Fitting Uncertainties Research Articles

The critical role of uncertainty in projections of hydrological extremes

Abstract. This paper aims to quantify the uncertainty in projections of future hydrological extremes in the Biala Tarnowska River at Koszyce gauging station, south Poland. The approach followed is based on several climate projections obtained from the EURO-CORDEX initiative, raw and bias-corrected realizations of catchment precipitation, and flow simulations derived using multiple hydrological model parameter sets. The projections cover the 21st century. Three sources of uncertainty are considered: one related to climate projection ensemble spread, the second related to the uncertainty in hydrological model parameters and the third related to the error in fitting theoretical distribution models to annual extreme flow series. The uncertainty of projected extreme indices related to hydrological model parameters was conditioned on flow observations from the reference period using the generalized likelihood uncertainty estimation (GLUE) approach, with separate criteria for high- and low-flow extremes. Extreme (low and high) flow quantiles were estimated using the generalized extreme value (GEV) distribution at different return periods and were based on two different lengths of the flow time series. A sensitivity analysis based on the analysis of variance (ANOVA) shows that the uncertainty introduced by the hydrological model parameters can be larger than the climate model variability and the distribution fit uncertainty for the low-flow extremes whilst for the high-flow extremes higher uncertainty is observed from climate models than from hydrological parameter and distribution fit uncertainties. This implies that ignoring one of the three uncertainty sources may cause great risk to future hydrological extreme adaptations and water resource planning and management.

Minimizing and Characterizing Uncertainties in Neutron Strain Measurements with Special Attention to Grain Size Effects

The accurate determination of strain during measurement using neutron diffraction depends on many factors. The statistical uncertainty of the diffraction data is not always the most important contributor to the total uncertainty in the measured strain. Other contributors, such as sample positioning, size and shape of the sampling (gauge) volume and the size and distribution of grains within the sampling volume, often play an important role as well. Grain size issues have been the least studied and their impact is often ignored even though the potential uncertainty contribution can be large. Certain methods such as oscillating the sample during measurement can help in reducing the magnitude of the grain size effect and hence also that of the related uncertainty contribution. A thorough characterization of uncertainties due to grain size effects however, in terms of absolute values that should be added to the statistical peak fitting uncertainties has not yet been implemented. This paper will present an improved method to characterize and estimate absolute uncertainty values due to grain size effects.

Multivariate Copula Analysis Toolbox (MvCAT): Describing dependence and underlying uncertainty using a Bayesian framework

AbstractWe present a newly developed Multivariate Copula Analysis Toolbox (MvCAT) which includes a wide range of copula families with different levels of complexity. MvCAT employs a Bayesian framework with a residual‐based Gaussian likelihood function for inferring copula parameters and estimating the underlying uncertainties. The contribution of this paper is threefold: (a) providing a Bayesian framework to approximate the predictive uncertainties of fitted copulas, (b) introducing a hybrid‐evolution Markov Chain Monte Carlo (MCMC) approach designed for numerical estimation of the posterior distribution of copula parameters, and (c) enabling the community to explore a wide range of copulas and evaluate them relative to the fitting uncertainties. We show that the commonly used local optimization methods for copula parameter estimation often get trapped in local minima. The proposed method, however, addresses this limitation and improves describing the dependence structure. MvCAT also enables evaluation of uncertainties relative to the length of record, which is fundamental to a wide range of applications such as multivariate frequency analysis.

Allyl Isothiocyanate Release from Edible Laminaria japonica for Time-Dependent Growth Deactivation of Foodborne Pathogens: I: Micrococcus luteus, Bacillus subtilis, and Listeria monocytogenes

Allyl isothiocyanate (AITC) is a natural occurring essential oil found in plants of the family Brassicaceae. It is a well-recognized antimicrobial agent against a variety of foodborne pathogens. By vapor and solution deposition methods into raw and de-oiled Laminaria japonica, an edible, brown seaweed, we demonstrate AITC vapor phase activity against Listeria monocytogenes, Bacillus subtilis, and Micrococcus luteus. Colony deactivation occurred for each bacterium in the range 99.87–99.99% within 72 h. The kinetics of these activities was fitted to the Weibull and the Albert-Mafart population decay models. Combined standard uncertainty in the final model fitting is introduced for these models, along with bias factor analysis. The former indicates the degree of fit of the models while the latter indicated which of the models was the most appropriate. In general, the bias factor analysis of the models indicated that the Albert-Mafart model was the superior. The continued activity of AITC after contact with the seaweed delivery system suggested that the L. japonica + AITC system would represent a viable natural, edible system for food preservation.

