scholarly journals A new uncertainty estimation technique for multiple datasets and its application to various precipitation products

2019 ◽  
Author(s):  
Xudong Zhou ◽  
Jan Polcher ◽  
Tao Yang ◽  
Ching-Sheng Huang
Keyword(s):  
Three Dimensional ◽  
Uncertainty Assessment ◽  
Temporal Variations ◽  
Variance Partitioning ◽  
Uncertainty Estimation ◽  
Comprehensive Assessment ◽  
Estimation Technique ◽  
Multiple Datasets ◽  
Uncertainty Estimates ◽  
Temporal And Spatial

Abstract. The uncertainty among climatological datasets can be characterized as the variance in space and time between various estimates of the same quantity. However, some of the current uncertainty estimates only evaluate variations in one single dimension (time or space) due to the limitation of estimation methodology as averaging variation is necessary for the other dimension. The influence on the uncertainty assessment of the ignorance of variations in one dimension is not well studied. This study introduces a new three-dimensional variance partitioning approach which avoids the averaging and provides an new uncertainty estimation (Ue) technique with consideration of both temporal and spatial variations. Comparisons of Ue to classic uncertainty estimations show that the classic metrics underestimate the uncertainty because of the averaging of variation in the time or space dimension, and Ue is around 20 % higher than classic estimations. The deviation between the new and classic metrics is higher for regions with strong spatial heterogeneity and where the spatial and temporal variations significantly differ. Decomposing of the new metric demonstrates that Ue is a comprehensive assessment of model uncertainty which has been included the model variations identified by the classic metrics. Multiple precipitation products of different types (gauge-based, merged products and GCMs) are used to better explain and understand the peculiarity of the new methodology. The new uncertainty estimation technique is flexible in its structure and particularly suitable for a comprehensive assessment of multiple datasets over a large regions within any given period.

scholarly journals A new uncertainty estimation approach with multiple datasets and implementation for various precipitation products

2020 ◽  
Vol 24 (4) ◽  
pp. 2061-2081 ◽  
Author(s):  
Xudong Zhou ◽  
Jan Polcher ◽  
Tao Yang ◽  
Ching-Sheng Huang
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Scales ◽  
Three Dimensional ◽  
Variance Partitioning ◽  
Uncertainty Estimation ◽  
The Other ◽  
New Approach ◽  
Multiple Datasets ◽  
Uncertainty Estimates ◽  
Spatiotemporal Scales

Abstract. Ensemble estimates based on multiple datasets are frequently applied once many datasets are available for the same climatic variable. An uncertainty estimate based on the difference between the ensemble datasets is always provided along with the ensemble mean estimate to show to what extent the ensemble members are consistent with each other. However, one fundamental flaw of classic uncertainty estimates is that only the uncertainty in one dimension (either the temporal variability or the spatial heterogeneity) can be considered, whereas the variation along the other dimension is dismissed due to limitations in algorithms for classic uncertainty estimates, resulting in an incomplete assessment of the uncertainties. This study introduces a three-dimensional variance partitioning approach and proposes a new uncertainty estimation (Ue) that includes the data uncertainties in both spatiotemporal scales. The new approach avoids pre-averaging in either of the spatiotemporal dimensions and, as a result, the Ue estimate is around 20 % higher than the classic uncertainty metrics. The deviation of Ue from the classic metrics is apparent for regions with strong spatial heterogeneity and where the variations significantly differ in temporal and spatial scales. This shows that classic metrics underestimate the uncertainty through averaging, which means a loss of information in the variations across spatiotemporal scales. Decomposing the formula for Ue shows that Ue has integrated four different variations across the ensemble dataset members, while only two of the components are represented in the classic uncertainty estimates. This analysis of the decomposition explains the correlation as well as the differences between the newly proposed Ue and the two classic uncertainty metrics. The new approach is implemented and analysed with multiple precipitation products of different types (e.g. gauge-based products, merged products and GCMs) which contain different sources of uncertainties with different magnitudes. Ue of the gauge-based precipitation products is the smallest, while Ue of the other products is generally larger because other uncertainty sources are included and the constraints of the observations are not as strong as in gauge-based products. This new three-dimensional approach is flexible in its structure and particularly suitable for a comprehensive assessment of multiple datasets over large regions within any given period.

Flow Past a Spinning Sphere With Surface Blowing and Heat Transfer

2005 ◽  
Vol 127 (1) ◽  
pp. 163-171 ◽  
Author(s):  
H. Niazmand ◽  
M. Renksizbulut
Keyword(s):  
Heat Transfer ◽  
Three Dimensional ◽  
Flow Regimes ◽  
Solid Sphere ◽  
Temporal Variations ◽  
Transfer Coefficients ◽  
Transfer Rates ◽  
Particle Spin ◽  
Flow Past ◽  
Angular Velocities

Computations are performed to determine the transient three-dimensional heat transfer rates and fluid forces acting on a stream-wise spinning sphere for Reynolds numbers in the range 10⩽Re⩽300 and angular velocities Ωx⩽2. In this Re range, classical flow past a solid sphere develops four different flow regimes, and the effects of particle spin are studied in each regime. Furthermore, the combined effects of particle spin and surface blowing are examined. Sphere spin increases drag in all flow regimes, while lift shows a nonmonotonic behavior. Heat transfer rates are not influenced by spin up to a certain Ωx but increase monotonically thereafter. An interesting feature associated with sphere spin is the development of a special wake regime such that the wake simply spins without temporal variations in its shape. For this flow condition, the magnitudes of the lift, drag, and heat transfer coefficients remain constant in time. Correlations are provided for drag and heat transfer.

