversion) originally formulated in stochastic terms, may be considered as utilizations of one of the three general methods suggested by the theory of ill-posed problems. The problem of grid refinement critical for inverse methods and nudging is discussed.

  6. A new approach for assimilation of 2D radar precipitation in a high-resolution NWP model

    DEFF Research Database (Denmark)

    Korsholm, Ulrik Smith; Petersen, Claus; Sass, Bent Hansen

    2015-01-01

    of precipitation, the strength of the nudging is proportional to the offset between observed and modelled precipitation, leading to increased moisture convergence. If the model over-predicts precipitation, the low level moisture source is reduced, and in-cloud moisture is nudged towards environmental values......A new approach for assimilation of 2D precipitation in numerical weather prediction models is presented and tested in a case with convective, heavy precipitation. In the scheme a nudging term is added to the horizontal velocity divergence tendency equation. In case of underproduction....... The method was implemented in the Danish Meteorological Institute numerical weather prediction (DMI NWP) nowcasting system, running with hourly cycles, performing a surface analysis and 3D variational analysis for upper air assimilation at each cycle restart, followed by nudging assimilation of precipitation...

  7. Visions and Revisions: Seamus Heaney, ‘Foreign’ Poetry, and The Problem of Assimilation

    Directory of Open Access Journals (Sweden)

    Magdalena Kay

    2015-07-01

    Full Text Available This essay considers the unusual position of Irish and Polish cultures and how it correlates to the construction of lyric subjects that appear unassimilable to dominant postcolonial literary-critical paradigms. Translation and assimilation become crucial concepts when understood in relation to attempts to take inspiration from foreign sources, especially when such attempts do not accord with typical patterns of influence. These concepts, however, only reveal their utility when they are grounded. The problem of assimilation is here considered in reference to debates over the Eastern European influences behind Seamus Heaney’s volume The Haw Lantern, which reveal the cultural pressures brought to bear upon a well-known poet whose work challenges dominant assumptions about the proper idiom of the Anglo-American lyric.

  8. Processing of 3D Weather Radar Data with Application for Assimilation in the NWP Model

    Directory of Open Access Journals (Sweden)

    Ośródka Katarzyna

    2014-09-01

    Full Text Available The paper is focused on the processing of 3D weather radar data to minimize the impact of a number of errors from different sources, both meteorological and non-meteorological. The data is also quantitatively characterized in terms of its quality. A set of dedicated algorithms based on analysis of the reflectivity field pattern is described. All the developed algorithms were tested on data from the Polish radar network POLRAD. Quality control plays a key role in avoiding the introduction of incorrect information into applications using radar data. One of the quality control methods is radar data assimilation in numerical weather prediction models to estimate initial conditions of the atmosphere. The study shows an experiment with quality controlled radar data assimilation in the COAMPS model using the ensemble Kalman filter technique. The analysis proved the potential of radar data for such applications; however, further investigations will be indispensable.

  9. Cellulose degradation and assimilation by the unicellular phototrophic eukaryote Chlamydomonas reinhardtii.

    Science.gov (United States)

    Blifernez-Klassen, Olga; Klassen, Viktor; Doebbe, Anja; Kersting, Klaudia; Grimm, Philipp; Wobbe, Lutz; Kruse, Olaf

    2012-01-01

    Plants convert sunlight to biomass, which is primarily composed of lignocellulose, the most abundant natural biopolymer and a potential feedstock for fuel and chemical production. Cellulose assimilation has so far only been described for heterotrophic organisms that rely on photosynthetically active primary producers of organic compounds. Among phototrophs, the unicellular green microalga Chlamydomonas reinhardtii is widely known as one of the best established model organisms. It occupies many habitats, including aquatic and soil ecosystems. This ubiquity underscores the versatile metabolic properties of this microorganism. Here we present yet another paradigm of adaptation for C. reinhardtii, highlighting its photoheterotrophic ability to utilize cellulose for growth in the absence of other carbon sources. When grown under CO(2)-limiting conditions in the light, secretion of endo-β-1,4-glucanases by the cell causes digestion of exogenous cellulose, followed by cellobiose uptake and assimilation. Phototrophic microbes like C. reinhardtii may thus serve as biocatalysts for cellulosic biofuel production.

  10. Salting our landscape: An integrated catchment model using readily accessible data to assess emerging road salt contamination to streams

    International Nuclear Information System (INIS)

    Jin Li; Whitehead, Paul; Siegel, Donald I.; Findlay, Stuart

    2011-01-01

    A new integrated catchment model for salinity has been developed to assess the transport of road salt from upland areas in watersheds to streams using readily accessible landscape, hydrologic, and meteorological data together with reported salt applications. We used Fishkill Creek (NY) as a representative watershed to test the model. Results showed good agreement between modeled and measured stream water chloride concentrations. These results suggest that a dominant mode of catchment simulation that does not entail complex deterministic modeling is an appropriate method to model salinization and to assess effects of future applications of road salt to streams. We heuristically increased and decreased salt applications by 100% and results showed that stream chloride concentrations increased by 13% and decreased by 7%, respectively. The model suggests that future management of salt application can reduce environmental concentrations, albeit over some time. - Highlights: → A new Integrated Catchment Model (INCA-Cl) is developed to simulate salinity. → Road salt application is important in controlling stream chloride concentration. → INCA-Cl can be used to manage and forecast the input and transport of chloride to the rivers. - A newly developed integrated catchment model for salinity can be used to manage and forecast the inputs and transport of chloride to streams.

  11. Salting our landscape: An integrated catchment model using readily accessible data to assess emerging road salt contamination to streams

    Energy Technology Data Exchange (ETDEWEB)

    Jin Li, E-mail: li.jin@ouce.ox.ac.uk [Earth Sciences Department, Syracuse University, Syracuse, NY 13210 (United States); School of Geography and the Environment, University of Oxford, Oxford, OX1 3QY (United Kingdom); Whitehead, Paul [School of Geography and the Environment, University of Oxford, Oxford, OX1 3QY (United Kingdom); Siegel, Donald I. [Earth Sciences Department, Syracuse University, Syracuse, NY 13210 (United States); Findlay, Stuart [Cary Institute of Ecosystem Studies, 2801 Sharon Turnpike, Millbrook, NY 12545 (United States)

    2011-05-15

    A new integrated catchment model for salinity has been developed to assess the transport of road salt from upland areas in watersheds to streams using readily accessible landscape, hydrologic, and meteorological data together with reported salt applications. We used Fishkill Creek (NY) as a representative watershed to test the model. Results showed good agreement between modeled and measured stream water chloride concentrations. These results suggest that a dominant mode of catchment simulation that does not entail complex deterministic modeling is an appropriate method to model salinization and to assess effects of future applications of road salt to streams. We heuristically increased and decreased salt applications by 100% and results showed that stream chloride concentrations increased by 13% and decreased by 7%, respectively. The model suggests that future management of salt application can reduce environmental concentrations, albeit over some time. - Highlights: > A new Integrated Catchment Model (INCA-Cl) is developed to simulate salinity. > Road salt application is important in controlling stream chloride concentration. > INCA-Cl can be used to manage and forecast the input and transport of chloride to the rivers. - A newly developed integrated catchment model for salinity can be used to manage and forecast the inputs and transport of chloride to streams.

  12. Improved fermentative L-cysteine overproduction by enhancing a newly identified thiosulfate assimilation pathway in Escherichia coli.

    Science.gov (United States)

    Kawano, Yusuke; Onishi, Fumito; Shiroyama, Maeka; Miura, Masashi; Tanaka, Naoyuki; Oshiro, Satoshi; Nonaka, Gen; Nakanishi, Tsuyoshi; Ohtsu, Iwao

    2017-09-01

    Sulfate (SO 4 2- ) is an often-utilized and well-understood inorganic sulfur source in microorganism culture. Recently, another inorganic sulfur source, thiosulfate (S 2 O 3 2- ), was proposed to be more advantageous in microbial growth and biotechnological applications. Although its assimilation pathway is known to depend on O-acetyl-L-serine sulfhydrylase B (CysM in Escherichia coli), its metabolism has not been extensively investigated. Therefore, we aimed to explore another yet-unidentified CysM-independent thiosulfate assimilation pathway in E. coli. ΔcysM cells could accumulate essential L-cysteine from thiosulfate as the sole sulfur source and could grow, albeit slowly, demonstrating that a CysM-independent thiosulfate assimilation pathway is present in E. coli. This pathway is expected to consist of the initial part of the thiosulfate to sulfite (SO 3 2- ) conversion, and the latter part might be shared with the final part of the known sulfate assimilation pathway [sulfite → sulfide (S 2- ) → L-cysteine]. This is because thiosulfate-grown ΔcysM cells could accumulate a level of sulfite and sulfide equivalent to that of wild-type cells. The catalysis of thiosulfate to sulfite is at least partly mediated by thiosulfate sulfurtransferase (GlpE), because its overexpression could enhance cellular thiosulfate sulfurtransferase activity in vitro and complement the slow-growth phenotype of thiosulfate-grown ΔcysM cells in vivo. GlpE is therefore concluded to function in the novel CysM-independent thiosulfate assimilation pathway by catalyzing thiosulfate to sulfite. We applied this insight to L-cysteine overproduction in E. coli and succeeded in enhancing it by GlpE overexpression in media containing glucose or glycerol as the main carbon source, by up to ~1.7-fold (1207 mg/l) or ~1.5-fold (1529 mg/l), respectively.

  13. Assimilation of stratospheric ozone in the chemical transport model STRATAQ

    Directory of Open Access Journals (Sweden)

    B. Grassi

    2004-09-01

    Full Text Available We describe a sequential assimilation approach useful for assimilating tracer measurements into a three-dimensional chemical transport model (CTM of the stratosphere. The numerical code, developed largely according to Kha00, uses parameterizations and simplifications allowing assimilation of sparse observations and the simultaneous evaluation of analysis errors, with reasonable computational requirements. Assimilation parameters are set by using χ2 and OmF (Observation minus Forecast statistics. The CTM used here is a high resolution three-dimensional model. It includes a detailed chemical package and is driven by UKMO (United Kingdom Meteorological Office analyses. We illustrate the method using assimilation of Upper Atmosphere Research Satellite/Microwave Limb Sounder (UARS/MLS ozone observations for three weeks during the 1996 antarctic spring. The comparison of results from the simulations with TOMS (Total Ozone Mapping Spectrometer measurements shows improved total ozone fields due to assimilation of MLS observations. Moreover, the assimilation gives indications on a possible model weakness in reproducing polar ozone values during springtime.

  14. Statistical techniques to extract information during SMAP soil moisture assimilation

    Science.gov (United States)

    Kolassa, J.; Reichle, R. H.; Liu, Q.; Alemohammad, S. H.; Gentine, P.

    2017-12-01

    Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, the need for bias correction prior to an assimilation of these estimates is reduced, which could result in a more effective use of the independent information provided by the satellite observations. In this study, a statistical neural network (NN) retrieval algorithm is calibrated using SMAP brightness temperature observations and modeled soil moisture estimates (similar to those used to calibrate the SMAP Level 4 DA system). Daily values of surface soil moisture are estimated using the NN and then assimilated into the NASA Catchment model. The skill of the assimilation estimates is assessed based on a comprehensive comparison to in situ measurements from the SMAP core and sparse network sites as well as the International Soil Moisture Network. The NN retrieval assimilation is found to significantly improve the model skill, particularly in areas where the model does not represent processes related to agricultural practices. Additionally, the NN method is compared to assimilation experiments using traditional bias correction techniques. The NN retrieval assimilation is found to more effectively use the independent information provided by SMAP resulting in larger model skill improvements than assimilation experiments using traditional bias correction techniques.

  15. On the role of perception in shaping phonological assimilation rules.

    Science.gov (United States)

    Hura, S L; Lindblom, B; Diehl, R L

    1992-01-01

    Assimilation of nasals to the place of articulation of following consonants is a common and natural process among the world's languages. Recent phonological theory attributes this naturalness to the postulated geometry of articulatory features and the notion of spreading (McCarthy, 1988). Others view assimilation as a result of perception (Ohala, 1990), or as perceptually tolerated articulatory simplification (Kohler, 1990). Kohler notes that certain consonant classes (such as nasals and stops) are more likely than other classes (such as fricatives) to undergo place assimilation to a following consonant. To explain this pattern, he proposes that assimilation tends not to occur when the members of a consonant class are relatively distinctive perceptually, such that their articulatory reduction would be particularly salient. This explanation, of course, presupposes that the stops and nasals which undergo place assimilation are less distinctive than fricatives, which tend not to assimilate. We report experimental results that confirm Kohler's perceptual assumption: In the context of a following word initial stop, fricatives were less confusable than nasals or unreleased stops. We conclude, in agreement with Ohala and Kohler, that perceptual factors are likely to shape phonological assimilation rules.

  16. Assimilation of stratospheric ozone in the chemical transport model STRATAQ

    Directory of Open Access Journals (Sweden)

    B. Grassi

    2004-09-01

    Full Text Available We describe a sequential assimilation approach useful for assimilating tracer measurements into a three-dimensional chemical transport model (CTM of the stratosphere. The numerical code, developed largely according to Kha00, uses parameterizations and simplifications allowing assimilation of sparse observations and the simultaneous evaluation of analysis errors, with reasonable computational requirements. Assimilation parameters are set by using χ2 and OmF (Observation minus Forecast statistics. The CTM used here is a high resolution three-dimensional model. It includes a detailed chemical package and is driven by UKMO (United Kingdom Meteorological Office analyses. We illustrate the method using assimilation of Upper Atmosphere Research Satellite/Microwave Limb Sounder (UARS/MLS ozone observations for three weeks during the 1996 antarctic spring. The comparison of results from the simulations with TOMS (Total Ozone Mapping Spectrometer measurements shows improved total ozone fields due to assimilation of MLS observations. Moreover, the assimilation gives indications on a possible model weakness in reproducing polar ozone values during springtime.

  17. SMOS brightness temperature assimilation into the Community Land Model

    Directory of Open Access Journals (Sweden)

    D. Rains

    2017-11-01

    Full Text Available SMOS (Soil Moisture and Ocean Salinity mission brightness temperatures at a single incident angle are assimilated into the Community Land Model (CLM across Australia to improve soil moisture simulations. Therefore, the data assimilation system DasPy is coupled to the local ensemble transform Kalman filter (LETKF as well as to the Community Microwave Emission Model (CMEM. Brightness temperature climatologies are precomputed to enable the assimilation of brightness temperature anomalies, making use of 6 years of SMOS data (2010–2015. Mean correlation R with in situ measurements increases moderately from 0.61 to 0.68 (11 % for upper soil layers if the root zone is included in the updates. A reduced improvement of 5 % is achieved if the assimilation is restricted to the upper soil layers. Root-zone simulations improve by 7 % when updating both the top layers and root zone, and by 4 % when only updating the top layers. Mean increments and increment standard deviations are compared for the experiments. The long-term assimilation impact is analysed by looking at a set of quantiles computed for soil moisture at each grid cell. Within hydrological monitoring systems, extreme dry or wet conditions are often defined via their relative occurrence, adding great importance to assimilation-induced quantile changes. Although still being limited now, longer L-band radiometer time series will become available and make model output improved by assimilating such data that are more usable for extreme event statistics.

  18. Chromatic assimilation unaffected by perceived depth of inducing light.

    Science.gov (United States)

    Shevell, Steven K; Cao, Dingcai

    2004-01-01

    Chromatic assimilation is a shift toward the color of nearby light. Several studies conclude that a neural process contributes to assimilation but the neural locus remains in question. Some studies posit a peripheral process, such as retinal receptive-field organization, while others claim the neural mechanism follows depth perception, figure/ground segregation, or perceptual grouping. The experiments here tested whether assimilation depends on a neural process that follows stereoscopic depth perception. By introducing binocular disparity, the test field judged in color was made to appear in a different depth plane than the light that induced assimilation. The chromaticity and spatial frequency of the inducing light, and the chromaticity of the test light, were varied. Chromatic assimilation was found with all inducing-light sizes and chromaticities, but the magnitude of assimilation did not depend on the perceived relative depth planes of the test and inducing fields. We found no evidence to support the view that chromatic assimilation depends on a neural process that follows binocular combination of the two eyes' signals.

  19. The cathepsin B inhibitor, z-FA-CMK is toxic and readily induced cell death in human T lymphocytes

    International Nuclear Information System (INIS)

    Liow, K.Y.; Chow, S.C.

    2013-01-01

    The cathepsin B inhibitor, benzyloxycarbonyl-phenylalanine-alanine-chloromethylketone (z-FA-CMK) was found to be toxic and readily induced cell death in the human T cell line, Jurkat, whereas two other analogs benzyloxycarbonyl-phenylalanine-alanine-fluoromethylketone (z-FA-FMK) and benzyloxycarbonyl-phenylalanine-alanine-diazomethylketone (z-FA-DMK) were not toxic. The toxicity of z-FA-CMK requires not only the CMK group, but also the presence of alanine in the P1 position and the benzyloxycarbonyl group at the N-terminal. Dose–response studies showed that lower concentrations of z-FA-CMK induced apoptosis in Jurkat T cells whereas higher concentrations induced necrosis. In z-FA-CMK-induced apoptosis, both initiator caspases (-8 and -9) and effector caspases (-3, -6 and -7) were processed to their respective subunits in Jurkat T cells. However, only the pro-form of the initiator caspases were reduced in z-FA-CMK-induced necrosis and no respective subunits were apparent. The caspase inihibitor benzyloxycarbonyl-valine-alanine-aspartic acid-(O-methyl)-fluoromehylketone (z-VAD-FMK) inhibits apoptosis and caspase processing in Jurkat T cells treated with low concentration of z-FA-CMK but has no effect on z-FA-CMK-induced necrosis and the loss of initiator caspases. This suggests that the loss of initiator caspases in Jurkat T cells during z-FA-CMK-induced necrosis is not a caspase-dependent process. Taken together, we have demonstrated that z-FA-CMK is toxic to Jurkat T cells and induces apoptosis at low concentrations, while at higher concentrations the cells die of necrosis. - Highlights: • z-FA-CMK is toxic and induce cell death in the human T cells. • z-FA-CMK toxicity requires the CMK group, alanine and the benzyloxycarbonyl group. • z-FA-CMK induced apoptosis at low concentration and necrosis at high concentration

  20. The cathepsin B inhibitor, z-FA-CMK is toxic and readily induced cell death in human T lymphocytes

    Energy Technology Data Exchange (ETDEWEB)

    Liow, K.Y.; Chow, S.C., E-mail: chow.sek.chuen@monash.edu

    2013-11-01

    The cathepsin B inhibitor, benzyloxycarbonyl-phenylalanine-alanine-chloromethylketone (z-FA-CMK) was found to be toxic and readily induced cell death in the human T cell line, Jurkat, whereas two other analogs benzyloxycarbonyl-phenylalanine-alanine-fluoromethylketone (z-FA-FMK) and benzyloxycarbonyl-phenylalanine-alanine-diazomethylketone (z-FA-DMK) were not toxic. The toxicity of z-FA-CMK requires not only the CMK group, but also the presence of alanine in the P1 position and the benzyloxycarbonyl group at the N-terminal. Dose–response studies showed that lower concentrations of z-FA-CMK induced apoptosis in Jurkat T cells whereas higher concentrations induced necrosis. In z-FA-CMK-induced apoptosis, both initiator caspases (-8 and -9) and effector caspases (-3, -6 and -7) were processed to their respective subunits in Jurkat T cells. However, only the pro-form of the initiator caspases were reduced in z-FA-CMK-induced necrosis and no respective subunits were apparent. The caspase inihibitor benzyloxycarbonyl-valine-alanine-aspartic acid-(O-methyl)-fluoromehylketone (z-VAD-FMK) inhibits apoptosis and caspase processing in Jurkat T cells treated with low concentration of z-FA-CMK but has no effect on z-FA-CMK-induced necrosis and the loss of initiator caspases. This suggests that the loss of initiator caspases in Jurkat T cells during z-FA-CMK-induced necrosis is not a caspase-dependent process. Taken together, we have demonstrated that z-FA-CMK is toxic to Jurkat T cells and induces apoptosis at low concentrations, while at higher concentrations the cells die of necrosis. - Highlights: • z-FA-CMK is toxic and induce cell death in the human T cells. • z-FA-CMK toxicity requires the CMK group, alanine and the benzyloxycarbonyl group. • z-FA-CMK induced apoptosis at low concentration and necrosis at high concentration.

  1. Functionalized paper--A readily accessible adsorbent for removal of dissolved heavy metal salts and nanoparticles from water.

    Science.gov (United States)

    Setyono, Daisy; Valiyaveettil, Suresh

    2016-01-25

    Paper, a readily available renewable resource, comprises of interwoven cellulosic fibers, which can be functionalized to develop interesting low-cost adsorbent material for water purification. In this study, polyethyleneimine (PEI)-functionalized paper was used for the removal of hazardous pollutants such as Au and Ag nanoparticles, Cr(VI) anions, Ni(2+), Cd(2+), and Cu(2+) cations from spiked water samples. Compared to untreated paper, the PEI-coated paper showed significant improvement in adsorption capacities toward the pollutants investigated in this study. Kinetics, isotherm models, pH, and desorption studies were carried out to study the adsorption mechanism of pollutants on the adsorbent surface. Adsorption of pollutants was better described by pseudo-second order kinetics and Langmuir isotherm model. Maximum adsorption of anionic pollutants was achieved at pH 5 while that of cations was at pH>6. Overall, the PEI-functionalized paper showed interesting Langmuir adsorption capacities for heavy metal ions such as Cr(VI) (68 mg/g), Ni(2+) (208 mg/g), Cd(2+) (370 mg/g), and Cu(2+) (435 mg/g) ions at neutral pH. In addition, the modified paper was also used to remove Ag-citrate (79 mg/g), Ag-PVP (46 mg/g), Au-citrate (30 mg/g), Au-PVP (17 mg/g) nanoparticles from water. Desorption of NPs from the adsorbent was done by washing with 2 M HCl or thiourea solution, while heavy metal ions were desorbed using 1 M NaOH or HNO3 solution. The modified paper retained its extraction efficiencies upon desorption of pollutants. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. The use of satellite data assimilation methods in regional NWP for solar irradiance forecasting

    Science.gov (United States)

    Kurzrock, Frederik; Cros, Sylvain; Chane-Ming, Fabrice; Potthast, Roland; Linguet, Laurent; Sébastien, Nicolas

    2016-04-01

    As an intermittent energy source, the injection of solar power into electricity grids requires irradiance forecasting in order to ensure grid stability. On time scales of more than six hours ahead, numerical weather prediction (NWP) is recognized as the most appropriate solution. However, the current representation of clouds in NWP models is not sufficiently precise for an accurate forecast of solar irradiance at ground level. Dynamical downscaling does not necessarily increase the quality of irradiance forecasts. Furthermore, incorrectly simulated cloud evolution is often the cause of inaccurate atmospheric analyses. In non-interconnected tropical areas, the large amplitudes of solar irradiance variability provide abundant solar yield but present significant problems for grid safety. Irradiance forecasting is particularly important for solar power stakeholders in these regions where PV electricity penetration is increasing. At the same time, NWP is markedly more challenging in tropic areas than in mid-latitudes due to the special characteristics of tropical homogeneous convective air masses. Numerous data assimilation methods and strategies have evolved and been applied to a large variety of global and regional NWP models in the recent decades. Assimilating data from geostationary meteorological satellites is an appropriate approach. Indeed, models converting radiances measured by satellites into cloud properties already exist. Moreover, data are available at high temporal frequencies, which enable a pertinent cloud cover evolution modelling for solar energy forecasts. In this work, we present a survey of different approaches which aim at improving cloud cover forecasts using the assimilation of geostationary meteorological satellite data into regional NWP models. Various approaches have been applied to a variety of models and satellites and in different regions of the world. Current methods focus on the assimilation of cloud-top information, derived from infrared

  3. The Effects of Varying Crustal Carbonate Composition on Assimilation and CO2 Degassing at Arc Volcanoes

    Science.gov (United States)

    Carter, L. B.; Holmes, A. K.; Dasgupta, R.; Tumiati, S.

    2015-12-01

    Magma-crustal carbonate interaction and subsequent decarbonation can provide an additional source of CO2 release to the exogenic system superimposed on mantle-derived CO2. Carbonate assimilation at present day volcanoes is often modeled by limestone consumption experiments [1-4]. Eruptive products, however, do not clearly display the characteristic ultracalcic melt compositions produced during limestone-magma interaction [4]. Yet estimated CO2outflux [5] and composition of volcanics in many volcanic systems may allow ~3-17% limestone- or dolostone-assimilated melt contribution. Crystallization may retain ultracalcic melts in pyroxenite cumulates. To extend our completed study on limestone assimilation, here we explore the effect of varying composition from calcite to dolomite on chemical and thermal decarbonation efficiency of crustal carbonates. Piston cylinder experiments at 0.5 GPa and 900-1200 °C demonstrate that residual mineralogy during interaction with magma shifts from CaTs cpx and anorthite/scapolite in the presence of calcite to Di cpx and Fo-rich olivine with dolomite. Silica-undersaturated melts double in magnesium content, while maintaining high (>30 wt.%) CaO values. At high-T, partial thermal breakdown of dolomite into periclase and CO2 is minimal (<5%) suggesting that in the presence of magma, CO2 is primarily released due to assimilation. Assimilated melts at identical P-T conditions depict similarly high volatile contents (10-20 wt.% by EMPA deficit at 0.5 GPa, 1150 °C with hydrous basalt) with calcite or dolomite. Analysis of the coexisting fluid phase indicates the majority of water is dissolved in the melt, while CO2 released from the carbonate is preferentially partitioned into the vapor. This suggests that although assimilated melts have a higher CO2 solubility, most of the CO2can easily degas from the vapor phase at arc volcanoes, possibly more so at volcanic plumbing systems traversing dolomite [8]. [1]Conte et al 2009 EuJMin (21) 763

  4. Synthesis, properties, and assimilation methods of aluminium hydride

    International Nuclear Information System (INIS)

    Mirsaidov, U.M.

    2013-01-01

    We have discovered a new source of aluminium hydride-conversion of tetrahydrofurane under influence of halogenous alkyls. We have proposed the chlorbenzene method of synthesis of AlH 3 , which excludes adhesion and ensure high quality of the product with respect to its purity, thermal stability, habits of crystals (round shape), and granulometric composition. We determined capability of benzyl chloride to fix AlH 4 -groups by the way of complexes formation. This allows increasing efficient concentration of AlH 3 solutions and their productivity. We have carried out 'direct' crystallization of aluminium hydride in one stage using interaction of binary metal hydride with aluminium chloride in the medium of ether-toluene at 60-100 d ig C a nd using solvent distillation. In the reaction of Li H with AlCl 3 , we achieved output of pure crystal AlH 3 of hexagonal modification, which was close to quantitative. We have discovered the assimilation methods of aluminium hydride in carrying out of solid-phase chemical reactions. (author)

  5. Towards a Comprehensive Dynamic-chemistry Assimilation for Eos-Chem: Plans and Status in NASA's Data Assimilation Office

    Science.gov (United States)

    Pawson, Steven; Lin, Shian-Jiann; Rood, Richard B.; Stajner, Ivanka; Nebuda, Sharon; Nielsen, J. Eric; Douglass, Anne R.

    2000-01-01

    In order to support the EOS-Chem project, a comprehensive assimilation package for the coupled chemical-dynamical system is being developed by the Data Assimilation Office at NASA GSFC. This involves development of a coupled chemistry/meteorology model and of data assimilation techniques for trace species and meteorology. The model is being developed using the flux-form semi-Lagrangian dynamical core of Lin and Rood, the physical parameterizations from the NCAR Community Climate Model, and atmospheric chemistry modules from the Atmospheric Chemistry and Dynamics branch at NASA GSFC. To date the following results have been obtained: (i) multi-annual simulations with the dynamics-radiation model show the credibility of the package for atmospheric simulations; (ii) initial simulations including a limited number of middle atmospheric trace gases reveal the realistic nature of transport mechanisms, although there is still a need for some improvements. Samples of these results will be shown. A meteorological assimilation system is currently being constructed using the model; this will form the basis for the proposed meteorological/chemical assimilation package. The latter part of the presentation will focus on areas targeted for development in the near and far terms, with the objective of Providing a comprehensive assimilation package for the EOS-Chem science experiment. The first stage will target ozone assimilation. The plans also encompass a reanalysis (ReSTS) for the 1991-1995 period, which includes the Mt. Pinatubo eruption and the time when a large number of UARS observations were available. One of the most challenging aspects of future developments will be to couple theoretical advances in tracer assimilation with the practical considerations of a real environment and eventually a near-real-time assimilation system.

  6. Efficient data assimilation algorithm for bathymetry application

    Science.gov (United States)

    Ghorbanidehno, H.; Lee, J. H.; Farthing, M.; Hesser, T.; Kitanidis, P. K.; Darve, E. F.

    2017-12-01

    Information on the evolving state of the nearshore zone bathymetry is crucial to shoreline management, recreational safety, and naval operations. The high cost and complex logistics of using ship-based surveys for bathymetry estimation have encouraged the use of remote sensing techniques. Data assimilation methods combine the remote sensing data and nearshore hydrodynamic models to estimate the unknown bathymetry and the corresponding uncertainties. In particular, several recent efforts have combined Kalman Filter-based techniques such as ensembled-based Kalman filters with indirect video-based observations to address the bathymetry inversion problem. However, these methods often suffer from ensemble collapse and uncertainty underestimation. Here, the Compressed State Kalman Filter (CSKF) method is used to estimate the bathymetry based on observed wave celerity. In order to demonstrate the accuracy and robustness of the CSKF method, we consider twin tests with synthetic observations of wave celerity, while the bathymetry profiles are chosen based on surveys taken by the U.S. Army Corps of Engineer Field Research Facility (FRF) in Duck, NC. The first test case is a bathymetry estimation problem for a spatially smooth and temporally constant bathymetry profile. The second test case is a bathymetry estimation problem for a temporally evolving bathymetry from a smooth to a non-smooth profile. For both problems, we compare the results of CSKF with those obtained by the local ensemble transform Kalman filter (LETKF), which is a popular ensemble-based Kalman filter method.

  7. Efficient Data Assimilation Algorithms for Bathymetry Applications

    Science.gov (United States)

    Ghorbanidehno, H.; Kokkinaki, A.; Lee, J. H.; Farthing, M.; Hesser, T.; Kitanidis, P. K.; Darve, E. F.

    2016-12-01

    Information on the evolving state of the nearshore zone bathymetry is crucial to shoreline management, recreational safety, and naval operations. The high cost and complex logistics of using ship-based surveys for bathymetry estimation have encouraged the use of remote sensing monitoring. Data assimilation methods combine monitoring data and models of nearshore dynamics to estimate the unknown bathymetry and the corresponding uncertainties. Existing applications have been limited to the basic Kalman Filter (KF) and the Ensemble Kalman Filter (EnKF). The former can only be applied to low-dimensional problems due to its computational cost; the latter often suffers from ensemble collapse and uncertainty underestimation. This work explores the use of different variants of the Kalman Filter for bathymetry applications. In particular, we compare the performance of the EnKF to the Unscented Kalman Filter and the Hierarchical Kalman Filter, both of which are KF variants for non-linear problems. The objective is to identify which method can better handle the nonlinearities of nearshore physics, while also having a reasonable computational cost. We present two applications; first, the bathymetry of a synthetic one-dimensional cross section normal to the shore is estimated from wave speed measurements. Second, real remote measurements with unknown error statistics are used and compared to in situ bathymetric survey data collected at the USACE Field Research Facility in Duck, NC. We evaluate the information content of different data sets and explore the impact of measurement error and nonlinearities.

  8. Iterative ensemble variational methods for nonlinear data assimilation: Application to transport and atmospheric chemistry

    International Nuclear Information System (INIS)

    Haussaire, Jean-Matthieu

    2017-01-01

    assimilation of real tropospheric ozone concentrations mitigates these results and shows how hard atmospheric chemistry data assimilation is. A strong model error is indeed attached to these models, stemming from multiple uncertainty sources. Two steps must be taken to tackle this issue. First of all, the data assimilation method used must be able to efficiently take into account the model error. However, most methods are developed under the assumption of a perfect model. To avoid this hypothesis, a new method has then been developed. Called IEnKF-Q, it expands the IEnKS to the model error framework. It has been validated on a low-order model, proving its superiority over data assimilation methods naively adapted to take into account model error. Nevertheless, such methods need to know the exact nature and amplitude of the model error which needs to be accounted for. Therefore, the second step is to use statistical tools to quantify this model error. The expectation-maximization algorithm, the naive and unbiased randomize-then-optimize algorithms, an importance sampling based on a Laplace proposal, and a Markov chain Monte Carlo simulation, potentially trans-dimensional, have been assessed, expanded, and compared to estimate the uncertainty on the retrieval of the source term of the Chernobyl and Fukushima-Daiichi nuclear power plant accidents. This thesis therefore improves the domain of 4D EnVar data assimilation by its methodological input and by paving the way to applying these methods on atmospheric chemistry models. (author) [fr

  9. Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation

    Science.gov (United States)

    Li, Shan; Zhang, Shaoqing; Liu, Zhengyu; Lu, Lv; Zhu, Jiang; Zhang, Xuefeng; Wu, Xinrong; Zhao, Ming; Vecchi, Gabriel A.; Zhang, Rong-Hua; Lin, Xiaopei

    2018-04-01

    Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.

  10. Open-Source Colorimeter

    OpenAIRE

    Anzalone, Gerald C.; Glover, Alexandra G.; Pearce, Joshua M.

    2013-01-01

    The high cost of what have historically been sophisticated research-related sensors and tools has limited their adoption to a relatively small group of well-funded researchers. This paper provides a methodology for applying an open-source approach to design and development of a colorimeter. A 3-D printable, open-source colorimeter utilizing only open-source hardware and software solutions and readily available discrete components is discussed and its performance compared to a commercial porta...

  11. Origin of primitive ocean island basalts by crustal gabbro assimilation and multiple recharge of plume-derived melts

    Science.gov (United States)

    Borisova, Anastassia Y.; Bohrson, Wendy A.; Grégoire, Michel

    2017-07-01

    Chemical Geodynamics relies on a paradigm that the isotopic composition of ocean island basalt (OIB) represents equilibrium with its primary mantle sources. However, the discovery of huge isotopic heterogeneity within olivine-hosted melt inclusions in primitive basalts from Kerguelen, Iceland, Hawaii and South Pacific Polynesia islands implies open-system behavior of OIBs, where during magma residence and transport, basaltic melts are contaminated by surrounding lithosphere. To constrain the processes of crustal assimilation by OIBs, we employed the Magma Chamber Simulator (MCS), an energy-constrained thermodynamic model of recharge, assimilation and fractional crystallization. For a case study of the 21-19 Ma basaltic series, the most primitive series ever found among the Kerguelen OIBs, we performed sixty-seven simulations in the pressure range from 0.2 to 1.0 GPa using compositions of olivine-hosted melt inclusions as parental magmas, and metagabbro xenoliths from the Kerguelen Archipelago as wallrock. MCS modeling requires that the assimilant is anatectic crustal melts (P2O5 ≤ 0.4 wt.% contents) derived from the Kerguelen oceanic metagabbro wallrock. To best fit the phenocryst assemblage observed in the investigated basaltic series, recharge of relatively large masses of hydrous primitive basaltic melts (H2O = 2-3 wt%; MgO = 7-10 wt.%) into a middle crustal chamber at 0.2 to 0.3 GPa is required. Our results thus highlight the important impact that crustal gabbro assimilation and mantle recharge can have on the geochemistry of mantle-derived olivine-phyric OIBs. The importance of crustal assimilation affecting primitive plume-derived basaltic melts underscores that isotopic and chemical equilibrium between ocean island basalts and associated deep plume mantle source(s) may be the exception rather than the rule.

  12. A new general dynamic model predicting radionuclide concentrations and fluxes in coastal areas from readily accessible driving variables

    International Nuclear Information System (INIS)

    Haakanson, Lars

    2004-01-01

    This paper presents a general, process-based dynamic model for coastal areas for radionuclides (metals, organics and nutrients) from both single pulse fallout and continuous deposition. The model gives radionuclide concentrations in water (total, dissolved and particulate phases and concentrations in sediments and fish) for entire defined coastal areas. The model gives monthly variations. It accounts for inflow from tributaries, direct fallout to the coastal area, internal fluxes (sedimentation, resuspension, diffusion, burial, mixing and biouptake and retention in fish) and fluxes to and from the sea outside the defined coastal area and/or adjacent coastal areas. The fluxes of water and substances between the sea and the coastal area are differentiated into three categories of coast types: (i) areas where the water exchange is regulated by tidal effects; (ii) open coastal areas where the water exchange is regulated by coastal currents; and (iii) semi-enclosed archipelago coasts. The coastal model gives the fluxes to and from the following four abiotic compartments: surface water, deep water, ET areas (i.e., areas where fine sediment erosion and transport processes dominate the bottom dynamic conditions and resuspension appears) and A-areas (i.e., areas of continuous fine sediment accumulation). Criteria to define the boundaries for the given coastal area towards the sea, and to define whether a coastal area is open or closed are given in operational terms. The model is simple to apply since all driving variables may be readily accessed from maps and standard monitoring programs. The driving variables are: latitude, catchment area, mean annual precipitation, fallout and month of fallout and parameters expressing coastal size and form as determined from, e.g., digitized bathymetric maps using a GIS program. Selected results: the predictions of radionuclide concentrations in water and fish largely depend on two factors, the concentration in the sea outside the given

  13. Assimilate unloading from maize (Zea mays L.) pedicel tissues

    International Nuclear Information System (INIS)

    Porter, G.A.; Knievel, D.P.; Shannon, J.C.

    1987-01-01

    Sugar and 14 C-assimilate release from the pedicel tissue of attached maize (Zea mays L.) kernels was studied following treatment with solute concentrations of up to 800 millimolal. Exposure and collection times ranged from 3 to 6 hours. Sugar and 14 C-assimilate unloading and collection in agar traps was reduced by 25 and 43%, respectively, following exposure to 800 millimolal mannitol. Inhibition of unloading was not specific to mannitol, since similar concentrations of glucose, fructose, or equimolar glucose plus fructose resulted in comparable inhibition. Ethylene glycol, a rapidly permeating solute which should not greatly influence cell turgor, did not inhibit 14 C-assimilate unloading. Based on these results, they suggest that inhibition of unloading by high concentrations of sugar or mannitol was due to reduced pedicel cell turgor. Changes in pedicel cell turgor may play a role in the regulation of assimilate transfer within the maize kernel

  14. Develop a Hybrid Coordinate Ocean Model with Data Assimilation Capabilities

    National Research Council Canada - National Science Library

    Thacker, W. C

    2003-01-01

    .... The objectives of the research are as follows: (1) to develop a methodology for assimilating temperature and salinity profiles from XBT, CTD, and ARGO float data that accommodates the peculiarities of HYCOM's hybrid vertical coordinates, allowing...

  15. Regional Ocean Modeling System (ROMS): CNMI: Data Assimilating

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the Commonwealth of the Northern Mariana Islands (CNMI)...

  16. Data assimilation in modeling ocean processes: A bibliographic study

    Digital Repository Service at National Institute of Oceanography (India)

    Mahadevan, R.; Fernandes, A.A.; Saran, A.K.

    An annotated bibliography on studies related to data assimilation in modeling ocean processes has been prepared. The bibliography listed here is not comprehensive and is not prepared from the original references. Information obtainable from...

  17. Air Quality Activities in the Global Modeling and Assimilation Office

    Science.gov (United States)

    Pawson, Steven

    2016-01-01

    GMAO's mission is to enhance the use of NASA's satellite observations in weather and climate modeling. This presentation will be discussing GMAO's mission, value of data assimilation, and some relevant (available) GMAO data products.

  18. UARS Correlative UKMO Daily Gridded Stratospheric Assimilated Data V001

    Data.gov (United States)

    National Aeronautics and Space Administration — The UARS Correlative assimilation data from the U.K. Meteorological Office (UKMO) consists of daily model runs at 12:00 GMT as a means of providing an independent...

  19. Regional Ocean Modeling System (ROMS): Samoa: Data Assimilating

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the islands of Samoa at approximately 3-km resolution....

  20. Regional Ocean Modeling System (ROMS): Main Hawaiian Islands: Data Assimilating

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Regional Ocean Modeling System (ROMS) 3-day, 3-hourly data assimilating hindcast for the region surrounding the main Hawaiian islands at approximately 4-km...

  1. The Culure Assimilator: An Approach to Cross-Cultural Training

    Science.gov (United States)

    Fiedler, Fred E.; And Others

    1971-01-01

    Evaluates the cultural assimilator, a kind of training manual to help members of one culture understand and adjust to another culture. Describes those constructed for the Arab countries, Iran, Thailand, Central America, and Greece. (MB)

  2. Regional Ocean Modeling System (ROMS): Oahu: Data Assimilating

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Regional Ocean Modeling System (ROMS) 2-day, 3-hourly data assimilating hindcast for the region surrounding the island of Oahu at approximately 1-km resolution....

  3. Disconfirmed hedonic expectations produce perceptual contrast, not assimilation.

    Science.gov (United States)

    Zellner, Debra A; Strickhouser, Dinah; Tornow, Carina E

    2004-01-01

    In studies of hedonic ratings, contrast is the usual result when expectations about test stimuli are produced through the presentation of context stimuli, whereas assimilation is the usual result when expectations about test stimuli are produced through labeling, advertising, or the relaying of information to the subject about the test stimuli. Both procedures produce expectations that are subsequently violated, but the outcomes are different. The present studies demonstrate that both assimilation and contrast can occur even when expectations are produced by verbal labels and the degree of violation of the expectation is held constant. One factor determining whether assimilation or contrast occurs appears to be the certainty of the expectation. Expectations that convey certainty are produced by methods that lead to social influence on subjects' ratings, producing assimilation. When social influence is not a factor and subjects give judgments influenced only by the perceived hedonic value of the stimulus, contrast is the result.

  4. Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

    Science.gov (United States)

    Zhu, Jiang; Stevens, E.; Zavodsky, B. T.; Zhang, X.; Heinrichs, T.; Broderson, D.