Phenomenological extraction of two-photon exchange amplitudes from elastic electron-proton scattering cross section data

In this work, I improve on and extend to low and high $Q^2$ values the extractions of the $\varepsilon$ dependence of the real parts of the two-photon exchange (TPE) amplitudes relative to the magnetic form factor, as well as the ratio $P_l/P_l^{Born} (\varepsilon,Q^2)$ by using world data on $\sigma_R(\varepsilon,Q^2)$ with an emphasis on precise new data covering the low-momentum region which is sensitive to the large-scale structure of the nucleon. I provide simple parametrizations of the TPE amplitudes, along with an estimate of the fit uncertainties. The extracted TPE amplitudes are compared with previous phenomenological extractions and TPE calculations. The $P_l/P_l^{Born}$ ratio is extracted by using the new parametrizations of the TPE amplitudes and compared to previous extractions, TPE calculations, and direct measurements at $Q^2$ = 2.50 (GeV/c)$^2$. The extracted TPE amplitudes are on the few-percentage-points level and behave roughly linearly with increasing $Q^2$ where they become nonlinear at high $Q^2$. Contrary to $Y_M$, which is influenced mainly by elastic contributions, I find $Y_E$ to be influenced by inelastic contributions at large $Q^2$ values. While $Y_E$ and $Y_3$ differ in magnitude, they have opposite sign and tend to partially cancel each other. This suggests that the TPE correction to $\sigma_R(\varepsilon,Q^2)$ is driven mainly by $Y_M$ and to a lesser extent by $Y_3$ in agreement with previous phenomenological extractions and hadronic TPE calculations.

Continuum limit of the D meson, Ds meson, and charmonium spectrum from Nf=2+1+1 twisted mass lattice QCD

We compute masses of $D$ meson, ${D}_{s}$ meson, and charmonium states using ${N}_{f}=2+1+1$ Wilson twisted mass lattice QCD. All results are extrapolated to physical light quark masses, to physical strange and charm quark masses, and to the continuum. Our analysis includes states with spin $J=0$, 1, 2, parity $\mathcal{P}=\ensuremath{-},+$, and in case of charmonium also charge conjugation $\mathcal{C}=\ensuremath{-},+$. Computations are based on a large set of quark-antiquark meson creation operators. We investigate and quantify all sources of systematic errors, including fitting range uncertainties, finite volume effects, isospin breaking effects, and the choice of the fitting ansatz for the combined chiral and continuum extrapolation such that the resulting meson masses can be compared directly and in a meaningful way to experimental results. Within combined statistical and systematic errors, which are between below 2 per mille and 3%, our results agree with available experimental results for most of the states. In the few cases where we observe discrepancies, we discuss possible reasons.

A Simulated Annealing based Optimization Algorithm for Automatic Variogram Model Fitting

AbstractFitting a theoretical model to an experimental variogram is an important issue in geostatistical studies because if the variogram model parameters are tainted with uncertainty, the latter will spread in the results of estimations and simulations. Although the most popular fitting method is fitting by eye, in some cases use is made of the automatic fitting method on the basis of putting together the geostatistical principles and optimization techniques to: 1) provide a basic model to improve fitting by eye, 2) fit a model to a large number of experimental variograms in a short time, and 3) incorporate the variogram related uncertainty in the model fitting. Effort has been made in this paper to improve the quality of the fitted model by improving the popular objective function (weighted least squares) in the automatic fitting. Also, since the variogram model function (£) and number of structures (m) too affect the model quality, a program has been provided in the MATLAB software that can present optimum nested variogram models using the simulated annealing method. Finally, to select the most desirable model from among the single/multi-structured fitted models, use has been made of the cross-validation method, and the best model has been introduced to the user as the output. In order to check the capability of the proposed objective function and the procedure, 3 case studies have been presented.