Uncertainty Estimation for Magnetic Maps

2021 ◽  
Author(s):  
Richard Saltus ◽  
Arnaud Chulliat ◽  
Brian Meyer ◽  
Christopher Amante
Keyword(s):  
Local Level ◽  
Uncertainty Estimation ◽  
Measured Data ◽  
Magnetic Minerals ◽  
Geochemical Environment ◽  
The Earth ◽  
Uncertainty Estimates ◽  
Wide Range ◽  
Machine Learning Applications ◽  
Map Data

<p>Magnetic maps depict spatial variations in the Earth’s magnetic field.  These variations occur at a wide range of scales and are produced via a variety of physical processes related to factors including structure and evolution of the Earth’s core field and the geologic distribution of magnetic minerals in the lithosphere.  Mankind has produced magnetic maps for 100’s of years with increasing fidelity and accuracy and there is a general understanding (particularly among the geophysicists who produce and use these maps) of the approximate level of resolution and accuracy of these maps.  However, few magnetic maps, or the digital grids that typically underpin these maps, have been produced with accompanying uncertainty quantification.  When uncertainty is addressed, it is typically a statistical representation at the grid or survey level (e.g., +- 10 nT overall uncertainty based on line crossings for a modern airborne survey) and not at the cell by cell local level.</p><p>As magnetic map data are increasingly used in complex inversions and in combination with other data or constraints (including in machine learning applications), it is increasingly important to have a handle on the uncertainties in these data.  An example of an application with need for detailed uncertainty estimation is the use of magnetic map information for alternative navigation.  In this application data from an onboard magnetometer is compared with previously mapped (or modeled) magnetic variations.  The uncertainty of this previously mapped information has immediate implications for the potential accuracy of navigation.</p><p>We are exploring the factors contributing to magnetic map uncertainty and producing uncertainty estimates for testing using new data collection in previously mapped (or modeled) map areas.  These factors include (but are likely not limited to) vintage and type of measured data, spatial distribution of measured data, expectation of magnetic variability (e.g., geologic or geochemical environment), statistics of redundant measurement, and spatial scale/resolution of the magnetic map or model.  The purpose of this talk is to discuss the overall issue and our initial results and solicit feedback and ideas from the interpretation community.</p>

Transient Analysis of Nonuniform Heat Input Propagation Through a Heat Sink Base

2017 ◽  
Vol 139 (2) ◽  
Author(s):  
Srivathsan Sudhakar ◽  
Justin A. Weibel
Keyword(s):  
Heat Source ◽  
Heat Input ◽  
Heat Sink ◽  
Three Dimensional ◽  
Temperature Response ◽  
Flow Distribution ◽  
Temporal Variations ◽  
Step Response ◽  
Dimensional System ◽  
Two Phase

For thermal management architectures wherein the heat sink is embedded close to a dynamic heat source, nonuniformities may propagate through the heat sink base to the coolant. Available transient models predict the effective heat spreading resistance to calculate chip temperature rise, or simplify to a representative axisymmetric geometry. The coolant-side temperature response is seldom considered, despite the potential influence on flow distribution and stability in two-phase microchannel heat sinks. This study solves three-dimensional transient heat conduction in a Cartesian chip-on-substrate geometry to predict spatial and temporal variations of temperature on the coolant side. The solution for the unit step response of the three-dimensional system is extended to any arbitrary temporal heat input using Duhamel's method. For time-periodic heat inputs, the steady-periodic solution is calculated using the method of complex temperature. As an example case, the solution of the coolant-side temperature response in the presence of different transient heat inputs from multiple heat sources is demonstrated. To represent a case where the thermal spreading from a heat source is localized, the problem is simplified to a single heat source at the center of the domain. Metrics are developed to quantify the degree of spatial and temporal nonuniformity in the coolant-side temperature profiles. These nonuniformities are mapped as a function of nondimensional geometric parameters and boundary conditions. Several case studies are presented to demonstrate the utility of such maps.

Temporal variations in bedload transport rates and sediment storage in gravel-bed rivers

1992 ◽  
Vol 16 (3) ◽  
pp. 319-338 ◽  
Author(s):  
Trevor Hoey
Keyword(s):  
Three Dimensional ◽  
Temporal Variations ◽  
Sampling Interval ◽  
Bedload Transport ◽  
Sediment Storage ◽  
Data Set ◽  
Gravel Bed ◽  
Wide Range ◽  
Gravel Bed Rivers ◽  
Bed Waves

Temporal variability in bedload transport rates and spatial variability in sediment storage have been reported with increasing frequency in recent years. A spatial and temporal classification for these features is suggested based on the gravel bedform classification of Church and Jones (1982). The identified scales, meso-, macro-, and mega- are each broad, and within each there is a wide range of processes acting to produce bedload fluctuations. Sampling the same data set with different sampling intervals yields a near linear relationship between sampling interval and pulse period. A range of modelling strategies has been applied to bed waves. The most successful have been those which allow for the three-dimensional nature of sediment storage processes, and which allow changes in the width and depth of stored sediment. The existence of bed waves makes equilibrium in gravel-bed rivers necessarily dynamic. Bedload pulses and bed waves can be regarded as equilibrium forms at sufficiently long timescales.