    2014-01-01

    Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

  5. Lead toxicity in Brassica pekinensis Rupr.: effect on nitrate assimilation and growth.

    Science.gov (United States)

    Xiong, Zhi-Ting; Zhao, Fei; Li, Min-jing

    2006-04-01

    Lead is a major heavy-metal contaminant in the environment that has various anthropogenic and natural sources. To study the phytotoxic effects of Pb on the popular vegetable Chinese cabbage (Brassica pekinensis Rupr.) via depression of nitrogen assimilation, pot culture experiments with three concentrations of treatment with Pb (0, 4, and 8 mmol/kg dry soil) were carried out. Our results demonstrated adverse effects of Pb on nitrogen assimilation and plant growth. The addition of Pb in the soil resulted in elevated accumulation of Pb in the shoots of the plants: Pb concentrations of 14.3, 202.3, and 418.2 mg/kg (DW) in the shoots were detected with the 0, 4, and 8 mmol/kg treatments, respectively. Compared to the control, Pb exposure (4 and 8 mmol/kg) significantly decreased shoot nitrate content (71% and 80% of the control), nitrate reductase activity (104% and 49% of the control), and free amino acid content (81% and 82% of the control), indicating decreased nitrogen assimilation in the plants. The effect of Pb also was shown by the progressive decline in shoot biomass with increasing Pb concentration in plant shoots and in the soil. However, at the treatment levels used in this study, lead did not induce visible toxic symptoms. The lowest-concentration Pb treatment (4 mmol/kg) stimulated chlorophyll b content but did not influence chlorophyll a content. The results suggested that the toxicity of Pb to the plants occurred at least partly via depression of nitrogen assimilation. Copyright 2006 Wiley Periodicals, Inc.

  6. Multi-parametric variational data assimilation for hydrological forecasting

    Science.gov (United States)

    Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.

    2017-12-01

    Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.

  7. Ethnicity, assimilation and harassment in the labor market

    OpenAIRE

    Epstein, Gil S.; Gang, Ira N.

    2008-01-01

    We often observe minority ethnic groups at a disadvantage relative to the majority. Why is this and what can be done about it? Efforts made to assimilate, and time, are two elements working to bring the minority into line with the majority. A third element, the degree to which the majority welcomes the minority, also plays a role. We develop a simple theoretical model useful for examining the consequences for assimilation and harassment of growth in the minority population, time, and the role...

  8. Joint Center for Satellite Data Assimilation Overview and Research Activities

    Science.gov (United States)

    Auligne, T.

    2017-12-01

    In 2001 NOAA/NESDIS, NOAA/NWS, NOAA/OAR, and NASA, subsequently joined by the US Navy and Air Force, came together to form the Joint Center for Satellite Data Assimilation (JCSDA) for the common purpose of accelerating the use of satellite data in environmental numerical prediction modeling by developing, using, and anticipating advances in numerical modeling, satellite-based remote sensing, and data assimilation methods. The primary focus was to bring these advances together to improve operational numerical model-based forecasting, under the premise that these partners have common technical and logistical challenges assimilating satellite observations into their modeling enterprises that could be better addressed through cooperative action and/or common solutions. Over the last 15 years, the JCSDA has made and continues to make major contributions to operational assimilation of satellite data. The JCSDA is a multi-agency U.S. government-owned-and-operated organization that was conceived as a venue for the several agencies NOAA, NASA, USAF and USN to collaborate on advancing the development and operational use of satellite observations into numerical model-based environmental analysis and forecasting. The primary mission of the JCSDA is to "accelerate and improve the quantitative use of research and operational satellite data in weather, ocean, climate and environmental analysis and prediction systems." This mission is fulfilled through directed research targeting the following key science objectives: Improved radiative transfer modeling; new instrument assimilation; assimilation of humidity, clouds, and precipitation observations; assimilation of land surface observations; assimilation of ocean surface observations; atmospheric composition; and chemistry and aerosols. The goal of this presentation is to briefly introduce the JCSDA's mission and vision, and to describe recent research activities across various JCSDA partners.

  9. Yeast identification: reassessment of assimilation tests as sole universal identifiers.

    Science.gov (United States)

    Spencer, J; Rawling, S; Stratford, M; Steels, H; Novodvorska, M; Archer, D B; Chandra, S

    2011-11-01

    To assess whether assimilation tests in isolation remain a valid method of identification of yeasts, when applied to a wide range of environmental and spoilage isolates. Seventy-one yeast strains were isolated from a soft drinks factory. These were identified using assimilation tests and by D1/D2 rDNA sequencing. When compared to sequencing, assimilation test identifications (MicroLog™) were 18·3% correct, a further 14·1% correct within the genus and 67·6% were incorrectly identified. The majority of the latter could be attributed to the rise in newly reported yeast species. Assimilation tests alone are unreliable as a universal means of yeast identification, because of numerous new species, variability of strains and increasing coincidence of assimilation profiles. Assimilation tests still have a useful role in the identification of common species, such as the majority of clinical isolates. It is probable, based on these results, that many yeast identifications reported in older literature are incorrect. This emphasizes the crucial need for accurate identification in present and future publications. © 2011 The Authors. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.

  10. IASI Radiance Data Assimilation in Local Ensemble Transform Kalman Filter

    Science.gov (United States)

    Cho, K.; Hyoung-Wook, C.; Jo, Y.

    2016-12-01

    Korea institute of Atmospheric Prediction Systems (KIAPS) is developing NWP model with data assimilation systems. Local Ensemble Transform Kalman Filter (LETKF) system, one of the data assimilation systems, has been developed for KIAPS Integrated Model (KIM) based on cubed-sphere grid and has successfully assimilated real data. LETKF data assimilation system has been extended to 4D- LETKF which considers time-evolving error covariance within assimilation window and IASI radiance data assimilation using KPOP (KIAPS package for observation processing) with RTTOV (Radiative Transfer for TOVS). The LETKF system is implementing semi operational prediction including conventional (sonde, aircraft) observation and AMSU-A (Advanced Microwave Sounding Unit-A) radiance data from April. Recently, the semi operational prediction system updated radiance observations including GPS-RO, AMV, IASI (Infrared Atmospheric Sounding Interferometer) data at July. A set of simulation of KIM with ne30np4 and 50 vertical levels (of top 0.3hPa) were carried out for short range forecast (10days) within semi operation prediction LETKF system with ensemble forecast 50 members. In order to only IASI impact, our experiments used only conventional and IAIS radiance data to same semi operational prediction set. We carried out sensitivity test for IAIS thinning method (3D and 4D). IASI observation number was increased by temporal (4D) thinning and the improvement of IASI radiance data impact on the forecast skill of model will expect.

  11. Cholesterol Assimilation by Lactobacillus Probiotic Bacteria: An In Vitro Investigation

    Directory of Open Access Journals (Sweden)

    Catherine Tomaro-Duchesneau

    2014-01-01

    Full Text Available Excess cholesterol is associated with cardiovascular diseases (CVD, an important cause of mortality worldwide. Current CVD therapeutic measures, lifestyle and dietary interventions, and pharmaceutical agents for regulating cholesterol levels are inadequate. Probiotic bacteria have demonstrated potential to lower cholesterol levels by different mechanisms, including bile salt hydrolase activity, production of compounds that inhibit enzymes such as 3-hydroxy-3-methylglutaryl coenzyme A, and cholesterol assimilation. This work investigates 11 Lactobacillus strains for cholesterol assimilation. Probiotic strains for investigation were selected from the literature: Lactobacillus reuteri NCIMB 11951, L. reuteri NCIMB 701359, L. reuteri NCIMB 702655, L. reuteri NCIMB 701089, L. reuteri NCIMB 702656, Lactobacillus fermentum NCIMB 5221, L. fermentum NCIMB 8829, L. fermentum NCIMB 2797, Lactobacillus rhamnosus ATCC 53103 GG, Lactobacillus acidophilus ATCC 314, and Lactobacillus plantarum ATCC 14917. Cholesterol assimilation was investigated in culture media and under simulated intestinal conditions. The best cholesterol assimilator was L. plantarum ATCC 14917 (15.18 ± 0.55 mg/1010 cfu in MRS broth. L. reuteri NCIMB 701089 assimilated over 67% (2254.70 ± 63.33 mg/1010 cfu of cholesterol, the most of all the strains, under intestinal conditions. This work demonstrates that probiotic bacteria can assimilate cholesterol under intestinal conditions, with L. reuteri NCIMB 701089 showing great potential as a CVD therapeutic.

  12. On the effectiveness of surface assimilation in probabilistic nowcasts of planetary boundary layer profiles

    Science.gov (United States)

    Rostkier-Edelstein, Dorita; Hacker, Joshua

    2013-04-01

    Surface observations comprise a wide, non-expensive and reliable source of information about the state of the near-surface planetary boundary layer (PBL). Operational data assimilation systems have encountered several difficulties in effectively assimilating them, among others due to their local-scale representativeness, the transient coupling between the surface and the atmosphere aloft and the balance constraints usually used. A long-term goal of this work is to find an efficient system for probabilistic PBL nowcasting that can be employed wherever surface observations are present. Earlier work showed that surface observations can be an important source of information with a single column model (SCM) and an ensemble filter (EF). Here we extend that work to quantify the probabilistic skill of ensemble SCM predictions with a model including added complexity. We adopt a factor separation analysis to quantify the contribution of surface assimilation relative to that of selected model components (parameterized radiation and externally imposed horizontal advection) to the probabilistic skill of the system, and of any beneficial or detrimental interactions between them. To assess the real utility of the flow-dependent covariances estimated with the EF and of the SCM of the PBL we compare the skill of the SCM/EF system to that of a reference one based on climatological covariances and a 30-min persistence model. It consists of a dressing technique, whereby a deterministic 3D mesoscale forecast (e.g. from WRF model) is adjusted and dressed with uncertainty using a seasonal sample of mesoscale forecasts and surface forecast errors. Results show that assimilation of surface observations can improve deterministic and probabilistic profile predictions more significantly than major model improvements. Flow-dependent covariances estimated with the SCM/EF show clear advantage over the use of climatological covariances when the flow is characterized by wide variability, when

  13. Exploring synchronisation in nonlinear data assimilation

    Science.gov (United States)

    Rodrigues-Pinheiro, Flavia; van Leeuwen, Peter Jan

    2016-04-01

    Present-day data assimilation methods are based on linearizations and face serious problems in strongly nonlinear cases such as convection. A promising solution to this problem is a particle filter, which provides a representation of the model probability density function (pdf) by a discrete set of model states, or particles. The basic particle filter uses Bayes's theorem directly, but does not work in high-dimensional cases. The performance can be improved by considering the proposal density freedom. This allows one to change the model equations to bring the particles closer to the observations, resulting in very efficient update schemes at observation times, but extending these schemes between observation times is computationally expensive. Simple solutions like nudging have been shown to be not powerful enough. A potential solution might be synchronization, in which one tries to synchronise the model of a system with the true evolution of the system via the observations. In practice this means that an extra term is added to the model equations that hampers growth of instabilities on the synchronization manifold. Especially the delayed versions, where observations are allowed to influence the state in the past have shown some remarkable successes. Unfortunately, all efforts ignore errors in the observations, and as soon as these are introduced the performance degrades considerably. There is a close connection between time-delayed synchronization and a Kalman Smoother, which does allow for observational (and other) errors. In this presentation we will explore this connection to the full, with a view to extend synchronization to more realistic settings. Specifically performance of the spread of information from observed to unobserved variables is studied in detail. The results indicate that this extended synchronisation is a promising tool to steer the model states towards the observations efficiently. If time permits, we will show initial results of embedding the

  14. Towards assimilation of InSAR data in operational weather models

    Science.gov (United States)

    Mulder, Gert; van Leijen, Freek; Barkmeijer, Jan; de Haan, Siebren; Hanssen, Ramon

    2017-04-01

    InSAR signal delays due to the varying atmospheric refractivity are a potential data source to improve weather models [1]. Especially with the launch of the new Sentinel-1 satellites, which increases data coverage, latency and accessibility, it may become possible to operationalize the assimilation of differential integrated refractivity (DIR) values in numerical weather models. Although studies exist on comparison between InSAR data and weather models [2], the impact of assimilation of DIR values in an operational weather model has never been assessed. In this study we present different ways to assimilate DIR values in an operational weather model and show the first forecast results. There are different possibilities to assimilate InSAR-data in a weather model. For example, (i) absolute DIR values can be derived using additional GNSS zenith or slant delay values, (ii) DIR values can be converted to water vapor pressures, or (iii) water vapor pressures can be derived for different heights by combining GNSS and InSAR data. However, an increasing number of assumptions in these processing steps will increase the uncertainty in the final results. Therefore, we chose to insert the InSAR derived DIR values after minimal additional processing. In this study we use the HARMONIE model [3], which is a spectral, non-hydrostatic model with a resolution of about 2.5 km. Currently, this is the operational model in 11 European countries and based on the AROME model [4]. To assimilate the DIR values in the weather model we use a simple adjustment of the weather parameters over the full slant column to match the DIR values. This is a first step towards a more sophisticated approach based on the 3D-VAR or 4D-VAR schemes [5]. Where both assimilation schemes can correct for different weather parameters simultaneously, and 4D-VAR allow us to assimilate DIR values at the exact moment of satellite overpass instead of the start of the forecast window. The approach will be demonstrated

  15. Real-time projections of cholera outbreaks through data assimilation and rainfall forecasting

    Science.gov (United States)

    Pasetto, Damiano; Finger, Flavio; Rinaldo, Andrea; Bertuzzo, Enrico

    2017-10-01

    Although treatment for cholera is well-known and cheap, outbreaks in epidemic regions still exact high death tolls mostly due to the unpreparedness of health care infrastructures to face unforeseen emergencies. In this context, mathematical models for the prediction of the evolution of an ongoing outbreak are of paramount importance. Here, we test a real-time forecasting framework that readily integrates new information as soon as available and periodically issues an updated forecast. The spread of cholera is modeled by a spatially-explicit scheme that accounts for the dynamics of susceptible, infected and recovered individuals hosted in different local communities connected through hydrologic and human mobility networks. The framework presents two major innovations for cholera modeling: the use of a data assimilation technique, specifically an ensemble Kalman filter, to update both state variables and parameters based on the observations, and the use of rainfall forecasts to force the model. The exercise of simulating the state of the system and the predictive capabilities of the novel tools, set at the initial phase of the 2010 Haitian cholera outbreak using only information that was available at that time, serves as a benchmark. Our results suggest that the assimilation procedure with the sequential update of the parameters outperforms calibration schemes based on Markov chain Monte Carlo. Moreover, in a forecasting mode the model usefully predicts the spatial incidence of cholera at least one month ahead. The performance decreases for longer time horizons yet allowing sufficient time to plan for deployment of medical supplies and staff, and to evaluate alternative strategies of emergency management.

  16. Global heating distributions for January 1979 calculated from GLA assimilated and simulated model-based datasets

    Science.gov (United States)

    Schaack, Todd K.; Lenzen, Allen J.; Johnson, Donald R.

    1991-01-01

    This study surveys the large-scale distribution of heating for January 1979 obtained from five sources of information. Through intercomparison of these distributions, with emphasis on satellite-derived information, an investigation is conducted into the global distribution of atmospheric heating and the impact of observations on the diagnostic estimates of heating derived from assimilated datasets. The results indicate a substantial impact of satellite information on diagnostic estimates of heating in regions where there is a scarcity of conventional observations. The addition of satellite data provides information on the atmosphere's temperature and wind structure that is important for estimation of the global distribution of heating and energy exchange.

  17. User Friendly Open GIS Tool for Large Scale Data Assimilation - a Case Study of Hydrological Modelling

    Science.gov (United States)

    Gupta, P. K.

    2012-08-01

    Open source software (OSS) coding has tremendous advantages over proprietary software. These are primarily fuelled by high level programming languages (JAVA, C++, Python etc...) and open source geospatial libraries (GDAL/OGR, GEOS, GeoTools etc.). Quantum GIS (QGIS) is a popular open source GIS package, which is licensed under GNU GPL and is written in C++. It allows users to perform specialised tasks by creating plugins in C++ and Python. This research article emphasises on exploiting this capability of QGIS to build and implement plugins across multiple platforms using the easy to learn - Python programming language. In the present study, a tool has been developed to assimilate large spatio-temporal datasets such as national level gridded rainfall, temperature, topographic (digital elevation model, slope, aspect), landuse/landcover and multi-layer soil data for input into hydrological models. At present this tool has been developed for Indian sub-continent. An attempt is also made to use popular scientific and numerical libraries to create custom applications for digital inclusion. In the hydrological modelling calibration and validation are important steps which are repetitively carried out for the same study region. As such the developed tool will be user friendly and used efficiently for these repetitive processes by reducing the time required for data management and handling. Moreover, it was found that the developed tool can easily assimilate large dataset in an organised manner.

  18. Data Assimilation in Forest Inventory: First Empirical Results

    Directory of Open Access Journals (Sweden)

    Mattias Nyström

    2015-12-01

    Full Text Available Data assimilation techniques were used to estimate forest stand data in 2011 by sequentially combining remote sensing based estimates of forest variables with predictions from growth models. Estimates of stand data, based on canopy height models obtained from image matching of digital aerial images at six different time-points between 2003 and 2011, served as input to the data assimilation. The assimilation routines were built on the extended Kalman filter. The study was conducted in hemi-boreal forest at the Remningstorp test site in southern Sweden (lat. 13°37′ N; long. 58°28′ E. The assimilation results were compared with two other methods used in practice for estimation of forest variables: the first was to use only the most recent estimate obtained from remotely sensed data (2011 and the second was to forecast the first estimate (2003 to the endpoint (2011. All three approaches were validated using nine 40 m radius validation plots, which were carefully measured in the field. The results showed that the data assimilation approach provided better results than the two alternative methods. Data assimilation of remote sensing time series has been used previously for calibrating forest ecosystem models, but, to our knowledge, this is the first study with real data where data assimilation has been used for estimating forest inventory data. The study constitutes a starting point for the development of a framework useful for sequentially utilizing all types of remote sensing data in order to provide precise and up-to-date estimates of forest stand parameters.

  19. Evaluating the performance of the Electron Density Assimilative Model (EDAM) in the Western European sector using modified Taylor diagrams

    Science.gov (United States)

    Jackson-Booth, N.; Parker, J.; Pryse, S. E.; Buckland, R.

    2017-12-01

    The Electron Density Assimilative Model (EDAM) is an ionospheric model that assimilates data sources into a background model, currently provided by IRI2007, to generate a global, or regional, 3D representation of the ionospheric electron density. In this study, slant total electron content (sTEC) between GPS satellites and 43 ground receivers in Europe were assimilated into EDAM to model the ionospheric electron density over western Europe. For the evaluation of the model an additional ground receiver (the truth station) was considered, which was not used in the assimilation process. Slant total electron contents for this station were calculated through the EDAM model along satellite-to-receiver paths corresponding to those of the observations made by the receiver. The modelled and observed sTEC were compared for each satellite and every day, between September 2002 and August 2003. For the comparison standard deviations of the modelled and observed sTEC were determined. These were used in modified Taylor Diagrams to display the mean-removed rms difference between the model and observations, the correlation between the two data sets and the bias of the modelled data. Taylor diagrams were obtained for the entire year, and each season and month. Results of the comparisons are presented and discussed, with a specific interest in times that show increased rms differences and decreased correlations between the data sets. The effect of the satellite calibration biases on the results are also considered.

  20. DART: New Research Using Ensemble Data Assimilation in Geophysical Models

    Science.gov (United States)

    Hoar, T. J.; Raeder, K.

    2015-12-01

    The Data Assimilation Research Testbed (DART) is a community facilityfor ensemble data assimilation developed and supported by the NationalCenter for Atmospheric Research. DART provides a comprehensive suite of software, documentation, and tutorials that can be used for ensemble data assimilation research, operations, and education. Scientists and software engineers at NCAR are available to support DART users who want to use existing DART products or develop their own applications. Current DART users range from university professors teaching data assimilation, to individual graduate students working with simple models, through national laboratories doing operational prediction with large state-of-the-art models. DART runs efficiently on many computational platforms ranging from laptops through thousands of cores on the newest supercomputers.This poster focuses on several recent research activities using DART with geophysical models.Using CAM/DART to understand whether OCO-2 Total Precipitable Water observations can be useful in numerical weather prediction.Impacts of the synergistic use of Infra-red CO retrievals (MOPITT, IASI) in CAM-CHEM/DART assimilations.Assimilation and Analysis of Observations of Amazonian Biomass Burning Emissions by MOPITT (aerosol optical depth), MODIS (carbon monoxide) and MISR (plume height).Long term evaluation of the chemical response of MOPITT-CO assimilation in CAM-CHEM/DART OSSEs for satellite planning and emission inversion capabilities.Improved forward observation operators for land models that have multiple land use/land cover segments in a single grid cell,Simulating mesoscale convective systems (MCSs) using a variable resolution, unstructured grid in the Model for Prediction Across Scales (MPAS) and DART.The mesoscale WRF+DART system generated an ensemble of year-long, real-time initializations of a convection allowing model over the United States.Constraining WACCM with observations in the tropical band (30S-30N) using DART

  1. Assimilation of Altimeter Data into a Quasigeostrophic Model of the Gulf Stream System. Part 2; Assimilation Results

    Science.gov (United States)

    Capotondi, Antonietta; Holland, William R.; Malanotte-Rizzoli, Paola

    1995-01-01

    The improvement in the climatological behavior of a numerical model as a consequence of the assimilation of surface data is investigated. The model used for this study is a quasigeostrophic (QG) model of the Gulf Stream region. The data that have been assimilated are maps of sea surface height that have been obtained as the superposition of sea surface height variability deduced from the Geosat altimeter measurements and a mean field constructed from historical hydrographic data. The method used for assimilating the data is the nudging technique. Nudging has been implemented in such a way as to achieve a high degree of convergence of the surface model fields toward the observations. Comparisons of the assimilation results with available in situ observations show a significant improvement in the degree of realism of the climatological model behavior, with respect to the model in which no data are assimilated. The remaining discrepancies in the model mean circulation seem to be mainly associated with deficiencies in the mean component of the surface data that are assimilated. On the other hand, the possibility of building into the model more realistic eddy characteristics through the assimilation of the surface eddy field proves very successful in driving components of the mean model circulation that are in relatively good agreement with the available observations. Comparisons with current meter time series during a time period partially overlapping the Geosat mission show that the model is able to 'correctly' extrapolate the instantaneous surface eddy signals to depths of approximately 1500 m. The correlation coefficient between current meter and model time series varies from values close to 0.7 in the top 1500 m to values as low as 0.1-0.2 in the deep ocean.

  2. An integrated GIS application system for soil moisture data assimilation

    Science.gov (United States)

    Wang, Di; Shen, Runping; Huang, Xiaolong; Shi, Chunxiang

    2014-11-01

    The gaps in knowledge and existing challenges in precisely describing the land surface process make it critical to represent the massive soil moisture data visually and mine the data for further research.This article introduces a comprehensive soil moisture assimilation data analysis system, which is instructed by tools of C#, IDL, ArcSDE, Visual Studio 2008 and SQL Server 2005. The system provides integrated service, management of efficient graphics visualization and analysis of land surface data assimilation. The system is not only able to improve the efficiency of data assimilation management, but also comprehensively integrate the data processing and analysis tools into GIS development environment. So analyzing the soil moisture assimilation data and accomplishing GIS spatial analysis can be realized in the same system. This system provides basic GIS map functions, massive data process and soil moisture products analysis etc. Besides,it takes full advantage of a spatial data engine called ArcSDE to effeciently manage, retrieve and store all kinds of data. In the system, characteristics of temporal and spatial pattern of soil moiture will be plotted. By analyzing the soil moisture impact factors, it is possible to acquire the correlation coefficients between soil moisture value and its every single impact factor. Daily and monthly comparative analysis of soil moisture products among observations, simulation results and assimilations can be made in this system to display the different trends of these products. Furthermore, soil moisture map production function is realized for business application.

  3. Development Of A Data Assimilation Capability For RAPID

    Science.gov (United States)

    Emery, C. M.; David, C. H.; Turmon, M.; Hobbs, J.; Allen, G. H.; Famiglietti, J. S.

    2017-12-01

    The global decline of in situ observations associated with the increasing ability to monitor surface water from space motivates the creation of data assimilation algorithms that merge computer models and space-based observations to produce consistent estimates of terrestrial hydrology that fill the spatiotemporal gaps in observations. RAPID is a routing model based on the Muskingum method that is capable of estimating river streamflow over large scales with a relatively short computing time. This model only requires limited inputs: a reach-based river network, and lateral surface and subsurface flow into the rivers. The relatively simple model physics imply that RAPID simulations could be significantly improved by including a data assimilation capability. Here we present the early developments of such data assimilation approach into RAPID. Given the linear and matrix-based structure of the model, we chose to apply a direct Kalman filter, hence allowing for the preservation of high computational speed. We correct the simulated streamflows by assimilating streamflow observations and our early results demonstrate the feasibility of the approach. Additionally, the use of in situ gauges at continental scales motivates the application of our new data assimilation scheme to altimetry measurements from existing (e.g. EnviSat, Jason 2) and upcoming satellite missions (e.g. SWOT), and ultimately apply the scheme globally.

  4. Kinetics of 15NH4+ assimilation in Zea mays

    International Nuclear Information System (INIS)

    Magalhaes, J.R.; Ju, G.C.; Rich, P.J.; Rhodes, D.

    1990-01-01

    Comparative studies of 15 NH 4 + assimilation were undertaken with a GDH1-null mutant of Zea mays and a related (but not strictly isogenic) GDH1-positive wild type from which this mutant was derived. The kinetics of 15 NH 4 + assimilation into free amino acids and total reduced nitrogen were monitored in both roots and shoots of 2-week-old seedlings supplied with 5 millimolar 99% ( 15 NH 4 ) 2 SO 4 via the aerated root medium in hydroponic culture over a 24-h period. The GDH1-null mutant, with a 10- to 15-fold lower total root GDH activity in comparison to the wild type, was found to exhibit a 40 to 50% lower rate of 15 NH 4 + assimilation into total reduced nitrogen. The lower rates of 15 NH 4 + assimilation in the mutant was associated with lower rates of labeling of several free amino acids (including glutamate, glutamine-amino N, aspartate, asparagine-amino N, and alanine) in both roots and shoots of the mutant in comparison to the wild type. Qualitatively, these labeling kinetics appear consistent with a reduced flux of 15 N via glutamate in the GDH1-null mutant. However, the responses of the two genotypes to the potent inhibitor of glutamine synthetase, methionine sulfoximine, and differences in morphology of the two genotypes (particularly a lower shoot:root ratio in the GDH1-null mutant) urge caution in concluding that GDH1 is solely responsible for these differences in ammonia assimilation rate

  5. Multiscale Data Assimilation for Large-Eddy Simulations

    Science.gov (United States)

    Li, Z.; Cheng, X.; Gustafson, W. I., Jr.; Xiao, H.; Vogelmann, A. M.; Endo, S.; Toto, T.

    2017-12-01

    Large-eddy simulation (LES) is a powerful tool for understanding atmospheric turbulence, boundary layer physics and cloud development, and there is a great need for developing data assimilation methodologies that can constrain LES models. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility has been developing the capability to routinely generate ensembles of LES. The LES ARM Symbiotic Simulation and Observation (LASSO) project (https://www.arm.gov/capabilities/modeling/lasso) is generating simulations for shallow convection days at the ARM Southern Great Plains site in Oklahoma. One of major objectives of LASSO is to develop the capability to observationally constrain LES using a hierarchy of ARM observations. We have implemented a multiscale data assimilation (MSDA) scheme, which allows data assimilation to be implemented separately for distinct spatial scales, so that the localized observations can be effectively assimilated to constrain the mesoscale fields in the LES area of about 15 km in width. The MSDA analysis is used to produce forcing data that drive LES. With such LES workflow we have examined 13 days with shallow convection selected from the period May-August 2016. We will describe the implementation of MSDA, present LES results, and address challenges and opportunities for applying data assimilation to LES studies.

  6. Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models

    Science.gov (United States)

    Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri

    2015-09-01

    Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.

  7. Assimilation of GNSS radio occultation observations in GRAPES

    Science.gov (United States)

    Liu, Y.; Xue, J.

    2014-07-01

    This paper reviews the development of the global navigation satellite system (GNSS) radio occultation (RO) observations assimilation in the Global/Regional Assimilation and PrEdiction System (GRAPES) of China Meteorological Administration, including the choice of data to assimilate, the data quality control, the observation operator, the tuning of observation error, and the results of the observation impact experiments. The results indicate that RO data have a significantly positive effect on analysis and forecast at all ranges in GRAPES not only in the Southern Hemisphere where conventional observations are lacking but also in the Northern Hemisphere where data are rich. It is noted that a relatively simple assimilation and forecast system in which only the conventional and RO observation are assimilated still has analysis and forecast skill even after nine months integration, and the analysis difference between both hemispheres is gradually reduced with height when compared with NCEP (National Centers for Enviromental Prediction) analysis. Finally, as a result of the new onboard payload of the Chinese FengYun-3 (FY-3) satellites, the research status of the RO of FY-3 satellites is also presented.

  8. Assimilating the Future for Better Forecasts and Earlier Warnings

    Science.gov (United States)

    Du, H.; Wheatcroft, E.; Smith, L. A.

    2016-12-01

    Multi-model ensembles have become popular tools to account for some of the uncertainty due to model inadequacy in weather and climate simulation-based predictions. The current multi-model forecasts focus on combining single model ensemble forecasts by means of statistical post-processing. Assuming each model is developed independently or with different primary target variables, each is likely to contain different dynamical strengths and weaknesses. Using statistical post-processing, such information is only carried by the simulations under a single model ensemble: no advantage is taken to influence simulations under the other models. A novel methodology, named Multi-model Cross Pollination in Time, is proposed for multi-model ensemble scheme with the aim of integrating the dynamical information regarding the future from each individual model operationally. The proposed approach generates model states in time via applying data assimilation scheme(s) to yield truly "multi-model trajectories". It is demonstrated to outperform traditional statistical post-processing in the 40-dimensional Lorenz96 flow. Data assimilation approaches are originally designed to improve state estimation from the past to the current time. The aim of this talk is to introduce a framework that uses data assimilation to improve model forecasts at future time (not to argue for any one particular data assimilation scheme). Illustration of applying data assimilation "in the future" to provide early warning of future high-impact events is also presented.

  9. Potential for wind extraction from 4D-Var assimilation of aerosols and moisture

    Science.gov (United States)

    Zaplotnik, Žiga; Žagar, Nedjeljka

    2017-04-01

    We discuss the potential of the four-dimensional variational data assimilation (4D-Var) to retrieve the unobserved wind field from observations of atmospheric tracers and the mass field through internal model dynamics and the multivariate relationships in the background-error term for 4D-Var. The presence of non-linear moist dynamics makes the wind retrieval from tracers very difficult. On the other hand, it has been shown that moisture observations strongly influence both tropical and mid-latitude wind field in 4D-Var. We present an intermediate complexity model that describes nonlinear interactions between the wind, temperature, aerosols and moisture including their sinks and sources in the framework of the so-called first baroclinic mode atmosphere envisaged by A. Gill. Aerosol physical processes, which are included in the model, are the non-linear advection, diffusion and sources and sinks that exist as dry and wet deposition and diffusion. Precipitation is parametrized according to the Betts-Miller scheme. The control vector for 4D-Var includes aerosols, moisture and the three dynamical variables. The former is analysed univariately whereas wind field and mass field are analysed in a multivariate fashion taking into account quasi-geostrophic and unbalanced dynamics. The OSSE type of studies are performed for the tropical region to assess the ability of 4D-Var to extract wind-field information from the time series of observations of tracers as a function of the flow nonlinearity, the observations density and the length of the assimilation window (12 hours and 24 hours), in dry and moist environment. Results show that the 4D-Var assimilation of aerosols and temperature data is beneficial for the wind analysis with analysis errors strongly dependent on the moist processes and reliable background-error covariances.

  10. Modelling fungal sink competitiveness with grains for assimilates in wheat infected by a biotrophic pathogen

    Science.gov (United States)

    Bancal, Marie-Odile; Hansart, Amandine; Sache, Ivan; Bancal, Pierre

    2012-01-01

    Background and Aims Experiments have shown that biotrophic fungi divert assimilates for their growth. However, no attempt has been made either to account for this additional sink or to predict to what extent it competes with both grain filling and plant reserve metabolism for carbon. Fungal sink competitiveness with grains was quantified by a mixed experimental–modelling approach based on winter wheat infected by Puccinia triticina. Methods One week after anthesis, plants grown under controlled conditions were inoculated with varying loads. Sporulation was recorded while plants underwent varying degrees of shading, ensuring a range of both fungal sink and host source levels. Inoculation load significantly increased both sporulating area and rate. Shading significantly affected net assimilation, reserve mobilization and sporulating area, but not grain filling or sporulation rates. An existing carbon partitioning (source–sink) model for wheat during the grain filling period was then enhanced, in which two parameters characterize every sink: carriage capacity and substrate affinity. Fungal sink competitiveness with host sources and sinks was modelled by representing spore production as another sink in diseased wheat during grain filling. Key Results Data from the experiment were fitted to the model to provide the fungal sink parameters. Fungal carriage capacity was 0·56 ± 0·01 µg dry matter °Cd−1 per lesion, much less than grain filling capacity, even in highly infected plants; however, fungal sporulation had a competitive priority for assimilates over grain filling. Simulation with virtual crops accounted for the importance of the relative contribution of photosynthesis loss, anticipated reserve depletion and spore production when light level and disease severity vary. The grain filling rate was less reduced than photosynthesis; however, over the long term, yield loss could double because the earlier reserve depletion observed here would shorten the

  11. Advances In Global Aerosol Modeling Applications Through Assimilation of Satellite-Based Lidar Measurements

    Science.gov (United States)

    Campbell, James; Hyer, Edward; Zhang, Jianglong; Reid, Jeffrey; Westphal, Douglas; Xian, Peng; Vaughan, Mark

    2010-05-01

    Modeling the instantaneous three-dimensional aerosol field and its downwind transport represents an endeavor with many practical benefits foreseeable to air quality, aviation, military and science agencies. The recent proliferation of multi-spectral active and passive satellite-based instruments measuring aerosol physical properties has served as an opportunity to develop and refine the techniques necessary to make such numerical modeling applications possible. Spurred by high-resolution global mapping of aerosol source regions, and combined with novel multivariate data assimilation techniques designed to consider these new data streams, operational forecasts of visibility and aerosol optical depths are now available in near real-time1. Active satellite-based aerosol profiling, accomplished using lidar instruments, represents a critical element for accurate analysis and transport modeling. Aerosol source functions, alone, can be limited in representing the macrophysical structure of injection scenarios within a model. Two-dimensional variational (2D-VAR; x, y) assimilation of aerosol optical depth from passive satellite observations significantly improves the analysis of the initial state. However, this procedure can not fully compensate for any potential vertical redistribution of mass required at the innovation step. The expense of an inaccurate vertical analysis of aerosol structure is corresponding errors downwind, since trajectory paths within successive forecast runs will likely diverge with height. In this paper, the application of a newly-designed system for 3D-VAR (x,y,z) assimilation of vertical aerosol extinction profiles derived from elastic-scattering lidar measurements is described [Campbell et al., 2009]. Performance is evaluated for use with the U. S. Navy Aerosol Analysis and Prediction System (NAAPS) by assimilating NASA/CNES satellite-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 0.532 μm measurements [Winker et al., 2009

  12. Revisiting the radionuclide atmospheric dispersion event of the Chernobyl disaster - modelling sensitivity and data assimilation

    Science.gov (United States)

    Roustan, Yelva; Duhanyan, Nora; Bocquet, Marc; Winiarek, Victor

    2013-04-01

    A sensitivity study of the numerical model, as well as, an inverse modelling approach applied to the atmospheric dispersion issues after the Chernobyl disaster are both presented in this paper. On the one hand, the robustness of the source term reconstruction through advanced data assimilation techniques was tested. On the other hand, the classical approaches for sensitivity analysis were enhanced by the use of an optimised forcing field which otherwise is known to be strongly uncertain. The POLYPHEMUS air quality system was used to perform the simulations of radionuclide dispersion. Activity concentrations in air and deposited to the ground of iodine-131, caesium-137 and caesium-134 were considered. The impact of the implemented parameterizations of the physical processes (dry and wet depositions, vertical turbulent diffusion), of the forcing fields (meteorology and source terms) and of the numerical configuration (horizontal resolution) were investigated for the sensitivity study of the model. A four dimensional variational scheme (4D-Var) based on the approximate adjoint of the chemistry transport model was used to invert the source term. The data assimilation is performed with measurements of activity concentrations in air extracted from the Radioactivity Environmental Monitoring (REM) database. For most of the investigated configurations (sensitivity study), the statistics to compare the model results to the field measurements as regards the concentrations in air are clearly improved while using a reconstructed source term. As regards the ground deposited concentrations, an improvement can only be seen in case of satisfactorily modelled episode. Through these studies, the source term and the meteorological fields are proved to have a major impact on the activity concentrations in air. These studies also reinforce the use of reconstructed source term instead of the usual estimated one. A more detailed parameterization of the deposition process seems also to be

  13. Blood Products and the Commodification Debate: The Blurry Concept of Altruism and the 'Implicit Price' of Readily Available Body Parts.

    Science.gov (United States)

    Dufner, Annette

    2015-12-01

    There is a widespread consensus that a commodification of body parts is to be prevented. Numerous policy papers by international organizations extend this view to the blood supply and recommend a system of uncompensated volunteers in this area--often, however, without making the arguments for this view explicit. This situation seems to indicate that a relevant source of justified worry or unease about the blood supply system has to do with the issue of commodification. As a result, the current health minister of Ontario is proposing a ban on compensation even for blood plasma--despite the fact that Canada can only generate 30 % of the plasma needed for fractionation into important plasma protein products and has to purchase the rest abroad. In the following, I am going to suggest a number of alternative perspectives on the debate in order to facilitate a less dogmatic and more differentiated debate about the matter. Especially in light of the often over-simplified notions of altruism and commodification, I conclude that the debate has not conclusively established that it would be morally objectionable to provide blood plasma donors with monetary compensation or with other forms of explicit social recognition as an incentive. This is especially true of donations for fractionation into medicinal products by profit-oriented pharmaceutical companies.

  14. Storm surge model based on variational data assimilation method

    Directory of Open Access Journals (Sweden)

    Shi-li Huang

    2010-06-01

    Full Text Available By combining computation and observation information, the variational data assimilation method has the ability to eliminate errors caused by the uncertainty of parameters in practical forecasting. It was applied to a storm surge model based on unstructured grids with high spatial resolution meant for improving the forecasting accuracy of the storm surge. By controlling the wind stress drag coefficient, the variation-based model was developed and validated through data assimilation tests in an actual storm surge induced by a typhoon. In the data assimilation tests, the model accurately identified the wind stress drag coefficient and obtained results close to the true state. Then, the actual storm surge induced by Typhoon 0515 was forecast by the developed model, and the results demonstrate its efficiency in practical application.

  15. a Thtee-Dimensional Variational Assimilation Scheme for Satellite Aod

    Science.gov (United States)

    Liang, Y.; Zang, Z.; You, W.

    2018-04-01

    A three-dimensional variational data assimilation scheme is designed for satellite AOD based on the IMPROVE (Interagency Monitoring of Protected Visual Environments) equation. The observation operator that simulates AOD from the control variables is established by the IMPROVE equation. All of the 16 control variables in the assimilation scheme are the mass concentrations of aerosol species from the Model for Simulation Aerosol Interactions and Chemistry scheme, so as to take advantage of this scheme in providing comprehensive analyses of species concentrations and size distributions as well as be calculating efficiently. The assimilation scheme can save computational resources as the IMPROVE equation is a quadratic equation. A single-point observation experiment shows that the information from the single-point AOD is effectively spread horizontally and vertically.

  16. Data Assimilation in Hydrodynamic Models of Continental Shelf Seas

    DEFF Research Database (Denmark)

    Sørensen, Jacob Viborg Tornfeldt

    2004-01-01

    . Assimilation of sea surface temperature and parameter estimation in hydrodynamic models are also considered. The main focus has been on the development of robust and efficient techniques applicable in real operational settings. The applied assimilation techniques all use a Kalman filter approach. They consist....... The assimilation schemes used in this work are primarily based on two ensemble based schemes, the Ensemble Kalman Filter and the Reduced Rank Square Root Kalman Filter. In order to investigate the applicability of these and derived schemes, the sensitivity to filter parameters, nonlinearity and bias is examined...... in artificial tests. Approximate schemes, which are theoretically presented as using regularised Kalman gains, are introduced and successfully applied in artificial as well real case scenarios. Particularly, distant dependent and slowly time varying or constant Kalman gains are shown to possess good hindcast...

  17. The Impact of the Assimilation of Aquarius Sea Surface Salinity Data in the GEOS Ocean Data Assimilation System

    Science.gov (United States)

    Vernieres, Guillaume Rene Jean; Kovach, Robin M.; Keppenne, Christian L.; Akella, Santharam; Brucker, Ludovic; Dinnat, Emmanuel Phillippe

    2014-01-01

    Ocean salinity and temperature differences drive thermohaline circulations. These properties also play a key role in the ocean-atmosphere coupling. With the availability of L-band space-borne observations, it becomes possible to provide global scale sea surface salinity (SSS) distribution. This study analyzes globally the along-track (Level 2) Aquarius SSS retrievals obtained using both passive and active L-band observations. Aquarius alongtrack retrieved SSS are assimilated into the ocean data assimilation component of Version 5 of the Goddard Earth Observing System (GEOS-5) assimilation and forecast model. We present a methodology to correct the large biases and errors apparent in Version 2.0 of the Aquarius SSS retrieval algorithm and map the observed Aquarius SSS retrieval into the ocean models bulk salinity in the topmost layer. The impact of the assimilation of the corrected SSS on the salinity analysis is evaluated by comparisons with insitu salinity observations from Argo. The results show a significant reduction of the global biases and RMS of observations-minus-forecast differences at in-situ locations. The most striking results are found in the tropics and southern latitudes. Our results highlight the complementary role and problems that arise during the assimilation of salinity information from in-situ (Argo) and space-borne surface (SSS) observations

  18. Assimilation of satellite color observations in a coupled ocean GCM-ecosystem model

    Science.gov (United States)

    Sarmiento, Jorge L.

    1992-01-01

    Monthly average coastal zone color scanner (CZCS) estimates of chlorophyll concentration were assimilated into an ocean global circulation model(GCM) containing a simple model of the pelagic ecosystem. The assimilation was performed in the simplest possible manner, to allow the assessment of whether there were major problems with the ecosystem model or with the assimilation procedure. The current ecosystem model performed well in some regions, but failed in others to assimilate chlorophyll estimates without disrupting important ecosystem properties. This experiment gave insight into those properties of the ecosystem model that must be changed to allow data assimilation to be generally successful, while raising other important issues about the assimilation procedure.