OSL dating of individual quartz ‘supergrains’ from the Ancient Middle Palaeolithic site of Cuesta de la Bajada, Spain

Dose saturation represents a fundamental limitation for obtaining finite optically stimulated luminescence (OSL) quartz ages over Middle Pleistocene timescales. Single-grain OSL studies typically reveal significant intra- and inter-sample variability in quartz dose saturation properties at the individual grain level. This enhanced variability may offer the potential to obtain extended-range chronologies exceeding the traditional upper age limits of multiple-grain OSL dating. However, there have been relatively few detailed assessments of single-grain OSL properties over high dose ranges. In this study we investigate extended-range single-grain OSL dating potential at Cuesta de la Bajada, one of the most important Ancient Middle Palaeolithic sites in the Iberian Peninsula. The quartz samples from this site exhibit exceptional dose saturation properties and contain significant populations of individual ‘supergrains’ with bright OSL signals, very high characteristic saturation dose (D0) limits of 200 to >600 Gy, and dose-response curves that closely conform to single saturating exponential functions. Assessments of OSL signal composition and the ability to successfully recover a known laboratory dose of 470 Gy support the potential for obtaining high equivalent dose (De) values with reasonable fitting uncertainties. A series of novel sensitivity tests are used to assess potential biases in supergrain De estimation over high dose ranges related to (i) thermally transferred signal contributions, (ii) choice of dose-response curve fitting function, and (iii) insufficient dose saturation properties of individual grains. The single-grain De values obtained using the standard quality assurance criteria and novel sensitivity tests are consistent at 2σ, and are in agreement with quartz Ti-centre ages obtained on two of three paired electron spin resonance (ESR) samples collected from Cuesta de la Bajada. These comparisons support the suitability of our single-grain OSL results and suggest there may be good potential for using quartz supergrains to establish extended-range chronologies at some Middle Pleistocene sites. Comparisons with other single-grain OSL studies across the Iberian central plains suggest that favourable dose saturation properties may be influenced by regional-scale geological controls. The importance of undertaking single-grain OSL dating at Cuesta de la Bajada is also demonstrated by the results of synthetic aliquot experiments, which reveal multiple-grain age offsets of 60–170 ka when unsuitable grain types are inadvertently included in the final age calculations. The single-grain OSL results indicate that the main archaeological horizon at Cuesta de la Bajada (unit CB3) accumulated between 264 ± 22 and 293 ± 24 ka. These ages are consistent with the chronologies of other key early Middle Palaeolithic sites in the region (Ambrona AS6 and Gran Dolina TD10) and indicate that the Ancient Middle Palaeolithic techno-complex likely spread across Iberia from at least Marine Isotope Stage 9 onwards.

Ground-based, integrated path differential absorption LIDAR measurement of CO2, CH4, and H2O near 1.6 μm.