Impact of a strong temperature gradient on grain growth in films

2021 ◽  
Author(s):  
Dana Zöllner
Keyword(s):  
Temperature Gradient ◽  
Grain Growth ◽  
Annealing Temperature ◽  
Three Dimensional ◽  
Drag Effect ◽  
Temperature Changes ◽  
Grain Boundary Mobility ◽  
Microstructural Coarsening ◽  
Temporal And Spatial ◽  
Model Algorithm

Abstract The migration of grain boundaries and, therewith, the phenomenon of grain growth depend strongly on the annealing temperature. Generally, higher temperatures are associated with higher mobilities of the boundaries and therewith faster microstructural coarsening. In the present study, the influence of a strong temperature gradient on grain growth in thin films is investigated. To that aim, a modified three-dimensional Potts model algorithm is employed, where the annealing temperature changes with the thickness of the sample taking grain boundary mobility and energy into account. The resulting drag effect has serious consequences for the temporal and spatial evolution of the grain microstructure.

scholarly journals Temporal and spatial variations in freeze warnings in the conterminous United States: 2005–2018

2019 ◽  
Vol 139 (3-4) ◽  
pp. 1379-1384
Author(s):  
Brandon Lawhorn ◽  
Robert C. Balling
Keyword(s):  
United States ◽  
Temporal Trends ◽  
The United States ◽  
Temporal Variations ◽  
Atmospheric Composition ◽  
Southeastern Us ◽  
The Us ◽  
Temporal And Spatial ◽  
Frost Free Period ◽  
Spatial And Temporal Trends

AbstractIt is well-documented that the United States (US), along with other mid-latitude land locations, has experienced warming in recent decades in response to changes in atmospheric composition. Among other changes, Easterling (2002) reported that the frost-free period is now longer across much of the US with the first frost in fall occurring later and the last freeze in spring occurring earlier. In this investigation, we explore spatial and temporal variations in all freeze warnings issued by the US National Weather Service. Freeze warning counts are highest in the southeastern US peaking overall in the spring and fall months. Freeze warnings tend to occur more toward summer moving northward and westward into more northerly states. Consistent with the warming in recent decades, we find statistically significant northward movements in freeze warning centroids in some months (December, February) across the study period (2005–2018). Detection of spatial and temporal trends in freeze warnings may be of interest to any number of scientists with applied climatological interests.

scholarly journals Analysis of temporal and spatial variability of atmospheric CO<sub>2</sub> concentration within Paris from the GreenLITE™ laser imaging experiment

2019 ◽  
Vol 19 (22) ◽  
pp. 13809-13825 ◽  
Author(s):  
Jinghui Lian ◽  
François-Marie Bréon ◽  
Grégoire Broquet ◽  
T. Scott Zaccheo ◽  
Jeremy Dobler ◽  
...  
Keyword(s):  
Urban Canopy ◽  
Temporal Variations ◽  
Horizontal Resolution ◽  
Atmospheric Co2 ◽  
Laser Imaging ◽  
Near Surface ◽  
Co2 Concentrations ◽  
Temporal And Spatial ◽  
The City

Abstract. In 2015, the Greenhouse gas Laser Imaging Tomography Experiment (GreenLITE™) measurement system was deployed for a long-duration experiment in the center of Paris, France. The system measures near-surface atmospheric CO2 concentrations integrated along 30 horizontal chords ranging in length from 2.3 to 5.2 km and covering an area of 25 km2 over the complex urban environment. In this study, we use this observing system together with six conventional in situ point measurements and the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and two urban canopy schemes (Urban Canopy Model – UCM; Building Effect Parameterization – BEP) at a horizontal resolution of 1 km to analyze the temporal and spatial variations in CO2 concentrations within the city of Paris and its vicinity for the 1-year period spanning December 2015 to November 2016. Such an analysis aims at supporting the development of CO2 atmospheric inversion systems at the city scale. Results show that both urban canopy schemes in the WRF-Chem model are capable of reproducing the seasonal cycle and most of the synoptic variations in the atmospheric CO2 point measurements over the suburban areas as well as the general corresponding spatial differences in CO2 concentration that span the urban area. However, within the city, there are larger discrepancies between the observations and the model results with very distinct features during winter and summer. During winter, the GreenLITE™ measurements clearly demonstrate that one urban canopy scheme (BEP) provides a much better description of temporal variations and horizontal differences in CO2 concentrations than the other (UCM) does. During summer, much larger CO2 horizontal differences are indicated by the GreenLITE™ system than both the in situ measurements and the model results, with systematic east–west variations.

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