  19. A Cyanide-Induced 3-Cyanoalanine Nitrilase in the Cyanide-Assimilating Bacterium Pseudomonas pseudoalcaligenes Strain CECT 5344.

    Science.gov (United States)

    Acera, Felipe; Carmona, María Isabel; Castillo, Francisco; Quesada, Alberto; Blasco, Rafael

    2017-05-01

    Pseudomonas pseudoalcaligenes CECT 5344 is a bacterium able to assimilate cyanide as a sole nitrogen source. Under this growth condition, a 3-cyanoalanine nitrilase enzymatic activity was induced. This activity was encoded by nit4 , one of the four nitrilase genes detected in the genome of this bacterium, and its expression in Escherichia coli enabled the recombinant strain to fully assimilate 3-cyanoalanine. P. pseudoalcaligenes CECT 5344 showed a weak growth level with 3-cyanoalanine as the N source, unless KCN was also added. Moreover, a nit4 knockout mutant of P. pseudoalcaligenes CECT 5344 became severely impaired in its ability to grow with 3-cyanoalanine and cyanide as nitrogen sources. The native enzyme expressed in E. coli was purified up to electrophoretic homogeneity and biochemically characterized. Nit4 seems to be specific for 3-cyanoalanine, and the amount of ammonium derived from the enzymatic activity doubled in the presence of exogenously added asparaginase activity, which demonstrated that the Nit4 enzyme had both 3-cyanoalanine nitrilase and hydratase activities. The nit4 gene is located downstream of the cyanide resistance transcriptional unit containing cio1 genes, whose expression levels are under the positive control of cyanide. Real-time PCR experiments revealed that nit4 expression was also positively regulated by cyanide in both minimal and LB media. These results suggest that this gene cluster including cio1 and nit4 could be involved both in cyanide resistance and in its assimilation by P. pseudoalcaligenes CECT 5344. IMPORTANCE Cyanide is a highly toxic molecule present in some industrial wastes due to its application in several manufacturing processes, such as gold mining and the electroplating industry. The biodegradation of cyanide from contaminated wastes could be an attractive alternative to physicochemical treatment. P. pseudoalcaligenes CECT 5344 is a bacterial strain able to assimilate cyanide under alkaline conditions, thus

  20. Biomass assimilation in coupled ecohydrodynamical model of the Mediterranean Sea

    Science.gov (United States)

    Crispi, G.; Bournaski, E.; Crise, A.

    2003-04-01

    Data assimilation has raised new interest in the last years in the context of the environmental sciences. The swift increment of the attention paid to it in oceanography is due to the coming age of operational services for the marine environment which is going to dramatically increase the demand for accurate, timely and reliable estimates of the space and time distribution both for physical and in a near future for biogeochemical fields. Data assimilation combines information derived from measurements with knowledge of the rules that govern the evolution of the system of interest through formalization and implementation in numerical models. The importance of ocean data assimilation has been recognized by several international programmes as JGOFS, GOOS and CLIVAR. This work presents an eco-hydrodynamic model of the Mediterranean Sea developed at the Istituto Nazionale di Oceanografia e di Geofisica Sperimentale - OGS, Trieste, Italy. It includes 3-D MOM-based hydrodynamics of the Mediterranean Sea, coupled with biochemical model of Nitrogen, Phytoplankton, Zooplankton, and Detritus (NPZD). Monthly mean wind forcings are adopted to force this MOM-NPZD model. For better prediction and analysis of N, P, Z and D distributions in the sea the model needs data assimilation from biomass observations on the sea surface. Chosen approach for evaluating performances of data assimilation techniques in coupled model is the definition of a twin experiment testbed where a reference run is carried out assuming its result as the truth. We define a sampling strategy to obtain different datasets to be incorporated in another ecological model in successive runs in order to appraise the potential of the data assimilation and sampling strategy. The runs carried out with different techniques and different spatio-temporal coverages are compared in order to evaluate the sensitivity to different coverage of dataset. The discussed alternative way is to assume the ecosystem at steady state and

  1. Ensemble streamflow assimilation with the National Water Model.

    Science.gov (United States)

    Rafieeinasab, A.; McCreight, J. L.; Noh, S.; Seo, D. J.; Gochis, D.

    2017-12-01

    Through case studies of flooding across the US, we compare the performance of the National Water Model (NWM) data assimilation (DA) scheme to that of a newly implemented ensemble Kalman filter approach. The NOAA National Water Model (NWM) is an operational implementation of the community WRF-Hydro modeling system. As of August 2016, the NWM forecasts of distributed hydrologic states and fluxes (including soil moisture, snowpack, ET, and ponded water) over the contiguous United States have been publicly disseminated by the National Center for Environmental Prediction (NCEP) . It also provides streamflow forecasts at more than 2.7 million river reaches up to 30 days in advance. The NWM employs a nudging scheme to assimilate more than 6,000 USGS streamflow observations and provide initial conditions for its forecasts. A problem with nudging is how the forecasts relax quickly to open-loop bias in the forecast. This has been partially addressed by an experimental bias correction approach which was found to have issues with phase errors during flooding events. In this work, we present an ensemble streamflow data assimilation approach combining new channel-only capabilities of the NWM and HydroDART (a coupling of the offline WRF-Hydro model and NCAR's Data Assimilation Research Testbed; DART). Our approach focuses on the single model state of discharge and incorporates error distributions on channel-influxes (overland and groundwater) in the assimilation via an ensemble Kalman filter (EnKF). In order to avoid filter degeneracy associated with a limited number of ensemble at large scale, DART's covariance inflation (Anderson, 2009) and localization capabilities are implemented and evaluated. The current NWM data assimilation scheme is compared to preliminary results from the EnKF application for several flooding case studies across the US.

  2. Assimilation of satellite altimeter data into an open ocean model

    Science.gov (United States)

    Vogeler, Armin; SchröTer, Jens

    1995-08-01

    Geosat sea surface height data are assimilated into an eddy-resolving quasi-geostrophic open ocean model using the adjoint technique. The method adjusts the initial conditions for all layers and is successful on the timescale of a few weeks. Time-varying values for the open boundaries are prescribed by a much larger quasi-geostrophic model of the Antarctic Circumpolar Current (ACC). Both models have the same resolution of approximately 20×20 km (1/3°×1/6°), have three layers, and include realistic bottom topography and coastlines. The open model box is embedded in the African sector of the ACC. For continuous assimilation of satellite data into the larger model the nudging technique is applied. These results are used for the adjoint optimization procedure as boundary conditions and as a first guess for the initial condition. For the open model box the difference between model and satellite sea surface height that remains after the nudging experiment amounts to a 19-cm root-mean-square error (rmse). By assimilation into the regional model this value can be reduced to a 6-cm rmse for an assimilation period of 20 days. Several experiments which attempt to improve the convergence of the iterative optimization method are reported. Scaling and regularization by smoothing have to be applied carefully. Especially during the first 10 iterations, the convergence can be improved considerably by low-pass filtering of the cost function gradient. The result of a perturbation experiment shows that for longer assimilation periods the influence of the boundary values becomes dominant and they should be determined inversely by data assimilation into the open ocean model.

  3. Assimilation scheme of the Mediterranean Forecasting System: operational implementation

    Directory of Open Access Journals (Sweden)

    E. Demirov

    Full Text Available This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP. The assimilation scheme, System for Ocean Forecast and Analysis (SOFA, is a reduced order Optimal Interpolation (OI scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF. The data assimilated are Sea Level Anomaly (SLA and temperature profiles from Expandable Bathy Termographs (XBT. The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT. The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS between the model forecast and the analysis (the forecast RMS is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements.

    Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction

  4. Assimilation scheme of the Mediterranean Forecasting System: operational implementation

    Directory of Open Access Journals (Sweden)

    E. Demirov

    2003-01-01

    Full Text Available This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP. The assimilation scheme, System for Ocean Forecast and Analysis (SOFA, is a reduced order Optimal Interpolation (OI scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF. The data assimilated are Sea Level Anomaly (SLA and temperature profiles from Expandable Bathy Termographs (XBT. The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT. The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS between the model forecast and the analysis (the forecast RMS is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements. Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction

  5. Accounting for Location Error in Kalman Filters: Integrating Animal Borne Sensor Data into Assimilation Schemes

    Science.gov (United States)

    Sengupta, Aritra; Foster, Scott D.; Patterson, Toby A.; Bravington, Mark

    2012-01-01

    Data assimilation is a crucial aspect of modern oceanography. It allows the future forecasting and backward smoothing of ocean state from the noisy observations. Statistical methods are employed to perform these tasks and are often based on or related to the Kalman filter. Typically Kalman filters assumes that the locations associated with observations are known with certainty. This is reasonable for typical oceanographic measurement methods. Recently, however an alternative and abundant source of data comes from the deployment of ocean sensors on marine animals. This source of data has some attractive properties: unlike traditional oceanographic collection platforms, it is relatively cheap to collect, plentiful, has multiple scientific uses and users, and samples areas of the ocean that are often difficult of costly to sample. However, inherent uncertainty in the location of the observations is a barrier to full utilisation of animal-borne sensor data in data-assimilation schemes. In this article we examine this issue and suggest a simple approximation to explicitly incorporate the location uncertainty, while staying in the scope of Kalman-filter-like methods. The approximation stems from a Taylor-series approximation to elements of the updating equation. PMID:22900005

  6. Multivariate and multiscale data assimilation in terrestrial systems: a review.

    Science.gov (United States)

    Montzka, Carsten; Pauwels, Valentijn R N; Franssen, Harrie-Jan Hendricks; Han, Xujun; Vereecken, Harry

    2012-11-26

    More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA) methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF), Particle Filter (PF) and variational methods (3/4D-VAR). In this review, we distinguish between four major DA approaches: (1) univariate single-scale DA (UVSS), which is the approach used in the majority of published DA applications, (2) univariate multiscale DA (UVMS) referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3) multivariate single-scale DA (MVSS) dealing with the assimilation of at least two different data types, and (4) combined multivariate multiscale DA (MVMS). Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a

  7. Multivariate and Multiscale Data Assimilation in Terrestrial Systems: A Review

    Directory of Open Access Journals (Sweden)

    Harry Vereecken

    2012-11-01

    Full Text Available More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF, Particle Filter (PF and variational methods (3/4D-VAR. In this review, we distinguish between four major DA approaches: (1 univariate single-scale DA (UVSS, which is the approach used in the majority of published DA applications, (2 univariate multiscale DA (UVMS referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3 multivariate single-scale DA (MVSS dealing with the assimilation of at least two different data types, and (4 combined multivariate multiscale DA (MVMS. Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a

  8. Reconstruction of Historical Weather by Assimilating Old Weather Diary Data

    Science.gov (United States)

    Neluwala, P.; Yoshimura, K.; Toride, K.; Hirano, J.; Ichino, M.; Okazaki, A.

    2017-12-01

    Climate can control not only human life style but also other living beings. It is important to investigate historical climate to understand the current and future climates. Information about daily weather can give a better understanding of past life on earth. Long-term weather influences crop calendar as well as the development of civilizations. Unfortunately, existing reconstructed daily weather data are limited to 1850s due to the availability of instrumental data. The climate data prior to that are derived from proxy materials (e.g., tree-ring width, ice core isotopes, etc.) which are either in annual or decadal scale. However, there are many historical documents which contain information about weather such as personal diaries. In Japan, around 20 diaries in average during the 16th - 19th centuries have been collected and converted into a digitized form. As such, diary data exist in many other countries. This study aims to reconstruct historical daily weather during the 18th and 19th centuries using personal daily diaries which have analogue weather descriptions such as `cloudy' or `sunny'. A recent study has shown the possibility of assimilating coarse weather data using idealized experiments. We further extend this study by assimilating modern weather descriptions similar to diary data in recent periods. The Global Spectral model (GSM) of National Centers for Environmental Prediction (NCEP) is used to reconstruct weather with the Local Ensemble Kalman filter (LETKF). Descriptive data are first converted to model variables such as total cloud cover (TCC), solar radiation and precipitation using empirical relationships. Those variables are then assimilated on a daily basis after adding random errors to consider the uncertainty of actual diary data. The assimilation of downward short wave solar radiation using weather descriptions improves RMSE from 64.3 w/m2 to 33.0 w/m2 and correlation coefficient (R) from 0.5 to 0.8 compared with the case without any

  9. SMAP Data Assimilation at NASA SPoRT

    Science.gov (United States)

    Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

    2016-01-01

    The NASA Short-Term Prediction Research and Transition (SPoRT) Center maintains a near-real- time run of the Noah Land Surface Model within the Land Information System (LIS) at 3-km resolution. Soil moisture products from this model are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. We have implemented assimilation of soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active/ Passive (SMAP) satellites, and are now evaluating the SMAP assimilation. The SMAP-enhanced LIS product is planned for public release by October 2016.

  10. Assimilation of radar-based nowcast into HIRLAM NWP model

    DEFF Research Database (Denmark)

    Jensen, David Getreuer; Petersen, Claus; Rasmussen, Michael R.

    2015-01-01

    The present study introduces a nowcast scheme that assimilates radar extrapolation data (RED) into a nowcasting version of the high resolution limited area model (HIRLAM) numerical weather prediction (NWP) model covering the area of Denmark. The RED are based on the Co-TREC (tracking radar echoes...... by correlation) methodology and are generated from cleaned radar mosaics from the Danish weather radar network. The assimilation technique is a newly developed method that increases model precipitation by increasing low-level convergence and decreasing convergence aloft in order to increase the vertical velocity....... The level of improved predictability relies on the RED quality, which again relies on the type of event....

  11. Data assimilation in integrated hydrological modeling using ensemble Kalman filtering

    DEFF Research Database (Denmark)

    Rasmussen, Jørn; Madsen, H.; Jensen, Karsten Høgh

    2015-01-01

    Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members...... and estimating parameters requires a much larger ensemble size than just assimilating groundwater head observations. However, the required ensemble size can be greatly reduced with the use of adaptive localization, which by far outperforms distance-based localization. The study is conducted using synthetic data...

  12. Data Assimilation for Management of Industrial Groundwater Contamination at a Regional Scale

    KAUST Repository

    El Gharamti, Mohamad

    2014-12-01

    Groundwater is one of the main sources for drinking water and agricultural activities. Various activities of both humans and nature may lead to groundwater pollution. Very often, pollution, or contamination, of groundwater goes undetected for long periods of time until it begins to a ect human health and/or the environment. Cleanup technologies used to remediate pollution can be costly and remediation processes are often protracted. A more practical and feasible way to manage groundwater contamination is to monitor and predict contamination and act as soon as there is risk to the population and the environment. Predicting groundwater contamination requires advanced numerical models of groundwater ow and solute transport. Such numerical modeling is increasingly becoming a reference criterion for water resources assessment and environmental protection. Subsurface numerical models are, however, subject to many sources of uncertainties from unknown parameters and approximate dynamics. This dissertation considers the sequential data assimilation approach and tackles the groundwater contamination problem at the port of Rotterdam in the Netherlands. Industrial concentration data are used to monitor and predict the fate of organic contaminants using a threedimensional coupled ow and reactive transport model. We propose a number of 5 novel assimilation techniques that address di erent challenges, including prohibitive computational burden, the nonlinearity and coupling of the subsurface dynamics, and the structural and parametric uncertainties. We also investigate the problem of optimal observational designs to optimize the location and the number of wells. The proposed new methods are based on the ensemble Kalman Filter (EnKF), which provides an e cient numerical solution to the Bayesian ltering problem. The dissertation rst investigates in depth the popular joint and dual ltering formulations of the state-parameters estimation problem. New methodologies, algorithmically

  13. Coupled atmosphere and land-surface assimilation of surface observations with a single column model and ensemble data assimilation

    Science.gov (United States)

    Rostkier-Edelstein, Dorita; Hacker, Joshua P.; Snyder, Chris

    2014-05-01

    Numerical weather prediction and data assimilation models are composed of coupled atmosphere and land-surface (LS) components. If possible, the assimilation procedure should be coupled so that observed information in one module is used to correct fields in the coupled module. There have been some attempts in this direction using optimal interpolation, nudging and 2/3DVAR data assimilation techniques. Aside from satellite remote sensed observations, reference height in-situ observations of temperature and moisture have been used in these studies. Among other problems, difficulties in coupled atmosphere and LS assimilation arise as a result of the different time scales characteristic of each component and the unsteady correlation between these components under varying flow conditions. Ensemble data-assimilation techniques rely on flow dependent observations-model covariances. Provided that correlations and covariances between land and atmosphere can be adequately simulated and sampled, ensemble data assimilation should enable appropriate assimilation of observations simultaneously into the atmospheric and LS states. Our aim is to explore assimilation of reference height in-situ temperature and moisture observations into the coupled atmosphere-LS modules(simultaneously) in NCAR's WRF-ARW model using the NCAR's DART ensemble data-assimilation system. Observing system simulation experiments (OSSEs) are performed using the single column model (SCM) version of WRF. Numerical experiments during a warm season are centered on an atmospheric and soil column in the South Great Plains. Synthetic observations are derived from "truth" WRF-SCM runs for a given date,initialized and forced using North American Regional Reanalyses (NARR). WRF-SCM atmospheric and LS ensembles are created by mixing the atmospheric and soil NARR profile centered on a given date with that from another day (randomly chosen from the same season) with weights drawn from a logit-normal distribution. Three

  14. Field determination of 137Cs assimilation efficiencies in wild cotton rats (Sigmodon hispidus)

    International Nuclear Information System (INIS)

    Garten, C.T. Jr.

    1980-01-01

    Unexplained anomalies have been found between predicted and observed values when a model is used to predict radiocesium uptake by wild cotton rats. An experiment is described in which laboratory-born cotton rats from wild parents were released into rat-proof enclosures on a site contaminated with 137 Cs. The rats fed on fescue growing in the enclosures. Samples of soil, fescue, rat carcasses and GI tracts from these plots were analyzed for 137 Cs. When assimilation efficiencies for radiocesium were calculated from the results of these measurements values lower than those previously assumed to apply to the uptake 134 137 Cs across the mammalian GI tract were obtained. It is suggested that these lower values may be due to the contribution of soil-bound 137 Cs to 137 Cs levels in plants and rat GI tracts since examination of GI tracts indicates that wild cotton rats ingest some soil, and soil-bound Cs cannot be readily extracted by gastric juice. (author)

  15. Hindcasting and Forecasting of Surface Flow Fields through Assimilating High Frequency Remotely Sensing Radar Data

    Directory of Open Access Journals (Sweden)

    Lei Ren

    2017-09-01

    Full Text Available In order to improve the forecasting ability of numerical models, a sequential data assimilation scheme, nudging, was applied to blend remotely sensing high-frequency (HF radar surface currents with results from a three-dimensional numerical, EFDC (Environmental Fluid Dynamics Code model. For the first time, this research presents the most appropriate nudging parameters, which were determined from sensitivity experiments. To examine the influence of data assimilation cycle lengths on forecasts and to extend forecasting improvements, the duration of data assimilation cycles was studied through assimilating linearly interpolated temporal radar data. Data assimilation nudging parameters have not been previously analyzed. Assimilation of HF radar measurements at each model computational timestep outperformed those assimilation models using longer data assimilation cycle lengths; root-mean-square error (RMSE values of both surface velocity components during a 12 h model forecasting period indicated that surface flow fields were significantly improved when implementing nudging assimilation at each model computational timestep. The Data Assimilation Skill Score (DASS technique was used to quantitatively evaluate forecast improvements. The averaged values of DASS over the data assimilation domain were 26% and 33% for east–west and north–south velocity components, respectively, over the half-day forecasting period. Correlation of Averaged Kinetic Energy (AKE was improved by more than 10% in the best data assimilation model. Time series of velocity components and surface flow fields were presented to illustrate the improvement resulting from data assimilation application over time.

  16. Development of the Ensemble Navy Aerosol Analysis Prediction System (ENAAPS and its application of the Data Assimilation Research Testbed (DART in support of aerosol forecasting

    Directory of Open Access Journals (Sweden)

    J. I. Rubin

    2016-03-01

    Full Text Available An ensemble-based forecast and data assimilation system has been developed for use in Navy aerosol forecasting. The system makes use of an ensemble of the Navy Aerosol Analysis Prediction System (ENAAPS at 1 × 1°, combined with an ensemble adjustment Kalman filter from NCAR's Data Assimilation Research Testbed (DART. The base ENAAPS-DART system discussed in this work utilizes the Navy Operational Global Analysis Prediction System (NOGAPS meteorological ensemble to drive offline NAAPS simulations coupled with the DART ensemble Kalman filter architecture to assimilate bias-corrected MODIS aerosol optical thickness (AOT retrievals. This work outlines the optimization of the 20-member ensemble system, including consideration of meteorology and source-perturbed ensemble members as well as covariance inflation. Additional tests with 80 meteorological and source members were also performed. An important finding of this work is that an adaptive covariance inflation method, which has not been previously tested for aerosol applications, was found to perform better than a temporally and spatially constant covariance inflation. Problems were identified with the constant inflation in regions with limited observational coverage. The second major finding of this work is that combined meteorology and aerosol source ensembles are superior to either in isolation and that both are necessary to produce a robust system with sufficient spread in the ensemble members as well as realistic correlation fields for spreading observational information. The inclusion of aerosol source ensembles improves correlation fields for large aerosol source regions, such as smoke and dust in Africa, by statistically separating freshly emitted from transported aerosol species. However, the source ensembles have limited efficacy during long-range transport. Conversely, the meteorological ensemble generates sufficient spread at the synoptic scale to enable observational impact

  17. Effects of Model Chemistry and Data Biases on Stratospheric Ozone Assimilation

    National Research Council Canada - National Science Library

    Coy, L; Allen, D. R; Eckermann, S. D; McCormack, J. P; Stajner, I; Hogan, T. F

    2007-01-01

    .... In this study, O-F statistics from the Global Ozone Assimilation Testing System (GOATS) are used to examine how ozone assimilation products and their associated O-F statistics depend on input data biases and ozone photochemistry parameterizations (OPP...

  18. Sensitivity of Satellite Altimetry Data Assimilation on a Weapon Acoustic Preset Using MODAS

    National Research Council Canada - National Science Library

    Chu, Peter; Mancini, Steven; Gottshall, Eric; Cwalina, David; Barron, Charlie N

    2007-01-01

    ...) is analyzed with SSP derived from the modular ocean data assimilation system (MODAS). The MODAS fields differ in that one uses altimeter data assimilated from three satellites while the other uses no altimeter data...

  19. Economic Assimilation and Outmigration of Immigrants in West-Germany

    NARCIS (Netherlands)

    Bellemare, C.

    2003-01-01

    By analyzing earnings of observed immigrants workers, the literature on the economic assimilation of immigrants has generally overlooked two potentially important selectivity issues.First, earnings of immigrant workers may di¿er substantially from those of non-workers.Second, earnings of immigrants

  20. Opinion Dynamics with Heterogeneous Interactions and Information Assimilation

    Science.gov (United States)

    Mir Tabatabaei, Seydeh Anahita

    2013-01-01

    In any modern society, individuals interact to form opinions on various topics, including economic, political, and social aspects. Opinions evolve as the result of the continuous exchange of information among individuals and of the assimilation of information distributed by media. The impact of individuals' opinions on each other forms a network,…

  1. Anterior Cingulate Cortex in Schema Assimilation and Expression

    Science.gov (United States)

    Wang, Szu-Han; Tse, Dorothy; Morris, Richard G. M.

    2012-01-01

    In humans and in animals, mental schemas can store information within an associative framework that enables rapid and efficient assimilation of new information. Using a hippocampal-dependent paired-associate task, we now report that the anterior cingulate cortex is part of a neocortical network of schema storage with NMDA receptor-mediated…

  2. Naming game with biased assimilation over adaptive networks

    Science.gov (United States)

    Fu, Guiyuan; Zhang, Weidong

    2018-01-01

    The dynamics of two-word naming game incorporating the influence of biased assimilation over adaptive network is investigated in this paper. Firstly an extended naming game with biased assimilation (NGBA) is proposed. The hearer in NGBA accepts the received information in a biased manner, where he may refuse to accept the conveyed word from the speaker with a predefined probability, if the conveyed word is different from his current memory. Secondly, the adaptive network is formulated by rewiring the links. Theoretical analysis is developed to show that the population in NGBA will eventually reach global consensus on either A or B. Numerical simulation results show that the larger strength of biased assimilation on both words, the slower convergence speed, while larger strength of biased assimilation on only one word can slightly accelerate the convergence; larger population size can make the rate of convergence slower to a large extent when it increases from a relatively small size, while such effect becomes minor when the population size is large; the behavior of adaptively reconnecting the existing links can greatly accelerate the rate of convergence especially on the sparse connected network.

  3. Volcanic Ash Data Assimilation System for Atmospheric Transport Model

    Science.gov (United States)

    Ishii, K.; Shimbori, T.; Sato, E.; Tokumoto, T.; Hayashi, Y.; Hashimoto, A.

    2017-12-01

    The Japan Meteorological Agency (JMA) has two operations for volcanic ash forecasts, which are Volcanic Ash Fall Forecast (VAFF) and Volcanic Ash Advisory (VAA). In these operations, the forecasts are calculated by atmospheric transport models including the advection process, the turbulent diffusion process, the gravitational fall process and the deposition process (wet/dry). The initial distribution of volcanic ash in the models is the most important but uncertain factor. In operations, the model of Suzuki (1983) with many empirical assumptions is adopted to the initial distribution. This adversely affects the reconstruction of actual eruption plumes.We are developing a volcanic ash data assimilation system using weather radars and meteorological satellite observation, in order to improve the initial distribution of the atmospheric transport models. Our data assimilation system is based on the three-dimensional variational data assimilation method (3D-Var). Analysis variables are ash concentration and size distribution parameters which are mutually independent. The radar observation is expected to provide three-dimensional parameters such as ash concentration and parameters of ash particle size distribution. On the other hand, the satellite observation is anticipated to provide two-dimensional parameters of ash clouds such as mass loading, top height and particle effective radius. In this study, we estimate the thickness of ash clouds using vertical wind shear of JMA numerical weather prediction, and apply for the volcanic ash data assimilation system.

  4. A reduced adjoint approach to variational data assimilation

    KAUST Repository

    Altaf, Muhammad; El Gharamti, Mohamad; Heemink, Arnold W.; Hoteit, Ibrahim

    2013-01-01

    The adjoint method has been used very often for variational data assimilation. The computational cost to run the adjoint model often exceeds several original model runs and the method needs significant programming efforts to implement the adjoint model code. The work proposed here is variational data assimilation based on proper orthogonal decomposition (POD) which avoids the implementation of the adjoint of the tangent linear approximation of the original nonlinear model. An ensemble of the forward model simulations is used to determine the approximation of the covariance matrix and only the dominant eigenvectors of this matrix are used to define a model subspace. The adjoint of the tangent linear model is replaced by the reduced adjoint based on this reduced space. Thus the adjoint model is run in reduced space with negligible computational cost. Once the gradient is obtained in reduced space it is projected back in full space and the minimization process is carried in full space. In the paper the reduced adjoint approach to variational data assimilation is introduced. The characteristics and performance of the method are illustrated with a number of data assimilation experiments in a ground water subsurface contaminant model. © 2012 Elsevier B.V.

  5. A reduced adjoint approach to variational data assimilation

    KAUST Repository

    Altaf, Muhammad

    2013-02-01

    The adjoint method has been used very often for variational data assimilation. The computational cost to run the adjoint model often exceeds several original model runs and the method needs significant programming efforts to implement the adjoint model code. The work proposed here is variational data assimilation based on proper orthogonal decomposition (POD) which avoids the implementation of the adjoint of the tangent linear approximation of the original nonlinear model. An ensemble of the forward model simulations is used to determine the approximation of the covariance matrix and only the dominant eigenvectors of this matrix are used to define a model subspace. The adjoint of the tangent linear model is replaced by the reduced adjoint based on this reduced space. Thus the adjoint model is run in reduced space with negligible computational cost. Once the gradient is obtained in reduced space it is projected back in full space and the minimization process is carried in full space. In the paper the reduced adjoint approach to variational data assimilation is introduced. The characteristics and performance of the method are illustrated with a number of data assimilation experiments in a ground water subsurface contaminant model. © 2012 Elsevier B.V.

  6. Probability Maps for the Visualization of Assimilation Ensemble Flow Data

    KAUST Repository

    Hollt, Thomas

    2015-05-25

    Ocean forecasts nowadays are created by running ensemble simulations in combination with data assimilation techniques. Most of these techniques resample the ensemble members after each assimilation cycle. This means that in a time series, after resampling, every member can follow up on any of the members before resampling. Tracking behavior over time, such as all possible paths of a particle in an ensemble vector field, becomes very difficult, as the number of combinations rises exponentially with the number of assimilation cycles. In general a single possible path is not of interest but only the probabilities that any point in space might be reached by a particle at some point in time. In this work we present an approach using probability-weighted piecewise particle trajectories to allow such a mapping interactively, instead of tracing quadrillions of individual particles. We achieve interactive rates by binning the domain and splitting up the tracing process into the individual assimilation cycles, so that particles that fall into the same bin after a cycle can be treated as a single particle with a larger probability as input for the next time step. As a result we loose the possibility to track individual particles, but can create probability maps for any desired seed at interactive rates.

  7. Music playlist generation by assimilating GMMs into SOMs

    NARCIS (Netherlands)

    Balkema, Wietse; van der Heijden, Ferdinand

    A method for music playlist generation, using assimilated Gaussian mixture models (GMMs) in self organizing maps (SOMs) is presented. Traditionally, the neurons in a SOM are represented by vectors, but in this paper we propose to use GMMs instead. To this end, we introduce a method to adapt a GMM

  8. Growth, assimilate partitioning and grain yield response of soybean ...

    African Journals Online (AJOL)

    This investigation tested variation in the growth components, assimilate partitioning and grain yield of soybean (Glycine max L. Merrrill) varieties established in CO2 enriched atmosphere when inoculated with mixtures of Arbuscular mycorrhizal fungi (AMF) species in the humid rainforest of Nigeria. A pot and a field ...

  9. Homophily and assimilation among sportactive adolescent substance users

    NARCIS (Netherlands)

    Pearson, M; Steglich, Ch.; Snijders, T.A.B.

    2006-01-01

    We analyse the co-evolution of social networks and substance use behaviour of adolescents and address the problem of separating the effects of homophily and assimilation. Adolescents who prefer friends with the same substance-use behaviour exhibit the homophily principle. Adolescents who adapt their

  10. Modelling Effluent Assimilative Capacity of Ikpoba River, Benin City ...

    African Journals Online (AJOL)

    The sheer display of reprehensible propensity on the part of public hospitals, abattoirs, breweries and city dwellers at large to discharge untreated waste, debris, scum and, in particular, municipal and industrial effluents into Ikpoba River has morphed into a situation whereby the assimilative capacity of the river has reached ...

  11. Satellite Data Assimilation within KIAPS-LETKF system

    Science.gov (United States)

    Jo, Y.; Lee, S., Sr.; Cho, K.

    2016-12-01

    Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing an ensemble data assimilation system using four-dimensional local ensemble transform kalman filter (LETKF; Hunt et al., 2007) within KIAPS Integrated Model (KIM), referred to as "KIAPS-LETKF". KIAPS-LETKF system was successfully evaluated with various Observing System Simulation Experiments (OSSEs) with NCAR Community Atmospheric Model - Spectral Element (Kang et al., 2013), which has fully unstructured quadrilateral meshes based on the cubed-sphere grid as the same grid system of KIM. Recently, assimilation of real observations has been conducted within the KIAPS-LETKF system with four-dimensional covariance functions over the 6-hr assimilation window. Then, conventional (e.g., sonde, aircraft, and surface) and satellite (e.g., AMSU-A, IASI, GPS-RO, and AMV) observations have been provided by the KIAPS Package for Observation Processing (KPOP). Wind speed prediction was found most beneficial due to ingestion of AMV and for the temperature prediction the improvement in assimilation is mostly due to ingestion of AMSU-A and IASI. However, some degradation in the simulation of the GPS-RO is presented in the upper stratosphere, even though GPS-RO leads positive impacts on the analysis and forecasts. We plan to test the bias correction method and several vertical localization strategies for radiance observations to improve analysis and forecast impacts.

  12. Abscisic acid and assimilate partitioning during seed development

    NARCIS (Netherlands)

    Bruijn, de S.M.

    1993-01-01

    This thesis describes the influence of abscisic acid (ABA) on the transport of assimilates to seeds and the deposition of reserves in seeds. It is well-known from literature that ABA accumulates in seeds during development, and that ABA concentrations in seeds correlate rather well with

  13. A Generic Software Framework for Data Assimilation and Model Calibration

    NARCIS (Netherlands)

    Van Velzen, N.

    2010-01-01

    The accuracy of dynamic simulation models can be increased by using observations in conjunction with a data assimilation or model calibration algorithm. However, implementing such algorithms usually increases the complexity of the model software significantly. By using concepts from object oriented

  14. Educational Attainments of Immigrant Offspring: Success or Segmented Assimilation?

    Science.gov (United States)

    Boyd, Monica

    2002-01-01

    Examined the educational attainments of adult offspring of immigrants age 20-64 years, analyzing data from Canada's 1996 Survey of Labour and Income Dynamics. Contrary to second generation decline and segmented underclass assimilation found in the United States, Canadian adult visible-minority immigrant offspring did not have lower educational…

  15. Global assimilation of X Project Loon stratospheric balloon observations

    Science.gov (United States)

    Coy, L.; Schoeberl, M. R.; Pawson, S.; Candido, S.; Carver, R. W.

    2017-12-01

    Project Loon has an overall goal of providing worldwide internet coverage using a network of long-duration super-pressure balloons. Beginning in 2013, Loon has launched over 1600 balloons from multiple tropical and middle latitude locations. These GPS tracked balloon trajectories provide lower stratospheric wind information over the oceans and remote land areas where traditional radiosonde soundings are sparse, thus providing unique coverage of lower stratospheric winds. To fully investigate these Loon winds we: 1) compare the Loon winds to winds produced by a global data assimilation system (DAS: NASA GEOS) and 2) assimilate the Loon winds into the same comprehensive DAS. Results show that in middle latitudes the Loon winds and DAS winds agree well and assimilating the Loon winds have only a small impact on short-term forecasting of the Loon winds, however, in the tropics the loon winds and DAS winds often disagree substantially (8 m/s or more in magnitude) and in these cases assimilating the loon winds significantly improves the forecast of the loon winds. By highlighting cases where the Loon and DAS winds differ, these results can lead to improved understanding of stratospheric winds, especially in the tropics.

  16. Lidar data assimilation for improved analyses of volcanic aerosol events

    Science.gov (United States)

    Lange, Anne Caroline; Elbern, Hendrik

    2014-05-01

    Observations of hazardous events with release of aerosols are hardly analyzable by today's data assimilation algorithms, without producing an attenuating bias. Skillful forecasts of unexpected aerosol events are essential for human health and to prevent an exposure of infirm persons and aircraft with possibly catastrophic outcome. Typical cases include mineral dust outbreaks, mostly from large desert regions, wild fires, and sea salt uplifts, while the focus aims for volcanic eruptions. In general, numerical chemistry and aerosol transport models cannot simulate such events without manual adjustments. The concept of data assimilation is able to correct the analysis, as long it is operationally implemented in the model system. Though, the tangent-linear approximation, which describes a substantial precondition for today's cutting edge data assimilation algorithms, is not valid during unexpected aerosol events. As part of the European COPERNICUS (earth observation) project MACC II and the national ESKP (Earth System Knowledge Platform) initiative, we developed a module that enables the assimilation of aerosol lidar observations, even during unforeseeable incidences of extreme emissions of particulate matter. Thereby, the influence of the background information has to be reduced adequately. Advanced lidar instruments comprise on the one hand the aspect of radiative transfer within the atmosphere and on the other hand they can deliver a detailed quantification of the detected aerosols. For the assimilation of maximal exploited lidar data, an appropriate lidar observation operator is constructed, compatible with the EURAD-IM (European Air Pollution and Dispersion - Inverse Model) system. The observation operator is able to map the modeled chemical and physical state on lidar attenuated backscatter, transmission, aerosol optical depth, as well as on the extinction and backscatter coefficients. Further, it has the ability to process the observed discrepancies with lidar

  17. Data Assimilation to Extract Soil Moisture Information from SMAP Observations

    Directory of Open Access Journals (Sweden)

    Jana Kolassa

    2017-11-01

    Full Text Available This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP observations. Neural network (NN and physically-based SMAP soil moisture retrievals were assimilated into the National Aeronautics and Space Administration (NASA Catchment model over the contiguous United States for April 2015 to March 2017. By construction, the NN retrievals are consistent with the global climatology of the Catchment model soil moisture. Assimilating the NN retrievals without further bias correction improved the surface and root zone correlations against in situ measurements from 14 SMAP core validation sites (CVS by 0.12 and 0.16, respectively, over the model-only skill, and reduced the surface and root zone unbiased root-mean-square error (ubRMSE by 0.005 m 3 m − 3 and 0.001 m 3 m − 3 , respectively. The assimilation reduced the average absolute surface bias against the CVS measurements by 0.009 m 3 m − 3 , but increased the root zone bias by 0.014 m 3 m − 3 . Assimilating the NN retrievals after a localized bias correction yielded slightly lower surface correlation and ubRMSE improvements, but generally the skill differences were small. The assimilation of the physically-based SMAP Level-2 passive soil moisture retrievals using a global bias correction yielded similar skill improvements, as did the direct assimilation of locally bias-corrected SMAP brightness temperatures within the SMAP Level-4 soil moisture algorithm. The results show that global bias correction methods may be able to extract more independent information from SMAP observations compared to local bias correction methods, but without accurate quality control and observation error characterization they are also more vulnerable to adverse effects from retrieval errors related to uncertainties in the retrieval inputs and algorithm. Furthermore, the results show that using global bias correction approaches without a

  18. Improving Forecast Skill by Assimilation of AIRS Temperature Soundings

    Science.gov (United States)

    Susskind, Joel; Reale, Oreste

    2010-01-01

    AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The AIRS Version 5 retrieval algorithm, is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates delta T(p) for retrieved quantities and the use of these error estimates for Quality Control. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 deg. latitude X 0.67 deg longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates delta (p) were used as the uncertainty for each measurement in the data assimilation process. We compared forecasts analyses generated from the analyses done by assimilation of AIRS temperature profiles with three different sets of thresholds; Standard, Medium, and Tight. Assimilation of Quality Controlled AIRS temperature profiles significantly improve 5-7 day forecast skill compared to that obtained without the benefit of AIRS data in all of the cases studied. In addition, assimilation of Quality Controlled AIRS temperature soundings performs better than assimilation of AIRS observed radiances. Based on the experiments shown, Tight Quality Control of AIRS temperature profile performs best

  19. Quantifying the source-sink balance and carbohydrate content in three tomato cultivars

    NARCIS (Netherlands)

    Li, T.; Heuvelink, E.; Marcelis, L.F.M.

    2015-01-01

    Supplementary lighting is frequently applied in the winter season for crop production in greenhouses. The effect of supplementary lighting on plant growth depends on the balance between assimilate production in source leaves and the overall capacity of the plants to use assimilates. This study aims

  20. Assimilation of diazotrophic nitrogen into pelagic food webs.

    Directory of Open Access Journals (Sweden)

    Ryan J Woodland

    Full Text Available The fate of diazotrophic nitrogen (N(D fixed by planktonic cyanobacteria in pelagic food webs remains unresolved, particularly for toxic cyanophytes that are selectively avoided by most herbivorous zooplankton. Current theory suggests that N(D fixed during cyanobacterial blooms can enter planktonic food webs contemporaneously with peak bloom biomass via direct grazing of zooplankton on cyanobacteria or via the uptake of bioavailable N(D (exuded from viable cyanobacterial cells by palatable phytoplankton or microbial consortia. Alternatively, N(D can enter planktonic food webs post-bloom following the remineralization of bloom detritus. Although the relative contribution of these processes to planktonic nutrient cycles is unknown, we hypothesized that assimilation of bioavailable N(D (e.g., nitrate, ammonium by palatable phytoplankton and subsequent grazing by zooplankton (either during or after the cyanobacterial bloom would be the primary pathway by which N(D was incorporated into the planktonic food web. Instead, in situ stable isotope measurements and grazing experiments clearly documented that the assimilation of N(D by zooplankton outpaced assimilation by palatable phytoplankton during a bloom of toxic Nodularia spumigena Mertens. We identified two distinct temporal phases in the trophic transfer of N(D from N. spumigena to the plankton community. The first phase was a highly dynamic transfer of N(D to zooplankton with rates that covaried with bloom biomass while bypassing other phytoplankton taxa; a trophic transfer that we infer was routed through bloom-associated bacteria. The second phase was a slowly accelerating assimilation of the dissolved-N(D pool by phytoplankton that was decoupled from contemporaneous variability in N. spumigena concentrations. These findings provide empirical evidence that N(D can be assimilated and transferred rapidly throughout natural plankton communities and yield insights into the specific processes

  1. Assimilation of SMOS Retrievals in the Land Information System

    Science.gov (United States)

    Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

    2016-01-01

    The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm(sub 3 cm(sub -3). These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve.