A ground-based, integrated path, differential absorption light detection and ranging (IPDA LIDAR) system is described and characterized for a series of nighttime studies of CO2, CH4, and H2O. The transmitter is based on an actively stabilized, continuous-wave, single-frequency external-cavity diode laser (ECDL) operating from 1.60 to 1.65 μm. The fixed frequency output of the ECDL is microwave sideband tuned using an electro-optical phase modulator driven by an arbitrary waveform generator and filtered using a confocal cavity to generate a sequence of 123 frequencies separated by 300 MHz. The scan sequence of single sideband frequencies of 600 ns duration covers a 37 GHz region at a spectral scan rate of 10 kHz (100 μs per scan). Simultaneously, an eye-safe backscatter LIDAR system at 1.064 μm is used to monitor the atmospheric boundary layer. IPDA LIDAR measurements of the CO2 and CH4 dry air mixing ratios are presented in comparison with those from a commercial cavity ring-down (CRD) instrument. Differences between the IPDA LIDAR and CRD concentrations in several cases appear to be well correlated with the atmospheric aerosol structure from the backscatter LIDAR measurements. IPDA LIDAR dry air mixing ratios of CO2 and CH4 are determined with fit uncertainties of 2.8 μmol/mol (ppm) for CO2 and 22 nmol/mol (ppb) for CH4 over 30 s measurement periods. For longer averaging times (up to 1200 s), improvements in these detection limits by up to 3-fold are estimated from Allan variance analyses. Two sources of systematic error are identified and methods to remove them are discussed, including speckle interference from wavelength decorrelation and the seed power dependence of amplified spontaneous emission. Accuracies in the dry air retrievals of CO2 and CH4 in a 30 s measurement period are estimated at 4 μmol/mol (1% of ambient levels) and 50 nmol/mol (3%), respectively.

SU-G-BRB-14: Uncertainty of Radiochromic Film Based Relative Dose Measurements

Purpose: Due to inherently non-linear dose response, measurement of relative dose distribution with radiochromic film requires measurement of absolute dose using a calibration curve following previously established reference dosimetry protocol. On the other hand, a functional form that converts the inherently non-linear dose response curve of the radiochromic film dosimetry system into linear one has been proposed recently [Devic et al, Med. Phys. 39 4850–4857 (2012)]. However, there is a question what would be the uncertainty of such measured relative dose. Methods: If the relative dose distribution is determined going through the reference dosimetry system (conversion of the response by using calibration curve into absolute dose) the total uncertainty of such determined relative dose will be calculated by summing in quadrature total uncertainties of doses measured at a given and at the reference point. On the other hand, if the relative dose is determined using linearization method, the new response variable is calculated as ζ=a(netOD)n/ln(netOD). In this case, the total uncertainty in relative dose will be calculated by summing in quadrature uncertainties for a new response function (σζ) for a given and the reference point. Results: Except at very low doses, where the measurement uncertainty dominates, the total relative dose uncertainty is less than 1% for the linear response method as compared to almost 2% uncertainty level for the reference dosimetry method. The result is not surprising having in mind that the total uncertainty of the reference dose method is dominated by the fitting uncertainty, which is mitigated in the case of linearization method. Conclusion: Linearization of the radiochromic film dose response provides a convenient and a more precise method for relative dose measurements as it does not require reference dosimetry and creation of calibration curve. However, the linearity of the newly introduced function must be verified. Dave Lewis is inventor and runs a consulting company for radiochromic films

Prediction uncertainty and optimal experimental design for learning dynamical systems.

Dynamical systems are frequently used to model biological systems. When these models are fit to data, it is necessary to ascertain the uncertainty in the model fit. Here, we present prediction deviation, a metric of uncertainty that determines the extent to which observed data have constrained the model's predictions. This is accomplished by solving an optimization problem that searches for a pair of models that each provides a good fit for the observed data, yet has maximally different predictions. We develop a method for estimating a priori the impact that additional experiments would have on the prediction deviation, allowing the experimenter to design a set of experiments that would most reduce uncertainty. We use prediction deviation to assess uncertainty in a model of interferon-alpha inhibition of viral infection, and to select a sequence of experiments that reduces this uncertainty. Finally, we prove a theoretical result which shows that prediction deviation provides bounds on the trajectories of the underlying true model. These results show that prediction deviation is a meaningful metric of uncertainty that can be used for optimal experimental design.

First Direct Evidence for Natal Wintering Ground Fidelity and Estimate of Juvenile Survival in the New Zealand Southern Right Whale Eubalaena australis.

