Response to Comment on "A bacterium that degrades and assimilates poly(ethylene terephthalate)".

PubMed

Yoshida, Shosuke; Hiraga, Kazumi; Takehana, Toshihiko; Taniguchi, Ikuo; Yamaji, Hironao; Maeda, Yasuhito; Toyohara, Kiyotsuna; Miyamoto, Kenji; Kimura, Yoshiharu; Oda, Kohei

2016-08-19

Yang et al suggest that the use of low-crystallinity poly(ethylene terephthalate) (PET) exaggerates our results. However, the primary focus of our study was identifying an organism capable of the biological degradation and assimilation of PET, regardless of its crystallinity. We provide additional PET depolymerization data that further support several other lines of data showing PET assimilation by growing cells of Ideonella sakaiensis. Copyright © 2016, American Association for the Advancement of Science.

The Preferred Learning Styles of Neurosurgeons, Neurosurgery Residents, and Neurology Residents: Implications in the Neurosurgical Field.

PubMed

Lai, Hung-Yi; Lee, Ching-Yi; Chiu, Angela; Lee, Shih-Tseng

2014-01-01

To delineate the learning style that best defines a successful practitioner in the field of neurosurgery by using a validated learning style inventory. The Kolb Learning Style Inventory, a validated assessment tool, was administered to all practicing neurosurgeons, neurosurgical residents, and neurology residents employed at Chang Gung Memorial Hospital, an institution that provides primary and tertiary clinical care in 3 locations, Linkou, Kaohsiung, and Chiayi. There were 81 participants who entered the study, and all completed the study. Neurosurgeons preferred the assimilating learning style (52%), followed by the diverging learning style (39%). Neurosurgery residents were slightly more evenly distributed across the learning styles; however, they still favored assimilating (32%) and diverging (41%). Neurology residents had the most clearly defined preferred learning style with assimilating (76%) obtaining the large majority and diverging (12%) being a distant second. The assimilating and diverging learning styles are the preferred learning styles among neurosurgeons, neurosurgery residents, and neurology residents. The assimilating learning style typically is the primary learning style for neurosurgeons and neurology residents. Neurosurgical residents start off with a diverging learning style and progress toward an assimilating learning style as they work toward becoming practicing neurosurgeons. The field of neurosurgery has limited opportunities for active experimentation, which may explain why individuals who prefer reflective observation are more likely to succeed in this field. Copyright © 2014 Elsevier Inc. All rights reserved.

DATA ASSIMILATION APPROACH FOR FORECAST OF SOLAR ACTIVITY CYCLES

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

Kitiashvili, Irina N., E-mail: irina.n.kitiashvili@nasa.gov

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

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

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

Dodds, W. K.; Collins, S. M.; Hamilton, S. K.

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

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

DOE PAGES

Dodds, W. K.; Collins, S. M.; Hamilton, S. K.; ...

2014-10-01

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

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

Sea lamprey carcasses exert local and variable food web effects in a nutrient-limited Atlantic coastal stream

USGS Publications Warehouse

Weaver, Daniel M.; Coghlan, Stephen M.; Zydlewski, Joseph D.

2016-01-01

Resource flows from adjacent ecosystems are critical in maintaining structure and function of freshwater food webs. Migrating sea lamprey (Petromyzon marinus) deliver a pulsed marine-derived nutrient subsidy to rivers in spring when the metabolic demand of producers and consumers are increasing. However, the spatial and temporal dynamics of these nutrient subsidies are not well characterized. We used sea lamprey carcass additions in a small stream to examine changes in nutrients, primary productivity, and nutrient assimilation among consumers. Algal biomass increased 57%–71% immediately adjacent to carcasses; however, broader spatial changes from multiple-site carcass addition may have been influenced by canopy cover. We detected assimilation of nutrients (via δ13C and δ15N) among several macroinvertebrate families including Heptageniidae, Hydropsychidae, and Perlidae. Our research suggests that subsidies may evoke localized patch-scale effects on food webs, and the pathways of assimilation in streams are likely coupled to adjacent terrestrial systems. This research underscores the importance of connectivity in streams, which may influence sea lamprey spawning and elicit varying food web responses from carcass subsidies due to fine-scale habitat variables.

Molybdenum limitation of microbial nitrogen assimilation in aquatic ecosystems and pure cultures.

PubMed

Glass, Jennifer B; Axler, Richard P; Chandra, Sudeep; Goldman, Charles R

2012-01-01

Molybdenum (Mo) is an essential micronutrient for biological assimilation of nitrogen gas and nitrate because it is present in the cofactors of nitrogenase and nitrate reductase enzymes. Although Mo is the most abundant transition metal in seawater (107 nM), it is present in low concentrations in most freshwaters, typically <20 nM. In 1960, it was discovered that primary productivity was limited by Mo scarcity (2-4 nM) in Castle Lake, a small, meso-oligotrophic lake in northern California. Follow up studies demonstrated that Mo also limited primary productivity in lakes in New Zealand, Alaska, and the Sierra Nevada. Research in the 1970s and 1980s showed that Mo limited primary productivity and nitrate uptake in Castle Lake only during periods of the growing season when nitrate concentrations were relatively high because ammonium assimilation does not require Mo. In the years since, research has shifted to investigate whether Mo limitation also occurs in marine and soil environments. Here we review studies of Mo limitation of nitrogen assimilation in natural microbial communities and pure cultures. We also summarize new data showing that the simultaneous addition of Mo and nitrate causes increased activity of proteins involved in nitrogen assimilation in the hypolimnion of Castle Lake when ammonium is scarce. Furthermore, we suggest that meter-scale Mo and oxygen depth profiles from Castle Lake are consistent with the hypothesis that nitrogen-fixing cyanobacteria in freshwater periphyton communities have higher Mo requirements than other microbial communities. Finally, we present topics for future research related to Mo bioavailability through time and with changing oxidation state.

Molybdenum limitation of microbial nitrogen assimilation in aquatic ecosystems and pure cultures

PubMed Central

Glass, Jennifer B.; Axler, Richard P.; Chandra, Sudeep; Goldman, Charles R.

2012-01-01

Molybdenum (Mo) is an essential micronutrient for biological assimilation of nitrogen gas and nitrate because it is present in the cofactors of nitrogenase and nitrate reductase enzymes. Although Mo is the most abundant transition metal in seawater (107 nM), it is present in low concentrations in most freshwaters, typically <20 nM. In 1960, it was discovered that primary productivity was limited by Mo scarcity (2–4 nM) in Castle Lake, a small, meso-oligotrophic lake in northern California. Follow up studies demonstrated that Mo also limited primary productivity in lakes in New Zealand, Alaska, and the Sierra Nevada. Research in the 1970s and 1980s showed that Mo limited primary productivity and nitrate uptake in Castle Lake only during periods of the growing season when nitrate concentrations were relatively high because ammonium assimilation does not require Mo. In the years since, research has shifted to investigate whether Mo limitation also occurs in marine and soil environments. Here we review studies of Mo limitation of nitrogen assimilation in natural microbial communities and pure cultures. We also summarize new data showing that the simultaneous addition of Mo and nitrate causes increased activity of proteins involved in nitrogen assimilation in the hypolimnion of Castle Lake when ammonium is scarce. Furthermore, we suggest that meter-scale Mo and oxygen depth profiles from Castle Lake are consistent with the hypothesis that nitrogen-fixing cyanobacteria in freshwater periphyton communities have higher Mo requirements than other microbial communities. Finally, we present topics for future research related to Mo bioavailability through time and with changing oxidation state. PMID:22993512

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.

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.

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

S-nitrosothiols regulate nitric oxide production and storage in plants through the nitrogen assimilation pathway

PubMed Central

Frungillo, Lucas; Skelly, Michael J.; Loake, Gary J.; Spoel, Steven H.; Salgado, Ione

2014-01-01

Nitrogen assimilation plays a vital role in plant metabolism. Assimilation of nitrate, the primary source of nitrogen in soil, is linked to generation of the redox signal nitric oxide (NO). An important mechanism by which NO regulates plant development and stress responses is through S-nitrosylation, i.e. covalent attachment of NO to cysteines to form S-nitrosothiols (SNO). Despite the importance of nitrogen assimilation and NO signalling, it remains largely unknown how these pathways are interconnected. Here we show that SNO signalling suppresses both nitrate uptake and reduction by transporters and reductases, respectively, to fine-tune nitrate homeostasis. Moreover, NO derived from nitrate assimilation suppresses the redox enzyme S-nitrosoglutathione Reductase 1 (GSNOR1) by S-nitrosylation, preventing scavenging of S-nitrosoglutathione, a major cellular bio-reservoir of NO. Hence, our data demonstrates that (S)NO controls its own generation and scavenging by modulating nitrate assimilation and GSNOR1 activity. PMID:25384398

Further Exploring the Potential for Assimilation of Unmanned Aircraft Observations to Benefit Hurricane Analyses and Forecasts

NASA Technical Reports Server (NTRS)

Sippel, Jason A.; Zhang, Fuqing; Weng, Yonghui; Braun, Scott A.; Cecil, Daniel J.

2015-01-01

This study explores the potential of assimilating data from multiple instruments onboard high-altitude, long-endurance unmanned aircraft to improve hurricane analyses and forecasts. A recent study found a significant positive impact on analyses and forecasts of Hurricane Karl when an ensemble Kalman filter was used to assimilate data from the High-altitude Imaging Wind and Rain Airborne Profiler (HIWRAP), a new Doppler radar onboard the NASA Global Hawk (GH) unmanned airborne system. The GH can also carry other useful instruments, including dropsondes and the Hurricane Imaging Radiometer (HIRAD), which is a new radiometer that estimates large swaths of wind speeds and rainfall at the ocean surface. The primary finding is that simultaneously assimilating data from HIWRAP and the other GH-compatible instruments results in further analysis and forecast improvement for Karl. The greatest improvement comes when HIWRAP, HIRAD, and dropsonde data are simultaneously assimilated.

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.

A weakly-constrained data assimilation approach to address rainfall-runoff model structural inadequacy in streamflow prediction

NASA Astrophysics Data System (ADS)

Lee, Haksu; Seo, Dong-Jun; Noh, Seong Jin

2016-11-01

This paper presents a simple yet effective weakly-constrained (WC) data assimilation (DA) approach for hydrologic models which accounts for model structural inadequacies associated with rainfall-runoff transformation processes. Compared to the strongly-constrained (SC) DA, WC DA adjusts the control variables less while producing similarly or more accurate analysis. Hence the adjusted model states are dynamically more consistent with those of the base model. The inadequacy of a rainfall-runoff model was modeled as an additive error to runoff components prior to routing and penalized in the objective function. Two example modeling applications, distributed and lumped, were carried out to investigate the effects of the WC DA approach on DA results. For distributed modeling, the distributed Sacramento Soil Moisture Accounting (SAC-SMA) model was applied to the TIFM7 Basin in Missouri, USA. For lumped modeling, the lumped SAC-SMA model was applied to nineteen basins in Texas. In both cases, the variational DA (VAR) technique was used to assimilate discharge data at the basin outlet. For distributed SAC-SMA, spatially homogeneous error modeling yielded updated states that are spatially much more similar to the a priori states, as quantified by Earth Mover's Distance (EMD), than spatially heterogeneous error modeling by up to ∼10 times. DA experiments using both lumped and distributed SAC-SMA modeling indicated that assimilating outlet flow using the WC approach generally produce smaller mean absolute difference as well as higher correlation between the a priori and the updated states than the SC approach, while producing similar or smaller root mean square error of streamflow analysis and prediction. Large differences were found in both lumped and distributed modeling cases between the updated and the a priori lower zone tension and primary free water contents for both WC and SC approaches, indicating possible model structural deficiency in describing low flows or evapotranspiration processes for the catchments studied. Also presented are the findings from this study and key issues relevant to WC DA approaches using hydrologic models.

Application of the Auto-Tuned Land Assimilation System (ATLAS) to ASCAT and SMOS soil moisture retrieval products

USDA-ARS?s Scientific Manuscript database

Land data assimilations are typically based on highly uncertain assumptions regarding the statistical structure of observation and modeling errors. Left uncorrected, poor assumptions can degrade the quality of analysis products generated by land data assimilation systems. Recently, Crow and van de...

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.

Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

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).

A Hybrid Approach to Data Assimilation for Reconstructing the Evolution of Mantle Dynamics

NASA Astrophysics Data System (ADS)

Zhou, Quan; Liu, Lijun

2017-11-01

Quantifying past mantle dynamic processes represents a major challenge in understanding the temporal evolution of the solid earth. Mantle convection modeling with data assimilation is one of the most powerful tools to investigate the dynamics of plate subduction and mantle convection. Although various data assimilation methods, both forward and inverse, have been created, these methods all have limitations in their capabilities to represent the real earth. Pure forward models tend to miss important mantle structures due to the incorrect initial condition and thus may lead to incorrect mantle evolution. In contrast, pure tomography-based models cannot effectively resolve the fine slab structure and would fail to predict important subduction-zone dynamic processes. Here we propose a hybrid data assimilation approach that combines the unique power of the sequential and adjoint algorithms, which can properly capture the detailed evolution of the downgoing slab and the tomographically constrained mantle structures, respectively. We apply this new method to reconstructing mantle dynamics below the western U.S. while considering large lateral viscosity variations. By comparing this result with those from several existing data assimilation methods, we demonstrate that the hybrid modeling approach recovers the realistic 4-D mantle dynamics the best.

A Hybrid Forward-Adjoint Data Assimilation Method for Reconstructing the Temporal Evolution of Mantle Dynamics

NASA Astrophysics Data System (ADS)

Zhou, Q.; Liu, L.

2017-12-01

Quantifying past mantle dynamic processes represents a major challenge in understanding the temporal evolution of the solid earth. Mantle convection modeling with data assimilation is one of the most powerful tools to investigate the dynamics of plate subduction and mantle convection. Although various data assimilation methods, both forward and inverse, have been created, these methods all have limitations in their capabilities to represent the real earth. Pure forward models tend to miss important mantle structures due to the incorrect initial condition and thus may lead to incorrect mantle evolution. In contrast, pure tomography-based models cannot effectively resolve the fine slab structure and would fail to predict important subduction-zone dynamic processes. Here we propose a hybrid data assimilation method that combines the unique power of the sequential and adjoint algorithms, which can properly capture the detailed evolution of the downgoing slab and the tomographically constrained mantle structures, respectively. We apply this new method to reconstructing mantle dynamics below the western U.S. while considering large lateral viscosity variations. By comparing this result with those from several existing data assimilation methods, we demonstrate that the hybrid modeling approach recovers the realistic 4-D mantle dynamics to the best.

Use of transcriptomics and co-expression networks to analyze the interconnections between nitrogen assimilation and photorespiratory metabolism

PubMed Central

Pérez-Delgado, Carmen M.; Moyano, Tomás C.; García-Calderón, Margarita; Canales, Javier; Gutiérrez, Rodrigo A.; Márquez, Antonio J.; Betti, Marco

2016-01-01

Nitrogen is one of the most important nutrients for plants and, in natural soils, its availability is often a major limiting factor for plant growth. Here we examine the effect of different forms of nitrogen nutrition and of photorespiration on gene expression in the model legume Lotus japonicus with the aim of identifying regulatory candidate genes co-ordinating primary nitrogen assimilation and photorespiration. The transcriptomic changes produced by the use of different nitrogen sources in leaves of L. japonicus plants combined with the transcriptomic changes produced in the same tissue by different photorespiratory conditions were examined. The results obtained provide novel information on the possible role of plastidic glutamine synthetase in the response to different nitrogen sources and in the C/N balance of L. japonicus plants. The use of gene co-expression networks establishes a clear relationship between photorespiration and primary nitrogen assimilation and identifies possible transcription factors connected to the genes of both routes. PMID:27117340

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

Evaluation of Oceanic Surface Observation for Reproducing the Upper Ocean Structure in ECHAM5/MPI-OM

NASA Astrophysics Data System (ADS)

Luo, Hao; Zheng, Fei; Zhu, Jiang

2017-12-01

Better constraints of initial conditions from data assimilation are necessary for climate simulations and predictions, and they are particularly important for the ocean due to its long climate memory; as such, ocean data assimilation (ODA) is regarded as an effective tool for seasonal to decadal predictions. In this work, an ODA system is established for a coupled climate model (ECHAM5/MPI-OM), which can assimilate all available oceanic observations using an ensemble optimal interpolation approach. To validate and isolate the performance of different surface observations in reproducing air-sea climate variations in the model, a set of observing system simulation experiments (OSSEs) was performed over 150 model years. Generally, assimilating sea surface temperature, sea surface salinity, and sea surface height (SSH) can reasonably reproduce the climate variability and vertical structure of the upper ocean, and assimilating SSH achieves the best results compared to the true states. For the El Niño-Southern Oscillation (ENSO), assimilating different surface observations captures true aspects of ENSO well, but assimilating SSH can further enhance the accuracy of ENSO-related feedback processes in the coupled model, leading to a more reasonable ENSO evolution and air-sea interaction over the tropical Pacific. For ocean heat content, there are still limitations in reproducing the long time-scale variability in the North Atlantic, even if SSH has been taken into consideration. These results demonstrate the effectiveness of assimilating surface observations in capturing the interannual signal and, to some extent, the decadal signal but still highlight the necessity of assimilating profile data to reproduce specific decadal variability.

Japan's Colonial Policies--From National Assimilation to the Kominka Movement: A Comparative Study of Primary Education in Taiwan and Korea (1937-1945)

ERIC Educational Resources Information Center

Peng, Huan-Sheng; Chu, Jo-Ying

2017-01-01

The eight-year-long period from Japan's initiation of the Second Sino-Japanese War in 1937 to its unconditional surrender in 1945 forced Japan to invest its national economy and industrial and scientific technologies in the war. In addition, in the name of the Greater East Asia Co-Prosperity Sphere, Japan initiated its assimilation and Kominka…

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.

Leaf nitrogen assimilation and partitioning differ among subtropical forest plants in response to canopy addition of nitrogen treatments

Treesearch

Nan Liu; Shuhua Wu; Qinfeng Guo; Jiaxin Wang; Ce Cao; Jun Wang

2018-01-01

Global increases in nitrogen deposition may alter forest structure and function by interferingwith plant nitrogen metabolism (e.g., assimilation and partitioning) and subsequent carbon assimilation, but it is unclear how these responses to nitrogen deposition differ among species. In this study, we conducted a 2-year experiment to investigate the effects of canopy...

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.

Multi-site assimilation of a terrestrial biosphere model (BETHY) using satellite derived soil moisture data

NASA Astrophysics Data System (ADS)

Wu, Mousong; Sholze, Marko

2017-04-01

We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.

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.

Model Improvement by Assimilating Observations of Storm-Induced Coastal Change

NASA Astrophysics Data System (ADS)

Long, J. W.; Plant, N. G.; Sopkin, K.

2010-12-01

Discrete, large scale, meteorological events such as hurricanes can cause wide-spread destruction of coastal islands, habitats, and infrastructure. The effects can vary significantly along the coast depending on the configuration of the coastline, variable dune elevations, changes in geomorphology (sandy beach vs. marshland), and alongshore variations in storm hydrodynamic forcing. There are two primary methods of determining the changing state of a coastal system. Process-based numerical models provide highly resolved (in space and time) representations of the dominant dynamics in a physical system but must employ certain parameterizations due to computational limitations. The predictive capability may also suffer from the lack of reliable initial or boundary conditions. On the other hand, observations of coastal topography before and after the storm allow the direct quantification of cumulative storm impacts. Unfortunately these measurements suffer from instrument noise and a lack of necessary temporal resolution. This research focuses on the combination of these two pieces of information to make more reliable forecasts of storm-induced coastal change. Of primary importance is the development of a data assimilation strategy that is efficient, applicable for use with highly nonlinear models, and able to quantify the remaining forecast uncertainty based on the reliability of each individual piece of information used in the assimilation process. We concentrate on an event time-scale and estimate/update unobserved model information (boundary conditions, free parameters, etc.) by assimilating direct observations of coastal change with those simulated by the model. The data assimilation can help estimate spatially varying quantities (e.g. friction coefficients) that are often modeled as homogeneous and identify processes inadequately characterized in the model.

Mycobacterium tuberculosis nitrogen assimilation and host colonization require aspartate

PubMed Central

Gouzy, Alexandre; Larrouy-Maumus, Gérald; Wu, Ting-Di; Peixoto, Antonio; Levillain, Florence; Lugo-Villarino, Geanncarlo; Gerquin-Kern, Jean-Luc; de Carvalho, Luiz Pedro Sório; Poquet, Yannick; Neyrolles, Olivier

2013-01-01

Here we identify the amino acid transporter AnsP1 as the unique aspartate importer in the human pathogen Mycobacterium tuberculosis. Metabolomic analysis of a mutant inactivated in AnsP1 revealed the transporter is essential for M. tuberculosis to assimilate nitrogen from aspartate. Virulence of the AnsP1 mutant is impaired in vivo, revealing aspartate is a primary nitrogen source required for host colonization by the tuberculosis bacillus. PMID:24077180

Light Regimes Shape Utilization of Extracellular Organic C and N in a Cyanobacterial Biofilm

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

Stuart, Rhona K.; Mayali, Xavier; Boaro, Amy A.

2016-06-28

Although it is becoming clear that many microbial primary producers can also play a role as organic consumers, we know very little about the metabolic regulation of photoautotroph organic matter consumption. Cyanobacteria in phototrophic biofilms can reuse extracellular organic carbon, but the metabolic drivers of extracellular processes are surprisingly complex. We investigated the metabolic foundations of organic matter reuse by comparing exoproteome composition and incorporation of 13C-labeled and 15N-labeled cyanobacterial extracellular organic matter (EOM) in a unicyanobacterial biofilm incubated using different light regimes. In the light and the dark, cyanobacterial direct organic C assimilation accounted for 32% and 43%, respectively,more » of all organic C assimilation in the community. Under photosynthesis conditions, we measured increased excretion of extracellular polymeric substances (EPS) and proteins involved in micronutrient transport, suggesting that requirements for micronutrients may drive EOM assimilation during daylight hours. This interpretation was supported by photosynthesis inhibition experiments, in which cyanobacteria incorporated N-rich EOM-derived material. In contrast, under dark, C-starved conditions, cyanobacteria incorporated C-rich EOM-derived organic matter, decreased excretion of EPS, and showed an increased abundance of degradative exoproteins, demonstrating the use of the extracellular domain for C storage. Sequence-structure modeling of one of these exoproteins predicted a specific hydrolytic activity that was subsequently detected, confirming increased EOM degradation in the dark. Associated heterotrophic bacteria increased in abundance and upregulated transport proteins under dark relative to light conditions. Taken together, our results indicate that biofilm cyanobacteria are successful competitors for organic C and N and that cyanobacterial nutrient and energy requirements control the use of EOM. IMPORTANCECyanobacteria are globally distributed primary producers, and the fate of their fixed C influences microbial biogeochemical cycling. This fate is complicated by cyanobacterial degradation and assimilation of organic matter, but because cyanobacteria are assumed to be poor competitors for organic matter consumption, regulation of this process is not well tested. In mats and biofilms, this is especially relevant because cyanobacteria produce an extensive organic extracellular matrix, providing the community with a rich source of nutrients. Light is a well-known regulator of cyanobacterial metabolism, so we characterized the effects of light availability on the incorporation of organic matter. Using stable isotope tracing at the single-cell level, we quantified photoautotroph assimilation under different metabolic conditions and integrated the results with proteomics to elucidate metabolic status. We found that cyanobacteria effectively compete for organic matter in the light and the dark and that nutrient requirements and community interactions contribute to cycling of extracellular organic matter.« less

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

PubMed Central

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

2018-01-01

Nitrogen (N) is one of the most important nutrients for plants and nitric oxide (NO) as a signaling plant growth regulator involved in nitrogen assimilation. Understanding the influence of exogenous NO on nitrogen metabolism at the gene expression and enzyme activity levels under different sources of nitrogen is vitally important for increasing nitrogen use efficiency (NUE). This study investigated the expression of key genes and enzymes in relation to nitrogen assimilation in two Australian wheat cultivars, a popular high NUE cv. Spitfire and a normal NUE cv. Westonia, under different combinations of nitrogen and sodium nitroprusside (SNP) as the NO donor. Application of NO increased the gene expressions and activities of nitrogen assimilation pathway enzymes in both cultivars at low levels of nitrogen. At high nitrogen supplies, the expressions and activities of N assimilation genes increased in response to exogenous NO only in cv. Spitfire but not in cv. Westonia. Exogenous NO caused an increase in leaf NO content at low N supplies in both cultivars, while under high nitrogen treatments, cv. Spitfire showed an increase under ammonium nitrate (NH4NO3) treatment but cv. Westonia was not affected. N assimilation gene expression and enzyme activity showed a clear relationship between exogenous NO, N concentration and N forms in primary plant nitrogen assimilation. Results reveal the possible role of NO and different nitrogen sources on nitrogen assimilation in Triticum aestivum plants. PMID:29320529

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

PubMed

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

2018-01-01

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

Habitat connectivity and ecosystem productivity: implications from a simple model.

USGS Publications Warehouse

Cloern, J.E.

2007-01-01

The import of resources (food, nutrients) sustains biological production and food webs in resource-limited habitats. Resource export from donor habitats subsidizes production in recipient habitats, but the ecosystem-scale consequences of resource translocation are generally unknown. Here, I use a nutrient-phytoplankton-zooplankton model to show how dispersive connectivity between a shallow autotrophic habitat and a deep heterotrophic pelagic habitat can amplify overall system production in metazoan food webs. This result derives from the finite capacity of suspension feeders to capture and assimilate food particles: excess primary production in closed autotrophic habitats cannot be assimilated by consumers; however, if excess phytoplankton production is exported to food-limited heterotrophic habitats, it can be assimilated by zooplankton to support additional secondary production. Transport of regenerated nutrients from heterotrophic to autotrophic habitats sustains higher system primary production. These simulation results imply that the ecosystem-scale efficiency of nutrient transformation into metazoan biomass can be constrained by the rate of resource exchange across habitats and that it is optimized when the transport rate matches the growth rate of primary producers. Slower transport (i.e., reduced connectivity) leads to nutrient limitation of primary production in autotrophic habitats and food limitation of secondary production in heterotrophic habitats. Habitat fragmentation can therefore impose energetic constraints on the carrying capacity of aquatic ecosystems. The outcomes of ecosystem restoration through habitat creation will be determined by both functions provided by newly created aquatic habitats and the rates of hydraulic connectivity between them.

Technical Report Series on Global Modeling and Data Assimilation. Volume 7: Proceedings of the Workshop on the GEOS-1 Five-year Assimilation

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Schubert, Siegfried; Rood, Richard

1995-01-01

The primary objective of the three-day workshop on results from the Data Assimilation Office (DAO) five-year assimilation was to provide timely feedback from the data users concerning the strengths and weaknesses of version 1 of the Goddard Earth Observing System (GEOS-1) assimilated products. A second objective was to assess user satisfaction with the current methods of data access and retrieval. There were a total of 49 presentations, with about half (23) of the presentations from scientists from outside of Goddard. The first two days were devoted to applications of data: studies of the energy diagnostics, precipitation and diabatic heating, hydrological modeling and moisture transport, cloud forcing and validation, various aspects of intraseasonal, seasonal, and interannual variability, ocean wind stress applications, and validation of surface fluxes. The last day included talks from the National Meteorological Center (NMC), the National Center for Atmospheric Research (NCAR), the Center for Ocean-Land-Atmosphere Studies (COLA), the United States Navy, and the European Center for Medium Range Weather Forecasts (ECMWF).

Factors affecting the estimate of primary production from space

NASA Technical Reports Server (NTRS)

Balch, W. M.; Byrne, C. F.

1994-01-01

Remote sensing of primary production in the euphotic zone has been based mostly on visible-band and water-leaving radiance measured with the coastal zone color scanner. There are some robust, simple relationships for calculating integral production based on surface measurements, but they also require knowledge for photoadaptive parameters such as maximum photosynthesis which currently cannot be obtained from spave. A 17,000-station data set is used to show that space-based estimates of maximum photosynthesis could improve predictions of psi, the water column light utiliztion index, which is an important term in many primary productivity models. Temperature is also examined as a factor for predicting hydrographic structure and primary production. A simple model is used to relate temperature and maximum photosynthesis; the model incorporates (1) the positive relationship between maximum photosynthesis and temperature and (2) the strongly negative relationship between temperature and nitrate in the ocean (which directly affects maximum growth rates via nitrogen limitation). Since these two factors relate to carbon and nitrogen, 'balanced carbon/nitrogen assimilation' was calculated using the Redfield ratio, It is expected that the relationship between maximum balanced carbon assimilation versus temperature is concave-down, with the peak dependent on nitrate uptake kinetics, temperature-nitrate relationships,a nd the carbon chlorophyll ration. These predictions were compared with the sea truth data. The minimum turnover time for nitrate was also calculated using this approach. Lastly, sea surface temperature gradients were used to predict the slope of isotherms (a proxy for the slope of isopycnals in many waters). Sea truth data show that at size scales of several hundred kilometers, surface temperature gradients can provide information on the slope of isotherms in the top 200 m of the water column. This is directly relevant to the supply of nutrients into the surface mixed layer, which is useful for predicting integral biomass and primary production.

Improving Global Reanalyses and Short Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; deSilva, Arlindo M.

2000-01-01

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a "1+1"D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the "1+1"D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+lD scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSM/I rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Improving Global Reanalyses and Short-Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

NASA Technical Reports Server (NTRS)

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

1999-01-01

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a 1+1D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the 1+1D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSW rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Articulatory mediation of speech perception: a causal analysis of multi-modal imaging data.

PubMed

Gow, David W; Segawa, Jennifer A

2009-02-01

The inherent confound between the organization of articulation and the acoustic-phonetic structure of the speech signal makes it exceptionally difficult to evaluate the competing claims of motor and acoustic-phonetic accounts of how listeners recognize coarticulated speech. Here we use Granger causation analyzes of high spatiotemporal resolution neural activation data derived from the integration of magnetic resonance imaging, magnetoencephalography and electroencephalography, to examine the role of lexical and articulatory mediation in listeners' ability to use phonetic context to compensate for place assimilation. Listeners heard two-word phrases such as pen pad and then saw two pictures, from which they had to select the one that depicted the phrase. Assimilation, lexical competitor environment and the phonological validity of assimilation context were all manipulated. Behavioral data showed an effect of context on the interpretation of assimilated segments. Analysis of 40 Hz gamma phase locking patterns identified a large distributed neural network including 16 distinct regions of interest (ROIs) spanning portions of both hemispheres in the first 200 ms of post-assimilation context. Granger analyzes of individual conditions showed differing patterns of causal interaction between ROIs during this interval, with hypothesized lexical and articulatory structures and pathways driving phonetic activation in the posterior superior temporal gyrus in assimilation conditions, but not in phonetically unambiguous conditions. These results lend strong support for the motor theory of speech perception, and clarify the role of lexical mediation in the phonetic processing of assimilated speech.

Update on the NASA GEOS-5 Aerosol Forecasting and Data Assimilation System

NASA Technical Reports Server (NTRS)

Colarco, Peter; da Silva, Arlindo; Aquila, Valentina; Bian, Huisheng; Buchard, Virginie; Castellanos, Patricia; Darmenov, Anton; Follette-Cook, Melanie; Govindaraju, Ravi; Keller, Christoph;

Carbonate-derived CO 2 purging magma at depth: Influence on the eruptive activity of Somma-Vesuvius, Italy

NASA Astrophysics Data System (ADS)

Dallai, Luigi; Cioni, Raffaello; Boschi, Chiara; D'Oriano, Claudia

2011-10-01

Mafic phenocrysts from selected products of the last 4 ka volcanic activity at Mt. Vesuvius were investigated for their chemical and O-isotope composition, as a proxy for primary magmas feeding the system. 18O/ 16O ratios of studied Mg-rich olivines suggest that near-primary shoshonitic to tephritic melts experienced a flux of sedimentary carbonate-derived CO 2, representing the early process of magma contamination in the roots of the volcanic structure. Bulk carbonate assimilation (physical digestion) mainly occurred in the shallow crust, strongly influencing magma chamber evolution. On a petrological and geochemical basis the effects of bulk sedimentary carbonate digestion on the chemical composition of the near-primary melts are resolved from those of carbonate-released CO 2 fluxed into magma. An important outcome of this process lies in the effect of external CO 2 in changing the overall volatile solubility of the magma, enhancing the ability of Vesuvius mafic magmas to rapidly rise and explosively erupt at the surface.

Improving Assimilated Global Data Sets using TMI Rainfall and Columnar Moisture Observations

NASA Technical Reports Server (NTRS)

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

1999-01-01

A global analysis that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data products contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. In this study, we show that assimilating precipitation and total precipitable water (TPW) retrievals derived from the TRMM Microwave Imager (TMI) improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the large-scale circulation produced by the Goddard Earth Observing System (GEOS) data assimilation system (DAS). In particular, assimilating TMI rain improves clouds and radiation in areas of active convection, as well as the latent heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW retrievals leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. The improved analysis also improves short-range forecasts in the tropics. Ensemble forecasts initialized with the GEOS analysis incorporating TMI rain rates and TPW yield smaller biases in tropical precipitation forecasts beyond 1 day and better 500 hPa geopotential height forecasts up to 5 days. Results of this study demonstrate the potential of using high-quality space-borne rainfall and moisture observations to improve the quality of assimilated global data for climate analysis and weather forecasting applications

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.

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.

Patterns and Variability in Global Ocean Chlorophyll: Satellite Observations and Modeling

NASA Technical Reports Server (NTRS)

Gregg, Watson

2004-01-01

Recent analyses of SeaWiFS data have shown that global ocean chlorophyll has increased more than 4% since 1998. The North Pacific ocean basin has increased nearly 19%. These trend analyses follow earlier results showing decadal declines in global ocean chlorophyll and primary production. To understand the causes of these changes and trends we have applied the newly developed NASA Ocean Biogeochemical Assimilation Model (OBAM), which is driven in mechanistic fashion by surface winds, sea surface temperature, atmospheric iron deposition, sea ice, and surface irradiance. The model utilizes chlorophyll from SeaWiFS in a daily assimilation. The model has in place many of the climatic variables that can be expected to produce the changes observed in SeaWiFS data. This enables us to diagnose the model performance, the assimilation performance, and possible causes for the increase in chlorophyll. A full discussion of the changes and trends, possible causes, modeling approaches, and data assimilation will be the focus of the seminar.

Physical attractiveness, issue agreement, and assimilation effects in candidate appraisal.

PubMed

Schubert, James N; Curran, Margaret Ann; Strungaru, Carmen

2011-01-01

This study examines the cognitive and affective factors of candidate appraisal by manipulating candidate attractiveness and levels of issue agreement with voters. Drawing upon research in evolutionary psychology and cognitive neuroscience, this analysis proposes that automatic processing of physical appearance predisposes affective disposition toward more attractive candidates, thereby influencing cognitive processing of issue information. An experimental design presented attractive and unattractive candidates who were either liberal or conservative in a mock primary election. The data show strong partial effects for appearance on vote intention, an interaction between appearance and issue agreement, and a tendency for voters to assimilate the dissimilar views of attractive candidates. We argue that physical appearance is important in primary elections when the differences in issue positions and ideology between candidates is small.

Interacting Effects of Light and Iron Availability on the Coupling of Photosynthetic Electron Transport and CO2-Assimilation in Marine Phytoplankton

PubMed Central

Schuback, Nina; Schallenberg, Christina; Duckham, Carolyn; Maldonado, Maria T.; Tortell, Philippe D.

2015-01-01

Iron availability directly affects photosynthesis and limits phytoplankton growth over vast oceanic regions. For this reason, the availability of iron is a crucial variable to consider in the development of active chlorophyll a fluorescence based estimates of phytoplankton primary productivity. These bio-optical approaches require a conversion factor to derive ecologically-relevant rates of CO2-assimilation from estimates of electron transport in photosystem II. The required conversion factor varies significantly across phytoplankton taxa and environmental conditions, but little information is available on its response to iron limitation. In this study, we examine the role of iron limitation, and the interacting effects of iron and light availability, on the coupling of photosynthetic electron transport and CO2-assimilation in marine phytoplankton. Our results show that excess irradiance causes increased decoupling of carbon fixation and electron transport, particularly under iron limiting conditions. We observed that reaction center II specific rates of electron transport (ETRRCII, mol e- mol RCII-1 s-1) increased under iron limitation, and we propose a simple conceptual model for this observation. We also observed a strong correlation between the derived conversion factor and the expression of non-photochemical quenching. Utilizing a dataset from in situ phytoplankton assemblages across a coastal – oceanic transect in the Northeast subarctic Pacific, this relationship was used to predict ETRRCII: CO2-assimilation conversion factors and carbon-based primary productivity from FRRF data, without the need for any additional measurements. PMID:26171963

Interacting Effects of Light and Iron Availability on the Coupling of Photosynthetic Electron Transport and CO2-Assimilation in Marine Phytoplankton.

PubMed

Schuback, Nina; Schallenberg, Christina; Duckham, Carolyn; Maldonado, Maria T; Tortell, Philippe D

2015-01-01

Iron availability directly affects photosynthesis and limits phytoplankton growth over vast oceanic regions. For this reason, the availability of iron is a crucial variable to consider in the development of active chlorophyll a fluorescence based estimates of phytoplankton primary productivity. These bio-optical approaches require a conversion factor to derive ecologically-relevant rates of CO2-assimilation from estimates of electron transport in photosystem II. The required conversion factor varies significantly across phytoplankton taxa and environmental conditions, but little information is available on its response to iron limitation. In this study, we examine the role of iron limitation, and the interacting effects of iron and light availability, on the coupling of photosynthetic electron transport and CO2-assimilation in marine phytoplankton. Our results show that excess irradiance causes increased decoupling of carbon fixation and electron transport, particularly under iron limiting conditions. We observed that reaction center II specific rates of electron transport (ETR(RCII), mol e- mol RCII(-1) s(-1)) increased under iron limitation, and we propose a simple conceptual model for this observation. We also observed a strong correlation between the derived conversion factor and the expression of non-photochemical quenching. Utilizing a dataset from in situ phytoplankton assemblages across a coastal--oceanic transect in the Northeast subarctic Pacific, this relationship was used to predict ETR(RCII): CO2-assimilation conversion factors and carbon-based primary productivity from FRRF data, without the need for any additional measurements.

Diagnostics of sources of tropospheric ozone using data assimilation during the KORUS-AQ campaign

NASA Astrophysics Data System (ADS)

Gaubert, B.; Emmons, L. K.; Miyazaki, K.; Buchholz, R. R.; Tang, W.; Arellano, A. F., Jr.; Tilmes, S.; Barré, J.; Worden, H. M.; Raeder, K.; Anderson, J. L.; Edwards, D. P.

2017-12-01

Atmospheric oxidative capacity plays a crucial role in the fate of greenhouse gases and air pollutants as well as in the formation of secondary pollutants such as tropospheric ozone. The attribution of sources of tropospheric ozone is a difficult task because of biases in input parameters and forcings such as emissions and meteorology in addition to errors in chemical schemes. We assimilate satellite remote sensing observations of ozone precursors such as carbon monoxide (CO) and nitrogen dioxide (NO2) in the global coupled chemistry-transport model: Community Atmosphere Model with Chemistry (CAM-Chem). The assimilation is completed using an Ensemble Adjustment Kalman Filter (EAKF) in the Data Assimilation Research Testbed (DART) framework which allows estimates of unobserved parameters and potential constraints on secondary pollutants and emissions. The ensemble will be constructed using perturbations in chemical kinetics, different emission fields and by assimilating meteorological observations to fully assess uncertainties in the chemical fields of targeted species. We present a set of tools such as emission tags (CO and propane), combined with diagnostic analysis of chemical regimes and perturbation of emissions ratios to estimate a regional budget of primary and secondary pollutants in East Asia and their sensitivity to data assimilation. This study benefits from the large set of aircraft and ozonesonde in-situ observations from the Korea-United States Air Quality (KORUS-AQ) campaign that occurred in South Korea in May-June 2016.

Supporting Operational Data Assimilation Capabilities to the Research Community

NASA Astrophysics Data System (ADS)

Shao, H.; Hu, M.; Stark, D. R.; Zhou, C.; Beck, J.; Ge, G.

2017-12-01

The Developmental Testbed Center (DTC), in partnership with the National Centers for Environmental Prediction (NCEP) and other operational and research institutions, provides operational data assimilation capabilities to the research community and helps transition research advances to operations. The primary data assimilation system supported currently by the DTC is the Gridpoint Statistical Interpolation (GSI) system and the National Oceanic and Atmospheric Administration (NOAA) Ensemble Kalman Filter (EnKF) system. GSI is a variational based system being used for daily operations at NOAA, NCEP, the National Aeronautics and Space Administration, and other operational agencies. Recently, GSI has evolved into a four-dimensional EnVar system. Since 2009, the DTC has been releasing the GSI code to the research community annually and providing user support. In addition to GSI, the DTC, in 2015, began supporting the ensemble based EnKF data assimilation system. EnKF shares the observation operator with GSI and therefore, just as GSI, can assimilate both conventional and non-conventional data (e.g., satellite radiance). Currently, EnKF is being implemented as part of the GSI based hybrid EnVar system for NCEP Global Forecast System operations. This paper will summarize the current code management and support framework for these two systems. Following that is a description of available community services and facilities. Also presented is the pathway for researchers to contribute their development to the daily operations of these data assimilation systems.

Assimilating the Future for Better Forecasts and Earlier Warnings

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Most Colorful Example of Genetic Assimilation? Exploring the Evolutionary Destiny of Recurrent Phenotypic Accommodation.

PubMed

Badyaev, Alexander V; Potticary, Ahva L; Morrison, Erin S

2017-08-01

Evolution of adaptation requires both generation of novel phenotypic variation and retention of a locally beneficial subset of this variation. Such retention can be facilitated by genetic assimilation, the accumulation of genetic and molecular mechanisms that stabilize induced phenotypes and assume progressively greater control over their reliable production. A particularly strong inference into genetic assimilation as an evolutionary process requires a system where it is possible to directly evaluate the extent to which an induced phenotype is progressively incorporated into preexisting developmental pathways. Evolution of diet-dependent pigmentation in birds-where external carotenoids are coopted into internal metabolism to a variable degree before being integrated with a feather's developmental processes-provides such an opportunity. Here we combine a metabolic network view of carotenoid evolution with detailed empirical study of feather modifications to show that the effect of physical properties of carotenoids on feather structure depends on their metabolic modification, their environmental recurrence, and biochemical redundancy, as predicted by the genetic assimilation hypothesis. Metabolized carotenoids caused less stochastic variation in feather structure and were more closely integrated with feather growth than were dietary carotenoids of the same molecular weight. These patterns were driven by the recurrence of organism-carotenoid associations: commonly used dietary carotenoids and biochemically redundant derived carotenoids caused less stochastic variation in feather structure than did rarely used or biochemically unique compounds. We discuss implications of genetic assimilation processes for the evolutionary diversification of diet-dependent animal coloration.

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.

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.

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.

Anaerobic Metabolism in the N-Limited Green Alga Selenastrum minutum: II. Assimilation of Ammonium by Anaerobic Cells.

PubMed

Vanlerberghe, G C; Turpin, D H

1990-11-01

The green alga Selenastrum minutum (Naeg.) Collins is able to assimilate NH(4) (+) in the dark under anaerobic conditions (GC Vanlerberghe, AK Horsey, HG Weger, DH Turpin [1989] Plant Physiol 91: 1551-1557). In the present study, analysis of metabolites following addition of NH(4) (+) to cells acclimated to anaerobic conditions has shown the following. There was a transient decline in adenylate energy charge from 0.6 to 0.4 followed by a recovery back to ~0.6. This was accompanied by a rapid increase in pyruvate/phosphoenolpyruvate and fructose-1,6-bisphosphate/fructose-6-phosphate ratios indicating activation of pyruvate kinase and 6-phosphofructokinase, respectively. There was also an increase in fructose-2,6-bisphosphate, which, since this alga lacks pyrophosphate dependent 6-phosphofructokinase can be inferred to inhibit gluconeogenic fructose-1,6-bisphosphatase. These changes resulted in an increase in the rate of anaerobic starch breakdown. Anaerobic NH(4) (+) assimilation also resulted in a two-fold increase in the rate of production of the major fermentative end-products in this alga, d-lactate and ethanol. There was no change in the rate of accumulation of the fermentative end product succinate but malate accumulated under anoxia during NH(4) (+) assimilation. A rapid increase in Gln and decline in Glu indicates that primary NH(4) (+) assimilation under anoxia was via glutamine synthetase-glutamate synthase. Almost all N assimilated under these conditions was sequestered in alanine. These results allow us to propose a model for the regulation of carbon metabolism during anaerobic NH(4) (+) assimilation.

Assessment of Two Types of Observations (SATWND and GPSRO) for the Operational Global 4DVAR System

NASA Astrophysics Data System (ADS)

Leng, H.

2017-12-01

The performance of a data assimilation system is significantly dependent on the quality and quantity of observations assimilated. In these years, more and more satellite observations have been applied in many operational assimilation systems. In this paper, the assessment of satellite-derived winds (SATWND) and GPS radio occultation (GPSRO) bending angles has been performed using a range of diagnostics. The main positive impacts are made when satellite-derived cloud data (GOES cloud data and MODIS cloud data) is assimilated, but benefit is hardly obtained from GPSRO data in the Operational Global 4DVAR System. In a full system configuration, the assimilation of satellite-derived observations is globally beneficial on the analysis, and the benefit can be well propagated into the forecast. The assimilation of the GPSRO observations has a slightly positive impact in the Tropics, but is neutral in the Northern Hemisphere and in the Southern Hemisphere. To assess the synergies of satellite-derived observations with other types of observation, experiments assimilating satellite-derived data and AMSU-A and AMSU-B observations were run. The results show that the analysis increments structure is not modified when AMSU-A and AMSU-B observations are also assimilated. This suggests that the impact of satellite-derived observations is not limited by the large impact of satellite radiance observations.

Structure and mechanism of soybean ATP sulfurylase and the committed step in plant sulfur assimilation

USDA-ARS?s Scientific Manuscript database

Enzymes of the sulfur assimilation pathway are potential targets for improving nutrient content and environmental stress responses in plants. The committed step in this pathway is catalyzed by ATP sulfurylase, which synthesizes adenosine-5'-phosphosulfate (APS) from sulfate and ATP. To better unde...

Impact of observation error structure on satellite soil moisture assimilation into a rainfall-runoff model

USDA-ARS?s Scientific Manuscript database

In Ensemble Kalman Filter (EnKF)-based data assimilation, the background prediction of a model is updated using observations and relative weights based on the model prediction and observation uncertainties. In practice, both model and observation uncertainties are difficult to quantify and they have...

"Que Assimilated, Brother, Yo Soy Asimilao": The Structuring of Puerto Rican Identity in the U.S.

ERIC Educational Resources Information Center

Flores, Juan

1985-01-01

Discusses the cultural identity and experiences of Puerto Ricans residing in New York City. Explores, through excerpts of poetry by "Nuyoricans," the themes of assimilation, attachment to the island of Puerto Rico, relations with Black and White New Yorkers, and bilingualism. (GC)

Interannual Variation in Phytoplankton Class-specific Primary Production at a Global Scale

NASA Technical Reports Server (NTRS)

Rousseaux, Cecile; Gregg, Watson

2014-01-01

Phytoplankton is responsible for over half of the net primary production on earth. The knowledge on the contribution of various phytoplankton groups to the total primary production is still poorly understood. Data from satellite observations suggest that for upwelling regions, photosynthetic rates by microplankton is higher than that of nanoplankton but that when the spatial extent is considered, the production by nanoplankton is comparable or even larger than microplankton. Here, we used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of 4 phytoplankton groups to the total primary production. Globally, diatoms were the group that contributed the most to the total phytoplankton production (approx. 50%) followed by coccolithophores and chlorophytes. Primary production by diatoms was highest in high latitude (>45 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We assessed the effects of climate variability on the class-specific primary production using global (i.e. Multivariate El Nino Index, MEI) and 'regional' climate indices (e.g. Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.

Mass Media Functions, Knowledge and Social Control

ERIC Educational Resources Information Center

Donohue, G. A.; And Others

1973-01-01

Develops a macro-view of mass media as interdependent parts of a total social system including a series of interrelated subsystems with primary function involving the generation, dissemination, and assimilation of information. (RB)

Phylogenetically conserved resource partitioning in the coastal microbial loop

DOE PAGES

Bryson, Samuel; Li, Zhou; Chavez, Francisco; ...

2017-08-11

Resource availability influences marine microbial community structure, suggesting that population-specific resource partitioning defines discrete niches. Identifying how resources are partitioned among populations, thereby characterizing functional guilds within the communities, remains a challenge for microbial ecologists. We used proteomic stable isotope probing (SIP) and NanoSIMS analysis of phylogenetic microarrays (Chip-SIP) along with 16S rRNA gene amplicon and metagenomic sequencing to characterize the assimilation of six 13C-labeled common metabolic substrates and changes in the microbial community structure within surface water collected from Monterey Bay, CA. Both sequencing approaches indicated distinct substrate-specific community shifts. However, observed changes in relative abundance for individual populationsmore » did not correlate well with directly measured substrate assimilation. The complementary SIP techniques identified assimilation of all six substrates by diverse taxa, but also revealed differential assimilation of substrates into protein and ribonucleotide biomass between taxa. Substrate assimilation trends indicated significantly conserved resource partitioning among populations within the Flavobacteriia, Alphaproteobacteria and Gammaproteobacteria classes, suggesting that functional guilds within marine microbial communities are phylogenetically cohesive. However, populations within these classes exhibited heterogeneity in biosynthetic activity, which distinguished high-activity copiotrophs from low-activity oligotrophs. These results indicate distinct growth responses between populations that is not apparent by genome sequencing alone.« less

Phylogenetically conserved resource partitioning in the coastal microbial loop

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

Bryson, Samuel; Li, Zhou; Chavez, Francisco

Resource availability influences marine microbial community structure, suggesting that population-specific resource partitioning defines discrete niches. Identifying how resources are partitioned among populations, thereby characterizing functional guilds within the communities, remains a challenge for microbial ecologists. We used proteomic stable isotope probing (SIP) and NanoSIMS analysis of phylogenetic microarrays (Chip-SIP) along with 16S rRNA gene amplicon and metagenomic sequencing to characterize the assimilation of six 13C-labeled common metabolic substrates and changes in the microbial community structure within surface water collected from Monterey Bay, CA. Both sequencing approaches indicated distinct substrate-specific community shifts. However, observed changes in relative abundance for individual populationsmore » did not correlate well with directly measured substrate assimilation. The complementary SIP techniques identified assimilation of all six substrates by diverse taxa, but also revealed differential assimilation of substrates into protein and ribonucleotide biomass between taxa. Substrate assimilation trends indicated significantly conserved resource partitioning among populations within the Flavobacteriia, Alphaproteobacteria and Gammaproteobacteria classes, suggesting that functional guilds within marine microbial communities are phylogenetically cohesive. However, populations within these classes exhibited heterogeneity in biosynthetic activity, which distinguished high-activity copiotrophs from low-activity oligotrophs. These results indicate distinct growth responses between populations that is not apparent by genome sequencing alone.« less

Phylogenetically conserved resource partitioning in the coastal microbial loop

PubMed Central

Bryson, Samuel; Li, Zhou; Chavez, Francisco; Weber, Peter K; Pett-Ridge, Jennifer; Hettich, Robert L; Pan, Chongle; Mayali, Xavier; Mueller, Ryan S

2017-01-01

Resource availability influences marine microbial community structure, suggesting that population-specific resource partitioning defines discrete niches. Identifying how resources are partitioned among populations, thereby characterizing functional guilds within the communities, remains a challenge for microbial ecologists. We used proteomic stable isotope probing (SIP) and NanoSIMS analysis of phylogenetic microarrays (Chip-SIP) along with 16S rRNA gene amplicon and metagenomic sequencing to characterize the assimilation of six 13C-labeled common metabolic substrates and changes in the microbial community structure within surface water collected from Monterey Bay, CA. Both sequencing approaches indicated distinct substrate-specific community shifts. However, observed changes in relative abundance for individual populations did not correlate well with directly measured substrate assimilation. The complementary SIP techniques identified assimilation of all six substrates by diverse taxa, but also revealed differential assimilation of substrates into protein and ribonucleotide biomass between taxa. Substrate assimilation trends indicated significantly conserved resource partitioning among populations within the Flavobacteriia, Alphaproteobacteria and Gammaproteobacteria classes, suggesting that functional guilds within marine microbial communities are phylogenetically cohesive. However, populations within these classes exhibited heterogeneity in biosynthetic activity, which distinguished high-activity copiotrophs from low-activity oligotrophs. These results indicate distinct growth responses between populations that is not apparent by genome sequencing alone. PMID:28800138

Data Assimilation Results from PLASMON

NASA Astrophysics Data System (ADS)

Jorgensen, A. M.; Lichtenberger, J.; Duffy, J.; Friedel, R. H.; Clilverd, M.; Heilig, B.; Vellante, M.; Manninen, J. K.; Raita, T.; Rodger, C. J.; Collier, A.; Reda, J.; Holzworth, R. H.; Ober, D. M.; Boudouridis, A.; Zesta, E.; Chi, P. J.

2013-12-01

VLF and magnetometer observations can be used to remotely sense the plasmasphere. VLF whistler waves can be used to measure the electron density and magnetic Field Line Resonance (FLR) measurements can be used to measure the mass density. In principle it is then possible to remotely map the plasmasphere with a network of ground-based stations which are also less expensive and more permanent than satellites. The PLASMON project, funded by the EU FP-7 program, is in the process of doing just this. A large number of ground-based observations will be input into a data assimilative framework which models the plasmasphere structure and dynamics. The data assimilation framework combines the Ensemble Kalman Filter with the Dynamic Global Core Plasma Model. In this presentation we will describe the plasmasphere model, the data assimilation approach that we have taken, PLASMON data and data assimilation results for specific events.

Building occupancy simulation and data assimilation using a graph-based agent-oriented model

NASA Astrophysics Data System (ADS)

Rai, Sanish; Hu, Xiaolin

2018-07-01

Building occupancy simulation and estimation simulates the dynamics of occupants and estimates their real-time spatial distribution in a building. It requires a simulation model and an algorithm for data assimilation that assimilates real-time sensor data into the simulation model. Existing building occupancy simulation models include agent-based models and graph-based models. The agent-based models suffer high computation cost for simulating large numbers of occupants, and graph-based models overlook the heterogeneity and detailed behaviors of individuals. Recognizing the limitations of existing models, this paper presents a new graph-based agent-oriented model which can efficiently simulate large numbers of occupants in various kinds of building structures. To support real-time occupancy dynamics estimation, a data assimilation framework based on Sequential Monte Carlo Methods is also developed and applied to the graph-based agent-oriented model to assimilate real-time sensor data. Experimental results show the effectiveness of the developed model and the data assimilation framework. The major contributions of this work are to provide an efficient model for building occupancy simulation that can accommodate large numbers of occupants and an effective data assimilation framework that can provide real-time estimations of building occupancy from sensor data.

Impact of GPM Rainrate Data Assimilation on Simulation of Hurricane Harvey (2017)

NASA Technical Reports Server (NTRS)

Li, Xuanli; Srikishen, Jayanthi; Zavodsky, Bradley; Mecikalski, John

2018-01-01

Built upon Tropical Rainfall Measuring Mission (TRMM) legacy for next-generation global observation of rain and snow. The GPM was launched in February 2014 with Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) onboard. The GPM has a broad global coverage approximately 70deg S -70deg N with a swath of 245/125-km for the Ka (35.5 GHz)/Ku (13.6 GHz) band radar, and 850-km for the 13-channel GMI. GPM also features better retrievals for heavy, moderate, and light rain and snowfall To develop methodology to assimilate GPM surface precipitation data with Grid-point Statistical Interpolation (GSI) data assimilation system and WRF ARW model To investigate the potential and the value of utilizing GPM observation into NWP for operational environment The GPM rain rate data has been successfully assimilated using the GSI rain data assimilation package. Impacts of rain rate data have been found in temperature and moisture fields of initial conditions. 2.Assimilation of either GPM IMERG or GPROF rain product produces significant improvement in precipitation amount and structure for Hurricane Harvey (2017) forecast. Since IMERG data is available half-hourly, further forecast improvement is expected with continuous assimilation of IMERG data

Does Ocean Color Data Assimilation Improve Estimates of Global Ocean Inorganic Carbon?