  2. Assimilation of diazotrophic nitrogen into pelagic food webs.

    Science.gov (United States)

    Woodland, Ryan J; Holland, Daryl P; Beardall, John; Smith, Jonathan; Scicluna, Todd; Cook, Perran L M

    2013-01-01

    The fate of diazotrophic nitrogen (N(D)) fixed by planktonic cyanobacteria in pelagic food webs remains unresolved, particularly for toxic cyanophytes that are selectively avoided by most herbivorous zooplankton. Current theory suggests that N(D) fixed during cyanobacterial blooms can enter planktonic food webs contemporaneously with peak bloom biomass via direct grazing of zooplankton on cyanobacteria or via the uptake of bioavailable N(D) (exuded from viable cyanobacterial cells) by palatable phytoplankton or microbial consortia. Alternatively, N(D) can enter planktonic food webs post-bloom following the remineralization of bloom detritus. Although the relative contribution of these processes to planktonic nutrient cycles is unknown, we hypothesized that assimilation of bioavailable N(D) (e.g., nitrate, ammonium) by palatable phytoplankton and subsequent grazing by zooplankton (either during or after the cyanobacterial bloom) would be the primary pathway by which N(D) was incorporated into the planktonic food web. Instead, in situ stable isotope measurements and grazing experiments clearly documented that the assimilation of N(D) by zooplankton outpaced assimilation by palatable phytoplankton during a bloom of toxic Nodularia spumigena Mertens. We identified two distinct temporal phases in the trophic transfer of N(D) from N. spumigena to the plankton community. The first phase was a highly dynamic transfer of N(D) to zooplankton with rates that covaried with bloom biomass while bypassing other phytoplankton taxa; a trophic transfer that we infer was routed through bloom-associated bacteria. The second phase was a slowly accelerating assimilation of the dissolved-N(D) pool by phytoplankton that was decoupled from contemporaneous variability in N. spumigena concentrations. These findings provide empirical evidence that N(D) can be assimilated and transferred rapidly throughout natural plankton communities and yield insights into the specific processes underlying

  3. A virtual reality catchment for data assimilation experiments

    Science.gov (United States)

    Schalge, Bernd; Rihani, Jehan; Haese, Barbara; Baroni, Gabriele; Erdal, Daniel; Neuweiler, Insa; Hendricks-Franssen, Harrie-Jan; Geppert, Gernot; Ament, Felix; Kollet, Stefan; Cirpka, Olaf; Saavedra, Pablo; Han, Xujun; Attinger, Sabine; Kunstmann, Harald; Vereecken, Harry; Simmer, Clemens

    2016-04-01

    Current data assimilation (DA) systems often lack the possibility to assimilate measurements across compartments to accurately estimate states and fluxes in subsurface-land surface-atmosphere systems (SLAS). In order to develop a new DA framework that is able to realize this cross-compartmental assimilation a comprehensive testing environment is needed. Therefore a virtual reality (VR) catchment is constructed with the Terrestrial System Modeling Platform (TerrSysMP). This catchment mimics the Neckar catchment in Germany. TerrSysMP employs the atmospheric model COSMO, the land surface model CLM and the hydrological model ParFlow coupled with the external coupler OASIS. We will show statistical tests to prove the plausibility of the VR. The VR is running in a fully-coupled mode (subsurface - land surface - atmosphere) which includes the interactions of subsurface dynamics with the atmosphere, such as the effects of soil moisture, which can influence near-surface temperatures, convection patterns or the surface heat fluxes. A reference high resolution run serves as the "truth" from which virtual observations are extracted with observation operators like virtual rain gauges, synoptic stations and satellite observations (amongst others). This effectively solves the otherwise often encountered data scarcity issues with respect to DA. Furthermore an ensemble of model runs at a reduced resolution is performed. This ensemble serves also for open loop runs to be compared with data assimilation experiments. The model runs with this ensemble served to identify sets of parameters that are especially sensitive to changes and have the largest impact on the system. These parameters were the focus of subsequent ensemble simulations and DA experiments. We will show to what extend the VR states can be re-constructed using data assimilation methods with only a limited number of virtual observations available.

  4. Development of KIAPS Observation Processing Package for Data Assimilation System

    Science.gov (United States)

    Kang, Jeon-Ho; Chun, Hyoung-Wook; Lee, Sihye; Han, Hyun-Jun; Ha, Su-Jin

    2015-04-01

    The Korea Institute of Atmospheric Prediction Systems (KIAPS) was founded in 2011 by the Korea Meteorological Administration (KMA) to develop Korea's own global Numerical Weather Prediction (NWP) system as nine year (2011-2019) project. Data assimilation team at KIAPS has been developing the observation processing system (KIAPS Package for Observation Processing: KPOP) to provide optimal observations to the data assimilation system for the KIAPS Global Model (KIAPS Integrated Model - Spectral Element method based on HOMME: KIM-SH). Currently, the KPOP is capable of processing the satellite radiance data (AMSU-A, IASI), GPS Radio Occultation (GPS-RO), AIRCRAFT (AMDAR, AIREP, and etc…), and synoptic observation (SONDE and SURFACE). KPOP adopted Radiative Transfer for TOVS version 10 (RTTOV_v10) to get brightness temperature (TB) for each channel at top of the atmosphere (TOA), and Radio Occultation Processing Package (ROPP) 1-dimensional forward module to get bending angle (BA) at each tangent point. The observation data are obtained from the KMA which has been composited with BUFR format to be converted with ODB that are used for operational data assimilation and monitoring at the KMA. The Unified Model (UM), Community Atmosphere - Spectral Element (CAM-SE) and KIM-SH model outputs are used for the bias correction (BC) and quality control (QC) of the observations, respectively. KPOP provides radiance and RO data for Local Ensemble Transform Kalman Filter (LETKF) and also provides SONDE, SURFACE and AIRCRAFT data for Three-Dimensional Variational Assimilation (3DVAR). We are expecting all of the observation type which processed in KPOP could be combined with both of the data assimilation method as soon as possible. The preliminary results from each observation type will be introduced with the current development status of the KPOP.

  5. ASSIMILATION OF COARSE-SCALEDATAUSINGTHE ENSEMBLE KALMAN FILTER

    KAUST Repository

    Efendiev, Yalchin

    2011-01-01

    Reservoir data is usually scale dependent and exhibits multiscale features. In this paper we use the ensemble Kalman filter (EnKF) to integrate data at different spatial scales for estimating reservoir fine-scale characteristics. Relationships between the various scales is modeled via upscaling techniques. We propose two versions of the EnKF to assimilate the multiscale data, (i) where all the data are assimilated together and (ii) the data are assimilated sequentially in batches. Ensemble members obtained after assimilating one set of data are used as a prior to assimilate the next set of data. Both of these versions are easily implementable with any other upscaling which links the fine to the coarse scales. The numerical results with different methods are presented in a twin experiment setup using a two-dimensional, two-phase (oil and water) flow model. Results are shown with coarse-scale permeability and coarse-scale saturation data. They indicate that additional data provides better fine-scale estimates and fractional flow predictions. We observed that the two versions of the EnKF differed in their estimates when coarse-scale permeability is provided, whereas their results are similar when coarse-scale saturation is used. This behavior is thought to be due to the nonlinearity of the upscaling operator in the case of the former data. We also tested our procedures with various precisions of the coarse-scale data to account for the inexact relationship between the fine and coarse scale data. As expected, the results show that higher precision in the coarse-scale data yielded improved estimates. With better coarse-scale modeling and inversion techniques as more data at multiple coarse scales is made available, the proposed modification to the EnKF could be relevant in future studies.

  6. CO2 enrichment inhibits shoot nitrate assimilation in C3 but not C4 plants and slows growth under nitrate in C3 plants.

    Science.gov (United States)

    Bloom, Arnold J; Asensio, Jose Salvador Rubaio; Randall, Lesley; Rachmilevitch, Shimon; Cousins, Asaph B; Carlisle, Eli A

    2012-02-01

    The CO2 concentration in Earth's atmosphere may double during this century. Plant responses to such an increase depend strongly on their nitrogen status, but the reasons have been uncertain. Here, we assessed shoot nitrate assimilation into amino acids via the shift in shoot CO2 and O2 fluxes when plants received nitrate instead of ammonium as a nitrogen source (deltaAQ). Shoot nitrate assimilation became negligible with increasing CO2 in a taxonomically diverse group of eight C3 plant species, was relatively insensitive to CO2 in three C4 species, and showed an intermediate sensitivity in two C3-C4 intermediate species. We then examined the influence of CO2 level and ammonium vs. nitrate nutrition on growth, assessed in terms of changes in fresh mass, of several C3 species and a Crassulacean acid metabolism (CAM) species. Elevated CO2 (720 micromol CO2/mol of all gases present) stimulated growth or had no effect in the five C3 species tested when they received ammonium as a nitrogen source but inhibited growth or had no effect if they received nitrate. Under nitrate, two C3 species grew faster at sub-ambient (approximately 310 micromol/mol) than elevated CO2. A CAM species grew faster at ambient than elevated or sub-ambient CO2 under either ammonium or nitrate nutrition. This study establishes that CO2 enrichment inhibits shoot nitrate assimilation in a wide variety of C3 plants and that this phenomenon can have a profound effect on their growth. This indicates that shoot nitrate assimilation provides an important contribution to the nitrate assimilation of an entire C3 plant. Thus, rising CO2 and its effects on shoot nitrate assimilation may influence the distribution of C3 plant species.

  7. A problem-solving environment for data assimilation in air quality modelling

    NARCIS (Netherlands)

    Velzen, N. van; Segers, A.J.

    2010-01-01

    A generic toolbox for data assimilation called COSTA (COmmon Set of Tools for the Assimilation of data) makes it possible to simplify the application of data assimilation to models and to try out various methods for a particular model. Concepts of object oriented programming are used to define

  8. Improving short-term air quality predictions over the U.S. using chemical data assimilation

    Science.gov (United States)

    Kumar, R.; Delle Monache, L.; Alessandrini, S.; Saide, P.; Lin, H. C.; Liu, Z.; Pfister, G.; Edwards, D. P.; Baker, B.; Tang, Y.; Lee, P.; Djalalova, I.; Wilczak, J. M.

    2017-12-01

    State and local air quality forecasters across the United States use air quality forecasts from the National Air Quality Forecasting Capability (NAQFC) at the National Oceanic and Atmospheric Administration (NOAA) as one of the key tools to protect the public from adverse air pollution related health effects by dispensing timely information about air pollution episodes. This project funded by the National Aeronautics and Space Administration (NASA) aims to enhance the decision-making process by improving the accuracy of NAQFC short-term predictions of ground-level particulate matter of less than 2.5 µm in diameter (PM2.5) by exploiting NASA Earth Science Data with chemical data assimilation. The NAQFC is based on the Community Multiscale Air Quality (CMAQ) model. To improve the initialization of PM2.5 in CMAQ, we developed a new capability in the community Gridpoint Statistical Interpolation (GSI) system to assimilate Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals in CMAQ. Specifically, we developed new capabilities within GSI to read/write CMAQ data, a forward operator that calculates AOD at 550 nm from CMAQ aerosol chemical composition and an adjoint of the forward operator that translates the changes in AOD to aerosol chemical composition. A generalized background error covariance program called "GEN_BE" has been extended to calculate background error covariance using CMAQ output. The background error variances are generated using a combination of both emissions and meteorological perturbations to better capture sources of uncertainties in PM2.5 simulations. The newly developed CMAQ-GSI system is used to perform daily 24-h PM2.5 forecasts with and without data assimilation from 15 July to 14 August 2014, and the resulting forecasts are compared against AirNOW PM2.5 measurements at 550 stations across the U. S. We find that the assimilation of MODIS AOD retrievals improves initialization of the CMAQ model

  9. Evaluation of Marine Microalga Diacronema vlkianum Biomass Fatty Acid Assimilation in Wistar Rats

    Directory of Open Access Journals (Sweden)

    Cristina de Mello-Sampayo

    2017-07-01

    Full Text Available Diacronema vlkianum is a marine microalgae for which supposed health promoting effects have been claimed based on its phytochemical composition. The potential use of its biomass as health ingredient, including detox-shakes, and the lack of bioavailability studies were the main concerns. In order to evaluate the microalgae-biomass assimilation and its health-benefits, single-dose (CD1-mice studies were followed by 66-days repeated-dose study in Wistar rats with the highest tested single-dose of microalgae equivalent to 101 mg/kg eicosapentaenoic acid + docosahexaenoic acid (EPA+DHA. Microalgae-supplementation modulated EPA and docosapentaenoic acid enrichment at arachidonic acid content expenditure in erythrocytes and liver, while increasing EPA content of heart and adipose tissues of rats. Those fatty acid (FA changes confirmed the D. vlkianum-biomass FA assimilation. The principal component analyses discriminated brain from other tissues, which formed two other groups (erythrocytes, liver, and heart separated from kidney and adipose tissues, pointing to a distinct signature of FA deposition for the brain and for the other organs. The improved serum lipid profile, omega-3 index and erythrocyte plasticity support the cardiovascular benefits of D. vlkianum. These results bolster the potential of D. vlkianum-biomass to become a “heart-healthy” food supplement providing a safe and renewable source of bioavailable omega-3 FA.

  10. Physically consistent data assimilation method based on feedback control for patient-specific blood flow analysis.

    Science.gov (United States)

    Ii, Satoshi; Adib, Mohd Azrul Hisham Mohd; Watanabe, Yoshiyuki; Wada, Shigeo

    2018-01-01

    This paper presents a novel data assimilation method for patient-specific blood flow analysis based on feedback control theory called the physically consistent feedback control-based data assimilation (PFC-DA) method. In the PFC-DA method, the signal, which is the residual error term of the velocity when comparing the numerical and reference measurement data, is cast as a source term in a Poisson equation for the scalar potential field that induces flow in a closed system. The pressure values at the inlet and outlet boundaries are recursively calculated by this scalar potential field. Hence, the flow field is physically consistent because it is driven by the calculated inlet and outlet pressures, without any artificial body forces. As compared with existing variational approaches, although this PFC-DA method does not guarantee the optimal solution, only one additional Poisson equation for the scalar potential field is required, providing a remarkable improvement for such a small additional computational cost at every iteration. Through numerical examples for 2D and 3D exact flow fields, with both noise-free and noisy reference data as well as a blood flow analysis on a cerebral aneurysm using actual patient data, the robustness and accuracy of this approach is shown. Moreover, the feasibility of a patient-specific practical blood flow analysis is demonstrated. Copyright © 2017 John Wiley & Sons, Ltd.

  11. Use of 13N in studies of fixation of dinitrogen and assimilation of ammonium by cyanobacteria

    International Nuclear Information System (INIS)

    Meeks, J.C.; Wolk, C.P.; Thomas, J.; Austin, S.M.; Galonsky, A.; Michigan State Univ., East Lansing

    1978-01-01

    13 N (tsub(1/2)=10min) has been used to identify the initial products of assimilation of N 2 and NH 4 + by intact filaments of a number of cyanobacteria and by heterocysts isolated from Anabaena cylindrica. Ammonium, the amide nitrogen of glutamine, and the α-amino nitrogen of glutamate, in that order, were the first observed products of fixation of [ 13 N]N 2 . Amide-labelled glutamine was the initial product of metabolism of 13 NH 4 + by A. cylindrica grown with either NH 4 + or N 2 as the nitrogen source. Glutamate was the second major product of 13 NH 4 + assimilation. Isolated heterocysts form [ 13 N]glutamine but not [ 13 N]glutamate from [ 13 N]N 2 or 13 NH 4 + . Formation of [ 13 N]glutamine from [ 13 N]N 2 was inhibited by acetylene, indicating metabolic coupling of the activity of glutamine synthetase to that of nitrogenase in these cells. A diffusible substance produced by heterocysts inhibits nearby cells of the same filament from differentiating into heterocysts. Glutamine (or a derivative of glutamine) may be involved in inhibiting differentiation of vegetative cells. (author)

  12. Transcriptomic analyses of nitrogen assimilation processes in a Chinese strain of Aureococcus anophagefferens

    Directory of Open Access Journals (Sweden)

    Li-Na Chen

    2015-09-01

    Full Text Available Aureococcus anophagefferens is a harmful alga that dominates plankton communities during brown tides in North America, Africa, and Asia. In order to figure out the processes of nitrogen assimilation in a Chinese strain of A. anophagefferens, RNA-seq technology was used to examine transcriptomic differences in A. anophagefferens that was grown on urea, nitrate, or a mixture of urea and nitrate, and that was under N-replete, limited and recovery conditions. We noted that transcripts upregulated by nitrate and N-limitation included those encoding proteins involved in amino acid, nucleotide and aminosugar transport, degradation of amides and cyanates, and nitrate assimilation pathway. The data suggest that A. anophagefferens possesses an ability to utilize a variety of dissolved organic nitrogen. Moreover, transcripts for synthesis of proteins, glutamate-derived amino acids, spermines and sterols were upregulated by urea. Transcripts encoding key enzymes that are involved in the ornithine–urea cycle (OUC and TCA cycle were differentially regulated by urea and nitrogen concentration, which suggests that the OUC may be linked to the TCA cycle and involved in reallocation of intracellular carbon and nitrogen. These genes regulated by urea may be crucial for the rapid proliferation of A. anophagefferens when urea is provided as the N source. Here, we provide the experimental procedures and analytical processes in detail. The data set is deposited in GEO with the accession number GSE60576.

  13. Sequential assimilation of volcanic monitoring data to quantify eruption potential: Application to Kerinci volcano

    Science.gov (United States)

    Zhan, Yan; Gregg, Patricia M.; Chaussard, Estelle; Aoki, Yosuke

    2017-12-01

    Quantifying the eruption potential of a restless volcano requires the ability to model parameters such as overpressure and calculate the host rock stress state as the system evolves. A critical challenge is developing a model-data fusion framework to take advantage of observational data and provide updates of the volcanic system through time. The Ensemble Kalman Filter (EnKF) uses a Monte Carlo approach to assimilate volcanic monitoring data and update models of volcanic unrest, providing time-varying estimates of overpressure and stress. Although the EnKF has been proven effective to forecast volcanic deformation using synthetic InSAR and GPS data, until now, it has not been applied to assimilate data from an active volcanic system. In this investigation, the EnKF is used to provide a “hindcast” of the 2009 explosive eruption of Kerinci volcano, Indonesia. A two-sources analytical model is used to simulate the surface deformation of Kerinci volcano observed by InSAR time-series data and to predict the system evolution. A deep, deflating dike-like source reproduces the subsiding signal on the flanks of the volcano, and a shallow spherical McTigue source reproduces the central uplift. EnKF predicted parameters are used in finite element models to calculate the host-rock stress state prior to the 2009 eruption. Mohr-Coulomb failure models reveal that the shallow magma reservoir is trending towards tensile failure prior to 2009, which may be the catalyst for the 2009 eruption. Our results illustrate that the EnKF shows significant promise for future applications to forecasting the eruption potential of restless volcanoes and hind-cast the triggering mechanisms of observed eruptions.

  14. Sequential Assimilation of Volcanic Monitoring Data to Quantify Eruption Potential: Application to Kerinci Volcano, Sumatra

    Directory of Open Access Journals (Sweden)

    Yan Zhan

    2017-12-01

    Full Text Available Quantifying the eruption potential of a restless volcano requires the ability to model parameters such as overpressure and calculate the host rock stress state as the system evolves. A critical challenge is developing a model-data fusion framework to take advantage of observational data and provide updates of the volcanic system through time. The Ensemble Kalman Filter (EnKF uses a Monte Carlo approach to assimilate volcanic monitoring data and update models of volcanic unrest, providing time-varying estimates of overpressure and stress. Although the EnKF has been proven effective to forecast volcanic deformation using synthetic InSAR and GPS data, until now, it has not been applied to assimilate data from an active volcanic system. In this investigation, the EnKF is used to provide a “hindcast” of the 2009 explosive eruption of Kerinci volcano, Indonesia. A two-sources analytical model is used to simulate the surface deformation of Kerinci volcano observed by InSAR time-series data and to predict the system evolution. A deep, deflating dike-like source reproduces the subsiding signal on the flanks of the volcano, and a shallow spherical McTigue source reproduces the central uplift. EnKF predicted parameters are used in finite element models to calculate the host-rock stress state prior to the 2009 eruption. Mohr-Coulomb failure models reveal that the host rock around the shallow magma reservoir is trending toward tensile failure prior to 2009, which may be the catalyst for the 2009 eruption. Our results illustrate that the EnKF shows significant promise for future applications to forecasting the eruption potential of restless volcanoes and hind-cast the triggering mechanisms of observed eruptions.

  15. Down-scaling wind energy resource from mesoscale to local scale by nesting and data assimilation with a CFD model

    International Nuclear Information System (INIS)

    Duraisamy Jothiprakasam, Venkatesh

    2014-01-01

    The development of wind energy generation requires precise and well-established methods for wind resource assessment, which is the initial step in every wind farm project. During the last two decades linear flow models were widely used in the wind industry for wind resource assessment and micro-siting. But the linear models inaccuracies in predicting the wind speeds in very complex terrain are well known and led to use of CFD, capable of modeling the complex flow in details around specific geographic features. Mesoscale models (NWP) are able to predict the wind regime at resolutions of several kilometers, but are not well suited to resolve the wind speed and turbulence induced by the topography features on the scale of a few hundred meters. CFD has proven successful in capturing flow details at smaller scales, but needs an accurate specification of the inlet conditions. Thus coupling NWP and CFD models is a better modeling approach for wind energy applications. A one-year field measurement campaign carried out in a complex terrain in southern France during 2007-2008 provides a well-documented data set both for input and validation data. The proposed new methodology aims to address two problems: the high spatial variation of the topography on the domain lateral boundaries, and the prediction errors of the mesoscale model. It is applied in this work using the open source CFD code Code-Saturne, coupled with the mesoscale forecast model of Meteo-France (ALADIN). The improvement is obtained by combining the mesoscale data as inlet condition and field measurement data assimilation into the CFD model. Newtonian relaxation (nudging) data assimilation technique is used to incorporate the measurement data into the CFD simulations. The methodology to reconstruct long term averages uses a clustering process to group the similar meteorological conditions and to reduce the number of CFD simulations needed to reproduce 1 year of atmospheric flow over the site. The assimilation

  16. Assimilation of NAD(+) precursors in Candida glabrata.

    Science.gov (United States)

    Ma, Biao; Pan, Shih-Jung; Zupancic, Margaret L; Cormack, Brendan P

    2007-10-01

    The yeast pathogen Candida glabrata is a nicotinamide adenine dinucleotide (NAD(+)) auxotroph and its growth depends on the environmental supply of vitamin precursors of NAD(+). C. glabrata salvage pathways defined in this article allow NAD(+) to be synthesized from three compounds - nicotinic acid (NA), nicotinamide (NAM) and nicotinamide riboside (NR). NA is salvaged through a functional Preiss-Handler pathway. NAM is first converted to NA by nicotinamidase and then salvaged by the Preiss-Handler pathway. Salvage of NR in C. glabrata occurs via two routes. The first, in which NR is phosphorylated by the NR kinase Nrk1, is independent of the Preiss-Handler pathway. The second is a novel pathway in which NR is degraded by the nucleosidases Pnp1 and Urh1, with a minor role for Meu1, and ultimately converted to NAD(+) via the nicotinamidase Pnc1 and the Preiss-Handler pathway. Using C. glabrata mutants whose growth depends exclusively on the external NA or NR supply, we also show that C. glabrata utilizes NR and to a lesser extent NA as NAD(+) sources during disseminated infection.

  17. Estimation of Key Parameters of the Coupled Energy and Water Model by Assimilating Land Surface Data

    Science.gov (United States)

    Abdolghafoorian, A.; Farhadi, L.

    2017-12-01

    Accurate estimation of land surface heat and moisture fluxes, as well as root zone soil moisture, is crucial in various hydrological, meteorological, and agricultural applications. Field measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state observations that are widely available from remote sensing across a range of scale. In this work, we applies the variational data assimilation approach to estimate land surface fluxes and soil moisture profile from the implicit information contained Land Surface Temperature (LST) and Soil Moisture (SM) (hereafter the VDA model). The VDA model is focused on the estimation of three key parameters: 1- neutral bulk heat transfer coefficient (CHN), 2- evaporative fraction from soil and canopy (EF), and 3- saturated hydraulic conductivity (Ksat). CHN and EF regulate the partitioning of available energy between sensible and latent heat fluxes. Ksat is one of the main parameters used in determining infiltration, runoff, groundwater recharge, and in simulating hydrological processes. In this study, a system of coupled parsimonious energy and water model will constrain the estimation of three unknown parameters in the VDA model. The profile of SM (LST) at multiple depths is estimated using moisture diffusion (heat diffusion) equation. In this study, the uncertainties of retrieved unknown parameters and fluxes are estimated from the inverse of Hesian matrix of cost function which is computed using the Lagrangian methodology. Analysis of uncertainty provides valuable information about the accuracy of estimated parameters and their correlation and guide the formulation of a well-posed estimation problem. The results of proposed algorithm are validated with a series of experiments using a synthetic data set generated by the simultaneous heat and

  18. Investigation of glycerol assimilation and cofactor metabolism in Lactococcus lactis

    DEFF Research Database (Denmark)

    Holm, Anders Koefoed

    of glycerol kinase from L. lactis, introduction of a heterologous glycerol assimilation pathway and construction of a library of NADH oxidase activity. Based on a preliminary analysis of transcription level data, an attempt was made to stimulate glycerol assimilation by overexpressing the glycerol kinase...... already present in L. lactis. The construction and verification of a strain with increased glycerol kinase activity was not fully completed and is still ongoing. Similarly the construction of mutants expressing a heterologous pathway for glycerol dissimilation is also an ongoing task. An artificial...... effects and improve the growth rate, though not completely to the level of the reference strain. The fact that this effect was predominantly observed while utilizing xylose implicates the involvement of the pentose phosphate pathway. A possible mechanism underlying the observed growth characteristics...

  19. Modulation of intestinal sulfur assimilation metabolism regulates iron homeostasis

    Science.gov (United States)

    Hudson, Benjamin H.; Hale, Andrew T.; Irving, Ryan P.; Li, Shenglan; York, John D.

    2018-01-01

    Sulfur assimilation is an evolutionarily conserved pathway that plays an essential role in cellular and metabolic processes, including sulfation, amino acid biosynthesis, and organismal development. We report that loss of a key enzymatic component of the pathway, bisphosphate 3′-nucleotidase (Bpnt1), in mice, both whole animal and intestine-specific, leads to iron-deficiency anemia. Analysis of mutant enterocytes demonstrates that modulation of their substrate 3′-phosphoadenosine 5′-phosphate (PAP) influences levels of key iron homeostasis factors involved in dietary iron reduction, import and transport, that in part mimic those reported for the loss of hypoxic-induced transcription factor, HIF-2α. Our studies define a genetic basis for iron-deficiency anemia, a molecular approach for rescuing loss of nucleotidase function, and an unanticipated link between nucleotide hydrolysis in the sulfur assimilation pathway and iron homeostasis. PMID:29507250

  20. Assimilation and transformation of benzene by higher plants

    Energy Technology Data Exchange (ETDEWEB)

    Durmishidze, S V; Ugrekhelidze, D Sh; Dzhikiya, A N

    1974-01-01

    Higher plants are capable of assimilating benzene, the molecules of which are subjected to deep chemical transformations; the products of its metabolism move along the plant. Taking part in total metabolism, carbon atoms of benzene molecules incorporate into composition of low-molecular compounds of the plant cell. The bulk of benzene carbon incorporates into composition of organic acids and a comparatively small part - into composition of amino acids. In the metabolism process benzene carbon localizes mainly in the chloroplasts. Phenol, muconic acid and CO/sub 2/ are isolated and identified from the products of benzene enzymatic oxidation. A range of benzene assimilation by higher plants is extremely wide. 9 references, 5 tables.

  1. Data Assimilation by Conditioning of Driving Noise on Future Observations

    KAUST Repository

    Lee, Wonjung

    2014-08-01

    Conventional recursive filtering approaches, designed for quantifying the state of an evolving stochastic dynamical system with intermittent observations, use a sequence of i) an uncertainty propagation step followed by ii) a step where the associated data is assimilated using Bayes\\' rule. Alternatively, the order of the steps can be switched to i) one step ahead data assimilation followed by ii) uncertainty propagation. In this paper, we apply this smoothing-based sequential filter to systems driven by random noise, however with the conditioning on future observation not only to the system variable but to the driving noise. Our research reveals that, for the nonlinear filtering problem, the conditioned driving noise is biased by a nonzero mean and in turn pushes forward the filtering solution in time closer to the true state when it drives the system. As a result our proposed method can yield a more accurate approximate solution for the state estimation problem. © 1991-2012 IEEE.

  2. Ensemble-Based Data Assimilation in Reservoir Characterization: A Review

    Directory of Open Access Journals (Sweden)

    Seungpil Jung

    2018-02-01

    Full Text Available This paper presents a review of ensemble-based data assimilation for strongly nonlinear problems on the characterization of heterogeneous reservoirs with different production histories. It concentrates on ensemble Kalman filter (EnKF and ensemble smoother (ES as representative frameworks, discusses their pros and cons, and investigates recent progress to overcome their drawbacks. The typical weaknesses of ensemble-based methods are non-Gaussian parameters, improper prior ensembles and finite population size. Three categorized approaches, to mitigate these limitations, are reviewed with recent accomplishments; improvement of Kalman gains, add-on of transformation functions, and independent evaluation of observed data. The data assimilation in heterogeneous reservoirs, applying the improved ensemble methods, is discussed on predicting unknown dynamic data in reservoir characterization.

  3. Herbicides effect on the nitrogen fertilizer assimilation by sensitive plants

    International Nuclear Information System (INIS)

    Ladonin, V.F.; Samojlov, L.N.

    1976-01-01

    It has been established in studying the effect of herbicides on pea plants that the penetration of the preparations into the tissues of leaves and stems results in a slight increase of the rate of formation of dry substance in the leaves of the treated plants within 24 hours after treatment as compared with control, whereas in the last period of the analysis the herbicides strongly inhibit the formation of dry substance in leaves. The applied herbicide doses have resulted in drastic changes of the distribution of the plant-assimilated nitrogen between the protein and non-protein fractions in the leaves and stems of pea. When affected by the studied herbicides, the fertilizer nitrogen supply to the pea plants changes and the rate of the fertilizer nitrogen assimilation by the plants varies noticeably. The regularities of the fertilizer nitrogen inclusion in the protein and non-protein nitrogen compounds of the above-ground pea organs have been studied

  4. Data assimilation in the hydrological dispersion module of Rodos

    International Nuclear Information System (INIS)

    Madsen, H.

    2003-01-01

    Full text: The Hydrological Dispersion Module (HDM) of the Real Time On-line Decision Support System for Nuclear Emergencies in Europe (RODOS) simulates the transport and dispersion of radionuclides in the aquatic environment. This includes wash-off from watersheds following an atmospheric deposition as well as direct releases and transport and sedimentation in rivers, lakes and reservoirs. The output from the HDM is used by the aquatic food and dose module in RODOS for calculating the transfer of radionuclides to man and the resulting radiation exposure. A data assimilation system is presently being developed for the HDM that effectively combines the numerical models with radionuclide measurements in order to improve the capabilities for prediction of radionuclide contamination of the aquatic environment. In addition, the data assimilation system offers a consistent framework for addressing model and measurement uncertainties and quantifying the resulting prediction uncertainty of the radionuclide contamination. The system will provide decision makers with more accurate forecasts of the radionuclide contamination as well as the associated uncertainty, and hence provide the basis for more efficient emergency management. One of the main uncertainties in the modelling of radionuclide wash-off from watersheds is related to the concentration and spatial distribution of the radionuclide deposition. In addition, for key model parameters such as wash-off coefficients, partition coefficients, and exchange rates for the 'water - suspended sediment' and 'suspended sediment - bottom layer' systems only rough and highly uncertain estimates can be given which introduce additional uncertainties. In the case of direct release into the water bodies, the uncertainty of the release rate will further add to the model prediction uncertainty. The deposition and the associated uncertainty are obtained from the Deposition Monitoring Module (DeMM). Thus, when gamma dose rate measurements

  5. Mathematical foundations of hybrid data assimilation from a synchronization perspective

    Science.gov (United States)

    Penny, Stephen G.

    2017-12-01

    The state-of-the-art data assimilation methods used today in operational weather prediction centers around the world can be classified as generalized one-way coupled impulsive synchronization. This classification permits the investigation of hybrid data assimilation methods, which combine dynamic error estimates of the system state with long time-averaged (climatological) error estimates, from a synchronization perspective. Illustrative results show how dynamically informed formulations of the coupling matrix (via an Ensemble Kalman Filter, EnKF) can lead to synchronization when observing networks are sparse and how hybrid methods can lead to synchronization when those dynamic formulations are inadequate (due to small ensemble sizes). A large-scale application with a global ocean general circulation model is also presented. Results indicate that the hybrid methods also have useful applications in generalized synchronization, in particular, for correcting systematic model errors.

  6. Regulation of assimilate partitioning by daylength and spectral quality

    Energy Technology Data Exchange (ETDEWEB)

    Britz, S.J. [USDA-Climate Stress Lab., Beltsville, MD (United States)

    1994-12-31

    Photosynthesis is the process by which plants utilize light energy to assimilate and transform carbon dioxide into products that support growth and development. The preceding review provides an excellent summary of photosynthetic mechanisms and diurnal patterns of carbon metabolism with emphasis on the importance of gradual changes in photosynthetically-active radiation at dawn and dusk. In addition to these direct effects of irradiance, there are indirect effects of light period duration and spectral quality on carbohydrate metabolism and assimilate partitioning. Both daylength and spectral quality trigger developmental phenomena such as flowering (e.g., photoperiodism) and shade avoidance responses, but their effects on partitioning of photoassimilates in leaves are less well known. Moreover, the adaptive significance to the plants of such effects is sometimes not clear.

  7. Leaching of assimilable silicon species from fly ash

    International Nuclear Information System (INIS)

    Piekos, R.; Paslawska, S.

    1998-01-01

    The objective of this study was to investigate the leaching of assimilable silicon species from coal fly ash with distilled water, sea waterand synthetic sea water at various fly ash/water ratios, pHs and temperatures. At the 1 g/100 ml fly ash/water ratio, less than 1 mg Si was found in 11 of aqueous slurries over the pH range 4-8 after 2 h at ambient temperature. The leaching was most effective at pH 10.5. At the fly ash/waterratio indicated, the pH of the suspensions decreased from 10.4 to 8.4 after 5days. The pH of fly ash slurries in sea water varied only slightly over time as compared with that in distilled water. Generally, the leaching of assimilable silicon species with distilled water was more intense than that with the sea water. 27 refs., 6 figs., 3 tabs

  8. Identification and activity of acetate-assimilating bacteria in diffuse fluids venting from two deep-sea hydrothermal systems.

    Science.gov (United States)

    Winkel, Matthias; Pjevac, Petra; Kleiner, Manuel; Littmann, Sten; Meyerdierks, Anke; Amann, Rudolf; Mußmann, Marc

    2014-12-01

    Diffuse hydrothermal fluids often contain organic compounds such as hydrocarbons, lipids, and organic acids. Microorganisms consuming these compounds at hydrothermal sites are so far only known from cultivation-dependent studies. To identify potential heterotrophs without prior cultivation, we combined microbial community analysis with short-term incubations using (13)C-labeled acetate at two distinct hydrothermal systems. We followed cell growth and assimilation of (13)C into single cells by nanoSIMS combined with fluorescence in situ hybridization (FISH). In 55 °C-fluids from the Menez Gwen hydrothermal system/Mid-Atlantic Ridge, a novel epsilonproteobacterial group accounted for nearly all assimilation of acetate, representing the first aerobic acetate-consuming member of the Nautiliales. In contrast, Gammaproteobacteria dominated the (13) C-acetate assimilation in incubations of 37 °C-fluids from the back-arc hydrothermal system in the Manus Basin/Papua New Guinea. Here, 16S rRNA gene sequences were mostly related to mesophilic Marinobacter, reflecting the high content of seawater in these fluids. The rapid growth of microorganisms upon acetate addition suggests that acetate consumers in diffuse fluids are copiotrophic opportunists, which quickly exploit their energy sources, whenever available under the spatially and temporally highly fluctuating conditions. Our data provide first insights into the heterotrophic microbial community, catalyzing an under-investigated part of microbial carbon cycling at hydrothermal vents. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  9. DARLA: Data Assimilation and Remote Sensing for Littoral Applications

    Science.gov (United States)

    2017-03-01

    at reasonable logistical or financial costs . Remote sensing provides an attractive alternative. We discuss the range of different sensors that are...DARLA: Data Assimilation and Remote Sensing for Littoral Applications Final Report Award Number: N000141010932 Andrew T. Jessup Chris Chickadel...20. Radermacher, M., M. Wengrove, J. V. de Vries, and R. Holman (2014), Applicability of video-derived bathymetry estimates to nearshore current

  10. Nitrogen and sulfur assimilation in plants and algae

    Czech Academy of Sciences Publication Activity Database

    Giordano, Mario; Raven, John A.

    2014-01-01

    Roč. 118, č. 2 (2014), s. 45-61 ISSN 0304-3770 Grant - others:University of Dundee(GB) SC 015096; Italian Ministry for Agriculture(IT) MIPAF, Bioforme project; Italian Ministry of Foreign Affairs(IT) MAE. Joint Italian-Israel Cooperation Program Institutional support: RVO:61388971 Keywords : nitrogen * sulfur * assimilation * algae Subject RIV: EE - Microbiology, Virology Impact factor: 1.608, year: 2014

  11. Bayesian Nonlinear Assimilation of Eulerian and Lagrangian Coastal Flow Data

    Science.gov (United States)

    2015-09-30

    Lagrangian Coastal Flow Data Dr. Pierre F.J. Lermusiaux Department of Mechanical Engineering Center for Ocean Science and Engineering Massachusetts...Develop and apply theory, schemes and computational systems for rigorous Bayesian nonlinear assimilation of Eulerian and Lagrangian coastal flow data...coastal ocean fields, both in Eulerian and Lagrangian forms. - Further develop and implement our GMM-DO schemes for robust Bayesian nonlinear estimation

  12. Carbon and nitrogen assimilation in deep subseafloor microbial cells

    OpenAIRE

    Morono, Yuki; Terada, Takeshi; Nishizawa, Manabu; Ito, Motoo; Hillion, François; Takahata, Naoto; Sano, Yuji; Inagaki, Fumio

    2011-01-01

    Remarkable numbers of microbial cells have been observed in global shallow to deep subseafloor sediments. Accumulating evidence indicates that deep and ancient sediments harbor living microbial life, where the flux of nutrients and energy are extremely low. However, their physiology and energy requirements remain largely unknown. We used stable isotope tracer incubation and nanometer-scale secondary ion MS to investigate the dynamics of carbon and nitrogen assimilation activities in individua...

  13. Readily Available Chiral Benzimidazoles-Derived Guanidines as Organocatalysts in the Asymmetric α-Amination of 1,3-Dicarbonyl Compounds.

    Science.gov (United States)

    Benavent, Llorenç; Puccetti, Francesco; Baeza, Alejandro; Gómez-Martínez, Melania

    2017-08-11

    The synthesis and the evaluation as organocatalysts of new chiral guanidines derived from benzimidazoles in the enantioselective α-amination of 1,3-dicarbonyl compounds using di- t -butylazodicarboxylate as aminating agent is herein disclosed. The catalysts are readily synthesized through the reaction of 2-chlorobezimidazole and a chiral amine in moderate-to-good yields. Among all of them, those derived from ( R )-1-phenylethan-1-amine ( 1 ) and ( S )-1-(2-naphthyl)ethan-1-amine ( 3 ) turned out to be the most efficient for such asymmetric transformation, rendering good-to-high yields and moderate-to-good enantioselectivities for the amination products.

  14. AMSR2 all-sky radiance assimilation and its impact on the analysis and forecast of Hurricane Sandy with a limited-area data assimilation system

    Directory of Open Access Journals (Sweden)

    Chun Yang

    2016-06-01

    Full Text Available A method to assimilate all-sky radiances from the Advanced Microwave Scanning Radiometer 2 (AMSR2 was developed within the Weather Research and Forecasting (WRF model's data assimilation (WRFDA system. The four essential elements are: (1 extending the community radiative transform model's (CRTM interface to include hydrometeor profiles; (2 using total water Qt as the moisture control variable; (3 using a warm-rain physics scheme for partitioning the Qt increment into individual increments of water vapour, cloud liquid water and rain; and (4 adopting a symmetric observation error model for all-sky radiance assimilation.Compared to a benchmark experiment with no AMSR2 data, the impact of assimilating clear-sky or all-sky AMSR2 radiances on the analysis and forecast of Hurricane Sandy (2012 was assessed through analysis/forecast cycling experiments using WRF and WRFDA's three-dimensional variational (3DVAR data assimilation scheme. With more cloud/precipitation-affected data being assimilated around tropical cyclone (TC core areas in the all-sky AMSR2 assimilation experiment, better analyses were obtained in terms of the TC's central sea level pressure (CSLP, warm-core structure and cloud distribution. Substantial (>20 % error reduction in track and CSLP forecasts was achieved from both clear-sky and all-sky AMSR2 assimilation experiments, and this improvement was consistent from the analysis time to 72-h forecasts. Moreover, the all-sky assimilation experiment consistently yielded better track and CSLP forecasts than the clear-sky did for all forecast lead times, due to a better analysis in the TC core areas. Positive forecast impact from assimilating AMSR2 radiances is also seen when verified against the European Center for Medium-Range Weather Forecasts (ECMWF analysis and the Stage IV precipitation analysis, with an overall larger positive impact from the all-sky assimilation experiment.

  15. Examining Dense Data Usage near the Regions with Severe Storms in All-Sky Microwave Radiance Data Assimilation and Impacts on GEOS Hurricane Analyses

    Science.gov (United States)

    Kim, Min-Jeong; Jin, Jianjun; McCarty, Will; El Akkraoui, Amal; Todling, Ricardo; Gelaro, Ron

    2018-01-01

    Many numerical weather prediction (NWP) centers assimilate radiances affected by clouds and precipitation from microwave sensors, with the expectation that these data can provide critical constraints on meteorological parameters in dynamically sensitive regions to make significant impacts on forecast accuracy for precipitation. The Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center assimilates all-sky microwave radiance data from various microwave sensors such as all-sky GPM Microwave Imager (GMI) radiance in the Goddard Earth Observing System (GEOS) atmospheric data assimilation system (ADAS), which includes the GEOS atmospheric model, the Gridpoint Statistical Interpolation (GSI) atmospheric analysis system, and the Goddard Aerosol Assimilation System (GAAS). So far, most of NWP centers apply same large data thinning distances, that are used in clear-sky radiance data to avoid correlated observation errors, to all-sky microwave radiance data. For example, NASA GMAO is applying 145 km thinning distances for most of satellite radiance data including microwave radiance data in which all-sky approach is implemented. Even with these coarse observation data usage in all-sky assimilation approach, noticeable positive impacts from all-sky microwave data on hurricane track forecasts were identified in GEOS-5 system. The motivation of this study is based on the dynamic thinning distance method developed in our all-sky framework to use of denser data in cloudy and precipitating regions due to relatively small spatial correlations of observation errors. To investigate the benefits of all-sky microwave radiance on hurricane forecasts, several hurricane cases selected between 2016-2017 are examined. The dynamic thinning distance method is utilized in our all-sky approach to understand the sources and mechanisms to explain the benefits of all-sky microwave radiance data from various microwave radiance sensors like Advanced Microwave Sounder Unit

  16. Data assimilation in the early phase: Kalman filtering RIMPUFF

    International Nuclear Information System (INIS)

    Astrup, P.; Turcanu, C.; Puch, R.O.; Palma, C.R.; Mikkelsen, T.