Juvenile survival and recruitment can be more sensitive to environmental, ecological and anthropogenic factors than adult survival, influencing population-level processes like recruitment and growth rate in long-lived, iteroparous species such as southern right whales. Conventionally, Southern right whales are individually identified using callosity patterns, which do not stabilise until 6–12 months, by which time the whale has left its natal wintering grounds. Here we use DNA profiling of skin biopsy samples to identify individual Southern right whales from year of birth and document their return to the species’ primary wintering ground in New Zealand waters, the Subantarctic Auckland Islands. We find evidence of natal fidelity to the New Zealand wintering ground by the recapture of 15 of 57 whales, first sampled in year of birth and available for subsequent recapture, during winter surveys to the Auckland Islands in 1995–1998 and 2006–2009. Four individuals were recaptured at the ages of 9 to 11, including two females first sampled as calves in 1998 and subsequently resampled as cows with calves in 2007. Using these capture-recapture records of known-age individuals, we estimate changes in survival with age using Cormack-Jolly-Seber models. Survival is modelled using discrete age classes and as a continuous function of age. Using a bootstrap method to account for uncertainty in model selection and fitting, we provide the first direct estimate of juvenile survival for this population. Our analyses indicate a high annual apparent survival for juveniles at between 0.87 (standard error (SE) 0.17, to age 1) and 0.95 (SE 0.05: ages 2–8). Individual identification by DNA profiling is an effective method for long-term demographic and genetic monitoring, particularly in animals that change identifiable features as they develop or experience tag loss over time.

Evaluation of the effect of data quality on the profile uncertainty of critical dimension small angle x-ray scattering

A line grating prepared via a self-aligned quadruple patterning method was measured using critical dimension small angle x-ray scattering. A Monte Carlo Markov chain algorithm was used to analyze the uncertainty of the model fit over subsets of the full angular range and for a time series with decreasing signal-to-noise in order to determine the effect of the data quality on the final profile shape uncertainty. These results show how the total measurement time can be reduced while maintaining satisfactory profile shape uncertainty. We found that the typical measurement conditions are highly oversampled and can be reduced considerably with only marginal effect on the shape uncertainty. A comparison is made between the synchrotron measurements and a laboratory system, demonstrating that both measurements result in similar structures.

Temporal and vertical distributions of anthropogenic 236U in the Japan Sea using a coral core and seawater samples

AbstractThe input history of 236U to the surface water of the Japan Sea was reconstructed through measurement of the 236U/238U atom ratio in annual bands of a coral skeleton which was collected at Iki Island in the Tsushima Strait, the main entrance to the Japan Sea. The 236U/238U atom ratios and concentrations of U isotopes were measured for the period 1935–2010 using AMS and ICP‐MS. The 236U/238U atom ratios revealed three prominent peaks: 4.51 × 10−9 in 1955, 6.15 × 10−9 in 1959 and 4.14 × 10−9 in 1963; thereafter the isotope ratios gradually decreased over the next several decades, attaining a value of ca.1.3 × 10−9 for the present day. A simplified depth profile model for 236U in the Japan Sea, using the reconstructed 236U value for the surface water together with observed depth profiles for 236U in the water column in 2010, yielded diffusion coefficients of 3.4–5.6 cm2/s for 6 sampling points. The diffusion coefficient values obtained for the northern stations were relatively large, and fitting uncertainty was also larger for stations in the northern region. It may be presumed that the distribution of 236U in the water columns have been influenced not only by diffusion but also by subduction of the surface water in the Japan Sea.

Advancements, measurement uncertainties, and recent comparisons of the NOAA frost point hygrometer.

The NOAA frost point hygrometer (FPH) is a balloon-borne instrument flown monthly at three sites to measure water vapor profiles up to 28 km. The FPH record from Boulder, Colorado, is the longest continuous stratospheric water vapor record. The instrument has an uncertainty in the stratosphere that is < 6 % and up to 12 % in the troposphere. A digital microcontroller version of the instrument improved upon the older versions in 2008 with sunlight filtering, better frost control, and resistance to radio frequency interference (RFI). A new thermistor calibration technique was implemented in 2014, decreasing the uncertainty in the thermistor calibration fit to less than 0.01 °C over the full range of frost – or dew point temperatures (−93 to +20 °C) measured during a profile. Results from multiple water vapor intercomparisons are presented, including the excellent agreement between the NOAA FPH and the direct tunable diode laser absorption spectrometer (dTDLAS) MC-PicT-1.4 during AquaVIT-2 chamber experiments over 6 days that provides confidence in the accuracy of the FPH measurements. Dual instrument flights with two FPHs or an FPH and a cryogenic frost point hygrometer (CFH) also show good agreement when launched on the same balloon. The results from these comparisons demonstrate the high level of accuracy of the NOAA FPH.