NASA Technical Reports Server (NTRS)

Gregg, Watson

2012-01-01

Ocean color data assimilation has been shown to dramatically improve chlorophyll abundances and distributions globally and regionally in the oceans. Chlorophyll is a proxy for phytoplankton biomass (which is explicitly defined in a model), and is related to the inorganic carbon cycle through the interactions of the organic carbon (particulate and dissolved) and through primary production where inorganic carbon is directly taken out of the system. Does ocean color data assimilation, whose effects on estimates of chlorophyll are demonstrable, trickle through the simulated ocean carbon system to produce improved estimates of inorganic carbon? Our emphasis here is dissolved inorganic carbon, pC02, and the air-sea flux. We use a sequential data assimilation method that assimilates chlorophyll directly and indirectly changes nutrient concentrations in a multi-variate approach. The results are decidedly mixed. Dissolved organic carbon estimates from the assimilation model are not meaningfully different from free-run, or unassimilated results, and comparisons with in situ data are similar. pC02 estimates are generally worse after data assimilation, with global estimates diverging 6.4% from in situ data, while free-run estimates are only 4.7% higher. Basin correlations are, however, slightly improved: r increase from 0.78 to 0.79, and slope closer to unity at 0.94 compared to 0.86. In contrast, air-sea flux of C02 is noticeably improved after data assimilation. Global differences decline from -0.635 mol/m2/y (stronger model sink from the atmosphere) to -0.202 mol/m2/y. Basin correlations are slightly improved from r=O.77 to r=0.78, with slope closer to unity (from 0.93 to 0.99). The Equatorial Atlantic appears as a slight sink in the free-run, but is correctly represented as a moderate source in the assimilation model. However, the assimilation model shows the Antarctic to be a source, rather than a modest sink and the North Indian basin is represented incorrectly as a sink rather than the source indicated by the free-run model and data estimates.

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.

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.

Variability in Tropospheric Ozone over China Derived from Assimilated GOME-2 Ozone Profiles

NASA Astrophysics Data System (ADS)

van Peet, J. C. A.; van der A, R. J.; Kelder, H. M.

2016-08-01

A tropospheric ozone dataset is derived from assimilated GOME-2 ozone profiles for 2008. Ozone profiles are retrieved with the OPERA algorithm, using the optimal estimation method. The retrievals are done on a spatial resolution of 160×160 km on 16 layers ranging from the surface up to 0.01 hPa. By using the averaging kernels in the data assimilation, the algorithm maintains the high resolution vertical structures of the model, while being constrained by observations with a lower vertical resolution.

Impact of TRMM and SSM/I-derived Precipitation and Moisture Data on the GEOS Global Analysis

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. The Data Assimilation Office at NASA's Goddard Space Flight Center has been exploring the use of space-based rainfall and total precipitable water (TPW) estimates to constrain these hydrological parameters in the Goddard Earth Observing System (GEOS) global data assimilation system. We present results showing that assimilating the 6-hour averaged rain rates and TPW estimates from the Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave/Imager (SSM/I) instruments improves not only the precipitation and moisture estimates but also reduce state-dependent systematic errors in key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation. The improved analysis also improves short-range forecasts beyond 1 day, but the impact is relatively modest compared with improvements in the time-averaged analysis. The study shows that, in the presence of biases and other errors of the forecast model, improving the short-range forecast is not necessarily prerequisite for improving the assimilation as a climate data set. The full impact of a given type of observation on the assimilated data set should not be measured solely in terms of forecast skills.

Phosphoenolpyruvate carboxylase intrinsically located in the chloroplast of rice plays a crucial role in ammonium assimilation

PubMed Central

Masumoto, Chisato; Miyazawa, Shin-Ichi; Ohkawa, Hiroshi; Fukuda, Takuya; Taniguchi, Yojiro; Murayama, Seiji; Kusano, Miyako; Saito, Kazuki; Fukayama, Hiroshi; Miyao, Mitsue

2010-01-01

Phosphoenolpyruvate carboxylase (PEPC) is a key enzyme of primary metabolism in bacteria, algae, and vascular plants, and is believed to be cytosolic. Here we show that rice (Oryza sativa L.) has a plant-type PEPC, Osppc4, that is targeted to the chloroplast. Osppc4 was expressed in all organs tested and showed high expression in the leaves. Its expression in the leaves was confined to mesophyll cells, and Osppc4 accounted for approximately one-third of total PEPC protein in the leaf blade. Recombinant Osppc4 was active in the PEPC reaction, showing Vmax comparable to cytosolic isozymes. Knockdown of Osppc4 expression by the RNAi technique resulted in stunting at the vegetative stage, which was much more marked when rice plants were grown with ammonium than with nitrate as the nitrogen source. Comparison of leaf metabolomes of ammonium-grown plants suggested that the knockdown suppressed ammonium assimilation and subsequent amino acid synthesis by reducing levels of organic acids, which are carbon skeleton donors for these processes. We also identified the chloroplastic PEPC gene in other Oryza species, all of which are adapted to waterlogged soil where the major nitrogen source is ammonium. This suggests that, in addition to glycolysis, the genus Oryza has a unique route to provide organic acids for ammonium assimilation that involves a chloroplastic PEPC, and that this route is crucial for growth with ammonium. This work provides evidence for diversity of primary ammonium assimilation in the leaves of vascular plants. PMID:20194759

Leaves play a central role in the adaptation of nitrogen and sulfur metabolism to ammonium nutrition in oilseed rape (Brassica napus).

PubMed

Coleto, Inmaculada; de la Peña, Marlon; Rodríguez-Escalante, Jon; Bejarano, Iraide; Glauser, Gaëtan; Aparicio-Tejo, Pedro M; González-Moro, M Begoña; Marino, Daniel

2017-09-20

The coordination between nitrogen (N) and sulfur (S) assimilation is required to suitably provide plants with organic compounds essential for their development and growth. The N source induces the adaptation of many metabolic processes in plants; however, there is scarce information about the influence that it may exert on the functioning of S metabolism. The aim of this work was to provide an overview of N and S metabolism in oilseed rape (Brassica napus) when exposed to different N sources. To do so, plants were grown in hydroponic conditions with nitrate or ammonium as N source at two concentrations (0.5 and 1 mM). Metabolic changes mainly occurred in leaves, where ammonium caused the up-regulation of enzymes involved in the primary assimilation of N and a general increase in the concentration of N-compounds (NH 4 + , amino acids and proteins). Similarly, the activity of key enzymes of primary S assimilation and the content of S-compounds (glutathione and glucosinolates) were also higher in leaves of ammonium-fed plants. Interestingly, sulfate level was lower in leaves of ammonium-fed plants, which was accompanied by the down-regulation of SULTR1 transporters gene expression. The results highlight the impact of the N source on different steps of N and S metabolism in oilseed rape, notably inducing N and S assimilation in leaves, and put forward the potential of N source management to modulate the synthesis of compounds with biotechnological interest, such as glucosinolates.

Trophodynamics of the Hanna Shoal Ecosystem (Chukchi Sea, Alaska): Connecting multiple end-members to a rich food web

NASA Astrophysics Data System (ADS)

McTigue, N. D.; Dunton, K. H.

2017-10-01

Predicting how alterations in sea ice-mediated primary production will impact Arctic food webs remains a challenge in forecasting ecological responses to climate change. One top-down approach to this challenge is to elucidate trophic roles of consumers as either specialists (i.e., consumers of predominantly one food resource) or generalists (i.e., consumers of multiple food resources) to categorize the dependence of consumers on each primary producer. At Hanna Shoal in the Chukchi Sea, Alaska, we used stable carbon and nitrogen isotope data to quantify trophic redundancy with standard ellipse areas at both the species and trophic guild levels. We also investigated species-level trophic plasticity by analyzing the varying extents that three end-members were assimilated by the food web using the mixing model simmr (Stable Isotope Mixing Model in R). Our results showed that ice algae, a combined phytoplankton and sediment organic matter composite (PSOM), and a hypothesized microphytobenthos (MPB) component were incorporated by consumers in the benthic food web, but their importance varied by species. Some primary consumers relied heavily on PSOM (e.g, the amphipods Ampelisca sp. and Byblis sp.; the copepod Calanus sp.), while others exhibited generalist feeding and obtained nutrition from multiple sources (e.g., the holothuroidean Ocnus glacialis, the gastropod Tachyrhynchus sp., the sipunculid Golfingia margaritacea, and the bivalves Ennucula tenuis, Nuculana pernula, Macoma sp., and Yoldia hyperborea). Most higher trophic level benthic predators, including the gastropods Buccinum sp., Cryptonatica affinis, and Neptunea sp, the seastar Leptasterias groenlandica, and the amphipod Anonyx sp. also exhibited trophic plasticity by coupling energy pathways from multiple primary producers including PSOM, ice algae, and MPB. Our stable isotope data indicate that consumers in the Hanna Shoal food web exhibit considerable trophic redundancy, while few species were specialists and assimilated only one end-member. Although most consumers were capable of obtaining nutrition from multiple food sources, the timing, quantity, and quality of ice-mediated primary production may still have pronounced effects on food web structure.

Global Gross Primary Productivity for 2015 Inferred from OCO-2 SIF and a Carbon-Cycle Data Assimilation System

NASA Astrophysics Data System (ADS)

Norton, A.; Rayner, P. J.; Scholze, M.; Koffi, E. N. D.

2016-12-01

The intercomparison study CMIP5 among other studies (e.g. Bodman et al., 2013) has shown that the land carbon flux contributes significantly to the uncertainty in projections of future CO2 concentration and climate (Friedlingstein et al., 2014)). The main challenge lies in disaggregating the relatively well-known net land carbon flux into its component fluxes, gross primary production (GPP) and respiration. Model simulations of these processes disagree considerably, and accurate observations of photosynthetic activity have proved a hindrance. Here we build upon the Carbon Cycle Data Assimilation System (CCDAS) (Rayner et al., 2005) to constrain estimates of one of these uncertain fluxes, GPP, using satellite observations of Solar Induced Fluorescence (SIF). SIF has considerable benefits over other proxy observations as it tracks not just the presence of vegetation but actual photosynthetic activity (Walther et al., 2016; Yang et al., 2015). To combine these observations with process-based simulations of GPP we have coupled the model SCOPE with the CCDAS model BETHY. This provides a mechanistic relationship between SIF and GPP, and the means to constrain the processes relevant to SIF and GPP via model parameters in a data assimilation system. We ingest SIF observations from NASA's Orbiting Carbon Observatory 2 (OCO-2) for 2015 into the data assimilation system to constrain estimates of GPP in space and time, while allowing for explicit consideration of uncertainties in parameters and observations. Here we present first results of the assimilation with SIF. Preliminary results indicate a constraint on global annual GPP of at least 75% when using SIF observations, reducing the uncertainty to < 3 PgC yr-1. A large portion of the constraint is propagated via parameters that describe leaf phenology. These results help to bring together state-of-the-art observations and model to improve understanding and predictive capability of GPP.

The Kalman Filter and High Performance Computing at NASA's Data Assimilation Office (DAO)

NASA Technical Reports Server (NTRS)

Lyster, Peter M.

1999-01-01

Atmospheric data assimilation is a method of combining actual observations with model simulations to produce a more accurate description of the earth system than the observations alone provide. The output of data assimilation, sometimes called "the analysis", are accurate regular, gridded datasets of observed and unobserved variables. This is used not only for weather forecasting but is becoming increasingly important for climate research. For example, these datasets may be used to assess retrospectively energy budgets or the effects of trace gases such as ozone. This allows researchers to understand processes driving weather and climate, which have important scientific and policy implications. The primary goal of the NASA's Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. This presentation will: (1) describe ongoing work on the advanced Kalman/Lagrangian filter parallel algorithm for the assimilation of trace gases in the stratosphere; and (2) discuss the Kalman filter in relation to other presentations from the DAO on Four Dimensional Data Assimilation at this meeting. Although the designation "Kalman filter" is often used to describe the overarching work, the series of talks will show that the scientific software and the kind of parallelization techniques that are being developed at the DAO are very different depending on the type of problem being considered, the extent to which the problem is mission critical, and the degree of Software Engineering that has to be applied.

Geomorphology controls the trophic base of stream food webs in a boreal watershed .

PubMed

Smits, Adrianne P; Schindler, Daniel E; Brett, Michael T

2015-07-01

Abstract. Physical attributes of rivers control the quantity and quality of energy sources available to consumers, but it remains untested whether geomorphic conditions of whole watersheds affect the assimilation of different resources by stream organisms. We compared the fatty acid (FA) compositions of two invertebrate taxa (caddisflies, mayflies) collected from 16 streams in southwest Alaska, USA, to assess how assimilation of terrestrial organic matter (OM) and algae varied across a landscape gradient in watershed features. We found relatively higher assimilation of algae in high-gradient streams compared with low-gradient streams, and the opposite pattern for assimilation of terrestrial OM and microbes. The strength of these patterns was more pronounced for caddisflies than mayflies. Invertebrates from low-gradient watersheds had FA markers unique to methane-oxidizing bacteria and sulfate-reducing microbes, indicating a contribution of anaerobic pathways to primary consumers. Diversity of FA composition was highest in watersheds of intermediate slopes that contain both significant terrestrial inputs as well as high algal biomass. By controlling the accumulation rate and processing of terrestrial OM, watershed features influence the energetic base of food webs in boreal streams.

Narratives of Assimilation, Divergence, and Hybridity: The Reproduction Decisions of College-Educated Mexican American Women

ERIC Educational Resources Information Center

Alvarado, Emmanuel; Nehring, Daniel

2012-01-01

Our study explored cultural understandings surrounding the reproductive decisions of US-born, college-educated Mexican American women through a series of semi-structured in-depth interviews. In considering the results, this article advances debates on Latina women's reproductive choices beyond the theoretical paradigms of "assimilation" and…

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.

AIDA - from Airborne Data Inversion to In-Depth Analysis

NASA Astrophysics Data System (ADS)

Meyer, U.; Goetze, H.; Schroeder, M.; Boerner, R.; Tezkan, B.; Winsemann, J.; Siemon, B.; Alvers, M.; Stoll, J. B.

2011-12-01

The rising competition in land use especially between water economy, agriculture, forestry, building material economy and other industries often leads to irreversible deterioration in the water and soil system (as salinization and degradation) which results in a long term damage of natural resources. A sustainable exploitation of the near subsurface by industry, economy and private households is a fundamental demand of a modern society. To fulfill this demand, a sound and comprehensive knowledge on structures and processes of the near subsurface is an important prerequisite. A spatial survey of the usable underground by aerogeophysical means and a subsequent ground geophysics survey targeted at special locations will deliver essential contributions within short time that make it possible to gain the needed additional knowledge. The complementary use of airborne and ground geophysics as well as the validation, assimilation and improvement of current findings by geological and hydrogeological investigations and plausibility tests leads to the following key questions: a) Which new and/or improved automatic algorithms (joint inversion, data assimilation and such) are useful to describe the structural setting of the usable subsurface by user specific characteristics as i.e. water volume, layer thicknesses, porosities etc.? b) What are the physical relations of the measured parameters (as electrical conductivities, magnetic susceptibilities, densities, etc.)? c) How can we deduce characteristics or parameters from the observations which describe near subsurface structures as ground water systems, their charge, discharge and recharge, vulnerabilities and other quantities? d) How plausible and realistic are the numerically obtained results in relation to user specific questions and parameters? e) Is it possible to compile material flux balances that describe spatial and time dependent impacts of environmental changes on aquifers and soils by repeated airborne surveys? In order to follow up these questions raised the project aims to achieve the following goals: a) Development of new and expansion of existent inversion strategies to improve structural parameter information on different space and time scales. b) Development, modification, and tests for a multi-parameter inversion (joint inversion). c) Development of new quantitative approaches in data assimilation and plausibility studies. d) Compilation of optimized work flows for fast employment by end users. e) Primary goal is to solve comparable society related problems (as salinization, erosion, contamination, degradation etc.) in regions within Germany and abroad by generalization of project results.

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.

SRB Data and Information

Atmospheric Science Data Center

2017-01-13

... grid. Model inputs of cloud amounts and other atmospheric state parameters are also available in some of the data sets. Primary inputs to ... Analysis (SMOBA), an assimilation product from NOAA's Climate Prediction Center. SRB products are reformatted for the use of ...

Improving Forecast Skill by Assimilation of AIRS Temperature Soundings

NASA Technical Reports Server (NTRS)

Susskind, Joel; Reale, Oreste

2010-01-01

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

Role of Satellite Rainfall Information in Improving Understanding of the Dynamical Link Between the Tropics and Extratropics Prospects of Improved Forecasts of Weather and Short-Term Climate Variability on Sub-Seasonal Time Scales

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.

2002-01-01

The tropics and extratropics are two dynamically distinct regimes. The coupling between these two regimes often defies simple analytical treatment. Progress in understanding of the dynamical interaction between the tropics and extratropics relies on better observational descriptions to guide theoretical development. However, global analyses currently contain significant errors in primary hydrological variables such as precipitation, evaporation, moisture, and clouds, especially in the tropics. Tropical analyses have been shown to be sensitive to parameterized precipitation processes, which are less than perfect, leading to order-one discrepancies between estimates produced by different data assimilation systems. One strategy for improvement is to assimilate rainfall observations to constrain the analysis and reduce uncertainties in variables physically linked to precipitation. At the Data Assimilation Office at the NASA Goddard Space Flight Center, we have been exploring the use of tropical rain rates derived from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments in global data assimilation. Results show that assimilating these data improves not only rainfall and moisture fields but also related climate parameters such as clouds and radiation, as well as the large-scale circulation and short-range forecasts. These studies suggest that assimilation of microwave rainfall observations from space has the potential to significantly improve the quality of 4-D assimilated datasets for climate investigations (Hou et al. 2001). In the next few years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission in 2007. Continued improvements in assimilation methodology, rainfall error estimates, and model parameterizations are needed to ensure that we derive maximum benefits from these observations.

Sensitivity of CAM-Chem/DART MOPITT CO Assimilation Performance to the Choice of Ensemble System Configuration: A Case Study for Fires in the Amazon

NASA Astrophysics Data System (ADS)

Arellano, A. F., Jr.; Tang, W.

2017-12-01

Assimilating observational data of chemical constituents into a modeling system is a powerful approach in assessing changes in atmospheric composition and estimating associated emissions. However, the results of such chemical data assimilation (DA) experiments are largely subject to various key factors such as: a) a priori information, b) error specification and representation, and c) structural biases in the modeling system. Here we investigate the sensitivity of an ensemble-based data assimilation state and emission estimates to these key factors. We focus on investigating the assimilation performance of the Community Earth System Model (CESM)/CAM-Chem with the Data Assimilation Research Testbed (DART) in representing biomass burning plumes in the Amazonia during the 2008 fire season. We conduct the following ensemble DA MOPITT CO experiments: 1) use of monthly-average NCAR's FINN surface fire emissionss, 2) use of daily FINN surface fire emissions, 3) use of daily FINN emissions with climatological injection heights, and 4) use of perturbed FINN emission parameters to represent not only the uncertainties in combustion activity but also in combustion efficiency. We show key diagnostics of assimilation performance for these experiments and verify with available ground-based and aircraft-based measurements.

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

PubMed

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

2012-01-01

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

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

Van Hook, R. I.; Yates, A. J.

Biological assimilation and transport of cadmium were determined for an arthropod food chain in an east Tennessee grassland community. Laboratory experiments demonstrated that there were no significant differences (P greater than 0.05) in assimilation rates (17 percent assimilation per day) or biological half-lives (7 days) of 109Cd either as soluble nitrate or insoluble oxide in crickets under identical conditions. Field experiments demonstrated that primary consumers (crickets) accumulated 109Cd much more rapidly (uptake rate = 0.55 day -1) than did the spider predators (uptake rate = 0.08 day -1). Equilibrium concentrations in crickets were obtained in 9 days (0.04 ppM cadmium),more » while equilibrium was not reached in spiders during the 30- day study. Food-chain concentration of cadmium did not occur as crickets accumulated levels of cadmium 60 percent of that in their vegetation food sources and spiders accumulated only 70 percent of the cadmium present in the cricket tissues.« less

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

Van Hook, R. I.; Yates, A. J.

Biological assimilation and transport of cadmium were determined for an arthropod food chain in an east Tennessee grassland community. Laboratory experiments demonstrated that there were no significant differences (P greater than 0.05) in assimilation rates (17 percent assimilation per day) or biological half-lives (7 days) of $sup 109$Cd either as soluble nitrate or insoluble oxide in crickets under identical conditions. Field experiments demonstrated that primary consumers (crickets) accumulated $sup 109$Cd much more rapidly (uptake rate = 0.55 day$sup -1$) than did the spider predators (uptake rate = 0.08 day$sup -1$). Equilibrium concentrations in crickets were obtained in 9 days (0.04more » ppM cadmium), while equilibrium was not reached in spiders during the 30- day study. Food-chain concentration of cadmium did not occur as crickets accumulated levels of cadmium 60 percent of that in their vegetation food sources and spiders accumulated only 70 percent of the cadmium present in the cricket tissues.« less

The importance of cytosolic glutamine synthetase in nitrogen assimilation and recycling

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

Bernard, S.M.; Habash, D.Z.

2009-07-02

Glutamine synthetase assimilates ammonium into amino acids, thus it is a key enzyme for nitrogen metabolism. The cytosolic isoenzymes of glutamine synthetase assimilate ammonium derived from primary nitrogen uptake and from various internal nitrogen recycling pathways. In this way, cytosolic glutamine synthetase is crucial for the remobilization of protein-derived nitrogen. Cytosolic glutamine synthetase is encoded by a small family of genes that are well conserved across plant species. Members of the cytosolic glutamine synthetase gene family are regulated in response to plant nitrogen status, as well as to environmental cues, such as nitrogen availability and biotic/abiotic stresses. The complex regulationmore » of cytosolic glutamine synthetase at the transcriptional to post-translational levels is key to the establishment of a specific physiological role for each isoenzyme. The diverse physiological roles of cytosolic glutamine synthetase isoenzymes are important in relation to current agricultural and ecological issues.« less

Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave Data

NASA Technical Reports Server (NTRS)

Bolten, John D.; Mladenova, Iliana E.; Crow, Wade; De Jeu, Richard

2016-01-01

A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.

Modeling Gross Primary Production of Agro-Forestry Ecosystems by Assimilation of Satellite-Derived Information in a Process-Based Model

PubMed Central

Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

2009-01-01

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale. PMID:22399948

Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model.

PubMed

Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

2009-01-01

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

Data Assimilation in the ADAPT Photospheric Flux Transport Model

DOE PAGES

Hickmann, Kyle S.; Godinez, Humberto C.; Henney, Carl J.; ...

2015-03-17

Global maps of the solar photospheric magnetic flux are fundamental drivers for simulations of the corona and solar wind and therefore are important predictors of geoeffective events. However, observations of the solar photosphere are only made intermittently over approximately half of the solar surface. The Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model uses localized ensemble Kalman filtering techniques to adjust a set of photospheric simulations to agree with the available observations. At the same time, this information is propagated to areas of the simulation that have not been observed. ADAPT implements a local ensemble transform Kalman filter (LETKF)more » to accomplish data assimilation, allowing the covariance structure of the flux-transport model to influence assimilation of photosphere observations while eliminating spurious correlations between ensemble members arising from a limited ensemble size. We give a detailed account of the implementation of the LETKF into ADAPT. Advantages of the LETKF scheme over previously implemented assimilation methods are highlighted.« less

The role of branch architecture in assimilate production and partitioning: the example of apple (Malus domestica)

PubMed Central

Fanwoua, Julienne; Bairam, Emna; Delaire, Mickael; Buck-Sorlin, Gerhard

2014-01-01

Understanding the role of branch architecture in carbon production and allocation is essential to gain more insight into the complex process of assimilate partitioning in fruit trees. This mini review reports on the current knowledge of the role of branch architecture in carbohydrate production and partitioning in apple. The first-order carrier branch of apple illustrates the complexity of branch structure emerging from bud activity events and encountered in many fruit trees. Branch architecture influences carbon production by determining leaf exposure to light and by affecting leaf internal characteristics related to leaf photosynthetic capacity. The dynamics of assimilate partitioning between branch organs depends on the stage of development of sources and sinks. The sink strength of various branch organs and their relative positioning on the branch also affect partitioning. Vascular connections between branch organs determine major pathways for branch assimilate transport. We propose directions for employing a modeling approach to further elucidate the role of branch architecture on assimilate partitioning. PMID:25071813

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.

Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability using High-Resolution Cloud Observations

NASA Astrophysics Data System (ADS)

Norris, P. M.; da Silva, A. M., Jr.

2016-12-01

Norris and da Silva recently published a method to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation (CDA). The gridcolumn model includes assumed-PDF intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used are MODIS cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases 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 is not gradient-based and allows 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. The new approach not only significantly reduces mean and standard deviation biases with respect to the assimilated observables, but also improves the simulated rotational-Ramman scattering cloud optical centroid pressure against independent (non-assimilated) retrievals from the OMI instrument. One obvious difficulty for the method, and other CDA methods, is the lack of information content in passive cloud observables on cloud vertical structure, beyond cloud-top and thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard is helpful, better honoring inversion structures in the background state.

Impact of variational assimilation using multivariate background error covariances on the simulation of monsoon depressions over India

NASA Astrophysics Data System (ADS)

Dhanya, M.; Chandrasekar, A.

2016-02-01

The background error covariance structure influences a variational data assimilation system immensely. The simulation of a weather phenomenon like monsoon depression can hence be influenced by the background correlation information used in the analysis formulation. The Weather Research and Forecasting Model Data assimilation (WRFDA) system includes an option for formulating multivariate background correlations for its three-dimensional variational (3DVar) system (cv6 option). The impact of using such a formulation in the simulation of three monsoon depressions over India is investigated in this study. Analysis and forecast fields generated using this option are compared with those obtained using the default formulation for regional background error correlations (cv5) in WRFDA and with a base run without any assimilation. The model rainfall forecasts are compared with rainfall observations from the Tropical Rainfall Measurement Mission (TRMM) and the other model forecast fields are compared with a high-resolution analysis as well as with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis. The results of the study indicate that inclusion of additional correlation information in background error statistics has a moderate impact on the vertical profiles of relative humidity, moisture convergence, horizontal divergence and the temperature structure at the depression centre at the analysis time of the cv5/cv6 sensitivity experiments. Moderate improvements are seen in two of the three depressions investigated in this study. An improved thermodynamic and moisture structure at the initial time is expected to provide for improved rainfall simulation. The results of the study indicate that the skill scores of accumulated rainfall are somewhat better for the cv6 option as compared to the cv5 option for at least two of the three depression cases studied, especially at the higher threshold levels. Considering the importance of utilising improved flow-dependent correlation structures for efficient data assimilation, the need for more studies on the impact of background error covariances is obvious.

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.

Anaerobic Metabolism in the N-Limited Green Alga Selenastrum minutum1

PubMed Central

Vanlerberghe, Greg C.; Turpin, David H.

1990-01-01

The green alga Selenastrum minutum (Naeg.) Collins is able to assimilate NH4+ in the dark under anaerobic conditions (GC Vanlerberghe, AK Horsey, HG Weger, DH Turpin [1989] Plant Physiol 91: 1551-1557). In the present study, analysis of metabolites following addition of NH4+ to cells acclimated to anaerobic conditions has shown the following. There was a transient decline in adenylate energy charge from 0.6 to 0.4 followed by a recovery back to ~0.6. This was accompanied by a rapid increase in pyruvate/phosphoenolpyruvate and fructose-1,6-bisphosphate/fructose-6-phosphate ratios indicating activation of pyruvate kinase and 6-phosphofructokinase, respectively. There was also an increase in fructose-2,6-bisphosphate, which, since this alga lacks pyrophosphate dependent 6-phosphofructokinase can be inferred to inhibit gluconeogenic fructose-1,6-bisphosphatase. These changes resulted in an increase in the rate of anaerobic starch breakdown. Anaerobic NH4+ assimilation also resulted in a two-fold increase in the rate of production of the major fermentative end-products in this alga, d-lactate and ethanol. There was no change in the rate of accumulation of the fermentative end product succinate but malate accumulated under anoxia during NH4+ assimilation. A rapid increase in Gln and decline in Glu indicates that primary NH4+ assimilation under anoxia was via glutamine synthetase-glutamate synthase. Almost all N assimilated under these conditions was sequestered in alanine. These results allow us to propose a model for the regulation of carbon metabolism during anaerobic NH4+ assimilation. PMID:16667806

Ecological Assimilation of Land and Climate Observations - the EALCO model

NASA Astrophysics Data System (ADS)

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

2004-05-01

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

Initialization and simulation of a landfalling typhoon using a variational bogus mapped data assimilation (BMDA)

NASA Astrophysics Data System (ADS)

Zhao, Y.; Wang, B.; Wang, Y.

2007-12-01

Recently, a new data assimilation method called “3-dimensional variational data assimilation of mapped observation (3DVM)” has been developed by the authors. We have shown that the new method is very efficient and inexpensive compared with its counterpart 4-dimensional variational data assimilation (4DVar). The new method has been implemented into the Penn State/NCAR mesoscale model MM5V1 (MM5_3DVM). In this study, we apply the new method to the bogus data assimilation (BDA) available in the original MM5 with the 4DVar. By the new approach, a specified sea-level pressure (SLP) field (bogus data) is incorporated into MM5 through the 3DVM (for convenient, we call it variational bogus mapped data assimilation - BMDA) instead of the original 4DVar data assimilation. To demonstrate the effectiveness of the new 3DVM method, initialization and simulation of a landfalling typhoon - typhoon Dan (1999) over the western North Pacific with the new method are compared with that with its counterpart 4DVar in MM5. Results show that the initial structure and the simulated intensity and track are improved more significantly using 3DVM than 4DVar. Sensitivity experiments also show that the simulated typhoon track and intensity are more sensitive to the size of the assimilation window in the 4DVar than that in the 3DVM. Meanwhile, 3DVM takes much less computing cost than its counterpart 4DVar for a given time window.

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

NASA Astrophysics Data System (ADS)

Penenko, Alexey; Penenko, Vladimir

2014-05-01

Contact concentration measurement data assimilation problem is considered for convection-diffusion-reaction models originating from the atmospheric chemistry study. High dimensionality of models imposes strict requirements on the computational efficiency of the algorithms. Data assimilation is carried out within the variation approach on a single time step of the approximated model. A control function is introduced into the source term of the model to provide flexibility for data assimilation. This function is evaluated as the minimum of the target functional that connects its norm to a misfit between measured and model-simulated data. In the case mathematical model acts as a natural Tikhonov regularizer for the ill-posed measurement data inversion problem. This provides flow-dependent and physically-plausible structure of the resulting analysis and reduces a need to calculate model error covariance matrices that are sought within conventional approach to data assimilation. The advantage comes at the cost of the adjoint problem solution. This issue is solved within the frameworks of splitting-based realization of the basic convection-diffusion-reaction model. The model is split with respect to physical processes and spatial variables. A contact measurement data is assimilated on each one-dimensional convection-diffusion splitting stage. In this case a computationally-efficient direct scheme for both direct and adjoint problem solution can be constructed based on the matrix sweep method. Data assimilation (or regularization) parameter that regulates ratio between model and data in the resulting analysis is obtained with Morozov discrepancy principle. For the proper performance the algorithm takes measurement noise estimation. In the case of Gaussian errors the probability that the used Chi-squared-based estimate is the upper one acts as the assimilation parameter. A solution obtained can be used as the initial guess for data assimilation algorithms that assimilate outside the splitting stages and involve iterations. Splitting method stage that is responsible for chemical transformation processes is realized with the explicit discrete-analytical scheme with respect to time. The scheme is based on analytical extraction of the exponential terms from the solution. This provides unconditional positive sign for the evaluated concentrations. Splitting-based structure of the algorithm provides means for efficient parallel realization. The work is partially supported by the Programs No 4 of Presidium RAS and No 3 of Mathematical Department of RAS, by RFBR project 11-01-00187 and Integrating projects of SD RAS No 8 and 35. Our studies are in the line with the goals of COST Action ES1004.

Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain

NASA Astrophysics Data System (ADS)

Gruber, A.; Crow, W. T.; Dorigo, W. A.

2018-02-01

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.

Mesoscale Ionospheric Prediction

DTIC Science & Technology

2006-09-30

Mesoscale Ionospheric Prediction Gary S. Bust 10000 Burnet Austin Texas, 78758 phone: (512) 835-3623 fax: (512) 835-3808 email: gbust...time-evolving non-linear numerical model of the mesoscale ionosphere , second to couple the mesoscale model to a mesoscale data assimilative analysis...third to use the new data-assimilative mesoscale model to investigate ionospheric structure and plasma instabilities, and fourth to apply the data

Adaptive changes in photosynthetic performance and secondary metabolites during white dead nettle micropropagation.

PubMed

Kapchina-Toteva, V; Dimitrova, M A; Stefanova, M; Koleva, D; Kostov, K; Yordanova, Zh P; Stefanov, D; Zhiponova, M K

2014-09-15

The white dead nettle, Lamium album L., is an herb that has been successfully cultivated under in vitro conditions. The L. album micropropagation system offers a combination of factors (light intensity, temperature, carbon dioxide (CO2) level, humidity) that are limiting for plant growth and bioactive capacity. To get a better understanding of the mechanism of plant acclimation towards environmental changes, we performed a comparative investigation on primary and secondary metabolism in fully expanded L. album leaves during the consecutive growth in in situ, in vitro, and ex vitro conditions. Although the genetic identity was not affected, structural and physiological deviations were observed, and the level of bioactive compounds was modified. During in vitro cultivation, the L. album leaves became thinner with unaffected overall leaf organization, but with a reduced number of palisade mesophyll layers. Structural deviation of the thylakoid membrane system was detected. In addition, the photosystem 2 (PS2) electron transport was retarded, and the plants were more vulnerable to light damage as indicated by the decreased photoprotection ability estimated by fluorescence parameters. The related CO2 assimilation and transpiration rates were subsequently reduced, as were the content of essential oils and phenolics. Transfer of the plants ex vitro did not increase the number of palisade numbers, but the chloroplast structure and PS2 functionality were recovered. Strikingly, the rates of CO2 assimilation and transpiration were increased compared to in situ control plants. While the phenolics content reached normal levels during ex vitro growth, the essential oils remained low. Overall, our study broadens the understanding about the nature of plant responses towards environmental conditions. Copyright © 2014 Elsevier GmbH. All rights reserved.

Assimilation of seasonal chlorophyll and nutrient data into an adjoint three-dimensional ocean carbon cycle model: Sensitivity analysis and ecosystem parameter optimization

NASA Astrophysics Data System (ADS)

Tjiputra, Jerry F.; Polzin, Dierk; Winguth, Arne M. E.

2007-03-01

An adjoint method is applied to a three-dimensional global ocean biogeochemical cycle model to optimize the ecosystem parameters on the basis of SeaWiFS surface chlorophyll observation. We showed with identical twin experiments that the model simulated chlorophyll concentration is sensitive to perturbation of phytoplankton and zooplankton exudation, herbivore egestion as fecal pellets, zooplankton grazing, and the assimilation efficiency parameters. The assimilation of SeaWiFS chlorophyll data significantly improved the prediction of chlorophyll concentration, especially in the high-latitude regions. Experiments that considered regional variations of parameters yielded a high seasonal variance of ecosystem parameters in the high latitudes, but a low variance in the tropical regions. These experiments indicate that the adjoint model is, despite the many uncertainties, generally capable to optimize sensitive parameters and carbon fluxes in the euphotic zone. The best fit regional parameters predict a global net primary production of 36 Pg C yr-1, which lies within the range suggested by Antoine et al. (1996). Additional constraints of nutrient data from the World Ocean Atlas showed further reduction in the model-data misfit and that assimilation with extensive data sets is necessary.

Improving Reanalyses Using TRMM and SSM/I-Derived Precipitation and Total Precipitable Water Observations

NASA Technical Reports Server (NTRS)

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

1999-01-01

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of rainfall and total precipitable water (TPW) observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve these fields in reanalyses. The DAO has developed a "1+1"D procedure to assimilate 6-hr averaged rainfall and TPW into the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS. The "1+1" designation refers to one spatial dimension plus one temporal dimension. The scheme minimizes the least-square differences between the satellite-retrieved rain rates and those produced by the column model over the 6-hr analysis window. The control variables are analysis increments of moisture within the Incremental Analysis Update (IAU) framework of the GEOS DAS. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but differs in its choice of the control variable. Instead of estimating the initial condition at the beginning of the assimilation cycle, it estimates the constant IAU forcing applied over a 6-hr assimilation cycle. In doing so, it imposes the forecast model as a weak constraint in a manner similar to the variational continuous assimilation techniques. We present results from an experiment in which the observed rain rate and TPW are assumed to be "perfect". They show that assimilating the TMI and SSM/I-derived surface precipitation and TPW observations improves not only the precipitation and moisture fields but also key climate parameters directly linked to convective activities such as clouds, the outgoing longwave radiation, and the large-scale circulation in the tropics. In particular, assimilating these data types reduce the state-dependent systematic errors in the assimilated products. The improved analysis also leads to a better short-range forecast, but the impact is modest compared with improvements in the time-averaged fields. These results suggest that, in the presence of biases and other errors of the forecast model, it is possible to improve the time-averaged "climate content" in the assimilated data without comparable improvements in the short-range forecast skill. Results of this experiment provide a useful benchmark for evaluating error covariance models for optimal use of these data types.

Methyl Jasmonate Alleviates Cadmium-Induced Photosynthetic Damages through Increased S-Assimilation and Glutathione Production in Mustard

PubMed Central

Per, Tasir S.; Khan, Nafees A.; Masood, Asim; Fatma, Mehar

2016-01-01

The effect of methyl jasmonate (MeJA) in mitigation of 50 μM cadmium (Cd) toxicity on structure and function of photosynthetic apparatus in presence or absence of 1.0 mM SO42– was investigated in mustard (Brassica juncea L. cv. Ro Agro 4001) at 30 days after sowing. Plants exhibited increased oxidative stress, impaired photosynthetic function when grown with Cd, but MeJA in presence of sulfur (S) more prominently ameliorated Cd effects through increased S-assimilation and production of reduced glutathione (GSH) and promoted photosynthetic functions. The transmission electron microscopy showed that MeJA protected chloroplast structure against Cd-toxicity. The use of GSH biosynthetic inhibitor, buthionine sulfoximine (BSO) substantiated the findings that ameliorating effect of MeJA was through GSH production. MeJA could not alleviate Cd effects when BSO was used due to unavailability of GSH even with the input of S. The study shows that MeJA regulates S-assimilation and GSH production for protection of structure and function of photosynthetic apparatus in mustard plants under Cd stress. PMID:28066485

Light Regimes Shape Utilization of Extracellular Organic C and N in a Cyanobacterial Biofilm

PubMed Central

Stuart, Rhona K.; Mayali, Xavier; Boaro, Amy A.; Zemla, Adam; Everroad, R. Craig; Nilson, Daniel; Weber, Peter K.; Lipton, Mary; Bebout, Brad M.; Pett-Ridge, Jennifer

2016-01-01

ABSTRACT Although it is becoming clear that many microbial primary producers can also play a role as organic consumers, we know very little about the metabolic regulation of photoautotroph organic matter consumption. Cyanobacteria in phototrophic biofilms can reuse extracellular organic carbon, but the metabolic drivers of extracellular processes are surprisingly complex. We investigated the metabolic foundations of organic matter reuse by comparing exoproteome composition and incorporation of 13C-labeled and 15N-labeled cyanobacterial extracellular organic matter (EOM) in a unicyanobacterial biofilm incubated using different light regimes. In the light and the dark, cyanobacterial direct organic C assimilation accounted for 32% and 43%, respectively, of all organic C assimilation in the community. Under photosynthesis conditions, we measured increased excretion of extracellular polymeric substances (EPS) and proteins involved in micronutrient transport, suggesting that requirements for micronutrients may drive EOM assimilation during daylight hours. This interpretation was supported by photosynthesis inhibition experiments, in which cyanobacteria incorporated N-rich EOM-derived material. In contrast, under dark, C-starved conditions, cyanobacteria incorporated C-rich EOM-derived organic matter, decreased excretion of EPS, and showed an increased abundance of degradative exoproteins, demonstrating the use of the extracellular domain for C storage. Sequence-structure modeling of one of these exoproteins predicted a specific hydrolytic activity that was subsequently detected, confirming increased EOM degradation in the dark. Associated heterotrophic bacteria increased in abundance and upregulated transport proteins under dark relative to light conditions. Taken together, our results indicate that biofilm cyanobacteria are successful competitors for organic C and N and that cyanobacterial nutrient and energy requirements control the use of EOM. PMID:27353754

Light Regimes Shape Utilization of Extracellular Organic C and N in a Cyanobacterial Biofilm

DOE PAGES

Stuart, Rhona K.; Mayali, Xavier; Boaro, Amy A.; ...

2016-06-28

Here it is becoming clear that many microbial primary producers can also play a role as organic consumers, we know very little about the metabolic regulation of photoautotroph organic matter consumption. Cyanobacteria in phototrophic biofilms can reuse extracellular organic carbon, but the metabolic drivers of extracellular processes are surprisingly complex. We investigated the metabolic foundations of organic matter reuse by comparing exoproteome composition and incorporation of 13C-labeled and 15N-labeled cyanobacterial extracellular organic matter (EOM) in a unicyanobacterial biofilm incubated using different light regimes. In the light and the dark, cyanobacterial direct organic C assimilation accounted for 32% and 43%, respectively,more » of all organic C assimilation in the community. Under photosynthesis conditions, we measured increased excretion of extracellular polymeric substances (EPS) and proteins involved in micronutrient transport, suggesting that requirements for micronutrients may drive EOM assimilation during daylight hours. This interpretation was supported by photosynthesis inhibition experiments, in which cyanobacteria incorporated N-rich EOM-derived material. In contrast, under dark, C-starved conditions, cyanobacteria incorporated C-rich EOM-derived organic matter, decreased excretion of EPS, and showed an increased abundance of degradative exoproteins, demonstrating the use of the extracellular domain for C storage. Sequence-structure modeling of one of these exoproteins predicted a specific hydrolytic activity that was subsequently detected, confirming increased EOM degradation in the dark. Associated heterotrophic bacteria increased in abundance and upregulated transport proteins under dark relative to light conditions. Taken together, our results indicate that biofilm cyanobacteria are successful competitors for organic C and N and that cyanobacterial nutrient and energy requirements control the use of EOM.« less

A mechanistic modeling and data assimilation framework for Mojave Desert ecohydrology

USGS Publications Warehouse

Ng, Gene-Hua Crystal.; Bedford, David; Miller, David

2014-01-01

This study demonstrates and addresses challenges in coupled ecohydrological modeling in deserts, which arise due to unique plant adaptations, marginal growing conditions, slow net primary production rates, and highly variable rainfall. We consider model uncertainty from both structural and parameter errors and present a mechanistic model for the shrub Larrea tridentata (creosote bush) under conditions found in the Mojave National Preserve in southeastern California (USA). Desert-specific plant and soil features are incorporated into the CLM-CN model by Oleson et al. (2010). We then develop a data assimilation framework using the ensemble Kalman filter (EnKF) to estimate model parameters based on soil moisture and leaf-area index observations. A new implementation procedure, the “multisite loop EnKF,” tackles parameter estimation difficulties found to affect desert ecohydrological applications. Specifically, the procedure iterates through data from various observation sites to alleviate adverse filter impacts from non-Gaussianity in small desert vegetation state values. It also readjusts inconsistent parameters and states through a model spin-up step that accounts for longer dynamical time scales due to infrequent rainfall in deserts. Observation error variance inflation may also be needed to help prevent divergence of estimates from true values. Synthetic test results highlight the importance of adequate observations for reducing model uncertainty, which can be achieved through data quality or quantity.

Ceiling effect in EMR system assimilation: a multiple case study in primary care family practices.

PubMed

Trudel, Marie-Claude; Marsan, Josianne; Paré, Guy; Raymond, Louis; Ortiz de Guinea, Ana; Maillet, Éric; Micheneau, Thomas

2017-04-20

There has been indisputable growth in adoption of electronic medical record (EMR) systems in the recent years. However, physicians' progress in using these systems has stagnated when measured with maturity scales. While this so-called ceiling effect has been observed and its consequences described in previous studies, there is a paucity of research on the elements that could explain such an outcome. We first suggest that in the context of EMR systems we are in presence of a "tiered ceiling effect" and then we show why such phenomenon occurs. We conducted in-depth case studies in three primary care medical practices in Canada where physicians had been using EMR systems for 3 years or more. A total of 37 semi-structured interviews were conducted with key informants: family physicians (about half of the interviews), nurses, secretaries, and administrative managers. Additional information was obtained through notes taken during observations of users interacting with their EMR systems and consultation of relevant documents at each site. We used abductive reasoning to infer explanations of the observed phenomenon by going back and forth between the case data and conceptual insights. Our analysis shows that a ceiling effect has taken place in the three clinics. We identified a set of conditions preventing the users from overcoming the ceiling. In adopting an EMR system, all three clinics essentially sought improved operational efficiency. This had an influence on the criteria used to assess the systems available on the market and eventually led to the adoption of a system that met the specified criteria without being optimal. Later, training sessions focussed on basic functionalities that minimally disturbed physicians' habits while helping their medical practices become more efficient. Satisfied with the outcome of their system use, physicians were likely to ignore more advanced EMR system functionalities. This was because their knowledge about EMR systems came almost exclusively from a single source of information: their EMR system vendors. This knowledge took the form of interpretations of what the innovation was (know-what), with little consideration of the rationales for innovation adoption (know-why) or hands-on strategies for adopting, implementing and assimilating the innovation in the organization (know-how). This paper provides a holistic view of the technological innovation process in primary care and contends that limited learning, satisficing behaviours and organizational inertia are important factors leading to the ceiling effect frequently experienced in the EMR system assimilation phase.

Effects of oligotrophication on primary production in peri-alpine lakes

NASA Astrophysics Data System (ADS)

Finger, David; Wüest, Alfred; Bossard, Peter

2013-08-01

During the second half of the 20th century untreated sewage released from housing and industry into natural waters led to a degradation of many freshwater lakes and reservoirs worldwide. In order to mitigate eutrophication, wastewater treatment plants, including Fe-induced phosphorus precipitation, were implemented throughout the industrialized world, leading to reoligotrophication in many freshwater lakes. To understand and assess the effects of reoligotrophication on primary productivity, we analyzed 28 years of 14C assimilation rates, as well as other biotic and abiotic parameters, such as global radiation, nutrient concentrations and plankton densities in peri-alpine Lake Lucerne, Switzerland. Using a simple productivity-light relationship, we estimated continuous primary production and discussed the relation between productivity and observed limnological parameters. Furthermore, we assessed the uncertainty of our modeling approach based on monthly 14C assimilation measurements using Monte Carlo simulations. Results confirm that monthly sampling of productivity is sufficient for identifying long-term trends in productivity and that conservation management has successfully improved water quality during the past three decades via reducing nutrients and primary production in the lake. However, even though nutrient concentrations have remained constant in recent years, annual primary production varies significantly from year to year. Despite the fact that nutrient concentrations have decreased by more than an order of magnitude, primary production has decreased only slightly. These results suggest that primary production correlates well to nutrients availability but meteorological conditions lead to interannual variability regardless of the trophic status of the lake. Accordingly, in oligotrophic freshwaters meteorological forcing may reduce productivity impacting on the entire food chain of the ecosystem.

The Use of Structured Social Interaction with the Culture-General Assimilator To Increase Cognitive Problem Solving about Intercultural Interactions in an Ethnically Diverse Population.

ERIC Educational Resources Information Center

Ilola, Lisa Marie

This study describes an intercultural learning program combining cooperative learning with critical incidents drawn from the culture-general assimilator developed by Brislin. The training program was adapted to school teachers, a population already identified as a high-risk group because of the frequency and unpredictability of the intercultural…

Short-Term Treatment with the Urease Inhibitor N-(n-Butyl) Thiophosphoric Triamide (NBPT) Alters Urea Assimilation and Modulates Transcriptional Profiles of Genes Involved in Primary and Secondary Metabolism in Maize Seedlings

PubMed Central

Zanin, Laura; Venuti, Silvia; Tomasi, Nicola; Zamboni, Anita; De Brito Francisco, Rita M.; Varanini, Zeno; Pinton, Roberto

2016-01-01

To limit nitrogen (N) losses from the soil, it has been suggested to provide urea to crops in conjunction with the urease inhibitor N-(n-butyl) thiophosphoric triamide (NBPT). However, recent studies reported that NBPT affects urea uptake and urease activity in plants. To shed light on these latter aspects, the effects of NBPT were studied analysing transcriptomic and metabolic changes occurring in urea-fed maize seedlings after a short-term exposure to the inhibitor. We provide evidence that NBPT treatment led to a wide reprogramming of plant metabolism. NBPT inhibited the activity of endogenous urease limiting the release and assimilation of ureic-ammonium, with a simultaneous accumulation of urea in plant tissues. Furthermore, NBPT determined changes in the glutamine, glutamate, and asparagine contents. Microarray data indicate that NBPT affects ureic-N assimilation and primary metabolism, such as glycolysis, TCA cycle, and electron transport chain, while activates the phenylalanine/tyrosine-derivative pathway. Moreover, the expression of genes relating to the transport and complexation of divalent metals was strongly modulated by NBPT. Data here presented suggest that when NBPT is provided in conjunction with urea an imbalance between C and N compounds might occur in plant cells. Under this condition, root cells also seem to activate a response to maintain the homeostasis of some micronutrients. PMID:27446099

New Perspectives on Immigrant Adaptation.

ERIC Educational Resources Information Center

Stepick, Alex

1983-01-01

Explores the assimilation and acculturation of immigrants into American society. Suggests that while adaptation is a product of various factors, it is less dependent on individual traits than on whether immigrants are incorporated into the primary, secondary, and enclave sectors of the economy. (Author/MJL)

Ocean Thermal and Color Evolution During the 1997/1998 ENSO Event

NASA Technical Reports Server (NTRS)

Rienecker, Michele

1998-01-01

A reduced gravity primitive equation modeling and assimilation system is used to study the evolution of the tropical Pacific during the 1997/1998 ENSO cycle. The modeling/assimilation scheme ingests satellite altimeter data and TAO temperature profiles and uses SSM/I satellite derived winds as surface boundary forcing. The four-dimensional structure of the upper ocean circulation structure will be compared against available in situ observations across the Pacific basin. In particular, variability near the Galapagos Islands will be highlighted during the spring of 1998 when phytoplankton concentrations were observed to increase a hundred-fold over a two week period.

Nitrate removal in stream ecosystems measured by 15N addition experiments: Total uptake

USGS Publications Warehouse

Hall, R.O.; Tank, J.L.; Sobota, D.J.; Mulholland, P.J.; O'Brien, J. M.; Dodds, W.K.; Webster, J.R.; Valett, H.M.; Poole, G.C.; Peterson, B.J.; Meyer, J.L.; McDowell, W.H.; Johnson, S.L.; Hamilton, S.K.; Grimm, N. B.; Gregory, S.V.; Dahm, Clifford N.; Cooper, L.W.; Ashkenas, L.R.; Thomas, S.M.; Sheibley, R.W.; Potter, J.D.; Niederlehner, B.R.; Johnson, L.T.; Helton, A.M.; Crenshaw, C.M.; Burgin, A.J.; Bernot, M.J.; Beaulieu, J.J.; Arangob, C.P.

2009-01-01

We measured uptake length of 15NO-3 in 72 streams in eight regions across the United States and Puerto Rico to develop quantitative predictive models on controls of NO-3 uptake length. As part of the Lotic Intersite Nitrogen eXperiment II project, we chose nine streams in each region corresponding to natural (reference), suburban-urban, and agricultural land uses. Study streams spanned a range of human land use to maximize variation in NO-3 concentration, geomorphology, and metabolism. We tested a causal model predicting controls on NO-3 uptake length using structural equation modeling. The model included concomitant measurements of ecosystem metabolism, hydraulic parameters, and nitrogen concentration. We compared this structural equation model to multiple regression models which included additional biotic, catchment, and riparian variables. The structural equation model explained 79% of the variation in log uptake length (S Wtot). Uptake length increased with specific discharge (Q/w) and increasing NO-3 concentrations, showing a loss in removal efficiency in streams with high NO-3 concentration. Uptake lengths shortened with increasing gross primary production, suggesting autotrophic assimilation dominated NO-3 removal. The fraction of catchment area as agriculture and suburban-urban land use weakly predicted NO-3 uptake in bivariate regression, and did improve prediction in a set of multiple regression models. Adding land use to the structural equation model showed that land use indirectly affected NO-3 uptake lengths via directly increasing both gross primary production and NO-3 concentration. Gross primary production shortened SWtot, while increasing NO-3 lengthened SWtot resulting in no net effect of land use on NO- 3 removal. ?? 2009.

Assimilation of the Microwave Limb Sounder Radiances

NASA Technical Reports Server (NTRS)

Wargan, K.; Read, W.; Livesey, N.; Wagner, P.; Nguyen. H.; Pawson, S.

2012-01-01

It has been shown that the assimilation of limb-sounder data can significantly improve the representation of ozone in NASA's GEOS Data Assimilation Systems (GEOS-DAS), particularly in the stratosphere. The studies conducted so far utilized retrieved data from the MIPAS, POAM, ILAS and EOS Microwave Limb Sounder (EOS MLS) instruments. Direct assimilation of the radiance data can be seen as the natural next step to those studies. The motivation behind working with radiances is twofold. First, retrieval algorithms use a priori data which are either climatological or are obtained from previous analyses. This introduces additional uncertainty and, in some cases, may lead to "self-contamination"- when the a priori is taken from the same assimilation system in which subsequently ingests the retrieved observations. Second, radiances can be available in near real time thus providing an opportunity for operational assimilation, which could help improve the use of infrared radiance instruments from operational satellite instruments. In this presentation we summarize our ongoing work on an implementation of the assimilation of EOS MLS radiances into the GEOS-5 DAS. This work focuses on assimilation of band 7 brightness temperatures which are sensitive to ozone. Our implementation uses the MLS Callable Forward Model developed by the MLS team at NASA JPL as the observation operator. We will describe our approach and recent results which are not yet final. In particular, we will demonstrate that this approach has a potential to improve the vertical structure of ozone in the lower tropical stratosphere as compared with the retrieved MLS product. We will discuss the computational efficiency of this implementation.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

[Simulating of carbon fluxes in bamboo forest ecosystem using BEPS model based on the LAI assimilated with Dual Ensemble Kalman Filter].

PubMed

Li, Xue Jian; Mao, Fang Jie; Du, Hua Qiang; Zhou, Guo Mo; Xu, Xiao Jun; Li, Ping Heng; Liu, Yu Li; Cui, Lu

2016-12-01

LAI is one of the most important observation data in the research of carbon cycle of forest ecosystem, and it is also an important parameter to drive process-based ecosystem model. The Moso bamboo forest (MBF) and Lei bamboo forest (LBF) were selected as the study targets. Firstly, the MODIS LAI time series data during 2014-2015 was assimilated with Dual Ensemble Kalman Filter method. Secondly, the high quality assimilated MBF LAI and LBF LAI were used as input dataset to drive BEPS model for simulating the gross primary productivity (GPP), net ecosystem exchange (NEE) and total ecosystem respiration (TER) of the two types of bamboo forest ecosystem, respectively. The modeled carbon fluxes were evaluated by the observed carbon fluxes data, and the effects of different quality LAI inputs on carbon cycle simulation were also studied. The LAI assimilated using Dual Ensemble Kalman Filter of MBF and LBF were significantly correlated with the observed LAI, with high R 2 of 0.81 and 0.91 respectively, and lower RMSE and absolute bias, which represented the great improvement of the accuracy of MODIS LAI products. With the driving of assimilated LAI, the modeled GPP, NEE, and TER were also highly correlated with the flux observation data, with the R 2 of 0.66, 0.47, and 0.64 for MBF, respectively, and 0.66, 0.45, and 0.73 for LBF, respectively. The accuracy of carbon fluxes modeled with assimilated LAI was higher than that acquired by the locally adjusted cubic-spline capping method, in which, the accuracy of mo-deled NEE for MBF and LBF increased by 11.2% and 11.8% at the most degrees, respectively.

