Carbon and nitrogen assimilation in deep subseafloor microbial cells.

PubMed

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

2011-11-08

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 individual microbial cells from 219-m-deep lower Pleistocene (460,000 y old) sediments from the northwestern Pacific off the Shimokita Peninsula of Japan. Sediment samples were incubated in vitro with (13)C- and/or (15)N-labeled glucose, pyruvate, acetate, bicarbonate, methane, ammonium, and amino acids. Significant incorporation of (13)C and/or (15)N and growth occurred in response to glucose, pyruvate, and amino acids (∼76% of total cells), whereas acetate and bicarbonate were incorporated without fostering growth. Among those substrates, a maximum substrate assimilation rate was observed at 67 × 10(-18) mol/cell per d with bicarbonate. Neither carbon assimilation nor growth was evident in response to methane. The atomic ratios between nitrogen incorporated from ammonium and the total cellular nitrogen consistently exceeded the ratios of carbon, suggesting that subseafloor microbes preferentially require nitrogen assimilation for the recovery in vitro. Our results showed that the most deeply buried subseafloor sedimentary microbes maintain potentials for metabolic activities and that growth is generally limited by energy but not by the availability of C and N compounds.

Carbon and nitrogen assimilation in deep subseafloor microbial cells

PubMed Central

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 individual microbial cells from 219-m-deep lower Pleistocene (460,000 y old) sediments from the northwestern Pacific off the Shimokita Peninsula of Japan. Sediment samples were incubated in vitro with 13C- and/or 15N-labeled glucose, pyruvate, acetate, bicarbonate, methane, ammonium, and amino acids. Significant incorporation of 13C and/or 15N and growth occurred in response to glucose, pyruvate, and amino acids (∼76% of total cells), whereas acetate and bicarbonate were incorporated without fostering growth. Among those substrates, a maximum substrate assimilation rate was observed at 67 × 10−18 mol/cell per d with bicarbonate. Neither carbon assimilation nor growth was evident in response to methane. The atomic ratios between nitrogen incorporated from ammonium and the total cellular nitrogen consistently exceeded the ratios of carbon, suggesting that subseafloor microbes preferentially require nitrogen assimilation for the recovery in vitro. Our results showed that the most deeply buried subseafloor sedimentary microbes maintain potentials for metabolic activities and that growth is generally limited by energy but not by the availability of C and N compounds. PMID:21987801

Pinus sylvestris switches respiration substrates under shading but not during drought

NASA Astrophysics Data System (ADS)

Hartmann, Henrik; Fischer, Sarah; Hanf, Stefan; Frosch, Torsten; Poppp, Jürgen; Trumbore, Susan

2015-04-01

Reduced carbon assimilation during prolonged drought forces trees to rely on stored carbon to maintain vital processes like respiration. It has been shown, however, that the use of carbohydrates, a major carbon storage pool and main respiratory substrate in plants, strongly declines with deceasing plant hydration. Yet, no empirical evidence has been produced to what degree other carbon storage compounds like lipids and proteins may fuel respiration during drought. We exposed young scots pine trees to carbon limitation using either drought or shading and assessed respiratory substrate use by monitoring the respiratory quotient, δ13C of respired CO2and concentrations of the major storage compounds, i.e. carbohydrates (COH), lipids and amino acids. Generally, respiration was dominated by the most abundant substrate. Only shaded trees shifted from carbohydrate-dominated to lipid-dominated respiration and showed progressive carbohydrate depletion. In drought trees respiration was strongly reduced and fueled with carbohydrates from also strongly reduced carbon assimilation. Initial COH content was maintained during drought probably due to reduced COH mobilization and use and the maintained COH content may have prevented lipid catabolism via sugar signaling. Our results suggest that respiratory substrates other than carbohydrates are used under carbohydrate limitation but not during drought. Thus, respiratory substrate change cannot provide an efficient means to counterbalance carbon limitation under natural drought.

The translational repressor Crc controls the Pseudomonas putida benzoate and alkane catabolic pathways using a multi-tier regulation strategy.

PubMed

Hernández-Arranz, Sofía; Moreno, Renata; Rojo, Fernando

2013-01-01

Metabolically versatile bacteria usually perceive aromatic compounds and hydrocarbons as non-preferred carbon sources, and their assimilation is inhibited if more preferable substrates are available. This is achieved via catabolite repression. In Pseudomonas putida, the expression of the genes allowing the assimilation of benzoate and n-alkanes is strongly inhibited by catabolite repression, a process controlled by the translational repressor Crc. Crc binds to and inhibits the translation of benR and alkS mRNAs, which encode the transcriptional activators that induce the expression of the benzoate and alkane degradation genes respectively. However, sequences similar to those recognized by Crc in benR and alkS mRNAs exist as well in the translation initiation regions of the mRNA of several structural genes of the benzoate and alkane pathways, which suggests that Crc may also regulate their translation. The present results show that some of these sites are functional, and that Crc inhibits the induction of both pathways by limiting not only the translation of their transcriptional activators, but also that of genes coding for the first enzyme in each pathway. Crc may also inhibit the translation of a gene involved in benzoate uptake. This multi-tier approach probably ensures the rapid regulation of pathway genes, minimizing the assimilation of non-preferred substrates when better options are available. A survey of possible Crc sites in the mRNAs of genes associated with other catabolic pathways suggested that targeting substrate uptake, pathway induction and/or pathway enzymes may be a common strategy to control the assimilation of non-preferred compounds. © 2012 Society for Applied Microbiology and Blackwell Publishing Ltd.

Selection of Crop Varieties for Efficient Production Using Urea, Ammonia, Nitrite, and Nitrate in Celss

NASA Technical Reports Server (NTRS)

Huffaker, R. C.

1982-01-01

The presence of NO2(-) in the external solution increased the overall efficiency of the mixed N sources by cereal leaves. The NH4(+) in the substrate solution decreased the efficiency of NO3(-) reduction, while NO3(-) in the substrate solution increased the efficiency of NH4(+) assimilation.

Proteomic-based stable isotope probing reveals taxonomically Distinct Patterns in Amino Acid Assimilation by Coastal Marine Bacterioplankton

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryson, Samuel; Li, Zhou; Pett-Ridge, Jennifer

Heterotrophic marine bacterioplankton are a critical component of the carbon cycle, processing nearly a quarter of annual global primary production, yet defining how substrate utilization preferences and resource partitioning structure these microbial communities remains a challenge. In this study, we utilized proteomics-based stable isotope probing (proteomic SIP) to characterize the assimilation of amino acids by coastal marine bacterioplankton populations. We incubated microcosms of seawater collected from Newport, OR and Monterey Bay, CA with 1 M 13C-amino acids for 15 and 32 hours. Subsequent analysis of 13C incorporation into protein biomass quantified the frequency and extent of isotope enrichment for identifiedmore » proteins. Using these metrics we tested whether amino acid assimilation patterns were different for specific bacterioplankton populations. Proteins associated with Rhodobacterales and Alteromonadales tended to have a significantly high number of tandem mass spectra from 13C-enriched peptides, while Flavobacteriales and SAR11 proteins generally had significantly low numbers of 13C-enriched spectra. Rhodobacterales proteins associated with amino acid transport and metabolism had an increased frequency of 13C-enriched spectra at time-point 2, while Alteromonadales ribosomal proteins were 13C- enriched across time-points. Overall, proteomic SIP facilitated quantitative comparisons of dissolved free amino acids assimilation by specific taxa, both between sympatric populations and between protein functional groups within discrete populations, allowing an unprecedented examination of population-level metabolic responses to resource acquisition in complex microbial communities.« less

Proteomic-based stable isotope probing reveals taxonomically Distinct Patterns in Amino Acid Assimilation by Coastal Marine Bacterioplankton

DOE PAGES

Bryson, Samuel; Li, Zhou; Pett-Ridge, Jennifer; ...

2016-04-26

Heterotrophic marine bacterioplankton are a critical component of the carbon cycle, processing nearly a quarter of annual global primary production, yet defining how substrate utilization preferences and resource partitioning structure these microbial communities remains a challenge. In this study, we utilized proteomics-based stable isotope probing (proteomic SIP) to characterize the assimilation of amino acids by coastal marine bacterioplankton populations. We incubated microcosms of seawater collected from Newport, OR and Monterey Bay, CA with 1 M 13C-amino acids for 15 and 32 hours. Subsequent analysis of 13C incorporation into protein biomass quantified the frequency and extent of isotope enrichment for identifiedmore » proteins. Using these metrics we tested whether amino acid assimilation patterns were different for specific bacterioplankton populations. Proteins associated with Rhodobacterales and Alteromonadales tended to have a significantly high number of tandem mass spectra from 13C-enriched peptides, while Flavobacteriales and SAR11 proteins generally had significantly low numbers of 13C-enriched spectra. Rhodobacterales proteins associated with amino acid transport and metabolism had an increased frequency of 13C-enriched spectra at time-point 2, while Alteromonadales ribosomal proteins were 13C- enriched across time-points. Overall, proteomic SIP facilitated quantitative comparisons of dissolved free amino acids assimilation by specific taxa, both between sympatric populations and between protein functional groups within discrete populations, allowing an unprecedented examination of population-level metabolic responses to resource acquisition in complex microbial communities.« less

Chromatic assimilation unaffected by perceived depth of inducing light.

PubMed

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.

The relative importance of exogenous and substrate-derived nitrogen for microbial growth during leaf decomposition

Treesearch

B.M. Cheever; J. R. Webster; E. E. Bilger; S. A. Thomas

2013-01-01

Heterotrophic microbes colonizing detritus obtain nitrogen (N) for growth by assimilating N from their substrate or immobilizing exogenous inorganic N. Microbial use of these two pools has different implications for N cycling and organic matter decomposition in the face of the global increase in biologically available N. We used sugar maple leaves labeled with

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

PubMed

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.

Isolation and growth characteristics of an EDTA-degrading member of the alpha-subclass of Proteobacteria.

PubMed

Weilenmann, Hans-Ueli; Engeli, Barbara; Bucheli-Witschel, Margarete; Egli, Thomas

2004-10-01

A Gram-negative, ethylenediaminetetraacetic acid (EDTA)-degrading bacterium (deposited at the German Culture Collection as strain DSM 9103) utilising EDTA as the only source of carbon, energy and nitrogen was isolated from a mixed EDTA-degrading population that was originally enriched in a column system from a mixture of activated sludge and soil. Chemotaxonomic analysis of quinones, polar lipids and fatty acids allowed allocation of the isolate to the alpha-subclass of Proteobacteria. 16S rDNA sequencing and phylogenetic analysis revealed highest similarity to the Mesorhizobium genus followed by the Aminobacter genus. However, the EDTA-degrading strain apparently forms a new branch within the Phyllobacteriaceae/Mesorhizobia family. Growth of the strain was rather slow not only on EDTA (micro(max) = 0.05 h(-1)) but also on other substrates. Classical substrate utilisation testing in batch culture suggested a quite restricted carbon source spectrum with only lactate, glutamate, and complexing agents chemically related to EDTA (nitrilotriacetate, iminodiacetate and ethylenediaminedisuccinate) supporting growth. However, when EDTA-limited continuous cultures of strain DSM 9103 were pulsed with fumarate, succinate, glucose or acetate, these substrates were assimilated immediately. Apparently, the strain can use a broader spectrum than indicated by traditional substrate testing techniques. The EDTA species CaEDTA and MgEDTA served as growth substrates of the strain because in the mineral medium employed EDTA was predicted to be mainly present in the form of these two complexes. The bacterium was not able to degrade Fe3+-complexed EDTA.

Single-cell measurement of archaeal and bacterial carbon assimilation in dark Pacific Ocean waters

NASA Astrophysics Data System (ADS)

Dekas, A. E.; Mayali, X.; Parada, A. E.; Fuhrman, J. A.; Weber, P. K.; Pett-Ridge, J.

2016-02-01

Microbial activity in the dark ocean plays a critical role in nutrient and elemental cycling. Here, we investigated the activity of archaea and bacteria on the single-cell level during dark incubations of Pacific Ocean water, and specifically their capacity for chemoautotrophy. Samples were collected 19 km off the coast of Los Angeles, at a depth of 150 m, and off the coast of San Francisco, at the surface. Incubations were amended with isotopically-labeled organic or inorganic carbon (13C-bicarbonate, 15N-amino acids or dual-labeled 13C-15N-amino acids), and uptake was detected using nanoscale secondary ion mass spectrometry (NanoSIMS). We analyzed 4,968 individual cells using an automated NanoSIMS analysis with particle-recognition software. After 7 days, 95% and 89% of cells (deep and shallow, respectively) demonstrated anabolic activity, i.e., incorporation of at least one isotopically-labeled substrate. Chemoautotrophy was detected at both sites, with 36% and 9% of cells (deep and shallow, respectively) assimilating 13C-bicarbonate in the dark. Fluorescence in situ hybridization coupled to NanoSIMS analysis was performed to link 16S rRNA phylogeny to patterns of C-assimilation. Thaumarchaea were found to dominate chemoautotrophy at both sites, with 13C-bicarbonate assimilation in nearly all cells hybridized with the Cren537 probe, but none hybridized with a general bacterial probe (Eub338). Conversely, widespread assimilation of both 15N and 13C from 15N-13C-amino acids was observed in the bacterial assemblage, but not in the Thaumarchaea. Interestingly, Thaumarchaeal cells were enriched in 15N after incubation with 15N-13C-amino acids, but not 13C, suggesting selective N assimilation from amino acids or substrate recycling. Together, our results demonstrate the value of single-cell measurements in characterizing patterns of C metabolism in mixed microbial community, and underscore the importance of Thaumarchaea in marine chemoautotrophy.

Efficiency of N use by wheat as a function of influx and efflux of NO3

NASA Technical Reports Server (NTRS)

Huffaker, R. C.; Aslam, M.; Ward, M. R.

1990-01-01

Since N assimilation is one of the most costly functions of a plant, its efflux before assimilation results in a serious energy cost and loss in efficiency which could decrease yields. Efficient crop production is critical to the Closed Ecology Life Support System (CELSS). The objective is to determine the extent of efflux of the N species NO3(-), NH4(+), NO2(-), and urea after uptake, and possible means of regulation. Researchers found that NO3 efflux became serious as its substrate level increased. Efflux/Influx (E/I) of NO3(-) was greater in darkness (35 percent) than in light (14 percent), and the ratio greatly increased with substrate NO3 (-), (up to 45 percent at 10 mM). It seems advantageous to use the lowest possible nutrient concentration of NO3(-). The feasibility of using ClO3(-) was assessed and its toxicity determined.

Influence of substrate surface loading on the kinetic behaviour of aerobic granules.

PubMed

Liu, Yu; Liu, Yong-Qiang; Wang, Zhi-Wu; Yang, Shu-Fang; Tay, Joo-Hwa

2005-06-01

In the aerobic granular sludge reactor, the substrate loading is related to the size of the aerobic granules cultivated. This study investigated the influence of substrate surface loading on the growth and substrate-utilization kinetics of aerobic granules. Results showed that microbial surface growth rate and surface biodegradation rate are fairly related to the substrate surface loading by the Monod-type equation. In this study, both the theoretical maximum growth yield and the Pirt maintenance coefficient were determined. It was found that the estimated theoretical maximum growth yield of aerobic granules was as low as 0.2 g biomass g(-1) chemical oxygen demand (COD) and 10-40% of input substrate-COD was consumed through the maintenance metabolism, while experimental results further showed that the unit oxygen uptake by aerobic granules was 0.68 g oxygen g(-1) COD, which was much higher than that reported in activated sludge processes. Based on the growth yield and unit oxygen uptake determined, an oxidative assimilation equation of acetate-fed aerobic granules was derived; and this was confirmed by respirometric tests. In aerobic granular culture, about 74% of the input substrate-carbon was converted to carbon dioxide. The growth yield of aerobic granules was three times lower than that of activated sludge. It is likely that high carbon dioxide production is the main cause of the low growth yield of aerobic granules, indicating a possible energy uncoupling in aerobic granular culture.

In-Situ 13C-Labeling of Microbial Phospholipid Fatty Acids: Tracing Substrate Assimilation in a Petroleum-Contaminated Aquifer

NASA Astrophysics Data System (ADS)

Pombo, S. A.; Schroth, M. H.; Pelz, O.; Zeyer, J.

2001-12-01

Stable isotope analysis of phospholipid-derived fatty acids (PLFA) is a novel tool to trace assimilation of organic carbon in microbial communities. The 13C-labeling of biomarker fatty acids allows the identification of specific microbial populations involved in the metabolism of particular substrates, supplemented in 13C-labeled form. The goal of this study was to investigate the feasibility of 13C-labeling of PLFA and produced dissolved inorganic carbon (DIC) in a petroleum hydrocarbon (PHC)-contaminated aquifer during an in-situ experiment. To this end, we performed a single-well "push-pull" test in a monitoring well located in the denitrifying zone of a PHC-contaminated aquifer in Studen, Switzerland. During the experiment, we injected 500 L of site groundwater that was amended with 13C-labeled acetate (50% [2-13C]) and nitrate as reactants, and bromide as conservative tracer. Following the injection, we extracted a total of 1000 L of test solution/groundwater mixture after 4, 23 and 46 h from the same location. Concentrations of anions were measured in samples collected during the extraction. From these data, we computed first order rate coefficients for consumption of acetate (0.70 +/- 0.05 1/d) and nitrate (0.63 +/- 0.08 1/d). In addition, we extracted and identified PLFA, and measured \\delta13C values of PLFA and DIC. After only 4 h of incubation, we detected 13C-enrichment of certain PLFA in suspended biomass of extracted groundwater. After 46 h, we measured enrichments of up to 5000 per mil in certain PLFA (e.g. 16:1ω 7c), and up to 1500 per mil in the produced DIC. Our results demonstrate the feasibility of in-situ 13C-labeling of PLFA and DIC using push-pull tests to determine microbial activities in-situ in a natural ecosystem.

Testing the Data Assimilation Capability of the Profiler Virtual Module

DTIC Science & Technology

2016-02-01

ARL-TR-7601 ● FEB 2016 US Army Research Laboratory Testing the Data Assimilation Capability of the Profiler Virtual Module by...originator. ARL-TR-7601 ● FEB 2016 US Army Research Laboratory Testing the Data Assimilation Capability of the Profiler Virtual...hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and

Modulation of intestinal sulfur assimilation metabolism regulates iron homeostasis

PubMed Central

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

Feasibility of co-composting of sewage sludge, spent mushroom substrate and wheat straw.

PubMed

Meng, Liqiang; Li, Weiguang; Zhang, Shumei; Wu, Chuandong; Lv, Longyi

2017-02-01

In this study, the lab-scale co-composting of sewage sludge (SS) with mushroom substrate (SMS) and wheat straw (WS) conducted for 20days was evaluated. The addition of SMS evidently increased CO 2 production and dehydrogenase activity. The combined addition of SMS and WS significantly improved the compost quality in terms of temperature, organic matter degradation and germination index, especially, reduced 21.9% of NH 3 emission. That's because SMS and WS possessed the complementarity of free air space and contained plenty of degradable carbon source. The SMS could create a comfortable environment for the nitrifying bacteria and improve nitrification. The carbohydrates from combined addition of SMS and WS could be utilized by thermophilic microorganisms, stimulate ammonia assimilation and reduce NH 3 emission. These results suggested that adding SMS and WS could not only improve the degradation of organic matter and the quality of compost product, but also stimulate ammonia assimilation and reduce ammonia emission. Copyright © 2016. Published by Elsevier Ltd.

Efficiency of N use by wheat as a function of influx and efflux of NO sub 3

NASA Technical Reports Server (NTRS)

Huffaker, R. C.; Aslam, M.; Ward, M. R.

1989-01-01

Since N assimilation is one of the most costly functions of a plant, its efflux before assimilation results in a serious energy cost and loss in efficiency which could decrease yields. Efficient crop production is critical to the Controlled Ecological Life-Support System (CELSS). The objective is to determine the extent of efflux of the N species NO3(-), NH4(+), NO2(-), and urea after uptake, and possible means of regulation. It was found that NO3(-) efflux became serious as its substrate level increased. Efflux/Influx (E/I) of 3NO3(-) was greater in darkness (35 pct) than in light (14 pct) and the ratio greatly increased with increased substrate NO3(-), (up to 45 pct at 10 mM). It seems advantageous to use the lowest possible nutrient concentration of NO3(-). The feasibility of using ClO3(-) as a trapping agent (competitive inhibitor of NO3(-) uptake) for effluxed NO3(-) was assessed and its toxicity determined.

Dietary bioavailability of Cu adsorbed to colloidal hydrous ferric oxide

USGS Publications Warehouse

Cain, Daniel J.; Croteau, Marie-Noële; Fuller, Christopher C.

2013-01-01

The dietary bioavailability of copper (Cu) adsorbed to synthetic colloidal hydrous ferric oxide (HFO) was evaluated from the assimilation of 65Cu by two benthic grazers, a gastropod and a larval mayfly. HFO was synthesized, labeled with 65Cu to achieve a Cu/Fe ratio comparable to that determined in naturally formed HFO, and then aged. The labeled colloids were mixed with a food source (the diatom Nitzschia palea) to yield dietary 65Cu concentrations ranging from 211 to 2204 nmol/g (dry weight). Animals were pulse fed the contaminated diet and assimilation of 65Cu from HFO was determined following 1–3 days of depuration. Mass transfer of 65Cu from HFO to the diatom was less than 1%, indicating that HFO was the source of 65Cu to the grazers. Estimates of assimilation efficiency indicated that the majority of Cu ingested as HFO was assimilated (values >70%), implying that colloidal HFO potentially represents a source of dietary Cu to benthic grazers, especially where there is active formation and infiltration of these particles into benthic substrates.

Assimilation of organic and inorganic nutrients by Erica root fungi from the fynbos ecosystem.

PubMed

Bizabani, Christine; Dames, Joanna Felicity

2016-03-01

Erica dominate the fynbos ecosystem, which is characterized by acidic soils that are rich in organic matter. The ericaceae associate with ericoid mycorrhizal (ERM) fungi for survival. In this study fungal biomass accumulation in vitro was used to determine nutrient utilisation of various inorganic and organic substrates. This is an initial step towards establishment of the ecological roles of typical ERM fungi and other root fungi associated with Erica plants, with regard to host nutrition. Meliniomyces sp., Acremonium implicatum, Leohumicola sp., Cryptosporiopsis erica, Oidiodendron maius and an unidentified Helotiales fungus were selected from fungi previously isolated and identified from Erica roots. Sole nitrogen sources ammonium, nitrate, arginine and Bovine Serum Albumin (BSA) were tested. Meliniomyces and Leohumicola species were able to utilise BSA effectively. Phosphorus nutrition was tested using orthophosphate, sodium inositol hexaphosphate and DNA. Most isolates preferred orthophosphate. Meliniomyces sp. and A. implicatum were able to accumulate significant biomass using DNA. Carbon utilisation was tested using glucose, cellobiose, carboxymethylcellulose, pectin and tannic acid substrates. All fungal isolates produced high biomass on glucose and cellobiose. The ability to utilize organic nutrient sources in culture, illustrates their potential role of these fungi in host nutrition in the fynbos ecosystem. Copyright © 2015 The British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Disconfirmed hedonic expectations produce perceptual contrast, not assimilation.

PubMed

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.

Data assimilation of non-conventional observations using GEOS-R flash lightning: 1D+4D-VAR approach vs. assimilation of images (Invited)

NASA Astrophysics Data System (ADS)

Navon, M. I.; Stefanescu, R.

2013-12-01

Previous assimilation of lightning used nudging approaches. We develop three approaches namely, 3D-VAR WRFDA and1D+nD-VAR (n=3,4) WRFDA . The present research uses Convective Available Potential Energy (CAPE) as a proxy between lightning data and model variables. To test performance of aforementioned schemes, we assess quality of resulting analysis and forecasts of precipitation compared to those from a control experiment and verify them against NCEP stage IV precipitation. Results demonstrate that assimilating lightning observations improves precipitation statistics during the assimilation window and for 3-7 h thereafter. The 1D+4D-VAR approach yielded the best performance significantly improving precipitation rmse errors by 25% and 27.5%,compared to control during the assimilation window for two tornadic test cases. Finally we propose a new approach to assimilate 2-D images of lightning flashes based on pixel intensity, mitigating dimensionality by a reduced order method.

Assimilative domain proficiency and performance in chemistry coursework

NASA Astrophysics Data System (ADS)

Byrnes, Scott William

The assimilation and synthesis of knowledge is essential for students to be successful in chemistry, yet not all students synthesize knowledge as intended. The study used the Learning Preference Checklist to classify students into one of three learning modalities -- visual, auditory, or kinesthetic (VAK). It also used the Kolb Learning Style Inventory (KLSI), which utilizes four learning domains - Converging, Accommodating, Diverging, and Assimilating - to explain the students' maturation process by showing shift from any domain towards the Assimilating domain. A shift approaching this domain was considered as improvement in the assimilation and synthesis of knowledge. This pre-experimental one-group pretest-posttest study was used to test the hypothesis that modifying a high school chemistry curriculum to accentuate a student's learning preference would result in a shift towards the Assimilative domain on the KLSI and if there was a correlation between the improvement in student learning and a shift towards the KLSI Assimilating domain. Forty-two high school students were issued the VAK and provided with differentiated instruction via homologous cooperative learning groups. Pre- and post-KLSI and chemistry concepts tests were administered. T test analyses showed no significant shift towards the Assimilating domain. Further Pearson's r analyses showed no significant correlation between the KLSI and exam scores. This study contributes to social change by providing empirical evidence related to the effectiveness infusing learning styles into the science curriculum and the integration of the KLSI to monitor cognitive development as tools in raising standardized test scores and enhancing academic achievement. Results from the study can also inform future research into learning styles through their incorporation into the science curriculum.

Ecophysiology of horse chestnut (Aesculus Hippocastanum L.) in degraded and restored urban sites

Treesearch

Jacek Oleksyn; Brian D. Kloeppel; Szymon Lukasiewicz; Piotr Karolewski; Peter B. Reich

2007-01-01

We explored changes in growth, phenology, net CO2 assimilation rate, water use efficiency, secondary defense compounds, substrate and foliage nutrient concentration of a degraded urban horse chestnut (Aesculus hippocastanum L.) site restored for three years using mulching (tree branches including foliage) and fertilization (...

Acetate Dissimilation and Assimilation in Mycobacterium tuberculosis Depend on Carbon Availability

PubMed Central

Rücker, Nadine; Billig, Sandra; Bücker, René; Jahn, Dieter

2015-01-01

ABSTRACT Mycobacterium tuberculosis persists inside granulomas in the human lung. Analysis of the metabolic composition of granulomas from guinea pigs revealed that one of the organic acids accumulating in the course of infection is acetate (B. S. Somashekar, A. G. Amin, C. D. Rithner, J. Troudt, R. Basaraba, A. Izzo, D. C. Crick, and D. Chatterjee, J Proteome Res 10:4186–4195, 2011, doi:http://dx.doi.org/10.1021/pr2003352), which might result either from metabolism of the pathogen or might be provided by the host itself. Our studies characterize a metabolic pathway by which M. tuberculosis generates acetate in the cause of fatty acid catabolism. The acetate formation depends on the enzymatic activities of Pta and AckA. Using actyl coenzyme A (acetyl-CoA) as a substrate, acetyl-phosphate is generated and finally dephosphorylated to acetate, which is secreted into the medium. Knockout mutants lacking either the pta or ackA gene showed significantly reduced acetate production when grown on fatty acids. This effect is even more pronounced when the glyoxylate shunt is blocked, resulting in higher acetate levels released to the medium. The secretion of acetate was followed by an assimilation of the metabolite when other carbon substrates became limiting. Our data indicate that during acetate assimilation, the Pta-AckA pathway acts in concert with another enzymatic reaction, namely, the acetyl-CoA synthetase (Acs) reaction. Thus, acetate metabolism might possess a dual function, mediating an overflow reaction to release excess carbon units and resumption of acetate as a carbon substrate. IMPORTANCE During infection, host-derived lipid components present the major carbon source at the infection site. β-Oxidation of fatty acids results in the formation of acetyl-CoA. In this study, we demonstrate that consumption of fatty acids by Mycobacterium tuberculosis activates an overflow mechanism, causing the pathogen to release excess carbon intermediates as acetate. The Pta-AckA pathway mediating acetate formation proved to be reversible, enabling M. tuberculosis to reutilize the previously secreted acetate as a carbon substrate for metabolism. PMID:26216844

Isolation of digested sludge-assimilating fungal strains and their potential applications.

PubMed

Fujii, K; Kai, Y; Matsunobu, S; Sato, H; Mikami, A

2013-09-01

Digested sludge (DS) is a major waste product of anaerobic digestion of sewage sludge and is resistant to biodegradation. In this study, we isolated and characterized DS-assimilating fungi from soil. We tried to isolate DS-assimilating strains by enrichment culture using DS as the nutrient source, but microbial growth was not observed in any culture. To eliminate the inhibitory effect of metals in DS on microbial growth, acid-treated DS was subsequently used for enrichment, and eight fungal strains were isolated from the subcultures. At least 10-30% reduction in sludge was observed after 1-week cultivation, and prolonged cultivation led to further sludge reduction. All isolates produced xylanase, chitinase and keratinase. Phylogenetic analysis revealed that the isolates were Penicillium, Fusarium, Chaetomium, Cunninghamella, Neosartorya and Umbelopsis. Some isolates were suggested novel species. To the best of our knowledge, our study is the first to report the isolation of DS-assimilating strains. These isolates may be useful for commercial production of microbial enzymes using DS as the substrate. Because xylan, chitin and keratin in sludge-hyphae complexes are considered to be partially depolymerized, this material could also be utilized as a readily available fertilizer. © 2013 The Society for Applied Microbiology.

RNA-Based Stable Isotope Probing Suggests Allobaculum spp. as Particularly Active Glucose Assimilators in a Complex Murine Microbiota Cultured In Vitro

PubMed Central

Herrmann, Elena; Young, Wayne; Rosendale, Douglas; Reichert-Grimm, Verena; Conrad, Ralf

2017-01-01

RNA-based stable isotope probing (RNA-SIP) and metabolic profiling were used to detect actively glucose-consuming bacteria in a complex microbial community obtained from a murine model system. A faeces-derived microbiota was incubated under anaerobic conditions for 0, 2, and 4 h with 40 mM [U13C]glucose. Isopycnic density gradient ultracentrifugation and fractionation of isolated RNA into labeled and unlabeled fractions followed by 16S rRNA sequencing showed a quick adaptation of the bacterial community in response to the added sugar, which was dominated by unclassified Lachnospiraceae species. Inspection of distinct fractions of isotope-labeled RNA revealed Allobaculum spp. as particularly active glucose utilizers in the system, as the corresponding RNA showed significantly higher proportions among the labeled RNA. With time, the labeled sugar was used by a wider spectrum of faecal bacteria. Metabolic profiling indicated rapid fermentation of [U13C]glucose, with lactate, acetate, and propionate being the principal 13C-labeled fermentation products, and suggested that “cross-feeding” occurred in the system. RNA-SIP combined with metabolic profiling of 13C-labeled products allowed insights into the microbial assimilation of a general model substrate, demonstrating the appropriateness of this technology to study assimilation processes of nutritionally more relevant substrates, for example, prebiotic carbohydrates, in the gut microbiota of mice as a model system. PMID:28299315

Sensitive and substrate-specific detection of metabolically active microorganisms in natural microbial consortia using community isotope arrays.

PubMed

Tourlousse, Dieter M; Kurisu, Futoshi; Tobino, Tomohiro; Furumai, Hiroaki

2013-05-01

The goal of this study was to develop and validate a novel fosmid-clone-based metagenome isotope array approach - termed the community isotope array (CIArray) - for sensitive detection and identification of microorganisms assimilating a radiolabeled substrate within complex microbial communities. More specifically, a sample-specific CIArray was used to identify anoxic phenol-degrading microorganisms in activated sludge treating synthetic coke-oven wastewater in a single-sludge predenitrification-nitrification process. Hybridization of the CIArray with DNA from the (14) C-phenol-amended sample indicated that bacteria assimilating (14) C-atoms, presumably directly from phenol, under nitrate-reducing conditions were abundant in the reactor, and taxonomic assignment of the fosmid clone end sequences suggested that they belonged to the Gammaproteobacteria. The specificity of the CIArray was validated by quantification of fosmid-clone-specific DNA in density-resolved DNA fractions from samples incubated with (13) C-phenol, which verified that all CIArray-positive probes stemmed from microorganisms that assimilated isotopically labeled carbon. This also demonstrated that the CIArray was more sensitive than DNA-SIP, as the former enabled positive detection at a phenol concentration that failed to yield a 'heavy' DNA fraction. Finally, two operational taxonomic units distantly related to marine Gammaproteobacteria were identified to account for more than half of 16S rRNA gene clones in the 'heavy' DNA library, corroborating the CIArray-based identification. © 2013 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

A short note on the assimilation of collocated and concurrent GPS and ionosonde data into the Electron Density Assimilative Model

NASA Astrophysics Data System (ADS)

Angling, M. J.; Jackson-Booth, N. K.

2011-12-01

The Electron Density Assimilative Model (EDAM) has been developed to provide real-time characterizations of the ionosphere by assimilating diverse data sets into a background model. Techniques have been developed to assimilate virtual height ionogram traces rather than relying on true height inversions. A test assimilation has been conducted using both GPS and ionosonde data as input. Postassimilation analysis shows that foF2 residuals can be degraded when only GPS data are assimilated. It has also been demonstrated that by using both data types it is possible to have low total electron content and foF2 residuals and that this is achieved by modifying the ionospheric slab thickness.

Torque Balances on the Taylor Cylinders in the Geomagnetic Data Assimilation

NASA Technical Reports Server (NTRS)

Kuang, Weijia; Tangborn, Andrew

2004-01-01

In this presentation we report on our continuing effort in geomagnetic data assimilation, aiming at understanding and predicting geomagnetic secular variation on decadal time scales. In particular, we focus on the effect of the torque balances on the cylindrical surfaces in the core co-axial with the Earth's rotation axis (the Taylor cylinders) on the time evolution of assimilated solutions. We use our MoSST core dynamics,model and observed geomagnetic field at the Earth's surface derived via Comprehensive Field Model (CFM) for the geomagnetic data assimilation. In our earlier studies, a model solution is selected randomly from our numerical database. It is then assimilated with the observations such that the poloidal field possesses the same field tomography on the core-mantel boundary (CMB) continued downward from surface observations. This tomography change is assumed to be effective through out the outer core. While this approach allows rapid convergence between model solutions and the observations, it also generates sevee numerical instabilities: the delicate balance between weak fluid inertia and the magnetic torques on the Taylor cylinders are completely altered. Consequently, the assimilated solution diverges quickly (in approximately 10% of the magnetic free-decay time in the core). To improve the assimilation, we propose a partial penetration of the assimilation from the CMB: The full-scale modification at the CMB decreases linearly and vanish at an interior radius r(sub a). We shall examine from our assimilation tests possible relationships between the convergence rate of the model solutions to observations and the cut-off radius r(sub a). A better assimilation shall serve our nudging tests in near future.

Torque Balances on the Taylor Cylinders in the Geomagnetic Data Assimilation

NASA Astrophysics Data System (ADS)

Kuang, W.; Tangborn, A.

2004-05-01

In this presentation we report on our continuing effort in geomagnetic data assimilation, aiming at understanding and predicting geomagnetic secular variation on decadal time scales. In particular, we focus on the effect of the torque balances on the cylindrical surfaces in the core co-axial with the Earth's rotation axis (the Taylor cylinders) on the time evolution of assimilated solutions. We use our MoSST core dynamics model and observed geomagnetic field at the Earth's surface derived via Comprehensive Field Model (CFM) for the geomagnetic data assimilation. In our earlier studies, a model solution is selected randomly from our numerical database. It is then assimilated with the observations such that the poloidal field possesses the same field tomography on the core-mantel boundary (CMB) continued downward from surface observations. This tomography change is assumed to be effective through out the outer core. While this approach allows rapid convergence between model solutions and the observations, it also generates sever numerical instabilities: the delicate balance between weak fluid inertia and the magnetic torques on the Taylor cylinders are completely altered. Consequently, the assimilated solution diverges quickly (in approximately 10% of the magnetic free-decay time in the core). To improve the assimilation, we propose a partial penetration of the assimilation from the CMB: The full-scale modification at the CMB decreases linearly and vanish at an interior radius ra. We shall examine from our assimilation tests possible relationships between the convergence rate of the model solutions to observations and the cut-off radius ra. A better assimilation shall serve our nudging tests in near future.

Over Expression of Sedoheptulose 1,7, bisphosphatase (SBPase) Significantly Improves Carbon Assimilation at Elevated CO2

USDA-ARS?s Scientific Manuscript database

Biochemical models of photosynthesis (A) show that it is most frequently limited by the slowest of two processes, maximum carboxylation capacity of the enzyme Rubisco (Vc,max) or the regeneration of RuBP via electron transport (J). At current CO2 levels Rubisco is not saturated by its substrate, the...

One-dimensional soil temperature assimilation experiment based on unscented particle filter and Common Land Model

NASA Astrophysics Data System (ADS)

Fu, Xiao Lei; Jin, Bao Ming; Jiang, Xiao Lei; Chen, Cheng

2018-06-01

Data assimilation is an efficient way to improve the simulation/prediction accuracy in many fields of geosciences especially in meteorological and hydrological applications. This study takes unscented particle filter (UPF) as an example to test its performance at different two probability distribution, Gaussian and Uniform distributions with two different assimilation frequencies experiments (1) assimilating hourly in situ soil surface temperature, (2) assimilating the original Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) once per day. The numerical experiment results show that the filter performs better when increasing the assimilation frequency. In addition, UPF is efficient for improving the soil variables (e.g., soil temperature) simulation/prediction accuracy, though it is not sensitive to the probability distribution for observation error in soil temperature assimilation.

Oxidation and Assimilation of Carbohydrates by Micrococcus sodonensis1

PubMed Central

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

A Global Carbon Assimilation System using a modified EnKF assimilation method

NASA Astrophysics Data System (ADS)

Zhang, S.; Zheng, X.; Chen, Z.; Dan, B.; Chen, J. M.; Yi, X.; Wang, L.; Wu, G.

2014-10-01

A Global Carbon Assimilation System based on Ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 abundance data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is based on the ensemble Kalman filter (EnKF), but with several new developments, including using analysis states to iteratively estimate ensemble forecast errors, and a maximum likelihood estimation of the inflation factors of the forecast and observation errors. The proposed assimilation approach is tested in observing system simulation experiments and then used to estimate the terrestrial ecosystem carbon fluxes and atmospheric CO2 distributions from 2002 to 2008. The results showed that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.

Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

NASA Astrophysics Data System (ADS)

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.

Extracellular enzyme kinetics scale with resource availability

USGS Publications Warehouse

Sinsabaugh, Robert L.; Belnap, Jayne; Findlay, Stuart G.; Follstad Shah, Jennifer J.; Hill, Brian H.; Kuehn, Kevin A.; Kuske, Cheryl; Litvak, Marcy E.; Martinez, Noelle G.; Moorhead, Daryl L.; Warnock, Daniel D.

2014-01-01

Microbial community metabolism relies on external digestion, mediated by extracellular enzymes that break down complex organic matter into molecules small enough for cells to assimilate. We analyzed the kinetics of 40 extracellular enzymes that mediate the degradation and assimilation of carbon, nitrogen and phosphorus by diverse aquatic and terrestrial microbial communities (1160 cases). Regression analyses were conducted by habitat (aquatic and terrestrial), enzyme class (hydrolases and oxidoreductases) and assay methodology (low affinity and high affinity substrates) to relate potential reaction rates to substrate availability. Across enzyme classes and habitats, the scaling relationships between apparent Vmax and apparent Km followed similar power laws with exponents of 0.44 to 0.67. These exponents, called elasticities, were not statistically distinct from a central value of 0.50, which occurs when the Km of an enzyme equals substrate concentration, a condition optimal for maintenance of steady state. We also conducted an ecosystem scale analysis of ten extracellular hydrolase activities in relation to soil and sediment organic carbon (2,000–5,000 cases/enzyme) that yielded elasticities near 1.0 (0.9 ± 0.2, n = 36). At the metabolomic scale, the elasticity of extracellular enzymatic reactions is the proportionality constant that connects the C:N:P stoichiometries of organic matter and ecoenzymatic activities. At the ecosystem scale, the elasticity of extracellular enzymatic reactions shows that organic matter ultimately limits effective enzyme binding sites. Our findings suggest that one mechanism by which microbial communities maintain homeostasis is regulating extracellular enzyme expression to optimize the short-term responsiveness of substrate acquisition. The analyses also show that, like elemental stoichiometry, the fundamental attributes of enzymatic reactions can be extrapolated from biochemical to community and ecosystem scales.

Integrating microbial physiology and enzyme traits in the quality model

NASA Astrophysics Data System (ADS)

Sainte-Marie, Julien; Barrandon, Matthieu; Martin, Francis; Saint-André, Laurent; Derrien, Delphine

2017-04-01

Microbe activity plays an undisputable role in soil carbon storage and there have been many calls to integrate microbial ecology in soil carbon (C) models. With regard to this challenge, a few trait-based microbial models of C dynamics have emerged during the past decade. They parameterize specific traits related to decomposer physiology (substrate use efficiency, growth and mortality rates...) and enzyme properties (enzyme production rate, catalytic properties of enzymes…). But these models are built on the premise that organic matter (OM) can be represented as one single entity or are divided into a few pools, while organic matter exists as a continuum of many different compounds spanning from intact plant molecules to highly oxidised microbial metabolites. In addition, a given molecule may also exist in different forms, depending on its stage of polymerization or on its interactions with other organic compounds or mineral phases of the soil. Here we develop a general theoretical model relating the evolution of soil organic matter, as a continuum of progressively decomposing compounds, with decomposer activity and enzyme traits. The model is based on the notion of quality developed by Agren and Bosatta (1998), which is a measure of molecule accessibility to degradation. The model integrates three major processes: OM depolymerisation by enzyme action, OM assimilation and OM biotransformation. For any enzyme, the model reports the quality range where this enzyme selectively operates and how the initial quality distribution of the OM subset evolves into another distribution of qualities under the enzyme action. The model also defines the quality range where the OM can be uptaken and assimilated by microbes. It finally describes how the quality of the assimilated molecules is transformed into another quality distribution, corresponding to the decomposer metabolites signature. Upon decomposer death, these metabolites return to the substrate. We explore here the how microbial physiology and enzyme traits can be incorporated in a model based on a continuous representation of the organic matter and evaluate how it can improve our ability to predict soil C cycling. To do so, we analyse the properties of the model by implementing different scenarii and test the sensitivity of its parameters. Agren, G. I., & Bosatta, E. (1998). Theoretical ecosystem ecology: understanding element cycles. Cambridge University Press.

Environmental Controls of Microbial Resource Partitioning in Soils

NASA Astrophysics Data System (ADS)

Kandeler, Ellen; Poll, Christian; Kramer, Susanne; Mueller, Karolin; Marhan, Sven

2015-04-01

The mineralization and flow of plant-derived carbon in soils is relevant to global carbon cycling. Current models of organismic carbon fluxes in soil assume that separate bacterial and fungal energy channels exist in soil. Recent studies disentangle the herbivore and detritivore pathways of microbial resource use, identify the key players contributing to these two different pathways, and determine to what extent microbial substrate use is affected by environmental controls. To follow the kinetics of litter and root decomposition and to quantify the contribution of key players, it is necessary to use isotopic approaches like PLFA-SIP and ergosterol-SIP. It was shown that bacteria and sugar consuming fungi initiated litter decomposition in an incubation experiment during the first two weeks, whereas higher fungi started to grow after the depletion of low molecular weight substrates. Analyses of PLFA-SIP revealed, for example, that fungi assimilated C directly from the litter, whereas bacteria took up substrates in the soil and therefore depended more on external transport processes than fungi. In addition, we will present data from a field experiment showing the incorporation of root and shoot litter C into organic and microbial C pools under field conditions over a period of two years. Similar amounts of C derived from the two resources differing in substrate quality and amount were incorporated into microbial C and ergosterol pools over time, indicating the importance of root-derived C for the soil food web. High incorporation of maize C (up to 76%) into ergosterol suggests fast and high assimilation of maize C into fungal biomass. Nevertheless, there is still a debate whether bacteria, archaea and fungi start feeding on new substrates at the same time or if their activity occurs at different successional stages. This presentation gives a summery of current knowledge on microbial resource partitioning under lab and field conditions.

Ontogenetic scaling of metabolism, growth, and assimilation: testing metabolic scaling theory with Manduca sexta larvae.

PubMed

Sears, Katie E; Kerkhoff, Andrew J; Messerman, Arianne; Itagaki, Haruhiko

2012-01-01

Metabolism, growth, and the assimilation of energy and materials are essential processes that are intricately related and depend heavily on animal size. However, models that relate the ontogenetic scaling of energy assimilation and metabolism to growth rely on assumptions that have yet to be rigorously tested. Based on detailed daily measurements of metabolism, growth, and assimilation in tobacco hornworms, Manduca sexta, we provide a first experimental test of the core assumptions of a metabolic scaling model of ontogenetic growth. Metabolic scaling parameters changed over development, in violation of the model assumptions. At the same time, the scaling of growth rate matches that of metabolic rate, with similar scaling exponents both across and within developmental instars. Rates of assimilation were much higher than expected during the first two instars and did not match the patterns of scaling of growth and metabolism, which suggests high costs of biosynthesis early in development. The rapid increase in size and discrete instars observed in larval insect development provide an ideal system for understanding how patterns of growth and metabolism emerge from fundamental cellular processes and the exchange of materials and energy between an organism and its environment.

Hydrologic and geochemical data assimilation at the Hanford 300 Area

NASA Astrophysics Data System (ADS)

Chen, X.; Hammond, G. E.; Murray, C. J.; Zachara, J. M.

2012-12-01

In modeling the uranium migration within the Integrated Field Research Challenge (IFRC) site at the Hanford 300 Area, uncertainties arise from both hydrologic and geochemical sources. The hydrologic uncertainty includes the transient flow boundary conditions induced by dynamic variations in Columbia River stage and the underlying heterogeneous hydraulic conductivity field, while the geochemical uncertainty is a result of limited knowledge of the geochemical reaction processes and parameters, as well as heterogeneity in uranium source terms. In this work, multiple types of data, including the results from constant-injection tests, borehole flowmeter profiling, and conservative tracer tests, are sequentially assimilated across scales within a Bayesian framework to reduce the hydrologic uncertainty. The hydrologic data assimilation is then followed by geochemical data assimilation, where the goal is to infer the heterogeneous distribution of uranium sources using uranium breakthrough curves from a desorption test that took place at high spring water table. We demonstrate in our study that Ensemble-based data assimilation techniques (Ensemble Kalman filter and smoother) are efficient in integrating multiple types of data sequentially for uncertainty reduction. The computational demand is managed by using the multi-realization capability within the parallel PFLOTRAN simulator.

Improvement of aerosol optical properties modeling over Eastern Asia with MODIS AOD assimilation in a global non-hydrostatic icosahedral aerosol transport model.

PubMed

Dai, Tie; Schutgens, Nick A J; Goto, Daisuke; Shi, Guangyu; Nakajima, Teruyuki

2014-12-01

A new global aerosol assimilation system adopting a more complex icosahedral grid configuration is developed. Sensitivity tests for the assimilation system are performed utilizing satellite retrieved aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the results over Eastern Asia are analyzed. The assimilated results are validated through independent Aerosol Robotic Network (AERONET) observations. Our results reveal that the ensemble and local patch sizes have little effect on the assimilation performance, whereas the ensemble perturbation method has the largest effect. Assimilation leads to significantly positive effect on the simulated AOD field, improving agreement with all of the 12 AERONET sites over the Eastern Asia based on both the correlation coefficient and the root mean square difference (assimilation efficiency). Meanwhile, better agreement of the Ångström Exponent (AE) field is achieved for 8 of the 12 sites due to the assimilation of AOD only. Copyright © 2014 Elsevier Ltd. All rights reserved.

Towards the operational estimation of a radiological plume using data assimilation after a radiological accidental atmospheric release

NASA Astrophysics Data System (ADS)

Winiarek, Victor; Vira, Julius; Bocquet, Marc; Sofiev, Mikhail; Saunier, Olivier

2011-06-01

In the event of an accidental atmospheric release of radionuclides from a nuclear power plant, accurate real-time forecasting of the activity concentrations of radionuclides is required by the decision makers for the preparation of adequate countermeasures. The accuracy of the forecast plume is highly dependent on the source term estimation. On several academic test cases, including real data, inverse modelling and data assimilation techniques were proven to help in the assessment of the source term. In this paper, a semi-automatic method is proposed for the sequential reconstruction of the plume, by implementing a sequential data assimilation algorithm based on inverse modelling, with a care to develop realistic methods for operational risk agencies. The performance of the assimilation scheme has been assessed through the intercomparison between French and Finnish frameworks. Two dispersion models have been used: Polair3D and Silam developed in two different research centres. Different release locations, as well as different meteorological situations are tested. The existing and newly planned surveillance networks are used and realistically large multiplicative observational errors are assumed. The inverse modelling scheme accounts for strong error bias encountered with such errors. The efficiency of the data assimilation system is tested via statistical indicators. For France and Finland, the average performance of the data assimilation system is strong. However there are outlying situations where the inversion fails because of a too poor observability. In addition, in the case where the power plant responsible for the accidental release is not known, robust statistical tools are developed and tested to discriminate candidate release sites.

Accelerating assimilation development for new observing systems using EFSO

NASA Astrophysics Data System (ADS)

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.

Ionospheric data assimilation applied to HF geolocation in the presence of traveling ionospheric disturbances

NASA Astrophysics Data System (ADS)

Mitchell, C. N.; Rankov, N. R.; Bust, G. S.; Miller, E.; Gaussiran, T.; Calfas, R.; Doyle, J. D.; Teig, L. J.; Werth, J. L.; Dekine, I.

2017-07-01

Ionospheric data assimilation is a technique to evaluate the 3-D time varying distribution of electron density using a combination of a physics-based model and observations. A new ionospheric data assimilation method is introduced that has the capability to resolve traveling ionospheric disturbances (TIDs). TIDs are important because they cause strong delay and refraction to radio signals that are detrimental to the accuracy of high-frequency (HF) geolocation systems. The capability to accurately specify the ionosphere through data assimilation can correct systems for the error caused by the unknown ionospheric refraction. The new data assimilation method introduced here uses ionospheric models in combination with observations of HF signals from known transmitters. The assimilation methodology was tested by the ability to predict the incoming angles of HF signals from transmitters at a set of nonassimilated test locations. The technique is demonstrated and validated using observations collected during 2 days of a dedicated campaign of ionospheric measurements at White Sands Missile Range in New Mexico in January 2014. This is the first time that full HF ionospheric data assimilation using an ensemble run of a physics-based model of ionospheric TIDs has been demonstrated. The results show a significant improvement over HF angle-of-arrival prediction using an empirical model and also over the classic method of single-site location using an ionosonde close to the midpoint of the path. The assimilative approach is extendable to include other types of ionospheric measurements.

Naval Research Laboratory Ecological -- Photochemical -- Bio-optical--Numerical Experiment (Neptune) Version 1: A Portable, Flexible Modeling Environment Designed to Resolve Time-dependent Feedbacks Between Upper Ocean Ecology, Photochemistry, and Optics

DTIC Science & Technology

2007-02-21

dependent upon the carbon gross growth efficiency ( GGE ) and the C:N:P ratio of the organic substrate. This calculation and its structural...product of the temperature adjusted maximum gross carbon assimilation rate, the carbon gross growth efficiency ( GGE ), and the uptake kinetics for DOC...substrate: max T 4 [ ]( ) [ ]Cb b DOCg g GGE n DOC ⎛ ⎞ = ⎜ ⎟+⎝ ⎠ (21) and ( )( 30)max T m30 m30min[ , ]Kt Tb b bg g g e −= (22) To

Backbone and stereospecific (13)C methyl Ile (δ1), Leu and Val side-chain chemical shift assignments of Crc.

PubMed

Sharma, Rakhi; Sahu, Bhubanananda; Ray, Malay K; Deshmukh, Mandar V

2015-04-01

Carbon catabolite repression (CCR) allows bacteria to selectively assimilate a preferred compound among a mixture of several potential carbon sources, thus boosting growth and economizing the cost of adaptability to variable nutrients in the environment. The RNA-binding catabolite repression control (Crc) protein acts as a global post-transcriptional regulator of CCR in Pseudomonas species. Crc triggers repression by inhibiting the expression of genes involved in transport and catabolism of non-preferred substrates, thus indirectly favoring assimilation of preferred one. We report here a nearly complete backbone and stereospecific (13)C methyl side-chain chemical shift assignments of Ile (δ1), Leu and Val of Crc (~ 31 kDa) from Pseudomonas syringae Lz4W.

Identification and characterization of the biotechnological potential of a wild strain of Paraconiothyrium sp.

PubMed

Arredondo-Santoyo, Marina; Vázquez-Garcidueñas, Ma Soledad; Vázquez-Marrufo, Gerardo

2018-04-30

The isolation and characterization of fungal strains from poorly described taxa allows undercover attributes of their basic biology useful for biotechnology. Here, a wild fungal strain (CMU-196) from recently described Paraconiothyrium genus was analyzed. CMU-196 was identified as Paraconiothyrium brasiliense by phylogenetic analysis of the rDNA internal transcribed spacer region (ITS). CMU-196 metabolized 57 out of 95 substrates of the Biolog FF microplates. Efficient assimilation of dextrins and glycogen indicates that CMU-196 is a good producer of amylolytic enzymes. It showed a remarkably assimilation of α-D-lactose, substrate described as inducer of cellulolytic activity but poorly assimilated by several fungi. Metabolically active mycelium of the strain decolorized broth supplemented with direct blue 71, Chicago sky blue and remazol brilliant blue R dyes. The former two dyes were also well removed from broth by mycelium inactivated by autoclaving. Both mycelia had low efficiency for removing fuchsin acid from broth and for decolorizing wastewater from the paper industry. CMU-196 strain showed extracellular laccase activity when potato dextrose broth was supplemented with Cu +2 , reaching a maximum activity of 46.8 (±0.33) U/L. Studied strain antagonized phytopathogenic Colletotrichum spp. fungi and Phytophthora spp. oomycetes in vitro, but is less effective towards Fusarium spp. fungi. CMU-196 antagonism includes overgrowing the mycelia of phytopathogens and growth inhibition, probably by hydrosoluble extracellular metabolites. The biotechnological potential of strain CMU-196 here described warrants further studies to have a more detailed knowledge of the mechanisms associated with its metabolic versatility, capacity for environmental detoxification, extracellular laccase production and antagonism against phytopathogens. This article is protected by copyright. All rights reserved. © 2018 American Institute of Chemical Engineers.

Atlas Assimilation Patterns in Different Types of Adult Craniocervical Junction Malformations.

PubMed

Ferreira, Edson Dener Zandonadi; Botelho, Ricardo Vieira

2015-11-01

This is a cross-sectional analysis of resonance magnetic images of 111 patients with craniocervical malformations and those of normal subjects. To test the hypothesis that atlas assimilation is associated with basilar invagination (BI) and atlas's anterior arch assimilation is associated with craniocervical instability and type I BI. Atlas assimilation is the most common malformation in the craniocervical junction. This condition has been associated with craniocervical instability and BI in isolated cases. We evaluated midline Magnetic Resonance Images (MRIs) (and/or CT scans) from patients with craniocervical junction malformation and normal subjects. The patients were separated into 3 groups: Chiari type I malformation, BI type I, and type II. The atlas assimilations were classified according to their embryological origins as follows: posterior, anterior, and both arches assimilation. We studied the craniometric values of 111 subjects, 78 with craniocervical junction malformation and 33 without malformations. Of the 78 malformations, 51 patients had Chiari type I and 27 had BI, of whom 10 presented with type I and 17 with type II BI. In the Chiari group, 41 showed no assimilation of the atlas. In the type I BI group, all patients presented with anterior arch assimilation, either in isolation or associated with assimilation of the posterior arch. 63% of the patients with type II BI presented with posterior arch assimilation, either in isolation or associated with anterior arch assimilation. In the control group, no patients had atlas assimilation. Anterior atlas assimilation leads to type I BI. Posterior atlas assimilation more frequently leads to type II BI. Separation in terms of anterior versus posterior atlas assimilation reflects a more accurate understanding of the clinical and embryological differences in craniocervical junction malformations. N/A.

Wetting Behavior of Calcium Ferrite Slags on Cristobalite Substrates

NASA Astrophysics Data System (ADS)

Yang, Mingrui; Lv, Xuewei; Wei, Ruirui; Xu, Jian; Bai, Chenguang

2018-03-01

Calcium ferrite (CF) is a significant intermediate adhesive phase in high-basicity sinters. The wettability between calcium ferrite (CF) and gangue plays an important role in the assimilation process. The wettability of CF-based slags, in which a constant amount (2 mass pct.) of Al2O3, MgO, SiO2, and TiO2 was added, on solid SiO2 (cristobalite) substrates at 1523 K (1250 °C) was investigated. The interfacial microstructure and spreading mechanisms were discussed for each sample. All the tested slag samples exhibited good wettability on the SiO2 substrate. The initial apparent contact angles were in the range of 20 to 50 deg, while the final apparent contact angles were 5 deg. The wetting process could be divided into three stages on the basis of the change in diameter, namely the "linear spreading" stage, "spreading rate reduction" stage, and "wetting equilibrium" stage. It was found that the CF-SiO2 wetting system exhibits dissolutive wetting and the dissolution of SiO2 into slag influences its spreading process. The spreading rate increases with a decrease in the ratio of viscosity to interfacial tension, which is a result of the addition of Al2O3, MgO, SiO2, and TiO2. After cooling, a deep corrosion pit was formed in the substrate and a diffusion layer was generated in front of the residual slag zone; further, some SiO2 and Fe2O3 solid solutions precipitated in the slag.

Wetting Behavior of Calcium Ferrite Slags on Cristobalite Substrates

NASA Astrophysics Data System (ADS)

Yang, Mingrui; Lv, Xuewei; Wei, Ruirui; Xu, Jian; Bai, Chenguang

2018-06-01

Calcium ferrite (CF) is a significant intermediate adhesive phase in high-basicity sinters. The wettability between calcium ferrite (CF) and gangue plays an important role in the assimilation process. The wettability of CF-based slags, in which a constant amount (2 mass pct.) of Al2O3, MgO, SiO2, and TiO2 was added, on solid SiO2 (cristobalite) substrates at 1523 K (1250 °C) was investigated. The interfacial microstructure and spreading mechanisms were discussed for each sample. All the tested slag samples exhibited good wettability on the SiO2 substrate. The initial apparent contact angles were in the range of 20 to 50 deg, while the final apparent contact angles were 5 deg. The wetting process could be divided into three stages on the basis of the change in diameter, namely the "linear spreading" stage, "spreading rate reduction" stage, and "wetting equilibrium" stage. It was found that the CF-SiO2 wetting system exhibits dissolutive wetting and the dissolution of SiO2 into slag influences its spreading process. The spreading rate increases with a decrease in the ratio of viscosity to interfacial tension, which is a result of the addition of Al2O3, MgO, SiO2, and TiO2. After cooling, a deep corrosion pit was formed in the substrate and a diffusion layer was generated in front of the residual slag zone; further, some SiO2 and Fe2O3 solid solutions precipitated in the slag.

Usefulness of Wave Data Assimilation to the WAVE WATCH III Modeling System

NASA Astrophysics Data System (ADS)

Choi, J. K.; Dykes, J. D.; Yaremchuk, M.; Wittmann, P.

2017-12-01

In-situ and remote-sensed wave data are more abundant currently than in years past, with excellent accuracy at global scales. Forecast skill of the WAVE WATCH III model is improved by assimilation of these measurements and they are also useful for model validation and calibration. It has been known that the impact of assimilation in wind-sea conditions is not large, but spectra that result in large swell with long term propagation are identified and assimilated, the improved accuracy of the initial conditions improve the long-term forecasts. The Navy's assimilation method started with the simple Optimal Interpolation (OI) method. Operationally, Fleet Numerical Meteorology and Oceanography Center uses the sequential 2DVar scheme, but a new approach has been tested based on an adjoint-free method to variational assimilation in WAVE WATCH III. We will present the status of wave data assimilation into the WAVE WATCH III numerical model and upcoming development of this new adjoint-free variational approach.

Analysis and forecast experiments incorporating satellite soundings and cloud and water vapor drift wind information

NASA Technical Reports Server (NTRS)

Goodman, Brian M.; Diak, George R.; Mills, Graham A.

1986-01-01

A system for assimilating conventional meteorological data and satellite-derived data in order to produce four-dimensional gridded data sets of the primary atmospheric variables used for updating limited area forecast models is described. The basic principles of a data assimilation scheme as proposed by Lorenc (1984) are discussed. The design of the system and its incremental assimilation cycles are schematically presented. The assimilation system was tested using radiosonde, buoy, VAS temperature, dew point, gradient wind data, cloud drift, and water vapor motion data. The rms vector errors for the data are analyzed.

An integrated proteomic approach uncovers novel substrates and functions of the Lon protease in Escherichia coli.

PubMed

Arends, Jan; Griego, Marcena; Thomanek, Nikolas; Lindemann, Claudia; Kutscher, Blanka; Meyer, Helmut E; Narberhaus, Franz

2018-04-30

Controlling the cellular abundance and proper function of proteins by proteolysis is a universal process in all living organisms. In Escherichia coli, the ATP-dependent Lon protease is crucial for protein quality control and regulatory processes. To understand how diverse substrates are selected and degraded, unbiased global approaches are needed. We employed a quantitative Super-SILAC mass spectrometry approach and compared the proteomes of a lon mutant and a strain producing the protease to discover Lon-dependent physiological functions. To identify Lon substrates, we took advantage of a Lon trapping variant, which is able to translocate substrates but unable to degrade them. Lon-associated proteins were identified by label-free LC-MS/MS. The combination of both approaches revealed a total of 14 novel Lon substrates. Besides the identification of known pathways affected by Lon, for example the superoxide-stress response, our cumulative data suggests previously unrecognized fundamental functions of Lon in sulfur assimilation, nucleotide biosynthesis, amino acid and central energy metabolism. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Protein-based stable isotope probing.

PubMed

Jehmlich, Nico; Schmidt, Frank; Taubert, Martin; Seifert, Jana; Bastida, Felipe; von Bergen, Martin; Richnow, Hans-Hermann; Vogt, Carsten

2010-12-01

We describe a stable isotope probing (SIP) technique that was developed to link microbe-specific metabolic function to phylogenetic information. Carbon ((13)C)- or nitrogen ((15)N)-labeled substrates (typically with >98% heavy label) were used in cultivation experiments and the heavy isotope incorporation into proteins (protein-SIP) on growth was determined. The amount of incorporation provides a measure for assimilation of a substrate, and the sequence information from peptide analysis obtained by mass spectrometry delivers phylogenetic information about the microorganisms responsible for the metabolism of the particular substrate. In this article, we provide guidelines for incubating microbial cultures with labeled substrates and a protocol for protein-SIP. The protocol guides readers through the proteomics pipeline, including protein extraction, gel-free and gel-based protein separation, the subsequent mass spectrometric analysis of peptides and the calculation of the incorporation of stable isotopes into peptides. Extraction of proteins and the mass fingerprint measurements of unlabeled and labeled fractions can be performed in 2-3 d.

Real-data tests of a single-Doppler radar assimilation system

NASA Astrophysics Data System (ADS)

Nehrkorn, Thomas; Hegarty, James; Hamill, Thomas M.

1994-06-01

Real data tests of a single-Doppler radar data assimilation and forecast system have been conducted for a Florida sea breeze case. The system consists of a hydrostatic mesoscale model used for prediction of the preconvective boundary layer, an objective analysis that combines model first guess fields with radar derived horizontal winds, a thermodynamic retrieval scheme that obtains temperature information from the three-dimensional wind field and its temporal evolution, and a Newtonian nudging scheme for forcing the model forecast to closer agreement with the analysis. As was found in earlier experiments with simulated data, assimilation using Newtonian nudging benefits from temperature data in addition to wind data. The thermodynamic retrieval technique was successful in retrieving a horizontal temperature gradient from the radar-derived wind fields that, when assimilated into the model, led to a significantly improved forecast of the seabreeze strength and position.

Perceptual belongingness determines the direction of lightness induction depending on grouping stability and intentionality.

PubMed

Murgia, Mauro; Prpic, Valter; Santoro, Ilaria; Sors, Fabrizio; Agostini, Tiziano; Galmonte, Alessandra

2016-09-01

Contrast and assimilation are two opposite perceptual phenomena deriving from the relationships among perceptual elements in a visual field. In contrast, perceptual differences are enhanced; while, in assimilation, they are decreased. Indeed, if contrast or assimilation occurs depends on various factors. Interestingly, Gestalt scientists explained both phenomena as the result of perceptual belongingness, giving rise to an intriguing paradox. Benary suggested that belongingness determines contrast; conversely, Fuchs suggested that it determines assimilation. This paradox can be related both to the grouping stability (stable/multi-stable) and to the grouping intentionality (intentional/non-intentional). In the present work we ran four experiments to test whether the contrast/assimilation outcomes depend on the above-mentioned variables. We found that, intentionality and multi-stability elicit assimilation; while, non-intentionality and stability elicit contrast. Copyright © 2016 Elsevier Ltd. All rights reserved.

Efficient aquatic bacterial metabolism of dissolved low-molecular-weight compounds from terrestrial sources.

PubMed

Berggren, Martin; Laudon, Hjalmar; Haei, Mahsa; Ström, Lena; Jansson, Mats

2010-03-01

Carboxylic acids (CAs), amino acids (AAs) and carbohydrates (CHs) in dissolved free forms can be readily assimilated by aquatic bacteria and metabolized at high growth efficiencies. Previous studies have shown that these low-molecular-weight (LMW) substrates are released by phytoplankton but also that unidentified LMW compounds of terrestrial origin is a subsidy for bacterial metabolism in unproductive freshwater systems. We tested the hypothesis that different terrestrially derived CA, AA and CH compounds can offer substantial support for aquatic bacterial metabolism in fresh waters that are dominated by allochthonous dissolved organic matter (DOM). Drainage water from three catchments of different characters in the Krycklan experimental area in Northern Sweden were studied at the rising and falling limb of the spring flood, using a 2-week bioassay approach. A variety of CA, AA and CH compounds were significantly assimilated by bacteria, meeting 15-100% of the bacterial carbon demand and explaining most of the observed variation in bacterial growth efficiency (BGE; R(2)=0.66). Of the 29 chemical species that was detected, acetate was the most important, representing 45% of the total bacterial consumption of all LMW compounds. We suggest that LMW organic compounds in boreal spring flood drainage could potentially support all in situ bacterial production in receiving lake waters during periods of weeks to months after the spring flood.

Pressurized Martian-Like Pure CO2 Atmosphere Supports Strong Growth of Cyanobacteria, and Causes Significant Changes in their Metabolism

NASA Astrophysics Data System (ADS)

Murukesan, Gayathri; Leino, Hannu; Mäenpää, Pirkko; Ståhle, Kurt; Raksajit, Wuttinun; Lehto, Harry J.; Allahverdiyeva-Rinne, Yagut; Lehto, Kirsi

2016-03-01

Surviving of crews during future missions to Mars will depend on reliable and adequate supplies of essential life support materials, i.e. oxygen, food, clean water, and fuel. The most economical and sustainable (and in long term, the only viable) way to provide these supplies on Martian bases is via bio-regenerative systems, by using local resources to drive oxygenic photosynthesis. Selected cyanobacteria, grown in adequately protective containment could serve as pioneer species to produce life sustaining substrates for higher organisms. The very high (95.3 %) CO2 content in Martian atmosphere would provide an abundant carbon source for photo-assimilation, but nitrogen would be a strongly limiting substrate for bio-assimilation in this environment, and would need to be supplemented by nitrogen fertilizing. The very high supply of carbon, with rate-limiting supply of nitrogen strongly affects the growth and the metabolic pathways of the photosynthetic organisms. Here we show that modified, Martian-like atmospheric composition (nearly 100 % CO2) under various low pressure conditions (starting from 50 mbar to maintain liquid water, up to 200 mbars) supports strong cellular growth. Under high CO2 / low N2 ratio the filamentous cyanobacteria produce significant amount of H2 during light due to differentiation of high amount of heterocysts.

Kinetic mechanism of the dimeric ATP sulfurylase from plants

PubMed Central

Ravilious, Geoffrey E.; Herrmann, Jonathan; Goo Lee, Soon; Westfall, Corey S.; Jez, Joseph M.

2013-01-01

In plants, sulfur must be obtained from the environment and assimilated into usable forms for metabolism. ATP sulfurylase catalyses the thermodynamically unfavourable formation of a mixed phosphosulfate anhydride in APS (adenosine 5′-phosphosulfate) from ATP and sulfate as the first committed step of sulfur assimilation in plants. In contrast to the multi-functional, allosterically regulated ATP sulfurylases from bacteria, fungi and mammals, the plant enzyme functions as a mono-functional, non-allosteric homodimer. Owing to these differences, here we examine the kinetic mechanism of soybean ATP sulfurylase [GmATPS1 (Glycine max (soybean) ATP sulfurylase isoform 1)]. For the forward reaction (APS synthesis), initial velocity methods indicate a single-displacement mechanism. Dead-end inhibition studies with chlorate showed competitive inhibition versus sulfate and non-competitive inhibition versus APS. Initial velocity studies of the reverse reaction (ATP synthesis) demonstrate a sequential mechanism with global fitting analysis suggesting an ordered binding of substrates. ITC (isothermal titration calorimetry) showed tight binding of APS to GmATPS1. In contrast, binding of PPi (pyrophosphate) to GmATPS1 was not detected, although titration of the E•APS complex with PPi in the absence of magnesium displayed ternary complex formation. These results suggest a kinetic mechanism in which ATP and APS are the first substrates bound in the forward and reverse reactions, respectively. PMID:23789618

Substrate and metabolite diffusion within model medium for soft cheese in relation to growth of Penicillium camembertii.

PubMed

Aldarf, Mazen; Fourcade, Florence; Amrane, Abdeltif; Prigent, Yves

2006-08-01

Penicillium camembertii was cultivated on a jellified peptone-lactate based medium to simulate the composition of Camembert cheese. Diffusional limitations due to substrate consumption were not involved in the linear growth recorded during culture, while nitrogen (peptone) limitation accounted for growth cessation. Examination of gradients confirmed that medium neutralization was the consequence of lactate consumption and ammonium production. The diffusion of the lactate assimilated from the core to the rind and that of the ammonium produced from the rind to the core was described by means of a diffusion/reaction model involving a partial linking of consumption or production to growth. The model matched experimental data throughout growth.

Lessons from a low-order coupled chemistry meteorology model and applications to a high-dimensional chemical transport model

NASA Astrophysics Data System (ADS)

Haussaire, Jean-Matthieu; Bocquet, Marc

2016-04-01

Atmospheric chemistry models are becoming increasingly complex, with multiphasic chemistry, size-resolved particulate matter, and possibly coupled to numerical weather prediction models. In the meantime, data assimilation methods have also become more sophisticated. Hence, it will become increasingly difficult to disentangle the merits of data assimilation schemes, of models, and of their numerical implementation in a successful high-dimensional data assimilation study. That is why we believe that the increasing variety of problems encountered in the field of atmospheric chemistry data assimilation puts forward the need for simple low-order models, albeit complex enough to capture the relevant dynamics, physics and chemistry that could impact the performance of data assimilation schemes. Following this analysis, we developped a low-order coupled chemistry meteorology model named L95-GRS [1]. The advective wind is simulated by the Lorenz-95 model, while the chemistry is made of 6 reactive species and simulates ozone concentrations. With this model, we carried out data assimilation experiments to estimate the state of the system as well as the forcing parameter of the wind and the emissions of chemical compounds. This model proved to be a powerful playground giving insights on the hardships of online and offline estimation of atmospheric pollution. Building on the results on this low-order model, we test advanced data assimilation methods on a state-of-the-art chemical transport model to check if the conclusions obtained with our low-order model still stand. References [1] Haussaire, J.-M. and Bocquet, M.: A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes, Geosci. Model Dev. Discuss., 8, 7347-7394, doi:10.5194/gmdd-8-7347-2015, 2015.

[Combination of phosphorus solubilizing and mobilizing fungi with phosphate rocks and volcanic materials to promote plant growth of lettuce (Lactuca sativa L.)].

PubMed

Velázquez, María S; Cabello, Marta N; Elíades, Lorena A; Russo, María L; Allegrucci, Natalia; Schalamuk, Santiago

Arbuscular mycorrhizal fungi (AMF) increase the uptake of soluble phosphates, while phosphorus solubilizing fungi (S) promote solubilization of insoluble phosphates complexes, favoring plant nutrition. Another alternative to maintaining crop productivity is to combine minerals and rocks that provide nutrients and other desirable properties. The aim of this work was to combine AMF and S with pyroclastic materials (ashes and pumices) from Puyehue volcano and phosphate rocks (PR) from Rio Chico Group (Chubut) - to formulate a substrate for the production of potted Lactuca sativa. A mixture of Terrafertil®:ashes was used as substrate. Penicillium thomii was the solubilizing fungus and Rhizophagus intraradices spores (AMF) was the P mobilizer (AEGIS® Irriga). The treatments were: 1) Substrate; 2) Substrate+AMF; 3) Substrate+S; 4) Substrate+AMF+S; 5) Substrate: PR; 6) Substrate: PR+AMF; 7) Substrate: PR+S and 8) Substrate: PR+AMF+S. Three replicates were performed per treatment. All parameters evaluated (total and assimilable P content in substrate, P in plant tissue and plant dry biomass) were significantly higher in plants grown in substrate containing PR and inoculas with S and AMF. This work confirms that the combination of S/AMF with Puyehue volcanic ashes, PR from the Río Chico Group and a commercial substrate promote the growth of L. sativa, thus increasing the added value of national geomaterials. Copyright © 2017 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

Air Quality Modeling Using the NASA GEOS-5 Multispecies Data Assimilation System

NASA Technical Reports Server (NTRS)

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.

Bioluminescence-Based Method for Measuring Assimilable Organic Carbon in Pretreatment Water for Reverse Osmosis Membrane Desalination ▿

PubMed Central

Weinrich, Lauren A.; Schneider, Orren D.; LeChevallier, Mark W.

2011-01-01

A bioluminescence-based assimilable organic carbon (AOC) test was developed for determining the biological growth potential of seawater within the reverse osmosis desalination pretreatment process. The test uses Vibrio harveyi, a marine organism that exhibits constitutive luminescence and is nutritionally robust. AOC was measured in both a pilot plant and a full-scale desalination plant pretreatment. PMID:21148685

Candida wancherniae sp. nov. and Candida morakotiae sp. nov., two novel ascomycetous anamorphic yeast species found in Thailand.

PubMed

Nakase, Takashi; Jindamorakot, Sasitorn; Ninomiya, Shinya; Imanishi, Yumi; Kawasaki, Hiroko

2009-04-01

Seven yeast strains isolated from natural substrates of Thailand were found to represent two novel species of Candida, an ascomycetous anamorphic genus. Three strains, ST-233, ST-259 and ST-260, isolated from insect frass and plant leaves were found to represent a single novel species related to Metschnikowia agaves in a tree based on the D1/D2 domain sequences of the 26S rRNA genes. This species is clearly discriminated from M. agaves by the carbon assimilation patterns and required vitamins. The remaining four strains, ST-18, ST-261, ST-606 and ST-658, isolated from the fruit body of a mushroom, insect frass, decayed jack fruit and an unidentified flower, were found to represent a single species which is related to Candida corydali, a recently described insect-associated species, in a neighbor-joining tree based on the D1/D2 sequences. This species is clearly discriminated from C. corydali by the ability to assimilate propane-1,2-diol and the inability to assimilate glucono-delta-lactone. They are described as Candida wancherniae sp. nov. and Candida morakotiae sp. nov., respectively.

Electron Donors Supporting Growth and Electroactivity of Geobacter sulfurreducens Anode Biofilms

PubMed Central

Speers, Allison M.

