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Full-Text Articles in Physical Sciences and Mathematics
Geostatistical Analysis Of An Experimental Stratigraphy, Y Zhang, M Person, C Paola, C W. Gable, X H. Wen, J M. Davis
Geostatistical Analysis Of An Experimental Stratigraphy, Y Zhang, M Person, C Paola, C W. Gable, X H. Wen, J M. Davis
Earth Sciences
[1] A high-resolution stratigraphic image of a flume-generated deposit was scaled up to sedimentary basin dimensions where a natural log hydraulic conductivity (ln( K)) was assigned to each pixel on the basis of gray scale and conductivity end-members. The synthetic ln( K) map has mean, variance, and frequency distributions that are comparable to a natural alluvial fan deposit. A geostatistical analysis was conducted on selected regions of this map containing fluvial, fluvial/ floodplain, shoreline, turbidite, and deepwater sedimentary facies. Experimental ln(K) variograms were computed along the major and minor statistical axes and horizontal and vertical coordinate axes. Exponential and power …
Effects Of Uncertainty In Climate Inputs On Simulated Evapotranspiration And Runoff In The Western Arctic, Michael A. Rawlins, Steve Frolking, Richard B. Lammers, Charles Vorosmarty
Effects Of Uncertainty In Climate Inputs On Simulated Evapotranspiration And Runoff In The Western Arctic, Michael A. Rawlins, Steve Frolking, Richard B. Lammers, Charles Vorosmarty
Earth Sciences
Hydrological models require accurate precipitation and air temperature inputs in order to adequately depict water fluxes and storages across Arctic regions. Biases such as gauge undercatch, as well as uncertainties in numerical weather prediction reanalysis data that propagate through water budget models, limit the ability to accurately model the terrestrial arctic water cycle. A hydrological model forced with three climate datasets and three methods of estimating potential evapotranspiration (PET) was used to better understand the impact of these processes on simulated water fluxes across the Western Arctic Linkage Experiment (WALE) domain. Climate data were drawn from the NCEP–NCAR reanalysis (NNR) …
Maximum A Posteriori Resampling Of Noisy, Spatially Correlated Data, John A. Goff, Chris Jenkins, Brian R. Calder
Maximum A Posteriori Resampling Of Noisy, Spatially Correlated Data, John A. Goff, Chris Jenkins, Brian R. Calder
Center for Coastal and Ocean Mapping
In any geologic application, noisy data are sources of consternation for researchers, inhibiting interpretability and marring images with unsightly and unrealistic artifacts. Filtering is the typical solution to dealing with noisy data. However, filtering commonly suffers from ad hoc (i.e., uncalibrated, ungoverned) application. We present here an alternative to filtering: a newly developed method for correcting noise in data by finding the “best” value given available information. The motivating rationale is that data points that are close to each other in space cannot differ by “too much,” where “too much” is governed by the field covariance. Data with large uncertainties …
Statistical Uncertainty Of Eddy Flux–Based Estimates Of Gross Ecosystem Carbon Exchange At Howland Forest, Maine, Stephen Hagen, Rob Braswell, Ernst Linder, Steve Frolking, Andrew D. Richardson, David Y. Hollinger
Statistical Uncertainty Of Eddy Flux–Based Estimates Of Gross Ecosystem Carbon Exchange At Howland Forest, Maine, Stephen Hagen, Rob Braswell, Ernst Linder, Steve Frolking, Andrew D. Richardson, David Y. Hollinger
Earth Sciences
We present an uncertainty analysis of gross ecosystem carbon exchange (GEE) estimates derived from 7 years of continuous eddy covariance measurements of forest-atmosphere CO2fluxes at Howland Forest, Maine, USA. These data, which have high temporal resolution, can be used to validate process modeling analyses, remote sensing assessments, and field surveys. However, separation of tower-based net ecosystem exchange (NEE) into its components (respiration losses and photosynthetic uptake) requires at least one application of a model, which is usually a regression model fitted to nighttime data and extrapolated for all daytime intervals. In addition, the existence of a significant amount …