Assimilation of Diazotrophic Nitrogen into Pelagic Food Webs

PubMed Central

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

2013-01-01

The fate of diazotrophic nitrogen (ND) fixed by planktonic cyanobacteria in pelagic food webs remains unresolved, particularly for toxic cyanophytes that are selectively avoided by most herbivorous zooplankton. Current theory suggests that ND fixed during cyanobacterial blooms can enter planktonic food webs contemporaneously with peak bloom biomass via direct grazing of zooplankton on cyanobacteria or via the uptake of bioavailable ND (exuded from viable cyanobacterial cells) by palatable phytoplankton or microbial consortia. Alternatively, ND can enter planktonic food webs post-bloom following the remineralization of bloom detritus. Although the relative contribution of these processes to planktonic nutrient cycles is unknown, we hypothesized that assimilation of bioavailable ND (e.g., nitrate, ammonium) by palatable phytoplankton and subsequent grazing by zooplankton (either during or after the cyanobacterial bloom) would be the primary pathway by which ND was incorporated into the planktonic food web. Instead, in situ stable isotope measurements and grazing experiments clearly documented that the assimilation of ND by zooplankton outpaced assimilation by palatable phytoplankton during a bloom of toxic Nodularia spumigena Mertens. We identified two distinct temporal phases in the trophic transfer of ND from N. spumigena to the plankton community. The first phase was a highly dynamic transfer of ND to zooplankton with rates that covaried with bloom biomass while bypassing other phytoplankton taxa; a trophic transfer that we infer was routed through bloom-associated bacteria. The second phase was a slowly accelerating assimilation of the dissolved-ND pool by phytoplankton that was decoupled from contemporaneous variability in N. spumigena concentrations. These findings provide empirical evidence that ND can be assimilated and transferred rapidly throughout natural plankton communities and yield insights into the specific processes underlying the propagation of ND through pelagic food webs. PMID:23840744

Assimilation of diazotrophic nitrogen into pelagic food webs.

PubMed

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

2013-01-01

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

Assimilation of Cloud Information in Numerical Weather Prediction Model in Southwest China

NASA Astrophysics Data System (ADS)

HENG, Z.

2016-12-01

Based on the ARPS Data Analysis System (ADAS), Weather Research and Forecasting (WRF) model, simulation experiments from July 1st 2015 to August 1st 2015 are conducted in the region of Southwest China. In the assimilation experiment (EXP), datasets from surface observations are assimilated, cloud information from weather Doppler radar, Fengyun-2E (FY-2E) geostationary satellite are retrieved by using the complex cloud analysis scheme in the ADAS, to insert microphysical variables and adjust the humility structure in the initial condition. As a control run (CTL), datasets from surface observations are assimilated, but no cloud information is used in the ADAS. The simulation result of a rainstorm caused by the Southwest Vortex during 14-15 July 2015 shows that, the EXP run has a better capability in representing the shape and intensity of precipitation, especially the center of rainstorm. The one-month inter-comparison of the initial and prediction results between the EXP and CTL runs reveled that, EXP runs can present a more reasonable phenomenon of rain and get a higher score in the rain prediction. Keywords: NWP, rainstorm, Data assimilation

Remote sensing of ocean surface currents: a review of what is being observed and what is being assimilated

NASA Astrophysics Data System (ADS)

Isern-Fontanet, Jordi; Ballabrera-Poy, Joaquim; Turiel, Antonio; García-Ladona, Emilio

2017-10-01

Ocean currents play a key role in Earth's climate - they impact almost any process taking place in the ocean and are of major importance for navigation and human activities at sea. Nevertheless, their observation and forecasting are still difficult. First, no observing system is able to provide direct measurements of global ocean currents on synoptic scales. Consequently, it has been necessary to use sea surface height and sea surface temperature measurements and refer to dynamical frameworks to derive the velocity field. Second, the assimilation of the velocity field into numerical models of ocean circulation is difficult mainly due to lack of data. Recent experiments that assimilate coastal-based radar data have shown that ocean currents will contribute to increasing the forecast skill of surface currents, but require application in multidata assimilation approaches to better identify the thermohaline structure of the ocean. In this paper we review the current knowledge in these fields and provide a global and systematic view of the technologies to retrieve ocean velocities in the upper ocean and the available approaches to assimilate this information into ocean models.

Inferring biogeochemistry past: a millennial-scale multimodel assimilation of multiple paleoecological proxies.

NASA Astrophysics Data System (ADS)

Dietze, M.; Raiho, A.; Fer, I.; Dawson, A.; Heilman, K.; Hooten, M.; McLachlan, J. S.; Moore, D. J.; Paciorek, C. J.; Pederson, N.; Rollinson, C.; Tipton, J.

2017-12-01

The pre-industrial period serves as an essential baseline against which we judge anthropogenic impacts on the earth's systems. However, direct measurements of key biogeochemical processes, such as carbon, water, and nutrient cycling, are absent for this period and there is no direct way to link paleoecological proxies, such as pollen and tree rings, to these processes. Process-based terrestrial ecosystem models provide a way to make inferences about the past, but have large uncertainties and by themselves often fail to capture much of the observed variability. Here we investigate the ability to improve inferences about pre-industrial biogeochemical cycles through the formal assimilation of proxy data into multiple process-based models. A Tobit ensemble filter with explicit estimation of process error was run at five sites across the eastern US for three models (LINKAGES, ED2, LPJ-GUESS). In addition to process error, the ensemble accounted for parameter uncertainty, estimated through the assimilation of the TRY and BETY trait databases, and driver uncertainty, accommodated by probabilistically downscaling and debiasing CMIP5 GCM output then filtering based on paleoclimate reconstructions. The assimilation was informed by four PalEON data products, each of which includes an explicit Bayesian error estimate: (1) STEPPS forest composition estimated from fossil pollen; (2) REFAB aboveground biomass (AGB) estimated from fossil pollen; (3) tree ring AGB and woody net primary productivity (wNPP); and (4) public land survey composition, stem density, and AGB. By comparing ensemble runs with and without data assimilation we are able to assess the information contribution of the proxy data to constraining biogeochemical fluxes, which is driven by the combination of model uncertainty, data uncertainty, and the strength of correlation between observed and unobserved quantities in the model ensemble. To our knowledge this is the first attempt at multi-model data assimilation with terrestrial ecosystem models. Results from the data-model assimilation allow us to assess the consistency across models in post-assimilation inferences about indirectly inferred quantities, such as GPP, soil carbon, and the water budget.

Development Of A Data Assimilation Capability For RAPID

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Recent Advances in Ozone Data Assimilation at the GMAO - Towards a New Reanalysis

NASA Technical Reports Server (NTRS)

Krzysztof, Wargan; Pawson, S.; Nielsen, J. E.; Witte, J.; Douglass, A.; Strahan, S.; Joiner, J.; Bhartia, P. K.; Livesey, N.; Read, W.;

Assimilation and conversion of 3,4-benzpyrene by plants under sterile conditions

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

Durmishidze, S.V.; Devdariani, T.V.; Kavtaradze, L.K.

1974-01-01

In this article the authors discuss the results of the oxidative conversion of BP to various individual compounds in plant roots and leaves. The experiments were conducted on 14-day alfalfa plants (Medicago sativa), ryegrass (Lolium multiflorum), chick-pea (Cicer arientinum), cucumbers (Cucumis sativus), pumpkin (Cucurbita), orchard grass (Dactylis glomerata), and vetch (Vicia faba), grown under sterile conditions on Knop's nutrient medium. Labeled 1,2-/sup 14/C-BP was synthesized in several steps using phthalic and 1,2-/sup 14/C-acetic anhydrides as the starting materials. The results of the experiments showed that the roots and leaves of various plants assimilate BP and subject it to profound chemicalmore » transformations. The conversion products are transported from the roots to the leaves and from the leaves to the roots. Low-molecular weight compounds, in particular, organic acids, provided most radioactive. The distribution of the radioactivity of the low-molecular weight substances among the plant organs depends on the site of the primary assimilation of 1,2-/sup 14/C-BP. In the case of assimilation of BP by the roots, the most radioactive are the low-molecular weight compounds of the root themselves, while in the case of assimilation of BP by the leaves, the most radioactive are the low-molecular weight compounds of the leaves. The same pattern is observed in the distribution of radioactivity among the organs of plants in the case of organic acids.« less

Toward the assimilation of biogeochemical data in the CMEMS BIOMER coupled physical-biogeochemical operational system

NASA Astrophysics Data System (ADS)

Lamouroux, Julien; Testut, Charles-Emmanuel; Lellouche, Jean-Michel; Perruche, Coralie; Paul, Julien

2017-04-01

The operational production of data-assimilated biogeochemical state of the ocean is one of the challenging core projects of the Copernicus Marine Environment Monitoring Service. In that framework - and with the April 2018 CMEMS V4 release as a target - Mercator Ocean is in charge of improving the realism of its global ¼° BIOMER coupled physical-biogeochemical (NEMO/PISCES) simulations, analyses and re-analyses, and to develop an effective capacity to routinely estimate the biogeochemical state of the ocean, through the implementation of biogeochemical data assimilation. Primary objectives are to enhance the time representation of the seasonal cycle in the real time and reanalysis systems, and to provide a better control of the production in the equatorial regions. The assimilation of BGC data will rely on a simplified version of the SEEK filter, where the error statistics do not evolve with the model dynamics. The associated forecast error covariances are based on the statistics of a collection of 3D ocean state anomalies. The anomalies are computed from a multi-year numerical experiment (free run without assimilation) with respect to a running mean in order to estimate the 7-day scale error on the ocean state at a given period of the year. These forecast error covariances rely thus on a fixed-basis seasonally variable ensemble of anomalies. This methodology, which is currently implemented in the "blue" component of the CMEMS operational forecast system, is now under adaptation to be applied to the biogeochemical part of the operational system. Regarding observations - and as a first step - the system shall rely on the CMEMS GlobColour Global Ocean surface chlorophyll concentration products, delivered in NRT. The objective of this poster is to provide a detailed overview of the implementation of the aforementioned data assimilation methodology in the CMEMS BIOMER forecasting system. Focus shall be put on (1) the assessment of the capabilities of this data assimilation methodology to provide satisfying statistics of the model variability errors (through space-time analysis of dedicated representers of satellite surface Chla observations), (2) the dedicated features of the data assimilation configuration that have been implemented so far (e.g. log-transformation of the analysis state, multivariate Chlorophyll-Nutrient control vector, etc.) and (3) the assessment of the performances of this future operational data assimilation configuration.

Towards water vapor assimilation into mesoscale models for improved precipitation forecast

NASA Astrophysics Data System (ADS)

Demoz, B.; Whiteman, D.; Venable, D.; Joseph, E.

2006-05-01

Atmospheric water vapor plays a primary role in the life cycle of clouds, precipitation and is crucial in understanding many aspects of the water cycle. It is very important to short-range mesoscale and storm-scale weather prediction. Specifically, accurate characterization of water vapor at low levels is a necessary condition for quantitative precipitation forecast (QPF), the initiation of convection and various thermodynamic and microphysical processes in mesoscale severe weather systems. However, quantification of its variability (both temporal and spatial) and integration of high quality and high frequency water vapor profiles into mesoscale models have been challenging. We report on a conceptual proposal that attempts to 1) define approporiate lidar-based data and instrumentation required for mesoscale data assimilation and 2) a possible federated network of ground-based lidars that may be capable of acquiring such high resolution water vapor data sets and 3) a possible frame work of assimilation of the data into a mesoscale model.

Approach to Integrate Global-Sun Models of Magnetic Flux Emergence and Transport for Space Weather Studies

NASA Technical Reports Server (NTRS)

Mansour, Nagi N.; Wray, Alan A.; Mehrotra, Piyush; Henney, Carl; Arge, Nick; Godinez, H.; Manchester, Ward; Koller, J.; Kosovichev, A.; Scherrer, P.;

Genomic data assimilation for estimating hybrid functional Petri net from time-course gene expression data.

PubMed

Nagasaki, Masao; Yamaguchi, Rui; Yoshida, Ryo; Imoto, Seiya; Doi, Atsushi; Tamada, Yoshinori; Matsuno, Hiroshi; Miyano, Satoru; Higuchi, Tomoyuki

2006-01-01

We propose an automatic construction method of the hybrid functional Petri net as a simulation model of biological pathways. The problems we consider are how we choose the values of parameters and how we set the network structure. Usually, we tune these unknown factors empirically so that the simulation results are consistent with biological knowledge. Obviously, this approach has the limitation in the size of network of interest. To extend the capability of the simulation model, we propose the use of data assimilation approach that was originally established in the field of geophysical simulation science. We provide genomic data assimilation framework that establishes a link between our simulation model and observed data like microarray gene expression data by using a nonlinear state space model. A key idea of our genomic data assimilation is that the unknown parameters in simulation model are converted as the parameter of the state space model and the estimates are obtained as the maximum a posteriori estimators. In the parameter estimation process, the simulation model is used to generate the system model in the state space model. Such a formulation enables us to handle both the model construction and the parameter tuning within a framework of the Bayesian statistical inferences. In particular, the Bayesian approach provides us a way of controlling overfitting during the parameter estimations that is essential for constructing a reliable biological pathway. We demonstrate the effectiveness of our approach using synthetic data. As a result, parameter estimation using genomic data assimilation works very well and the network structure is suitably selected.

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.

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.

Forest canopy hydraulics

Treesearch

David R. Woodruff; Frederick C. Meinzer; Katherine A. McCulloh

2016-01-01

Water and carbon cycles are strongly coordinated and water availability is a primary limiting factor in many terrestrial ecosystems. Photosynthesis requires sufficient water supply to leaves and constraints on delivery at any point in the hydraulic continuum can lead to stomatal closure and reduced photosynthesis. Thus, maximizing water transport enhances assimilation...

Assimilating solar-induced chlorophyll fluorescence into the terrestrial biosphere model BETHY-SCOPE v1.0: model description and information content

NASA Astrophysics Data System (ADS)

Norton, Alexander J.; Rayner, Peter J.; Koffi, Ernest N.; Scholze, Marko

2018-04-01

The synthesis of model and observational information using data assimilation can improve our understanding of the terrestrial carbon cycle, a key component of the Earth's climate-carbon system. Here we provide a data assimilation framework for combining observations of solar-induced chlorophyll fluorescence (SIF) and a process-based model to improve estimates of terrestrial carbon uptake or gross primary production (GPP). We then quantify and assess the constraint SIF provides on the uncertainty in global GPP through model process parameters in an error propagation study. By incorporating 1 year of SIF observations from the GOSAT satellite, we find that the parametric uncertainty in global annual GPP is reduced by 73 % from ±19.0 to ±5.2 Pg C yr-1. This improvement is achieved through strong constraint of leaf growth processes and weak to moderate constraint of physiological parameters. We also find that the inclusion of uncertainty in shortwave down-radiation forcing has a net-zero effect on uncertainty in GPP when incorporated into the SIF assimilation framework. This study demonstrates the powerful capacity of SIF to reduce uncertainties in process-based model estimates of GPP and the potential for improving our predictive capability of this uncertain carbon flux.

Algal productivity and nitrate assimilation in an effluent dominated concrete lined stream

USGS Publications Warehouse

Kent, Robert; Belitz, Kenneth; Burton, Carmen

2005-01-01

This study examined algal productivity and nitrate assimilation in a 2.85 km reach of Cucamonga Creek, California, a concrete lined channel receiving treated municipal wastewater. Stream nitrate concentrations observed at two stations indicated nearly continuous loss throughout the diel study. Nitrate loss in the reach was approximately 11 mg/L/d or 1.0 g/m2/d as N, most of which occurred during daylight. The peak rate of nitrate loss (1.13 mg/l/hr) occurred just prior to an afternoon total CO2 depletion. Gross primary productivity, as estimated by a model using the observed differences in dissolved oxygen between the two stations, was 228 mg/L/d, or 21 g/m2/d as O2. The observed diel variations in productivity, nitrate loss, pH, dissolved oxygen, and CO2indicate that nitrate loss was primarily due to algal assimilation. The observed levels of productivity and nitrate assimilation were exceptionally high on a mass per volume basis compared to studies on other streams; these rates occurred because of the shallow stream depth. This study suggests that concrete‐lined channels can provide an important environmental service: lowering of nitrate concentrations similar to rates observed in biological treatment systems.

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.

Simulation of wheat growth and development based on organ-level photosynthesis and assimilate allocation.

PubMed

Evers, J B; Vos, J; Yin, X; Romero, P; van der Putten, P E L; Struik, P C

2010-05-01

Intimate relationships exist between form and function of plants, determining many processes governing their growth and development. However, in most crop simulation models that have been created to simulate plant growth and, for example, predict biomass production, plant structure has been neglected. In this study, a detailed simulation model of growth and development of spring wheat (Triticum aestivum) is presented, which integrates degree of tillering and canopy architecture with organ-level light interception, photosynthesis, and dry-matter partitioning. An existing spatially explicit 3D architectural model of wheat development was extended with routines for organ-level microclimate, photosynthesis, assimilate distribution within the plant structure according to organ demands, and organ growth and development. Outgrowth of tiller buds was made dependent on the ratio between assimilate supply and demand of the plants. Organ-level photosynthesis, biomass production, and bud outgrowth were simulated satisfactorily. However, to improve crop simulation results more efforts are needed mechanistically to model other major plant physiological processes such as nitrogen uptake and distribution, tiller death, and leaf senescence. Nevertheless, the work presented here is a significant step forwards towards a mechanistic functional-structural plant model, which integrates plant architecture with key plant processes.

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

NASA Astrophysics Data System (ADS)

Mitchell, K. E.

2006-12-01

The Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) applies several different analyses of observed precipitation in both the data assimilation and validation components of NCEP's global and regional numerical weather and climate prediction/analysis systems (including in NCEP global and regional reanalysis). This invited talk will survey these data assimilation and validation applications and methodologies, as well as the temporal frequency, spatial domains, spatial resolution, data sources, data density and data quality control in the precipitation analyses that are applied. Some of the precipitation analyses applied by EMC are produced by NCEP's Climate Prediction Center (CPC), while others are produced by the River Forecast Centers (RFCs) of the National Weather Service (NWS), or by automated algorithms of the NWS WSR-88D Radar Product Generator (RPG). Depending on the specific type of application in data assimilation or model forecast validation, the temporal resolution of the precipitation analyses may be hourly, daily, or pentad (5-day) and the domain may be global, continental U.S. (CONUS), or Mexico. The data sources for precipitation include ground-based gauge observations, radar-based estimates, and satellite-based estimates. The precipitation analyses over the CONUS are analyses of either hourly, daily or monthly totals of precipitation, and they are of two distinct types: gauge-only or primarily radar-estimated. The gauge-only CONUS analysis of daily precipitation utilizes an orographic-adjustment technique (based on the well-known PRISM precipitation climatology of Oregon State University) developed by the NWS Office of Hydrologic Development (OHD). The primary NCEP global precipitation analysis is the pentad CPC Merged Analysis of Precipitation (CMAP), which blends both gauge observations and satellite estimates. The presentation will include a brief comparison between the CMAP analysis and other global precipitation analyses by other institutions. Other global precipitation analyses produced by other methodologies are also used by EMC in certain applications, such as CPC's well-known satellite-IR based technique known as "GPI", and satellite-microwave based estimates from NESDIS or NASA. Finally, the presentation will cover the three assimilation methods used by EMC to assimilate precipitation data, including 1) 3D-VAR variational assimilation in NCEP's Global Data Assimilation System (GDAS), 2) direct insertion of precipitation-inferred vertical latent heating profiles in NCEP's N. American Data Assimilation System (NDAS) and its N. American Regional Reanalysis (NARR) counterpart, and 3) direct use of observed precipitation to drive the Noah land model component of NCEP's Global and N. American Land Data Assimilation Systems (GLDAS and NLDAS). In the applications of precipitation analyses in data assimilation at NCEP, the analyses are temporally disaggregated to hourly or less using time-weights calculated from A) either radar-based estimates or an analysis of hourly gauge-observations for the CONUS-domain daily precipitation analyses, or B) global model forecasts of 6-hourly precipitation (followed by linear interpolation to hourly or less) for the global CMAP precipitation analysis.

CUMULATE ROCKS ASSOCIATED WITH CARBONATE ASSIMILATION, HORTAVÆR COMPLEX, NORTH-CENTRAL NORWAY

NASA Astrophysics Data System (ADS)

Barnes, C. G.; Prestvik, T.; Li, Y.

2009-12-01

The Hortavær igneous complex intruded high-grade metamorphic rocks of the Caledonian Helgeland Nappe Complex at ca. 466 Ma. The complex is an unusual mafic-silicic layered intrusion (MASLI) because the principal felsic rock type is syenite and because the syenite formed in situ rather than by deep-seated partial melting of crustal rocks. Magma differentiation in the complex was by assimilation, primarily of calc-silicate rocks and melts with contributions from marble and semi-pelites, plus fractional crystallization. The effect of assimilation of calcite-rich rocks was to enhance stability of fassaitic clinopyroxene at the expense of olivine, which resulted in alkali-rich residual melts and lowering of silica activity. This combination of MASLI-style emplacement and carbonate assimilation produced three types of cumulate rocks: (1) Syenitic cumulates formed by liquid-crystal separation. As sheets of mafic magma were loaded on crystal-rich syenitic magma, residual liquid was expelled, penetrating the overlying mafic sheets in flame structures, and leaving a cumulate syenite. (2) Reaction cumulates. Carbonate assimilation, illustrated by a simple assimilation reaction: olivine + calcite + melt = clinopyroxene + CO2 resulted in cpx-rich cumulates such as clinopyroxenite, gabbro, and mela-monzodiorite, many of which contain igneous calcite. (3) Magmatic skarns. Calc-silicate host rocks underwent partial melting during assimilation, yielding a Ca-rich melt as the principal assimilated material and permitting extensive reaction with surrounding magma to form Kspar + cpx + garnet-rich ‘cumulate’ rocks. Cumulate types (2) and (3) do not reflect traditional views of cumulate rocks but instead result from a series of melt-present discontinuous (peritectic) reactions and partial melting of calc-silicate xenoliths. In the Hortavær complex, such cumulates are evident because of the distinctive peritectic cumulate assemblages. It is unclear whether assimilation of ‘normal’ silicate rocks results in peritectic assemblages, or whether they could be identified as such if they exist.

Mantle circulation models with variational data assimilation: Inferring past mantle flow and structure from plate motion histories and seismic tomography

NASA Astrophysics Data System (ADS)

Bunge, Hans-Peter

2002-08-01

Earth's mantle overturns itself about once every 200 Million years (myrs). Prima facie evidence for this overturn is the motion of tectonic plates at the surface of the Earth driving the geologic activity of our planet. Supporting evidence also comes from seismic tomograms of the Earth's interior that reveal the convective currents in remarkable clarity. Much has been learned about the physics of solid state mantle convection over the past two decades aided primarily by sophisticated computer simulations. Such simulations are reaching the threshold of fully resolving the convective system globally. In this talk we will review recent progress in mantle dynamics studies. We will then turn our attention to the fundamental question of whether it is possible to explicitly reconstruct mantle flow back in time. This is a classic problem of history matching, amenable to control theory and data assimilation. The technical advances that make such approach feasible are dramatically increasing compute resources, represented for example through Beowulf clusters, and new observational initiatives, represented for example through the US-Array effort that should lead to an order-of-magnitude improvement in our ability to resolve Earth structure seismically below North America. In fact, new observational constraints on deep Earth structure illustrate the growing importance of of improving our data assimilation skills in deep Earth models. We will explore data assimilation through high resolution global adjoint models of mantle circulation and conclude that it is feasible to reconstruct mantle flow back in time for at least the past 100 myrs.

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.

Ecological Physiology of Synechococcus sp. Strain SH-94-5, a Naturally Occurring Cyanobacterium Deficient in Nitrate Assimilation

PubMed Central

Miller, Scott R.; Castenholz, Richard W.

2001-01-01

Synechococcus sp. strain SH-94-5 is a nitrate assimilation-deficient cyanobacterium which was isolated from an ammonium-replete hot spring in central Oregon. While this clone could grow on ammonium and some forms of organic nitrogen as sole nitrogen sources, it could not grow on either nitrate or nitrite, even under conditions favoring passive diffusion. It was determined that this clone does not express functional nitrate reductase or nitrite reductase and that the lack of activity of either enzyme is not due to inactivation of the cyanobacterial nitrogen control protein NtcA. A few other naturally occurring cyanobacterial strains are also nitrate assimilation deficient, and phylogenetic analyses indicated that the ability to utilize nitrate has been independently lost at least four times during the evolutionary history of the cyanobacteria. This phenotype is associated with the presence of environmental ammonium, a negative regulator of nitrate assimilation gene expression, which may indicate that natural selection to maintain functional copies of nitrate assimilation genes has been relaxed in these habitats. These results suggest how the evolutionary fates of conditionally expressed genes might differ between environments and thereby effect ecological divergence and biogeographical structure in the microbial world. PMID:11425713

Ecological physiology of Synechococcus sp. strain SH-94-5, a naturally occurring cyanobacterium deficient in nitrate assimilation

NASA Technical Reports Server (NTRS)

Miller, S. R.; Castenholz, R. W.

2001-01-01

Synechococcus sp. strain SH-94-5 is a nitrate assimilation-deficient cyanobacterium which was isolated from an ammonium-replete hot spring in central Oregon. While this clone could grow on ammonium and some forms of organic nitrogen as sole nitrogen sources, it could not grow on either nitrate or nitrite, even under conditions favoring passive diffusion. It was determined that this clone does not express functional nitrate reductase or nitrite reductase and that the lack of activity of either enzyme is not due to inactivation of the cyanobacterial nitrogen control protein NtcA. A few other naturally occurring cyanobacterial strains are also nitrate assimilation deficient, and phylogenetic analyses indicated that the ability to utilize nitrate has been independently lost at least four times during the evolutionary history of the cyanobacteria. This phenotype is associated with the presence of environmental ammonium, a negative regulator of nitrate assimilation gene expression, which may indicate that natural selection to maintain functional copies of nitrate assimilation genes has been relaxed in these habitats. These results suggest how the evolutionary fates of conditionally expressed genes might differ between environments and thereby effect ecological divergence and biogeographical structure in the microbial world.

Assimilation of Ocean-Color Plankton Functional Types to Improve Marine Ecosystem Simulations

NASA Astrophysics Data System (ADS)

Ciavatta, S.; Brewin, R. J. W.; Skákala, J.; Polimene, L.; de Mora, L.; Artioli, Y.; Allen, J. I.

2018-02-01

We assimilated phytoplankton functional types (PFTs) derived from ocean color into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error-characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton, and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical-biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998-2003. The skill of the reference and reanalysis simulations in estimating ocean color and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean-color PFTs (except nanoplankton), as well as the not-assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not-assimilated in situ data of PFTs, as well as of phosphate and pCO2, impacting the simulation of the air-sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf-sea ecosystems.

The Madden-Julian Oscillation in the NCAR Community Earth System Model Coupled Data Assimilation System

NASA Astrophysics Data System (ADS)

Chatterjee, A.; Anderson, J. L.; Moncrieff, M.; Collins, N.; Danabasoglu, G.; Hoar, T.; Karspeck, A. R.; Neale, R. B.; Raeder, K.; Tribbia, J. J.

2014-12-01

We present a quantitative evaluation of the simulated MJO in analyses produced with a coupled data assimilation (CDA) framework developed at the National Center for Atmosphere Research. This system is based on the Community Earth System Model (CESM; previously known as the Community Climate System Model -CCSM) interfaced to a community facility for ensemble data assimilation (Data Assimilation Research Testbed - DART). The system (multi-component CDA) assimilates data into each of the respective ocean/atmosphere/land model components during the assimilation step followed by an exchange of information between the model components during the forecast step. Note that this is an advancement over many existing prototypes of coupled data assimilation systems, which typically assimilate observations only in one of the model components (i.e., single-component CDA). The more realistic treatment of air-sea interactions and improvements to the model mean state in the multi-component CDA recover many aspects of MJO representation, from its space-time structure and propagation (see Figure 1) to the governing relationships between precipitation and sea surface temperature on intra-seasonal scales. Standard qualitative and process-based diagnostics identified by the MJO Task Force (currently under the auspices of the Working Group on Numerical Experimentation) have been used to detect the MJO signals across a suite of coupled model experiments involving both multi-component and single-component DA experiments as well as a free run of the coupled CESM model (i.e., CMIP5 style without data assimilation). Short predictability experiments during the boreal winter are used to demonstrate that the decay rates of the MJO convective anomalies are slower in the multi-component CDA system, which allows it to retain the MJO dynamics for a longer period. We anticipate that the knowledge gained through this study will enhance our understanding of the MJO feedback mechanisms across the air-sea interface, especially regarding ocean impacts on the MJO as well as highlight the capability of coupled data assimilation systems for related tropical intraseasonal variability predictions.

Documentation and Validation of the Goddard Earth Observing System (GEOS) Data Assimilation System, Version 4

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); daSilva, Arlindo; Dee, Dick; Bloom, Stephen; Bosilovich, Michael; Pawson, Steven; Schubert, Siegfried; Wu, Man-Li; Sienkiewicz, Meta; Stajner, Ivanka

2005-01-01

This document describes the structure and validation of a frozen version of the Goddard Earth Observing System Data Assimilation System (GEOS DAS): GEOS-4.0.3. Significant features of GEOS-4 include: version 3 of the Community Climate Model (CCM3) with the addition of a finite volume dynamical core; version two of the Community Land Model (CLM2); the Physical-space Statistical Analysis System (PSAS); and an interactive retrieval system (iRET) for assimilating TOVS radiance data. Upon completion of the GEOS-4 validation in December 2003, GEOS-4 became operational on 15 January 2004. Products from GEOS-4 have been used in supporting field campaigns and for reprocessing several years of data for CERES.

Evaluation of crustal recycling during the evolution of Archean-age Matachewan basaltic magmas

NASA Technical Reports Server (NTRS)

Nelson, Dennis O.

1989-01-01

The simplest model for the Matachewan-Hearst Dike (MHD) magmas is assimilation-fractional crystallization (AFC), presumably occurring at the base of the crust during underplating. Subduction zone enriched mantle sources are not required. Trace elements suggest that the mantle sources for the MHD were depleted, but possessed a degree of heterogeneity. Rates of assimilation were approximately 0.5 (= Ma/Mc); the contaminant mass was less than 20 percent. The contaminant was dominated by tonalites-randodiorites, similar to xenoliths and rocks in the Kapuskasing Structural Zone (KSZ). Assimilation of partial melts of light-rare earth and garnet-bearing basaltic precursors may have produced some the MHD magmas. Apparently, previous underplating-AFC processes had already produced a thick crust. The silicic granitoid assimilant for the MHD magmas was probably produced by earlier processing of underplated mafic crust (4, 5, 10, 21 and 30). Calculations suggest that the derived silicic rocks possess negative Ta and Ti anomalies even though they were not the product of subduction.

Treating Sample Covariances for Use in Strongly Coupled Atmosphere-Ocean Data Assimilation

NASA Astrophysics Data System (ADS)

Smith, Polly J.; Lawless, Amos S.; Nichols, Nancy K.

2018-01-01

Strongly coupled data assimilation requires cross-domain forecast error covariances; information from ensembles can be used, but limited sampling means that ensemble derived error covariances are routinely rank deficient and/or ill-conditioned and marred by noise. Thus, they require modification before they can be incorporated into a standard assimilation framework. Here we compare methods for improving the rank and conditioning of multivariate sample error covariance matrices for coupled atmosphere-ocean data assimilation. The first method, reconditioning, alters the matrix eigenvalues directly; this preserves the correlation structures but does not remove sampling noise. We show that it is better to recondition the correlation matrix rather than the covariance matrix as this prevents small but dynamically important modes from being lost. The second method, model state-space localization via the Schur product, effectively removes sample noise but can dampen small cross-correlation signals. A combination that exploits the merits of each is found to offer an effective alternative.

Advanced Satellite-Derived Wind Observations, Assimilation, and Targeting Strategies during TCS-08 for Developing Improved Operational Analysis and Prediction of Western Pacific Tropical Cyclones

DTIC Science & Technology

2012-09-30

influences on TC structure evolve up to landfall or extratropical transition. In particular, winds derived from geostationary satellites have been shown... extratropical transition, it is clear that a dedicated research effort is needed to optimize the satellite data processing strategies, assimilation...and applications to better understand the behavior of the near- storm environmental flow fields during these evolutionary TC stages. To our knowledge

Advanced Satellite-Derived Wind Observations, Assimilation, and Targeting Strategies during TCS-08 for Developing Improved Operational Analysis and Prediction of Western Pacific Tropical Cyclones

DTIC Science & Technology

2011-09-30

influences on TC structure evolve up to landfall or extratropical transition. In particular, winds derived from geostationary satellites have been...and extratropical transition, it is clear that a dedicated research effort is needed to optimize the satellite data processing strategies...assimilation, and applications to better understand the behavior of the near- storm environmental flow fields during these evolutionary TC stages. To our

Development of a copula-based particle filter (CopPF) approach for hydrologic data assimilation under consideration of parameter interdependence

NASA Astrophysics Data System (ADS)

Fan, Y. R.; Huang, G. H.; Baetz, B. W.; Li, Y. P.; Huang, K.

2017-06-01

In this study, a copula-based particle filter (CopPF) approach was developed for sequential hydrological data assimilation by considering parameter correlation structures. In CopPF, multivariate copulas are proposed to reflect parameter interdependence before the resampling procedure with new particles then being sampled from the obtained copulas. Such a process can overcome both particle degeneration and sample impoverishment. The applicability of CopPF is illustrated with three case studies using a two-parameter simplified model and two conceptual hydrologic models. The results for the simplified model indicate that model parameters are highly correlated in the data assimilation process, suggesting a demand for full description of their dependence structure. Synthetic experiments on hydrologic data assimilation indicate that CopPF can rejuvenate particle evolution in large spaces and thus achieve good performances with low sample size scenarios. The applicability of CopPF is further illustrated through two real-case studies. It is shown that, compared with traditional particle filter (PF) and particle Markov chain Monte Carlo (PMCMC) approaches, the proposed method can provide more accurate results for both deterministic and probabilistic prediction with a sample size of 100. Furthermore, the sample size would not significantly influence the performance of CopPF. Also, the copula resampling approach dominates parameter evolution in CopPF, with more than 50% of particles sampled by copulas in most sample size scenarios.

The impact of water vapor assimilation on quantitative precipitation forecast over the Washington, DC metropolitan area

NASA Astrophysics Data System (ADS)

Walford, Segayle Cereta

Forecasting subtle, small-scale convective cases in both winter and summer time is an ongoing challenge in weather forecasting. Recent studies have shown that better structure of moisture within the boundary layer is crucial for improving forecasting skills, particularly quantitative precipitation forecasting (QPF). Lidars, which take high temporal observations of moisture, are able to capture very detailed structures, especially within the boundary layer where convection often begins. This study first investigates the extent to which an aerosol and a water vapor lidar are able to capture key boundary layer processes necessary for the development of convection. The results of this preliminary study show that the water vapor lidar is best able to capture the small scale water vapor variability that is necessary for the development of convection. These results are then used to investigate impacts of assimilating moisture from the Howard University Raman Lidar (HURL) for one mesoscale convective case, July 27-28, 2006. The data for this case is from the Water Vapor Validation Experiment-Satellite and Sondes (WAVES) field campaign located at the Howard University Beltsville Site (HUBS) in Beltsville, MD. Specifically, lidar-based water vapor mixing ratio profiles are assimilated into the Weather Research and Forecasting (WRF) regional model over a 4 km grid resolution over Washington, DC. Model verification is conducted using the Meteorological Evaluation Tool (MET) and the results from the lidar run are then compared to a control (no assimilation) run. The findings indicate that quantitatively conclusions cannot be draw from this one case study. However, qualitatively, the assimilation of the lidar observations improved the equivalent potential temperature, and water vapor distribution of the region. This difference changed location, strength and spatial coverage of the convective system over the HUBS region.

Soil water content effects on net ecosystem CO2 exchange and actual evapotranspiration in a Mediterranean semiarid savanna of Central Chile.

PubMed

Meza, Francisco J; Montes, Carlo; Bravo-Martínez, Felipe; Serrano-Ortiz, Penélope; Kowalski, Andrew S

2018-06-05

Biosphere-atmosphere water and carbon fluxes depend on ecosystem structure, and their magnitudes and seasonal behavior are driven by environmental and biological factors. We studied the seasonal behavior of net ecosystem CO 2 exchange (NEE), Gross Primary Productivity (GPP), Ecosystem Respiration (RE), and actual evapotranspiration (ETa) obtained by eddy covariance measurements during two years in a Mediterranean Acacia savanna ecosystem (Acacia caven) in Central Chile. The annual carbon balance was -53 g C m -2 in 2011 and -111 g C m -2 in 2012, showing that the ecosystem acts as a net sink of CO 2 , notwithstanding water limitations on photosynthesis observed in this particularly dry period. Total annual ETa was of 128 mm in 2011 and 139 mm in 2012. Both NEE and ETa exhibited strong seasonality with peak values recorded in the winter season (July to September), as a result of ecosystem phenology, soil water content and rainfall occurrence. Consequently, the maximum carbon assimilation rate occurred in wintertime. Results show that soil water content is a major driver of GPP and RE, defining their seasonal patterns and the annual carbon assimilation capacity of the ecosystem, and also modulating the effect that solar radiation and air temperature have on NEE components at shorter time scales.

A computational analysis of the three isoforms of glutamate dehydrogenase reveals structural features of the isoform EC 1.4.1.4 supporting a key role in ammonium assimilation by plants

PubMed Central

Jaspard, Emmanuel

2006-01-01

Background There are three isoforms of glutamate dehydrogenase. The isoform EC 1.4.1.4 (GDH4) catalyses glutamate synthesis from 2-oxoglutarate and ammonium, using NAD(P)H. Ammonium assimilation is critical for plant growth. Although GDH4 from animals and prokaryotes are well characterized, there are few data concerning plant GDH4, even from those whose genomes are well annotated. Results A large set of the three GDH isoforms was built resulting in 116 non-redundant full polypeptide sequences. A computational analysis was made to gain more information concerning the structure – function relationship of GDH4 from plants (Eukaryota, Viridiplantae). The tested plant GDH4 sequences were the two ones known to date, those of Chlorella sorokiniana. This analysis revealed several structural features specific of plant GDH4: (i) the lack of a structure called "antenna"; (ii) the NAD(P)-binding motif GAGNVA; and (iii) a second putative coenzyme-binding motif GVLTGKG together with four residues involved in the binding of the reduced form of NADP. Conclusion A number of structural features specific of plant GDH4 have been found. The results reinforce the probable key role of GDH4 in ammonium assimilation by plants. Reviewers This article was reviewed by Tina Bakolitsa (nominated by Eugene Koonin), Martin Jambon (nominated by Laura Landweber), Sandor Pangor and Franck Eisenhaber. PMID:17173671

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.

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.

Petrographic, geochemical and isotopic evidence of crustal assimilation processes in the Ponte Nova alkaline mafic-ultramafic massif, SE Brazil

NASA Astrophysics Data System (ADS)

Azzone, Rogério Guitarrari; Montecinos Munoz, Patricio; Enrich, Gaston Eduardo Rojas; Alves, Adriana; Ruberti, Excelso; Gomes, Celsode Barros

2016-09-01

Crustal assimilation plus crystal fractionation processes of different basanite magma batches control the evolution of the Ponte Nova cretaceous alkaline mafic-ultramafic massif in SE Brazil. This massif is composed of several intrusions, the main ones with a cumulate character. Disequilibrium features in the early-crystallized phases (e.g., corrosion and sieve textures in cores of clinopyroxene crystals, spongy-cellular-textured plagioclase crystals, gulf corrosion texture in olivine crystals) and classical hybridization textures (e.g., blade biotite and acicular apatite crystals) provide strong evidence of open-system behavior. All samples are olivine- and nepheline-normative rocks with basic-ultrabasic and potassic characters and variable incompatible element enrichments. The wide ranges of whole-rock 87Sr/86Sri and 143Nd/144Ndi ratios (0.70432-0.70641 and 0.512216-0.512555, respectively) are indicative of crustal contribution from the Precambrian basement host rocks. Plagioclase and apatite 87Sr/86Sr ratios (0.70422-0.70927) obtained for the most primitive samples of each intrusion indicate disequilibrium conditions from early- to principal-crystallization stages. Isotope mixing-model curves between the least contaminated alkaline basic magma and heterogeneous local crustal components indicate that each intrusion of the massif is differentiated from the others by varied degrees of crustal contribution. The primary mechanisms of crustal contribution to the Ponte Nova massif involve the assimilation of host rock xenoliths during the development of the chamber environment and the assimilation of partial melts from the surrounding host rocks. Thermodynamic models using the melts algorithm indicate that parental alkaline basic magmas can be strongly affected by contamination processes subsequently to their initial stages of crystallization when there is sufficient energy to assimilate partial melts of crustal host rocks. The assimilation processes are considered to be responsible for the increse in the K2O/Na2O, Ba/Sr and Rb/Sr ratios. This enrichment was associated with the relevant role of biotite breakdown in the assimilated host rock partial melts. The petrological model for the Ponte Nova massif is explained as repeated influxes of antecryst-laden basanite magmas that deposited most of their suspended crystals on the floor of the upper-crust magma chamber. Each intrusion is representative of relatively primitive olivine- and clinopyroxene-phyric basanites that had assimilated different degrees of partial melts of heterogeneous host rocks. This study reveals the relevant role of crustal assimilation processes in the magmatic evolution of nepheline-normative rocks, especially in upper-crust chamber environments.

Phytoplankton community composition and primary production in the tropical tidal ecosystem, Maputo Bay (the Indian Ocean)

NASA Astrophysics Data System (ADS)

Olofsson, Malin; Karlberg, Maria; Lage, Sandra; Ploug, Helle

2017-07-01

Maputo Bay is highly affected by large tidal changes and riverine freshwater input with a phytoplankton biomass peak during March each year. Microscopy analysis was used to describe how the phytoplankton community composition was affected by tidal changes, during four in situ incubation experiments. Using stable isotope tracers, new and total primary production, based on nitrate (15NO3-)- and carbon (13C-bicarbonate)-assimilation were estimated. The highest biovolume of phytoplankton (> 2 μm) and also the highest C- and NO3--assimilation rates (nM h-1) were found at spring-high tide. The C:N (mol:mol) ratio of particulate organic matter (POM) varied between 6.0 and 8.2. The proportion of diatoms in the phytoplankton community was higher at spring-high tide as compared to neap-low tide, whereas dinoflagellates were found in a reverse pattern. New production ranged between 6.3% and 10.4% of total primary production and was thus within the range previously reported for tropical regions. The largest proportion of NO3--based new production relative to total production was estimated during calm conditions and spring-high tide. Concordantly, a large fraction of the microplanktonic community covered their N-demand by other sources of N than NO3-.

Adjoint assimilation of altimetric, surface drifter, and hydrographic data in a quasi-geostrophic model of the Azores Current

NASA Astrophysics Data System (ADS)

Morrow, Rosemary; de Mey, Pierre

1995-12-01

The flow characteristics in the region of the Azores Current are investigated by assimilating TOPEX/POSEIDON and ERS 1 altimeter data into the multilevel Harvard quasigeostrophic (QG) model with open boundaries (Miller et al., 1983) using an adjoint variational scheme (Moore, 1991). The study site lies in the path of the Azores Current, where a branch retroflects to the south in the vicinity of the Madeira Rise. The region was the site of an intensive field program in 1993, SEMAPHORE. We had two main aims in this adjoint assimilation project. The first was to see whether the adjoint method could be applied locally to optimize an initial guess field, derived from the continous assimilation of altimetry data using optimal interpolation (OI). The second aim was to assimilate a variety of different data sets and evaluate their importance in constraining our QG model. The adjoint assimilation of surface data was effective in optimizing the initial conditions from OI. After 20 iterations the cost function was generally reduced by 50-80%, depending on the chosen data constraints. The primary adjustment process was via the barotropic mode. Altimetry proved to be a good constraint on the variable flow field, in particular, for constraining the barotropic field. The excellent data quality of the TOPEX/POSEIDON (T/P) altimeter data provided smooth and reliable forcing; but for our mesoscale study in a region of long decorrelation times O(30 days), the spatial coverage from the combined T/P and ERS 1 data sets was more important for constraining the solution and providing stable flow at all levels. Surface drifters provided an excellent constraint on both the barotropic and baroclinic model fields. More importantly, the drifters provided a reliable measure of the mean field. Hydrographic data were also applied as a constraint; in general, hydrography provided a weak but effective constraint on the vertical Rossby modes in the model. Finally, forecasts run over a 2-month period indicate that the initial conditions optimized by the 20-day adjoint assimilation provide more stable, longer-term forecasts.

Interannual Variation in Phytoplankton Class-Specific Primary Production at a Global Scale

NASA Technical Reports Server (NTRS)

Rousseaux, Cecile Severine; Gregg, Watson W.

2014-01-01

We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of 4 phytoplankton groups to the total primary production. First we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms were the group that contributed the most to the total phytoplankton production (50, the equivalent of 20 PgC y-1. Coccolithophores and chlorophytes each contributed to 20 (7 PgC y-1 of the total primary production and cyanobacteria represented about 10 (4 PgC y(sub-1) of the total primary production. Primary production by diatoms was highest in high latitude (45) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4 (1-2 PgC y-1. We assessed the effects of climate variability on the class-specific primary production using global (i.e. Multivariate El Nio Index, MEI) and regional climate indices (e.g. Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p 0.05) between the MEI and the class-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatomscyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on the class-specific primary production in the Southern Ocean. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.

Interannual Variation in Phytoplankton Primary Production at a Global Scale

NASA Technical Reports Server (NTRS)

Rousseaux, Cecile Severine; Gregg, Watson W.

2013-01-01

We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of four phytoplankton groups to the total primary production. First, we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms contributed the most to the total phytoplankton production ((is)approximately 50%, the equivalent of 20 PgC·y1). Coccolithophores and chlorophytes each contributed approximately 20% ((is) approximately 7 PgC·y1) of the total primary production and cyanobacteria represented about 10% ((is) approximately 4 PgC·y1) of the total primary production. Primary production by diatoms was highest in the high latitudes ((is) greater than 40 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4% (1-2 PgC·y1). We assessed the effects of climate variability on group-specific primary production using global (i.e., Multivariate El Niño Index, MEI) and "regional" climate indices (e.g., Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p (is) less than 0.05) between the MEI and the group-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatoms/cyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on group-specific primary production in the Southern Ocean. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.

Consistent changes in the taxonomic structure and functional attributes of bacterial communities during primary succession.

PubMed

Ortiz-Álvarez, Rüdiger; Fierer, Noah; de Los Ríos, Asunción; Casamayor, Emilio O; Barberán, Albert

2018-02-20

Ecologists have long studied primary succession, the changes that occur in biological communities after initial colonization of an environment. Most of this work has focused on succession in plant communities, laying the conceptual foundation for much of what we currently know about community assembly patterns over time. Because of their prevalence and importance in ecosystems, an increasing number of studies have focused on microbial community dynamics during succession. Here, we conducted a meta-analysis of bacterial primary succession patterns across a range of distinct habitats, including the infant gut, plant surfaces, soil chronosequences, and aquatic environments, to determine whether consistent changes in bacterial diversity, community composition, and functional traits are evident over the course of succession. Although these distinct habitats harbor unique bacterial communities, we were able to identify patterns in community assembly that were shared across habitat types. We found an increase in taxonomic and functional diversity with time while the taxonomic composition and functional profiles of communities became less variable (lower beta diversity) in late successional stages. In addition, we found consistent decreases in the rRNA operon copy number and in the high-efficient phosphate assimilation process (Pst system) suggesting that reductions in resource availability during succession select for taxa adapted to low-resource conditions. Together, these results highlight that, like many plant communities, microbial communities also exhibit predictable patterns during primary succession.

Personalized glucose forecasting for type 2 diabetes using data assimilation

PubMed Central

Albers, David J.; Gluckman, Bruce; Ginsberg, Henry; Hripcsak, George; Mamykina, Lena

2017-01-01

Type 2 diabetes leads to premature death and reduced quality of life for 8% of Americans. Nutrition management is critical to maintaining glycemic control, yet it is difficult to achieve due to the high individual differences in glycemic response to nutrition. Anticipating glycemic impact of different meals can be challenging not only for individuals with diabetes, but also for expert diabetes educators. Personalized computational models that can accurately forecast an impact of a given meal on an individual’s blood glucose levels can serve as the engine for a new generation of decision support tools for individuals with diabetes. However, to be useful in practice, these computational engines need to generate accurate forecasts based on limited datasets consistent with typical self-monitoring practices of individuals with type 2 diabetes. This paper uses three forecasting machines: (i) data assimilation, a technique borrowed from atmospheric physics and engineering that uses Bayesian modeling to infuse data with human knowledge represented in a mechanistic model, to generate real-time, personalized, adaptable glucose forecasts; (ii) model averaging of data assimilation output; and (iii) dynamical Gaussian process model regression. The proposed data assimilation machine, the primary focus of the paper, uses a modified dual unscented Kalman filter to estimate states and parameters, personalizing the mechanistic models. Model selection is used to make a personalized model selection for the individual and their measurement characteristics. The data assimilation forecasts are empirically evaluated against actual postprandial glucose measurements captured by individuals with type 2 diabetes, and against predictions generated by experienced diabetes educators after reviewing a set of historical nutritional records and glucose measurements for the same individual. The evaluation suggests that the data assimilation forecasts compare well with specific glucose measurements and match or exceed in accuracy expert forecasts. We conclude by examining ways to present predictions as forecast-derived range quantities and evaluate the comparative advantages of these ranges. PMID:28448498

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.

Using snow data assimilation to improve ensemble streamflow forecasting for the Upper Colorado River Basin

NASA Astrophysics Data System (ADS)

Micheletty, P. D.; Perrot, D.; Day, G. N.; Lhotak, J.; Quebbeman, J.; Park, G. H.; Carney, S.

2017-12-01

Water supply forecasting in the western United States is inextricably linked to snowmelt processes, as approximately 70-85% of total annual runoff comes from water stored in seasonal mountain snowpacks. Snowmelt-generated streamflow is vital to a variety of downstream uses; the Upper Colorado River Basin (UCRB) alone provides water supply for 25 million people, irrigation water for 3.5 million acres, and drives hydropower generation at Lake Powell. April-July water supply forecasts produced by the National Weather Service (NWS) Colorado Basin River Forecast Center (CBRFC) are critical to basin water management. The primary objective of this project as part of the NASA Water Resources Applied Science Program, is to improve water supply forecasting for the UCRB by assimilating satellite and ground snowpack observations into a distributed hydrologic model at various times during the snow accumulation and melt seasons. To do this, we have built a framework that uses an Ensemble Kalman Filter (EnKF) to update modeled snow water equivalent (SWE) states in the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) with spatially interpolated SNOTEL snow water equivalent (SWE) observations and products from the MODIS Snow Covered-Area and Grain size retrieval algorithm (when available). We have generated April-July water supply reforecasts for a 20-year period (1991-2010) for several headwater catchments in the UCRB using HL-RDHM and snow data assimilation in the Ensemble Streamflow Prediction (ESP) framework. The existing CBRFC ESP reforecasts will provide a baseline for comparison to determine whether the data assimilation process adds skill to the water supply forecasts. Preliminary results from one headwater basin show improved skill in water supply forecasting when HL-RDHM is run with the data assimilation step compared to HL-RDHM run without the data assimilation step, particularly in years when MODSCAG data were available (2000-2010). The final forecasting framework developed during this project will be delivered to CBRFC and run operationally for a set of pilot basins.

Canopy carbon net assimilation of an urban, naturally assembled brownfield forest

NASA Astrophysics Data System (ADS)

Schafer, K. V.; Wadhwa, S.; Tripathee, R.; Gallagher, F. J.

2010-12-01

In this study, we have been investigating an urban brownfield at Liberty State Park that has been abandoned approximately for 40 years. Natural colonization has taken place that allowed a pioneer forest to grow with primarily Betula populifera and Populus spec. Despite soil metal contamination this urban forest exhibits moderate annual productivity and serves as a carbon sink. Diameters at breast height (DBH, 1.35 m above ground) of all trees in a study plot were measured. Aboveground biomass equations were determined for both species through destructive sampling. Aboveground net primary production was about 770 gC m-2 a-1 in 2009. Canopy net assimilation (AnC) was modeled with the canopy conductance constrained assimilation (4CA) model using measured sapflux derived conductance and photosynthetic parameters measured with a LICOR 6400. Annual AnC in 2009 was approximately 1500 gC m-2 a-1 thus with a partitioning of biomass and respiration in the same range of most natural forest with less anthropogenic induced stress. Urban brownfields thus can serve as C sinks and provide phytostabilization of contaminants.

Sulfur assimilation and the role of sulfur in plant metabolism: a survey.

PubMed

Droux, Michel

2004-01-01

Sulfur occurs in two major amino-acids, cysteine (Cys) and methionine (Met), essential for the primary and secondary metabolism of the plant. Cys, as the first carbon/nitrogen-reduced sulfur product resulting from the sulfate assimilation pathway, serves as a sulfur donor for Met, glutathione, vitamins, co-factors, and sulfur compounds that play a major role in the growth and development of plant cells. This sulfur imprinting occurs in a myriad of fundamental processes, from photosynthesis to carbon and nitrogen metabolism. Cys and Met occur in proteins, with the former playing a wide range of functions in proteins catalysis. In addition, the sulfur atom in proteins forms part of a redox buffer, as for glutathione, through specific detoxification/protection mechanisms. In this review, a survey of sulfur assimilation from sulfate to Cys, Met and glutathione is presented with highlights on open questions on their respective biosynthetic pathways and regulations that derived from recent findings. These are addressed at the biochemical and molecular levels with respect to the fate of Cys and Met throughout the plant-cell metabolism.

Health Assimilation among Hispanic Immigrants in the United States: The Impact of Ignoring Arrival-cohort Effects.

PubMed

Hamilton, Tod G; Palermo, Tia; Green, Tiffany L

2015-12-01

A large literature has documented that Hispanic immigrants have a health advantage over their U.S.-born counterparts upon arrival in the United States. Few studies, however, have disentangled the effects of immigrants' arrival cohort from their tenure of U.S. residence, an omission that could produce imprecise estimates of the degree of health decline experienced by Hispanic immigrants as their U.S. tenure increases. Using data from the 1996-to-2014 waves of the March Current Population Survey, we show that the health (i.e., self-rated health) of Hispanic immigrants varies by both arrival cohort and U.S. tenure for immigrants hailing from most of the primary sending countries/regions of Hispanic immigrants. We also find evidence that acculturation plays an important role in determining the health trajectories of Hispanic immigrants. With respect to self-rated health, however, our findings demonstrate that omitting arrival-cohort measures from health assimilation models may result in overestimates of the degree of downward health assimilation experienced by Hispanic immigrants. © American Sociological Association 2015.

The GEOS-5 Data Assimilation System-Documentation of Versions 5.0.1, 5.1.0, and 5.2.0

NASA Technical Reports Server (NTRS)

Suarez, Max J.; Rienecker, M. M.; Todling, R.; Bacmeister, J.; Takacs, L.; Liu, H. C.; Gu, W.; Sienkiewicz, M.; Koster, R. D.; Gelaro, R.;

Utilization of microbial iron assimilation processes for the development of new antibiotics and inspiration for the design of new anticancer agents.