2012-01-01

Geobacter bacteria efficiently oxidize acetate into electricity in bioelectrochemical systems, yet the range of fermentation products that support the growth of anode biofilms and electricity production has not been thoroughly investigated. Here, we show that Geobacter sulfurreducens oxidized formate and lactate with electrodes and Fe(III) as terminal electron acceptors, though with reduced efficiency compared to acetate. The structure of the formate and lactate biofilms increased in roughness, and the substratum coverage decreased, to alleviate the metabolic constraints derived from the assimilation of carbon from the substrates. Low levels of acetate promoted formate carbon assimilation and biofilm growth and increased the system's performance to levels comparable to those with acetate only. Lactate carbon assimilation also limited biofilm growth and led to the partial oxidization of lactate to acetate. However, lactate was fully oxidized in the presence of fumarate, which redirected carbon fluxes into the tricarboxylic acid (TCA) cycle, and by acetate-grown biofilms. These results expand the known ranges of electron donors for Geobacter-driven fuel cells and identify microbial constraints that can be targeted to develop better-performing strains and increase the performance of bioelectrochemical systems. PMID:22101036

Compound-specific 15N analysis of amino acids in 15N tracer experiments provide an estimate of newly synthesised soil protein from inorganic and organic substrates

NASA Astrophysics Data System (ADS)

Charteris, Alice; Michaelides, Katerina; Evershed, Richard

2015-04-01

Organic N concentrations far exceed those of inorganic N in most soils and despite much investigation, the composition and cycling of this complex pool of SOM remains poorly understood. A particular problem has been separating more recalcitrant soil organic N from that actively cycling through the soil system; an important consideration in N cycling studies and for the soil's nutrient supplying capacity. The use of 15N-labelled substrates as stable isotope tracers has contributed much to our understanding of the soil system, but the complexity and heterogeneity of soil organic N prevents thorough compound-specific 15N analyses of organic N compounds and makes it difficult to examine any 15N-labelled organic products in any detail. As a result, a significant proportion of previous work has either simply assumed that since the majority of soil N is organic, all of the 15N retained in the soil is organic N (e.g. Sebilo et al., 2013) or subtracted 15N-labelled inorganic compounds from bulk values (e.g. Pilbeam et al., 1997). While the latter approach is more accurate, these methods only provide an estimate of the bulk 15N value of an extremely complex and non-uniformly labelled organic pool. A more detailed approach has been to use microbial biomass extraction (Brookes et al., 1985) and subsequent N isotopic analysis to determine the 15N value of biomass-N, representing the fraction of 15N assimilated by microbes or the 15N cycling through the 'living' or 'active' portion of soil organic N. However, this extraction method can only generate estimates and some lack of confidence in its validity and reliability remains. Here, we present an alternative technique to obtain a measure of the assimilation of an applied 15N substrate by the soil microbial biomass and an estimate of the newly synthesized soil protein, which is representative of the magnitude of the active soil microbial biomass. The technique uses a stable isotope tracer and compound-specific 15N analysis, but unlike previous works analyses for amino acids (representing organic products) rather than ammonium (NH4+) and nitrate (NO3-). Amino acids are commonly referred to as 'the building blocks of life' as they form the proteins which regulate life's essential biochemical reactions. Proteinaceous matter generally comprises 20-40% of total soil N and is ubiquitous in living organisms, so is a likely 'organic product' of microbial activity/assimilation. Hence, we consider it likely that amino acids represent the major organic nitrogenous products and a reasonable 'proxy' for/measure of the assimilation of an applied 15N substrate by the soil microbial biomass and an estimate of the newly synthesized soil protein. Brookes, P. C. et al. Soil Biol Biochem. 1985, 17, 837-842. Jenkinson, D. S. et al. Soil Biol Biochem. 2004, 36, 5-7. Nannipieri, P. et al. Plant Soil. 1999, 208, 43-56. Pilbeam, C. J. et al. J Agr Sci. 1997, 128, 415-424. Sebilo, M. et al. PNAS. 2013, 110, 18185-18189.

All-Sky Microwave Imager Data Assimilation at NASA GMAO

NASA Technical Reports Server (NTRS)

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

2017-01-01

Efforts in all-sky satellite data assimilation at the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center have been focused on the development of GSI configurations to assimilate all-sky data from microwave imagers such as the GPM Microwave Imager (GMI) and Global Change Observation Mission-Water (GCOM-W) Advanced Microwave Scanning Radiometer 2 (AMSR-2). Electromagnetic characteristics associated with their wavelengths allow microwave imager data to be relatively transparent to atmospheric gases and thin ice clouds, and highly sensitive to precipitation. Therefore, GMAOs all-sky data assimilation efforts are primarily focused on utilizing these data in precipitating regions. The all-sky framework being tested at GMAO employs the GSI in a hybrid 4D-EnVar configuration of the Goddard Earth Observing System (GEOS) data assimilation system, which will be included in the next formal update of GEOS. This article provides an overview of the development of all-sky radiance assimilation in GEOS, including some performance metrics. In addition, various projects underway at GMAO designed to enhance the all-sky implementation will be introduced.

Low assimilation efficiency of photorespiratory ammonia in conifer leaves.

PubMed

Miyazawa, Shin-Ichi; Nishiguchi, Mitsuru; Futamura, Norihiro; Yukawa, Tomohisa; Miyao, Mitsue; Maruyama, Tsuyoshi Emilio; Kawahara, Takayuki

2018-06-09

Glutamine synthetase (GS) localized in the chloroplasts, GS2, is a key enzyme in the assimilation of ammonia (NH 3 ) produced from the photorespiration pathway in angiosperms, but it is absent from some coniferous species belonging to Pinaceae such as Pinus. We examined whether the absence of GS2 is common in conifers (Pinidae) and also addressed the question of whether assimilation efficiency of photorespiratory NH 3 differs between conifers that may potentially lack GS2 and angiosperms. Search of the expressed sequence tag database of Cryptomeria japonica, a conifer in Cupressaceae, and immunoblotting analyses of leaf GS proteins of 13 species from all family members in Pinidae revealed that all tested conifers exhibited only GS1 isoforms. We compared leaf NH 3 compensation point (γ NH3 ) and the increments in leaf ammonium content per unit photorespiratory activity (NH 3 leakiness), i.e. inverse measures of the assimilation efficiency, between conifers (C. japonica and Pinus densiflora) and angiosperms (Phaseolus vulgaris and two Populus species). Both γ NH3 and NH 3 leakiness were higher in the two conifers than in the three angiosperms tested. Thus, we concluded that the absence of GS2 is common in conifers, and assimilation efficiency of photorespiratory NH 3 is intrinsically lower in conifer leaves than in angiosperm leaves. These results imply that acquisition of GS2 in land plants is an adaptive mechanism for efficient NH 3 assimilation under photorespiratory environments.

Steroid biotransformations in biphasic systems with Yarrowia lipolytica expressing human liver cytochrome P450 genes

PubMed Central

2012-01-01

Background Yarrowia lipolytica efficiently metabolizes and assimilates hydrophobic compounds such as n-alkanes and fatty acids. Efficient substrate uptake is enabled by naturally secreted emulsifiers and a modified cell surface hydrophobicity and protrusions formed by this yeast. We were examining the potential of recombinant Y. lipolytica as a biocatalyst for the oxidation of hardly soluble hydrophobic steroids. Furthermore, two-liquid biphasic culture systems were evaluated to increase substrate availability. While cells, together with water soluble nutrients, are maintained in the aqueous phase, substrates and most of the products are contained in a second water-immiscible organic solvent phase. Results For the first time we have co-expressed the human cytochromes P450 2D6 and 3A4 genes in Y. lipolytica together with human cytochrome P450 reductase (hCPR) or Y. lipolytica cytochrome P450 reductase (YlCPR). These whole-cell biocatalysts were used for the conversion of poorly soluble steroids in biphasic systems. Employing a biphasic system with the organic solvent and Y. lipolytica carbon source ethyl oleate for the whole-cell bioconversion of progesterone, the initial specific hydroxylation rate in a 1.5 L stirred tank bioreactor was further increased 2-fold. Furthermore, the product formation was significantly prolonged as compared to the aqueous system. Co-expression of the human CPR gene led to a 4-10-fold higher specific activity, compared to the co-overexpression of the native Y. lipolytica CPR gene. Multicopy transformants showed a 50-70-fold increase of activity as compared to single copy strains. Conclusions Alkane-assimilating yeast Y. lipolytica, coupled with the described expression strategies, demonstrated its high potential for biotransformations of hydrophobic substrates in two-liquid biphasic systems. Especially organic solvents which can be efficiently taken up and/or metabolized by the cell might enable more efficient bioconversion as compared to aqueous systems and even enable simple, continuous or at least high yield long time processes. PMID:22876969

Biodegradation of Polychlorinated Methanes in Methanogenic Systems

DTIC Science & Technology

1991-01-01

occurring toxicant and C-1 growth substrate. J. General Microbiol. 132:1139-1142. 18. Hoover, S. R. and N. Porges. 1952. Assimilation of dairy wastes by...carbon and electron donor source; (3) to examine the level of micronutrients - provided as yeast extract (YE) - needed in the system feed; (4) to...provided the electron donor needed to consume oxygen and lower the redox potential in the precolumn; YE provided micronutrients . No reductant (Na2S

Multiscale Data Assimilation

DTIC Science & Technology

2014-09-30

good test 3 case to study the multiscale data assimilation capabilities of our GMM-DO filter. We also performed stochastic simulations with our DO...Morakot and internal tides. The ignorance score and Kullback - Leibler divergence were employed to measure the skill of the multiscale pdf forecasts...read off from the posterior of the augmented state vector. We implemented this new smoother and tested it using a 2D-in-space stochastic flow exiting

Evaluating Snow Data Assimilation Framework for Streamflow Forecasting Applications Using Hindcast Verification

NASA Astrophysics Data System (ADS)

Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

2012-12-01

Snow water equivalent (SWE) estimation is a key factor in producing reliable streamflow simulations and forecasts in snow dominated areas. However, measuring or predicting SWE has significant uncertainty. Sequential data assimilation, which updates states using both observed and modeled data based on error estimation, has been shown to reduce streamflow simulation errors but has had limited testing for forecasting applications. In the current study, a snow data assimilation framework integrated with the National Weather System River Forecasting System (NWSRFS) is evaluated for use in ensemble streamflow prediction (ESP). Seasonal water supply ESP hindcasts are generated for the North Fork of the American River Basin (NFARB) in northern California. Parameter sets from the California Nevada River Forecast Center (CNRFC), the Differential Evolution Adaptive Metropolis (DREAM) algorithm and the Multistep Automated Calibration Scheme (MACS) are tested both with and without sequential data assimilation. The traditional ESP method considers uncertainty in future climate conditions using historical temperature and precipitation time series to generate future streamflow scenarios conditioned on the current basin state. We include data uncertainty analysis in the forecasting framework through the DREAM-based parameter set which is part of a recently developed Integrated Uncertainty and Ensemble-based data Assimilation framework (ICEA). Extensive verification of all tested approaches is undertaken using traditional forecast verification measures, including root mean square error (RMSE), Nash-Sutcliffe efficiency coefficient (NSE), volumetric bias, joint distribution, rank probability score (RPS), and discrimination and reliability plots. In comparison to the RFC parameters, the DREAM and MACS sets show significant improvement in volumetric bias in flow. Use of assimilation improves hindcasts of higher flows but does not significantly improve performance in the mid flow and low flow categories.

Improving Forecast Skill by Assimilation of AIRS Cloud Cleared Radiances RiCC

NASA Technical Reports Server (NTRS)

Susskind, Joel; Rosenberg, Robert I.; Iredell, Lena

2015-01-01

ECMWF, NCEP, and GMAO routinely assimilate radiosonde and other in-situ observations along with satellite IR and MW Sounder radiance observations. NCEP and GMAO use the NCEP GSI Data Assimilation System (DAS).GSI DAS assimilates AIRS, CrIS, IASI channel radiances Ri on a channel-by-channel, case-by-case basis, only for those channels i thought to be unaffected by cloud cover. This test excludes Ri for most tropospheric sounding channels under partial cloud cover conditions. AIRS Version-6 RiCC is a derived quantity representative of what AIRS channel i would have seen if the AIRS FOR were cloud free. All values of RiCC have case-by-case error estimates RiCC associated with them. Our experiments present to the GSI QCd values of AIRS RiCC in place of AIRS Ri observations. GSI DAS assimilates only those values of RiCC it thinks are cloud free. This potentially allows for better coverage of assimilated QCd values of RiCC as compared to Ri.

Use of MODIS Cloud Top Pressure to Improve Assimilation Yields of AIRS Radiances in GSI

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi

2014-01-01

Radiances from hyperspectral sounders such as the Atmospheric Infrared Sounder (AIRS) are routinely assimilated both globally and regionally in operational numerical weather prediction (NWP) systems using the Gridpoint Statistical Interpolation (GSI) data assimilation system. However, only thinned, cloud-free radiances from a 281-channel subset are used, so the overall percentage of these observations that are assimilated is somewhere on the order of 5%. Cloud checks are performed within GSI to determine which channels peak above cloud top; inaccuracies may lead to less assimilated radiances or introduction of biases from cloud-contaminated radiances.Relatively large footprint from AIRS may not optimally represent small-scale cloud features that might be better resolved by higher-resolution imagers like the Moderate Resolution Imaging Spectroradiometer (MODIS). Objective of this project is to "swap" the MODIS-derived cloud top pressure (CTP) for that designated by the AIRS-only quality control within GSI to test the hypothesis that better representation of cloud features will result in higher assimilated radiance yields and improved forecasts.

A comparison of linear and non-linear data assimilation methods using the NEMO ocean model

NASA Astrophysics Data System (ADS)

Kirchgessner, Paul; Tödter, Julian; Nerger, Lars

2015-04-01

The assimilation behavior of the widely used LETKF is compared with the Equivalent Weight Particle Filter (EWPF) in a data assimilation application with an idealized configuration of the NEMO ocean model. The experiments show how the different filter methods behave when they are applied to a realistic ocean test case. The LETKF is an ensemble-based Kalman filter, which assumes Gaussian error distributions and hence implicitly requires model linearity. In contrast, the EWPF is a fully nonlinear data assimilation method that does not rely on a particular error distribution. The EWPF has been demonstrated to work well in highly nonlinear situations, like in a model solving a barotropic vorticity equation, but it is still unknown how the assimilation performance compares to ensemble Kalman filters in realistic situations. For the experiments, twin assimilation experiments with a square basin configuration of the NEMO model are performed. The configuration simulates a double gyre, which exhibits significant nonlinearity. The LETKF and EWPF are both implemented in PDAF (Parallel Data Assimilation Framework, http://pdaf.awi.de), which ensures identical experimental conditions for both filters. To account for the nonlinearity, the assimilation skill of the two methods is assessed by using different statistical metrics, like CRPS and Histograms.

Modeling of competitive mutualistic relationships. Application to cellulose degradation by Streptomyces sp. strains.

PubMed

Thierie, Jacques; Penninckx, Michel J

2007-12-01

A "cascade" model depicts microbial degradation of a complex nutrient/substrate through a succession of intermediate compounds. Each stage is characterized by a particular species producing a typical degradation enzyme induced by its own degradation product. The final compound of the cascade consists of a single assimilable substrate used by all species. This results in a competition situation, whereas the contribution of all strains to the production of a complete set of efficient enzymes generates a mutualistic relationship. The model was shown to be appropriate to describe degradation of cellulose by a consortium of Streptomyces sp. strains. The simplicity and the model capacity for generalization are promising and could be used for various degradation processes both at laboratory and environmental scales.

Arbuscular mycorrhizal colonization of giant sequoia (Sequoiadendron giganteum) in response to restoration practices.

PubMed

Fahey, Catherine; York, Robert A; Pawlowska, Teresa E

2012-01-01

Interactions with soil microbiota determine the success of restoring plants to their native habitats. The goal of our study was to understand the effects of restoration practices on interactions of giant sequoia Sequoiadendron giganteum with arbuscular mycorrhizal (AM) fungi (Glomeromycota). Natural regeneration of Sequoiadendron is threatened by the absence of severe fires that create forest canopy gaps. Generating artificial canopy gaps offers an alternative tool for giant sequoia restoration. We investigated the effect of regeneration practices, including (i) sapling location within gaps, (ii) gap size and (iii) soil substrate, on AM fungal colonization of giant sequoia sapling roots in a native giant sequoia grove of the Sierra Nevada, California. We found that the extent of AM fungal root colonization was positively correlated with sapling height and light availability, which were related to the location of the sapling within the gap and the gap size. While colonization frequency by arbuscules in saplings on ash substrate was higher relative to saplings in mineral soil, the total AM fungal root colonization was similar between the substrates. A negative correlation between root colonization by Glomeromycota and non-AM fungal species indicated antagonistic interactions between different classes of root-associated fungi. Using DNA genotyping, we identified six AM fungal taxa representing genera Glomus and Ambispora present in Sequoiadendron roots. Overall, we found that AM fungal colonization of giant sequoia roots was associated with availability of plant-assimilated carbon to the fungus rather than with the AM fungal supply of mineral nutrients to the roots. We conclude that restoration practices affecting light availability and carbon assimilation alter feedbacks between sapling growth and activity of AM fungi in the roots.

Crystal structures of mammalian glutamine synthetases illustrate substrate-induced conformational changes and provide opportunities for drug and herbicide design.

PubMed

Krajewski, Wojciech W; Collins, Ruairi; Holmberg-Schiavone, Lovisa; Jones, T Alwyn; Karlberg, Tobias; Mowbray, Sherry L

2008-01-04

Glutamine synthetase (GS) catalyzes the ligation of glutamate and ammonia to form glutamine, with concomitant hydrolysis of ATP. In mammals, the activity eliminates cytotoxic ammonia, at the same time converting neurotoxic glutamate to harmless glutamine; there are a number of links between changes in GS activity and neurodegenerative disorders, such as Alzheimer's disease. In plants, because of its importance in the assimilation and re-assimilation of ammonia, the enzyme is a target of some herbicides. GS is also a central component of bacterial nitrogen metabolism and a potential drug target. Previous studies had investigated the structures of bacterial and plant GSs. In the present publication, we report the first structures of mammalian GSs. The apo form of the canine enzyme was solved by molecular replacement and refined at a resolution of 3 A. Two structures of human glutamine synthetase represent complexes with: a) phosphate, ADP, and manganese, and b) a phosphorylated form of the inhibitor methionine sulfoximine, ADP and manganese; these structures were refined to resolutions of 2.05 A and 2.6 A, respectively. Loop movements near the active site generate more closed forms of the eukaryotic enzymes when substrates are bound; the largest changes are associated with the binding of the nucleotide. Comparisons with earlier structures provide a basis for the design of drugs that are specifically directed at either human or bacterial enzymes. The site of binding the amino acid substrate is highly conserved in bacterial and eukaryotic GSs, whereas the nucleotide binding site varies to a much larger degree. Thus, the latter site offers the best target for specific drug design. Differences between mammalian and plant enzymes are much more subtle, suggesting that herbicides targeting GS must be designed with caution.

Improving GEOS-5 seven day forecast skill by assimilation of quality controlled AIRS temperature profiles

NASA Astrophysics Data System (ADS)

Susskind, J.; Rosenberg, R. I.

2016-12-01

The GEOS-5 Data Assimilation System (DAS) generates a global analysis every six hours by combining the previous six hour forecast for that time period with contemporaneous observations. These observations include in-situ observations as well as those taken by satellite borne instruments, such as AIRS/AMSU on EOS Aqua and CrIS/ATMS on S-NPP. Operational data assimilation methodology assimilates observed channel radiances Ri for IR sounding instruments such as AIRS and CrIS, but only for those channels i in a given scene whose radiances are thought to be unaffected by clouds. A limitation of this approach is that radiances in most tropospheric sounding channels are affected by clouds under partial cloud cover conditions, which occurs most of the time. The AIRS Science Team Version-6 retrieval algorithm generates cloud cleared radiances (CCR's) for each channel in a given scene, which represent the radiances AIRS would have observed if the scene were cloud free, and then uses them to determine quality controlled (QC'd) temperature profiles T(p) under all cloud conditions. There are potential advantages to assimilate either AIRS QC'd CCR's or QC'd T(p) instead of Ri in that the spatial coverage of observations is greater under partial cloud cover. We tested these two alternate data assimilation approaches by running three parallel data assimilation experiments over different time periods using GEOS-5. Experiment 1 assimilated all observations as done operationally, Experiment 2 assimilated QC'd values of AIRS CCRs in place of AIRS radiances, and Experiment 3 assimilated QC'd values of T(p) in place of observed radiances. Assimilation of QC'd AIRS T(p) resulted in significant improvement in seven day forecast skill compared to assimilation of CCR's or assimilation of observed radiances, especially in the Southern Hemisphere Extra-tropics.

Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model

NASA Astrophysics Data System (ADS)

Khaki, M.; Hoteit, I.; Kuhn, M.; Awange, J.; Forootan, E.; van Dijk, A. I. J. M.; Schumacher, M.; Pattiaratchi, C.

2017-09-01

The time-variable terrestrial water storage (TWS) products from the Gravity Recovery And Climate Experiment (GRACE) have been increasingly used in recent years to improve the simulation of hydrological models by applying data assimilation techniques. In this study, for the first time, we assess the performance of the most popular data assimilation sequential techniques for integrating GRACE TWS into the World-Wide Water Resources Assessment (W3RA) model. We implement and test stochastic and deterministic ensemble-based Kalman filters (EnKF), as well as Particle filters (PF) using two different resampling approaches of Multinomial Resampling and Systematic Resampling. These choices provide various opportunities for weighting observations and model simulations during the assimilation and also accounting for error distributions. Particularly, the deterministic EnKF is tested to avoid perturbing observations before assimilation (that is the case in an ordinary EnKF). Gaussian-based random updates in the EnKF approaches likely do not fully represent the statistical properties of the model simulations and TWS observations. Therefore, the fully non-Gaussian PF is also applied to estimate more realistic updates. Monthly GRACE TWS are assimilated into W3RA covering the entire Australia. To evaluate the filters performances and analyze their impact on model simulations, their estimates are validated by independent in-situ measurements. Our results indicate that all implemented filters improve the estimation of water storage simulations of W3RA. The best results are obtained using two versions of deterministic EnKF, i.e. the Square Root Analysis (SQRA) scheme and the Ensemble Square Root Filter (EnSRF), respectively, improving the model groundwater estimations errors by 34% and 31% compared to a model run without assimilation. Applying the PF along with Systematic Resampling successfully decreases the model estimation error by 23%.

Becoming a vampire without being bitten: the narrative collective-assimilation hypothesis.

PubMed

Gabriel, Shira; Young, Ariana F

2011-08-01

We propose the narrative collective-assimilation hypothesis--that experiencing a narrative leads one to psychologically become a part of the collective described within the narrative. In a test of this hypothesis, participants read passages from either a book about wizards (from the Harry Potter series) or a book about vampires (from the Twilight series). Both implicit and explicit measures revealed that participants who read about wizards psychologically became wizards, whereas those who read about vampires psychologically became vampires. The results also suggested that narrative collective assimilation is psychologically meaningful and relates to the basic human need for connection. Specifically, the tendency to fulfill belongingness needs through group affiliation moderated the extent to which narrative collective assimilation occurred, and narrative collective assimilation led to increases in life satisfaction and positive mood, two primary outcomes of belonging. The implications for the importance of narratives, the need to belong to groups, and social surrogacy are discussed.

Applications of the Non-Conventional Yeast Yarrowia lipolytica

NASA Astrophysics Data System (ADS)

Thevenieau, France; Nicaud, Jean-Marc; Gaillardin, Claude

The yeast Yarrowia lipolytica is often found associated to proteinaceous or hydrophobic substrates such as alkanes or lipids. To assimilate these hydropho-bic substrates, Y. lipolytica has developed an adaptative strategy resulting in elaborated morphological and physiological changes leading to terminal and β-oxidation of substrates as well as to lipid storage. The completion of the Y. lipolytica genome greatly improved our understanding of these mechanisms. Three main applications of this metabolism will be discussed. The first class corresponds to bioconver-sion processes for the production of secondary metabolites (citric acid), of aroma ( γ - lactone, green note, epoxy geraniol) and of chemicals (dicarboxylic acids). The second class leads to fine chemical production by enantio separation of pharmaceutical compounds using Y. lipolytica enzymes such as epoxyde hydrolase or lipase. The third one refers to production of Single Cell Oils (SCO) from agriculture feedstock. In addition to its ability to handle hydrophobic substrates, Y. lipolytica has also been recognised as a strong secretor of various proteins such as proteases, lipases, RNases and others. A comprehensive review of recent developments of the Y. lipolytica expression/secretion system will finally be presented.

Development and implementation of a remote-sensing and in situ data-assimilating version of CMAQ for operational PM2.5 forecasting. Part 1: MODIS aerosol optical depth (AOD) data-assimilation design and testing.

PubMed

McHenry, John N; Vukovich, Jeffery M; Hsu, N Christina

2015-12-01

This two-part paper reports on the development, implementation, and improvement of a version of the Community Multi-Scale Air Quality (CMAQ) model that assimilates real-time remotely-sensed aerosol optical depth (AOD) information and ground-based PM2.5 monitor data in routine prognostic application. The model is being used by operational air quality forecasters to help guide their daily issuance of state or local-agency-based air quality alerts (e.g. action days, health advisories). Part 1 describes the development and testing of the initial assimilation capability, which was implemented offline in partnership with NASA and the Visibility Improvement State and Tribal Association of the Southeast (VISTAS) Regional Planning Organization (RPO). In the initial effort, MODIS-derived aerosol optical depth (AOD) data are input into a variational data-assimilation scheme using both the traditional Dark Target and relatively new "Deep Blue" retrieval methods. Evaluation of the developmental offline version, reported in Part 1 here, showed sufficient promise to implement the capability within the online, prognostic operational model described in Part 2. In Part 2, the addition of real-time surface PM2.5 monitoring data to improve the assimilation and an initial evaluation of the prognostic modeling system across the continental United States (CONUS) is presented. Air quality forecasts are now routinely used to understand when air pollution may reach unhealthy levels. For the first time, an operational air quality forecast model that includes the assimilation of remotely-sensed aerosol optical depth and ground based PM2.5 observations is being used. The assimilation enables quantifiable improvements in model forecast skill, which improves confidence in the accuracy of the officially-issued forecasts. This helps air quality stakeholders be more effective in taking mitigating actions (reducing power consumption, ride-sharing, etc.) and avoiding exposures that could otherwise result in more serious air quality episodes or more deleterious health effects.

Physiological Importance and Mechanisms of Protein Hydrolysate Absorption

NASA Astrophysics Data System (ADS)

Zhanghi, Brian M.; Matthews, James C.

Understanding opportunities to maximize the efficient digestion and assimilation by production animals of plant- and animal-derived protein products is critical for farmers, nutritionists, and feed manufacturers to sustain and expand the affordable production of high quality animal products for human consumption. The challenge to nutritionists is to match gastrointestinal tract load to existing or ­inducible digestive and absorptive capacities. The challenge to feed manufacturers is to develop products that are efficient substrates for digestion, absorption, and/or both events. Ultimately, the efficient absorption of digesta proteins depends on the mediated passage (transport) of protein hydrosylate products as dipeptides and unbound amino acids across the lumen- and blood-facing membranes of intestinal absorptive cells. Data testing the relative efficiency of supplying protein as hydrolysates or specific dipeptides versus as free amino acids, and the response of animals in several physiological states to feeding of protein hydrolysates, are presented and reviewed in this chapter. Next, data describing the transport mechanisms responsible for absorbing protein hydrolysate digestion products, and the known and putative regulation of these mechanisms by their substrates (small peptides) and hormones are presented and reviewed. Several conclusions are drawn regarding the efficient use of protein hydrolysate-based diets for particular physiological states, the economically-practical application of which likely will depend on technological advances in the manufacture of protein hydrolysate products.

Fresh insight to functioning of selected enzymes of the nitrogen cycle.

PubMed

Eady, Robert R; Antonyuk, Svetlana V; Hasnain, S Samar

2016-04-01

The global nitrogen cycle is the process in which different forms of environmental N are interconverted by microorganisms either for assimilation into biomass or in respiratory energy-generating pathways. This short review highlights developments over the last 5 years in our understanding of functionality of nitrogenase, Cu-nitrite reductase, NO reductase and N2O reductase, complex metalloenzymes that catalyze electron/proton-coupled substrate reduction reactions. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Crc/CrcZ-CrcY global regulatory system helps the integration of gluconeogenic and glycolytic metabolism in Pseudomonas putida.

PubMed

La Rosa, Ruggero; Nogales, Juan; Rojo, Fernando

2015-09-01

In metabolically versatile bacteria, carbon catabolite repression (CCR) facilitates the preferential assimilation of the most efficient carbon sources, improving growth rates and fitness. In Pseudomonas putida, the Crc and Hfq proteins and the CrcZ and CrcY small RNAs, which are believed to antagonize Crc/Hfq, are key players in CCR. Unlike that seen in other bacterial species, succinate and glucose elicit weak CCR in this bacterium. In the present work, metabolic, transcriptomic and constraint-based metabolic flux analyses were combined to clarify whether P. putida prefers succinate or glucose, and to identify the role of the Crc protein in the metabolism of these compounds. When provided simultaneously, succinate was consumed faster than glucose, although both compounds were metabolized. CrcZ and CrcY levels were lower when both substrates were present than when only one was provided, suggesting a role for Crc in coordinating metabolism of these compounds. Flux distribution analysis suggested that, when both substrates are present, Crc works to organize a metabolism in which carbon compounds flow in opposite directions: from glucose to pyruvate, and from succinate to pyruvate. Thus, our results support that Crc not only favours the assimilation of preferred compounds, but balances carbon fluxes, optimizing metabolism and growth. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

The extracellular matrix of the oleolytic biofilms of Marinobacter hydrocarbonoclasticus comprises cytoplasmic proteins and T2SS effectors that promote growth on hydrocarbons and lipids.

PubMed

Ennouri, Habiba; d'Abzac, Paul; Hakil, Florence; Branchu, Priscilla; Naïtali, Murielle; Lomenech, Anne-Marie; Oueslati, Ridha; Desbrières, Jacques; Sivadon, Pierre; Grimaud, Régis

2017-01-01

The assimilation of the nearly water insoluble substrates hydrocarbons and lipids by bacteria entails specific adaptations such as the formation of oleolytic biofilms. The present article reports that the extracellular matrix of an oleolytic biofilm formed by Marinobacter hydrocarbonoclasticus at n-hexadecane-water interfaces is largely composed of proteins typically cytoplasmic such as translation factors and chaperones, and a lesser amount of proteins of unknown function that are predicted extra-cytoplasmic. Matrix proteins appear to form a structured film on hydrophobic interfaces and were found mandatory for the development of biofilms on lipids, alkanes and polystyrene. Exo-proteins secreted through the type-2 secretion system (T2SS) were shown to be essential for the formation of oleolytic biofilms on both alkanes and triglycerides. The T2SS effector involved in biofilm formation on triglycerides was identified as a lipase. In the case of biofilm formation on n-hexadecane, the T2SS effector is likely involved in the mass transfer, capture or transport of alkanes. We propose that M. hydrocarbonoclasticus uses cytoplasmic proteins released by cell lysis to form a proteinaceous matrix and dedicated proteins secreted through the T2SS to act specifically in the assimilation pathways of hydrophobic substrates. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Contribution Of The SWOT Mission To Large-Scale Hydrological Modeling Using Data Assimilation

NASA Astrophysics Data System (ADS)

Emery, C. M.; Biancamaria, S.; Boone, A. A.; Ricci, S. M.; Rochoux, M. C.; Garambois, P. A.; Paris, A.; Calmant, S.

2016-12-01

The purpose of this work is to improve water fluxes estimation on the continental surfaces, at interanual and interseasonal scale (from few years to decennial time period). More specifically, it studies contribution of the incoming SWOT satellite mission to improve hydrology model at global scale, and using the land surface model ISBA-TRIP. This model corresponds to the continental component of the CNRM (French meteorological research center)'s climatic model. This study explores the potential of satellite data to correct either input parameters of the river routing scheme TRIP or its state variables. To do so, a data assimilation platform (using an Ensemble Kalman Filter, EnKF) has been implemented to assimilate SWOT virtual observations as well as discharges estimated from real nadir altimetry data. A series of twin experiments is used to test and validate the parameter estimation module of the platform. SWOT virtual-observations of water heights along SWOT tracks (with a 10 cm white noise model error) are assimilated to correct the river routing model parameters. To begin with, we chose to focus exclusively on the river manning coefficient, with the possibility to easily extend to other parameters such as the river widths. First results show that the platform is able to recover the "true" Manning distribution assimilating SWOT-like water heights. The error on the coefficients goes from 35 % before assimilation to 9 % after four SWOT orbit repeat period of 21 days. In the state estimation mode, daily assimilation cycles are realized to correct TRIP river water storage initial state by assimilating ENVISAT-based discharge. Those observations are derived from ENVISAT water elevation measures, using rating curves from the MGB-IPH hydrological model (calibrated over the Amazon using in situ gages discharge). Using such kind of observation allows going beyond idealized twin experiments and also to test contribution of a remotely-sensed discharge product, which could prefigure the SWOT discharge product. The results show that discharge after assimilation are globally improved : the root-mean-square error between the analysis discharge ensemble mean and in situ discharges is reduced by 30 %, compared to the root-mean-square error between the free run and in situ discharges.

Assimilable organic carbon (AOC) determination using GFP-tagged Pseudomonas fluorescens P-17 in water by flow cytometry.

PubMed

Tang, Peng; Wu, Jie; Liu, Hou; Liu, Youcai; Zhou, Xingding

2018-01-01

One of the newly developed methods for Assimilable organic carbon (AOC) determination is leveraged on the cell enumeration by flow cytometry (FC) which could provide a rapid and automated solution for AOC measurement. However, cell samples staining with fluorescence dye is indispensable to reduce background and machine noise. This step would bring additional cost and time consuming for this method. In this study, a green fluorescence protein (GFP) tagged strain derived of AOC testing strain Pseudomonas fluorescens P-17 (GFP-P17) was generated using Tn5 transposon mutagenesis. Continuous culture of this mutant GFP-P17 showed stable expression of eGFP signal detected by flow cytometry without staining step. In addition, this GFP-P17 strain displayed faster growth rate and had a wider range of carbon substrate utilization patterns as compared with P17 wild-type. With this strain, the capability of a new FC method with no dye staining was explored in standard acetate solution, which suggests linear correlation of counts with acetate carbon concentration. Furthermore, this FC method with GFP-P17 strain is applicable in monitoring GAC/BAC efficiency and condition as similar trends of AOC level in water treatment process were measured by both FC method and conventional spread plating count method. Therefore, this fast and easily applicable GFP-P17 based FC method could serve as a tool for routine microbiological drinking water monitoring.

On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

NASA Astrophysics Data System (ADS)

Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

2017-12-01

Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

Variational Continuous Assimilation of TMI and SSM/I Rain Rates: Impact on GEOS-3 Hurricane Analyses and Forecasts

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; Reale, Oreste

2003-01-01

We describe a variational continuous assimilation (VCA) algorithm for assimilating tropical rainfall data using moisture and temperature tendency corrections as the control variable to offset model deficiencies. For rainfall assimilation, model errors are of special concern since model-predicted precipitation is based on parameterized moist physics, which can have substantial systematic errors. This study examines whether a VCA scheme using the forecast model as a weak constraint offers an effective pathway to precipitation assimilation. The particular scheme we exarnine employs a '1+1' dimension precipitation observation operator based on a 6-h integration of a column model of moist physics from the Goddard Earth Observing System (GEOS) global data assimilation system DAS). In earlier studies, we tested a simplified version of this scheme and obtained improved monthly-mean analyses and better short-range forecast skills. This paper describes the full implementation ofthe 1+1D VCA scheme using background and observation error statistics, and examines how it may improve GEOS analyses and forecasts of prominent tropical weather systems such as hurricanes. Parallel assimilation experiments with and without rainfall data for Hurricanes Bonnie and Floyd show that assimilating 6-h TMI and SSM/I surfice rain rates leads to more realistic storm features in the analysis, which, in turn, provide better initial conditions for 5-day storm track prediction and precipitation forecast. These results provide evidence that addressing model deficiencies in moisture tendency may be crucial to making effective use of precipitation information in data assimilation.

Differential Assimilation of Inorganic Carbon and Leucine by Prochlorococcus in the Oligotrophic North Pacific Subtropical Gyre

PubMed Central

Björkman, Karin M.; Church, Matthew J.; Doggett, Joseph K.; Karl, David M.

2015-01-01

The light effect on photoheterotrophic processes in Prochlorococcus, and primary and bacterial productivity in the oligotrophic North Pacific Subtropical Gyre was investigated using 14C-bicarbonate and 3H-leucine. Light and dark incubation experiments were conducted in situ throughout the euphotic zone (0–175 m) on nine expeditions to Station ALOHA over a 3-year period. Photosynthetrons were also used to elucidate rate responses in leucine and inorganic carbon assimilation as a function of light intensity. Taxonomic group and cell-specific rates were assessed using flow cytometric sorting. The light:dark assimilation rate ratios of leucine in the top 150 m were ∼7:1 for Prochlorococcus, whereas the light:dark ratios for the non-pigmented bacteria (NPB) were not significant different from 1:1. Prochlorococcus assimilated leucine in the dark at per cell rates similar to the NPB, with a contribution to the total community bacterial production, integrated over the euphotic zone, of approximately 20% in the dark and 60% in the light. Depth-resolved primary productivity and leucine incorporation showed that the ratio of Prochlorococcus leucine:primary production peaked at 100 m then declined steeply below the deep chlorophyll maximum (DCM). The photosynthetron experiments revealed that, for Prochlorococcus at the DCM, the saturating irradiance (Ek) for leucine incorporation was reached at approximately half the light intensity required for light saturation of 14C-bicarbonate assimilation. Additionally, high and low red fluorescing Prochlorococcus populations (HRF and LRF), co-occurring at the DCM, had similar Ek values for their respective substrates, however, maximum assimilation rates, for both leucine and inorganic carbon, were two times greater for HRF cells. Our results show that Prochlorococcus contributes significantly to bacterial production estimates using 3H-leucine, whether or not the incubations are conducted in the dark or light, and this should be considered when making assessments of bacterial production in marine environments where Prochlorococcus is present. Furthermore, Prochlorococcus primary productivity showed rate to light-flux patterns that were different from its light enhanced leucine incorporation. This decoupling from autotrophic growth may indicate a separate light stimulated mechanism for leucine acquisition. PMID:26733953

The effect of dietary nicotine on the allocation of assimilated food to energy metabolism and growth in fourth-instar larvae of the southern armyworm, Spodoptera eridania (Lepidoptera: Noctuidae).

PubMed

Cresswell, James E; Merritt, Stewart Z; Martin, Michael M

1992-03-01

Dietary nicotine (0.5%), which is a substrate of the PSMO (polysubstrate monooxygenase) detoxification system in the southern armyworm Spodoptera eridania, has significant negative effects on the weight of food ingested, weight gained, relative growth rate (RGR), and efficiency of conversion of digested food (ECD) by fourthinstar S. eridania larvae on a nutrient-rich artificial diet. It has a significant positive effect on the weight of food respired by the larvae. Thus, the detoxification of nicotine by the PSMO system exacts a fitness cost and imposes a metabolic cost on S. eridania larvae. In contrast, dietary α-(+)-pinene, an inducer of the PSMO system, neither exacts a fitness cost nor imposes a metabolic cost on the larvae. We believe this to be the first study to demonstrate unequivocally that the negative effect of a dietary toxin on net growth efficiency (ECD) in an insect herbivore is due to an increase in the allocation of assimilated food to energy metabolism and not to a decrease in the amount of food assimilated. This study, therefore, supports the hypothesis that detoxification can impose a significant metabolic load on an insect herbivore. Implications of a corroboration of the metabolic load hypothesis are discussed.

Nitrification in the euphotic zone as evidenced by nitrate dual isotopic composition: Observations from Monterey Bay, California

USGS Publications Warehouse

Wankel, Scott D.; Kendall, C.; Pennington, J.T.; Chavez, F.P.; Paytan, A.

2007-01-01

Coupled measurements of nitrate (NO3-), nitrogen (N), and oxygen (O) isotopic composition (??15NNO3 and ??18ONO3) were made in surface waters of Monterey Bay to investigate multiple N cycling processes occurring within surface waters. Profiles collected throughout the year at three sites exhibit a wide range of values, suggesting simultaneous and variable influence of both phytoplankton NO3- assimilation and nitrification within the euphotic zone. Specifically, increases ??18ONO3 were consistently greater than those in ??15NN03. A coupled isotope steady state box model was used to estimate the amount of NO3- supplied by nitrification in surface waters relative to that supplied from deeper water. The model highlights the importance of the branching reaction during ammonium (NH4+) consumption, in which NH4+ either serves as a substrate for regenerated production or for nitrification. Our observations indicate that a previously unrecognized proportion of nitrate-based productivity, on average 15 to 27%, is supported by nitrification in surface waters and should not be considered new production. This work also highlights the need for a better understanding of isotope effects of NH4+ oxidation, NH4+ assimilation, and NO4+ assimilation in marine environments.

Validation Test Report for the Navy Coastal Ocean Model Four-Dimensional Variational Assimilation (NCOM 4DVAR) System Version 1.0

DTIC Science & Technology

2015-08-14

assimilated directly into a free surface ocean  model using NCOM 4DVAR methods without generating gravity waves.  The  latter is a serious  problem  that... The  bias of buoyancy frequency  in  the   left plot of figure 4‐19  reveals that  the  NCOM 4DVAR is doing fairly well at predicting  the   stratification ...Test Report for the Navy Coastal Ocean Model Four-Dimensional Variational Assimilation (NCOM 4DVAR) System Version 1.0 Scott Smith matthew carrier

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Crow, Wade T.; Thorp, Kelly R.; Moran, Mary S.; Reichle, Rolf H.; Gupta, Hoshin V.

2012-01-01

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Cybernetic modeling based on pathway analysis for Penicillium chrysogenum fed-batch fermentation.

PubMed

Geng, Jun; Yuan, Jingqi

2010-08-01

A macrokinetic model employing cybernetic methodology is proposed to describe mycelium growth and penicillin production. Based on the primordial and complete metabolic network of Penicillium chrysogenum found in the literature, the modeling procedure is guided by metabolic flux analysis and cybernetic modeling framework. The abstracted cybernetic model describes the transients of the consumption rates of the substrates, the assimilation rates of intermediates, the biomass growth rate, as well as the penicillin formation rate. Combined with the bioreactor model, these reaction rates are linked with the most important state variables, i.e., mycelium, substrate and product concentrations. Simplex method is used to estimate the sensitive parameters of the model. Finally, validation of the model is carried out with 20 batches of industrial-scale penicillin cultivation.

Effect of Data Assimilation Parameters on The Optimized Surface CO2 Flux in Asia

NASA Astrophysics Data System (ADS)

Kim, Hyunjung; Kim, Hyun Mee; Kim, Jinwoong; Cho, Chun-Ho

2018-02-01

In this study, CarbonTracker, an inverse modeling system based on the ensemble Kalman filter, was used to evaluate the effects of data assimilation parameters (assimilation window length and ensemble size) on the estimation of surface CO2 fluxes in Asia. Several experiments with different parameters were conducted, and the results were verified using CO2 concentration observations. The assimilation window lengths tested were 3, 5, 7, and 10 weeks, and the ensemble sizes were 100, 150, and 300. Therefore, a total of 12 experiments using combinations of these parameters were conducted. The experimental period was from January 2006 to December 2009. Differences between the optimized surface CO2 fluxes of the experiments were largest in the Eurasian Boreal (EB) area, followed by Eurasian Temperate (ET) and Tropical Asia (TA), and were larger in boreal summer than in boreal winter. The effect of ensemble size on the optimized biosphere flux is larger than the effect of the assimilation window length in Asia, but the importance of them varies in specific regions in Asia. The optimized biosphere flux was more sensitive to the assimilation window length in EB, whereas it was sensitive to the ensemble size as well as the assimilation window length in ET. The larger the ensemble size and the shorter the assimilation window length, the larger the uncertainty (i.e., spread of ensemble) of optimized surface CO2 fluxes. The 10-week assimilation window and 300 ensemble size were the optimal configuration for CarbonTracker in the Asian region based on several verifications using CO2 concentration measurements.

Three extracellular dipeptidyl peptidases found in Aspergillus oryzae show varying substrate specificities.

PubMed

Maeda, Hiroshi; Sakai, Daisuke; Kobayashi, Takuji; Morita, Hiroto; Okamoto, Ayako; Takeuchi, Michio; Kusumoto, Ken-Ichi; Amano, Hitoshi; Ishida, Hiroki; Yamagata, Youhei

2016-06-01

Three extracellular dipeptidyl peptidase genes, dppB, dppE, and dppF, were unveiled by sequence analysis of the Aspergillus oryzae genome. We investigated their differential enzymatic profiles, in order to gain an understanding of the diversity of these genes. The three dipeptidyl peptidases were expressed using Aspergillus nidulans as the host. Each recombinant enzyme was purified and subsequently characterized. The enzymes displayed similar optimum pH values, but optimum temperatures, pH stabilities, and substrate specificities varied. DppB was identified as a Xaa-Prolyl dipeptidyl peptidase, while DppE scissile substrates were similar to the substrates for Aspergillus fumigatus DPPV (AfDPPV). DppF was found to be a novel enzyme that could digest both substrates for A. fumigatus DPPIV and AfDPPV. Semi-quantitative PCR revealed that the transcription of dppB in A. oryzae was induced by protein substrates and repressed by the addition of an inorganic nitrogen source, despite the presence of protein substrates. The transcription of dppE depended on its growth time, while the transcription of dppF was not affected by the type of the nitrogen source in the medium, and it started during the early stage of the fungal growth. Based on these results, we conclude that these enzymes may represent the nutrition acquisition enzymes. Additionally, DppF may be one of the sensor peptidases responsible for the detection of the protein substrates in A. oryzae environment. DppB may be involved in nitrogen assimilation control, since the transcription of dppB was repressed by NaNO3, despite the presence of protein substrates.

Radiance Assimilation Shows Promise for Snowpack Characterization: A 1-D Case Study

NASA Technical Reports Server (NTRS)

Durand, Michael; Kim, Edward; Margulis, Steve

2008-01-01

We demonstrate an ensemble-based radiometric data assimilation (DA) methodology for estimating snow depth and snow grain size using ground-based passive microwave (PM) observations at 18.7 and 36.5 GHz collected during the NASA CLPX-1, March 2003, Colorado, USA. A land surface model was used to develop a prior estimate of the snowpack states, and a radiative transfer model was used to relate the modeled states to the observations. Snow depth bias was -53.3 cm prior to the assimilation, and -7.3 cm after the assimilation. Snow depth estimated by a non-DA-based retrieval algorithm using the same PM data had a bias of -18.3 cm. The sensitivity of the assimilation scheme to the grain size uncertainty was evaluated; over the range of grain size uncertainty tested, the posterior snow depth estimate bias ranges from -2.99 cm to -9.85 cm, which is uniformly better than both the prior and retrieval estimates. This study demonstrates the potential applicability of radiometric DA at larger scales.

Recent Updates to SWANFAR (registered trademark), a 5DVAR Data Assimilation System for SWAN

DTIC Science & Technology

2016-11-10

earized system was tested with datasets from Duck , NC, by Walker (2006) and later by Veeramony et al. (2010). Both studies demonstrated that, for...Warrior Free-Floating Buoy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2.2 Duck , NC...11 8 Domain for one-week non-stationary assimilation at Duck , NC. Color contours indicate bathymetry. From right

The Academic Achievement of Immigrant Children in Japan: An Empirical Analysis of the Assimilation Hypothesis

ERIC Educational Resources Information Center

Ishida, Kenji; Nakamuro, Makiko; Takenaka, Ayumi

2016-01-01

In this study, we test the assimilation thesis by comparing the academic achievement between native students and first and second generation immigrant pupils. It is the first empirical study that systematically analyzes the native-immigrant achievement gap in Japan. Although numerous studies have examined the achievement gap, most of them are…

Pinus sylvestris switches respiration substrates under shading but not during drought.

PubMed

Fischer, Sarah; Hanf, Stefan; Frosch, Torsten; Gleixner, Gerd; Popp, Jürgen; Trumbore, Susan; Hartmann, Henrik

2015-08-01

Reduced carbon (C) assimilation during prolonged drought forces trees to rely on stored C to maintain vital processes like respiration. It has been shown, however, that the use of carbohydrates, a major C storage pool and apparently the main respiratory substrate in plants, strongly declines with decreasing plant hydration. Yet no empirical evidence has been produced to what degree other C storage compounds like lipids and proteins may fuel respiration during drought. We exposed young scots pine trees to C limitation using either drought or shading and assessed respiratory substrate use by monitoring the respiratory quotient, δ(13) C of respired CO2 and concentrations of the major storage compounds, that is, carbohydrates, lipids and amino acids. Only shaded trees shifted from carbohydrate-dominated to lipid-dominated respiration and showed progressive carbohydrate depletion. In drought trees, the fraction of carbohydrates used in respiration did not decline but respiration rates were strongly reduced. The lower consumption and potentially allocation from other organs may have caused initial carbohydrate content to remain constant during the experiment. Our results suggest that respiratory substrates other than carbohydrates are used under carbohydrate limitation but not during drought. Thus, respiratory substrate shift cannot provide an efficient means to counterbalance C limitation under natural drought. © 2015 The Authors New Phytologist © 2015 New Phytologist Trust.

A single-substrate model to interpret high-resolution intra-annual stable isotope signals in tree ring cellulose

NASA Astrophysics Data System (ADS)

Ogée, J.; Barbour, M. M.; Dewar, R. C.; Wingate, L.; Bert, D.; Bosc, A.; Lambrot, C.; Stievenard, M.; Bariac, T.; Berbigier, P.; Loustau, D.

2007-12-01

High-resolution measurements of the carbon and oxygen stable isotope composition of cellulose in annual tree rings (δ13Ccellulose and δ18Ocellulose, respectively) reveal well-defined seasonal patterns that could contain valuable records of past climate and tree function. Interpreting these signals is nonetheless complex because they not only record the signature of current assimilates, but also depend on carbon allocation dynamics within the trees. Here, we will present a single-substrate model for wood growth in order to interpret qualitatively and quantitatively these seasonal isotopic signals. We will also show how this model can relate to more complex models of phloem transport and cambial activity. The model will then be tested against an isotopic intra-annual chronology collected on a Pinus pinaster tree equipped with point dendrometers and growing on a Carboeurope site where climate, soil and flux variables are also monitored. The empirical δ13Ccellulose and δ18Ocellulose signals exhibit dynamic seasonal patterns with clear differences between years, which makes it suitable for model testing. We will show how our simple model of carbohydrate reserves, forced by sap flow and eddy covariance measurements, enables us to interpret these seasonal and inter-annual patterns. Finally, we will present a sensitivity analysis of the model, showing how gas-exchange parameters, carbon and water pool sizes or wood maturation times affect these isotopic signals. Acknowledgements: this study benefited from the CarboEurope-IP Bray site facilities and was funded by the French INSU programme Eclipse, with an additional support from the INRA department EFPA.

Temperature Data Assimilation with Salinity Corrections: Validation for the NSIPP Ocean Data Assimilation System in the Tropical Pacific Ocean, 1993-1998

NASA Technical Reports Server (NTRS)

Troccoli, Alberto; Rienecker, Michele M.; Keppenne, Christian L.; Johnson, Gregory C.

2003-01-01

The NASA Seasonal-to-Interannual Prediction Project (NSIPP) has developed an Ocean data assimilation system to initialize the quasi-isopycnal ocean model used in our experimental coupled-model forecast system. Initial tests of the system have focused on the assimilation of temperature profiles in an optimal interpolation framework. It is now recognized that correction of temperature only often introduces spurious water masses. The resulting density distribution can be statically unstable and also have a detrimental impact on the velocity distribution. Several simple schemes have been developed to try to correct these deficiencies. Here the salinity field is corrected by using a scheme which assumes that the temperature-salinity relationship of the model background is preserved during the assimilation. The scheme was first introduced for a zlevel model by Troccoli and Haines (1999). A large set of subsurface observations of salinity and temperature is used to cross-validate two data assimilation experiments run for the 6-year period 1993-1998. In these two experiments only subsurface temperature observations are used, but in one case the salinity field is also updated whenever temperature observations are available.

Assimilation of remote sensing observations into a continuous distributed hydrological model: impacts on the hydrologic cycle

NASA Astrophysics Data System (ADS)

Laiolo, Paola; Gabellani, Simone; Campo, Lorenzo; Cenci, Luca; Silvestro, Francesco; Delogu, Fabio; Boni, Giorgio; Rudari, Roberto

2015-04-01

The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce in-situ data. This work investigates the impact of the assimilation of different remote sensing products on the hydrological cycle by using a continuous physically based distributed hydrological model. Three soil moisture products derived by ASCAT (Advanced SCATterometer) are used to update the model state variables. The satellite-derived products are assimilated into the hydrological model using different assimilation techniques: a simple nudging and the Ensemble Kalman Filter. Moreover two assimilation strategies are evaluated to assess the impact of assimilating the satellite products at model spatial resolution or at the satellite scale. The experiments are carried out for three Italian catchments on multi year period. The benefits on the model predictions of discharge, LST, evapotranspiration and soil moisture dynamics are tested and discussed.

Moving horizon estimation for assimilating H-SAF remote sensing data into the HBV hydrological model

NASA Astrophysics Data System (ADS)

Montero, Rodolfo Alvarado; Schwanenberg, Dirk; Krahe, Peter; Lisniak, Dmytro; Sensoy, Aynur; Sorman, A. Arda; Akkol, Bulut

2016-06-01

Remote sensing information has been extensively developed over the past few years including spatially distributed data for hydrological applications at high resolution. The implementation of these products in operational flow forecasting systems is still an active field of research, wherein data assimilation plays a vital role on the improvement of initial conditions of streamflow forecasts. We present a novel implementation of a variational method based on Moving Horizon Estimation (MHE), in application to the conceptual rainfall-runoff model HBV, to simultaneously assimilate remotely sensed snow covered area (SCA), snow water equivalent (SWE), soil moisture (SM) and in situ measurements of streamflow data using large assimilation windows of up to one year. This innovative application of the MHE approach allows to simultaneously update precipitation, temperature, soil moisture as well as upper and lower zones water storages of the conceptual model, within the assimilation window, without an explicit formulation of error covariance matrixes and it enables a highly flexible formulation of distance metrics for the agreement of simulated and observed variables. The framework is tested in two data-dense sites in Germany and one data-sparse environment in Turkey. Results show a potential improvement of the lead time performance of streamflow forecasts by using perfect time series of state variables generated by the simulation of the conceptual rainfall-runoff model itself. The framework is also tested using new operational data products from the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) of EUMETSAT. This study is the first application of H-SAF products to hydrological forecasting systems and it verifies their added value. Results from assimilating H-SAF observations lead to a slight reduction of the streamflow forecast skill in all three cases compared to the assimilation of streamflow data only. On the other hand, the forecast skill of soil moisture shows a significant improvement.

Evidence for an operative glutamine translocator in chloroplasts from maritime pine (Pinus pinaster Ait.) cotyledons.

PubMed

Claros, M G; Aguilar, M L; Cánovas, F M

2010-09-01

In higher plants, ammonium is assimilated into amino acids through the glutamine synthetase (GS)/glutamate synthase (GOGAT) cycle. This metabolic cycle is distributed in different cellular compartments in conifer seedlings: glutamine synthesis occurs in the cytosol and glutamate synthesis within the chloroplast. A method for preparing intact chloroplasts of pine cotyledons is presented with the aim of identifying a glutamine-glutamate translocator. Glutamine-glutamate exchange has been studied using the double silicone layer system, suggesting the existence of a translocator that imports glutamine into the chloroplast and exports glutamate to the cytoplasm. The translocator identified is specific for glutamine and glutamate, and the kinetic constants for both substrates indicate that it is unsaturated at intracellular concentrations. Thus, the experimental evidence obtained supports the model of the GS/GOGAT cycle in developing pine seedlings that accounts for the stoichiometric balance of metabolites. As a result, the efficient assimilation of free ammonia produced by photorespiration, nitrate reduction, storage protein mobilisation, phenylpropanoid pathway or S-adenosylmethionine synthesis is guaranteed.

OK, thanks! A new mutualism between Chlamydomonas and methylobacteria facilitates growth on amino acids and peptides.

PubMed

Calatrava, Victoria; Hom, Erik F Y; Llamas, Ángel; Fernández, Emilio; Galván, Aurora

2018-04-01

Nitrogen is a key nutrient for land plants and phytoplankton in terrestrial and aquatic ecosystems. The model alga Chlamydomonas reinhardtii can grow efficiently on several inorganic nitrogen sources (e.g. ammonium, nitrate, nitrite) as well as many amino acids. In this study, we show that Chlamydomonas is unable to use proline, hydroxyproline and peptides that contain these amino acids. However, we discovered that algal growth on these substrates is supported in association with Methylobacterium spp., and that a mutualistic carbon-nitrogen metabolic exchange between Chlamydomonas and Methylobacterium spp. is established. Specifically, the mineralization of these amino acids and peptides by Methylobacterium spp. produces ammonium that can be assimilated by Chlamydomonas, and CO2 photosynthetically fixed by Chlamydomonas yields glycerol that can be assimilated by Methylobacterium. As Chlamydomonas is an algal ancestor to land plants and Methylobacterium is a plant growth-promoting bacterium, this new model of mutualism may facilitate insights into the ecology and evolution of plant-bacterial interactions and design principles of synthetic ecology.

Evaluation of assimilatory sulphur metabolism in Caldicellulosiruptor saccharolyticus.

PubMed

Pawar, Sudhanshu S; van Niel, Ed W J

2014-10-01

Caldicellulosiruptor saccharolyticus has gained reputation as being among the best microorganisms to produce H2 due to possession of various appropriate features. The quest to develop an inexpensive cultivation medium led to determine a possible replacement of the expensive component cysteine, i.e. sulphate. C. saccharolyticus assimilated sulphate successfully in absence of a reducing agent without releasing hydrogen sulphide. A complete set of genes coding for enzymes required for sulphate assimilation were found in the majority of Caldicellulosiruptor species including C. saccharolyticus. C. saccharolyticus displayed indifferent physiological behaviour to source of sulphur when grown under favourable conditions in continuous cultures. Increasing the usual concentration of sulphur in the feed medium increased substrate conversion. Choice of sulphur source did not affect the tolerance of C. saccharolyticus to high partial pressures of H2. Thus, sulphate can be a principle sulphur source in an economically viable and more sustainable biohydrogen process using C. saccharolyticus. Copyright © 2014 Elsevier Ltd. All rights reserved.

RNA-based stable isotope probing (RNA-SIP) to unravel intestinal host-microbe interactions.

PubMed

Egert, Markus; Weis, Severin; Schnell, Sylvia

2018-05-30

The RNA-SIP technology, introduced into molecular microbial ecology in 2002, is an elegant technique to link the structure and function of complex microbial communities, i.e. to identify microbial key-players involved in distinct degradation and assimilation processes under in-situ conditions. Due to its dependence of microbial RNA, this technique is particularly suited for environments with high numbers of very active, i.e. significantly RNA-expressing, bacteria. So far, it was mainly used in environmental studies using microbiotas from soil or water habitats. Here we outline and summarize our application of RNA-SIP for the identification of bacteria involved in the degradation and assimilation of prebiotic carbohydrates in intestinal samples of human and animal origin. Following an isotope label from a prebiotic substrate into the RNA of distinct bacterial taxa will help to better understand the functionality of these medically and economically important nutrients in an intestinal environment. Copyright © 2018 Elsevier Inc. All rights reserved.

Assimilation of ASCAT near-surface soil moisture into the French SIM hydrological model

NASA Astrophysics Data System (ADS)

Draper, C.; Mahfouf, J.-F.; Calvet, J.-C.; Martin, E.; Wagner, W.

2011-06-01

The impact of assimilating near-surface soil moisture into the SAFRAN-ISBA-MODCOU (SIM) hydrological model over France is examined. Specifically, the root-zone soil moisture in the ISBA land surface model is constrained over three and a half years, by assimilating the ASCAT-derived surface degree of saturation product, using a Simplified Extended Kalman Filter. In this experiment ISBA is forced with the near-real time SAFRAN analysis, which analyses the variables required to force ISBA from relevant observations available before the real time data cut-off. The assimilation results are tested against ISBA forecasts generated with a higher quality delayed cut-off SAFRAN analysis. Ideally, assimilating the ASCAT data will constrain the ISBA surface state to correct for errors in the near-real time SAFRAN forcing, the most significant of which was a substantial dry bias caused by a dry precipitation bias. The assimilation successfully reduced the mean root-zone soil moisture bias, relative to the delayed cut-off forecasts, by close to 50 % of the open-loop value. The improved soil moisture in the model then led to significant improvements in the forecast hydrological cycle, reducing the drainage, runoff, and evapotranspiration biases (by 17 %, 11 %, and 70 %, respectively). When coupled to the MODCOU hydrogeological model, the ASCAT assimilation also led to improved streamflow forecasts, increasing the mean discharge ratio, relative to the delayed cut off forecasts, from 0.68 to 0.76. These results demonstrate that assimilating near-surface soil moisture observations can effectively constrain the SIM model hydrology, while also confirming the accuracy of the ASCAT surface degree of saturation product. This latter point highlights how assimilation experiments can contribute towards the difficult issue of validating remotely sensed land surface observations over large spatial scales.

Photosynthetic carbon assimilation in the coccolithophorid Emiliania huxleyi (Haptophyta): Evidence for the predominant operation of the c3 cycle and the contribution of {beta}-carboxylases to the active anaplerotic reaction.

PubMed

Tsuji, Yoshinori; Suzuki, Iwane; Shiraiwa, Yoshihiro

2009-02-01

The coccolithophorid Emiliania huxleyi (Haptophyta) is a representative and unique marine phytoplankton species that fixes inorganic carbon by photosynthesis and calci-fication. We examined the initial process of photosynthetic carbon assimilation by analyses of metabolites, enzymes and genes. When the cells were incubated with a radioactive substrate (2.3 mM NaH(14)CO(3)) for 10 s under illumination, 70% of the (14)C was incorporated into the 80% methanol-soluble fraction. Eighty-five and 15% of (14)C in the soluble fraction was incorporated into phosphate esters (P-esters), including the C(3) cycle intermediates and a C(4) compound, aspartate, respectively. A pulse-chase experiment showed that (14)C in P-esters was mainly transferred into lipids, while [(14)C]aspartate, [(14)C]alanine and [(14)C]glutamate levels remained almost constant. These results indicate that the C(3) cycle functions as the initial pathway of carbon assimilation and that beta-carboxylation contributes to the production of amino acids in subsequent metabolism. Transcriptional analysis of beta-carboxylases such as pyruvate carboxylase (PYC), phosphoenolpyruvate carboxylase (PEPC) and phosphoenolpyruvate carboxykinase (PEPCK) revealed that PYC and PEPC transcripts were greatly increased under illumination, whereas the PEPCK transcript decreased remarkably. PEPC activity was higher in light-grown cells than in dark-adapted cells. PYC activity was detected in isolated chloroplasts of light-grown cells. According to analysis of their deduced N-terminal sequence, PYC and PEPC are predicted to be located in the chloroplasts and mitochondria, respectively. These results suggest that E. huxleyi possesses unique carbon assimila-tion mechanisms in which beta-carboxylation by both PYC and PEPC plays important roles in different organelles.

Estimating the soil moisture profile by assimilating near-surface observations with the ensemble Kalman filter (EnKF)

NASA Astrophysics Data System (ADS)

Zhang, Shuwen; Li, Haorui; Zhang, Weidong; Qiu, Chongjian; Li, Xin

2005-11-01

The paper investigates the ability to retrieve the true soil moisture profile by assimilating near-surface soil moisture into a soil moisture model with an ensemble Kaiman filter (EnKF) assimilation scheme, including the effect of ensemble size, update interval and nonlinearities in the profile retrieval, the required time for full retrieval of the soil moisture profiles, and the possible influence of the depth of the soil moisture observation. These questions are addressed by a desktop study using synthetic data. The “true” soil moisture profiles are generated from the soil moisture model under the boundary condition of 0.5 cm d-1 evaporation. To test the assimilation schemes, the model is initialized with a poor initial guess of the soil moisture profile, and different ensemble sizes are tested showing that an ensemble of 40 members is enough to represent the covariance of the model forecasts. Also compared are the results with those from the direct insertion assimilation scheme, showing that the EnKF is superior to the direct insertion assimilation scheme, for hourly observations, with retrieval of the soil moisture profile being achieved in 16 h as compared to 12 days or more. For daily observations, the true soil moisture profile is achieved in about 15 days with the EnKF, but it is impossible to approximate the true moisture within 18 days by using direct insertion. It is also found that observation depth does not have a significant effect on profile retrieval time for the EnKF. The nonlinearities have some negative influence on the optimal estimates of soil moisture profile but not very seriously.

IASI Radiance Data Assimilation in Local Ensemble Transform Kalman Filter

NASA Astrophysics Data System (ADS)

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.

Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data

NASA Astrophysics Data System (ADS)

Chen, X.; Murakami, H.; Hahn, M. S.; Hammond, G. E.; Rockhold, M. L.; Rubin, Y.

2010-12-01

Tracer testing under natural or forced gradient flow provides useful information for characterizing subsurface properties, by monitoring and modeling the tracer plume migration in a heterogeneous aquifer. At the Hanford 300 Area, non-reactive tracer experiments, in addition to constant-rate injection tests and electromagnetic borehole flowmeter (EBF) profiling, were conducted to characterize the heterogeneous hydraulic conductivity field. A Bayesian data assimilation technique, method of anchored distributions (MAD), is applied to assimilate the experimental tracer test data and to infer the three-dimensional heterogeneous structure of the hydraulic conductivity in the saturated zone of the Hanford formation. In this study, the prior information of the underlying random hydraulic conductivity field was obtained from previous field characterization efforts using the constant-rate injection tests and the EBF data. The posterior distribution of the random field is obtained by further conditioning the field on the temporal moments of tracer breakthrough curves at various observation wells. The parallel three-dimensional flow and transport code PFLOTRAN is implemented to cope with the highly transient flow boundary conditions at the site and to meet the computational demand of the proposed method. The validation results show that the field conditioned on the tracer test data better reproduces the tracer transport behavior compared to the field characterized previously without the tracer test data. A synthetic study proves that the proposed method can effectively assimilate tracer test data to capture the essential spatial heterogeneity of the three-dimensional hydraulic conductivity field. These characterization results will improve conceptual models developed for the site, including reactive transport models. The study successfully demonstrates the capability of MAD to assimilate multi-scale multi-type field data within a consistent Bayesian framework. The MAD framework can potentially be applied to combine geophysical data with other types of data in site characterization.

Phylogenetic identification of methanogens assimilating acetate-derived carbon in dairy and swine manures.

PubMed

Barret, Maialen; Gagnon, Nathalie; Morissette, Bruno; Kalmokoff, Martin L; Topp, Edward; Brooks, Stephen P J; Matias, Fernando; Neufeld, Josh D; Talbot, Guylaine

2015-02-01

In order to develop approaches for reducing the carbon footprint of the swine and dairy industries, it is important first to identify the methanogenic communities that drive methane emissions from stored manure. In this study, the metabolically active methanogens in substrate-starved manure samples taken from two dairy and one swine manure storage tanks were identified using [(13)C]-acetate and DNA stable-isotope probing (DNA-SIP). Molecular analysis of recovered genomic [(13)C]-DNA revealed that two distinct clusters of unclassified methanogen populations affiliated with the Methanoculleus genus, and the populations affiliated with Methanoculleus chikugoensis assimilated acetate-derived carbon (acetate-C) in swine and dairy starved manure samples, respectively. Furthermore, carbon flow calculations indicated that these populations were the primary contributors to methane emissions during these anoxic SIP incubations. Comparative analysis of mcrA gene abundance (coding for a key enzyme of methanogenesis) for Methanoculleus spp. in fresh feces and a wider range of stored dairy or swine manure samples, by real-time quantitative PCR using newly designed specific primers, demonstrated that the abundance of this genus significantly increased during storage. The findings supported the involvement of these particular methanogen populations as methane emitters from swine and dairy manure storage tanks. The study revealed that the ability to assimilate acetate-C for growth in manure differed within the Methanoculleus genus. Crown Copyright © 2014. Published by Elsevier GmbH. All rights reserved.

On using scatterometer and altimeter data to improve storm surge forecasting in the Adriatic Sea

NASA Astrophysics Data System (ADS)

Bajo, Marco; Umgiesser, Georg; De Biasio, Francesco; Vignudelli, Stefano; Zecchetto, Stefano

2017-04-01

Satellite data are seldom used in storm surge forecasting. Among the most important issues related to the storm surge forecasting are the quality of the model wind forcing and the initial condition of the sea surface elevation. In this work, focused on storm surge forecasting in the Adriatic Sea, satellite scatterometer wind data are used to correct the wind speed and direction biases of the ECMWF global atmospheric model by tuning the spatial fields, as an alternative to data assimilation. The capability of such an unbiased wind is tested against that of a high resolution wind, produced by a regional non-hydrostatic model. On the other hand, altimeter Total Water Level Envelope (TWLE) data, which provide the sea level elevation, are used to improve the accuracy of the initial state of the model simulations. This is done by assimilating into a storm surge model the TWLE obtained by the altimeter observations along ground tracks, after subtraction of the tidal components. In order to test the methodology, eleven storm surge events recorded in Venice, from 2008 to 2012, have been simulated using different configurations of forcing wind and altimeter data assimilation. Results show that the relative error on the estimation of the maximum surge peak, averaged over the cases considered, decreases from 13% to 7% using both the unbiased wind and the altimeter data assimilation, while forcing the hydrodynamic model with the high resolution wind (no tuning), the altimeter data assimilation reduces the error from 9% to 6%.

Oregon Washington Coastal Ocean Forecast System: Real-time Modeling and Data Assimilation

NASA Astrophysics Data System (ADS)

Erofeeva, S.; Kurapov, A. L.; Pasmans, I.

2016-02-01

Three-day forecasts of ocean currents, temperature and salinity along the Oregon and Washington coasts are produced daily by a numerical ROMS-based ocean circulation model. NAM is used to derive atmospheric forcing for the model. Fresh water discharge from Columbia River, Fraser River, and small rivers in Puget Sound are included. The forecast is constrained by open boundary conditions derived from the global Navy HYCOM model and once in 3 days assimilation of recent data, including HF radar surface currents, sea surface temperature from the GOES satellite, and SSH from several satellite altimetry missions. 4-dimensional variational data assimilation is implemented in 3-day time windows using the tangent linear and adjoint codes developed at OSU. The system is semi-autonomous - all the data, including NAM and HYCOM fields are automatically updated, and daily operational forecast is automatically initiated. The pre-assimilation data quality control and post-assimilation forecast quality control require the operator's involvement. The daily forecast and 60 days of hindcast fields are available for public on opendap. As part of the system model validation plots to various satellites and SEAGLIDER are also automatically updated and available on the web (http://ingria.coas.oregonstate.edu/rtdavow/). Lessons learned in this pilot real-time coastal ocean forecasting project help develop and test metrics for forecast skill assessment for the West Coast Operational Forecast System (WCOFS), currently at testing and development phase at the National Oceanic and Atmospheric Administration (NOAA).

The impact of Surface Wind Velocity Data Assimilation on the Predictability of Plume Advection in the Lower Troposphere

NASA Astrophysics Data System (ADS)

Sekiyama, Thomas; Kajino, Mizuo; Kunii, Masaru

2017-04-01

The authors investigated the impact of surface wind velocity data assimilation on the predictability of plume advection in the lower troposphere exploiting the radioactive cesium emitted by the Fukushima nuclear accident in March 2011 as an atmospheric tracer. It was because the radioactive cesium plume was dispersed from the sole point source exactly placed at the Fukushima Daiichi Nuclear Power Plant and its surface concentration was measured at many locations with a high frequency and high accuracy. We used a non-hydrostatic regional weather prediction model with a horizontal resolution of 3 km, which was coupled with an ensemble Kalman filter data assimilation system in this study, to simulate the wind velocity and plume advection. The main module of this weather prediction model has been developed and used operationally by the Japan Meteorological Agency (JMA) since before March 2011. The weather observation data assimilated into the model simulation were provided from two data resources; [#1] the JMA observation archives collected for numerical weather predictions (NWPs) and [#2] the land-surface wind velocity data archived by the JMA surface weather observation network. The former dataset [#1] does not contain land-surface wind velocity observations because their spatial representativeness is relatively small and therefore the land-surface wind velocity data assimilation normally deteriorates the more than one day NWP performance. The latter dataset [#2] is usually used for real-time weather monitoring and never used for the data assimilation of more than one day NWPs. We conducted two experiments (STD and TEST) to reproduce the radioactive cesium plume behavior for 48 hours from 12UTC 14 March to 12UTC 16 March 2011 over the land area of western Japan. The STD experiment was performed to replicate the operational NWP using only the #1 dataset, not assimilating land-surface wind observations. In contrast, the TEST experiment was performed assimilating both the #1 dataset and the #2 dataset including land-surface wind observations measured at more than 200 stations in the model domain. The meteorological boundary conditions for both the experiments were imported from the JMA operational global NWP model results. The modeled radioactive cesium concentrations were examined for plume arrival timing at each observatory comparing with the hourly-measured "suspended particulate matter" filter tape's cesium concentrations retrieved by Tsuruta et al. at more than 40 observatories. The averaged difference of the plume arrival times at 40 observatories between the observational reality and the STD experiment was 82.0 minutes; at this time, the forecast period was 13 hours on average. Meanwhile, The averaged difference of the TEST experiment was 72.8 minutes, which was smaller than that of the STD experiment with a statistical significance of 99.2 %. In summary, the land-surface wind velocity data assimilation improves the predictability of plume advection in the lower troposphere at least in the case of wintertime air pollution over complex terrain. We need more investigation into the data assimilation impact of land-surface weather observations on the predictability of pollutant dispersion especially in the planetary boundary layer.

Assimilation of Feng-Yun-3B satellite microwave humidity sounder data over land

NASA Astrophysics Data System (ADS)

Chen, Keyi; Bormann, Niels; English, Stephen; Zhu, Jiang

2018-03-01

The ECMWF has been assimilating Feng-Yun-3B (FY-3B) satellite microwave humidity sounder (MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz (vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS (Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.

Towards the Operational Ensemble-based Data Assimilation System for the Wave Field at the National Weather Service

NASA Astrophysics Data System (ADS)

Flampouris, Stylianos; Penny, Steve; Alves, Henrique

2017-04-01

The National Centers for Environmental Prediction (NCEP) of the National Oceanic and Atmospheric Administration (NOAA) provides the operational wave forecast for the US National Weather Service (NWS). Given the continuous efforts to improve forecast, NCEP is developing an ensemble-based data assimilation system, based on the local ensemble transform Kalman filter (LETKF), the existing operational global wave ensemble system (GWES) and on satellite and in-situ observations. While the LETKF was designed for atmospheric applications (Hunt et al 2007), and has been adapted for several ocean models (e.g. Penny 2016), this is the first time applied for oceanic waves assimilation. This new wave assimilation system provides a global estimation of the surface sea state and its approximate uncertainty. It achieves this by analyzing the 21-member ensemble of the significant wave height provided by GWES every 6h. Observations from four altimeters and all the available in-situ measurements are used in this analysis. The analysis of the significant wave height is used for initializing the next forecasting cycle; the data assimilation system is currently being tested for operational use.