Accuracy of atmospheric parameters of FGK dwarfs determined by spectrum fitting

We performed extensive tests of the accuracy of atmospheric parameter determination for FGK stars based on the spectrum fitting procedure Spectroscopy Made Easy (SME). Our stellar sample consists of 13 objects, including the Sun, in the temperature range 5000--6600~K and metallicity range -1.4 -- +0.4. The analysed stars have the advantage of having parameters derived by interferometry. For each star we use spectra obtained with different spectrographs and different signal-to-noise ratios (S/N). For the fitting we adopted three different sets of constraints and test how the derived parameters depend upon the spectral regions (masks) used in SME. We developed and implemented in SME a new method for estimating uncertainties in the resulting parameters based on fitting residuals, partial derivatives, and data uncertainties. For stars in the 5700--6600 K range the best agreement with the effective temperatures derived by interferometry is achieved when spectrum fitting includes the H$\alpha$ and H$\beta$ lines, while for cooler stars the choice of the mask does not affect the results. The derived atmospheric parameters do not strongly depend on spectral resolution and S/N of the observations, while the uncertainties in temperature and surface gravity increase with increasing effective temperature, with minima at 50~K in Teff and 0.1~dex in log g, for spectra with S/N=150--200. A NLTE analysis of the TiI/TiII and FeI/FeII ionisation equilibria and abundances determined from the atomic CI (NLTE) and molecular CH species supports the parameters we derived with SME by fitting the observed spectra including the hydrogen lines.

Integrative Bayesian analysis of neuroimaging-genetic data with application to cocaine dependence

Neuroimaging and genetic studies provide distinct and complementary information about the structural and biological aspects of a disease. Integrating the two sources of data facilitates the investigation of the links between genetic variability and brain mechanisms among different individuals for various medical disorders. This article presents a general statistical framework for integrative Bayesian analysis of neuroimaging-genetic (iBANG) data, which is motivated by a neuroimaging-genetic study in cocaine dependence. Statistical inference necessitated the integration of spatially dependent voxel-level measurements with various patient-level genetic and demographic characteristics under an appropriate probability model to account for the multiple inherent sources of variation. Our framework uses Bayesian model averaging to integrate genetic information into the analysis of voxel-wise neuroimaging data, accounting for spatial correlations in the voxels. Using multiplicity controls based on the false discovery rate, we delineate voxels associated with genetic and demographic features that may impact diffusion as measured by fractional anisotropy (FA) obtained from DTI images. We demonstrate the benefits of accounting for model uncertainties in both model fit and prediction. Our results suggest that cocaine consumption is associated with FA reduction in most white matter regions of interest in the brain. Additionally, gene polymorphisms associated with GABAergic, serotonergic and dopaminergic neurotransmitters and receptors were associated with FA.

Quantifying uncertainty of past pCO2 determined from changes in C3 plant carbon isotope fractionation

