scholarly journals Performance of Alternative “Normals” for Tracking Climate Changes, Using Homogenized and Nonhomogenized Seasonal U.S. Surface Temperatures

2013 ◽  
Vol 52 (8) ◽  
pp. 1677-1687 ◽  
Author(s):  
Daniel S. Wilks ◽  
Robert E. Livezey
Keyword(s):  
Continuous Functions ◽  
Optimal Choice ◽  
Aggregated Data ◽  
Station Data ◽  
Specification Method ◽  
Historical Climatology ◽  
Single Method ◽  
Temperature Climate ◽  
Network Station ◽  
Climate Prediction Center

AbstractEleven alternatives to the annually updated 30-yr average for specifying climate “normals” are considered for the purpose of projecting nonstationarity in the mean U.S. temperature climate during 2006–12. Comparisons are made for homogenized U.S. Historical Climatology Network station data, corresponding nonhomogenized station data, and spatially aggregated (“megadivision”) data. The use of homogenized station data shows clear improvement over nonhomogenized station data and spatially aggregated data in terms of mean-squared specification errors on independent data. The best single method overall was the most recent 15-yr average as implemented by the Climate Prediction Center (CPC15), consistent with previous work using nonhomogenized and spatially aggregated data, although “hinge” functions with the change point fixed at 1975 performed well for the spring and summer seasons. A hybrid normals-specification method, using one of these piecewise continuous functions when the regressions are sufficiently strong and the CPC15 otherwise, exhibits a favorable trade-off between squared error and bias that may make it an optimal choice for some users.

scholarly journals An Assessment of High-Resolution Gridded Temperature Datasets over California

2018 ◽  
Vol 31 (10) ◽  
pp. 3789-3810 ◽  
Author(s):  
Daniel Walton ◽  
Alex Hall
Keyword(s):  
High Resolution ◽  
Complex Terrain ◽  
Dynamical Downscaling ◽  
Station Data ◽  
Daily Data ◽  
Historical Climatology ◽  
Systematic Biases ◽  
Global Historical Climatology Network ◽  
Lapse Rates ◽  
Physical Principles

Abstract High-resolution gridded datasets are in high demand because they are spatially complete and include important finescale details. Previous assessments have been limited to two to three gridded datasets or analyzed the datasets only at the station locations. Here, eight high-resolution gridded temperature datasets are assessed two ways: at the stations, by comparing with Global Historical Climatology Network–Daily data; and away from the stations, using physical principles. This assessment includes six station-based datasets, one interpolated reanalysis, and one dynamically downscaled reanalysis. California is used as a test domain because of its complex terrain and coastlines, features known to differentiate gridded datasets. As expected, climatologies of station-based datasets agree closely with station data. However, away from stations, spread in climatologies can exceed 6°C. Some station-based datasets are very likely biased near the coast and in complex terrain, due to inaccurate lapse rates. Many station-based datasets have large unphysical trends (>1°C decade−1) due to unhomogenized or missing station data—an issue that has been fixed in some datasets by using homogenization algorithms. Meanwhile, reanalysis-based gridded datasets have systematic biases relative to station data. Dynamically downscaled reanalysis has smaller biases than interpolated reanalysis, and has more realistic variability and trends. Dynamical downscaling also captures snow–albedo feedback, which station-based datasets miss. Overall, these results indicate that 1) gridded dataset choice can be a substantial source of uncertainty, and 2) some datasets are better suited for certain applications.

scholarly journals SC-Earth: A Station-based Serially Complete Earth Dataset from 1950 to 2019

2021 ◽  
pp. 1-47
Author(s):  
Guoqiang Tang ◽  
Martyn P. Clark ◽  
Simon Michael Papalexiou
Keyword(s):  
Missing Values ◽  
Meteorological Data ◽  
Oceanic Islands ◽  
Dew Point ◽  
Time Shift ◽  
Gap Filling ◽  
Quantile Mapping ◽  
Station Data ◽  
Historical Climatology ◽  
The Tropics