Accumulation of α-Keto Acids as Essential Components in Cyanide Assimilation by Pseudomonas fluorescens NCIMB 11764

PubMed Central

Kunz, Daniel A.; Chen, Jui-Lin; Pan, Guangliang

1998-01-01

Pyruvate (Pyr) and α-ketoglutarate (αKg) accumulated when cells of Pseudomonas fluorescens NCIMB 11764 were cultivated on growth-limiting amounts of ammonia or cyanide and were shown to be responsible for the nonenzymatic removal of cyanide from culture fluids as previously reported (J.-L. Chen and D. A. Kunz, FEMS Microbiol. Lett. 156:61–67, 1997). The accumulation of keto acids in the medium paralleled the increase in cyanide-removing activity, with maximal activity (760 μmol of cyanide removed min−1 ml of culture fluid−1) being recovered after 72 h of cultivation, at which time the keto acid concentration was 23 mM. The reaction products that formed between the biologically formed keto acids and cyanide were unambiguously identified as the corresponding cyanohydrins by 13C nuclear magnetic resonance spectroscopy. Both the Pyr and α-Kg cyanohydrins were further metabolized by cell extracts and served also as nitrogenous growth substrates. Radiotracer experiments showed that CO2 (and NH3) were formed as enzymatic conversion products, with the keto acid being regenerated as a coproduct. Evidence that the enzyme responsible for cyanohydrin conversion is cyanide oxygenase, which was shown previously to be required for cyanide utilization, is based on results showing that (i) conversion occurred only when extracts were induced for the enzyme, (ii) conversion was oxygen and reduced-pyridine nucleotide dependent, and (iii) a mutant strain defective in the enzyme was unable to grow when it was provided with the cyanohydrins as a growth substrate. Pyr and αKg were further shown to protect cells from cyanide poisoning, and excretion of the two was directly linked to utilization of cyanide as a growth substrate. The results provide the basis for a new mechanism of cyanide detoxification and assimilation in which keto acids play an essential role. PMID:9797306

The gluconeogenesis pathway is involved in maintenance of enterohaemorrhagic Escherichia coli O157:H7 in bovine intestinal content.

PubMed

Bertin, Yolande; Deval, Christiane; de la Foye, Anne; Masson, Luke; Gannon, Victor; Harel, Josée; Martin, Christine; Desvaux, Mickaël; Forano, Evelyne

2014-01-01

Enterohaemorrhagic Escherichia coli (EHEC) are responsible for outbreaks of food- and water-borne illness. The bovine gastrointestinal tract (GIT) is thought to be the principle reservoir of EHEC. Knowledge of the nutrients essential for EHEC growth and survival in the bovine intestine may help in developing strategies to limit their shedding in bovine faeces thus reducing the risk of human illnesses. To identify specific metabolic pathways induced in the animal GIT, the transcriptome profiles of EHEC O157:H7 EDL933 during incubation in bovine small intestine contents (BSIC) and minimal medium supplemented with glucose were compared. The transcriptome analysis revealed that genes responsible for the assimilation of ethanolamine, urea, agmatine and amino acids (Asp, Thr, Gly, Ser and Trp) were strongly up-regulated suggesting that these compounds are the main nitrogen sources for EHEC in BSIC. A central role for the gluconeogenesis pathway and assimilation of gluconeogenic substrates was also pinpointed in EHEC incubated in BSIC. Our results suggested that three amino acids (Asp, Ser and Trp), glycerol, glycerol 3-phosphate, L-lactate and C4-dicarboxylates are important carbon sources for EHEC in BSIC. The ability to use gluconeogenic substrates as nitrogen sources (amino acids) and/or carbon sources (amino acids, glycerol and lactate) may provide a growth advantage to the bacteria in intestinal fluids. Accordingly, aspartate (2.4 mM), serine (1.9 mM), glycerol (5.8 mM) and lactate (3.6 mM) were present in BSIC and may represent the main gluconeogenic substrates potentially used by EHEC. A double mutant of E. coli EDL933 defective for phosphoenolpyruvate synthase (PpsA) and phosphoenolpyruvate carboxykinase (PckA), unable to utilize tricarboxylic acid (TCA) intermediates was constructed. Growth competition experiments between EHEC EDL933 and the isogenic mutant strain in BSIC clearly showed a significant competitive growth advantage of the wild-type strain further illustrating the importance of the gluconeogenesis pathway in maintaining EHEC in the bovine GIT.

DOE Office of Scientific and Technical Information (OSTI.GOV)

French, Jarrod B.; Ealick, Steven E.

Many plants, fungi, and bacteria catabolize allantoin as a mechanism for nitrogen assimilation. Recent reports have shown that in plants and some bacteria the product of hydrolysis of allantoin by allantoinase is the unstable intermediate ureidoglycine. While this molecule can spontaneously decay, genetic analysis of some bacterial genomes indicates that an aminotransferase may be present in the pathway. Here we present evidence that Klebsiella pneumoniae HpxJ is an aminotransferase that preferentially converts ureidoglycine and an {alpha}-keto acid into oxalurate and the corresponding amino acid. We determined the crystal structure of HpxJ, allowing us to present an explanation for substrate specificity.

Assimilation of Unusual Carbon Compounds

NASA Astrophysics Data System (ADS)

Middelhoven, Wouter J.

Yeast taxa traditionally are distinguished by growth tests on several sugars and organic acids. During the last decades it became apparent that many yeast species assimilate a much greater variety of naturally occurring carbon compounds as sole source of carbon and energy. These abilities are indicative of a greater role of yeasts in the carbon cycle than previously assumed. Especially in acidic soils and other habitats, yeasts may play a role in the degradation of carbon compounds. Such compounds include purines like uric acid and adenine, aliphatic amines, diamines and hydroxyamines, phenolics and other benzene compounds and polysaccharides. Assimilation of purines and amines is a feature of many ascomycetes and basidiomycetes. However, benzene compounds are degraded by only a few ascomycetous yeasts (e.g. the Stephanoascus/ Blastobotrys clade and black yeastlike fungi) but by many basidiomycetes, e.g. Filobasidiales, Trichosporonales, red yeasts producing ballistoconidia and related species, but not by Tremellales. Assimilation of polysaccharides is wide-spread among basidiomycetes

CATS Version 2 Aerosol Feature Detection and Applications for Data Assimilation

NASA Technical Reports Server (NTRS)

Nowottnick, Ed; Yorks, John; McGill, Matt; Scott, Stan; Palm, Stephen; Hlavka, Dennis; Hart, William; Selmer, Patrick; Kupchock, Andrew; Pauly, Rebecca

2017-01-01

Using GEOS-5, we are developing a 1D ENS approach for assimilating CATS near real time observations of total attenuated backscatter at 1064 nm: a) After performing a 1-ENS assimilation of a cloud-free profile, the GEOS-5 analysis closely followed observed total attenuated backscatter. b) Vertical localization length scales were varied for the well-mixed PBL and the free troposphere After assimilating a cloud free segment of a CATS granule, the fine detail of a dust event was obtained in the GEOS-5 analysis for both total attenuated backscatter and extinction. Future Work: a) Explore horizontal localization and test within a cloudy aerosol layer. b) Address noisy analysis increments in the free troposphere where both CATS and GEOS-5 aerosol loadings are low. c) Develop a technique to screen CATS ground return from profiles. d) "Dynamic" lidar ratio that will evolve in conjunction with simulated aerosol mixtures.

High-Frequency Planetary Waves in the Polar Middle Atmosphere as seen in a data Assimilation System

NASA Technical Reports Server (NTRS)

Coy, L.; Stajner, I.; DaSilva, A. M.; Joiner, J.; Rood, R. B.; Pawson, S.; Lin, S. J.

2003-01-01

This study examines the winter southern hemisphere vortex of 1998 using four times daily output from a data assimilation system to focus on the polar 2-day, wave number 2 component of the 4-day wave. The data assimilation system products are from a test version of the finite volume data assimilation system (fvDAS) being developed at Goddard Space Flight Center (GSFC) and include an ozone assimilation system. Results show that the polar 2-day wave dominates during July 1998 at 70 degrees. The period of the quasi 2-day wave is somewhat shorter than 2 days (about 1.7 days) during July 1998 with an average perturbation temperature amplitude for the month of over 2.5 K. The 2-day wave propagates more slowly than the zonal mean zonal wind, consistent with Rossby wave theory, and has EP flux divergence regions associated with regions of negative horizontal potential vorticity gradients, as expected from linear instability theory. Results for the assimilation-produced ozone mixing ratio show that the 2-day wave represents a major source of ozone variation in this region. The ozone wave in the assimilation system is in good agreement with the wave seen in the POAM (Polar Ozone and Aerosol Measurement) ozone observations for the same time period. Some differences with linear instability theory are noted as well as spectral peaks in the ozone field, not seen in the temperature field, that may be a consequence of advection.

Improved track forecasting of a typhoon reaching landfall from four-dimensional variational data assimilation of AMSU-A retrieved data

NASA Astrophysics Data System (ADS)

Zhao, Ying; Wang, Bin; Ji, Zhongzhen; Liang, Xudong; Deng, Guo; Zhang, Xin

2005-07-01

In this study, an attempt to improve typhoon forecasts is made by incorporating three-dimensional Advanced Microwave Sounding Unit-A (AMSU-A) retrieved wind and temperature and the central sea level pressure of cyclones from typhoon reports or bogus surface low data into initial conditions, on the basis of the Fifth-Generation National Center for Atmospheric Research/Pennsylvania State University Mesoscale Model (MM5) four-dimensional variational data assimilation (4DVar) system with a full-physics adjoint model. All the above-mentioned data are found to be useful for improvement of typhoon forecasts in this mesoscale data assimilation experiment. The comparison tests showed the following results: (1) The assimilation of the satellite-retrieved data was found to have a positive impact on the typhoon track forecast, but the landing position error is ˜150 km. (2) The assimilation of both the satellite-retrieved data and moving information of the typhoon center dramatically improved the track forecast and captured the recurvature and landfall. The mean track error during the 72-hour forecast is 69 km. The predicted typhoon intensity, however, is much weaker than that from observations. (3) The assimilation of both the satellite-retrieved data and the bogus surface low data improved the intensity and track forecasts more significantly than the assimilation of only bogus surface low data (bogus data assimilation) did. The mean errors during the 72-hour forecast are 2.6 hPa for the minimum sea level pressure and 87 km for track position. However, the forecasted landing time is ˜6 hours earlier than the observed one.

Assimilation of ASCAT near-surface soil moisture into the SIM hydrological model over France

NASA Astrophysics Data System (ADS)

Draper, C.; Mahfouf, J.-F.; Calvet, J.-C.; Martin, E.; Wagner, W.

2011-12-01

This study examines whether the assimilation of remotely sensed near-surface soil moisture observations might benefit an operational hydrological model, specifically Météo-France's SAFRAN-ISBA-MODCOU (SIM) model. Soil moisture data derived from ASCAT backscatter observations are assimilated into SIM using a Simplified Extended Kalman Filter (SEKF) over 3.5 years. The benefit of the assimilation is tested by comparison to a delayed cut-off version of SIM, in which the land surface is forced with more accurate atmospheric analyses, due to the availability of additional atmospheric observations after the near-real time data cut-off. However, comparing the near-real time and delayed cut-off SIM models revealed that the main difference between them is a dry bias in the near-real time precipitation forcing, which resulted in a dry bias in the root-zone soil moisture and associated surface moisture flux forecasts. While assimilating the ASCAT data did reduce the root-zone soil moisture dry bias (by nearly 50%), this was more likely due to a bias within the SEKF, than due to the assimilation having accurately responded to the precipitation errors. Several improvements to the assimilation are identified to address this, and a bias-aware strategy is suggested for explicitly correcting the model bias. However, in this experiment the moisture added by the SEKF was quickly lost from the model surface due to the enhanced surface fluxes (particularly drainage) induced by the wetter soil moisture states. Consequently, by the end of each winter, during which frozen conditions prevent the ASCAT data from being assimilated, the model land surface had returned to its original (dry-biased) climate. This highlights that it would be more effective to address the precipitation bias directly, than to correct it by constraining the model soil moisture through data assimilation.

Global SWOT Data Assimilation of River Hydrodynamic Model; the Twin Simulation Test of CaMa-Flood

NASA Astrophysics Data System (ADS)

Ikeshima, D.; Yamazaki, D.; Kanae, S.

2016-12-01

CaMa-Flood is a global scale model for simulating hydrodynamics in large scale rivers. It can simulate river hydrodynamics such as river discharge, flooded area, water depth and so on by inputting water runoff derived from land surface model. Recently many improvements at parameters or terrestrial data are under process to enhance the reproducibility of true natural phenomena. However, there are still some errors between nature and simulated result due to uncertainties in each model. SWOT (Surface water and Ocean Topography) is a satellite, which is going to be launched in 2021, can measure open water surface elevation. SWOT observed data can be used to calibrate hydrodynamics model at river flow forecasting and is expected to improve model's accuracy. Combining observation data into model to calibrate is called data assimilation. In this research, we developed data-assimilated river flow simulation system in global scale, using CaMa-Flood as river hydrodynamics model and simulated SWOT as observation data. Generally at data assimilation, calibrating "model value" with "observation value" makes "assimilated value". However, the observed data of SWOT satellite will not be available until its launch in 2021. Instead, we simulated the SWOT observed data using CaMa-Flood. Putting "pure input" into CaMa-Flood produce "true water storage". Extracting actual daily swath of SWOT from "true water storage" made simulated observation. For "model value", we made "disturbed water storage" by putting "noise disturbed input" to CaMa-Flood. Since both "model value" and "observation value" are made by same model, we named this twin simulation. At twin simulation, simulated observation of "true water storage" is combined with "disturbed water storage" to make "assimilated value". As the data assimilation method, we used ensemble Kalman filter. If "assimilated value" is closer to "true water storage" than "disturbed water storage", the data assimilation can be marked effective. Also by changing the input disturbance of "disturbed water storage", acceptable rate of uncertainty at the input may be discussed.

A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods

NASA Astrophysics Data System (ADS)

Tang, Youhua; Pagowski, Mariusz; Chai, Tianfeng; Pan, Li; Lee, Pius; Baker, Barry; Kumar, Rajesh; Delle Monache, Luca; Tong, Daniel; Kim, Hyun-Cheol

2017-12-01

This study applies the Gridpoint Statistical Interpolation (GSI) 3D-Var assimilation tool originally developed by the National Centers for Environmental Prediction (NCEP), to improve surface PM2.5 predictions over the contiguous United States (CONUS) by assimilating aerosol optical depth (AOD) and surface PM2.5 in version 5.1 of the Community Multi-scale Air Quality (CMAQ) modeling system. An optimal interpolation (OI) method implemented earlier (Tang et al., 2015) for the CMAQ modeling system is also tested for the same period (July 2011) over the same CONUS. Both GSI and OI methods assimilate surface PM2.5 observations at 00:00, 06:00, 12:00 and 18:00 UTC, and MODIS AOD at 18:00 UTC. The assimilations of observations using both GSI and OI generally help reduce the prediction biases and improve correlation between model predictions and observations. In the GSI experiments, assimilation of surface PM2.5 (particle matter with diameter < 2.5 µm) leads to stronger increments in surface PM2.5 compared to its MODIS AOD assimilation at the 550 nm wavelength. In contrast, we find a stronger OI impact of the MODIS AOD on surface aerosols at 18:00 UTC compared to the surface PM2.5 OI method. GSI produces smoother result and yields overall better correlation coefficient and root mean squared error (RMSE). It should be noted that the 3D-Var and OI methods used here have several big differences besides the data assimilation schemes. For instance, the OI uses relatively big model uncertainties, which helps yield smaller mean biases, but sometimes causes the RMSE to increase. We also examine and discuss the sensitivity of the assimilation experiments' results to the AOD forward operators.

Identification and characterization of multiple rubisco activases in chemoautotrophic bacteria

PubMed Central

Tsai, Yi-Chin Candace; Lapina, Maria Claribel; Bhushan, Shashi; Mueller-Cajar, Oliver

2015-01-01

Ribulose-1,5-bisphosphate carboxylase/oxygenase (rubisco) is responsible for almost all biological CO2 assimilation, but forms inhibited complexes with its substrate ribulose-1,5-bisphosphate (RuBP) and other sugar phosphates. The distantly related AAA+ proteins rubisco activase and CbbX remodel inhibited rubisco complexes to effect inhibitor release in plants and α-proteobacteria, respectively. Here we characterize a third class of rubisco activase in the chemolithoautotroph Acidithiobacillus ferrooxidans. Two sets of isoforms of CbbQ and CbbO form hetero-oligomers that function as specific activases for two structurally diverse rubisco forms. Mutational analysis supports a model wherein the AAA+ protein CbbQ functions as motor and CbbO is a substrate adaptor that binds rubisco via a von Willebrand factor A domain. Understanding the mechanisms employed by nature to overcome rubisco's shortcomings will increase our toolbox for engineering photosynthetic carbon dioxide fixation. PMID:26567524

Quantifying substrate uptake by individual cells of marine bacterioplankton by catalyzed reporter deposition fluorescence in situ hybridization combined with microautoradiography.

PubMed

Sintes, Eva; Herndl, Gerhard J

2006-11-01

Catalyzed reporter deposition fluorescence in situ hybridization combined with microautoradiography (MICRO-CARD-FISH) is increasingly being used to obtain qualitative information on substrate uptake by individual members of specific prokaryotic communities. Here we evaluated the potential for using this approach quantitatively by relating the measured silver grain area around cells taking up (3)H-labeled leucine to bulk leucine uptake measurements. The increase in the silver grain area over time around leucine-assimilating cells of coastal bacterial assemblages was linear during 4 to 6 h of incubation. By establishing standardized conditions for specific activity levels and concomitantly performing uptake measurements with the bulk community, MICRO-CARD-FISH can be used quantitatively to determine uptake rates on a single-cell level. Therefore, this approach allows comparisons of single-cell activities for bacterial communities obtained from different sites or growing under different ecological conditions.

Quantifying Substrate Uptake by Individual Cells of Marine Bacterioplankton by Catalyzed Reporter Deposition Fluorescence In Situ Hybridization Combined with Microautoradiography▿

PubMed Central

Sintes, Eva; Herndl, Gerhard J.

2006-01-01

Catalyzed reporter deposition fluorescence in situ hybridization combined with microautoradiography (MICRO-CARD-FISH) is increasingly being used to obtain qualitative information on substrate uptake by individual members of specific prokaryotic communities. Here we evaluated the potential for using this approach quantitatively by relating the measured silver grain area around cells taking up 3H-labeled leucine to bulk leucine uptake measurements. The increase in the silver grain area over time around leucine-assimilating cells of coastal bacterial assemblages was linear during 4 to 6 h of incubation. By establishing standardized conditions for specific activity levels and concomitantly performing uptake measurements with the bulk community, MICRO-CARD-FISH can be used quantitatively to determine uptake rates on a single-cell level. Therefore, this approach allows comparisons of single-cell activities for bacterial communities obtained from different sites or growing under different ecological conditions. PMID:16950912

Utah State University Global Assimilation of Ionospheric Measurements Gauss-Markov Kalman filter model of the ionosphere: Model description and validation

NASA Astrophysics Data System (ADS)

Scherliess, L.; Schunk, R. W.; Sojka, J. J.; Thompson, D. C.; Zhu, L.

2006-11-01

The Utah State University Gauss-Markov Kalman Filter (GMKF) was developed as part of the Global Assimilation of Ionospheric Measurements (GAIM) program. The GMKF uses a physics-based model of the ionosphere and a Gauss-Markov Kalman filter as a basis for assimilating a diverse set of real-time (or near real-time) observations. The physics-based model is the Ionospheric Forecast Model (IFM), which accounts for five ion species and covers the E region, F region, and the topside from 90 to 1400 km altitude. Within the GMKF, the IFM derived ionospheric densities constitute a background density field on which perturbations are superimposed based on the available data and their errors. In the current configuration, the GMKF assimilates slant total electron content (TEC) from a variable number of global positioning satellite (GPS) ground sites, bottomside electron density (Ne) profiles from a variable number of ionosondes, in situ Ne from four Defense Meteorological Satellite Program (DMSP) satellites, and nighttime line-of-sight ultraviolet (UV) radiances measured by satellites. To test the GMKF for real-time operations and to validate its ionospheric density specifications, we have tested the model performance for a variety of geophysical conditions. During these model runs various combination of data types and data quantities were assimilated. To simulate real-time operations, the model ran continuously and automatically and produced three-dimensional global electron density distributions in 15 min increments. In this paper we will describe the Gauss-Markov Kalman filter model and present results of our validation study, with an emphasis on comparisons with independent observations.

The Los Alamos dynamic radiation environment assimilation model (DREAM) for space weather specification and forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reeves, Geoffrey D; Friedel, Reiner H W; Chen, Yue

2008-01-01

The Dynamic Radiation Environment Assimilation Model (DREAM) was developed at Los Alamos National Laboratory to assess, quantify, and predict the hazards from the natural space environment and the anthropogenic environment produced by high altitude nuclear explosions (HANE). DREAM was initially developed as a basic research activity to understand and predict the dynamics of the Earth's Van Allen radiation belts. It uses Kalman filter techniques to assimilate data from space environment instruments with a physics-based model of the radiation belts. DREAM can assimilate data from a variety of types of instruments and data with various levels of resolution and fidelity bymore » assigning appropriate uncertainties to the observations. Data from any spacecraft orbit can be assimilated but DREAM was designed to function with as few as two spacecraft inputs: one from geosynchronous orbit and one from GPS orbit. With those inputs, DREAM can be used to predict the environment at any satellite in any orbit whether space environment data are available in those orbits or not. Even with very limited data input and relatively simple physics models, DREAM specifies the space environment in the radiation belts to a high level of accuracy. DREAM has been extensively tested and evaluated as we transition from research to operations. We report here on one set of test results in which we predict the environment in a highly-elliptical polar orbit. We also discuss long-duration reanalysis for spacecraft design, using DREAM for real-time operations, and prospects for 1-week forecasts of the radiation belt environment.« less

Ontogenetic shifts in thermal tolerance, selected body temperature and thermal dependence of food assimilation and locomotor performance in a lacertid lizard, Eremias brenchleyi.

PubMed

Xu, Xue-Feng; Ji, Xiang

2006-01-01

We used Eremias brenchleyi as a model animal to examine differences in thermal tolerance, selected body temperature, and the thermal dependence of food assimilation and locomotor performance between juvenile and adult lizards. Adults selected higher body temperatures (33.5 vs. 31.7 degrees C) and were able to tolerate a wider range of body temperatures (3.4-43.6 vs. 5.1-40.8 degrees C) than juveniles. Within the body temperature range of 26-38 degrees C, adults overall ate more than juveniles, and food passage rate was faster in adults than juveniles. Apparent digestive coefficient (ADC) and assimilation efficiency (AE) varied among temperature treatments but no clear temperature associated patterns could be discerned for these two variables. At each test temperature ADC and AE were both higher in adults than in juveniles. Sprint speed increased with increase in body temperature at lower body temperatures, but decreased at higher body temperatures. At each test temperature adults ran faster than did juveniles, and the range of body temperatures where lizards maintained 90% of maximum speed differed between adults (27-34 degrees C) and juveniles (29-37 degrees C). Optimal temperatures and thermal sensitivities differed between food assimilation and sprint speed. Our results not only show strong patterns of ontogenetic variation in thermal tolerance, selected body temperature and thermal dependence of food assimilation and locomotor performance in E. brenchleyi, but also add support for the multiple optima hypothesis for the thermal dependence of behavioral and physiological variables in reptiles.

Identification of Methanoculleus spp. as active methanogens during anoxic incubations of swine manure storage tank samples.

PubMed

Barret, Maialen; Gagnon, Nathalie; Kalmokoff, Martin L; Topp, Edward; Verastegui, Yris; Brooks, Stephen P J; Matias, Fernando; Neufeld, Josh D; Talbot, Guylaine

2013-01-01

Methane emissions represent a major environmental concern associated with manure management in the livestock industry. A more thorough understanding of how microbial communities function in manure storage tanks is a prerequisite for mitigating methane emissions. Identifying the microorganisms that are metabolically active is an important first step. Methanogenic archaea are major contributors to methanogenesis in stored swine manure, and we investigated active methanogenic populations by DNA stable isotope probing (DNA-SIP). Following a preincubation of manure samples under anoxic conditions to induce substrate starvation, [U-(13)C]acetate was added as a labeled substrate. Fingerprint analysis of density-fractionated DNA, using length-heterogeneity analysis of PCR-amplified mcrA genes (encoding the alpha subunit of methyl coenzyme M reductase), showed that the incorporation of (13)C into DNA was detectable at in situ acetate concentrations (~7 g/liter). Fingerprints of DNA retrieved from heavy fractions of the (13)C treatment were primarily enriched in a 483-bp amplicon and, to a lesser extent, in a 481-bp amplicon. Analyses based on clone libraries of the mcrA and 16S rRNA genes revealed that both of these heavy DNA amplicons corresponded to Methanoculleus spp. Our results demonstrate that uncultivated methanogenic archaea related to Methanoculleus spp. were major contributors to acetate-C assimilation during the anoxic incubation of swine manure storage tank samples. Carbon assimilation and dissimilation rate estimations suggested that Methanoculleus spp. were also major contributors to methane emissions and that the hydrogenotrophic pathway predominated during methanogenesis.

Rhodosporidium toruloides: a new platform organism for conversion of lignocellulose into terpene biofuels and bioproducts

DOE PAGES

Yaegashi, Junko; Kirby, James; Ito, Masakazu; ...

2017-10-23

Economical conversion of lignocellulosic biomass into biofuels and bioproducts is central to the establishment of a robust bioeconomy. This requires a conversion host that is able to both efficiently assimilate the major lignocellulose-derived carbon sources and divert their metabolites toward specific bioproducts. In this study, the carotenogenic yeast Rhodosporidium toruloides was examined for its ability to convert lignocellulose into two non-native sesquiterpenes with biofuel (bisabolene) and pharmaceutical (amorphadiene) applications. We found that R. toruloides can efficiently convert a mixture of glucose and xylose from hydrolyzed lignocellulose into these bioproducts, and unlike many conventional production hosts, its growth and productivity weremore » enhanced in lignocellulosic hydrolysates relative to purified substrates. This organism was demonstrated to have superior growth in corn stover hydrolysates prepared by two different pretreatment methods, one using a novel biocompatible ionic liquid (IL) choline α-ketoglutarate, which produced 261 mg/L of bisabolene at bench scale, and the other using an alkaline pretreatment, which produced 680 mg/L of bisabolene in a high-gravity fe d-batch bioreactor. Interestingly, R. toruloides was also observed to assimilate p-coumaric acid liberated from acylated grass lignin in the IL hydrolysate, a finding we verified with purified substrates. R. toruloides was also able to consume several additional compounds with aromatic motifs similar to lignin monomers, suggesting that this organism may have the metabolic potential to convert depolymerized lignin streams alongside lignocellulosic sugars. This study highlights the natural compatibility of R. toruloides with bioprocess conditions relevant to lignocellulosic biorefineries and demonstrates its ability to produce non-native terpenes.« less

Rhodosporidium toruloides: a new platform organism for conversion of lignocellulose into terpene biofuels and bioproducts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yaegashi, Junko; Kirby, James; Ito, Masakazu

Economical conversion of lignocellulosic biomass into biofuels and bioproducts is central to the establishment of a robust bioeconomy. This requires a conversion host that is able to both efficiently assimilate the major lignocellulose-derived carbon sources and divert their metabolites toward specific bioproducts. In this study, the carotenogenic yeast Rhodosporidium toruloides was examined for its ability to convert lignocellulose into two non-native sesquiterpenes with biofuel (bisabolene) and pharmaceutical (amorphadiene) applications. We found that R. toruloides can efficiently convert a mixture of glucose and xylose from hydrolyzed lignocellulose into these bioproducts, and unlike many conventional production hosts, its growth and productivity weremore » enhanced in lignocellulosic hydrolysates relative to purified substrates. This organism was demonstrated to have superior growth in corn stover hydrolysates prepared by two different pretreatment methods, one using a novel biocompatible ionic liquid (IL) choline α-ketoglutarate, which produced 261 mg/L of bisabolene at bench scale, and the other using an alkaline pretreatment, which produced 680 mg/L of bisabolene in a high-gravity fe d-batch bioreactor. Interestingly, R. toruloides was also observed to assimilate p-coumaric acid liberated from acylated grass lignin in the IL hydrolysate, a finding we verified with purified substrates. R. toruloides was also able to consume several additional compounds with aromatic motifs similar to lignin monomers, suggesting that this organism may have the metabolic potential to convert depolymerized lignin streams alongside lignocellulosic sugars. This study highlights the natural compatibility of R. toruloides with bioprocess conditions relevant to lignocellulosic biorefineries and demonstrates its ability to produce non-native terpenes.« less

Identification of Methanoculleus spp. as Active Methanogens during Anoxic Incubations of Swine Manure Storage Tank Samples

PubMed Central

Barret, Maialen; Gagnon, Nathalie; Kalmokoff, Martin L.; Topp, Edward; Verastegui, Yris; Brooks, Stephen P. J.; Matias, Fernando; Neufeld, Josh D.

2013-01-01

Methane emissions represent a major environmental concern associated with manure management in the livestock industry. A more thorough understanding of how microbial communities function in manure storage tanks is a prerequisite for mitigating methane emissions. Identifying the microorganisms that are metabolically active is an important first step. Methanogenic archaea are major contributors to methanogenesis in stored swine manure, and we investigated active methanogenic populations by DNA stable isotope probing (DNA-SIP). Following a preincubation of manure samples under anoxic conditions to induce substrate starvation, [U-13C]acetate was added as a labeled substrate. Fingerprint analysis of density-fractionated DNA, using length-heterogeneity analysis of PCR-amplified mcrA genes (encoding the alpha subunit of methyl coenzyme M reductase), showed that the incorporation of 13C into DNA was detectable at in situ acetate concentrations (∼7 g/liter). Fingerprints of DNA retrieved from heavy fractions of the 13C treatment were primarily enriched in a 483-bp amplicon and, to a lesser extent, in a 481-bp amplicon. Analyses based on clone libraries of the mcrA and 16S rRNA genes revealed that both of these heavy DNA amplicons corresponded to Methanoculleus spp. Our results demonstrate that uncultivated methanogenic archaea related to Methanoculleus spp. were major contributors to acetate-C assimilation during the anoxic incubation of swine manure storage tank samples. Carbon assimilation and dissimilation rate estimations suggested that Methanoculleus spp. were also major contributors to methane emissions and that the hydrogenotrophic pathway predominated during methanogenesis. PMID:23104405

Isolation and Characterization of Hydrocarbon-Degrading Yeast Strains from Petroleum Contaminated Industrial Wastewater

PubMed Central

Gargouri, Boutheina; Mhiri, Najla; Karray, Fatma; Aloui, Fathi; Sayadi, Sami

2015-01-01

Two yeast strains are enriched and isolated from industrial refinery wastewater. These strains were observed for their ability to utilize several classes of petroleum hydrocarbons substrates, such as n-alkanes and aromatic hydrocarbons as a sole carbon source. Phylogenetic analysis based on the D1/D2 variable domain and the ITS-region sequences indicated that strains HC1 and HC4 were members of the genera Candida and Trichosporon, respectively. The mechanism of hydrocarbon uptaking by yeast, Candida, and Trichosporon has been studied by means of the kinetic analysis of hydrocarbons-degrading yeasts growth and substrate assimilation. Biodegradation capacity and biomass quantity were daily measured during twelve days by gravimetric analysis and gas chromatography coupled with mass spectrometry techniques. Removal of n-alkanes indicated a strong ability of hydrocarbon biodegradation by the isolated yeast strains. These two strains grew on long-chain n-alkane, diesel oil, and crude oil but failed to grow on short-chain n-alkane and aromatic hydrocarbons. Growth measurement attributes of the isolates, using n-hexadecane, diesel oil, and crude oil as substrates, showed that strain HC1 had better degradation for hydrocarbon substrates than strain HC4. In conclusion, these yeast strains can be useful for the bioremediation process and decreasing petroleum pollution in wastewater contaminated with petroleum hydrocarbons. PMID:26339653

Isolation and Characterization of Hydrocarbon-Degrading Yeast Strains from Petroleum Contaminated Industrial Wastewater.

PubMed

Gargouri, Boutheina; Mhiri, Najla; Karray, Fatma; Aloui, Fathi; Sayadi, Sami

2015-01-01

Two yeast strains are enriched and isolated from industrial refinery wastewater. These strains were observed for their ability to utilize several classes of petroleum hydrocarbons substrates, such as n-alkanes and aromatic hydrocarbons as a sole carbon source. Phylogenetic analysis based on the D1/D2 variable domain and the ITS-region sequences indicated that strains HC1 and HC4 were members of the genera Candida and Trichosporon, respectively. The mechanism of hydrocarbon uptaking by yeast, Candida, and Trichosporon has been studied by means of the kinetic analysis of hydrocarbons-degrading yeasts growth and substrate assimilation. Biodegradation capacity and biomass quantity were daily measured during twelve days by gravimetric analysis and gas chromatography coupled with mass spectrometry techniques. Removal of n-alkanes indicated a strong ability of hydrocarbon biodegradation by the isolated yeast strains. These two strains grew on long-chain n-alkane, diesel oil, and crude oil but failed to grow on short-chain n-alkane and aromatic hydrocarbons. Growth measurement attributes of the isolates, using n-hexadecane, diesel oil, and crude oil as substrates, showed that strain HC1 had better degradation for hydrocarbon substrates than strain HC4. In conclusion, these yeast strains can be useful for the bioremediation process and decreasing petroleum pollution in wastewater contaminated with petroleum hydrocarbons.

Data assimilation and bathymetric inversion in a two-dimensional horizontal surf zone model

NASA Astrophysics Data System (ADS)

Wilson, G. W.; Ã-Zkan-Haller, H. T.; Holman, R. A.

2010-12-01

A methodology is described for assimilating observations in a steady state two-dimensional horizontal (2-DH) model of nearshore hydrodynamics (waves and currents), using an ensemble-based statistical estimator. In this application, we treat bathymetry as a model parameter, which is subject to a specified prior uncertainty. The statistical estimator uses state augmentation to produce posterior (inverse, updated) estimates of bathymetry, wave height, and currents, as well as their posterior uncertainties. A case study is presented, using data from a 2-D array of in situ sensors on a natural beach (Duck, NC). The prior bathymetry is obtained by interpolation from recent bathymetric surveys; however, the resulting prior circulation is not in agreement with measurements. After assimilating data (significant wave height and alongshore current), the accuracy of modeled fields is improved, and this is quantified by comparing with observations (both assimilated and unassimilated). Hence, for the present data, 2-DH bathymetric uncertainty is an important source of error in the model and can be quantified and corrected using data assimilation. Here the bathymetric uncertainty is ascribed to inadequate temporal sampling; bathymetric surveys were conducted on a daily basis, but bathymetric change occurred on hourly timescales during storms, such that hydrodynamic model skill was significantly degraded. Further tests are performed to analyze the model sensitivities used in the assimilation and to determine the influence of different observation types and sampling schemes.

Bioavailability of particle-associated silver, cadmium, and zinc to the estuarine amphipod Leptocheirus plumulosus through dietary ingestion

USGS Publications Warehouse

Schlekat, C.E.; Decho, Alan W.; Chandler, G.T.

2000-01-01

We conducted experiments to determine effects of particle type on assimilatory metal bioavailability to Leptocheirus plumulosus, an infaunal, estuarine amphipod that is commonly used in sediment toxicity tests. The following particles were used to represent natural food items encountered by this surface-deposit and suspension-feeding amphipod: bacterial exopolymeric sediment coatings, polymeric coatings made from Spartina alterniflora extract, amorphous iron oxide coatings, the diatom Phaeodactylum tricornutum, the chlorophyte Dunaliella tertiolecta, processed estuarine sediment, and fresh estuarine sediment. Bioavailability of the gamma-emitting radioisotopes 110mAg, 109Cd, and 65Zn was measured as the efficiency with which L. plumulosus assimilated metals from particles using pulse-chase methods. Ag and Cd assimilation efficiencies were highest from bacterial exopolymeric coatings. Zn assimilation efficiency exhibited considerable interexperimental variation; the highest Zn assimilation efficiencies were measured from phytoplankton and processed sediment. In general, Ag and Cd assimilation efficiencies from phytoplankton were low and not related to the proportion of metal associated with cell cytosol or cytoplasm, a phenomenon reported for other particle-ingesting invertebrates. Amphipod digestive processes explain differences in Ag and Cd assimilation efficiencies between exopolymeric coatings and phytoplankton. Results highlight the importance of labile polymeric organic carbon sediment coatings in dietary metals uptake by this benthic invertebrate, rather than recalcitrant organic carbon, mineralogical features such as iron oxides, or phytoplankton.

Evaluation of two momentum control variable schemes and their impact on the variational assimilation of radarwind data: Case study of a squall line

NASA Astrophysics Data System (ADS)

Li, Xin; Zeng, Mingjian; Wang, Yuan; Wang, Wenlan; Wu, Haiying; Mei, Haixia

2016-10-01

Different choices of control variables in variational assimilation can bring about different influences on the analyzed atmospheric state. Based on the WRF model's three-dimensional variational assimilation system, this study compares the behavior of two momentum control variable options—streamfunction velocity potential ( ψ-χ) and horizontal wind components ( U-V)—in radar wind data assimilation for a squall line case that occurred in Jiangsu Province on 24 August 2014. The wind increment from the single observation test shows that the ψ-χ control variable scheme produces negative increments in the neighborhood around the observation point because streamfunction and velocity potential preserve integrals of velocity. On the contrary, the U-V control variable scheme objectively reflects the information of the observation itself. Furthermore, radial velocity data from 17 Doppler radars in eastern China are assimilated. As compared to the impact of conventional observation, the assimilation of radar radial velocity based on the U-V control variable scheme significantly improves the mesoscale dynamic field in the initial condition. The enhanced low-level jet stream, water vapor convergence and low-level wind shear result in better squall line forecasting. However, the ψ-χ control variable scheme generates a discontinuous wind field and unrealistic convergence/divergence in the analyzed field, which lead to a degraded precipitation forecast.

Nitrogen assimilation in denitrifier Bacillus azotoformans LMG 9581T.

PubMed

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).

Implementation of a GPS-RO data processing system for the KIAPS-LETKF data assimilation system

NASA Astrophysics Data System (ADS)

Kwon, H.; Kang, J.-S.; Jo, Y.; Kang, J. H.

2014-11-01

The Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing a new global numerical weather prediction model and an advanced data assimilation system. As part of the KIAPS Package for Observation Processing (KPOP) system for data assimilation, preprocessing and quality control modules for bending angle measurements of global positioning system radio occultation (GPS-RO) data have been implemented and examined. GPS-RO data processing system is composed of several steps for checking observation locations, missing values, physical values for Earth radius of curvature, and geoid undulation. An observation-minus-background check is implemented by use of a one-dimensional observational bending angle operator and tangent point drift is also considered in the quality control process. We have tested GPS-RO observations utilized by the Korean Meteorological Administration (KMA) within KPOP, based on both the KMA global model and the National Center for Atmospheric Research (NCAR) Community Atmosphere Model-Spectral Element (CAM-SE) as a model background. Background fields from the CAM-SE model are incorporated for the preparation of assimilation experiments with the KIAPS-LETKF data assimilation system, which has been successfully implemented to a cubed-sphere model with fully unstructured quadrilateral meshes. As a result of data processing, the bending angle departure statistics between observation and background shows significant improvement. Also, the first experiment in assimilating GPS-RO bending angle resulting from KPOP within KIAPS-LETKF shows encouraging results.

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

NASA Technical Reports Server (NTRS)

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%.

Lactose-induced cell death of beta-galactosidase mutants in Kluyveromyces lactis.

PubMed

Lodi, Tiziana; Donnini, Claudia

2005-05-01

The Kluyveromyces lactis lac4 mutants, lacking the beta-galactosidase gene, cannot assimilate lactose, but grow normally on many other carbon sources. However, when these carbon sources and lactose were simultaneously present in the growth media, the mutants were unable to grow. The effect of lactose was cytotoxic since the addition of lactose to an exponentially-growing culture resulted in 90% loss of viability of the lac4 cells. An osmotic stabilizing agent prevented cells killing, supporting the hypothesis that the lactose toxicity could be mainly due to intracellular osmotic pressure. Deletion of the lactose permease gene, LAC12, abolished the inhibitory effect of lactose and allowed the cell to assimilate other carbon substrates. The lac4 strains gave rise, with unusually high frequency, to spontaneous mutants tolerant to lactose (lar1 mutation: lactose resistant). These mutants were unable to take up lactose. Indeed, lar1 mutation turned out to be allelic to LAC12. The high mutability of the LAC12 locus may be an advantage for survival of K. lactis whose main habitat is lactose-containing niches.

Efficient conversion of mannitol derived from brown seaweed to fructose for fermentation with a thraustochytrid.

PubMed

Tajima, Takahisa; Tomita, Kousuke; Miyahara, Hiroyuki; Watanabe, Kenshi; Aki, Tsunehiro; Okamura, Yoshiko; Matsumura, Yukihiko; Nakashimada, Yutaka; Kato, Junichi

2018-02-01

Macroalgae are a promising biomass feedstock for energy and valuable chemicals. Mannitol and alginate are the major carbohydrates found in the microalga Laminaria japonica (Konbu). To convert mannitol to fructose for its utilization as a carbon source in mannitol non-assimilating bacteria, a psychrophile-based simple biocatalyst (PSCat) was constructed using a psychrophile as a host by expressing mesophilic enzymes, including mannitol 2-dehydrogenase for mannitol oxidation, and NADH oxidase and alkyl hydroxyperoxide reductase for NAD + regeneration. PSCat was treated at 40 °C to inactivate the psychrophilic enzymes responsible for byproduct formation and to increase the membrane permeability of the substrate. PSCat efficiently converted mannitol to fructose with high conversion yield without additional input of NAD + . Konbu extract containing mannitol was converted to fructose with hydroperoxide scavenging, inhibiting the mannitol dehydrogenase activity. Auranthiochytrium sp. could grow well in the presence of fructose converted by PSCat. Thus, PSCat is a potential carbohydrate converter for mannitol non-assimilating microorganism. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Improving Weather Forecasts Through Reduced Precision Data Assimilation

NASA Astrophysics Data System (ADS)

Hatfield, Samuel; Düben, Peter; Palmer, Tim

2017-04-01

We present a new approach for improving the efficiency of data assimilation, by trading numerical precision for computational speed. Future supercomputers will allow a greater choice of precision, so that models can use a level of precision that is commensurate with the model uncertainty. Previous studies have already indicated that the quality of climate and weather forecasts is not significantly degraded when using a precision less than double precision [1,2], but so far these studies have not considered data assimilation. Data assimilation is inherently uncertain due to the use of relatively long assimilation windows, noisy observations and imperfect models. Thus, the larger rounding errors incurred from reducing precision may be within the tolerance of the system. Lower precision arithmetic is cheaper, and so by reducing precision in ensemble data assimilation, we can redistribute computational resources towards, for example, a larger ensemble size. Because larger ensembles provide a better estimate of the underlying distribution and are less reliant on covariance inflation and localisation, lowering precision could actually allow us to improve the accuracy of weather forecasts. We will present results on how lowering numerical precision affects the performance of an ensemble data assimilation system, consisting of the Lorenz '96 toy atmospheric model and the ensemble square root filter. We run the system at half precision (using an emulation tool), and compare the results with simulations at single and double precision. We estimate that half precision assimilation with a larger ensemble can reduce assimilation error by 30%, with respect to double precision assimilation with a smaller ensemble, for no extra computational cost. This results in around half a day extra of skillful weather forecasts, if the error-doubling characteristics of the Lorenz '96 model are mapped to those of the real atmosphere. Additionally, we investigate the sensitivity of these results to observational error and assimilation window length. Half precision hardware will become available very shortly, with the introduction of Nvidia's Pascal GPU architecture and the Intel Knights Mill coprocessor. We hope that the results presented here will encourage the uptake of this hardware. References [1] Peter D. Düben and T. N. Palmer, 2014: Benchmark Tests for Numerical Weather Forecasts on Inexact Hardware, Mon. Weather Rev., 142, 3809-3829 [2] Peter D. Düben, Hugh McNamara and T. N. Palmer, 2014: The use of imprecise processing to improve accuracy in weather & climate prediction, J. Comput. Phys., 271, 2-18

Observability of discretized partial differential equations

NASA Technical Reports Server (NTRS)

Cohn, Stephen E.; Dee, Dick P.

1988-01-01

It is shown that complete observability of the discrete model used to assimilate data from a linear partial differential equation (PDE) system is necessary and sufficient for asymptotic stability of the data assimilation process. The observability theory for discrete systems is reviewed and applied to obtain simple observability tests for discretized constant-coefficient PDEs. Examples are used to show how numerical dispersion can result in discrete dynamics with multiple eigenvalues, thereby detracting from observability.

Lay theory of race affects and moderates Asian Americans' responses toward American culture.

PubMed

No, Sun; Hong, Ying-yi; Liao, Hsin-Ya; Lee, Kyoungmi; Wood, Dustin; Chao, Melody Manchi

2008-10-01

People may hold different understandings of race that might affect how they respond to the culture of groups deemed to be racially distinct. The present research tests how this process is moderated by the minority individual's lay theory of race. An essentialist lay theory of race (i.e., that race reflects deep-seated, inalterable essence and is indicative of traits and ability) would orient racial minorities to rigidly adhere to their ethnic culture, whereas a social constructionist lay theory of race (i.e., that race is socially constructed, malleable, and arbitrary) would orient racial minorities to identify and cognitively assimilate toward the majority culture. To test these predictions, the authors conducted 4 studies with Asian American participants. The first 2 studies examine the effect of one's lay theory of race on perceived racial differences and identification with American culture. The last 2 studies tested the moderating effect of lay theory of race on identification and assimilation toward the majority American culture after this culture had been primed. The results generally supported the prediction that the social constructionist theory was associated with more perceived similarity between Asians and Americans and more consistent identification and assimilation toward American culture, compared with the essentialist theory.

Flexible digestion strategies and trace metal assimilation in marine bivalves

USGS Publications Warehouse

Decho, Alan W.; Luoma, Samuel N.

1996-01-01

Pulse-chase experiments show that two marine bivalves take optimal advantage of different types of particulate food by varying food retention time in a flexible two-phase digestive system. For example, carbon is efficiently assimilated from bacteria by subjecting nearly all the ingested bacteria to prolonged digestion. Prolonging digestion also enhances assimilation of metals, many of which are toxic in minute quantities if they are biologically available. Detritus-feeding aquatic organisms have always lived in environments naturally rich in particle-reactive metals. We suggest that avoiding excess assimilation of metals could be a factor in the evolution of digestion strategies. We tested that suggestion by studying digestion of particles containing different Cr concentrations. We show that bivalves are capable of modifying the digestive processing of food to reduce exposure to high, biologically available, Cr concentrations. The evolution of a mechanism in some species to avoid high concentrations of metals in food could influence how effects of modern metal pollution are manifested in marine ecosystems.

Seasonal-to-decadal predictability in the Nordic Seas and Arctic with the Norwegian Climate Prediction Model

NASA Astrophysics Data System (ADS)

Counillon, Francois; Kimmritz, Madlen; Keenlyside, Noel; Wang, Yiguo; Bethke, Ingo

2017-04-01

The Norwegian Climate Prediction Model combines the Norwegian Earth System Model and the Ensemble Kalman Filter data assimilation method. The prediction skills of different versions of the system (with 30 members) are tested in the Nordic Seas and the Arctic region. Comparing the hindcasts branched from a SST-only assimilation run with a free ensemble run of 30 members, we are able to dissociate the predictability rooted in the external forcing from the predictability harvest from SST derived initial conditions. The latter adds predictability in the North Atlantic subpolar gyre and the Nordic Seas regions and overall there is very little degradation or forecast drift. Combined assimilation of SST and T-S profiles further improves the prediction skill in the Nordic Seas and into the Arctic. These lead to multi-year predictability in the high-latitudes. Ongoing developments of strongly coupled assimilation (ocean and sea ice) of ice concentration in idealized twin experiment will be shown, as way to further enhance prediction skill in the Arctic.

Identity processing styles and the need for self-esteem in middle-aged and older adults.

PubMed

Sneed, J R; Whitbourne, S K

2001-01-01

This study was a test of the relationship between self-esteem and the identity processing styles of identity assimilation (i.e., maintaining consistent views of the self), accommodation (i.e., changing the self ), and a balance between consistency seeking and identity change. A community sample of 242 older adults ranging in age from forty to ninety-five (M = 63.31) completed measures of identity processing and self-esteem. Previous research has demonstrated that identity assimilation increases with age in order to maintain self-esteem in the domain of physical and cognitive functioning; this is referred to as the identity assimilation effect (IAE). Based on this research, a similar result was expected in the domain of personality. Although identity assimilation and balance predicted increases in self-esteem, and identity accommodation predicted decreases in self-esteem, as predicted, no interaction effects were observed. The results of this study suggest the IAE may be domain specific to physical and cognitive functioning.

Paleo Data Assimilation of Pseudo-Tree-Ring-Width Chronologies in a Climate Model

NASA Astrophysics Data System (ADS)

Fallah Hassanabadi, B.; Acevedo, W.; Reich, S.; Cubasch, U.

2016-12-01

Using the Time-Averaged Ensemble Kalman Filter (EnKF) and a forward model, we assimilate the pseudo Tree-Ring-Width (TRW) chronologies into an Atmospheric Global Circulation model. This study investigates several aspects of Paleo-Data Assimilation (PDA) within a perfect-model set-up: (i) we test the performance of several forward operators in the framework of a PDA-based climate reconstruction, (ii) compare the PDA-based simulations' skill against the free ensemble runs and (iii) inverstigate the skill of the "online" (with cycling) DA and the "off-line" (no-cycling) DA. In our experiments, the "online" (with cycling) PDA approach did not outperform the "off-line" (no-cycling) one, despite its considerable additional implementation complexity. On the other hand, it was observed that the error reduction achieved by assimilating a particular pseudo-TRW chronology is modulated by the strength of the yearly internal variability of the model at the chronology site. This result might help the dendrochronology community to optimize their sampling efforts.

Spatialized Application of Remotely Sensed Data Assimilation Methods for Farmland Drought Monitoring Using Two Different Crop Models

NASA Astrophysics Data System (ADS)

Silvestro, Paolo Cosmo; Casa, Raffaele; Pignatti, Stefano; Castaldi, Fabio; Yang, Hao; Guijun, Yang

2016-08-01

The aim of this work was to develop a tool to evaluate the effect of water stress on yield losses at the farmland and regional scale, by assimilating remotely sensed biophysical variables into crop growth models. Biophysical variables were retrieved from HJ1A, HJ1B and Landsat 8 images, using an algorithm based on the training of artificial neural networks on PROSAIL.For the assimilation, two crop models of differing degree of complexity were used: Aquacrop and SAFY. For Aquacrop, an optimization procedure to reduce the difference between the remotely sensed and simulated CC was developed. For the modified version of SAFY, the assimilation procedure was based on the Ensemble Kalman Filter.These procedures were tested in a spatialized application, by using data collected in the rural area of Yangling (Shaanxi Province) between 2013 and 2015Results were validated by utilizing yield data both from ground measurements and statistical survey.

A case study of GWE satellite data impact on GLA assimilation analyses of two ocean cyclones

NASA Technical Reports Server (NTRS)

Gallimore, R. G.; Johnson, D. R.

1986-01-01

The effects of the Global Weather Experiment (GWE) data obtained on January 18-20, 1979 on Goddard Laboratory for Atmospheres assimilation analyses of simultaneous cyclones in the western Pacific and Atlantic oceans are examined. The ability of satellite data within assimilation models to determine the baroclinic structures of developing extratropical cyclones is evaluated. The impact of the satellite data on the amplitude and phase of the temperature structure within the storm domain, potential energy, and baroclinic growth rate is studied. The GWE data are compared with Data Systems Test results. It is noted that it is necessary to characterize satellite effects on the baroclinic structure of cyclone waves which degrade numerical weather predictions of cyclogenesis.

Acidotolerant Bacteria and Fungi as a Sink of Methanol-Derived Carbon in a Deciduous Forest Soil

PubMed Central

Morawe, Mareen; Hoeke, Henrike; Wissenbach, Dirk K.; Lentendu, Guillaume; Wubet, Tesfaye; Kröber, Eileen; Kolb, Steffen

2017-01-01

Methanol is an abundant atmospheric volatile organic compound that is released from both living and decaying plant material. In forest and other aerated soils, methanol can be consumed by methanol-utilizing microorganisms that constitute a known terrestrial sink. However, the environmental factors that drive the biodiversity of such methanol-utilizers have been hardly resolved. Soil-derived isolates of methanol-utilizers can also often assimilate multicarbon compounds as alternative substrates. Here, we conducted a comparative DNA stable isotope probing experiment under methylotrophic (only [13C1]-methanol was supplemented) and combined substrate conditions ([12C1]-methanol and alternative multi-carbon [13Cu]-substrates were simultaneously supplemented) to (i) identify methanol-utilizing microorganisms of a deciduous forest soil (European beech dominated temperate forest in Germany), (ii) assess their substrate range in the soil environment, and (iii) evaluate their trophic links to other soil microorganisms. The applied multi-carbon substrates represented typical intermediates of organic matter degradation, such as acetate, plant-derived sugars (xylose and glucose), and a lignin-derived aromatic compound (vanillic acid). An experimentally induced pH shift was associated with substantial changes of the diversity of active methanol-utilizers suggesting that soil pH was a niche-defining factor of these microorganisms. The main bacterial methanol-utilizers were members of the Beijerinckiaceae (Bacteria) that played a central role in a detected methanol-based food web. A clear preference for methanol or multi-carbon substrates as carbon source of different Beijerinckiaceae-affiliated phylotypes was observed suggesting a restricted substrate range of the methylotrophic representatives. Apart from Bacteria, we also identified the yeasts Cryptococcus and Trichosporon as methanol-derived carbon-utilizing fungi suggesting that further research is needed to exclude or prove methylotrophy of these fungi. PMID:28790984

Sequential Bayesian Geostatistical Inversion and Evaluation of Combined Data Worth for Aquifer Characterization at the Hanford 300 Area

NASA Astrophysics Data System (ADS)

Murakami, H.; Chen, X.; Hahn, M. S.; Over, M. W.; Rockhold, M. L.; Vermeul, V.; Hammond, G. E.; Zachara, J. M.; Rubin, Y.

2010-12-01

Subsurface characterization for predicting groundwater flow and contaminant transport requires us to integrate large and diverse datasets in a consistent manner, and quantify the associated uncertainty. In this study, we sequentially assimilated multiple types of datasets for characterizing a three-dimensional heterogeneous hydraulic conductivity field at the Hanford 300 Area. The datasets included constant-rate injection tests, electromagnetic borehole flowmeter tests, lithology profile and tracer tests. We used the method of anchored distributions (MAD), which is a modular-structured Bayesian geostatistical inversion method. MAD has two major advantages over the other inversion methods. First, it can directly infer a joint distribution of parameters, which can be used as an input in stochastic simulations for prediction. In MAD, in addition to typical geostatistical structural parameters, the parameter vector includes multiple point values of the heterogeneous field, called anchors, which capture local trends and reduce uncertainty in the prediction. Second, MAD allows us to integrate the datasets sequentially in a Bayesian framework such that it updates the posterior distribution, as a new dataset is included. The sequential assimilation can decrease computational burden significantly. We applied MAD to assimilate different combinations of the datasets, and then compared the inversion results. For the injection and tracer test assimilation, we calculated temporal moments of pressure build-up and breakthrough curves, respectively, to reduce the data dimension. A massive parallel flow and transport code PFLOTRAN is used for simulating the tracer test. For comparison, we used different metrics based on the breakthrough curves not used in the inversion, such as mean arrival time, peak concentration and early arrival time. This comparison intends to yield the combined data worth, i.e. which combination of the datasets is the most effective for a certain metric, which will be useful for guiding the further characterization effort at the site and also the future characterization projects at the other sites.

Comparison of different filter methods for data assimilation in the unsaturated zone

NASA Astrophysics Data System (ADS)

Lange, Natascha; Berkhahn, Simon; Erdal, Daniel; Neuweiler, Insa

2016-04-01

The unsaturated zone is an important compartment, which plays a role for the division of terrestrial water fluxes into surface runoff, groundwater recharge and evapotranspiration. For data assimilation in coupled systems it is therefore important to have a good representation of the unsaturated zone in the model. Flow processes in the unsaturated zone have all the typical features of flow in porous media: Processes can have long memory and as observations are scarce, hydraulic model parameters cannot be determined easily. However, they are important for the quality of model predictions. On top of that, the established flow models are highly non-linear. For these reasons, the use of the popular Ensemble Kalman filter as a data assimilation method to estimate state and parameters in unsaturated zone models could be questioned. With respect to the long process memory in the subsurface, it has been suggested that iterative filters and smoothers may be more suitable for parameter estimation in unsaturated media. We test the performance of different iterative filters and smoothers for data assimilation with a focus on parameter updates in the unsaturated zone. In particular we compare the Iterative Ensemble Kalman Filter and Smoother as introduced by Bocquet and Sakov (2013) as well as the Confirming Ensemble Kalman Filter and the modified Restart Ensemble Kalman Filter proposed by Song et al. (2014) to the original Ensemble Kalman Filter (Evensen, 2009). This is done with simple test cases generated numerically. We consider also test examples with layering structure, as a layering structure is often found in natural soils. We assume that observations are water content, obtained from TDR probes or other observation methods sampling relatively small volumes. Particularly in larger data assimilation frameworks, a reasonable balance between computational effort and quality of results has to be found. Therefore, we compare computational costs of the different methods as well as the quality of open loop model predictions and the estimated parameters. Bocquet, M. and P. Sakov, 2013: Joint state and parameter estimation with an iterative ensemble Kalman smoother, Nonlinear Processes in Geophysics 20(5): 803-818. Evensen, G., 2009: Data assimilation: The ensemble Kalman filter. Springer Science & Business Media. Song, X.H., L.S. Shi, M. Ye, J.Z. Yang and I.M. Navon, 2014: Numerical comparison of iterative ensemble Kalman filters for unsaturated flow inverse modeling. Vadose Zone Journal 13(2), 10.2136/vzj2013.05.0083.

Enhanced Assimilation of InSAR Displacement and Well Data for Groundwater Monitoring

NASA Astrophysics Data System (ADS)

Abdullin, A.; Jonsson, S.

2016-12-01

Ground deformation related to aquifer exploitation can cause damage to buildings and infrastructure leading to major economic losses and sometimes even loss of human lives. Understanding reservoir behavior helps in assessing possible future ground movement and water depletion hazard of a region under study. We have developed an InSAR-based data assimilation framework for groundwater reservoirs that efficiently incorporates InSAR data for improved reservoir management and forecasts. InSAR displacement data are integrated with the groundwater modeling software MODFLOW using ensemble-based assimilation approaches. We have examined several Ensemble Methods for updating model parameters such as hydraulic conductivity and model variables like pressure head while simultaneously providing an estimate of the uncertainty. A realistic three-dimensional aquifer model was built to demonstrate the capability of the Ensemble Methods incorporating InSAR-derived displacement measurements. We find from these numerical tests that including both ground deformation and well water level data as observations improves the RMSE of the hydraulic conductivity estimate by up to 20% comparing to using only one type of observations. The RMSE estimation of this property after the final time step is similar for Ensemble Kalman Filter (EnKF), Ensemble Smoother (ES) and ES with multiple data assimilation (ES-MDA) methods. The results suggest that the high spatial and temporal resolution subsidence observations from InSAR are very helpful for accurately quantifying hydraulic parameters. We have tested the framework on several different examples and have found good performance in improving aquifer properties estimation, which should prove useful for groundwater management. Our ongoing work focuses on assimilating real InSAR-derived time series and hydraulic head data for calibrating and predicting aquifer properties of basin-wide groundwater systems.

Monte Carlo Bayesian Inference on a Statistical Model of Sub-gridcolumn Moisture Variability Using High-resolution Cloud Observations . Part II; Sensitivity Tests and Results

NASA Technical Reports Server (NTRS)

da Silva, Arlindo M.; Norris, Peter M.

2013-01-01

Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.

Assimilation of CryoSat-2 altimetry to a hydrodynamic model of the Brahmaputra river

NASA Astrophysics Data System (ADS)

Schneider, Raphael; Nygaard Godiksen, Peter; Ridler, Marc-Etienne; Madsen, Henrik; Bauer-Gottwein, Peter

2016-04-01

Remote sensing provides valuable data for parameterization and updating of hydrological models, for example water level measurements of inland water bodies from satellite radar altimeters. Satellite altimetry data from repeat-orbit missions such as Envisat, ERS or Jason has been used in many studies, also synthetic wide-swath altimetry data as expected from the SWOT mission. This study is one of the first hydrologic applications of altimetry data from a drifting orbit satellite mission, namely CryoSat-2. CryoSat-2 is equipped with the SIRAL instrument, a new type of radar altimeter similar to SRAL on Sentinel-3. CryoSat-2 SARIn level 2 data is used to improve a 1D hydrodynamic model of the Brahmaputra river basin in South Asia set up in the DHI MIKE 11 software. CryoSat-2 water levels were extracted over river masks derived from Landsat imagery. After discharge calibration, simulated water levels were fitted to the CryoSat-2 data along the Assam valley by adapting cross section shapes and datums. The resulting hydrodynamic model shows accurate spatio-temporal representation of water levels, which is a prerequisite for real-time model updating by assimilation of CryoSat-2 altimetry or multi-mission data in general. For this task, a data assimilation framework has been developed and linked with the MIKE 11 model. It is a flexible framework that can assimilate water level data which are arbitrarily distributed in time and space. Different types of error models, data assimilation methods, etc. can easily be used and tested. Furthermore, it is not only possible to update the water level of the hydrodynamic model, but also the states of the rainfall-runoff models providing the forcing of the hydrodynamic model. The setup has been used to assimilate CryoSat-2 observations over the Assam valley for the years 2010 to 2013. Different data assimilation methods and localizations were tested, together with different model error representations. Furthermore, the impact of different filtering and clustering methods and error descriptions of the CryoSat-2 observations was evaluated. Performance improvement in terms of discharge and water level forecast due to the assimilation of satellite altimetry data was then evaluated. The model forecasts were also compared to climatology and persistence forecasts. Using ensemble based filters, the evaluation was done not only based on performance criteria for the central forecast such as root-mean-square error (RMSE) and Nash-Sutcliffe model efficiency (NSE), but also based on sharpness, reliability and continuous ranked probability score (CRPS) of the ensemble of probabilistic forecasts.

Functional expression of a heterologous nickel-dependent, ATP-independent urease in Saccharomyces cerevisiae.

PubMed

Milne, N; Luttik, M A H; Cueto Rojas, H F; Wahl, A; van Maris, A J A; Pronk, J T; Daran, J M

2015-07-01

In microbial processes for production of proteins, biomass and nitrogen-containing commodity chemicals, ATP requirements for nitrogen assimilation affect product yields on the energy producing substrate. In Saccharomyces cerevisiae, a current host for heterologous protein production and potential platform for production of nitrogen-containing chemicals, uptake and assimilation of ammonium requires 1 ATP per incorporated NH3. Urea assimilation by this yeast is more energy efficient but still requires 0.5 ATP per NH3 produced. To decrease ATP costs for nitrogen assimilation, the S. cerevisiae gene encoding ATP-dependent urease (DUR1,2) was replaced by a Schizosaccharomyces pombe gene encoding ATP-independent urease (ure2), along with its accessory genes ureD, ureF and ureG. Since S. pombe ure2 is a Ni(2+)-dependent enzyme and Saccharomyces cerevisiae does not express native Ni(2+)-dependent enzymes, the S. pombe high-affinity nickel-transporter gene (nic1) was also expressed. Expression of the S. pombe genes into dur1,2Δ S. cerevisiae yielded an in vitro ATP-independent urease activity of 0.44±0.01 µmol min(-1) mg protein(-1) and restored growth on urea as sole nitrogen source. Functional expression of the Nic1 transporter was essential for growth on urea at low Ni(2+) concentrations. The maximum specific growth rates of the engineered strain on urea and ammonium were lower than those of a DUR1,2 reference strain. In glucose-limited chemostat cultures with urea as nitrogen source, the engineered strain exhibited an increased release of ammonia and reduced nitrogen content of the biomass. Our results indicate a new strategy for improving yeast-based production of nitrogen-containing chemicals and demonstrate that Ni(2+)-dependent enzymes can be functionally expressed in S. cerevisiae. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

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

PubMed Central

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 duration of grain filling. Conclusions Source–sink modelling holds the promise of accounting for plant–pathogen interactions over time under fluctuating climatic/lighting conditions in a robust way. PMID:22589327

A nudging-based data assimilation method: the Back and Forth Nudging (BFN) algorithm

NASA Astrophysics Data System (ADS)

Auroux, D.; Blum, J.

2008-03-01

This paper deals with a new data assimilation algorithm, called Back and Forth Nudging. The standard nudging technique consists in adding to the equations of the model a relaxation term that is supposed to force the observations to the model. The BFN algorithm consists in repeatedly performing forward and backward integrations of the model with relaxation (or nudging) terms, using opposite signs in the direct and inverse integrations, so as to make the backward evolution numerically stable. This algorithm has first been tested on the standard Lorenz model with discrete observations (perfect or noisy) and compared with the variational assimilation method. The same type of study has then been performed on the viscous Burgers equation, comparing again with the variational method and focusing on the time evolution of the reconstruction error, i.e. the difference between the reference trajectory and the identified one over a time period composed of an assimilation period followed by a prediction period. The possible use of the BFN algorithm as an initialization for the variational method has also been investigated. Finally the algorithm has been tested on a layered quasi-geostrophic model with sea-surface height observations. The behaviours of the two algorithms have been compared in the presence of perfect or noisy observations, and also for imperfect models. This has allowed us to reach a conclusion concerning the relative performances of the two algorithms.

Assimilation of global versus local data sets into a regional model of the Gulf Stream system. 1. Data effectiveness

NASA Astrophysics Data System (ADS)

Malanotte-Rizzoli, Paola; Young, Roberta E.

1995-12-01

The primary objective of this paper is to assess the relative effectiveness of data sets with different space coverage and time resolution when they are assimilated into an ocean circulation model. We focus on obtaining realistic numerical simulations of the Gulf Stream system typically of the order of 3-month duration by constructing a "synthetic" ocean simultaneously consistent with the model dynamics and the observations. The model used is the Semispectral Primitive Equation Model. The data sets are the "global" Optimal Thermal Interpolation Scheme (OTIS) 3 of the Fleet Numerical Oceanography Center providing temperature and salinity fields with global coverage and with bi-weekly frequency, and the localized measurements, mostly of current velocities, from the central and eastern array moorings of the Synoptic Ocean Prediction (SYNOP) program, with daily frequency but with a very small spatial coverage. We use a suboptimal assimilation technique ("nudging"). Even though this technique has already been used in idealized data assimilation studies, to our knowledge this is the first study in which the effectiveness of nudging is tested by assimilating real observations of the interior temperature and salinity fields. This is also the first work in which a systematic assimilation is carried out of the localized, high-quality SYNOP data sets in numerical experiments longer than 1-2 weeks, that is, not aimed to forecasting. We assimilate (1) the global OTIS 3 alone, (2) the local SYNOP observations alone, and (3) both OTIS 3 and SYNOP observations. We assess the success of the assimilations with quantitative measures of performance, both on the global and local scale. The results can be summarized as follows. The intermittent assimilation of the global OTIS 3 is necessary to keep the model "on track" over 3-month simulations on the global scale. As OTIS 3 is assimilated at every model grid point, a "gentle" weight must be prescribed to it so as not to overconstrain the model. However, in these assimilations the predicted velocity fields over the SYNOP arrays are greatly in error. The continuous assimilation of the localized SYNOP data sets with a strong weight is necessary to obtain local realistic evolutions. Then assimilation of velocity measurements alone recovers the density structure over the array area. However, the spatial coverage of the SYNOP measurements is too small to constrain the model on the global scale. Thus the blending of both types of datasets is necessary in the assimilation as they constrain different time and space scales. Our choice of "gentle" nudging weight for the global OTIS 3 and "strong" weight for the local SYNOP data provides for realistic simulations of the Gulf Stream system, both globally and locally, on the 3- to 4-month-long timescale, the one governed by the Gulf Stream jet internal dynamics.

Multisource data assimilation in a Richards equation-based integrated hydrological model: a real-world application to an experimental hillslope

NASA Astrophysics Data System (ADS)

Camporese, M.; Botto, A.

2017-12-01

Data assimilation is becoming increasingly popular in hydrological and earth system modeling, as it allows for direct integration of multisource observation data in modeling predictions and uncertainty reduction. For this reason, data assimilation has been recently the focus of much attention also for integrated surface-subsurface hydrological models, whereby multiple terrestrial compartments (e.g., snow cover, surface water, groundwater) are solved simultaneously, in an attempt to tackle environmental problems in a holistic approach. Recent examples include the joint assimilation of water table, soil moisture, and river discharge measurements in catchment models of coupled surface-subsurface flow using the ensemble Kalman filter (EnKF). Although the EnKF has been specifically developed to deal with nonlinear models, integrated hydrological models based on the Richards equation still represent a challenge, due to strong nonlinearities that may significantly affect the filter performance. Thus, more studies are needed to investigate the capabilities of EnKF to correct the system state and identify parameters in cases where the unsaturated zone dynamics are dominant. Here, the model CATHY (CATchment HYdrology) is applied to reproduce the hydrological dynamics observed in an experimental hillslope, equipped with tensiometers, water content reflectometer probes, and tipping bucket flow gages to monitor the hillslope response to a series of artificial rainfall events. We assimilate pressure head, soil moisture, and subsurface outflow with EnKF in a number of assimilation scenarios and discuss the challenges, issues, and tradeoffs arising from the assimilation of multisource data in a real-world test case, with particular focus on the capability of DA to update the subsurface parameters.

Newtonian nudging for a Richards equation-based distributed hydrological model

NASA Astrophysics Data System (ADS)

Paniconi, Claudio; Marrocu, Marino; Putti, Mario; Verbunt, Mark

The objective of data assimilation is to provide physically consistent estimates of spatially distributed environmental variables. In this study a relatively simple data assimilation method has been implemented in a relatively complex hydrological model. The data assimilation technique is Newtonian relaxation or nudging, in which model variables are driven towards observations by a forcing term added to the model equations. The forcing term is proportional to the difference between simulation and observation (relaxation component) and contains four-dimensional weighting functions that can incorporate prior knowledge about the spatial and temporal variability and characteristic scales of the state variable(s) being assimilated. The numerical model couples a three-dimensional finite element Richards equation solver for variably saturated porous media and a finite difference diffusion wave approximation based on digital elevation data for surface water dynamics. We describe the implementation of the data assimilation algorithm for the coupled model and report on the numerical and hydrological performance of the resulting assimilation scheme. Nudging is shown to be successful in improving the hydrological simulation results, and it introduces little computational cost, in terms of CPU and other numerical aspects of the model's behavior, in some cases even improving numerical performance compared to model runs without nudging. We also examine the sensitivity of the model to nudging term parameters including the spatio-temporal influence coefficients in the weighting functions. Overall the nudging algorithm is quite flexible, for instance in dealing with concurrent observation datasets, gridded or scattered data, and different state variables, and the implementation presented here can be readily extended to any of these features not already incorporated. Moreover the nudging code and tests can serve as a basis for implementation of more sophisticated data assimilation techniques in a Richards equation-based hydrological model.

Assimilation of GPM GMI Rainfall Product with WRF GSI

NASA Technical Reports Server (NTRS)

Li, Xuanli; Mecikalski, John; Zavodsky, Bradley

2015-01-01

The Global Precipitation Measurement (GPM) is an international mission to provide next-generation observations of rain and snow worldwide. The GPM built on Tropical Rainfall Measuring Mission (TRMM) legacy, while the core observatory will extend the observations to higher latitudes. The GPM observations can help advance our understanding of precipitation microphysics and storm structures. Launched on February 27th, 2014, the GPM core observatory is carrying advanced instruments that can be used to quantify when, where, and how much it rains or snows around the world. Therefore, the use of GPM data in numerical modeling work is a new area and will have a broad impact in both research and operational communities. The goal of this research is to examine the methodology of assimilation of the GPM retrieved products. The data assimilation system used in this study is the community Gridpoint Statistical Interpolation (GSI) system for the Weather Research and Forecasting (WRF) model developed by the Development Testbed Center (DTC). The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this research explores regional assimilation of the GPM products with case studies. Our presentation will highlight our recent effort on the assimilation of the GPM product 2AGPROFGMI, the retrieved Microwave Imager (GMI) rainfall rate data for initializing a real convective storm. WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to other GPM products. Further details of the methodology of data assimilation, preliminary result and test on the impact of GPM data and the influence on precipitation forecast will be presented at the conference.

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

Discharge data assimilation in a distributed hydrologic model for flood forecasting purposes

NASA Astrophysics Data System (ADS)

Ercolani, G.; Castelli, F.

2017-12-01

Flood early warning systems benefit from accurate river flow forecasts, and data assimilation may improve their reliability. However, the actual enhancement that can be obtained in the operational practice should be investigated in detail and quantified. In this work we assess the benefits that the simultaneous assimilation of discharge observations at multiple locations can bring to flow forecasting through a distributed hydrologic model. The distributed model, MOBIDIC, is part of the operational flood forecasting chain of Tuscany Region in Central Italy. The assimilation system adopts a mixed variational-Monte Carlo approach to update efficiently initial river flow, soil moisture, and a parameter related to runoff production. The evaluation of the system is based on numerous hindcast experiments of real events. The events are characterized by significant rainfall that resulted in both high and relatively low flow in the river network. The area of study is the main basin of Tuscany Region, i.e. Arno river basin, which extends over about 8300 km2 and whose mean annual precipitation is around 800 mm. Arno's mainstream, with its nearly 240 km length, passes through major Tuscan cities, as Florence and Pisa, that are vulnerable to floods (e.g. flood of November 1966). The assimilation tests follow the usage of the model in the forecasting chain, employing the operational resolution in both space and time (500 m and 15 minutes respectively) and releasing new flow forecasts every 6 hours. The assimilation strategy is evaluated in respect to open loop simulations, i.e. runs that do not exploit discharge observations through data assimilation. We compare hydrographs in their entirety, as well as classical performance indexes, as error on peak flow and Nash-Sutcliffe efficiency. The dependence of performances on lead time and location is assessed. Results indicate that the operational forecasting chain can benefit from the developed assimilation system, although with a significant variability due to the specific characteristics of any single event, and with downstream locations more sensitive to observations than upstream sites.

Implementation of a GPS-RO data processing system for the KIAPS-LETKF data assimilation system

NASA Astrophysics Data System (ADS)

Kwon, H.; Kang, J.-S.; Jo, Y.; Kang, J. H.

2015-03-01

The Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing a new global numerical weather prediction model and an advanced data assimilation system. As part of the KIAPS package for observation processing (KPOP) system for data assimilation, preprocessing, and quality control modules for bending-angle measurements of global positioning system radio occultation (GPS-RO) data have been implemented and examined. The GPS-RO data processing system is composed of several steps for checking observation locations, missing values, physical values for Earth radius of curvature, and geoid undulation. An observation-minus-background check is implemented by use of a one-dimensional observational bending-angle operator, and tangent point drift is also considered in the quality control process. We have tested GPS-RO observations utilized by the Korean Meteorological Administration (KMA) within KPOP, based on both the KMA global model and the National Center for Atmospheric Research Community Atmosphere Model with Spectral Element dynamical core (CAM-SE) as a model background. Background fields from the CAM-SE model are incorporated for the preparation of assimilation experiments with the KIAPS local ensemble transform Kalman filter (LETKF) data assimilation system, which has been successfully implemented to a cubed-sphere model with unstructured quadrilateral meshes. As a result of data processing, the bending-angle departure statistics between observation and background show significant improvement. Also, the first experiment in assimilating GPS-RO bending angle from KPOP within KIAPS-LETKF shows encouraging results.

A statistical data assimilation method for seasonal streamflow forecasting to optimize hydropower reservoir management in data-scarce regions

NASA Astrophysics Data System (ADS)

Arsenault, R.; Mai, J.; Latraverse, M.; Tolson, B.