PubMed

Miller, Marvin J; Zhu, Helen; Xu, Yanping; Wu, Chunrui; Walz, Andrew J; Vergne, Anne; Roosenberg, John M; Moraski, Garrett; Minnick, Albert A; McKee-Dolence, Julia; Hu, Jingdan; Fennell, Kelley; Kurt Dolence, E; Dong, Li; Franzblau, Scott; Malouin, Francois; Möllmann, Ute

2009-02-01

Pathogenic microbes rapidly develop resistance to antibiotics. To keep ahead in the "microbial war", extensive interdisciplinary research is needed. A primary cause of drug resistance is the overuse of antibiotics that can result in alteration of microbial permeability, alteration of drug target binding sites, induction of enzymes that destroy antibiotics (ie., beta-lactamase) and even induction of efflux mechanisms. A combination of chemical syntheses, microbiological and biochemical studies demonstrate that the known critical dependence of iron assimilation by microbes for growth and virulence can be exploited for the development of new approaches to antibiotic therapy. Iron recognition and active transport relies on the biosyntheses and use of microbe-selective iron-chelating compounds called siderophores. Our studies, and those of others, demonstrate that siderophores and analogs can be used for iron transport-mediated drug delivery ("Trojan Horse" antibiotics) and induction of iron limitation/starvation (Development of new agents to block iron assimilation). Recent extensions of the use of siderophores for the development of novel potent and selective anticancer agents are also described.

Utilization of microbial iron assimilation processes for the development of new antibiotics and inspiration for the design of new anticancer agents

PubMed Central

Zhu, Helen; Xu, Yanping; Wu, Chunrui; Walz, Andrew J.; Vergne, Anne; Roosenberg, John M.; Moraski, Garrett; Minnick, Albert A.; McKee-Dolence, Julia; Hu, Jingdan; Fennell, Kelley; Dolence, E. Kurt; Dong, Li; Franzblau, Scott; Malouin, Francois; Möllmann, Ute

2014-01-01

Pathogenic microbes rapidly develop resistance to antibiotics. To keep ahead in the “microbial war”, extensive interdisciplinary research is needed. A primary cause of drug resistance is the overuse of antibiotics that can result in alteration of microbial permeability, alteration of drug target binding sites, induction of enzymes that destroy antibiotics (ie., beta-lactamase) and even induction of efflux mechanisms. A combination of chemical syntheses, microbiological and biochemical studies demonstrate that the known critical dependence of iron assimilation by microbes for growth and virulence can be exploited for the development of new approaches to antibiotic therapy. Iron recognition and active transport relies on the biosyntheses and use of microbe-selective iron-chelating compounds called siderophores. Our studies, and those of others, demonstrate that siderophores and analogs can be used for iron transport-mediated drug delivery (“Trojan Horse” antibiotics) and induction of iron limitation/starvation (Development of new agents to block iron assimilation). Recent extensions of the use of siderophores for the development of novel potent and selective anticancer agents are also described. PMID:19130268

Optimality in Data Assimilation

NASA Astrophysics Data System (ADS)

Nearing, Grey; Yatheendradas, Soni

2016-04-01

It costs a lot more to develop and launch an earth-observing satellite than it does to build a data assimilation system. As such, we propose that it is important to understand the efficiency of our assimilation algorithms at extracting information from remote sensing retrievals. To address this, we propose that it is necessary to adopt completely general definition of "optimality" that explicitly acknowledges all differences between the parametric constraints of our assimilation algorithm (e.g., Gaussianity, partial linearity, Markovian updates) and the true nature of the environmetnal system and observing system. In fact, it is not only possible, but incredibly straightforward, to measure the optimality (in this more general sense) of any data assimilation algorithm as applied to any intended model or natural system. We measure the information content of remote sensing data conditional on the fact that we are already running a model and then measure the actual information extracted by data assimilation. The ratio of the two is an efficiency metric, and optimality is defined as occurring when the data assimilation algorithm is perfectly efficient at extracting information from the retrievals. We measure the information content of the remote sensing data in a way that, unlike triple collocation, does not rely on any a priori presumed relationship (e.g., linear) between the retrieval and the ground truth, however, like triple-collocation, is insensitive to the spatial mismatch between point-based measurements and grid-scale retrievals. This theory and method is therefore suitable for use with both dense and sparse validation networks. Additionally, the method we propose is *constructive* in the sense that it provides guidance on how to improve data assimilation systems. All data assimilation strategies can be reduced to approximations of Bayes' law, and we measure the fractions of total information loss that are due to individual assumptions or approximations in the prior (i.e., the model uncertainty distribution), and in the likelihood (i.e., the observation operator and observation uncertainty distribution). In this way, we can directly identify the parts of a data assimilation algorithm that contribute most to assimilation error in a way that (unlike traditional DA performance metrics) considers nonlinearity in the model and observation and non-optimality in the fit between filter assumptions and the real system. To reiterate, the method we propose is theoretically rigorous but also dead-to-rights simple, and can be implemented in no more than a few hours by a competent programmer. We use this to show that careful applications of the Ensemble Kalman Filter use substantially less than half of the information contained in remote sensing soil moisture retrievals (LPRM, AMSR-E, SMOS, and SMOPS). We propose that this finding may explain some of the results from several recent large-scale experiments that show lower-than-expected value to assimilating soil moisture retrievals into land surface models forced by high-quality precipitation data. Our results have important implications for the SMAP mission because over half of the SMAP-affiliated "early adopters" plan to use the EnKF as their primary method for extracting information from SMAP retrievals.

An Aural Learning Project: Assimilating Jazz Education Methods for Traditional Applied Pedagogy

ERIC Educational Resources Information Center

Gamso, Nancy M.

2011-01-01

The Aural Learning Project (ALP) was developed to incorporate jazz method components into the author's classical practice and her applied woodwind lesson curriculum. The primary objective was to place a more focused pedagogical emphasis on listening and hearing than is traditionally used in the classical applied curriculum. The components of the…

Reconciling Epistemological Orientations: Toward a Wholistic Nishnaabe (Ojibwe/Odawa/Potawatomi) Education.

ERIC Educational Resources Information Center

Corbiere, Alan Ojiig

The education of First Nations people has been used primarily for assimilation purposes. The last 30 years have witnessed the beginnings of First Nations' control of education with the primary impetus being self-determination. Achieving self-determination through education has been hindered by the social and cultural problems associated with…

Poultry Disease Risk Management: Biosecurity Instructional CD-ROM

ERIC Educational Resources Information Center

Vaillancourt, Jean-Pierre; Lambert, Gene; Popovich, Laura W.

2007-01-01

Delivery and formatting techniques for technical materials have traditionally been determined by common sense, not cognitive theory. In fact, for hundreds of years, verbal messages in the form of lecture and print have been the primary method of disseminating information to the learner. To move beyond verbal messages and toward the assimilation of…

Integrating fAPARchl and PRInadir from EO-1/Hyperion to predict cornfield daily gross primary production (GPP)

USDA-ARS?s Scientific Manuscript database

Accurate estimates of terrestrial carbon sequestration is essential for evaluating changes in the carbon cycle due to global climate change. In a recent assessment of 26 carbon assimilation models at 39 FLUXNET tower sites across the United States and Canada, all models failed to adequately compute...

Relationships between Cognition of Teachers and Quality of Teaching Style in Elementary Science.

ERIC Educational Resources Information Center

McKenna, Leonard N.

This study is concerned with preservice primary school teachers (N=100), a group of tertiary students who traditionally come from the secondary school stream. These students have, on the whole, avoided subjects like physics, chemistry, and mathematics that demand a high level of cognitive development for understanding/assimilation of abstract…

Magnesium deficiency results in damage of nitrogen and carbon cross-talk of maize and improvement by cerium addition.

PubMed

Zhao, Haiquan; Zhou, Qiuping; Zhou, Min; Li, Chunxiao; Gong, Xiaolan; Liu, Chao; Qu, Chunxiang; Si, Wenhui; Hong, Fashui

2012-07-01

Magnesium (Mg) deficiency has been reported to affect plant photosynthesis and growth, and cerium (Ce) was considered to be able to improve plant growth. However, the mechanisms of Mg deficiency and Ce on plant growth remain poorly understood. The main aim of this work is to identify whether or not Mg deprivation affects the interdependent nitrogen and carbon assimilations in the maize leaves and whether or not Ce modulates the assimilations in the maize leaves under Mg deficiency. Maize plants were cultivated in Hoagland’s solution. They were subjected to Mg deficiency and to cerium chloride administration in the Mg-present Hoagland’s media and Mg-deficient Hoagland’s media.After 2 weeks,we measured chlorophyll (Chl) a fluorescence and the activities of nitrate reductase (NR), sucrose-phosphate synthase(SPS), and phosphoenolpyruvate carboxylase (PEPCase)in metabolic checkpoints coordinating primary nitrogen and carbon assimilations in the maize leaves. The results showed that Mg deficiency significantly inhibited plant growth and decreased the activities of NR, SPS, and PEPCase and the synthesis of Chl and protein. Mg deprivation in maize also significantly decreased the oxygen evolution, electron transport,and efficiency of photochemical energy conversion by photosystem II (PSII). However, Ce addition may promote nitrogen and carbon assimilations, increase PSII activities,and improve maize growth under Mg deficiency. Moreover,our findings would help promote usage of Mg or Ce fertilizers in maize production.

Multivariate Error Covariance Estimates by Monte-Carlo Simulation for Assimilation Studies in the Pacific Ocean

NASA Technical Reports Server (NTRS)

Borovikov, Anna; Rienecker, Michele M.; Keppenne, Christian; Johnson, Gregory C.

2004-01-01

One of the most difficult aspects of ocean state estimation is the prescription of the model forecast error covariances. The paucity of ocean observations limits our ability to estimate the covariance structures from model-observation differences. In most practical applications, simple covariances are usually prescribed. Rarely are cross-covariances between different model variables used. Here a comparison is made between a univariate Optimal Interpolation (UOI) scheme and a multivariate OI algorithm (MvOI) in the assimilation of ocean temperature. In the UOI case only temperature is updated using a Gaussian covariance function and in the MvOI salinity, zonal and meridional velocities as well as temperature, are updated using an empirically estimated multivariate covariance matrix. Earlier studies have shown that a univariate OI has a detrimental effect on the salinity and velocity fields of the model. Apparently, in a sequential framework it is important to analyze temperature and salinity together. For the MvOI an estimation of the model error statistics is made by Monte-Carlo techniques from an ensemble of model integrations. An important advantage of using an ensemble of ocean states is that it provides a natural way to estimate cross-covariances between the fields of different physical variables constituting the model state vector, at the same time incorporating the model's dynamical and thermodynamical constraints as well as the effects of physical boundaries. Only temperature observations from the Tropical Atmosphere-Ocean array have been assimilated in this study. In order to investigate the efficacy of the multivariate scheme two data assimilation experiments are validated with a large independent set of recently published subsurface observations of salinity, zonal velocity and temperature. For reference, a third control run with no data assimilation is used to check how the data assimilation affects systematic model errors. While the performance of the UOI and MvOI is similar with respect to the temperature field, the salinity and velocity fields are greatly improved when multivariate correction is used, as evident from the analyses of the rms differences of these fields and independent observations. The MvOI assimilation is found to improve upon the control run in generating the water masses with properties close to the observed, while the UOI failed to maintain the temperature and salinity structure.

Advanced Satellite-Derived Wind Observations, Assimilation, and Targeting Strategies during TCS-08 for Developing Improved Operational Analysis and Prediction of Western Pacific Tropical Cyclones

DTIC Science & Technology

2013-09-30

TC structure evolve up to landfall or extratropical transition. In particular, winds derived from geostationary satellites have been shown to be an... extratropical transition, it is clear that a dedicated research effort is needed to optimize the satellite data processing strategies, assimilation, and...applications to better understand the behavior of the near- storm environmental flow fields during these evolutionary TC stages. To our knowledge, this

Numerical simulations of tropical cyclones with assimilation of satellite, radar and in-situ observations: lessons learned from recent field programs and real-time experimental forecasts

NASA Astrophysics Data System (ADS)

Pu, Z.; Zhang, L.

2010-12-01

The impact of data assimilation on the predictability of tropical cyclones is examined with the cases from recent field programs and real-time hurricane forecast experiments. Mesoscale numerical simulations are performed to simulate major typhoons during the T-PARC/TCS08 field campaign with the assimilation of satellite, radar and in-situ observations. Results confirmed that data assimilation has indeed resulted in improved numerical simulations of tropical cyclones. However, positive impacts from the satellite and radar data are strongly depend on the quality of these data. Specifically, it is found that the overall impacts of assimilating AIRS retrieved atmospheric temperature and moisture profiles on numerical simulations of tropical cyclones are very sensitive to the bias corrections of the data.For instance, the dry biases of moisture profiles can cause the decay of tropical cyclones in the numerical simulations.In addition, the quality of airborne Doppler radar data has strong influence on numerical simulations of tropical cyclones in terms of their track, intensity and precipitation structures. Outcomes from assimilating radar data with various quality thresholds suggest that a trade-off between the quality and area coverage of the radar data is necessary in the practice. Some of those experiences obtained from the field case studies are applied to the near-real time experimental hurricane forecasts during the 2010 hurricane season. Results and issues raised from the case studies and real-time experiments will be discussed.

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.

Revisiting the latent heat nudging scheme for the rainfall assimilation of a simulated convective storm

NASA Astrophysics Data System (ADS)

Leuenberger, D.; Rossa, A.

2007-12-01

Next-generation, operational, high-resolution numerical weather prediction models require economical assimilation schemes for radar data. In the present study we evaluate and characterise the latent heat nudging (LHN) rainfall assimilation scheme within a meso-γ scale NWP model in the framework of identical twin simulations of an idealised supercell storm. Consideration is given to the model’s dynamical response to the forcing as well as to the sensitivity of the LHN scheme to uncertainty in the observations and the environment. The results indicate that the LHN scheme is well able to capture the dynamical structure and the right rainfall amount of the storm in a perfect environment. This holds true even in degraded environments but a number of important issues arise. In particular, changes in the low-level humidity field are found to affect mainly the precipitation amplitude during the assimilation with a fast adaptation of the storm to the system dynamics determined by the environment during the free forecast. A constant bias in the environmental wind field, on the other hand, has the potential to render a successful assimilation with the LHN scheme difficult, as the velocity of the forcing is not consistent with the system propagation speed determined by the wind. If the rainfall forcing moves too fast, the system propagation is supported and the assimilated storm and forecasts initialised therefrom develop properly. A too slow forcing, on the other hand, can decelerate the system and eventually disturb the system dynamics by decoupling the low-level moisture inflow from the main updrafts during the assimilation. This distortion is sustained in the free forecast. It has further been found that a sufficient temporal resolution of the rainfall input is crucial for the successful assimilation of a fast moving, coherent convective storm and that the LHN scheme, when applied to a convective storm, appears to necessitate a careful tuning.

Stratospheric Assimilation of Chemical Tracer Observations Using a Kalman Filter. Pt. 2; Chi-Square Validated Results and Analysis of Variance and Correlation Dynamics

NASA Technical Reports Server (NTRS)

Menard, Richard; Chang, Lang-Ping

1998-01-01

A Kalman filter system designed for the assimilation of limb-sounding observations of stratospheric chemical tracers, which has four tunable covariance parameters, was developed in Part I (Menard et al. 1998) The assimilation results of CH4 observations from the Cryogenic Limb Array Etalon Sounder instrument (CLAES) and the Halogen Observation Experiment instrument (HALOE) on board of the Upper Atmosphere Research Satellite are described in this paper. A robust (chi)(sup 2) criterion, which provides a statistical validation of the forecast and observational error covariances, was used to estimate the tunable variance parameters of the system. In particular, an estimate of the model error variance was obtained. The effect of model error on the forecast error variance became critical after only three days of assimilation of CLAES observations, although it took 14 days of forecast to double the initial error variance. We further found that the model error due to numerical discretization as arising in the standard Kalman filter algorithm, is comparable in size to the physical model error due to wind and transport modeling errors together. Separate assimilations of CLAES and HALOE observations were compared to validate the state estimate away from the observed locations. A wave-breaking event that took place several thousands of kilometers away from the HALOE observation locations was well captured by the Kalman filter due to highly anisotropic forecast error correlations. The forecast error correlation in the assimilation of the CLAES observations was found to have a structure similar to that in pure forecast mode except for smaller length scales. Finally, we have conducted an analysis of the variance and correlation dynamics to determine their relative importance in chemical tracer assimilation problems. Results show that the optimality of a tracer assimilation system depends, for the most part, on having flow-dependent error correlation rather than on evolving the error variance.

Experimental Constraints on the Origin of Lunar High-Ti Ultramafic Glasses

NASA Technical Reports Server (NTRS)

Wagner, T. P.; Grove, T. L.

1996-01-01

Phase equilibria and dissolution rate experiments are used to develop a petrogenetic model for the high-Ti lunar ultramafic glasses. Near-liquidus phase relations of the Apollo 14 black glass, the most Ti-rich lunar ultramafic glass, are determined to 2.2-GPa. The liquidus is saturated with Cr-spinel at 1-atm, olivine between approximately 0.5- and 1.5-GPa, and low-Ca pyroxene + Cr-spinel above 1.5-GPa. Ilmenite does not crystallize near the liquidus and implies that high-Ti ultramafic glasses are not produced by melting of an ilmenite-saturated source. We infer that high-Ti ultramafic magmas are derived from low-Ti ultramafic parent magmas by assimilation of ilmenite +/- clinopyroxene +/- urKREEP +/- pigeonite in the shallow lunar interior. Heat is provided by adiabatic ascent of the low-Ti ultramafic primary magmas from the deeper lunar interior and crystallization of olivine during assimilation. The assimilation reaction is modeled by mass balance and requires that ilmenite and high-Ca pyroxene are assimilated in a approximately 3:1 ratio, a much higher ratio than the proportion in which these minerals are thought to exist in the lunar interior. In an effort to understand the kinetic controls on this reaction, the dissolution of ilmenite is examined experimentally in both low- and high-Ti lunar magmas. We find that ilmenite dissolves incongruently to Cr-spinel and a high-Ti melt. The dissolution reaction proceeds by a diffusion-controlled mechanism. An assimilation model for the origin of high-Ti melts is developed that leaves the magma ocean cumulates in their initial stratigraphic positions and obviates source hybridization models that require lunar overturn.

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.

Soil Respiration in European Grasslands in Relation to Climate and Assimilate Supply

PubMed Central

Bahn, Michael; Rodeghiero, Mirco; Anderson-Dunn, Margaret; Dore, Sabina; Gimeno, Cristina; Drösler, Matthias; Williams, Michael; Ammann, Christof; Berninger, Frank; Flechard, Chris; Jones, Stephanie; Balzarolo, Manuela; Kumar, Suresh; Newesely, Christian; Priwitzer, Tibor; Raschi, Antonio; Siegwolf, Rolf; Susiluoto, Sanna; Tenhunen, John; Wohlfahrt, Georg; Cernusca, Alexander

2010-01-01

Soil respiration constitutes the second largest flux of carbon (C) between terrestrial ecosystems and the atmosphere. This study provides a synthesis of soil respiration (Rs) in 20 European grasslands across a climatic transect, including ten meadows, eight pastures and two unmanaged grasslands. Maximum rates of Rs (Rsmax), Rs at a reference soil temperature (10°C; Rs10) and annual Rs (estimated for 13 sites) ranged from 1.9 to 15.9 μmol CO2 m−2 s−1, 0.3 to 5.5 μmol CO2 m−2 s−1 and 58 to 1988 g C m−2 y−1, respectively. Values obtained for Central European mountain meadows are amongst the highest so far reported for any type of ecosystem. Across all sites Rsmax was closely related to Rs10. Assimilate supply affected Rs at timescales from daily (but not necessarily diurnal) to annual. Reductions of assimilate supply by removal of aboveground biomass through grazing and cutting resulted in a rapid and a significant decrease of Rs. Temperature-independent seasonal fluctuations of Rs of an intensively managed pasture were closely related to changes in leaf area index (LAI). Across sites Rs10 increased with mean annual soil temperature (MAT), LAI and gross primary productivity (GPP), indicating that assimilate supply overrides potential acclimation to prevailing temperatures. Also annual Rs was closely related to LAI and GPP. Because the latter two parameters were coupled to MAT, temperature was a suitable surrogate for deriving estimates of annual Rs across the grasslands studied. These findings contribute to our understanding of regional patterns of soil C fluxes and highlight the importance of assimilate supply for soil CO2 emissions at various timescales. PMID:20936099

A model of regional primary production for use with coarse resolution satellite data

NASA Technical Reports Server (NTRS)

Prince, S. D.

1991-01-01

A model of crop primary production, which was originally developed to relate the amount of absorbed photosynthetically active radiation (APAR) to net production in field studies, is discussed in the context of coarse resolution regional remote sensing of primary production. The model depends on an approximately linear relationship between APAR and the normalized difference vegetation index. A more comprehensive form of the conventional model is shown to be necessary when different physiological types of plants or heterogeneous vegetation types occur within the study area. The predicted variable in the new model is total assimilation (net production plus respiration) rather than net production alone or harvest yield.

Multifunctional Collaborative Modeling and Analysis Methods in Engineering Science

NASA Technical Reports Server (NTRS)

Ransom, Jonathan B.; Broduer, Steve (Technical Monitor)

2001-01-01

Engineers are challenged to produce better designs in less time and for less cost. Hence, to investigate novel and revolutionary design concepts, accurate, high-fidelity results must be assimilated rapidly into the design, analysis, and simulation process. This assimilation should consider diverse mathematical modeling and multi-discipline interactions necessitated by concepts exploiting advanced materials and structures. Integrated high-fidelity methods with diverse engineering applications provide the enabling technologies to assimilate these high-fidelity, multi-disciplinary results rapidly at an early stage in the design. These integrated methods must be multifunctional, collaborative, and applicable to the general field of engineering science and mechanics. Multifunctional methodologies and analysis procedures are formulated for interfacing diverse subdomain idealizations including multi-fidelity modeling methods and multi-discipline analysis methods. These methods, based on the method of weighted residuals, ensure accurate compatibility of primary and secondary variables across the subdomain interfaces. Methods are developed using diverse mathematical modeling (i.e., finite difference and finite element methods) and multi-fidelity modeling among the subdomains. Several benchmark scalar-field and vector-field problems in engineering science are presented with extensions to multidisciplinary problems. Results for all problems presented are in overall good agreement with the exact analytical solution or the reference numerical solution. Based on the results, the integrated modeling approach using the finite element method for multi-fidelity discretization among the subdomains is identified as most robust. The multiple-method approach is advantageous when interfacing diverse disciplines in which each of the method's strengths are utilized. The multifunctional methodology presented provides an effective mechanism by which domains with diverse idealizations are interfaced. This capability rapidly provides the high-fidelity results needed in the early design phase. Moreover, the capability is applicable to the general field of engineering science and mechanics. Hence, it provides a collaborative capability that accounts for interactions among engineering analysis methods.

Assessment of SMAP soil moisture for global simulation of gross primary production

NASA Astrophysics Data System (ADS)

He, Liming; Chen, Jing M.; Liu, Jane; Bélair, Stéphane; Luo, Xiangzhong

2017-07-01

In this study, high-quality soil moisture data derived from the Soil Moisture Active Passive (SMAP) satellite measurements are evaluated from a perspective of improving the estimation of the global gross primary production (GPP) using a process-based ecosystem model, namely, the Boreal Ecosystem Productivity Simulator (BEPS). The SMAP soil moisture data are assimilated into BEPS using an ensemble Kalman filter. The correlation coefficient (r) between simulated GPP from the sunlit leaves and Sun-induced chlorophyll fluorescence (SIF) measured by Global Ozone Monitoring Experiment-2 is used as an indicator to evaluate the performance of the GPP simulation. Areas with SMAP data in low quality (i.e., forests), or with SIF in low magnitude (e.g., deserts), or both are excluded from the analysis. With the assimilated SMAP data, the r value is enhanced for Africa, Asia, and North America by 0.016, 0.013, and 0.013, respectively (p < 0.05). Significant improvement in r appears in single-cropping agricultural land where the irrigation is not considered in the model but well captured by SMAP (e.g., 0.09 in North America, p < 0.05). With the assimilation of SMAP, areas with weak model performances are identified in double or triple cropping cropland (e.g., part of North China Plain) and/or mountainous area (e.g., Spain and Turkey). The correlation coefficient is enhanced by 0.01 in global average for shrub, grass, and cropland. This enhancement is small and insignificant because nonwater-stressed areas are included.

Model-based assessment of a Northwestern Tropical Pacific moored array to monitor intraseasonal variability

NASA Astrophysics Data System (ADS)

Liu, Danian; Zhu, Jiang; Shu, Yeqiang; Wang, Dongxiao; Wang, Weiqiang; Cai, Shuqun

2018-06-01

The Northwestern Tropical Pacific Ocean (NWTPO) moorings observing system, including 15 moorings, was established in 2013 to provide velocity profile data. Observing system simulation experiments (OSSEs) were carried out to assess the ability of the observation system to monitor intraseasonal variability in a pilot study, where ideal "mooring-observed" velocity was assimilated using Ensemble Optimal Interpolation (EnOI) based on the Regional Oceanic Modeling System (ROMS). Because errors between the control and "nature" runs have a mesoscale structure, a random ensemble derived from 20-90-day bandpass-filtered nine-year model outputs is proved to be more appropriate for the NWTPO mooring array assimilation than a random ensemble derived from a 30-day running mean. The simulation of the intraseasonal currents in the North Equatorial Current (NEC), North Equatorial Countercurrent (NECC), and Equatorial Undercurrent (EUC) areas can be improved by assimilating velocity profiles using a 20-90-day bandpass-filtered ensemble. The root mean square errors (RMSEs) of the intraseasonal zonal (U) and meridional velocity (V) above 500 m depth within the study area (between 0°N-18°N and 122°E-147°E) were reduced by 15.4% and 16.9%, respectively. Improvements in the downstream area of the NEC moorings transect were optimum where the RMSEs of the intraseasonal velocities above 500 m were reduced by more than 30%. Assimilating velocity profiles can have a positive impact on the simulation and forecast of thermohaline structure and sea level anomalies in the ocean.

Modifications to a LATE MERISTEM IDENTITY-1 gene are responsible for the major leaf shapes of Upland cotton (Gossypium hirsutum L.)

USDA-ARS?s Scientific Manuscript database

Leaf shape varies spectacularly among plants. Leaves are the primary source of photo-assimilate in crop plants and understanding the genetic basis of variation in leaf morphology is critical to improving agricultural productivity. Leaf shape played a unique role in cotton improvement, as breeders ha...

Correlationally Assessing the Relationship of Information Technology Investments in Electronic Medical Records to Business Value

ERIC Educational Resources Information Center

Richardson, Daniel J.

2009-01-01

The lag in information exchange and assimilation adoption experienced by modern primary care physicians in the conduct of evidence based medicine may be affecting health care system productivity and patient quality of care. Further, interest in whether or not information technology (IT) investments show an increase in business value has increased…

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

The work is devoted to data assimilation algorithm for atmospheric chemistry transport and transformation models. In the work a control function is introduced into the model source term (emission rate) to provide flexibility to adjust to data. This function is evaluated as the constrained minimum of the target functional combining a control function norm with a norm of the misfit between measured data and its model-simulated analog. Transport and transformation processes model is acting as a constraint. The constrained minimization problem is solved with Euler-Lagrange variational principle [1] which allows reducing it to a system of direct, adjoint and control function estimate relations. This provides a physically-plausible structure of the resulting analysis without model error covariance matrices that are sought within conventional approaches to data assimilation. High dimensionality of the atmospheric chemistry models and a real-time mode of operation demand for computational efficiency of the data assimilation algorithms. Computational issues with complicated models can be solved by using a splitting technique. Within this approach a complex model is split to a set of relatively independent simpler models equipped with a coupling procedure. In a fine-grained approach data assimilation is carried out quasi-independently on the separate splitting stages with shared measurement data [2]. In integrated schemes data assimilation is carried out with respect to the split model as a whole. We compare the two approaches both theoretically and numerically. Data assimilation on the transport stage is carried out with a direct algorithm without iterations. Different algorithms to assimilate data on nonlinear transformation stage are compared. In the work we compare data assimilation results for both artificial and real measurement data. With these data we study the impact of transformation processes and data assimilation to the performance of the modeling system [3]. The work has been partially supported by RFBR grant 14-01-00125 and RAS Presidium II.4P. References: [1] Penenko V.V., Tsvetova E.A., Penenko A.V. Development of variational approach for direct and inverse problems of atmospheric hydrodynamics and chemistry // IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS, 2015, v 51 , p. 311 - 319 [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. [3] A. Penenko; V. Penenko; R. Nuterman; A. Baklanov and A. Mahura Direct variational data assimilation algorithm for atmospheric chemistry data with transport and transformation model, Proc. SPIE 9680, 21st International Symposium Atmospheric and Ocean Optics: Atmospheric Physics, 968076 (November 19, 2015); doi:10.1117/12.2206008;http://dx.doi.org/10.1117/12.2206008

The origin and evolution of sulfur in an Archean volcano-sedimentary basin, Deer Lake area, Minnesota. M.S. Thesis

NASA Technical Reports Server (NTRS)

Nicol, D. L.

1980-01-01

Rocks of the Deer Lake area, northcentral Minnesota, consist of Archean (age greater than 2.6 billion years) metasediments and metavolcanics intruded by mafic layered sills. Geologic and sulfur isotopic data suggest that sulfides in the sediments are bacteriogenic, having formed in response to the activity of sulfate reducing bacteria during diagenesis. Deposition of the sediments appears to have occurred in a deep marine basin with restricted circulation of sea water. The bulk of the sulfur in the igneous rocks is of deep seated origin, but basal contacts of the sills show evidence of assimilation of biogenic sulfur from the intruded sediments. This assimilation of biogenic sulfur is the primary geochemical control of local Cu-Ni sulfide mineralization.

Developmental Trajectories of Acculturation in Hispanic Adolescents: Associations With Family Functioning and Adolescent Risk Behavior

PubMed Central

Schwartz, Seth J.; Rosiers, Sabrina Des; Huang, Shi; Zamboanga, Byron L.; Unger, Jennifer B.; Knight, George P.; Pantin, Hilda; Szapocznik, José

2012-01-01

The present study examined longitudinal acculturation patterns, and their associations with family functioning and adolescent risk behaviors, in Hispanic immigrant families. A sample of 266 Hispanic adolescents (mean age 13.4) and their primary parents completed measures of acculturation, family functioning, and adolescent conduct problems, substance use, and sexual behavior at five timepoints. Mixture models yielded three trajectory classes apiece for adolescent and parent acculturation. Assimilated adolescents reported the poorest family functioning, but adolescent assimilation negatively predicted adolescent cigarette smoking, sexual activity, and unprotected sex indirectly through family functioning. Follow-up analyses indicated that discrepancies between adolescent and parent family functioning reports predicted these adolescent outcomes. Results are discussed regarding acculturation trajectories, adolescent risk behavior, and the mediating role of family functioning. PMID:23848416

Fungal endophytes of Catharanthus roseus enhance vindoline content by modulating structural and regulatory genes related to terpenoid indole alkaloid biosynthesis

PubMed Central

Pandey, Shiv S.; Singh, Sucheta; Babu, C. S. Vivek; Shanker, Karuna; Srivastava, N. K.; Shukla, Ashutosh K.; Kalra, Alok

2016-01-01

Not much is known about the mechanism of endophyte-mediated induction of secondary metabolite production in Catharanthus roseus. In the present study two fungal endophytes, Curvularia sp. CATDLF5 and Choanephora infundibulifera CATDLF6 were isolated from the leaves of the plant that were found to enhance vindoline content by 229–403%. The isolated endophytes did not affect the primary metabolism of the plant as the maximum quantum efficiency of PSII, net CO2 assimilation, plant biomass and starch content of endophyte-inoculated plants was similar to endophyte-free control plants. Expression of terpenoid indole alkaloid (TIA) pathway genes, geraniol 10-hydroxylase (G10H), tryptophan decarboxylase (TDC), strictosidine synthase (STR), 16-hydoxytabersonine-O-methyltransferase (16OMT), desacetoxyvindoline-4-hydroxylase (D4H), deacetylvindoline-4-O-acetyltransferase (DAT) were upregulated in endophyte-inoculated plants. Endophyte inoculation upregulated the expression of the gene for transcriptional activator octadecanoid-responsive Catharanthus AP2-domain protein (ORCA3) and downregulated the expression of Cys2/His2-type zinc finger protein family transcriptional repressors (ZCTs). The gene for the vacuolar class III peroxidase (PRX1), responsible for coupling vindoline and catharanthine, was upregulated in endophyte-inoculated plants. These endophytes may enhance vindoline production by modulating the expression of key structural and regulatory genes of vindoline biosynthesis without affecting the primary metabolism of the host plant. PMID:27220774

Structure of the Upper Troposphere-Lower Stratosphere (UTLS) in GEOS-5

NASA Technical Reports Server (NTRS)

Pawson, Steven

2011-01-01

This study examines the structure of the upper troposphere and lower stratosphere in the GEOS-5 data assimilation system. Near-real time analyses, with a horizontal resolution of one-half or one quarter degree and a vertical resolution of about 1km in the tropopause region are examined with an emphasis on spatial structures at and around the tropopause. The contributions of in-situ observations of temperature and microwave and infrared radiances to the analyses are discussed, with some focus on the interplay between these types of observations. For a historical analysis (Merra) performed with GEOS-5, the impacts of changing observations on the assimilation system are examined in some detail - this documents some aspects of the time dependence of analysis that must be taken into account in the isolation of true geophysical trends. Finally, some sensitivities of the ozone analyses to input data and correlated errors between temperature and ozone are discussed.

What predicts successful literacy acquisition in a second language?

PubMed Central

Frost, Ram; Siegelman, Noam; Narkiss, Alona; Afek, Liron

2013-01-01

We examined whether success (or failure) in assimilating the structure of a second language could be predicted by general statistical learning abilities that are non-linguistic in nature. We employed a visual statistical learning (VSL) task, monitoring our participants’ implicit learning of the transitional probabilities of visual shapes. A pretest revealed that performance in the VSL task is not correlated with abilities related to a general G factor or working memory. We found that native speakers of English who picked up the implicit statistical structure embedded in the continuous stream of shapes, on average, better assimilated the Semitic structure of Hebrew words. Our findings thus suggest that languages and their writing systems are characterized by idiosyncratic correlations of form and meaning, and these are picked up in the process of literacy acquisition, as they are picked up in any other type of learning, for the purpose of making sense of the environment. PMID:23698615

Leaf nitrogen assimilation and partitioning differ among subtropical forest plants in response to canopy addition of nitrogen treatments.

PubMed

Liu, Nan; Wu, Shuhua; Guo, Qinfeng; Wang, Jiaxin; Cao, Ce; Wang, Jun

2018-05-12

Global increases in nitrogen deposition may alter forest structure and function by interfering with plant nitrogen metabolism (e.g., assimilation and partitioning) and subsequent carbon assimilation, but it is unclear how these responses to nitrogen deposition differ among species. In this study, we conducted a 2-year experiment to investigate the effects of canopy addition of nitrogen (CAN) on leaf nitrogen assimilation and partitioning in three subtropical forest plants (Castanea henryi, Ardisia quinquegona, and Blastus cochinchinensis). We hypothesized that responses of leaf nitrogen assimilation and partitioning to CAN differ among subtropical forest plants. CAN increased leaf nitrate reductase (NR) activity, and leaf nitrogen and chlorophyll contents but reduced leaf maximum photosynthetic rate (A max ), photosynthetic nitrogen use efficiency (PNUE), ribulose-1,5-bisphosphate carboxylase (Rubisco) activity, and metabolic protein content of an overstory tree species C. henryi. In an understory tree A. quinquegona, CAN increased NR activity and glutamine synthetase activity and therefore increased metabolic protein synthesis (e.g., Rubisco) in leaves. In the shrub B. cochinchinensis, CAN increased A max , PNUE, Rubisco content, metabolic protein content, and Rubisco activity in leaves. Leaf nitrogen assimilation and partitioning results indicated that A. quinquegona and B. cochinchinensis may better acclimate to CAN than C. henryi and that the acclimation mechanism differs among the species. Results from this study suggest that long-term elevated atmospheric nitrogen deposition has contributed to the ongoing transformation of subtropical forests into communities dominated by small trees and shrubs. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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.

Assimilation of all-weather GMI and ATMS observations into HWRF

NASA Astrophysics Data System (ADS)

Moradi, I.; Evans, F.; McCarty, W.; Marks, F.; Eriksson, P.

2017-12-01

We propose a novel Bayesian Monte Carlo Integration (BMCI) technique to retrieve the profiles of temperature, water vapor, and cloud liquid/ice water content from microwave cloudy measurements in the presence of TCs. These retrievals then can either be directly used by meteorologists to analyze the structure of TCs or be assimilated to provide accurate initial conditions for the NWP models. The technique is applied to the data from the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) and Global Precipitation Measurement (GPM) Microwave Imager (GMI).

From chemolithoautotrophs to electrolithoautotrophs: CO2 fixation by Fe(II)-oxidizing bacteria coupled with direct uptake of electrons from solid electron sources.

PubMed

Ishii, Takumi; Kawaichi, Satoshi; Nakagawa, Hirotaka; Hashimoto, Kazuhito; Nakamura, Ryuhei

2015-01-01

At deep-sea vent systems, hydrothermal emissions rich in reductive chemicals replace solar energy as fuels to support microbial carbon assimilation. Until recently, all the microbial components at vent systems have been assumed to be fostered by the primary production of chemolithoautotrophs; however, both the laboratory and on-site studies demonstrated electrical current generation at vent systems and have suggested that a portion of microbial carbon assimilation is stimulated by the direct uptake of electrons from electrically conductive minerals. Here we show that chemolithoautotrophic Fe(II)-oxidizing bacterium, Acidithiobacillus ferrooxidans, switches the electron source for carbon assimilation from diffusible Fe(2+) ions to an electrode under the condition that electrical current is the only source of energy and electrons. Site-specific marking of a cytochrome aa3 complex (aa3 complex) and a cytochrome bc1 complex (bc1 complex) in viable cells demonstrated that the electrons taken directly from an electrode are used for O2 reduction via a down-hill pathway, which generates proton motive force that is used for pushing the electrons to NAD(+) through a bc1 complex. Activation of carbon dioxide fixation by a direct electron uptake was also confirmed by the clear potential dependency of cell growth. These results reveal a previously unknown bioenergetic versatility of Fe(II)-oxidizing bacteria to use solid electron sources and will help with understanding carbon assimilation of microbial components living in electronically conductive chimney habitats.

From chemolithoautotrophs to electrolithoautotrophs: CO2 fixation by Fe(II)-oxidizing bacteria coupled with direct uptake of electrons from solid electron sources

PubMed Central

Ishii, Takumi; Kawaichi, Satoshi; Nakagawa, Hirotaka; Hashimoto, Kazuhito; Nakamura, Ryuhei

2015-01-01

At deep-sea vent systems, hydrothermal emissions rich in reductive chemicals replace solar energy as fuels to support microbial carbon assimilation. Until recently, all the microbial components at vent systems have been assumed to be fostered by the primary production of chemolithoautotrophs; however, both the laboratory and on-site studies demonstrated electrical current generation at vent systems and have suggested that a portion of microbial carbon assimilation is stimulated by the direct uptake of electrons from electrically conductive minerals. Here we show that chemolithoautotrophic Fe(II)-oxidizing bacterium, Acidithiobacillus ferrooxidans, switches the electron source for carbon assimilation from diffusible Fe2+ ions to an electrode under the condition that electrical current is the only source of energy and electrons. Site-specific marking of a cytochrome aa3 complex (aa3 complex) and a cytochrome bc1 complex (bc1 complex) in viable cells demonstrated that the electrons taken directly from an electrode are used for O2 reduction via a down-hill pathway, which generates proton motive force that is used for pushing the electrons to NAD+ through a bc1 complex. Activation of carbon dioxide fixation by a direct electron uptake was also confirmed by the clear potential dependency of cell growth. These results reveal a previously unknown bioenergetic versatility of Fe(II)-oxidizing bacteria to use solid electron sources and will help with understanding carbon assimilation of microbial components living in electronically conductive chimney habitats. PMID:26500609

OLYMPEX Data Workshop: GPM View

NASA Technical Reports Server (NTRS)

Petersen, W.

2017-01-01

OLYMPEX Primary Objectives: Datasets to enable: (1) Direct validation over complex terrain at multiple scales, liquid and frozen precip types, (a) Do we capture terrain and synoptic regime transitions, orographic enhancements/structure, full range of precipitation intensity (e.g., very light to heavy) and types, spatial variability? (b) How well can we estimate space/time-accumulated precipitation over terrain (liquid + frozen)? (2) Physical validation of algorithms in mid-latitude cold season frontal systems over ocean and complex terrain, (a) What are the column properties of frozen, melting, liquid hydrometeors-their relative contributions to estimated surface precipitation, transition under the influence of terrain gradients, and systematic variability as a function of synoptic regime? (3) Integrated hydrologic validation in complex terrain, (a) Can satellite estimates be combined with modeling over complex topography to drive improved products (assimilation, downscaling) [Level IV products] (b) What are capabilities and limitations for use of satellite-based precipitation estimates in stream/river flow forecasting?

Technical Report Series on Global Modeling and Data Assimilation. Volume 40; Soil Moisture Active Passive (SMAP) Project Assessment Report for the Beta-Release L4_SM Data Product

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Liu, Qing; Colliander, Andreas; Conaty, Austin; Jackson, Thomas; Kimball, John

2015-01-01

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public beta release scheduled for 30 October 2015. The primary objective of the beta release is to allow users to familiarize themselves with the data product before the validated product becomes available. The beta release also allows users to conduct their own assessment of the data and to provide feedback to the L4_SM science data product team. The assessment of the L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to upscaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 1 validation and supports the beta release of the data. The validation against sparse network measurements and the evaluation of the assimilation diagnostics address Stage 2 validation criteria by expanding the assessment to regional and global scales.

Effects of Nitrogen Fertilization on Synthesis of Primary and Secondary Metabolites in Three Varieties of Kacip Fatimah (Labisia Pumila Blume)

PubMed Central

Ibrahim, Mohd Hafiz; Jaafar, Hawa Z.E.; Rahmat, Asmah; Rahman, Zaharah Abdul

2011-01-01

A split plot 3 by 4 experiment was designed to examine the impact of 15-week variable levels of nitrogen fertilization (0, 90, 180 and 270 kg N/ha) on the characteristics of total flavonoids (TF), total phenolics (TP), total non structurable carbohydrate (TNC), net assimilation rate, leaf chlorophyll content, carbon to nitrogen ratio (C/N), phenyl alanine lyase activity (PAL) and protein content, and their relationships, in three varieties of Labisia pumila Blume (alata, pumila and lanceolata). The treatment effects were solely contributed by nitrogen application; there was neither varietal nor interaction effect observed. As nitrogen levels increased from 0 to 270 kg N/ha, the production of TNC was found to decrease steadily. Production of TF and TP reached their peaks under 0 followed by 90, 180 and 270 kg N/ha treatment. However, net assimilation rate was enhanced as nitrogen fertilization increased from 0 to 270 kg N/ha. The increase in production of TP and TF under low nitrogen levels (0 and 90 kg N/ha) was found to be correlated with enhanced PAL activity. The enhancement in PAL activity was followed by reduction in production of soluble protein under low nitrogen fertilization indicating more availability of amino acid phenyl alanine (phe) under low nitrogen content that stimulate the production of carbon based secondary metabolites (CBSM). The latter was manifested by high C/N ratio in L. pumila plants. PMID:21954355

Symplasmic transport and phloem loading in gymnosperm leaves

PubMed Central

Liesche, Johannes; Martens, Helle Juel

2010-01-01

Despite more than 130 years of research, phloem loading is far from being understood in gymnosperms. In part this is due to the special architecture of their leaves. They differ from angiosperm leaves among others by having a transfusion tissue between bundle sheath and the axial vascular elements. This article reviews the somewhat inaccessible and/or neglected literature and identifies the key points for pre-phloem transport and loading of photoassimilates. The pre-phloem pathway of assimilates is structurally characterized by a high number of plasmodesmata between all cell types starting in the mesophyll and continuing via bundle sheath, transfusion parenchyma, Strasburger cells up to the sieve elements. Occurrence of median cavities and branching indicates that primary plasmodesmata get secondarily modified and multiplied during expansion growth. Only functional tests can elucidate whether this symplasmic pathway is indeed continuous for assimilates, and if phloem loading in gymnosperms is comparable with the symplasmic loading mode in many angiosperm trees. In contrast to angiosperms, the bundle sheath has properties of an endodermis and is equipped with Casparian strips or other wall modifications that form a domain border for any apoplasmic transport. It constitutes a key point of control for nutrient transport, where the opposing flow of mineral nutrients and photoassimilates has to be accommodated in each single cell, bringing to mind the principle of a revolving door. The review lists a number of experiments needed to elucidate the mode of phloem loading in gymnosperms. PMID:21107620

Biomagnification profiles of polycyclic aromatic hydrocarbons, alkylphenols and polychlorinated biphenyls in Tokyo Bay elucidated by delta13C and delta15N isotope ratios as guides to trophic web structure.

PubMed

Takeuchi, Ichiro; Miyoshi, Noriko; Mizukawa, Kaoruko; Takada, Hideshige; Ikemoto, Tokutaka; Omori, Koji; Tsuchiya, Kotaro

2009-05-01

Biomagnification profiles of polycyclic aromatic hydrocarbons (PAHs), alkylphenols, and polychlorinated biphenyls (PCBs) from the innermost part of Tokyo Bay, Japan were analyzed using stable carbon (delta(13)C) and nitrogen (delta(15)N) isotope ratios as guides to trophic web structure. delta(15)N analysis indicated that all species of mollusks tested were primary consumers, while decapods and fish were secondary consumers. Higher concentrations of PCBs occurred in decapods and fish than in mollusks. In contrast, concentrations of PAHs and alkylphenols were lower in decapods and fish than in mollusks. Unlike PCBs, whose concentrations largely increased with increasing delta(15)N (i.e. increasing trophic level), all PAHs and alkylphenols analyzed followed a reverse trend. Molecular weights of PAHs are lower than those of PCBs, therefore low membrane permeability caused by large molecular size is an unlikely factor in the "biodilution" of PAHs. Organisms at higher trophic levels may rapidly metabolize PAHs or they may assimilate less of them.

Patterns and variability in seedling carbon assimilation: implications for tree recruitment under climate change.

PubMed

Peltier, Drew M P; Ibáñez, Inés

2015-01-01

Predicting future forests' structure and functioning is a critical goal for ecologists, thus information on seedling recruitment will be crucial in determining the composition and structure of future forest ecosystems. In particular, seedlings' photosynthetic response to a changing environment will be a key component determining whether particular species establish enough individuals to maintain populations, as growth is a major determinant of survival. We quantified photosynthetic responses of sugar maple (Acer saccharum Marsh.), pignut hickory (Carya glabra Mill.), northern red oak (Quercus rubra L.) and eastern black oak (Quercus velutina Lam.) seedlings to environmental conditions including light habitat, temperature, soil moisture and vapor pressure deficit (VPD) using extensive in situ gas exchange measurements spanning an entire growing season. We estimated the parameters in a hierarchical Bayesian version of the Farquhar model of photosynthesis, additionally informed by soil moisture and VPD, and found that maximum Rubisco carboxylation (V(cmax)) and electron transport (J(max)) rates showed significant seasonal variation, but not the peaked patterns observed in studies of adult trees. Vapor pressure deficit and soil moisture limited J(max) and V(cmax) for all four species. Predictions indicate large declines in summer carbon assimilation rates under a 3 °C increase in mean annual temperature projected by climate models, while spring and fall assimilation rates may increase. Our model predicts decreases in summer assimilation rates in gap habitats with at least 90% probability, and with 20-99.9% probability in understory habitats depending on species. Predictions also show 70% probability of increases in fall and 52% probability in spring in understory habitats. All species were impacted, but our findings suggest that oak species may be favored in northeastern North America under projected increases in temperature due to superior assimilation rates under these conditions, though as growing seasons become longer, the effects of climate change on seedling photosynthesis may be complex. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Mantle-circulation models with sequential data assimilation: inferring present-day mantle structure from plate-motion histories.

PubMed

Bunge, Hans-Peter; Richards, M A; Baumgardner, J R

2002-11-15

Data assimilation is an approach to studying geodynamic models consistent simultaneously with observables and the governing equations of mantle flow. Such an approach is essential in mantle circulation models, where we seek to constrain an unknown initial condition some time in the past, and thus cannot hope to use first-principles convection calculations to infer the flow history of the mantle. One of the most important observables for mantle-flow history comes from models of Mesozoic and Cenozoic plate motion that provide constraints not only on the surface velocity of the mantle but also on the evolution of internal mantle-buoyancy forces due to subducted oceanic slabs. Here we present five mantle circulation models with an assimilated plate-motion history spanning the past 120 Myr, a time period for which reliable plate-motion reconstructions are available. All models agree well with upper- and mid-mantle heterogeneity imaged by seismic tomography. A simple standard model of whole-mantle convection, including a factor 40 viscosity increase from the upper to the lower mantle and predominantly internal heat generation, reveals downwellings related to Farallon and Tethys subduction. Adding 35% bottom heating from the core has the predictable effect of producing prominent high-temperature anomalies and a strong thermal boundary layer at the base of the mantle. Significantly delaying mantle flow through the transition zone either by modelling the dynamic effects of an endothermic phase reaction or by including a steep, factor 100, viscosity rise from the upper to the lower mantle results in substantial transition-zone heterogeneity, enhanced by the effects of trench migration implicit in the assimilated plate-motion history. An expected result is the failure to account for heterogeneity structure in the deepest mantle below 1500 km, which is influenced by Jurassic plate motions and thus cannot be modelled from sequential assimilation of plate motion histories limited in age to the Cretaceous. This result implies that sequential assimilation of past plate-motion models is ineffective in studying the temporal evolution of core-mantle-boundary heterogeneity, and that a method for extrapolating present-day information backwards in time is required. For short time periods (of the order of perhaps a few tens of Myr) such a method exists in the form of crude 'backward' convection calculations. For longer time periods (of the order of a mantle overturn), a rigorous approach to extrapolating information back in time exists in the form of iterative nonlinear optimization methods that carry assimilated information into the past through the use of an adjoint mantle convection model.

The Global Precipitation Mission

NASA Technical Reports Server (NTRS)

Braun, Scott; Kummerow, Christian

2000-01-01

The Global Precipitation Mission (GPM), expected to begin around 2006, is a follow-up to the Tropical Rainfall Measuring Mission (TRMM). Unlike TRMM, which primarily samples the tropics, GPM will sample both the tropics and mid-latitudes. The primary, or core, satellite will be a single, enhanced TRMM satellite that can quantify the 3-D spatial distributions of precipitation and its associated latent heat release. The core satellite will be complemented by a constellation of very small and inexpensive drones with passive microwave instruments that will sample the rainfall with sufficient frequency to be not only of climate interest, but also have local, short-term impacts by providing global rainfall coverage at approx. 3 h intervals. The data is expected to have substantial impact upon quantitative precipitation estimation/forecasting and data assimilation into global and mesoscale numerical models. Based upon previous studies of rainfall data assimilation, GPM is expected to lead to significant improvements in forecasts of extratropical and tropical cyclones. For example, GPM rainfall data can provide improved initialization of frontal systems over the Pacific and Atlantic Oceans. The purpose of this talk is to provide information about GPM to the USWRP (U.S. Weather Research Program) community and to discuss impacts on quantitative precipitation estimation/forecasting and data assimilation.

Comparing WSA coronal and solar wind model predictions driven by line-of-sight and vector HMI ADAPT maps

NASA Astrophysics Data System (ADS)

Arge, C. N.; Henney, C. J.; Shurkin, K.; Wallace, S.

2017-12-01

As the primary input to nearly all coronal models, reliable estimates of the global solar photospheric magnetic field distribution are critical for accurate modeling and understanding of solar and heliospheric magnetic fields. The Air Force Data Assimilative Photospheric flux Transport (ADAPT) model generates synchronic (i.e., globally instantaneous) maps by evolving observed solar magnetic flux using relatively well understood transport processes when measurements are not available and then updating modeled flux with new observations (available from both the Earth and the far-side of the Sun) using data assimilation methods that rigorously take into account model and observational uncertainties. ADAPT is capable of assimilating line-of-sight and vector magnetic field data from all observatory sources including the expected photospheric vector magnetograms from the Polarimetric and Helioseismic Imager (PHI) on the Solar Orbiter, as well as those generated using helioseismic methods. This paper compares Wang-Sheeley-Arge (WSA) coronal and solar wind modeling results at Earth and STEREO A & B using ADAPT input model maps derived from both line-of-site and vector SDO/HMI magnetograms that include methods for incorporating observations of a large, newly emerged (July 2010) far-side active region (AR11087).

Algal Nitrate Assimilation and Productivity in an Urban, Concrete-Lined Stream Dominated by Tertiary Treated Municipal Waste-Water

NASA Astrophysics Data System (ADS)

Kent, R. H.; Burton, C. A.

2001-12-01

This study examined the extent and variabiltity of nitrate loss in a 2.85 km reach of Cucamonga Creek, which is concrete-lined and dominated by treated municipal waste-water. Primary production was measured to determine if the loss could be attributed to algal assimilation. Samples for nitrite plus nitrate analysis were collected at the top and bottom of the study reach every hour throughout the 24-hour sampling period; samples for analyses of other parameters were collected less frequently. Water temperature, dissolved oxygen (DO), pH and specific conductance were monitored continuously throughout the sampling period using in-stream probes. During the two weeks prior to the study, periphyton samples were collected periodically at four stations along the reach for standing crop measurements and a growth rate time-series using Chlorophyll A and ash-free-dry mass. Water samples from the upstream station were compared to those taken an hour later (the approximate travel time) at the downstream station. Nitrate concentrations were lower at the downstream station in 21 of 25 of the paired samples, indicating nearly continuous loss in the reach. The total loss of NO3 for the day was about 0.71 g as N/m2. Most of the loss occurred during daylight hours, with the peak occurring at midday. During the night, CO2 concentrations were relatively constant at about 25 mg/L. Concentrations began to decline at sunrise, and declined to 0 mg/L at the lower site after midday. Peak nitrate loss occurred at about the same time as the CO2 concentration was at its minimum. DO declined slightly during the night, began to rise at sunrise, reached a peak during midday, and declined in late afternoon through evening; pH followed a similar pattern. Net primary productivity, as measured by the differences in DO between the two sites was 13 g O2/m2 for the day. Using the Redfield ratio, the predicted nitrate assimilation is about 0.66 g NO3 as N/m2. The continuous loss of nitrate between the two sites; the comparability between the observed loss in nitrate and that predicted using the Redfield ratio; and the timing of changes in nitrate loss, DO, pH and CO2 indicate that nitrate loss in this concrete-lined channel was primarily due to algal assimilation. The timing of the peak nitrate loss relative to the depletion of CO2 suggests that CO2 may be limiting photosynthesis, and therefore assimilation of nitrate by algae.

A Civilising Mission? Perceptions and Representations of the New Zealand Native Schools System

ERIC Educational Resources Information Center

Simon, Judith, Ed.; Smith, Linda Tuhiwai, Ed.

The Native Schools system was a system of village primary schools for Maori children operated by the New Zealand state from 1867 to 1969. The official purpose of the system was assimilation. Virtually all previous historical accounts of the Native Schools have been written by Pakeha (non-Maori, usually of European descent) and based on material…

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.

Impact of assimilation of conventional and satellite meteorological observations on the numerical simulation of a Bay of Bengal Tropical Cyclone of November 2008 near Tamilnadu using WRF model

NASA Astrophysics Data System (ADS)

Srinivas, C. V.; Yesubabu, V.; Venkatesan, R.; Ramarkrishna, S. S. V. S.