    2004-09-01

    In the framework of the DAONEM project (Data Assimilation for Off-site Nuclear Emergency Management), a data assimilation module, ADUM (Atmospheric Dispersion Updating Module), for the mesoscale atmospheric dispersion program RIMPUFF (Risoe Mesoscale Puff model) part of the early-phase programs of RODOS (Realtime Online DecisiOn Support system for nuclear emergencies) has been developed. It is built on the Kalman filtering algorithm and it assimilates 10-minute averaged gamma dose rates measured at ground level stations. Since the gamma rates are non-linear functions of the state vector variables, the applied Kalman filter is the so-called Extended Kalman filter. In more ways the implementation is non standard: 1) the number of state vector variables varies with time, and 2) the state vector variables are prediction updated with 1-minute time steps but only Kalman filtered every 10 minutes, and this based on time averaged measurements. Given reasonable conditions, i.e. a spatially dense distribution of gamma monitors and a realistic wind field, the developed ADUM module is found to be able to enhance the prediction of the gamma dose field. Based on some of the Kalman filtering parameters, another module, ToDeMM, has been developed for providing the late-phase DeMM (Deposition Monitoring Module) of RODOS with an ensemble of fields of ground level air concentrations and wet deposited material. This accounts for the uncertainty estimation of this kind of quantities as calculated by RIMPUFF for use by DeMM. (au)

  17. Nonlinear problems in data-assimilation : Can synchronization help?

    Science.gov (United States)

    Tribbia, J. J.; Duane, G. S.

    2009-12-01

    Over the past several years, operational weather centers have initiated ensemble prediction and assimilation techniques to estimate the error covariance of forecasts in the short and the medium range. The ensemble techniques used are based on linear methods. The theory This technique s been shown to be a useful indicator of skill in the linear range where forecast errors are small relative to climatological variance. While this advance has been impressive, there are still ad hoc aspects of its use in practice, like the need for covariance inflation which are troubling. Furthermore, to be of utility in the nonlinear range an ensemble assimilation and prediction method must be capable of giving probabilistic information for the situation where a probability density forecast becomes multi-modal. A prototypical, simplest example of such a situation is the planetary-wave regime transition where the pdf is bimodal. Our recent research show how the inconsistencies and extensions of linear methodology can be consistently treated using the paradigm of synchronization which views the problems of assimilation and forecasting as that of optimizing the forecast model state with respect to the future evolution of the atmosphere.

  18. Data assimilation in the decision support system RODOS

    International Nuclear Information System (INIS)

    Rojas-Palma, C.; Madsen, H.; Gering, F.; Puch, R.; Turcanu, C.; Astrup, P.; Mueller, H.; Richter, K.; Zheleznyak, M.; Treebushny, D.; Kolomeev, M.; Kamaev, D.; Wynn, H.

    2003-01-01

    Model predictions for a rapid assessment and prognosis of possible radiological consequences after an accidental release of radionuclides play an important role in nuclear emergency management. Radiological observations, e.g. dose rate measurements, can be used to improve such model predictions. The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based on Kalman filters,are under development for several modules of the RODOS system, including the atmospheric dispersion, deposition, food chain and hydrological models. The use of such a generic data assimilation methodology enables the propagation of uncertainties throughout the various modules of the system. This would in turn provide decision makers with uncertainty estimates taking into account both model and observation errors. This paper describes the methodology employed as well as results of some preliminary studies based on simulated data. (author)

  19. Regime-dependence of Impacts of Radar Rainfall Data Assimilation

    Science.gov (United States)

    Craig, G. C.; Keil, C.

    2009-04-01

    Experience from the first operational trials of assimilation of radar data in kilometre scale numerical weather prediction models (operating without cumulus parameterisation) shows that the positive impact of the radar data on convective precipitation forecasts typically decay within a few hours, although certain cases show much longer impacts. Here the impact time of radar data assimilation is related to characteristics of the meteorological environment. This QPF uncertainty is investigated using an ensemble of 10 forecasts at 2.8 km horizontal resolution based on different initial and boundary conditions from a global forecast ensemble. Control forecasts are compared with forecasts where radar reflectivity data is assimilated using latent heat nudging. Examination of different cases of convection in southern Germany suggests that the forecasts can be separated into two regimes using a convective timescale. Short impact times are associated with short convective timescales that are characteristic of equilibrium convection. In this regime the statistical properties of the convection are constrained by the large-scale forcing, and effects of the radar data are lost within a few hours as the convection rapidly returns to equilibrium. When the convective timescale is large (non-equilibrium conditions), the impact of the radar data is longer since convective systems are triggered by the latent heat nudging and are able to persist for many hours in the very unstable conditions present in these cases.

  20. Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

    Science.gov (United States)

    Wang, Jun; Breen, Daniel; Akinin, Abraham; Broccard, Frederic; Abarbanel, Henry D I; Cauwenberghs, Gert

    2017-12-01

    Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

  1. Application of statistical dynamical turbulence closures to data assimilation

    International Nuclear Information System (INIS)

    O'Kane, Terence J; Frederiksen, Jorgen S

    2010-01-01

    We describe the development of an accurate yet computationally tractable statistical dynamical closure theory for general inhomogeneous turbulent flows, coined the quasi-diagonal direct interaction approximation closure (QDIA), and its application to problems in data assimilation. The QDIA provides prognostic equations for evolving mean fields, covariances and higher-order non-Gaussian terms, all of which are also required in the formulation of data assimilation schemes for nonlinear geophysical flows. The QDIA is a generalization of the class of direct interaction approximation theories, initially developed by Kraichnan (1959 J. Fluid Mech. 5 497) for isotropic turbulence, to fully inhomogeneous flows and has been further generalized to allow for both inhomogeneous and non-Gaussian initial conditions and long integrations. A regularization procedure or empirical vertex renormalization that ensures correct inertial range spectra is also described. The aim of this paper is to provide a coherent mathematical description of the QDIA turbulence closure and closure-based data assimilation scheme we have labeled the statistical dynamical Kalman filter. The mathematical formalism presented has been synthesized from recent works of the authors with some additional material and is presented in sufficient detail that the paper is of a pedagogical nature.

  2. Data assimilation method based on the constraints of confidence region

    Science.gov (United States)

    Li, Yong; Li, Siming; Sheng, Yao; Wang, Luheng

    2018-03-01

    The ensemble Kalman filter (EnKF) is a distinguished data assimilation method that is widely used and studied in various fields including methodology and oceanography. However, due to the limited sample size or imprecise dynamics model, it is usually easy for the forecast error variance to be underestimated, which further leads to the phenomenon of filter divergence. Additionally, the assimilation results of the initial stage are poor if the initial condition settings differ greatly from the true initial state. To address these problems, the variance inflation procedure is usually adopted. In this paper, we propose a new method based on the constraints of a confidence region constructed by the observations, called EnCR, to estimate the inflation parameter of the forecast error variance of the EnKF method. In the new method, the state estimate is more robust to both the inaccurate forecast models and initial condition settings. The new method is compared with other adaptive data assimilation methods in the Lorenz-63 and Lorenz-96 models under various model parameter settings. The simulation results show that the new method performs better than the competing methods.

  3. Motion estimation by data assimilation in reduced dynamic models

    International Nuclear Information System (INIS)

    Drifi, Karim

    2013-01-01

    Motion estimation is a major challenge in the field of image sequence analysis. This thesis is a study of the dynamics of geophysical flows visualized by satellite imagery. Satellite image sequences are currently underused for the task of motion estimation. A good understanding of geophysical flows allows a better analysis and forecast of phenomena in domains such as oceanography and meteorology. Data assimilation provides an excellent framework for achieving a compromise between heterogeneous data, especially numerical models and observations. Hence, in this thesis we set out to apply variational data assimilation methods to estimate motion on image sequences. As one of the major drawbacks of applying these assimilation techniques is the considerable computation time and memory required, we therefore define and use a model reduction method in order to significantly decrease the necessary computation time and the memory. We then explore the possibilities that reduced models provide for motion estimation, particularly the possibility of strictly imposing some known constraints on the computed solutions. In particular, we show how to estimate a divergence free motion with boundary conditions on a complex spatial domain [fr

  4. Uncertainty of Flood Forecasting Based on Radar Rainfall Data Assimilation

    Directory of Open Access Journals (Sweden)

    Xinchi Chen

    2016-01-01

    Full Text Available Precipitation is the core data input to hydrological forecasting. The uncertainty in precipitation forecast data can lead to poor performance of predictive hydrological models. Radar-based precipitation measurement offers advantages over ground-based measurement in the quantitative estimation of temporal and spatial aspects of precipitation, but errors inherent in this method will still act to reduce the performance. Using data from White Lotus River of Hubei Province, China, five methods were used to assimilate radar rainfall data transformed from the classified Z-R relationship, and the postassimilation data were compared with precipitation measured by rain gauges. The five sets of assimilated rainfall data were then used as input to the Xinanjiang model. The effect of precipitation data input error on runoff simulation was analyzed quantitatively by disturbing the input data using the Breeding of Growing Modes method. The results of practical application demonstrated that the statistical weight integration and variational assimilation methods were superior. The corresponding performance in flood hydrograph prediction was also better using the statistical weight integration and variational methods compared to the others. It was found that the errors of radar rainfall data disturbed by the Breeding of Growing Modes had a tendency to accumulate through the hydrological model.

  5. DATA ASSIMILATION APPROACH FOR FORECAST OF SOLAR ACTIVITY CYCLES

    Energy Technology Data Exchange (ETDEWEB)

    Kitiashvili, Irina N., E-mail: irina.n.kitiashvili@nasa.gov [NASA Ames Research Center, Moffett Field, Mountain View, CA 94035 (United States)

    2016-11-01

    Numerous attempts to predict future solar cycles are mostly based on empirical relations derived from observations of previous cycles, and they yield a wide range of predicted strengths and durations of the cycles. Results obtained with current dynamo models also deviate strongly from each other, thus raising questions about criteria to quantify the reliability of such predictions. The primary difficulties in modeling future solar activity are shortcomings of both the dynamo models and observations that do not allow us to determine the current and past states of the global solar magnetic structure and its dynamics. Data assimilation is a relatively new approach to develop physics-based predictions and estimate their uncertainties in situations where the physical properties of a system are not well-known. This paper presents an application of the ensemble Kalman filter method for modeling and prediction of solar cycles through use of a low-order nonlinear dynamo model that includes the essential physics and can describe general properties of the sunspot cycles. Despite the simplicity of this model, the data assimilation approach provides reasonable estimates for the strengths of future solar cycles. In particular, the prediction of Cycle 24 calculated and published in 2008 is so far holding up quite well. In this paper, I will present my first attempt to predict Cycle 25 using the data assimilation approach, and discuss the uncertainties of that prediction.

  6. Effect of Vertical Canopy Architecture on Transpiration, Thermoregulation and Carbon Assimilation

    Directory of Open Access Journals (Sweden)

    Tirtha Banerjee

    2018-04-01

    Full Text Available Quantifying the impact of natural and anthropogenic disturbances such as deforestation, forest fires and vegetation thinning among others on net ecosystem—atmosphere exchanges of carbon dioxide, water vapor and heat—is an important aspect in the context of modeling global carbon, water and energy cycles. The absence of canopy architectural variation in horizontal and vertical directions is a major source of uncertainty in current climate models attempting to address these issues. This manuscript demonstrates the importance of considering the vertical distribution of foliage density by coupling a leaf level plant biophysics model with analytical solutions of wind flow and light attenuation in a horizontally homogeneous canopy. It is demonstrated that plant physiological response in terms of carbon assimilation, transpiration and canopy surface temperature can be widely different for two canopies with the same leaf area index (LAI but different leaf area density distributions, under several conditions of wind speed, light availability, soil moisture availability and atmospheric evaporative demand.

  7. Photoperiodic control of soybean 14C-assimilate partitioning during the seed filling period

    International Nuclear Information System (INIS)

    Morandi, E.N.

    1986-01-01

    Photoperiod not only controls the timing of flowering, but also affects later stages of seed development. To study its effect on assimilate partitioning, soybean plants were kept in short days (SD) or night interrupted (NI) during seed filling. The source-sink ratio was fixed to one leaflet-one pod per node. The node was girdle-isolated and its leaflet was pulse labelled with 14 CO 2 . SD plants partitioned more 14 C into seeds, while NI plants showed higher proportions in the petiole, stem and carpel. Seed growth rate and final seed dry weight were increased by 40% in SD. The sugar/starch ratio was increased in cotyledons and decreased in leaves of SD plants. In contrast, NI plants showed more 14 C incorporation into proteins. No changes were detected in carbon exchange ratio, dark respiration and total node dry weight. Thus, photoperiodic induced changes in carbohydrate and protein partitioning occurred without changes in the overall assimilatory process

  8. Assimilating satellite-based canopy height within an ecosystem model to estimate aboveground forest biomass

    Science.gov (United States)

    Joetzjer, E.; Pillet, M.; Ciais, P.; Barbier, N.; Chave, J.; Schlund, M.; Maignan, F.; Barichivich, J.; Luyssaert, S.; Hérault, B.; von Poncet, F.; Poulter, B.

    2017-07-01

    Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.

  9. Improving the reliability of the prognosis of radiation exposures using data assimilation

    International Nuclear Information System (INIS)

    Twenhoefel, C.J.W.; Eleveld, H.

    2003-01-01

    Full text: During large-scale nuclear accidents quantitative risk estimates usually underlie a countermeasure strategy. Because of the overwhelming social and economical impact of countermeasures not only the speed but also the reliability of the underlying calculations are of prime importance. Real-time atmospheric dispersion models are an important tool to support the decision-makers with spatial and temporal information on the dispersion forecast and the extent of the expected contamination. Due to the stochastic and chaotic nature of the atmosphere the real-time calculation of air dispersion is quite complicated. The accuracy of the calculated spatial and temporal distributions of air concentration, deposition and the corresponding radiation levels is limited due to uncertainties in the applied dispersion algorithms, limitations in knowledge and availability of atmospheric input data and knowledge of the release and the release conditions during an emergency. To improve the prognosis of the radiation exposure it is envisaged to use the on-line data of the National Radioactivity Monitoring Network. In a first step the monitored gamma radiation levels are related to the calculated external radiation levels from source term estimates based on the plant status. In the next step both the results of air dispersion model calculations and the data of the monitoring network are compared using RIVM's dispersion model validation tool [1-2]. From this a quantitative measure for the agreement between a model run and a particular measurement set can be deduced. This will be followed by a data assimilation technique based an RIVM's validation tool which provides an improved reliability of the prognosis when compared to intermediate, i.e. previous model runs. An uncertainty and sensitivity analysis of the air dispersion model must identify the relevant input parameters. In the absence of elevated levels on our monitoring network the Kincaid data set will be used to demonstrate

  10. Correcting Biases in a lower resolution global circulation model with data assimilation

    Science.gov (United States)

    Canter, Martin; Barth, Alexander

    2016-04-01

    With this work, we aim at developping a new method of bias correction using data assimilation. This method is based on the stochastic forcing of a model to correct bias. First, through a preliminary run, we estimate the bias of the model and its possible sources. Then, we establish a forcing term which is directly added inside the model's equations. We create an ensemble of runs and consider the forcing term as a control variable during the assimilation of observations. We then use this analysed forcing term to correct the bias of the model. Since the forcing is added inside the model, it acts as a source term, unlike external forcings such as wind. This procedure has been developed and successfully tested with a twin experiment on a Lorenz 95 model. It is currently being applied and tested on the sea ice ocean NEMO LIM model, which is used in the PredAntar project. NEMO LIM is a global and low resolution (2 degrees) coupled model (hydrodynamic model and sea ice model) with long time steps allowing simulations over several decades. Due to its low resolution, the model is subject to bias in area where strong currents are present. We aim at correcting this bias by using perturbed current fields from higher resolution models and randomly generated perturbations. The random perturbations need to be constrained in order to respect the physical properties of the ocean, and not create unwanted phenomena. To construct those random perturbations, we first create a random field with the Diva tool (Data-Interpolating Variational Analysis). Using a cost function, this tool penalizes abrupt variations in the field, while using a custom correlation length. It also decouples disconnected areas based on topography. Then, we filter the field to smoothen it and remove small scale variations. We use this field as a random stream function, and take its derivatives to get zonal and meridional velocity fields. We also constrain the stream function along the coasts in order not to have

  11. Key aspects of stratospheric tracer modeling using assimilated winds

    Directory of Open Access Journals (Sweden)

    B. Bregman

    2006-01-01

    Full Text Available This study describes key aspects of global chemistry-transport models and their impact on stratospheric tracer transport. We concentrate on global models that use assimilated winds from numerical weather predictions, but the results also apply to tracer transport in general circulation models. We examined grid resolution, numerical diffusion, air parcel dispersion, the wind or mass flux update frequency, and time interpolation. The evaluation is performed with assimilated meteorology from the "operational analyses or operational data" (OD from the European Centre for Medium-Range Weather Forecasts (ECMWF. We also show the effect of the mass flux update frequency using the ECMWF 40-year re-analyses (ERA40. We applied the three-dimensional chemistry-transport Tracer Model version 5 (TM5 and a trajectory model and performed several diagnoses focusing on different transport regimes. Covering different time and spatial scales, we examined (1 polar vortex dynamics during the Arctic winter, (2 the large-scale stratospheric meridional circulation, and (3 air parcel dispersion in the tropical lower stratosphere. Tracer distributions inside the Arctic polar vortex show considerably worse agreement with observations when the model grid resolution in the polar region is reduced to avoid numerical instability. The results are sensitive to the diffusivity of the advection. Nevertheless, the use of a computational cheaper but diffusive advection scheme is feasible for tracer transport when the horizontal grid resolution is equal or smaller than 1 degree. The use of time interpolated winds improves the tracer distributions, particularly in the middle and upper stratosphere. Considerable improvement is found both in the large-scale tracer distribution and in the polar regions when the update frequency of the assimilated winds is increased from 6 to 3 h. It considerably reduces the vertical dispersion of air parcels in the tropical lower stratosphere. Strong

  12. Furfural Inhibits Growth by Limiting Sulfur Assimilation in Ethanologenic Escherichia coli Strain LY180▿

    Science.gov (United States)

    Miller, Elliot N.; Jarboe, Laura R.; Turner, Peter C.; Pharkya, Priti; Yomano, Lorraine P.; York, Sean W.; Nunn, David; Shanmugam, K. T.; Ingram, Lonnie O.

    2009-01-01

    A wide variety of commercial products can be potentially made from monomeric sugars produced by the dilute acid hydrolysis of lignocellulosic biomass. However, this process is accompanied by side products such as furfural that hinder microbial growth and fermentation. To investigate the mechanism of furfural inhibition, mRNA microarrays of an ethanologenic strain of Escherichia coli (LY180) were compared immediately prior to and 15 min after a moderate furfural challenge. Expression of genes and regulators associated with the biosynthesis of cysteine and methionine was increased by furfural, consistent with a limitation of these critical metabolites. This was in contrast to a general stringent response and decreased expression of many other biosynthetic genes. Of the 20 amino acids individually tested as supplements (100 μM each), cysteine and methionine were the most effective in increasing furfural tolerance with serine (precursor of cysteine), histidine, and arginine of lesser benefit. Supplementation with other reduced sulfur sources such as d-cysteine and thiosulfate also increased furfural tolerance. In contrast, supplementation with taurine, a sulfur source that requires 3 molecules of NADPH for sulfur assimilation, was of no benefit. Furfural tolerance was also increased by inserting a plasmid encoding pntAB, a cytoplasmic NADH/NADPH transhydrogenase. Based on these results, a model is proposed for the inhibition of growth in which the reduction of furfural by YqhD, an enzyme with a low Km for NADPH, depletes NADPH sufficiently to limit the assimilation of sulfur into amino acids (cysteine and methionine) by CysIJ (sulfite reductase). PMID:19684179

  13. A hybrid modeling with data assimilation to evaluate human exposure level

    Science.gov (United States)

    Koo, Y. S.; Cheong, H. K.; Choi, D.; Kim, A. L.; Yun, H. Y.

    2015-12-01

    Exposure models are designed to better represent human contact with PM (Particulate Matter) and other air pollutants such as CO, SO2, O3, and NO2. The exposure concentrations of the air pollutants to human are determined by global and regional long range transport of global and regional scales from Europe and China as well as local emissions from urban and road vehicle sources. To assess the exposure level in detail, the multiple scale influence from background to local sources should be considered. A hybrid air quality modeling methodology combing a grid-based chemical transport model with a local plume dispersion model was used to provide spatially and temporally resolved air quality concentration for human exposure levels in Korea. In the hybrid modeling approach, concentrations from a grid-based chemical transport model and a local plume dispersion model are added to provide contributions from photochemical interactions, long-range (regional) transport and local-scale dispersion. The CAMx (Comprehensive Air quality Model with Extensions was used for the background concentrations from anthropogenic and natural emissions in East Asia including Korea while the road dispersion by vehicle emission was calculated by CALPUFF model. The total exposure level of the pollutants was finally assessed by summing the background and road contributions. In the hybrid modeling, the data assimilation method based on the optimal interpolation was applied to overcome the discrepancies between the model predicted concentrations and observations. The air quality data from the air quality monitoring stations in Korea. The spatial resolution of the hybrid model was 50m for the Seoul Metropolitan Ares. This example clearly demonstrates that the exposure level could be estimated to the fine scale for the exposure assessment by using the hybrid modeling approach with data assimilation.

  14. Estimation of gross land-use change and its uncertainty using a Bayesian data assimilation approach

    Science.gov (United States)

    Levy, Peter; van Oijen, Marcel; Buys, Gwen; Tomlinson, Sam

    2018-03-01

    We present a method for estimating land-use change using a Bayesian data assimilation approach. The approach provides a general framework for combining multiple disparate data sources with a simple model. This allows us to constrain estimates of gross land-use change with reliable national-scale census data, whilst retaining the detailed information available from several other sources. Eight different data sources, with three different data structures, were combined in our posterior estimate of land use and land-use change, and other data sources could easily be added in future. The tendency for observations to underestimate gross land-use change is accounted for by allowing for a skewed distribution in the likelihood function. The data structure produced has high temporal and spatial resolution, and is appropriate for dynamic process-based modelling. Uncertainty is propagated appropriately into the output, so we have a full posterior distribution of output and parameters. The data are available in the widely used netCDF file format from http://eidc.ceh.ac.uk/.

  15. On the assimilation of satellite derived soil moisture in numerical weather prediction models

    Science.gov (United States)

    Drusch, M.

    2006-12-01

    Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

  16. Reliable and accurate point-based prediction of cumulative infiltration using soil readily available characteristics: A comparison between GMDH, ANN, and MLR

    Science.gov (United States)

    Rahmati, Mehdi

    2017-08-01

    Developing accurate and reliable pedo-transfer functions (PTFs) to predict soil non-readily available characteristics is one of the most concerned topic in soil science and selecting more appropriate predictors is a crucial factor in PTFs' development. Group method of data handling (GMDH), which finds an approximate relationship between a set of input and output variables, not only provide an explicit procedure to select the most essential PTF input variables, but also results in more accurate and reliable estimates than other mostly applied methodologies. Therefore, the current research was aimed to apply GMDH in comparison with multivariate linear regression (MLR) and artificial neural network (ANN) to develop several PTFs to predict soil cumulative infiltration point-basely at specific time intervals (0.5-45 min) using soil readily available characteristics (RACs). In this regard, soil infiltration curves as well as several soil RACs including soil primary particles (clay (CC), silt (Si), and sand (Sa)), saturated hydraulic conductivity (Ks), bulk (Db) and particle (Dp) densities, organic carbon (OC), wet-aggregate stability (WAS), electrical conductivity (EC), and soil antecedent (θi) and field saturated (θfs) water contents were measured at 134 different points in Lighvan watershed, northwest of Iran. Then, applying GMDH, MLR, and ANN methodologies, several PTFs have been developed to predict cumulative infiltrations using two sets of selected soil RACs including and excluding Ks. According to the test data, results showed that developed PTFs by GMDH and MLR procedures using all soil RACs including Ks resulted in more accurate (with E values of 0.673-0.963) and reliable (with CV values lower than 11 percent) predictions of cumulative infiltrations at different specific time steps. In contrast, ANN procedure had lower accuracy (with E values of 0.356-0.890) and reliability (with CV values up to 50 percent) compared to GMDH and MLR. The results also revealed

  17. Changes in assimilation of C3 marsh plants by resident fishes in estuarine systems with distinct hydrogeomorphology features.

    Directory of Open Access Journals (Sweden)

    Adna Ferreira Garcia

    2015-11-01

    Full Text Available Although saltmarshes are widely recognized as important habitats providing shelter for estuarine organisms and protection against predators, there is still no consensus on the trophic value of marsh plants for estuarine food webs. We employed stable isotopes to evaluate differences in assimilation of nutrients derived from marsh plants with C3 (Juncus acutus, Scirpus maritimus, Scirpus olneyi and C4 (Spartina densiflora photosynthetic pathways by resident fishes in three estuaries with contrasting hydrogeomorphology characteristics. Carbon (δ13C and nitrogen (δ15N stable isotope ratios of basal food sources (C3 and C4 marsh plants, macroalgae, seagrass and seston and estuarine resident fishes (Achirus garmani, Atherinella brasiliensis, Genidens genidens, Ctenogobius shufeldti, Jenynsia multidentata, Odonthestes argentinensis were analyzed in two choked lagoons (Tramandai-29°S, Patos-30°S and a coastal river (Chui-33°S. Average δ13C values of consumers were statistically significant higher in the two choked-type estuaries (Tramandaí: -16.11; Patos: -15.82 than in the coastal river (Chui: -24.32 (p0.292. SIAR mixing models revealed that the most assimilated basal food sources by consumers in the choked-type lagoon estuaries were a pool of 13C enriched food sources (macroalgae, C4 marsh and seagrass and seston (95% credibility interval: 0.38 to 0.80 and 0.00 to 0.54, respectively. In contrast, nutrients derived from C3-marsh plants were the main basal food source assimilated by estuarine resident fishes at the coastal river (0.33 to 0.87. These findings could be explained by the absence of extensive shallow embayments and a steeper slope at the coastal river that could promote higher transport of C3-marsh detritus and, consequently, higher assimilation by estuarine fishes. In contrast, detritus derived from C3 marsh plants could be trapped in the upper intertidal zone of choked-typed estuaries and, consequently, be less available for aquatic

  18. USER FRIENDLY OPEN GIS TOOL FOR LARGE SCALE DATA ASSIMILATION – A CASE STUDY OF HYDROLOGICAL MODELLING

    Directory of Open Access Journals (Sweden)

    P. K. Gupta

    2012-08-01

    Full Text Available Open source software (OSS coding has tremendous advantages over proprietary software. These are primarily fuelled by high level programming languages (JAVA, C++, Python etc... and open source geospatial libraries (GDAL/OGR, GEOS, GeoTools etc.. Quantum GIS (QGIS is a popular open source GIS package, which is licensed under GNU GPL and is written in C++. It allows users to perform specialised tasks by creating plugins in C++ and Python. This research article emphasises on exploiting this capability of QGIS to build and implement plugins across multiple platforms using the easy to learn – Python programming language. In the present study, a tool has been developed to assimilate large spatio-temporal datasets such as national level gridded rainfall, temperature, topographic (digital elevation model, slope, aspect, landuse/landcover and multi-layer soil data for input into hydrological models. At present this tool has been developed for Indian sub-continent. An attempt is also made to use popular scientific and numerical libraries to create custom applications for digital inclusion. In the hydrological modelling calibration and validation are important steps which are repetitively carried out for the same study region. As such the developed tool will be user friendly and used efficiently for these repetitive processes by reducing the time required for data management and handling. Moreover, it was found that the developed tool can easily assimilate large dataset in an organised manner.

  19. Assimilation of NUCAPS Retrieved Profiles in GSI for Unique Forecasting Applications

    Science.gov (United States)

    Berndt, Emily Beth; Zavodsky, Bradley; Srikishen, Jayanthi; Blankenship, Clay

    2015-01-01

    Hyperspectral IR profiles can be assimilated in GSI as a separate observation other than radiosondes with only changes to tables in the fix directory. Assimilation of profiles does produce changes to analysis fields and evidenced by: Innovations larger than +/-2.0 K are present and represent where individual profiles impact the final temperature analysis.The updated temperature analysis is colder behind the cold front and warmer in the warm sector. The updated moisture analysis is modified more in the low levels and tends to be drier than the original model background Analysis of model output shows: Differences relative to 13-km RAP analyses are smaller when profiles are assimilated with NUCAPS errors. CAPE is under-forecasted when assimilating NUCAPS profiles, which could be problematic for severe weather forecasting Refining the assimilation technique to incorporate an error covariance matrix and creating a separate GSI module to assimilate satellite profiles may improve results.

  20. The coupling of high-speed high resolution experimental data and LES through data assimilation techniques

    Science.gov (United States)

    Harris, S.; Labahn, J. W.; Frank, J. H.; Ihme, M.

    2017-11-01

    Data assimilation techniques can be integrated with time-resolved numerical simulations to improve predictions of transient phenomena. In this study, optimal interpolation and nudging are employed for assimilating high-speed high-resolution measurements obtained for an inert jet into high-fidelity large-eddy simulations. This experimental data set was chosen as it provides both high spacial and temporal resolution for the three-component velocity field in the shear layer of the jet. Our first objective is to investigate the impact that data assimilation has on the resulting flow field for this inert jet. This is accomplished by determining the region influenced by the data assimilation and corresponding effect on the instantaneous flow structures. The second objective is to determine optimal weightings for two data assimilation techniques. The third objective is to investigate how the frequency at which the data is assimilated affects the overall predictions. Graduate Research Assistant, Department of Mechanical Engineering.

  1. DARLA: Data Assimilation and Remote Sensing for Littoral Applications

    Science.gov (United States)

    Jessup, A.; Holman, R. A.; Chickadel, C.; Elgar, S.; Farquharson, G.; Haller, M. C.; Kurapov, A. L.; Özkan-Haller, H. T.; Raubenheimer, B.; Thomson, J. M.

    2012-12-01

    DARLA is 5-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced data assimilation (DA) modeling to (a) evaluate and improve remote sensing retrieval algorithms for environmental parameters, (b) determine the extent to which remote sensing data can be used in place of in situ data in models, and (c) infer bathymetry for littoral environments by combining remotely-sensed parameters and data assimilation models. The project uses microwave, electro-optical, and infrared techniques to characterize the littoral ocean with a focus on wave and current parameters required for DA modeling. In conjunction with the RIVET (River and Inlets) Project, extensive in situ measurements provide ground truth for both the remote sensing retrieval algorithms and the DA modeling. Our goal is to use remote sensing to constrain data assimilation models of wave and circulation dynamics in a tidal inlet and surrounding beaches. We seek to improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments. The objectives are to test the following three hypotheses: 1. Environmental parameter estimation using remote sensing techniques can be significantly improved by fusion of multiple sensor products. 2. Data assimilation models can be adequately constrained (i.e., forced or guided) with environmental parameters derived from remote sensing measurements. 3. Bathymetry on open beaches, river mouths, and at tidal inlets can be inferred from a combination of remotely-sensed parameters and data assimilation models. Our approach is to conduct a series of field experiments combining remote sensing and in situ measurements to investigate signature physics and to gather data for developing and testing DA models. A preliminary experiment conducted at

  2. Assimilation of MODIS Dark Target and Deep Blue Observations in the Dust Aerosol Component of NMMB-MONARCH version 1.0

    Science.gov (United States)

    Di Tomaso, Enza; Schutgens, Nick A. J.; Jorba, Oriol; Perez Garcia-Pando, Carlos

    2017-01-01

    A data assimilation capability has been built for the NMMB-MONARCH chemical weather prediction system, with a focus on mineral dust, a prominent type of aerosol. An ensemble-based Kalman filter technique (namely the local ensemble transform Kalman filter - LETKF) has been utilized to optimally combine model background and satellite retrievals. Our implementation of the ensemble is based on known uncertainties in the physical parametrizations of the dust emission scheme. Experiments showed that MODIS AOD retrievals using the Dark Target algorithm can help NMMB-MONARCH to better characterize atmospheric dust. This is particularly true for the analysis of the dust outflow in the Sahel region and over the African Atlantic coast. The assimilation of MODIS AOD retrievals based on the Deep Blue algorithm has a further positive impact in the analysis downwind from the strongest dust sources of the Sahara and in the Arabian Peninsula. An analysis-initialized forecast performs better (lower forecast error and higher correlation with observations) than a standard forecast, with the exception of underestimating dust in the long-range Atlantic transport and degradation of the temporal evolution of dust in some regions after day 1. Particularly relevant is the improved forecast over the Sahara throughout the forecast range thanks to the assimilation of Deep Blue retrievals over areas not easily covered by other observational datasets.The present study on mineral dust is a first step towards data assimilation with a complete aerosol prediction system that includes multiple aerosol species.

  3. [Al3+ Absorption and Assimilation by Four Ectomycorrhizal Fungi].

    Science.gov (United States)

    Wang, Ming-xia; Yuan, Ling; Huang, Jian-guo; Zhou, Zhi-feng

    2015-09-01

    The present experiment was carried out in order to know the resistance mechanism of the ectomycorrhizal (ECM) fungi under Al stress, to establish the theoretical foundation to alleviate the Al toxicity of trees, to guide the selection of Al-resisted ECM fungi and preserve forest health. The absorption and assimilation of Al3+ by four ECM fungi [Pisolithus tinctorius (Pt 715), Suillus luteus (Sl 08 and Sl 14), Gyroporus cyanescens (Gc 99)], which were isolated from different forest soils, were investigated in pure culture in liquid media. The growths of Pt 715 and Sl 08 were less affected by Al3+, but growths of S114 and Gc 99 were obviously inhibited by Al3+. With the increasing of Al3+ concentration in culture, the absorption and assimilation of Al3+ by four ECM fungi increased. It indicated that the concentration of Al3+ in environments might be the primary factor determining the Al3+ content in the cell of each tested fungi. Amounts of Al3+ absorbed (in total or calculated in unit hyphae) by the Al3+ tolerant strains (Pt 715 and Sl 08) were significantly lower than those by the Al3+ sensitive strains (S1 14 and Gc 99), which illustrated that reducing the absorption of Al3+ under Al3+ stress environment might be an effective approach to alleviate the Al3+ poison for these Al3+ tolerant strains. Furthermore, Al3+ stress could stimulate the ECM fungi to assimilate more N, P, and K, which might indicate that increasing requirement of the nutrients also could be helpful for ECM fungi to fight against the harmful effects caused by Al3+ stress.

  4. Data-Driven Model Uncertainty Estimation in Hydrologic Data Assimilation

    Science.gov (United States)

    Pathiraja, S.; Moradkhani, H.; Marshall, L.; Sharma, A.; Geenens, G.

    2018-02-01

    The increasing availability of earth observations necessitates mathematical methods to optimally combine such data with hydrologic models. Several algorithms exist for such purposes, under the umbrella of data assimilation (DA). However, DA methods are often applied in a suboptimal fashion for complex real-world problems, due largely to several practical implementation issues. One such issue is error characterization, which is known to be critical for a successful assimilation. Mischaracterized errors lead to suboptimal forecasts, and in the worst case, to degraded estimates even compared to the no assimilation case. Model uncertainty characterization has received little attention relative to other aspects of DA science. Traditional methods rely on subjective, ad hoc tuning factors or parametric distribution assumptions that may not always be applicable. We propose a novel data-driven approach (named SDMU) to model uncertainty characterization for DA studies where (1) the system states are partially observed and (2) minimal prior knowledge of the model error processes is available, except that the errors display state dependence. It includes an approach for estimating the uncertainty in hidden model states, with the end goal of improving predictions of observed variables. The SDMU is therefore suited to DA studies where the observed variables are of primary interest. Its efficacy is demonstrated through a synthetic case study with low-dimensional chaotic dynamics and a real hydrologic experiment for one-day-ahead streamflow forecasting. In both experiments, the proposed method leads to substantial improvements in the hidden states and observed system outputs over a standard method involving perturbation with Gaussian noise.

  5. Nonlinear error dynamics for cycled data assimilation methods

    International Nuclear Information System (INIS)

    Moodey, Alexander J F; Lawless, Amos S; Potthast, Roland W E; Van Leeuwen, Peter Jan

    2013-01-01

    We investigate the error dynamics for cycled data assimilation systems, such that the inverse problem of state determination is solved at t k , k = 1, 2, 3, …, with a first guess given by the state propagated via a dynamical system model M k from time t k−1 to time t k . In particular, for nonlinear dynamical systems M k that are Lipschitz continuous with respect to their initial states, we provide deterministic estimates for the development of the error ‖e k ‖ ≔ ‖x (a) k − x (t) k ‖ between the estimated state x (a) and the true state x (t) over time. Clearly, observation error of size δ > 0 leads to an estimation error in every assimilation step. These errors can accumulate, if they are not (a) controlled in the reconstruction and (b) damped by the dynamical system M k under consideration. A data assimilation method is called stable, if the error in the estimate is bounded in time by some constant C. The key task of this work is to provide estimates for the error ‖e k ‖, depending on the size δ of the observation error, the reconstruction operator R α , the observation operator H and the Lipschitz constants K (1) and K (2) on the lower and higher modes of M k controlling the damping behaviour of the dynamics. We show that systems can be stabilized by choosing α sufficiently small, but the bound C will then depend on the data error δ in the form c‖R α ‖δ with some constant c. Since ‖R α ‖ → ∞ for α → 0, the constant might be large. Numerical examples for this behaviour in the nonlinear case are provided using a (low-dimensional) Lorenz ‘63 system. (paper)

  6. Ecological Assimilation of Land and Climate Observations - the EALCO model

    Science.gov (United States)

    Wang, S.; Zhang, Y.; Trishchenko, A.

    2004-05-01

    Ecosystems are intrinsically dynamic and interact with climate at a highly integrated level. Climate variables are the main driving factors in controlling the ecosystem physical, physiological, and biogeochemical processes including energy balance, water balance, photosynthesis, respiration, and nutrient cycling. On the other hand, ecosystems function as an integrity and feedback on the climate system through their control on surface radiation balance, energy partitioning, and greenhouse gases exchange. To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at national scale, it is imperative that ecosystem models have the capability of assimilating the large scale geospatial information including satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes. EALCO includes the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS database. It provides both national and local scale model outputs for ecosystem responses to climate change including radiation and energy balances, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, and nutrient (N) cycling. These results form the foundation for the assessment of climate change impact on ecosystems, their services, and adaptation options. In this poster, the main algorithms for the radiation, energy, water, carbon, and nitrogen simulations were diagrammed. Sample input data layers at Canada national scale were illustrated. Model outputs including the Canada wide spatial distributions of net

  7. An improved state-parameter analysis of ecosystem models using data assimilation

    Science.gov (United States)

    Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.

    2008-01-01

    Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the

  8. A New Methodology for the Extension of the Impact of Data Assimilation on Ocean Wave Prediction

    Science.gov (United States)

    2008-07-01

    Assimilation method The analysis fields used were corrected by an assimilation method developed at the Norwegian Meteorological Insti- tute ( Breivik and Reistad...523–535 525 becomes equal to the solution obtained by optimal interpolation (see Bratseth 1986 and Breivik and Reistad 1994). The iterations begin with...updated accordingly. A more detailed description of the assimilation method is given in Breivik and Reistad (1994). 2.3 Kolmogorov–Zurbenko filters

  9. Variational Data Assimilative Modeling of the Gulf of Maine Circulation in Spring and Summer 2010

    OpenAIRE

    Li, Yizhen; He, Ruoying; Chen, Ke; McGillicuddy, Dennis J.

    2015-01-01

    A data assimilative ocean circulation model is used to hindcast the Gulf of Maine (GOM) circulation in spring and summer 2010. Using the recently developed incremental strong constraint 4D Variational data assimilation algorithm, the model assimilates satellite sea surface temperature and in situ temperature and salinity profiles measured by expendable bathythermograph, Argo floats, and shipboard CTD casts. Validation against independent observations shows that the model skill is significantl...

  10. Employment and Wage Assimilation of Male First-generation immigrants in Denmark

    DEFF Research Database (Denmark)

    Husted, Leif; Nielsen, Helena Skyt; Rosholm, Michael

    2001-01-01

    Labour market assimilation of Danish first generation male immigrants is analysed based on two panel data sets covering the population of immigrants and 10% of the Danish population during 1984-1995. Wages and employment probabilities are estimated jointly in a random effects model which corrects...... for unobserved cohort and individual effects and panel selectivity due to missing wage information. The results show that immigrants assimilate partially to Danes, but the assimilation process differs between refugees and non-refugees....

  11. Assimilation of water and dietary ions by the gastrointestinal tract during digestion in seawater-acclimated rainbow trout.

    Science.gov (United States)

    Bucking, Carol; Fitzpatrick, John L; Nadella, Sunita R; McGaw, Iain J; Wood, Chris M

    2011-07-01

    Recent studies focusing on the consequences of feeding for ion and water balance in freshwater fish have revealed the need for similar comparative studies in seawater fish. A detailed time course sampling of gastrointestinal (GI) tract contents following the ingestion of a single meal of a commercial diet revealed the assimilation of both water and dietary ions (Na(+), Cl(-), K(+), Ca(2+), Mg(2+)) along the GI tract of seawater-acclimated rainbow trout (Oncorhynchus mykiss) which had been fasted for 1 week. Consumption of the meal did not change the drinking rate. There was a large secretion of fluid into the anterior intestine and caecae (presumably bile and/or pancreatic secretions). As a result, net assimilation (63%) of the ingested water along the GI tract was lower than generally reported for fasted trout. Mg(2+) was neither secreted into nor absorbed from the GI tract on a net basis. Only K(+) (93% assimilated) and Ca(2+) (43% assimilated) were absorbed in amounts in excess of those provided by ingested seawater, suggesting that dietary sources of K(+) and Ca(2+) may be important to seawater teleosts. The oesophagus-stomach served as a major site of absorption for Na(+), Cl(-), K(+), Ca(2+), and Mg(2+), and the anterior intestine and caecae as a major site of net secretion for all of these ions, except Cl(-). Despite large absorptive fluxes of these ions, the ionic composition of the plasma was maintained during the digestion of the meal. The results of the present study were compared with previous work on freshwater-acclimated rainbow trout, highlighting some important differences, but also several similarities on the assimilation of water and ions along the gastrointestinal tract during digestion. This study highlights the complicated array of ion and water transport that occurs in the intestine during digestion while revealing the importance of dietary K(+) and Ca(2+) to seawater-acclimated rainbow trout. Additionally, this study reveals that digestion

  12. Assimilation of passive and active CCI soil moisture products into hydrological modelling: an intercomparison study in Europe

    Science.gov (United States)

    Maggioni, V.; Massari, C.; Camici, S.; Brocca, L.; Marchesini, I.

