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1.
Bethany Behrens Yosuke Miyairi Adam D. Sproson Masako Yamane Yusuke Yokoyama 《第四纪科学杂志》2019,34(8):603-608
Understanding Antarctic Ice Sheet dynamics related to global climate change is of scientific and societal interest as the future behaviour of the ice sheet under the currently changing climate is unknown. We present beryllium‐10 (10Be) analysis of a high‐resolution marine sediment core from the Adélie Basin near the eastern Wilkes Land margin, which is susceptible to marine ice sheet instability due to the low‐lying nature and down‐sloping trough of the Wilkes Subglacial Basin. Combined with a newly constructed age model using compound specific radiocarbon dates, the data reveal three events associated with high meteoric 10Be at ca. ~10 ka, ca. ~6.5 ka and from ca. ~4 ka. We interpret these high meteoric 10Be events to be derived from the deposition of 10Be released from the ice sheet during meltwater discharge. In particular, the shift to higher meteoric 10Be concentration at~4 ka may correspond to changes in climate patterns at this time. Copyright © 2019 John Wiley & Sons, Ltd. 相似文献
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Acta Geotechnica - Liquid bridges in unsaturated soils attach to grain contacts and contribute to strengthening microscopic bonding forces, which leads to macroscopic high strength and stiffness... 相似文献
4.
Yosuke Fujii 《Journal of Oceanography》2005,61(1):167-181
I present the derivation of the Preconditioned Optimizing Utility for Large-dimensional analyses (POpULar), which is developed for adopting a non-diagonal background error covariance matrix in nonlinear variational analyses (i.e., analyses employing a non-quadratic cost function). POpULar is based on the idea of a linear preconditioned conjugate gradient method widely adopted in ocean data assimilation systems. POpULar uses the background error covariance matrix as a preconditioner without any decomposition of the matrix. This preconditioning accelerates the convergence. Moreover, the inverse of the matrix is not required. POpULar therefore allows us easily to handle the correlations among deviations of control variables (i.e., the variables which will be analyzed) from their background in nonlinear problems. In order to demonstrate the usefulness of POpULar, we illustrate two effects which are often neglected in studies of ocean data assimilation before. One is the effect of correlations among the deviations of control variables in an adjoint analysis. The other is the nonlinear effect of sea surface dynamic height calculation required when sea surface height observation is employed in a three-dimensional ocean analysis. As the results, these effects are not so small to neglect. 相似文献
5.
Mesoscale features in the eastward extension of the Kuroshio were investigated using assimilation of TOPEX/POSEIDON (T/P)
data into a three-layer quasi-geostrophic model. The T/P data exhibited an elongated state of the southern recirculation gyre
in 1993–95 and 1997, between whose two periods the gyre had a contracted state in 1995–96. A few stationary eddies were located
in the southern gyre during the contracted state. The baroclinic instability, which was indicated by the phase shift from
the uppermost-to the lowest-layer anomalies toward the downstream side, was evident near the Kuroshio Extension (KE) path.
Since the instability never appeared in the artificial model without bottom topography, the topographic barrier for the eastward
flow in the lowest layer was a necessary condition for the instability. The instability synchronized with the transition in
the western region of the KE axis from the elongated to the contracted states. This evolution was interpreted as if the baroclinic
instability played some part in the KE states and was a trigger for the transition from the elongated to the contracted states. 相似文献
6.
A Reconstruction of Observed Profiles in the Sea East of Japan Using Vertical Coupled Temperature-Salinity EOF Modes 总被引：4，自引：0，他引：4
It is important to estimate hard-to-observe parameters in the ocean interior from easy-to-observe parameters. This study therefore
demostrates a reconstruction of observed temperature and salinity profiles of the sea east of Japan (30°≈40°N, 140°≈150°E).
The reconstruction was done by estimating suboptimal state from several values of the observed profiles and/or sea surface
dynamic height (SDH) calculated from the profiles. The estimation used a variational method with vertical coupled temperature-salinity
empirical orthogonal function (EOF) modes. Profiles of temperature and salinity in the subtropical region are effectively
reconstructed from in situ temperature profile data, or sea surface temperature (SST) and SDH. For example, the analyzed temperature field from SST
and SDH has an accuracy to within 1°C in the subtropical region. Salinity in the sea north of Kuroshio, however, is difficult
to estimate because of its complex variability which is less correlated with temperature than in the subtropical region. Sea
surface salinity is useful to estimate the subsurface structure. We also show the possibility that the estimation is improved
by considering nonlinearity in the equation calculating SDH from temperature and salinity analysis values in order to examine
the misfit between analysis and observation. Analysis using TOPEX/POSEIDON altimetry data instead of SDH was also performed.
This revised version was published online in July 2006 with corrections to the Cover Date. 相似文献
7.