2010-12-01

The objective of this study is to examine the impact of assimilation of conventional and satellite data on the prediction of a severe cyclonic storm that formed in the Bay of Bengal during November 2008 with the four-dimensional data assimilation (FDDA) technique. The Weather Research and Forecasting (WRF ARW) model was used to study the structure, evolution, and intensification of the storm. Five sets of numerical simulations were performed using the WRF. In the first one, called Control run, the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) was used for the initial and boundary conditions. In the remaining experiments available observations were used to obtain an improved analysis and FDDA grid nudging was performed for a pre-forecast period of 24 h. The second simulation (FDDAALL) was performed with all the data of the Quick Scatterometer (QSCAT), Special Sensor Microwave Imager (SSM/I) winds, conventional surface, and upper air meteorological observations. QSCAT wind alone was used in the third simulation (FDDAQSCAT), the SSM/I wind alone in the fourth (FDDASSMI) and the conventional observations alone in the fifth (FDDAAWS). The FDDAALL with assimilation of all observations, produced sea level pressure pattern closely agreeing with the analysis. Examination of various parameters indicated that the Control run over predicted the intensity of the storm with large error in its track and landfall position. The assimilation experiment with QSCAT winds performed marginally better than the one with SSM/I winds due to better representation of surface wind vectors. The FDDAALL outperformed all the simulations for the intensity, movement, and rainfall associated with the storm. Results suggest that the combination of land-based surface, upper air observations along with satellite winds for assimilation produced better prediction than the assimilation with individual data sets.

Physical heterogeneity and aquatic community function in river networks: A case study from the Kanawha River Basin, USA

NASA Astrophysics Data System (ADS)

Thoms, M. C.; Delong, M. D.; Flotemersch, J. E.; Collins, S. E.

2017-08-01

The geomorphological character of a river network provides the template upon which evolution acts to create unique biological communities. Deciphering commonly observed patterns and processes within riverine landscapes resulting from the interplay between physical and biological components is a central tenet for the interdisciplinary field of river science. Relationships between the physical heterogeneity and food web character of functional process zones (FPZs) - large tracts of river with a similar geomorphic character -in the Kanawha River (West Virginia, USA) are examined in this study. Food web character was measured as food chain length (FCL), which reflects ecological community structure and ecosystem function. Our results show that the same basal resources were present throughout the Kanawha River but that their assimilation into the aquatic food web by primary consumers differed between FPZs. Differences in the trophic position of higher consumers (fish) were also recorded between FPZs. Overall, the morphological heterogeneity and heterogeneity of the river bed sediment of FPZs were significantly correlated with FCL. Specifically, FCL increases with greater FPZ physical heterogeneity. The result of this study does not support the current paradigm that ecosystem size is the primary determinant of food web character in river ecosystems.

Improving volcanic sulfur dioxide cloud dispersal forecasts by progressive assimilation of satellite observations

NASA Astrophysics Data System (ADS)

Boichu, Marie; Clarisse, Lieven; Khvorostyanov, Dmitry; Clerbaux, Cathy

2014-04-01

Forecasting the dispersal of volcanic clouds during an eruption is of primary importance, especially for ensuring aviation safety. As volcanic emissions are characterized by rapid variations of emission rate and height, the (generally) high level of uncertainty in the emission parameters represents a critical issue that limits the robustness of volcanic cloud dispersal forecasts. An inverse modeling scheme, combining satellite observations of the volcanic cloud with a regional chemistry-transport model, allows reconstructing this source term at high temporal resolution. We demonstrate here how a progressive assimilation of freshly acquired satellite observations, via such an inverse modeling procedure, allows for delivering robust sulfur dioxide (SO2) cloud dispersal forecasts during the eruption. This approach provides a computationally cheap estimate of the expected location and mass loading of volcanic clouds, including the identification of SO2-rich parts.

Housing Tenure and Residential Segregation in Metropolitan America

PubMed Central

Friedman, Samantha; Tsao, Hui-shien; Chen, Cheng

2013-01-01

Homeownership, a symbol of the American dream, is one of the primary ways through which families accumulate wealth, particularly for blacks and Hispanics. Surprisingly, no study has explicitly documented the segregation of minority owners and renters from whites. Using data from Census 2000, this study aims to fill this gap. Analyses here reveal that the segregation of black renters relative to whites is significantly lower than the segregation of black owners from whites, controlling for relevant socioeconomic and demographic factors, contrary to the notion that homeownership represents an endpoint in the residential assimilation process. The patterns for Hispanics and Asians conform more to expectations under the spatial assimilation model. The findings here suggest that race and ethnicity continue to be as important in shaping residential segregation as socioeconomic status, and raise concerns about the benefits of homeownership, particularly for blacks. PMID:23292639

Soil nitrogen biogeochemical cycles in karst ecosystems, southwest China

NASA Astrophysics Data System (ADS)

Li, Dejun; Chen, Hao; Xiao, Kongcao; Wang, Kelin

2017-04-01

Soil nitrogen (N) status are crucial for ecosystem development and carbon sequestration. Although most terrestrial ecosystems are proposed to be limited by N, some tropical low-land forests have been found to be N saturated. Nevertheless, soil N status in the karst ecosystems of southwest China have not been well assessed so far. In the present study, N status in the karst ecosystems were evaluated based on several lines of evidence. Bulk N content increased rapidly along a post-agricultural succession sequence including cropland, grassland, shrubland, secondary forest and primary forest. Across the sequence, soil N accumulated with an average rate of 12.4 g N m-2 yr-1. Soil N stock recovered to the primary forest level in about 67 years following agricultural abandonment. Nitrate concentrations increased while ammonium concentrations decreased with years following agricultural abandonment. N release from bedrock weathering was likely a potential N source in addition to atmospheric N deposition and biological N fixation. Both gross N mineralization and nitrification (GN) rates decreased initially and then increased greatly following agricultural abandonment. The rate of dissimilatory nitrate reduction to ammonium (DNRA) was highest in the shrubland while lowest in the cropland and forest. Across the vegetation types, DNRA was lowest among the gross rates. Gross ammonium immobilization (GAI) tended to decrease while there was no clear variation pattern for gross nitrate immobilization during the post-agricultural succession. DNRA and nitrate assimilation combined only accounted for 22% to 57% of gross nitrification across the vegetation types. Due to the high nitrate production while low nitrate consumption, net nitrate production was found to vary following the pattern of gross nitrification and explained 69% of soil nitrate variance. Comparison of gross N transformations between a secondary karst forest and an adjacent non-karst forest showed that the gross rates of N mineralization, nitrification, dissimilatory nitrate reduction to ammonium (DNRA) and nitrate assimilation were significantly greater in the karst forest. Ammonium assimilation was comparable to gross N mineralization, so that ammonium could be efficiently conserved in the non-karst forest. Meanwhile, the produced nitrate was almost completely retained via DNRA and nitrate assimilation. This resulted in a negligible net nitrate production in the non-karst forest. In contrast, ammonium assimilation rate only accounted for half of gross N mineralization rate in the karst forest. DNRA and nitrate assimilation accounted for 21% and 51% of gross nitrification, respectively. Due to relatively low nitrate retention capacity, nitrate was accumulated in the karst forest. Our results indicate that 1) N would not be the limiting nutrient for secondary succession and ecological restoration in the karst region, 2) the decoupling of nitrate consumption with production results in the increase of soil nitrate level and hence nitrate leaching risk during post-agricultural succession in the karst region, and 3) the non-karst forest with red soil holds a very conservative N cycle, but the N cycle in the karst forest is leaky.

Carbon dioxide exchange of buds and developing shoots of boreal Norway spruce exposed to elevated or ambient CO2 concentration and temperature in whole-tree chambers.

PubMed

Hall, Marianne; Räntfors, Mats; Slaney, Michelle; Linder, Sune; Wallin, Göran

2009-04-01

Effects of ambient and elevated temperature and atmospheric carbon dioxide concentration ([CO2]) on CO2 assimilation rate and the structural and phenological development of shoots during their first growing season were studied in 45-year-old Norway spruce trees (Picea abies (L.) Karst.) enclosed in whole-tree chambers. Continuous measurements of net assimilation rate (NAR) in individual buds and shoots were made from early bud development to late August in two consecutive years. The largest effect of elevated temperature (TE) was manifest early in the season as an earlier start and completion of shoot length development, and a 1-3-week earlier shift from negative to positive NAR compared with the ambient temperature (TA) treatments. The largest effect of elevated [CO2] (CE) was found later in the season, with a 30% increase in maximum NAR compared with trees in the ambient [CO2] treatments (CA), and shoots assimilating their own mass in terms of carbon earlier in the CE treatments than in the CA treatments. Once the net carbon assimilation compensation point (NACP) had been reached, TE had little or no effect on the development of NAR performance, whereas CE had little effect before the NACP. No interactive effects of TE and CE on NAR were found. We conclude that in a climate predicted for northern Sweden in 2100, current-year shoots of P. abies will assimilate their own mass in terms of carbon 20-30 days earlier compared with the current climate, and thereby significantly contribute to canopy assimilation during their first year.

Improving near-range forecasts of severe precipitation with GNSS and InSAR high-resolution data

NASA Astrophysics Data System (ADS)

Miranda, P. M.; Mateus, P.; Nico, G.; Catalão, J.; Pinto, P.; Tomé, R.; Benevides, P.

2017-12-01

Precipitable water vapor (PWV) maps obtained by GNSS observations are now routinely incorporated into meteorological reanalysis by the main forecast centers such as ECMWF and NCEP. Such data, however, represent a small subset of the available microwave information, which now includes many regional networks of GNSS stations capable to produce frequent updates of the PWV distribution (at least at hourly time scales), and in some cases very high resolution PWV-anomaly fields that may be produced by SAR interferometry (Mateus et al 2013). Such very high resolution fields can be assimilated into state of the art forecast models such as WRF improving it's performance (Mateus et al 2016). In the present study, the assimilation of InSAR data from Sentinel 1A is used to analyse the evolution of two severe precipitation events, which occurred 12 hours apart in the city of Adra in 6-7 September 2015, southern Spain, timed after the two successive passages of the Sentinel. Such events, which produced a flash flood with casualties and large structural damage, were not forecasted by the operational models, but are very accurately reproduced once InSAR data is assimilated, as shown by local observations including weather radar. The physical processes involved in the development of the storm are discussed in some detail, by comparing different simulations: a control run, an experiment with GNSS assimilation, and the experiment with InSAR assimilation. While InSAR images are at this time only available every 6 days, the fact that an improvement of the water vapor distribution by data assimilation can have such a dramatic impact in severe weather forecasts suggests there is significant room for improvement in near term forecasting, by a better incorporation of both higher resolution GNSS data and more frequent SAR images.

South Atlantic Ocean circulation: Simulation experiments with a quasi-geostrophic model and assimilation of TOPEX/POSEIDON and ERS 1 altimeter data

NASA Astrophysics Data System (ADS)

Florenchie, P.; Verron, J.

1998-10-01

Simulation experiments of South Atlantic Ocean circulations are conducted with a 1/6°, four-layered, quasi-geostrophic model. By means of a simple nudging data assimilation procedure along satellite tracks, TOPEX/POSEIDON and ERS 1 altimeter measurements are introduced into the model to control the simulation of the basin-scale circulation for the period from October 1992 to September 1994. The model circulation appears to be strongly influenced by the introduction of altimeter data, offering a consistent picture of South Atlantic Ocean circulations. Comparisons with observations show that the assimilating model successfully simulates the kinematic behavior of a large number of surface circulation components. The assimilation procedure enables us to produce schematic diagrams of South Atlantic circulation in which patterns ranging from basin-scale currents to mesoscale eddies are portrayed in a realistic way, with respect to their complexity. The major features of the South Atlantic circulation are described and analyzed, with special emphasis on the Brazil-Malvinas Confluence region, the Subtropical Gyre with the formation of frontal structures, and the Agulhas Retroflection. The Agulhas eddy-shedding process has been studied extensively. Fourteen eddies appear to be shed during the 2-year experiment. Because of their strong surface topographic signature, Agulhas eddies have been tracked continuously during the assimilation experiment as they cross the South Atlantic basin westward. Other effects of the assimilation procedure are shown, such as the intensification of the Subtropical Gyre, the appearance of a strong seasonal cycle in the Brazil Current transport, and the increase of the mean Brazil Current transport. This last result, combined with the westward oriention of the Agulhas eddies' trajectories, leads to a southward transport of mean eddy kinetic energy across 30°S.

Insights on multivariate updates of physical and biogeochemical ocean variables using an Ensemble Kalman Filter and an idealized model of upwelling

NASA Astrophysics Data System (ADS)

Yu, Liuqian; Fennel, Katja; Bertino, Laurent; Gharamti, Mohamad El; Thompson, Keith R.

2018-06-01

Effective data assimilation methods for incorporating observations into marine biogeochemical models are required to improve hindcasts, nowcasts and forecasts of the ocean's biogeochemical state. Recent assimilation efforts have shown that updating model physics alone can degrade biogeochemical fields while only updating biogeochemical variables may not improve a model's predictive skill when the physical fields are inaccurate. Here we systematically investigate whether multivariate updates of physical and biogeochemical model states are superior to only updating either physical or biogeochemical variables. We conducted a series of twin experiments in an idealized ocean channel that experiences wind-driven upwelling. The forecast model was forced with biased wind stress and perturbed biogeochemical model parameters compared to the model run representing the "truth". Taking advantage of the multivariate nature of the deterministic Ensemble Kalman Filter (DEnKF), we assimilated different combinations of synthetic physical (sea surface height, sea surface temperature and temperature profiles) and biogeochemical (surface chlorophyll and nitrate profiles) observations. We show that when biogeochemical and physical properties are highly correlated (e.g., thermocline and nutricline), multivariate updates of both are essential for improving model skill and can be accomplished by assimilating either physical (e.g., temperature profiles) or biogeochemical (e.g., nutrient profiles) observations. In our idealized domain, the improvement is largely due to a better representation of nutrient upwelling, which results in a more accurate nutrient input into the euphotic zone. In contrast, assimilating surface chlorophyll improves the model state only slightly, because surface chlorophyll contains little information about the vertical density structure. We also show that a degradation of the correlation between observed subsurface temperature and nutrient fields, which has been an issue in several previous assimilation studies, can be reduced by multivariate updates of physical and biogeochemical fields.

Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model

NASA Astrophysics Data System (ADS)

Acevedo, Walter; Fallah, Bijan; Reich, Sebastian; Cubasch, Ulrich

2017-05-01

Paleoclimate data assimilation (DA) is a promising technique to systematically combine the information from climate model simulations and proxy records. Here, we investigate the assimilation of tree-ring-width (TRW) chronologies into an atmospheric global climate model using ensemble Kalman filter (EnKF) techniques and a process-based tree-growth forward model as an observation operator. Our results, within a perfect-model experiment setting, indicate that the "online DA" approach did not outperform the "off-line" one, despite its considerable additional implementation complexity. On the other hand, it was observed that the nonlinear response of tree growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged EnKF methodology. Moreover, for the first time we show that this skill loss appears significantly sensitive to the structure of the growth rate function, used to represent the principle of limiting factors (PLF) within the forward model. In general, our experiments showed that the error reduction achieved by assimilating pseudo-TRW chronologies is modulated by the magnitude of the yearly internal variability in the model. This result might help the dendrochronology community to optimize their sampling efforts.

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.

Coral Reef Color: Remote and In-Situ Imaging Spectroscopy of Reef Structure and Function

NASA Astrophysics Data System (ADS)

Hochberg, E. J.

2016-02-01

Coral reefs are threatened at local to global scales by a litany of anthropogenic impacts, including overfishing, coastal development, marine and watershed pollution, rising ocean temperatures, and ocean acidification. However, available data for the primary indicator of coral reef condition — proportional cover of living coral — are surprisingly sparse and show patterns that contradict the prevailing understanding of how environment impacts reef condition. Remote sensing is the only available tool for acquiring synoptic, uniform data on reef condition at regional to global scales. Discrimination between coral and other reef benthos relies on narrow wavebands afforded by imaging spectroscopy. The same spectral information allows non-invasive quantification of photosynthetic pigment composition, which shows unexpected phenological trends. There is also potential to link biodiversity with optical diversity, though there has been no effort in that direction. Imaging spectroscopy underlies the light-use efficiency model for reef primary production by quantifying light capture, which in turn indicates biochemical capacity for CO2 assimilation. Reef calcification is strongly correlated with primary production, suggesting the possibility for an optics-based model of that aspect of reef function, as well. By scaling these spectral models for use with remote sensing, we can vastly improve our understanding of reef structure, function, and overall condition across regional to global scales. By analyzing those remote sensing products against ancillary environmental data, we can construct secondary models to predict reef futures in the era of global change. This final point is the objective of CORAL (COral Reef Airborne Laboratory), a three-year project funded under NASA's Earth Venture Suborbital-2 program to investigate the relationship between coral reef condition at the ecosystem scale and various nominal biogeophysical forcing parameters.

Coral Reef Color: Remote and In-Situ Imaging Spectroscopy of Reef Structure and Function

NASA Astrophysics Data System (ADS)

Hochberg, E. J.

2015-12-01

Coral reefs are threatened at local to global scales by a litany of anthropogenic impacts, including overfishing, coastal development, marine and watershed pollution, rising ocean temperatures, and ocean acidification. However, available data for the primary indicator of coral reef condition — proportional cover of living coral — are surprisingly sparse and show patterns that contradict the prevailing understanding of how environment impacts reef condition. Remote sensing is the only available tool for acquiring synoptic, uniform data on reef condition at regional to global scales. Discrimination between coral and other reef benthos relies on narrow wavebands afforded by imaging spectroscopy. The same spectral information allows non-invasive quantification of photosynthetic pigment composition, which shows unexpected phenological trends. There is also potential to link biodiversity with optical diversity, though there has been no effort in that direction. Imaging spectroscopy underlies the light-use efficiency model for reef primary production by quantifying light capture, which in turn indicates biochemical capacity for CO2 assimilation. Reef calcification is strongly correlated with primary production, suggesting the possibility for an optics-based model of that aspect of reef function, as well. By scaling these spectral models for use with remote sensing, we can vastly improve our understanding of reef structure, function, and overall condition across regional to global scales. By analyzing those remote sensing products against ancillary environmental data, we can construct secondary models to predict reef futures in the era of global change. This final point is the objective of CORAL (COral Reef Airborne Laboratory), a three-year project funded under NASA's Earth Venture Suborbital-2 program to investigate the relationship between coral reef condition at the ecosystem scale and various nominal biogeophysical forcing parameters.

RuBisCO large-subunit gene primers for assessing the CO2-assimilating planktonic community structure in Jiaozhou Bay, China.

PubMed

Chi, Xiang-Qun; Wang, Long; Guo, Ruoyu; Zhao, Dexi; Li, Jia; Zhang, Yongyu; Jiao, Nianzhi

2018-06-19

The protein coding genes (rbcL/cbbL/cbbM) for RuBisCO large subunit, the most abundant protein on earth that drives biological CO2 fixation, were considered as useful marker genes in characterizing CO2-assimilating plankton. However, their community specificity has hindered comprehensive screening of genetic diversity. In this study, six different rbcL/cbbL/cbbM primers were employed to screen clone libraries to identify CO2-assimilating plankton in Jiaozhou Bay. The following community compositions were observed: the community components in Form I A/B rbcL/cbbL clone library mainly comprised Chlorophyta and Proteobacteria, Form ID2 and ID3 libraries consisted of Bacillariophyta, Form II cbbM library consisted of Proteobacteria and Alveolata, and both Form I green and red libraries included Proteobacteria, respectively. At the genus taxonomic level, no overlaps among these clone libraries were observed, except for ID2 and ID3. Overall, the phytoplankton in Jiaozhou Bay mainly consists of Bacillariophyta, Chlorophyta, Cryptophyta, Haptophyceae, and Alveolata. The CO2-assimilating prokaryotes mainly consist of Proteobacteria. Considering the high sequence specificities of these marker genes, we propose that the joint use of multiple primers may be utilized in unveiling the diversity of CO2-assimilating organisms. In addition, designing novel RuBisCO gene primers that generate longer amplicons and have broader phylogenetic coverage may be necessary in the future.

A mesoscale hybrid data assimilation system based on the JMA nonhydrostatic model

NASA Astrophysics Data System (ADS)

Ito, K.; Kunii, M.; Kawabata, T. T.; Saito, K. K.; Duc, L. L.

2015-12-01

This work evaluates the potential of a hybrid ensemble Kalman filter and four-dimensional variational (4D-Var) data assimilation system for predicting severe weather events from a deterministic point of view. This hybrid system is an adjoint-based 4D-Var system using a background error covariance matrix constructed from the mixture of a so-called NMC method and perturbations in a local ensemble transform Kalman filter data assimilation system, both of which are based on the Japan Meteorological Agency nonhydrostatic model. To construct the background error covariance matrix, we investigated two types of schemes. One is a spatial localization scheme and the other is neighboring ensemble approach, which regards the result at a horizontally spatially shifted point in each ensemble member as that obtained from a different realization of ensemble simulation. An assimilation of a pseudo single-observation located to the north of a tropical cyclone (TC) yielded an analysis increment of wind and temperature physically consistent with what is expected for a mature TC in both hybrid systems, whereas an analysis increment in a 4D-Var system using a static background error covariance distorted a structure of the mature TC. Real data assimilation experiments applied to 4 TCs and 3 local heavy rainfall events showed that hybrid systems and EnKF provided better initial conditions than the NMC-based 4D-Var, both for predicting the intensity and track forecast of TCs and for the location and amount of local heavy rainfall events.

A Wavelet based Suboptimal Kalman Filter for Assimilation of Stratospheric Chemical Tracer Observations

NASA Technical Reports Server (NTRS)

Tangborn, Andrew; Auger, Ludovic

2003-01-01

A suboptimal Kalman filter system which evolves error covariances in terms of a truncated set of wavelet coefficients has been developed for the assimilation of chemical tracer observations of CH4. This scheme projects the discretized covariance propagation equations and covariance matrix onto an orthogonal set of compactly supported wavelets. Wavelet representation is localized in both location and scale, which allows for efficient representation of the inherently anisotropic structure of the error covariances. The truncation is carried out in such a way that the resolution of the error covariance is reduced only in the zonal direction, where gradients are smaller. Assimilation experiments which last 24 days, and used different degrees of truncation were carried out. These reduced the covariance size by 90, 97 and 99 % and the computational cost of covariance propagation by 80, 93 and 96 % respectively. The difference in both error covariance and the tracer field between the truncated and full systems over this period were found to be not growing in the first case, and growing relatively slowly in the later two cases. The largest errors in the tracer fields were found to occur in regions of largest zonal gradients in the constituent field. This results indicate that propagation of error covariances for a global two-dimensional data assimilation system are currently feasible. Recommendations for further reduction in computational cost are made with the goal of extending this technique to three-dimensional global assimilation systems.

Towards improved hydrologic predictions using data assimilation techniques for water resource management at the continental scale

NASA Astrophysics Data System (ADS)

Naz, Bibi; Kurtz, Wolfgang; Kollet, Stefan; Hendricks Franssen, Harrie-Jan; Sharples, Wendy; Görgen, Klaus; Keune, Jessica; Kulkarni, Ketan

2017-04-01

More accurate and reliable hydrologic simulations are important for many applications such as water resource management, future water availability projections and predictions of extreme events. However, simulation of spatial and temporal variations in the critical water budget components such as precipitation, snow, evaporation and runoff is highly uncertain, due to errors in e.g. model structure and inputs (hydrologic parameters and forcings). In this study, we use data assimilation techniques to improve the predictability of continental-scale water fluxes using in-situ measurements along with remotely sensed information to improve hydrologic predications for water resource systems. The Community Land Model, version 3.5 (CLM) integrated with the Parallel Data Assimilation Framework (PDAF) was implemented at spatial resolution of 1/36 degree (3 km) over the European CORDEX domain. The modeling system was forced with a high-resolution reanalysis system COSMO-REA6 from Hans-Ertel Centre for Weather Research (HErZ) and ERA-Interim datasets for time period of 1994-2014. A series of data assimilation experiments were conducted to assess the efficiency of assimilation of various observations, such as river discharge data, remotely sensed soil moisture, terrestrial water storage and snow measurements into the CLM-PDAF at regional to continental scales. This setup not only allows to quantify uncertainties, but also improves streamflow predictions by updating simultaneously model states and parameters utilizing observational information. The results from different regions, watershed sizes, spatial resolutions and timescales are compared and discussed in this study.

Historical Archaeology of the United States Industrial Indian School at Phoenix: Investigations of a Turn of the Century Trash Dump. Anthropological Field Studies Number 42.

ERIC Educational Resources Information Center

Lindauer, Owen; Ferguson, Deborah; Glass, Margaret; Hatfield, Virginia; McKenna, Jeanette A.; Dering, Phil

The Phoenix Indian School served as a coeducational, federal educational institution for American Indian primary and secondary students between 1891 and 1990. Covering 10 blocks and enrolling over 600 Indian children aged 8-18, this boarding school used education to assimilate students into Anglo-American culture. This monograph describes…

Carbon assimilation and transfer through kelp forests in the NE Atlantic is diminished under a warmer ocean climate.

PubMed

Pessarrodona, Albert; Moore, Pippa J; Sayer, Martin D J; Smale, Dan A

2018-06-03

Global climate change is affecting carbon cycling by driving changes in primary productivity and rates of carbon fixation, release and storage within Earth's vegetated systems. There is, however, limited understanding of how carbon flow between donor and recipient habitats will respond to climatic changes. Macroalgal-dominated habitats, such as kelp forests, are gaining recognition as important carbon donors within coastal carbon cycles, yet rates of carbon assimilation and transfer through these habitats are poorly resolved. Here, we investigated the likely impacts of ocean warming on coastal carbon cycling by quantifying rates of carbon assimilation and transfer in Laminaria hyperborea kelp forests-one of the most extensive coastal vegetated habitat types in the NE Atlantic-along a latitudinal temperature gradient. Kelp forests within warm climatic regimes assimilated, on average, more than three times less carbon and donated less than half the amount of particulate carbon compared to those from cold regimes. These patterns were not related to variability in other environmental parameters. Across their wider geographical distribution, plants exhibited reduced sizes toward their warm-water equatorward range edge, further suggesting that carbon flow is reduced under warmer climates. Overall, we estimated that Laminaria hyperborea forests stored ~11.49 Tg C in living biomass and released particulate carbon at a rate of ~5.71 Tg C year -1 . This estimated flow of carbon was markedly higher than reported values for most other marine and terrestrial vegetated habitat types in Europe. Together, our observations suggest that continued warming will diminish the amount of carbon that is assimilated and transported through temperate kelp forests in NE Atlantic, with potential consequences for the coastal carbon cycle. Our findings underline the need to consider climate-driven changes in the capacity of ecosystems to fix and donate carbon when assessing the impacts of climate change on carbon cycling. © 2018 The Authors Global Change Biology Published by John Wiley & Sons Ltd.

Temporary storage or permanent removal? The division of nitrogen between biotic assimilation and denitrification in stormwater biofiltration systems.

PubMed

Payne, Emily G I; Fletcher, Tim D; Russell, Douglas G; Grace, Michael R; Cavagnaro, Timothy R; Evrard, Victor; Deletic, Ana; Hatt, Belinda E; Cook, Perran L M

2014-01-01

The long-term efficacy of stormwater treatment systems requires continuous pollutant removal without substantial re-release. Hence, the division of incoming pollutants between temporary and permanent removal pathways is fundamental. This is pertinent to nitrogen, a critical water body pollutant, which on a broad level may be assimilated by plants or microbes and temporarily stored, or transformed by bacteria to gaseous forms and permanently lost via denitrification. Biofiltration systems have demonstrated effective removal of nitrogen from urban stormwater runoff, but to date studies have been limited to a 'black-box' approach. The lack of understanding on internal nitrogen processes constrains future design and threatens the reliability of long-term system performance. While nitrogen processes have been thoroughly studied in other environments, including wastewater treatment wetlands, biofiltration systems differ fundamentally in design and the composition and hydrology of stormwater inflows, with intermittent inundation and prolonged dry periods. Two mesocosm experiments were conducted to investigate biofilter nitrogen processes using the stable isotope tracer 15NO3(-) (nitrate) over the course of one inflow event. The immediate partitioning of 15NO3(-) between biotic assimilation and denitrification were investigated for a range of different inflow concentrations and plant species. Assimilation was the primary fate for NO3(-) under typical stormwater concentrations (∼1-2 mg N/L), contributing an average 89-99% of 15NO3(-) processing in biofilter columns containing the most effective plant species, while only 0-3% was denitrified and 0-8% remained in the pore water. Denitrification played a greater role for columns containing less effective species, processing up to 8% of 15NO3(-), and increased further with nitrate loading. This study uniquely applied isotope tracing to biofiltration systems and revealed the dominance of assimilation in stormwater biofilters. The findings raise important questions about nitrogen release upon plant senescence, seasonally and in the long term, which have implications on the management and design of biofiltration systems.

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.

Data-Driven Model Uncertainty Estimation in Hydrologic Data Assimilation

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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.

Sull'Integrazione delle Strutture Numeriche nella Scuola dell'Obbligo (Integrating Numerical Structures in Mandatory School).

ERIC Educational Resources Information Center

Bonotto, C.

1995-01-01

Attempted to verify knowledge regarding decimal and rational numbers in children ages 10-14. Discusses how pupils can receive and assimilate extensions of the number system from natural numbers to decimals and fractions and later can integrate this extension into a single and coherent numerical structure. (Author/MKR)

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

CHROMagar Candida as the Sole Primary Medium for Isolation of Yeasts and as a Source Medium for the Rapid-Assimilation-of-Trehalose Test

PubMed Central

Murray, Melissa P.; Zinchuk, Riva; Larone, Davise H.

2005-01-01

The chromogenic medium BBL CHROMagar Candida (CAC) was evaluated as a sole primary medium for the isolation of yeasts from clinical specimens in which yeasts are the primary concern. Additionally, the reliability of the rapid-assimilation-of-trehalose (RAT) test in yielding correct results with isolates taken from CAC was assessed. A total of 270 throat, urine, and genital (TUG) specimens were streaked onto CAC, Sabouraud dextrose agar (SDA), inhibitory mold agar (IMA), and Mycosel (MYC). A total of 69 blood culture broths that were smear positive for yeast were streaked onto CAC and SDA. A 1-h RAT test (NCCLS M35-A) was performed simultaneously on isolates from CAC and SDA. A total of 112 TUG specimens yielded yeast colonies (CAC, 111 colonies; IMA, 105; SDA, 103; MYC, 91). The 69 blood culture yeasts grew on both CAC and SDA. Mixed cultures of yeasts were detected on 11 CAC plates but were unrecognized on other media. Colonies suspected of being C. glabrata on 32 CAC plates were all RAT test positive and confirmed to be C. glabrata; of 59 colonies with various characteristics of color and morphology on CAC, none were RAT positive, and all were conventionally identified as yeasts other than C. glabrata (sensitivity and specificity, 100%). The same isolates from SDA tested for RAT produced six false negatives and no false positives (sensitivity, 81%; specificity, 100%). The results show that CAC can be used as the sole primary medium for recovery of yeasts from clinical specimens. Additionally, isolates grown on CAC yield excellent results with the RAT test utilized in this study. PMID:15750085

CHROMagar Candida as the sole primary medium for isolation of yeasts and as a source medium for the rapid-assimilation-of-trehalose test.

PubMed

Murray, Melissa P; Zinchuk, Riva; Larone, Davise H

2005-03-01

The chromogenic medium BBL CHROMagar Candida (CAC) was evaluated as a sole primary medium for the isolation of yeasts from clinical specimens in which yeasts are the primary concern. Additionally, the reliability of the rapid-assimilation-of-trehalose (RAT) test in yielding correct results with isolates taken from CAC was assessed. A total of 270 throat, urine, and genital (TUG) specimens were streaked onto CAC, Sabouraud dextrose agar (SDA), inhibitory mold agar (IMA), and Mycosel (MYC). A total of 69 blood culture broths that were smear positive for yeast were streaked onto CAC and SDA. A 1-h RAT test (NCCLS M35-A) was performed simultaneously on isolates from CAC and SDA. A total of 112 TUG specimens yielded yeast colonies (CAC, 111 colonies; IMA, 105; SDA, 103; MYC, 91). The 69 blood culture yeasts grew on both CAC and SDA. Mixed cultures of yeasts were detected on 11 CAC plates but were unrecognized on other media. Colonies suspected of being C. glabrata on 32 CAC plates were all RAT test positive and confirmed to be C. glabrata; of 59 colonies with various characteristics of color and morphology on CAC, none were RAT positive, and all were conventionally identified as yeasts other than C. glabrata (sensitivity and specificity, 100%). The same isolates from SDA tested for RAT produced six false negatives and no false positives (sensitivity, 81%; specificity, 100%). The results show that CAC can be used as the sole primary medium for recovery of yeasts from clinical specimens. Additionally, isolates grown on CAC yield excellent results with the RAT test utilized in this study.

FUSION++: A New Data Assimilative Model for Electron Density Forecasting

NASA Astrophysics Data System (ADS)

Bust, G. S.; Comberiate, J.; Paxton, L. J.; Kelly, M.; Datta-Barua, S.

2014-12-01

There is a continuing need within the operational space weather community, both civilian and military, for accurate, robust data assimilative specifications and forecasts of the global electron density field, as well as derived RF application product specifications and forecasts obtained from the electron density field. The spatial scales of interest range from a hundred to a few thousand kilometers horizontally (synoptic large scale structuring) and meters to kilometers (small scale structuring that cause scintillations). RF space weather applications affected by electron density variability on these scales include navigation, communication and geo-location of RF frequencies ranging from 100's of Hz to GHz. For many of these applications, the necessary forecast time periods range from nowcasts to 1-3 hours. For more "mission planning" applications, necessary forecast times can range from hours to days. In this paper we present a new ionosphere-thermosphere (IT) specification and forecast model being developed at JHU/APL based upon the well-known data assimilation algorithms Ionospheric Data Assimilation Four Dimensional (IDA4D) and Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE). This new forecast model, "Forward Update Simple IONosphere model Plus IDA4D Plus EMPIRE (FUSION++), ingests data from observations related to electron density, winds, electric fields and neutral composition and provides improved specification and forecast of electron density. In addition, the new model provides improved specification of winds, electric fields and composition. We will present a short overview and derivation of the methodology behind FUSION++, some preliminary results using real observational sources, example derived RF application products such as HF bi-static propagation, and initial comparisons with independent data sources for validation.

The Impact of Ocean Data Assimilation on Seasonal-to-Interannual Forecasts: A Case Study of the 2006 El Nino Event

NASA Technical Reports Server (NTRS)

Yang, Shu-Chih; Rienecker, Michele; Keppenne, Christian

2010-01-01

This study investigates the impact of four different ocean analyses on coupled forecasts of the 2006 El Nino event. Forecasts initialized in June 2006 using ocean analyses from an assimilation that uses flow-dependent background error covariances are compared with those using static error covariances that are not flow dependent. The flow-dependent error covariances reflect the error structures related to the background ENSO instability and are generated by the coupled breeding method. The ocean analyses used in this study result from the assimilation of temperature and salinity, with the salinity data available from Argo floats. Of the analyses, the one using information from the coupled bred vectors (BV) replicates the observed equatorial long wave propagation best and exhibits more warming features leading to the 2006 El Nino event. The forecasts initialized from the BV-based analysis agree best with the observations in terms of the growth of the warm anomaly through two warming phases. This better performance is related to the impact of the salinity analysis on the state evolution in the equatorial thermocline. The early warming is traced back to salinity differences in the upper ocean of the equatorial central Pacific, while the second warming, corresponding to the mature phase, is associated with the effect of the salinity assimilation on the depth of the thermocline in the western equatorial Pacific. The series of forecast experiments conducted here show that the structure of the salinity in the initial conditions is important to the forecasts of the extension of the warm pool and the evolution of the 2006 El Ni o event.

Impact of ozone observations on the structure of a tropical cyclone using coupled atmosphere-chemistry data assimilation

NASA Astrophysics Data System (ADS)

Lim, S.; Park, S. K.; Zupanski, M.

2015-04-01

Since the air quality forecast is related to both chemistry and meteorology, the coupled atmosphere-chemistry data assimilation (DA) system is essential to air quality forecasting. Ozone (O3) plays an important role in chemical reactions and is usually assimilated in chemical DA. In tropical cyclones (TCs), O3 usually shows a lower concentration inside the eyewall and an elevated concentration around the eye, impacting atmospheric as well as chemical variables. To identify the impact of O3 observations on TC structure, including atmospheric and chemical information, we employed the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) with an ensemble-based DA algorithm - the maximum likelihood ensemble filter (MLEF). For a TC case that occurred over the East Asia, our results indicate that the ensemble forecast is reasonable, accompanied with larger background state uncertainty over the TC, and also over eastern China. Similarly, the assimilation of O3 observations impacts atmospheric and chemical variables near the TC and over eastern China. The strongest impact on air quality in the lower troposphere was over China, likely due to the pollution advection. In the vicinity of the TC, however, the strongest impact on chemical variables adjustment was at higher levels. The impact on atmospheric variables was similar in both over China and near the TC. The analysis results are validated using several measures that include the cost function, root-mean-squared error with respect to observations, and degrees of freedom for signal (DFS). All measures indicate a positive impact of DA on the analysis - the cost function and root mean square error have decreased by 16.9 and 8.87%, respectively. In particular, the DFS indicates a strong positive impact of observations in the TC area, with a weaker maximum over northeast China.

Assimilating satellite soil moisture into rainfall-runoff modelling: towards a systematic study

NASA Astrophysics Data System (ADS)

Massari, Christian; Tarpanelli, Angelica; Brocca, Luca; Moramarco, Tommaso

2015-04-01

Soil moisture is the main factor for the repartition of the mass and energy fluxes between the land surface and the atmosphere thus playing a fundamental role in the hydrological cycle. Indeed, soil moisture represents the initial condition of rainfall-runoff modelling that determines the flood response of a catchment. Different initial soil moisture conditions can discriminate between catastrophic and minor effects of a given rainfall event. Therefore, improving the estimation of initial soil moisture conditions will reduce uncertainties in early warning flood forecasting models addressing the mitigation of flood hazard. In recent years, satellite soil moisture products have become available with fine spatial-temporal resolution and a good accuracy. Therefore, a number of studies have been published in which the impact of the assimilation of satellite soil moisture data into rainfall-runoff modelling is investigated. Unfortunately, data assimilation involves a series of assumptions and choices that significantly affect the final result. Given a satellite soil moisture observation, a rainfall-runoff model and a data assimilation technique, an improvement or a deterioration of discharge predictions can be obtained depending on the choices made in the data assimilation procedure. Consequently, large discrepancies have been obtained in the studies published so far likely due to the differences in the implementation of the data assimilation technique. On this basis, a comprehensive and robust procedure for the assimilation of satellite soil moisture data into rainfall-runoff modelling is developed here and applied to six subcatchment of the Upper Tiber River Basin for which high-quality hydrometeorological hourly observations are available in the period 1989-2013. The satellite soil moisture product used in this study is obtained from the Advanced SCATterometer (ASCAT) onboard Metop-A satellite and it is available since 2007. The MISDc ("Modello Idrologico SemiDistribuito in continuo") continuous hydrological model is used for flood simulation. The Ensemble Kalman Filter (EnKF) is employed as data assimilation technique for its flexibility and good performance in a number of previous applications. Different components are involved in the developed data assimilation procedure. For the correction of the bias between satellite and modelled soil moisture data three different techniques are considered: mean-variance matching, Cumulative Density Function (CDF) matching and least square linear regression. For properly generating the ensembles of model states, required in the application of EnKF technique, an exhaustive search of the model error parameterization and structure is carried out, differentiated for each study catchments. A number of scores and statistics are employed for the evaluation the reliability of the ensemble. Similarly, different configurations for the observation error are investigated. Results show that for four out six catchments the assimilation of the ASCAT soil moisture product improves discharge simulation in the validation period 2010-2013, mainly during flood events. The two catchments in which the assimilation does not improve the results are located in the mountainous part of the region where both MISDc and satellite data perform worse. The analysis on the data assimilation choices highlights that the selection of the observation error seems to have the largest influence on discharge simulation. Finally, the bias correction approaches have a lower effect and the selection of linear techniques is preferable. The assessment of all the components involved in the data assimilation procedure provides a clear understanding of results and it is advised to follow a similar procedure in this kind of studies.

Improving spatial perception in 5-yr.-old Spanish children.

PubMed

Jiménez, Andrés Canto; Sicilia, Antonio Oña; Vera, Juan Granda

2007-06-01

Assimilation of distance perception was studied in 70 Spanish primary school children. This assimilation involves the generation of projective images which are acquired through two mechanisms. One mechanism is spatial perception, wherein perceptual processes develop ensuring successful immersion in space and the acquisition of visual cues which a person may use to interpret images seen in the distance. The other mechanism is movement through space so that these images are produced. The present study evaluated the influence on improvements in spatial perception of using increasingly larger spaces for training sessions within a motor skills program. Visual parameters were measured in relation to the capture and tracking of moving objects or ocular motility and speed of detection or visual reaction time. Analysis showed that for the group trained in increasingly larger spaces, ocular motility and visual reaction time were significantly improved during. different phases of the program.

Evidence for crustal recycling during the Archean: The parental magmas of the stillwater complex

NASA Technical Reports Server (NTRS)

Mccallum, I. S.

1988-01-01

The petrology and geochemistry of the Stillwater Complex, an Archean (2.7 Ga) layered mafic intrusion in the Beartooth Mountains of Montana is discussed. Efforts to reconstruct the compositions of possible parental magmas and thereby place some constraints on the composition and history of their mantle source regions was studied. A high-Mg andesite or boninite magma best matches the crystallization sequences and mineral compositions of Stillwater cumulates, and represents either a primary magma composition or a secondary magma formed, for example, by assimilation of crustal material by a very Mg-rich melt such as komatiite. Isotopic data do not support the extensive amounts of assimilation required by the komatiite parent hypothesis, and it is argued that the Stillwater magma was generated from a mantle source that had been enriched by recycling and homogenization of older crustal material over a large area.

Formaldehyde as a carbon and electron shuttle between autotroph and heterotroph populations in acidic hydrothermal vents of Norris Geyser Basin, Yellowstone National Park.

PubMed

Moran, James J; Whitmore, Laura M; Isern, Nancy G; Romine, Margaret F; Riha, Krystin M; Inskeep, William P; Kreuzer, Helen W

2016-05-01

The Norris Geyser Basin in Yellowstone National Park contains a large number of hydrothermal systems, which host microbial populations supported by primary productivity associated with a suite of chemolithotrophic metabolisms. We demonstrate that Metallosphaera yellowstonensis MK1, a facultative autotrophic archaeon isolated from a hyperthermal acidic hydrous ferric oxide (HFO) spring in Norris Geyser Basin, excretes formaldehyde during autotrophic growth. To determine the fate of formaldehyde in this low organic carbon environment, we incubated native microbial mat (containing M. yellowstonensis) from a HFO spring with (13)C-formaldehyde. Isotopic analysis of incubation-derived CO2 and biomass showed that formaldehyde was both oxidized and assimilated by members of the community. Autotrophy, formaldehyde oxidation, and formaldehyde assimilation displayed different sensitivities to chemical inhibitors, suggesting that distinct sub-populations in the mat selectively perform these functions. Our results demonstrate that electrons originally resulting from iron oxidation can energetically fuel autotrophic carbon fixation and associated formaldehyde excretion, and that formaldehyde is both oxidized and assimilated by different organisms within the native microbial community. Thus, formaldehyde can effectively act as a carbon and electron shuttle connecting the autotrophic, iron oxidizing members with associated heterotrophic members in the HFO community.

Modeling whole-tree carbon assimilation rate using observed transpiration rates and needle sugar carbon isotope ratios.

PubMed

Hu, Jia; Moore, David J P; Riveros-Iregui, Diego A; Burns, Sean P; Monson, Russell K

2010-03-01

*Understanding controls over plant-atmosphere CO(2) exchange is important for quantifying carbon budgets across a range of spatial and temporal scales. In this study, we used a simple approach to estimate whole-tree CO(2) assimilation rate (A(Tree)) in a subalpine forest ecosystem. *We analysed the carbon isotope ratio (delta(13)C) of extracted needle sugars and combined it with the daytime leaf-to-air vapor pressure deficit to estimate tree water-use efficiency (WUE). The estimated WUE was then combined with observations of tree transpiration rate (E) using sap flow techniques to estimate A(Tree). Estimates of A(Tree) for the three dominant tree species in the forest were combined with species distribution and tree size to estimate and gross primary productivity (GPP) using an ecosystem process model. *A sensitivity analysis showed that estimates of A(Tree) were more sensitive to dynamics in E than delta(13)C. At the ecosystem scale, the abundance of lodgepole pine trees influenced seasonal dynamics in GPP considerably more than Engelmann spruce and subalpine fir because of its greater sensitivity of E to seasonal climate variation. *The results provide the framework for a nondestructive method for estimating whole-tree carbon assimilation rate and ecosystem GPP over daily-to weekly time scales.

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.

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.

Challenges in Ocean Data Assimilation for the US West Coast

NASA Astrophysics Data System (ADS)

Li, Z.; Chao, Y.; Farrara, J.; Wang, X.

2006-12-01

A three-dimensional variational data assimilation (3DVAR) system has been developed for the Regional Ocean Modeling System (ROMS), and it is called ROMS-DAS. This system provides a capability of predicting meso- to small-scale variations with temporal scales from hours to days in the coastal oceans. To cope with the particular difficulties that result from complex coastlines and bottom topography, unbalanced flows and sparse observations, ROMS-DAS utilizes several novel strategies. These strategies include the implementation of three-dimensional anisotropic and inhomogeneous error correlations, application of particular weak dynamic constraints, and implementation of efficient and reliable algorithms for minimizing the cost function. The ROMS-DAS system was applied in field experiments for Monterey Bay during both 2003 (Autonomous Ocean Sampling Network - AOSN) and 2006 (MB06). These two experiments included intensive data collection from a variety of observational platforms, including satellites, airplanes, High Frequency radars, Acoustic Doppler Current Profilers, ships, drifters, buoys, autonomous underwater vehicles (AUV), and particularly a fleet of undersea gliders. Using these data sets, various data assimilation experiments were performed to address several major data assimilation challenges that arise from multi-scales structures, inhomogeneous properties, dynamical imbalance of the flow, and tides. Basing on these experiments, a set of strategies were formulated to deal with those challenges.

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

Climate Data Guide - Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)

NASA Technical Reports Server (NTRS)

Cullather, Richard; Bosilovich, Michael

2017-01-01

The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) is a global atmospheric reanalysis produced by the NASA Global Modeling and Assimilation Office (GMAO). It spans the satellite observing era from 1980 to the present. The goals of MERRA-2 are to provide a regularly-gridded, homogeneous record of the global atmosphere, and to incorporate additional aspects of the climate system including trace gas constituents (stratospheric ozone), and improved land surface representation, and cryospheric processes. MERRA-2 is also the first satellite-era global reanalysis to assimilate space-based observations of aerosols and represent their interactions with other physical processes in the climate system. The inclusion of these additional components are consistent with the overall objectives of an Integrated Earth System Analysis (IESA). MERRA-2 is intended to replace the original MERRA product, and reflects recent advances in atmospheric modeling and data assimilation. Modern hyperspectral radiance and microwave observations, along with GPS-Radio Occultation and NASA ozone datasets are now assimilated in MERRA-2. Much of the structure of the data files remains the same in MERRA-2. While the original MERRA data format was HDF-EOS, the MERRA-2 supplied binary data format is now NetCDF4 (with lossy compression to save space).

USSR Report, International Affairs

DTIC Science & Technology

1987-02-11

shown that the cycle "A New Development—Assimilation in Production " has accelerated to practically twice its original speed thanks to these forms of... new production capacities to manufacture hydrodynamic transmissions for scrapers and loaders, and in doing so, will be assisted by a partner—the...creation of new forms of production through joint efforts. Of primary importance in achieving these new forms are mobile and flexible contacts that are in

Improving Aerosol and Visibility Forecasting Capabilities Using Current and Future Generations of Satellite Observations

DTIC Science & Technology

2012-09-30

improving forecast performance over cloudy regions using the Ozone Monitoring Instrument (OMI) Aerosol Index; and 2) preparing for the post-MODIS...meteorological fields, the International Geosphere-Biosphere Programme (IGBP) SW and LW surface characteristics, and an ozone climatology are used as...The primary impact of CALIOP assimilation on the model is the redistribution of mass toward the boundary layer from the free troposphere . For high

Carbon-Water-Energy Relations for Selected River Basins

NASA Technical Reports Server (NTRS)

Choudhury, B. J.

1998-01-01

A biophysical process-based model was run using satellite, assimilated and ancillary data for four years (1987-1990) to calculate components of total evaporation (transpiration, interception, soil and snow evaporation), net radiation, absorbed photosynthetically active radiation and net primary productivity over the global land surface. Satellite observations provided fractional vegetation cover, solar and photosynthetically active radiation incident of the surface, surface albedo, fractional cloud cover, air temperature and vapor pressure. The friction velocity and surface air pressure are obtained from a four dimensional data assimilation results, while precipitation is either only surface observations or a blended product of surface and satellite observations. All surface and satellite data are monthly mean values; precipitation has been disaggregated into daily values. All biophysical parameters of the model are prescribed according to published records. From these global land surface calculations results for river basins are derived using digital templates of basin boundaries. Comparisons with field observations (micrometeorologic, catchment water balance, biomass production) and atmospheric water budget analysis for monthly evaporation from six river basins have been done to assess errors in the calculations. Comparisons are also made with previous estimates of zonal variations of evaporation and net primary productivity. Efficiencies of transpiration, total evaporation and radiation use, and evaporative fraction for selected river basins will be presented.

On improving the communication between models and data.

PubMed

Dietze, Michael C; Lebauer, David S; Kooper, Rob

2013-09-01

The potential for model-data synthesis is growing in importance as we enter an era of 'big data', greater connectivity and faster computation. Realizing this potential requires that the research community broaden its perspective about how and why they interact with models. Models can be viewed as scaffolds that allow data at different scales to inform each other through our understanding of underlying processes. Perceptions of relevance, accessibility and informatics are presented as the primary barriers to broader adoption of models by the community, while an inability to fully utilize the breadth of expertise and data from the community is a primary barrier to model improvement. Overall, we promote a community-based paradigm to model-data synthesis and highlight some of the tools and techniques that facilitate this approach. Scientific workflows address critical informatics issues in transparency, repeatability and automation, while intuitive, flexible web-based interfaces make running and visualizing models more accessible. Bayesian statistics provides powerful tools for assimilating a diversity of data types and for the analysis of uncertainty. Uncertainty analyses enable new measurements to target those processes most limiting our predictive ability. Moving forward, tools for information management and data assimilation need to be improved and made more accessible. © 2013 John Wiley & Sons Ltd.

Nitrate fertilisation does not enhance CO2 responses in two tropical seagrass species

NASA Astrophysics Data System (ADS)

Ow, Y. X.; Vogel, N.; Collier, C. J.; Holtum, J. A. M.; Flores, F.; Uthicke, S.

2016-03-01

Seagrasses are often considered “winners” of ocean acidification (OA); however, seagrass productivity responses to OA could be limited by nitrogen availability, since nitrogen-derived metabolites are required for carbon assimilation. We tested nitrogen uptake and assimilation, photosynthesis, growth, and carbon allocation responses of the tropical seagrasses Halodule uninervis and Thalassia hemprichii to OA scenarios (428, 734 and 1213 μatm pCO2) under two nutrients levels (0.3 and 1.9 μM NO3-). Net primary production (measured as oxygen production) and growth in H. uninervis increased with pCO2 enrichment, but were not affected by nitrate enrichment. However, nitrate enrichment reduced whole plant respiration in H. uninervis. Net primary production and growth did not show significant changes with pCO2 or nitrate by the end of the experiment (24 d) in T. hemprichii. However, nitrate incorporation in T. hemprichii was higher with nitrate enrichment. There was no evidence that nitrogen demand increased with pCO2 enrichment in either species. Contrary to our initial hypothesis, nutrient increases to levels approximating present day flood plumes only had small effects on metabolism. This study highlights that the paradigm of increased productivity of seagrasses under ocean acidification may not be valid for all species under all environmental conditions.

Nitrate fertilisation does not enhance CO2 responses in two tropical seagrass species.

PubMed

Ow, Y X; Vogel, N; Collier, C J; Holtum, J A M; Flores, F; Uthicke, S

2016-03-15

Seagrasses are often considered "winners" of ocean acidification (OA); however, seagrass productivity responses to OA could be limited by nitrogen availability, since nitrogen-derived metabolites are required for carbon assimilation. We tested nitrogen uptake and assimilation, photosynthesis, growth, and carbon allocation responses of the tropical seagrasses Halodule uninervis and Thalassia hemprichii to OA scenarios (428, 734 and 1213 μatm pCO2) under two nutrients levels (0.3 and 1.9 μM NO3(-)). Net primary production (measured as oxygen production) and growth in H. uninervis increased with pCO2 enrichment, but were not affected by nitrate enrichment. However, nitrate enrichment reduced whole plant respiration in H. uninervis. Net primary production and growth did not show significant changes with pCO2 or nitrate by the end of the experiment (24 d) in T. hemprichii. However, nitrate incorporation in T. hemprichii was higher with nitrate enrichment. There was no evidence that nitrogen demand increased with pCO2 enrichment in either species. Contrary to our initial hypothesis, nutrient increases to levels approximating present day flood plumes only had small effects on metabolism. This study highlights that the paradigm of increased productivity of seagrasses under ocean acidification may not be valid for all species under all environmental conditions.

Nitrate fertilisation does not enhance CO2 responses in two tropical seagrass species

PubMed Central

Ow, Y. X.; Vogel, N.; Collier, C. J.; Holtum, J. A. M.; Flores, F.; Uthicke, S.

2016-01-01

Seagrasses are often considered “winners” of ocean acidification (OA); however, seagrass productivity responses to OA could be limited by nitrogen availability, since nitrogen-derived metabolites are required for carbon assimilation. We tested nitrogen uptake and assimilation, photosynthesis, growth, and carbon allocation responses of the tropical seagrasses Halodule uninervis and Thalassia hemprichii to OA scenarios (428, 734 and 1213 μatm pCO2) under two nutrients levels (0.3 and 1.9 μM NO3−). Net primary production (measured as oxygen production) and growth in H. uninervis increased with pCO2 enrichment, but were not affected by nitrate enrichment. However, nitrate enrichment reduced whole plant respiration in H. uninervis. Net primary production and growth did not show significant changes with pCO2 or nitrate by the end of the experiment (24 d) in T. hemprichii. However, nitrate incorporation in T. hemprichii was higher with nitrate enrichment. There was no evidence that nitrogen demand increased with pCO2 enrichment in either species. Contrary to our initial hypothesis, nutrient increases to levels approximating present day flood plumes only had small effects on metabolism. This study highlights that the paradigm of increased productivity of seagrasses under ocean acidification may not be valid for all species under all environmental conditions. PMID:26976685

Cognitive Flexibility and Undergraduate Physiology Students: Increasing Advanced Knowledge Acquisition within an Ill-Structured Domain

ERIC Educational Resources Information Center

Rhodes, Ashley E.; Rozell, Timothy G.

2017-01-01

Cognitive flexibility is defined as the ability to assimilate previously learned information and concepts to generate novel solutions to new problems. This skill is crucial for success within ill-structured domains such as biology, physiology, and medicine, where many concepts are simultaneously required for understanding a complex problem, yet…

Tree crown structure indicators in a natural uneven-aged mixed coniferous forest in northeastern Mexico

Treesearch

Javier Jimenez-Perez; Oscar Aguirre-Calderon; Horst Kramer

2006-01-01

Characterization of tree crown structure provides critical information to assess a variety of ecological conditions for multiple purposes and applications. For biomass growth, for example, tree crowns have basic physiological functions: assimilation, respiration, and transpiration. How tree crowns spatially interact and grow can bring about a seamless landscape of...

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.