    2017-12-01

    Soil moisture (SM) is a key variable in rainfall-runoff partitioning since it acts on the main hydrological processes taking part within a catchment. Modeling SM is often a difficult task due to its large variability at different temporal and spatial scales. Ground soil moisture measurements are a valuable tool for improving runoff prediction but are often limited and suffer from spatial representativeness issues. Remotely sensed observations offer a new source of data able to cope the latter issues thus opening new possibilities for improving flood simulations worldwide. Today, several different SM products are available at increased accuracy with respect to the past. Some interesting products are those derived from the Climate Change Initiative (CCI) which offer the most complete and most consistent global SM data record based on active and passive microwave sensors.Thanks to the combination of multiple sensors within an active, a passive and an active+passive products, the CCI SM is expected to provide a significant benefit for the improvement of rainfall-runoff simulations through data assimilation. However, previous studies have shown that the success of the assimilation is not only related to the accuracy of the observations but also to the specific climate and the catchment physical and hydrological characteristics as well as to many necessary choices related to the assimilation technique. These choices along with the type of SM observations (i.e. passive or active) might play an important role for the success or the failure of the assimilation exercise which is not still clear. In this study, based on a large dataset of catchments covering large part of the Europe, we assimilated satellite SM observations from the passive and the active CCI SM products into Modello Idrologico Semiditribuito in Continuo (MISDc, Brocca et al. 2011). Rainfall and temperature data were collected from the European Climate Assessment & Dataset (E-OBS) while discharge data were

  13. Distribution of carbon-14 assimilated by wheat awns

    International Nuclear Information System (INIS)

    Olugbemi, L.B.

    1978-01-01

    The pattern of distribution of carbon assimilated by awns was investigated in two lines of Triticum aestivum. Single awns on basal florets of spikelets in the central part of the ear were dosed with 14 C0 2 . Five days after dosing, 99% of the carbon-14 recovered was in the spikelet bearing the awn. Of the carbon-14 exported from the treated awn 57% went to the grain of the first floret, 1% to the second, 28% to the third and 7% to the fourth. (author)

  14. Testing the Data Assimilation Capability of the Profiler Virtual Module

    Science.gov (United States)

    2016-02-01

    plane between a given grid point and the obs point, and R is the maximum distance over which an obs has influence. In the PVM WRF, the maximum error...ensemble Kalman filter approach to data assimilation in WRF/ DART . Q.J.R Meterorol. Soc. 2012:DOI:10.1002/qj.1939. Liu C, Xiao Q, Wang B. An ensemble...Tinklepaugh K, Dobek J. NWP goes to war . . . , Preprints. Paper presented at: 22nd Conference on Weather Analysis and Forecasting/18th Conference on

  15. A THEORETICAL STUDY ON SIMPLIFIED KALMAN FILTER IN DATA ASSIMILATION

    Institute of Scientific and Technical Information of China (English)

    Ma Zhai-pu; Huang Da-ji; Zhang Ben-zhao

    2003-01-01

    In this paper, we put forward a new method to reduce the calculation amount of the gain matrix of Kalman filter in data assimilation. We rewrite the vector describing the total state variables with two vectors whose dimensions are small and thus obtain the main parts and the trivial parts of the state variables. On the basis of the rewrittten formula, we not only develop a reduced Kalman filter scheme, but also obtain the transition equations about truncation errors, with which the validity of the main parts acting for the total state variables can be evaluated quantitatively. The error transition equations thus offer an indirect testimony to the rationality of the main parts.

  16. Integrating biogeochemistry and ecology into ocean data assimilation systems

    DEFF Research Database (Denmark)

    Brasseur, Pierre; Gruber, Nicolas; Barciela, Rosa

    2009-01-01

    that are not yet considered essential, such as upper-ocean vertical fluxes that are critically important to biological activity. Further, the observing systems will need to be expanded in terms of in situ platforms (with intensified deployments of sensors for O-2 and chlorophyll, and inclusion of new sensors...... for nutrients, zooplankton, micronekton biomass, and others), satellite missions (e.g., hyperspectral instruments for ocean color, lidar systems for mixed-layer depths, and wide-swath altimeters for coastal sea level), and improved methods to assimilate these new measurements....

  17. Meteorological data assimilation for real-time emergency response

    International Nuclear Information System (INIS)

    Sugiyama, G.; Chan, S.T.

    1996-11-01

    The US Department of Energy's Atmospheric Release Advisory Capability (ARAC) provides real-time dose assessments of airborne pollutant releases. Diverse data assimilation techniques are required to meet the needs of a new generation of ARAC models and to take advantage of the rapidly expanding availability of meteorological data. We are developing a hierarchy of algorithms to provide gridded meteorological fields which can be used to drive dispersion codes or to provide initial fields for mesoscale models. Data to be processed include winds, temperature, moisture, and turbulence

  18. ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS

    Energy Technology Data Exchange (ETDEWEB)

    Chiswell, S.; Buckley, R.

    2009-01-15

    During the year 2008, the United States National Weather Service (NWS) completed an eight fold increase in sampling capability for weather radars to 250 m resolution. This increase is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current NWS operational model domains utilize grid spacing an order of magnitude larger than the radar data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of radar reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution was investigated under a Laboratory Directed Research and Development (LDRD) 'quick hit' grant to determine the impact of improved data resolution on model predictions with specific initial proof of concept application to daily Savannah River Site operations and emergency response. Development of software to process NWS radar reflectivity and radial velocity data was undertaken for assimilation of observations into numerical models. Data values within the radar data volume undergo automated quality control (QC) analysis routines developed in support of this project to eliminate empty/missing data points, decrease anomalous propagation values, and determine error thresholds by utilizing the calculated variances among data values. The Weather Research and Forecasting model (WRF) three dimensional variational data assimilation package (WRF-3DVAR) was used to incorporate the QC'ed radar data into input and boundary conditions. The lack of observational data in the vicinity of SRS available to NWS operational models signifies an important data void where radar observations can provide significant input. These observations greatly enhance the knowledge of storm structures and the environmental conditions which influence their development. As the increase in computational power and availability has

  19. Studies on the translocation and distribution characteristics of carbon assimilates in blackberry

    International Nuclear Information System (INIS)

    Wang Shuyu; Liu Hongjia

    1990-08-01

    The translocation and distribution characteristics of carbon assimilates were studied with the method of 14 CO 2 feeding. The results indicated that there were different translocation and distribution characteristics of carbon assimilates among the upper, middle and lower leaves in a shoot during annual cycle. Taking away leaves, sun-shading and drought could raise the exporting ratio of carbon assimilates in the feeding leaves and could change the distributing model of the tree. Most of the carbon assimilates were translocated to basic born branch after sun-shading and drought

  20. Study on transference of assimilate in filling summer maize using isotope 14C

    International Nuclear Information System (INIS)

    Fan Zhongxue; Wang Pu; Liang Zhenxing

    2001-01-01

    The dynamic of assimilate transference from the ear leaf to grain during effective grain filling stage was studied by 14 C tracer. The results showed that the rates of assimilate transportation out of the ear leaf and transference to grain changed very fast. The rate was very big in 4 - 6 hour just after 14 C feeding and decreased with time. The grain which accumulated 14 C-assimilate in a higher rate and got much more 14 C-assimilate in fixed time could develop into larger size

  1. Improving wind energy forecasts using an Ensemble Kalman Filter data assimilation technique in a fully coupled hydrologic and atmospheric model

    Science.gov (United States)

    Williams, J. L.; Maxwell, R. M.; Delle Monache, L.

    2012-12-01

    Wind power is rapidly gaining prominence as a major source of renewable energy. Harnessing this promising energy source is challenging because of the chaotic nature of wind and its propensity to change speed and direction over short time scales. Accurate forecasting tools are critical to support the integration of wind energy into power grids and to maximize its impact on renewable energy portfolios. Numerous studies have shown that soil moisture distribution and land surface vegetative processes profoundly influence atmospheric boundary layer development and weather processes on local and regional scales. Using the PF.WRF model, a fully-coupled hydrologic and atmospheric model employing the ParFlow hydrologic model with the Weather Research and Forecasting model coupled via mass and energy fluxes across the land surface, we have explored the connections between the land surface and the atmosphere in terms of land surface energy flux partitioning and coupled variable fields including hydraulic conductivity, soil moisture and wind speed, and demonstrated that reductions in uncertainty in these coupled fields propagate through the hydrologic and atmospheric system. We have adapted the Data Assimilation Research Testbed (DART), an implementation of the robust Ensemble Kalman Filter data assimilation algorithm, to expand our capability to nudge forecasts produced with the PF.WRF model using observational data. Using a semi-idealized simulation domain, we examine the effects of assimilating observations of variables such as wind speed and temperature collected in the atmosphere, and land surface and subsurface observations such as soil moisture on the quality of forecast outputs. The sensitivities we find in this study will enable further studies to optimize observation collection to maximize the utility of the PF.WRF-DART forecasting system.

  2. 2008 Co2 Assimilation in Plants: Genome to Biome Gordon Research Conference - August 17-22

    Energy Technology Data Exchange (ETDEWEB)

    James V. Maroney

    2009-08-12

    Formerly entitled 'CO2 Fixation and Metabolism in Green Plants', this long-standing Gordon Research Conference has been held on a triennial basis since 1976. In 1990 the participants decided to alternate between sites in the U.S. and outside the U.S. The 2005 conference was held in Europe at the Centre Paul Langevin in Aussois, France, so the 2008 conference returns to a U.S. site - the University of New England in Biddeford, Maine. The 2008 conference covers basic plant research related to photosynthesis and the subsequent regulation and engineering of carbon assimilation. Approaches that range from post-genomic technologies and systems biology, through to fundamental biochemistry, physiology and molecular biology are integrated within ecological and agronomic contexts. As such, the meeting provides the rare opportunity of a single venue for discussing all aspects of the 'carbon-side' of photosynthesis - from genome to biome. The 2008 conference will include an emphasis on the central role of carbon assimilation by plants for developing new sources of bioenergy and for achieving a carbon-neutral planet. A special characteristic of this conference is its 'intimacy' with approximately 110 conferees, ranging from beginning graduate students and postdoctoral associates to leading senior plant scientists, engaged in open and forward-thinking discussions in an informal, friendly setting. With extended time devoted to discussion, and the encouragement to challenge dogma, it is unlike other meetings in the U.S. or abroad. Another novel feature of the conference is a session devoted to the latest 'hot off the press' findings by both established and early career scientists, picked from the abstracts. Together with an expanded poster discussion in the evening sessions, this session provides an opportunity for early career scientists to present interesting new data and to 'test drive' hypotheses in a collegial atmosphere.

  3. Geotechnical parameter spatial distribution stochastic analysis based on multi-precision information assimilation

    Science.gov (United States)

    Wang, C.; Rubin, Y.

    2014-12-01

    Spatial distribution of important geotechnical parameter named compression modulus Es contributes considerably to the understanding of the underlying geological processes and the adequate assessment of the Es mechanics effects for differential settlement of large continuous structure foundation. These analyses should be derived using an assimilating approach that combines in-situ static cone penetration test (CPT) with borehole experiments. To achieve such a task, the Es distribution of stratum of silty clay in region A of China Expo Center (Shanghai) is studied using the Bayesian-maximum entropy method. This method integrates rigorously and efficiently multi-precision of different geotechnical investigations and sources of uncertainty. Single CPT samplings were modeled as a rational probability density curve by maximum entropy theory. Spatial prior multivariate probability density function (PDF) and likelihood PDF of the CPT positions were built by borehole experiments and the potential value of the prediction point, then, preceding numerical integration on the CPT probability density curves, the posterior probability density curve of the prediction point would be calculated by the Bayesian reverse interpolation framework. The results were compared between Gaussian Sequential Stochastic Simulation and Bayesian methods. The differences were also discussed between single CPT samplings of normal distribution and simulated probability density curve based on maximum entropy theory. It is shown that the study of Es spatial distributions can be improved by properly incorporating CPT sampling variation into interpolation process, whereas more informative estimations are generated by considering CPT Uncertainty for the estimation points. Calculation illustrates the significance of stochastic Es characterization in a stratum, and identifies limitations associated with inadequate geostatistical interpolation techniques. This characterization results will provide a multi

  4. Comparison of different incremental analysis update schemes in a realistic assimilation system with Ensemble Kalman Filter

    Science.gov (United States)

    Yan, Y.; Barth, A.; Beckers, J. M.; Brankart, J. M.; Brasseur, P.; Candille, G.

    2017-07-01

    In this paper, three incremental analysis update schemes (IAU 0, IAU 50 and IAU 100) are compared in the same assimilation experiments with a realistic eddy permitting primitive equation model of the North Atlantic Ocean using the Ensemble Kalman Filter. The difference between the three IAU schemes lies on the position of the increment update window. The relevance of each IAU scheme is evaluated through analyses on both thermohaline and dynamical variables. The validation of the assimilation results is performed according to both deterministic and probabilistic metrics against different sources of observations. For deterministic validation, the ensemble mean and the ensemble spread are compared to the observations. For probabilistic validation, the continuous ranked probability score (CRPS) is used to evaluate the ensemble forecast system according to reliability and resolution. The reliability is further decomposed into bias and dispersion by the reduced centred random variable (RCRV) score. The obtained results show that 1) the IAU 50 scheme has the same performance as the IAU 100 scheme 2) the IAU 50/100 schemes outperform the IAU 0 scheme in error covariance propagation for thermohaline variables in relatively stable region, while the IAU 0 scheme outperforms the IAU 50/100 schemes in dynamical variables estimation in dynamically active region 3) in case with sufficient number of observations and good error specification, the impact of IAU schemes is negligible. The differences between the IAU 0 scheme and the IAU 50/100 schemes are mainly due to different model integration time and different instability (density inversion, large vertical velocity, etc.) induced by the increment update. The longer model integration time with the IAU 50/100 schemes, especially the free model integration, on one hand, allows for better re-establishment of the equilibrium model state, on the other hand, smooths the strong gradients in dynamically active region.

  5. Assimilation of Polder aerosol optical thickness into LMD2-Inca model in order to study aerosol-climate interactions; Etude des interactions entre aerosols et climat: assimilation des observations spatiales de Polder dans LMDz-Inca

    Energy Technology Data Exchange (ETDEWEB)

    Generoso, S.

    2004-12-15

    Aerosols influence the Earth radiative budget both through their direct (scattering and absorption of solar radiation) and indirect (impacts on cloud microphysics) effects. The anthropogenic perturbation due to aerosol emissions is of the same order of magnitude than the one due to greenhouse gases, but less well known. To improve our knowledge, we need to better know aerosol spatial and temporal distributions. Indeed, aerosol modeling still suffers from large uncertainties in sources and transport, while satellite observations are incomplete (no detection in the presence of clouds, no information on the vertical distribution or on the chemical nature). Moreover, field campaigns are localized in space and time. This study aims to reduce uncertainties in aerosol distributions, developing assimilation of satellite data into a chemical transport model. The basic idea is to combine information obtained from spatial observation (optical thickness) and modeling studies (aerosol types, vertical distribution). In this study, we assimilate data from the POLDER space-borne instrument into the LMDz-INCA model. The results show the advantage of merging information from different sources. In many regions, the method reduces uncertainties on aerosol distribution (reduction of RMS error). An application of the method to the study of aerosol impact on cloud microphysics is shown. (author)

  6. Accounting for the Assimilative Capacity of Water Systems in Scotland

    Directory of Open Access Journals (Sweden)

    Paula Novo

    2017-07-01

    Full Text Available A key methodological challenge in understanding the relationship between the economy and the underlying ecosystem base resides in how to account for the ecosystem’s degradation and the decline of associated ecosystem services. In this study, we use information on nutrients and metals concentrations from the Environmental Change Network (ECN database and the Scottish Environment Protection Agency (SEPA for the period 2000–2010 in order to assess the assimilation capacity of water systems. The research covers five upstream sites and 17 downstream sites in northeast Scotland. Our results highlight the relevance of considering a number of pollutants, and suggest that elements such as arsenic, lead and mercury can pose a threat to ecosystems’ sustainability and health. However, little research has been done in terms of their assimilation capacity and their impact on grey water footprint assessments. In addition, the results indicate that background conditions might be relevant when performing sustainability analysis at different spatial scales. The study also poses relevant questions in relation to land management approaches versus traditional ‘end-of-pipe’ water treatment approaches, and the definition of maximum and background concentrations. In this regard, further studies will be required to understand the trade-offs between different ecosystem services depending on how these concentrations are defined.

  7. A storm-time plasmasphere evolution study using data assimilation

    Science.gov (United States)

    Nikoukar, R.; Bust, G. S.; Bishop, R. L.; Coster, A. J.; Lemon, C.; Turner, D. L.; Roeder, J. L.

    2017-12-01

    In this work, we study the evolution of the Earth's plasmasphere during geomagnetic active periods using the Plasmasphere Data Assimilation (PDA) model. The total electron content (TEC) measurements from an extensive network of global ground-based GPS receivers as well as GPS receivers on-board Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) satellites and Communications/Navigation Outage Forecasting System (C/NOFS) satellite are ingested into the model. Global Core Plasma model, which is an empirical plasmasphere model, is utilized as the background model. Based on the 3D-VAR optimization, the PDA assimilative model benefits from incorporation of regularization techniques to prevent non-physical altitudinal variation in density estimates due to the limited-angle observational geometry. This work focuses on the plasmapause location, plasmasphere erosion time scales and refilling rates during the main and recovery phases of geomagnetic storms as estimated from the PDA 3-dimensional global maps of electron density in the ionosphere/plasmasphere. The comparison between the PDA results with in-situ density measurements from THEMIS and Van Allen Probes, and the RCM-E first-principle model will be also presented.

  8. A Microwave Radiance Assimilation Study for a Tundra Snowpack

    Science.gov (United States)

    Kim, Edward; Durand, Michael; Margulis, Steve; England, Anthony

    2010-01-01

    Recent studies have begun exploring the assimilation of microwave radiances for the modeling and retrieval of snow properties. At a point scale, and for short durations (i week), radiance assimilation (RA) results are encouraging. However, in order to determine how practical RA might be for snow retrievals when applied over longer durations, larger spatial scales, and/or different snow types, we must expand the scope of the tests. In this paper we use coincident microwave radiance measurements and station data from a tundra site on the North Slope of Alaska. The field data are from the 3rd Radio-brightness Energy Balance Experiment (REBEX-3) carried out in 1994-95 by the University of Michigan. This dataset will provide a test of RA over months instead of one week, and for a very different type of snow than previous snow RA studies. We will address the following questions: flow well can a snowpack physical model (SM), forced with local weather, match measured conditions for a tundra snowpack?; How well can a microwave emission model, driven by the snowpack model, match measured microwave brightnesses for a tundra snowpack?; How well does RA increase or decrease the fidelity of estimates of snow depth and temperatures for a tundra snowpack?

  9. Dynamic calibration of agent-based models using data assimilation.

    Science.gov (United States)

    Ward, Jonathan A; Evans, Andrew J; Malleson, Nicolas S

    2016-04-01

    A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it. Second, we want to illustrate to data assimilation experts the value of using such methods in the context of ABMs of complex social systems and the new challenges these types of model present. We work towards these goals within the context of a simple question of practical value: how many people are there in Leeds (or any other major city) right now? We build a hierarchy of exemplar models that we use to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds.

  10. The evolution of menstruation: A new model for genetic assimilation

    Science.gov (United States)

    Emera, D.; Romero, R.; Wagner, G.

    2012-01-01

    Why do humans menstruate while most mammals do not? Here, we present our answer to this long-debated question, arguing that (i) menstruation occurs as a mechanistic consequence of hormone-induced differentiation of the endometrium (referred to as spontaneous decidualization, or SD); (ii) SD evolved because of maternal-fetal conflict; and (iii) SD evolved by genetic assimilation of the decidualization reaction, which is induced by the fetus in non-menstruating species. The idea that menstruation occurs as a consequence of SD has been proposed in the past, but here we present a novel hypothesis on how SD evolved. We argue that decidualization became genetically stabilized in menstruating lineages, allowing females to prepare for pregnancy without any signal from the fetus. We present three models for the evolution of SD by genetic assimilation, based on recent advances in our understanding of the mechanisms of endometrial differentiation and implantation. Testing these models will ultimately shed light on the evolutionary significance of menstruation, as well as on the etiology of human reproductive disorders like endometriosis and recurrent pregnancy loss. PMID:22057551

  11. Selenium uptake, translocation, assimilation and metabolic fate in plants.

    Science.gov (United States)

    Sors, T G; Ellis, D R; Salt, D E

    2005-12-01

    The chemical and physical resemblance between selenium (Se) and sulfur (S) establishes that both these elements share common metabolic pathways in plants. The presence of isologous Se and S compounds indicates that these elements compete in biochemical processes that affect uptake, translocation and assimilation throughout plant development. Yet, minor but crucial differences in reactivity and other metabolic interactions infer that some biochemical processes involving Se may be excluded from those relating to S. This review examines the current understanding of physiological and biochemical relationships between S and Se metabolism by highlighting their similarities and differences in relation to uptake, transport and assimilation pathways as observed in Se hyperaccumulator and non-accumulator plant species. The exploitation of genetic resources used in bioengineering strategies of plants is illuminating the function of sulfate transporters and key enzymes of the S assimilatory pathway in relation to Se accumulation and final metabolic fate. These strategies are providing the basic framework by which to resolve questions relating to the essentiality of Se in plants and the mechanisms utilized by Se hyperaccumulators to circumvent toxicity. In addition, such approaches may assist in the future application of genetically engineered Se accumulating plants for environmental renewal and human health objectives.

  12. Estimating the ecology of extinct species with paleoecological data assimilation

    Science.gov (United States)

    Raiho, A.; McLachlan, J. S.; Dietze, M.

    2017-12-01

    In order to understand long term, unobservable ecosystem processes, ecologists must use both paleoecoloigcal data and ecosystem models. Models parameterize species competitive interactions using modern data. But, modern ecological or physiological observations are not available for extinct species, making it difficult for models to conceptualize their ecology. For instance, American chestnut (Castanea dentata), who played a large role in forests of northeastern US, was decimated by disease to virtual extinction. Since chestnut's demise, defining its ecology has been controversial. Models typically assume that chestnut's ecology was very similar to oak; They parameterize chestnut like oak species. These assumptions are drawn from paleoecological data, but these data are often reported without uncertainty. Since the paleoecological data are often reported without uncertainty, paleoecological data has never been directly incorporated with ecosystem models. We developed a Bayesian statistical model to estimate fractional composition from paleoecological data with uncertainty. Then, we assimilated this data product into an ecosystem model for long term forest succession using a generalized ensemble adjustment filter to determine which species demographic parameters lead to changes in species composition over the last 2,000 years at Harvard Forest. We found that chestnut was strongly negatively correlated with white pine (Pinus strobus) and red oak (Quercus rubra) in the process covariance matrix, suggesting a strong competitive interaction that is not currently understood by models for forest succession. These findings provide support for utilizing a data assimilation framework to ecologically interpret paleoecological data or data products to learn about the ecology of extinct species.

  13. Four-Dimensional Data Assimilation Using the Adjoint Method

    Science.gov (United States)

    Bao, Jian-Wen

    The calculus of variations is used to confirm that variational four-dimensional data assimilation (FDDA) using the adjoint method can be implemented when the numerical model equations have a finite number of first-order discontinuous points. These points represent the on/off switches associated with physical processes, for which the Jacobian matrix of the model equation does not exist. Numerical evidence suggests that, in some situations when the adjoint method is used for FDDA, the temperature field retrieved using horizontal wind data is numerically not unique. A physical interpretation of this type of non-uniqueness of the retrieval is proposed in terms of energetics. The adjoint equations of a numerical model can also be used for model-parameter estimation. A general computational procedure is developed to determine the size and distribution of any internal model parameter. The procedure is then applied to a one-dimensional shallow -fluid model in the context of analysis-nudging FDDA: the weighting coefficients used by the Newtonian nudging technique are determined. The sensitivity of these nudging coefficients to the optimal objectives and constraints is investigated. Experiments of FDDA using the adjoint method are conducted using the dry version of the hydrostatic Penn State/NCAR mesoscale model (MM4) and its adjoint. The minimization procedure converges and the initialization experiment is successful. Temperature-retrieval experiments involving an assimilation of the horizontal wind are also carried out using the adjoint of MM4.

  14. Rhenium-188 - advantages and clinical potential for use of a readily available, cost effective therapeutic radioisotope for applications in nuclear medicine, oncology and interventional cardiology

    International Nuclear Information System (INIS)

    Knapp, F.F. jr.

    2002-01-01

    Full text: Carrier-free rhenium-188 (Re-188) is readily available from the alumina-based tungsten-188/rhenium-188 generator system and has many attractive properties for a wide variety of therapeutic applications. The 16.9 h half-life, emission of the 2.2 MeV beta particle and versatile chemistry make Re-188 an important candidate for applications where high radiation penetration is required. In addition, emission of a gamma photon (155 KeV, 15 %) permits evaluation of biodistribution, pharmacokinetics and dosimetry estimates. The long physical half-life of the tungsten-188 (W-188) parent (t 1/2 69 days) and consistent generator performance - with high Re-188 yields and low W-188 parent breakthrough - result in an indefinite shelf-life of several months, dependent on the levels of Re-188 required. Post generator elution in-growth of 62 % of Re-188 after 24 hours in combination with high elution yields (75-85 %) result in 50 % daily yields of the maximal Re-188 available. In addition to research being conducted for the development of a wide variety of new therapeutic radiopharmaceuticals and devices, Re-188 is also being evaluated in physician-sponsored clinical trials in over 15 countries, with applications in nuclear medicine, oncology and interventional cardiology. One major current clinical application involves post-angiographic treatment of arterial segments following PTCA using Re-188 perrhenate or MAG3 liquid-filled balloons as an effective and cost-effective approach for inhibition of the hyperplastic response to vessel damage, which delivers uniform dose to the vessel wall. Re-188-HEDP is being used for palliation of metastatic bone pain palliation. This agent is readily prepared from a simple 'kit' and provides pain palliation as effective as other commercially available agents. The use of the Re-188-labeled Anti-NCA-95 antibody (BW 50/183; CD66 a,b,c,e) in conjunction which external beam irradiation and chemotherapy is an effective method for

  15. Potential of an ensemble Kalman smoother for stratospheric chemical-dynamical data assimilation

    Directory of Open Access Journals (Sweden)

    Thomas Milewski

    2013-02-01

    Full Text Available A new stratospheric ensemble Kalman smoother (EnKS system is introduced, and the potential of assimilating posterior stratospheric observations to better constrain the whole model state at analysis time is investigated. A set of idealised perfect-model Observation System Simulation Experiments (OSSE assimilating synthetic limb-sounding temperature or ozone retrievals are performed with a chemistry–climate model. The impact during the analysis step is characterised in terms of the root mean square error reduction between the forecast state and the analysis state. The performances of (1 a fixed-lag EnKS assimilating observations spread over 48 hours and (2 an ensemble Kalman Filter (EnKF assimilating a denser network of observations are compared with a reference EnKF. The ozone assimilation with EnKS shows a significant additional reduction of analysis error of the order of 10% for dynamical and chemical variables in the extratropical upper troposphere lower stratosphere (UTLS and Polar Vortex regions when compared to the reference EnKF. This reduction has similar magnitude to the one achieved by the denser-network EnKF assimilation. Similarly, the temperature assimilation with EnKS significantly decreases the error in the UTLS for the wind variables like the denser-network EnKF assimilation. However, the temperature assimilation with EnKS has little or no significant impact on the temperature and ozone analyses, whereas the denser-network EnKF shows improvement with respect to the reference EnKF. The different analysis impacts from the assimilation of current and posterior ozone observations indicate the capacity of time-lagged background-error covariances to represent temporal interactions up to 48 hours between variables during the ensemble data assimilation analysis step, and the possibility to use posterior observations whenever additional current observations are unavailable. The possible application of the EnKS for reanalyses is

  16. Delaying chloroplast turnover increases water-deficit stress tolerance through the enhancement of nitrogen assimilation in rice.

    Science.gov (United States)

    Sade, Nir; Umnajkitikorn, Kamolchanok; Rubio Wilhelmi, Maria Del Mar; Wright, Matthew; Wang, Songhu; Blumwald, Eduardo

    2018-02-12

    Abiotic stress-induced senescence in crops is a process particularly affecting the photosynthetic apparatus, decreasing photosynthetic activity and inducing chloroplast degradation. A pathway for stress-induced chloroplast degradation that involves the CHLOROPLAST VESICULATION (CV) gene was characterized in rice (Oryza sativa) plants. OsCV expression was up-regulated with the age of the plants and when plants were exposed to water-deficit conditions. The down-regulation of OsCV expression contributed to the maintenance of the chloroplast integrity under stress. OsCV-silenced plants displayed enhanced source fitness (i.e. carbon and nitrogen assimilation) and photorespiration, leading to water-deficit stress tolerance. Co-immunoprecipitation, intracellular co-localization, and bimolecular fluorescence demonstrated the in vivo interaction between OsCV and chloroplastic glutamine synthetase (OsGS2), affecting source-sink relationships of the plants under stress. Our results would indicate that the OsCV-mediated chloroplast degradation pathway is involved in the regulation of nitrogen assimilation during stress-induced plant senescence. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  17. Improving volcanic ash predictions with the HYSPLIT dispersion model by assimilating MODIS satellite retrievals

    Science.gov (United States)

    Chai, Tianfeng; Crawford, Alice; Stunder, Barbara; Pavolonis, Michael J.; Draxler, Roland; Stein, Ariel

    2017-02-01

    beneficial for the current case. In addition, extra constraints on the source terms can be given by explicitly enforcing no-ash for the atmosphere columns above or below the observed ash cloud top height. However, in this case such extra constraints are not helpful for the inverse modeling. It is also found that simultaneously assimilating observations at different times produces better hindcasts than only assimilating the most recent observations.

  18. Enhanced Soil Moisture Initialization Using Blended Soil Moisture Product and Regional Optimization of LSM-RTM Coupled Land Data Assimilation System.

    Science.gov (United States)

    Nair, A. S.; Indu, J.

    2017-12-01

    Prediction of soil moisture dynamics is high priority research challenge because of the complex land-atmosphere interaction processes. Soil moisture (SM) plays a decisive role in governing water and energy balance of the terrestrial system. An accurate SM estimate is imperative for hydrological and weather prediction models. Though SM estimates are available from microwave remote sensing and land surface model (LSM) simulations, it is affected by uncertainties from several sources during estimation. Past studies have generally focused on land data assimilation (DA) for improving LSM predictions by assimilating soil moisture from single satellite sensor. This approach is limited by the large time gap between two consequent soil moisture observations due to satellite repeat cycle of more than three days at the equator. To overcome this, in the present study, we have performed DA using ensemble products from the soil moisture operational product system (SMOPS) blended soil moisture retrievals from different satellite sensors into Noah LSM. Before the assimilation period, the Noah LSM is initialized by cycling through seven multiple loops from 2008 to 2010 forcing with Global data assimilation system (GDAS) data over the Indian subcontinent. We assimilated SMOPS into Noah LSM for a period of two years from 2010 to 2011 using Ensemble Kalman Filter within NASA's land information system (LIS) framework. Results show that DA has improved Noah LSM prediction with a high correlation of 0.96 and low root mean square difference of 0.0303 m3/m3 (figure 1a). Further, this study has also investigated the notion of assimilating microwave brightness temperature (Tb) as a proxy for SM estimates owing to the close proximity of Tb and SM. Preliminary sensitivity analysis show a strong need for regional parameterization of radiative transfer models (RTMs) to improve Tb simulation. Towards this goal, we have optimized the forward RTM using swarm optimization technique for direct Tb

  19. Short term memory may be the depletion of the readily releasable pool of presynaptic neurotransmitter vesicles of a metastable long term memory trace pattern.

    Science.gov (United States)

    Tarnow, Eugen

    2009-09-01

    The Tagging/Retagging model of short term memory was introduced earlier (Tarnow in Cogn Neurodyn 2(4):347-353, 2008) to explain the linear relationship between response time and correct response probability for word recall and recognition: At the initial stimulus presentation the words displayed tag the corresponding long term memory locations. The tagging process is linear in time and takes about one second to reach a tagging level of 100%. After stimulus presentation the tagging level decays logarithmically with time to 50% after 14 s and to 20% after 220 s. If a probe word is reintroduced the tagging level has to return to 100% for the word to be properly identified, which leads to a delay in response time. This delay is proportional to the tagging loss. The tagging level is directly related to the probability of correct word recall and recognition. Evidence presented suggests that the tagging level is the level of depletion of the Readily Releasable Pool (RRP) of neurotransmitter vesicles at presynaptic terminals. The evidence includes the initial linear relationship between tagging level and time as well as the subsequent logarithmic decay of the tagging level. The activation of a short term memory may thus be the depletion of RRP (exocytosis) and short term memory decay may be the ensuing recycling of the neurotransmitter vesicles (endocytosis). The pattern of depleted presynaptic terminals corresponds to the long term memory trace.

  20. Assimilation of Real-Time Satellite And Human Sensor Networks for Modeling Natural Disasters

    Science.gov (United States)

    Aulov, O.; Halem, M.; Lary, D. J.

    2011-12-01

    We describe the development of underlying technologies needed to address the merging of a web of real time satellite sensor Web (SSW) and Human Sensor Web (HSW) needed to augment the US response to extreme events. As an initial prototyping step and use case scenario, we consider the development of two major system tools that can be transitioned from research to the responding operational agency for mitigating coastal oil spills. These tools consist of the capture of Situation Aware (SA) Social Media (SM) Data, and assimilation of the processed information into forecasting models to provide incident decision managers with interactive virtual spatial temporal animations superimposed with probabilistic data estimates. The system methodologies are equally applicable to the wider class of extreme events such as plume dispersions from volcanoes or massive fires, major floods, hurricane impacts, radioactive isotope dispersions from nuclear accidents, etc. A successful feasibility demonstration of this technology has been shown in the case of the Deepwater Horizon Oil Spill where Human Sensor Networks have been combined with a geophysical model to perform parameter assessments. Flickr images of beached oil were mined from the spill area, geolocated and timestamped and converted into geophysical data. This data was incorporated into General NOAA Operational Modeling Environment (GNOME), a Lagrangian forecast model that uses near real-time surface winds, ocean currents, and satellite shape profiles of oil to generate a forecast of plume movement. As a result, improved estimates of diffusive coefficients and rates of oil spill were determined. Current approaches for providing satellite derived oil distributions are collected from a satellite sensor web of operational and research sensors from many countries, and a manual analysis is performed by NESDIS. A real time SA HSW processing system based on geolocated SM data from sources such as Twitter, Flickr, YouTube etc., greatly

  1. A variational ensemble scheme for noisy image data assimilation

    Science.gov (United States)

    Yang, Yin; Robinson, Cordelia; Heitz, Dominique; Mémin, Etienne

    2014-05-01

    Data assimilation techniques aim at recovering a system state variables trajectory denoted as X, along time from partially observed noisy measurements of the system denoted as Y. These procedures, which couple dynamics and noisy measurements of the system, fulfill indeed a twofold objective. On one hand, they provide a denoising - or reconstruction - procedure of the data through a given model framework and on the other hand, they provide estimation procedures for unknown parameters of the dynamics. A standard variational data assimilation problem can be formulated as the minimization of the following objective function with respect to the initial discrepancy, η, from the background initial guess: δ« J(η(x)) = 1∥Xb (x) - X (t ,x)∥2 + 1 tf∥H(X (t,x ))- Y (t,x)∥2dt. 2 0 0 B 2 t0 R (1) where the observation operator H links the state variable and the measurements. The cost function can be interpreted as the log likelihood function associated to the a posteriori distribution of the state given the past history of measurements and the background. In this work, we aim at studying ensemble based optimal control strategies for data assimilation. Such formulation nicely combines the ingredients of ensemble Kalman filters and variational data assimilation (4DVar). It is also formulated as the minimization of the objective function (1), but similarly to ensemble filter, it introduces in its objective function an empirical ensemble-based background-error covariance defined as: B ≡ )(Xb - )T>. (2) Thus, it works in an off-line smoothing mode rather than on the fly like sequential filters. Such resulting ensemble variational data assimilation technique corresponds to a relatively new family of methods [1,2,3]. It presents two main advantages: first, it does not require anymore to construct the adjoint of the dynamics tangent linear operator, which is a considerable advantage with respect to the method's implementation, and second, it enables the handling of a flow

  2. Impact of Information Incongruity and Authors Group Membership on Assimilation and Accommodation

    Science.gov (United States)

    Moskaliuk, J.; Matschke, C.

    2018-01-01

    Learning is a complex process that can be differentiated into assimilation and accommodation. The Internet enables both types of learning through collaboration. There is, however, little research investigating the specific impact of social and information incongruity on assimilation and accommodation. The current research investigates how the…

  3. Potential performances of remotely sensed LAI assimilation in WOFOST model based on an OSS experiment

    NARCIS (Netherlands)

    Curnel, Y.; Wit, de A.J.W.; Duveiller, G.; Defourny, P.

    2011-01-01

    An Observing System Simulation Experiment (OSSE) has been defined to assess the potentialities of assimilating winter wheat leaf area index (LAI) estimations derived from remote sensing into the crop growth model WOFOST. Two assimilation strategies are considered: one based on Ensemble Kalman Filter

  4. Straight-line assimilation in home-leaving? A comparison of Turks, Somalis and Danes

    DEFF Research Database (Denmark)

    Nielsen, Rikke Skovgaard

    2016-01-01

    The purpose of this paper is to test the evidence for spatial assimilation and straight-line assimilation in the transition of leaving home in Denmark. Based on data from the extensive Danish registers, the paper analyses the home-leaving patterns of Danes, Turkish immigrants, Turkish descendants...

  5. A Framework for Research on E-Learning Assimilation in SMEs: A Strategic Perspective

    Science.gov (United States)

    Raymond, Louis; Uwizeyemungu, Sylvestre; Bergeron, Francois; Gauvin, Stephane

    2012-01-01

    Purpose: This study aims to propose an integrative conceptual framework of e-learning adoption and assimilation that is adapted to the specific context of small to medium-sized enterprises (SMEs). Design/methodology/approach: The literature on the state of e-learning usage in SMEs and on the IT adoption and assimilation factors that can be…

  6. Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments

    Science.gov (United States)

    van Peet, Jacob C. A.; van der A, Ronald J.; Kelder, Hennie M.; Levelt, Pieternel F.

    2018-02-01

    A three-dimensional global ozone distribution has been derived from assimilation of ozone profiles that were observed by satellites. By simultaneous assimilation of ozone profiles retrieved from the nadir looking satellite instruments Global Ozone Monitoring Experiment 2 (GOME-2) and Ozone Monitoring Instrument (OMI), which measure the atmosphere at different times of the day, the quality of the derived atmospheric ozone field has been improved. The assimilation is using an extended Kalman filter in which chemical transport model TM5 has been used for the forecast. The combined assimilation of both GOME-2 and OMI improves upon the assimilation results of a single sensor. The new assimilation system has been demonstrated by processing 4 years of data from 2008 to 2011. Validation of the assimilation output by comparison with sondes shows that biases vary between -5 and +10 % between the surface and 100 hPa. The biases for the combined assimilation vary between -3 and +3 % in the region between 100 and 10 hPa where GOME-2 and OMI are most sensitive. This is a strong improvement compared to direct retrievals of ozone profiles from satellite observations.

  7. Assimilation or Ethnicization: An Exploration of Inland Tibet Class Education Policy and Practice

    Science.gov (United States)

    Miaoyan, Yang; Dunzhu, Nima

    2015-01-01

    Assimilation and ethnicization are mainstream voices in current studies of ethnic relations. The former suspects that current social system arrangements are meant to assimilate minority groups into the cultural system of the mainstream ethnic group, while the latter believes that current systemic arrangements will cause minority groups to tend…

  8. Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

    OpenAIRE

    M. Bocquet; H. Elbern; H. Eskes; M. Hirtl; R. Žabkar; G. R. Carmichael; J. Flemming; A. Inness; M. Pagowski; J. L. Pérez Camaño; P. E. Saide; R. San Jose; M. Sofiev; J. Vira; A. Baklanov

    2015-01-01

    Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of three-dimensional chemical (including aerosol) concentrations and perform inverse modeling of input variables or model parameters (e.g., emissions). Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. They offer the possibility to assimilate both meteorologica...

  9. Data Assimilation within the Advanced Circulation (ADCIRC) Modeling Framework for Hurricane Storm Surge Forecasting

    KAUST Repository

    Butler, T.; Altaf, Muhammad; Dawson, C.; Hoteit, Ibrahim; Luo, X.; Mayo, T.

    2012-01-01

    levels, and wave heights—during these extreme events. This type of data, if available in real time, could be used in a data assimilation framework to improve hurricane storm surge forecasts. In this paper a data assimilation methodology for storm surge

  10. Air Quality Modeling Using the NASA GEOS-5 Multispecies Data Assimilation System

    Science.gov (United States)

    Keller, Christoph A.; Pawson, Steven; Wargan, Krzysztof; Weir, Brad

    2018-01-01

    The NASA Goddard Earth Observing System (GEOS) data assimilation system (DAS) has been expanded to include chemically reactive tropospheric trace gases including ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). This system combines model analyses from the GEOS-5 model with detailed atmospheric chemistry and observations from MLS (O3), OMI (O3 and NO2), and MOPITT (CO). We show results from a variety of assimilation test experiments, highlighting the improvements in the representation of model species concentrations by up to 50% compared to an assimilation-free control experiment. Taking into account the rapid chemical cycling of NO2 when applying the assimilation increments greatly improves assimilation skills for NO2 and provides large benefits for model concentrations near the surface. Analysis of the geospatial distribution of the assimilation increments suggest that the free-running model overestimates biomass burning emissions but underestimates lightning NOx emissions by 5-20%. We discuss the capability of the chemical data assimilation system to improve atmospheric composition forecasts through improved initial value and boundary condition inputs, particularly during air pollution events. We find that the current assimilation system meaningfully improves short-term forecasts (1-3 day). For longer-term forecasts more emphasis on updating the emissions instead of initial concentration fields is needed.