Norihisa?UsuiEmail author Shiro?Ishizaki Yosuke?Fujii Masafumi?Kamachi 《Journal of Oceanography》2011,67(3):253-262
We assess validity of a Gaussian error assumption, the basic assumption in data assimilation theory, and propose two kinds
of constraints regarding non-Gaussian statistics. In the mixed water region (MWR) off the east coast of Japan exhibiting complicated
frontal structures, a probability density function (PDF) of subsurface temperature shows double peaks corresponding to the
Kuroshio and Oyashio waters. The complicated frontal structures characterized by the temperature PDF sometimes cause large
innovations, bringing about a non-Gaussianity of errors. It is also revealed that assimilated results with a standard three-dimensional
variational (3DVAR) scheme have some issues in MWR, arising from the non-Gaussianity of errors. The Oyashio water sometimes
becomes unrealistically cold. The double peaks seen in the observed temperature PDF are too smoothed. To improve the assimilated
field in MWR, we introduce two kinds of constraints, J
c1 and J
c2, which model the observed temperature PDF. The constraint J
c1 prevents the unrealistically cold Oyashio water, and J
c2 intends to reproduce the double peaks. The assimilated fields are significantly improved by using these constraints. The
constraint J
c1 effectively reduces the unrealistically cold Oyashio water. The double peaks in the observed temperature PDF are successfully
reproduced by J
c2. In addition, not only subsurface temperature but also whole level temperature and salinity (T–S) fields are improved by
adopting J
c1 and J
c2 to a multivariate 3DVAR scheme with vertical coupled T–S empirical orthogonal function modes. 相似文献
8.
Ishitsuka Kazuya Kobayashi Yosuke Watanabe Norihiro Yamaya Yusuke Bjarkason Elvar Suzuki Anna Mogi Toru Asanuma Hiroshi Kajiwara Tatsuya Sugimoto Takeshi Saito Ryoichi 《Natural Resources Research》2021,30(5):3289-3314
The temperature distribution at depth is a key variable when assessing the potential of a supercritical geothermal resource as well as a conventional geothermal resource. Data-driven estimation by a machine-learning approach is a promising way to estimate temperature distributions at depth in geothermal fields. In this study, we developed two methodologies—one based on Bayesian estimation and the other on neural networks—to estimate temperature distributions in geothermal fields. These methodologies can be used to supplement existing temperature logs, by estimating temperature distributions in unexplored regions of the subsurface, based on electrical resistivity data, observed geological/mineralogical boundaries, and microseismic observations. We evaluated the accuracy and characteristics of these methodologies using a numerical model of the Kakkonda geothermal field, Japan, where a temperature above 500 °C was observed below a depth of about 3.7 km. When using geological and geophysical knowledge as prior information for the machine learning methods, the results demonstrate that the approaches can provide subsurface temperature estimates that are consistent with the temperature distribution given by the numerical model. Using a numerical model as a benchmark helps to understand the characteristics of the machine learning approaches and may help to identify ways of improving these methods.
相似文献9.
Yoshihiko Kariya Go Sato Kuniyasu Mokudai Jiro Komori Masaki Ishii Ryoko Nishii Yosuke Miyazawa Noriko Tsumura 《Landslides》2007,4(1):91-94
This paper describes a rockfall event in the Daisekkei Valley of Mount Shirouma-dake (2,932 m), the northern Japanese Alps.
The rockfall occurred on a steep cliff comprising well-jointed felsites and produced debris of ≥8,000 m3. Most debris was deposited on an elongated snowpatch located immediately beneath the cliff, and it caused casualties among
people who were trekking along a trail on the snowpatch. Additionally, a large rock block slipped 1 km on the snowpatch. The
rockfall could have been due to the differential retreat of the rockwall, which contains areas of high- and low-density joints.
Seasonal and diurnal freeze–thaw activities and snow avalanches and wash appear to be important factors responsible for the
retreat. Although some rock blocks that can collapse further remain on the rockwall, the position of the mountain trail in
the Daisekkei Valley is fixed. Fundamental reform of tourism systems for climbers, including education on natural hazards,
is required. 相似文献
10.
Nicolas Luco Yasuhiro Mori Yosuke Funahashi C. Allin Cornell Masayoshi Nakashima 《地震工程与结构动力学》2003,32(14):2267-2288
Predictors (or estimates) of seismic structural demands that are less computationally time‐consuming than non‐linear dynamic analysis can be useful for structural performance assessment and for design. In this paper, we evaluate the bias and precision of predictors that make use of, at most, (i) elastic modal vibration properties of the given structure, (ii) the results of a non‐linear static pushover analysis of the structure, and (iii) elastic and inelastic single‐degree‐of‐freedom time‐history analyses for the specified ground motion record. The main predictor of interest is an extension of first‐mode elastic spectral acceleration that additionally takes into account both the second‐mode contribution to (elastic) structural response and the effects of inelasticity. This predictor is evaluated with respect to non‐linear dynamic analysis results for ‘fishbone’ models of steel moment‐resisting frame (SMRF) buildings. The relatively small number of degrees of freedom for each fishbone model allows us to consider several short‐to‐long period buildings and numerous near‐ and far‐field earthquake ground motions of interest in both Japan and the U.S. Before doing so, though, we verify that estimates of the bias and precision of the predictor obtained using fishbone models are effectively equivalent to those based on typical ‘full‐frame’ models of the same buildings. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献