Cognitive group therapy for depressive students: The case study

PubMed Central

Tiuraniemi, Juhani; Korhola, Jarno

2009-01-01

The aims of this study were to assess whether a course of cognitive group therapy could help depressed students and to assess whether assimilation analysis offers a useful way of analysing students' progress through therapy. “Johanna” was a patient in a group that was designed for depressive students who had difficulties with their studies. The assimilation of Johanna's problematic experience progressed as the meetings continued from level one (unpleasant thoughts) to level six (solving the problem). Johanna's problematic experience manifested itself as severe and excessive criticism towards herself and her study performance. As the group meetings progressed, Johanna found a new kind of tolerance that increased her determination and assertiveness regarding the studies. The dialogical structure of Johanna's problematic experience changed: she found hope and she was more assertive after the process. The results indicated that this kind of psycho-educational group therapy was an effective method for treating depression. The assimilation analysis offered a useful way of analysing the therapy process. PMID:20523883

An integrated uncertainty analysis and data assimilation approach for improved streamflow predictions

NASA Astrophysics Data System (ADS)

Hogue, T. S.; He, M.; Franz, K. J.; Margulis, S. A.; Vrugt, J. A.

2010-12-01

The current study presents an integrated uncertainty analysis and data assimilation approach to improve streamflow predictions while simultaneously providing meaningful estimates of the associated uncertainty. Study models include the National Weather Service (NWS) operational snow model (SNOW17) and rainfall-runoff model (SAC-SMA). The proposed approach uses the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) to simultaneously estimate uncertainties in model parameters, forcing, and observations. An ensemble Kalman filter (EnKF) is configured with the DREAM-identified uncertainty structure and applied to assimilating snow water equivalent data into the SNOW17 model for improved snowmelt simulations. Snowmelt estimates then serves as an input to the SAC-SMA model to provide streamflow predictions at the basin outlet. The robustness and usefulness of the approach is evaluated for a snow-dominated watershed in the northern Sierra Mountains. This presentation describes the implementation of DREAM and EnKF into the coupled SNOW17 and SAC-SMA models and summarizes study results and findings.

The effect of clinorotation on structural and functional organization of assimilative tissues, cells and growth regulator activity in orchids of different age

NASA Astrophysics Data System (ADS)

Cherevchenko, T.; Zaimenko, N.; Sitnyanska, N.; Majko, T.; Grishko, M. M.

Ultrastructural analyses of assimilative tissues of the orchids, Cymbidium hybridum and Doritis pulcherrima, show that, in plants of different age, chloroplasts differ in structure and stage of membrane system development. Variability was found in the number, size and electron density of plastoglobuli, and in the orientation and length of thylakoid membranes. We consider significant the increase of the plastoglobuli which completely fill the stroma of chloroplasts in cells of old leaves and, under conditions of clinorotation (using a horizontal clinostat at 3 r.p.m.), are able to block membrane function. In the early stages of orchid plant development, the content of substances with auxin-like activity (as judged by bioassay) in the leaves was low, but increased with age. Clinorotation resulted in a sharp decrease of their content. There was a concomitant increase in the content of growth inhibitors of a phenolic nature.

Assimilation of Consanguineous Mafic Intrutions: Layered Crustal Sill Complexes as Reactive Filters for Continental Basalts

NASA Astrophysics Data System (ADS)

Shervais, J. W.; Hanan, B. B.; Vetter, S. K.

2007-12-01

Continental basalts commonly display variations in their chemical compositions that are inferred to reflect fractionational crystallization (FC), recharge-FC (RFC), assimilation-FC (AFC), or recharge-AFC (RAFC). The dominance of AFC-related processes reflects the intrinsic linkage between crystallization (which releases latent heat) and assimilation (which consumes latent heat). One of the central questions in any assimilation process, however, is what exactly is being assimilated. It is commonly assumed in most AFC models for the intrusion of basalt into continental crust that the contaminant is pre-existing continental crust - that is, felsic gneiss of roughly granodioritic to tonalitic composition, which is enriched in K2O and other large ion lithophiles relative to mantle-derived basalts. These continental gneisses are commonly Precambrian in age and are enriched in the lithophilic isotope ratios 87Sr/86Sr, 207Pb/204Pb, and 208Pb/204Pb, and depleted in 143Nd/144Nd. As a result, AFC-related processes involving this ancient continental crust component typically result in basaltic lavas that are enriched in LILE (e.g., K) relative to high-field strength elements (e.g., Ti, P) and enriched in the heavy isotopes of Sr, Pb, and Nd compared to the primary or parental magma. Contrary to these expectations, basalts of the Snake River volcanic province that display chemical variations diagnostic of AFC (e.g., increasing La/Lu with decreasing mg#) are commonly characterized by essentially constant isotopic ratios of Sr, Pb and Nd, and by LILE/HFSE ratios (e.g., K/P) that decrease with decreasing mg#. We propose that these basalts assimilated a ferrogabbro derived from a parent magma that was the same or similar to the magmas being intruded to recharge the system. Melts derived from this ferrogabbro would be low in K and enriched in Fe, Ti, P, and La/Lu relative to the primitive recharge magma; the isotopic composition would be the same as the primitive recharge magma. We infer that this exchange took place within a 10 km thick mafic sill complex that has been imaged seismically at depths of 12-22 km the middle crust. We propose that this process may apply to a wide range of continental basalts.

A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle

DOE PAGES

Peylin, Philippe; Bacour, Cédric; MacBean, Natasha; ...

2016-09-20

Here, large uncertainties in land surface models (LSMs) simulations still arise from inaccurate forcing, poor description of land surface heterogeneity (soil and vegetation properties), incorrect model parameter values and incomplete representation of biogeochemical processes. The recent increase in the number and type of carbon cycle-related observations, including both in situ and remote sensing measurements, has opened a new road to optimize model parameters via robust statistical model–data integration techniques, in order to reduce the uncertainties of simulated carbon fluxes and stocks. In this study we present a carbon cycle data assimilation system that assimilates three major data streams, namely themore » Moderate Resolution Imaging Spectroradiometer (MODIS)-Normalized Difference Vegetation Index (NDVI) observations of vegetation activity, net ecosystem exchange (NEE) and latent heat (LE) flux measurements at more than 70 sites (FLUXNET), as well as atmospheric CO 2 concentrations at 53 surface stations, in order to optimize the main parameters (around 180 parameters in total) of the Organizing Carbon and Hydrology in Dynamics Ecosystems (ORCHIDEE) LSM (version 1.9.5 used for the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations). The system relies on a stepwise approach that assimilates each data stream in turn, propagating the information gained on the parameters from one step to the next. Overall, the ORCHIDEE model is able to achieve a consistent fit to all three data streams, which suggests that current LSMs have reached the level of development to assimilate these observations. The assimilation of MODIS-NDVI (step 1) reduced the growing season length in ORCHIDEE for temperate and boreal ecosystems, thus decreasing the global mean annual gross primary production (GPP). Using FLUXNET data (step 2) led to large improvements in the seasonal cycle of the NEE and LE fluxes for all ecosystems (i.e., increased amplitude for temperate ecosystems). The assimilation of atmospheric CO 2, using the general circulation model (GCM) of the Laboratoire de Météorologie Dynamique (LMDz; step 3), provides an overall constraint (i.e., constraint on large-scale net CO 2 fluxes), resulting in an improvement of the fit to the observed atmospheric CO 2 growth rate. Thus, the optimized model predicts a land C (carbon) sink of around 2.2 PgC yr -1 (for the 2000–2009 period), which is more compatible with current estimates from the Global Carbon Project (GCP) than the prior value. The consistency of the stepwise approach is evaluated with back-compatibility checks. The final optimized model (after step 3) does not significantly degrade the fit to MODIS-NDVI and FLUXNET data that were assimilated in the first two steps, suggesting that a stepwise approach can be used instead of the more “challenging” implementation of a simultaneous optimization in which all data streams are assimilated together. Most parameters, including the scalar of the initial soil carbon pool size, changed during the optimization with a large error reduction. This work opens new perspectives for better predictions of the land carbon budgets.« less

A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle

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

Peylin, Philippe; Bacour, Cédric; MacBean, Natasha

Here, large uncertainties in land surface models (LSMs) simulations still arise from inaccurate forcing, poor description of land surface heterogeneity (soil and vegetation properties), incorrect model parameter values and incomplete representation of biogeochemical processes. The recent increase in the number and type of carbon cycle-related observations, including both in situ and remote sensing measurements, has opened a new road to optimize model parameters via robust statistical model–data integration techniques, in order to reduce the uncertainties of simulated carbon fluxes and stocks. In this study we present a carbon cycle data assimilation system that assimilates three major data streams, namely themore » Moderate Resolution Imaging Spectroradiometer (MODIS)-Normalized Difference Vegetation Index (NDVI) observations of vegetation activity, net ecosystem exchange (NEE) and latent heat (LE) flux measurements at more than 70 sites (FLUXNET), as well as atmospheric CO 2 concentrations at 53 surface stations, in order to optimize the main parameters (around 180 parameters in total) of the Organizing Carbon and Hydrology in Dynamics Ecosystems (ORCHIDEE) LSM (version 1.9.5 used for the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations). The system relies on a stepwise approach that assimilates each data stream in turn, propagating the information gained on the parameters from one step to the next. Overall, the ORCHIDEE model is able to achieve a consistent fit to all three data streams, which suggests that current LSMs have reached the level of development to assimilate these observations. The assimilation of MODIS-NDVI (step 1) reduced the growing season length in ORCHIDEE for temperate and boreal ecosystems, thus decreasing the global mean annual gross primary production (GPP). Using FLUXNET data (step 2) led to large improvements in the seasonal cycle of the NEE and LE fluxes for all ecosystems (i.e., increased amplitude for temperate ecosystems). The assimilation of atmospheric CO 2, using the general circulation model (GCM) of the Laboratoire de Météorologie Dynamique (LMDz; step 3), provides an overall constraint (i.e., constraint on large-scale net CO 2 fluxes), resulting in an improvement of the fit to the observed atmospheric CO 2 growth rate. Thus, the optimized model predicts a land C (carbon) sink of around 2.2 PgC yr -1 (for the 2000–2009 period), which is more compatible with current estimates from the Global Carbon Project (GCP) than the prior value. The consistency of the stepwise approach is evaluated with back-compatibility checks. The final optimized model (after step 3) does not significantly degrade the fit to MODIS-NDVI and FLUXNET data that were assimilated in the first two steps, suggesting that a stepwise approach can be used instead of the more “challenging” implementation of a simultaneous optimization in which all data streams are assimilated together. Most parameters, including the scalar of the initial soil carbon pool size, changed during the optimization with a large error reduction. This work opens new perspectives for better predictions of the land carbon budgets.« less

A new method for evaluating impacts of data assimilation with respect to tropical cyclone intensity forecast problem

NASA Astrophysics Data System (ADS)

Vukicevic, T.; Uhlhorn, E.; Reasor, P.; Klotz, B.

2012-12-01

A significant potential for improving numerical model forecast skill of tropical cyclone (TC) intensity by assimilation of airborne inner core observations in high resolution models has been demonstrated in recent studies. Although encouraging , the results so far have not provided clear guidance on the critical information added by the inner core data assimilation with respect to the intensity forecast skill. Better understanding of the relationship between the intensity forecast and the value added by the assimilation is required to further the progress, including the assimilation of satellite observations. One of the major difficulties in evaluating such a relationship is the forecast verification metric of TC intensity: the maximum one-minute sustained wind speed at 10 m above surface. The difficulty results from two issues : 1) the metric refers to a practically unobservable quantity since it is an extreme value in a highly turbulent, and spatially-extensive wind field and 2) model- and observation-based estimates of this measure are not compatible in terms of spatial and temporal scales, even in high-resolution models. Although the need for predicting the extreme value of near surface wind is well justified, and the observation-based estimates that are used in practice are well thought of, a revised metric for the intensity is proposed for the purpose of numerical forecast evaluation and the impacts on the forecast. The metric should enable a robust observation- and model-resolvable and phenomenologically-based evaluation of the impacts. It is shown that the maximum intensity could be represented in terms of decomposition into deterministic and stochastic components of the wind field. Using the vortex-centric cylindrical reference frame, the deterministic component is defined as the sum of amplitudes of azimuthal wave numbers 0 and 1 at the radius of maximum wind, whereas the stochastic component is represented by a non-Gaussian PDF. This decomposition is exact and fully independent of individual TC properties. The decomposition of the maximum wind intensity was first evaluated using several sources of data including Step Frequency Microwave Radiometer surface wind speeds from NOAA and Air Force reconnaissance flights,NOAA P-3 Tail Doppler Radar measurements, and best track maximum intensity estimates as well as the simulations from Hurricane WRF Ensemble Data Assimilation System (HEDAS) experiments for 83 real data cases. The results confirmed validity of the method: the stochastic component of the maximum exibited a non-Gaussian PDF with small mean amplitude and variance that was comparable to the known best track error estimates. The results of the decomposition were then used to evaluate the impact of the improved initial conditions on the forecast. It was shown that the errors in the deterministic component of the intensity had the dominant effect on the forecast skill for the studied cases. This result suggests that the data assimilation of the inner core observations could focus primarily on improving the analysis of wave number 0 and 1 initial structure and on the mechanisms responsible for forcing the evolution of this low-wavenumber structure. For the latter analysis, the assimilation of airborne and satellite remote sensing observations could play significant role.

Development and evaluation of a new taxonomy of mobility-related assistive technology devices.

PubMed

Shoemaker, Laura L; Lenker, James A; Fuhrer, Marcus J; Jutai, Jeffrey W; Demers, Louise; DeRuyter, Frank

2010-10-01

This article reports on the development of a new taxonomy for mobility-related assistive technology devices. A prototype taxonomy was created based on the extant literature. Five mobility device experts were engaged in a modified Delphi process to evaluate and refine the taxonomy. Multiple iterations of expert feedback and revision yielded consensual agreement on the structure and terminology of a new mobility device taxonomy. The taxonomy uses a hierarchical framework to classify ambulation aids and wheeled mobility devices, including their key features that impact mobility. Five attributes of the new taxonomy differentiate it from previous mobility-related device classifications: (1) hierarchical structure, (2) primary device categories are grouped based on their intended mobility impact, (3) comprehensive inclusion of technical features, (4) a capacity to assimilate reimbursement codes, and (5) availability of a detailed glossary. The taxonomy is intended to support assistive technology outcomes research. The taxonomy will enable researchers to capture mobility-related assistive technology device interventions with precision and provide a common terminology that will allow comparisons among studies. The prominence of technical features within the new taxonomy will hopefully promote research that helps clinicians predict how devices will perform, thus aiding clinical decision making and supporting funding recommendations.

SrNdPb isotopic and trace element evidence for crustal contamination of plume-derived flood basalts: Oligocene flood volcanism in western Yemen

NASA Astrophysics Data System (ADS)

Baker, J. A.; Thirlwall, M. F.; Menzies, M. A.

1996-07-01

Oligocene flood basalts from western Yemen have a relatively limited range in initial isotopic composition compared with other continental flood basalts: 87Sr/86Sr = 0.70365-0.70555 ; 143Nd/144Nd = 0.5129-0.51248 ( ɛNd = +6.0 to -2.4) ; 206pb/204Pb = 17.9-19.3 . Most compositions lie outside the isotopic ranges of temporally and spatially appropriate mantle source compositions observed in this area, i.e., Red Sea/Gulf of Aden MORB mantle, the Afar plume, and Pan-African lithospheric mantle Correlations between indices of fractionation, silica, and isotope ratios suggest that crustal contamination has substantially modified the primary isotopic and incompatible trace element characteristics of the flood basalts. However, significant scatter in these correlations was produced by: (a) the heterogeneous isotopic composition of Pan-African crust; (b) the difference in susceptibility of magmas to contamination as a result of variable incompatible trace element contents in primary melts produced by differing degrees of partial melting; (c) the presence or absence of plagioclase as a fractionating phase generating complex contamination trajectories for Sr; (d) sampling over a wide area not representing a single coherent magmatic system; and (e) variation in contamination mechanisms from assimilation associated with fractionation (AFC) to assimilation by hot mafic magmas with little concomitant fractionation. The presence of plagioclase as a fractionating phase in some suites that were undergoing AFC requires assimilation to have taken place within the crust and, coupled with the limited LREE-enrichment accompanying isotopic variations, excludes the possibility that an AFC-type process took place during magma transfer through the lithospheric mantle. Isotopic compositions of some of the inferred crustal assimilants are similar to those postulated by other workers for an enriched lithospheric mantle source of many flood basalts in southwestern Yemen, Ethiopia, and Djibouti. The western Yemen flood basalts contain 0-30% crust which largely swamps their primary lead isotopic signature, but the primary SrNd isotopic signature is close to that of the least contaminated and isotopically most depleted flood basalts. LREE/HFSE and LILE/HFSE ratios also correlate with isotopic data as a result of crustal contamination. However, Nb/La and K/Nb ratios of >1.1 and <150, respectively, in least contaminated samples require an OIB-like source. The pre-contamination isotopic signature is estimated to be: 87Sr/86Sr ˜ 0.7036; 143Nd/144Nd ˜ 0.51292 ; 206Pb/204Pb ˜ 18.4-19.0 . This, coupled with low LILE/HFSE ratios, suggest the source has characteristics akin to the Afar plume. A mantle source isotopically more depleted than Bulk Earth, but not as depleted as MORB, coupled with LILE depletion, also characterises other examples of plume-derived flood volcanism. This mantle reservoir is responsible for the second largest outbursts of volcanism on Earth and has radiogenic isotopic characteristics akin to PREMA mantle, but the incompatible trace element signature of HIMU mantle.

The sRNA NsiR4 is involved in nitrogen assimilation control in cyanobacteria by targeting glutamine synthetase inactivating factor IF7.

PubMed

Klähn, Stephan; Schaal, Christoph; Georg, Jens; Baumgartner, Desirée; Knippen, Gernot; Hagemann, Martin; Muro-Pastor, Alicia M; Hess, Wolfgang R

2015-11-10

Glutamine synthetase (GS), a key enzyme in biological nitrogen assimilation, is regulated in multiple ways in response to varying nitrogen sources and levels. Here we show a small regulatory RNA, NsiR4 (nitrogen stress-induced RNA 4), which plays an important role in the regulation of GS in cyanobacteria. NsiR4 expression in the unicellular Synechocystis sp. PCC 6803 and in the filamentous, nitrogen-fixing Anabaena sp. PCC 7120 is stimulated through nitrogen limitation via NtcA, the global transcriptional regulator of genes involved in nitrogen metabolism. NsiR4 is widely conserved throughout the cyanobacterial phylum, suggesting a conserved function. In silico target prediction, transcriptome profiling on pulse overexpression, and site-directed mutagenesis experiments using a heterologous reporter system showed that NsiR4 interacts with the 5'UTR of gifA mRNA, which encodes glutamine synthetase inactivating factor (IF)7. In Synechocystis, we observed an inverse relationship between the levels of NsiR4 and the accumulation of IF7 in vivo. This NsiR4-dependent modulation of gifA (IF7) mRNA accumulation influenced the glutamine pool and thus [Formula: see text] assimilation via GS. As a second target, we identified ssr1528, a hitherto uncharacterized nitrogen-regulated gene. Competition experiments between WT and an ΔnsiR4 KO mutant showed that the lack of NsiR4 led to decreased acclimation capabilities of Synechocystis toward oscillating nitrogen levels. These results suggest a role for NsiR4 in the regulation of nitrogen metabolism in cyanobacteria, especially for the adaptation to rapid changes in available nitrogen sources and concentrations. NsiR4 is, to our knowledge, the first identified bacterial sRNA regulating the primary assimilation of a macronutrient.

Improved Stratospheric Temperature Retrievals for Climate Reanalysis

NASA Technical Reports Server (NTRS)

Rokke, L.; Joiner, J.

1999-01-01

The Data Assimilation Office (DAO) is embarking on plans to generate a twenty year reanalysis data set of climatic atmospheric variables. One of the focus points will be in the evaluation of the dynamics of the stratosphere. The Stratospheric Sounding Unit (SSU), flown as part of the TIROS Operational Vertical Sounder (TOVS), is one of the primary stratospheric temperature sensors flown consistently throughout the reanalysis period. Seven unique sensors made the measurements over time, with individual instrument characteristics that need to be addressed. The stratospheric temperatures being assimilated across satellite platforms will profoundly impact the reanalysis dynamical fields. To attempt to quantify aspects of instrument and retrieval bias we are carefully collecting and analyzing all available information on the sensors, their instrument anomalies, forward model errors and retrieval biases. For the retrieval of stratospheric temperatures, we adapted the minimum variance approach of Jazwinski (1970) and Rodgers (1976) and applied it to the SSU soundings. In our algorithm, the state vector contains an initial guess of temperature from a model six hour forecast provided by the Goddard EOS Data Assimilation System (GEOS/DAS). This is combined with an a priori covariance matrix, a forward model parameterization, and specifications of instrument noise characteristics. A quasi-Newtonian iteration is used to obtain convergence of the retrieved state to the measurement vector. This algorithm also enables us to analyze and address the systematic errors associated with the unique characteristics of the cell pressures on the individual SSU instruments and the resolving power of the instruments to vertical gradients in the stratosphere. The preliminary results of the improved retrievals and their assimilation as well as baseline calculations of bias and rms error between the NESDIS operational product and col-located ground measurements will be presented.

Land Surface Data Assimilation and the Northern Gulf Coast Land/Sea Breeze

NASA Technical Reports Server (NTRS)

Lapenta, William M.; Blackwell, Keith; Suggs, Ron; McNider, Richard T.; Jedlovec, Gary; Kimball, Sytske; Arnold, James E. (Technical Monitor)

2002-01-01

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The sea/land breeze is a well-documented mesoscale circulation that affects many coastal areas of the world including the northern Gulf Coast of the United States. The focus of this paper is to examine how the satellite assimilation technique impacts the simulation of a sea breeze circulation observed along the Mississippi/Alabama coast in the spring of 2001. The technique is implemented within the PSU/NCAR MM5 V3-4 and applied on a 4-km domain for this particular application. It is recognized that a 4-km grid spacing is too coarse to explicitly resolve the detailed, mesoscale structure of sea breezes. Nevertheless, the model can forecast certain characteristics of the observed sea breeze including a thermally direct circulation that results from differential low-level heating across the land-sea interface. Our intent is to determine the sensitivity of the circulation to the differential land surface forcing produced via the assimilation of GOES skin temperature tendencies. Results will be quantified through statistical verification techniques.

Application of Land Surface Data Assimilation to Simulations of Sea Breeze Circulations

NASA Technical Reports Server (NTRS)

Mackaro, Scott; Lapenta, William M.; Blackwell, Keith; Suggs, Ron; McNider, Richard T.; Jedlovec, Gary; Kimball, Sytske

2003-01-01

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite- observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The sea/land breeze is a well-documented mesoscale circulation that affects many coastal areas of the world including the northern Gulf Coast of the United States. The focus of this paper is to examine how the satellite assimilation technique impacts the simulation of a sea breeze circulation observed along the Mississippi/Alabama coast in the spring of 2001. The technique is implemented within the PSUNCAR MM5 V3-5 and applied at spatial resolutions of 12- and 4-km. It is recognized that even 4-km grid spacing is too coarse to explicitly resolve the detailed, mesoscale structure of sea breezes. Nevertheless, the model can forecast certain characteristics of the observed sea breeze including a thermally direct circulation that results from differential low-level heating across the land-sea interface. Our intent is to determine the sensitivity of the circulation to the differential land surface forcing produced via the assimilation of GOES skin temperature tendencies. Results will be quantified through statistical verification techniques.

Rapid Weakening of Hurricane Joaquin in Strong Vertical Wind Shear and Cold SSTs: Numerical Simulations with Assimilation of High-Definition Sounding System Dropsondes During Tropical Cyclone Intensity Experiment

NASA Astrophysics Data System (ADS)

Pu, Z.; Zhang, S.

2017-12-01

Observations from High-Definition Sounding System (HDSS) Dropsondes, collected for Hurricane Joaquin (2005) during the Office of Naval Research Tropical Cyclone Intensity (TCI) Experiment in 2015, are assimilated into the Gridpoint Statistical Interpolation (GSI)-based hybrid data assimilation systems embedded in the NCEP Hurricane Weather Research and Forecasting (HWRF) system. A three-dimensional and a four-dimensional ensemble-variational hybrid (3DEnVAR and 4DEnVar) data assimilation configuration are used. It is found that the experiments with assimilation of the HDSS dropsonde observations capture well the intensity changes during the rapid weakening (RW) of Hurricane Joaquin. Compared with 3DEnVAR, 4DEnVar leads to better assimilation results and subsequent forecasts and thus offers a set of simulations to diagnose the processes associated with the RW of Hurricane Joaquin. A drastic increase in the vertical wind shear (VWS, with a magnitude of 12 m s-1) is found before the RW. This high VWS is persistent during the 0-12 h period of RW, inducing changes in the vortex structure of Hurricane Joaquin through dry air intrusion in the mid-level and the dilution of the upper-level warm core. The transport of low air from above into the boundary layer occurs at the same time, resulting in depressed values in the storm inflow layer and reduced eyewall values through the updraft. As a consequence, downdrafts flush the boundary layer with low air, leading to the weakening of inflow in the boundary layers. When Hurricane Joaquin moves over an area where the SSTs are below 28oC within the hurricane inner core during the 18-30 h period of RW, the cold SSTs significantly inhibit latent and sensible heat release within the hurricane inner core and its vicinity, thus resulting in the continuous weakening of Hurricane Joaquin.

Rapid Weakening of Hurricane Joaquin in Strong Vertical Wind Shear and Cold SSTs: Numerical Simulations with Assimilation of High-Definition Sounding System Dropsondes During Tropical Cyclone Intensity Experiment

NASA Astrophysics Data System (ADS)

Pikelnaya, O.; Polidori, A.; Tisopulos, L.; Mellqvist, J.; Samuelsson, J.; Robinson, R. A.; Innocenti, F.; Perry, S.

2016-12-01

Observations from High-Definition Sounding System (HDSS) Dropsondes, collected for Hurricane Joaquin (2005) during the Office of Naval Research Tropical Cyclone Intensity (TCI) Experiment in 2015, are assimilated into the Gridpoint Statistical Interpolation (GSI)-based hybrid data assimilation systems embedded in the NCEP Hurricane Weather Research and Forecasting (HWRF) system. A three-dimensional and a four-dimensional ensemble-variational hybrid (3DEnVAR and 4DEnVar) data assimilation configuration are used. It is found that the experiments with assimilation of the HDSS dropsonde observations capture well the intensity changes during the rapid weakening (RW) of Hurricane Joaquin. Compared with 3DEnVAR, 4DEnVar leads to better assimilation results and subsequent forecasts and thus offers a set of simulations to diagnose the processes associated with the RW of Hurricane Joaquin. A drastic increase in the vertical wind shear (VWS, with a magnitude of 12 m s-1) is found before the RW. This high VWS is persistent during the 0-12 h period of RW, inducing changes in the vortex structure of Hurricane Joaquin through dry air intrusion in the mid-level and the dilution of the upper-level warm core. The transport of low air from above into the boundary layer occurs at the same time, resulting in depressed values in the storm inflow layer and reduced eyewall values through the updraft. As a consequence, downdrafts flush the boundary layer with low air, leading to the weakening of inflow in the boundary layers. When Hurricane Joaquin moves over an area where the SSTs are below 28oC within the hurricane inner core during the 18-30 h period of RW, the cold SSTs significantly inhibit latent and sensible heat release within the hurricane inner core and its vicinity, thus resulting in the continuous weakening of Hurricane Joaquin.

Grounding the figure.

PubMed

Calis, G; Leeuwenberg, E

1981-12-01

Coding rules can be formulated in which the shortest description of a figure-ground pattern exhibits a hierarchical structure, with the ground playing a primary and the figure a secondary role. We hypothesized that the process of perception involves and assimilation phase followed by a test phase in which the ground is tested before the figure. Experiments are described in which pairs of consecutive, superimposed patterns are presented in rapid succession, resulting in a subjective impression of seeing one pattern only. In these presentations, the second pattern introduces some deliberate distortion of the figure or ground displayed in the first pattern. Maximal distortions of the ground occur at shorter stimulus onset asynchronies than maximal distortions of the figure, suggesting that the ground codes are processed before figure codes. Moreover, patterns presenting the ground first are more likely to be perceived as ground, regardless of the distortions, than patterns presenting the figure first. This quasi masking or microgenetic approach might be relevant to theories on :mediations of immediate, or direct" perception.

Implementing change in primary care practices using electronic medical records: a conceptual framework.

PubMed

Nemeth, Lynne S; Feifer, Chris; Stuart, Gail W; Ornstein, Steven M

2008-01-16

Implementing change in primary care is difficult, and little practical guidance is available to assist small primary care practices. Methods to structure care and develop new roles are often needed to implement an evidence-based practice that improves care. This study explored the process of change used to implement clinical guidelines for primary and secondary prevention of cardiovascular disease in primary care practices that used a common electronic medical record (EMR). Multiple conceptual frameworks informed the design of this study designed to explain the complex phenomena of implementing change in primary care practice. Qualitative methods were used to examine the processes of change that practice members used to implement the guidelines. Purposive sampling in eight primary care practices within the Practice Partner Research Network-Translating Researching into Practice (PPRNet-TRIP II) clinical trial yielded 28 staff members and clinicians who were interviewed regarding how change in practice occurred while implementing clinical guidelines for primary and secondary prevention of cardiovascular disease and strokes. A conceptual framework for implementing clinical guidelines into primary care practice was developed through this research. Seven concepts and their relationships were modelled within this framework: leaders setting a vision with clear goals for staff to embrace; involving the team to enable the goals and vision for the practice to be achieved; enhancing communication systems to reinforce goals for patient care; developing the team to enable the staff to contribute toward practice improvement; taking small steps, encouraging practices' tests of small changes in practice; assimilating the electronic medical record to maximize clinical effectiveness, enhancing practices' use of the electronic tool they have invested in for patient care improvement; and providing feedback within a culture of improvement, leading to an iterative cycle of goal setting by leaders. This conceptual framework provides a mental model which can serve as a guide for practice leaders implementing clinical guidelines in primary care practice using electronic medical records. Using the concepts as implementation and evaluation criteria, program developers and teams can stimulate improvements in their practice settings. Investing in collaborative team development of clinicians and staff may enable the practice environment to be more adaptive to change and improvement.

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

Tracing Carbon Flow from Primary Production to a Gulf Coast Salt Marsh Consumer, the Seaside Sparrow (Ammodramus maritimus)

NASA Astrophysics Data System (ADS)

Johnson, J. J.; Polito, M. J.; Olin, J.

2016-02-01

Determining the relative contributions of primary producers to salt marsh food webs is fundamental to understanding how these systems are structured. Biomarkers such as bulk carbon isotopes (13C/12C) and fatty acids have become popular tracers of trophic dynamics, based on the principle that the composition of biomarkers in consumer tissues is a reflection of the composition of these same biomarkers in a consumer's diet. However, the use of bulk stable isotope and fatty acid analyses to assess carbon flow in food webs is often hampered by confounding factors such as isotopic fractionation and fatty acid modifications that can occur between trophic levels. In contrast, compound-specific stable isotope analysis of amino acids may offer a more precise tracking of carbon flow through complex food webs. This is because the isotopic values of essential amino acids in consumer tissues are assimilated largely unchanged from their primary sources at the base of the food web. The aim of this study was to test the consistency of three different methods (bulk carbon stable isotope, fatty acid and compound-specific stable isotope analyses) while examining the carbon source pool underlying the diet of a common marsh consumer, the seaside sparrow (A. maritimus). This comparison allows us to gain a better idea of the relative merits of these analytical methods and contribute to a clearer model of overall trophic dynamics in a salt marsh food web.

CHARACTERIZATION OF THE ALKANE-INDUCIBLE CYTOCHROME P450 (P450ALK) GENE FROM THE YEAST CANDIDA TROPICALIS: IDENTIFICATION OF A NEW P450 FAMILY

EPA Science Inventory

The P450alk gene, which is inducible by the assimilation of alkane in Candida tropicalis, was sequenced and characterized. Structural features described in promoter and terminator regions of Saccharomyces yeast genes are present in the P450alk gene and some particular structures ...

Operational Hydrological Forecasting During the Iphex-iop Campaign - Meet the Challenge

NASA Technical Reports Server (NTRS)

Tao, Jing; Wu, Di; Gourley, Jonathan; Zhang, Sara Q.; Crow, Wade; Peters-Lidard, Christa D.; Barros, Ana P.

2016-01-01

An operational streamflow forecasting testbed was implemented during the Intense Observing Period (IOP) of the Integrated Precipitation and Hydrology Experiment (IPHEx-IOP) in May-June 2014 to characterize flood predictability in complex terrain. Specifically, hydrological forecasts were issued daily for 12 headwater catchments in the Southern Appalachians using the Duke Coupled surface-groundwater Hydrology Model (DCHM) forced by hourly atmospheric fields and QPFs (Quantitative Precipitation Forecasts) produced by the NASA-Unified Weather Research and Forecasting (NU-WRF) model. Previous day hindcasts forced by radar-based QPEs (Quantitative Precipitation Estimates) were used to provide initial conditions for present day forecasts. This manuscript first describes the operational testbed framework and workflow during the IPHEx-IOP including a synthesis of results. Second, various data assimilation approaches are explored a posteriori (post-IOP) to improve operational (flash) flood forecasting. Although all flood events during the IOP were predicted by the IPHEx operational testbed with lead times of up to 6 h, significant errors of over- and, or under-prediction were identified that could be traced back to the QPFs and subgrid-scale variability of radar QPEs. To improve operational flood prediction, three data-merging strategies were pursued post-IOP: (1) the spatial patterns of QPFs were improved through assimilation of satellite-based microwave radiances into NU-WRF; (2) QPEs were improved by merging raingauge observations with ground-based radar observations using bias-correction methods to produce streamflow hindcasts and associated uncertainty envelope capturing the streamflow observations, and (3) river discharge observations were assimilated into the DCHM to improve streamflow forecasts using the Ensemble Kalman Filter (EnKF), the fixed-lag Ensemble Kalman Smoother (EnKS), and the Asynchronous EnKF (i.e. AEnKF) methods. Both flood hindcasts and forecasts were significantly improved by assimilating discharge observations into the DCHM. Specifically, Nash-Sutcliff Efficiency (NSE) values as high as 0.98, 0.71 and 0.99 at 15-min time-scales were attained for three headwater catchments in the inner mountain region demonstrating that the assimilation of discharge observations at the basins outlet can reduce the errors and uncertainties in soil moisture at very small scales. Success in operational flood forecasting at lead times of 6, 9, 12 and 15 h was also achieved through discharge assimilation with NSEs of 0.87, 0.78, 0.72 and 0.51, respectively. Analysis of experiments using various data assimilation system configurations indicates that the optimal assimilation time window depends both on basin properties and storm-specific space-time-structure of rainfall, and therefore adaptive, context-aware configurations of the data assimilation system are recommended to address the challenges of flood prediction in headwater basins.

Operational hydrological forecasting during the IPHEx-IOP campaign - Meet the challenge

NASA Astrophysics Data System (ADS)

Tao, Jing; Wu, Di; Gourley, Jonathan; Zhang, Sara Q.; Crow, Wade; Peters-Lidard, Christa; Barros, Ana P.

2016-10-01

An operational streamflow forecasting testbed was implemented during the Intense Observing Period (IOP) of the Integrated Precipitation and Hydrology Experiment (IPHEx-IOP) in May-June 2014 to characterize flood predictability in complex terrain. Specifically, hydrological forecasts were issued daily for 12 headwater catchments in the Southern Appalachians using the Duke Coupled surface-groundwater Hydrology Model (DCHM) forced by hourly atmospheric fields and QPFs (Quantitative Precipitation Forecasts) produced by the NASA-Unified Weather Research and Forecasting (NU-WRF) model. Previous day hindcasts forced by radar-based QPEs (Quantitative Precipitation Estimates) were used to provide initial conditions for present day forecasts. This manuscript first describes the operational testbed framework and workflow during the IPHEx-IOP including a synthesis of results. Second, various data assimilation approaches are explored a posteriori (post-IOP) to improve operational (flash) flood forecasting. Although all flood events during the IOP were predicted by the IPHEx operational testbed with lead times of up to 6 h, significant errors of over- and, or under-prediction were identified that could be traced back to the QPFs and subgrid-scale variability of radar QPEs. To improve operational flood prediction, three data-merging strategies were pursued post-IOP: (1) the spatial patterns of QPFs were improved through assimilation of satellite-based microwave radiances into NU-WRF; (2) QPEs were improved by merging raingauge observations with ground-based radar observations using bias-correction methods to produce streamflow hindcasts and associated uncertainty envelope capturing the streamflow observations, and (3) river discharge observations were assimilated into the DCHM to improve streamflow forecasts using the Ensemble Kalman Filter (EnKF), the fixed-lag Ensemble Kalman Smoother (EnKS), and the Asynchronous EnKF (i.e. AEnKF) methods. Both flood hindcasts and forecasts were significantly improved by assimilating discharge observations into the DCHM. Specifically, Nash-Sutcliff Efficiency (NSE) values as high as 0.98, 0.71 and 0.99 at 15-min time-scales were attained for three headwater catchments in the inner mountain region demonstrating that the assimilation of discharge observations at the basin's outlet can reduce the errors and uncertainties in soil moisture at very small scales. Success in operational flood forecasting at lead times of 6, 9, 12 and 15 h was also achieved through discharge assimilation with NSEs of 0.87, 0.78, 0.72 and 0.51, respectively. Analysis of experiments using various data assimilation system configurations indicates that the optimal assimilation time window depends both on basin properties and storm-specific space-time-structure of rainfall, and therefore adaptive, context-aware configurations of the data assimilation system are recommended to address the challenges of flood prediction in headwater basins.

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.

Impacts of Different Assimilation Methodologies on Crop Yield Estimates Using Active and Passive Microwave Dataset at L-Band

NASA Astrophysics Data System (ADS)

Liu, P.; Bongiovanni, T. E.; Monsivais-Huertero, A.; Bindlish, R.; Judge, J.

2013-12-01

Accurate estimates of crop yield are important for managing agricultural production and food security. Although the crop growth models, such as the Decision Support System Agrotechnology Transfer (DSSAT), have been used to simulate crop growth and development, the crop yield estimates still diverge from the reality due to different sources of errors in the models and computation. Auxiliary observations may be incorporated into such dynamic models to improve predictions using data assimilation. Active and passive (AP) microwave observations at L-band (1-2 GHz) are sensitive to dielectric and geometric properties of soil and vegetation, including soil moisture (SM), vegetation water content (VWC), surface roughness, and vegetation structure. Because SM and VWC are one of the governing factors in estimating crop yield, microwave observations may be used to improve crop yield estimates. Current studies have shown that active observations are more sensitive to the surface roughness of soil and vegetation structure during the growing season, while the passive observations are more sensitive to the SM. Backscatter and emission models linked with the DSSAT model (DSSAT-A-P) allow assimilation of microwave observations of backscattering coefficient (σ0) and brightness temperature (TB) may provide biophysically realistic estimates of model states and parameters. The present ESA Soil Moisture Ocean Salinity (SMOS) mission provides passive observations at 1.41 GHz at 25 km every 2-3 days, and the NASA/CNDAE Aquarius mission provides L-band AP observations at spatial resolution of 150 km with a repeat coverage of 7 days for global SM products. In 2014, the planned NASA Soil Moisture Active Passive mission will provide AP observations at 1.26 and 1.41 GHz at the spatial resolutions of 3 and 30 km, respectively, with a repeat coverage of 2-3 days. The goal of this study is to understand the impacts of assimilation of asynchronous and synchronous AP observations on crop yield estimates. An Ensemble Kalman Filter-based methodology is implemented to incorporate σ0 and TB from Aquarius and SMOS in the DSSAT-A-P model to improve crop yield for two growing seasons of soybean -a normal and a drought affected season- in the rain-fed region of the Brazilian La Plata Basin, South America. Different scenarios of assimilation, including active only, passive only, and combined AP observations were considered. The elements of the state vector included both model states and parameters related to soil and vegetation. The number of elements included in the state vector changed depending upon different scenarios of assimilation and also upon the growth stages. Crop yield estimates were compared for different scenarios during the two seasons. A synthetic experiment conducted previously showed an improvement of crop estimates in the RMSD by 90 kg/ha using combined AP compared to the openloop and active only assimilation over the region.

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

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

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.

Temporary Storage or Permanent Removal? The Division of Nitrogen between Biotic Assimilation and Denitrification in Stormwater Biofiltration Systems

PubMed Central

Payne, Emily G. I.; Fletcher, Tim D.; Russell, Douglas G.; Grace, Michael R.; Cavagnaro, Timothy R.; Evrard, Victor; Deletic, Ana; Hatt, Belinda E.; Cook, Perran L. M.

2014-01-01

The long-term efficacy of stormwater treatment systems requires continuous pollutant removal without substantial re-release. Hence, the division of incoming pollutants between temporary and permanent removal pathways is fundamental. This is pertinent to nitrogen, a critical water body pollutant, which on a broad level may be assimilated by plants or microbes and temporarily stored, or transformed by bacteria to gaseous forms and permanently lost via denitrification. Biofiltration systems have demonstrated effective removal of nitrogen from urban stormwater runoff, but to date studies have been limited to a ‘black-box’ approach. The lack of understanding on internal nitrogen processes constrains future design and threatens the reliability of long-term system performance. While nitrogen processes have been thoroughly studied in other environments, including wastewater treatment wetlands, biofiltration systems differ fundamentally in design and the composition and hydrology of stormwater inflows, with intermittent inundation and prolonged dry periods. Two mesocosm experiments were conducted to investigate biofilter nitrogen processes using the stable isotope tracer 15NO3 − (nitrate) over the course of one inflow event. The immediate partitioning of 15NO3 − between biotic assimilation and denitrification were investigated for a range of different inflow concentrations and plant species. Assimilation was the primary fate for NO3 − under typical stormwater concentrations (∼1–2 mg N/L), contributing an average 89–99% of 15NO3 − processing in biofilter columns containing the most effective plant species, while only 0–3% was denitrified and 0–8% remained in the pore water. Denitrification played a greater role for columns containing less effective species, processing up to 8% of 15NO3 −, and increased further with nitrate loading. This study uniquely applied isotope tracing to biofiltration systems and revealed the dominance of assimilation in stormwater biofilters. The findings raise important questions about nitrogen release upon plant senescence, seasonally and in the long term, which have implications on the management and design of biofiltration systems. PMID:24670377

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.

Variation of the North Equatorial Current, Mindanao Current, and Kuroshio Current in a high-resolution data assimilation during 2008-2012

NASA Astrophysics Data System (ADS)

Zhai, Fangguo; Wang, Qingye; Wang, Fujun; Hu, Dunxin

2014-11-01

Outputs from a high-resolution data assimilation system, the global Hybrid Coordinate Ocean Model and Navy Coupled Ocean Data Assimilation (HYCOM+NCODA) 1/12° analysis, were analyzed for the period September 2008 to February 2012. The objectives were to evaluate the performance of the system in simulating ocean circulation in the tropical northwestern Pacific and to examine the seasonal to interannual variations of the western boundary currents. The HYCOM assimilation compares well with altimetry observations and mooring current measurements. The mean structures and standard deviations of velocities of the North Equatorial Current (NEC), Mindanao Current (MC) and Kuroshio Current (KC) also compare well with previous observations. Seasonal to interannual variations of the NEC transport volume are closely correlated with the MC transport volume, instead of that of the KC. The NEC and MC transport volumes mainly show well-defined annual cycles, with their maxima in spring and minima in fall, and are closely related to the circulation changes in the Mindanao Dome (MD) region. In seasons of transport maxima, the MD region experiences negative SSH anomalies and a cyclonic gyre anomaly, and in seasons of transport minima the situation is reversed. The sea surface NEC bifurcation latitude (NBL) in the HYCOM assimilation also agrees well with altimetry observations. In 2009, the NBL shows an annual cycle similar to previous studies, reaching its southernmost position in summer and its northernmost position in winter. In 2010 and 2011, the NBL variations are dominantly influenced by La Niña events. The dynamics responsible for the seasonal to interannual variations of the NEC-MC-KC current system are also discussed.

Nitrate Reductase Knockout Uncouples Nitrate Transport from Nitrate Assimilation and Drives Repartitioning of Carbon Flux in a Model Pennate Diatom[OPEN

PubMed Central

Smith, Sarah R.; McCrow, John P.; Tan, Maxine; Lichtle, Christian; Goodenough, Ursula; Bowler, Chris P.; Dupont, Christopher L.

2017-01-01

The ecological prominence of diatoms in the ocean environment largely results from their superior competitive ability for dissolved nitrate (NO3−). To investigate the cellular and genetic basis of diatom NO3− assimilation, we generated a knockout in the nitrate reductase gene (NR-KO) of the model pennate diatom Phaeodactylum tricornutum. In NR-KO cells, N-assimilation was abolished although NO3− transport remained intact. Unassimilated NO3− accumulated in NR-KO cells, resulting in swelling and associated changes in biochemical composition and physiology. Elevated expression of genes encoding putative vacuolar NO3− chloride channel transporters plus electron micrographs indicating enlarged vacuoles suggested vacuolar storage of NO3−. Triacylglycerol concentrations in the NR-KO cells increased immediately following the addition of NO3−, and these increases coincided with elevated gene expression of key triacylglycerol biosynthesis components. Simultaneously, induction of transcripts encoding proteins involved in thylakoid membrane lipid recycling suggested more abrupt repartitioning of carbon resources in NR-KO cells compared with the wild type. Conversely, ribosomal structure and photosystem genes were immediately deactivated in NR-KO cells following NO3− addition, followed within hours by deactivation of genes encoding enzymes for chlorophyll biosynthesis and carbon fixation and metabolism. N-assimilation pathway genes respond uniquely, apparently induced simultaneously by both NO3− replete and deplete conditions. PMID:28765511

Nitrate Reductase Knockout Uncouples Nitrate Transport from Nitrate Assimilation and Drives Repartitioning of Carbon Flux in a Model Pennate Diatom

DOE PAGES

McCarthy, James K.; Smith, Sarah R.; McCrow, John P.; ...

2017-09-07

The ecological prominence of diatoms in the ocean environment largely results from their superior competitive ability for dissolved nitrate (NO 3 -). To investigate the cellular and genetic basis of diatom NO 3 - assimilation, in this paper we generated a knockout in the nitrate reductase gene (NR-KO) of the model pennate diatom Phaeodactylum tricornutum. In NR-KO cells, N-assimilation was abolished although NO 3 - transport remained intact. Unassimilated NO 3 - accumulated in NR-KO cells, resulting in swelling and associated changes in biochemical composition and physiology. Elevated expression of genes encoding putative vacuolar NO 3 - chloride channel transportersmore » plus electron micrographs indicating enlarged vacuoles suggested vacuolar storage of NO 3 -. Triacylglycerol concentrations in the NR-KO cells increased immediately following the addition of NO 3 -, and these increases coincided with elevated gene expression of key triacylglycerol biosynthesis components. Simultaneously, induction of transcripts encoding proteins involved in thylakoid membrane lipid recycling suggested more abrupt repartitioning of carbon resources in NR-KO cells compared with the wild type. Conversely, ribosomal structure and photosystem genes were immediately deactivated in NR-KO cells following NO 3 - addition, followed within hours by deactivation of genes encoding enzymes for chlorophyll biosynthesis and carbon fixation and metabolism. Finally, N-assimilation pathway genes respond uniquely, apparently induced simultaneously by both NO 3 - replete and deplete conditions.« less

Nitrate Reductase Knockout Uncouples Nitrate Transport from Nitrate Assimilation and Drives Repartitioning of Carbon Flux in a Model Pennate Diatom

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

McCarthy, James K.; Smith, Sarah R.; McCrow, John P.

The ecological prominence of diatoms in the ocean environment largely results from their superior competitive ability for dissolved nitrate (NO 3 -). To investigate the cellular and genetic basis of diatom NO 3 - assimilation, in this paper we generated a knockout in the nitrate reductase gene (NR-KO) of the model pennate diatom Phaeodactylum tricornutum. In NR-KO cells, N-assimilation was abolished although NO 3 - transport remained intact. Unassimilated NO 3 - accumulated in NR-KO cells, resulting in swelling and associated changes in biochemical composition and physiology. Elevated expression of genes encoding putative vacuolar NO 3 - chloride channel transportersmore » plus electron micrographs indicating enlarged vacuoles suggested vacuolar storage of NO 3 -. Triacylglycerol concentrations in the NR-KO cells increased immediately following the addition of NO 3 -, and these increases coincided with elevated gene expression of key triacylglycerol biosynthesis components. Simultaneously, induction of transcripts encoding proteins involved in thylakoid membrane lipid recycling suggested more abrupt repartitioning of carbon resources in NR-KO cells compared with the wild type. Conversely, ribosomal structure and photosystem genes were immediately deactivated in NR-KO cells following NO 3 - addition, followed within hours by deactivation of genes encoding enzymes for chlorophyll biosynthesis and carbon fixation and metabolism. Finally, N-assimilation pathway genes respond uniquely, apparently induced simultaneously by both NO 3 - replete and deplete conditions.« less

Continental scale data assimilation of discharge and its effect on flow predictions

NASA Astrophysics Data System (ADS)

Weerts, Albrecht; Schellekens, Jaap; van Dijk, Albert

2017-04-01

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist (Emmerton et al., 2016). Current global flood forecasting system heavily rely on forecast forcing (precipitation, temperature, reference potential evaporation) to derive initial state estimates of the hydrological model for the next forecast (e.g. by glueing the first day of subsequent forecast as proxy for the historical observed forcing). It is clear that this approach is not perfect and that data assimilation can help to overcome some of the weaknesses of this approach. So far most hydrologic da studies have focused mostly on catchment scale. Here we conduct a da experiment by assimilating multiple streamflow observations across the contiguous united states (CONUS) and Europe into a global hydrological model (W3RA) and run with and without localization method using OpenDA in the global flood forecasting information system (GLOFFIS). It is shown that assimilation of streamflow holds considerable potential for improving global scale flood forecasting (improving NSE scores from 0 to 0.7 and beyond). Weakness in the model (e.g. structural problems and missing processes) and forcing that influence the performance will be highlighted.

Continental scale data assimilation of discharge and its effect on flow predictions across the contiguous US (CONUS)

NASA Astrophysics Data System (ADS)

Weerts, A.; Schellekens, J.; van Dijk, A.; Molenaar, R.

2016-12-01

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist (Emmerton et al., 2016). Current global flood forecasting system heavily rely on forecast forcing (precipitation, temperature, reference potential evaporation) to derive initial state estimates of the hydrological model for the next forecast (e.g. by glueing the first day of subsequent forecast as proxy for the historical observed forcing). It is clear that this approach is not perfect and that data assimilation can help to overcome some of the weaknesses of this approach. So far most hydrologic da studies have focused mostly on catchment scale. Here we conduct a da experiment by assimilating multiple streamflow observations across the contiguous united states (CONUS) into a global hydrological model (W3RA) and run with and without localization method using OpenDA in the global flood forecasting information system (GLOFFIS). It is shown that assimilation of streamflow holds considerable potential for improving global scale flood forecasting (improving NSE scores from 0 to 0.7 and beyond). Weakness in the model (e.g. structural problems and missing processes) and forcing that influence the performance will be highlighted.

Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

PubMed

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

2017-12-01

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

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 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.

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.

An Investigation of the Characterization of Cloud Contamination in Hyperspectral Radiances

NASA Technical Reports Server (NTRS)

McCarty, William; Jedlovec, Gary J.; LeMarshall, John

2007-01-01

In regions lacking direct observations, the assimilation of radiances from infrared and microwave sounders is the primary method for characterizing the atmosphere in the analysis process. In recent years, technological advances have led to the launching of more advanced sounders, particularly in the thermal infrared spectrum. With the advent of these hyperspectral sounders, the amount of data available for the analysis process has and will continue to be dramatically increased. However, the utilization of infrared radiances in variational assimilation can be problematic in the presence of clouds; specifically the assessment of the presence of clouds in an instantaneous field of view (IFOV) and the contamination in the individual channels within the IFOV. Various techniques have been developed to determine if a channel is contaminated by clouds. The work presented in this paper and subsequent presentation will investigate traditional techniques and compare them to a new technique, the C02 sorting technique, which utilizes the high spectral resolution of the Atmospheric Infrared Sounder (AIRS) within the framework of the Gridpoint Statistical Interpolation (GSI) 3DVAR system. Ultimately, this work is done in preparation for the assessment of short-term forecast impacts with the regional assimilation of AIRS radiances within the analysis fields of the Weather Research and Forecast Nonhydrostatic Mesoscale Model (WRF-NMM) at the NASA Short-term Prediction Research and Transition (SPORT) Center.

Growth Responses of Three Dominant Wetland Plant Species to Various Flooding and Nutrient Levels

NASA Astrophysics Data System (ADS)

Barrett, S.; Shaffer, G. P.

2017-12-01

Coastal Louisiana is experiencing a greater rate of wetland loss than any other wetland system in the United States. This is primarily due to anthropogenic stressors such as flood control levees, backfilling and development of wetlands, and other hydrologic modifications. Methods employed to mitigate wetland loss include the construction of river diversions and assimilation wetlands, which can provide consistent sources of freshwater influx and nutrients to impounded swamps and marshes. It is well known that prolonged flooding causes strain on wetland plant communities and facilitates or exacerbates wetland degradation. However, because river diversions and assimilation wetlands bring high nutrient loads along with freshwater, there is debate over whether prolonged flooding or high influx of nutrients is the primary cause of stress in river diversion and assimilation wetland discharge areas. This mesocosm experiment addresses this question by isolating the effects of flooding and nutrients on the biomass of baldcypress (Taxodium distichum), maidencane (Panicum hemitomon), and cordgrass (Spartina patens) over the course of a growing season. The results of this study provide clarity as to whether flooding stress, high nutrient loads, or both cause a reduction in wetland plant productivity. By evaluating the growth responses of T. distichum, P. hemitomon, and S. patens at varying nutrient regimes, we gain insight on how these more dominant species will react to high nutrient discharges from large river diversions, such as those proposed in Louisiana's 2017 Master Plan.

A prototype upper-atmospheric data assimilation scheme based on optimal interpolation: 2. Numerical experiments

NASA Astrophysics Data System (ADS)

Akmaev, R. a.

1999-04-01

In Part 1 of this work ([Akmaev, 1999]), an overview of the theory of optimal interpolation (OI) ([Gandin, 1963]) and related techniques of data assimilation based on linear optimal estimation ([Liebelt, 1967]; [Catlin, 1989]; [Mendel, 1995]) is presented. The approach implies the use in data analysis of additional statistical information in the form of statistical moments, e.g., the mean and covariance (correlation). The a priori statistical characteristics, if available, make it possible to constrain expected errors and obtain optimal in some sense estimates of the true state from a set of observations in a given domain in space and/or time. The primary objective of OI is to provide estimates away from the observations, i.e., to fill in data voids in the domain under consideration. Additionally, OI performs smoothing suppressing the noise, i.e., the spectral components that are presumably not present in the true signal. Usually, the criterion of optimality is minimum variance of the expected errors and the whole approach may be considered constrained least squares or least squares with a priori information. Obviously, data assimilation techniques capable of incorporating any additional information are potentially superior to techniques that have no access to such information as, for example, the conventional least squares (e.g., [Liebelt, 1967]; [Weisberg, 1985]; [Press et al., 1992]; [Mendel, 1995]).

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

Metabolic effectors secreted by bacterial pathogens: essential facilitators of plastid endosymbiosis?

PubMed

Ball, Steven G; Subtil, Agathe; Bhattacharya, Debashish; Moustafa, Ahmed; Weber, Andreas P M; Gehre, Lena; Colleoni, Christophe; Arias, Maria-Cecilia; Cenci, Ugo; Dauvillée, David

2013-01-01

Under the endosymbiont hypothesis, over a billion years ago a heterotrophic eukaryote entered into a symbiotic relationship with a cyanobacterium (the cyanobiont). This partnership culminated in the plastid that has spread to forms as diverse as plants and diatoms. However, why primary plastid acquisition has not been repeated multiple times remains unclear. Here, we report a possible answer to this question by showing that primary plastid endosymbiosis was likely to have been primed by the secretion in the host cytosol of effector proteins from intracellular Chlamydiales pathogens. We provide evidence suggesting that the cyanobiont might have rescued its afflicted host by feeding photosynthetic carbon into a chlamydia-controlled assimilation pathway.