2017-12-01

Probabilistic ensemble forecasts generated by the ensemble streamflow prediction (ESP) methodology are subject to biases due to errors in the hydrological model's initial states. In day-to-day operations, hydrologists must compensate for discrepancies between observed and simulated states such as streamflow. However, in data-scarce regions, little to no information is available to guide the streamflow assimilation process. The manual assimilation process can then lead to more uncertainty due to the numerous options available to the forecaster. Furthermore, the model's mass balance may be compromised and could affect future forecasts. In this study we propose a data-driven approach in which specific variables that may be adjusted during assimilation are defined. The underlying principle was to identify key variables that would be the most appropriate to modify during streamflow assimilation depending on the initial conditions such as the time period of the assimilation, the snow water equivalent of the snowpack and meteorological conditions. The variables to adjust were determined by performing an automatic variational data assimilation on individual (or combinations of) model state variables and meteorological forcing. The assimilation aimed to simultaneously optimize: (1) the error between the observed and simulated streamflow at the timepoint where the forecasts starts and (2) the bias between medium to long-term observed and simulated flows, which were simulated by running the model with the observed meteorological data on a hindcast period. The optimal variables were then classified according to the initial conditions at the time period where the forecast is initiated. The proposed method was evaluated by measuring the average electricity generation of a hydropower complex in Québec, Canada driven by this method. A test-bed which simulates the real-world assimilation, forecasting, water release optimization and decision-making of a hydropower cascade was developed to assess the performance of each individual process in the reservoir management chain. Here the proposed method was compared to the PF algorithm while keeping all other elements intact. Preliminary results are encouraging in terms of power generation and robustness for the proposed approach.

Information flow in an atmospheric model and data assimilation

NASA Astrophysics Data System (ADS)

Yoon, Young-noh

2011-12-01

Weather forecasting consists of two processes, model integration and analysis (data assimilation). During the model integration, the state estimate produced by the analysis evolves to the next cycle time according to the atmospheric model to become the background estimate. The analysis then produces a new state estimate by combining the background state estimate with new observations, and the cycle repeats. In an ensemble Kalman filter, the probability distribution of the state estimate is represented by an ensemble of sample states, and the covariance matrix is calculated using the ensemble of sample states. We perform numerical experiments on toy atmospheric models introduced by Lorenz in 2005 to study the information flow in an atmospheric model in conjunction with ensemble Kalman filtering for data assimilation. This dissertation consists of two parts. The first part of this dissertation is about the propagation of information and the use of localization in ensemble Kalman filtering. If we can perform data assimilation locally by considering the observations and the state variables only near each grid point, then we can reduce the number of ensemble members necessary to cover the probability distribution of the state estimate, reducing the computational cost for the data assimilation and the model integration. Several localized versions of the ensemble Kalman filter have been proposed. Although tests applying such schemes have proven them to be extremely promising, a full basic understanding of the rationale and limitations of localization is currently lacking. We address these issues and elucidate the role played by chaotic wave dynamics in the propagation of information and the resulting impact on forecasts. The second part of this dissertation is about ensemble regional data assimilation using joint states. Assuming that we have a global model and a regional model of higher accuracy defined in a subregion inside the global region, we propose a data assimilation scheme that produces the analyses for the global and the regional model simultaneously, considering forecast information from both models. We show that our new data assimilation scheme produces better results both in the subregion and the global region than the data assimilation scheme that produces the analyses for the global and the regional model separately.

High-Resolution Assimilation of GRACE Terrestrial Water Storage Observations to Represent Local-Scale Water Table Depths

NASA Astrophysics Data System (ADS)

Stampoulis, D.; Reager, J. T., II; David, C. H.; Famiglietti, J. S.; Andreadis, K.

2017-12-01

Despite the numerous advances in hydrologic modeling and improvements in Land Surface Models, an accurate representation of the water table depth (WTD) still does not exist. Data assimilation of observations of the joint NASA and DLR mission, Gravity Recovery and Climate Experiment (GRACE) leads to statistically significant improvements in the accuracy of hydrologic models, ultimately resulting in more reliable estimates of water storage. However, the usually shallow groundwater compartment of the models presents a problem with GRACE assimilation techniques, as these satellite observations account for much deeper aquifers. To improve the accuracy of groundwater estimates and allow the representation of the WTD at fine spatial scales we implemented a novel approach that enables a large-scale data integration system to assimilate GRACE data. This was achieved by augmenting the Variable Infiltration Capacity (VIC) hydrologic model, which is the core component of the Regional Hydrologic Extremes Assessment System (RHEAS), a high-resolution modeling framework developed at the Jet Propulsion Laboratory (JPL) for hydrologic modeling and data assimilation. The model has insufficient subsurface characterization and therefore, to reproduce groundwater variability not only in shallow depths but also in deep aquifers, as well as to allow GRACE assimilation, a fourth soil layer of varying depth ( 1000 meters) was added in VIC as the bottom layer. To initialize a water table in the model we used gridded global WTD data at 1 km resolution which were spatially aggregated to match the model's resolution. Simulations were then performed to test the augmented model's ability to capture seasonal and inter-annual trends of groundwater. The 4-layer version of VIC was run with and without assimilating GRACE Total Water Storage anomalies (TWSA) over the Central Valley in California. This is the first-ever assimilation of GRACE TWSA for the determination of realistic water table depths, at fine scales that are required for local water management. In addition, Open Loop and GRACE-assimilation simulations of water table depth were compared to in-situ data over the state of California, derived from observation wells operated/maintained by the U.S. Geological Service.

Preliminary Results from an Assimilation of Saharan Dust Using TOMS Radiances and the GOCART Model

NASA Technical Reports Server (NTRS)

Weaver, C. J.; daSilva, Arlindo; Ginoux, Paul; Torres, Omar; Einaudi, Franco (Technical Monitor)

2000-01-01

At NASA Goddard we are developing a global aerosol data assimilation system that combines advances in remote sensing and modeling of atmospheric aerosols. The goal is to provide high resolution, 3-D aerosol distributions to the research community. Our first step is to develop a simple assimilation system for Saharan mineral aerosol. The Goddard Chemistry and Aerosol Radiation model (GOCART) provides accurate 3-D mineral aerosol size distributions. Surface mobilization, wet and dry deposition, convective and long-range transport are all driven by assimilated fields from the Goddard Earth Observing System Data Assimilation System, GEOS-DAS. Our version of GOCART transports sizes from .08-10 microns and only simulates Saharan dust. We draw the assimilation to two observables in this study: the TOMS aerosol index (Al) which is directly related to the ratio of the 340 and 380 radiances and the 380 radiance alone. The forward model that simulates the observables requires the aerosol optical thickness, the single scattering albedo and the height of the aerosol layer from the GOCART fields. The forward model also requires a refractive index for the dust. We test three index values to see which best fits the TOMS observables. These are 1) for Saharan dust reported by Patterson, 2) for a mixture of Saharan dust and a highly reflective material (sea salt or sulfate) and 3) for pure illite. The assimilation works best assuming either pure illite or the dust mixture. Our assimilation cycle first determines values of the aerosol index (Al) and the radiance at 380 nm based on the GOCART aerosol fields. Differences between the observed and GOCART model calculated Al and 380 nm radiance are first analyzed horizontally using the Physical-space Statistical Analysis System (PSAS). A quasi-Newton iteration is then performed to produce analyzed 3D aerosol fields according to parameterized background and observation error covariances. We only assimilate observations into the the GOCART model over regions of Africa and the Atlantic where mineral aerosols are dominant and carbonaceous aerosols are minimal.

Assimilation of attenuated data from X-band network radars using ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Cheng, Jing

To use reflectivity data from X-band radars for quantitative precipitation estimation and storm-scale data assimilation, the effect of attenuation must be properly accounted for. Traditional approaches try to make correction to the attenuated reflectivity first before using the data. An alternative, theoretically more attractive approach builds the attenuation effect into the reflectivity observation operator of a data assimilation system, such as an ensemble Kalman filter (EnKF), allowing direct assimilation of the attenuated reflectivity and taking advantage of microphysical state estimation using EnKF methods for a potentially more accurate solution. This study first tests the approach for the CASA (Center for Collaborative Adaptive Sensing of the Atmosphere) X-band radar network configuration through observing system simulation experiments (OSSE) for a quasi-linear convective system (QLCS) that has more significant attenuation than isolated storms. To avoid the problem of potentially giving too much weight to fully attenuated reflectivity, an analytical, echo-intensity-dependent model for the observation error (AEM) is developed and is found to improve the performance of the filter. By building the attenuation into the forward observation operator and combining it with the application of AEM, the assimilation of attenuated CASA observations is able to produce a reasonably accurate analysis of the QLCS inside CASA radar network coverage. Compared with foregoing assimilation of radar data with weak radar reflectivity or assimilating only radial velocity data, our method can suppress the growth of spurious echoes while obtaining a more accurate analysis in the terms of root-mean-square (RMS) error. Sensitivity experiments are designed to examine the effectiveness of AEM by introducing multiple sources of observation errors into the simulated observations. The performance of such an approach in the presence of resolution-induced model error is also evaluated and good results are obtained. The same EnKF framework with attenuation correction is used to test different possible configurations of 2 hypothetical radars added to the existing network of 4 CASA radars through OSSEs. Though plans to expand the CASA radar network did not materialize, such experiments can provide guidance in the site selection of future X-band or other short-wavelength radar networks, as well as examining the benefit of X-band radar networks that consist of a much larger number of radars. Two QLCSs with different propagation speeds are generated and serve as the truth for our OSSEs. Assimilation and forecast results are compared among the OSSEs, assimilating only X-band or short-wavelength radar data. Overall, radar networks with larger downstream spatial coverage tend to provide overall the best analyses and 1-hour forecasts. The best analyses and forecasts of convective scale structure, however, are obtained when Dual- or Multi-Doppler coverage is preferred, even at the expense of minor loss in spatial coverage. Built-in attenuation correction is then applied, for the first time, to a real case (the 24 May 2011 tornadic storm near Chickasha, Oklahoma), using data from the X-band CASA radars. The attenuation correction procedure is found to be very effective---the analyses obtained using attenuated data are better than those obtained using pre-corrected data when all the values of reflectivity observations are assimilated. The effectiveness of the procedure is further examined by comparing the deterministic and ensemble forecasts started from the analysis of each experiment. The deterministic forecast experiment results indicate that assimilating un-corrected observations directly actually retains some information that might be lost in the pre-corrected CASA observations by forecasting a longer-lasting trailing line, similar to that observed in WSR-88D data. In the ensemble forecasts, assimilating un-corrected observations directly, using our attenuation-correcting EnKF, results in a forecast with a more intense tornado track than the experiment that assimilates all values of pre-corrected CASA data. This work is the first to assimilate attenuated observations from a radar network in OSSEs, as well as the first attempt to directly assimilate real, uncorrected CASA data into a numerical weather prediction (NWP) model using EnKF.

New Developments in the Data Assimilation Research Testbed

NASA Astrophysics Data System (ADS)

Hoar, T. J.; Anderson, J. L.; Raeder, K.; Karspeck, A. R.; Romine, G.; Liu, H.; Collins, N.

2011-12-01

NCAR's Data Assimilation Research Testbed (DART) is a community facility that provides ensemble data assimilation tools for geophysical applications. DART works with an expanding set of models and a wide range of conventional and novel observations, and provides a variety of assimilation algorithms and diagnostic tools. The Kodiak release of DART became available in July 2011 and includes more than 20 major feature enhancements, support for 24 models, support for (at least) 14 observation formats, expanded documentation and diagnostic tools, and 12 new utilities. A few examples of research projects that demonstrate the effectiveness and flexibility of the DART are described. The Community Atmosphere Model (CAM) and DART assimilated all the observations that were used in the NCEP/NCAR Reanalysis to produce a global, 6-hourly, 80-member ensemble reanalysis for 1998 through the present. The dataset is ideal for research applications that would benefit from an ensemble of equally-likely atmospheric states that are consistent with observations. Individual ensemble members may be used as a "data atmosphere" in any Community Earth System Model (CESM) experiment. The CESM interfaces for the Parallel Ocean Program (POP) and the Community Land Model (CLM) also support multiple instances, allowing data assimilation experiments exploiting unique atmospheric forcing for each POP or CLM model instance. A multi-year DART ocean assimilation has been completed and provides valuable insight into the successes and challenges of oceanic data assimilation. The DART/CLM research focuses on snow cover fraction and snow depth. The Weather Research and Forecasting (WRF) model was used with DART to perform a real-time CONUS domain mesoscale ensemble analysis with continuous cycling for 47 days. A member was selected once daily for high-resolution convective forecasts supporting a test phase of the Deep Convective Clouds and Chemistry experiment and the Storm Prediction Center spring experiment. The impacts of Moderate Resolution Imaging Spectroradiometer (MODIS) infrared and Advanced Microwave Scanning Radiometer (AMSR) microwave total precipitable water (TPW) observations on analyses and forecasts of tropical cyclone Sinlaku (2008) are investigated by performing assimilations with a 45km resolution WRF model over the Western Pacific domain for 8-14 Septmber, 2008. Particular emphasis is on the performance of the assimilation algorithms in the hurricane core and the impact of novel observations in the hurricane core.

From LIMS to OMPS-LP: limb ozone observations for future reanalyses

NASA Astrophysics Data System (ADS)

Wargan, K.; Kramarova, N. A.; Remsberg, E. E.; Coy, L.; Harvey, L.; Livesey, N. J.; Pawson, S.

2017-12-01

High vertical resolution and accuracy of ozone data from satellite-borne limb sounders have made them an invaluable tool in scientific studies of the middle and upper atmosphere. However, it was not until recently that these measurements were successfully incorporated in atmospheric reanalyses: of the major multidecadal reanalyses only ECMWF's ERA-Interim/ERA5 and NASA's MERRA-2 use limb ozone data. Validation and comparison studies have demonstrated that the addition of observations from the Microwave Limb Sounder (MLS) on EOS Aura greatly improved the quality of ozone fields in MERRA-2 making these assimilated data sets useful for scientific research. In this presentation, we will show the results of test experiments assimilating retrieved ozone from the Limb Infrared Monitor of the Stratosphere (LIMS, 1978/1979) and Ozone Mapping Profiler Suite Limb Profiler (OMPS-LP, 2012 to present). Our approach builds on the established assimilation methodology used for MLS in MERRA-2 and, in the case of OMPS-LP, extends the excellent record of MLS ozone assimilation into the post-EOS era in Earth observations. We will show case studies, discuss comparisons of the new experiments with MERRA-2, strategies for bias correction and the potential for combined assimilation of multiple limb ozone data types in future reanalyses for studies of multidecadal stratospheric ozone changes including trends.

Improved Land Use and Leaf Area Index Enhances WRF-3DVAR Satellite Radiance Assimilation: A Case Study Focusing on Rainfall Simulation in the Shule River Basin during July 2013

NASA Astrophysics Data System (ADS)

Yang, Junhua; Ji, Zhenming; Chen, Deliang; Kang, Shichang; Fu, Congshen; Duan, Keqin; Shen, Miaogen

2018-06-01

The application of satellite radiance assimilation can improve the simulation of precipitation by numerical weather prediction models. However, substantial quantities of satellite data, especially those derived from low-level (surface-sensitive) channels, are rejected for use because of the difficulty in realistically modeling land surface emissivity and energy budgets. Here, we used an improved land use and leaf area index (LAI) dataset in the WRF-3DVAR assimilation system to explore the benefit of using improved quality of land surface information to improve rainfall simulation for the Shule River Basin in the northeastern Tibetan Plateau as a case study. The results for July 2013 show that, for low-level channels (e.g., channel 3), the underestimation of brightness temperature in the original simulation was largely removed by more realistic land surface information. In addition, more satellite data could be utilized in the assimilation because the realistic land use and LAI data allowed more satellite radiance data to pass the deviation test and get used by the assimilation, which resulted in improved initial driving fields and better simulation in terms of temperature, relative humidity, vertical convection, and cumulative precipitation.

Satellite Data Assimilation within KIAPS-LETKF system

NASA Astrophysics Data System (ADS)

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.

Beyond English Proficiency: Rethinking Immigrant Integration

PubMed Central

Akresh, Ilana Redstone; Massey, Douglas S.; Frank, Reanne

2014-01-01

We develop and test a conceptual model of English language acquisition and the strength of the latter in predicting social and cultural assimilation. We present evidence that the path to English proficiency begins with exposure to English in the home country and on prior U.S. trips. English proficiency, then, has direct links to the intermediate migration outcomes of occupational status in the U.S., the amount of time in the U.S. since the most recent trip, and the co-ethnic residential context in the U.S. In turn, pre-migration characteristics and the intermediate characteristics work in tandem with English proficiency to determine social assimilation in the U.S., while cultural assimilation is primarily determined by pre-migration habits. A shift in focus to English use is desirable in studies of immigrant integration. PMID:24576636

Assimilation, Distribution, and Root Exudation of 14C by Ponderosa Pine Seedlings under Induced Water Stress 1

PubMed Central

Reid, C. P. Patrick

1974-01-01

The effect of specific levels of induced water stress on the root exudation of 14C from 9-month-old and 12-month-old ponderosa pine (Pinus ponderosa Laws.) seedlings was examined. Polyethylene glycol (PEG-4000) was used to decrease root solution water potentials by 0, −1.9, −2.6, −5.5, −9.6 and −11.9 bars in either aerated 0.25X Hoagland's nutrient solution or aerated distilled water. Assimilation of 14CO2 by plants under stress and subsequent translocation of 14C label to the roots were both inhibited by a decrease in substrate water potential. Six days after 14CO2 introduction essentially no 14C was detected in the roots of plants maintained at solution potentials of −5.5 bars or below. In subsequent studies 14CO2 was introduced 4 days prior to induction of stress. This allowed sufficient time for distribution of 14C label throughout the root system. Root exudation of 14C-labeled sugars, amino acids, and organic acids from plants in nutrient solution showed an increase from 0 to −1.9 bars, a decline from −1.9 to about −5.5 bars, and then an increase again from −5.5 to −11.9 bars. As substrate potential decreased, sugars as a percentage of total exudate increased, organic acids decreased and amino acids showed a slight decrease. Marked changes in percentages occurred between 0 and −2.6 bars. The exudation of sugars, amino acids, and organic acids from plants in distilled water showed similar trends in response to water stress as those in nutrient solution, but the quantity of total 14C exuded was greater. Images PMID:16658835

The complex leaves of the monkey's comb (Amphilophium crucigerum, Bignoniaceae): a climbing strategy without glue.

PubMed

Seidelmann, Katrin; Melzer, Björn; Speck, Thomas

2012-11-01

Monkey's comb (Amphilophium crucigerum) is a widely spread neotropical leaf climber that develops attachment pads for anchorage. A single complex leaf of the species comprises a basal pair of foliate, assimilating leaflets and apical, attaching leaflet tendrils. This study aims to analyze these leaves and their ontogenetic development for a better understanding of the attachment process, the form-structure-function relationships involved, and the overall maturation of the leaves. Thorough morphometrical, morphological, and anatomical analyses incorporated high-resolution microscopy, various staining techniques, SEM, and photographic recordings over the entire ontogenetic course of leaf development. The foliate, assimilating leaflets and the anchorage of the more apical leaflet tendrils acted independently of each other. Attachment was achieved by coiling of the leaflet tendrils and/or development of attachment pads at the tendril apices that grow opportunistically into gaps and fissures of the substrate. In contact zones with the substrate, the cells of the pads differentiate into a vessel element-like tissue. During the entire attachment process of the plant, no glue was excreted. The complex leaves of monkey's comb are highly differentiated organs with specialized leaf parts whose functions-photosynthesis or attachment-work independently of each other. The function of attachment includes coiling and maturation process of the leaflet tendrils and the formation of attachment pads, resulting in a biomechanically sound and persistent anchorage of the plant without the need of glue excretion. This kind of glue-less attachment is not only of interest in the framework of analyzing the functional variety of attachment structures evolved in climbing plants, but also for the development of innovative biomimetic attachment structures for manifold technical applications.

The performance of immigrants in the Norwegian labor market.

PubMed

Hayfron, J E

1998-01-01

"This paper tests the assimilation hypothesis with Norwegian data. Using both cross-section and cohort analyses, the results show that the 1970-1979 immigrant cohort experienced an earnings growth of about 11% between 1980 and 1990, when their earnings profile was compared to that of natives. This is lower than the 19% assimilation rate predicted by the cross-section method. On the contrary, the results reveal a rapid earnings divergence across cohorts, and between the 1960-1969 cohort and natives." excerpt

Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Xingyuan; Murakami, Haruko; Hahn, Melanie S.

2012-06-01

Tracer testing under natural or forced gradient flow holds the potential to provide useful information for characterizing subsurface properties, through monitoring, modeling and interpretation of the tracer plume migration in an aquifer. Non-reactive tracer experiments were conducted at the Hanford 300 Area, along with constant-rate injection tests and electromagnetic borehole flowmeter (EBF) profiling. A Bayesian data assimilation technique, the method of anchored distributions (MAD) [Rubin et al., 2010], was applied to assimilate the experimental tracer test data with the other types of data and to infer the three-dimensional heterogeneous structure of the hydraulic conductivity in the saturated zone of themore » Hanford formation. In this study, the Bayesian prior information on the underlying random hydraulic conductivity field was obtained from previous field characterization efforts using the constant-rate injection tests and the EBF data. The posterior distribution of the conductivity field was obtained by further conditioning the field on the temporal moments of tracer breakthrough curves at various observation wells. MAD was implemented with the massively-parallel three-dimensional flow and transport code PFLOTRAN to cope with the highly transient flow boundary conditions at the site and to meet the computational demands of MAD. A synthetic study proved that the proposed method could effectively invert tracer test data to capture the essential spatial heterogeneity of the three-dimensional hydraulic conductivity field. Application of MAD to actual field data shows that the hydrogeological model, when conditioned on the tracer test data, can reproduce the tracer transport behavior better than the field characterized without the tracer test data. This study successfully demonstrates that MAD can sequentially assimilate multi-scale multi-type field data through a consistent Bayesian framework.« less

Development of the WRF-CO2 4D-Var assimilation system v1.0

NASA Astrophysics Data System (ADS)

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.

Identifying organism involved in new and regenerated production using TAG-SIP

NASA Astrophysics Data System (ADS)

Morando, M.; Capone, D. G.

2016-02-01

The coupling of stable isotope probing (SIP) with high throughput sequencing (TAG-SIP), allows examination of DNA from individual taxa for the incorporation of a specific isotopically labeled substrate, facilitating an in-depth investigation of the activity and functional diversity of in situ microbial communities. This approach was applied to the monthly San Pedro Ocean Time-series (SPOT), during April of 2014 in order to characterize the organisms involved in new and regenerated production by investigating the assimilation of 15N-NO3-, 15N-NH4+, and 15N-urea at several light depths throughout the euphotic zone. Overall, very little variation was seen between the DNA banding patterns and density of each discrete OTU compared over multiple control treatments, i.e. unlabeled substrate was added to each control and so any disparity between the DNA banding of these OTU replicates reflects methodological variation. The lack of disparity found here further demonstrates TAG-SIP's high precision, accuracy, and more importantly validates the TAG-SIP's reproducibility in both gradient formation and DNA sedimentation with respect to density. The mean density of these discrete control OTU DNA bands (n=7) were then compared to those of their isotopically treated equivalent OTU after a 24h incubation in order to accurately assess and identify significant shifts in DNA density. Therefore we are confident that differences in density between control and treated sample DNA greater than the variation quantified among the controls themselves, is direct evidence of `heavy' isotope incorporation, i.e. metabolic activity and growth. Direct evidence of activity was found in a broad range of taxa, thought not every treatment yielded positive results. As expected the majority of the organisms identified as assimilators were found within the 15N-NH4+ treatments. Many taxa displayed evidence of uptake in one or more but not all treatments providing evidence on which taxa are metabolizing a broad range of substrates as opposed to those which are specializing. Overall, this dataset provides unique insight into which organisms contribute to new biomass formation and ultimately to carbon export and those that help maintain the population through the recycling of nutrients.

Extracellular enzymatic activities and physiological profiles of yeasts colonizing fruit trees.

PubMed

Molnárová, Jana; Vadkertiová, Renáta; Stratilová, Eva

2014-07-01

Yeasts form a significant and diverse part of the phyllosphere microbiota. Some yeasts that inhabit plants have been found to exhibit extracellular enzymatic activities. The aim of the present study was to investigate the ability of yeasts isolated from leaves, fruits, and blossoms of fruit trees cultivated in Southwest Slovakia to produce extracellular enzymes, and to discover whether the yeasts originating from these plant organs differ from each other in their physiological properties. In total, 92 strains belonging to 29 different species were tested for: extracellular protease, β-glucosidase, lipase, and polygalacturonase activities; fermentation abilities; the assimilation of xylose, saccharose and alcohols (methanol, ethanol, glycerol); and for growth in a medium with 33% glucose. The black yeast Aureobasidium pullulans showed the largest spectrum of activities of all the species tested. Almost 70% of the strains tested demonstrated some enzymatic activity, and more than 90% utilized one of the carbon compounds tested. Intraspecies variations were found for the species of the genera Cryptococcus and Pseudozyma. Interspecies differences of strains exhibiting some enzymatic activities and utilizing alcohols were also noted. The largest proportion of the yeasts exhibited β-glucosidase activity and assimilated alcohols independently of their origin. The highest number of strains positive for all activities tested was found among the yeasts associated with leaves. Yeasts isolated from blossoms assimilated saccharose and D-xylose the most frequently of all the yeasts tested. The majority of the fruit-inhabiting yeasts grew in the medium with higher osmotic pressure. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Iron deficiency affects nitrogen metabolism in cucumber (Cucumis sativus L.) plants

PubMed Central

2012-01-01

Background Nitrogen is a principal limiting nutrient in plant growth and development. Among factors that may limit NO3- assimilation, Fe potentially plays a crucial role being a metal cofactor of enzymes of the reductive assimilatory pathway. Very few information is available about the changes of nitrogen metabolism occurring under Fe deficiency in Strategy I plants. The aim of this work was to study how cucumber (Cucumis sativus L.) plants modify their nitrogen metabolism when grown under iron deficiency. Results The activity of enzymes involved in the reductive assimilation of nitrate and the reactions that produce the substrates for the ammonium assimilation both at root and at leaf levels in Fe-deficient cucumber plants were investigated. Under Fe deficiency, only nitrate reductase (EC 1.7.1.1) activity decreased both at the root and leaf level, whilst for glutamine synthetase (EC 6.3.1.2) and glutamate synthase (EC 1.4.1.14) an increase was found. Accordingly, the transcript analysis for these enzymes showed the same behaviour except for root nitrate reductase which increased. Furthermore, it was found that amino acid concentration greatly decreased in Fe-deficient roots, whilst it increased in the corresponding leaves. Moreover, amino acids increased in the xylem sap of Fe-deficient plants. Conclusions The data obtained in this work provided new insights on the responses of plants to Fe deficiency, suggesting that this nutritional disorder differentially affected N metabolism in root and in leaf. Indeed under Fe deficiency, roots respond more efficiently, sustaining the whole plant by furnishing metabolites (i.e. aa, organic acids) to the leaves. PMID:23057967

On the resilience of nitrogen assimilation by intact roots under starvation, as revealed by isotopic and metabolomic techniques.

PubMed

Bathellier, Camille; Tcherkez, Guillaume; Mauve, Caroline; Bligny, Richard; Gout, Elizabeth; Ghashghaie, Jaleh

2009-09-01

The response of root metabolism to variations in carbon source availability is critical for whole-plant nitrogen (N) assimilation and growth. However, the effect of changes in the carbohydrate input to intact roots is currently not well understood and, for example, both smaller and larger values of root:shoot ratios or root N uptake have been observed so far under elevated CO(2). In addition, previous studies on sugar starvation mainly focused on senescent or excised organs while an increasing body of data suggests that intact roots may behave differently with, for example, little protein remobilization. Here, we investigated the carbon and nitrogen primary metabolism in intact roots of French bean (Phaseolus vulgaris L.) plants maintained under continuous darkness for 4 days. We combined natural isotopic (15)N/(14)N measurements, metabolomic and (13)C-labeling data and show that intact roots continued nitrate assimilation to glutamate for at least 3 days while the respiration rate decreased. The activity of the tricarboxylic acid cycle diminished so that glutamate synthesis was sustained by the anaplerotic phosphoenolpyruvate carboxylase fixation. Presumably, the pentose phosphate pathway contributed to provide reducing power for nitrate reduction. All the biosynthetic metabolic fluxes were nevertheless down-regulated and, consequently, the concentration of all amino acids decreased. This is the case of asparagine, strongly suggesting that, as opposed to excised root tips, protein remobilization in intact roots remained very low for 3 days in spite of the restriction of respiratory substrates. Copyright (c) 2009 John Wiley & Sons, Ltd.

Constraining 3-PG with a new δ13C submodel: a test using the δ13C of tree rings.

PubMed

Wei, Liang; Marshall, John D; Link, Timothy E; Kavanagh, Kathleen L; DU, Enhao; Pangle, Robert E; Gag, Peter J; Ubierna, Nerea

2014-01-01

A semi-mechanistic forest growth model, 3-PG (Physiological Principles Predicting Growth), was extended to calculate δ(13)C in tree rings. The δ(13)C estimates were based on the model's existing description of carbon assimilation and canopy conductance. The model was tested in two ~80-year-old natural stands of Abies grandis (grand fir) in northern Idaho. We used as many independent measurements as possible to parameterize the model. Measured parameters included quantum yield, specific leaf area, soil water content and litterfall rate. Predictions were compared with measurements of transpiration by sap flux, stem biomass, tree diameter growth, leaf area index and δ(13)C. Sensitivity analysis showed that the model's predictions of δ(13)C were sensitive to key parameters controlling carbon assimilation and canopy conductance, which would have allowed it to fail had the model been parameterized or programmed incorrectly. Instead, the simulated δ(13)C of tree rings was no different from measurements (P > 0.05). The δ(13)C submodel provides a convenient means of constraining parameter space and avoiding model artefacts. This δ(13)C test may be applied to any forest growth model that includes realistic simulations of carbon assimilation and transpiration. © 2013 John Wiley & Sons Ltd.

Impact of CYGNSS Data on Tropical Cyclone Analyses and Forecasts in a Regional OSSE Framework

NASA Astrophysics Data System (ADS)

Annane, B.; McNoldy, B. D.; Leidner, S. M.; Atlas, R. M.; Hoffman, R.; Majumdar, S.

2016-12-01

The Cyclone Global Navigation Satellite System, or CYGNSS, is a planned constellation of micro-satellites that will utilize reflected Global Positioning System (GPS) satellite signals to retrieve ocean surface wind speed along the satellites' ground tracks. The orbits are designed so that there is excellent coverage of the tropics and subtropics, resulting in more thorough spatial sampling and improved sampling intervals over tropical cyclones than is possible with current spaceborne scatterometer and passive microwave sensor platforms. Furthermore, CYGNSS will be able to retrieve winds under all precipitating conditions, and over a large range of wind speeds.A regional Observing System Simulation Experiment (OSSE) framework was developed at NOAA/AOML and University of Miami that features a high-resolution regional nature run (27-km regional domain with 9/3/1 km storm-following nests; Nolan et al., 2013) embedded within a lower-resolution global nature run . Simulated observations are generated by sampling from the nature run and are provided to a data assimilation scheme, which produces analyses for a high-resolution regional forecast model, the 2014 operational Hurricane-WRF model. For data assimilation, NOAA's GSI and EnKF systems are used. Analyses are performed on the parent domain at 9-km resolution. The forecast model uses a single storm-following 3-km resolution nest. Synthetic CYGNSS wind speed data have also been created, and the impacts of the assimilation of these data on the forecasts of tropical cyclone track and intensity will be discussed.In addition to the choice of assimilation scheme, we have also examined a number of other factors/parameters that effect the impact of simulated CYGNSS observations, including frequency of data assimilation cycling (e.g., hourly, 3-hourly and 6-hourly) and the assimilation of scalar versus vector synthetic CYGNSS winds.We have found sensitivity to all of the factors tested and will summarize the methods used for testing as well as results. Generally, we have found that more frequent cycling is better than less; and flow-dependent background error covariances (e.g., EnKF) are better than static or climatological assumptions about the background error covariance.

A multi-data stream assimilation framework for the assessment of volcanic unrest

NASA Astrophysics Data System (ADS)

Gregg, Patricia M.; Pettijohn, J. Cory

2016-01-01

Active volcanoes pose a constant risk to populations living in their vicinity. Significant effort has been spent to increase monitoring and data collection campaigns to mitigate potential volcano disasters. To utilize these datasets to their fullest extent, a new generation of model-data fusion techniques is required that combine multiple, disparate observations of volcanic activity with cutting-edge modeling techniques to provide efficient assessment of volcanic unrest. The purpose of this paper is to develop a data assimilation framework for volcano applications. Specifically, the Ensemble Kalman Filter (EnKF) is adapted to assimilate GPS and InSAR data into viscoelastic, time-forward, finite element models of an evolving magma system to provide model forecasts and error estimations. Since the goal of this investigation is to provide a methodological framework, our efforts are focused on theoretical development and synthetic tests to illustrate the effectiveness of the EnKF and its applicability in physical volcanology. The synthetic tests provide two critical results: (1) a proof of concept for using the EnKF for multi dataset assimilation in investigations of volcanic activity; and (2) the comparison of spatially limited, but temporally dense, GPS data with temporally limited InSAR observations for evaluating magma chamber dynamics during periods of volcanic unrest. Results indicate that the temporally dense information provided by GPS observations results in faster convergence and more accurate model predictions. However, most importantly, the synthetic tests illustrate that the EnKF is able to swiftly respond to data updates by changing the model forecast trajectory to match incoming observations. The synthetic results demonstrate a great potential for utilizing the EnKF model-data fusion method to assess volcanic unrest and provide model forecasts. The development of these new techniques provides: (1) a framework for future applications of rapid data assimilation and model development during volcanic crises; (2) a method for hind-casting to investigate previous volcanic eruptions, including potential eruption triggering mechanisms and precursors; and (3) an approach for optimizing survey designs for future data collection campaigns at active volcanic systems.

Detecting Non-Gaussian and Lognormal Characteristics of Temperature and Water Vapor Mixing Ratio

NASA Astrophysics Data System (ADS)

Kliewer, A.; Fletcher, S. J.; Jones, A. S.; Forsythe, J. M.

2017-12-01

Many operational data assimilation and retrieval systems assume that the errors and variables come from a Gaussian distribution. This study builds upon previous results that shows that positive definite variables, specifically water vapor mixing ratio and temperature, can follow a non-Gaussian distribution and moreover a lognormal distribution. Previously, statistical testing procedures which included the Jarque-Bera test, the Shapiro-Wilk test, the Chi-squared goodness-of-fit test, and a composite test which incorporated the results of the former tests were employed to determine locations and time spans where atmospheric variables assume a non-Gaussian distribution. These tests are now investigated in a "sliding window" fashion in order to extend the testing procedure to near real-time. The analyzed 1-degree resolution data comes from the National Oceanic and Atmospheric Administration (NOAA) Global Forecast System (GFS) six hour forecast from the 0Z analysis. These results indicate the necessity of a Data Assimilation (DA) system to be able to properly use the lognormally-distributed variables in an appropriate Bayesian analysis that does not assume the variables are Gaussian.

Can plant phloem properties affect the link between ecosystem assimilation and respiration?

NASA Astrophysics Data System (ADS)

Mencuccini, M.; Hölttä, T.; Sevanto, S.; Nikinmaa, E.

2012-04-01

Phloem transport of carbohydrates in plants under field conditions is currently not well understood. This is largely the result of the lack of techniques suitable for measuring phloem physiological properties continuously under field conditions. This lack of knowledge is currently hampering our efforts to link ecosystem-level processes of carbon fixation, allocation and use, especially belowground. On theoretical grounds, the properties of the transport pathway from canopy to roots must be important in affecting the link between carbon assimilation and respiration, but it is unclear whether their effect is partially or entirely masked by processes occurring in other parts of the ecosystem. One can also predict the characteristic time scales over which these effects should occur and, as consequence, predict whether the transfer of turgor and osmotic signals from the site of carbon assimilation to the sites of carbon use are likely to control respiration. We will present two sources of evidence suggesting that the properties of the phloem transport system may affect processes that are dependent on the supply of carbon substrate, such as root or soil respiration. Firstly, we will summarize the results of a literature survey on soil and ecosystem respiration where the speed of transfer of photosynthetic sugars from the plant canopy to the soil surface was determined. Estimates of the transfer speed could be grouped according to whether the study employed isotopic or canopy soil flux-based techniques. These two groups provided very different estimates of transfer times likely because transport of sucrose molecules, and pressure-concentration waves, in phloem differed. Secondly, we will argue that simultaneous measurements of bark and xylem diameters provide a novel tool to determine the continuous variations of phloem turgor in vivo in the field. We will present a model that interprets these changes in xylem and live bark diameters and present data testing the model predictions for mature trees in the field. At the diurnal scale, the calculated phloem turgor signal related to patterns of photosynthetic activity and inferred phloem loading. At the seasonal scale, phloem turgor showed rapid changes during two droughts and after two rainfall events consistent with physiological predictions of phloem transport. Daily cumulative totals of calculated phloem osmotic concentrations were strongly related to daily cumulative totals of canopy photosynthesis. We propose that this method has potential for continuous field monitoring of tree phloem function.

Improving precipitation forecast with hybrid 3DVar and time-lagged ensembles in a heavy rainfall event

NASA Astrophysics Data System (ADS)

Wang, Yuanbing; Min, Jinzhong; Chen, Yaodeng; Huang, Xiang-Yu; Zeng, Mingjian; Li, Xin

2017-01-01

This study evaluates the performance of three-dimensional variational (3DVar) and a hybrid data assimilation system using time-lagged ensembles in a heavy rainfall event. The time-lagged ensembles are constructed by sampling from a moving time window of 3 h along a model trajectory, which is economical and easy to implement. The proposed hybrid data assimilation system introduces flow-dependent error covariance derived from time-lagged ensemble into variational cost function without significantly increasing computational cost. Single observation tests are performed to document characteristic of the hybrid system. The sensitivity of precipitation forecasts to ensemble covariance weight and localization scale is investigated. Additionally, the TLEn-Var is evaluated and compared to the ETKF(ensemble transformed Kalman filter)-based hybrid assimilation within a continuously cycling framework, through which new hybrid analyses are produced every 3 h over 10 days. The 24 h accumulated precipitation, moisture, wind are analyzed between 3DVar and the hybrid assimilation using time-lagged ensembles. Results show that model states and precipitation forecast skill are improved by the hybrid assimilation using time-lagged ensembles compared with 3DVar. Simulation of the precipitable water and structure of the wind are also improved. Cyclonic wind increments are generated near the rainfall center, leading to an improved precipitation forecast. This study indicates that the hybrid data assimilation using time-lagged ensembles seems like a viable alternative or supplement in the complex models for some weather service agencies that have limited computing resources to conduct large size of ensembles.

Assimilation of SMOS Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

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.

Assimilation of SMOS Retrievals in the Land Information System

PubMed Central

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

2018-01-01

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 cm3 cm−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. PMID:29367795

Evaluation of Bogus Vortex Techniques with Four-Dimensional Variational Data Assimilation

NASA Technical Reports Server (NTRS)

Pu, Zhao-Xia; Braun, Scott A.

2000-01-01

The effectiveness of techniques for creating "bogus" vortices in numerical simulations of hurricanes is examined by using the Penn State/NCAR nonhydrostatic mesoscale model (MM5) and its adjoint system. A series of four-dimensional variational data assimilation (4-D VAR) experiments is conducted to generate an initial vortex for Hurricane Georges (1998) in the Atlantic Ocean by assimilating bogus sea-level pressure and surface wind information into the mesoscale numerical model. Several different strategies are tested for improving the vortex representation. The initial vortices produced by the 4-D VAR technique are able to reproduce many of the structural features of mature hurricanes. The vortices also result in significant improvements to the hurricane forecasts in terms of both intensity and track. In particular, with assimilation of only bogus sea-level pressure information, the response in the wind field is contained largely within the divergent component, with strong convergence leading to strong upward motion near the center. Although the intensity of the initial vortex seems to be well represented, a dramatic spin down of the storm occurs within the first 6 h of the forecast. With assimilation of bogus surface wind data only, an expected dominance of the rotational component of the wind field is generated, but the minimum pressure is adjusted inadequately compared to the actual hurricane minimum pressure. Only when both the bogus surface pressure and wind information are assimilated together does the model produce a vortex that represents the actual intensity of the hurricane and results in significant improvements to forecasts of both hurricane intensity and track.

High-Resolution Regional Reanalysis in China: Evaluation of 1 Year Period Experiments

NASA Astrophysics Data System (ADS)

Zhang, Qi; Pan, Yinong; Wang, Shuyu; Xu, Jianjun; Tang, Jianping

2017-10-01

Globally, reanalysis data sets are widely used in assessing climate change, validating numerical models, and understanding the interactions between the components of a climate system. However, due to the relatively coarse resolution, most global reanalysis data sets are not suitable to apply at the local and regional scales directly with the inadequate descriptions of mesoscale systems and climatic extreme incidents such as mesoscale convective systems, squall lines, tropical cyclones, regional droughts, and heat waves. In this study, by using a data assimilation system of Gridpoint Statistical Interpolation, and a mesoscale atmospheric model of Weather Research and Forecast model, we build a regional reanalysis system. This is preliminary and the first experimental attempt to construct a high-resolution reanalysis for China main land. Four regional test bed data sets are generated for year 2013 via three widely used methods (classical dynamical downscaling, spectral nudging, and data assimilation) and a hybrid method with data assimilation coupled with spectral nudging. Temperature at 2 m, precipitation, and upper level atmospheric variables are evaluated by comparing against observations for one-year-long tests. It can be concluded that the regional reanalysis with assimilation and nudging methods can better produce the atmospheric variables from surface to upper levels, and regional extreme events such as heat waves, than the classical dynamical downscaling. Compared to the ERA-Interim global reanalysis, the hybrid nudging method performs slightly better in reproducing upper level temperature and low-level moisture over China, which improves regional reanalysis data quality.

Screen-level data assimilation of observations and pseudo-observations in COSMO-I2

NASA Astrophysics Data System (ADS)

Milelli, Dr.; Turco, Dr.; Cane, Dr.; Oberto, Dr.; Pelosini, Dr.

2009-09-01

The COSMO model has been developed by the COnsortium for Small-scale MOdelling, an over-national consortium coordinating the cooperation of the national and regional weather services of Germany, Italy, Switzerland, Greece, Poland and Romania. Its operational version does not make use of the 2m temperature, since it has been shown to have potentially adverse effects on the stability of the planetary boundary layer. Moreover, in pre-operational tests, it has been showed to degrade the low-tropospheric thermal structure of the model. The 2m temperature is at the moment only used in the soil moisture analysis, where it has the potential to modify the surface fluxes and to improve the prediction of 2m temperature during the forecast time. Despite these facts, there is an option in the model for the inclusion of 2m temperature in the assimilation cycle. For this reason, considering the great number of non-GTS stations in the ARPA Piemonte ground network, it has been decided to try the assimilation of 2m temperature in the COSMO-I2 version of the model, which has a horizontal resolution of about 3 km more similar to the average resolution of the thermometers. Two different test periods have been considered, from 1 to 15 September 2008 (summer-like weather) and from 3 to 17 January 2009 (winter-like weather). Every day we have run two simulations up to +24h, starting at 00UTC and 12UTC in order to investigate also the dependence on the initial state of the PBL. The aim of the work is to investigate the assimilation of the non-GTS data in the first 12h of the simulations in order to create an operational very high-resolution analysis, but also to test the option of running in the future a very short-range forecast (+12h to +18h) starting from these analyses. The results, in terms of RMSE, Mean Error (ME) and diurnal cycle of some surface variables such as 2m temperature, 2m relative humidity and 10m wind intensity, and in terms of vertical profile of temperature, show in general a positive impact during the assimilation cycle and below 1000-1500 m respectively and a neutral impact elsewhere, because the effect of the nudging vanishes a few hours after the end of the assimilation. As a second step, we introduced the assimilation of the 2 m temperature forecasts given by the Multimodel SuperEnsemble technique for all the available stations of the ARPA Piemonte network into the model, as if they were observations (we call them pseudo-observations), from +12h to +24h. The Multimodel SuperEnsemble technique is a powerful post-processing method for the estimation of weather forecast parameters. Several model outputs are combined, using weights calculated during a so-called training period. This technique has already been tested and implemented in many works on limited-area models in order to obtain reliable forecasts in complex orography regions. Also in this case we observe a positive impact mainly on the surface variables, but the effect lasts up to +24h.

Nitrogen and Sulfur Requirements for Clostridium thermocellum and Caldicellulosiruptor bescii on Cellulosic Substrates in Minimal Nutrient Media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kridelbaugh, Donna M; Nelson, Josh C; Engle, Nancy L

2013-01-01

Growth media for cellulolytic Clostridium thermocellum and Caldicellulosiruptor bescii bacteria usually contain excess nutrients that would increase costs for consolidated bioprocessing for biofuel production and create a waste stream with nitrogen, sulfur and phosphate. C. thermocellum was grown on crystalline cellulose with varying concentrations of nitrogen and sulfur compounds, and growth rate and alcohol production response curves were determined. Both bacteria assimilated sulfate in the presence of ascorbate reductant, increasing the ratio of oxidized to reduced fermentation products. From these results, a low ionic strength, defined minimal nutrient medium with decreased nitrogen, sulfur, phosphate and vitamin supplements was developed formore » the fermentation of cellobiose, cellulose and acid-pretreated Populus. Carbon and electron balance calculations indicate the unidentified residual fermentation products must include highly reduced molecules. Both bacterial populations were maintained in co-cultures with substrates containing xylan or hemicellulose in defined medium with sulfate and basal vitamin supplements.« less

Substrate Interactions during the Biodegradation of Benzene, Toluene, Ethylbenzene, and Xylene (BTEX) Hydrocarbons by the Fungus Cladophialophora sp. Strain T1

PubMed Central

Prenafeta-Boldú, F. X.; Vervoort, J.; Grotenhuis, J. T. C.; van Groenestijn, J. W.

2002-01-01

The soil fungus Cladophialophora sp. strain T1 (= ATCC MYA-2335) was capable of growth on a model water-soluble fraction of gasoline that contained all six BTEX components (benzene, toluene, ethylbenzene, and the xylene isomers). Benzene was not metabolized, but the alkylated benzenes (toluene, ethylbenzene, and xylenes) were degraded by a combination of assimilation and cometabolism. Toluene and ethylbenzene were used as sources of carbon and energy, whereas the xylenes were cometabolized to different extents. o-Xylene and m-xylene were converted to phthalates as end metabolites; p-xylene was not degraded in complex BTEX mixtures but, in combination with toluene, appeared to be mineralized. The metabolic profiles and the inhibitory nature of the substrate interactions indicated that toluene, ethylbenzene, and xylene were degraded at the side chain by the same monooxygenase enzyme. Our findings suggest that soil fungi could contribute significantly to bioremediation of BTEX pollution. PMID:12039717

Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) degradation by Acetobacterium paludosum.

PubMed

Sherburne, Leslie A; Shrout, Joshua D; Alvarez, Pedro J J

2005-12-01

Substrates and nutrients are often added to contaminated soil or groundwater to enhance bioremediation. Nevertheless, this practice may be counterproductive in some cases where nutrient addition might relieve selective pressure for pollutant biodegradation. Batch experiments with a homoacetogenic pure culture of Acetobacterium paludosum showed that anaerobic RDX degradation is the fastest when auxiliary growth substrates (yeast extract plus fructose) and nitrogen sources (ammonium) are not added. This bacterium degraded RDX faster under autotrophic (H2-fed) than under heterotrophic conditions, even though heterotrophic growth was faster. The inhibitory effect of ammonium is postulated to be due to the repression of enzymes that initiate RDX degradation by reducing its nitro groups, based on the known fact that ammonia represses nitrate and nitrite reductases. This observation suggests that the absence of easily assimilated nitrogen sources, such as ammonium, enhances RDX degradation. Although specific end products of RDX degradation were not determined, the production of nitrous oxide (N2O) suggests that A. paludosum cleaved the triazine ring.

On the assimilation of SWOT type data into 2D shallow-water models

NASA Astrophysics Data System (ADS)

Frédéric, Couderc; Denis, Dartus; Pierre-André, Garambois; Ronan, Madec; Jérôme, Monnier; Jean-Paul, Villa

2013-04-01

In river hydraulics, assimilation of water level measurements at gauging stations is well controlled, while assimilation of images is still delicate. In the present talk, we address the richness of satellite mapped information to constrain a 2D shallow-water model, but also related difficulties. 2D shallow models may be necessary for small scale modelling in particular for low-water and flood plain flows. Since in both cases, the dynamics of the wet-dry front is essential, one has to elaborate robust and accurate solvers. In this contribution we introduce robust second order, stable finite volume scheme [CoMaMoViDaLa]. Comparisons of real like tests cases with more classical solvers highlight the importance of an accurate flood plain modelling. A preliminary inverse study is presented in a flood plain flow case, [LaMo] [HoLaMoPu]. As a first step, a 0th order data processing model improves observation operator and produces more reliable water level derived from rough measurements [PuRa]. Then, both model and flow behaviours can be better understood thanks to variational sensitivities based on a gradient computation and adjoint equations. It can reveal several difficulties that a model designer has to tackle. Next, a 4D-Var data assimilation algorithm used with spatialized data leads to improved model calibration and potentially leads to identify river discharges. All the algorithms are implemented into DassFlow software (Fortran, MPI, adjoint) [Da]. All these results and experiments (accurate wet-dry front dynamics, sensitivities analysis, identification of discharges and calibration of model) are currently performed in view to use data from the future SWOT mission. [CoMaMoViDaLa] F. Couderc, R. Madec, J. Monnier, J.-P. Vila, D. Dartus, K. Larnier. "Sensitivity analysis and variational data assimilation for geophysical shallow water flows". Submitted. [Da] DassFlow - Data Assimilation for Free Surface Flows. Computational software http://www-gmm.insa-toulouse.fr/~monnier/DassFlow/ [HoLaMoPu] R. Hostache, X. Lai, J. Monnier, C. Puech. "Assimilation of spatial distributed water levels into a shallow-water flood model. Part II: using a remote sensing image of Mosel river". J. Hydrology (2010). [LaMo] X. Lai, J. Monnier. "Assimilation of spatial distributed water levels into a shallow-water flood model. Part I: mathematical method and test case". J. Hydrology (2009). [PuRa] C. Puech, D. Raclot. "Using geographic information systems and aerial photographs to determine water levels during floods". Hydrol. Process., 16, 1593 - 1602, (2002). [RoDa] H. Roux, D. Dartus. "Use of Parameter Optimization to Estimate a Flood Wave: Potential Applications to Remote Sensing of Rivers". J. Hydrology (2006).

Application of duckweed for human urine treatment in Bioregenerative Life Support System

NASA Astrophysics Data System (ADS)

Manukovsky, Nickolay; Kovalev, Vladimir

The object of the study was the common duckweed Lemna minor L. Thanks to the ability to assimilate mineral and organic substances, duckweed is used to purify water in sewage lagoons. In addition, duckweed biomass is known to be a potential high-protein feed resource for domestic animals and fish. The aim of the study was to estimate an application of duckweed in a two-stage treatment of human urine in Bioregenerative Life Support System (BLSS). At the first stage, the urine’s organic matter is oxidized by hydrogen peroxide. Diluted solution of oxidized urine is used for cultivation of duckweed. The appointment of duckweed is the assimilation of mineralized substances of urine. Part of the duckweed biomass yield directly or after composting could be embedded in the soil-like substrate as organic fertilizer to compensate the carry-over in consequence of plant growing. The rest duckweed biomass could be used as a feed for animals in BLSS. Then, the residual culture liquid is concentrated and used as a source of dietary salt. It takes 10-15 m2 of duckweed culture per crewmember to treat oxidized urine. The BLSS configuration including two-component subsystem of urine treatment is presented.

[Streptoverticillium griseoviridum n. sp., a producer of the candidin-amphotericin B group, antifungal heptaene nonaromatic antibiotic 0185].

PubMed

Konev, Iu E; Efimova, V M; Etingov, E D; Zaval'naia, N M

1978-02-01

An actinomyceteous strain LIA-0185 producing a heptaenic non-aromatic antibiotic of the candidin type was isolated from a soil sample taken in the Georgian SSR under the programme of screening antifungal antibiotics. The taxonomic study of the strain showed that it belonged to the series of viridoflavum and had the following main taxonomic features: the sporophores in the whorls, straight, remote: the aerial mycelium from yellow to dark-olive-grey; the substrate mycelium olive; the soluble pigment absent; the melanine pigment was produced on the peptone medium; the culture formed H2S; assimilated glucose, mannose, inozide and to a lesser extent fructose; did not assimilate arabinose, xylose, sucrose, lactose, ramnose and raffinose. The strain inhibited the growth of yeast and fungi, grampositive bacteria and actinomycetes and produced a complex of non-aromatic heptaenic antibiotics. The actinomycete differed from the other whorl cultures. It was classified as a new species Sv. griseoviridum sp. nov. The antibiotic complex was a mixture of 2 components, i. e. I and II present approximately in equal amounts. Component II was analogous to candidin. Component I was a new original substance.

Mesoscale data assimilation for a local severe rainfall event with the NHM-LETKF system

NASA Astrophysics Data System (ADS)

Kunii, M.

2013-12-01

This study aims to improve forecasts of local severe weather events through data assimilation and ensemble forecasting approaches. Here, the local ensemble transform Kalman filter (LETKF) is implemented with the Japan Meteorological Agency's nonhydrostatic model (NHM). The newly developed NHM-LETKF contains an adaptive inflation scheme and a spatial covariance localization scheme with physical distance. One-way nested analysis in which a finer-resolution LETKF is conducted by using the outputs of an outer model also becomes feasible. These new contents should enhance the potential of the LETKF for convective scale events. The NHM-LETKF is applied to a local severe rainfall event in Japan in 2012. Comparison of the root mean square errors between the model first guess and analysis reveals that the system assimilates observations appropriately. Analysis ensemble spreads indicate a significant increase around the time torrential rainfall occurred, which would imply an increase in the uncertainty of environmental fields. Forecasts initialized with LETKF analyses successfully capture intense rainfalls, suggesting that the system can work effectively for local severe weather. Investigation of probabilistic forecasts by ensemble forecasting indicates that this could become a reliable data source for decision making in the future. A one-way nested data assimilation scheme is also tested. The experiment results demonstrate that assimilation with a finer-resolution model provides an advantage in the quantitative precipitation forecasting of local severe weather conditions.

Towards Improved High-Resolution Land Surface Hydrologic Reanalysis Using a Physically-Based Hydrologic Model and Data Assimilation

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Zhang, F.; Duffy, C.; Yu, X.

2014-12-01

A coupled physically based land surface hydrologic model, Flux-PIHM, has been developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM has been implemented and manually calibrated at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Model predictions of discharge, point soil moisture, point water table depth, sensible and latent heat fluxes, and soil temperature show good agreement with observations. When calibrated only using discharge, and soil moisture and water table depth at one point, Flux-PIHM is able to resolve the observed 101 m scale soil moisture pattern at the Shale Hills watershed when an appropriate map of soil hydraulic properties is provided. A Flux-PIHM data assimilation system has been developed by incorporating EnKF for model parameter and state estimation. Both synthetic and real data assimilation experiments have been performed at the Shale Hills watershed. Synthetic experiment results show that the data assimilation system is able to simultaneously provide accurate estimates of multiple parameters. In the real data experiment, the EnKF estimated parameters and manually calibrated parameters yield similar model performances, but the EnKF method significantly decreases the time and labor required for calibration. The data requirements for accurate Flux-PIHM parameter estimation via data assimilation using synthetic observations have been tested. Results show that by assimilating only in situ outlet discharge, soil water content at one point, and the land surface temperature averaged over the whole watershed, the data assimilation system can provide an accurate representation of watershed hydrology. Observations of these key variables are available with national and even global spatial coverage (e.g., MODIS surface temperature, SMAP soil moisture, and the USGS gauging stations). National atmospheric reanalysis products, soil databases and land cover databases (e.g., NLDAS-2, SSURGO, NLCD) can provide high resolution forcing and input data. Therefore the Flux-PIHM data assimilation system could be readily expanded to other watersheds to provide regional scale land surface and hydrologic reanalysis with high spatial temporal resolution.

NOAA HRD's HEDAS Data Assimilation System's performance for the 2010 Atlantic Hurricane Season

NASA Astrophysics Data System (ADS)

Sellwood, K.; Aksoy, A.; Vukicevic, T.; Lorsolo, S.

2010-12-01

The Hurricane Ensemble Data Assimilation System (HEDAS) was developed at the Hurricane Research Division (HRD) of NOAA, in conjunction with an experimental version of the Hurricane Weather and Research Forecast model (HWRFx), in an effort to improve the initial representation of the hurricane vortex by utilizing high resolution in-situ data collected during NOAA’s Hurricane Field Program. HEDAS implements the “ensemble square root “ filter of Whitaker and Hamill (2002) using a 30 member ensemble obtained from NOAA/ESRL’s ensemble Kalman filter (EnKF) system and the assimilation is performed on a 3-km nest centered on the hurricane vortex. As part of NOAA’s Hurricane Forecast Improvement Program (HFIP), HEDAS will be run in a semi-operational mode for the first time during the 2010 Atlantic hurricane season and will assimilate airborne Doppler radar winds, dropwindsonde and flight level wind, temperature, pressure and relative humidity, and Stepped Frequency Microwave Radiometer surface wind observations as they become available. HEDAS has been implemented in an experimental mode for the cases of Hurricane Bill, 2009 and Paloma, 2008 to confirm functionality and determine the optimal configuration of the system. This test case demonstrates the importance of assimilating thermodynamic data in addition to wind observations and the benefit of increasing the quantity and distribution of observations. Applying HEDAS to a larger sample of storm forecasts would provide further insight into the behavior of the model when inner core aircraft observations are assimilated. The main focus of this talk will be to present a summary of HEDAS performance in the HWRFx model for the inaugural season. The HEDAS analyses and the resulting HWRFx forecasts will be compared with HWRFx analyses and forecasts produced concurrently using the HRD modeling group’s vortex initialization which does not employ data assimilation. The initial vortex and subsequent forecasts will be evaluated based on the thermodynamic structure, wind field, track and intensity. Related HEDAS research to be presented by HRD’s data assimilation group include evaluations of the geostrophic wind balance and covariance structures for the Bill experiments, and Observation System Simulation experiments (OSSEs) for the case of hurricane Paloma using both model generated and real observations.

Coupled assimilation for an intermediated coupled ENSO prediction model

NASA Astrophysics Data System (ADS)

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.

Copernicus stratospheric ozone service, 2009-2012: validation, system intercomparison and roles of input data sets

NASA Astrophysics Data System (ADS)

Lefever, K.; van der A, R.; Baier, F.; Christophe, Y.; Errera, Q.; Eskes, H.; Flemming, J.; Inness, A.; Jones, L.; Lambert, J.-C.; Langerock, B.; Schultz, M. G.; Stein, O.; Wagner, A.; Chabrillat, S.

2015-03-01

This paper evaluates and discusses the quality of the stratospheric ozone analyses delivered in near real time by the MACC (Monitoring Atmospheric Composition and Climate) project during the 3-year period between September 2009 and September 2012. Ozone analyses produced by four different chemical data assimilation (CDA) systems are examined and compared: the Integrated Forecast System coupled to the Model for OZone And Related chemical Tracers (IFS-MOZART); the Belgian Assimilation System for Chemical ObsErvations (BASCOE); the Synoptic Analysis of Chemical Constituents by Advanced Data Assimilation (SACADA); and the Data Assimilation Model based on Transport Model version 3 (TM3DAM). The assimilated satellite ozone retrievals differed for each system; SACADA and TM3DAM assimilated only total ozone observations, BASCOE assimilated profiles for ozone and some related species, while IFS-MOZART assimilated both types of ozone observations. All analyses deliver total column values that agree well with ground-based observations (biases < 5%) and have a realistic seasonal cycle, except for BASCOE analyses, which underestimate total ozone in the tropics all year long by 7 to 10%, and SACADA analyses, which overestimate total ozone in polar night regions by up to 30%. The validation of the vertical distribution is based on independent observations from ozonesondes and the ACE-FTS (Atmospheric Chemistry Experiment - Fourier Transform Spectrometer) satellite instrument. It cannot be performed with TM3DAM, which is designed only to deliver analyses of total ozone columns. Vertically alternating positive and negative biases are found in the IFS-MOZART analyses as well as an overestimation of 30 to 60% in the polar lower stratosphere during polar ozone depletion events. SACADA underestimates lower stratospheric ozone by up to 50% during these events above the South Pole and overestimates it by approximately the same amount in the tropics. The three-dimensional (3-D) analyses delivered by BASCOE are found to have the best quality among the three systems resolving the vertical dimension, with biases not exceeding 10% all year long, at all stratospheric levels and in all latitude bands, except in the tropical lowermost stratosphere. The northern spring 2011 period is studied in more detail to evaluate the ability of the analyses to represent the exceptional ozone depletion event, which happened above the Arctic in March 2011. Offline sensitivity tests are performed during this month and indicate that the differences between the forward models or the assimilation algorithms are much less important than the characteristics of the assimilated data sets. They also show that IFS-MOZART is able to deliver realistic analyses of ozone both in the troposphere and in the stratosphere, but this requires the assimilation of observations from nadir-looking instruments as well as the assimilation of profiles, which are well resolved vertically and extend into the lowermost stratosphere.

Predicting the response of soil organic matter microbial decomposition to moisture

NASA Astrophysics Data System (ADS)

Chenu, Claire; Garnier, Patricia; Monga, Olivier; Moyano, Fernando; Pot, Valérie; Nunan, Naoise; Coucheney, Elsa; Otten, Wilfred

2014-05-01

Next to temperature, soil moisture is a main driver of soil C and N transformations in soils, because it affects microbial activity and survival. The moisture sensitivity of soil organic matter decay may be a source of uncertainty of similar magnitude to that of the temperature sensitivity and receives much less attention. The basic concepts and mechanisms relating soil water to microorganisms were identified early (i.e. in steady state conditions : direct effects on microbial physiology, diffusion substrates, nutrients, extracellular enzymes, diffusion of oxygen, movement of microorganisms). However, accounting for how moisture controls soil microbial activity remains essentially empirical and poorly accounts for soil characteristics. Soil microorganisms live in a complex 3-D framework of mineral and organic particles defining pores of various sizes, connections with adjacent pores, and with pore walls of contrasted nature, which result in a variety of microhabitats. The water regime to which microorganisms are exposed can be predicted to depend the size and connectivity of pores in which they are located. Furthermore, the spatial distribution of microorganisms as well as that of organic matter is very heterogeneous, determining the diffusion distances between substrates and decomposers. A new generation of pore scale models of C dynamics in soil may challenge the difficulty of modelling such a complex system. These models are based on an explicit representation of soil structure (i.e. soil particles and voids), microorganisms and organic matter localisation. We tested here the ability of such a model to account for changes in microbial respiration with soil moisture. In the model MOSAIC II, soil pore space is described using a sphere network coming from a geometrical modelling algorithm. MicroCT tomography images were used to implement this representation of soil structure. A biological sub-model describes the hydrolysis of insoluble SOM into dissolved organic matter, its assimilation, respiration and microbial mortality. A recent improvement of the model was the description of the diffusion of soluble organic matter. We tested the model using the results from an experiment where a simple substrate (fructose) was decomposed by bacteria within a simple media (sand). Separate incubations in microcosms were carried out using five different bacterial communities at two different moisture conditions corresponding to water potentials of -0.01 and -0.1 bars. We calibrated the biological parameters using the experimental data obtained at high water content and we tested the model without any parameters change at low water content. Both the experiments and simulations showed a decrease in mineralisation with a decrease of water content, of which pattern depended on the bacterial species and its physiological characteristics. The model was able to correctly simulate the decrease of connectivity between substrate and microorganism due the decrease of water content. The potential and required developments of such models in describing how heterotrophic respiration is affected by micro-scale distribution and processes in soils and in testing scenarios regarding water regimes in a changing climate is discussed.

The ASSET intercomparison of stratosphere and lower mesosphere humidity analyses

NASA Astrophysics Data System (ADS)

Thornton, H. E.; Jackson, D. R.; Bekki, S.; Bormann, N.; Errera, Q.; Geer, A. J.; Lahoz, W. A.; Rharmili, S.

2008-07-01

This paper presents results from the first detailed intercomparison of stratosphere-lower mesosphere water vapour analyses; it builds on earlier results from the "Assimilation of ENVISAT Data" (ASSET) project. With the availability of high resolution, good quality Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) water vapour profiles, the ability of four different atmospheric models to assimilate these data is tested. MIPAS data have been assimilated over September 2003 into the models of the European Centre for Medium Range Weather Forecasts (ECMWF), the Belgian Institute for Space and Aeronomy (BIRA-IASB), the French Service d'Aéronomie (SA-IPSL) and the UK Met Office. The resultant middle atmosphere humidity analyses are compared against independent satellite data from the Halogen Occultation Experiment (HALOE), the Polar Ozone and Aerosol Measurement (POAM III) and the Stratospheric Aerosol and Gas Experiment (SAGE II). The MIPAS water vapour profiles are generally well assimilated in the ECMWF, BIRA-IASB and SA systems, producing stratosphere-mesosphere water vapour fields where the main features compare favourably with the independent observations. However, the models are less capable of assimilating the MIPAS data where water vapour values are locally extreme or in regions of strong humidity gradients, such as the Southern Hemisphere lower stratosphere polar vortex. Differences in the analyses can be attributed to the choice of humidity control variable, how the background error covariance matrix is generated, the model resolution and its complexity, the degree of quality control of the observations and the use of observations near the model boundaries. Due to the poor performance of the Met Office analyses the results are not included in the intercomparison, but are discussed separately. The Met Office results highlight the pitfalls in humidity assimilation, and provide lessons that should be learnt by developers of stratospheric humidity assimilation systems. In particular, they underline the importance of the background error covariances in generating a realistic troposphere to mesosphere water vapour analysis.

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

PubMed

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.

Comparison of different assimilation methodologies of groundwater levels to improve predictions of root zone soil moisture with an integrated terrestrial system model

NASA Astrophysics Data System (ADS)

Zhang, Hongjuan; Kurtz, Wolfgang; Kollet, Stefan; Vereecken, Harry; Franssen, Harrie-Jan Hendricks

2018-01-01

The linkage between root zone soil moisture and groundwater is either neglected or simplified in most land surface models. The fully-coupled subsurface-land surface model TerrSysMP including variably saturated groundwater dynamics is used in this work. We test and compare five data assimilation methodologies for assimilating groundwater level data via the ensemble Kalman filter (EnKF) to improve root zone soil moisture estimation with TerrSysMP. Groundwater level data are assimilated in the form of pressure head or soil moisture (set equal to porosity in the saturated zone) to update state vectors. In the five assimilation methodologies, the state vector contains either (i) pressure head, or (ii) log-transformed pressure head, or (iii) soil moisture, or (iv) pressure head for the saturated zone only, or (v) a combination of pressure head and soil moisture, pressure head for the saturated zone and soil moisture for the unsaturated zone. These methodologies are evaluated in synthetic experiments which are performed for different climate conditions, soil types and plant functional types to simulate various root zone soil moisture distributions and groundwater levels. The results demonstrate that EnKF cannot properly handle strongly skewed pressure distributions which are caused by extreme negative pressure heads in the unsaturated zone during dry periods. This problem can only be alleviated by methodology (iii), (iv) and (v). The last approach gives the best results and avoids unphysical updates related to strongly skewed pressure heads in the unsaturated zone. If groundwater level data are assimilated by methodology (iii), EnKF fails to update the state vector containing the soil moisture values if for (almost) all the realizations the observation does not bring significant new information. Synthetic experiments for the joint assimilation of groundwater levels and surface soil moisture support methodology (v) and show great potential for improving the representation of root zone soil moisture.

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results

PubMed Central

Norris, Peter M.; da Silva, Arlindo M.

2018-01-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational–Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state. PMID:29618848

Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability Using High-Resolution Cloud Observations. Part 2: Sensitivity Tests and Results

NASA Technical Reports Server (NTRS)

Norris, Peter M.; da Silva, Arlindo M.

2016-01-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.

Development of Gridded Innovations and Observations Supplement to MERRA-2

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Da Silva, Arlindo M.; Robertson, Franklin R.

2017-01-01

Atmospheric reanalysis have become an important source of data for weather and climate research, owing to the continuity of the data, but especially because of the multitude of observational data included (radiosondes, commercial aircraft, retrieved data products and radiances). However, the presence of assimilated observations can vary based on numerous factors, and so it is difficult or impossible for a researcher to say with any degree of certainty how many and what type of observations contributed to the reanalysis data they are using at any give point in time or space. For example, quality control, transmission interruptions, and station outages can occasionally affect data availability. While orbital paths can be known, drift in certain instruments and the large number of available instruments makes it challenging to know which satellite is observing any region at any point in the diurnal cycle. Furthermore, there is information from the statistics generated by the data assimilation that can help understand the model and the quality of the reanalysis. Typically, the assimilated observations and their innovations are in observation-space data formats and have not been made easily available to reanalysis users.A test data set has been developed to make the MERRA-2 assimilated observations available for rapid and general use, by simplifying the data format. The observations are binned to a grid similar as MERRA-2 and saved as netCDF. This data collection includes the mean and number of observations in the bin as well as its variance. The data will also include the innovations from the data assimilation, the forecast departure and the analysis increment, as well as bias correction (for satellite radiances). We refer to this proof-of-concept data as the MERRA-2 Gridded Innovations and Observations (GIO). In this paper, we present the data format and its strengths and limitations with some initial testing and validation of the methodology.

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results.

PubMed

Norris, Peter M; da Silva, Arlindo M

2016-07-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.

Preliminary Evaluation of a Regional Atmospheric Chemical Data Assimilation System for Environmental Surveillance

PubMed Central

Lee, Pius; Liu, Yang

2014-01-01

We report the progress of an ongoing effort by the Air Resources Laboratory, NOAA to build a prototype regional Chemical Analysis System (ARLCAS). The ARLCAS focuses on providing long-term analysis of the three dimensional (3D) air-pollutant concentration fields over the continental U.S. It leverages expertise from the NASA Earth Science Division-sponsored Air Quality Applied Science Team (AQAST) for the state-of-science knowledge in atmospheric and data assimilation sciences. The ARLCAS complies with national operational center requirement protocols and aims to have the modeling system to be maintained by a national center. Meteorology and chemistry observations consist of land-, air- and space-based observed and quality-assured data. We develop modularized testing to investigate the efficacies of the various components of the ARLCAS. The sensitivity testing of data assimilation schemes showed that with the increment of additional observational data sets, the accuracy of the analysis chemical fields also increased incrementally in varying margins. The benefit is especially noted for additional data sets based on a different platform and/or a different retrieval algorithm. We also described a plan to apply the analysis chemical fields in environmental surveillance at the Centers for Disease Control and Prevention. PMID:25514141

Preliminary evaluation of a regional atmospheric chemical data assimilation system for environmental surveillance.

PubMed

Lee, Pius; Liu, Yang

2014-12-01

We report the progress of an ongoing effort by the Air Resources Laboratory, NOAA to build a prototype regional Chemical Analysis System (ARLCAS). The ARLCAS focuses on providing long-term analysis of the three dimensional (3D) air-pollutant concentration fields over the continental U.S. It leverages expertise from the NASA Earth Science Division-sponsored Air Quality Applied Science Team (AQAST) for the state-of-science knowledge in atmospheric and data assimilation sciences. The ARLCAS complies with national operational center requirement protocols and aims to have the modeling system to be maintained by a national center. Meteorology and chemistry observations consist of land-, air- and space-based observed and quality-assured data. We develop modularized testing to investigate the efficacies of the various components of the ARLCAS. The sensitivity testing of data assimilation schemes showed that with the increment of additional observational data sets, the accuracy of the analysis chemical fields also increased incrementally in varying margins. The benefit is especially noted for additional data sets based on a different platform and/or a different retrieval algorithm. We also described a plan to apply the analysis chemical fields in environmental surveillance at the Centers for Disease Control and Prevention.

Generalized Background Error covariance matrix model (GEN_BE v2.0)

NASA Astrophysics Data System (ADS)

Descombes, G.; Auligné, T.; Vandenberghe, F.; Barker, D. M.

2014-07-01

The specification of state background error statistics is a key component of data assimilation since it affects the impact observations will have on the analysis. In the variational data assimilation approach, applied in geophysical sciences, the dimensions of the background error covariance matrix (B) are usually too large to be explicitly determined and B needs to be modeled. Recent efforts to include new variables in the analysis such as cloud parameters and chemical species have required the development of the code to GENerate the Background Errors (GEN_BE) version 2.0 for the Weather Research and Forecasting (WRF) community model to allow for a simpler, flexible, robust, and community-oriented framework that gathers methods used by meteorological operational centers and researchers. We present the advantages of this new design for the data assimilation community by performing benchmarks and showing some of the new features on data assimilation test cases. As data assimilation for clouds remains a challenge, we present a multivariate approach that includes hydrometeors in the control variables and new correlated errors. In addition, the GEN_BE v2.0 code is employed to diagnose error parameter statistics for chemical species, which shows that it is a tool flexible enough to involve new control variables. While the generation of the background errors statistics code has been first developed for atmospheric research, the new version (GEN_BE v2.0) can be easily extended to other domains of science and be chosen as a testbed for diagnostic and new modeling of B. Initially developed for variational data assimilation, the model of the B matrix may be useful for variational ensemble hybrid methods as well.

Generalized background error covariance matrix model (GEN_BE v2.0)

NASA Astrophysics Data System (ADS)

Descombes, G.; Auligné, T.; Vandenberghe, F.; Barker, D. M.; Barré, J.

2015-03-01

The specification of state background error statistics is a key component of data assimilation since it affects the impact observations will have on the analysis. In the variational data assimilation approach, applied in geophysical sciences, the dimensions of the background error covariance matrix (B) are usually too large to be explicitly determined and B needs to be modeled. Recent efforts to include new variables in the analysis such as cloud parameters and chemical species have required the development of the code to GENerate the Background Errors (GEN_BE) version 2.0 for the Weather Research and Forecasting (WRF) community model. GEN_BE allows for a simpler, flexible, robust, and community-oriented framework that gathers methods used by some meteorological operational centers and researchers. We present the advantages of this new design for the data assimilation community by performing benchmarks of different modeling of B and showing some of the new features in data assimilation test cases. As data assimilation for clouds remains a challenge, we present a multivariate approach that includes hydrometeors in the control variables and new correlated errors. In addition, the GEN_BE v2.0 code is employed to diagnose error parameter statistics for chemical species, which shows that it is a tool flexible enough to implement new control variables. While the generation of the background errors statistics code was first developed for atmospheric research, the new version (GEN_BE v2.0) can be easily applied to other domains of science and chosen to diagnose and model B. Initially developed for variational data assimilation, the model of the B matrix may be useful for variational ensemble hybrid methods as well.

Hydrologic data assimilation with a hillslope-scale-resolving model and L band radar observations: Synthetic experiments with the ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Flores, Alejandro N.; Bras, Rafael L.; Entekhabi, Dara

2012-08-01

Soil moisture information is critical for applications like landslide susceptibility analysis and military trafficability assessment. Existing technologies cannot observe soil moisture at spatial scales of hillslopes (e.g., 100 to 102 m) and over large areas (e.g., 102 to 105 km2) with sufficiently high temporal coverage (e.g., days). Physics-based hydrologic models can simulate soil moisture at the necessary spatial and temporal scales, albeit with error. We develop and test a data assimilation framework based on the ensemble Kalman filter for constraining uncertain simulated high-resolution soil moisture fields to anticipated remote sensing products, specifically NASA's Soil Moisture Active-Passive (SMAP) mission, which will provide global L band microwave observation approximately every 2-3 days. The framework directly assimilates SMAP synthetic 3 km radar backscatter observations to update hillslope-scale bare soil moisture estimates from a physics-based model. Downscaling from 3 km observations to hillslope scales is achieved through the data assimilation algorithm. Assimilation reduces bias in near-surface soil moisture (e.g., top 10 cm) by approximately 0.05 m3/m3and expected root-mean-square errors by at least 60% in much of the watershed, relative to an open loop simulation. However, near-surface moisture estimates in channel and valley bottoms do not improve, and estimates of profile-integrated moisture throughout the watershed do not substantially improve. We discuss the implications of this work, focusing on ongoing efforts to improve soil moisture estimation in the entire soil profile through joint assimilation of other satellite (e.g., vegetation) and in situ soil moisture measurements.

Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

NASA Astrophysics Data System (ADS)

Laiolo, P.; Gabellani, S.; Campo, L.; Silvestro, F.; Delogu, F.; Rudari, R.; Pulvirenti, L.; Boni, G.; Fascetti, F.; Pierdicca, N.; Crapolicchio, R.; Hasenauer, S.; Puca, S.

2016-06-01

The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012-June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash-Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.

Impact of the assimilation of satellite soil moisture and LST on the hydrological cycle

NASA Astrophysics Data System (ADS)

Laiolo, Paola; Gabellani, Simone; Delogu, Fabio; Silvestro, Francesco; Rudari, Roberto; Campo, Lorenzo; Boni, Giorgio

2014-05-01

The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce ground based data. The aim of this work is to investigate the impacts on the performances of a distributed hydrological model (Continuum) of the assimilation of satellite-derived soil moisture products and Land Surface (LST). In this work three different soil moisture (SM) products, derived by ASCAT sensor, are used. These data are provided by the EUMETSAT's H-SAF (Satellite Application Facility on Support to Operational Hydrology and Water Management) program. The considered soil moisture products are: large scale surface soil moisture (SM OBS 1 - H07), small scale surface soil moisture (SM OBS 2 - H08) and profile index in the roots region (SM DAS 2 - H14). These data are compared with soil moisture estimated by Continuum model on the Orba catchment (800 km2), in the northern part of Italy, for the period July 2012-June 2013. Different assimilation experiments have been performed. The first experiment consists in the assimilation of the SM products by using a simple Nudging technique; the second one is the assimilation of only LST data, derived from MSG satellite, and the third is the assimilation of both SM products and LST. The benefits on the model predictions of discharge, LST and soil moisture dynamics were tested.

Regional Data Assimilation Using a Stretched-Grid Approach and Ensemble Calculations

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, M. S.; Takacs, L. L.; Govindaraju, R. C.; Atlas, Robert (Technical Monitor)

2002-01-01

The global variable resolution stretched grid (SG) version of the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) incorporating the GEOS SG-GCM (Fox-Rabinovitz 2000, Fox-Rabinovitz et al. 2001a,b), has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The major area of interest with enhanced regional resolution used in different SG-DAS experiments includes a rectangle over the U.S. with 50 or 60 km horizontal resolution. The analyses and diagnostics are produced for all mandatory levels from the surface to 0.2 hPa. The assimilated regional mesoscale products are consistent with global scale circulation characteristics due to using the SG-approach. Both the stretched grid and basic uniform grid DASs use the same amount of global grid-points and are compared in terms of regional product quality.

Assimilative modeling of low latitude ionosphere

NASA Technical Reports Server (NTRS)

Pi, Xiaoqing; Wang, Chunining; Hajj, George A.; Rosen, I. Gary; Wilson, Brian D.; Mannucci, Anthony J.

2004-01-01

In this paper we present an observation system simulation experiment for modeling low-latitude ionosphere using a 3-dimensional (3-D) global assimilative ionospheric model (GAIM). The experiment is conducted to test the effectiveness of GAIM with a 4-D variational approach (4DVAR) in estimation of the ExB drift and thermospheric wind in the magnetic meridional planes simultaneously for all longitude or local time sectors. The operational Global Positioning System (GPS) satellites and the ground-based global GPS receiver network of the International GPS Service are used in the experiment as the data assimilation source. 'The optimization of the ionospheric state (electron density) modeling is performed through a nonlinear least-squares minimization process that adjusts the dynamical forces to reduce the difference between the modeled and observed slant total electron content in the entire modeled region. The present experiment for multiple force estimations reinforces our previous assessment made through single driver estimations conducted for the ExB drift only.

A hybrid variational ensemble data assimilation for the HIgh Resolution Limited Area Model (HIRLAM)

NASA Astrophysics Data System (ADS)

Gustafsson, N.; Bojarova, J.; Vignes, O.

2014-02-01

A hybrid variational ensemble data assimilation has been developed on top of the HIRLAM variational data assimilation. It provides the possibility of applying a flow-dependent background error covariance model during the data assimilation at the same time as full rank characteristics of the variational data assimilation are preserved. The hybrid formulation is based on an augmentation of the assimilation control variable with localised weights to be assigned to a set of ensemble member perturbations (deviations from the ensemble mean). The flow-dependency of the hybrid assimilation is demonstrated in single simulated observation impact studies and the improved performance of the hybrid assimilation in comparison with pure 3-dimensional variational as well as pure ensemble assimilation is also proven in real observation assimilation experiments. The performance of the hybrid assimilation is comparable to the performance of the 4-dimensional variational data assimilation. The sensitivity to various parameters of the hybrid assimilation scheme and the sensitivity to the applied ensemble generation techniques are also examined. In particular, the inclusion of ensemble perturbations with a lagged validity time has been examined with encouraging results.

Nitrate assimilation is inhibited by elevated CO2 in field-grown wheat

NASA Astrophysics Data System (ADS)

J. Bloom, Arnold; Burger, Martin; A. Kimball, Bruce; J. Pinter, Paul, Jr.

2014-06-01

Total protein and nitrogen concentrations in plants generally decline under elevated CO2 atmospheres. Explanations for this decline include that plants under elevated CO2 grow larger, diluting the protein within their tissues; that carbohydrates accumulate within leaves, downregulating the amount of the most prevalent protein Rubisco; that carbon enrichment of the rhizosphere leads to progressively greater limitations of the nitrogen available to plants; and that elevated CO2 directly inhibits plant nitrogen metabolism, especially the assimilation of nitrate into proteins in leaves of C3 plants. Recently, several meta-analyses have indicated that CO2 inhibition of nitrate assimilation is the explanation most consistent with observations. Here, we present the first direct field test of this explanation. We analysed wheat (Triticum aestivum L.) grown under elevated and ambient CO2 concentrations in the free-air CO2 enrichment experiment at Maricopa, Arizona. In leaf tissue, the ratio of nitrate to total nitrogen concentration and the stable isotope ratios of organic nitrogen and free nitrate showed that nitrate assimilation was slower under elevated than ambient CO2. These findings imply that food quality will suffer under the CO2 levels anticipated during this century unless more sophisticated approaches to nitrogen fertilization are employed.

Implementation of a Parallel Kalman Filter for Stratospheric Chemical Tracer Assimilation

NASA Technical Reports Server (NTRS)

Chang, Lang-Ping; Lyster, Peter M.; Menard, R.; Cohn, S. E.

1998-01-01

A Kalman filter for the assimilation of long-lived atmospheric chemical constituents has been developed for two-dimensional transport models on isentropic surfaces over the globe. An important attribute of the Kalman filter is that it calculates error covariances of the constituent fields using the tracer dynamics. Consequently, the current Kalman-filter assimilation is a five-dimensional problem (coordinates of two points and time), and it can only be handled on computers with large memory and high floating point speed. In this paper, an implementation of the Kalman filter for distributed-memory, message-passing parallel computers is discussed. Two approaches were studied: an operator decomposition and a covariance decomposition. The latter was found to be more scalable than the former, and it possesses the property that the dynamical model does not need to be parallelized, which is of considerable practical advantage. This code is currently used to assimilate constituent data retrieved by limb sounders on the Upper Atmosphere Research Satellite. Tests of the code examined the variance transport and observability properties. Aspects of the parallel implementation, some timing results, and a brief discussion of the physical results will be presented.

Assimilation of river altimetry data for effective bed elevation and roughness coefficient

NASA Astrophysics Data System (ADS)

Brêda, João Paulo L. F.; Paiva, Rodrigo C. D.; Bravo, Juan Martin; Passaia, Otávio

2017-04-01

Hydrodynamic models of large rivers are important prediction tools of river discharge, height and floods. However, these techniques still carry considerable errors; part of them related to parameters uncertainties related to river bathymetry and roughness coefficient. Data from recent spatial altimetry missions offers an opportunity to reduce parameters uncertainty through inverse methods. This study aims to develop and access different methods of altimetry data assimilation to improve river bottom levels and Manning roughness estimations in a 1-D hydrodynamic model. The case study was a 1,100 km reach of the Madeira River, a tributary of the Amazon. The tested assimilation methods are direct insertion, linear interpolation, SCE-UA global optimization algorithm and a Kalman Filter adaptation. The Kalman Filter method is composed by new physically based covariance functions developed from steady-flow and backwater equations. It is accessed the benefits of altimetry missions with different spatio-temporal resolutions, such as ICESAT-1, Envisat and Jason 2. Level time series of 5 gauging stations and 5 GPS river height profiles are used to assess and validate the assimilation methods. Finally, the potential of future missions are discussed, such as ICESAT-2 and SWOT satellites.

Fungal–bacterial dynamics and their contribution to terrigenous carbon turnover in relation to organic matter quality

PubMed Central

Fabian, Jenny; Zlatanovic, Sanja; Mutz, Michael; Premke, Katrin

2017-01-01

Ecological functions of fungal and bacterial decomposers vary with environmental conditions. However, the response of these decomposers to particulate organic matter (POM) quality, which varies widely in aquatic ecosystems, remains poorly understood. Here we investigated how POM pools of substrates of different qualities determine the relative contributions of aquatic fungi and bacteria to terrigenous carbon (C) turnover. To this end, surface sediments were incubated with different POM pools of algae and/or leaf litter. 13C stable-isotope measurements of C mineralization were combined with phospholipid analysis to link the metabolic activities and substrate preferences of fungal and bacterial heterotrophs to dynamics in their abundance. We found that the presence of labile POM greatly affected the dominance of bacteria over fungi within the degrader communities and stimulated the decomposition of beech litter primarily through an increase in metabolic activity. Our data indicated that fungi primarily contribute to terrigenous C turnover by providing litter C for the microbial loop, whereas bacteria determine whether the supplied C substrate is assimilated into biomass or recycled back into the atmosphere in relation to phosphate availability. Thus, this study provides a better understanding of the role of fungi and bacteria in terrestrial–aquatic C cycling in relation to environmental conditions. PMID:27983721

The role of Monosaccharide Transport Proteins in carbohydrate assimilation, distribution, metabolism and homeostasis

PubMed Central

Cura, Anthony J.; Carruthers, Anthony

2012-01-01

The facilitated diffusion of glucose, galactose, fructose, urate, myoinositol and dehydroascorbic acid in mammals is catalyzed by a family of 14 monosaccharide transport proteins called GLUTs. These transporters may be divided into 3 classes according to sequence similarity and function/substrate specificity. GLUT1 appears to be highly expressed in glycolytically active cells and has been co-opted in vitamin C auxotrophs to maintain the redox state of the blood through transport of dehydroascorbate. Several GLUTs are definitive glucose/galactose transporters, GLUT2 and GLUT5 are physiologically important fructose transporters, GLUT9 appears to be a urate transporter while GLUT13 (HMIT1) is a proton/myoinositol co-transporter. The physiologic substrates of some GLUTs remain to be established. The GLUTs are expressed in a tissue specific manner where affinity, specificity and capacity for substrate transport are paramount for tissue function. Although great strides have been made in characterizing GLUT-catalyzed monosaccharide transport and mapping GLUT membrane topography and determinants of substrate specificity, a unifying model for GLUT structure and function remains elusive. The GLUTs play a major role in carbohydrate homeostasis and the redistribution of sugar-derived carbons among the various organ systems. This is accomplished through a multiplicity of GLUT-dependent glucose sensing and effector mechanisms that regulate monosaccharide ingestion, absorption, distribution, cellular transport and metabolism and recovery/retention. Glucose transport and metabolism have co-evolved in mammals to support cerebral glucose utilization. PMID:22943001

Plant growth modeling at the JSC variable pressure growth chamber - An application of experimental design

NASA Technical Reports Server (NTRS)

Miller, Adam M.; Edeen, Marybeth; Sirko, Robert J.

1992-01-01

This paper describes the approach and results of an effort to characterize plant growth under various environmental conditions at the Johnson Space Center variable pressure growth chamber. Using a field of applied mathematics and statistics known as design of experiments (DOE), we developed a test plan for varying environmental parameters during a lettuce growth experiment. The test plan was developed using a Box-Behnken approach to DOE. As a result of the experimental runs, we have developed empirical models of both the transpiration process and carbon dioxide assimilation for Waldman's Green lettuce over specified ranges of environmental parameters including carbon dioxide concentration, light intensity, dew-point temperature, and air velocity. This model also predicts transpiration and carbon dioxide assimilation for different ages of the plant canopy.

Nematode feeding strategies and the fate of dissolved organic matter carbon in different deep-sea sedimentary environments

NASA Astrophysics Data System (ADS)

Pape, Ellen; van Oevelen, Dick; Moodley, Leon; Soetaert, Karline; Vanreusel, Ann

2013-10-01

Sediments sampled from the Galicia Bank seamount and the adjacent slope (northeast Atlantic), and from a western Mediterranean slope site, were injected onboard with 13C-enriched dissolved organic matter (DOM) to evaluate nematode feeding strategies and the fate of DOM carbon in different benthic environments. We hypothesized that nematode 13C label assimilation resulted from either direct DOM uptake or feeding on 13C labeled bacteria. Slope sediments were injected with glucose ("simple" DOM) or "complex" diatom-derived DOM to investigate the influence of DOM composition on carbon assimilation. The time-series (1, 7 and 14 days) experiment at the seamount site was the first study to reveal a higher 13C enrichment of nematodes than bacteria and sediments after 7 days. Although isotope dynamics indicated that both DOM and bacteria were plausible candidate food sources, the contribution to nematode secondary production and metabolic requirements (estimated from biomass-dependent respiration rates) was higher for bacteria than for DOM at all sites. The seamount nematode community showed higher carbon assimilation rates than the slope assemblages, which may reflect an adaptation to the food-poor environment. Our results suggested that the trophic importance of bacteria did not depend on the amount of labile sedimentary organic matter. Furthermore, there was a discrepancy between carbon assimilation rates observed in the experiments and the feeding type classification, based on buccal morphology. Sites with a similar feeding type composition (i.e. the northeast Atlantic sites) showed large differences in uptake, whilst the nematode assemblages at the two slope sites, which had a differing trophic structure, took up similar amounts of the DOM associated carbon. Our results did not indicate substantial differences in carbon processing related to the complexity of the DOM substrate. The quantity of processed carbon (5-42% of added DOM) was determined by the bacteria, and was primarily respired. The bulk of the added 13C-DOM was not ingested by the benthic biota under study, and a considerable fraction was possibly adsorbed onto the sediment grains.

From LIMS to OMPS-LP: Limb Ozone Observations for Future Reanalyses

NASA Technical Reports Server (NTRS)

Wargan, K.; Kramarova, N.; Remsberg, E.; Coy, L.; Harvey, L.; Livesey, N.; Pawson, S.

2017-01-01

High vertical resolution and accuracy of ozone data from satellite-borne limb sounders has made them an invaluable tool in scientific studies of the middle and upper atmosphere. However, it was not until recently that these measurements were successfully incorporated in atmospheric reanalyses: of the major multidecadal reanalyses only ECMWF's (European Centre for Medium-Range Weather Forecasts') ERA (ECMWF Re-Analysis)-Interim/ERA5 and NASA's MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications-2) use limb ozone data. Validation and comparison studies have demonstrated that the addition of observations from the Microwave Limb Sounder (MLS) on EOS (Earth Observing System) Aura greatly improved the quality of ozone fields in MERRA-2 making these assimilated data sets useful for scientific research. In this presentation, we will show the results of test experiments assimilating retrieved ozone from the Limb Infrared Monitor of the Stratosphere (LIMS, 1978/1979) and Ozone Mapping Profiler Suite Limb Profiler (OMPS-LP, 2012 to present). Our approach builds on the established assimilation methodology used for MLS in MERRA-2 and, in the case of OMPS-LP, extends the excellent record of MLS ozone assimilation into the post-EOS era in Earth observations. We will show case studies, discuss comparisons of the new experiments with MERRA-2, strategies for bias correction and the potential for combined assimilation of multiple limb ozone data types in future reanalyses for studies of multidecadal stratospheric ozone changes including trends.

Continuous data assimilation for downscaling large-footprint soil moisture retrievals

NASA Astrophysics Data System (ADS)

Altaf, Muhammad U.; Jana, Raghavendra B.; Hoteit, Ibrahim; McCabe, Matthew F.

2016-10-01

Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model's large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (HYDRUS) are subjected to data assimilation conditioned upon coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

Impact of advanced technology microwave sounder data in the NCMRWF 4D-VAR data assimilation system

NASA Astrophysics Data System (ADS)

Rani, S. Indira; Srinivas, D.; Mallick, Swapan; George, John P.

2016-05-01

This study demonstrates the added benefits of assimilating the Advanced Technology Microwave Sounder (ATMS) radiances from the Suomi-NPP satellite in the NCMRWF Unified Model (NCUM). ATMS is a cross-track scanning microwave radiometer inherited the legacy of two very successful instrument namely, Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS). ATMS has 22 channels: 11 temperature sounding channels around 50-60 GHz oxygen band and 6 moisture sounding channels around the 183GHz water vapour band in addition to 5 channels sensitive to the surface in clear conditions, or to water vapour, rain, and cloud when conditions are not clear (at 23, 31, 50, 51 and 89 GHz). Before operational assimilation of any new observation by NWP centres it is standard practice to assess data quality with respect to NWP model background (short-forecast) fields. Quality of all channels is estimated against the model background and the biases are computed and compared against that from the similar observations. The impact of the ATMS data on global analyses and forecasts is tested by adding the ATMS data in the NCUM Observation Processing system (OPS) and 4D-Var variational assimilation (VAR) system. This paper also discusses the pre-operational numerical experiments conducted to assess the impact of ATMS radiances in the NCUM assimilation system. It is noted that the performance of ATMS is stable and it contributes to the performance of the model, complimenting observations from other instruments.

A Variable-Resolution Stretched-Grid General Circulation Model and Data Assimilation System with Multiple Areas of Interest: Studying the Anomalous Regional Climate Events of 1998

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence; Govindaraju, Ravi C.; Atlas, Robert (Technical Monitor)

2002-01-01

The new stretched-grid design with multiple (four) areas of interest, one at each global quadrant, is implemented into both a stretched-grid GCM (general circulation model) and a stretched-grid data assimilation system (DAS). The four areas of interest include: the U.S./Northern Mexico, the El Nino area/Central South America, India/China, and the Eastern Indian Ocean/Australia. Both the stretched-grid GCM and DAS annual (November 1997 through December 1998) integrations are performed with 50 km regional resolution. The efficient regional down-scaling to mesoscales is obtained for each of the four areas of interest while the consistent interactions between regional and global scales and the high quality of global circulation, are preserved. This is the advantage of the stretched-grid approach. The global variable resolution DAS incorporating the stretched-grid GCM has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The anomalous regional climate events of 1998 that occurred over the U.S., Mexico, South America, China, India, African Sahel, and Australia are investigated in both simulation and data assimilation modes. Tree assimilated products are also used, along with gauge precipitation data, for validating the simulation results. The obtained results show that the stretched-grid GCM and DAS are capable of producing realistic high quality simulated and assimilated products at mesoscale resolution for regional climate studies and applications.

River discharge estimation from synthetic SWOT-type observations using variational data assimilation and the full Saint-Venant hydraulic model

NASA Astrophysics Data System (ADS)

Oubanas, Hind; Gejadze, Igor; Malaterre, Pierre-Olivier; Mercier, Franck

2018-04-01

The upcoming Surface Water and Ocean Topography satellite mission, to be launched in 2021, will measure river water surface elevation, slope and width, with an unprecedented level of accuracy for a remote sensing tool. This work investigates the river discharge estimation from synthetic SWOT observations, in the presence of strong uncertainties in the model inputs, i.e. the river bathymetry and bed roughness. The estimation problem is solved by a novel variant of the standard variational data assimilation, the '4D-Var' method, involving the full Saint-Venant 1.5D-network hydraulic model SIC2. The assimilation scheme simultaneously estimates the discharge, bed elevation and bed roughness coefficient and is designed to assimilate both satellite and in situ measurements. The method is tested on a 50 km-long reach of the Garonne River during a five-month period of the year 2010, characterized by multiple flooding events. First, the impact of the sampling frequency on discharge estimation is investigated. Secondly, discharge as well as the spatially distributed bed elevation and bed roughness coefficient are determined simultaneously. Results demonstrate feasibility and efficiency of the chosen combination of the estimation method and of the hydraulic model. Assimilation of the SWOT data results into an accurate estimation of the discharge at observation times, and a local improvement in the bed level and bed roughness coefficient. However, the latter estimates are not generally usable for different independent experiments.

Impact of using scatterometer and altimeter data on storm surge forecasting

NASA Astrophysics Data System (ADS)

Bajo, Marco; De Biasio, Francesco; Umgiesser, Georg; Vignudelli, Stefano; Zecchetto, Stefano

2017-05-01

Satellite data are rarely used in storm surge models because of the lack of established methodologies. Nevertheless, they can provide useful information on surface wind and sea level, which can potentially improve the forecast. In this paper satellite wind data are used to correct the bias of wind originating from a global atmospheric model, while satellite sea level data are used to improve the initial conditions of the model simulations. In a first step, the capability of global winds (biased and unbiased) to adequately force a storm surge model are assessed against that of a high resolution local wind. Then, the added value of direct assimilation of satellite altimeter data in the storm surge model is tested. Eleven storm surge events, recorded in Venice from 2008 to 2012, are simulated using different configurations of wind forcing and altimeter data assimilation. Focusing on the maximum surge peak, results show that the relative error, averaged over the eleven cases considered, decreases from 13% to 7%, using both the unbiased wind and assimilating the altimeter data, while, if the high resolution local wind is used to force the hydrodynamic model, the altimeter data assimilation reduces the error from 9% to 6%. Yet, the overall capabilities in reproducing the surge in the first day of forecast, measured by the correlation and by the rms error, improve only with the use of the unbiased global wind and not with the use of high resolution local wind and altimeter data assimilation.

Automated life-detection experiments for the Viking mission to Mars

NASA Technical Reports Server (NTRS)

Klein, H. P.

1974-01-01

As part of the Viking mission to Mars in 1975, an automated set of instruments is being built to test for the presence of metabolizing organisms on that planet. Three separate modules are combined in this instrument so that samples of the Martian surface can be subjected to a broad array of experimental conditions so as to measure biological activity. The first, the Pyrolytic Release Module, will expose surface samples to a mixture of C-14O and C-14O2 in the presence of Martian atmosphere and a light source that simulates the Martian visible spectrum. The assay system is designed to determine the extent of assimilation of CO or CO2 into organic compounds. The Gas Exchange Module will incubate surface samples in a humidified CO2 atmosphere. At specified times, portions of the incubation atmosphere will be analyzed by gas chromatography to detect the release or uptake of CO2 and several additional gases. The Label Release Module will incubate surface samples with a dilute aqueous solution of simple radioactive organic substrates in Martian atmosphere, and the gas phase will be monitored continuously for the release of labeled CO2.

Design of a New Glutamine-Fipronil Conjugate with α-Amino Acid Function and its Uptake by A. thaliana Lysine Histidine Transporter 1 ( AtLHT1).

PubMed

Jiang, Xunyuan; Xie, Yun; Ren, Zhanfu; Ganeteg, Ulrika; Lin, Fei; Zhao, Chen; Xu, Hanhong

2018-06-26

Creating novel pesticides with phloem-mobility is essential for controlling insects in vascular tissue and root, and conjugating existing pesticides with amino acid is an effective approach. In order to obtain highly phloem-mobile candidate for efficient pesticide, an electro-neutral L-glutamine-fipronil conjugate (L-GlnF) retaining α-amino acid function was designed and synthesized to fit the substrate specificity of amino acid transporter. Cotyledon uptake and phloem loading tests with Ricinus communis have verified that L-GlnF was phloem mobile, and its phloem mobility was higher than its enantiomer D-GlnF and other previously reported amino acid-fipronil conjugates. Inhibition experiments then suggested that the uptake of L-GlnF was, at least partially, mediated by active transport mechanism. This inference was further strengthened by assimilation experiments with Xenopus oocytes and genetically modified Arabidopsis thaliana, which showed direct correlation between the uptake of L-GlnF and expression of amino acid transporter AtLHT1. Thus, conjugation with L-Gln appears to be a potential strategy to ensure the uptake of pesticides via endogenous amino acid transport system.

Biofouling reduction in recirculating cooling systems through biofiltration of process water.

PubMed

Meesters, K P H; Van Groenestijn, J W; Gerritse, J

2003-02-01

Biofouling is a serious problem in industrial recirculating cooling systems. It damages equipment, through biocorrosion, and causes clogging and increased energy consumption, through decreased heat transfer. In this research a fixed-bed biofilter was developed which removed assimilable organic carbon (AOC) from process water, thus limiting the major substrate for the growth of biofouling. The biofilter was tested in a laboratory model recirculating cooling water system, including a heat exchanger and a cooling tower. A second identical model system without a biofilter served as a reference. Both installations were challenged with organic carbon (sucrose and yeast extract) to provoke biofouling. The biofilter improved the quality of the recirculating cooling water by reducing the AOC content, the ATP concentration, bacterial numbers (30-40 fold) and the turbidity (OD660). The process of biofouling in the heat exchangers, the process water pipelines and the cooling towers, was monitored by protein increase, heat transfer resistance, and chlorine demanded for maintenance. This revealed that biofouling was lower in the system with the biofilter compared to the reference installation. It was concluded that AOC removal through biofiltration provides an attractive, environmental-friendly means to reduce biofouling in industrial cooling systems.

Snow multivariable data assimilation for hydrological predictions in mountain areas

NASA Astrophysics Data System (ADS)

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-based and remotely sensed data of different snow-related variables (snow albedo and surface temperature, Snow Water Equivalent from passive microwave sensors and Snow Cover Area). SMASH performance was evaluated in the period June 2012 - December 2013 at the meteorological station of Torgnon (Tellinod, 2 160 msl), located in Aosta Valley, a mountain region in northwestern Italy. The EnKF algorithm was firstly tested by assimilating several ground-based measurements: snow depth, land surface temperature, snow density and albedo. The assimilation of snow observed data revealed an overall considerable enhancement of model predictions with respect to the open loop experiments. A first attempt to integrate also remote sensed information was performed by assimilating the Land Surface Temperature (LST) from METEOSAT Second Generation (MSG), leading to good results. The analysis allowed identifying the snow depth and the snowpack surface temperature as the most impacting variables in the assimilation process. In order to pinpoint an optimal number of ensemble instances, SMASH performances were also quantitatively evaluated by varying the instances amount. Furthermore, the impact of the data assimilation frequency was analyzed by varying the assimilation time step (3h, 6h, 12h, 24h).

Flow-through SIP - A novel stable isotope probing approach limiting cross-feeding

NASA Astrophysics Data System (ADS)

Mooshammer, Maria; Kitzinger, Katharina; Schintlmeister, Arno; Kjedal, Henrik; Nielsen, Jeppe Lund; Nielsen, Per; Wagner, Michael

2017-04-01

Stable isotope probing (SIP) is a widely applied tool to link specific microbial populations to metabolic processes in the environment without the prerequisite of cultivation, which has greatly advanced our understanding of the role of microorganisms in biogeochemical cycling. SIP relies on tracing specific isotopically labeled substrates (e.g., 13C, 15N, 18O) into cellular biomarkers, such as DNA, RNA or phospholipid fatty acids, and is considered to be a robust technique to identify microbial populations that assimilate the labeled substrate. However, cross-feeding can occur when labeled metabolites are released from a primary consumer and then used by other microorganisms. This leads to erroneous identification of organisms that are not directly responsible for the process of interest, but are rather connected to primary consumers via a microbial food web. Here, we introduce a new approach that has the potential to eliminate the effect of cross-feeding in SIP studies and can thus also be used to distinguish primary consumers from other members of microbial food webs. In this approach, a monolayer of microbial cells are placed on a filter membrane, and labeled substrates are supplied by a continuous flow. By means of flow-through, labeled metabolites and degradation products are constantly removed, preventing secondary consumption of the substrate. We present results from a proof-of-concept experiment using nitrifiers from activated sludge as model system, in which we used fluorescence in situ hybridization (FISH) with rRNA-targeted oligonucleotide probes for identification of nitrifiers in combination with nanoscale secondary ion mass spectrometry (NanoSIMS) for visualization of isotope incorporation at the single-cell level. Our results show that flow-through SIP is a promising approach to significantly reduce cross-feeding and secondary substrate consumption in SIP experiments.

Assimilation of SMOS brightness temperatures in the ECMWF EKF for the analysis of soil moisture

NASA Astrophysics Data System (ADS)

Munoz-Sabater, Joaquin

2012-07-01

Since November 2nd 2009, the European Centre for Medium-Range Weather Forecasts (ECMWF) has being monitoring, in Near Real Time (NRT), L-band brightness temperatures measured by the Soil Moisture and Ocean Salinity (SMOS) satellite mission of the European Space Agency (ESA). The main objective of the monitoring suite for SMOS data is to systematically monitor the difference between SMOS observed brightness temperatures and the corresponding model equivalent simulated by the Community Microwave Emission Model (CMEM), the so-called first guess departures. This is a crucial step, as first guess departures is the quantity used in the analysis. The ultimate goal is to investigate how the assimilation of SMOS brightness temperatures over land improves the weather forecast skill, through a more accurate initialization of the global soil moisture state. In this presentation, some significant results from the activities preparing for the assimilation of SMOS data are shown. Among these activities, an effective data thinning strategy, a practical approach to reduce noise from the observed brightness temperatures and a bias correction scheme are of special interest. Firstly, SMOS data needs to be significantly thinned as the data volume delivered for a single orbit is too large for the current operational capabilities in any Numerical Weather Prediction system. Different thinning strategies have been analysed and tested. The most suitable one is the assimilation of SMOS brightness temperatures which match the ECMWF T511 (~40 km) reduced Gaussian Grid. Secondly, SMOS observational noise is reduced significantly by averaging the data in angular bins. In addition, this methodology contributes to further thinning of the SMOS data before the analysis. Finally, a bias correction scheme based on a CDF matching is applied to the observations to ensure an unbiased dataset ready for assimilation in the ECMWF surface analysis system. The current ECMWF operational soil moisture analysis system is based on a point-wise Extended Kalman Filter (EKF). This system assimilates proxy surface observations, i.e., 2 m air temperature and relative humidity to analyse the soil moisture state. Recent developments have also made it possible to assimilate remote sensing data coming from active and passive instruments. In particular, the ECMWF EKF can also assimilate data from the Advanced Scatterometer (ASCAT) onboard METOP-A and, more recently, from SMOS brightness temperatures observations. The first preliminary assimilation results will be shown. The analysis fields will be evaluated through comparison to in-situ data from different regions.

Assimilation of sea ice concentration data in the Arctic via DART/CICE5 in the CESM1

NASA Astrophysics Data System (ADS)

Zhang, Y.; Bitz, C. M.; Anderson, J. L.; Collins, N.; Hendricks, J.; Hoar, T. J.; Raeder, K.

2016-12-01

Arctic sea ice cover has been experiencing significant reduction in the past few decades. Climate models predict that the Arctic Ocean may be ice-free in late summer within a few decades. Better sea ice prediction is crucial for regional and global climate prediction that are vital to human activities such as maritime shipping and subsistence hunting, as well as wildlife protection as animals face habitat loss. The physical processes involved with the persistence and re-emergence of sea ice cover are found to extend the predictability of sea ice concentration (SIC) and thickness at the regional scale up to several years. This motivates us to investigate sea ice predictability stemming from initial values of the sea ice cover. Data assimilation is a useful technique to combine observations and model forecasts to reconstruct the states of sea ice in the past and provide more accurate initial conditions for sea ice prediction. This work links the most recent version of the Los Alamos sea ice model (CICE5) within the Community Earth System Model version 1.5 (CESM1.5) and the Data Assimilation Research Testbed (DART). The linked DART/CICE5 is ideal to assimilate multi-scale and multivariate sea ice observations using an ensemble Kalman filter (EnKF). The study is focused on the assimilation of SIC data that impact SIC, sea ice thickness, and snow thickness. The ensemble sea ice model states are constructed by introducing uncertainties in atmospheric forcing and key model parameters. The ensemble atmospheric forcing is a reanalysis product generated with DART and the Community Atmosphere Model (CAM). We also perturb two model parameters that are found to contribute significantly to the model uncertainty in previous studies. This study applies perfect model observing system simulation experiments (OSSEs) to investigate data assimilation algorithms and post-processing methods. One of the ensemble members of a CICE5 free run is chosen as the truth. Daily synthetic observations are obtained by adding 15% random noise to the truth. Experiments assimilating the synthetic observations are then conducted to test the effectiveness of different data assimilation algorithms (e.g., localization and inflation) and post-processing methods (e.g., how to distribute the total increment of SIC into each ice thickness category).

O the Development and Use of Four-Dimensional Data Assimilation in Limited-Area Mesoscale Models Used for Meteorological Analysis.

NASA Astrophysics Data System (ADS)

Stauffer, David R.

1990-01-01

The application of dynamic relationships to the analysis problem for the atmosphere is extended to use a full-physics limited-area mesoscale model as the dynamic constraint. A four-dimensional data assimilation (FDDA) scheme based on Newtonian relaxation or "nudging" is developed and evaluated in the Penn State/National Center for Atmospheric Research (PSU/NCAR) mesoscale model, which is used here as a dynamic-analysis tool. The thesis is to determine what assimilation strategies and what meterological fields (mass, wind or both) have the greatest positive impact on the 72-h numerical simulations (dynamic analyses) of two mid-latitude, real-data cases. The basic FDDA methodology is tested in a 10-layer version of the model with a bulk-aerodynamic (single-layer) representation of the planetary boundary layer (PBL), and refined in a 15-layer version of the model by considering the effects of data assimilation within a multi-layer PBL scheme. As designed, the model solution can be relaxed toward either gridded analyses ("analysis nudging"), or toward the actual observations ("obs nudging"). The data used for assimilation include standard 12-hourly rawinsonde data, and also 3-hourly mesoalpha-scale surface data which are applied within the model's multi-layer PBL. Continuous assimilation of standard-resolution rawinsonde data into the 10-layer model successfully reduced large-scale amplitude and phase errors while the model realistically simulated mesoscale structures poorly defined or absent in the rawinsonde analyses and in the model simulations without FDDA. Nudging the model fields directly toward the rawinsonde observations generally produced results comparable to nudging toward gridded analyses. This obs -nudging technique is especially attractive for the assimilation of high-frequency, asynoptic data. Assimilation of 3-hourly surface wind and moisture data into the 15-layer FDDA system was most effective for improving the simulated precipitation fields because a significant portion of the vertically integrated moisture convergence often occurs in the PBL. Overall, the best dynamic analyses for the PBL, mass, wind and precipitation fields were obtained by nudging toward analyses of rawinsonde wind, temperature and moisture (the latter uses a weaker nudging coefficient) above the model PBL and toward analyses of surface-layer wind and moisture within the model PBL.

Snow water equivalent monitoring retrieved by assimilating passive microwave observations in a coupled snowpack evolution and microwave emission models over North-Eastern Canada

NASA Astrophysics Data System (ADS)

Royer, A.; Larue, F.; De Sève, D.; Roy, A.; Vionnet, V.; Picard, G.; Cosme, E.

2017-12-01

Over northern snow-dominated basins, the snow water equivalent (SWE) is of primary interest for spring streamflow forecasting. SWE retrievals from satellite data are still not well resolved, in particular from microwave (MW) measurements, the only type of data sensible to snow mass. Also, the use of snowpack models is challenging due to the large uncertainties in meteorological input forcings. This project aims to improve SWE prediction by assimilation of satellite brightness temperature (TB), without any ground-based observations. The proposed approach is the coupling of a detailed multilayer snowpack model (Crocus) with a MW snow emission model (DMRT-ML). The assimilation scheme is a Sequential Importance Resampling Particle filter, through ensembles of perturbed meteorological forcings according to their respective uncertainties. Crocus simulations driven by operational meteorological forecasts from the Canadian Global Environmental Multiscale model at 10 km spatial resolution were compared to continuous daily SWE measurements over Québec, North-Eastern Canada (56° - 45°N). The results show a mean bias of the maximum SWE overestimated by 16% with variations up to +32%. This observed large variability could lead to dramatic consequences on spring flood forecasts. Results of Crocus-DMRT-ML coupling compared to surface-based TB measurements (at 11, 19 and 37 GHz) show that the Crocus snowpack microstructure described by sticky hard spheres within DMRT has to be scaled by a snow stickiness of 0.18, significantly reducing the overall RMSE of simulated TBs. The ability of assimilation of daily TBs to correct the simulated SWE is first presented through twin experiments with synthetic data, and then with AMSR-2 satellite time series of TBs along the winter taking into account atmospheric and forest canopy interferences (absorption and emission). The differences between TBs at 19-37 GHz and at 11-19 GHz, in vertical polarization, were assimilated. This assimilation test with synthetic data gives a SWE RMSE reduced by a factor of 2 after assimilation. Assimilation of AMSR-2 TBs shows improvement in SWE retrievals compared to continuous in-situ SWE measurements. The accuracy is discussed as a function of boreal forest density and LAI (MODIS-based data), having significant effects.

Lidar data assimilation for improved analyses of volcanic aerosol events

NASA Astrophysics Data System (ADS)

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 data in a variational data assimilation algorithm. The implemented method is tested by the assimilation of CALIPSO attenuated backscatter data that were taken during the eruption of the Eyjafjallajökull volcano in April 2010. It turned out that the implemented module is fully capable to integrate unexpected aerosol events in an automatic way into reasonable analyses. The estimations of the aerosol mass concentrations showed promising properties for the application of observations that are taken by lidar systems with both, higher and lower sophistication than CALIOP.

Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

NASA Astrophysics Data System (ADS)

Albergel, Clément; Munier, Simon; Leroux, Delphine Jennifer; Dewaele, Hélène; Fairbairn, David; Lavinia Barbu, Alina; Gelati, Emiliano; Dorigo, Wouter; Faroux, Stéphanie; Meurey, Catherine; Le Moigne, Patrick; Decharme, Bertrand; Mahfouf, Jean-Francois; Calvet, Jean-Christophe

2017-10-01

In this study, a global land data assimilation system (LDAS-Monde) is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the interactions between soil-biosphere-atmosphere (ISBA, Interactions between Soil, Biosphere and Atmosphere) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. SSM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF), which uses finite differences from perturbed simulations to generate flow dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 to 100 cm depth). A sensitivity test of the Jacobians over 2000-2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and SSM have an impact on the different control variables. From the assimilation of SSM, the LDAS is more effective in modifying soil moisture (SM) from the top layers of soil, as model sensitivity to SSM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 to 60 cm). The assimilation is more efficient in summer and autumn than in winter and spring. Results shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. A comprehensive evaluation of the assimilation impact is conducted using (i) agricultural statistics over France, (ii) river discharge observations, (iii) satellite-derived estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project and (iv) spatially gridded observation-based estimates of upscaled gross primary production and evapotranspiration from the FLUXNET network. Comparisons with those four datasets highlight neutral to highly positive improvement.

Assimilation of neural network soil moisture in land surface models

NASA Astrophysics Data System (ADS)

Rodriguez-Fernandez, Nemesio; de Rosnay, Patricia; Albergel, Clement; Aires, Filipe; Prigent, Catherine; Kerr, Yann; Richaume, Philippe; Muñoz-Sabater, Joaquin; Drusch, Matthias

2017-04-01

In this study a set of land surface data assimilation (DA) experiments making use of satellite derived soil moisture (SM) are presented. These experiments have two objectives: (1) to test the information content of satellite remote sensing of soil moisture for numerical weather prediction (NWP) models, and (2) to test a simplified assimilation of these data through the use of a Neural Network (NN) retrieval. Advanced Scatterometer (ASCAT) and Soil Moisture and Ocean Salinity (SMOS) data were used. The SMOS soil moisture dataset was obtained specifically for this project training a NN using SMOS brightness temperatures as input and using as reference for the training European Centre for Medium-Range Weather Forecasts (ECMWF) H-TESSEL SM fields. In this way, the SMOS NN SM dataset has a similar climatology to that of the model and it does not present a global bias with respect to the model. The DA experiments are computed using a surface-only Land Data Assimilation System (so-LDAS) based on the HTESSEL land surface model. This system is very computationally efficient and allows to perform long surface assimilation experiments (one whole year, 2012). SMOS NN SM DA experiments are compared to ASCAT SM DA experiments. In both cases, experiments with and without 2 m air temperature and relative humidity DA are discussed using different observation errors for the ASCAT and SMOS datasets. Seasonal, geographical and soil-depth-related differences between the results of those experiments are presented and discussed. The different SM analysed fields are evaluated against a large number of in situ measurements of SM. On average, the SM analysis gives in general similar results to the model open loop with no assimilation even if significant differences can be seen for specific sites with in situ measurements. The sensitivity to observation errors to the SM dataset slightly differs depending on the networks of in situ measurements, however it is relatively low for the tests conducted here. Finally, the effect of the soil moisture analysis on the NWP is evaluated comparing experiments for different configurations of the system, with and without (Open Loop) soil moisture data assimilation. ssimilation of ASCAT soil moisture improves the forecast in the tropics and adds information with respect to the near surface conventional observations. In contrast, SMOS degrades the forecast in the Tropics in July-September. In the Southern hemisphere ASCAT degrades the forecast in July-September both alone and using 2m air temperature and relative humidity. On the other hand, experiments using SMOS (even without screen level variables) improve the forecast for all the seasons, in particular, in July-December. In the northern hemisphere both with ASCAT and SMOS, the experiments using 2m air temperature and relative humidity improve the forecast in April-September. SMOS alone has a significant positive effect in July-September for experiments with low observation error. Maps of the forecast skill with respect to the open loop experiment show that SMOS improves the forecast in North America and to a lesser extent in northern Asia for up to 72 hours.

Lifetime Segmented Assimilation Trajectories and Health Outcomes in Latino and Other Community Residents

PubMed Central

Marsiglia, Flavio F.; Kulis, Stephen; Kellison, Joshua G.

2010-01-01

Objectives. Under an ecodevelopmental framework, we examined lifetime segmented assimilation trajectories (diverging assimilation pathways influenced by prior life conditions) and related them to quality-of-life indicators in a diverse sample of 258 men in the Pheonix, AZ, metropolitan area. Methods. We used a growth mixture model analysis of lifetime changes in socioeconomic status, and used acculturation to identify distinct lifetime segmented assimilation trajectory groups, which we compared on life satisfaction, exercise, and dietary behaviors. We hypothesized that lifetime assimilation change toward mainstream American culture (upward assimilation) would be associated with favorable health outcomes, and downward assimilation change with unfavorable health outcomes. Results. A growth mixture model latent class analysis identified 4 distinct assimilation trajectory groups. In partial support of the study hypotheses, the extreme upward assimilation trajectory group (the most successful of the assimilation pathways) exhibited the highest life satisfaction and the lowest frequency of unhealthy food consumption. Conclusions. Upward segmented assimilation is associated in adulthood with certain positive health outcomes. This may be the first study to model upward and downward lifetime segmented assimilation trajectories, and to associate these with life satisfaction, exercise, and dietary behaviors. PMID:20167890

Integration of Carbon, Nitrogen, and Oxygen Metabolism in Escherichia coli--Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rabinowitz, Joshua D; Wingreen, Ned s; Rabitz, Herschel A

2012-10-22

A key challenge for living systems is balancing utilization of multiple elemental nutrients, such as carbon, nitrogen, and oxygen, whose availability is subject to environmental fluctuations. As growth can be limited by the scarcity of any one nutrient, the rate at which each nutrient is assimilated must be sensitive not only to its own availability, but also to that of other nutrients. Remarkably, across diverse nutrient conditions, E. coli grows nearly optimally, balancing effectively the conversion of carbon into energy versus biomass. To investigate the link between the metabolism of different nutrients, we quantified metabolic responses to nutrient perturbations usingmore » LC-MS based metabolomics and built differential equation models that bridge multiple nutrient systems. We discovered that the carbonaceous substrate of nitrogen assimilation, -ketoglutarate, directly inhibits glucose uptake and that the upstream glycolytic metabolite, fructose-1,6-bisphosphate, ultrasensitively regulates anaplerosis to allow rapid adaptation to changing carbon availability. We also showed that NADH controls the metabolic response to changing oxygen levels. Our findings support a general mechanism for nutrient integration: limitation for a nutrient other than carbon leads to build-up of the most closely related product of carbon metabolism, which in turn feedback inhibits further carbon uptake.« less

Documenting Chemical Assimilation in a Basaltic Lava Flow

NASA Technical Reports Server (NTRS)

Young, K. E.; Bleacher, J. E.; Needham, D. H.; Evans, C.; Whelley, P. L.; Scheidt, S.; Williams, D.; Rogers, A. D.; Glotch, T.

2017-01-01

Lava channels are features seen throughout the inner Solar System, including on Earth, the Moon, and Mars. Flow emplacement is therefore a crucial process in the shaping of planetary surfaces. Many studies have investigated the dynamics of lava flow emplacement, both on Earth and on the Moon [1,2,3] but none have focused on how the compositional and structural characteristics of the substrate over which a flow was emplaced influenced its final flow morphology. Within the length of one flow, it is common for flows to change in morphology, a quality linked to lava rheology (a function of multiple factors including viscosity, temperature, composition, etc.). The relationship between rheology and temperature has been well-studied [4,5,6] but less is understood about the relationship between a pre-flow terrain's chemistry and how the interaction between this flow and the new flow might affect lava rheology and therefore emplacement dynamics. Lava erosion. Through visual observations of active terrestrial flows, lava erosion has been well-documented [i.e. 7,8,9,10]. Lava erosion is the process by which flow composition is altered as the active lava melts and assimilates the pre-flow terrain over which it moves. Though this process has been observed, there is only one instance of where it was been geochemically documented.

Improvement on D-xylose to Xylitol Biotransformation by Candida guilliermondii Using Cells Permeabilized with Triton X-100 and Selected Process Conditions.

PubMed

Cortez, Daniela Vieira; Mussatto, Solange I; Roberto, Inês Conceição

2016-11-01

Cells of Candida guilliermondii permeabilized with Triton X-100 were able to efficiently produce xylitol from a medium composed only by D-xylose and MgCl 2 ·6H 2 O in potassium phosphate buffer, at 35 °C and pH 6.5. Under these conditions, the results were similar to those obtained when cofactor and co-substrate or nutrients were added to the medium (about 95 % D-xylose was assimilated producing 42 g/L of xylitol, corresponding to 0.80 g/g yield and 2.65 g/L h volumetric productivity). Furthermore, the permeabilized cells kept the D-xylose assimilation in about 90 % and the xylitol production in approx. 40 g/L during three bioconversion cycles of 16 h each. These values are highly relevant when compared to others reported in the literature using enzyme technology and fermentative process, thereby demonstrating the effectiveness of the proposed method. The present study reveals that the use of permeabilized cells is an interesting alternative to obtain high xylitol productivity using low cost medium formulation. This approach may allow the future development of xylitol production from xylose present in lignocellulosic biomass, with additional potential for implementation in biorefinery strategies.

Sea Ice in the NCEP Seasonal Forecast System

NASA Astrophysics Data System (ADS)

Wu, X.; Saha, S.; Grumbine, R. W.; Bailey, D. A.; Carton, J.; Penny, S. G.

2017-12-01

Sea ice is known to play a significant role in the global climate system. For a weather or climate forecast system (CFS), it is important that the realistic distribution of sea ice is represented. Sea ice prediction is challenging; sea ice can form or melt, it can move with wind and/or ocean current; sea ice interacts with both the air above and ocean underneath, it influences by, and has impact on the air and ocean conditions. NCEP has developed coupled CFS (version 2, CFSv2) and also carried out CFS reanalysis (CFSR), which includes a coupled model with the NCEP global forecast system, a land model, an ocean model (GFDL MOM4), and a sea ice model. In this work, we present the NCEP coupled model, the CFSv2 sea ice component that includes a dynamic thermodynamic sea ice model and a simple "assimilation" scheme, how sea ice has been assimilated in CFSR, the characteristics of the sea ice from CFSR and CFSv2, and the improvements of sea ice needed for future seasonal prediction system, part of the Unified Global Coupled System (UGCS), which is being developed and under testing, including sea ice data assimilation with the Local Ensemble Transform Kalman Filter (LETKF). Preliminary results from the UGCS testing will also be presented.

A Microwave Radiance Assimilation Study for a Tundra Snowpack

NASA Technical Reports Server (NTRS)

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?

Towards a satellite driven land surface model using SURFEX modelling platform Offline Data Assimilation: an assessment of the method over Europe and the Mediterranean basin

NASA Astrophysics Data System (ADS)

Albergel, Clément; Munier, Simon; Leroux, Delphine; Fairbairn, David; Dorigo, Wouter; Decharme, Bertrand; Calvet, Jean-Christophe

2017-04-01

Modelling platforms including Land Surface Models (LSMs), forced by gridded atmospheric variables and coupled to river routing models are necessary to increase our understanding of the terrestrial water cycle. These LSMs need to simulate biogeophysical variables like Surface and Root Zone Soil Moisture (SSM, RZSM), Leaf Area Index (LAI) in a way that is fully consistent with the representation of surface/energy fluxes and river discharge simulations. Global SSM and LAI products are now operationally available from spaceborne instruments and they can be used to constrain LSMs through Data Assimilation (DA) techniques. In this study, an offline data assimilation system implemented in Météo-France's modelling platform (SURFEX) is tested over Europe and the Mediterranean basin to increase prediction accuracy for land surface variables. The resulting Land Data Assimilation System (LDAS) makes use of a simplified Extended Kalman Filter (SEKF). It is able to ingests information from satellite derived (i) SSM from the latest version of the ESA Climate Change Initiative as well as (ii) LAI from the Copernicus GLS project to constrain the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (ISBA-CTRIP). ERA-Interim observations based atmospheric forcing with precipitations corrected from Global Precipitation Climatology Centre observations (GPCC) is used to force ISBA-CTRIP at a resolution of 0.5 degree over 2000-2015. The model sensitivity to the assimilated observations is presented and a set of statistical diagnostics used to evaluate the impact of assimilating SSM and LAI on different model biogeophysical variables are provided. It is demonstrated that the assimilation scheme works effectively. The SEKF is able to extract useful information from the data signal at the grid scale and distribute the RZSM and LAI increments throughout the model impacting soil moisture, terrestrial vegetation and water cycle, surface carbon and energy fluxes.

Evaluation and Improvement of Polar WRF simulations using the observed atmospheric profiles in the Arctic seasonal ice zone

NASA Astrophysics Data System (ADS)

Liu, Z.; Schweiger, A. J. B.

2016-12-01

We use the Polar Weather Research and Forecasting (WRF) model to simulate atmospheric conditions during the Seasonal Ice Zone Reconnaissance Survey (SIZRS) over the Beaufort Sea in the summer since 2013. With the 119 SIZRS dropsondes in the18 cross sections along the 150W and 140W longitude lines, we evaluate the performance of WRF simulations and two forcing data sets, the ERA-Interim reanalysis and the Global Forecast System (GFS) analysis, and explore the improvement of the Polar WRF performance when the dropsonde data are assimilated using observation nudging. Polar WRF, ERA-Interim, and GFS can reproduce the general features of the observed mean atmospheric profiles, such as low-level temperature inversion, low-level jet (LLJ) and specific humidity inversion. The Polar WRF significantly improves the mean LLJ, with a lower and stronger jet and a larger turning angle than the forcing, which is likely related to the lower values of the boundary layer diffusion in WRF than in the global models such as ECMWF and GFS. The Polar WRF simulated relative humidity closely resembles the forcing datasets while having large biases compared to observations. This suggests that the performance of Polar WRF and its forecasts in this region are limited by the quality of the forcing dataset and that the assimilation of more and better-calibrated observations, such as humidity data, is critical for their improvement. We investigate the potential of assimilating the SIZRS dropsonde dataset in improving the weather forecast over the Beaufort Sea. A simple local nudging approach is adopted. Along SIZRS flight cross sections, a set of Polar WRF simulations are performed with varying number of variables and dropsonde profiles assimilated. Different model physics are tested to examine the sensitivity of different aspects of model physics, such as boundary layer schemes, cloud microphysics, and radiation parameterization, to data assimilation. The comparison of the Polar WRF runs with assimilation and the runs without assimilation demonstrates the importance of SIZRS dropsonde data to the improvement of atmospheric analysis and reanalysis such as GFS and ERA-Interim, and consequently to the improvement of weather forecast in this region.

The ASSET intercomparison of stratosphere and lower mesosphere humidity analyses

NASA Astrophysics Data System (ADS)

Thornton, H. E.; Jackson, D. R.; Bekki, S.; Bormann, N.; Errera, Q.; Geer, A. J.; Lahoz, W. A.; Rharmili, S.

2009-02-01

This paper presents results from the first detailed intercomparison of stratosphere-lower mesosphere water vapour analyses; it builds on earlier results from the EU funded framework V "Assimilation of ENVISAT Data" (ASSET) project. Stratospheric water vapour plays an important role in many key atmospheric processes and therefore an improved understanding of its daily variability is desirable. With the availability of high resolution, good quality Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) water vapour profiles, the ability of four different atmospheric models to assimilate these data is tested. MIPAS data have been assimilated over September 2003 into the models of the European Centre for Medium Range Weather Forecasts (ECMWF), the Belgian Institute for Space and Aeronomy (BIRA-IASB), the French Service d'Aéronomie (SA-IPSL) and the UK Met Office. The resultant middle atmosphere humidity analyses are compared against independent satellite data from the Halogen Occultation Experiment (HALOE), the Polar Ozone and Aerosol Measurement (POAM III) and the Stratospheric Aerosol and Gas Experiment (SAGE II). The MIPAS water vapour profiles are generally well assimilated in the ECMWF, BIRA-IASB and SA systems, producing stratosphere-mesosphere water vapour fields where the main features compare favourably with the independent observations. However, the models are less capable of assimilating the MIPAS data where water vapour values are locally extreme or in regions of strong humidity gradients, such as the southern hemisphere lower stratosphere polar vortex. Differences in the analyses can be attributed to the choice of humidity control variable, how the background error covariance matrix is generated, the model resolution and its complexity, the degree of quality control of the observations and the use of observations near the model boundaries. Due to the poor performance of the Met Office analyses the results are not included in the intercomparison, but are discussed separately. The Met Office results highlight the pitfalls in humidity assimilation, and provide lessons that should be learnt by developers of stratospheric humidity assimilation systems. In particular, they underline the importance of the background error covariances in generating a realistic troposphere to mesosphere water vapour analysis.

Streamflow forecasting and data assimilation: bias in precipitation, soil moisture states, and groundwater fluxes.

NASA Astrophysics Data System (ADS)

McCreight, J. L.; Gochis, D. J.; Hoar, T.; Dugger, A. L.; Yu, W.

2014-12-01

Uncertainty in precipitation forcing, soil moisture states, and model groundwater fluxes are first-order sources of error in streamflow forecasting. While near-surface estimates of soil moisture are now available from satellite, very few soil moisture observations below 5 cm depth or groundwater discharge estimates are available for operational forecasting. Radar precipitation estimates are subject to large biases, particularly during extreme events (e.g. Steiner et al., 2010) and their correction is not typically available in real-time. Streamflow data, however, are readily available in near-real-time and can be assimilated operationally to help constrain uncertainty in these uncertain states and improve streamflow forecasts. We examine the ability of streamflow observations to diagnose bias in the three most uncertain variables: precipitation forcing, soil moisture states, and groundwater fluxes. We investigate strategies for their subsequent bias correction. These include spinup and calibration strategies with and without the use of data assimilation and the determination of the proper spinup timescales. Global and spatially distributed multipliers on the uncertain states included in the assimilation state vector (e.g. Seo et al., 2003) will also be evaluated. We examine real cases and observing system simulation experiments for both normal and extreme rainfall events. One of our test cases considers the Colorado Front Range flood of September 2013 where the range of disagreement amongst five precipitation estimates spanned a factor of five with only one exhibiting appreciable positive bias (Gochis et al, submitted). Our experiments are conducted using the WRF-Hydro model with the NoahMP land surface component and the data assimilation research testbed (DART). A variety of ensemble data assimilation approaches (filters) are considered. ReferencesGochis, DJ, et al. "The Great Colorado Flood of September 2013" BAMS (Submitted 4-7-14). Seo, DJ, V Koren, and N Cajina. "Real-time variational assimilation of hydrologic and hydrometeorological data into operational hydrologic forecasting." J Hydromet (2003). Steiner, Matthias, JA Smith, SJ Burges, CV Alonso, and RW Darden. "Effect of bias adjustment and rain gauge data quality control on radar rainfall estimation." WRR (1999).

Development of a multi-data assimilation scheme to integrate Bio-Argo floats data with ocean colour satellite data into the CMEMS MFC-Biogeochemistry

NASA Astrophysics Data System (ADS)

Cossarini, Gianpiero; D'Ortenzio, Fabrizio; Mariotti, Laura; Mignot, Alexandre; Salon, Stefano

2017-04-01

The Mediterranean Sea is a very promising site to develop and test the assimilation of Bio-Argo data since 1) the Bio-Argo network is one of the densest of the global ocean, and 2) a consolidate data assimilation framework of biogeochemical variables (3DVAR-BIO, presently based on assimilation of satellite-estimated surface chlorophyll data) already exists within the CMEMS biogeochemical model system for Mediterranean Sea. The MASSIMILI project, granted by the CMEMS Service Evolution initiative, is aimed to develop the assimilation of Bio-Argo Floats data into the CMEMS biogeochemical model system of the Mediterranean Sea, by means of an upgrade of the 3DVAR-BIO scheme. Specific developments of the 3DVAR-BIO scheme focus on the estimate of new operators of the variational decomposition of the background error covariance matrix and on the implementation of the new observation operator specifically for the Bio-Argo float vertical profile data. In particular, a new horizontal covariance operator for chlorophyll, nitrate and oxygen is based on 3D fields of horizontal correlation radius calculated from a long-term reanalysis simulation. A new vertical covariance operator is built on monthly and spatial varying EOF decomposition to account for the spatiotemporal variability of vertical structure of the three variables error covariance. Further, the observation error covariance is a key factor for an effective assimilation of the Bio-Argo data into the model dynamics. The sensitivities of assimilation to the different factors are estimated. First results of the implementation of the new 3DVAR-BIO scheme show the impact of Bio-Argo data on the 3D fields of chlorophyll, nitrate and oxygen. Tuning the length scale factors of horizontal covariance, analysing the sensitivity of the observation error covariance, introducing non-diagonal biogeochemical covariance operator and non-diagonal multi-platform operator (i.e. Bio-Argo and satellite) are crucial future steps for the success of the MASSIMILI project. In our contribute, we will discuss the recent and promising advancements this strategic project has been having in the past year and its potential for the whole operational biogeochemical modelling community.

Numerical sensitivity analysis of a variational data assimilation procedure for cardiac conductivities

NASA Astrophysics Data System (ADS)

Barone, Alessandro; Fenton, Flavio; Veneziani, Alessandro

2017-09-01

An accurate estimation of cardiac conductivities is critical in computational electro-cardiology, yet experimental results in the literature significantly disagree on the values and ratios between longitudinal and tangential coefficients. These are known to have a strong impact on the propagation of potential particularly during defibrillation shocks. Data assimilation is a procedure for merging experimental data and numerical simulations in a rigorous way. In particular, variational data assimilation relies on the least-square minimization of the misfit between simulations and experiments, constrained by the underlying mathematical model, which in this study is represented by the classical Bidomain system, or its common simplification given by the Monodomain problem. Operating on the conductivity tensors as control variables of the minimization, we obtain a parameter estimation procedure. As the theory of this approach currently provides only an existence proof and it is not informative for practical experiments, we present here an extensive numerical simulation campaign to assess practical critical issues such as the size and the location of the measurement sites needed for in silico test cases of potential experimental and realistic settings. This will be finalized with a real validation of the variational data assimilation procedure. Results indicate the presence of lower and upper bounds for the number of sites which guarantee an accurate and minimally redundant parameter estimation, the location of sites being generally non critical for properly designed experiments. An effective combination of parameter estimation based on the Monodomain and Bidomain models is tested for the sake of computational efficiency. Parameter estimation based on the Monodomain equation potentially leads to the accurate computation of the transmembrane potential in real settings.

Developing hydrological monitoring system based on HF radar for islands and reefs in the South China Sea

NASA Astrophysics Data System (ADS)

Li, J.; Shi, P.; Chen, J.; Zhu, Y.; Li, B.

2016-12-01

There are many islands (or reefs) in the South China Sea. The hydrological properties (currents and waves) around the islands are highly spatially variable compared to those of coastal region of mainland, because the shorelines are more complex with much smaller scale, and the topographies are step-shape with a much sharper slope. The currents and waves with high spatial variations may destroy the buildings or engineering on shorelines, or even influence the structural stability of reefs. Therefore, it is necessary to establish monitoring systems to obtain the high-resolution hydrological information. This study propose a plan for developing a hydrological monitoring system based on HF radar on the shoreline of a typical island in the southern South China Sea: firstly, the HF radar are integrated with auxiliary equipment (such as dynamo, fuel tank, air conditioner, communication facilities) in a container to build a whole monitoring platform; synchronously, several buoys are set within the radar visibility for data calibration and validation; and finally, the current and wave observations collected by the HF radar are assimilated with numerical models to obtain long-term and high-precision reanalysis products. To test the feasibility of this plan, our research group has built two HF radar sites at the western coastal region of Guangdong Province. The collected data were used to extract surface current information and assimilated with an ocean model. The results show that the data assimilation can highly improve the surface current simulation, especially for typhoon periods. Continuous data with intervals between 6 and 12 hour are the most suitable for ideal assimilations. On the other hand, the test also reveal that developing similar monitoring system on island environments need advanced radars that have higher resolutions and a better performance for persistent work.

A Decadal Inversion of CO2 Using the Global Eulerian-Lagrangian Coupled Atmospheric Model (GELCA): Sensitivity to the Ground-Based Observation Network

NASA Technical Reports Server (NTRS)

Shirai, T.; Ishizawa, M.; Zhuravlev, R.; Ganshin, A.; Belikov, D.; Saito, M.; Oda, T.; Valsala, V.; Gomez-Pelaez, A. J.; Langenfelds, R.;

Simultaneous glucose and xylose uptake by an acetone/butanol/ethanol producing laboratory Clostridium beijerinckii strain SE-2.

PubMed

Zhang, Jie; Zhu, Wen; Xu, Haipeng; Li, Yan; Hua, Dongliang; Jin, Fuqiang; Gao, Mintian; Zhang, Xiaodong

2016-04-01

Most butanol-producing strains of Clostridium prefer glucose over xylose, leading to a slower butanol production from lignocellulose hydrolysates. It is therefore beneficial to find and use a strain that can simultaneously use both glucose and xylose. Clostridium beijerinckii SE-2 strain assimilated glucose and xylose simultaneously and produced ABE (acetone/butanol/ethanol). The classic diauxic growth behavior was not seen. Similar rates of sugar consumption (4.44 mM glucose h(-1) and 6.66 mM xylose h(-1)) were observed suggesting this strain could use either glucose or xylose as the substrate and it has a similar capability to degrade these two sugars. With different initial glucose:xylose ratios, glucose and xylose were consumed simultaneously at rates roughly proportional to their individual concentrations in the medium, leading to complete utilization of both sugars at the same time. ABE production profiles were similar on different substrates. Transcriptional studies on the effect of glucose and xylose supplementation, however, suggests a clear glucose inhibition on xylose metabolism-related genes is still present.

Stochastic spectral projection of electrochemical thermal model for lithium-ion cell state estimation

NASA Astrophysics Data System (ADS)

Tagade, Piyush; Hariharan, Krishnan S.; Kolake, Subramanya Mayya; Song, Taewon; Oh, Dukjin

2017-03-01

A novel approach for integrating a pseudo-two dimensional electrochemical thermal (P2D-ECT) model and data assimilation algorithm is presented for lithium-ion cell state estimation. This approach refrains from making any simplifications in the P2D-ECT model while making it amenable for online state estimation. Though deterministic, uncertainty in the initial states induces stochasticity in the P2D-ECT model. This stochasticity is resolved by spectrally projecting the stochastic P2D-ECT model on a set of orthogonal multivariate Hermite polynomials. Volume averaging in the stochastic dimensions is proposed for efficient numerical solution of the resultant model. A state estimation framework is developed using a transformation of the orthogonal basis to assimilate the measurables with this system of equations. Effectiveness of the proposed method is first demonstrated by assimilating the cell voltage and temperature data generated using a synthetic test bed. This validated method is used with the experimentally observed cell voltage and temperature data for state estimation at different operating conditions and drive cycle protocols. The results show increased prediction accuracy when the data is assimilated every 30s. High accuracy of the estimated states is exploited to infer temperature dependent behavior of the lithium-ion cell.

Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level Set Transformation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammond, Glenn Edward; Song, Xuehang; Ye, Ming

A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. Themore » spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.« less

Estimation of Turbulent Heat Fluxes by Assimilation of Land Surface Temperature Observations From GOES Satellites Into an Ensemble Kalman Smoother Framework

NASA Astrophysics Data System (ADS)

Xu, Tongren; Bateni, S. M.; Neale, C. M. U.; Auligne, T.; Liu, Shaomin

2018-03-01

In different studies, land surface temperature (LST) observations have been assimilated into the variational data assimilation (VDA) approaches to estimate turbulent heat fluxes. The VDA methods yield accurate turbulent heat fluxes, but they need an adjoint model, which is difficult to derive and code. They also cannot directly calculate the uncertainty of their estimates. To overcome the abovementioned drawbacks, this study assimilates LST data from Geostationary Operational Environmental Satellite into the ensemble Kalman smoother (EnKS) data assimilation system to estimate turbulent heat fluxes. EnKS does not need to derive the adjoint term and directly generates statistical information on the accuracy of its predictions. It uses the heat diffusion equation to simulate LST. EnKS with the state augmentation approach finds the optimal values for the unknown parameters (i.e., evaporative fraction and neutral bulk heat transfer coefficient, CHN) by minimizing the misfit between LST observations from Geostationary Operational Environmental Satellite and LST estimations from the heat diffusion equation. The augmented EnKS scheme is tested over six Ameriflux sites with a wide range of hydrological and vegetative conditions. The results show that EnKS can predict not only the model parameters and turbulent heat fluxes but also their uncertainties over a variety of land surface conditions. Compared to the variational method, EnKS yields suboptimal turbulent heat fluxes. However, suboptimality of EnKS is small, and its results are comparable to those of the VDA method. Overall, EnKS is a feasible and reliable method for estimation of turbulent heat fluxes.

On the assimilation-discrimination relationship in American English adults’ French vowel learning1

PubMed Central

Levy, Erika S.

2009-01-01

A quantitative “cross-language assimilation overlap” method for testing predictions of the Perceptual Assimilation Model (PAM) was implemented to compare results of a discrimination experiment with the listeners’ previously reported assimilation data. The experiment examined discrimination of Parisian French (PF) front rounded vowels ∕y∕ and ∕œ∕. Three groups of American English listeners differing in their French experience (no experience [NoExp], formal experience [ModExp], and extensive formal-plus-immersion experience [HiExp]) performed discrimination of PF ∕y-u∕, ∕y-o∕, ∕œ-o∕, ∕œ-u∕, ∕y-i∕, ∕y-ɛ∕, ∕œ-ɛ∕, ∕œ-i∕, ∕y-œ∕, ∕u-i∕, and ∕a-ɛ∕. Vowels were in bilabial ∕rabVp∕ and alveolar ∕radVt∕ contexts. More errors were found for PF front vs back rounded vowel pairs (16%) than for PF front unrounded vs rounded pairs (2%). Overall, ModExp listeners did not perform more accurately (11% errors) than NoExp listeners (13% errors). Extensive immersion experience, however, was associated with fewer errors (3%) than formal experience alone, although discrimination of PF ∕y-u∕ remained relatively poor (12% errors) for HiExp listeners. More errors occurred on pairs involving front vs back rounded vowels in alveolar context (20% errors) than in bilabial (11% errors). Significant correlations were revealed between listeners’ assimilation overlap scores and their discrimination errors, suggesting that the PAM may be extended to second-language (L2) vowel learning. PMID:19894844

Data assimilation experiments using diffusive back-and-forth nudging for the NEMO ocean model

NASA Astrophysics Data System (ADS)

Ruggiero, G. A.; Ourmières, Y.; Cosme, E.; Blum, J.; Auroux, D.; Verron, J.

2015-04-01

The diffusive back-and-forth nudging (DBFN) is an easy-to-implement iterative data assimilation method based on the well-known nudging method. It consists of a sequence of forward and backward model integrations, within a given time window, both of them using a feedback term to the observations. Therefore, in the DBFN, the nudging asymptotic behaviour is translated into an infinite number of iterations within a bounded time domain. In this method, the backward integration is carried out thanks to what is called backward model, which is basically the forward model with reversed time step sign. To maintain numeral stability, the diffusion terms also have their sign reversed, giving a diffusive character to the algorithm. In this article the DBFN performance to control a primitive equation ocean model is investigated. In this kind of model non-resolved scales are modelled by diffusion operators which dissipate energy that cascade from large to small scales. Thus, in this article, the DBFN approximations and their consequences for the data assimilation system set-up are analysed. Our main result is that the DBFN may provide results which are comparable to those produced by a 4Dvar implementation with a much simpler implementation and a shorter CPU time for convergence. The conducted sensitivity tests show that the 4Dvar profits of long assimilation windows to propagate surface information downwards, and that for the DBFN, it is worth using short assimilation windows to reduce the impact of diffusion-induced errors. Moreover, the DBFN is less sensitive to the first guess than the 4Dvar.

Testing particle filters on convective scale dynamics

NASA Astrophysics Data System (ADS)

Haslehner, Mylene; Craig, George. C.; Janjic, Tijana

2014-05-01

Particle filters have been developed in recent years to deal with highly nonlinear dynamics and non Gaussian error statistics that also characterize data assimilation on convective scales. In this work we explore the use of the efficient particle filter (P.v. Leeuwen, 2011) for convective scale data assimilation application. The method is tested in idealized setting, on two stochastic models. The models were designed to reproduce some of the properties of convection, for example the rapid development and decay of convective clouds. The first model is a simple one-dimensional, discrete state birth-death model of clouds (Craig and Würsch, 2012). For this model, the efficient particle filter that includes nudging the variables shows significant improvement compared to Ensemble Kalman Filter and Sequential Importance Resampling (SIR) particle filter. The success of the combination of nudging and resampling, measured as RMS error with respect to the 'true state', is proportional to the nudging intensity. Significantly, even a very weak nudging intensity brings notable improvement over SIR. The second model is a modified version of a stochastic shallow water model (Würsch and Craig 2013), which contains more realistic dynamical characteristics of convective scale phenomena. Using the efficient particle filter and different combination of observations of the three field variables (wind, water 'height' and rain) allows the particle filter to be evaluated in comparison to a regime where only nudging is used. Sensitivity to the properties of the model error covariance is also considered. Finally, criteria are identified under which the efficient particle filter outperforms nudging alone. References: Craig, G. C. and M. Würsch, 2012: The impact of localization and observation averaging for convective-scale data assimilation in a simple stochastic model. Q. J. R. Meteorol. Soc.,139, 515-523. Van Leeuwen, P. J., 2011: Efficient non-linear data assimilation in geophysical fluid dynamics. - Computers and Fluids, doi:10,1016/j.compfluid.2010.11.011, 1096 2011. Würsch, M. and G. C. Craig, 2013: A simple dynamical model of cumulus convection for data assimilation research, submitted to Met. Zeitschrift.

Data Assimilation Techniques for Ionospheric Reference Scenarios - project overview and first results

NASA Astrophysics Data System (ADS)

Gerzen, Tatjana; Mainul Hoque, M.; Wilken, Volker; Minkwitz, David; Schlüter, Stefan

2015-04-01

The European Geostationary Navigation Overlay Service (EGNOS) is the European Satellite Based Augmentation Service (SBAS) that provides value added services, in particular to Safety of Live (SoL) users of the Global Navigation Satellite Systems (GNSS). In the frame of the European GNSS Evolution Programme (EGEP), ESA has launched several activities, which are aiming to support the design, development and qualification of the future operational EGNOS infrastructure and associated services. The ionosphere is the part of the upper Earth's atmosphere between about 50 km and 1000 km above the Earth's surface, which contains sufficient free electrons to cause strong impact on radio signal propagation. Therefore, treatment of the ionosphere is a critical issue to guarantee the EGNOS system performance. In order to conduct the EGNOS end-to-end performance simulations and to assure the capability for maintaining integrity of the EGNOS system especially during ionospheric storm conditions, Ionospheric Reference Scenarios (IRSs) are introduced by ESA. The project Data Assimilation Techniques for Ionospheric Reference Scenarios (DAIS) - aims to generate improved EGNOS IRSs by combining space borne and ground based GNSS observations. The main focus of this project is to demonstrate that ionospheric radio occultation (IRO) measurements can significantly contribute to fill data gaps in GNSS ground networks (particularly in Africa and over the oceans) when generating the IRSs. The primary tasks are the calculation and validation of time series of IRSs (i.e. TEC maps) by a 3D assimilation approach that combines IRO and ground based GNSS measurements with an ionospheric background model in an optimal way. In the first phase of the project we selected appropriate test periods, one presenting perturbed and the other one - nominal ionospheric conditions, collected and filtered the corresponding data. We defined and developed an applicable technique for the 3D assimilation and applied this technique for the generation of IRSs covering the EGNOS V3 service area. This presentation gives an overview about the DAIS project and the first results. We outline the assimilation approach, show test run results and finally address and discuss open questions.

Data assimilation in the low noise regime

NASA Astrophysics Data System (ADS)

Weare, J.; Vanden-Eijnden, E.

2012-12-01

On-line data assimilation techniques such as ensemble Kalman filters and particle filters tend to lose accuracy dramatically when presented with an unlikely observation. Such observation may be caused by an unusually large measurement error or reflect a rare fluctuation in the dynamics of the system. Over a long enough span of time it becomes likely that one or several of these events will occur. In some cases they are signatures of the most interesting features of the underlying system and their prediction becomes the primary focus of the data assimilation procedure. The Kuroshio or Black Current that runs along the eastern coast of Japan is an example of just such a system. It undergoes infrequent but dramatic changes of state between a small meander during which the current remains close to the coast of Japan, and a large meander during which the current bulges away from the coast. Because of the important role that the Kuroshio plays in distributing heat and salinity in the surrounding region, prediction of these transitions is of acute interest. { Here we focus on a regime in which both the stochastic forcing on the system and the observational noise are small. In this setting large deviation theory can be used to understand why standard filtering methods fail and guide the design of the more effective data assimilation techniques. Motivated by our large deviations analysis we propose several data assimilation strategies capable of efficiently handling rare events such as the transitions of the Kuroshio. These techniques are tested on a model of the Kuroshio and shown to perform much better than standard filtering methods.Here the sequence of observations (circles) are taken directly from one of our Kuroshio model's transition events from the small meander to the large meander. We tested two new algorithms (Algorithms 3 and 4 in the legend) motivated by our large deviations analysis as well as a standard particle filter and an ensemble Kalman filter. The parameters of each algorithm are chosen so that their costs are comparable. The particle filter and an ensemble Kalman filter fail to accurately track the transition. Algorithms 3 and 4 maintain accuracy (and smaller scale resolution) throughout the transition.

Population level differences in thermal sensitivity of energy assimilation in terrestrial salamanders.

PubMed

Clay, Timothy A; Gifford, Matthew E

2017-02-01

Thermal adaptation predicts that thermal sensitivity of physiological traits should be optimized to thermal conditions most frequently experienced. Furthermore, thermodynamic constraints predict that species with higher thermal optima should have higher performance maxima and narrower performance breadths. We tested these predictions by examining the thermal sensitivity of energy assimilation between populations within two species of terrestrial-lungless salamanders, Plethodon albagula and P. montanus. Within P. albagula, we examined populations that were latitudinally separated by >450km. Within P. montanus, we examined populations that were elevationally separated by >900m. Thermal sensitivity of energy assimilation varied substantially between populations of P. albagula separated latitudinally, but did not vary between populations of P. montanus separated elevationally. Specifically, in P. albagula, the lower latitude population had a higher thermal optimum, higher maximal performance, and narrower performance breadth compared to the higher latitude population. Furthermore, across all individuals as thermal optima increased, performance maxima also increased, providing support for the theory that "hotter is better". Copyright © 2016 Elsevier Ltd. All rights reserved.