Knowledge of the past concentrations of atmospheric CO2 level (pCO2) is critical to understanding climate sensitivity to changing pCO2. Towards this, a new proxy for pCO2 has been developed based on changes in carbon isotope fractionation (Δ13C) in C3 land plants. The accuracy of this approach has been validated against ice-core pCO2 records, suggesting the potential to apply this proxy to other geological periods; however, no thorough uncertainty assessment of the proxy has been conducted. Here, we first analyze the uncertainty in the model-curve fit through the experimental data using a bootstrap approach. Then, errors of the five input parameters for the proxy are evaluated using sensitivity analysis; these include the carbon isotope composition of atmospheric CO2 (δ13CCO2) and that of the plant material (δ13Corg) for two time periods, a reference time (t=0) and the time period of interest (t), and the value of pCO2 at time t=0. We then propagated the errors on the reconstructed pCO2 using a Monte Carlo random sampling approach that combined the uncertainties of the curve fitting and the five inputs for a scenario in which the reference time was the Holocene with a target period for the reconstructed pCO2 during the Cenozoic. We find that the error in the reconstructed pCO2(t) increases with increasing pCO2(t), yet remains <122% (positive error) and <40% (negative error) for pCO2(t)<1000ppmv. The error assessment suggests that it can be used with confidence for much of the Cenozoic and perhaps the majority of the last 400 million years, which is characterized by pCO2 levels generally less than 1000 ppmv. Towards this, an application of this uncertainty analysis is presented for the Paleogene (52–63Ma) using published data. The resulting pCO2(t) levels calculated using this method average 470 +288/−147ppmv (1σ, n=75), and overlap with previous pCO2(t) estimates determined for this time period using stomata, liverwort, and paleosol proxies. The analysis presented here assumes that the paleoenvironment in which the plants grew is unknown and is determined to be the largest source of error in the reconstructed pCO2(t) levels; errors in pCO2(t) could be reduced provided independent determination of the paleoenvironmental conditions at the fossil site.

Spectral improvement by fourier thresholding of in vivo dynamic spectroscopy data

MR spectroscopy (MRS) typically requires averaging of multiple acquisitions to achieve adequate signal-to-noise ratio (SNR). In systems undergoing dynamic changes this can compromise the temporal resolution of the measurement. One such example is (31) P MRS of exercising skeletal muscle. Spectral improvement by Fourier thresholding (SIFT) offers a way of suppressing noise without averaging. In this study, we evaluate the performance of SIFT in healthy subjects and clinical cases. (31) P MRS of the calf or thigh muscle of subjects (n = 12) was measured continuously before, during, and after exercise. The data were processed conventionally and with the addition of SIFT before quantifying peak amplitudes and frequencies. The postexercise increase in the amplitude of phosphocreatine was also characterized by fitting with an exponential function to obtain the recovery time constant. Substantial reductions in the uncertainty of peak fitting for phosphocreatine (73%) and inorganic phosphate (60%) were observed when using SIFT relative to conventional processing alone. SIFT also reduced the phosphocreatine recovery time constant uncertainty by 38%. SIFT considerably improves SNR, which improved quantification and parameter estimation. It is suitable for any type of time varying MRS and is both straightforward and fast to apply. Magn Reson Med 76:978-985, 2016. © 2015 Wiley Periodicals, Inc.

Evaluation of MAX-DOAS aerosol retrievals by coincident observations using CRDS, lidar, and sky radiometer inTsukuba, Japan

Abstract. Coincident aerosol observations of multi-axis differential optical absorption spectroscopy (MAX-DOAS), cavity ring-down spectroscopy (CRDS), lidar, and sky radiometer were conducted in Tsukuba, Japan, on 5–18 October 2010. MAX-DOAS aerosol retrieval (for aerosol extinction coefficient and aerosol optical depth at 476 nm) was evaluated from the viewpoint of the need for a correction factor for oxygen collision complexes (O4 or O2–O2) absorption. The present study strongly supports this need, as systematic residuals at relatively high elevation angles (20 and 30°) were evident in MAX-DOAS profile retrievals conducted without the correction. However, adopting a single number for the correction factor (fO4 = 1.25) for all of the elevation angles led to systematic overestimation of near-surface aerosol extinction coefficients, as reported in the literature. To achieve agreement with all three observations, we limited the set of elevation angles to ≤10° and adopted an elevation-angle-dependent correction factor for practical profile retrievals with scattered light observations by a ground-based MAX-DOAS. With these modifications, we expect to minimize the possible effects of temperature-dependent O4 absorption cross section and uncertainty in DOAS fit on an aerosol profile retrieval, although more efforts are encouraged to quantitatively identify a physical explanation for the need of a correction factor.