Complete genome sequence of Paenibacillus sp. strain JDR-2

Treesearch

Virginia Chow; Guang Nong; Franz J. St. John; John D. Rice; Ellen Dickstein; Olga Chertkov; David Bruce; Chris Detter; Thomas Brettin; James Han; Tanja Woyke; Sam Pitluck; Matt Nolan; Amrita Pati; Joel Martin; Alex Copeland; Miriam L. Land; Lynne Goodwin; Jeffrey B. Jones; Lonnie O. Ingram; Keelnathan T. Shanmugam; James F. Preston

2012-01-01

Paenibacillus sp. strain JDR-2, an aggressively xylanolytic bacterium isolated from sweetgum (Liquidambar styraciflua) wood, is able to efficiently depolymerize, assimilate and metabolize 4-O-methylglucuronoxylan, the predominant structural component of hardwood hemicelluloses. A basis for this capability was first supported by...

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.

The SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) Product

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Crow, Wade; Koster, Randal; Kimball, John

2010-01-01

The Soil Moisture Active and Passive (SMAP) mission is being developed by NASA for launch in 2013 as one of four first-tier missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space in 2007. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. In this paper we describe the assimilation of SMAP observations for the generation of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product. The SMAP mission makes simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band) from a sun-synchronous low-earth orbit. Measurements will be obtained across a 1000 km wide swath using conical scanning at a constant incidence angle (40 deg). The radar resolution varies from 1-3 km over the outer 70% of the swath to about 30 km near the center of the swath. The radiometer resolution is 40 km across the entire swath. The radiometer measurements will allow high-accuracy but coarse resolution (40 km) measurements. The radar measurements will add significantly higher resolution information. The radar is however very sensitive to surface roughness and vegetation structure. The combination of the two measurements allows optimal blending of the advantages of each instrument. SMAP directly observes only surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (approximately top 1 m of the soil column), which is not directly measured by SMAP. The foremost objective of the SMAP L4_SM product is to fill this gap and provide estimates of root zone soil moisture that are informed by and consistent with SMAP observations. Such estimates are obtained by merging SMAP observations with estimates from a land surface model in a soil moisture data assimilation system. The land surface model component of the assimilation system is driven with observations-based surface meteorological forcing data, including precipitation, which is the most important driver for soil moisture. The model also encapsulates knowledge of key land surface processes, including the vertical transfer of soil moisture between the surface and root zone reservoirs. Finally, the model interpolates and extrapolates SMAP observations in time and in space. The L4_SM product thus provides a comprehensive and consistent picture of land surface hydrological conditions based on SMAP observations and complementary information from a variety of sources. The assimilation algorithm considers the respective uncertainties of each component and yields a product that is superior to satellite or model data alone. Error estimates for the L4_SM product are generated as a by-product of the data assimilation system.

Metabolism of organic acids, nitrogen and amino acids in chlorotic leaves of 'Honeycrisp' apple (Malus domestica Borkh) with excessive accumulation of carbohydrates.

PubMed

Wang, Huicong; Ma, Fangfang; Cheng, Lailiang

2010-07-01

Metabolite profiles and activities of key enzymes in the metabolism of organic acids, nitrogen and amino acids were compared between chlorotic leaves and normal leaves of 'Honeycrisp' apple to understand how accumulation of non-structural carbohydrates affects the metabolism of organic acids, nitrogen and amino acids. Excessive accumulation of non-structural carbohydrates and much lower CO(2) assimilation were found in chlorotic leaves than in normal leaves, confirming feedback inhibition of photosynthesis in chlorotic leaves. Dark respiration and activities of several key enzymes in glycolysis and tricarboxylic acid (TCA) cycle, ATP-phosphofructokinase, pyruvate kinase, citrate synthase, aconitase and isocitrate dehydrogenase were significantly higher in chlorotic leaves than in normal leaves. However, concentrations of most organic acids including phosphoenolpyruvate (PEP), pyruvate, oxaloacetate, 2-oxoglutarate, malate and fumarate, and activities of key enzymes involved in the anapleurotic pathway including PEP carboxylase, NAD-malate dehydrogenase and NAD-malic enzyme were significantly lower in chlorotic leaves than in normal leaves. Concentrations of soluble proteins and most free amino acids were significantly lower in chlorotic leaves than in normal leaves. Activities of key enzymes in nitrogen assimilation and amino acid synthesis, including nitrate reductase, glutamine synthetase, ferredoxin and NADH-dependent glutamate synthase, and glutamate pyruvate transaminase were significantly lower in chlorotic leaves than in normal leaves. It was concluded that, in response to excessive accumulation of non-structural carbohydrates, glycolysis and TCA cycle were up-regulated to "consume" the excess carbon available, whereas the anapleurotic pathway, nitrogen assimilation and amino acid synthesis were down-regulated to reduce the overall rate of amino acid and protein synthesis.

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.

Evidence for the assimilation of ancient glacier organic carbon in a proglacial stream food web

USGS Publications Warehouse

Fellman, Jason; Hood, Eran; Raymond, Peter A.; Hudson, J.H.; Bozeman, Maura; Arimitsu, Mayumi L.

2015-01-01

We used natural abundance δ13C, δ15N, and Δ14C to compare trophic linkages between potential carbon sources (leaf litter, epilithic biofilm, and particulate organic matter) and consumers (aquatic macroinvertebrates and fish) in a nonglacial stream and two reaches of the heavily glaciated Herbert River. We tested the hypothesis that proglacial stream food webs are sustained by organic carbon released from glacial ecosystems. Carbon sources and consumers in the nonglacial stream had carbon isotope values that ranged from -30‰ to -25‰ for δ13C and from -14‰ to 53‰ for Δ14C reflecting a food web sustained mainly on contemporary primary production. In contrast, biofilm in the two glacial stream sites was highly Δ14C-depleted (-215‰ to 175‰) relative to the nonglacial stream consistent with the assimilation of ancient glacier organic carbon. IsoSource modeling showed that in upper Herbert River, macroinvertebrates (Δ14C = -171‰ to 22‰) and juvenile salmonids (Δ14C = −102‰ to 17‰) reflected a feeding history of both biofilm (~ 56%) and leaf litter (~ 40%). We estimate that in upper Herbert River on average 36% of the carbon incorporated into consumer biomass is derived from the glacier ecosystem. Thus, 14C-depleted glacial organic carbon was likely transferred to higher trophic levels through a feeding history of bacterial uptake of dissolved organic carbon and subsequent consumption of 14C-depleted biofilm by invertebrates and ultimately fish. Our findings show that the metazoan food web is sustained in part by glacial organic carbon such that future changes in glacial runoff could influence the stability and trophic structure of proglacial aquatic ecosystems.

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

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

Thomas, R. Quinn; Brooks, Evan B.; Jersild, Annika L.

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions,more » DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO 2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 10 5 km 2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO 2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO 2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO 2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO 2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.« less

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

DOE PAGES

Thomas, R. Quinn; Brooks, Evan B.; Jersild, Annika L.; ...

2017-07-26

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions,more » DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO 2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 10 5 km 2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO 2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO 2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO 2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO 2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.« less

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

NASA Astrophysics Data System (ADS)

Quinn Thomas, R.; Brooks, Evan B.; Jersild, Annika L.; Ward, Eric J.; Wynne, Randolph H.; Albaugh, Timothy J.; Dinon-Aldridge, Heather; Burkhart, Harold E.; Domec, Jean-Christophe; Fox, Thomas R.; Gonzalez-Benecke, Carlos A.; Martin, Timothy A.; Noormets, Asko; Sampson, David A.; Teskey, Robert O.

2017-07-01

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model-data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.

A 3D Optimal Interpolation Assimilation Scheme of HF Radar Current Data into a Numerical Ocean Model

NASA Astrophysics Data System (ADS)

Ragnoli, Emanuele; Zhuk, Sergiy; Donncha, Fearghal O.; Suits, Frank; Hartnett, Michael

2013-04-01

In this work a technique for the 3D assimilation of ocean surface current measurements into a numerical ocean model based on data from High Frequency Radar (HFR) systems is presented. The technique is the combination of supplementary forcing on the surface and of and Ekman layer projection of the correction in the depth. Optimal interpolation through BLUE (Best Linear Unbiased Estimator) of the model predicted velocity and HFR observations is computed in order to derive a supplementary forcing applied at the surface boundary. In the depth the assimilation is propagated using an additional Ekman pumping (vertical velocity) based on the correction achieved by BLUE. In this work a HFR data assimilation system for hydrodynamic modelling of Galway Bay in Ireland is developed; it demonstrates the viability of adopting data assimilation techniques to improve the performance of numerical models in regions characterized by significant wind-driven flows. A network of CODAR Seasonde high frequency radars (HFR) deployed within Galway Bay, on the West Coast of Ireland, provides flow measurements adopted for this study. This system provides real-time synoptic measurements of both ocean surface currents and ocean surface waves in regions of the bay where radials from two or more radars intersect. Radar systems have a number of unique advantages in ocean modelling data assimilation schemes, namely, the ability to provide two-dimensional mapping of surface currents at resolutions that capture the complex structure related to coastal topography and the intrinsic instability scales of coastal circulation at a relatively low-cost. The radar system used in this study operates at a frequency of 25MHz which provides a sampling range of 25km at a spatial resolution of 300m.A detailed dataset of HFR observed velocities is collected at 60 minute intervals for a period chosen for comparison due to frequent occurrences of highly-energetic, storm-force events. In conjunction with this, a comprehensive weather station, tide gauge and river monitoring program is conducted. The data are then used to maintain density fields within the model and to force the wind direction and magnitude on flows. The Data Assimilation scheme is then assessed and validated via HFR surface flow measurements.

Microbial life in the Lake Medee, the largest deep-sea salt-saturated formation

NASA Astrophysics Data System (ADS)

Yakimov, Michail M.; La Cono, Violetta; Slepak, Vladlen Z.; La Spada, Gina; Arcadi, Erika; Messina, Enzo; Borghini, Mireno; Monticelli, Luis S.; Rojo, David; Barbas, Coral; Golyshina, Olga V.; Ferrer, Manuel; Golyshin, Peter N.; Giuliano, Laura

2013-12-01

Deep-sea hypersaline anoxic lakes (DHALs) of the Eastern Mediterranean represent some of the most hostile environments on our planet. We investigated microbial life in the recently discovered Lake Medee, the largest DHAL found to-date. Medee has two unique features: a complex geobiochemical stratification and an absence of chemolithoautotrophic Epsilonproteobacteria, which usually play the primary role in dark bicarbonate assimilation in DHALs interfaces. Presumably because of these features, Medee is less productive and exhibits reduced diversity of autochthonous prokaryotes in its interior. Indeed, the brine community almost exclusively consists of the members of euryarchaeal MSBL1 and bacterial KB1 candidate divisions. Our experiments utilizing cultivation and [14C]-assimilation, showed that these organisms at least partially rely on reductive cleavage of osmoprotectant glycine betaine and are engaged in trophic cooperation. These findings provide novel insights into how prokaryotic communities can adapt to salt-saturated conditions and sustain active metabolism at the thermodynamic edge of life.

Identity as a 'patchwork': aspects of identity among low-income Brazilian travestis.

PubMed

Garcia, Marcos Roberto Vieira

2009-08-01

This paper is based on findings from a qualitative study that took place within the context of a four-year healthcare programme directed towards low-income travestis in the central area of Sao Paulo, Brazil. Throughout the study the formation of social identity among travestis was investigated through a focus on four axes: gender, body, work and violence. This paper subjects the identity of the travestis to a critical analysis and proposes a view of their sense of self as a 'patchwork' assembled through the assimilation of various fragments of identity common in Brazilian society. The primary identities assimilated by the travestis under study were, in the area of femininity, the submissive woman, the puta ['whore'] and the super-seductive woman and, in the area of masculinity, the viado ['queer'], the malandro ['rascal'] and the bandido ['bandit']. The resulting travesti identity exhibited not only gender ambiguity, but also contradictions among the feminine identities described, as well as among the masculine ones.

Petrogenesis of mare basalts - A record of lunar volcanism

NASA Astrophysics Data System (ADS)

Neal, Clive R.; Taylor, Lawrence A.

1992-06-01

The classification, sources, and overall petrogenesis of mare basalts are reviewed. All mare basalt analyses are used to define a sixfold classification scheme using TiO2 contents as the primary division. A secondary division is made using Al2O3 contents, and a tertiary division is defined using K contents. Such divisions and subdivisions yield a classification containing 12 categories, of which six are accounted for by the existing Apollo and Luna collections. A variety of postmagma-generation such as fractional crystallization, either alone or combined with wallrock assimilation, are invoked to explain the compositional ranges of the various mare basalt suites. High-Ti mare basalts are found at Apollo 1 and Apollo 17 sites; the A-11 basalts contain lower TiO2 abundances, a considerably larger range in trace-element contents, and the only occurrence of high-Ti/high-K mare basalts. The low-Ti basalts exhibit a wide range of major-and trace-element compositions and require source heterogeneity, fractional crystallization, and some assimilation.

Ionospheric Simulation System for Satellite Observations and Global Assimilative Model Experiments - ISOGAME

NASA Technical Reports Server (NTRS)

Pi, Xiaoqing; Mannucci, Anthony J.; Verkhoglyadova, Olga; Stephens, Philip; Iijima, Bryron A.

2013-01-01

Modeling and imaging the Earth's ionosphere as well as understanding its structures, inhomogeneities, and disturbances is a key part of NASA's Heliophysics Directorate science roadmap. This invention provides a design tool for scientific missions focused on the ionosphere. It is a scientifically important and technologically challenging task to assess the impact of a new observation system quantitatively on our capability of imaging and modeling the ionosphere. This question is often raised whenever a new satellite system is proposed, a new type of data is emerging, or a new modeling technique is developed. The proposed constellation would be part of a new observation system with more low-Earth orbiters tracking more radio occultation signals broadcast by Global Navigation Satellite System (GNSS) than those offered by the current GPS and COSMIC observation system. A simulation system was developed to fulfill this task. The system is composed of a suite of software that combines the Global Assimilative Ionospheric Model (GAIM) including first-principles and empirical ionospheric models, a multiple- dipole geomagnetic field model, data assimilation modules, observation simulator, visualization software, and orbit design, simulation, and optimization software.

Development of fine-resolution analyses and expanded large-scale forcing properties. Part I: Methodology and evaluation

DOE PAGES

Li, Zhijin; Vogelmann, Andrew M.; Feng, Sha; ...

2015-01-20

We produce fine-resolution, three-dimensional fields of meteorological and other variables for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The Community Gridpoint Statistical Interpolation system is implemented in a multiscale data assimilation (MS-DA) framework that is used within the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. The MS-DA algorithm uses existing reanalysis products and constrains fine-scale atmospheric properties by assimilating high-resolution observations. A set of experiments show that the data assimilation analysis realistically reproduces the intensity, structure, and time evolution of clouds and precipitation associated with a mesoscale convective system.more » Evaluations also show that the large-scale forcing derived from the fine-resolution analysis has an overall accuracy comparable to the existing ARM operational product. For enhanced applications, the fine-resolution fields are used to characterize the contribution of subgrid variability to the large-scale forcing and to derive hydrometeor forcing, which are presented in companion papers.« less

Performance Evaluation of EnKF-based Hydrogeological Site Characterization using Color Coherent Vectors

NASA Astrophysics Data System (ADS)

Moslehi, M.; de Barros, F.

2017-12-01

Complexity of hydrogeological systems arises from the multi-scale heterogeneity and insufficient measurements of their underlying parameters such as hydraulic conductivity and porosity. An inadequate characterization of hydrogeological properties can significantly decrease the trustworthiness of numerical models that predict groundwater flow and solute transport. Therefore, a variety of data assimilation methods have been proposed in order to estimate hydrogeological parameters from spatially scarce data by incorporating the governing physical models. In this work, we propose a novel framework for evaluating the performance of these estimation methods. We focus on the Ensemble Kalman Filter (EnKF) approach that is a widely used data assimilation technique. It reconciles multiple sources of measurements to sequentially estimate model parameters such as the hydraulic conductivity. Several methods have been used in the literature to quantify the accuracy of the estimations obtained by EnKF, including Rank Histograms, RMSE and Ensemble Spread. However, these commonly used methods do not regard the spatial information and variability of geological formations. This can cause hydraulic conductivity fields with very different spatial structures to have similar histograms or RMSE. We propose a vision-based approach that can quantify the accuracy of estimations by considering the spatial structure embedded in the estimated fields. Our new approach consists of adapting a new metric, Color Coherent Vectors (CCV), to evaluate the accuracy of estimated fields achieved by EnKF. CCV is a histogram-based technique for comparing images that incorporate spatial information. We represent estimated fields as digital three-channel images and use CCV to compare and quantify the accuracy of estimations. The sensitivity of CCV to spatial information makes it a suitable metric for assessing the performance of spatial data assimilation techniques. Under various factors of data assimilation methods such as number, layout, and type of measurements, we compare the performance of CCV with other metrics such as RMSE. By simulating hydrogeological processes using estimated and true fields, we observe that CCV outperforms other existing evaluation metrics.

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.

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.

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.

Y-chromosome R-M343 African Lineages and Sickle Cell Disease reveal structured assimilation in Lebanon

PubMed Central

Haber, Marc; Platt, Daniel E; Khoury, Simon; Badro, Danielle A; Abboud, Miguel; Smith, Chris Tyler; Zalloua, Pierre A

2012-01-01

We have sought to identify signals of assimilation of African male lines in Lebanon by exploring the association of sickle cell disease in Lebanon with Y-chromosome haplogroups that are informative of the disease origin and its exclusivity to the Muslim community. A total of 732 samples were analyzed including 33 sickle cell disease patients from Lebanon genotyped for 28 binary markers and 19 short tandem repeats on the non-recombinant segment of the Y chromosome. Genetic organization was identified using populations known to have influenced the genetic structure of the Lebanese population, in addition to African populations with high incidence of sickle cell disease. Y-chromosome haplogroup R-M343 sub-lineages distinguish between sub-Saharan African and Lebanese Y chromosomes. We detected a limited penetration of sickle cell disease into Lebanese R-M343 carriers, restricted to Lebanese Muslims. We suggest that this penetration brought the sickle cell gene along with the African R-M343, probably with the Saharan caravan slave trade. PMID:20981037

Interference thinking in constructing students’ knowledge to solve mathematical problems

NASA Astrophysics Data System (ADS)

Jayanti, W. E.; Usodo, B.; Subanti, S.

2018-04-01

This research aims to describe interference thinking in constructing students’ knowledge to solve mathematical problems. Interference thinking in solving problems occurs when students have two concepts that interfere with each other’s concept. Construction of problem-solving can be traced using Piaget’s assimilation and accommodation framework, helping to know the students’ thinking structures in solving the problems. The method of this research was a qualitative method with case research strategy. The data in this research involving problem-solving result and transcripts of interviews about students’ errors in solving the problem. The results of this research focus only on the student who experience proactive interference, where student in solving a problem using old information to interfere with the ability to recall new information. The student who experience interference thinking in constructing their knowledge occurs when the students’ thinking structures in the assimilation and accommodation process are incomplete. However, after being given reflection to the student, then the students’ thinking process has reached equilibrium condition even though the result obtained remains wrong.

Temperature and Carbon Assimilation Regulate the Chlorosome Biogenesis in Green Sulfur Bacteria

PubMed Central

Tang, Joseph Kuo-Hsiang; Saikin, Semion K.; Pingali, Sai Venkatesh; Enriquez, Miriam M.; Huh, Joonsuk; Frank, Harry A.; Urban, Volker S.; Aspuru-Guzik, Alán

2013-01-01

Green photosynthetic bacteria adjust the structure and functionality of the chlorosome—the light-absorbing antenna complex—in response to environmental stress factors. The chlorosome is a natural self-assembled aggregate of bacteriochlorophyll (BChl) molecules. In this study, we report the regulation of the biogenesis of the Chlorobaculum tepidum chlorosome by carbon assimilation in conjunction with temperature changes. Our studies indicate that the carbon source and thermal stress culture of C. tepidum grows slower and incorporates fewer BChl c in the chlorosome. Compared with the chlorosome from other cultural conditions we investigated, the chlorosome from the carbon source and thermal stress culture displays (a) smaller cross-sectional radius and overall size, (b) simplified BChl c homologs with smaller side chains, (c) blue-shifted Qy absorption maxima, and (d) a sigmoid-shaped circular dichroism spectra. Using a theoretical model, we analyze how the observed spectral modifications can be associated with structural changes of BChl aggregates inside the chlorosome. Our report suggests a mechanism of metabolic regulation for chlorosome biogenesis. PMID:24047985

[The influence of meaning making following stressful life experiences on change of self-concept].

PubMed

Horita, Ryo; Sugie, Masashi

2013-10-01

As interest in meaning making following stressful life experiences continues to grow, it is important to clarify the features and functions of the meaning- making process. We examined the influence of meaning making following stressful life experiences on change of self-concept. In two studies, university students selected their most stressful life experience and completed the Assimilation and Accommodation of Meaning Making Scale. In Study 1, 235 university students also completed questionnaires regarding post-traumatic growth and positive change of the sense of identity following their stressful life experience. The results of covariance structure analysis indicated that accommodation promoted a positive change of self-concept. In Study 2, 199 university students completed questionnaires regarding change of self-concept and emotion as a positive or negative change following stressful life experiences. The results of covariance structure analysis indicated that accommodation promoted a positive change, similar to the results of Study 1. In addition, accommodation also promoted negative change. However, assimilation did not promote positive change but did restrain negative change.

Use of Quality Controlled AIRS Temperature Soundings to Improve Forecast Skill

NASA Technical Reports Server (NTRS)

Susskind, Joel; Reale, Oreste; Iredell, Lena

2010-01-01

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. Also included are the clear column radiances used to derive these products which are representative of the radiances AIRS would have seen if there were no clouds in the field of view. All products also have error estimates. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20 percent, in cases with up to 90 percent effective cloud cover. The products are designed for data assimilation purposes for the improvement of numerical weather prediction, as well as for the study of climate and meteorological processes. With regard to data assimilation, one can use either the products themselves or the clear column radiances from which the products were derived. The AIRS Version 5 retrieval algorithm is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates for retrieved quantities and clear column radiances, and the use of these error estimates for Quality Control. The temperature profile error estimates are used to determine a case-by-case characteristic pressure pbest, down to which the profile is considered acceptable for data assimilation purposes. The characteristic pressure p(sub best) is determined by comparing the case dependent error estimate (delta)T(p) to the threshold values (Delta)T(p). The AIRS Version 5 data set provides error estimates of T(p) at all levels, and also profile dependent values of pbest based on use of a Standard profile dependent threshold (Delta)T(p). These Standard thresholds were designed as a compromise between optimal use for data assimilation purposes, which requires highest accuracy (tighter Quality Control), and climate purposes, which requires more spatial coverage (looser Quality Control). Subsequent research using Version 5 sounding and error estimates showed that tighter Quality Control performs better for data assimilation proposes, while looser Quality Control better spatial coverage) performs better for climate purposes. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 degree latitude x 0.67 degree longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates (delta)T(p) were used as the uncertainty for each measurement in the data assimilation process.

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.

Induction of the Nitrate Assimilation nirA Operon and Protein-Protein Interactions in the Maturation of Nitrate and Nitrite Reductases in the Cyanobacterium Anabaena sp. Strain PCC 7120.

PubMed

Frías, José E; Flores, Enrique

2015-07-01

Nitrate is widely used as a nitrogen source by cyanobacteria, in which the nitrate assimilation structural genes frequently constitute the so-called nirA operon. This operon contains the genes encoding nitrite reductase (nirA), a nitrate/nitrite transporter (frequently an ABC-type transporter; nrtABCD), and nitrate reductase (narB). In the model filamentous cyanobacterium Anabaena sp. strain PCC 7120, which can fix N2 in specialized cells termed heterocysts, the nirA operon is expressed at high levels only in media containing nitrate or nitrite and lacking ammonium, a preferred nitrogen source. Here we examined the genes downstream of the nirA operon in Anabaena and found that a small open reading frame of unknown function, alr0613, can be cotranscribed with the operon. The next gene in the genome, alr0614 (narM), showed an expression pattern similar to that of the nirA operon, implying correlated expression of narM and the operon. A mutant of narM with an insertion mutation failed to produce nitrate reductase activity, consistent with the idea that NarM is required for the maturation of NarB. Both narM and narB mutants were impaired in the nitrate-dependent induction of the nirA operon, suggesting that nitrite is an inducer of the operon in Anabaena. It has previously been shown that the nitrite reductase protein NirA requires NirB, a protein likely involved in protein-protein interactions, to attain maximum activity. Bacterial two-hybrid analysis confirmed possible NirA-NirB and NarB-NarM interactions, suggesting that the development of both nitrite reductase and nitrate reductase activities in cyanobacteria involves physical interaction of the corresponding enzymes with their cognate partners, NirB and NarM, respectively. Nitrate is an important source of nitrogen for many microorganisms that is utilized through the nitrate assimilation system, which includes nitrate/nitrite membrane transporters and the nitrate and nitrite reductases. Many cyanobacteria assimilate nitrate, but regulation of the nitrate assimilation system varies in different cyanobacterial groups. In the N2-fixing, heterocyst-forming cyanobacteria, the nirA operon, which includes the structural genes for the nitrate assimilation system, is expressed in the presence of nitrate or nitrite if ammonium is not available to the cells. Here we studied the genes required for production of an active nitrate reductase, providing information on the nitrate-dependent induction of the operon, and found evidence for possible protein-protein interactions in the maturation of nitrate reductase and nitrite reductase. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

A multi-sites analysis on the ozone effects on Gross Primary Production of European forests.

PubMed

Proietti, C; Anav, A; De Marco, A; Sicard, P; Vitale, M

2016-06-15

Ozone (O3) is both a greenhouse gas and a secondary air pollutant causing adverse impacts on forests ecosystems at different scales, from cellular to ecosystem level. Specifically, the phytotoxic nature of O3 can impair CO2 assimilation that, in turn affects forest productivity. This study aims to evaluate the effects of tropospheric O3 on Gross Primary Production (GPP) at 37 European forest sites during the time period 2000-2010. Due to the lack of carbon assimilation data at O3 monitoring stations (and vice-versa) this study makes a first attempt to combine high resolution MODIS Gross Primary Production (GPP) estimates and O3 measurement data. Partial Correlations, Anomalies Analysis and the Random Forests Analysis (RFA) were used to quantify the effects of tropospheric O3 concentration and its uptake on GPP and to evaluate the most important factors affecting inter-annual GPP changes. Our results showed, along a North-West/South-East European transect, a negative impact of O3 on GPP ranging from 0.4% to 30%, although a key role of meteorological parameters respect to pollutant variables in affecting GPP was found. In particular, meteorological parameters, namely air temperature (T), soil water content (SWC) and relative humidity (RH) are the most important predictors at 81% of test sites. Moreover, it is interesting to highlight a key role of SWC in the Mediterranean areas (Spanish, Italian and French test sites) confirming that, soil moisture and soil water availability affect vegetation growth and photosynthesis especially in arid or semi-arid ecosystems such as the Mediterranean climate regions. Considering the pivotal role of GPP in the global carbon balance and the O3 ability to reduce primary productivity of the forests, this study can help in assessing the O3 impacts on ecosystem services, including wood production and carbon sequestration. Copyright © 2016 Elsevier B.V. All rights reserved.

Comment on "Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?" by Mazzoleni et al. (2017)

NASA Astrophysics Data System (ADS)

Viero, Daniele P.

2018-01-01

Citizen science and crowdsourcing are gaining increasing attention among hydrologists. In a recent contribution, Mazzoleni et al. (2017) investigated the integration of crowdsourced data (CSD) into hydrological models to improve the accuracy of real-time flood forecasts. The authors used synthetic CSD (i.e. not actually measured), because real CSD were not available at the time of the study. In their work, which is a proof-of-concept study, Mazzoleni et al. (2017) showed that assimilation of CSD improves the overall model performance; the impact of irregular frequency of available CSD, and that of data uncertainty, were also deeply assessed. However, the use of synthetic CSD in conjunction with (semi-)distributed hydrological models deserves further discussion. As a result of equifinality, poor model identifiability, and deficiencies in model structure, internal states of (semi-)distributed models can hardly mimic the actual states of complex systems away from calibration points. Accordingly, the use of synthetic CSD that are drawn from model internal states under best-fit conditions can lead to overestimation of the effectiveness of CSD assimilation in improving flood prediction. Operational flood forecasting, which results in decisions of high societal value, requires robust knowledge of the model behaviour and an in-depth assessment of both model structure and forcing data. Additional guidelines are given that are useful for the a priori evaluation of CSD for real-time flood forecasting and, hopefully, for planning apt design strategies for both model calibration and collection of CSD.

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).

Convective dynamics - Panel report

NASA Technical Reports Server (NTRS)

Carbone, Richard; Foote, G. Brant; Moncrieff, Mitch; Gal-Chen, Tzvi; Cotton, William; Heymsfield, Gerald

1990-01-01

Aspects of highly organized forms of deep convection at midlatitudes are reviewed. Past emphasis in field work and cloud modeling has been directed toward severe weather as evidenced by research on tornadoes, hail, and strong surface winds. A number of specific issues concerning future thrusts, tactics, and techniques in convective dynamics are presented. These subjects include; convective modes and parameterization, global structure and scale interaction, convective energetics, transport studies, anvils and scale interaction, and scale selection. Also discussed are analysis workshops, four-dimensional data assimilation, matching models with observations, network Doppler analyses, mesoscale variability, and high-resolution/high-performance Doppler. It is also noted, that, classical surface measurements and soundings, flight-level research aircraft data, passive satellite data, and traditional photogrammetric studies are examples of datasets that require assimilation and integration.

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.

Oxygen isotope composition of mafic magmas at Vesuvius

NASA Astrophysics Data System (ADS)

Dallai, L.; Cioni, R.; Boschi, C.; D'Oriano, C.

2009-12-01

The oxygen isotope composition of olivine and clinopyroxene from four plinian (AD 79 Pompeii, 3960 BP Avellino), subplinian (AD 472 Pollena) and violent strombolian (Middle Age activity) eruptions were measured to constrain the nature and evolution of the primary magmas of the last 4000 years of Mt. Vesuvius activity. A large set of mm-sized crystals was accurately separated from selected juvenile material of the four eruptions. Crystals were analyzed for their major and trace element compositions (EPMA, Laser Ablation ICP-MS), and for 18O/16O ratios. As oxygen isotope composition of uncontaminated mantle rocks on world-wide scale is well constrained (δ18Oolivine = 5.2 ± 0.3; δ18Ocpx = 5.6 ± 0.3 ‰), the measured values can be conveniently used to monitor the effects of assimilation/contamination of crustal rocks in the evolution of the primary magmas. Instead, typically uncontaminated mantle values are hardly recovered in Italian Quaternary magmas, mostly due to the widespread occurrence of crustal contamination of the primary magmas during their ascent to the surface (e.g. Alban Hills, Ernici Mts., and Aeolian Islands). Low δ18O values have been measured in olivine from Pompeii eruption (δ18Oolivine = 5.54 ± 0.03‰), whereas higher O-compositions are recorded in mafic minerals from pumices or scoria of the other three eruptions. Measured olivine and clinopyroxene share quite homogeneous chemical compositions (Olivine Fo 85-90 ; Diopside En 45-48, respectively), and represent phases crystallized in near primary mafic magmas, as also constrained by their trace element compositions. Data on melt inclusions hosted in crystals of these compositions have been largely collected in the past demonstrating that they crystallized from mafic melt, basaltic to tephritic in composition. Published data on volatile content of these melt inclusions reveal the coexistence of dissolved water and carbon dioxide, and a minimum trapping pressure around 200-300 MPa, suggesting that crystal growth possibly occurred during magma ascent from the source region or in a shallow reservoir at about 8-10 km depth. Recently, experimental data have suggested massive carbonate assimilation (up to about 20%) to derive potassic alkali magmas from trachybasaltic melts. Accordingly, the δ18O variability and the trace element contents of the studied minerals suggest possible contamination of primary melts by an O-isotope enriched, REE-poor contaminant like the limestone of Vesuvius basement. The δ18Oolivine and δ18Ocpx of the studied minerals define variable degrees of carbonate assimilation and magma crystallization for the different eruptions, and possibly within the same eruption, and show evidence of oxygen isotope equilibrium at high temperature. However, energy-constrained AFC model suggest that carbonate contamination was limited. On the basis of our data, we suggest that interaction between magma and a fluxing, decarbonation-derived CO2 fluid may be partly accounted for the measured O-isotope compositions.

Implicit and Explicit: An Experiment in Applied Psycholinguistics, Assessing Different Methods of Teaching Grammatical Structures in English as a Foreign Language.

ERIC Educational Resources Information Center

Olsson, Margareta

Project 3 of the GUME research project on foreign language teaching methods, in line with Projects 1 and 2, questions whether the best effect in language teaching is achieved solely by intensive drilling of the structure in question (the implicit method) or if grammatical explanations further the assimilation of the patterns so that, within the…

Linking physiological processes with mangrove forest structure: phosphorus deficiency limits canopy development, hydraulic conductivity and photosynthetic carbon gain in dwarf Rhizophora mangle.

PubMed

Lovelock, Catherine E; Ball, Marilyn C; Choat, Brendan; Engelbrecht, Bettina M J; Holbrook, N Michelle; Feller, Ilka C

2006-05-01

Spatial gradients in mangrove tree height in barrier islands of Belize are associated with nutrient deficiency and sustained flooding in the absence of a salinity gradient. While nutrient deficiency is likely to affect many parameters, here we show that addition of phosphorus (P) to dwarf mangroves stimulated increases in diameters of xylem vessels, area of conductive xylem tissue and leaf area index (LAI) of the canopy. These changes in structure were consistent with related changes in function, as addition of P also increased hydraulic conductivity (Ks), stomatal conductance and photosynthetic assimilation rates to the same levels measured in taller trees fringing the seaward margin of the mangrove. Increased xylem vessel size and corresponding enhancements in stem hydraulic conductivity in P fertilized dwarf trees came at the cost of enhanced mid-day loss of hydraulic conductivity and was associated with decreased assimilation rates in the afternoon. Analysis of trait plasticity identifies hydraulic properties of trees as more plastic than those of leaf structural and physiological characteristics, implying that hydraulic properties are key in controlling growth in mangroves. Alleviation of P deficiency, which released trees from hydraulic limitations, reduced the structural and functional distinctions between dwarf and taller fringing tree forms of Rhizophora mangle.

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

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.

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.

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).

Mingus Discontinuous Multiphysics

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

Pat Notz, Dan Turner

Mingus provides hybrid coupled local/non-local mechanics analysis capabilities that extend several traditional methods to applications with inherent discontinuities. Its primary features include adaptations of solid mechanics, fluid dynamics and digital image correlation that naturally accommodate dijointed data or irregular solution fields by assimilating a variety of discretizations (such as control volume finite elements, peridynamics and meshless control point clouds). The goal of this software is to provide an analysis framework form multiphysics engineering problems with an integrated image correlation capability that can be used for experimental validation and model

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.

Nitrogen Assimilation in Escherichia coli: Putting Molecular Data into a Systems Perspective

PubMed Central

van Heeswijk, Wally C.; Westerhoff, Hans V.

2013-01-01

SUMMARY We present a comprehensive overview of the hierarchical network of intracellular processes revolving around central nitrogen metabolism in Escherichia coli. The hierarchy intertwines transport, metabolism, signaling leading to posttranslational modification, and transcription. The protein components of the network include an ammonium transporter (AmtB), a glutamine transporter (GlnHPQ), two ammonium assimilation pathways (glutamine synthetase [GS]-glutamate synthase [glutamine 2-oxoglutarate amidotransferase {GOGAT}] and glutamate dehydrogenase [GDH]), the two bifunctional enzymes adenylyl transferase/adenylyl-removing enzyme (ATase) and uridylyl transferase/uridylyl-removing enzyme (UTase), the two trimeric signal transduction proteins (GlnB and GlnK), the two-component regulatory system composed of the histidine protein kinase nitrogen regulator II (NRII) and the response nitrogen regulator I (NRI), three global transcriptional regulators called nitrogen assimilation control (Nac) protein, leucine-responsive regulatory protein (Lrp), and cyclic AMP (cAMP) receptor protein (Crp), the glutaminases, and the nitrogen-phosphotransferase system. First, the structural and molecular knowledge on these proteins is reviewed. Thereafter, the activities of the components as they engage together in transport, metabolism, signal transduction, and transcription and their regulation are discussed. Next, old and new molecular data and physiological data are put into a common perspective on integral cellular functioning, especially with the aim of resolving counterintuitive or paradoxical processes featured in nitrogen assimilation. Finally, we articulate what still remains to be discovered and what general lessons can be learned from the vast amounts of data that are available now. PMID:24296575

Metaphor and hyperassociativity: the imagination mechanisms behind emotion assimilation in sleep and dreaming

PubMed Central

Malinowski, Josie E.; Horton, Caroline L.

2015-01-01

In this paper we propose an emotion assimilation function of sleep and dreaming. We offer explanations both for the mechanisms by which waking-life memories are initially selected for processing during sleep, and for the mechanisms by which those memories are subsequently transformed during sleep. We propose that emotions act as a marker for information to be selectively processed during sleep, including consolidation into long term memory structures and integration into pre-existing memory networks; that dreaming reflects these emotion assimilation processes; and that the associations between memory fragments activated during sleep give rise to measureable elements of dream metaphor and hyperassociativity. The latter are a direct reflection, and the phenomenological experience, of emotional memory assimilation processes occurring during sleep. While many theories previously have posited a role for emotion processing and/or emotional memory consolidation during sleep and dreaming, sleep theories often do not take enough account of important dream science data, yet dream research, when conducted systematically and under ideal conditions, can greatly enhance theorizing around the functions of sleep. Similarly, dream theories often fail to consider the implications of sleep-dependent memory research, which can augment our understanding of dream functioning. Here, we offer a synthesized view, taking detailed account of both sleep and dream data and theories. We draw on extensive literature from sleep and dream experiments and theories, including often-overlooked data from dream science which we believe reflects sleep phenomenology, to bring together important ideas and findings from both domains. PMID:26347669

Rain radar measurement error estimation using data assimilation in an advection-based nowcasting system

NASA Astrophysics Data System (ADS)

Merker, Claire; Ament, Felix; Clemens, Marco

2017-04-01

The quantification of measurement uncertainty for rain radar data remains challenging. Radar reflectivity measurements are affected, amongst other things, by calibration errors, noise, blocking and clutter, and attenuation. Their combined impact on measurement accuracy is difficult to quantify due to incomplete process understanding and complex interdependencies. An improved quality assessment of rain radar measurements is of interest for applications both in meteorology and hydrology, for example for precipitation ensemble generation, rainfall runoff simulations, or in data assimilation for numerical weather prediction. Especially a detailed description of the spatial and temporal structure of errors is beneficial in order to make best use of the areal precipitation information provided by radars. Radar precipitation ensembles are one promising approach to represent spatially variable radar measurement errors. We present a method combining ensemble radar precipitation nowcasting with data assimilation to estimate radar measurement uncertainty at each pixel. This combination of ensemble forecast and observation yields a consistent spatial and temporal evolution of the radar error field. We use an advection-based nowcasting method to generate an ensemble reflectivity forecast from initial data of a rain radar network. Subsequently, reflectivity data from single radars is assimilated into the forecast using the Local Ensemble Transform Kalman Filter. The spread of the resulting analysis ensemble provides a flow-dependent, spatially and temporally correlated reflectivity error estimate at each pixel. We will present first case studies that illustrate the method using data from a high-resolution X-band radar network.

Assimilation of Sea Surface Temperature in a doubly, two-way nested primitive equation model of the Ligurian Sea

NASA Astrophysics Data System (ADS)

Barth, A.; Alvera-Azcarate, A.; Rixen, M.; Beckers, J.-M.; Testut, C.-E.; Brankart, J.-M.; Brasseur, P.

2003-04-01

The GHER 3D primitive equation model is implemented with three different resolutions: a low resolution model (1/4^o) covering the whole Mediterranean Sea, an intermediate resolution model (1/20^o) of the Liguro-Provençal basin and a high resolution model (1/60^o) simulating the fine mesoscale structures in the Ligurian Sea. Boundary conditions and the averaged fields (feedback) are exchanged between two successive nesting levels. The model of the Ligurian Sea is also coupled with the assimilation package SESAM. It allows to assimilate satellite data and in situ observations using the local adaptative SEEK (Singular Evolutive Extended Kalman) filter. Instead of evolving the error space by the numerically expensive Lyapunov equation, a simplified algebraic equation depending on the misfit between observation and model forecast is used. Starting from the 1st January 1998 the low and intermediate resolution models are spun up for 18 months. The initial conditions for the Ligurian Sea are interpolated from the intermediate resolution model. The three models are then integrated until August 1999. During this period AVHRR Sea Surface Temperature of the Ligurian Sea is assimilated. The results are validated by using CTD and XBT profiles of the SIRENA cruise from the SACLANT Center. The overall objective of this study is pre-operational. It should help to identify limitations and weaknesses of forecasting methods and to suggest improvements of existing operational models.

Metaphor and hyperassociativity: the imagination mechanisms behind emotion assimilation in sleep and dreaming.

PubMed

Malinowski, Josie E; Horton, Caroline L

2015-01-01

In this paper we propose an emotion assimilation function of sleep and dreaming. We offer explanations both for the mechanisms by which waking-life memories are initially selected for processing during sleep, and for the mechanisms by which those memories are subsequently transformed during sleep. We propose that emotions act as a marker for information to be selectively processed during sleep, including consolidation into long term memory structures and integration into pre-existing memory networks; that dreaming reflects these emotion assimilation processes; and that the associations between memory fragments activated during sleep give rise to measureable elements of dream metaphor and hyperassociativity. The latter are a direct reflection, and the phenomenological experience, of emotional memory assimilation processes occurring during sleep. While many theories previously have posited a role for emotion processing and/or emotional memory consolidation during sleep and dreaming, sleep theories often do not take enough account of important dream science data, yet dream research, when conducted systematically and under ideal conditions, can greatly enhance theorizing around the functions of sleep. Similarly, dream theories often fail to consider the implications of sleep-dependent memory research, which can augment our understanding of dream functioning. Here, we offer a synthesized view, taking detailed account of both sleep and dream data and theories. We draw on extensive literature from sleep and dream experiments and theories, including often-overlooked data from dream science which we believe reflects sleep phenomenology, to bring together important ideas and findings from both domains.

[Revision of the primary care version of the ICD-10. Mental disorders].

PubMed

Varela-González, O; López-Ibor, J J

2007-01-01

Although the difficulty of applying psychiatric classifications to primary care has been widely criticized, there have been few investigations up to now to define and systematize the real demands in regards to these nosological systems. Recently, the revised version of the Mental and Behavior Disorders Chapter of the ICD 10 has been published. The new tool is the result of an elaboration process mainly developed by a group of 971 primary care physicians coordinated by 55 psychiatrists. The project was organized into three phases: a) evaluation of the current version and collection of proposals for change; b) definition of objectives for an optimized version; and c) writing a proposal of revised text. The result is a text that is more assimilable to a diagnostic and therapeutic guide than a mere coding system, more adapted to the role that the primary care physician can play in each disorder, more up-dated (especially in the treatment section) and more specific in many aspects.

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.

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

Glaser, D.; Connolly, J.; Berghoffen, A.

The resident bald eagles of the lower Columbia River have lower productivity and higher contaminant levels than other bald eagles of the Pacific Northwest. The primary population stressors are believed to be habitat loss, human disturbance, p,p{prime}DDE, PCBs, dioxins and furans. The primary effect of habitat loss is to reduce the carrying capacity of the region for nesting sites, and the primary effects of human disturbance and contamination by organic compounds are to reduce productivity. The purpose of this study was to quantitatively evaluate the effects of all of, these potential stressors on the bald eagle population dynamics. A modelmore » of the population dynamics was developed. The model structure includes a physiologically-based toxicokinetic (PBTK) submodel to estimate the degree of contamination, which is linked via a toxicology submodel to a population dynamics submodel. The PBTK submodel is time-variable, incorporating species-specific bioenergetics, as well as contaminant assimilation and excretion rates for each compound of interest. Calculated body burdens and egg concentrations for each compound account for spatial and temporal variations in feeding habits and prey contaminant levels. The population submodel includes fecundity and survival information, as well as a limit to the number of breeding pairs (carrying capacity) and a population of non-breeding subadults and adults (floaters). Model simulations are performed in a Monte Carlo framework. Results include estimates of the persistence, resistance and resilience of the population: the probability of extinction, the relationship between magnitude of stress and change in population size, and the time course of recovery of a population following a reduction in stress.« less

Reducing the uncertainty of parameters controlling seasonal carbon and water fluxes in Chinese forests and its implication for simulated climate sensitivities

NASA Astrophysics Data System (ADS)

Li, Yue; Yang, Hui; Wang, Tao; MacBean, Natasha; Bacour, Cédric; Ciais, Philippe; Zhang, Yiping; Zhou, Guangsheng; Piao, Shilong

2017-08-01

Reducing parameter uncertainty of process-based terrestrial ecosystem models (TEMs) is one of the primary targets for accurately estimating carbon budgets and predicting ecosystem responses to climate change. However, parameters in TEMs are rarely constrained by observations from Chinese forest ecosystems, which are important carbon sink over the northern hemispheric land. In this study, eddy covariance data from six forest sites in China are used to optimize parameters of the ORganizing Carbon and Hydrology In Dynamics EcosystEms TEM. The model-data assimilation through parameter optimization largely reduces the prior model errors and improves the simulated seasonal cycle and summer diurnal cycle of net ecosystem exchange, latent heat fluxes, and gross primary production and ecosystem respiration. Climate change experiments based on the optimized model are deployed to indicate that forest net primary production (NPP) is suppressed in response to warming in the southern China but stimulated in the northeastern China. Altered precipitation has an asymmetric impact on forest NPP at sites in water-limited regions, with the optimization-induced reduction in response of NPP to precipitation decline being as large as 61% at a deciduous broadleaf forest site. We find that seasonal optimization alters forest carbon cycle responses to environmental change, with the parameter optimization consistently reducing the simulated positive response of heterotrophic respiration to warming. Evaluations from independent observations suggest that improving model structure still matters most for long-term carbon stock and its changes, in particular, nutrient- and age-related changes of photosynthetic rates, carbon allocation, and tree mortality.

Tracing Carbon Flow Through Food Webs on Isolated Coral Reefs in the Central Pacific Ocean Using a Compound-Specific Stable Isotope Approach

NASA Astrophysics Data System (ADS)

Thorrold, S.; McMahon, K.; Braun, C.; Berumen, M. L.; Houghton, L. A.

2016-02-01

Coral reefs support spectacularly productive and diverse communities in tropical and sub-tropical waters throughout the world's oceans. Debate continues, however, on the degree to which reef biomass is supported by new water column or benthic primary production and recycled detrital carbon. We coupled analyses of stable carbon isotopes in essential amino acids with Bayesian mixing models to quantify carbon flow from pelagic primary producers, benthic macroalgae and autotrophic symbionts in corals, along with detrital carbon, to coral reef fishes across several feeding guilds and trophic positions, including apex predators (gray reef and black tip reef sharks), on reefs in the Phoenix Islands Protected Area. Excellent separation in multivariate isotope space among end-members at the base of the food web allowed us to quantify the relative proportion of carbon produced by each of the end-members that is assimilated by focal reef fish species. Low local human impacts on the study reefs provided the opportunity to examine carbon fluxs in fully functioning reef food webs, thereby providing an important baseline for examingn human impacts in food webs on stressed reefs in more populated regions in the tropics. Moreover the study reefs are located along a significant gradient in dissolved N concentrations, allowing us to test if end-member proportions vary as a function of pelagic primary productivity levels. Our work provides insights into the roles that diverse carbon sources may play in the structure, function and resilience of coral reef ecosystems.

Identification of 2-keto-3-deoxy-d-Gluconate Kinase and 2-keto-3-deoxy-d-Phosphogluconate Aldolase in an Alginate-Assimilating Bacterium, Flavobacterium sp. Strain UMI-01

PubMed Central

Nishiyama, Ryuji; Inoue, Akira; Ojima, Takao

2017-01-01

Recently, we identified an alginate-assimilating gene cluster in the genome of Flavobacterium sp. strain UMI-01, a member of Bacteroidetes. Alginate lyase genes and a 4-deoxy-l-erythro-5-hexoseulose uronic acid (DEH) reductase gene in the cluster have already been characterized; however, 2-keto-3-deoxy-d-gluconate (KDG) kinase and 2-keto-3-deoxy-6-phosphogluconate (KDPG) aldolase genes, i.e., flkin and flald, still remained uncharacterized. The amino acid sequences deduced from flkin and flald showed low identities with those of corresponding enzymes of Saccharophagus degradans 2-40T, a member of Proteobacteria (Kim et al., Process Biochem., 2016). This led us to consider that the DEH-assimilating enzymes of Bacteroidetes species are somewhat deviated from those of Proteobacteria species. Thus, in the present study, we first assessed the characteristics in the primary structures of KDG kinase and KDG aldolase of the strain UMI-01, and then investigated the enzymatic properties of recombinant enzymes, recFlKin and recFlAld, expressed by an Escherichia coli expression system. Multiple-sequence alignment among KDG kinases and KDG aldolases from several Proteobacteria and Bacteroidetes species indicated that the strain UMI-01 enzymes showed considerably low sequence identities (15%–25%) with the Proteobacteria enzymes, while they showed relatively high identities (47%–68%) with the Bacteroidetes enzymes. Phylogenetic analyses for these enzymes indicated the distant relationship between the Proteobacteria enzymes and the Bacteroidetes enzymes, i.e., they formed distinct clusters in the phylogenetic tree. recFlKin and recFlAld produced with the genes flkin and flald, respectively, were confirmed to show KDG kinase and KDPG aldolase activities. Namely, recFlKin produced 1.7 mM KDPG in a reaction mixture containing 2.5 mM KDG and 2.5 mM ATP in a 90-min reaction, while recFlAld produced 1.2 mM pyruvate in the reaction mixture containing 5 mM KDPG at the equilibrium state. An in vitro alginate-metabolizing system constructed from recFlKin, recFlAld, and previously reported alginate lyases and DEH reductase of the strain UMI-01 could convert alginate to pyruvate and glyceraldehyde-3-phosphate with an efficiency of 38%. PMID:28216576

Mantle Circulation Models with variational data assimilation: Inferring past mantle flow and structure from plate motion histories and seismic tomography

NASA Astrophysics Data System (ADS)

Bunge, H.; Hagelberg, C.; Travis, B.

2002-12-01

EarthScope will deliver data on structure and dynamics of continental North America and the underlying mantle on an unprecedented scale. Indeed, the scope of EarthScope makes its mission comparable to the large remote sensing efforts that are transforming the oceanographic and atmospheric sciences today. Arguably the main impact of new solid Earth observing systems is to transform our use of geodynamic models increasingly from conditions that are data poor to an environment that is data rich. Oceanographers and meteorologists already have made substantial progress in adapting to this environment, by developing new approaches of interpreting oceanographic and atmospheric data objectively through data assimilation methods in their models. However, a similarly rigorous theoretical framework for merging EarthScope derived solid Earth data with geodynamic models has yet to be devised. Here we explore the feasibility of data assimilation in mantle convection studies in an attempt to fit global geodynamic model calculations explicitly to tomographic and tectonic constraints. This is an inverse problem not quite unlike the inverse problem of finding optimal seismic velocity structures faced by seismologists. We derive the generalized inverse of mantle convection from a variational approach and present the adjoint equations of mantle flow. The substantial computational burden associated with solutions to the generalized inverse problem of mantle convection is made feasible using a highly efficient finite element approach based on the 3-D spherical fully parallelized mantle dynamics code TERRA, implemented on a cost-effective topical PC-cluster (geowulf) dedicated specifically to large-scale geophysical simulations. This dedicated geophysical modeling computer allows us to investigate global inverse convection problems having a spatial discretization of less than 50 km throughout the mantle. We present a synthetic high-resolution modeling experiment to demonstrate that mid-Cretaceous mantle structure can be inferred accurately from our inverse approach assuming present-day mantle structure is well-known, even if an initial first guess assumption about the mid-Cretaceous mantle involved only a simple 1-D radial temperature profile. We suggest that geodynamic inverse modeling should make it possible to infer a number of flow parameters from observational constraints of the mantle.

Simulation of fruit-set and trophic competition and optimization of yield advantages in six Capsicum cultivars using functional-structural plant modelling.

PubMed

Ma, Y T; Wubs, A M; Mathieu, A; Heuvelink, E; Zhu, J Y; Hu, B G; Cournède, P H; de Reffye, P

2011-04-01

Many indeterminate plants can have wide fluctuations in the pattern of fruit-set and harvest. Fruit-set in these types of plants depends largely on the balance between source (assimilate supply) and sink strength (assimilate demand) within the plant. This study aims to evaluate the ability of functional-structural plant models to simulate different fruit-set patterns among Capsicum cultivars through source-sink relationships. A greenhouse experiment of six Capsicum cultivars characterized with different fruit weight and fruit-set was conducted. Fruit-set patterns and potential fruit sink strength were determined through measurement. Source and sink strength of other organs were determined via the GREENLAB model, with a description of plant organ weight and dimensions according to plant topological structure established from the measured data as inputs. Parameter optimization was determined using a generalized least squares method for the entire growth cycle. Fruit sink strength differed among cultivars. Vegetative sink strength was generally lower for large-fruited cultivars than for small-fruited ones. The larger the size of the fruit, the larger variation there was in fruit-set and fruit yield. Large-fruited cultivars need a higher source-sink ratio for fruit-set, which means higher demand for assimilates. Temporal heterogeneity of fruit-set affected both number and yield of fruit. The simulation study showed that reducing heterogeneity of fruit-set was obtained by different approaches: for example, increasing source strength; decreasing vegetative sink strength, source-sink ratio for fruit-set and flower appearance rate; and harvesting individual fruits earlier before full ripeness. Simulation results showed that, when we increased source strength or decreased vegetative sink strength, fruit-set and fruit weight increased. However, no significant differences were found between large-fruited and small-fruited groups of cultivars regarding the effects of source and vegetative sink strength on fruit-set and fruit weight. When the source-sink ratio at fruit-set decreased, the number of fruit retained on the plant increased competition for assimilates with vegetative organs. Therefore, total plant and vegetative dry weights decreased, especially for large-fruited cultivars. Optimization study showed that temporal heterogeneity of fruit-set and ripening was predicted to be reduced when fruits were harvested earlier. Furthermore, there was a 20 % increase in the number of extra fruit set.

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.

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)

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.

Isotopic evidence indicates saprotrophy in post-fire Morchella in Oregon and Alaska.

PubMed

Hobbie, Erik A; Rice, Samuel F; Weber, Nancy S; Smith, Jane E

2016-01-01

We assessed the nutritional strategy of true morels (genus Morchella) collected in 2003 and 2004 in Oregon and Alaska, 1 or 2 y after forest fires. We hypothesized that the patterns of stable isotopes (δ(13)C and δ(15)N) in the sporocarps would match those of saprotrophic fungi and that radiocarbon (Δ(14)C) analyses would indicate that Morchella was assimilating old carbon not current-year photosynthate. We compared radiocarbon and stable isotopes in Morchella with values from concurrently collected foliage, the ectomycorrhizal Geopyxis carbonaria (Alb. & Schwein.) Sacc., the saprotrophic Plicaria endocarpoides (Berk.) Rifai, and with literature to determine isotopic values for ectomycorrhizal or saprotrophic fungi. Geopyxis, Plicaria and Morchella, respectively, were 3‰, 5‰ and 6‰ higher in 13C than foliage and 5‰, 7‰ and 7‰ higher in (15)N. High (15)N enrichment in Morchella indicated that recent litter was not the primary source for Morchella nitrogen, and similar (13)C and (15)N enrichments to Plicaria suggest that Morchella assimilates its carbon and nitrogen from the same source pool as this saprotrophic fungus. From radiocarbon analyses Morchella averaged 11 ± 6 y old (n = 19), Plicaria averaged 17 ± 5 y old (n = 3), foliage averaged 1 ± 2 y old (n = 8) and Geopyxis (n = 1) resembled foliage in Δ(14)C. We conclude that morels fruiting in post-fire environments in our study assimilated old carbon and were saprotrophic. © 2016 by The Mycological Society of America.