Exploring New Pathways in Precipitation Assimilation

NASA Technical Reports Server (NTRS)

Hou, Arthur; Zhang, Sara Q.

2004-01-01

Precipitation assimilation poses a special challenge in that the forward model for rain in a global forecast system is based on parameterized physics, which can have large systematic errors that must be rectified to use precipitation data effectively within a standard statistical analysis framework. We examine some key issues in precipitation assimilation and describe several exploratory studies in assimilating rainfall and latent heating information in NASA's global data assimilation systems using the forecast model as a weak constraint. We present results from two research activities. The first is the assimilation of surface rainfall data using a time-continuous variational assimilation based on a column model of the full moist physics. The second is the assimilation of convective and stratiform latent heating retrievals from microwave sensors using a variational technique with physical parameters in the moist physics schemes as a control variable. We will show the impact of assimilating these data on analyses and forecasts. Among the lessons learned are (1) that the time-continuous application of moisture/temperature tendency corrections to mitigate model deficiencies offers an effective strategy for assimilating precipitation information, and (2) that the model prognostic variables must be allowed to directly respond to an improved rain and latent heating field within an analysis cycle to reap the full benefit of assimilating precipitation information. of microwave radiances versus retrieval information in raining areas, and initial efforts in developing ensemble techniques such as Kalman filter/smoother for precipitation assimilation. Looking to the future, we discuss new research directions including the assimilation

Characterization of Chloroplastic Fructose 1,6-Bisphosphate Aldolases as Lysine-methylated Proteins in Plants*

PubMed Central

Mininno, Morgane; Brugière, Sabine; Pautre, Virginie; Gilgen, Annabelle; Ma, Sheng; Ferro, Myriam; Tardif, Marianne; Alban, Claude; Ravanel, Stéphane

2012-01-01

In pea (Pisum sativum), the protein-lysine methyltransferase (PsLSMT) catalyzes the trimethylation of Lys-14 in the large subunit (LS) of ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco), the enzyme catalyzing the CO2 fixation step during photosynthesis. Homologs of PsLSMT, herein referred to as LSMT-like enzymes, are found in all plant genomes, but methylation of LS Rubisco is not universal in the plant kingdom, suggesting a species-specific protein substrate specificity of the methyltransferase. In this study, we report the biochemical characterization of the LSMT-like enzyme from Arabidopsis thaliana (AtLSMT-L), with a focus on its substrate specificity. We show that, in Arabidopsis, LS Rubisco is not naturally methylated and that the physiological substrates of AtLSMT-L are chloroplastic fructose 1,6-bisphosphate aldolase isoforms. These enzymes, which are involved in the assimilation of CO2 through the Calvin cycle and in chloroplastic glycolysis, are trimethylated at a conserved lysyl residue located close to the C terminus. Both AtLSMT-L and PsLSMT are able to methylate aldolases with similar kinetic parameters and product specificity. Thus, the divergent substrate specificity of LSMT-like enzymes from pea and Arabidopsis concerns only Rubisco. AtLSMT-L is able to interact with unmethylated Rubisco, but the complex is catalytically unproductive. Trimethylation does not modify the kinetic properties and tetrameric organization of aldolases in vitro. The identification of aldolases as methyl proteins in Arabidopsis and other species like pea suggests a role of protein lysine methylation in carbon metabolism in chloroplasts. PMID:22547063

Variation in Leaf Respiration Rates at Night Correlates with Carbohydrate and Amino Acid Supply1[OPEN

PubMed Central

Lee, Chun Pong; Cheng, Riyan

2017-01-01

Plant respiration can theoretically be fueled by and dependent upon an array of central metabolism components; however, which ones are responsible for the quantitative variation found in respiratory rates is unknown. Here, large-scale screens revealed 2-fold variation in nighttime leaf respiration rate (RN) among mature leaves from an Arabidopsis (Arabidopsis thaliana) natural accession collection grown under common favorable conditions. RN variation was mostly maintained in the absence of genetic variation, which emphasized the low heritability of RN and its plasticity toward relatively small environmental differences within the sampling regime. To pursue metabolic explanations for leaf RN variation, parallel metabolite level profiling and assays of total protein and starch were performed. Within an accession, RN correlated strongly with stored carbon substrates, including starch and dicarboxylic acids, as well as sucrose, major amino acids, shikimate, and salicylic acid. Among different accessions, metabolite-RN correlations were maintained with protein, sucrose, and major amino acids but not stored carbon substrates. A complementary screen of the effect of exogenous metabolites and effectors on leaf RN revealed that (1) RN is stimulated by the uncoupler FCCP and high levels of substrates, demonstrating that both adenylate turnover and substrate supply can limit leaf RN, and (2) inorganic nitrogen did not stimulate RN, consistent with limited nighttime nitrogen assimilation. Simultaneous measurements of RN and protein synthesis revealed that these processes were largely uncorrelated in mature leaves. These results indicate that differences in preceding daytime metabolic activities are the major source of variation in mature leaf RN under favorable controlled conditions. PMID:28615345

Tropospheric ozone reduces carbon assimilation in trees: estimates from analysis of continuous flux measurements.

PubMed

Fares, Silvano; Vargas, Rodrigo; Detto, Matteo; Goldstein, Allen H; Karlik, John; Paoletti, Elena; Vitale, Marcello

2013-08-01

High ground-level ozone concentrations are typical of Mediterranean climates. Plant exposure to this oxidant is known to reduce carbon assimilation. Ozone damage has been traditionally measured through manipulative experiments that do not consider long-term exposure and propagate large uncertainty by up-scaling leaf-level observations to ecosystem-level interpretations. We analyzed long-term continuous measurements (>9 site-years at 30 min resolution) of environmental and eco-physiological parameters at three Mediterranean ecosystems: (i) forest site dominated by Pinus ponderosa in the Sierra Mountains in California, USA; (ii) forest site composed of a mixture of Quercus spp. and P. pinea in the Tyrrhenian sea coast near Rome, Italy; and (iii) orchard site of Citrus sinensis cultivated in the California Central Valley, USA. We hypothesized that higher levels of ozone concentration in the atmosphere result in a decrease in carbon assimilation by trees under field conditions. This hypothesis was tested using time series analysis such as wavelet coherence and spectral Granger causality, and complemented with multivariate linear and nonlinear statistical analyses. We found that reduction in carbon assimilation was more related to stomatal ozone deposition than to ozone concentration. The negative effects of ozone occurred within a day of exposure/uptake. Decoupling between carbon assimilation and stomatal aperture increased with the amount of ozone pollution. Up to 12-19% of the carbon assimilation reduction in P. ponderosa and in the Citrus plantation was explained by higher stomatal ozone deposition. In contrast, the Italian site did not show reductions in gross primary productivity either by ozone concentration or stomatal ozone deposition, mainly due to the lower ozone concentrations in the periurban site over the shorter period of investigation. These results highlight the importance of plant adaptation/sensitivity under field conditions, and the importance of continuous long-term measurements to explain ozone damage to real-world forests and calculate metrics for ozone-risk assessment. © 2013 John Wiley & Sons Ltd.

A near real time regional JPSS and GOES-R data assimilation system for high impact weather research and applications

NASA Astrophysics Data System (ADS)

Li, J.; Wang, P.; Han, H.; Schmit, T. J.

2014-12-01

JPSS and GOES-R observations play important role in numerical weather prediction (NWP). However, how to best represent the information from satellite observations and how to get value added information from these satellite data into regional NWP models, including both radiance and derived products, still need investigations. In order to enhance the applications of JPSS and GOES-R data in regional NWP for high impact weather forecasts, scientists from Cooperative Institute of Meteorological Satellite Studies (CIMSS) at University of Wisconsin-Madison have recently developed a near realtime regional Satellite Data Assimilation system for Tropical storm forecasts (SDAT) (http://cimss.ssec.wisc.edu/sdat). The system consists of the community Gridpoint Statistical Interpolation (GSI) assimilation system and the advanced Weather Research Forecast (WRF) model. In addition to assimilate GOES, AMSUA/AMSUB, HIRS, MHS, ATMS (Suomi-NPP), AIRS and IASI radiances, the SDAT is also able to assimilate satellite-derived products such as hyperspectral IR retrieved temperature and moisture profiles, total precipitable water (TPW), GOES Sounder (and future GOES-R) layer precipitable water (LPW) and GOES Imager atmospheric motion vector (AMV) products into the system. Real time forecasted GOES infrared (IR) images simulated from SDAT output have also been part of the SDAT system for applications and forecast evaluations. To set up the system parameters, a series of experiments have been carried out to test the impacts of different initialization schemes, including different background error matrix, different NCEP global model date sets, and different WRF model horizontal resolutions. Using SDAT as a research testbed, researches have been conducted for different satellite data impacts study, as well as different techniques for handling clouds in radiance assimilation. Since the fall of 2013, the SDAT system has been running in near real time. The results from historical cases and 2014 hurricane season cases will be compared with the operational GFS and HWRF, and presented at the meeting.

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

NASA Astrophysics Data System (ADS)

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 channels. For example, those information have been directly assimilated by modifying the water vapour profile in the initial conditions of the WRF model in California using GOES satellite imagery. In Europe, the assimilation of cloud-top height and relative humidity has been performed in an indirect approach using an ensemble Kalman filter. In this case Meteosat SEVIRI cloud information has been assimilated in the COSMO model. Although such methods generally provide improved cloud cover forecasts in mid-latitudes, the major limitation is that only clear-sky or completely cloudy cases can be considered. Indeed, fractional clouds cause a measured signal mixing cold clouds and warmer Earth surface. If the model's initial state is directly forced by cloud properties observed by satellite, the changed model fields have to be smoothed in order to avoid numerical instability. Other crucial aspects which influence forecast quality in the case of satellite radiance assimilation are channel selection, bias and error treatment. The overall promising satellite data assimilation methods in regional NWP have not yet been explicitly applied and tested under tropical conditions. Therefore, a deeper understanding on the benefits of such methods is necessary to improve irradiance forecast schemes.

Regional Ocean Data Assimilation

NASA Astrophysics Data System (ADS)

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 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.

Grain growth prediction based on data assimilation by implementing 4DVar on multi-phase-field model

NASA Astrophysics Data System (ADS)

Ito, Shin-ichi; Nagao, Hiromichi; Kasuya, Tadashi; Inoue, Junya

2017-12-01

We propose a method to predict grain growth based on data assimilation by using a four-dimensional variational method (4DVar). When implemented on a multi-phase-field model, the proposed method allows us to calculate the predicted grain structures and uncertainties in them that depend on the quality and quantity of the observational data. We confirm through numerical tests involving synthetic data that the proposed method correctly reproduces the true phase-field assumed in advance. Furthermore, it successfully quantifies uncertainties in the predicted grain structures, where such uncertainty quantifications provide valuable information to optimize the experimental design.

Regional ocean data assimilation.

PubMed

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 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.

Heat balance statistics derived from four-dimensional assimilations with a global circulation model

NASA Technical Reports Server (NTRS)

Schubert, S. D.; Herman, G. F.

1981-01-01

The reported investigation was conducted to develop a reliable procedure for obtaining the diabatic and vertical terms required for atmospheric heat balance studies. The method developed employs a four-dimensional assimilation mode in connection with the general circulation model of NASA's Goddard Laboratory for Atmospheric Sciences. The initial analysis was conducted with data obtained in connection with the 1976 Data Systems Test. On the basis of the results of the investigation, it appears possible to use the model's observationally constrained diagnostics to provide estimates of the global distribution of virtually all of the quantities which are needed to compute the atmosphere's heat and energy balance.

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

PubMed

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.

Steady-state kinetic mechanism of the NADP+- and NAD+-dependent reactions catalysed by betaine aldehyde dehydrogenase from Pseudomonas aeruginosa.

PubMed Central

Velasco-García, R; González-Segura, L; Muñoz-Clares, R A

2000-01-01

Betaine aldehyde dehydrogenase (BADH) catalyses the irreversible oxidation of betaine aldehyde to glycine betaine with the concomitant reduction of NAD(P)(+) to NADP(H). In Pseudomonas aeruginosa this reaction is a compulsory step in the assimilation of carbon and nitrogen when bacteria are growing in choline or choline precursors. The kinetic mechanisms of the NAD(+)- and NADP(+)-dependent reactions were examined by steady-state kinetic methods and by dinucleotide binding experiments. The double-reciprocal patterns obtained for initial velocity with NAD(P)(+) and for product and dead-end inhibition establish that both mechanisms are steady-state random. However, quantitative analysis of the inhibitions, and comparison with binding data, suggest a preferred route of addition of substrates and release of products in which NAD(P)(+) binds first and NAD(P)H leaves last, particularly in the NADP(+)-dependent reaction. Abortive binding of the dinucleotides, or their analogue ADP, in the betaine aldehyde site was inferred from total substrate inhibition by the dinucleotides, and parabolic inhibition by NADH and ADP. A weak partial uncompetitive substrate inhibition by the aldehyde was observed only in the NADP(+)-dependent reaction. The kinetics of P. aeruginosa BADH is very similar to that of glucose-6-phosphate dehydrogenase, suggesting that both enzymes fulfil a similar amphibolic metabolic role when the bacteria grow in choline and when they grow in glucose. PMID:11104673

Nitrosothiol signaling and protein nitrosation in cell death.

PubMed

Iyer, Anand Krishnan V; Rojanasakul, Yon; Azad, Neelam

2014-11-15

Nitric oxide, a reactive free radical, is an important signaling molecule that can lead to a plethora of cellular effects affecting homeostasis. A well-established mechanism by which NO manifests its effect on cellular functions is the post-translational chemical modification of cysteine thiols in substrate proteins by a process known as S-nitrosation. Studies that investigate regulation of cellular functions through NO have increasingly established S-nitrosation as the primary modulatory mechanism in their respective systems. There has been a substantial increase in the number of reports citing various candidate proteins undergoing S-nitrosation, which affects cell-death and -survival pathways in a number of tissues including heart, lung, brain and blood. With an exponentially growing list of proteins being identified as substrates for S-nitrosation, it is important to assimilate this information in different cell/tissue systems in order to gain an overall view of protein regulation of both individual proteins and a class of protein substrates. This will allow for broad mapping of proteins as a function of S-nitrosation, and help delineate their global effects on pathophysiological responses including cell death and survival. This information will not only provide a much better understanding of overall functional relevance of NO in the context of various disease states, it will also facilitate the generation of novel therapeutics to combat specific diseases that are driven by NO-mediated S-nitrosation. Copyright © 2014 Elsevier Inc. All rights reserved.

Degradation of formaldehyde at high concentrations by phenol-adapted Ralstonia eutropha closely related to pink-pigmented facultative methylotrophs.

PubMed

Habibi, Alireza; Vahabzadeh, Farzaneh

2013-01-01

The ability of the phenol-adapted Ralstonia eutropha to utilize formaldehyde (FD) as the sole source of carbon and energy was studied. Adaptation to FD was accomplished by substituting FD for glucose in a stepwise manner. The bacterium in the liquid test culture could tolerate concentrations of FD up to 900 mg L(-1). Degradation of FD was complete in 528 h at 30°C with shaking at 150 rpm (r = 1.67 mg L(-1) h(-1)), q = 0.035 g(FD) g(cell) (-1) h(-1). Substrate inhibition kinetics (Haldane and Luong equations) are used to describe the experimental data. At non-inhibitory concentrations of FD, the Monod equation was used. According to the Luong model, the values of the maximum specific growth rate (μ(max)), half-saturation coefficient (k(S)), the maximum allowable formaldehyde concentration (S(m)), and the shape factor (n) were 0.117 h(-1), 47.6 mg L(-1), 900 mg L(-1), and 2.2, respectively. The growth response of the test bacterium to consecutive FD feedings was examined, and the FD-adapted R. eutropha cells were able to degrade 1000 mg L(-1) FD in 150 h through 4 cycles of FD feeds. During FD degradation, formic acid metabolite was formed. Assimilation of FD, methanol, formic acid, and oxalate by the test bacterium was accompanied by the formation of a pink pigment. The carotenoid nature of the cellular pigment has been confirmed and the test bacterium appeared to be closely related to pink-pigmented facultative methylotrophs (PPFM). The extent of harm to soil exposed to biotreated wastewaters containing FD may be moderated due to the association between methylotrophic/oxalotrophic bacteria and plants.

Assimilation of SeaWiFS Ocean Chlorophyll Data into a Three-Dimensional Global Ocean Model

NASA Technical Reports Server (NTRS)

Gregg, Watson W.

2005-01-01

Assimilation of satellite ocean color data is a relatively new phenomenon in ocean sciences. However, with routine observations from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), launched in late 1997, and now with new data from the Moderate Resolution Imaging Spectroradometer (MODIS) Aqua, there is increasing interest in ocean color data assimilation. Here SeaWiFS chlorophyll data were assimilated with an established thre-dimentional global ocean model. The assimilation improved estimates of hlorophyll and primary production relative to a free-run (no assimilation) model. This represents the first attempt at ocean color data assimilation using NASA satellites in a global model. The results suggest the potential of assimilation of satellite ocean chlorophyll data for improving models.

4DVAR data Assimilation with the Regional Ocean Modeling System (ROMS): Impact on the Water Mass Distributions in the Yellow Sea

NASA Astrophysics Data System (ADS)

Lee, Joon-Ho; Kim, Taekyun; Pang, Ig-Chan; Moon, Jae-Hong

2018-04-01

In this study, we evaluate the performance of the recently developed incremental strong constraint 4-dimensional variational (4DVAR) data assimilation applied to the Yellow Sea (YS) using the Regional Ocean Modeling System (ROMS). Two assimilation experiments are compared: assimilating remote-sensed sea surface temperature (SST) and both the SST and in-situ profiles measured by shipboard CTD casts into a regional ocean modeling from January to December of 2011. By comparing the two assimilation experiments against a free-run without data assimilation, we investigate how the assimilation affects the hydrographic structures in the YS. Results indicate that the SST assimilation notably improves the model behavior at the surface when compared to the nonassimilative free-run. The SST assimilation also has an impact on the subsurface water structure in the eastern YS; however, the improvement is seasonally dependent, that is, the correction becomes more effective in winter than in summer. This is due to a strong stratification in summer that prevents the assimilation of SST from affecting the subsurface temperature. A significant improvement to the subsurface temperature is made when the in-situ profiles of temperature and salinity are assimilated, forming a tongue-shaped YS bottom cold water from the YS toward the southwestern seas of Jeju Island.

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Zaitchik, Benjamin F.; Rodell, Matt

2008-01-01

The NASA Gravity Recovery and Climate Experiment (GRACE) system of satellites provides observations of large-scale, monthly terrestrial water storage (TWS) changes. In. this presentation we describe a land data assimilation system that ingests GRACE observations and show that the assimilation improves estimates of water storage and fluxes, as evaluated against independent measurements. The ensemble-based land data assimilation system uses a Kalman smoother approach along with the NASA Catchment Land Surface Model (CLSM). We assimilated GRACE-derived TWS anomalies for each of the four major sub-basins of the Mississippi into the Catchment Land Surface Model (CLSM). Compared with the open-loop (no assimilation) CLSM simulation, assimilation estimates of groundwater variability exhibited enhanced skill with respect to measured groundwater. Assimilation also significantly increased the correlation between simulated TWS and gauged river flow for all four sub-basins and for the Mississippi River basin itself. In addition, model performance was evaluated for watersheds smaller than the scale of GRACE observations, in the majority of cases, GRACE assimilation led to increased correlation between TWS estimates and gauged river flow, indicating that data assimilation has considerable potential to downscale GRACE data for hydrological applications. We will also describe how the output from the GRACE land data assimilation system is now being prepared for use in the North American Drought Monitor.

Selenite reduction by the thioredoxin system: kinetics and identification of protein-bound selenide.

PubMed

Tamura, Takashi; Sato, Kumi; Komori, Kentaro; Imai, Takeshi; Kuwahara, Mitsuhiko; Okugochi, Takahiro; Mihara, Hisaaki; Esaki, Nobuyoshi; Inagaki, Kenji

2011-01-01

Selenite (SeO(3)(2-)) assimilation into a bacterial selenoprotein depends on thioredoxin (trx) reductase in Esherichia coli, but the molecular mechanism has not been elucidated. The mineral-oil overlay method made it possible to carry out anaerobic enzyme assay, which demonstrated an initial lag-phase followed by time-dependent steady NADPH consumption with a positive cooperativity toward selenite and trx. SDS-PAGE/autoradiography using (75)Se-labeled selenite as substrate revealed the formation of trx-bound selenium in the reaction mixture. The protein-bound selenium has metabolic significance in being stabilized in the divalent state, and it also produced the selenopersulfide (-S-SeH) form by the catalysis of E. coli trx reductase (TrxB).

Assimilation of Quality Controlled AIRS Temperature Profiles using the NCEP GFS

NASA Technical Reports Server (NTRS)

Susskind, Joel; Reale, Oreste; Iredell, Lena; Rosenberg, Robert

2013-01-01

We have previously conducted a number of data assimilation experiments using AIRS Version-5 quality controlled temperature profiles as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The data assimilation and forecast system we used was the Goddard Earth Observing System Model , Version-5 (GEOS-5) Data Assimilation System (DAS), which represents a combination of the NASA GEOS-5 forecast model with the National Centers for Environmental Prediction (NCEP) operational Grid Point Statistical Interpolation (GSI) global analysis scheme. All analyses and forecasts were run at a 0.5deg x 0.625deg spatial resolution. Data assimilation experiments were conducted in four different seasons, each in a different year. Three different sets of data assimilation experiments were run during each time period: Control; AIRS T(p); and AIRS Radiance. In the "Control" analysis, all the data used operationally by NCEP was assimilated, but no AIRS data was assimilated. Radiances from the Aqua AMSU-A instrument were also assimilated operationally by NCEP and are included in the "Control". The AIRS Radiance assimilation adds AIRS observed radiance observations for a select set of channels to the data set being assimilated, as done operationally by NCEP. In the AIRS T(p) assimilation, all information used in the Control was assimilated as well as Quality Controlled AIRS Version-5 temperature profiles, i.e., AIRS T(p) information was substituted for AIRS radiance information. The AIRS Version-5 temperature profiles were presented to the GSI analysis as rawinsonde profiles, assimilated down to a case-by-case appropriate pressure level p(sub best) determined using the Quality Control procedure. Version-5 also determines case-by-case, level-by-level error estimates of the temperature profiles, which were used as the uncertainty of each temperature measurement. These experiments using GEOS-5 have shown that forecasts resulting from analyses using the AIRS T(p) assimilation system were superior to those from the Radiance assimilation system, both with regard to global 7 day forecast skill and also the ability to predict storm tracks and intensity.

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

2012-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.

Role of catabolite regulatory mechanisms in control of carbohydrate utilization by the rumen anaerobic fungus Neocallimastix frontalis.

PubMed Central

Mountfort, D O; Asher, R A

1983-01-01

Neocallimastix frontalis PN-1 utilized the soluble sugars D-glucose, D-cellobiose, D-fructose, maltose, sucrose, and D-xylose for growth. L-Arabinose, D-galactose, D-mannose, and D-xylitol did not support growth of the fungus. Paired substrate test systems were used to determine whether any two sugars were utilized simultaneously or sequentially. Of the paired monosaccharides tested, glucose was found to be preferentially utilized compared with fructose and xylose. The disaccharides cellobiose and sucrose were preferentially utilized compared with fructose and glucose, respectively, an cellobiose was also the preferred substrate compared with xylose. Xylose was the preferred substrate compared with maltose. In further incubations, the fungus was grown on the substrate utilized last in the two-substrate tests. After moderate growth was attained, the preferred substrate was added to the culture medium. Inhibition of nonpreferred substrate utilization by the addition of the preferred substrate was taken as evidence of catabolite regulation. For the various combinations of substrates tested, fructose and xylose utilization was found to be inhibited in the presence of glucose, indicating that catabolite regulation was involved. No clear-cut inhibition was observed with any of the other substrate combinations tested. The significance of these findings in relation to rumen microbial interactions and competitions is discussed. PMID:6660873

Innovative test method for the estimation of the foaming tendency of substrates for biogas plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moeller, Lucie, E-mail: lucie.moeller@ufz.de; Eismann, Frank, E-mail: info@antoc.de; Wißmann, Daniel, E-mail: d.s.wissmann@gmx.de

2015-07-15

Graphical abstract: Display Omitted - Highlights: • Foaming in biogas plants depends on the interactions between substrate and digestate. • Foaming tests enable the evaluation of substrate foaming tendency in biogas plants. • Leipzig foam tester enables foaming tests of substrates prior to use. - Abstract: Excessive foaming in anaerobic digestion occurs at many biogas plants and can cause problems including plugged gas pipes. Unfortunately, the majority of biogas plant operators are unable to identify the causes of foaming in their biogas reactor. The occurrence of foaming is often related to the chemical composition of substrates fed to the reactor.more » The consistency of the digestate itself is also a crucial part of the foam formation process. Thus, no specific recommendations concerning substrates can be given in order to prevent foam formation in biogas plants. The safest way to avoid foaming is to test the foaming tendency of substrates on-site. A possible solution is offered by an innovative foaming test. With the help of this tool, biogas plant operators can evaluate the foaming disposition of new substrates prior to use in order to adjust the composition of substrate mixes.« less

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

NASA Technical Reports Server (NTRS)

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.

Health Information Exchange (HIE): A literature review, assimilation pattern and a proposed classification for a new policy approach.

PubMed

Esmaeilzadeh, Pouyan; Sambasivan, Murali

2016-12-01

Literature shows existence of barriers to Healthcare Information Exchange (HIE) assimilation process. A number of studies have considered assimilation of HIE as a whole phenomenon without regard to its multifaceted nature. Thus, the pattern of HIE assimilation in healthcare providers has not been clearly studied due to the effects of contingency factors on different assimilation phases. This study is aimed at defining HIE assimilation phases, recognizing assimilation pattern, and proposing a classification to highlight unique issues associated with HIE assimilation. A literature review of existing studies related to HIE efforts from 2005 was undertaken. Four electronic research databases (PubMed, Web of Science, CINAHL, and Academic Search Premiere) were searched for articles addressing different phases of HIE assimilation process. Two hundred and fifty-four articles were initially selected. Out of 254, 44 studies met the inclusion criteria and were reviewed. The assimilation of HIE is a complicated and a multi-staged process. Our findings indicated that HIE assimilation process consisted of four main phases: initiation, organizational adoption decision, implementation and institutionalization. The data helped us recognize the assimilation pattern of HIE in healthcare organizations. The results provide useful theoretical implications for research by defining HIE assimilation pattern. The findings of the study also have practical implications for policy makers. The findings show the importance of raising national awareness of HIE potential benefits, financial incentive programs, use of standard guidelines, implementation of certified technology, technical assistance, training programs and trust between healthcare providers. The study highlights deficiencies in the current policy using the literature and identifies the "pattern" as an indication for a new policy approach. Copyright © 2016 Elsevier Inc. All rights reserved.

Data Assimilation Experiments using Quality Controlled AIRS Version 5 Temperature Soundings

NASA Technical Reports Server (NTRS)

Susskind, Joel

2008-01-01

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AlRS data. Version 5 contains accurate case-by-case error estimates for most derived products, which are also used for quality control. We have conducted forecast impact experiments assimilating AlRS quality controlled temperature profiles using the NASA GEOS-5 data assimilation system, consisting of the NCEP GSI analysis coupled with the NASA FVGCM. Assimilation of quality controlled temperature profiles resulted in significantly improved forecast skill in both the Northern Hemisphere and Southern Hemisphere Extra-Tropics, compared to that obtained from analyses obtained when all data used operationally by NCEP except for AlRS data is assimilated. Experiments using different Quality Control thresholds for assimilation of AlRS temperature retrievals showed that a medium quality control threshold performed better than a tighter threshold, which provided better overall sounding accuracy; or a looser threshold, which provided better spatial coverage of accepted soundings. We are conducting more experiments to further optimize this balance of spatial coverage and sounding accuracy from the data assimilation perspective. In all cases, temperature soundings were assimilated well below cloud level in partially cloudy cases. The positive impact of assimilating AlRS derived atmospheric temperatures all but vanished when only AIRS stratospheric temperatures were assimilated. Forecast skill resulting from assimilation of AlRS radiances uncontaminated by clouds, instead of AlRS temperature soundings, was only slightly better than that resulting from assimilation of only stratospheric AlRS temperatures. This reduction in forecast skill is most likely the result of significant loss of tropospheric information when only AIRS radiances unaffected by clouds are used in the data assimilation process.

Assimilating MODIS-based albedo and snow cover fraction into the Common Land Model to improve snow depth simulation with direct insertion and deterministic ensemble Kalman filter methods

NASA Astrophysics Data System (ADS)

Xu, Jianhui; Shu, Hong

2014-09-01

This study assesses the analysis performance of assimilating the Moderate Resolution Imaging Spectroradiometer (MODIS)-based albedo and snow cover fraction (SCF) separately or jointly into the physically based Common Land Model (CoLM). A direct insertion method (DI) is proposed to assimilate the black and white-sky albedos into the CoLM. The MODIS-based albedo is calculated with the MODIS bidirectional reflectance distribution function (BRDF) model parameters product (MCD43B1) and the solar zenith angle as estimated in the CoLM for each time step. Meanwhile, the MODIS SCF (MOD10A1) is assimilated into the CoLM using the deterministic ensemble Kalman filter (DEnKF) method. A new DEnKF-albedo assimilation scheme for integrating the DI and DEnKF assimilation schemes is proposed. Our assimilation results are validated against in situ snow depth observations from November 2008 to March 2009 at five sites in the Altay region of China. The experimental results show that all three data assimilation schemes can improve snow depth simulations. But overall, the DEnKF-albedo assimilation shows the best analysis performance as it significantly reduces the bias and root-mean-square error (RMSE) during the snow accumulation and ablation periods at all sites except for the Fuyun site. The SCF assimilation via DEnKF produces better results than the albedo assimilation via DI, implying that the albedo assimilation that indirectly updates the snow depth state variable is less efficient than the direct SCF assimilation. For the Fuyun site, the DEnKF-albedo scheme tends to overestimate the snow depth accumulation with the maximum bias and RMSE values because of the large positive innovation (observation minus forecast).

Identification of medically relevant Nocardia species with an abbreviated battery of tests.

PubMed

Kiska, Deanna L; Hicks, Karen; Pettit, David J

2002-04-01

Identification of Nocardia to the species level is useful for predicting antimicrobial susceptibility patterns and defining the pathogenicity and geographic distribution of these organisms. We sought to develop an identification method which was accurate, timely, and employed tests which would be readily available in most clinical laboratories. We evaluated the API 20C AUX yeast identification system as well as several biochemical tests and Kirby-Bauer susceptibility patterns for the identification of 75 isolates encompassing the 8 medically relevant Nocardia species. There were few biochemical reactions that were sufficiently unique for species identification; of note, N. nova were positive for arylsulfatase, N. farcinica were positive for opacification of Middlebrook 7H11 agar, and N. brasiliensis and N. pseudobrasiliensis were the only species capable of liquefying gelatin. API 20C sugar assimilation patterns were unique for N. transvalensis, N. asteroides IV, and N. brevicatena. There was overlap among the assimilation patterns for the other species. Species-specific patterns of susceptibility to gentamicin, tobramycin, amikacin, and erythromycin were obtained for N. nova, N. farcinica, and N. brevicatena, while there was overlap among the susceptibility patterns for the other isolates. No single method could identify all Nocardia isolates to the species level; therefore, a combination of methods was necessary. An algorithm utilizing antibiotic susceptibility patterns, citrate utilization, acetamide utilization, and assimilation of inositol and adonitol accurately identified all isolates. The algorithm was expanded to include infrequent drug susceptibility patterns which have been reported in the literature but which were not seen in this study.

DARLA: Data Assimilation and Remote Sensing for Littoral Applications

NASA Astrophysics Data System (ADS)

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 the Field Research Facility at Duck, NC in September 2010 focused on assimilation of tower-based electo-optical, infrared, and radar measurements in predictions of longshore currents. Here we provide an overview of our contribution to the RIVET I experiment at New River Inlet, NC in May 2012. During the course of the 3-week measurement period, continuous tower-based remote sensing measurements were made using electro-optical, infrared, and radar techniques covering the nearshore zone and the inlet mouth. A total of 50 hours of airborne measurements were made using high-resolution infrared imagers and a customized along track interferometric synthetic aperture radar (ATI SAR). The airborne IR imagery provides kilometer-scale mapping of frontal features that evolve as the inlet flow interacts with the oceanic wave and current fields. The ATI SAR provides maps of the two-dimensional surface currents. Near-surface measurements of turbulent velocities and surface waves using SWIFT drifters, designed to measures near-surface properties relevant to remote sensing, complimented the extensive in situ measurements by RIVET investigators.

Developmental adjustments of house sparrow (Passer domesticus) nestlings to diet composition.

PubMed

Brzek, Paweł; Kohl, Kevin; Caviedes-Vidal, Enrique; Karasov, William H

2009-05-01

House sparrow nestlings are fed primarily on insects during the first 3 days of their life, and seeds become gradually more important afterwards. We tested whether developmental changes in size and functional capacity of the digestive tract in young house sparrows are genetically hard-wired and independent of diet, or can be modified by food type. Under laboratory conditions, we hand-fed young house sparrows with either a starch-free insect-like diet, based mainly on protein and fat, or a starch-containing diet with a mix of substrates similar to that offered to older nestlings in natural nests when they are gradually weaned from an insect to a seed diet. Patterns of overall development in body size and thermoregulatory ability, and in alimentary organ size increase, were relatively similar in house sparrow nestlings developing on both diets. However, total intestinal maltase activity, important in carbohydrate breakdown, was at least twice as high in house sparrow nestlings fed the starch-containing diet (P<0.001). The change in maltase activity of nestlings was specific, as no change occurred in aminopeptidase-N activity in the same tissues. There was no significant diet effect on digesta retention time, but assimilation efficiency for radiolabeled starch tended to be higher (P=0.054) in nestlings raised on starch-containing diet. Future studies must test whether the diet-dependent increase in maltase activity during development is irreversible or reversible, reflecting, respectively, a developmental plasticity or a phenotypic flexibility.

Increased Ratio of Electron Transport to Net Assimilation Rate Supports Elevated Isoprenoid Emission Rate in Eucalypts under Drought1[W][OPEN

PubMed Central

Dani, Kaidala Ganesha Srikanta; Jamie, Ian McLeod; Prentice, Iain Colin; Atwell, Brian James

2014-01-01

Plants undergoing heat and low-CO2 stresses emit large amounts of volatile isoprenoids compared with those in stress-free conditions. One hypothesis posits that the balance between reducing power availability and its use in carbon assimilation determines constitutive isoprenoid emission rates in plants and potentially even their maximum emission capacity under brief periods of stress. To test this, we used abiotic stresses to manipulate the availability of reducing power. Specifically, we examined the effects of mild to severe drought on photosynthetic electron transport rate (ETR) and net carbon assimilation rate (NAR) and the relationship between estimated energy pools and constitutive volatile isoprenoid emission rates in two species of eucalypts: Eucalyptus occidentalis (drought tolerant) and Eucalyptus camaldulensis (drought sensitive). Isoprenoid emission rates were insensitive to mild drought, and the rates increased when the decline in NAR reached a certain species-specific threshold. ETR was sustained under drought and the ETR-NAR ratio increased, driving constitutive isoprenoid emission until severe drought caused carbon limitation of the methylerythritol phosphate pathway. The estimated residual reducing power unused for carbon assimilation, based on the energetic status model, significantly correlated with constitutive isoprenoid emission rates across gradients of drought (r2 > 0.8) and photorespiratory stress (r2 > 0.9). Carbon availability could critically limit emission rates under severe drought and photorespiratory stresses. Under most instances of moderate abiotic stress levels, increased isoprenoid emission rates compete with photorespiration for the residual reducing power not invested in carbon assimilation. A similar mechanism also explains the individual positive effects of low-CO2, heat, and drought stresses on isoprenoid emission. PMID:25139160

Newtonian Nudging For A Richards Equation-based Distributed Hydrological Model

NASA Astrophysics Data System (ADS)

Paniconi, C.; Marrocu, M.; Putti, M.; Verbunt, M.

In this study a relatively simple data assimilation method has been implemented in a relatively complex hydrological model. The data assimilation technique is Newtonian relaxation or nudging, in which model variables are driven towards observations by a forcing term added to the model equations. The forcing term is proportional to the difference between simulation and observation (relaxation component) and contains four-dimensional weighting functions that can incorporate prior knowledge about the spatial and temporal variability and characteristic scales of the state variable(s) being assimilated. The numerical model couples a three-dimensional finite element Richards equation solver for variably saturated porous media and a finite difference diffusion wave approximation based on digital elevation data for surface water dynamics. We describe the implementation of the data assimilation algorithm for the coupled model and report on the numerical and hydrological performance of the resulting assimila- tion scheme. Nudging is shown to be successful in improving the hydrological sim- ulation results, and it introduces little computational cost, in terms of CPU and other numerical aspects of the model's behavior, in some cases even improving numerical performance compared to model runs without nudging. We also examine the sensitiv- ity of the model to nudging term parameters including the spatio-temporal influence coefficients in the weighting functions. Overall the nudging algorithm is quite flexi- ble, for instance in dealing with concurrent observation datasets, gridded or scattered data, and different state variables, and the implementation presented here can be read- ily extended to any features not already incorporated. Moreover the nudging code and tests can serve as a basis for implementation of more sophisticated data assimilation techniques in a Richards equation-based hydrological model.

A unifying conceptual model for the environmental responses of isoprene emissions from plants.

PubMed

Morfopoulos, Catherine; Prentice, Iain C; Keenan, Trevor F; Friedlingstein, Pierre; Medlyn, Belinda E; Peñuelas, Josep; Possell, Malcolm

2013-11-01

Isoprene is the most important volatile organic compound emitted by land plants in terms of abundance and environmental effects. Controls on isoprene emission rates include light, temperature, water supply and CO2 concentration. A need to quantify these controls has long been recognized. There are already models that give realistic results, but they are complex, highly empirical and require separate responses to different drivers. This study sets out to find a simpler, unifying principle. A simple model is presented based on the idea of balancing demands for reducing power (derived from photosynthetic electron transport) in primary metabolism versus the secondary pathway that leads to the synthesis of isoprene. This model's ability to account for key features in a variety of experimental data sets is assessed. The model simultaneously predicts the fundamental responses observed in short-term experiments, namely: (1) the decoupling between carbon assimilation and isoprene emission; (2) a continued increase in isoprene emission with photosynthetically active radiation (PAR) at high PAR, after carbon assimilation has saturated; (3) a maximum of isoprene emission at low internal CO2 concentration (ci) and an asymptotic decline thereafter with increasing ci; (4) maintenance of high isoprene emissions when carbon assimilation is restricted by drought; and (5) a temperature optimum higher than that of photosynthesis, but lower than that of isoprene synthase activity. A simple model was used to test the hypothesis that reducing power available to the synthesis pathway for isoprene varies according to the extent to which the needs of carbon assimilation are satisfied. Despite its simplicity the model explains much in terms of the observed response of isoprene to external drivers as well as the observed decoupling between carbon assimilation and isoprene emission. The concept has the potential to improve global-scale modelling of vegetation isoprene emission.

Assimilation of remote sensing observations into a sediment transport model of China's largest freshwater lake: spatial and temporal effects.

PubMed

Zhang, Peng; Chen, Xiaoling; Lu, Jianzhong; Zhang, Wei

2015-12-01

Numerical models are important tools that are used in studies of sediment dynamics in inland and coastal waters, and these models can now benefit from the use of integrated remote sensing observations. This study explores a scheme for assimilating remotely sensed suspended sediment (from charge-coupled device (CCD) images obtained from the Huanjing (HJ) satellite) into a two-dimensional sediment transport model of Poyang Lake, the largest freshwater lake in China. Optimal interpolation is used as the assimilation method, and model predictions are obtained by combining four remote sensing images. The parameters for optimal interpolation are determined through a series of assimilation experiments evaluating the sediment predictions based on field measurements. The model with assimilation of remotely sensed sediment reduces the root-mean-square error of the predicted sediment concentrations by 39.4% relative to the model without assimilation, demonstrating the effectiveness of the assimilation scheme. The spatial effect of assimilation is explored by comparing model predictions with remotely sensed sediment, revealing that the model with assimilation generates reasonable spatial distribution patterns of suspended sediment. The temporal effect of assimilation on the model's predictive capabilities varies spatially, with an average temporal effect of approximately 10.8 days. The current velocities which dominate the rate and direction of sediment transport most likely result in spatial differences in the temporal effect of assimilation on model predictions.

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

NASA Astrophysics Data System (ADS)

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.

The influence of social comparison on cognitive bias modification and emotional vulnerability.

PubMed

Standage, Helen; Harris, Jemma; Fox, Elaine

2014-02-01

The Cognitive Bias Modification (CBM) paradigm was devised to test predictions that cognitive biases have a causal influence on emotional status. Increasingly, however, researchers are testing the potential clinical applications of CBM. Although generally successful in reducing emotional vulnerability in clinical populations, the impact of CBM interventions has been somewhat variable. The aim of the current experiment was to investigate whether social comparison processing might be an important moderator of CBM. Healthy participants were presented with 80 valenced scenarios devised to induce a positive or negative interpretative bias. Critically, participants answered a series of questions designed to establish whether they assimilated or contrasted themselves with the valenced descriptions. The induction of an interpretation bias that was congruent with the valence of the training scenarios was successful only for participants who tended to assimilate the valenced scenarios, and not for those participants who tended to evaluate themselves against the scenarios. Furthermore, the predicted influence of CBM on emotional outcomes occurred only for those who had an assimilative rather than evaluative orientation toward CBM training material. Of key importance, results indicated that "evaluators" showed increased emotional vulnerability following positive CBM training. This result has both theoretical and clinical implications in suggesting that the success of CBM is dependent upon the way in which participants socially compare themselves with CBM training material. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Ocean Data Assimilation Systems for GODAE

DTIC Science & Technology

2009-09-01

we describe some of the ocean data assimilation systems that have been developed within the Global Ocean Data Assimilation Experiment (GODAE...assimilation systems in the post-GODAF. time period beyond 2008. 15. SUBJECT TERMS Global Ocean Data Assimilation Experiment, ARGO, subsurface...E. R. Franchi , 7000 Public Affairs (Unclassified/ Unlimited Only), Code 703o 4 yj ?>-* i o’ 1. Release of this paper is approved. 2. To the

Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal adjustment scale

NASA Astrophysics Data System (ADS)

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 assimilation at any adjustment scale produces streamflow predictions with a spatial correlation structure more consistent with that of streamflow observations. We also describe diagnosing the complexity of the assimilation problem using the spatial correlation information associated with the streamflow process, and discuss the effect of timing errors in a simulated hydrograph on the performance of the data assimilation procedure.

Quadratic Polynomial Regression using Serial Observation Processing:Implementation within DART

NASA Astrophysics Data System (ADS)

Hodyss, D.; Anderson, J. L.; Collins, N.; Campbell, W. F.; Reinecke, P. A.

2017-12-01

Many Ensemble-Based Kalman ltering (EBKF) algorithms process the observations serially. Serial observation processing views the data assimilation process as an iterative sequence of scalar update equations. What is useful about this data assimilation algorithm is that it has very low memory requirements and does not need complex methods to perform the typical high-dimensional inverse calculation of many other algorithms. Recently, the push has been towards the prediction, and therefore the assimilation of observations, for regions and phenomena for which high-resolution is required and/or highly nonlinear physical processes are operating. For these situations, a basic hypothesis is that the use of the EBKF is sub-optimal and performance gains could be achieved by accounting for aspects of the non-Gaussianty. To this end, we develop here a new component of the Data Assimilation Research Testbed [DART] to allow for a wide-variety of users to test this hypothesis. This new version of DART allows one to run several variants of the EBKF as well as several variants of the quadratic polynomial lter using the same forecast model and observations. Dierences between the results of the two systems will then highlight the degree of non-Gaussianity in the system being examined. We will illustrate in this work the differences between the performance of linear versus quadratic polynomial regression in a hierarchy of models from Lorenz-63 to a simple general circulation model.

Molecular and physiological evidence of genetic assimilation to high CO2 in the marine nitrogen fixer Trichodesmium.

PubMed

Walworth, Nathan G; Lee, Michael D; Fu, Fei-Xue; Hutchins, David A; Webb, Eric A

2016-11-22

Most investigations of biogeochemically important microbes have focused on plastic (short-term) phenotypic responses in the absence of genetic change, whereas few have investigated adaptive (long-term) responses. However, no studies to date have investigated the molecular progression underlying the transition from plasticity to adaptation under elevated CO 2 for a marine nitrogen-fixer. To address this gap, we cultured the globally important cyanobacterium Trichodesmium at both low and high CO 2 for 4.5 y, followed by reciprocal transplantation experiments to test for adaptation. Intriguingly, fitness actually increased in all high-CO 2 adapted cell lines in the ancestral environment upon reciprocal transplantation. By leveraging coordinated phenotypic and transcriptomic profiles, we identified expression changes and pathway enrichments that rapidly responded to elevated CO 2 and were maintained upon adaptation, providing strong evidence for genetic assimilation. These candidate genes and pathways included those involved in photosystems, transcriptional regulation, cell signaling, carbon/nitrogen storage, and energy metabolism. Conversely, significant changes in specific sigma factor expression were only observed upon adaptation. These data reveal genetic assimilation as a potentially adaptive response of Trichodesmium and importantly elucidate underlying metabolic pathways paralleling the fixation of the plastic phenotype upon adaptation, thereby contributing to the few available data demonstrating genetic assimilation in microbial photoautotrophs. These molecular insights are thus critical for identifying pathways under selection as drivers in plasticity and adaptation.

Data assimilation and model evaluation experiment datasets

NASA Technical Reports Server (NTRS)

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.

Assimilation of MLS and OMI Ozone Data

NASA Technical Reports Server (NTRS)

Stajner, I.; Wargan, K.; Chang, L.-P.; Hayashi, H.; Pawson, S.; Froidevaux, L.; Livesey, N.

2005-01-01

Ozone data from Aura Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) were assimilated into the ozone model at NASA's Global Modeling and Assimilation Office (GMAO). This assimilation produces ozone fields that are superior to those from the operational GMAO assimilation of Solar Backscatter Ultraviolet (SBUV/2) instrument data. Assimilation of Aura data improves the representation of the "ozone hole" and the agreement with independent Stratospheric Aerosol and Gas Experiment (SAGE) III and ozone sonde data. Ozone in the lower stratosphere is captured better: mean state, vertical gradients, spatial and temporal variability are all improved. Inclusion of OMI and MLS data together, or separately, in the assimilation system provides a way of checking how consistent OMI and MLS data are with each other, and with the ozone model. We found that differences between OMI total ozone column data and model forecasts decrease after MLS data are assimilated. This indicates that MLS stratospheric ozone profiles are consistent with OMI total ozone columns. The evaluation of error characteristics of OMI and MLS ozone will continue as data from newer versions of retrievals becomes available. We report on the initial step in obtaining global assimilated ozone fields that combine measurements from different Aura instruments, the ozone model at the GMAO, and their respective error characteristics. We plan to use assimilated ozone fields in estimation of tropospheric ozone. We also plan to investigate impacts of assimilated ozone fields on numerical weather prediction through their use in radiative models and in the assimilation of infrared nadir radiance data from NASA's Advanced Infrared Sounder (AIRS).

Assimilation of total lightning data using the three-dimensional variational method at convection-allowing resolution

NASA Astrophysics Data System (ADS)

Zhang, Rong; Zhang, Yijun; Xu, Liangtao; Zheng, Dong; Yao, Wen

2017-08-01

A large number of observational analyses have shown that lightning data can be used to indicate areas of deep convection. It is important to assimilate observed lightning data into numerical models, so that more small-scale information can be incorporated to improve the quality of the initial condition and the subsequent forecasts. In this study, the empirical relationship between flash rate, water vapor mixing ratio, and graupel mixing ratio was used to adjust the model relative humidity, which was then assimilated by using the three-dimensional variational data assimilation system of the Weather Research and Forecasting model in cycling mode at 10-min intervals. To find the appropriate assimilation time-window length that yielded significant improvement in both the initial conditions and subsequent forecasts, four experiments with different assimilation time-window lengths were conducted for a squall line case that occurred on 10 July 2007 in North China. It was found that 60 min was the appropriate assimilation time-window length for this case, and longer assimilation window length was unnecessary since no further improvement was present. Forecasts of 1-h accumulated precipitation during the assimilation period and the subsequent 3-h accumulated precipitation were significantly improved compared with the control experiment without lightning data assimilation. The simulated reflectivity was optimal after 30 min of the forecast, it remained optimal during the following 42 min, and the positive effect from lightning data assimilation began to diminish after 72 min of the forecast. Overall, the improvement from lightning data assimilation can be maintained for about 3 h.

Morphodynamic data assimilation used to understand changing coasts

USGS Publications Warehouse

Plant, Nathaniel G.; Long, Joseph W.

2015-01-01

Morphodynamic data assimilation blends observations with model predictions and comes in many forms, including linear regression, Kalman filter, brute-force parameter estimation, variational assimilation, and Bayesian analysis. Importantly, data assimilation can be used to identify sources of prediction errors that lead to improved fundamental understanding. Overall, models incorporating data assimilation yield better information to the people who must make decisions impacting safety and wellbeing in coastal regions that experience hazards due to storms, sea-level rise, and erosion. We present examples of data assimilation associated with morphologic change. We conclude that enough morphodynamic predictive capability is available now to be useful to people, and that we will increase our understanding and the level of detail of our predictions through assimilation of observations and numerical-statistical models.

Efficient Methods to Assimilate Satellite Retrievals Based on Information Content. Part 2; Suboptimal Retrieval Assimilation

NASA Technical Reports Server (NTRS)

Joiner, J.; Dee, D. P.

1998-01-01

One of the outstanding problems in data assimilation has been and continues to be how best to utilize satellite data while balancing the tradeoff between accuracy and computational cost. A number of weather prediction centers have recently achieved remarkable success in improving their forecast skill by changing the method by which satellite data are assimilated into the forecast model from the traditional approach of assimilating retrievals to the direct assimilation of radiances in a variational framework. The operational implementation of such a substantial change in methodology involves a great number of technical details, e.g., pertaining to quality control procedures, systematic error correction techniques, and tuning of the statistical parameters in the analysis algorithm. Although there are clear theoretical advantages to the direct radiance assimilation approach, it is not obvious at all to what extent the improvements that have been obtained so far can be attributed to the change in methodology, or to various technical aspects of the implementation. The issue is of interest because retrieval assimilation retains many practical and logistical advantages which may become even more significant in the near future when increasingly high-volume data sources become available. The central question we address here is: how much improvement can we expect from assimilating radiances rather than retrievals, all other things being equal? We compare the two approaches in a simplified one-dimensional theoretical framework, in which problems related to quality control and systematic error correction are conveniently absent. By assuming a perfect radiative transfer model and perfect knowledge of radiance and background error covariances, we are able to formulate a nonlinear local error analysis for each assimilation method. Direct radiance assimilation is optimal in this idealized context, while the traditional method of assimilating retrievals is suboptimal because it ignores the cross-covariances between background errors and retrieval errors. We show that interactive retrieval assimilation (where the same background used for assimilation is also used in the retrieval step) is equivalent to direct assimilation of radiances with suboptimal analysis weights. We illustrate and extend these theoretical arguments with several one-dimensional assimilation experiments, where we estimate vertical atmospheric profiles using simulated data from both the High-resolution InfraRed Sounder 2 (HIRS2) and the future Atmospheric InfraRed Sounder (AIRS).

Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments

NASA Astrophysics Data System (ADS)

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.

Improving Assimilated Global Climate Data Using TRMM and SSM/I Rainfall and Moisture Data

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.

1999-01-01

Current global analyses contain significant errors in primary hydrological fields such as precipitation, evaporation, and related cloud and moisture in the tropics. Work has been underway at NASA's Data Assimilation Office to explore the use of TRMM and SSM/I-derived rainfall and total precipitable water (TPW) data in global data assimilation to directly constrain these hydrological parameters. We found that assimilating these data types improves not only the precipitation and moisture estimates but also key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation in the tropics. We will present results showing that assimilating TRMM and SSM/I 6-hour averaged rain rates and TPW estimates significantly reduces the state-dependent systematic errors in assimilated products. Specifically, rainfall assimilation improves cloud and latent heating distributions, which, in turn, improves the cloudy-sky radiation and the large-scale circulation, while TPW assimilation reduces moisture biases to improve radiation in clear-sky regions. Rainfall and TPW assimilation also improves tropical forecasts beyond 1 day.

Learning style impact on knowledge gains in human patient simulation.

PubMed

Shinnick, Mary Ann; Woo, Mary A

2015-01-01

Human patient simulation (HPS) is a widely used method of teaching in nursing education. While it is believed that a student's learning style impacts knowledge gains in HPS, there is little evidence to support this. This study sought to determine the impact of learning style on knowledge gains after a heart failure (HF) simulation experience in pre-licensure nursing students. A convenience sample of four cohorts of prelicensure nursing students (n=161) were recruited from three Baccalaureate Schools of Nursing at the same point in their curriculum (age 25.7±6.6 years; gender=85.5% female) and participated in HPS using a HF simulation on a high-fidelity manikin. Learning style was assessed by the Kolb Learning Style Inventory (LSI) and pre- and post-HPS knowledge measured by parallel, validated, knowledge tests. The LSI identifies 4 learning styles, (Assimilating Diverging, Accommodating, and Converging). In some cases, learners present a balanced learning profile-an emphasis of all four equally. Statistical analysis consisted of t-tests and ANOVA. HF knowledge scores post-HPS compared to pre-HPS scores revealed a mean improvement of 7 points (p<0.001) showing evidence of learning. Within group score increases between the pre-test and post-test were seen for the Assimilating (66.68±20.87 to 83.35±12.59; p=0.07), Diverging (61.95±11.08 to 69.86±12.33; p<0.01) and balanced profiles (64.4±12.45 to 71.8±10.14; p<0.01), but not for Converging or Accommodating profiles (73% of sample). Post-hoc paired t-tests revealed a large effect size for the Assimilators (0.91) and moderate effect sizes for both the Divergers and balanced profiles (0.67 and 0.65, respectively). These findings confirm that knowledge gains occur with HPS and provide evidence that HPS is an effective teaching methodology for nursing students identifying with most types of learning styles. Copyright © 2014 Elsevier Ltd. All rights reserved.

Testing a Coupled Global-limited-area Data Assimilation System using Observations from the 2004 Pacific Typhoon Season

NASA Astrophysics Data System (ADS)

Holt, C. R.; Szunyogh, I.; Gyarmati, G.; Hoffman, R. N.; Leidner, M.

2011-12-01

Tropical cyclone (TC) track and intensity forecasts have improved in recent years due to increased model resolution, improved data assimilation, and the rapid increase in the number of routinely assimilated observations over oceans. The data assimilation approach that has received the most attention in recent years is Ensemble Kalman Filtering (EnKF). The most attractive feature of the EnKF is that it uses a fully flow-dependent estimate of the error statistics, which can have important benefits for the analysis of rapidly developing TCs. We implement the Local Ensemble Transform Kalman Filter algorithm, a vari- ation of the EnKF, on a reduced-resolution version of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model and the NCEP Regional Spectral Model (RSM) to build a coupled global-limited area anal- ysis/forecast system. This is the first time, to our knowledge, that such a system is used for the analysis and forecast of tropical cyclones. We use data from summer 2004 to study eight tropical cyclones in the Northwest Pacific. The benchmark data sets that we use to assess the performance of our system are the NCEP Reanalysis and the NCEP Operational GFS analyses from 2004. These benchmark analyses were both obtained by the Statistical Spectral Interpolation, which was the operational data assimilation system of NCEP in 2004. The GFS Operational analysis assimilated a large number of satellite radiance observations in addition to the observations assimilated in our system. All analyses are verified against the Joint Typhoon Warning Center Best Track data set. The errors are calculated for the position and intensity of the TCs. The global component of the ensemble-based system shows improvement in po- sition analysis over the NCEP Reanalysis, but shows no significant difference from the NCEP operational analysis for most of the storm tracks. The regional com- ponent of our system improves position analysis over all the global analyses. The intensity analyses, measured by the minimum sea level pressure, are of similar quality in all of the analyses. Regional deterministic forecasts started from our analyses are generally not significantly different from those started from the GFS operational analysis. On average, the regional experiments performed better for longer than 48 h sea level pressure forecasts, while the global forecast performed better in predicting the position for longer than 48 h.

Open source data assimilation framework for hydrological modeling

NASA Astrophysics Data System (ADS)

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 processes from a different domain or have different spatial and temporal resolutions. An open source framework that bridges OpenMI and OpenDA is presented. The framework provides a generic and easy means for any OpenMI compliant model to assimilate observation measurements. An example test case will be presented using MikeSHE, and OpenMI compliant fully coupled integrated hydrological model that can accurately simulate the feedback dynamics of overland flow, unsaturated zone and saturated zone.

Exploring coupled 4D-Var data assimilation using an idealised atmosphere-ocean model

NASA Astrophysics Data System (ADS)

Smith, Polly; Fowler, Alison; Lawless, Amos; Haines, Keith

2014-05-01

The successful application of data assimilation techniques to operational numerical weather prediction and ocean forecasting systems has led to an increased interest in their use for the initialisation of coupled atmosphere-ocean models in prediction on seasonal to decadal timescales. Coupled data assimilation presents a significant challenge but offers a long list of potential benefits including improved use of near-surface observations, reduction of initialisation shocks in coupled forecasts, and generation of a consistent system state for the initialisation of coupled forecasts across all timescales. In this work we explore some of the fundamental questions in the design of coupled data assimilation systems within the context of an idealised one-dimensional coupled atmosphere-ocean model. The system is based on the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) atmosphere model and a K-Profile Parameterisation (KKP) mixed layer ocean model developed by the National Centre for Atmospheric Science (NCAS) climate group at the University of Reading. It employs a strong constraint incremental 4D-Var scheme and is designed to enable the effective exploration of various approaches to performing coupled model data assimilation whilst avoiding many of the issues associated with more complex models. Working with this simple framework enables a greater range and quantity of experiments to be performed. Here, we will describe the development of our simplified single-column coupled atmosphere-ocean 4D-Var assimilation system and present preliminary results from a series of identical twin experiments devised to investigate and compare the behaviour and sensitivities of different coupled data assimilation methodologies. This includes comparing fully and weakly coupled assimilations with uncoupled assimilation, investigating whether coupled assimilation can eliminate or lessen initialisation shock in coupled model forecasts, and exploring the effect of the assimilation window length in coupled assimilations. These experiments will facilitate a greater theoretical understanding of the coupled atmosphere-ocean data assimilation problem and thus help guide the design and implementation of different coupling strategies within operational systems. This research is funded by the European Space Agency (ESA) and the UK Natural Environment Research Council (NERC). The ESA funded component is part of the Data Assimilation Projects - Coupled Model Data Assimilation initiative whose goal is to advance data assimilation techniques in fully coupled atmosphere-ocean models (see http://www.esa-da.org/). It is being conducted in parallel to the development of prototype weakly coupled data assimilation systems at both the UK Met Office and ECMWF.

Bioconversion of Xylan to triglycerides by oil-rich yeasts. [Cryptococcus albidus; Cryptococcus terricoluus; Trichosporon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fall, R.; Phelps, P.; Spindler, D.

A series of lipid-accumulating yeasts was examined for their potential to saccharify xylan and accumulate triglyceride. Of the genera tested, including Candida, Cryptococcus, Lipomyces, Rhodosporidium, Rhodotorula, and Trichosporon, only Crytococcus and Trichosporon isolates saccharified xylan. All of the strains could assimilate xylose and accumuate triglyceride under nitrogen-limiting conditions. Strains of Cryptococcus albidus were found to be especially useful for a one-step saccharification of xylan coupled to triglyceride synthesis. Crytococcus terricolus, a strain constitutive for lipid accumulation, lacked extracellular xylanase, but did assimilate xylose and xylobiose and was able to continuously convert xylan to triglyceride if the culture medium was supplementedmore » with xylanase. 22 references.« less

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

NASA Astrophysics Data System (ADS)

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

A Global Data Assimilation System for Atmospheric Aerosol

NASA Technical Reports Server (NTRS)

daSilva, Arlindo

1999-01-01

We will give an overview of an aerosol data assimilation system which combines advances in remote sensing of atmospheric aerosols, aerosol modeling and data assimilation methodology to produce high spatial and temporal resolution 3D aerosol fields. Initially, the Goddard Aerosol Assimilation System (GAAS) will assimilate TOMS, AVHRR and AERONET observations; later we will include MODIS and MISR. This data assimilation capability will allows us to integrate complementing aerosol observations from these platforms, enabling the development of an assimilated aerosol climatology as well as a global aerosol forecasting system in support of field campaigns. Furthermore, this system provides an interactive retrieval framework for each aerosol observing satellites, in particular TOMS and AVHRR. The Goddard Aerosol Assimilation System (GAAS) takes advantage of recent advances in constituent data assimilation at DAO, including flow dependent parameterizations of error covariances and the proper consideration of model bias. For its prognostic transport model, GAAS will utilize the Goddard Ozone, Chemistry, Aerosol, Radiation and Transport (GOCART) model developed at NASA/GSFC Codes 916 and 910.3. GOCART includes the Lin-Rood flux-form, semi-Langrangian transport model with parameterized aerosol chemistry and physical processes for absorbing (dust and black carbon) and non-absorbing aerosols (sulfate and organic carbon). Observations and model fields are combined using a constituent version of DAO's Physical-space Statistical Analysis System (PSAS), including its adaptive quality control system. In this talk we describe the main components of this assimilation system and present preliminary results obtained by assimilating TOMS data.

Additive effects due to biochar and endophyte application enable soybean to enhance nutrient uptake and modulate nutritional parameters* #

PubMed Central

Waqas, Muhammad; Kim, Yoon-Ha; Khan, Abdul Latif; Shahzad, Raheem; Asaf, Sajjad; Hamayun, Muhammad; Kang, Sang-Mo; Khan, Muhammad Aaqil; Lee, In-Jung

2017-01-01

We studied the effects of hardwood-derived biochar (BC) and the phytohormone-producing endophyte Galactomyces geotrichum WLL1 in soybean (Glycine max (L.) Merr.) with respect to basic, macro-and micronutrient uptakes and assimilations, and their subsequent effects on the regulation of functional amino acids, isoflavones, fatty acid composition, total sugar contents, total phenolic contents, and 1,1-diphenyl-2-picrylhydrazyl (DPPH)-scavenging activity. The assimilation of basic nutrients such as nitrogen was up-regulated, leaving carbon, oxygen, and hydrogen unaffected in BC+G. geotrichum-treated soybean plants. In comparison, the uptakes of macro-and micronutrients fluctuated in the individual or co-application of BC and G. geotrichum in soybean plant organs and rhizospheric substrate. Moreover, the same attribute was recorded for the regulation of functional amino acids, isoflavones, fatty acid composition, total sugar contents, total phenolic contents, and DPPH-scavenging activity. Collectively, these results showed that BC+G. geotrichum-treated soybean yielded better results than did the plants treated with individual applications. It was concluded that BC is an additional nutriment source and that the G. geotrichum acts as a plant biostimulating source and the effects of both are additive towards plant growth promotion. Strategies involving the incorporation of BC and endophytic symbiosis may help achieve eco-friendly agricultural production, thus reducing the excessive use of chemical agents. PMID:28124840

Field Detection of Chemical Assimilation in A Basaltic Lava Flow

NASA Technical Reports Server (NTRS)

Young, K. E.; Bleacher, J. E.; Needham, D. H.; Evans, C. A.; Whelley, P. L.; Scheidt, S. P.; Williams, D. A.; Rogers, A. D.; Glotch, T.

2017-01-01

Lava channels are features seen throughout the inner Solar System, including on Earth, the Moon, and Mars. Flow emplacement is therefore a crucial process in the shaping of planetary surfaces. Many studies, including some completed by members of this team at the December 1974 lava flow, have investigated the dynamics of lava flow emplacement, both on Earth and on the Moon and how pre-flow terrain can impact final channel morphology, but far fewer have focused on how the compositional characteristics of the substrate over which a flow was em-placed influenced its final flow morphology. Within the length of one flow, it is common for flows to change in morphology, a quality linked to rheology (a function of multiple factors including viscosi-ty, temperature, composition, etc.). The relationship between rheology and temperature has been well-studied but less is known about the relationship between an older flow's chemistry and how the interaction between this flow and the new flow might affect lava rheology and therefore emplacement dynamics. Lava erosion. Through visual observations of active terrestrial flows, mechanical erosion by flowing lava has been well-documented. Lava erosion by which flow composition is altered as the active lava melts and assimilates the pre-flow terrain over which it moves is also hypothesized to affect channel formation. However, there is only one previous field study that geochemically documents the process in recent basaltic flow systems.

Applying meta-pathway analyses through metagenomics to identify the functional properties of the major bacterial communities of a single spontaneous cocoa bean fermentation process sample.

PubMed

Illeghems, Koen; Weckx, Stefan; De Vuyst, Luc

2015-09-01

A high-resolution functional metagenomic analysis of a representative single sample of a Brazilian spontaneous cocoa bean fermentation process was carried out to gain insight into its bacterial community functioning. By reconstruction of microbial meta-pathways based on metagenomic data, the current knowledge about the metabolic capabilities of bacterial members involved in the cocoa bean fermentation ecosystem was extended. Functional meta-pathway analysis revealed the distribution of the metabolic pathways between the bacterial members involved. The metabolic capabilities of the lactic acid bacteria present were most associated with the heterolactic fermentation and citrate assimilation pathways. The role of Enterobacteriaceae in the conversion of substrates was shown through the use of the mixed-acid fermentation and methylglyoxal detoxification pathways. Furthermore, several other potential functional roles for Enterobacteriaceae were indicated, such as pectinolysis and citrate assimilation. Concerning acetic acid bacteria, metabolic pathways were partially reconstructed, in particular those related to responses toward stress, explaining their metabolic activities during cocoa bean fermentation processes. Further, the in-depth metagenomic analysis unveiled functionalities involved in bacterial competitiveness, such as the occurrence of CRISPRs and potential bacteriocin production. Finally, comparative analysis of the metagenomic data with bacterial genomes of cocoa bean fermentation isolates revealed the applicability of the selected strains as functional starter cultures. Copyright © 2015 Elsevier Ltd. All rights reserved.

Continuing Themes in Assimilation Through Education.

ERIC Educational Resources Information Center

Strouse, Joan

1987-01-01

Discusses assimilation and adaptation of immigrants in the United States. Summarizes major sociological theories on assimilation. Focuses on schools as instruments of assimilation that attempt to force Anglo-conformity upon students. The refugee student's perceptions of his or her problems and opportunities are discussed. (PS)

Agrobacterium uses a unique ligand-binding mode for trapping opines and acquiring a competitive advantage in the niche construction on plant host.

PubMed

Lang, Julien; Vigouroux, Armelle; Planamente, Sara; El Sahili, Abbas; Blin, Pauline; Aumont-Nicaise, Magali; Dessaux, Yves; Moréra, Solange; Faure, Denis

2014-10-01

By modifying the nuclear genome of its host, the plant pathogen Agrobacterium tumefaciens induces the development of plant tumours in which it proliferates. The transformed plant tissues accumulate uncommon low molecular weight compounds called opines that are growth substrates for A. tumefaciens. In the pathogen-induced niche (the plant tumour), a selective advantage conferred by opine assimilation has been hypothesized, but not experimentally demonstrated. Here, using genetics and structural biology, we deciphered how the pathogen is able to bind opines and use them to efficiently compete in the plant tumour. We report high resolution X-ray structures of the periplasmic binding protein (PBP) NocT unliganded and liganded with the opine nopaline (a condensation product of arginine and α-ketoglurate) and its lactam derivative pyronopaline. NocT exhibited an affinity for pyronopaline (K(D) of 0.6 µM) greater than that for nopaline (KD of 3.7 µM). Although the binding-mode of the arginine part of nopaline/pyronopaline in NocT resembled that of arginine in other PBPs, affinity measurement by two different techniques showed that NocT did not bind arginine. In contrast, NocT presented specific residues such as M117 to stabilize the bound opines. NocT relatives that exhibit the nopaline/pyronopaline-binding mode were only found in genomes of the genus Agrobacterium. Transcriptomics and reverse genetics revealed that A. tumefaciens uses the same pathway for assimilating nopaline and pyronopaline. Fitness measurements showed that NocT is required for a competitive colonization of the plant tumour by A. tumefaciens. Moreover, even though the Ti-plasmid conjugal transfer was not regulated by nopaline, the competitive advantage gained by the nopaline-assimilating Ti-plasmid donors led to a preferential horizontal propagation of this Ti-plasmid amongst the agrobacteria colonizing the plant-tumour niche. This work provided structural and genetic evidences to support the niche construction paradigm in bacterial pathogens.

Agrobacterium Uses a Unique Ligand-Binding Mode for Trapping Opines and Acquiring A Competitive Advantage in the Niche Construction on Plant Host

PubMed Central

Planamente, Sara; El Sahili, Abbas; Blin, Pauline; Aumont-Nicaise, Magali; Dessaux, Yves; Moréra, Solange; Faure, Denis

2014-01-01

By modifying the nuclear genome of its host, the plant pathogen Agrobacterium tumefaciens induces the development of plant tumours in which it proliferates. The transformed plant tissues accumulate uncommon low molecular weight compounds called opines that are growth substrates for A. tumefaciens. In the pathogen-induced niche (the plant tumour), a selective advantage conferred by opine assimilation has been hypothesized, but not experimentally demonstrated. Here, using genetics and structural biology, we deciphered how the pathogen is able to bind opines and use them to efficiently compete in the plant tumour. We report high resolution X-ray structures of the periplasmic binding protein (PBP) NocT unliganded and liganded with the opine nopaline (a condensation product of arginine and α-ketoglurate) and its lactam derivative pyronopaline. NocT exhibited an affinity for pyronopaline (KD of 0.6 µM) greater than that for nopaline (KD of 3.7 µM). Although the binding-mode of the arginine part of nopaline/pyronopaline in NocT resembled that of arginine in other PBPs, affinity measurement by two different techniques showed that NocT did not bind arginine. In contrast, NocT presented specific residues such as M117 to stabilize the bound opines. NocT relatives that exhibit the nopaline/pyronopaline-binding mode were only found in genomes of the genus Agrobacterium. Transcriptomics and reverse genetics revealed that A. tumefaciens uses the same pathway for assimilating nopaline and pyronopaline. Fitness measurements showed that NocT is required for a competitive colonization of the plant tumour by A. tumefaciens. Moreover, even though the Ti-plasmid conjugal transfer was not regulated by nopaline, the competitive advantage gained by the nopaline-assimilating Ti-plasmid donors led to a preferential horizontal propagation of this Ti-plasmid amongst the agrobacteria colonizing the plant-tumour niche. This work provided structural and genetic evidences to support the niche construction paradigm in bacterial pathogens. PMID:25299655

Ensemble-Based Assimilation of Aerosol Observations in GEOS-5

NASA Technical Reports Server (NTRS)

Buchard, V.; Da Silva, A.

2016-01-01

MERRA-2 is the latest Aerosol Reanalysis produced at NASA's Global Modeling Assimilation Office (GMAO) from 1979 to present. This reanalysis is based on a version of the GEOS-5 model radiatively coupled to GOCART aerosols and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from AVHRR over ocean, MODIS sensors on both Terra and Aqua satellites, MISR over bright surfaces and AERONET data. In order to assimilate lidar profiles of aerosols, we are updating the aerosol component of our assimilation system to an Ensemble Kalman Filter (EnKF) type of scheme using ensembles generated routinely by the meteorological assimilation. Following the work performed with the first NASA's aerosol reanalysis (MERRAero), we first validate the vertical structure of MERRA-2 aerosol assimilated fields using CALIOP data over regions of particular interest during 2008.

Comparison of different assimilation schemes in an operational assimilation system with Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Yan, Yajing; Barth, Alexander; Beckers, Jean-Marie; Candille, Guillem; Brankart, Jean-Michel; Brasseur, Pierre

2016-04-01

In this paper, four assimilation schemes, including an intermittent assimilation scheme (INT) and three incremental assimilation 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 three IAU schemes differ from each other in the position of the increment update window that has the same size as the assimilation window. 0, 50 and 100 correspond to the degree of superposition of the increment update window on the current assimilation window. Sea surface height, sea surface temperature, and temperature profiles at depth collected between January and December 2005 are assimilated. Sixty ensemble members are generated by adding realistic noise to the forcing parameters related to the temperature. The ensemble is diagnosed and validated by comparison between the ensemble spread and the model/observation difference, as well as by rank histogram before the assimilation experiments The relevance of each assimilation scheme is evaluated through analyses on thermohaline variables and the current velocities. The results of the assimilation are assessed according to both deterministic and probabilistic metrics with independent/semi-independent observations. For deterministic validation, the ensemble means, together with the ensemble spreads are compared to the observations, in order to diagnose the ensemble distribution properties in a deterministic way. 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 centered random variable (RCRV) score in order to investigate the reliability properties of the ensemble forecast system.

The Influence of Maternal Acculturation, Neighborhood Disadvantage, and Parenting on Chinese American Adolescents' Conduct Problems: Testing the Segmented Assimilation Hypothesis

ERIC Educational Resources Information Center

Liu, Lisa L.; Lau, Anna S.; Chen, Angela Chia-Chen; Dinh, Khanh T.; Kim, Su Yeong

2009-01-01

Associations among neighborhood disadvantage, maternal acculturation, parenting and conduct problems were investigated in a sample of 444 Chinese American adolescents. Adolescents (54% female, 46% male) ranged from 12 to 15 years of age (mean age = 13.0 years). Multilevel modeling was employed to test the hypothesis that the association between…

Assimilation of Stratospheric Meteorological and Constituent Observations: A Review

NASA Technical Reports Server (NTRS)

Rood, Richard B.; Pawson, Steven

2004-01-01

This talk reviews the assimilation of meteorological and constituent observations of the stratosphere. The first efforts to assimilate observations into stratospheric models were during the early 1980s, and a number of research studies followed during the next decade. Since the launch of the Upper Atmospheric Research Satellite (UARS) in 1991, model-assimilated data sets of the stratospheric meteorological state have been routinely available. These assimilated data sets were critical in bringing together observations from the different instruments on UARS as well as linking UARS observations to measurements from other platforms. Using trajectory-mapping techniques, meteorological assimilation analyses are, now, widely used in the analysis of constituent observations and have increased the level of quantitative study of stratospheric chemistry and transport. During the 1990s the use of winds and temperatures from assimilated data sets became standard for offline chemistry and transport modeling. variability in middle latitudes. The transport experiments, however, reveal a set of shortcomings that become obvious as systematic errors are integrated over time. Generally, the tropics are not well represented, mixing between the tropics and middle latitudes is overestimated, and the residual circulation is not accurate. These shortcomings reveal underlying fundamental challenges related to bias and noise. Current studies using model simulation and data assimilation in controlled experimentation are highlighting the issues that must be addressed if assimilated data sets are to be convincingly used to study interannual variability and decadal change. observations. The primary focus has been on stratospheric ozone, but there are efforts that investigate a suite of reactive chemical constituents. Recent progress in ozone assimilation shows the potential of assimilation to contribute to the validation of ozone observations and, ultimately, the retrieval of ozone profiles from space-based radiance measurements. Assimilated data sets provide accurate analyses of synoptic and planetary Scale At the same time, stratospheric assimilation is evolving to include constituent

DasPy – Open Source Multivariate Land Data Assimilation Framework with High Performance Computing

NASA Astrophysics Data System (ADS)

Han, Xujun; Li, Xin; Montzka, Carsten; Kollet, Stefan; Vereecken, Harry; Hendricks Franssen, Harrie-Jan

2015-04-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. Multivariate data assimilation refers to the simultaneous assimilation of observation data for multiple model state variables into a simulation model. Our main motivation was to develop an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with C++ and Fortran language. This system has been evaluated in several soil moisture, L-band brightness temperature and land surface temperature assimilation studies. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be represented by perturbed atmospheric forcings, perturbed soil and vegetation properties and model initial conditions. The CLM4.5 (Community Land Model) was integrated as the model operator. The CMEM (Community Microwave Emission Modelling Platform), COSMIC (COsmic-ray Soil Moisture Interaction Code) and the two source formulation were integrated as observation operators for assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy is parallelized using the hybrid MPI (Message Passing Interface) and OpenMP (Open Multi-Processing) techniques. All the input and output data flow is organized efficiently using the commonly used NetCDF file format. Online 1D and 2D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

Impact of assimilating GOES imager clear-sky radiance with a rapid refresh assimilation system for convection-permitting forecast over Mexico

NASA Astrophysics Data System (ADS)

Yang, Chun; Liu, Zhiquan; Gao, Feng; Childs, Peter P.; Min, Jinzhong

2017-05-01

The Geostationary Operational Environmental Satellite (GOES) imager data could provide a continuous image of the evolutionary pattern of severe weather phenomena with its high spatial and temporal resolution. The capability to assimilate the GOES imager radiances has been developed within the Weather Research and Forecasting model's data assimilation system. Compared to the benchmark experiment with no GOES imager data, the impact of assimilating GOES imager radiances on the analysis and forecast of convective process over Mexico in 7-10 March 2016 was assessed through analysis/forecast cycling experiments using rapid refresh assimilation system with hybrid-3DEnVar scheme. With GOES imager radiance assimilation, better analyses were obtained in terms of the humidity, temperature, and simulated water vapor channel brightness temperature distribution. Positive forecast impacts from assimilating GOES imager radiance were seen when verified against the Tropospheric Airborne Meteorological Data Reporting observation, GOES imager observation, and Mexico station precipitation data.