  11. An OSSE Study for Deep Argo Array using the GFDL Ensemble Coupled Data Assimilation System

    Science.gov (United States)

    Chang, You-Soon; Zhang, Shaoqing; Rosati, Anthony; Vecchi, Gabriel A.; Yang, Xiaosong

    2018-03-01

    An observing system simulation experiment (OSSE) using an ensemble coupled data assimilation system was designed to investigate the impact of deep ocean Argo profile assimilation in a biased numerical climate system. Based on the modern Argo observational array and an artificial extension to full depth, "observations" drawn from one coupled general circulation model (CM2.0) were assimilated into another model (CM2.1). Our results showed that coupled data assimilation with simultaneous atmospheric and oceanic constraints plays a significant role in preventing deep ocean drift. However, the extension of the Argo array to full depth did not significantly improve the quality of the oceanic climate estimation within the bias magnitude in the twin experiment. Even in the "identical" twin experiment for the deep Argo array from the same model (CM2.1) with the assimilation model, no significant changes were shown in the deep ocean, such as in the Atlantic meridional overturning circulation and the Antarctic bottom water cell. The small ensemble spread and corresponding weak constraints by the deep Argo profiles with medium spatial and temporal resolution may explain why the deep Argo profiles did not improve the deep ocean features in the assimilation system. Additional studies using different assimilation methods with improved spatial and temporal resolution of the deep Argo array are necessary in order to more thoroughly understand the impact of the deep Argo array on the assimilation system.

  12. Are changes in sulfate assimilation pathway needed for evolution of C4 photosynthesis?

    Directory of Open Access Journals (Sweden)

    Silke Christine Weckopp

    2015-01-01

    Full Text Available C4 photosynthesis characteristically features a cell-specific localization of enzymes involved in CO2 assimilation in bundle sheath cells or mesophyll cells. Interestingly, enzymes of sulfur assimilation are also specifically present in bundle sheath cells of maize and many other C4 species. This localization, however, could not be confirmed in C4 species of the genus Flaveria. It was, therefore, concluded that the bundle sheath localization of sulfate assimilation occurs only in C4 monocots. However, recently the sulfate assimilation pathway was found coordinately enriched in bundle sheath cells of Arabidopsis, opening new questions about the significance of such cell-specific localization of the pathway. In addition, next generation sequencing revealed expression gradients of many genes from C3 to C4 species and mathematical modelling proposed a sequence of adaptations during the evolutionary path from C3 to C4. Indeed, such gradient, with higher expression of genes for sulfate reduction in C4 species, has been observed within the genus Flaveria. These new tools provide the basis for reexamining the intriguing question of compartmentalization of sulfur assimilation. Therefore, this review summarizes the findings on spatial separation of sulfur assimilation in C4 plants and Arabidopsis, assesses the information on sulfur assimilation provided by the recent transcriptomics data and discusses their possible impact on understanding this interesting feature of plant sulfur metabolism to find out whether changes in sulfate assimilation are part of a general evolutionary trajectory towards C4 photosynthesis.

  13. Novel heterotrophic nitrogen removal and assimilation characteristic of the newly isolated bacterium Pseudomonas stutzeri AD-1.

    Science.gov (United States)

    Qing, Hui; Donde, Oscar Omondi; Tian, Cuicui; Wang, Chunbo; Wu, Xingqiang; Feng, Shanshan; Liu, Yao; Xiao, Bangding

    2018-04-18

    AD-1, an aerobic denitrifier, was isolated from activated sludge and identified as Pseudomonas stutzeri. AD-1 completely removed NO 3 - or NO 2 - and removed 99.5% of NH 4 + during individual culturing in a broth medium with an initial nitrogen concentration of approximately 50 mg L -1 . Results showed that larger amounts of nitrogen were removed through assimilation by the bacteria. And when NH 4 + was used as the sole nitrogen source in the culture medium, neither NO 2 - nor NO 3 - was detected, thus indicating that AD-1 may not be a heterotrophic nitrifier. Only trace amount of N 2 O was detected during the denitrification process. Single factor experiments indicated that the optimal culture conditions for AD-1 were: a carbon-nitrogen ratio (C/N) of 15, a temperature of 25°C and sodium succinate or glucose as a carbon source. In conclusion, due to the ability of AD-1 to utilize nitrogen of different forms with high efficiencies for its growth while producing only trace emissions of N 2 O, the bacterium had outstanding potential to use in the bioremediation of high-nitrogen-containing wastewaters. Meanwhile, it may also be a proper candidate for biotreatment of high concentration organic wastewater. Copyright © 2018 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  14. Evaluation of Gaussian approximations for data assimilation in reservoir models

    KAUST Repository

    Iglesias, Marco A.

    2013-07-14

    The Bayesian framework is the standard approach for data assimilation in reservoir modeling. This framework involves characterizing the posterior distribution of geological parameters in terms of a given prior distribution and data from the reservoir dynamics, together with a forward model connecting the space of geological parameters to the data space. Since the posterior distribution quantifies the uncertainty in the geologic parameters of the reservoir, the characterization of the posterior is fundamental for the optimal management of reservoirs. Unfortunately, due to the large-scale highly nonlinear properties of standard reservoir models, characterizing the posterior is computationally prohibitive. Instead, more affordable ad hoc techniques, based on Gaussian approximations, are often used for characterizing the posterior distribution. Evaluating the performance of those Gaussian approximations is typically conducted by assessing their ability at reproducing the truth within the confidence interval provided by the ad hoc technique under consideration. This has the disadvantage of mixing up the approximation properties of the history matching algorithm employed with the information content of the particular observations used, making it hard to evaluate the effect of the ad hoc approximations alone. In this paper, we avoid this disadvantage by comparing the ad hoc techniques with a fully resolved state-of-the-art probing of the Bayesian posterior distribution. The ad hoc techniques whose performance we assess are based on (1) linearization around the maximum a posteriori estimate, (2) randomized maximum likelihood, and (3) ensemble Kalman filter-type methods. In order to fully resolve the posterior distribution, we implement a state-of-the art Markov chain Monte Carlo (MCMC) method that scales well with respect to the dimension of the parameter space, enabling us to study realistic forward models, in two space dimensions, at a high level of grid refinement. Our

  15. Variational data assimilation system "INM RAS - Black Sea"

    Science.gov (United States)

    Parmuzin, Eugene; Agoshkov, Valery; Assovskiy, Maksim; Giniatulin, Sergey; Zakharova, Natalia; Kuimov, Grigory; Fomin, Vladimir

    2013-04-01

    Development of Informational-Computational Systems (ICS) for Data Assimilation Procedures is one of multidisciplinary problems. To study and solve these problems one needs to apply modern results from different disciplines and recent developments in: mathematical modeling; theory of adjoint equations and optimal control; inverse problems; numerical methods theory; numerical algebra and scientific computing. The problems discussed above are studied in the Institute of Numerical Mathematics of the Russian Academy of Science (INM RAS) in ICS for Personal Computers (PC). Special problems and questions arise while effective ICS versions for PC are being developed. These problems and questions can be solved with applying modern methods of numerical mathematics and by solving "parallelism problem" using OpenMP technology and special linear algebra packages. In this work the results on the ICS development for PC-ICS "INM RAS - Black Sea" are presented. In the work the following problems and questions are discussed: practical problems that can be studied by ICS; parallelism problems and their solutions with applying of OpenMP technology and the linear algebra packages used in ICS "INM - Black Sea"; Interface of ICS. The results of ICS "INM RAS - Black Sea" testing are presented. Efficiency of technologies and methods applied are discussed. The work was supported by RFBR, grants No. 13-01-00753, 13-05-00715 and by The Ministry of education and science of Russian Federation, project 8291, project 11.519.11.1005 References: [1] V.I. Agoshkov, M.V. Assovskii, S.A. Lebedev, Numerical simulation of Black Sea hydrothermodynamics taking into account tide-forming forces. Russ. J. Numer. Anal. Math. Modelling (2012) 27, No.1, 5-31 [2] E.I. Parmuzin, V.I. Agoshkov, Numerical solution of the variational assimilation problem for sea surface temperature in the model of the Black Sea dynamics. Russ. J. Numer. Anal. Math. Modelling (2012) 27, No.1, 69-94 [3] V.B. Zalesny, N.A. Diansky, V

  16. The Effects of Chlorophyll Assimilation on Carbon Fluxes in a Global Biogeochemical Model. [Technical Report Series on Global Modeling and Data Assimilation

    Science.gov (United States)

    Koster, Randal D. (Editor); Rousseaux, Cecile Severine; Gregg, Watson W.

    2014-01-01

    In this paper, we investigated whether the assimilation of remotely-sensed chlorophyll data can improve the estimates of air-sea carbon dioxide fluxes (FCO2). Using a global, established biogeochemical model (NASA Ocean Biogeochemical Model, NOBM) for the period 2003-2010, we found that the global FCO2 values produced in the free-run and after assimilation were within -0.6 mol C m(sup -2) y(sup -1) of the observations. The effect of satellite chlorophyll assimilation was assessed in 12 major oceanographic regions. The region with the highest bias was the North Atlantic. Here the model underestimated the fluxes by 1.4 mol C m(sup -2) y(sup -1) whereas all the other regions were within 1 mol C m(sup -2) y(sup -1) of the data. The FCO2 values were not strongly impacted by the assimilation, and the uncertainty in FCO2 was not decreased, despite the decrease in the uncertainty in chlorophyll concentration. Chlorophyll concentrations were within approximately 25% of the database in 7 out of the 12 regions, and the assimilation improved the chlorophyll concentration in the regions with the highest bias by 10-20%. These results suggest that the assimilation of chlorophyll data does not considerably improve FCO2 estimates and that other components of the carbon cycle play a role that could further improve our FCO2 estimates.

  17. Assimilate unloading from maize (Zea mays L.) pedicel tissues. II. Effects of chemical agents on sugar, amino acid, and 14C-assimilate unloading

    International Nuclear Information System (INIS)

    Porter, G.A.; Knievel, D.P.; Shannon, J.C.

    1987-01-01

    Sugar, amino acid, and 14 C-assimilate release from attached maize (Zea mays L.) pedicels was studied following treatment with several chemical inhibitors. In the absence of these agents, sugar release was nearly linear over a 7-hour period. At least 13 amino acids were released with glutamine comprising over 30% of the total. Release was not affected by potassium concentration, 10-minute pretreatments with p-chloromercuribenzene sulfonic acid (PCMBS) or dithiothreitol, and low concentrations of CaCl 2 . Three hours or more exposure to PCMBS, dinitrophenol, N-ethylmaleimide, or 2,4,6-trinitrobenzene sulfonic acid strongly inhibited 14 C-assimilate, sugar, and amino acid release from the pedicel. These treatments also reduced 14 C-assimilate movement into the kernel bases. It is, therefore, likely that reduced unloading, caused by these relatively long-term exposures to chemical inhibitors, was related to reduced translocation of assimilates into treated kernels. Whether this effect is due to disruption of kernel metabolism and sieve element function or reduced assimilate unloading and subsequent accumulation of unlabeled assimilates within the pedicel tissues cannot be determined at this time

  18. Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal adjustment scale

    Science.gov (United States)

    Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.

    2012-01-01

    State updating of distributed rainfall-runoff models via streamflow assimilation is subject to overfitting because large dimensionality of the state space of the model may render the assimilation problem seriously under-determined. To examine the issue in the context of operational hydrology, we carry out a set of real-world experiments in which streamflow data is assimilated into gridded Sacramento Soil Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM) with the variational data assimilation technique. Study basins include four basins in Oklahoma and five basins in Texas. To assess the sensitivity of data assimilation performance to dimensionality reduction in the control vector, we used nine different spatiotemporal adjustment scales, where state variables are adjusted in a lumped, semi-distributed, or distributed fashion and biases in precipitation and potential evaporation (PE) are adjusted hourly, 6-hourly, or kept time-invariant. For each adjustment scale, three different streamflow assimilation scenarios are explored, where streamflow observations at basin interior points, at the basin outlet, or at both interior points and the outlet are assimilated. The streamflow assimilation experiments with nine different basins show that the optimum spatiotemporal adjustment scale varies from one basin to another and may be different for streamflow analysis and prediction in all of the three streamflow assimilation scenarios. The most preferred adjustment scale for seven out of nine basins is found to be the distributed, hourly scale, despite the fact that several independent validation results at this adjustment scale indicated the occurrence of overfitting. Basins with highly correlated interior and outlet flows tend to be less sensitive to the adjustment scale and could benefit more from streamflow assimilation. In comparison to outlet flow assimilation, interior flow

  19. Response of an eddy-permitting ocean model to the assimilation of sparse in situ data

    Science.gov (United States)

    Li, Jian-Guo; Killworth, Peter D.; Smeed, David A.

    2003-04-01

    The response of an eddy-permitting ocean model to changes introduced by data assimilation is studied when the available in situ data are sparse in both space and time (typical for the majority of the ocean). Temperature and salinity (T&S) profiles from the WOCE upper ocean thermal data set were assimilated into a primitive equation ocean model over the North Atlantic, using a simple nudging scheme with a time window of about 2 days and a horizontal spatial radius of about 1°. When data are sparse the model returns to its unassimilated behavior, locally "forgetting" or rejecting the assimilation, on timescales determined by the local advection and diffusion. Increasing the spatial weighting radius effectively reduces both processes and hence lengthens the model restoring time (and with it, the impact of assimilation). Increasing the nudging factor enhances the assimilation effect but has little effect on the model restoring time.

  20. Time compression diseconomies in environmental management: the effect of assimilation on environmental performance.

    Science.gov (United States)

    Lannelongue, Gustavo; Gonzalez-Benito, Javier; Gonzalez-Benito, Oscar; Gonzalez-Zapatero, Carmen

    2015-01-01

    This research addresses the relationship between an organisation's assimilation of its environmental management system (EMS), the experience it gains through it, and its environmental performance. Assimilation here refers to the degree to which the requirements of the management standard are integrated within a plant's daily operations. Basing ourselves on the heterogeneity of organisations, we argue that assimilation and experience will inform environmental performance. Furthermore, we posit that the relationship between assimilation and environmental performance depends on experience. The attempt to obtain greater assimilation in a shorter time leads an organisation to record a poorer environmental outcome, which we shall refer to as time compression diseconomies in environmental management. We provide empirical evidence based on 154 plants pertaining to firms in Spain subject to the European Union's CO2 Emissions Trading System. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Impact of real-time measurements for data assimilation in reservoir simulation

    Energy Technology Data Exchange (ETDEWEB)

    Schulze-Riegert, R; Krosche, M [Scandpower Petroleum Technology GmbH, Hamburg (Germany); Pajonk, O [TU Braunschweig (Germany). Inst. fuer Wissenschaftliches Rechnen; Myrland, T [Morges Teknisk-Naturvitenskapelige Univ. (NTNU), Trondheim (Germany)

    2008-10-23

    This paper gives an overview on the conceptual background of data assimilation techniques. The framework of sequential data assimilation as described for the ensemble Kalman filter implementation allows a continuous integration of new measurement data. The initial diversity of ensemble members will be critical for the assimilation process and the ability to successfully assimilate measurement data. At the same time the initial ensemble will impact the propagation of uncertainties with crucial consequences for production forecasts. Data assimilation techniques have complimentary features compared to other optimization techniques built on selection or regression schemes. Specifically, EnKF is applicable to real field cases and defines an important perspective for facilitating continuous reservoir simulation model updates in a reservoir life cycle. (orig.)

  2. MATLAB algorithm to implement soil water data assimilation with the Ensemble Kalman Filter using HYDRUS.

    Science.gov (United States)

    Valdes-Abellan, Javier; Pachepsky, Yakov; Martinez, Gonzalo

    2018-01-01

    Data assimilation is becoming a promising technique in hydrologic modelling to update not only model states but also to infer model parameters, specifically to infer soil hydraulic properties in Richard-equation-based soil water models. The Ensemble Kalman Filter method is one of the most widely employed method among the different data assimilation alternatives. In this study the complete Matlab© code used to study soil data assimilation efficiency under different soil and climatic conditions is shown. The code shows the method how data assimilation through EnKF was implemented. Richards equation was solved by the used of Hydrus-1D software which was run from Matlab. •MATLAB routines are released to be used/modified without restrictions for other researchers•Data assimilation Ensemble Kalman Filter method code.•Soil water Richard equation flow solved by Hydrus-1D.

  3. Improving 7-Day Forecast Skill by Assimilation of Retrieved AIRS Temperature Profiles

    Science.gov (United States)

    Susskind, Joel; Rosenberg, Bob

    2016-01-01

    We conducted a new set of Data Assimilation Experiments covering the period January 1 to February 29, 2016 using the GEOS-5 DAS. Our experiments assimilate all data used operationally by GMAO (Control) with some modifications. Significant improvement in Global and Southern Hemisphere Extra-tropical 7-day forecast skill was obtained when: We assimilated AIRS Quality Controlled temperature profiles in place of observed AIRS radiances, and also did not assimilate CrISATMS radiances, nor did we assimilate radiosonde temperature profiles or aircraft temperatures. This new methodology did not improve or degrade 7-day Northern Hemispheric Extra-tropical forecast skill. We are conducting experiments aimed at further improving of Northern Hemisphere Extra-tropical forecast skill.

  4. Spatially Distributed Assimilation of Remotely Sensed Leaf Area Index and Potential Evapotranspiration for Hydrologic Modeling in Wetland Landscapes

    Science.gov (United States)

    Rajib, A.; Evenson, G. R.; Golden, H. E.; Lane, C.

    2017-12-01

    Evapotranspiration (ET), a highly dynamic flux in wetland landscapes, regulates the accuracy of surface/sub-surface runoff simulation in a hydrologic model. Accordingly, considerable uncertainty in simulating ET-related processes remains, including our limited ability to incorporate realistic ground conditions, particularly those involved with complex land-atmosphere feedbacks, vegetation growth, and energy balances. Uncertainty persists despite using high resolution topography and/or detailed land use data. Thus, a good hydrologic model can produce right answers for wrong reasons. In this study, we develop an efficient approach for multi-variable assimilation of remotely sensed earth observations (EOs) into a hydrologic model and apply it in the 1700 km2 Pipestem Creek watershed in the Prairie Pothole Region of North Dakota, USA. Our goal is to employ EOs, specifically Leaf Area Index (LAI) and Potential Evapotranspiration (PET), as surrogates for the aforementioned processes without overruling the model's built-in physical/semi-empirical process conceptualizations. To do this, we modified the source code of an already-improved version of the Soil and Water Assessment Tool (SWAT) for wetland hydrology (Evenson et al. 2016 HP 30(22):4168) to directly assimilate remotely-sensed LAI and PET (obtained from the 500 m and 1 km Moderate Resolution Imaging Spectroradiometer (MODIS) gridded products, respectively) into each model Hydrologic Response Unit (HRU). Two configurations of the model, one with and one without EO assimilation, are calibrated against streamflow observations at the watershed outlet. Spatio-temporal changes in the HRU-level water balance, based on calibrated outputs, are evaluated using MODIS Actual Evapotranspiration (AET) as a reference. It is expected that the model configuration having remotely sensed LAI and PET, will simulate more realistic land-atmosphere feedbacks, vegetation growth and energy balance. As a result, this will decrease simulated

  5. Development of the WRF-CO2 4D-Var assimilation system v1.0

    Directory of Open Access Journals (Sweden)

    T. Zheng

    2018-05-01

    Full Text Available Regional atmospheric CO2 inversions commonly use Lagrangian particle trajectory model simulations to calculate the required influence function, which quantifies the sensitivity of a receptor to flux sources. In this paper, an adjoint-based four-dimensional variational (4D-Var assimilation system, WRF-CO2 4D-Var, is developed to provide an alternative approach. This system is developed based on the Weather Research and Forecasting (WRF modeling system, including the system coupled to chemistry (WRF-Chem, with tangent linear and adjoint codes (WRFPLUS, and with data assimilation (WRFDA, all in version 3.6. In WRF-CO2 4D-Var, CO2 is modeled as a tracer and its feedback to meteorology is ignored. This configuration allows most WRF physical parameterizations to be used in the assimilation system without incurring a large amount of code development. WRF-CO2 4D-Var solves for the optimized CO2 flux scaling factors in a Bayesian framework. Two variational optimization schemes are implemented for the system: the first uses the limited memory Broyden–Fletcher–Goldfarb–Shanno (BFGS minimization algorithm (L-BFGS-B and the second uses the Lanczos conjugate gradient (CG in an incremental approach. WRFPLUS forward, tangent linear, and adjoint models are modified to include the physical and dynamical processes involved in the atmospheric transport of CO2. The system is tested by simulations over a domain covering the continental United States at 48 km  ×  48 km grid spacing. The accuracy of the tangent linear and adjoint models is assessed by comparing against finite difference sensitivity. The system's effectiveness for CO2 inverse modeling is tested using pseudo-observation data. The results of the sensitivity and inverse modeling tests demonstrate the potential usefulness of WRF-CO2 4D-Var for regional CO2 inversions.

  6. Development of the WRF-CO2 4D-Var assimilation system v1.0

    Science.gov (United States)

    Zheng, Tao; French, Nancy H. F.; Baxter, Martin

    2018-05-01

    Regional atmospheric CO2 inversions commonly use Lagrangian particle trajectory model simulations to calculate the required influence function, which quantifies the sensitivity of a receptor to flux sources. In this paper, an adjoint-based four-dimensional variational (4D-Var) assimilation system, WRF-CO2 4D-Var, is developed to provide an alternative approach. This system is developed based on the Weather Research and Forecasting (WRF) modeling system, including the system coupled to chemistry (WRF-Chem), with tangent linear and adjoint codes (WRFPLUS), and with data assimilation (WRFDA), all in version 3.6. In WRF-CO2 4D-Var, CO2 is modeled as a tracer and its feedback to meteorology is ignored. This configuration allows most WRF physical parameterizations to be used in the assimilation system without incurring a large amount of code development. WRF-CO2 4D-Var solves for the optimized CO2 flux scaling factors in a Bayesian framework. Two variational optimization schemes are implemented for the system: the first uses the limited memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) minimization algorithm (L-BFGS-B) and the second uses the Lanczos conjugate gradient (CG) in an incremental approach. WRFPLUS forward, tangent linear, and adjoint models are modified to include the physical and dynamical processes involved in the atmospheric transport of CO2. The system is tested by simulations over a domain covering the continental United States at 48 km × 48 km grid spacing. The accuracy of the tangent linear and adjoint models is assessed by comparing against finite difference sensitivity. The system's effectiveness for CO2 inverse modeling is tested using pseudo-observation data. The results of the sensitivity and inverse modeling tests demonstrate the potential usefulness of WRF-CO2 4D-Var for regional CO2 inversions.

  7. Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

    Science.gov (United States)

    Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

    2011-01-01

    The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

  8. Physical attractiveness, issue agreement, and assimilation effects in candidate appraisal.

    Science.gov (United States)

    Schubert, James N; Curran, Margaret Ann; Strungaru, Carmen

    2011-01-01

    This study examines the cognitive and affective factors of candidate appraisal by manipulating candidate attractiveness and levels of issue agreement with voters. Drawing upon research in evolutionary psychology and cognitive neuroscience, this analysis proposes that automatic processing of physical appearance predisposes affective disposition toward more attractive candidates, thereby influencing cognitive processing of issue information. An experimental design presented attractive and unattractive candidates who were either liberal or conservative in a mock primary election. The data show strong partial effects for appearance on vote intention, an interaction between appearance and issue agreement, and a tendency for voters to assimilate the dissimilar views of attractive candidates. We argue that physical appearance is important in primary elections when the differences in issue positions and ideology between candidates is small.

  9. Sample size reduction in groundwater surveys via sparse data assimilation

    KAUST Repository

    Hussain, Z.

    2013-04-01

    In this paper, we focus on sparse signal recovery methods for data assimilation in groundwater models. The objective of this work is to exploit the commonly understood spatial sparsity in hydrodynamic models and thereby reduce the number of measurements to image a dynamic groundwater profile. To achieve this we employ a Bayesian compressive sensing framework that lets us adaptively select the next measurement to reduce the estimation error. An extension to the Bayesian compressive sensing framework is also proposed which incorporates the additional model information to estimate system states from even lesser measurements. Instead of using cumulative imaging-like measurements, such as those used in standard compressive sensing, we use sparse binary matrices. This choice of measurements can be interpreted as randomly sampling only a small subset of dug wells at each time step, instead of sampling the entire grid. Therefore, this framework offers groundwater surveyors a significant reduction in surveying effort without compromising the quality of the survey. © 2013 IEEE.

  10. Sample size reduction in groundwater surveys via sparse data assimilation

    KAUST Repository

    Hussain, Z.; Muhammad, A.

    2013-01-01

    In this paper, we focus on sparse signal recovery methods for data assimilation in groundwater models. The objective of this work is to exploit the commonly understood spatial sparsity in hydrodynamic models and thereby reduce the number of measurements to image a dynamic groundwater profile. To achieve this we employ a Bayesian compressive sensing framework that lets us adaptively select the next measurement to reduce the estimation error. An extension to the Bayesian compressive sensing framework is also proposed which incorporates the additional model information to estimate system states from even lesser measurements. Instead of using cumulative imaging-like measurements, such as those used in standard compressive sensing, we use sparse binary matrices. This choice of measurements can be interpreted as randomly sampling only a small subset of dug wells at each time step, instead of sampling the entire grid. Therefore, this framework offers groundwater surveyors a significant reduction in surveying effort without compromising the quality of the survey. © 2013 IEEE.

  11. Kalman filter data assimilation: targeting observations and parameter estimation.

    Science.gov (United States)

    Bellsky, Thomas; Kostelich, Eric J; Mahalov, Alex

    2014-06-01

    This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.

  12. Kalman filter data assimilation: Targeting observations and parameter estimation

    International Nuclear Information System (INIS)

    Bellsky, Thomas; Kostelich, Eric J.; Mahalov, Alex

    2014-01-01

    This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation

  13. Data assimilation in the early phase: Kalman filtering RIMPUFF

    DEFF Research Database (Denmark)

    Astrup, P.; Turcanu, C.; Puch, R.O.

    2004-01-01

    of RODOS (Realtime Online DecisiOn Support system for nuclear emergencies) – has been developed. It is built on the Kalman filtering algorithm and it assimilates 10-minute averaged gamma dose rates measured atground level stations. Since the gamma rates are non-linear functions of the state vector...... variables, the applied Kalman filter is the so-called Extended Kalman filter. In more ways the implementation is non standard: 1) the number of state vectorvariables varies with time, and 2) the state vector variables are prediction updated with 1-minute time steps but only Kalman filtered every 10 minutes......, and this based on time averaged measurements. Given reasonable conditions, i.e. a spatially densedistribution of gamma monitors and a realistic wind field, the developed ADUM module is found to be able to enhance the prediction of the gamma dose field. Based on some of the Kalman filtering parameters, another...

  14. Assimilating American Indians in James Fenimore Cooper’s Novels?

    Directory of Open Access Journals (Sweden)

    Peprník Michal

    2016-07-01

    Full Text Available The article employs critical concepts from sociology and anthropology to examine the stereotype of the Vanishing Indian and disclose its contradictory character. The article argues that in James Fenimore Cooper’s late novels from the 1840s a type of American Indian appears who can be regarded as a Vanishing Indian in many respects as he displays some slight degree of assimilation but at the same time he can be found to reveal a surprising amount of resistance to the process of vanishing and marginalization. His peculiar mode of survival and his mode of living demonstrate a certain degree of acculturation, which comes close to Gerald Vizenor’s survivance and for which I propose a term critical integration. I base my study on Susquesus (alias Trackless, Cooper’s less well-known character from The Littlepage Manuscripts, a three-book family saga.

  15. Weighted ensemble transform Kalman filter for image assimilation

    Directory of Open Access Journals (Sweden)

    Sebastien Beyou

    2013-01-01

    Full Text Available This study proposes an extension of the Weighted Ensemble Kalman filter (WEnKF proposed by Papadakis et al. (2010 for the assimilation of image observations. The main focus of this study is on a novel formulation of the Weighted filter with the Ensemble Transform Kalman filter (WETKF, incorporating directly as a measurement model a non-linear image reconstruction criterion. This technique has been compared to the original WEnKF on numerical and real world data of 2-D turbulence observed through the transport of a passive scalar. In particular, it has been applied for the reconstruction of oceanic surface current vorticity fields from sea surface temperature (SST satellite data. This latter technique enables a consistent recovery along time of oceanic surface currents and vorticity maps in presence of large missing data areas and strong noise.

  16. MicroRNA-224 is Readily Detectable in Urine of Individuals with Diabetes Mellitus and is a Potential Indicator of Beta-Cell Demise

    Directory of Open Access Journals (Sweden)

    Siobhán Bacon

    2015-06-01

    Full Text Available MicroRNA (miRNA are a class of non-coding, 19–25 nucleotide RNA critical for network-level regulation of gene expression. miRNA serve as paracrine signaling molecules. Using an unbiased array approach, we previously identified elevated levels of miR-224 and miR-103 to be associated with a monogenic form of diabetes; HNF1A-MODY. miR-224 is a novel miRNA in the field of diabetes. We sought to explore the role of miR-224 as a potential biomarker in diabetes, and whether such diabetes-associated-miRNA can also be detected in the urine of patients. Absolute levels of miR-224 and miR-103 were determined in the urine of n = 144 individuals including carriers of a HNF1A mutation, participants with type 1 diabetes mellitus (T1DM, type 2 diabetes mellitus (T2DM and normal controls. Expression levels were correlated with clinical and biochemical parameters. miR-224 was significantly elevated in the urine of carriers of a HNF1A mutation and participants with T1DM. miR-103 was highly expressed in urine across all diabetes cohorts when compared to controls. For both miR-224 and-103, we found a significant correlation between serum and urine levels (p < 0.01. We demonstrate that miRNA can be readily detected in the urine independent of clinical indices of renal dysfunction. We surmise that the differential expression levels of miR-224 in both HNF1A-MODY mutation carriers and T1DM may be an attempt to compensate for beta-cell demise.

  17. The restriction-modification genes of Escherichia coli K-12 may not be selfish: they do not resist loss and are readily replaced by alleles conferring different specificities.

    Science.gov (United States)

    O'Neill, M; Chen, A; Murray, N E

    1997-12-23

    Type II restriction and modification (R-M) genes have been described as selfish because they have been shown to impose selection for the maintenance of the plasmid that encodes them. In our experiments, the type I R-M system EcoKI does not behave in the same way. The genes specifying EcoKI are, however, normally residents of the chromosome and therefore our analyses were extended to monitor the deletion of chromosomal genes rather than loss of plasmid vector. If EcoKI were to behave in the same way as the plasmid-encoded type II R-M systems, the loss of the relevant chromosomal genes by mutation or recombination should lead to cell death because the cell would become deficient in modification enzyme and the bacterial chromosome would be vulnerable to the restriction endonuclease. Our data contradict this prediction; they reveal that functional type I R-M genes in the chromosome are readily replaced by mutant alleles and by alleles encoding a type I R-M system of different specificity. The acquisition of allelic genes conferring a new sequence specificity, but not the loss of the resident genes, is dependent on the product of an unlinked gene, one predicted [Prakash-Cheng, A., Chung, S. S. & Ryu, J. (1993) Mol. Gen. Genet. 241, 491-496] to be relevant to control of expression of the genes that encode EcoKI. Our evidence suggests that not all R-M systems are evolving as "selfish" units; rather, the diversity and distribution of the family of type I enzymes we have investigated require an alternative selective pressure.

  18. Enhancement of Photovoltaic Performance by Utilizing Readily Accessible Hole Transporting Layer of Vanadium(V) Oxide Hydrate in a Polymer-Fullerene Blend Solar Cell.

    Science.gov (United States)

    Jiang, Youyu; Xiao, Shengqiang; Xu, Biao; Zhan, Chun; Mai, Liqiang; Lu, Xinhui; You, Wei

    2016-05-11

    Herein, a successful application of V2O5·nH2O film as hole transporting layer (HTL) instead of PSS in polymer solar cells is demonstrated. The V2O5·nH2O layer was spin-coated from V2O5·nH2O sol made from melting-quenching sol-gel method by directly using vanadium oxide powder, which is readily accessible and cost-effective. V2O5·nH2O (n ≈ 1) HTL is found to have comparable work function and smooth surface to that of PSS. For the solar cell containing V2O5·nH2O HTL and the active layer of the blend of a novel polymer donor (PBDSe-DT2PyT) and the acceptor of PC71BM, the PCE was significantly improved to 5.87% with a 30% increase over 4.55% attained with PSS HTL. Incorporation of V2O5·nH2O as HTL in the polymer solar cell was found to enhance the crystallinity of the active layer, electron-blocking at the anode and the light-harvest in the wavelength range of 400-550 nm in the cell. V2O5·nH2O HTL improves the charge generation and collection and suppress the charge recombination within the PBDSe-DT2PyT:PC71BM solar cell, leading to a simultaneous enhancement in Voc, Jsc, and FF. The V2O5·nH2O HTL proposed in this work is envisioned to be of great potential to fabricate highly efficient PSCs with low-cost and massive production.

  19. The Impact of AMSU-A Radiance Assimilation in the U.S. Navy's Operational Global Atmospheric Prediction System (NOGAPS)

    National Research Council Canada - National Science Library

    Baker, Nancy L; Hogan, T. F; Campbell, W. F; Pauley, R. L; Swadley, S. D

    2005-01-01

    ...) sensor suite onboard NOAA 15 and 16 for NOGAPS. The direct assimilation of AMSU-A radiances replaced the assimilation of ATOVS temperature retrievals produced by NOAA's National Environmental Satellite, Data and Information Service (NESDIS...

  20. Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions

    NARCIS (Netherlands)

    Babenhauserheide, A.; Basu, S.; Peters, W.

    2015-01-01

    Data assimilation systems allow for estimating surface fluxes of greenhouse gases from atmospheric concentration measurements. Good knowledge about fluxes is essential to understand how climate change affects ecosystems and to characterize feedback mechanisms. Based on assimilation of more than one

  1. Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions

    NARCIS (Netherlands)

    Babenhauserheide, A.; Basu, S.; Houweling, S.; Peters, W.; Butz, A.

    2015-01-01

    Data assimilation systems allow for estimating surface fluxes of greenhouse gases from atmospheric concentration measurements. Good knowledge about fluxes is essential to understand how climate change affects ecosystems and to characterize feedback mechanisms. Based on the assimilation of more than

  2. Studies on retranslocation of accumulated assimilates in 'Delaware' grapevines, (1)

    International Nuclear Information System (INIS)

    Yang, Yau-Shiang; Hori, Yutaka

    1979-01-01

    Potted Delaware grapevines were supplied with 14 CO 2 in summer or autumn, and the accumulation and retranslocation of 14 C-assimilates were investigated. At pruning time, 14 C-assimilates were distributed to the roots at higher ratio than to the trunks and canes, and this trend was more marked in the autumn feeding than the summer feeding. The respiratory consumption and retranslocation of 14 C during the growth period of new shoots were evaluated as the percentage of 14 C found in the vines just after pruning. The percentage of the respiratory consumption of 14 C was evidently higher in the autumn feeding. The retranslocation began with the bud burst, and reached maximum at the 6- to 8-leaf stages in the vines fed 14 CO 2 in autumn and at the 10-leaf stage in those fed in summer. The retranslocation in both groups ceased by the flowering stage. Such course of the retranslocation with time was recognized in radioautographs of the new shoots. The maximum percentage of the translocation to the newly developed shoots was 5.1 - 5.2 and 15.3 - 10.7 in the vines fed 14 CO 2 in summer and autumn, respectively. It was peculiar to the new shoots that nearly half of their ethanol-soluble 14 C was found in amino acids unlike the one-sided distribution to soluble carbohydrates in the trunks and roots. It was assumed that amino acids were retranslocated to the new shoots after they had been synthesized in the roots. (Kaihara, S.)

  3. Nonlinear data assimilation using synchronization in a particle filter

    Science.gov (United States)

    Rodrigues-Pinheiro, Flavia; Van Leeuwen, Peter Jan

    2017-04-01

    Current data assimilation methods still face problems in strongly nonlinear cases. A promising solution is a particle filter, which provides a representation of the model probability density function by a discrete set of particles. However, the basic particle filter does not work in high-dimensional cases. The performance can be improved by considering the proposal density freedom. A potential choice of proposal density might come from the synchronisation theory, in which one tries to synchronise the model with the true evolution of a system using one-way coupling via the observations. In practice, an extra term is added to the model equations that damps growth of instabilities on the synchronisation manifold. When only part of the system is observed synchronization can be achieved via a time embedding, similar to smoothers in data assimilation. In this work, two new ideas are tested. First, ensemble-based time embedding, similar to an ensemble smoother or 4DEnsVar is used on each particle, avoiding the need for tangent-linear models and adjoint calculations. Tests were performed using Lorenz96 model for 20, 100 and 1000-dimension systems. Results show state-averaged synchronisation errors smaller than observation errors even in partly observed systems, suggesting that the scheme is a promising tool to steer model states to the truth. Next, we combine these efficient particles using an extension of the Implicit Equal-Weights Particle Filter, a particle filter that ensures equal weights for all particles, avoiding filter degeneracy by construction. Promising results will be shown on low- and high-dimensional Lorenz96 models, and the pros and cons of these new ideas will be discussed.

  4. Establishing the connection between crowd-sourced data and decision makers

    Science.gov (United States)

    Paxton, L. J.; Swartz, W.; Strong, S. B.; Nix, M. G.; Schaefer, R. K.; Weiss, M.

    2014-12-01

    There are many challenges in using, developing, and ensuring the viability of crowd-sourced data. Establishing and maintaining relevance is one of them but each participant in the challenge has different criteria for relevance. Consider, for example, the collection of data using smart phones. Some participants just like to contribute to something they consider good for the community. How do you engender that commitment? This becomes especially problematic when an additional sensor may need to be added to the smart phone. Certainly the humanitarian-egalitarian may be willing to "buy-in" but what value does it hold for the entrepreneurial-individualist? Another challenge is that of the crowd-sourced data themselves. Most readily available apps collect only one kind of data. The frontier lies in not only aggregating the data from those devices but in fusing the data with other data types (e.g. satellite imagery, installed sensors, radars, etc.). Doing this requires resources and the establishment and negotiation of data rights, how data are valued, how data are used, and the model used for support of the process (e.g. profit-driven, communal, scientific, etc.). In this talk we will discuss a few problems that we have looked at wherein distributed sensor networks provide potential value, data fusion is a "value multiplier" of those crowd-sourced data and how we make that connection to decision makers. We have explored active decision making through our Global Assimilation of Information for Action project (see our old website http://gaia.jhuapl.edu) and the use of "serious games" to establish affinities and illuminate opportunities and issues. We assert that the field of dreams approach ("build it and they will come") is not a sufficiently robust approach; the decision-makers (or paying customers) must be involved in the process of defining the data system products and quantifying the value proposition for their clients.

  5. Assimilation of Atmospheric InfraRed Sounder (AIRS) Profiles using WRF-Var

    Science.gov (United States)

    Zavodsky, Brad; Jedlovec, Gary J.; Lapenta, William

    2008-01-01

    The Weather Research and Forecasting (WRF) model contains a three-dimensional variational (3DVAR) assimilation system (WRF-Var), which allows a user to join data from multiple sources into one coherent analysis. WRF-Var combines observations with a background field traditionally generated using a previous model forecast through minimization of a cost function. In data sparse regions, remotely-sensed observations may be able to improve analyses and produce improved forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The combined AIRS/AMSU system provides radiance measurements used as input to a sophisticated retrieval scheme which has been shown to produce temperature profiles with an accuracy of 1 K over 1 km layers and humidity profiles with accuracy of 15% in 2 km layers in both clear and partly cloudy conditions. The retrieval algorithm also provides estimates of the accuracy of the retrieved values at each pressure level, allowing the user to select profiles based on the required error tolerances of the application. The purpose of this paper is to describe a procedure to optimally assimilate high-resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background field type using gen_be and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics in the WRF-Var. The AIRS thermodynamic profiles are obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators are used to select the highest quality temperature and moisture

  6. Parameter sensitivity of three Kalman Filter Schemes for the assimilation of tide guage data in coastal and self sea models

    DEFF Research Database (Denmark)

    Sørensen, Jacob Viborg Tornfeldt; Madsen, Henrik; Madsen, H.

    2006-01-01

    In applications of data assimilation algorithms, a number of poorly known assimilation parameters usually need to be specified. Hence, the documented success of data assimilation methodologies must rely on a moderate sensitivity to these parameters. This contribution presents a parameter sensitiv...

  7. multi-scale data assimilation approaches and error characterisation applied to the inverse modelling of atmospheric constituent emission fields

    International Nuclear Information System (INIS)

    Koohkan, Mohammad Reza

    2012-01-01

    Data assimilation in geophysical sciences aims at optimally estimating the state of the system or some parameters of the system's physical model. To do so, data assimilation needs three types of information: observations and background information, a physical/numerical model, and some statistical description that prescribes uncertainties to each component of the system. In my dissertation, new methodologies of data assimilation are used in atmospheric chemistry and physics: the joint use of a 4D-Var with a sub-grid statistical model to consistently account for representativeness errors, accounting for multiple scale in the BLUE estimation principle, and a better estimation of prior errors using objective estimation of hyper-parameters. These three approaches will be specifically applied to inverse modelling problems focusing on the emission fields of tracers or pollutants. First, in order to estimate the emission inventories of carbon monoxide over France, in-situ stations which are impacted by the representativeness errors are used. A sub-grid model is introduced and coupled with a 4D-Var to reduce the representativeness error. Indeed, the results of inverse modelling showed that the 4D-Var routine was not fit to handle the representativeness issues. The coupled data assimilation system led to a much better representation of the CO concentration variability, with a significant improvement of statistical indicators, and more consistent estimation of the CO emission inventory. Second, the evaluation of the potential of the IMS (International Monitoring System) radionuclide network is performed for the inversion of an accidental source. In order to assess the performance of the global network, a multi-scale adaptive grid is optimised using a criterion based on degrees of freedom for the signal (DFS). The results show that several specific regions remain poorly observed by the IMS network. Finally, the inversion of the surface fluxes of Volatile Organic Compounds

  8. Effect of increasing proportions of lignocellulosic cosubstrate on the single-phase and two-phase digestion of readily biodegradable substrate

    International Nuclear Information System (INIS)

    Ganesh, Rangaraj; Torrijos, Michel; Sousbie, Philippe; Lugardon, Aurelien; Steyer, Jean Philippe; Delgenes, Jean Philippe

    2015-01-01

    The influence of different proportions of lignocellulosic substrate (cow manure with straw, CM) on the single-phase (conventional reactor) and two-phase (acidification/methanation with solids and liquid recirculation) digestion of a readily biodegradable substrate (fruit and vegetable waste, FVW) was investigated in order to determine the optimum cosubstrate ratio and the process best suited for codigestion. Both processes were fed initially with FVW, followed by FVW and CM at 80%:20% and 60%:40% (on volatile solids, VS basis) during an experiment run over eleven months. For the single-phase process, energy yield and VS destruction decreased by 11% and 9% with the 80%:20% FVW and CM ratio and by 16% and 17% with the 60%:40% feed ratio when compared to 100% FVW feed. For the two-phase process, energy yield and VS destruction decreased by 21% and 14% with 80%:20% feed ratio and by 48% and 33% with 60%:40% feed ratio compared to 100% FVW. Substrate solubilization in the acidification reactor was very efficient for all the feed proportions but it resulted in compounds other than volatile fatty acid (non-VFA COD) which were not easily amenable to methane generation. This led to a lower energy yield per kg of VS fed in the two-phase process compared to the single-phase process for the respective waste combination. For single-phase digestion, both 80%:20% and 60%:40% ratios were effective co-substrate combinations due to their higher energy yield. The two-phase process can be used for these ratios if higher VS reduction and a higher loading rate are the objectives. - Highlights: • Effect of cow manure addition on the digestion of fruit and vegetable waste studied. • Single and two-phase processes were compared for three different waste ratios. • Methane and energy yields were higher by single-phase than the two-phase process. • FVW-Cow manure ratios of 80%:20% and 60%:40% found effective for single-phase digestion. • Two-phase process resulted in higher solids

  9. Remote Forensics May Bring the Next Sea Change in E-discovery: Are All Networked Computers Now Readily Accessible Under the Revised Federal Rules of Civil Procedure?