Sources and Processes Affecting Particulate Matter Pollution over North China

NASA Astrophysics Data System (ADS)

Zhang, L.; Shao, J.; Lu, X.; Zhao, Y.; Gong, S.; Henze, D. K.

2015-12-01

Severe fine particulate matter (PM2.5) pollution over North China has received broad attention worldwide in recent years. Better understanding the sources and processes controlling pollution over this region is of great importance with urgent implications for air quality policy. We will present a four-dimensional variational (4D-Var) data assimilation system using the GEOS-Chem chemical transport model and its adjoint model at 0.25° × 0.3125° horizontal resolution, and apply it to analyze the factors affecting PM2.5 concentrations over North China. Hourly surface observations of PM2.5 and sulfur dioxide (SO2) from the China National Environmental Monitoring Center (CNEMC) can be assimilated into the model to evaluate and constrain aerosol (primary and precursors) emissions. Application of the data assimilation system to the APEC period (the Asia-Pacific Economic Cooperation summit; 5-11 November 2014) shows that 46% of the PM2.5 pollution reduction during APEC ("The APEC Blue") can be attributed to meteorology conditions and the rest 54% to emission reductions due to strict emission controls. Ammonia emissions are shown to significantly contribute to PM2.5 over North China in the fall. By converting sulfuric acid and nitric acid to longer-lived ammonium sulfate and ammonium nitrate aerosols, ammonia plays an important role in promoting their regional transport influences. We will also discuss the pathways and mechanisms of external long-range transport influences to the PM2.5 pollution over North China.

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 Incorporation and Initialization of Cloud Water/ice in AN Operational Forecast Model

NASA Astrophysics Data System (ADS)

Zhao, Qingyun

Quantitative precipitation forecasts have been one of the weakest aspects of numerical weather prediction models. Theoretical studies show that the errors in precipitation calculation can arise from three sources: errors in the large-scale forecasts of primary variables, errors in the crude treatment of condensation/evaporation and precipitation processes, and errors in the model initial conditions. A new precipitation parameterization scheme has been developed to investigate the forecast value of improved precipitation physics via the introduction of cloud water and cloud ice into a numerical prediction model. The main feature of this scheme is the explicit calculation of cloud water and cloud ice in both the convective and stratiform precipitation parameterization. This scheme has been applied to the eta model at the National Meteorological Center. Four extensive tests have been performed. The statistical results showed a significant improvement in the model precipitation forecasts. Diagnostic studies suggest that the inclusion of cloud ice is important in transferring water vapor to precipitation and in the enhancement of latent heat release; the latter subsequently affects the vertical motion field significantly. Since three-dimensional cloud data is absent from the analysis/assimilation system for most numerical models, a method has been proposed to incorporate observed precipitation and nephanalysis data into the data assimilation system to obtain the initial cloud field for the eta model. In this scheme, the initial moisture and vertical motion fields are also improved at the same time as cloud initialization. The physical initialization is performed in a dynamical initialization framework that uses the Newtonian dynamical relaxation method to nudge the model's wind and mass fields toward analyses during a 12-hour data assimilation period. Results from a case study showed that a realistic cloud field was produced by this method at the end of the data assimilation period. Precipitation forecasts have been significantly improved as a result of the improved initial cloud, moisture and vertical motion fields.

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.

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.

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.

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.

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.

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.

Initialization, Prediction and Diagnosis of the Rapid Intensification of Tropical Cyclones using the Australian Community Climate and Earth System Simulator, ACCESS

DTIC Science & Technology

2012-10-12

structure on the evolving storm behaviour. 13 7. Large scale influences on Rapid Intensification and Extratropical Transition: RI and ET...assimilation techniques to better initialize and validate TC structures (including the intense inner core and storm asymmetries) consistent with the large...Without vortex specification, initial conditions usually contain a weak and misplaced circulation. Based on estimates of central pressure and storm size

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.

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.

Demonstration of Both a Photosynthetic and a Nonphotosynthetic CO(2) Requirement for NH(4) Assimilation in the Green Alga Selenastrum minutum.

PubMed

Amory, A M; Vanlerberghe, G C; Turpin, D H

1991-01-01

Nitrogen-limited and nitrogen-sufficient cell cultures of Selenastrum minutum (Naeg.) Collins (Chlorophyta) were used to investigate the dependence of NH(4) (+) assimilation on exogenous CO(2). N-sufficient cells were only able to assimilate NH(4) (+) maximally in the presence of CO(2) and light. Inhibition of photosynthesis with 3-(3,4-dichlorophenyl)-1,1-dimethylurea, diuron also inhibited NH(4) (+) assimilation. These results indicate that NH(4) (+) assimilation by N-sufficient cells exhibited a strict requirement for photosynthetic CO(2) fixation. N-limited cells assimilated NH(4) (+) both in the dark and in the light in the presence of 3-(3,4-dichlorophenyl)-1,1-dimethylurea, diuron, indicating that photosynthetic CO(2) fixation was not required for NH(4) (+) assimilation. Using CO(2) removal techniques reported previously in the literature, we were unable to demonstrate CO(2)-dependent NH(4) (+) assimilation in N-limited cells. However, employing more stringent CO(2) removal techniques we were able to show a CO(2) dependence of NH(4) (+) assimilation in both the light and dark, which was independent of photosynthesis. The results indicate two independent CO(2) requirements for NH(4) (+) assimilation. The first is as a substrate for photosynthetic CO(2) fixation, whereas the second is a nonphoto-synthetic requirement, presumably as a substrate for the anaplerotic reaction catalyzed by phosphoenolpyruvate carboxylase.

Demonstration of Both a Photosynthetic and a Nonphotosynthetic CO2 Requirement for NH4+ Assimilation in the Green Alga Selenastrum minutum1

PubMed Central

Amory, Alan M.; Vanlerberghe, Greg C.; Turpin, David H.

1991-01-01

Nitrogen-limited and nitrogen-sufficient cell cultures of Selenastrum minutum (Naeg.) Collins (Chlorophyta) were used to investigate the dependence of NH4+ assimilation on exogenous CO2. N-sufficient cells were only able to assimilate NH4+ maximally in the presence of CO2 and light. Inhibition of photosynthesis with 3-(3,4-dichlorophenyl)-1,1-dimethylurea, diuron also inhibited NH4+ assimilation. These results indicate that NH4+ assimilation by N-sufficient cells exhibited a strict requirement for photosynthetic CO2 fixation. N-limited cells assimilated NH4+ both in the dark and in the light in the presence of 3-(3,4-dichlorophenyl)-1,1-dimethylurea, diuron, indicating that photosynthetic CO2 fixation was not required for NH4+ assimilation. Using CO2 removal techniques reported previously in the literature, we were unable to demonstrate CO2-dependent NH4+ assimilation in N-limited cells. However, employing more stringent CO2 removal techniques we were able to show a CO2 dependence of NH4+ assimilation in both the light and dark, which was independent of photosynthesis. The results indicate two independent CO2 requirements for NH4+ assimilation. The first is as a substrate for photosynthetic CO2 fixation, whereas the second is a nonphoto-synthetic requirement, presumably as a substrate for the anaplerotic reaction catalyzed by phosphoenolpyruvate carboxylase. PMID:16667950

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.

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.

Tracing carbon flow through coral reef food webs using a compound-specific stable isotope approach.

PubMed

McMahon, Kelton W; Thorrold, Simon R; Houghton, Leah A; Berumen, Michael L

2016-03-01

Coral reefs support spectacularly productive and diverse communities in tropical and sub-tropical waters throughout the world's oceans. Debate continues, however, on the degree to which reef biomass is supported by new water column production, benthic primary production, and recycled detrital carbon (C). We coupled compound-specific stable C isotope ratio (δ(13)C) analyses with Bayesian mixing models to quantify C flow from primary producers to coral reef fishes across multiple feeding guilds and trophic positions in the Red Sea. Analyses of reef fishes with putative diets composed primarily of zooplankton (Amblyglyphidodon indicus), benthic macroalgae (Stegastes nigricans), reef-associated detritus (Ctenochaetus striatus), and coral tissue (Chaetodon trifascialis) confirmed that δ(13)C values of essential amino acids from all baseline C sources were both isotopically diagnostic and accurately recorded in consumer tissues. While all four source end-members contributed to the production of coral reef fishes in our study, a single-source end-member often dominated dietary C assimilation of a given species, even for highly mobile, generalist top predators. Microbially reworked detritus was an important secondary C source for most species. Seascape configuration played an important role in structuring resource utilization patterns. For instance, Lutjanus ehrenbergii showed a significant shift from a benthic macroalgal food web on shelf reefs (71 ± 13 % of dietary C) to a phytoplankton-based food web (72 ± 11 %) on oceanic reefs. Our work provides insights into the roles that diverse C sources play in the structure and function of coral reef ecosystems and illustrates a powerful fingerprinting method to develop and test nutritional frameworks for understanding resource utilization.

Short-term dynamics and partitioning of newly assimilated carbon in the foliage of adult beech and pine are driven by seasonal variations

NASA Astrophysics Data System (ADS)

Desalme, Dorine; Priault, Pierrick; Gérant, Dominique; Dannoura, Masako; Maillard, Pascale; Plain, Caroline; Epron, Daniel

2017-04-01

Carbon (C) allocation is a key process determining C cycling in forest ecosystems. However, the mechanisms underlying the annual patterns of C partitioning in trees, influenced by tree phenology and environmental conditions, are not well identified yet. This study aimed to characterize the short-term dynamics and partitioning of newly assimilated carbon in the foliage of adult European beeches (Fagus sylvatica) and maritime pines (Pinus pinaster) across the seasons. We hypothesized that residence times of recently assimilated C in C compounds should change according to the seasons and that seasonal pattern should differ between deciduous and evergreen tree species, since they have different phenology. 13CO2 pulse-labelling experiments were performed in situ at different dates corresponding to different phenological stages. In beech leaves and pine needles, C contents, isotopic compositions, and 13C dynamics parameters were determined in total organic matter (bulk foliage), in polar fraction (PF, including soluble sugars, amino acids, organic acids) and in starch. For both species and at each phenological stage, 13C amount in bulk foliage decreased following a two-pool exponential model, highlighting the partitioning of newly assimilated C between 'mobile' and 'stable' pools. The relative proportion of the stable pool was maximal in beech leaves in May, when leaves were still growing and could incorporate newly assimilated C in structural C compounds. Young pine needles were still receiving C from previous-year needles in June (two months after budburst) although they are already photosynthesizing, acting as a strong C sink. In summer, short mean residence times of 13C (MRT) in foliage of both tree species reflected the fast respiration and exportation of recent photosynthates to support the whole tree C demand (e.g., supplying perennial organ growth). At the end of the growing season, pre-senescing beech leaves were supplying 13C to perennial organs, whereas overwintering pine needles accumulated labelled PF, probably to acclimate to colder winter temperatures. Results of this experiment revealed that the dynamics and the in-leaf partitioning of newly assimilated C varied seasonally according to the phenology of the two species. In the future, coupling 13C pulse labelling with compound-specific isotope analysis will be promising for tracing the allocation of newly assimilated C to various physiological functions such as growth, export, osmoregulation and defence in trees submitted to global changes.

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…

Improving Global Analysis and Short-Range Forecast Using Rainfall and Moisture Observations Derived from TRMM and SSM/I Passive Microwave Instruments

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.; Kummerow, Christian D.; Simpson, Joanne

2000-01-01

The Global Precipitation Mission, a satellite project under consideration as a follow-on to the Tropical Rainfall Measuring Mission (TRMM) by the National Aeronautics and Space Agency (NASA) in the United States, the National Space Development Agency (NASDA) in Japan, and other international partners, comprises an improved TRMM-like satellite and a constellation of 8 satellites carrying passive microwave radiometers to provide global rainfall measurements at 3-hour intervals. The success of this concept relies on the merits of rainfall estimates derived from passive microwave radiometers. This article offers a proof-of-concept demonstration of the benefits of using, rainfall and total precipitable water (TPW) information derived from such instruments in global data assimilation with observations from the TRMM Microwave Imager (TMI) and 2 Special Sensor Microwave/Imager (SSM/I) instruments. Global analyses that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data analyses contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. We show that assimilating the 6-h averaged TMI and SSM/I surface rainrate and TPW retrievals improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the upper tropospheric moisture in the analysis produced by the Goddard Earth Observing System (GEOS) Data Assimilation System, as verified against radiation measurements by the Clouds and the Earth's Radiant Energy System (CERES) instrument and brightness temperature observations by the TIROS Operational Vertical Sounder (TOVS) instruments. Typically, rainfall assimilation improves clouds and radiation in areas of active convection, as well as the latent heating and large-scale motions in the tropics, while TPW assimilation leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. Ensemble forecasts initialized with analyses that incorporate TMI and SSM/I rainfall and TPW data also yield better short-range predictions of geopotential heights, winds, and precipitation in the tropics. This study offers a compelling illustration of the potential of using rainfall and TPW information derived from passive microwave instruments to significantly improve the quality of 4-dimensional global datasets for climate analysis and weather forecasting applications.

The Roles of the Yellowstone Hotspot and Crustal Assimilation in Generating Pleistocene-Holocene Basalts on the Eastern Snake River Plain

NASA Astrophysics Data System (ADS)

Mintz, H.; Chadwick, J.

2017-12-01

The southwest motion of the North American plate across the Yellowstone hotspot created a chain of age-progressive rhyolitic calderas over the past 16 myr. in southern Idaho, U.S. The focus of Yellowstone activity now resides in northwest Wyoming, but basaltic volcanism has continued in its wake in southern Idaho on the eastern Snake River Plain (ESRP). These younger basaltic lavas are not age progressive and have buried the Yellowstone rhyolites on the ESRP. The ultimate source of the basalts is commonly ascribed to the passage or presence of the hotspot. However, the mechanisms involved, and the relative roles of the hotspot, other mantle sources, and the North American crust in generating the ESRP basalts remain unclear and have been the subject of recent geochemical and isotopic studies. In this study, the role of crustal assimilation is addressed by analyzing the chemical and isotopic characteristics of some of the youngest Pleistocene-Holocene tholeiitic volcanic fields on the ESRP, which were erupted through varying thicknesses of continental crust. Samples were analyzed from the Hell's Half Acre flow (5,200 years old; all dates Kuntz et al., 1986, 1994), Cerro Grande flow (13,380 years), and Black Butte Crater (a.k.a. Shoshone) flow (10,130 years), which were erupted at distances from between about 200 to 300 km from the current location of the hotspot. The crust of the ESRP thins from northeast to southwest, from about 47 km at the Hells Half Acre flow to 40 km at the Black Butte Crater flow, a thickness difference of about 15%. The apparently similar tectonic and magmatic environments of the three sampled flows suggest the crustal thickness variation may be a primary influence on the magnitude of assimilation and therefore the isotopic characteristics of the lavas. The goal of this work is to constrain the relative role of assimilation and to understand the source(s) of the magmas and the Yellowstone hotspot contribution. Major elements, trace elements, and Pb-Sr-Nd isotopic data for the flows and crustal xenoliths, in conjunction with mixing modeling with MELTS software, constrain potential differences in fractional crystallization, residence times in the crust, and crustal assimilation for the flows.

How to improve an un-alterable model forecast? A sequential data assimilation based error updating approach

NASA Astrophysics Data System (ADS)

Gragne, A. S.; Sharma, A.; Mehrotra, R.; Alfredsen, K. T.

2012-12-01

Accuracy of reservoir inflow forecasts is instrumental for maximizing value of water resources and influences operation of hydropower reservoirs significantly. Improving hourly reservoir inflow forecasts over a 24 hours lead-time is considered with the day-ahead (Elspot) market of the Nordic exchange market in perspectives. The procedure presented comprises of an error model added on top of an un-alterable constant parameter conceptual model, and a sequential data assimilation routine. The structure of the error model was investigated using freely available software for detecting mathematical relationships in a given dataset (EUREQA) and adopted to contain minimum complexity for computational reasons. As new streamflow data become available the extra information manifested in the discrepancies between measurements and conceptual model outputs are extracted and assimilated into the forecasting system recursively using Sequential Monte Carlo technique. Besides improving forecast skills significantly, the probabilistic inflow forecasts provided by the present approach entrains suitable information for reducing uncertainty in decision making processes related to hydropower systems operation. The potential of the current procedure for improving accuracy of inflow forecasts at lead-times unto 24 hours and its reliability in different seasons of the year will be illustrated and discussed thoroughly.

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

Assimilation of qualitative hydrological information in water-related risk framework

NASA Astrophysics Data System (ADS)

Mazzoleni, Maurizio; Alfonso, Leonardo; Solomatine, Dimitri

2013-04-01

In recent years water-related risks are increasing worldwide. In particular, floods have been one of the most damaging natural disasters in Europe, in terms of economic losses. Non-structural measures such as flood risk mapping are generally used to reduce the impact of flood in important area. The increasing data availability makes it possible to develop new models which can be used to assimilate different kinds of information and reduce the uncertainty of the state of a basin. The aim of this work is to propose a methodology to assimilate uncertain, qualitative information within hydrological models in order to improve the evaluation of catchment responses. Qualitative information is defined here as the one that can be interpreted as and assimilated into a hydrological model as a fuzzy value, for instance those coming from text messages or citizen's pictures. The methodology is applied in the Brue catchment, located in the South West of England, having a drainage area of 135 km2, average annual rainfall of 867 mm and average discharge of 1.92 m3/s at Lovington considering the period among 1961 and 1990. In order to estimate the response of the catchment to a flood event with given intensity, a conceptual distributed hydrological model was implemented. First, the basin was divided in different sub-basins, then, the hydrograph at the outlet section was estimated using a Nash cascade model and the propagation of the flood wave was carried out considering the lag time in the other each sub-basins. The assimilation of the qualitative information was carried out using different techniques. The results of this work show how the spatial location and uncertainty of the qualitative information can affect the flow hydrograph in the outlet section and the consequent flood extent in the downstream area. This study is part of the FP7 European Project WeSenseIt.

Stratospheric water vapor and ozone evaluation in reanalyses as part of the SPARC Reanalysis Intercomparison Project (S-RIP)

NASA Astrophysics Data System (ADS)

Davis, S. M.; Hegglin, M. I.; Fujiwara, M.; Manney, G. L.; Dragani, R.; Nash, E.; Tegtmeier, S.; Kobayashi, C.; Harada, Y.; Long, C. S.; Wargan, K.; Rosenlof, K. H.

2017-12-01

Reanalyses are widely used to understand atmospheric processes and past variability, and are often used to stand in as "observations" for comparisons with climate model output. Because of the central role of water vapor (WV) and ozone (O3) in climate change, it is important to understand how accurately and consistently these species are represented in existing global reanalyses. Here we present the results of WV and O3 intercomparisons that have been performed as part of the SPARC (Stratosphere-troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The comparisons cover a range of timescales and evaluate both inter-reanalysis and observation-reanalysis differences. The assimilation of total column ozone (TCO) observations in newer reanalyses results in realistic representations of TCO in reanalyses except when data coverage is lacking, such as during polar night. The vertical distribution of ozone is also relatively well represented in the stratosphere in reanalyses, particularly given the relatively weak constraints on ozone vertical structure provided by most assimilated observations and the simplistic representations of ozone photochemical processes in most of the reanalysis forecast models. For times when vertically resolved observations are not assimilated, biases in the vertical distribution of ozone are found in the upper troposphere and lower stratosphere in all reanalyses. In contrast to O3, reanalysis stratospheric WV fields are not directly constrained by assimilated data. Observations of atmospheric humidity are typically used only in the troposphere, below a specified vertical level at or near the tropopause. The fidelity of reanalysis stratospheric WV products is therefore dependent on the reanalyses' representation of processes that influence stratospheric WV, such as tropical tropopause layer temperatures and methane oxidation. The lack of assimilated observations and known deficiencies in the representation of stratospheric transport in reanalyses result in much poorer agreement amongst observational and reanalysis estimates of stratospheric WV. Hence, stratospheric WV products from the current generation of reanalyses should generally not be used in scientific studies.

Estimating the Uncertain Mathematical Structure of Hydrological Model via Bayesian Data Assimilation

NASA Astrophysics Data System (ADS)

Bulygina, N.; Gupta, H.; O'Donell, G.; Wheater, H.

2008-12-01

The structure of hydrological model at macro scale (e.g. watershed) is inherently uncertain due to many factors, including the lack of a robust hydrological theory at the macro scale. In this work, we assume that a suitable conceptual model for the hydrologic system has already been determined - i.e., the system boundaries have been specified, the important state variables and input and output fluxes to be included have been selected, and the major hydrological processes and geometries of their interconnections have been identified. The structural identification problem then is to specify the mathematical form of the relationships between the inputs, state variables and outputs, so that a computational model can be constructed for making simulations and/or predictions of system input-state-output behaviour. We show how Bayesian data assimilation can be used to merge both prior beliefs in the form of pre-assumed model equations with information derived from the data to construct a posterior model. The approach, entitled Bayesian Estimation of Structure (BESt), is used to estimate a hydrological model for a small basin in England, at hourly time scales, conditioned on the assumption of 3-dimensional state - soil moisture storage, fast and slow flow stores - conceptual model structure. Inputs to the system are precipitation and potential evapotranspiration, and outputs are actual evapotranspiration and streamflow discharge. Results show the difference between prior and posterior mathematical structures, as well as provide prediction confidence intervals that reflect three types of uncertainty: due to initial conditions, due to input and due to mathematical structure.

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.

Alterations in leaf nitrogen metabolism indicated the structural changes of subtropical forest by canopy addition of nitrogen.

PubMed

Liu, Nan; Wang, Jiaxin; Guo, Qinfeng; Wu, Shuhua; Rao, Xingquan; Cai, Xi'an; Lin, Zhifang

2018-09-30

Globally, nitrogen deposition increment has caused forest structural changes due to imbalanced plant nitrogen metabolism and subsequent carbon assimilation. Here, a 2 consecutive-year experiment was conducted to reveal the effects of canopy addition of nitrogen (CAN) on nitrogen absorption, assimilation, and allocation in leaves of three subtropical forest woody species (Castanea henryi, Ardisia quinquegona, and Blastus cochinchinensis). We hypothesized that CAN altered leaf nitrogen absorption, assimilation and partitioning of different plants in different ways in subtropical forest. It shows that CAN increased maximum photosynthetic rate (A max ), photosynthetic nitrogen use efficiency (PNUE), and metabolic protein content of the two understory species A. quinquegona and B. cochinchinensis. By contrary, for the overstory species, C. henryi, A max , PNUE, and metabolic protein content were significantly reduced in response to CAN. We found that changes in leaf nitrogen metabolism were mainly due to the differences in enzyme (e.g. Ribulose-1,5-bisphosphate carboxylase, nitrate reductase, nitrite reductase and glutamine synthetase) activities under CAN treatment. Our results indicated that C. henryi may be more susceptible to CAN treatment, and both A. quinquegona and B. cochinchinensis could better adapt to CAN treatment but in different ways. Our findings may partially explain the ongoing degradation of subtropical forest into a community dominated by small trees and shrubs in recent decades. It is possible that persistent high levels of atmospheric nitrogen deposition will lead to the steady replacement of dominant woody species in this subtropical forest. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The Online Classroom: A Self-Actualising Theme Park or a Trial by Multimedia?

ERIC Educational Resources Information Center

Baskin, Colin; Anderson, Neil

2003-01-01

This paper begins with three very "public" examples of how education providers across Australia are attempting to assimilate new teaching and learning technologies into existing teaching and learning structures. The transition, as predicted, is not altogether smooth. The dual concepts of the online classrooms as a "self-actualising…

Unstructured vs. Structured Use of Laptops in Higher Education

ERIC Educational Resources Information Center

Kay, Robin H.; Lauricella, Sharon

2011-01-01

A majority of today's higher education students have been nurtured on a steady diet of technology and Internet access, leading to the increased presence of laptops in higher education classrooms. However, many instructors are unsure whether or how to assimilate this technology into their lessons. The purpose of the following study was to examine…

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Temperature and carbon assimilation regulate the chlorosome biogenesis in green sulfur bacteria.

PubMed

Tang, Joseph Kuo-Hsiang; Saikin, Semion K; Pingali, Sai Venkatesh; Enriquez, Miriam M; Huh, Joonsuk; Frank, Harry A; Urban, Volker S; Aspuru-Guzik, Alán

2013-09-17

Green photosynthetic bacteria adjust the structure and functionality of the chlorosome-the light-absorbing antenna complex-in response to environmental stress factors. The chlorosome is a natural self-assembled aggregate of bacteriochlorophyll (BChl) molecules. In this study, we report the regulation of the biogenesis of the Chlorobaculum tepidum chlorosome by carbon assimilation in conjunction with temperature changes. Our studies indicate that the carbon source and thermal stress culture of C. tepidum grows slower and incorporates fewer BChl c in the chlorosome. Compared with the chlorosome from other cultural conditions we investigated, the chlorosome from the carbon source and thermal stress culture displays (a) smaller cross-sectional radius and overall size, (b) simplified BChl c homologs with smaller side chains, (c) blue-shifted Qy absorption maxima, and (d) a sigmoid-shaped circular dichroism spectra. Using a theoretical model, we analyze how the observed spectral modifications can be associated with structural changes of BChl aggregates inside the chlorosome. Our report suggests a mechanism of metabolic regulation for chlorosome biogenesis. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Assimilation and Individual Differences in Emotion: The Dynamics of Anger and Approach Motivation.

PubMed

Lechuga, Julia; Fernandez, Norma P

2011-03-01

Individuals who cross cultural boundaries face many challenges when trying to adapt to a receiving culture. Adaptation challenges such as learning to maneuver across societal domains may become increasingly complex if structural level factors such as discrimination are present. Researchers have conceptualized acculturation as a relatively autonomous decision indicating that four acculturation strategies exist: assimilation, separation, integration, and marginalization. Moreover, researchers have also long debated the link between acculturation strategy, adaptation hassles and negative health outcomes. However, models seeking to explain how individual difference and structural level variables may influence each other and subsequently influence acculturation and adaptation are needed. The purpose of this study is to lay the foundation for the conceptualization of such a model. We propose that temperamental predispositions to negative emotionality, anger, and impulsivity may highlight discrimination which in turn may lead to increases in acculturative stress and negative markers of psychosocial well-being. We used SEM to test our hypothesized model. Results supported a modified model. Implications for the measurement of adaptation and interventions are discussed.

Assimilation and Individual Differences in Emotion: The Dynamics of Anger and Approach Motivation

PubMed Central

Lechuga, Julia; Fernandez, Norma P.

2011-01-01

Individuals who cross cultural boundaries face many challenges when trying to adapt to a receiving culture. Adaptation challenges such as learning to maneuver across societal domains may become increasingly complex if structural level factors such as discrimination are present. Researchers have conceptualized acculturation as a relatively autonomous decision indicating that four acculturation strategies exist: assimilation, separation, integration, and marginalization. Moreover, researchers have also long debated the link between acculturation strategy, adaptation hassles and negative health outcomes. However, models seeking to explain how individual difference and structural level variables may influence each other and subsequently influence acculturation and adaptation are needed. The purpose of this study is to lay the foundation for the conceptualization of such a model. We propose that temperamental predispositions to negative emotionality, anger, and impulsivity may highlight discrimination which in turn may lead to increases in acculturative stress and negative markers of psychosocial well-being. We used SEM to test our hypothesized model. Results supported a modified model. Implications for the measurement of adaptation and interventions are discussed. PMID:21625350

Balanced Atmospheric Data Assimilation

NASA Astrophysics Data System (ADS)

Hastermann, Gottfried; Reinhardt, Maria; Klein, Rupert; Reich, Sebastian

2017-04-01

The atmosphere's multi-scale structure poses several major challenges in numerical weather prediction. One of these arises in the context of data assimilation. The large-scale dynamics of the atmosphere are balanced in the sense that acoustic or rapid internal wave oscillations generally come with negligibly small amplitudes. If triggered artificially, however, through inappropriate initialization or by data assimilation, such oscillations can have a detrimental effect on forecast quality as they interact with the moist aerothermodynamics of the atmosphere. In the setting of sequential Bayesian data assimilation, we therefore investigate two different strategies to reduce these artificial oscillations induced by the analysis step. On the one hand, we develop a new modification for a local ensemble transform Kalman filter, which penalizes imbalances via a minimization problem. On the other hand, we modify the first steps of the subsequent forecast to push the ensemble members back to the slow evolution. We therefore propose the use of certain asymptotically consistent integrators that can blend between the balanced and the unbalanced evolution model seamlessly. In our work, we furthermore present numerical results and performance of the proposed methods for two nonlinear ordinary differential equation models, where we can identify the different scales clearly. The first one is a Lorenz 96 model coupled with a wave equation. In this case the balance relation is linear and the imbalances are caused only by the localization of the filter. The second one is the elastic double pendulum where the balance relation itself is already highly nonlinear. In both cases the methods perform very well and could significantly reduce the imbalances and therefore increase the forecast quality of the slow variables.

EcoPAD, an interactive platform for near real-time ecological forecasting by assimilating data into model

NASA Astrophysics Data System (ADS)

MA, S.; Huang, Y.; Stacy, M.; Jiang, J.; Sundi, N.; Ricciuto, D. M.; Hanson, P. J.; Luo, Y.; Saruta, V.

2017-12-01

Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our study presents a smart system - Ecological Platform for Assimilation of Data (EcoPAD) - which streamlines web request-response, data management, model execution, result storage and visualization. EcoPAD allows users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, (v) conduct ecological forecasting, and (vi) detect ecosystem acclimation to climate change. One of the key innovations of the web-based EcoPAD is the automated near- or real-time forecasting of ecosystem dynamics with uncertainty fully quantified. The user friendly webpage enables non-modelers to explore their data for simulation and data assimilation. As a case study, we applied EcoPAD to the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment project in the northern peatland, assimilated multiple data streams into a process based ecosystem model, enhanced timely feedback between modelers and experimenters, ultimately improved ecosystem forecasting and made better use of current knowledge. Built in a framework with flexible API, EcoPAD is easily portable and will benefit scientific communities, policy makers as well as the general public.

Provenance effect on carbon assimilation, photochemistry and leaf morphology in Mediterranean Cistus species under chilling stress.

PubMed

Puglielli, G; Cuevas Román, F J; Catoni, R; Moreno Rojas, J M; Gratani, L; Varone, L

2017-07-01

The potential resilience of shrub species to environmental change deserves attention in those areas threatened by climate change, such as the Mediterranean Basin. We asked if leaves produced under different climate conditions through the winter season to spring can highlight the leaf traits involved in determining potential resilience of three Cistus spp. to changing environmental conditions and to what extent intraspecific differences affect such a response. We analysed carbon assimilation, maximum quantum efficiency of PSII photochemistry (F v /F m ) and leaf morphological control of the photosynthetic process in leaves formed through the winter season into spring in C. creticus subsp. eriocephalus (CE), C. salvifolius (CS) and C. monspeliensis (CM) grown from seed of different provenances under common garden conditions. Intraspecific differences were found in F v /F m for CE and CS. Carbon assimilation-related parameters were not affected by provenance. Moreover, our analysis highlighted that the functional relationships investigated can follow seasonal changes and revealed patterns originating from species-specific differences in LMA arising during the favourable period. Cistus spp. have great ability to modify the structure and function of their leaves in the mid-term in order to cope with changing environmental conditions. The F v /F m response to chilling reveals that susceptibility to photoinhibition is a trait under selection in Cistus species. Concerning carbon assimilation, differing ability to control stomatal opening was highlighted between species. Moreover, seasonal changes of the functional relationships investigated can have predictable consequences on species leaf turnover strategies. © 2017 German Botanical Society and The Royal Botanical Society of the Netherlands.

Chemical and structural characterization of copper adsorbed on mosses (Bryophyta).

PubMed

González, Aridane G; Jimenez-Villacorta, Felix; Beike, Anna K; Reski, Ralf; Adamo, Paola; Pokrovsky, Oleg S

2016-05-05

The adsorption of copper on passive biomonitors (devitalized mosses Hypnum sp., Sphagnum denticulatum, Pseudoscleropodium purum and Brachythecium rutabulum) was studied under different experimental conditions such as a function of pH and Cu concentration in solution. Cu assimilation by living Physcomitrella patents was also investigated. Molecular structure of surface adsorbed and incorporated Cu was studied by X-ray Absorption Spectroscopy (XAS). Devitalized mosses exhibited the universal adsorption pattern of Cu as a function of pH, with a total binding sites number 0.05-0.06 mmolg(dry)(-1) and a maximal adsorption capacity of 0.93-1.25 mmolg(dry)(-1) for these devitalized species. The Extended X-ray Absorption Fine Structure (EXAFS) fit of the first neighbor demonstrated that for all studied mosses there are ∼4.5 O/N atoms around Cu at ∼1.95 Å likely in a pseudo-square geometry. The X-ray Absorption Near Edge Structure (XANES) analysis demonstrated that Cu(II)-cellulose (representing carboxylate groups) and Cu(II)-phosphate are the main moss surface binding moieties, and the percentage of these sites varies as a function of solution pH. P. patens exposed during one month to Cu(2+) yielded ∼20% of Cu(I) in the form of Cu-S(CN) complexes, suggesting metabolically-controlled reduction of adsorbed and assimilated Cu(2+). Copyright © 2016 Elsevier B.V. All rights reserved.

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.

From teosinte to maize: the catastrophic sexual transmutation.

PubMed

Iltis, H H

1983-11-25

An alternative to the theory that the ear of maize (Zea mays ssp. mays) evolved from a slender female ear of a Mexican annual teosinte holds that it was derived from the central spike of a male teosinte inflorescence (tassel) which terminates the primary lateral branches. This alternative hypothesis is more consistent with morphology and explains the anomalous lack of significant genetic and biochemical differences between these taxa. Maize, the only cereal with unisexual inflorescences, evolved through a sudden epigenetic sexual transmutation involving condensation of primary branches, which brought their tassels into the zone of female expression, leading to strong apical dominance and a catastrophic shift in nutrient allocation. Initially, this quantum change may have involved no new mutations, but rather genetic assimilation under human selection of an abnormality, perhaps environmentally triggered.

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.

Seasonal trends in photosynthesis and electron transport during the Mediterranean summer drought in leaves of deciduous oaks.

PubMed

Osuna, Jessica L; Baldocchi, Dennis D; Kobayashi, Hideki; Dawson, Todd E

2015-05-01

The California Mediterranean savanna has harsh summer conditions with minimal soil moisture, high temperature, high incoming solar radiation and little or no precipitation. Deciduous blue oaks, Quercus douglasii Hook. and Arn., are winter-deciduous obligate phreatophytes, transpiring mostly groundwater throughout the summer drought. The objective of this work is to fully characterize the seasonal trends of photosynthesis in blue oaks as well as the mechanistic relationships between leaf structure and function. We estimate radiative load of the leaves via the FLiES model and perform in situ measurements of leaf water potential, leaf nitrogen content, an index of chlorophyll content (SPAD readings), photosynthetic and electron transport capacity, and instantaneous rates of CO2 assimilation and electron transport. We measured multiple trees over 3 years providing data from a range of conditions. Our study included one individual that demonstrated strong drought stress as indicated by changes in SPAD readings, leaf nitrogen and all measures of leaf functioning. In the year following severe environmental stress, one individual altered foliation patterns on the crown but did not die. In all other individuals, we found that net carbon assimilation and photosynthetic capacity decreased during the summer drought. SPAD values, electron transport rate (ETR) and quantum yield of photosystem II (PSII) did not show a strong decrease during the summer drought. In most individuals, PSII activity and SPAD readings did not indicate leaf structural or functional damage throughout the season. While net carbon assimilation was tightly coupled to stomatal conductance, the coupling was not as tight with ETR possibly due to contributions from photorespiration or other protective processes. Our work demonstrates that the blue oaks avoid structural damage by maintaining the capacity to convert and dissipate incoming solar radiation during the hot summer drought and are effective at fixing carbon by maximizing rates during the mild spring conditions. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Diagnostic Comparison of Meteorological Analyses during the 2002 Antarctic Winter

NASA Technical Reports Server (NTRS)

Manney, Gloria L.; Allen, Douglas R.; Kruger, Kirstin; Naujokat, Barbara; Santee, Michelle L.; Sabutis, Joseph L.; Pawson, Steven; Swinbank, Richard; Randall, Cora E.; Simmons, Adrian J.;

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

Parallelization of the Physical-Space Statistical Analysis System (PSAS)

NASA Technical Reports Server (NTRS)

Larson, J. W.; Guo, J.; Lyster, P. M.

1999-01-01

Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational reproducibility is well known in the parallel computing community. It is a requirement that the parallel code perform calculations in a fashion that will yield identical results on different configurations of processing elements on the same platform. In some cases this problem can be solved by sacrificing performance. Meeting this requirement and still achieving high performance is very difficult. Topics to be discussed include: current PSAS design and parallelization strategy; reproducibility issues; load balance vs. database memory demands, possible solutions to these problems.

Radar-driven High-resolution Hydrometeorological Forecasts of the 26 September 2007 Venice flash flood

NASA Astrophysics Data System (ADS)

Massimo Rossa, Andrea; Laudanna Del Guerra, Franco; Borga, Marco; Zanon, Francesco; Settin, Tommaso; Leuenberger, Daniel

2010-05-01

Space and time scales of flash floods are such that flash flood forecasting and warning systems depend upon the accurate real-time provision of rainfall information, high-resolution numerical weather prediction (NWP) forecasts and the use of hydrological models. Currently available high-resolution NWP model models can potentially provide warning forecasters information on the future evolution of storms and their internal structure, thereby increasing convective-scale warning lead times. However, it is essential that the model be started with a very accurate representation of on-going convection, which calls for assimilation of high-resolution rainfall data. This study aims to assess the feasibility of using carefully checked radar-derived quantitative precipitation estimates (QPE) for assimilation into NWP and hydrological models. The hydrometeorological modeling chain includes the convection-permitting NWP model COSMO-2 and a hydrologic-hydraulic models built upon the concept of geomorphological transport. Radar rainfall observations are assimilated into the NWP model via the latent heat nudging method. The study is focused on 26 September 2007 extreme flash flood event which impacted the coastal area of north-eastern Italy around Venice. The hydro-meteorological modeling system is implemented over the Dese river, a 90 km2 catchment flowing to the Venice lagoon. The radar rainfall observations are carefully checked for artifacts, including beam attenuation, by means of physics-based correction procedures and comparison with a dense network of raingauges. The impact of the radar QPE in the assimilation cycle of the NWP model is very significant, in that the main individual organized convective systems were successfully introduced into the model state, both in terms of timing and localization. Also, incorrectly localized precipitation in the model reference run without rainfall assimilation was correctly reduced to about the observed levels. On the other hand, the highest rainfall intensities were underestimated by 20% at a scale of 1000 km2, and the local peaks by 50%. The positive impact of the assimilated radar rainfall was carried over into the free forecast for about 2-5 hours, depending on when this forecast was started, and was larger, when the main mesoscale convective system was present in the initial conditions. The improvements of the meteorological model simulations were directly propagated to the river flow simulations, with an extension of the warning lead time up to three hours.

Carbon cycling of European croplands: A framework for the assimilation of optical and microwave Earth observation data

NASA Astrophysics Data System (ADS)

Revill, Andrew; Sus, Oliver; Williams, Mathew

2013-04-01

Croplands are traditionally managed to maximise the production of food, feed, fibre and bioenergy. Advancements in agricultural technologies, together with land-use change, have approximately doubled World grain harvests over the past 50 years. Cropland ecosystems also play a significant role in the global carbon (C) cycle and, through changes to C storage in response to management activities, they can provide opportunities for climate change mitigation. However, quantifying and understanding the cropland C cycle is complex, due to variable environmental drivers, varied management practices and often highly heterogeneous landscapes. Efforts to upscale processes using simulation models must resolve these challenges. Here we show how data assimilation (DA) approaches can link C cycle modelling to Earth observation (EO) and reduce uncertainty in upscaling. We evaluate a framework for the assimilation of leaf area index (LAI) time series, empirically derived from EO optical and radar sensors, for state-updating a model of crop development and C fluxes. Sensors are selected with fine spatial resolutions (20-50 m) to resolve variability across field sizes typically used in European agriculture. Sequential DA is used to improve the canopy development simulation, which is validated by comparing time-series LAI and net ecosystem exchange (NEE) predictions to independent ground measurements and eddy covariance observations at multiple European cereal crop sites. Significant empirical relationships were established between the LAI ground measurements and the optical reflectance and radar backscatter, which allowed for single LAI calibrations being valid for all the cropland sites for each sensor. The DA of all EO LAI estimates results indicated clear adjustments in LAI and an enhanced representation of daily CO2 exchanges, particularly around the time of peak C uptake. Compared to the simulation without DA, the assimilation of all EO LAI estimates improved the predicted at-harvest cumulative NEE for all cropland sites by an average of 69%. The use of radar sensors, being relatively unaffected by cloud cover and sensitive to the structural properties of the crop, significantly improves the analyses when compared to the combined, and individual, use of the optical LAI estimates. When assimilating the radar derived LAI only, the estimated at-harvest cumulative NEE was improved by 79% when compared to the simulation without DA. Future developments would include the spatial upscaling of the existing model framework and the assimilation of additional state variables, such as soil moisture.

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.

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.

Electrical signaling and photosynthesis: can they co-exist together?

PubMed

Pavlovič, Andrej; Mancuso, Stefano

2011-06-01

Mechanical irritation of trigger hairs and subsequent generation of action potentials have significant impact on photosynthesis and respiration in carnivorous Venus flytrap (Dionaea muscipula). Action potential-mediated inhibition of photosynthesis and stimulation of respiration is confined only to the trap and was not recorded in adjacent photosynthetic lamina. We showed that the main primary target of electrical signals on assimilation is in the dark enzymatic reaction of photosynthesis. Without doubt, the electrical signaling is costly, and the possible co-existence of such type of signals and photosynthesis in plant cell is discussed.

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

Hill, Walter R.; Griffiths, Natalie A.

Primary consumers play important roles in the cycling of nutrients in headwater streams, storing assimilated nutrients in growing tissue and recycling them through excretion. Though environmental conditions in most headwater streams and their surrounding terrestrial ecosystems vary considerably over the course of a year, relatively little is known about the effects of seasonality on consumer nutrient recycling these streams. Here, we measured nitrogen accumulated through growth and excreted by the grazing snail Elimia clavaeformis (Pleuroceridae) over the course of 12 months in Walker Branch, identifying close connections between in-stream nitrogen processing and seasonal changes in the surrounding forest.

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.

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

Structure and Dynamics of the Quasi-Biennial Oscillation in MERRA-2.

PubMed

Coy, Lawrence; Wargan, Krzysztof; Molod, Andrea M; McCarty, William R; Pawson, Steven

2016-07-01

The structure, dynamics, and ozone signal of the Quasi-Biennial Oscillation produced by the 35-year NASA MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications) reanalysis are examined based on monthly mean output. Along with the analysis of the QBO in assimilation winds and ozone, the QBO forcings created by assimilated observations, dynamics, parameterized gravity wave drag, and ozone chemistry parameterization are examined and compared with the original MERRA system. Results show that the MERRA-2 reanalysis produces a realistic QBO in the zonal winds, mean meridional circulation, and ozone over the 1980-2015 time period. In particular, the MERRA-2 zonal winds show improved representation of the QBO 50 hPa westerly phase amplitude at Singapore when compared to MERRA. The use of limb ozone observations creates improved vertical structure and realistic downward propagation of the ozone QBO signal during times when the MLS ozone limb observations are available (October 2004 to present). The increased equatorial GWD in MERRA-2 has reduced the zonal wind data analysis contribution compared to MERRA so that the QBO mean meridional circulation can be expected to be more physically forced and therefore more physically consistent. This can be important for applications in which MERRA-2 winds are used to drive transport experiments.

Structure and Dynamics of the Quasi-Biennial Oscillation in MERRA-2

PubMed Central

Coy, Lawrence; Wargan, Krzysztof; Molod, Andrea M.; McCarty, William R.; Pawson, Steven

2018-01-01

The structure, dynamics, and ozone signal of the Quasi-Biennial Oscillation produced by the 35-year NASA MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications) reanalysis are examined based on monthly mean output. Along with the analysis of the QBO in assimilation winds and ozone, the QBO forcings created by assimilated observations, dynamics, parameterized gravity wave drag, and ozone chemistry parameterization are examined and compared with the original MERRA system. Results show that the MERRA-2 reanalysis produces a realistic QBO in the zonal winds, mean meridional circulation, and ozone over the 1980–2015 time period. In particular, the MERRA-2 zonal winds show improved representation of the QBO 50 hPa westerly phase amplitude at Singapore when compared to MERRA. The use of limb ozone observations creates improved vertical structure and realistic downward propagation of the ozone QBO signal during times when the MLS ozone limb observations are available (October 2004 to present). The increased equatorial GWD in MERRA-2 has reduced the zonal wind data analysis contribution compared to MERRA so that the QBO mean meridional circulation can be expected to be more physically forced and therefore more physically consistent. This can be important for applications in which MERRA-2 winds are used to drive transport experiments. PMID:29551854

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.

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.

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.

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.

Improving the Algae Bloom Prediction through the Assimilation of the Remotely Sensed Chlorophyll-A Data in a Generic Ecological Model in the North Sea

NASA Astrophysics Data System (ADS)

El Serafy, Ghada

2010-05-01

Harmful algae can cause damage to co-existing organisms, tourism and farmers. Accurate predictions of algal future composition and abundance as well as when and where algal blooms may occur could help early warning and mitigating. The Generic Ecological Model, GEM, [Blauw et al 2008] is an instrument that can be applied to any water system (fresh, transitional or coastal) to calculate the primary production, chlorophyll-a concentration and phytoplankton species composition. It consists of physical, chemical and ecological model components which are coupled together to build one generic and flexible modeling tool. For the North Sea, the model has been analyzed to assess sensitivity of the simulated chlorophyll-a concentration to a subset of ecologically significant set of factors. The research led to the definition of the most significant set of parameters to the algae blooming process in the North Sea [Salacinska et al 2009]. In order to improve the prediction of the model, the set of parameters and the chlorophyll-a concentration can be further estimated through the use of data assimilation. In this research, the Ensemble Kalman Filter (EnKF) data assimilation technique is used to assimilate the chlorophyll-a data of the North Sea, retrieved from MEdium Resolution Imaging Sensor (MERIS) spectrometer data [Peters et al 2005], in the GEM model. The chlorophyll-a data includes concentrations and error information that enable their use in data assimilation. For the same purpose, the uncertainty of the ecological generic model, GEM has been quantified by means of Monte Carlo approach. Through a study covering the year of 2003, the research demonstrates that both data and model are sufficiently robust for a successful assimilation. The results show that through the assimilation of the satellite data, a better description of the algae bloom has been achieved and an improvement of the capability of the model to predict the algae bloom for the North Sea has been confirmed. Blauw A.N., Los F.J., Bokhorst M., Erftemeijer P.L.A., (2009), GEM: a Generic Ecological Model for estuaries and coastal waters. Journal of Hydrobiologia, Volume 618, Number 1, 175-198. Peters, S.W.M., Eleveld, M. Pasterkamp, R., Woerd, H. van der, Devolder, M., Jans, S., Park, Y., Ruddick, K., Block, T., Brockmann, C., Doerffer, R., Krasemann, H., Röttgers, R., Schönfeld, W., Jørgensen, P.V., Tilstone, G., Martinez-Vicente, V., Moore, G., Sørensen, K., Høkedal, J., Johnsen, T.M., Lømsland, E.R., Aas, E. (2005). Atlas of Chlorophyll-a concentration for the North Sea based on MERIS imagery of 2003. IVM report, Vrije Universiteit Amsterdam, 117 pp. ISBN 90-5192-026-1. Salacinska K., El Serafy G.Y., Blauw A., Los F.J., (2009) Sensitivity analysis of the two dimensional application of the Generic Ecological Model (GEM) to algal bloom prediction in the North Sea, Journal of Ecological Modeling, volume 221, 7, pp 178-190, DOI: 10.1016/j.ecolmodel.2009.10.001

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.

Quantifying fire emissions and associated aerosols species using assimilation of satellite carbon monoxide retrievals.

NASA Astrophysics Data System (ADS)

Barre, J.; Edwards, D. P.; Worden, H. M.

2016-12-01

Wildfires tend to be more intense and hence costly and are predicted to increase in frequency under a warming climate. For example, the recent August 2015 Washington State fires were the largest in the state's history. Also in September and October 2015 very intense fires over Indonesia produced some of the highest concentration of carbon monoxide (CO) ever seen from space. Such larges fires impact not only the local environment but also affects air quality far downwind through the long-range transport of pollutants. Global to continental scale coverage showing the evolution of CO resulting from fire emission is available from satellite observations. Carbon monoxide is the only atmospheric trace gas for which satellite multispectral retrievals have demonstrated reliable independent profile information close to the surface and also higher in the free troposphere. The unique CO profile product from Terra/MOPITT clearly distinguishes near-surface CO from the free troposphere CO. Also previous studies have suggested strong correlations between primary emissions of fire organic and black carbon aerosols and CO. We will present results from the Ensemble Adjustement Kalman Filter (DART) system that has been developed to assimilate MOPITT CO in the global scale chemistry-climate model CAM-Chem. The ensemble technique allows inference on various fire model state variables such as CO emissions and also aerosol species resulting from fires such as organic and black carbon. The benefit of MOPITT CO assimilation on the Washington and Indonesian fire cases studies will be diagnosed regarding the CO fire emissions, black and organic carbon inference using the ensemble information.

Progress in Modeling Global Atmospheric CO2 Fluxes and Transport: Results from Simulations with Diurnal Fluxes

NASA Technical Reports Server (NTRS)

Collatz, G. James; Kawa, R.

2007-01-01

Progress in better determining CO2 sources and sinks will almost certainly rely on utilization of more extensive and intensive CO2 and related observations including those from satellite remote sensing. Use of advanced data requires improved modeling and analysis capability. Under NASA Carbon Cycle Science support we seek to develop and integrate improved formulations for 1) atmospheric transport, 2) terrestrial uptake and release, 3) biomass and 4) fossil fuel burning, and 5) observational data analysis including inverse calculations. The transport modeling is based on meteorological data assimilation analysis from the Goddard Modeling and Assimilation Office. Use of assimilated met data enables model comparison to CO2 and other observations across a wide range of scales of variability. In this presentation we focus on the short end of the temporal variability spectrum: hourly to synoptic to seasonal. Using CO2 fluxes at varying temporal resolution from the SIB 2 and CASA biosphere models, we examine the model's ability to simulate CO2 variability in comparison to observations at different times, locations, and altitudes. We find that the model can resolve much of the variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The influence of key process representations is inferred. The high degree of fidelity in these simulations leads us to anticipate incorporation of realtime, highly resolved observations into a multiscale carbon cycle analysis system that will begin to bridge the gap between top-down and bottom-up flux estimation, which is a primary focus of NACP.

Analysis of Seasonal Chlorophyll-a Using An Adjoint Three-Dimensional Ocean Carbon Cycle Model

NASA Astrophysics Data System (ADS)

Tjiputra, J.; Winguth, A.; Polzin, D.

2004-12-01

The misfit between numerical ocean model and observations can be reduced using data assimilation. This can be achieved by optimizing the model parameter values using adjoint model. The adjoint model minimizes the model-data misfit by estimating the sensitivity or gradient of the cost function with respect to initial condition, boundary condition, or parameters. The adjoint technique was used to assimilate seasonal chlorophyll-a data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite to a marine biogeochemical model HAMOCC5.1. An Identical Twin Experiment (ITE) was conducted to test the robustness of the model and the non-linearity level of the forward model. The ITE experiment successfully recovered most of the perturbed parameter to their initial values, and identified the most sensitive ecosystem parameters, which contribute significantly to model-data bias. The regional assimilations of SeaWiFS chlorophyll-a data into the model were able to reduce the model-data misfit (i.e. the cost function) significantly. The cost function reduction mostly occurred in the high latitudes (e.g. the model-data misfit in the northern region during summer season was reduced by 54%). On the other hand, the equatorial regions appear to be relatively stable with no strong reduction in cost function. The optimized parameter set is used to forecast the carbon fluxes between marine ecosystem compartments (e.g. Phytoplankton, Zooplankton, Nutrients, Particulate Organic Carbon, and Dissolved Organic Carbon). The a posteriori model run using the regional best-fit parameterization yields approximately 36 PgC/yr of global net primary productions in the euphotic zone.

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.

Environmental Regulation of Heterosis in the Allopolyploid Arabidopsis suecica1[OPEN

PubMed Central

Solhaug, Erik M.; Ihinger, Jacie; Gamboa, Veronica; Bradford, Denise; Doerge, R.W.

2016-01-01

Allopolyploids are organisms possessing more than two complete sets of chromosomes from two or more species and are frequently more vigorous than their progenitors. To address the question why allopolyploids display hybrid vigor, we compared the natural allopolyploid Arabidopsis suecica to its progenitor species Arabidopsis thaliana and Arabidopsis arenosa. We measured chlorophyll content, CO2 assimilation, and carbohydrate production under varying light conditions and found that the allopolyploid assimilates more CO2 per unit chlorophyll than either of the two progenitor species in high intensity light. The increased carbon assimilation corresponds with greater starch accumulation, but only in strong light, suggesting that the strength of hybrid vigor is dependent on environmental conditions. In weaker light A. suecica tends to produce as much primary metabolites as the better progenitor. We found that gene expression of LIMIT DEXTRINASE1, a debranching enzyme that cleaves branch points within starch molecules, is at the same level in the allopolyploid as in the maternal progenitor A. thaliana and significantly more expressed than in the paternal progenitor A. arenosa. However, expression differences of β-amylases and GLUCAN-WATER DIKINASE1 were not statistically significantly elevated in the allopolyploid over progenitor expression levels. In contrast to allopolyploids, autopolyploid A. thaliana showed the same photosynthetic rate as diploids, indicating that polyploidization alone is likely not the reason for enhanced vigor in the allopolyploid. Taken together, our data suggest that the magnitude of heterosis in A. suecica is environmentally regulated, arises from more efficient photosynthesis, and, under specific conditions, leads to greater starch accumulation than in its progenitor species. PMID:26896394

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.

Sensitivity of the model error parameter specification in weak-constraint four-dimensional variational data assimilation

NASA Astrophysics Data System (ADS)

Shaw, Jeremy A.; Daescu, Dacian N.

2017-08-01

This article presents the mathematical framework to evaluate the sensitivity of a forecast error aspect to the input parameters of a weak-constraint four-dimensional variational data assimilation system (w4D-Var DAS), extending the established theory from strong-constraint 4D-Var. Emphasis is placed on the derivation of the equations for evaluating the forecast sensitivity to parameters in the DAS representation of the model error statistics, including bias, standard deviation, and correlation structure. A novel adjoint-based procedure for adaptive tuning of the specified model error covariance matrix is introduced. Results from numerical convergence tests establish the validity of the model error sensitivity equations. Preliminary experiments providing a proof-of-concept are performed using the Lorenz multi-scale model to illustrate the theoretical concepts and potential benefits for practical applications.

Implementing of lognormal humidity and cloud-related control variables for the NCEP GSI hybrid EnVAR Assimilation scheme.

NASA Astrophysics Data System (ADS)

Fletcher, S. J.; Kleist, D.; Ide, K.

2017-12-01

As the resolution of operational global numerical weather prediction system approach the meso-scale, then the assumption of Gaussianity for the errors at these scales may not valid. However, it is also true that synoptic variables that are positive definite in behavior, for example humidity, cannot be optimally analyzed with a Gaussian error structure, where the increment could force the full field to go negative. In this presentation we present the initial work of implementing a mixed Gaussian-lognormal approximation for the temperature and moisture variable in both the ensemble and variational component of the NCEP GSI hybrid EnVAR. We shall also lay the foundation for the implementation of the lognormal approximation to cloud related control variables to allow for a possible more consistent assimilation of cloudy radiances.