Validation of trophic and anthropic underwater noise as settlement trigger in blue mussels

NASA Astrophysics Data System (ADS)

Jolivet, Aurélie; Tremblay, Rejean; Olivier, Fréderic; Gervaise, Cédric; Sonier, Rémi; Genard, Bertrand; Chauvaud, Laurent

2016-09-01

Like the majority of benthic invertebrates, the blue mussel Mytilus edulis has a bentho-pelagic cycle with its larval settlement being a complex phenomenon involving numerous factors. Among these factors, underwater noise and pelagic trophic conditions have been weakly studied in previous researches. Under laboratory conditions, we tested the hypothesis that picoplankton assimilation by the pediveliger blue mussel larvae acts as a food cue that interacts with anthropic underwater sound to stimulate settlement. We used 13C-labeling microalgae to validate the assimilation of different picoplankton species in the tissues of pediveliger larvae. Our results clearly confirm our hypothesis with a significant synergic effect of these two factors. However, only the picoeukaryotes strains assimilated by larvae stimulated the settlement, whereas the non-ingested picocyanobacteria did not. Similar positive responses were observed with underwater sound characterized by low frequency vessel noises. The combination of both factors (trophic and vessel noise) drastically increased the mussel settlement by an order of 4 compared to the control (without picoplankton and noise). Settlement levels ranged from 16.5 to 67% in 67 h.

Gender differences in identity processes and self-esteem in middle and later adulthood.

PubMed

Skultety, Karyn M; Krauss Whitbourne, Susan

2004-01-01

Gender differences were examined in the identity processes of identity assimilation (maintaining identity despite age changes), identity accommodation (changing identity) and balance (using both processes) and in the relationship of these processes to self-esteem. We tested a community sample of 222 adults (131 females and 91 males) ranging from 40 to 84 years of age (M = 57.5, SD = 12.1). Analysis of variance yielded evidence showing greater use of identity accommodation for women. Identity accommodation was negatively associated with self-esteem for both genders, while identity assimilation was positively associated with self-esteem for women only. For both men and women, identity balance was positively related to self-esteem. Women's use of the identity processes in relation to self-esteem is discussed. Societal views on aging are suggested to impact women, such that they engage in identity accommodation while benefiting from identity assimilation. From these findings, it appears that examining the processes contributing to the maintenance of self-esteem may be a more useful approach to characterizing the aging process and gender differences than focusing on mean differences alone.

Assimilation of L2 vowels to L1 phonemes governs L2 learning in adulthood: a behavioral and ERP study

PubMed Central

Grimaldi, Mirko; Sisinni, Bianca; Gili Fivela, Barbara; Invitto, Sara; Resta, Donatella; Alku, Paavo; Brattico, Elvira

2014-01-01

According to the Perceptual Assimilation Model (PAM), articulatory similarity/dissimilarity between sounds of the second language (L2) and the native language (L1) governs L2 learnability in adulthood and predicts L2 sound perception by naïve listeners. We performed behavioral and neurophysiological experiments on two groups of university students at the first and fifth years of the English language curriculum and on a group of naïve listeners. Categorization and discrimination tests, as well as the mismatch negativity (MMN) brain response to L2 sound changes, showed that the discriminatory capabilities of the students did not significantly differ from those of the naïve subjects. In line with the PAM model, we extend the findings of previous behavioral studies showing that, at the neural level, classroom instruction in adulthood relies on assimilation of L2 vowels to L1 phoneme categories and does not trigger improvement in L2 phonetic discrimination. Implications for L2 classroom teaching practices are discussed. PMID:24860470

Social Relationships, Social Assimilation, and Substance-Use Disorders among Adult Latinos in the U.S

PubMed Central

Canino, Glorisa; Vega, William A.; Sribney, William M.; Warner, Lynn A.; Alegría, Margarita

2009-01-01

Based on social control perspectives and results from prior studies we test hypotheses about the extent to which characteristics of family and social networks are associated with substance use disorders (SUD), and whether these associations vary by sex. In this study SUD is alcohol or illicit drug abuse or dependence as defined by criteria of the Diagnostic and Statistical Manual of the American Psychiatric Association. With nationally representative data of adult Latinos from the National Latino and Asian American Survey (NLAAS), we found that respondents’ language use with family, rather than language proficiency, appears to be a more efficient proxy for social assimilation to represent differential levels of risk of SUD. SUD was positively associated with problematic family relations for men but not women, and SUD was positively associated with more frequent interactions with friends for women but not men. The results suggest that the salient features of social assimilation associated with SUD include the context of language use and transformations in family and social network relationships that differ in important ways between Latino men and women. PMID:20011228

Farmland Drought Evaluation Based on the Assimilation of Multi-Temporal Multi-Source Remote Sensing Data into AquaCrop Model

NASA Astrophysics Data System (ADS)

Yang, Guijun; Yang, Hao; Jin, Xiuliang; Pignatti, Stefano; Casa, Faffaele; Silverstro, Paolo Cosmo

2016-08-01

Drought is the most costly natural disasters in China and all over the world. It is very important to evaluate the drought-induced crop yield losses and further improve water use efficiency at regional scale. Firstly, crop biomass was estimated by the combined use of Synthetic Aperture Radar (SAR) and optical remote sensing data. Then the estimated biophysical variable was assimilated into crop growth model (FAO AquaCrop) by the Particle Swarm Optimization (PSO) method from farmland scale to regional scale.At farmland scale, the most important crop parameters of AquaCrop model were determined to reduce the used parameters in assimilation procedure. The Extended Fourier Amplitude Sensitivity Test (EFAST) method was used for assessing the contribution of different crop parameters to model output. Moreover, the AquaCrop model was calibrated using the experiment data in Xiaotangshan, Beijing.At regional scale, spatial application of our methods were carried out and validated in the rural area of Yangling, Shaanxi Province, in 2014. This study will provide guideline to make irrigation decision of balancing of water consumption and yield loss.

The evolution of menstruation: A new model for genetic assimilation

PubMed Central

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

Genomic, proteomic, and biochemical analyses of oleaginous Mucor circinelloides: evaluating its capability in utilizing cellulolytic substrates for lipid production.

PubMed

Wei, Hui; Wang, Wei; Yarbrough, John M; Baker, John O; Laurens, Lieve; Van Wychen, Stefanie; Chen, Xiaowen; Taylor, Larry E; Xu, Qi; Himmel, Michael E; Zhang, Min

2013-01-01

Lipid production by oleaginous microorganisms is a promising route to produce raw material for the production of biodiesel. However, most of these organisms must be grown on sugars and agro-industrial wastes because they cannot directly utilize lignocellulosic substrates. We report the first comprehensive investigation of Mucor circinelloides, one of a few oleaginous fungi for which genome sequences are available, for its potential to assimilate cellulose and produce lipids. Our genomic analysis revealed the existence of genes encoding 13 endoglucanases (7 of them secretory), 3 β-D-glucosidases (2 of them secretory) and 243 other glycoside hydrolase (GH) proteins, but not genes for exoglucanases such as cellobiohydrolases (CBH) that are required for breakdown of cellulose to cellobiose. Analysis of the major PAGE gel bands of secretome proteins confirmed expression of two secretory endoglucanases and one β-D-glucosidase, along with a set of accessory cell wall-degrading enzymes and 11 proteins of unknown function. We found that M. circinelloides can grow on CMC (carboxymethyl cellulose) and cellobiose, confirming the enzymatic activities of endoglucanases and β-D-glucosidases, respectively. The data suggested that M. circinelloides could be made usable as a consolidated bioprocessing (CBP) strain by introducing a CBH (e.g. CBHI) into the microorganism. This proposal was validated by our demonstration that M. circinelloides growing on Avicel supplemented with CBHI produced about 33% of the lipid that was generated in glucose medium. Furthermore, fatty acid methyl ester (FAME) analysis showed that when growing on pre-saccharified Avicel substrates, it produced a higher proportion of C14 fatty acids, which has an interesting implication in that shorter fatty acid chains have characteristics that are ideal for use in jet fuel. This substrate-specific shift in FAME profile warrants further investigation.

Raman microspectroscopy for in situ examination of carbon-microbe-mineral interactions

NASA Astrophysics Data System (ADS)

Creamer, C.; Foster, A. L.; Lawrence, C. R.; Mcfarland, J. W.; Waldrop, M. P.

2016-12-01

The changing paradigm of soil organic matter formation and turnover is focused at the nexus of microbe-carbon-mineral interactions. However, visualizing biotic and abiotic stabilization of C on mineral surfaces is difficult given our current techniques. Therefore we investigated Raman microspectroscopy as a potential tool to examine microbially mediated organo-mineral associations. Raman microspectroscopy is a non-destructive technique that has been used to identify microorganisms and minerals, and to quantify microbial assimilation of 13C labeled substrates in culture. We developed a partial least squares regression (PLSR) model to accurately quantify (within 5%) adsorption of four model 12C substrates (glucose, glutamic acid, oxalic acid, p-hydroxybenzoic acid) on a range of soil minerals. We also developed a PLSR model to quantify the incorporation of 13C into E. coli cells. Using these two models, along with measures of the 13C content of respired CO2, we determined the allocation of glucose-derived C into mineral-associated microbial biomass and respired CO2 in situ and through time. We observed progressive 13C enrichment of microbial biomass with incubation time, as well as 13C enrichment of CO2 indicating preferential decomposition of glucose-derived C. We will also present results on the application of our in situ chamber to quantify the formation of organo-mineral associations under both abiotic and biotic conditions with a variety of C and mineral substrates, as well as the rate of turnover and stabilization of microbial residues. Application of Raman microspectroscopy to microbial-mineral interactions represents a novel method to quantify microbial transformation of C substrates and subsequent mineral stabilization without destructive sampling, and has the potential to provide new insights to our conceptual understanding of carbon-microbe-mineral interactions.

Variational assimilation of VAS data into the mass model

NASA Technical Reports Server (NTRS)

Cram, J. M.; Kaplan, M. L.

1984-01-01

Experiments are reported in which VAS data at 1200, 1500, and 1800 GMT 20 July 1981 were assimilated using both the adiabatic and full physics version of the Mesoscale Atmospheric Simulation System (MASS). A nonassimilation forecast is compared with forecasts assimilating temperature gradients only and forecasts assimilating both temperature and humidity gradients. The effects of successive vs single assimilations are also examined. It is noted that the greatest improvements to the forecast resulted when the VAS data resolved the mesoscale structure of the temperature and relative humidity fields. When this structure was assimilated into MASS, the ensuing simulations more clearly defined a mesoscale structure in the developing instabilities.

Application of data assimilation methods for analysis and integration of observed and modeled Arctic Sea ice motions

NASA Astrophysics Data System (ADS)

Meier, Walter Neil

This thesis demonstrates the applicability of data assimilation methods to improve observed and modeled ice motion fields and to demonstrate the effects of assimilated motion on Arctic processes important to the global climate and of practical concern to human activities. Ice motions derived from 85 GHz and 37 GHz SSM/I imagery and estimated from two-dimensional dynamic-thermodynamic sea ice models are compared to buoy observations. Mean error, error standard deviation, and correlation with buoys are computed for the model domain. SSM/I motions generally have a lower bias, but higher error standard deviations and lower correlation with buoys than model motions. There are notable variations in the statistics depending on the region of the Arctic, season, and ice characteristics. Assimilation methods are investigated and blending and optimal interpolation strategies are implemented. Blending assimilation improves error statistics slightly, but the effect of the assimilation is reduced due to noise in the SSM/I motions and is thus not an effective method to improve ice motion estimates. However, optimal interpolation assimilation reduces motion errors by 25--30% over modeled motions and 40--45% over SSM/I motions. Optimal interpolation assimilation is beneficial in all regions, seasons and ice conditions, and is particularly effective in regimes where modeled and SSM/I errors are high. Assimilation alters annual average motion fields. Modeled ice products of ice thickness, ice divergence, Fram Strait ice volume export, transport across the Arctic and interannual basin averages are also influenced by assimilated motions. Assimilation improves estimates of pollutant transport and corrects synoptic-scale errors in the motion fields caused by incorrect forcings or errors in model physics. The portability of the optimal interpolation assimilation method is demonstrated by implementing the strategy in an ice thickness distribution (ITD) model. This research presents an innovative method of combining a new data set of SSM/I-derived ice motions with three different sea ice models via two data assimilation methods. The work described here is the first example of assimilating remotely-sensed data within high-resolution and detailed dynamic-thermodynamic sea ice models. The results demonstrate that assimilation is a valuable resource for determining accurate ice motion in the Arctic.

A Module for Assimilating Hyperspectral Infrared Retrieved Profiles into the Gridpoint Statistical Interpolation System for Unique Forecasting Applications

NASA Technical Reports Server (NTRS)

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

2015-01-01

Hyperspectral infrared sounder radiance data are assimilated into operational modeling systems however the process is computationally expensive and only approximately 1% of available data are assimilated due to data thinning as well as the fact that radiances are restricted to cloud-free fields of view. In contrast, the number of hyperspectral infrared profiles assimilated is much higher since the retrieved profiles can be assimilated in some partly cloudy scenes due to profile coupling other data, such as microwave or neural networks, as first guesses to the retrieval process. As the operational data assimilation community attempts to assimilate cloud-affected radiances, it is possible that the use of retrieved profiles might offer an alternative methodology that is less complex and more computationally efficient to solve this problem. The NASA Short-term Prediction Research and Transition (SPoRT) Center has assimilated hyperspectral infrared retrieved profiles into Weather Research and Forecasting Model (WRF) simulations using the Gridpoint Statistical Interpolation (GSI) System. Early research at SPoRT demonstrated improved initial conditions when assimilating Atmospheric Infrared Sounder (AIRS) thermodynamic profiles into WRF (using WRF-Var and assigning more appropriate error weighting to the profiles) to improve regional analysis and heavy precipitation forecasts. Successful early work has led to more recent research utilizing WRF and GSI for applications including the assimilation of AIRS profiles to improve WRF forecasts of atmospheric rivers and assimilation of AIRS, Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI) profiles to improve model representation of tropopause folds and associated non-convective wind events. Although more hyperspectral infrared retrieved profiles can be assimilated into model forecasts, one disadvantage is the retrieved profiles have traditionally been assigned the same error values as the rawinsonde observations when assimilated with GSI. Typically, satellitederived profile errors are larger and more difficult to quantify than traditional rawinsonde observations (especially in the boundary layer), so it is important to appropriately assign observation errors within GSI to eliminate potential spurious innovations and analysis increments that can sometimes arise when using retrieved profiles. The goal of this study is to describe modifications to the GSI source code to more appropriately assimilate hyperspectral infrared retrieved profiles and outline preliminary results that show the differences between a model simulation that assimilated the profiles as rawinsonde observations and one that assimilated the profiles in a module with the appropriate error values.

Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J.M.; Reichle, Rolf H.; Houser, Paul R.; Arsenault, Kristi R.; Verhoest, Niko E.C.; Paulwels, Valentijn R.N.

2009-01-01

An ensemble Kalman filter (EnKF) is used in a suite of synthetic experiments to assimilate coarse-scale (25 km) snow water equivalent (SWE) observations (typical of satellite retrievals) into fine-scale (1 km) model simulations. Coarse-scale observations are assimilated directly using an observation operator for mapping between the coarse and fine scales or, alternatively, after disaggregation (re-gridding) to the fine-scale model resolution prior to data assimilation. In either case observations are assimilated either simultaneously or independently for each location. Results indicate that assimilating disaggregated fine-scale observations independently (method 1D-F1) is less efficient than assimilating a collection of neighboring disaggregated observations (method 3D-Fm). Direct assimilation of coarse-scale observations is superior to a priori disaggregation. Independent assimilation of individual coarse-scale observations (method 3D-C1) can bring the overall mean analyzed field close to the truth, but does not necessarily improve estimates of the fine-scale structure. There is a clear benefit to simultaneously assimilating multiple coarse-scale observations (method 3D-Cm) even as the entire domain is observed, indicating that underlying spatial error correlations can be exploited to improve SWE estimates. Method 3D-Cm avoids artificial transitions at the coarse observation pixel boundaries and can reduce the RMSE by 60% when compared to the open loop in this study.

Assimilation of SBUV Version 8 Radiances into the GEOS Ozone DAS

NASA Technical Reports Server (NTRS)

Mueller, Martin D.; Stajner, Ivanka; Bhartia, Pawan K.

2004-01-01

In operational weather forecasting, the assimilation of brightness temperatures from satellite sounders, instead of assimilation of 1D-retrievals has become increasingly common practice over the last two decades. Compared to these systems, assimilation of trace gases is still at a relatively early stage of development, and efforts to directly assimilate radiances instead of retrieved products have just begun a few years ago, partially because it requires much more computation power due to the employment of a radiative transport forward model (FM). This paper will focus on a method to assimilate SBUV/2 radiances (albedos) into the Global Earth Observation System Ozone Data Assimilation Scheme (GEOS-03DAS). While SBUV-type instruments cannot compete with newer sensors in terms of spectral and horizontal resolution, they feature a continuous data record back to 1978, which makes them very valuable for trend studies. Assimilation can help spreading their ground coverage over the whole globe, as has been previously demonstrated with the GEOS-03DAS using SBUV Version 6 ozone profiles. Now, the DAS has been updated to use the newly released SBUV Version 8 data. We will compare pre]lmlnarv results of SBUV radiance assimilation with the assimilation of retrieved ozone profiles, discuss methods to deal with the increased computational load, and try to assess the error characteristics and future potential of the new approach.

Changes in symptom intensity and emotion valence during the process of assimilation of a problematic experience: A quantitative study of a good outcome case of cognitive-behavioral therapy.

PubMed

Basto, Isabel; Pinheiro, Patrícia; Stiles, William B; Rijo, Daniel; Salgado, João

2017-07-01

The assimilation model describes the change process in psychotherapy. In this study we analyzed the relation of assimilation with changes in symptom intensity, measured session by session, and changes in emotional valence, measured for each emotional episode, in the case of a 33-year-old woman treated for depression with cognitive-behavioral therapy. Results showed the theoretically expected negative relation between assimilation of the client's main concerns and symptom intensity, and the relation between assimilation levels and emotional valence corresponded closely to the assimilation model's theoretical feelings curve. The results show how emotions work as markers of the client's current assimilation level, which could help the therapist adjust the intervention, moment by moment, to the client's needs.

Structure of Methylobacterium extorquens malyl-CoA lyase: CoA-substrate binding correlates with domain shift

DOE PAGES

Gonzalez, Javier M.; Marti-Arbona, Ricardo; Chen, Julian C. -H.; ...

2017-01-27

Malyl-CoA lyase (MCL) is an Mg 2+-dependent enzyme that catalyzes the reversible cleavage of (2 S)-4-malyl-CoA to yield acetyl-CoA and glyoxylate. MCL enzymes, which are found in a variety of bacteria, are members of the citrate lyase-like family and are involved in the assimilation of one- and two-carbon compounds. Here, the 1.56 Å resolution X-ray crystal structure of MCL from Methylobacterium extorquens AM1 with bound Mg 2+is presented. Structural alignment with the closely related Rhodobacter sphaeroides malyl-CoA lyase complexed with Mg 2+, oxalate and CoA allows a detailed analysis of the domain motion of the enzyme caused by substrate binding.more » Alignment of the structures shows that a simple hinge motion centered on the conserved residues Phe268 and Thr269 moves the C-terminal domain by about 30° relative to the rest of the molecule. Furthermore, this domain motion positions a conserved aspartate residue located in the C-terminal domain in the active site of the adjacent monomer, which may serve as a general acid/base in the catalytic mechanism.« less

Structure of Methylobacterium extorquens malyl-CoA lyase: CoA-substrate binding correlates with domain shift

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gonzalez, Javier M.; Marti-Arbona, Ricardo; Chen, Julian C. -H.

Malyl-CoA lyase (MCL) is an Mg 2+-dependent enzyme that catalyzes the reversible cleavage of (2 S)-4-malyl-CoA to yield acetyl-CoA and glyoxylate. MCL enzymes, which are found in a variety of bacteria, are members of the citrate lyase-like family and are involved in the assimilation of one- and two-carbon compounds. Here, the 1.56 Å resolution X-ray crystal structure of MCL from Methylobacterium extorquens AM1 with bound Mg 2+is presented. Structural alignment with the closely related Rhodobacter sphaeroides malyl-CoA lyase complexed with Mg 2+, oxalate and CoA allows a detailed analysis of the domain motion of the enzyme caused by substrate binding.more » Alignment of the structures shows that a simple hinge motion centered on the conserved residues Phe268 and Thr269 moves the C-terminal domain by about 30° relative to the rest of the molecule. Furthermore, this domain motion positions a conserved aspartate residue located in the C-terminal domain in the active site of the adjacent monomer, which may serve as a general acid/base in the catalytic mechanism.« less

Robust Hydrological Forecasting for High-resolution Distributed Models Using a Unified Data Assimilation Approach

NASA Astrophysics Data System (ADS)

Hernandez, F.; Liang, X.

2017-12-01

Reliable real-time hydrological forecasting, to predict important phenomena such as floods, is invaluable to the society. However, modern high-resolution distributed models have faced challenges when dealing with uncertainties that are caused by the large number of parameters and initial state estimations involved. Therefore, to rely on these high-resolution models for critical real-time forecast applications, considerable improvements on the parameter and initial state estimation techniques must be made. In this work we present a unified data assimilation algorithm called Optimized PareTo Inverse Modeling through Inverse STochastic Search (OPTIMISTS) to deal with the challenge of having robust flood forecasting for high-resolution distributed models. This new algorithm combines the advantages of particle filters and variational methods in a unique way to overcome their individual weaknesses. The analysis of candidate particles compares model results with observations in a flexible time frame, and a multi-objective approach is proposed which attempts to simultaneously minimize differences with the observations and departures from the background states by using both Bayesian sampling and non-convex evolutionary optimization. Moreover, the resulting Pareto front is given a probabilistic interpretation through kernel density estimation to create a non-Gaussian distribution of the states. OPTIMISTS was tested on a low-resolution distributed land surface model using VIC (Variable Infiltration Capacity) and on a high-resolution distributed hydrological model using the DHSVM (Distributed Hydrology Soil Vegetation Model). In the tests streamflow observations are assimilated. OPTIMISTS was also compared with a traditional particle filter and a variational method. Results show that our method can reliably produce adequate forecasts and that it is able to outperform those resulting from assimilating the observations using a particle filter or an evolutionary 4D variational method alone. In addition, our method is shown to be efficient in tackling high-resolution applications with robust results.

The Global Structure of UTLS Ozone in GEOS-5: A Multi-Year Assimilation of EOS Aura Data

NASA Technical Reports Server (NTRS)

Wargan, Krzysztof; Pawson, Steven; Olsen, Mark A.; Witte, Jacquelyn C.; Douglass, Anne R.; Ziemke, Jerald R.; Strahan, Susan E.; Nielsen, J. Eric

2015-01-01

Eight years of ozone measurements retrieved from the Ozone Monitoring Instrument (OMI) and the Microwave Limb Sounder, both on the EOS Aura satellite, have been assimilated into the Goddard Earth Observing System version 5 (GEOS-5) data assimilation system. This study thoroughly evaluates this assimilated product, highlighting its potential for science. The impact of observations on the GEOS-5 system is explored by examining the spatial distribution of the observation-minus-forecast statistics. Independent data are used for product validation. The correlation coefficient of the lower-stratospheric ozone column with ozonesondes is 0.99 and the bias is 0.5%, indicating the success of the assimilation in reproducing the ozone variability in that layer. The upper-tropospheric assimilated ozone column is about 10% lower than the ozonesonde column but the correlation is still high (0.87). The assimilation is shown to realistically capture the sharp cross-tropopause gradient in ozone mixing ratio. Occurrence of transport-driven low ozone laminae in the assimilation system is similar to that obtained from the High Resolution Dynamics Limb Sounder (HIRDLS) above the 400 K potential temperature surface but the assimilation produces fewer laminae than seen by HIRDLS below that surface. Although the assimilation produces 5 - 8 fewer occurrences per day (up to approximately 20%) during the three years of HIRDLS data, the interannual variability is captured correctly. This data-driven assimilated product is complementary to ozone fields generated from chemistry and transport models. Applications include study of the radiative forcing by ozone and tracer transport near the tropopause.

Culture Training: Validation Evidence for the Culture Assimilator.

ERIC Educational Resources Information Center

Mitchell, Terence R.; And Others

The culture assimilator, a programed self-instructional approach to culture training, is described and a series of laboratory experiments and field studies validating the culture assimilator are reviewed. These studies show that the culture assimilator is an effective method of decreasing some of the stress experienced when one works with people…

Bicultural Advertising and Hispanic Acculturation

ERIC Educational Resources Information Center

Tsai, Wan-Hsiu Sunny; Li, Cong

2012-01-01

This study examined the moderating effects of acculturation modes (assimilated, integrated, and separated) on Hispanic consumers' responses to three advertising targeting strategies (Caucasian targeted, bicultural, and Hispanic targeted). The hypotheses were empirically tested in a 3 x 3 factorial experiment with 155 self-identified Hispanic adult…

Initializing carbon cycle predictions from the Community Land Model by assimilating global biomass observations

NASA Astrophysics Data System (ADS)

Fox, A. M.; Hoar, T. J.; Smith, W. K.; Moore, D. J.

2017-12-01

The locations and longevity of terrestrial carbon sinks remain uncertain, however it is clear that in order to predict long-term climate changes the role of the biosphere in surface energy and carbon balance must be understood and incorporated into earth system models (ESMs). Aboveground biomass, the amount of carbon stored in vegetation, is a key component of the terrestrial carbon cycle, representing the balance of uptake through gross primary productivity (GPP), losses from respiration, senescence and mortality over hundreds of years. The best predictions of current and future land-atmosphere fluxes are likely from the integration of process-based knowledge contained in models and information from observations of changes in carbon stocks using data assimilation (DA). By exploiting long times series, it is possible to accurately detect variability and change in carbon cycle dynamics through monitoring ecosystem states, for example biomass derived from vegetation optical depth (VOD), and use this information to initialize models before making predictions. To make maximum use of information about the current state of global ecosystems when using models we have developed a system that combines the Community Land Model (CLM) with the Data Assimilation Research Testbed (DART), a community tool for ensemble DA. This DA system is highly innovative in its complexity, completeness and capabilities. Here we described a series of activities, using both Observation System Simulation Experiments (OSSEs) and real observations, that have allowed us to quantify the potential impact of assimilating VOD data into CLM-DART on future land-atmosphere fluxes. VOD data are particularly suitable to use in this activity due to their long temporal coverage and appropriate scale when combined with CLM, but their absolute values rely on many assumptions. Therefore, we have had to assess the implications of the VOD retrieval algorithms, with an emphasis on detecting uncertainty due to assumptions and inputs in the algorithms that are incompatible with those encoded within CLM. It is probable that VOD describes changes in biomass more accurately than absolute values, so in additional to sequential assimilation of observations, we have tested alternative filter algorithms, and assimilating VOD anomalies.

"Big Data Assimilation" for 30-second-update 100-m-mesh Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Miyoshi, Takemasa; Lien, Guo-Yuan; Kunii, Masaru; Ruiz, Juan; Maejima, Yasumitsu; Otsuka, Shigenori; Kondo, Keiichi; Seko, Hiromu; Satoh, Shinsuke; Ushio, Tomoo; Bessho, Kotaro; Kamide, Kazumi; Tomita, Hirofumi; Nishizawa, Seiya; Yamaura, Tsuyoshi; Ishikawa, Yutaka

2017-04-01

A typical lifetime of a single cumulonimbus is within an hour, and radar observations often show rapid changes in only a 5-minute period. For precise prediction of such rapidly-changing local severe storms, we have developed what we call a "Big Data Assimilation" (BDA) system that performs 30-second-update data assimilation cycles at 100-m grid spacing. The concept shares that of NOAA's Warn-on-Forecast (WoF), in which rapidly-updated high-resolution NWP will play a central role in issuing severe-storm warnings even only minutes in advance. The 100-m resolution and 30-second update frequency are a leap above typical recent research settings, and it was possible by the fortunate combination of Japan's most advanced supercomputing and sensing technologies: the 10-petaflops K computer and the Phased Array Weather Radar (PAWR). The X-band PAWR is capable of a dense three-dimensional volume scan at 100-m range resolution with 100 elevation angles and 300 azimuth angles, up to 60-km range within 30 seconds. The PAWR data show temporally-smooth evolution of convective rainstorms. This gives us a hope that we may assume the Gaussian error distribution in 30-second forecasts before strong nonlinear dynamics distort the error distribution for rapidly-changing convective storms. With this in mind, we apply the Local Ensemble Transform Kalman Filter (LETKF) that considers flow-dependent error covariance explicitly under the Gaussian-error assumption. The flow-dependence would be particularly important in rapidly-changing convective weather. Using a 100-member ensemble at 100-m resolution, we have tested the Big Data Assimilation system in real-world cases of sudden local rainstorms, and obtained promising results. However, the real-time application is a big challenge, and currently it takes 10 minutes for a cycle. We explore approaches to accelerating the computations, such as using single-precision arrays in the model computation and developing an efficient I/O middleware for passing the large data between model and data assimilation as quickly as possible. In this presentation, we will present the most up-to-date progress of our Big Data Assimilation research.

Probabilistic In Situ Stress Estimation and Forecasting using Sequential Data Assimilation

NASA Astrophysics Data System (ADS)

Fichtner, A.; van Dinther, Y.; Kuensch, H. R.

2017-12-01

Our physical understanding and forecasting ability of earthquakes, and other solid Earth dynamic processes, is significantly hampered by limited indications on the evolving state of stress and strength on faults. Integrating observations and physics-based numerical modeling to quantitatively estimate this evolution of a fault's state is crucial. However, systematic attempts are limited and tenuous, especially in light of the scarcity and uncertainty of natural data and the difficulty of modelling the physics governing earthquakes. We adopt the statistical framework of sequential data assimilation - extensively developed for weather forecasting - to efficiently integrate observations and prior knowledge in a forward model, while acknowledging errors in both. To prove this concept we perform a perfect model test in a simplified subduction zone setup, where we assimilate synthetic noised data on velocities and stresses from a single location. Using an Ensemble Kalman Filter, these data and their errors are assimilated to update 150 ensemble members from a Partial Differential Equation-driven seismic cycle model. Probabilistic estimates of fault stress and dynamic strength evolution capture the truth exceptionally well. This is possible, because the sampled error covariance matrix contains prior information from the physics that relates velocities, stresses and pressure at the surface to those at the fault. During the analysis step, stress and strength distributions are thus reconstructed such that fault coupling can be updated to either inhibit or trigger events. In the subsequent forecast step the physical equations are solved to propagate the updated states forward in time and thus provide probabilistic information on the occurrence of the next event. At subsequent assimilation steps, the system's forecasting ability turns out to be significantly better than that of a periodic recurrence model (requiring an alarm 17% vs. 68% of the time). This thus provides distinct added value with respect to using observations or numerical models separately. Although several challenges for applications to a natural setting remain, these first results indicate the large potential of data assimilation techniques for probabilistic seismic hazard assessment and other challenges in dynamic solid earth systems.

Methanol Metabolism in Pseudomonad C

PubMed Central

Stieglitz, B.; Mateles, R. I.

1973-01-01

Cell suspensions of pseudomonad C, a bacterium capable of growth on methanol as sole carbon source, were able to oxidize methanol, formaldehyde, and formate, although the rates of oxidation for the latter two compounds were much slower. The latter compounds also could not serve as sole carbon sources. Through the use of labeled compounds, it was shown that in the presence of methanol, formaldehyde, formate, and bicarbonate were incorporated into trichloroacetic acid-precipitable material. Hexose phosphate synthetase activity was found, indicating the assimilation of methanol via an allulose pathway. No hydroxypyruvate reductase activity was found, nor was any complex membrane structure observed. Such a combination of characteristics has been observed in an obligate methylotroph (Pseudomonas W1), but pseudomonad C can utilize a variety of non-methyl substrates. Images PMID:4349032

Using augmented reality to teach and learn biochemistry.

PubMed

Vega Garzón, Juan Carlos; Magrini, Marcio Luiz; Galembeck, Eduardo

2017-09-01

Understanding metabolism and metabolic pathways constitutes one of the central aims for students of biological sciences. Learning metabolic pathways should be focused on the understanding of general concepts and core principles. New technologies such Augmented Reality (AR) have shown potential to improve assimilation of biochemistry abstract concepts because students can manipulate 3D molecules in real time. Here we describe an application named Augmented Reality Metabolic Pathways (ARMET), which allowed students to visualize the 3D molecular structure of substrates and products, thus perceiving changes in each molecule. The structural modification of molecules shows students the flow and exchange of compounds and energy through metabolism. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(5):417-420, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

[Effect of excess ethanol on the growth of yeasts of the genus Candida during continuous cultivation].

PubMed

Shkidchenko, A N; Shul'ga, A V; Gurina, L V

1988-01-01

The effect of flow rates and a specific ethanol load on the growth of Candida utilis and Candida krusei was studied in the process of one-step and three-step cultivation. The productive capacity of fermenters and the economic coefficient of yeast biomass production were shown to depend on the ability of microbial populations to assimilate a certain quantity of a carbon substrate per unit time. When a specific ethanol load exceeds the optimal one, the respiratory activity of a population and the economic coefficient of growth fall down whereas the accumulation of metabolites in the cultural broth increases. The steady state of biomass can be maintained in the process of continuous cultivation by inhibiting the yeast growth with an excess of ethanol.

The effect of a reciprocal peat transplant between two contrasting Central European sites on C cycling and C isotope ratios

NASA Astrophysics Data System (ADS)

Novak, M.; Zemanova, L.; Buzek, F.; Jackova, I.; Adamova, M.; Komarek, A.; Vile, M. A.; Kelman Wieder, R.; Stepanova, M.

2010-03-01

An 18-month reciprocal peat transplant experiment was conducted between two peatlands in the Czech Republic. Both sites were 100% Sphagnum-covered, with no vascular plants, and no hummocks and hollows. Atmospheric depositions of sulfur were up to 10 times higher at the northern site Velke jerabi jezero (VJJ), compared to the southern site Cervene blato (CB). Forty-cm deep peat cores, 10-cm in diameter, were used as transplants and controls in five replicates. Our objective was to evaluate whether CO2 and CH4 emissions from Sphagnum peat bogs are governed mainly by organic matter quality in the substrate, or by environmental conditions. Emission rates and δ13C values of CO2 and CH4 were measured in the laboratory at time t=18 months. All measured parameters converged to those of the host site, indicating that, at least in the short-term perspective, environmental conditions were a more important control of greenhouse gas emissions than organic carbon quality in the substrate. Since sulfate reducers outcompete methanogens, we hypothesized that the S-polluted site VJJ should have lower methane emissions than CB. In fact, the opposite was true, with significantly (p<0.01) higher methane emissions from VJJ. Additionally, as a first step in an effort to link C isotope composition of emitted gases and residual peat substrate, we determined whether multiple vertical δ13C profiles in peat agree. A high degree of within-site homogeneity in δ13C was found. When a specific vertical δ13C trend was seen in one peat core, the same trend was also seen in all the remaining peat cores from the wetland. The δ13C value increased downcore at both CB and VJJ. At VJJ, however, 20 cm below surface, a reversal to lower δ13C downcore was seen. Based on 210Pb dating, peat at 20-cm depth at VJJ was only 15 years old. Increasing δ13C values in VJJ peat accumulated between 1880-1990 could not be caused by assimilation of atmospheric CO2 gradually enriched in the light isotope 12C due to fossil fuel burning. Rather they were a result of a combination of isotope fractionations accompanying assimilation and mineralization of Sphagnum C. These isotope fractionations may record information about past changes in C storage in wetlands.

A Novel High-Throughput 1536-well Notch1 γ-Secretase AlphaLISA Assay

PubMed Central

Chau, De-ming; Shum, David; Radu, Constantin; Bhinder, Bhavneet; Gin, David; Gilchrist, M. Lane; Djaballah, Hakim; Li, Yue-Ming

2013-01-01

The Notch pathway plays a crucial role in cell fate decisions through controlling various cellular processes. Overactive Notch signal contributes to cancer development from leukemias to solid tumors. γ-Secretase is an intramembrane protease responsible for the final proteolytic step of Notch that releases the membrane-tethered Notch fragment for signaling. Therefore, γ-secretase is an attractive drug target in treating Notch-mediated cancers. However, the absence of high-throughput γ-secretase assay using Notch substrate has limited the identification and development of γ-secretase inhibitors that specifically target the Notch signaling pathway. Here, we report on the development of a 1536-well γ-secretase assay using a biotinylated recombinant Notch1 substrate. We effectively assimilated and miniaturized this newly developed Notch1 substrate with the AlphaLISA detection technology and demonstrated its robustness with a calculated Z’ score of 0.66. We further validated this optimized assay by performing a pilot screening against a chemical library consisting of ~5,600 chemicals and identified known γ-secretase inhibitors e.g. DAPT, and Calpeptin; as well as a novel γ-secretase inhibitor referred to as KD-I-085. This assay is the first reported 1536-well AlphaLISA format and represents a novel high-throughput Notch1-γ-secretase assay, which provides an unprecedented opportunity to discover Notch-selective γ-secretase inhibitors that can be potentially used for the treatment of cancer and other human disorders. PMID:23448293

Versatile transformations of hydrocarbons in anaerobic bacteria: substrate ranges and regio- and stereo-chemistry of activation reactions†

PubMed Central

Jarling, René; Kühner, Simon; Basílio Janke, Eline; Gruner, Andrea; Drozdowska, Marta; Golding, Bernard T.; Rabus, Ralf; Wilkes, Heinz

2015-01-01

Anaerobic metabolism of hydrocarbons proceeds either via addition to fumarate or by hydroxylation in various microorganisms, e.g., sulfate-reducing or denitrifying bacteria, which are specialized in utilizing n-alkanes or alkylbenzenes as growth substrates. General pathways for carbon assimilation and energy gain have been elucidated for a limited number of possible substrates. In this work the metabolic activity of 11 bacterial strains during anaerobic growth with crude oil was investigated and compared with the metabolite patterns appearing during anaerobic growth with more than 40 different hydrocarbons supplied as binary mixtures. We show that the range of co-metabolically formed alkyl- and arylalkyl-succinates is much broader in n-alkane than in alkylbenzene utilizers. The structures and stereochemistry of these products are resolved. Furthermore, we demonstrate that anaerobic hydroxylation of alkylbenzenes does not only occur in denitrifiers but also in sulfate reducers. We propose that these processes play a role in detoxification under conditions of solvent stress. The thermophilic sulfate-reducing strain TD3 is shown to produce n-alkylsuccinates, which are suggested not to derive from terminal activation of n-alkanes, but rather to represent intermediates of a metabolic pathway short-cutting fumarate regeneration by reverse action of succinate synthase. The outcomes of this study provide a basis for geochemically tracing such processes in natural habitats and contribute to an improved understanding of microbial activity in hydrocarbon-rich anoxic environments. PMID:26441848

Development of an Operational TS Dataset Production System for the Data Assimilation System

NASA Astrophysics Data System (ADS)

Kim, Sung Dae; Park, Hyuk Min; Kim, Young Ho; Park, Kwang Soon

2017-04-01

An operational TS (Temperature and Salinity) dataset production system was developed to provide near real-time data to the data assimilation system periodically. It collects the latest 15 days' TS data of the north western pacific area (20°N - 55°N, 110°E - 150°E), applies QC tests to the archived data and supplies them to numerical prediction models of KIOST (Korea Institute of Ocean Science and Technology). The latest real-time TS data are collected from Argo GDAC and GTSPP data server every week. Argo data are downloaded from /latest_data directory of Argo GDAC. Because many duplicated data exist when all profile data are extracted from all Argo netCDF files, DB system is used to avoid duplication. All metadata (float ID, location, observation date and time, etc) of all Argo floats is stored into Database system and a Matlab program was developed to manipulate DB data, to check the duplication and to exclude duplicated data. GTSPP data are downloaded from /realtime directory of GTSPP data service. The latest data except ARGO data are extracted from the original data. Another Matlab program was coded to inspect all collected data using 10 QC tests and produce final dataset which can be used by the assimilation system. Three regional range tests to inspect annual, seasonal and monthly variations are included in the QC procedures. The C program was developed to provide regional ranges to data managers. It can calculate upper limit and lower limit of temperature and salinity at depth from 0 to 1550m. The final TS dataset contains the latest 15 days' TS data in netCDF format. It is updated every week and transmitted to numerical modeler of KIOST for operational use.

Assessment of SWE data assimilation for ensemble streamflow predictions

NASA Astrophysics Data System (ADS)

Franz, Kristie J.; Hogue, Terri S.; Barik, Muhammad; He, Minxue

2014-11-01

An assessment of data assimilation (DA) for Ensemble Streamflow Prediction (ESP) using seasonal water supply hindcasting in the North Fork of the American River Basin (NFARB) and the National Weather Service (NWS) hydrologic forecast models is undertaken. Two parameter sets, one from the California Nevada River Forecast Center (RFC) and one from the Differential Evolution Adaptive Metropolis (DREAM) algorithm, are tested. For each parameter set, hindcasts are generated using initial conditions derived with and without the inclusion of a DA scheme that integrates snow water equivalent (SWE) observations. The DREAM-DA scenario uses an Integrated Uncertainty and Ensemble-based data Assimilation (ICEA) framework that also considers model and parameter uncertainty. Hindcasts are evaluated using deterministic and probabilistic forecast verification metrics. In general, the impact of DA on the skill of the seasonal water supply predictions is mixed. For deterministic (ensemble mean) predictions, the Percent Bias (PBias) is improved with integration of the DA. DREAM-DA and the RFC-DA have the lowest biases and the RFC-DA has the lowest Root Mean Squared Error (RMSE). However, the RFC and DREAM-DA have similar RMSE scores. For the probabilistic predictions, the RFC and DREAM have the highest Continuous Ranked Probability Skill Scores (CRPSS) and the RFC has the best discrimination for low flows. Reliability results are similar between the non-DA and DA tests and the DREAM and DREAM-DA have better reliability than the RFC and RFC-DA for forecast dates February 1 and later. Despite producing improved streamflow simulations in previous studies, the hindcast analysis suggests that the DA method tested may not result in obvious improvements in streamflow forecasts. We advocate that integration of hindcasting and probabilistic metrics provides more rigorous insight on model performance for forecasting applications, such as in this study.

Dynamics of leaf gas exchange, xylem and phloem transport, water potential and carbohydrate concentration in a realistic 3-D model tree crown.

PubMed

Nikinmaa, Eero; Sievänen, Risto; Hölttä, Teemu

2014-09-01

Tree models simulate productivity using general gas exchange responses and structural relationships, but they rarely check whether leaf gas exchange and resulting water and assimilate transport and driving pressure gradients remain within acceptable physical boundaries. This study presents an implementation of the cohesion-tension theory of xylem transport and the Münch hypothesis of phloem transport in a realistic 3-D tree structure and assesses the gas exchange and transport dynamics. A mechanistic model of xylem and phloem transport was used, together with a tested leaf assimilation and transpiration model in a realistic tree architecture to simulate leaf gas exchange and water and carbohydrate transport within an 8-year-old Scots pine tree. The model solved the dynamics of the amounts of water and sucrose solute in the xylem, cambium and phloem using a fine-grained mesh with a system of coupled ordinary differential equations. The simulations predicted the observed patterns of pressure gradients and sugar concentration. Diurnal variation of environmental conditions influenced tree-level gradients in turgor pressure and sugar concentration, which are important drivers of carbon allocation. The results and between-shoot variation were sensitive to structural and functional parameters such as tree-level scaling of conduit size and phloem unloading. Linking whole-tree-level water and assimilate transport, gas exchange and sink activity opens a new avenue for plant studies, as features that are difficult to measure can be studied dynamically with the model. Tree-level responses to local and external conditions can be tested, thus making the approach described here a good test-bench for studies of whole-tree physiology.

Improving 7-Day Forecast Skill by Assimilation of Retrieved AIRS Temperature Profiles

NASA Technical Reports Server (NTRS)

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.

Overview of Chinese GRAPES Data Assimilation System

NASA Astrophysics Data System (ADS)

Liu, Yan

2017-04-01

The development of data assimilation system of Global and Regional Assimilation and Prediction System (GRAPES in short) which is Chinese new generation operational numerical weather prediction system completed in recent years is reviewed in this paper, including the design scheme and main characteristics. GRAPES adopts the variational approach with stresses at application of various remote sensing observational data. Its development path is from three dimensional to four dimensional assimilation. It may be implemented with limited area or global configurations. The three dimensional variational data assimilation systems have been operational in the national and a few of regional meteorological centers. The global four dimensional assimilation system is in pre-operational experiments, and will be upgraded. After a brief introduction to the GRAPES data assimilation system, results of a series of validations of GRAPES analyses against the observation data and analyses derived from other operational NWP center to assess its performance are presented.

Benefits and Pitfalls of GRACE Terrestrial Water Storage Data Assimilation

NASA Technical Reports Server (NTRS)

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.

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

NASA Astrophysics Data System (ADS)

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.

Assimilation of NUCAPS Retrieved Profiles in GSI for Unique Forecasting Applications

NASA Technical Reports Server (NTRS)

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.

Thermospheric Data Assimilation

DTIC Science & Technology

2016-05-05

forecasting longer than 3 days. Furthermore, validation of assimilation analyses with independent CHAMP mass density observations confirms that the...approach developed in this project. 15. SUBJECT TERMS Data assimilation, Ensemble forecasting , Thermosphere-ionosphere coupled data assimilation...Neutral mass density specification and forecasting , 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 6 19a. NAME

On the role of perception in shaping phonological assimilation rules.

PubMed

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.

Skill Assessment in Ocean Biological Data Assimilation

NASA Technical Reports Server (NTRS)

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.

Assimilation for skin SST in the NASA GEOS atmospheric data assimilation system.

PubMed

Akella, Santha; Todling, Ricardo; Suarez, Max

2017-01-01

The present article describes the sea surface temperature (SST) developments implemented in the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric Data Assimilation System (ADAS). These are enhancements that contribute to the development of an atmosphere-ocean coupled data assimilation system using GEOS. In the current quasi-operational GEOS-ADAS, the SST is a boundary condition prescribed based on the OSTIA product, therefore SST and skin SST (Ts) are identical. This work modifies the GEOS-ADAS Ts by modeling and assimilating near sea surface sensitive satellite infrared (IR) observations. The atmosphere-ocean interface layer of the GEOS atmospheric general circulation model (AGCM) is updated to include near surface diurnal warming and cool-skin effects. The GEOS analysis system is also updated to directly assimilate SST-relevant Advanced Very High Resolution Radiometer (AVHRR) radiance observations. Data assimilation experiments designed to evaluate the Ts modification in GEOS-ADAS show improvements in the assimilation of radiance observations that extends beyond the thermal IR bands of AVHRR. In particular, many channels of hyperspectral sensors, such as those of the Atmospheric Infrared Sounder (AIRS), and Infrared Atmospheric Sounding Interferometer (IASI) are also better assimilated. We also obtained improved fit to withheld, in-situ buoy measurement of near-surface SST. Evaluation of forecast skill scores show marginal to neutral benefit from the modified Ts.

Satellite radiance data assimilation for binary tropical cyclone cases over the western North Pacific

NASA Astrophysics Data System (ADS)

Choi, Yonghan; Cha, Dong-Hyun; Lee, Myong-In; Kim, Joowan; Jin, Chun-Sil; Park, Sang-Hun; Joh, Min-Su

2017-06-01

A total of three binary tropical cyclone (TC) cases over the Western North Pacific are selected to investigate the effects of satellite radiance data assimilation on analyses and forecasts of binary TCs. Two parallel cycling experiments with a 6 h interval are performed for each binary TC case, and the difference between the two experiments is whether satellite radiance observations are assimilated. Satellite radiance observations are assimilated using the Weather Research and Forecasting Data Assimilation (WRFDA)'s three-dimensional variational (3D-Var) system, which includes the observation operator, quality control procedures, and bias correction algorithm for radiance observations. On average, radiance assimilation results in slight improvements of environmental fields and track forecasts of binary TC cases, but the detailed effects vary with the case. When there is no direct interaction between binary TCs, radiance assimilation leads to better depictions of environmental fields, and finally it results in improved track forecasts. However, positive effects of radiance assimilation on track forecasts can be reduced when there exists a direct interaction between binary TCs and intensities/structures of binary TCs are not represented well. An initialization method (e.g., dynamic initialization) combined with radiance assimilation and/or more advanced DA techniques (e.g., hybrid method) can be considered to overcome these limitations.

Improving Robustness of Hydrologic Ensemble Predictions Through Probabilistic Pre- and Post-Processing in Sequential Data Assimilation

NASA Astrophysics Data System (ADS)

Wang, S.; Ancell, B. C.; Huang, G. H.; Baetz, B. W.

2018-03-01

Data assimilation using the ensemble Kalman filter (EnKF) has been increasingly recognized as a promising tool for probabilistic hydrologic predictions. However, little effort has been made to conduct the pre- and post-processing of assimilation experiments, posing a significant challenge in achieving the best performance of hydrologic predictions. This paper presents a unified data assimilation framework for improving the robustness of hydrologic ensemble predictions. Statistical pre-processing of assimilation experiments is conducted through the factorial design and analysis to identify the best EnKF settings with maximized performance. After the data assimilation operation, statistical post-processing analysis is also performed through the factorial polynomial chaos expansion to efficiently address uncertainties in hydrologic predictions, as well as to explicitly reveal potential interactions among model parameters and their contributions to the predictive accuracy. In addition, the Gaussian anamorphosis is used to establish a seamless bridge between data assimilation and uncertainty quantification of hydrologic predictions. Both synthetic and real data assimilation experiments are carried out to demonstrate feasibility and applicability of the proposed methodology in the Guadalupe River basin, Texas. Results suggest that statistical pre- and post-processing of data assimilation experiments provide meaningful insights into the dynamic behavior of hydrologic systems and enhance robustness of hydrologic ensemble predictions.

Assimilation for Skin SST in the NASA GEOS Atmospheric Data Assimilation System

NASA Technical Reports Server (NTRS)

Akella, Santha; Todling, Ricardo; Suarez, Max

2017-01-01

The present article describes the sea surface temperature (SST) developments implemented in the Goddard Earth Observing System, Version 5 (GEOS) Atmospheric Data Assimilation System (ADAS). These are enhancements that contribute to the development of an atmosphere-ocean coupled data assimilation system using GEOS. In the current quasi-operational GEOS-ADAS, the SST is a boundary condition prescribed based on the OSTIA product, therefore SST and skin SST (Ts) are identical. This work modifies the GEOS-ADAS Ts by modelling and assimilating near sea surface sensitive satellite infrared (IR) observations. The atmosphere-ocean interface layer of the GEOS atmospheric general circulation model (AGCM) is updated to include near-surface diurnal warming and cool-skin effects. The GEOS analysis system is also updated to directly assimilate SST-relevant Advanced Very High Resolution Radiometer (AVHRR) radiance observations. Data assimilation experiments designed to evaluate the Ts modification in GEOS-ADAS show improvements in the assimilation of radiance observations that extend beyond the thermal infrared bands of AVHRR. In particular, many channels of hyperspectral sensors, such as those of the Atmospheric Infrared Sounder (AIRS), and Infrared Atmospheric Sounding Interferometer (IASI) are also better assimilated. We also obtained improved fit to withheld insitu buoy measurement of near-surface SST. Evaluation of forecast skill scores show neutral to marginal benefit from the modified Ts.

Assimilation of Global Radar Backscatter and Radiometer Brightness Temperature Observations to Improve Soil Moisture and Land Evaporation Estimates

NASA Technical Reports Server (NTRS)

Lievens, H.; Martens, B.; Verhoest, N. E. C.; Hahn, S.; Reichle, R. H.; Miralles, D. G.

2017-01-01

Active radar backscatter (s?) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s? and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s? or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s? and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.

Assimilation of granite by basaltic magma at Burnt Lava flow, Medicine Lake volcano, northern California: Decoupling of heat and mass transfer

USGS Publications Warehouse

Grove, T.L.; Kinzler, R.J.; Baker, M.B.; Donnelly-Nolan, J. M.; Lesher, C.E.

1988-01-01

At Medicine Lake volcano, California, andesite of the Holocene Burnt Lava flow has been produced by fractional crystallization of parental high alumina basalt (HAB) accompanied by assimilation of granitic crustal material. Burnt Lava contains inclusions of quenched HAB liquid, a potential parent magma of the andesite, highly melted granitic crustal xenoliths, and xenocryst assemblages which provide a record of the fractional crystallization and crustal assimilation process. Samples of granitic crustal material occur as xenoliths in other Holocene and Pleistocene lavas, and these xenoliths are used to constrain geochemical models of the assimilation process. A large amount of assimilation accompanied fractional crystallization to produce the contaminated Burnt lava andesites. Models which assume that assimilation and fractionation occurred simultaneously estimate the ratio of assimilation to fractional crystallization (R) to be >1 and best fits to all geochemical data are at an R value of 1.35 at F=0.68. Petrologic evidence, however, indicates that the assimilation process did not involve continuous addition of granitic crust as fractionation occurred. Instead, heat and mass transfer were separated in space and time. During the assimilation process, HAB magma underwent large amounts of fractional crystallization which was not accompanied by significant amounts of assimilation. This fractionation process supplied heat to melt granitic crust. The models proposed to explain the contamination process involve fractionation, replenishment by parental HAB, and mixing of evolved and parental magmas with melted granitic crust. ?? 1988 Springer-Verlag.

Diversity of Geotrichum candidum Strains Isolated from Traditional Cheesemaking Fabrications in France

PubMed Central

Marcellino, N.; Beuvier, E.; Grappin, R.; Guéguen, M.; Benson, D. R.

2001-01-01

The diversity of French fungus-ripened cheeses is due partly to the succession of fungi that colonize the cheese during ripening. Geotrichum candidum appears in the early stages of ripening on soft cheeses such as Camembert and semihard cheeses such as St. Nectaire and Reblochon. Its lipases and proteases promote flavor development, and its aminopeptidases reduce bitterness imparted by low-molecular-weight peptides in cheese. We assessed the genetic diversity of G. candidum strains by using random amplification of polymorphic DNA (RAPD)-PCR correlated with phenotypic tests for carbon assimilation and salt tolerance. Strains were isolated from milk, curd, and cheese collected in seven major cheesemaking regions of France. Sixty-four isolates were characterized. We found high genetic diversity of G. candidum even within the same cheesemaking regions. Strains did not group according to region. All of the strains from the Haute-Savoie were able to assimilate lactate as the sole source of carbon, while lactate assimilation varied among strains from the Auvergne. Strains varied in d-mannitol assimilation, and none used citrate as the sole source of carbon. Yeast-like colony morphology predominated in Reblochon, while all of the strains isolated from St. Nectaire were filamentous. The RAPD-PCR technique readily differentiated Geotrichum fragrans isolated from milk and curd in a St. Nectaire cheesemaking facility. This study reveals an enormous diversity of G. candidum that has been empirically selected through the centuries by the cheesemakers of France. PMID:11571181

Diversity of Geotrichum candidum strains isolated from traditional cheesemaking fabrications in France.

PubMed

Marcellino, N; Beuvier, E; Grappin, R; Guéguen, M; Benson, D R

2001-10-01

The diversity of French fungus-ripened cheeses is due partly to the succession of fungi that colonize the cheese during ripening. Geotrichum candidum appears in the early stages of ripening on soft cheeses such as Camembert and semihard cheeses such as St. Nectaire and Reblochon. Its lipases and proteases promote flavor development, and its aminopeptidases reduce bitterness imparted by low-molecular-weight peptides in cheese. We assessed the genetic diversity of G. candidum strains by using random amplification of polymorphic DNA (RAPD)-PCR correlated with phenotypic tests for carbon assimilation and salt tolerance. Strains were isolated from milk, curd, and cheese collected in seven major cheesemaking regions of France. Sixty-four isolates were characterized. We found high genetic diversity of G. candidum even within the same cheesemaking regions. Strains did not group according to region. All of the strains from the Haute-Savoie were able to assimilate lactate as the sole source of carbon, while lactate assimilation varied among strains from the Auvergne. Strains varied in D-mannitol assimilation, and none used citrate as the sole source of carbon. Yeast-like colony morphology predominated in Reblochon, while all of the strains isolated from St. Nectaire were filamentous. The RAPD-PCR technique readily differentiated Geotrichum fragrans isolated from milk and curd in a St. Nectaire cheesemaking facility. This study reveals an enormous diversity of G. candidum that has been empirically selected through the centuries by the cheesemakers of France.

Data Assimilation at FLUXNET to Improve Models towards Ecological Forecasting (Invited)

NASA Astrophysics Data System (ADS)

Luo, Y.

2009-12-01

Dramatically increased volumes of data from observational and experimental networks such as FLUXNET call for transformation of ecological research to increase its emphasis on quantitative forecasting. Ecological forecasting will also meet the societal need to develop better strategies for natural resource management in a world of ongoing global change. Traditionally, ecological forecasting has been based on process-based models, informed by data in largely ad hoc ways. Although most ecological models incorporate some representation of mechanistic processes, today’s ecological models are generally not adequate to quantify real-world dynamics and provide reliable forecasts with accompanying estimates of uncertainty. A key tool to improve ecological forecasting is data assimilation, which uses data to inform initial conditions and to help constrain a model during simulation to yield results that approximate reality as closely as possible. In an era with dramatically increased availability of data from observational and experimental networks, data assimilation is a key technique that helps convert the raw data into ecologically meaningful products so as to accelerate our understanding of ecological processes, test ecological theory, forecast changes in ecological services, and better serve the society. This talk will use examples to illustrate how data from FLUXNET have been assimilated with process-based models to improve estimates of model parameters and state variables; to quantify uncertainties in ecological forecasting arising from observations, models and their interactions; and to evaluate information contributions of data and model toward short- and long-term forecasting of ecosystem responses to global change.

Anaerobic hydrolysis and acidification of organic substrates: determination of anaerobic hydrolytic potential.

PubMed

Rajagopal, Rajinikanth; Béline, Fabrice

2011-05-01

This study aimed to develop a biochemical-test mainly to evaluate the hydrolytic-potential of different substrates and to apply this test to characterize various organic substrates. Outcome of this study can be used for optimization of the WWTPs through enhancement of N/P removal or anaerobic digestion. Out of four series of batch experiments, the first two tests were conducted to determine the optimal operating conditions (test duration, inoculum-ratio etc.) for the hydrolytic-potential test using secondary and synthetically-prepared sludges. Based on the results (generation of CODs, pH and VFA), test duration was fixed between 6 and 7d allowing to attain maximum hydrolysis and to avoid methanogenesis. Effect of inoculum-ratios on acid fermentation of sludge was not significantly noticed. Using this methodology, third and fourth tests were performed to characterize various organic substrates namely secondary, pre-treated sludge, pig and two different cattle slurries. VFA production was shown to be substantially dependent on substrates types. Copyright © 2011 Elsevier Ltd. All rights reserved.

A novel nanoparticle approach for imaging nutrient uptake by soil bacteria

NASA Astrophysics Data System (ADS)

O'Brien, S. L.; Whiteside, M. D.; Sholto-Douglas, D.; Antonopoulos, D. A.; Boyanov, M.; Durall, D. M.; Jones, M. D.; Lai, B.; O'Loughlin, E. J.; Kemner, K. M.

2014-12-01

The metabolic activities of soil microbes are the primary drivers of biogeochemical processes controlling the terrestrial carbon cycle, nutrient availability to plants, contaminant remediation, water quality, and other ecosystem services. However, we have a limited understanding of microbial metabolic processes such as nutrient uptake rates, substrate preferences, or how microbes and microbial metabolism are distributed throughout their habitat. Here we use a novel imaging technique with quantum dots (QDs, engineered semiconductor nanoparticles that produce size or composition-dependent fluorescence) to measure bacterial uptake of substrates of varying complexity. Cultures of two organisms differing in cell wall structure — Bacillus subtilis and Pseudomonas fluorescens — were grown in one of four ecologically relevant experimental conditions: nitrogen (N) limitation, phosphorus (P) limitation, N and P limitation, or no nutrient limitation. The cultures were then exposed to QDs with and without organic nutrients attached. X-ray fluorescence imaging was performed at 2ID-D at the Advanced Photon Source (APS) to determine the elemental distributions within both planktonic and surface-adhered (i.e, biofilms) cells. Uptake of unconjugated QDs was neglibible, and QDs conjugated to organic substrates varied depending on growth conditions and substrate, suggesting that they are a useful indicator of bacterial ecology. Cellular uptake was similar for the two bacterial species (2212 ± 273 nanoparticles per cm3 of cell volume for B. subtilis and 1682 ± 264 for P. fluorescens). On average, QD assimilation was six times greater when N or P was limiting, and cells took up about twice as much phosphoserine compared to other substrates, likely because it was the only compound providing both N and P. These results showed that regardless of their cell wall structure, bacteria can selectively take up quantifiable levels of QDs based on substrate and environmental conditions. APS images are consistent with those produced with confocal and optical microscopes, indicating that the XRF approach can detect bacterial uptake of CdSe-core QDs. These findings offer a new way to experimentally investigate basic bacterial ecology such as metabolic activity and biofilm development and function.

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

NASA Technical Reports Server (NTRS)

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.

Analysis of the hydrological response of a distributed physically-based model using post-assimilation (EnKF) diagnostics of streamflow and in situ soil moisture observations

NASA Astrophysics Data System (ADS)

Trudel, Mélanie; Leconte, Robert; Paniconi, Claudio

2014-06-01

Data assimilation techniques not only enhance model simulations and forecast, they also provide the opportunity to obtain a diagnostic of both the model and observations used in the assimilation process. In this research, an ensemble Kalman filter was used to assimilate streamflow observations at a basin outlet and at interior locations, as well as soil moisture at two different depths (15 and 45 cm). The simulation model is the distributed physically-based hydrological model CATHY (CATchment HYdrology) and the study site is the Des Anglais watershed, a 690 km2 river basin located in southern Quebec, Canada. Use of Latin hypercube sampling instead of a conventional Monte Carlo method to generate the ensemble reduced the size of the ensemble, and therefore the calculation time. Different post-assimilation diagnostics, based on innovations (observation minus background), analysis residuals (observation minus analysis), and analysis increments (analysis minus background), were used to evaluate assimilation optimality. An important issue in data assimilation is the estimation of error covariance matrices. These diagnostics were also used in a calibration exercise to determine the standard deviation of model parameters, forcing data, and observations that led to optimal assimilations. The analysis of innovations showed a lag between the model forecast and the observation during rainfall events. Assimilation of streamflow observations corrected this discrepancy. Assimilation of outlet streamflow observations improved the Nash-Sutcliffe efficiencies (NSE) between the model forecast (one day) and the observation at both outlet and interior point locations, owing to the structure of the state vector used. However, assimilation of streamflow observations systematically increased the simulated soil moisture values.

Preliminary Results from an Assimilation of TOMS Aerosol Observations Into the GOCART Model

NASA Technical Reports Server (NTRS)

daSilva, Arlindo; Weaver, Clark J.; Ginoux, Paul; Torres, Omar; Einaudi, Franco (Technical Monitor)

2000-01-01

At NASA Goddard we are developing a global aerosol data assimilation system that combines advances in remote sensing and modeling of atmospheric aerosols. The goal is to provide high resolution, 3-D aerosol distributions to the research community. Our first step is to develop a simple assimilation system for Saharan mineral aerosol. The Goddard Chemistry and Aerosol Radiation model (GOCART) provides accurate 3-D mineral aerosol size distributions that compare well with TOMS satellite observations. Surface, mobilization, wet and dry deposition, convective and long-range transport are all driven by assimilated fields from the Goddard Earth Observing System Data Assimilation System, GEOS-DAS. Our version of GOCART transports sizes from.08-10 microns and only simulates Saharan dust. TOMS radiance observations in the ultra violet provide information on the mineral and carbonaceous aerosol fields. We use two main observables in this study: the TOMS aerosol index (AI) which is directly related to the ratio of the 340 and 380 radiances and the 380 radiance. These are sensitive to the aerosol optical thickness, the single scattering albedo and the height of the aerosol layer. The Goddard Aerosol Assimilation System (GAAS) uses the Data Assimilation Office's Physical-space Statistical Analysis System (PSAS) to combine TOMS observations and GOCART model first guess fields. At this initial phase we only assimilate observations into the the GOCART model over regions of Africa and the Atlantic where mineral aerosols dominant and carbonaceous aerosols are minimal, Our preliminary results during summer show that the assimilation with TOMS data modifies both the aerosol mass loading and the single scattering albedo. Assimilated aerosol fields will be compared with assimilated aerosol fields from GOCART and AERONET observations over Cape Verde.

Variational Assimilation of Global Microwave Rainfall Retrievals: Physical and Dynamical Impact on GEOS Analyses and Forecasts

NASA Technical Reports Server (NTRS)

Lin, Xin; Zhang, Sara Q.; Hou, Arthur Y.

2006-01-01

Global microwave rainfall retrievals from a 5-satellite constellation, including TMI from TRMM, SSWI from DMSP F13, F14 and F15, and AMSR-E from EOS-AQUA, are assimilated into the NASA Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) using a 1-D variational continuous assimilation (VCA) algorithm. The physical and dynamical impact of rainfall assimilation on GEOS analyses and forecasts is examined at various temporal and spatial scales. This study demonstrates that the 1-D VCA algorithm, which was originally developed and evaluated for rainfall assimilations over tropical oceans, can effectively assimilate satellite microwave rainfall retrievals and improve GEOS analyses over both the Tropics and the extratropics where the atmospheric processes are dominated by different large-scale dynamics and moist physics, and also over the land, where rainfall estimates from passive microwave radiometers are believed to be less accurate. Results show that rainfall assimilation renders the GEOS analysis physically and dynamically more consistent with the observed precipitation at the monthly-mean and 6-hour time scales. Over regions where the model precipitation tends to misbehave in distinctly different rainy regimes, the 1-D VCA algorithm, by compensating for errors in the model s moist time-tendency in a 6-h analysis window, is able to bring the rainfall analysis closer to the observed. The radiation and cloud fields also tend to be in better agreement with independent satellite observations in the rainfall-assimilation m especially over regions where rainfall analyses indicate large improvements. Assimilation experiments with and without rainfall data for a midlatitude frontal system clearly indicates that the GEOS analysis is improved through changes in the thermodynamic and dynamic fields that respond to the rainfall assimilation. The synoptic structures of temperature, moisture, winds, divergence, and vertical motion, as well as vorticity are more realistically captured across the front. Short-term forecasts using initial conditions assimilated with rainfall data also show slight improvements. 1

A multi-source data assimilation framework for flood forecasting: Accounting for runoff routing lags

NASA Astrophysics Data System (ADS)

Meng, S.; Xie, X.

2015-12-01

In the flood forecasting practice, model performance is usually degraded due to various sources of uncertainties, including the uncertainties from input data, model parameters, model structures and output observations. Data assimilation is a useful methodology to reduce uncertainties in flood forecasting. For the short-term flood forecasting, an accurate estimation of initial soil moisture condition will improve the forecasting performance. Considering the time delay of runoff routing is another important effect for the forecasting performance. Moreover, the observation data of hydrological variables (including ground observations and satellite observations) are becoming easily available. The reliability of the short-term flood forecasting could be improved by assimilating multi-source data. The objective of this study is to develop a multi-source data assimilation framework for real-time flood forecasting. In this data assimilation framework, the first step is assimilating the up-layer soil moisture observations to update model state and generated runoff based on the ensemble Kalman filter (EnKF) method, and the second step is assimilating discharge observations to update model state and runoff within a fixed time window based on the ensemble Kalman smoother (EnKS) method. This smoothing technique is adopted to account for the runoff routing lag. Using such assimilation framework of the soil moisture and discharge observations is expected to improve the flood forecasting. In order to distinguish the effectiveness of this dual-step assimilation framework, we designed a dual-EnKF algorithm in which the observed soil moisture and discharge are assimilated separately without accounting for the runoff routing lag. The results show that the multi-source data assimilation framework can effectively improve flood forecasting, especially when the runoff routing has a distinct time lag. Thus, this new data assimilation framework holds a great potential in operational flood forecasting by merging observations from ground measurement and remote sensing retrivals.

Evaluating Model Performance of an Ensemble-based Chemical Data Assimilation System During INTEX-B Field Mission

NASA Technical Reports Server (NTRS)

Arellano, A. F., Jr.; Raeder, K.; Anderson, J. L.; Hess, P. G.; Emmons, L. K.; Edwards, D. P.; Pfister, G. G.; Campos, T. L.; Sachse, G. W.

2007-01-01

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 NSFINCAR 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. The work described above also brought to light several short-comings of the data assimilation approach for CO profiles. Because of the limited vertical resolution of the measurement, the retrievals at different altitudes are correlated which can lead to problems with numerical error and overall efficiency. This has resulted in a manuscript that is about to be submitted to JGR:

DasPy 1.0 - the Open Source Multivariate Land Data Assimilation Framework in combination with the Community Land Model 4.5

NASA Astrophysics Data System (ADS)

Han, X.; Li, X.; He, G.; Kumbhar, P.; Montzka, C.; Kollet, S.; Miyoshi, T.; Rosolem, R.; Zhang, Y.; Vereecken, H.; Franssen, H.-J. H.

2015-08-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. Multivariate data assimilation refers to the simultaneous assimilation of observation data from multiple model state variables into a simulation model. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. We developed an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with the C++ and Fortran programming languages. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be introduced by perturbed atmospheric forcing data, and represented by perturbed soil and vegetation parameters and model initial conditions. The Community Land Model (CLM) was integrated as the model operator. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. The Community Microwave Emission Modelling platform (CMEM), COsmic-ray Soil Moisture Interaction Code (COSMIC) and the Two-Source Formulation (TSF) were integrated as observation operators for the assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy has been evaluated in several assimilation studies of neutron count intensity (soil moisture), L-band brightness temperature and land surface temperature. DasPy is parallelized using the hybrid Message Passing Interface and Open Multi-Processing techniques. All the input and output data flows are organized efficiently using the commonly used NetCDF file format. Online 1-D and 2-D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, J.; Madsen, H.; Jensen, K. H.; Refsgaard, J. C.

2015-08-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both stream flow and groundwater modeling. The Colored Noise Kalman filter (ColKF) and the Separate bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman Filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved stream flow modeling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modeling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behavior and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, Jørn; Madsen, Henrik; Høgh Jensen, Karsten; Refsgaard, Jens Christian

2016-05-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment-scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both streamflow and groundwater modelling. The coloured noise Kalman filter (ColKF) and the separate-bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved streamflow modelling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modelling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behaviour and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

An operational global-scale ocean thermal analysis system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clancy, R. M.; Pollak, K.D.; Phoebus, P.A.

1990-04-01

The Optimum Thermal Interpolation System (OTIS) is an ocean thermal analysis system designed for operational use at FNOC. It is based on the optimum interpolation of the assimilation technique and functions in an analysis-prediction-analysis data assimilation cycle with the TOPS mixed-layer model. OTIS provides a rigorous framework for combining real-time data, climatology, and predictions from numerical ocean prediction models to produce a large-scale synoptic representation of ocean thermal structure. The techniques and assumptions used in OTIS are documented and results of operational tests of global scale OTIS at FNOC are presented. The tests involved comparisons of OTIS against an existingmore » operational ocean thermal structure model and were conducted during February, March, and April 1988. Qualitative comparison of the two products suggests that OTIS gives a more realistic representation of subsurface anomalies and horizontal gradients and that it also gives a more accurate analysis of the thermal structure, with improvements largest below the mixed layer. 37 refs.« less

LWS Proposal to Provide Scientific Guidance and Modeling Support for the Ionospheric Mapping Mission. Part 1

NASA Technical Reports Server (NTRS)

Richmond, Arthur D.

2005-01-01

A data assimilation system for specifying the thermospheric density has been developed over the last several years. This system ingests GRACE/CHAMP-type in situ as well as SSULI/SSUSI remote sensing observations while making use of a physical model, the Coupled Thermosphere-Ionosphere Model (CTIM) (Fuller-Rowel1 et al., 1996). The Kalman filter was implemented as the backbone to the data assimilation system, which provides a statistically 'best' estimate as well as an estimate of the error in its state. The system was tested using a simulated thermosphere and observations. CHAMP data were then used to provide the system with a real data source. The results of this study are herein.

Aerosol EnKF at GMAO

NASA Technical Reports Server (NTRS)

Buchard, Virginie; Da Silva, Arlindo; Todling, Ricardo

2017-01-01

In the GEOS near real-time system, as well as in MERRA-2 which is the latest reanalysis produced at NASAs Global Modeling and Assimilation Office(GMAO), the assimilation of aerosol observations is performed by means of a so-called analysis splitting method. In line with the transition of the GEOS meteorological data assimilation system to a hybrid Ensemble-Variational formulation, we are updating the aerosol component of our assimilation system to an ensemble square root filter(EnSRF; Whitaker and Hamill (2002)) type of scheme.We present a summary of our preliminary results of the assimilation of column integrated aerosol observations (Aerosol Optical Depth; AOD) using an Ensemble Square Root Filters (EnSRF) scheme and the ensemble members produced routinely by the meteorological assimilation.

Soil moisture assimilation using a modified ensemble transform Kalman filter with water balance constraint

NASA Astrophysics Data System (ADS)

Wu, Guocan; Zheng, Xiaogu; Dan, Bo

2016-04-01

The shallow soil moisture observations are assimilated into Common Land Model (CoLM) to estimate the soil moisture in different layers. The forecast error is inflated to improve the analysis state accuracy and the water balance constraint is adopted to reduce the water budget residual in the assimilation procedure. The experiment results illustrate that the adaptive forecast error inflation can reduce the analysis error, while the proper inflation layer can be selected based on the -2log-likelihood function of the innovation statistic. The water balance constraint can result in reducing water budget residual substantially, at a low cost of assimilation accuracy loss. The assimilation scheme can be potentially applied to assimilate the remote sensing data.

Anaerobic Metabolism in the N-Limited Green Alga Selenastrum minutum: III. Alanine Is the Product of Anaerobic Ammonium Assimilation.

PubMed

Vanlerberghe, G C; Joy, K W; Turpin, D H

1991-02-01

We have determined the flow of (15)N into free amino acids of the N-limited green alga Selenastrum minutum (Naeg.) Collins after addition of (15)NH(4) (+) to aerobic or anaerobic cells. Under aerobic conditions, only a small proportion of the N assimilated was retained in the free amino acid pool. However, under anaerobic conditions almost all assimilated NH(4) (+) accumulates in alanine. This is a unique feature of anaerobic NH(4) (+) assimilation. The pathway of carbon flow to alanine results in the production of ATP and reductant which matches exactly the requirements of NH(4) (+) assimilation. Alanine synthesis is therefore an excellent strategy to maintain energy and redox balance during anaerobic NH(4) (+) assimilation.

