4,886 research outputs found

    Uncertainty Quantification of GEOS-5 L-band Radiative Transfer Model Parameters Using Bayesian Inference and SMOS Observations

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    Uncertainties in L-band (1.4 GHz) radiative transfer modeling (RTM) affect the simulation of brightness temperatures (Tb) over land and the inversion of satellite-observed Tb into soil moisture retrievals. In particular, accurate estimates of the microwave soil roughness, vegetation opacity and scattering albedo for large-scale applications are difficult to obtain from field studies and often lack an uncertainty estimate. Here, a Markov Chain Monte Carlo (MCMC) simulation method is used to determine satellite-scale estimates of RTM parameters and their posterior uncertainty by minimizing the misfit between long-term averages and standard deviations of simulated and observed Tb at a range of incidence angles, at horizontal and vertical polarization, and for morning and evening overpasses. Tb simulations are generated with the Goddard Earth Observing System (GEOS-5) and confronted with Tb observations from the Soil Moisture Ocean Salinity (SMOS) mission. The MCMC algorithm suggests that the relative uncertainty of the RTM parameter estimates is typically less than 25 of the maximum a posteriori density (MAP) parameter value. Furthermore, the actual root-mean-square-differences in long-term Tb averages and standard deviations are found consistent with the respective estimated total simulation and observation error standard deviations of m3.1K and s2.4K. It is also shown that the MAP parameter values estimated through MCMC simulation are in close agreement with those obtained with Particle Swarm Optimization (PSO)

    Assimilation of Freeze - Thaw Observations into the NASA Catchment Land Surface Model

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    The land surface freeze-thaw (F-T) state plays a key role in the hydrological and carbon cycles and thus affects water and energy exchanges and vegetation productivity at the land surface. In this study, we developed an F-T assimilation algorithm for the NASA Goddard Earth Observing System, version 5 (GEOS-5) modeling and assimilation framework. The algorithm includes a newly developed observation operator that diagnoses the landscape F-T state in the GEOS-5 Catchment land surface model. The F-T analysis is a rule-based approach that adjusts Catchment model state variables in response to binary F-T observations, while also considering forecast and observation errors. A regional observing system simulation experiment was conducted using synthetically generated F-T observations. The assimilation of perfect (error-free) F-T observations reduced the root-mean-square errors (RMSE) of surface temperature and soil temperature by 0.206 C and 0.061 C, respectively, when compared to model estimates (equivalent to a relative RMSE reduction of 6.7 percent and 3.1 percent, respectively). For a maximum classification error (CEmax) of 10 percent in the synthetic F-T observations, the F-T assimilation reduced the RMSE of surface temperature and soil temperature by 0.178 C and 0.036 C, respectively. For CEmax=20 percent, the F-T assimilation still reduces the RMSE of model surface temperature estimates by 0.149 C but yields no improvement over the model soil temperature estimates. The F-T assimilation scheme is being developed to exploit planned operational F-T products from the NASA Soil Moisture Active Passive (SMAP) mission

    Assimilation of Passive and Active Microwave Soil Moisture Retrievals

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    Root-zone soil moisture is an important control over the partition of land surface energy and moisture, and the assimilation of remotely sensed near-surface soil moisture has been shown to improve model profile soil moisture [1]. To date, efforts to assimilate remotely sensed near-surface soil moisture at large scales have focused on soil moisture derived from the passive microwave Advanced Microwave Scanning Radiometer (AMSR-E) and the active Advanced Scatterometer (ASCAT; together with its predecessor on the European Remote Sensing satellites (ERS. The assimilation of passive and active microwave soil moisture observations has not yet been directly compared, and so this study compares the impact of assimilating ASCAT and AMSR-E soil moisture data, both separately and together. Since the soil moisture retrieval skill from active and passive microwave data is thought to differ according to surface characteristics [2], the impact of each assimilation on the model soil moisture skill is assessed according to land cover type, by comparison to in situ soil moisture observations

    Sympathetic Cooling with Two Atomic Species in an Optical Trap

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    We simultaneously trap ultracold lithium and cesium atoms in an optical dipole trap formed by the focus of a CO2_2 laser and study the exchange of thermal energy between the gases. The cesium gas, which is optically cooled to 20őľ20 \muK, efficiently decreases the temperature of the lithium gas through sympathetic cooling. The measured cross section for thermalizing 133^{133}Cs-7^7Li collisions is 8√ó10‚ąí128 \times 10^{-12} cm2^2, for both species in their lowest hyperfine ground state. Besides thermalization, we observe evaporation of lithium purely through elastic cesium-lithium collisions (sympathetic evaporation).Comment: 4 pages 3 fig

    Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

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    The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-ofthe-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979-present. This study introduces a supplemental and improved set of land surface hydrological fields ("MERRA-Land") generated by re-running a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim (ERA-I) reanalysis. MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 US basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies

    A novel role for the root cap in phosphate uptake and homeostasis

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    The root cap has a fundamental role in sensing environmental cues as well as regulating root growth via altered meristem activity. Despite this well-established role in the control of developmental processes in roots, the root cap's function in nutrition remains obscure. Here, we uncover its role in phosphate nutrition by targeted cellular inactivation or phosphate transport complementation in Arabidopsis, using a transactivation strategy with an innovative high-resolution real-time P-33 imaging technique. Remarkably, the diminutive size of the root cap cells at the root-to-soil exchange surface accounts for a significant amount of the total seedling phosphate uptake (approximately 20%). This level of Pi absorption is sufficient for shoot biomass production (up to a 180% gain in soil), as well as repression of Pi starvation-induced genes. These results extend our understanding of this important tissue from its previously described roles in environmental perception to novel functions in mineral nutrition and homeostasis control

    Genetic Diversity and Virulence Potential of Shiga Toxin-Producing Escherichia coli O113:H21 Strains Isolated from Clinical, Environmental, and Food Sources

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    Shiga toxin-producing Escherichia coli strains of serotype O113:H21 have caused severe human diseases, but they are unusual in that they do not produce adherence factors coded by the locus of enterocyte effacement. Here, a PCR microarray was used to characterize 65 O113:H21 strains isolated from the environment, food, and clinical infections from various countries. in comparison to the pathogenic strains that were implicated in hemolytic-uremic syndrome in Australia, there were no clear differences between the pathogens and the environmental strains with respect to the 41 genetic markers tested. Furthermore, all of the strains carried only Shiga toxin subtypes associated with human infections, suggesting that the environmental strains have the potential to cause disease. Most of the O113:H21 strains were closely related and belonged in the same clonal group (ST-223), but CRISPR analysis showed a great degree of genetic diversity among the O113:H21 strains.French Joint Ministerial Program of R&D against CBRNE RisksFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Food & Drug Adm, Div Microbiol, College Pk, MD 20740 USAFrench Agcy Food Environm & Occupat Hlth & Safety, Lab Food Safety, Maisons Alfort, FranceFood & Drug Adm, Div Mol Biol, Laurel, MD USAUniversidade Federal de São Paulo, Dept Microbiol Immunol & Parasitol, São Paulo, BrazilFed Inst Risk Assessment, Natl Reference Lab Escherichia coli, Berlin, GermanyInst Nacl Enfermedades Infecciosas ANLIS Dr Carlo, Serv Fisiopatogenia, Buenos Aires, DF, ArgentinaUniv Melbourne, Peter Doherty Inst Infect & Immun, Dept Microbiol & Immunol, Melbourne, Vic, AustraliaUniv Adelaide, Res Ctr Infect Dis, Sch Mol & Biomed Sci, Adelaide, SA, AustraliaUniversidade Federal de São Paulo, Dept Microbiol Immunol & Parasitol, São Paulo, BrazilFrench Joint Ministerial Program of R&D against CBRNE Risks: C17609-2Web of Scienc

    Population gene introgression and high genome plasticity for the zoonotic pathogen Streptococcus agalactiae

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    The influence that bacterial adaptation (or niche partitioning) within species has on gene spillover and transmission among bacteria populations occupying different niches is not well understood. Streptococcus agalactiae is an important bacterial pathogen that has a taxonomically diverse host range making it an excellent model system to study these processes. Here we analyze a global set of 901 genome sequences from nine diverse host species to advance our understanding of these processes. Bayesian clustering analysis delineated twelve major populations that closely aligned with niches. Comparative genomics revealed extensive gene gain/loss among populations and a large pan-genome of 9,527 genes, which remained open and was strongly partitioned among niches. As a result, the biochemical characteristics of eleven populations were highly distinctive (significantly enriched). Positive selection was detected and biochemical characteristics of the dispensable genes under selection were enriched in ten populations. Despite the strong gene partitioning, phylogenomics detected gene spillover. In particular, tetracycline resistance (which likely evolved in the human-associated population) from humans to bovine, canines, seals, and fish, demonstrating how a gene selected in one host can ultimately be transmitted into another, and biased transmission from humans to bovines was confirmed with a Bayesian migration analysis. Our findings show high bacterial genome plasticity acting in balance with selection pressure from distinct functional requirements of niches that is associated with an extensive and highly partitioned dispensable genome, likely facilitating continued and expansive adaptation
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