    Directory of Open Access Journals (Sweden)

    AleJoseph J. Schwerha

    2008-09-01

    on geographically dispersed computers remotely.  That process, in general, is often defined as remote forensics. The question is now whether newly available remote forensic solution indicate that all networked computers are readily accessible under the current state of the law.  This article attempts to define remote forensics, examines a selection of applicable court decisions, and then analyzes the currently available commercial software packages that allow remote forensics.

  10. Reliable prediction of clinical outcome in patients with chronic HCV infection and compensated advanced hepatic fibrosis: a validated model using objective and readily available clinical parameters.

    Science.gov (United States)

    van der Meer, Adriaan J; Hansen, Bettina E; Fattovich, Giovanna; Feld, Jordan J; Wedemeyer, Heiner; Dufour, Jean-François; Lammert, Frank; Duarte-Rojo, Andres; Manns, Michael P; Ieluzzi, Donatella; Zeuzem, Stefan; Hofmann, W Peter; de Knegt, Robert J; Veldt, Bart J; Janssen, Harry L A

    2015-02-01

    Reliable tools to predict long-term outcome among patients with well compensated advanced liver disease due to chronic HCV infection are lacking. Risk scores for mortality and for cirrhosis-related complications were constructed with Cox regression analysis in a derivation cohort and evaluated in a validation cohort, both including patients with chronic HCV infection and advanced fibrosis. In the derivation cohort, 100/405 patients died during a median 8.1 (IQR 5.7-11.1) years of follow-up. Multivariate Cox analyses showed age (HR=1.06, 95% CI 1.04 to 1.09, pstatistic=0.78, 95% CI 0.72 to 0.83). In the validation cohort, 58/296 patients with cirrhosis died during a median of 6.6 (IQR 4.4-9.0) years. Among patients with estimated 5-year mortality risks 10%, the observed 5-year mortality rates in the derivation cohort and validation cohort were 0.9% (95% CI 0.0 to 2.7) and 2.6% (95% CI 0.0 to 6.1), 8.1% (95% CI 1.8 to 14.4) and 8.0% (95% CI 1.3 to 14.7), 21.8% (95% CI 13.2 to 30.4) and 20.9% (95% CI 13.6 to 28.1), respectively (C statistic in validation cohort = 0.76, 95% CI 0.69 to 0.83). The risk score for cirrhosis-related complications also incorporated HCV genotype (C statistic = 0.80, 95% CI 0.76 to 0.83 in the derivation cohort; and 0.74, 95% CI 0.68 to 0.79 in the validation cohort). Prognosis of patients with chronic HCV infection and compensated advanced liver disease can be accurately assessed with risk scores including readily available objective clinical parameters. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  11. Source-sink relationships in radish plant

    Directory of Open Access Journals (Sweden)

    Z. Starck

    2015-01-01

    Full Text Available The problem of source-sink relationships in di- and tetraploidal radish plants grown in. hydroponic cultures was investigated in two stages of their development: with intensively growing swollen hypocotyl and in the period of actively accumulating nutrients in the storage organ. It was found, that the proportion, between the mass of organs, their RGR and NAR was very similar in di- and tetraploidal populations, probably owing to a similar rate of photosynthesis and pattern of assimilates distribution. The high variability of swollen hypocotyls size is slightly correlated with the size of the whole aerial part and is not correlated with the rate of photosynthesis in leaves. Partial defoliation of radish plants did not affect the rate of photosynthesis of the remaining leaves. Only in the cotyledones the oldest donors of 14C-assimilates, a slight compensation of photosynthesis was reported. It may suggest, that the rate of photosynthesis in radish plants is not under the control of sink activity. The size of the storage organ have determined in some extent its attractive force and influenced the amount of 14C-assimilates exported from their donors. Translocation of photosynthates from the young, still growing leaves was conditioned mainly by their retention power. Therefore, in young radish plants cotyledons were the main donor of 14C-assimilates.

  12. Methane assimilation and trophic interactions with marine Methylomicrobium in deep-water coral reef sediment off the coast of Norway.

    Science.gov (United States)

    Jensen, Sigmund; Neufeld, Josh D; Birkeland, Nils-Kåre; Hovland, Martin; Murrell, John Colin

    2008-11-01

    Deep-water coral reefs are seafloor environments with diverse biological communities surrounded by cold permanent darkness. Sources of energy and carbon for the nourishment of these reefs are presently unclear. We investigated one aspect of the food web using DNA stable-isotope probing (DNA-SIP). Sediment from beneath a Lophelia pertusa reef off the coast of Norway was incubated until assimilation of 5 micromol 13CH4 g(-1) wet weight occurred. Extracted DNA was separated into 'light' and 'heavy' fractions for analysis of labelling. Bacterial community fingerprinting of PCR-amplified 16S rRNA gene fragments revealed two predominant 13C-specific bands. Sequencing of these bands indicated that carbon from 13CH4 had been assimilated by a Methylomicrobium and an uncultivated member of the Gammaproteobacteria. Cloning and sequencing of 16S rRNA genes from the heavy DNA, in addition to genes encoding particulate methane monooxygenase and methanol dehydrogenase, all linked Methylomicrobium with methane metabolism. Putative cross-feeders were affiliated with Methylophaga (Gammaproteobacteria), Hyphomicrobium (Alphaproteobacteria) and previously unrecognized methylotrophs of the Gammaproteobacteria, Alphaproteobacteria, Deferribacteres and Bacteroidetes. This first marine methane SIP study provides evidence for the presence of methylotrophs that participate in sediment food webs associated with deep-water coral reefs.

  13. Skin Temperature Analysis and Bias Correction in a Coupled Land-Atmosphere Data Assimilation System

    Science.gov (United States)

    Bosilovich, Michael G.; Radakovich, Jon D.; daSilva, Arlindo; Todling, Ricardo; Verter, Frances

    2006-01-01

    In an initial investigation, remotely sensed surface temperature is assimilated into a coupled atmosphere/land global data assimilation system, with explicit accounting for biases in the model state. In this scheme, an incremental bias correction term is introduced in the model's surface energy budget. In its simplest form, the algorithm estimates and corrects a constant time mean bias for each gridpoint; additional benefits are attained with a refined version of the algorithm which allows for a correction of the mean diurnal cycle. The method is validated against the assimilated observations, as well as independent near-surface air temperature observations. In many regions, not accounting for the diurnal cycle of bias caused degradation of the diurnal amplitude of background model air temperature. Energy fluxes collected through the Coordinated Enhanced Observing Period (CEOP) are used to more closely inspect the surface energy budget. In general, sensible heat flux is improved with the surface temperature assimilation, and two stations show a reduction of bias by as much as 30 Wm(sup -2) Rondonia station in Amazonia, the Bowen ratio changes direction in an improvement related to the temperature assimilation. However, at many stations the monthly latent heat flux bias is slightly increased. These results show the impact of univariate assimilation of surface temperature observations on the surface energy budget, and suggest the need for multivariate land data assimilation. The results also show the need for independent validation data, especially flux stations in varied climate regimes.

  14. Translocation and distribution of 14C-assimilation products in soybeans with different growth property

    International Nuclear Information System (INIS)

    Yoshida, Koichi; Gotoh, Kanji

    1975-01-01

    To 3 different kinds of soybeans, Tokachinagaha (Determinate), Koganejiro (Intermediate), and Harosoy (Indeterminate), 14 C was given at 3 stages of growth, namely, initial flowering, young pod development, and seed fattening periods. The 14 C assimilation efficiency, namely, the value of total 14 C assimilated divided by the area of the leaves which assimilated 14 C, was large when the leaf area was small. The value decreased with the increase of the leaf area. The rate of translocation of 14 C assimilation products was 20-50% in the period of initial flowering. The rate was highest in Tokachinagaha, followed by Koganejiro and Harosoy in this order. The difference was small in the period of young pod development. In the period of initial flowering, the distribution of 14 C to lower leaves and branches was high in Harosoy. In the period of young pod development, 30-40% of the assimilated 14 C was found in stems. This distribution is possibly due to temporary storage. In the period of seed fattening, 80-90% of the assimilated 14 C was present in pods and seeds. It was then concluded that the movement of assimilated products is high in the determinate type in the initial growth period. In the seed fattening period, the rate is high in the indeterminate type soy beans. (Fukutomi, T.)

  15. Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

    Science.gov (United States)

    Li, Zhijin; Chao, Yi; Li, P. Peggy

    2012-01-01

    A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

  16. Bio-Optical Data Assimilation With Observational Error Covariance Derived From an Ensemble of Satellite Images

    Science.gov (United States)

    Shulman, Igor; Gould, Richard W.; Frolov, Sergey; McCarthy, Sean; Penta, Brad; Anderson, Stephanie; Sakalaukus, Peter

    2018-03-01

    An ensemble-based approach to specify observational error covariance in the data assimilation of satellite bio-optical properties is proposed. The observational error covariance is derived from statistical properties of the generated ensemble of satellite MODIS-Aqua chlorophyll (Chl) images. The proposed observational error covariance is used in the Optimal Interpolation scheme for the assimilation of MODIS-Aqua Chl observations. The forecast error covariance is specified in the subspace of the multivariate (bio-optical, physical) empirical orthogonal functions (EOFs) estimated from a month-long model run. The assimilation of surface MODIS-Aqua Chl improved surface and subsurface model Chl predictions. Comparisons with surface and subsurface water samples demonstrate that data assimilation run with the proposed observational error covariance has higher RMSE than the data assimilation run with "optimistic" assumption about observational errors (10% of the ensemble mean), but has smaller or comparable RMSE than data assimilation run with an assumption that observational errors equal to 35% of the ensemble mean (the target error for satellite data product for chlorophyll). Also, with the assimilation of the MODIS-Aqua Chl data, the RMSE between observed and model-predicted fractions of diatoms to the total phytoplankton is reduced by a factor of two in comparison to the nonassimilative run.

  17. Assimilation of ice and water observations from SAR imagery to improve estimates of sea ice concentration

    Directory of Open Access Journals (Sweden)

    K. Andrea Scott

    2015-09-01

    Full Text Available In this paper, the assimilation of binary observations calculated from synthetic aperture radar (SAR images of sea ice is investigated. Ice and water observations are obtained from a set of SAR images by thresholding ice and water probabilities calculated using a supervised maximum likelihood estimator (MLE. These ice and water observations are then assimilated in combination with ice concentration from passive microwave imagery for the purpose of estimating sea ice concentration. Due to the fact that the observations are binary, consisting of zeros and ones, while the state vector is a continuous variable (ice concentration, the forward model used to map the state vector to the observation space requires special consideration. Both linear and non-linear forward models were investigated. In both cases, the assimilation of SAR data was able to produce ice concentration analyses in closer agreement with image analysis charts than when assimilating passive microwave data only. When both passive microwave and SAR data are assimilated, the bias between the ice concentration analyses and the ice concentration from ice charts is 19.78%, as compared to 26.72% when only passive microwave data are assimilated. The method presented here for the assimilation of SAR data could be applied to other binary observations, such as ice/water information from visual/infrared sensors.

  18. Sequential assimilation of multi-mission dynamical topography into a global finite-element ocean model

    Directory of Open Access Journals (Sweden)

    S. Skachko

    2008-12-01

    Full Text Available This study focuses on an accurate estimation of ocean circulation via assimilation of satellite measurements of ocean dynamical topography into the global finite-element ocean model (FEOM. The dynamical topography data are derived from a complex analysis of multi-mission altimetry data combined with a referenced earth geoid. The assimilation is split into two parts. First, the mean dynamic topography is adjusted. To this end an adiabatic pressure correction method is used which reduces model divergence from the real evolution. Second, a sequential assimilation technique is applied to improve the representation of thermodynamical processes by assimilating the time varying dynamic topography. A method is used according to which the temperature and salinity are updated following the vertical structure of the first baroclinic mode. It is shown that the method leads to a partially successful assimilation approach reducing the rms difference between the model and data from 16 cm to 2 cm. This improvement of the mean state is accompanied by significant improvement of temporal variability in our analysis. However, it remains suboptimal, showing a tendency in the forecast phase of returning toward a free run without data assimilation. Both the mean difference and standard deviation of the difference between the forecast and observation data are reduced as the result of assimilation.

  19. Nocturnal uptake and assimilation of nitrogen dioxide by C3 and CAM plants.

    Science.gov (United States)

    Takahashi, Misa; Konaka, Daisuke; Sakamoto, Atsushi; Morikawa, Hiromichi

    2005-01-01

    In order to investigate nocturnal uptake and assimilation of NO2 by C3 and crassulacean acid metabolism (CAM) plants, they were fumigated with 4 microl l(-1) 15N-labeled nitrogen dioxide (NO2) for 8 h. The amount of NO2 and assimilation of NO2 by plants were determined by mass spectrometry and Kjeldahl-nitrogen based mass spectrometry, respectively. C3 plants such as kenaf (Hibiscus cannabinus), tobacco (Nicotiana tabacum) and ground cherry (Physalis alkekengi) showed a high uptake and assimilation during daytime as high as 1100 to 2700 ng N mg(-1) dry weight. While tobacco and ground cherry strongly reduced uptake and assimilation of NO2 during nighttime, kenaf kept high nocturnal uptake and assimilation of NO2 as high as about 1500 ng N mg(-1) dry weight. Stomatal conductance measurements indicated that there were no significant differences to account for the differences in the uptake of NO2 by tobacco and kenaf during nighttime. CAM plants such as Sedum sp., Kalanchoe blossfeldiana (kalanchoe) and Aloe arborescens exhibited nocturnal uptake and assimilation of NO2. However, the values of uptake and assimilation of NO2 both during daytime and nighttime was very low (at most about 500 ng N mg(-1) dry weight) as compared with those of above mentioned C3 plants. The present findings indicate that kenaf is an efficient phytoremediator of NO2 both during daytime and nighttime.

  20. Assimilation of SAPHIR radiance: impact on hyperspectral radiances in 4D-VAR

    Science.gov (United States)

    Indira Rani, S.; Doherty, Amy; Atkinson, Nigel; Bell, William; Newman, Stuart; Renshaw, Richard; George, John P.; Rajagopal, E. N.

    2016-04-01

    Assimilation of a new observation dataset in an NWP system may affect the quality of an existing observation data set against the model background (short forecast), which in-turn influence the use of an existing observation in the NWP system. Effect of the use of one data set on the use of another data set can be quantified as positive, negative or neutral. Impact of the addition of new dataset is defined as positive if the number of assimilated observations of an existing type of observation increases, and bias and standard deviation decreases compared to the control (without the new dataset) experiment. Recently a new dataset, Megha Tropiques SAPHIR radiances, which provides atmospheric humidity information, is added in the Unified Model 4D-VAR assimilation system. In this paper we discuss the impact of SAPHIR on the assimilation of hyper-spectral radiances like AIRS, IASI and CrIS. Though SAPHIR is a Microwave instrument, its impact can be clearly seen in the use of hyper-spectral radiances in the 4D-VAR data assimilation systems in addition to other Microwave and InfraRed observation. SAPHIR assimilation decreased the standard deviation of the spectral channels of wave number from 650 -1600 cm-1 in all the three hyperspectral radiances. Similar impact on the hyperspectral radiances can be seen due to the assimilation of other Microwave radiances like from AMSR2 and SSMIS Imager.

  1. Evidence for the assimilation of ancient glacier organic carbon in a proglacial stream food web

    Science.gov (United States)

    Fellman, Jason; Hood, Eran; Raymond, Peter A.; Hudson, J.H.; Bozeman, Maura; Arimitsu, Mayumi L.

    2015-01-01

    We used natural abundance δ13C, δ15N, and Δ14C to compare trophic linkages between potential carbon sources (leaf litter, epilithic biofilm, and particulate organic matter) and consumers (aquatic macroinvertebrates and fish) in a nonglacial stream and two reaches of the heavily glaciated Herbert River. We tested the hypothesis that proglacial stream food webs are sustained by organic carbon released from glacial ecosystems. Carbon sources and consumers in the nonglacial stream had carbon isotope values that ranged from -30‰ to -25‰ for δ13C and from -14‰ to 53‰ for Δ14C reflecting a food web sustained mainly on contemporary primary production. In contrast, biofilm in the two glacial stream sites was highly Δ14C-depleted (-215‰ to 175‰) relative to the nonglacial stream consistent with the assimilation of ancient glacier organic carbon. IsoSource modeling showed that in upper Herbert River, macroinvertebrates (Δ14C = -171‰ to 22‰) and juvenile salmonids (Δ14C = −102‰ to 17‰) reflected a feeding history of both biofilm (~ 56%) and leaf litter (~ 40%). We estimate that in upper Herbert River on average 36% of the carbon incorporated into consumer biomass is derived from the glacier ecosystem. Thus, 14C-depleted glacial organic carbon was likely transferred to higher trophic levels through a feeding history of bacterial uptake of dissolved organic carbon and subsequent consumption of 14C-depleted biofilm by invertebrates and ultimately fish. Our findings show that the metazoan food web is sustained in part by glacial organic carbon such that future changes in glacial runoff could influence the stability and trophic structure of proglacial aquatic ecosystems.

  2. A balanced Kalman filter ocean data assimilation system with application to the South Australian Sea

    Science.gov (United States)

    Li, Yi; Toumi, Ralf

    2017-08-01

    In this paper, an Ensemble Kalman Filter (EnKF) based regional ocean data assimilation system has been developed and applied to the South Australian Sea. This system consists of the data assimilation algorithm provided by the NCAR Data Assimilation Research Testbed (DART) and the Regional Ocean Modelling System (ROMS). We describe the first implementation of the physical balance operator (temperature-salinity, hydrostatic and geostrophic balance) to DART, to reduce the spurious waves which may be introduced during the data assimilation process. The effect of the balance operator is validated in both an idealised shallow water model and the ROMS model real case study. In the shallow water model, the geostrophic balance operator eliminates spurious ageostrophic waves and produces a better sea surface height (SSH) and velocity analysis and forecast. Its impact increases as the sea surface height and wind stress increase. In the real case, satellite-observed sea surface temperature (SST) and SSH are assimilated in the South Australian Sea with 50 ensembles using the Ensemble Adjustment Kalman Filter (EAKF). Assimilating SSH and SST enhances the estimation of SSH and SST in the entire domain, respectively. Assimilation with the balance operator produces a more realistic simulation of surface currents and subsurface temperature profile. The best improvement is obtained when only SSH is assimilated with the balance operator. A case study with a storm suggests that the benefit of the balance operator is of particular importance under high wind stress conditions. Implementing the balance operator could be a general benefit to ocean data assimilation systems.

  3. Impact of assimilation window length on diurnal features in a Mars atmospheric analysis

    Directory of Open Access Journals (Sweden)

    Yongjing Zhao

    2015-05-01

    Full Text Available Effective simulation of diurnal variability is an important aspect of many geophysical data assimilation systems. For the Martian atmosphere, thermal tides are particularly prominent and contribute much to the Martian atmospheric circulation, dynamics and dust transport. To study the Mars diurnal variability and Mars thermal tides, the Geophysical Fluid Dynamics Laboratory Mars Global Climate Model with the 4D-local ensemble transform Kalman filter (4D-LETKF is used to perform an analysis assimilating spacecraft temperature retrievals. We find that the use of a ‘traditional’ 6-hr assimilation cycle induces spurious forcing of a resonantly enhanced semi-diurnal Kelvin waves represented in both surface pressure and mid-level temperature by forming a wave 4 pattern in the diurnal averaged analysis increment that acts as a ‘topographic’ stationary forcing. Different assimilation window lengths in the 4D-LETKF are introduced to remove the artificially induced resonance. It is found that short assimilation window lengths not only remove the spurious resonance, but also push the migrating semi-diurnal temperature variation at 50 Pa closer to the estimated ‘true’ tides even in the absence of a radiatively active water ice cloud parameterisation. In order to compare the performance of different assimilation window lengths, short-term to mid-range forecasts based on the hour 00 and 12 assimilation are evaluated and compared. Results show that during Northern Hemisphere summer, it is not the assimilation window length, but the radiatively active water ice clouds that influence the model prediction. A ‘diurnal bias correction’ that includes bias correction fields dependent on the local time is shown to effectively reduce the forecast root mean square differences between forecasts and observations, compensate for the absence of water ice cloud parameterisation and enhance Martian atmosphere prediction. The implications of these results for

  4. Assimilation of Remotely Sensed Leaf Area Index into the Community Land Model with Explicit Carbon and Nitrogen Components using Data Assimilation Research Testbed

    Science.gov (United States)

    Ling, X.; Fu, C.; Yang, Z. L.; Guo, W.

    2017-12-01

    Information of the spatial and temporal patterns of leaf area index (LAI) is crucial to understand the exchanges of momentum, carbon, energy, and water between the terrestrial ecosystem and the atmosphere, while both in-situ observation and model simulation usually show distinct deficiency in terms of LAI coverage and value. Land data assimilation, combined with observation and simulation together, is a promising way to provide variable estimation. The Data Assimilation Research Testbed (DART) developed and maintained by the National Centre for Atmospheric Research (NCAR) provides a powerful tool to facilitate the combination of assimilation algorithms, models, and real (as well as synthetic) observations to better understanding of all three. Here we systematically investigated the effects of data assimilation on improving LAI simulation based on NCAR Community Land Model with the prognostic carbon-nitrogen option (CLM4CN) linked with DART using the deterministic Ensemble Adjustment Kalman Filter (EAKF). Random 40-member atmospheric forcing was used to drive the CLM4CN with or without LAI assimilation. The Global Land Surface Satellite LAI data (GLASS LAI) LAI is assimilated into the CLM4CN at a frequency of 8 days, and LAI (and leaf carbon / nitrogen) are adjusted at each time step. The results show that assimilating remotely sensed LAI into the CLM4CN is an effective method for improving model performance. In detail, the CLM4-CN simulated LAI systematically overestimates global LAI, especially in low latitude with the largest bias of 5 m2/m2. While if updating both LAI and leaf carbon and leaf nitrogen simultaneously during assimilation, the analyzed LAI can be corrected, especially in low latitude regions with the bias controlled around ±1 m2/m2. Analyzed LAI could also represent the seasonal variation except for the Southern Temperate (23°S-90°S). The obviously improved regions located in the center of Africa, Amazon, the South of Eurasia, the northeast of

  5. An 15N study of the effects of nitrate, ammonium, and nitrate + ammonium nutrition on nitrogen assimilation in Zea mays L

    International Nuclear Information System (INIS)

    Murphy, A.T.

    1984-10-01

    A brief review of the literature on the effects of nitrate and ammonium nitrogen sources on plant growth, and the assimilation of those nitrogen sources, has been presented. It was concluded that ammonium nutrition produces optimum growth, with nitrate + ammonium being a better nitrogen source than only nitrate. Leaf blade nitrate reductase activity exceeded that of the root in nitrate-fed plants, suggesting that the shoot is the major region of nitrate assimilation. This is further supported by the results of xylem exudate analysis, where 93% of the newly-absorbed nitrogen exported by the roots was detected as nitrate. Evidence in support of this hypothesis was also obtained by studying the distribution of 15 N in the various nitrogenous compounds. The effects of nitrogen source on plant growth, organic nitrogen and inorganic nitrogen contents, and the rates of incorporation into nitrogenous compounds were studied. The observed differences were explained with reference to the effects of the various nitrogen sources on the physiology of the plants. The experimental techniques included assays of the enzymes nitrate reductase and glutamine synthetase, whole plant growth studies, and the analysis of nitrogenous compounds of xylem exudate and those extracted from the leaf blade, leaf base, and root regions of maize plants after feeding with a nutrient solution containing nitrogen as 15 N

  6. Assimilação foliar de enxofre elementar pela soja Foliar elementary sulfur assimilation by soybean

    Directory of Open Access Journals (Sweden)

    Godofredo Cesar Vitti

    2007-02-01

    Full Text Available O objetivo deste trabalho foi avaliar a assimilação de enxofre elementar (S0, aplicado nas folhas de soja, e sua eficiência comparada à adubação feita ao solo, de acordo com a dose e a natureza da fonte do nutriente. O S0 aplicado às folhas, independentemente da dose e fonte, foi assimilado pela planta, o que acarretou em aumento no teor de proteína total na folha. Todas as fontes de S aplicadas às folhas aumentaram a produção de grãos, semelhantemente à aplicação ao solo. Observou-se uma mesma produtividade com o uso de 20 kg ha-1 de S0 no solo ou de 6 kg ha-1 via foliar. A eficiência da aplicação de S via foliar, com base no conteúdo de proteína solúvel total, foi superior à da aplicação ao solo.The objective of this work was to evaluate the elementary sulfur (S0 assimilation applied on soybean leaves, and its efficiency compared to the fertilization done in the soil, according to the dose and nature of the nutrient source. The S0 applied to leaves, independently of the dose and source, was assimilated by the plant, what resulted in increase of total protein content in the leaf. All S sources applied to leaves increased the grain yield, similarly to the application to the soil. The same productivity was observed with the use of 20 kg ha-1 of S0 in the soil or 6 kg ha-1 applied to leaves. The elementary S application efficiency on leaves, based on the content of total soluble protein, was superior to application efficiency on soil.

  7. The OSSE Framework at the NASA Global Modeling and Assimilation Office (GMAO)

    Science.gov (United States)

    Moradi, I.; Prive, N.; McCarty, W.; Errico, R. M.; Gelaro, R.

    2017-12-01

    This abstract summarizes the OSSE framework developed at the Global Modeling and Assimilation Office at the National Aeronautics and Space Administration (NASA/GMAO). Some of the OSSE techniques developed at GMAO including simulation of realistic observations, e.g., adding errors to simulated observations, are now widely used by the community to evaluate the impact of new observations on the weather forecasts. This talk presents some of the recent progresses and challenges in simulating realistic observations, radiative transfer modeling support for the GMAO OSSE activities, assimilation of OSSE observations into data assimilation systems, and evaluating the impact of simulated observations on the forecast skills.

  8. IMITATING MODEL OF ASSIMILATION AND FORGETTING OF THE LOGICALLY CONNECTED INFORMATION

    Directory of Open Access Journals (Sweden)

    Robert Valerievich Mayer

    2017-09-01

    Full Text Available The educational material we present as a set of a number of information blocks consisting of learning material elements (LMEs; therefore its assimilation and forgetting occurs differently, than in the Ebbinghaus’s experiments. The purpose of the article is constructing of a computer model of assimilation and forgetting of the logically connected information allowing: 1 to prove the fast rise of understanding while training; 2 to receive the forgetting curve for the comprehended information. The modeling methods help to receive the graphs of the knowledge level dependence on time. It is shown, that the processes of assimilation and forgetting occurs according to the logistic law.

  9. A coherent structure approach for parameter estimation in Lagrangian Data Assimilation

    Science.gov (United States)

    Maclean, John; Santitissadeekorn, Naratip; Jones, Christopher K. R. T.

    2017-12-01

    We introduce a data assimilation method to estimate model parameters with observations of passive tracers by directly assimilating Lagrangian Coherent Structures. Our approach differs from the usual Lagrangian Data Assimilation approach, where parameters are estimated based on tracer trajectories. We employ the Approximate Bayesian Computation (ABC) framework to avoid computing the likelihood function of the coherent structure, which is usually unavailable. We solve the ABC by a Sequential Monte Carlo (SMC) method, and use Principal Component Analysis (PCA) to identify the coherent patterns from tracer trajectory data. Our new method shows remarkably improved results compared to the bootstrap particle filter when the physical model exhibits chaotic advection.

  10. Studies on translocation of tritiated assimilates into potatoes and wheat grains

    International Nuclear Information System (INIS)

    Mueller, J.; Diabate, S.; Strack, S.; Raskob, W.

    1993-01-01

    Tritium released in the enviroment may be converted to organically bound tritium (OBT), mainly by photosynthesis in green leaves. Tritiated assimilates can be translocated from leaves to storage organs of crop plants. This should be considered in models calculating the dose due to the ingestion pathway. This paper describes experiments with wheat and potatoes, which have been designed to study the translocation of tritiated assimilates. Additionally, gas exchange measurements have been performed with the leaves of those plants. A model has been developed to estimate the generation of OBT and the translocation of tritiated assimilates into edible plant parts. (orig.) [de

  11. Understanding climatological, instantaneous and reference VTEC maps, its variability, its relation to STEC and its assimilation by VTEC models

    Science.gov (United States)

    Orus, R.; Prieto-Cerdeira, R.

    2012-12-01

    As the next Solar Maximum peak is approaching, forecasted for the late 2013, it is a good opportunity to study the ionospheric behaviour in such conditions and how this behaviour can be estimated and corrected by existing climatological models - e.g.. NeQuick, International Reference Ionosphere (IRI)- , as well as, GNSS driven models, such as Klobuchar, NeQuick Galileo, SBAS MOPS (EGNOS and WAAS corrections) and Near Real Time Global Ionospheric Maps (GIM) or regional Maps computed by different institutions. In this framework, technology advances allow to increase the computational and radio frequency channels capabilities of low-cost receivers embedded in handheld devices (such mobile phones, pads, trekking clocks, photo-cameras, etc). This may enable the active use of received ionospheric data or correction parameters from different data sources. The study is centred in understanding the ionosphere but focusing on its impact on the position error for low-cost single-frequency receivers. This study tests optimal ways to take advantage of a big amount of Real or Near Real Time ionospheric information and the way to combine various corrections in order to reach a better navigation solution. In this context, the use of real time estimation vTEC data coming from EGNOS or WAAS or near real time GIMs are used to feed the standard GPS single-frequency ionospheric correction models (Klobuchar) and get enhanced Ionospheric corrections with minor changes on the navigation software. This is done by using a Taylor expansion over the 8 coefficients send by GPS. Moreover, the same datasets are used to assimilate it in NeQuick, for broadcast coefficients, as well as, for grid assimilation. As a side product, electron density profiles in Near Real Time could be estimated with data assimilated from different ionospheric sources. Finally, the ionospheric delay estimation for multi-constellation receivers could take benefit from a common and more accurate ionospheric model being

  12. Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

    Science.gov (United States)

    Quinn Thomas, R.; Brooks, Evan B.; Jersild, Annika L.; Ward, Eric J.; Wynne, Randolph H.; Albaugh, Timothy J.; Dinon-Aldridge, Heather; Burkhart, Harold E.; Domec, Jean-Christophe; Fox, Thomas R.; Gonzalez-Benecke, Carlos A.; Martin, Timothy A.; Noormets, Asko; Sampson, David A.; Teskey, Robert O.

    2017-07-01

    Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model-data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present

  13. Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

    Directory of Open Access Journals (Sweden)

    R. Q. Thomas

    2017-07-01

    Full Text Available Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2 concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6  ×  105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field

  14. Assimilation of formaldehyde and other C1-compounds by Gliocladium deliquescens and Paecilomyces varioti

    International Nuclear Information System (INIS)

    Sakaguchi, Kenji; Kurane, Ryuichiro; Murata, Machiko

    1975-01-01

    Two fungi were isolated from soil which grew on 0.1--0.2% formaldehyde as the sole carbon source, and identified as Gliocladium deliquescens and Paecilomyces varioti. Both the strains could grow on 5% methanol and 5% Na-formate, while the former could grow even on 7% methanol. Metabolic pathways were traced through two dimensional paper chromatography and autoradiographic techniques using 14 C-formaldehyde, 14 C-methanol or 14 C-CO 2 as substrates. The intracellular metabolites were persued and their quantitative variation with time was measured. Along with the fact that serine and malate appeared in the earlier time, then appeared organic acids and amino acids belonging to TCA cycle, and the fact that hydroxy-pyruvate reductase and phosphoenolpyruvate carboxylase activities were much stronger in methanol culture than in ethanol culture, it was concluded that the two fungi followed the serine pathway in assimilating C 1 -compounds. Oxidation enzymes of methanol and formaldehyde were also studied, and an oxidizing system was found besides usual NAD linked methanol or formaldehyde dehydrogenases. (auth.)

  15. Bayesian modeling of the assimilative capacity component of nutrient total maximum daily loads

    Science.gov (United States)

    Faulkner, B. R.

    2008-08-01

    Implementing stream restoration techniques and best management practices to reduce nonpoint source nutrients implies enhancement of the assimilative capacity for the stream system. In this paper, a Bayesian method for evaluating this component of a total maximum daily load (TMDL) load capacity is developed and applied. The joint distribution of nutrient retention metrics from a literature review of 495 measurements was used for Monte Carlo sampling with a process transfer function for nutrient attenuation. Using the resulting histograms of nutrient retention, reference prior distributions were developed for sites in which some of the metrics contributing to the transfer function were measured. Contributing metrics for the prior include stream discharge, cross-sectional area, fraction of storage volume to free stream volume, denitrification rate constant, storage zone mass transfer rate, dispersion coefficient, and others. Confidence of compliance (CC) that any given level of nutrient retention has been achieved is also determined using this approach. The shape of the CC curve is dependent on the metrics measured and serves in part as a measure of the information provided by the metrics to predict nutrient retention. It is also a direct measurement, with a margin of safety, of the fraction of export load that can be reduced through changing retention metrics. For an impaired stream in western Oklahoma, a combination of prior information and measurement of nutrient attenuation was used to illustrate the proposed approach. This method may be considered for TMDL implementation.

  16. Improving Regional Forecast by Assimilating Atmospheric InfraRed Sounder (AIRS) Profiles into WRF Model

    Science.gov (United States)

    Chou, Shih-Hung; Zavodsky, Brad; Jedlovec, Gary J.

    2009-01-01

    In data sparse regions, remotely-sensed observations can be used to improve analyses and produce improved forecasts. One such source comes from the Atmospheric InfraRed Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The purpose of this paper is to describe a procedure to optimally assimilate high resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background type, and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics. The AIRS thermodynamic profiles are derived from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators were used to select the highest quality temperature and moisture data for each profile location and pressure level. The analyses were then used to conduct a month-long series of regional forecasts over the continental U.S. The long-term impacts of AIRS profiles on forecast were assessed against verifying NAM analyses and stage IV precipitation data.

  17. An assimilation test of Doppler radar reflectivity and radial velocity from different height layers in improving the WRF rainfall forecasts

    Science.gov (United States)

    Tian, Jiyang; Liu, Jia; Yan, Denghua; Li, Chuanzhe; Chu, Zhigang; Yu, Fuliang

    2017-12-01

    Hydrological forecasts require high-resolution and accurate rainfall information, which is one of the most difficult variables to be captured by the mesoscale Numerical Weather Prediction (NWP) systems. Radar data assimilation is an effective method for improving rainfall forecasts by correcting the initial and lateral boundary conditions of the NWP system. The aim of this study is to explore an efficient way of utilizing the Doppler radar observations for data assimilation, which is implemented by exploring the effect of assimilating radar data from different height layers on the improvement of the NWP rainfall accuracy. The Weather Research and Forecasting (WRF) model is used for numerical rainfall forecast in the Zijingguan catchment located in the ;Jing-Jin-Ji; (Beijing-Tianjin-Hebei) Region of Northern China, and the three-dimensional variational data assimilation (3-DVar) technique is adopted to assimilate the radar data. Radar reflectivity and radial velocity are assimilated separately and jointly. Each type of radar data is divided into seven data sets according to the height layers: (1) 2000 m, and (7) all layers. The results show that radar reflectivity assimilation leads to better results than radial velocity assimilation. The accuracy of the forecasted rainfall deteriorates with the rise of the height of the assimilated radar reflectivity. The same results can be found when assimilating radar reflectivity and radial velocity at the same time. The conclusions of this study provide a reference for efficient assimilation of the radar data in improving the NWP rainfall products.

  18. Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

    Science.gov (United States)

    Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang

    2018-01-01

    Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.

  19. Spatial profile of contours inducing long-range color assimilation.

    Science.gov (United States)

    Devinck, Frédéric; Spillmann, Lothar; Werner, John S

    2006-01-01

    Color induction was measured using a matching method for two spatial patterns, each composed of double contours. In one pattern (the standard), the contours had sharp edges to induce the Watercolor Effect (WCE); in the other, the two contours had a spatial taper so that the overall profile produced a sawtooth edge, or ramped stimulus. These patterns were chosen based on our previous study demonstrating that the strength of the chromatic WCE depends on a luminance difference between the two contours. Low-pass chromatic mechanisms, unlike bandpass luminance mechanisms, may be expected to be insensitive to the difference between the two spatial profiles. The strength of the watercolor spreading was similar for the two patterns at narrow widths of the contour possibly because of chromatic aberration, but with wider contours, the standard stimulus produced stronger assimilation than the ramped stimulus. This research suggests that luminance-dependent chromatic mechanisms mediate the WCE and that these mechanisms are sensitive to differences in the two spatial profiles of the pattern contours only when they are wide.

  20. Bayesian Lagrangian Data Assimilation and Drifter Deployment Strategies

    Science.gov (United States)

    Dutt, A.; Lermusiaux, P. F. J.

    2017-12-01

    Ocean currents transport a variety of natural (e.g. water masses, phytoplankton, zooplankton, sediments, etc.) and man-made materials and other objects (e.g. pollutants, floating debris, search and rescue, etc.). Lagrangian Coherent Structures (LCSs) or the most influential/persistent material lines in a flow, provide a robust approach to characterize such Lagrangian transports and organize classic trajectories. Using the flow-map stochastic advection and a dynamically-orthogonal decomposition, we develop uncertainty prediction schemes for both Eulerian and Lagrangian variables. We then extend our Bayesian Gaussian Mixture Model (GMM)-DO filter to a joint Eulerian-Lagrangian Bayesian data assimilation scheme. The resulting nonlinear filter allows the simultaneous non-Gaussian estimation of Eulerian variables (e.g. velocity, temperature, salinity, etc.) and Lagrangian variables (e.g. drifter/float positions, trajectories, LCSs, etc.). Its results are showcased using a double-gyre flow with a random frequency, a stochastic flow past a cylinder, and realistic ocean examples. We further show how our Bayesian mutual information and adaptive sampling equations provide a rigorous efficient methodology to plan optimal drifter deployment strategies and predict the optimal times, locations, and types of measurements to be collected.

  1. A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

    KAUST Repository

    Altaf, Muhammad

    2014-08-01

    This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

  2. The genetic assimilation in language borrowing inferred from Jing People.

    Science.gov (United States)

    Huang, Xiufeng; Zhou, Qinghui; Bin, Xiaoyun; Lai, Shu; Lin, Chaowen; Hu, Rong; Xiao, Jiashun; Luo, Dajun; Li, Yingxiang; Wei, Lan-Hai; Yeh, Hui-Yuan; Chen, Gang; Wang, Chuan-Chao

    2018-02-28

    The Jing people are a recognized ethnic group in Guangxi, southwest China, who are the immigrants from Vietnam during the 16th century. They speak Vietnamese but with lots of language borrowings from Cantonese, Zhuang, and Mandarin. However, it's unclear if there is large-scale gene flow from surrounding populations into Jing people during their language change due to the very limited genetic information of this population. We collected blood samples from 37 Jing and 3 Han Chinese individuals from Wanwei, Shanxin, and Wutou islands in Guangxi and genotyped about 600,000 genome-wide single nucleotide polymorphisms (SNPs). We used Principal Component Analysis (PCA), ADMIXTURE analysis, f statistics, qpWave and qpAdm to infer the population genetic structure and admixture. Our data revealed that the Jing people are genetically similar to the populations in southwest China and mainland Southeast Asia. But compared with Vietnamese, they show significant evidence of gene flow from surrounding East Asians. The admixture proportion is estimated to be around 35-42% in different Jing groups using southern Han Chinese as a proxy. The majority of the paternal lineages of Jing people are most likely from surrounding East Asians. We conclude that the formation and language change of present-day Jing people have involved genetic assimilation of surrounding East Asian populations. The language borrowing, in this case, is not only a cultural phenomenon but has involved demic diffusion. © 2018 Wiley Periodicals, Inc.

  3. CLAES Product Improvement by use of GSFC Data Assimilation System

    Science.gov (United States)

    Kumer, J. B.; Douglass, Anne (Technical Monitor)

    2001-01-01

    Recent development in chemistry transport models (CTM) and in data assimilation systems (DAS) indicate impressive predictive capability for the movement of airparcels and the chemistry that goes on within these. This project was aimed at exploring the use of this capability to achieve improved retrieval of geophysical parameters from remote sensing data. The specific goal was to improve retrieval of the CLAES CH4 data obtained during the active north high latitude dynamics event of 18 to 25 February 1992. The model capabilities would be used: (1) rather than climatology to improve on the first guess and the a-priori fields, and (2) to provide horizontal gradients to include in the retrieval forward model. The retrieval would be implemented with the first forward DAS prediction. The results would feed back to the DAS and a second DAS prediction for first guess, a-priori and gradients would feed to the retrieval. The process would repeat to convergence and then proceed to the next day.

  4. Improving urban wind flow predictions through data assimilation

    Science.gov (United States)

    Sousa, Jorge; Gorle, Catherine

    2017-11-01

    Computational fluid dynamic is fundamentally important to several aspects in the design of sustainable and resilient urban environments. The prediction of the flow pattern for example can help to determine pedestrian wind comfort, air quality, optimal building ventilation strategies, and wind loading on buildings. However, the significant variability and uncertainty in the boundary conditions poses a challenge when interpreting results as a basis for design decisions. To improve our understanding of the uncertainties in the models and develop better predictive tools, we started a pilot field measurement campaign on Stanford University's campus combined with