Unusual isotopic composition of C-CO2 from sterilized soil microcosms: a new way to separate intracellular from extracellular respiratory metabolisms.

NASA Astrophysics Data System (ADS)

Kéraval, Benoit; Alvarez, Gaël; Lehours, Anne Catherine; Amblard, Christian; Fontaine, Sebastien

2015-04-01

The mineralization of organic C requires two main steps. First, microorganisms secrete exoenzymes in soil in order to depolymerize plant and microbial cell walls and release soluble substrates for microbial assimilation. The second step of mineralization, during which C is released as CO2, implies the absorption and utilization of solubilized substrates by microbial cells with the aim to produce energy (ATP). In cells, soluble substrates are carried out by a cascade of respiratory enzymes, along which protons and electrons are transferred from a substrate to oxygen. Given the complexity of this oxidative metabolism and the typical fragility of respiratory enzymes, it is traditionally considered that respiration (second step of C mineralization process) is strictly an intracellular metabolism process. The recurrent observations of substantial CO2 emissions in soil microcosms where microbial cells have been reduced to extremely low levels challenges this paradigm. In a recent study where some respiratory enzymes have shown to function in an extracellular context in soils, Maire et al. (2013) suggested that an extracellular oxidative metabolism (EXOMET) substantially contributes to CO2 emission from soils. This idea is supported by the recent publication of Blankinship et al., 2014 who showed the presence of active enzymes involved in the Krebs cycle on soil particles. Many controversies subsist in the scientific community due to the presence of non-proliferating but morphologically intact cells after irradiation that could substantially contribute to those soil CO2 emissions. To test whether a purely extracellular oxidative metabolism contribute to soil CO2 emissions, we combined high doses of gamma irradiations to different time of soil autoclaving. The presence of active and non-active cells in soil was checked by DNA and RNA extraction and by electronic microscopy. None active cells (RNA-containing cells) were detectable after irradiation, but some morphological intact cells were observed by microscopy. These "ghost" cells were completely destroyed by the irradiation-autoclaving combination releasing large amount of soluble C. The soil respiration (O2 consumption and CO2 production) was reduced by irradiation and autoclaving but not stopped, suggesting the presence of an EXOMET. The delta 13C of CO2 released in the irradiated-autoclaved soil was strongly depleted (-70‰) indicating that this extracellular metabolism induced a substantial isotopic fractionation. Our findings suggest that two main oxidative metabolisms co-occur in soils: cell respiration and EXOMET. The isotopic fractionation induced by the EXOMET open perspectives for its quantification in non-sterilized living soils.

Sequential Data Assimilation for Seismicity: a Proof of Concept

NASA Astrophysics Data System (ADS)

van Dinther, Ylona; Kuensch, Hans Rudolf; Fichtner, Andreas

2017-04-01

Integrating geological and geophysical observations, laboratory results and physics-based numerical modeling is crucial to improve our understanding of the occurrence of large subduction earthquakes. How to do this integration is less obvious, especially in light of the scarcity and uncertainty of natural and laboratory data and the difficulty of modeling the physics governing earthquakes. One way to efficiently combine information from these sources in order to estimate states and/or parameters is data assimilation, a mathematically sound framework extensively developed for weather forecasting purposes. We demonstrate the potential of using data assimilation by applying an Ensemble Kalman Filter to recover the current and forecast the future state of stress and strength on the megathrust based on data from a single borehole. Data and its errors are for the first time assimilated to - using the least-squares solution of Bayes theorem - update a Partial Differential Equation-driven seismic cycle model. This visco-elasto-plastic continuum forward model solves Navier-Stokes equations with a rate-dependent friction coefficient. To prove this concept we perform a perfect model test in an analogue subduction zone setting. Synthetic numerical data from a single analogue borehole are assimilated into 150 ensemble models. Since we know the true state of the numerical data model, a quantitative and qualitative evaluation shows that meaningful information on the stress and strength is available, even when only data from a single borehole is assimilated over only a part of a seismic cycle. This is possible, since the sampled error covariance matrix contains prior information on the physics that relates velocities, stresses, and pressures at the surface to those at the fault. During the analysis step, stress and strength distributions are thus reconstructed in such a way that fault coupling can be updated to either inhibit or trigger events. In the subsequent forward propagation step the physical equations are solved to propagate the updated states forward in time and thus provide probabilistic information on the occurrence of the next analogue earthquake. At the next assimilation step(s), the systems forecasting ability turns out to be distinctly better than using a periodic model to forecast this simple, quasi-periodic sequence. Combining our knowledge of physical laws with observations thus seems to be a useful tool that could be used to improve probabilistic seismic hazard assessment and increase our physical understanding of the spatiotemporal occurrence of earthquakes, subduction zones, and other Solid Earth systems.

Improved water balance component estimates through joint assimilation of GRACE water storage and SMOS soil moisture retrievals

NASA Astrophysics Data System (ADS)

Tian, Siyuan; Tregoning, Paul; Renzullo, Luigi J.; van Dijk, Albert I. J. M.; Walker, Jeffrey P.; Pauwels, Valentijn R. N.; Allgeyer, Sébastien

2017-03-01

The accuracy of global water balance estimates is limited by the lack of observations at large scale and the uncertainties of model simulations. Global retrievals of terrestrial water storage (TWS) change and soil moisture (SM) from satellites provide an opportunity to improve model estimates through data assimilation. However, combining these two data sets is challenging due to the disparity in temporal and spatial resolution at both vertical and horizontal scale. For the first time, TWS observations from the Gravity Recovery and Climate Experiment (GRACE) and near-surface SM observations from the Soil Moisture and Ocean Salinity (SMOS) were jointly assimilated into a water balance model using the Ensemble Kalman Smoother from January 2010 to December 2013 for the Australian continent. The performance of joint assimilation was assessed against open-loop model simulations and the assimilation of either GRACE TWS anomalies or SMOS SM alone. The SMOS-only assimilation improved SM estimates but reduced the accuracy of groundwater and TWS estimates. The GRACE-only assimilation improved groundwater estimates but did not always produce accurate estimates of SM. The joint assimilation typically led to more accurate water storage profile estimates with improved surface SM, root-zone SM, and groundwater estimates against in situ observations. The assimilation successfully downscaled GRACE-derived integrated water storage horizontally and vertically into individual water stores at the same spatial scale as the model and SMOS, and partitioned monthly averaged TWS into daily estimates. These results demonstrate that satellite TWS and SM measurements can be jointly assimilated to produce improved water balance component estimates.

A balanced Kalman filter ocean data assimilation system with application to the South Australian Sea

NASA Astrophysics Data System (ADS)

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.

Assimilative model for ionospheric dynamics employing delay, Doppler, and direction of arrival measurements from multiple HF channels

NASA Astrophysics Data System (ADS)

Fridman, Sergey V.; Nickisch, L. J.; Hausman, Mark; Zunich, George

2016-03-01

We describe the development of new HF data assimilation capabilities for our ionospheric inversion algorithm called GPSII (GPS Ionospheric Inversion). Previously existing capabilities of this algorithm included assimilation of GPS total electron content data as well as assimilation of backscatter ionograms. In the present effort we concentrated on developing assimilation tools for data related to HF propagation channels. Measurements of propagation delay, angle of arrival, and the ionosphere-induced Doppler from any number of known propagation links can now be utilized by GPSII. The resulting ionospheric model is consistent with all assimilated measurements. This means that ray tracing simulations of the assimilated propagation links are guaranteed to be in agreement with measured data within the errors of measurement. The key theoretical element for assimilating HF data is the raypath response operator (RPRO) which describes response of raypath parameters to infinitesimal variations of electron density in the ionosphere. We construct the RPRO out of the fundamental solution of linearized ray tracing equations for a dynamic magnetoactive plasma. We demonstrate performance and internal consistency of the algorithm using propagation delay data from multiple oblique ionograms (courtesy of Defence Science and Technology Organisation, Australia) as well as with time series of near-vertical incidence sky wave data (courtesy of the Intelligence Advanced Research Projects Activity HFGeo Program Government team). In all cases GPSII produces electron density distributions which are smooth in space and in time. We simulate the assimilated propagation links by performing ray tracing through GPSII-produced ionosphere and observe that simulated data are indeed in agreement with assimilated measurements.

Joint Assimilation of SMOS Brightness Temperature and GRACE Terrestrial Water Storage Observations for Improved Soil Moisture Estimation

NASA Technical Reports Server (NTRS)

Girotto, Manuela; Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Rodell, Matthew

2017-01-01

Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0 - 5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.

Application of an Ensemble Smoother to Precipitation Assimilation

NASA Technical Reports Server (NTRS)

Zhang, Sara; Zupanski, Dusanka; Hou, Arthur; Zupanski, Milija

2008-01-01

Assimilation of precipitation in a global modeling system poses a special challenge in that the observation operators for precipitation processes are highly nonlinear. In the variational approach, substantial development work and model simplifications are required to include precipitation-related physical processes in the tangent linear model and its adjoint. An ensemble based data assimilation algorithm "Maximum Likelihood Ensemble Smoother (MLES)" has been developed to explore the ensemble representation of the precipitation observation operator with nonlinear convection and large-scale moist physics. An ensemble assimilation system based on the NASA GEOS-5 GCM has been constructed to assimilate satellite precipitation data within the MLES framework. The configuration of the smoother takes the time dimension into account for the relationship between state variables and observable rainfall. The full nonlinear forward model ensembles are used to represent components involving the observation operator and its transpose. Several assimilation experiments using satellite precipitation observations have been carried out to investigate the effectiveness of the ensemble representation of the nonlinear observation operator and the data impact of assimilating rain retrievals from the TMI and SSM/I sensors. Preliminary results show that this ensemble assimilation approach is capable of extracting information from nonlinear observations to improve the analysis and forecast if ensemble size is adequate, and a suitable localization scheme is applied. In addition to a dynamically consistent precipitation analysis, the assimilation system produces a statistical estimate of the analysis uncertainty.

Joint assimilation of SMOS brightness temperature and GRACE terrestrial water storage observations for improved soil moisture estimation

NASA Astrophysics Data System (ADS)

Girotto, M.; Reichle, R. H.; De Lannoy, G.; Rodell, M.

2017-12-01

Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0-5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.

Assimilation for skin SST in the NASA GEOS atmospheric data assimilation system

PubMed Central

Akella, Santha; Todling, Ricardo; Suarez, Max

2018-01-01

The present article describes the sea surface temperature (SST) developments implemented in the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric Data Assimilation System (ADAS). These are enhancements that contribute to the development of an atmosphere-ocean coupled data assimilation system using GEOS. In the current quasi-operational GEOS-ADAS, the SST is a boundary condition prescribed based on the OSTIA product, therefore SST and skin SST (Ts) are identical. This work modifies the GEOS-ADAS Ts by modeling and assimilating near sea surface sensitive satellite infrared (IR) observations. The atmosphere-ocean interface layer of the GEOS atmospheric general circulation model (AGCM) is updated to include near surface diurnal warming and cool-skin effects. The GEOS analysis system is also updated to directly assimilate SST-relevant Advanced Very High Resolution Radiometer (AVHRR) radiance observations. Data assimilation experiments designed to evaluate the Ts modification in GEOS-ADAS show improvements in the assimilation of radiance observations that extends beyond the thermal IR bands of AVHRR. In particular, many channels of hyperspectral sensors, such as those of the Atmospheric Infrared Sounder (AIRS), and Infrared Atmospheric Sounding Interferometer (IASI) are also better assimilated. We also obtained improved fit to withheld, in-situ buoy measurement of near-surface SST. Evaluation of forecast skill scores show marginal to neutral benefit from the modified Ts. PMID:29628531

High density electronic circuit and process for making

DOEpatents

Morgan, William P.

1999-01-01

High density circuits with posts that protrude beyond one surface of a substrate to provide easy mounting of devices such as integrated circuits. The posts also provide stress relief to accommodate differential thermal expansion. The process allows high interconnect density with fewer alignment restrictions and less wasted circuit area than previous processes. The resulting substrates can be test platforms for die testing and for multi-chip module substrate testing. The test platform can contain active components and emulate realistic operational conditions, replacing shorts/opens net testing.

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post streamline the interaction of analysis, forecast, and post-processing systems within NCEP. The NEMS Force, and will eventually provide support to the community through the Developmental Test Center (DTC

Endogenous circadian regulation of carbon dioxide exchange in terrestrial ecosystems

USDA-ARS?s Scientific Manuscript database

We tested the hypothesis that diurnal changes in terrestrial CO2 exchange are driven exclusively by the direct effect of the physical environment on plant physiology. We failed to corroborate this assumption, finding instead large diurnal fluctuations in whole ecosystem carbon assimilation across a ...

The Role of Culture Theory in Cross-Cultural Training: A Multimethod Study of Culture-Specific, Culture-General, and Culture Theory-Based Assimilators.

ERIC Educational Resources Information Center

Bhawuk, Dharm P. S.

1998-01-01

In a multimethod evaluation of cross-cultural training tools involving 102 exchange students at a midwestern university, a theory-based individualism and collectivism assimilator tool had significant advantages over culture-specific and culture-general assimilators and a control condition. Results support theory-based culture assimilators. (SLD)

Therapist activities preceding setbacks in the assimilation process.

PubMed

Gabalda, Isabel Caro; Stiles, William B; Pérez Ruiz, Sergio

2016-11-01

This study examined the therapist activities immediately preceding assimilation setbacks in the treatment of a good-outcome client treated with linguistic therapy of evaluation (LTE). Setbacks (N = 105) were defined as decreases of one or more assimilation stages from one passage to the next dealing with the same theme. The therapist activities immediately preceding those setbacks were classified using two kinds of codes: (a) therapist interventions and (b) positions the therapist took toward the client's internal voices. Preceding setbacks to early assimilation stages, where the problem was unformulated, the therapist was more often actively listening, and the setbacks were more often attributable to pushing a theme beyond the client's working zone. Preceding setbacks to later assimilation stages, where the problem was at least formulated, the therapist was more likely to be directing clients to consider alternatives, following the LTE agenda, and setbacks were more often attributable to the client following these directives shifting attention to less assimilated (but nevertheless formulated) aspects of the problem. At least in this case, setbacks followed systematically different therapist activities depending on the problem's stage of assimilation. Possible implications for the assimilation model's account of setbacks and for practice are discussed.

Effects of 4D-Var data assimilation using remote sensing precipitation products in a WRF over the complex Heihe River Basin

NASA Astrophysics Data System (ADS)

Pan, Xiaoduo; Li, Xin; Cheng, Guodong

2017-04-01

Traditionally, ground-based, in situ observations, remote sensing, and regional climate modeling, individually, cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrain. Data assimilation techniques are often used to assimilate ground observations and remote sensing products into models for dynamic downscaling. In this study, the Weather Research and Forecasting (WRF) model was used to assimilate two satellite precipitation products (TRMM 3B42 and FY-2D) using the 4D-Var data assimilation method. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly for short-term weather forecasting. Future work is proposed to assimilate a suite of remote sensing data, e.g., the combination of precipitation and soil moisture data, into a WRF model to improve 7-8 day forecasts of precipitation and other atmospheric variables.

AIRS Impact on Analysis and Forecast of an Extreme Rainfall Event (Indus River Valley 2010) with a Global Data Assimilation and Forecast System

NASA Technical Reports Server (NTRS)

Reale, O.; Lau, W. K.; Susskind, J.; Rosenberg, R.

2011-01-01

A set of data assimilation and forecast experiments are performed with the NASA Global data assimilation and forecast system GEOS-5, to compare the impact of different approaches towards assimilation of Advanced Infrared Spectrometer (AIRS) data on the precipitation analysis and forecast skill. The event chosen is an extreme rainfall episode which occurred in late July 11 2010 in Pakistan, causing massive floods along the Indus River Valley. Results show that the assimilation of quality-controlled AIRS temperature retrievals obtained under partly cloudy conditions produce better precipitation analyses, and substantially better 7-day forecasts, than assimilation of clear-sky radiances. The improvement of precipitation forecast skill up to 7 day is very significant in the tropics, and is caused by an improved representation, attributed to cloudy retrieval assimilation, of two contributing mechanisms: the low-level moisture advection, and the concentration of moisture over the area in the days preceding the precipitation peak.

Impact of data assimilation on ocean current forecasts in the Angola Basin

NASA Astrophysics Data System (ADS)

Phillipson, Luke; Toumi, Ralf

2017-06-01

The ocean current predictability in the data limited Angola Basin was investigated using the Regional Ocean Modelling System (ROMS) with four-dimensional variational data assimilation. Six experiments were undertaken comprising a baseline case of the assimilation of salinity/temperature profiles and satellite sea surface temperature, with the subsequent addition of altimetry, OSCAR (satellite-derived sea surface currents), drifters, altimetry and drifters combined, and OSCAR and drifters combined. The addition of drifters significantly improves Lagrangian predictability in comparison to the baseline case as well as the addition of either altimetry or OSCAR. OSCAR assimilation only improves Lagrangian predictability as much as altimetry assimilation. On average the assimilation of either altimetry or OSCAR with drifter velocities does not significantly improve Lagrangian predictability compared to the drifter assimilation alone, even degrading predictability in some cases. When the forecast current speed is large, it is more likely that the combination improves trajectory forecasts. Conversely, when the currents are weaker, it is more likely that the combination degrades the trajectory forecast.

Direct variational data assimilation algorithm for atmospheric chemistry data with transport and transformation model

NASA Astrophysics Data System (ADS)

Penenko, Alexey; Penenko, Vladimir; Nuterman, Roman; Baklanov, Alexander; Mahura, Alexander

2015-11-01

Atmospheric chemistry dynamics is studied with convection-diffusion-reaction model. The numerical Data Assimilation algorithm presented is based on the additive-averaged splitting schemes. It carries out ''fine-grained'' variational data assimilation on the separate splitting stages with respect to spatial dimensions and processes i.e. the same measurement data is assimilated to different parts of the split model. This design has efficient implementation due to the direct data assimilation algorithms of the transport process along coordinate lines. Results of numerical experiments with chemical data assimilation algorithm of in situ concentration measurements on real data scenario have been presented. In order to construct the scenario, meteorological data has been taken from EnviroHIRLAM model output, initial conditions from MOZART model output and measurements from Airbase database.

Variational fine-grained data assimilation schemes for atmospheric chemistry transport and transformation models

NASA Astrophysics Data System (ADS)

Penenko, Alexey; Penenko, Vladimir; Tsvetova, Elena

2015-04-01

The paper concerns data assimilation problem for an atmospheric chemistry transport and transformation models. Data assimilation is carried out within variation approach on a single time step of the approximated model. 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 minimum of the target functional combining control function norm to a misfit between measured and model-simulated analog of data. This provides a flow-dependent and physically-plausible structure of the resulting analysis and reduces the need to calculate model error covariance matrices that are sought within conventional approach to data assimilation. Extension of the atmospheric transport model with a chemical transformations module influences data assimilation algorithms performance. This influence is investigated with numerical experiments for different meteorological conditions altering convection-diffusion processes characteristics, namely strong, medium and low wind conditions. To study the impact of transformation and data assimilation, we compare results for a convection-diffusion model (without data assimilation), convection-diffusion with assimilation, convection-diffusion-reaction (without data assimilation) and convection-diffusion-reaction-assimilation models. Both high dimensionalities of the atmospheric chemistry models and a real-time mode of operation demand for computational efficiency of the algorithms. Computational issues with complicated models can be solved by using a splitting technique. As the result a model is presented as a set of relatively independent simple models equipped with a kind of coupling procedure. With regard to data assimilation two approaches can be identified. In a fine-grained approach data assimilation is carried out on the separate splitting stages [1,2] independently on shared measurement data. The same situation arises when constructing a hybrid model out of two models each having its own assimilation scheme. In integrated schemes data assimilation is carried out with respect to the split model as a whole. First approach is more efficient from computational point of view, for in some important cases it can be implemented without iterations [2]. Its shortcoming is that control functions in different part of the model are adjusted independently thus having less evident physical sense. With the aid of numerical experiments we compare the two approaches. Work has been partially supported by COST Action ES1004 STSM Grants #16817 and #21654, RFBR 14-01-31482 mol a and 14-01-00125, Programmes # 4 Presidium RAS and # 3 MSD RAS, integration projects SB RAS #8 and #35. References: [1] V. V. Penenko Variational methods of data assimilation and inverse problems for studying the atmosphere, ocean, and environment Num. Anal. and Appl., 2009 V 2 No 4, 341-351. [2] A.V. Penenko and V.V. Penenko. Direct data assimilation method for convection-diffusion models based on splitting scheme. Computational technologies, 19(4):69-83, 2014.

A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model

NASA Astrophysics Data System (ADS)

Capecchi, V.; Gozzini, B.

2012-04-01

The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say θ(b,1) derived from global model) towards the ASCAT derived value (say ^θ A). The soil moisture analysis θ(a,1) is given by: { θ + K (^θA - θ ) l = 1 θ(a,1) = θ(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently implementing and testing an EKF for combining conventional observations and remote sensed soil moisture data in order to produce a more accurate analysis. In the present work verification skills (RMSE, BIAS, correlation) of both control and test run are presented using observed data collected by International Soil Moisture Network. Moreover improvements in temperature predictions are evaluated.

Investigating genotype specific response in photosynthetic behavior under drought stress and nitrogen limitation in Brassica rapa.

NASA Astrophysics Data System (ADS)

Pleban, J. R.; Mackay, D. S.; Ewers, B. E.; Weinig, C.; Aston, T.

2015-12-01

Challenges in terrestrial ecosystem modeling include characterizing the impact of stress on vegetation and the heterogeneous behavior of different species within the environment. In an effort to address these challenges the impacts of drought and nutrient limitation on the CO2 assimilation of multiple genotypes of Brassica rapa was investigated using the Farquhar Model (FM) of photosynthesis following a Bayesian parameterization and updating scheme. Leaf gas exchange and chlorophyll fluorescence measurements from an unstressed group (well-watered/well-fertilized) and two stressed groups (drought/well-fertilized and well-watered/nutrient limited) were used to estimate FM model parameters. Unstressed individuals were used to initialize Bayesian parameter estimation. Posterior mean estimates yielded a close fit with data as observed assimilation (An) closely matched predicted (Ap) with mean standard error for all individuals ranging from 0.8 to 3.1 μmol CO2 m-2 s-1. Posterior parameter distributions of the unstressed individuals were combined and fit to distributions to establish species level Bayesian priors of FM parameters for testing stress responses. Species level distributions of unstressed group identified mean maximum rates of carboxylation standardized to 25° (Vcmax25) as 101.8 μmol m-2 s-1 (± 29.0) and mean maximum rates of electron transport standardized to 25° (Jmax25) as 319.7 μmol m-2 s-1 (± 64.4). These updated priors were used to test the response of drought and nutrient limitations on assimilation. In the well-watered/nutrient limited group a decrease of 28.0 μmol m-2 s-1 was observed in mean estimate of Vcmax25, a decrease of 27.9 μmol m-2 s-1 in Jmax25 and a decrease in quantum yield from 0.40 mol photon/mol e- in unstressed individuals to 0.14 in the nutrient limited group. In the drought/well-fertilized group a decrease was also observed in Vcmax25 and Jmax25. The genotype specific unstressed and stressed responses were then used to parameterize an ecosystem process model with application at the field scale to investigate mechanisms of stress response in B. rapa by testing a variety of functional forms to limit assimilation in hydraulic or nutrient limited conditions.

Data Assimilation of AirSWOT and Synthetically Derived SWOT Observations of Water Surface Elevation in a Multichannel River

NASA Astrophysics Data System (ADS)

Altenau, E. H.; Pavelsky, T.; Andreadis, K.; Bates, P. D.; Neal, J. C.

2017-12-01

Multichannel rivers continue to be challenging features to quantify, especially at regional and global scales, which is problematic because accurate representations of such environments are needed to properly monitor the earth's water cycle as it adjusts to climate change. It has been demonstrated that higher-complexity, 2D models outperform lower-complexity, 1D models in simulating multichannel river hydraulics at regional scales due to the inclusion of the channel network's connectivity. However, new remote sensing measurements from the future Surface Water and Ocean Topography (SWOT) mission and it's airborne analog AirSWOT offer new observations that can be used to try and improve the lower-complexity, 1D models to achieve accuracies closer to the higher-complexity, 2D codes. Here, we use an Ensemble Kalman Filter (EnKF) to assimilate AirSWOT water surface elevation (WSE) measurements from a 2015 field campaign into a 1D hydrodynamic model along a 90 km reach of Tanana River, AK. This work is the first to test data assimilation methods using real SWOT-like data from AirSWOT. Additionally, synthetic SWOT observations of WSE are generated across the same study site using a fine-resolution 2D model and assimilated into the coarser-resolution 1D model. Lastly, we compare the abilities of AirSWOT and the synthetic-SWOT observations to improve spatial and temporal model outputs in WSEs. Results indicate 1D model outputs of spatially distributed WSEs improve as observational coverage increases, and improvements in temporal fluctuations in WSEs depend on the number of observations. Furthermore, results reveal that assimilation of AirSWOT observations produce greater error reductions in 1D model outputs compared to synthetic SWOT observations due to lower measurement errors. Both AirSWOT and the synthetic SWOT observations significantly lower spatial and temporal errors in 1D model outputs of WSEs.

US-TEC: A new data assimilation product from the Space Environment Center characterizing the ionospheric total electron content using real-time GPS data

NASA Astrophysics Data System (ADS)

Fuller-Rowell, Tim; Araujo-Pradere, Eduardo; Minter, Cliff; Codrescu, Mihail; Spencer, Paul; Robertson, Doug; Jacobson, Abram R.

2006-12-01

The potential of data assimilation for operational numerical weather forecasting has been appreciated for many years. For space weather it is a new path that we are just beginning to explore. With the emergence of satellite constellations and the networks of ground-based observations, sufficient data sources are now available to make the application of data assimilation techniques a viable option. The first space weather product at Space Environment Center (SEC) utilizing data assimilation techniques, US-TEC, was launched as a test operational product in November 2004. US-TEC characterizes the ionospheric total electron content (TEC) over the continental United States (CONUS) every 15 min with about a 15-min latency. US-TEC is based on a Kalman filter data assimilation scheme driven by a ground-based network of real-time GPS stations. The product includes a map of the vertical TEC, an estimate of the uncertainty in the map, and the departure of the TEC from a 10-day average at that particular universal time. In addition, data files are provided for vertical TEC and the line-of-sight electron content to all GPS satellites in view over the CONUS at that time. The information can be used to improve single-frequency GPS positioning by providing more accurate corrections for the ionospheric signal delay, or it can be used to initialize rapid integer ambiguity resolution schemes for dual-frequency GPS systems. Validation of US-TEC indicates an accuracy of the line-of-sight electron content of between 2 and 3 TEC units (1 TECU = 1016 el m-2), equivalent to less than 50 cm signal delay at L1 frequencies, which promises value for GPS users. This is the first step along a path that will likely lead to major improvement in space weather forecasting, paralleling the advances achieved in meteorological weather forecasting.

A unifying conceptual model for the environmental responses of isoprene emissions from plants

PubMed Central

Morfopoulos, Catherine; Prentice, Iain C.; Keenan, Trevor F.; Friedlingstein, Pierre; Medlyn, Belinda E.; Peñuelas, Josep; Possell, Malcolm

2013-01-01

Background and Aims Isoprene is the most important volatile organic compound emitted by land plants in terms of abundance and environmental effects. Controls on isoprene emission rates include light, temperature, water supply and CO2 concentration. A need to quantify these controls has long been recognized. There are already models that give realistic results, but they are complex, highly empirical and require separate responses to different drivers. This study sets out to find a simpler, unifying principle. Methods A simple model is presented based on the idea of balancing demands for reducing power (derived from photosynthetic electron transport) in primary metabolism versus the secondary pathway that leads to the synthesis of isoprene. This model's ability to account for key features in a variety of experimental data sets is assessed. Key results The model simultaneously predicts the fundamental responses observed in short-term experiments, namely: (1) the decoupling between carbon assimilation and isoprene emission; (2) a continued increase in isoprene emission with photosynthetically active radiation (PAR) at high PAR, after carbon assimilation has saturated; (3) a maximum of isoprene emission at low internal CO2 concentration (ci) and an asymptotic decline thereafter with increasing ci; (4) maintenance of high isoprene emissions when carbon assimilation is restricted by drought; and (5) a temperature optimum higher than that of photosynthesis, but lower than that of isoprene synthase activity. Conclusions A simple model was used to test the hypothesis that reducing power available to the synthesis pathway for isoprene varies according to the extent to which the needs of carbon assimilation are satisfied. Despite its simplicity the model explains much in terms of the observed response of isoprene to external drivers as well as the observed decoupling between carbon assimilation and isoprene emission. The concept has the potential to improve global-scale modelling of vegetation isoprene emission. PMID:24052559

Iron assimilation by the clam Laternula elliptica: Do stable isotopes (δ⁵⁶Fe) help to decipher the sources?

PubMed

Poigner, Harald; Wilhelms-Dick, Dorothee; Abele, Doris; Staubwasser, Michael; Henkel, Susann

2015-09-01

Iron stable isotope signatures (δ(56)Fe) in hemolymph (bivalve blood) of the Antarctic bivalve Laternula elliptica were analyzed by Multiple Collector-Inductively Coupled Plasma-Mass Spectrometry (MC-ICP-MS) to test whether the isotopic fingerprint can be tracked back to the predominant sources of the assimilated Fe. An earlier investigation of Fe concentrations in L. elliptica hemolymph suggested that an assimilation of reactive and bioavailable Fe (oxyhydr)oxide particles (i.e. ferrihydrite), precipitated from pore water Fe around the benthic boundary, is responsible for the high Fe concentration in L. elliptica (Poigner et al., 2013 b). At two stations in Potter Cove (King George Island, Antarctica) bivalve hemolymph showed mean δ(56)Fe values of -1.19 ± 0.34‰ and -1.04 ± 0.39 ‰, respectively, which is between 0.5‰ and 0.85‰ lighter than the pool of easily reducible Fe (oxyhydr)oxides of the surface sediments (-0.3‰ to -0.6‰). This is in agreement with the enrichment of lighter Fe isotopes at higher trophic levels, resulting from the preferential assimilation of light isotopes from nutrition. Nevertheless, δ(56)Fe hemolymph values from both stations showed a high variability, ranging between -0.21‰ (value close to unaltered/primary Fe(oxyhydr)oxide minerals) and -1.91‰ (typical for pore water Fe or diagenetic Fe precipitates), which we interpret as a "mixed" δ(56)Fe signature caused by Fe assimilation from different sources with varying Fe contents and δ(56)Fe values. Furthermore, mass dependent Fe fractionation related to physiological processes within the bivalve cannot be ruled out. This is the first study addressing the potential of Fe isotopes for tracing back food sources of bivalves. Copyright © 2015 Elsevier Ltd. All rights reserved.

Strategies to reduce the complexity of hydrologic data assimilation for high-dimensional models

NASA Astrophysics Data System (ADS)

Hernandez, F.; Liang, X.

2017-12-01

Probabilistic forecasts in the geosciences offer invaluable information by allowing to estimate the uncertainty of predicted conditions (including threats like floods and droughts). However, while forecast systems based on modern data assimilation algorithms are capable of producing multi-variate probability distributions of future conditions, the computational resources required to fully characterize the dependencies between the model's state variables render their applicability impractical for high-resolution cases. This occurs because of the quadratic space complexity of storing the covariance matrices that encode these dependencies and the cubic time complexity of performing inference operations with them. In this work we introduce two complementary strategies to reduce the size of the covariance matrices that are at the heart of Bayesian assimilation methods—like some variants of (ensemble) Kalman filters and of particle filters—and variational methods. The first strategy involves the optimized grouping of state variables by clustering individual cells of the model into "super-cells." A dynamic fuzzy clustering approach is used to take into account the states (e.g., soil moisture) and forcings (e.g., precipitation) of each cell at each time step. The second strategy consists in finding a compressed representation of the covariance matrix that still encodes the most relevant information but that can be more efficiently stored and processed. A learning and a belief-propagation inference algorithm are developed to take advantage of this modified low-rank representation. The two proposed strategies are incorporated into OPTIMISTS, a state-of-the-art hybrid Bayesian/variational data assimilation algorithm, and comparative streamflow forecasting tests are performed using two watersheds modeled with the Distributed Hydrology Soil Vegetation Model (DHSVM). Contrasts are made between the efficiency gains and forecast accuracy losses of each strategy used in isolation, and of those achieved through their coupling. We expect these developments to help catalyze improvements in the predictive accuracy of large-scale forecasting operations by lowering the costs of deploying advanced data assimilation techniques.

How does warming affect carbon allocation, respiration and residence time in trees? An isotope tracer approach in a eucalypt

NASA Astrophysics Data System (ADS)

Pendall, E.; Drake, J. E.; Furze, M.; Barton, C. V.; Carillo, Y.; Richter, A.; Tjoelker, M. G.

2017-12-01

Climate warming has the potential to alter the balance between photosynthetic carbon assimilation and respiratory losses in forest trees, leading to uncertainty in predicting their future physiological functioning. In a previous experiment, warming decreased canopy CO2 assimilation (A) rates of Eucalyptus tereticornis trees, but respiration (R) rates were usually not significantly affected, due to physiological acclimation to temperature. This led to a slight increase in (R/A) and thus decrease in plant carbon use efficiency with climate warming. In contrast to carbon fluxes, the effect of warming on carbon allocation and residence time in trees has received less attention. We conducted a study to test the hypothesis that warming would decrease the allocation of C belowground owing to reduced cost of nutrient uptake. E. parramattensis trees were grown in the field in unique whole-tree chambers operated at ambient and ambient +3 °C temperature treatments (n=3 per treatment). We applied a 13CO2 pulse and followed the label in CO2 respired from leaves, roots, canopy and soil, in plant sugars, and in rhizosphere microbes over a 3-week period in conjunction with measurements of tree growth. The 9-m tall, 57 m3 whole-tree chambers were monitored for CO2 concentrations in independent canopy and below ground (root and soil) compartments; periodic monitoring of δ13C values in air in the compartments allowed us to quantify the amount of 13CO2 assimilated and respired by each tree. Warmed trees grew faster and assimilated more of the label than control trees, but the 13C allocation to canopy, root and soil respiration was not altered. However, warming appeared to reduce the residence time of carbon respired from leaves, and especially from roots and soil, indicating that autotrophic respiration has the potential to feedback to climate change. This experiment provides insights into how warming may affect the fate of assimilated carbon from the leaf to the ecosystem scale.

Assimilation of enterprise technology upgrades: a factor-based study

NASA Astrophysics Data System (ADS)

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.

Cryptococcus spp isolated from dust microhabitat in Brazilian libraries.

PubMed

Leite, Diniz P; Amadio, Janaina V R S; Martins, Evelin R; Simões, Sara A A; Yamamoto, Ana Caroline A; Leal-Santos, Fábio A; Takahara, Doracilde T; Hahn, Rosane C

2012-06-08

The Cryptococcus spp is currently composed of encapsulated yeasts of cosmopolitan distribution, including the etiological agents of cryptococcosis. The fungus are found mainly in substrates of animal and plant origin. Human infection occurs through inhalation of spores present in the environment. Eighty-four swab collections were performed on dust found on books in three libraries in the city of Cuiabá, state of Mato Grosso, Brazil. The material was seeded in Sabouraud agar and then observed for characteristics compatible with colonies with a creamy to mucous aspect; the material was then isolated in birdseed (Niger) agar and cultivated at a temperature of 37°C for 5 to 7 days. Identification of isolated colonies was performed by microscopic observation in fresh preparations dyed with India ink, additional tests performed on CGB (L-canavanine glycine bromothymol blue), urea broth, and carbohydrate assimilation tests (auxanogram). Of the 84 samples collected from book dust, 18 (21.4%) were positive for Cryptococcus spp totalizing 41 UFC's. The most frequently isolated species was C. gattii 15 (36.6%); followed by C. terreus, 12 (29.3%); C. luteolus 4 (9.8%); C. neoformans, and C. uniguttulatus 3 (7.3%), and C. albidus and C. humiculus with 2 (4.6%) of the isolates. The high biodiversity of the yeasts of the Cryptococcus genus, isolated from different environmental sources in urban areas of Brazil suggests the possibility of individuals whose immune systems have been compromised or even healthy individuals coming into sources of fungal propagules on a daily bases throughout their lives. This study demonstrates the acquisition possible of cryptococcosis infection from dust in libraries.

Cellulosimicrobium funkei: first report of infection in a nonimmunocompromised patient and useful phenotypic tests for differentiation from Cellulosimicrobium cellulans and Cellulosimicrobium terreum.

PubMed

Petkar, Hawabibee; Li, Anthony; Bunce, Nicholas; Duffy, Kim; Malnick, Henry; Shah, Jayesh J

2011-03-01

Cellulosimicrobium funkei is a rare, opportunistic pathogen. We describe a case of bacteremia and possibly prosthetic valve endocarditis by this organism in a nonimmunocompromised patient. Useful phenotypic tests for differentiating C. funkei from Cellulosimicrobium cellulans and Cellulosimicrobium terreum include motility, raffinose fermentation, glycogen, D-xylose, and methyl-α-D-glucopyranoside assimilation, and growth at 35°C.

Aerosol data assimilation in the chemical transport model MOCAGE during the TRAQA/ChArMEx campaign: aerosol optical depth

NASA Astrophysics Data System (ADS)

Sič, Bojan; El Amraoui, Laaziz; Piacentini, Andrea; Marécal, Virginie; Emili, Emanuele; Cariolle, Daniel; Prather, Michael; Attié, Jean-Luc

2016-11-01

In this study, we describe the development of the aerosol optical depth (AOD) assimilation module in the chemistry transport model (CTM) MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle). Our goal is to assimilate the spatially averaged 2-D column AOD data from the National Aeronautics and Space Administration (NASA) Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and to estimate improvements in a 3-D CTM assimilation run compared to a direct model run. Our assimilation system uses 3-D-FGAT (first guess at appropriate time) as an assimilation method and the total 3-D aerosol concentration as a control variable. In order to have an extensive validation dataset, we carried out our experiment in the northern summer of 2012 when the pre-ChArMEx (CHemistry and AeRosol MEditerranean EXperiment) field campaign TRAQA (TRAnsport à longue distance et Qualité de l'Air dans le bassin méditerranéen) took place in the western Mediterranean basin. The assimilated model run is evaluated independently against a range of aerosol properties (2-D and 3-D) measured by in situ instruments (the TRAQA size-resolved balloon and aircraft measurements), the satellite Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument and ground-based instruments from the Aerosol Robotic Network (AERONET) network. The evaluation demonstrates that the AOD assimilation greatly improves aerosol representation in the model. For example, the comparison of the direct and the assimilated model run with AERONET data shows that the assimilation increased the correlation (from 0.74 to 0.88), and reduced the bias (from 0.050 to 0.006) and the root mean square error in the AOD (from 0.12 to 0.07). When compared to the 3-D concentration data obtained by the in situ aircraft and balloon measurements, the assimilation consistently improves the model output. The best results as expected occur when the shape of the vertical profile is correctly simulated by the direct model. We also examine how the assimilation can influence the modelled aerosol vertical distribution. The results show that a 2-D continuous AOD assimilation can improve the 3-D vertical profile, as a result of differential horizontal transport of aerosols in the model.

Thermal coefficients of technology assimilation by natural systems

NASA Technical Reports Server (NTRS)

Mueller, R. F.

1971-01-01

Estimates of thermal coefficients of the rates of technology assimilation processes was made. Consideration of such processes as vegetation and soil recovery and pollution assimilation indicates that these processes proceed ten to several hundred times more slowly in earth's cold regions than in temperate regions. It was suggested that these differential assimilation rates are important data in planning for technological expansion in Arctic regions.

A Unified Data Assimilation Strategy for Regional Coupled Atmosphere-Ocean Prediction Systems

NASA Astrophysics Data System (ADS)

Xie, Lian; Liu, Bin; Zhang, Fuqing; Weng, Yonghui

2014-05-01

Improving tropical cyclone (TC) forecasts is a top priority in weather forecasting. Assimilating various observational data to produce better initial conditions for numerical models using advanced data assimilation techniques has been shown to benefit TC intensity forecasts, whereas assimilating large-scale environmental circulation into regional models by spectral nudging or Scale-Selective Data Assimilation (SSDA) has been demonstrated to improve TC track forecasts. Meanwhile, taking into account various air-sea interaction processes by high-resolution coupled air-sea modelling systems has also been shown to improve TC intensity forecasts. Despite the advances in data assimilation and air-sea coupled models, large errors in TC intensity and track forecasting remain. For example, Hurricane Nate (2011) has brought considerable challenge for the TC operational forecasting community, with very large intensity forecast errors (27, 25, and 40 kts for 48, 72, and 96 h, respectively) for the official forecasts. Considering the slow-moving nature of Hurricane Nate, it is reasonable to hypothesize that air-sea interaction processes played a critical role in the intensity change of the storm, and accurate representation of the upper ocean dynamics and thermodynamics is necessary to quantitatively describe the air-sea interaction processes. Currently, data assimilation techniques are generally only applied to hurricane forecasting in stand-alone atmospheric or oceanic model. In fact, most of the regional hurricane forecasting models only included data assimilation techniques for improving the initial condition of the atmospheric model. In such a situation, the benefit of adjustments in one model (atmospheric or oceanic) by assimilating observational data can be compromised by errors from the other model. Thus, unified data assimilation techniques for coupled air-sea modelling systems, which not only simultaneously assimilate atmospheric and oceanic observations into the coupled air-sea modelling system, but also nudging the large-scale environmental flow in the regional model towards global model forecasts are of increasing necessity. In this presentation, we will outline a strategy for an integrated approach in air-sea coupled data assimilation and discuss its benefits and feasibility from incremental results for select historical hurricane cases.

Dynamically adaptive data-driven simulation of extreme hydrological flows

NASA Astrophysics Data System (ADS)

Kumar Jain, Pushkar; Mandli, Kyle; Hoteit, Ibrahim; Knio, Omar; Dawson, Clint

2018-02-01

Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

The evolution of menstruation: a new model for genetic assimilation: explaining molecular origins of maternal responses to fetal invasiveness.

PubMed

Emera, Deena; Romero, Roberto; Wagner, Günter

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. Copyright © 2012 WILEY Periodicals, Inc.

Testing mechanistic models of growth in insects.

PubMed

Maino, James L; Kearney, Michael R

2015-11-22

Insects are typified by their small size, large numbers, impressive reproductive output and rapid growth. However, insect growth is not simply rapid; rather, insects follow a qualitatively distinct trajectory to many other animals. Here we present a mechanistic growth model for insects and show that increasing specific assimilation during the growth phase can explain the near-exponential growth trajectory of insects. The presented model is tested against growth data on 50 insects, and compared against other mechanistic growth models. Unlike the other mechanistic models, our growth model predicts energy reserves per biomass to increase with age, which implies a higher production efficiency and energy density of biomass in later instars. These predictions are tested against data compiled from the literature whereby it is confirmed that insects increase their production efficiency (by 24 percentage points) and energy density (by 4 J mg(-1)) between hatching and the attainment of full size. The model suggests that insects achieve greater production efficiencies and enhanced growth rates by increasing specific assimilation and increasing energy reserves per biomass, which are less costly to maintain than structural biomass. Our findings illustrate how the explanatory and predictive power of mechanistic growth models comes from their grounding in underlying biological processes. © 2015 The Author(s).

Toward a multivariate reanalysis of the North Atlantic ocean biogeochemistry during 1998-2006 based on the assimilation of SeaWiFS chlorophyll data

NASA Astrophysics Data System (ADS)

Fontana, C.; Brasseur, P.; Brankart, J.-M.

2012-04-01

Today, the routine assimilation of satellite data into operational models of the ocean circulation is mature enough to enable the production of global reanalyses describing the ocean circulation variability during the past decades. The expansion of the "reanalysis" concept from ocean physics to biogeochemistry is a timely challenge that motivates the present study. The objective of this paper is to investigate the potential benefits of assimilating satellite-estimated chlorophyll data into a basin-scale three-dimensional coupled physical-biogeochemical model of the North-Atlantic. The aim is on one hand to improve forecasts of ocean biogeochemical properties and on the other hand to define a methodology for producing data-driven climatologies based on coupled physical-biogeochemical modelling. A simplified variant of the Kalman filter is used to assimilate ocean color data during a 9 year-long period. In this frame, two experiences are carried out, with and without anamorphic transformations of the state vector variables. Data assimilation efficiency is assessed with respect to the assimilated data set, the nitrate World Ocean Atlas database and a derived climatology. Along the simulation period, the non-linear assimilation scheme clearly improves the surface chlorophyll concentrations analysis and forecast, especially in the North Atlantic bloom region. Nitrate concentration forecasts are also improved thanks to the assimilation of ocean color data while this improvement is limited to the upper layer of the water column, in agreement with recent related litterature. This feature is explained by the weak correlation taken into account by the assimilation between surface phytoplankton and nitrate concentration deeper than 50 m. The assessement of the non-linear assimilation experiments indicates that the proposed methodology provides the skeleton of an assimilative system suitable for reanalysing the ocean biogeochemistry based on ocean color data.

Toward a multivariate reanalysis of the North Atlantic Ocean biogeochemistry during 1998-2006 based on the assimilation of SeaWiFS chlorophyll data

NASA Astrophysics Data System (ADS)

Fontana, C.; Brasseur, P.; Brankart, J.-M.

2013-01-01

Today, the routine assimilation of satellite data into operational models of ocean circulation is mature enough to enable the production of global reanalyses describing the ocean circulation variability during the past decades. The expansion of the "reanalysis" concept from ocean physics to biogeochemistry is a timely challenge that motivates the present study. The objective of this paper is to investigate the potential benefits of assimilating satellite-estimated chlorophyll data into a basin-scale three-dimensional coupled physical-biogeochemical model of the North Atlantic. The aim is on the one hand to improve forecasts of ocean biogeochemical properties and on the other hand to define a methodology for producing data-driven climatologies based on coupled physical-biogeochemical modeling. A simplified variant of the Kalman filter is used to assimilate ocean color data during a 9-year period. In this frame, two experiments are carried out, with and without anamorphic transformations of the state vector variables. Data assimilation efficiency is assessed with respect to the assimilated data set, nitrate of the World Ocean Atlas database and a derived climatology. Along the simulation period, the non-linear assimilation scheme clearly improves the surface analysis and forecast chlorophyll concentrations, especially in the North Atlantic bloom region. Nitrate concentration forecasts are also improved thanks to the assimilation of ocean color data while this improvement is limited to the upper layer of the water column, in agreement with recent related literature. This feature is explained by the weak correlation taken into account by the assimilation between surface phytoplankton and nitrate concentrations deeper than 50 meters. The assessment of the non-linear assimilation experiments indicates that the proposed methodology provides the skeleton of an assimilative system suitable for reanalyzing the ocean biogeochemistry based on ocean color data.

Accounting for spatial correlation errors in the assimilation of GRACE into hydrological models through localization

NASA Astrophysics Data System (ADS)

Khaki, M.; Schumacher, M.; Forootan, E.; Kuhn, M.; Awange, J. L.; van Dijk, A. I. J. M.

2017-10-01

Assimilation of terrestrial water storage (TWS) information from the Gravity Recovery And Climate Experiment (GRACE) satellite mission can provide significant improvements in hydrological modelling. However, the rather coarse spatial resolution of GRACE TWS and its spatially correlated errors pose considerable challenges for achieving realistic assimilation results. Consequently, successful data assimilation depends on rigorous modelling of the full error covariance matrix of the GRACE TWS estimates, as well as realistic error behavior for hydrological model simulations. In this study, we assess the application of local analysis (LA) to maximize the contribution of GRACE TWS in hydrological data assimilation. For this, we assimilate GRACE TWS into the World-Wide Water Resources Assessment system (W3RA) over the Australian continent while applying LA and accounting for existing spatial correlations using the full error covariance matrix. GRACE TWS data is applied with different spatial resolutions including 1° to 5° grids, as well as basin averages. The ensemble-based sequential filtering technique of the Square Root Analysis (SQRA) is applied to assimilate TWS data into W3RA. For each spatial scale, the performance of the data assimilation is assessed through comparison with independent in-situ ground water and soil moisture observations. Overall, the results demonstrate that LA is able to stabilize the inversion process (within the implementation of the SQRA filter) leading to less errors for all spatial scales considered with an average RMSE improvement of 54% (e.g., 52.23 mm down to 26.80 mm) for all the cases with respect to groundwater in-situ measurements. Validating the assimilated results with groundwater observations indicates that LA leads to 13% better (in terms of RMSE) assimilation results compared to the cases with Gaussian errors assumptions. This highlights the great potential of LA and the use of the full error covariance matrix of GRACE TWS estimates for improved data assimilation results.

Simultaneous state-parameter estimation supports the evaluation of data assimilation performance and measurement design for soil-water-atmosphere-plant system

NASA Astrophysics Data System (ADS)

Hu, Shun; Shi, Liangsheng; Zha, Yuanyuan; Williams, Mathew; Lin, Lin

2017-12-01

Improvements to agricultural water and crop managements require detailed information on crop and soil states, and their evolution. Data assimilation provides an attractive way of obtaining these information by integrating measurements with model in a sequential manner. However, data assimilation for soil-water-atmosphere-plant (SWAP) system is still lack of comprehensive exploration due to a large number of variables and parameters in the system. In this study, simultaneous state-parameter estimation using ensemble Kalman filter (EnKF) was employed to evaluate the data assimilation performance and provide advice on measurement design for SWAP system. The results demonstrated that a proper selection of state vector is critical to effective data assimilation. Especially, updating the development stage was able to avoid the negative effect of ;phenological shift;, which was caused by the contrasted phenological stage in different ensemble members. Simultaneous state-parameter estimation (SSPE) assimilation strategy outperformed updating-state-only (USO) assimilation strategy because of its ability to alleviate the inconsistency between model variables and parameters. However, the performance of SSPE assimilation strategy could deteriorate with an increasing number of uncertain parameters as a result of soil stratification and limited knowledge on crop parameters. In addition to the most easily available surface soil moisture (SSM) and leaf area index (LAI) measurements, deep soil moisture, grain yield or other auxiliary data were required to provide sufficient constraints on parameter estimation and to assure the data assimilation performance. This study provides an insight into the response of soil moisture and grain yield to data assimilation in SWAP system and is helpful for soil moisture movement and crop growth modeling and measurement design in practice.

Methodological Developments in Geophysical Assimilation Modeling

NASA Astrophysics Data System (ADS)

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 investigate critical issues related to knowledge reliability, such as uncertainty due to model structure error (conceptual uncertainty).

Multi-Scale 4DVAR Assimilation of Glider Teams on the North Carolina Shelf

NASA Astrophysics Data System (ADS)

Osborne, J. J. V.; Carrier, M.; Book, J. W.; Barron, C. N.; Rice, A. E.; Rowley, C. D.; Smedstad, L.; Souopgui, I.; Teague, W. J.

2017-12-01

We demonstrate a method to assimilate glider profile data from multiple gliders in close proximity ( 10 km or less). Gliders were deployed in a field experiment from 17 May until 4 June 2017, north of Cape Hatteras and inshore of the Gulf Stream. Gliders were divided into two teams, generally two or three gliders per team. One team was tasked with station keeping and the other with moving and sampling regions of high variability in temperature and salinity. Glider data are assimilated into the Relocatable Navy Coastal Ocean Model (RELO NCOM) with four dimensional variational assimilation (NCOM-4DVAR). RELO NCOM is used by the US Navy to predict the ocean. RELO NCOM is a baroclinic, Boussinesq, free-surface, and hydrostatic ocean model with a flexible sigma-z vertical coordinate. Two domains are used, one focused north and one focused south of Cape Hatteras. The domains overlap near the gliders, thus providing two forecasts near the gliders. Both domains have 1 km horizontal resolution. Data are assimilated in a newly-developed multi-scale data-processing and assimilating approach using NCOM-4DVAR. This enables NCOM-4DVAR to use many more observations than standard NCOM-4DVAR, improving the analysis and forecast. Assimilation experiments use station-keeping glider data, moving glider data, or all glider data. Sea surface temperature (SST) data and satellite altimeter (SSH) data are also assimilated. An additional experiment omits glider data but still assimilates SST and SSH data. Conductivity, temperature, and depth (CTD) profiles from the R/V Savannah are used for validation, including data from an underway CTD (UCTD). Data from glider teams have the potential to significantly improve model forecasts. Missions using teams of gliders can be planned to maximize data assimilation for optimal impact on model predictions.

The role of ensemble-based statistics in variational assimilation of cloud-affected observations from infrared imagers

NASA Astrophysics Data System (ADS)

Hacker, Joshua; Vandenberghe, Francois; Jung, Byoung-Jo; Snyder, Chris

2017-04-01

Effective assimilation of cloud-affected radiance observations from space-borne imagers, with the aim of improving cloud analysis and forecasting, has proven to be difficult. Large observation biases, nonlinear observation operators, and non-Gaussian innovation statistics present many challenges. Ensemble-variational data assimilation (EnVar) systems offer the benefits of flow-dependent background error statistics from an ensemble, and the ability of variational minimization to handle nonlinearity. The specific benefits of ensemble statistics, relative to static background errors more commonly used in variational systems, have not been quantified for the problem of assimilating cloudy radiances. A simple experiment framework is constructed with a regional NWP model and operational variational data assimilation system, to provide the basis understanding the importance of ensemble statistics in cloudy radiance assimilation. Restricting the observations to those corresponding to clouds in the background forecast leads to innovations that are more Gaussian. The number of large innovations is reduced compared to the more general case of all observations, but not eliminated. The Huber norm is investigated to handle the fat tails of the distributions, and allow more observations to be assimilated without the need for strict background checks that eliminate them. Comparing assimilation using only ensemble background error statistics with assimilation using only static background error statistics elucidates the importance of the ensemble statistics. Although the cost functions in both experiments converge to similar values after sufficient outer-loop iterations, the resulting cloud water, ice, and snow content are greater in the ensemble-based analysis. The subsequent forecasts from the ensemble-based analysis also retain more condensed water species, indicating that the local environment is more supportive of clouds. In this presentation we provide details that explain the apparent benefit from using ensembles for cloudy radiance assimilation in an EnVar context.

Next generation initiation techniques

NASA Technical Reports Server (NTRS)

Warner, Tom; Derber, John; Zupanski, Milija; Cohn, Steve; Verlinde, Hans

1993-01-01

Four-dimensional data assimilation strategies can generally be classified as either current or next generation, depending upon whether they are used operationally or not. Current-generation data-assimilation techniques are those that are presently used routinely in operational-forecasting or research applications. They can be classified into the following categories: intermittent assimilation, Newtonian relaxation, and physical initialization. It should be noted that these techniques are the subject of continued research, and their improvement will parallel the development of next generation techniques described by the other speakers. Next generation assimilation techniques are those that are under development but are not yet used operationally. Most of these procedures are derived from control theory or variational methods and primarily represent continuous assimilation approaches, in which the data and model dynamics are 'fitted' to each other in an optimal way. Another 'next generation' category is the initialization of convective-scale models. Intermittent assimilation systems use an objective analysis to combine all observations within a time window that is centered on the analysis time. Continuous first-generation assimilation systems are usually based on the Newtonian-relaxation or 'nudging' techniques. Physical initialization procedures generally involve the use of standard or nonstandard data to force some physical process in the model during an assimilation period. Under the topic of next-generation assimilation techniques, variational approaches are currently being actively developed. Variational approaches seek to minimize a cost or penalty function which measures a model's fit to observations, background fields and other imposed constraints. Alternatively, the Kalman filter technique, which is also under investigation as a data assimilation procedure for numerical weather prediction, can yield acceptable initial conditions for mesoscale models. The third kind of next-generation technique involves strategies to initialize convective scale (non-hydrostatic) models.

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

NASA Astrophysics Data System (ADS)

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 multivariate sea ice concentration observations to constrain the model's ice thickness, concentration, and parameters.

Light-Stimulated Bacterial Production and Amino Acid Assimilation by Cyanobacteria and Other Microbes in the North Atlantic Ocean▿

PubMed Central

Michelou, Vanessa K.; Cottrell, Matthew T.; Kirchman, David L.

2007-01-01

We examined the contribution of photoheterotrophic microbes—those capable of light-mediated assimilation of organic compounds—to bacterial production and amino acid assimilation along a transect from Florida to Iceland from 28 May to 9 July 2005. Bacterial production (leucine incorporation at a 20 nM final concentration) was on average 30% higher in light than in dark-incubated samples, but the effect varied greatly (3% to 60%). To further characterize this light effect, we examined the abundance of potential photoheterotrophs and measured their contribution to bacterial production and amino acid assimilation (0.5 nM addition) using flow cytometry. Prochlorococcus and Synechococcus were abundant in surface waters where light-dependent leucine incorporation was observed, whereas aerobic anoxygenic phototrophic bacteria were abundant but did not correlate with the light effect. The per-cell assimilation rates of Prochlorococcus and Synechococcus were comparable to or higher than those of other prokaryotes, especially in the light. Picoeukaryotes also took up leucine (20 nM) and other amino acids (0.5 nM), but rates normalized to biovolume were much lower than those of prokaryotes. Prochlorococcus was responsible for 80% of light-stimulated bacterial production and amino acid assimilation in surface waters south of the Azores, while Synechococcus accounted for on average 12% of total assimilation. However, nearly 40% of the light-stimulated leucine assimilation was not accounted for by these groups, suggesting that assimilation by other microbes is also affected by light. Our results clarify the contribution of cyanobacteria to photoheterotrophy and highlight the potential role of other photoheterotrophs in biomass production and dissolved-organic-matter assimilation. PMID:17630296

Mitochondrial Respiration Can Support NO(3) and NO(2) Reduction during Photosynthesis : Interactions between Photosynthesis, Respiration, and N Assimilation in the N-Limited Green Alga Selenastrum minutum.

PubMed

Weger, H G; Turpin, D H

1989-02-01

Mass spectrometric analysis shows that assimilation of inorganic nitrogen (NH(4) (+), NO(2) (-), NO(3) (-)) by N-limited cells of Selenastrum minutum (Naeg.) Collins results in a stimulation of tricarboxylic acid cycle (TCA cycle) CO(2) release in both the light and dark. In a previous study we have shown that TCA cycle reductant generated during NH(4) (+) assimilation is oxidized via the cytochrome electron transport chain, resulting in an increase in respiratory O(2) consumption during photosynthesis (HG Weger, DG Birch, IR Elrifi, DH Turpin [1988] Plant Physiol 86: 688-692). NO(3) (-) and NO(2) (-) assimilation resulted in a larger stimulation of TCA cycle CO(2) release than did NH(4) (+), but a much smaller stimulation of mitochondrial O(2) consumption. NH(4) (+) assimilation was the same in the light and dark and insensitive to DCMU, but was 82% inhibited by anaerobiosis in both the light and dark. NO(3) (-) and NO(2) (-) assimilation rates were maximal in the light, but assimilation could proceed at substantial rates in the light in the presence of DCMU and in the dark. Unlike NH(4) (+), NO(3) (-) and NO(2) (-) assimilation were relatively insensitive to anaerobiosis. These results indicated that operation of the mitochondrial electron transport chain was not required to maintain TCA cycle activity during NO(3) (-) and NO(2) (-) assimilation, suggesting an alternative sink for TCA cycle generated reductant. Evaluation of changes in gross O(2) consumption during NO(3) (-) and NO(2) (-) assimilation suggest that TCA cycle reductant was exported to the chloroplast during photosynthesis and used to support NO(3) (-) and NO(2) (-) reduction.

THE AGWA – KINEROS2 SUITE OF MODELING TOOLS

USDA-ARS?s Scientific Manuscript database

A suite of modeling tools ranging from the event-based KINEROS2 flash-flood forecasting tool to the continuous (K2-O2) KINEROS-OPUS biogeochemistry tool. The KINEROS2 flash flood forecasting tool is being tested with the National Weather Service (NEW) is described. Tne NWS version assimilates Dig...

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Chuang (POST) Fanglin Yang (VSDB) Perry Shafran (VERIFICATION) Ilya Rivin (HYCOM) David Behringer (MOM4 * Functional Equivalence test for MOM4p0 on GAEA - Dave Behringer * NCEP Gaea module - $NETCDF * Use a forum

Questionnaire of Executive Function for Dancers: An Ecological Approach

ERIC Educational Resources Information Center

Wong, Alina; Rodriguez, Mabel; Quevedo, Liliana; de Cossio, Lourdes Fernandez; Borges, Ariel; Reyes, Alicia; Corral, Roberto; Blanco, Florentino; Alvarez, Miguel

2012-01-01

There is a current debate about the ecological validity of executive function (EF) tests. Consistent with the verisimilitude approach, this research proposes the Ballet Executive Scale (BES), a self-rating questionnaire that assimilates idiosyncratic executive behaviors of classical dance community. The BES was administrated to 149 adolescents,…

Discrimination of Arabic Contrasts by American Learners

ERIC Educational Resources Information Center

Al Mahmoud, Mahmoud S.

2013-01-01

This article reports on second language perception of non-native contrasts. The study specifically tests the perceptual assimilation model (PAM) by examining American learners' ability to discriminate Arabic contrasts. Twenty two native American speakers enrolled in a university level Arabic language program took part in a forced choice AXB…

Insights into the Regulation of DMSP Synthesis in the Diatom Thalassiosira pseudonana through APR Activity, Proteomics and Gene Expression Analyses on Cells Acclimating to Changes in Salinity, Light and Nitrogen

PubMed Central

Kettles, Nicola Louise; Kopriva, Stanislav; Malin, Gill

2014-01-01

Despite the importance of dimethylsulphoniopropionate (DMSP) in the global sulphur cycle and climate regulation, the biological pathways underpinning its synthesis in marine phytoplankton remain poorly understood. The intracellular concentration of DMSP increases with increased salinity, increased light intensity and nitrogen starvation in the diatom Thalassiosira pseudonana. We used these conditions to investigate DMSP synthesis at the cellular level via analysis of enzyme activity, gene expression and proteome comparison. The activity of the key sulphur assimilatory enzyme, adenosine 5′-phosphosulphate reductase was not coordinated with increasing intracellular DMSP concentration. Under all three treatments coordination in the expression of sulphur assimilation genes was limited to increases in sulphite reductase transcripts. Similarly, proteomic 2D gel analysis only revealed an increase in phosphoenolpyruvate carboxylase following increases in DMSP concentration. Our findings suggest that increased sulphur assimilation might not be required for increased DMSP synthesis, instead the availability of carbon and nitrogen substrates may be important in the regulation of this pathway. This contrasts with the regulation of sulphur metabolism in higher plants, which generally involves up-regulation of several sulphur assimilatory enzymes. In T. pseudonana changes relating to sulphur metabolism were specific to the individual treatments and, given that little coordination was seen in transcript and protein responses across the three growth conditions, different patterns of regulation might be responsible for the increase in DMSP concentration seen under each treatment. PMID:24733415

Co-regulation of dark and light reactions in three biochemical subtypes of C(4) species.

PubMed

Kiirats, Olavi; Kramer, David M; Edwards, Gerald E

2010-08-01

Regulation of light harvesting in response to changes in light intensity, CO(2) and O(2) concentration was studied in C(4) species representing three different metabolic subtypes: Sorghum bicolor (NADP-malic enzyme), Amaranthus edulis (NAD-malic enzyme), and Panicum texanum (PEP-carboxykinase). Several photosynthetic parameters were measured on the intact leaf level including CO(2) assimilation rates, O(2) evolution, photosystem II activities, thylakoid proton circuit and dissipation of excitation energy. Gross rates of O(2) evolution (J(O)₂'), measured by analysis of chlorophyll fluorescence), net rates of O(2) evolution and CO(2) assimilation responded in parallel to changes in light and CO(2) levels. The C(4) subtypes had similar energy requirements for photosynthesis since there were no significant differences in maximal quantum efficiencies for gross rates of O(2) evolution (average value = 0.072 O(2)/quanta absorbed, approximately 14 quanta per O(2) evolved). At saturating actinic light intensities, when photosynthesis was suppressed by decreasing CO(2), ATP synthase proton conductivity (g (H) (+)) responded strongly to changes in electron flow, decreasing linearly with J(O)₂', which was previously observed in C(3) plants. It is proposed that g (H) (+) is controlled at the substrate level by inorganic phosphate availability. The results suggest development of nonphotochemical quenching in C(4) plants is controlled by a decrease in g (H) (+), which causes an increase in proton motive force by restricting proton efflux from the lumen, rather than by cyclic or pseudocyclic electron flow.

A combined cell based approach to identify P-glycoprotein substrates and inhibitors in a single assay.

PubMed

Balimane, Praveen V; Chong, Saeho

2005-09-14

The objective of this project was to develop a cell based in vitro experimental procedure that can differentiate P-glycoprotein (P-gp) substrates from inhibitors in a single assay. Caco-2 cells grown to confluency on 12-well Transwell were used for this study. The efflux permeability (B to A) of P-gp specific probe (viz., digoxin) in the presence of test compounds (e.g. substrates, inhibitors and non-substrates of P-gp) was monitored, and the influx permeability (A to B) of test compounds was evaluated after complete P-gp blockade. Radiolabelled digoxin was added on the basolateral side with buffer on the apical side. The digoxin concentration appearing on the apical side represents digoxin efflux permeability during the control phase (0-1 h period). After 1 h, a test compound (10 microM) was added on the apical side. The reduced efflux permeability of digoxin suggests that the added test compound is an inhibitor. The influx permeability of test compound is also determined during the 1-2 h study period by measuring the concentration of the test compound in the basolateral side. At the end of 2 h, a potent P-gp inhibitor (GF120918) was added. The increased influx permeability of test compound during the 2-3 h incubation period indicates that the added test compound is a substrate. Samples were taken from both sides at the end of 1-3 h and the concentrations of the test compounds and digoxin were quantitated. Digoxin efflux permeability remained unchanged when incubated with P-gp substrates (e.g., etoposide, rhodamine123, taxol). However, when a P-gp inhibitor was added to the apical side, the digoxin efflux (B to A permeability) was significantly reduced (ketoconazole=51% reduction) as expected. The influx permeability of substrates increased significantly (rhodamine123=70%, taxol=220%, digoxin=290%) after the P-gp inhibitor (GF120918) was introduced, whereas the influx permeability of P-gp inhibitor and non-substrates was not affected by GF120918. Thus, this combined assay provides an efficient cell based in vitro screening tool to simultaneously distinguish compounds that are P-gp substrates from P-gp inhibitors.

User's Guide - WRF Lightning Assimilation

EPA Pesticide Factsheets

This document describes how to run WRF with the lightning assimilation technique described in Heath et al. (2016). The assimilation method uses gridded lightning data to trigger and suppress sub-grid deep convection in Kain-Fritsch.

Sampling, feasibility, and priors in data assimilation

DOE PAGES

Tu, Xuemin; Morzfeld, Matthias; Miller, Robert N.; ...

2016-03-01

Importance sampling algorithms are discussed in detail, with an emphasis on implicit sampling, and applied to data assimilation via particle filters. Implicit sampling makes it possible to use the data to find high-probability samples at relatively low cost, making the assimilation more efficient. A new analysis of the feasibility of data assimilation is presented, showing in detail why feasibility depends on the Frobenius norm of the covariance matrix of the noise and not on the number of variables. A discussion of the convergence of particular particle filters follows. A major open problem in numerical data assimilation is the determination ofmore » appropriate priors, a progress report on recent work on this problem is given. The analysis highlights the need for a careful attention both to the data and to the physics in data assimilation problems.« less

An OSSE Study for Deep Argo Array using the GFDL Ensemble Coupled Data Assimilation System

NASA Astrophysics Data System (ADS)

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.

Added Value of Assimilating Himawari-8 AHI Water Vapor Radiances on Analyses and Forecasts for "7.19" Severe Storm Over North China

NASA Astrophysics Data System (ADS)

Wang, Yuanbing; Liu, Zhiquan; Yang, Sen; Min, Jinzhong; Chen, Liqiang; Chen, Yaodeng; Zhang, Tao

2018-04-01

Himawari-8 is the first launched and operational new-generation geostationary meteorological satellite. The Advanced Himawari Imager (AHI) on board Himawari-8 provides continuous high-resolution observations of severe weather phenomena in space and time. In this study, the capability to assimilate AHI radiances has been developed within the Weather Research and Forecasting (WRF) model's data assimilation system. As the first attempt to assimilate AHI using WRF data assimilation at convective scales, the added value of hourly AHI clear-sky radiances from three water vapor channels on convection-permitting (3 km) analyses and forecasts of the "7.19" severe rainstorm that occurred over north China during 18-21 July 2016 was investigated. Analyses were produced hourly, and 24 h forecasts were produced every 6 h. The results showed that improved wind and humidity fields were obtained in analyses and forecasts verified against conventional observations after assimilating AHI water vapor radiances when compared to the control experiment which assimilated only conventional observations. It was also found that the assimilation of AHI water vapor radiances had a clearly positive impact on the rainfall forecast for the first 6 h lead time, especially for heavy rainfall exceeding 100 mm when verified against the observed rainfall. Furthermore, the horizontal and vertical distribution of features in the moisture fields were improved after assimilating AHI water vapor radiances, eventually contributing to a better forecast of the severe rainstorm.

Evaluation of radar and automatic weather station data assimilation for a heavy rainfall event in southern China

NASA Astrophysics Data System (ADS)

Hou, Tuanjie; Kong, Fanyou; Chen, Xunlai; Lei, Hengchi; Hu, Zhaoxia

2015-07-01

To improve the accuracy of short-term (0-12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System (HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting (WRF-ARW) model and the Advanced Regional Prediction System (ARPS) three-dimensional variational data assimilation (3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station (AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting (QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to 9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6-9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score (FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction.

Understanding the influence of assimilating satellite-derived observations on mesoscale analyses and forecasts of tropical cyclone track and structure

NASA Astrophysics Data System (ADS)

Wu, Ting-Chi

This dissertation research explores the influence of assimilating satellite-derived observations on mesoscale numerical analyses and forecasts of tropical cyclones (TC). The ultimate goal is to provide more accurate mesoscale analyses of TC and its surrounding environment for superior TC track and intensity forecasts. High spatial and temporal resolution satellite-derived observations are prepared for two TC cases, Typhoon Sinlaku and Hurricane Ike (both 2008). The Advanced Research version of the Weather and Research Forecasting Model (ARW-WRF) is employed and data is assimilated using the Ensemble Adjustment Kalman Filter (EAKF) implemented in the Data Assimilation Research Testbed. In the first part of this research, the influence of assimilating enhanced atmospheric motion vectors (AMVs) derived from geostationary satellites is examined by comparing three parallel WRF/EnKF experiments. The control experiment assimilates the same AMV dataset assimilated in NCEP operational analysis along with conventional observations from radiosondes, aircraft, and advisory TC position data. During Sinlaku and Ike, the Cooperative Institute for Meteorological Satellite Studies (CIMSS) generates hourly AMVs along with Rapid-Scan (RS) AMVs when the satellite RS mode is activated. With an order of magnitude more AMV data assimilated, the assimilation of hourly CIMSS AMV dataset exhibit superior initial TC position, intensity and structure estimates to the control analyses and the subsequent short-range forecasts. When RS AMVs are processed and assimilated, the addition of RS AMVs offers additional modification to the TC and its environment and leads to Sinlaku's recurvature toward Japan, albeit prematurely. The results demonstrate the promise of assimilating enhanced AMV data into regional TC models. The second part of this research continues the work in the first part and further explores the influence of assimilating enhanced AMV datasets by conducting parallel data-denial WRF/EnKF experiments that assimilate AMVs subsetted horizontally by their distances to the TC center (interior and exterior) and vertically by their assigned heights (upper, middle, and lower layers). For both Sinlaku and Ike, it is found: 1) interior AMVs are important for accurate TC intensity, 2) excluding upper-layer AMVs generally results in larger track errors and ensemble spread, 3) exclusion of interior AMVs has the largest impact on the forecast of TC size than exclusively removing AMVs in particular tropospheric layers, 4) the largest ensemble spreads are found in track, intensity, and size forecasts when interior and upper-layer AMVs are not included, 5) withholding the middle-layer AMVs can improve the track forecasts. Findings from this study could influence future scenarios that involve the targeted acquisition and assimilation of high-density AMV observations in TC events. The last part of the research focuses on the assimilation of hyperspectral temperature and moisture soundings and microwave based vertically-integrated total precipitable water (TPW) products derived from polar-orbiting satellites. A comparison is made between the assimilation of soundings retrieved from the combined use of Advanced Microwave Scanning Radiometer and Atmospheric Infrared Sounder (AMSU-AIRS) and sounding products provided by CIMSS (CIMSS-AIRS). AMSU-AIRS soundings provide broad spatial coverage albeit coarse resolution, whilst CIMSS-AIRS is geared towards mesoscale applications and thus provide higher spatial resolution but restricted coverage due to the use of radiance in clear sky. The assimilation of bias-corrected CIMSS-AIRS soundings provides slightly more accurate TC structure than the control case. The assimilation of AMSU-AIRS improves the track forecasts but produces weaker and smaller storm. Preliminary results of assimilating TPW product derived from the Advanced Microwave Scanning Radiometer-EOS indicate improved TC structure over the control case. However, the short-range forecasts exhibit the largest TC track errors. In all, this study demonstrates the influence of assimilating high-resolution satellite data on mesoscale analyses and forecasts of TC track and structure. The results suggest the inclusion and assimilation of observations with high temporal resolution, broad spatial coverage, and greater proximity to TCs does indeed improve TC track and structure forecasts. Such findings are beneficial for future decisions on data collecting and retrievals that are essential for TC forecasts.

SOFI/Substrate integrity testing for cryogenic propellant tanks at extreme thermal gradient conditions

NASA Astrophysics Data System (ADS)

Haynes, M.; Fabian, P.

2015-12-01

Liquid propellant tank insulation for space flight requires low weight as well as high insulation factors. Use of Spray-On Foam Insulation (SOFI) is an accepted, cost effective technique for insulating a single wall cryogenic propellant tank and has been used extensively throughout the aerospace industry. Determining the bond integrity of the SOFI to the metallic substrate as well as its ability to withstand the in-service strains, both mechanical and thermal, is critical to the longevity of the insulation. This determination has previously been performed using highly volatile, explosive cryogens, which increases the test costs enormously, as well as greatly increasing the risk to both equipment and personnel. CTD has developed a new test system, based on a previous NASA test that simulates the mechanical and thermal strains associated with filling a large fuel tank with a cryogen. The test enables a relatively small SOFI/substrate sample to be monitored for any deformations, delaminations, or disjunctures during the cooling and mechanical straining process of the substrate, and enables the concurrent application of thermal and physical strains to two specimens at the same time. The thermal strains are applied by cooling the substrate to the desired cryogen temperature (from 4 K to 250 K) while maintaining the outside surface of the SOFI foam at ambient conditions. Multiple temperature monitoring points are exercised to ensure even cooling across the substrate, while at the same time, surface temperatures of the SOFI can be monitored to determine the heat flow. The system also allows for direct measurement of the strains in the substrate during the test. The test system as well as test data from testing at 20 K, for liquid Hydrogen simulation, will be discussed.

Processing of phonological variation in children with hearing loss: compensation for English place assimilation in connected speech.

PubMed

Skoruppa, Katrin; Rosen, Stuart

2014-06-01

In this study, the authors explored phonological processing in connected speech in children with hearing loss. Specifically, the authors investigated these children's sensitivity to English place assimilation, by which alveolar consonants like t and n can adapt to following sounds (e.g., the word ten can be realized as tem in the phrase ten pounds). Twenty-seven 4- to 8-year-old children with moderate to profound hearing impairments, using hearing aids (n = 10) or cochlear implants (n = 17), and 19 children with normal hearing participated. They were asked to choose between pictures of familiar (e.g., pen) and unfamiliar objects (e.g., astrolabe) after hearing t- and n-final words in sentences. Standard pronunciations (Can you find the pen dear?) and assimilated forms in correct (… pem please?) and incorrect contexts (… pem dear?) were presented. As expected, the children with normal hearing chose the familiar object more often for standard forms and correct assimilations than for incorrect assimilations. Thus, they are sensitive to word-final place changes and compensate for assimilation. However, the children with hearing impairment demonstrated reduced sensitivity to word-final place changes, and no compensation for assimilation. Restricted analyses revealed that children with hearing aids who showed good perceptual skills compensated for assimilation in plosives only.