AbstractMeteorological data from ground stations suffer from temporal discontinuities caused by missing values and short measurement periods. Gap filling and reconstruction techniques have proven to be effective in producing serially complete station datasets (SCDs) that are used for a myriad of meteorological applications (e.g., developing gridded meteorological datasets and validating models). To our knowledge, all SCDs are developed at regional scales. In this study, we developed the serially complete Earth (SC-Earth) dataset, which provides daily precipitation, mean temperature, temperature range, dew-point temperature, and wind speed data from 1950 to 2019. SC-Earth utilizes raw station data from the Global Historical Climatology Network-Daily (GHCN-D) and the Global Surface Summary of the Day (GSOD). A unified station repository is generated based on GHCN-D and GSOD after station merging and strict quality control. ERA5 is optimally matched with station data considering the time shift issue and then used to assist the global gap filling. SC-Earth is generated by merging estimates from 15 strategies based on quantile mapping, spatial interpolation, machine learning, and multi-strategy merging. The final estimates are bias corrected using a combination of quantile mapping and quantile delta mapping. Comprehensive validation demonstrates that SC-Earth has high accuracy around the globe, with degraded quality in the tropics and oceanic islands due to sparse station networks, strong spatial precipitation gradients, and degraded ERA5 estimates. Meanwhile, SC-Earth inherits potential limitations such as inhomogeneity and precipitation undercatch from raw station data, which may affect its application in some cases. Overall, the high-quality and high-density SC-Earth dataset will benefit research in fields of hydrology, ecology, meteorology, and climate.

1151: The Medical-Expulsive Therapy for Distal Ureteral Stones: Which is the Optimal Choice?

2004 ◽  
Vol 171 (4S) ◽  
pp. 303-304 ◽  
Author(s):  
Marco Dellabella ◽  
Giulio Milanese ◽  
Giovanni Muzzonigro
Keyword(s):  
Optimal Choice ◽  
Ureteral Stones ◽  
Medical Expulsive Therapy

Idiographic Dynamics of Positive Affect in GAD

2020 ◽  
Vol 36 (3) ◽  
pp. 500-509
Author(s):  
Hannah G. Bosley ◽  
Devon B. Sandel ◽  
Aaron J. Fisher
Keyword(s):  
Positive Affect ◽  
Structural Equation ◽  
Alternative Hypothesis ◽  
Equation Model ◽  
Aggregated Data ◽  
Regulatory Strategy ◽  
Constant State ◽  
Automatic Search ◽  
Time Lagged ◽  
Exploratory Procedure

Abstract. Generalized anxiety disorder (GAD) is associated with worry and emotion regulation difficulties. The contrast-avoidance model suggests that individuals with GAD use worry to regulate emotion: by worrying, they maintain a constant state of negative affect (NA), avoiding a feared sudden shift into NA. We tested an extension of this model to positive affect (PA). During a week-long ecological momentary assessment (EMA) period, 96 undergraduates with a GAD analog provided four daily measurements of worry, dampening (i.e., PA suppression), and PA. We hypothesized a time-lagged mediation relationship in which higher worry predicts later dampening, and dampening predicts subsequently lower PA. A lag-2 structural equation model was fit to the group-aggregated data and to each individual time-series to test this hypothesis. Although worry and PA were negatively correlated in 87 participants, our model was not supported at the nomothetic level. However, idiographically, our model was well-fit for about a third (38.5%) of participants. We then used automatic search as an idiographic exploratory procedure to detect other time-lagged relationships between these constructs. While 46 individuals exhibited some cross-lagged relationships, no clear pattern emerged across participants. An alternative hypothesis about the speed of the relationship between variables is discussed using contemporaneous correlations of worry, dampening, and PA. Findings suggest heterogeneity in the function of worry as a regulatory strategy, and the importance of temporal scale for detection of time-lagged effects.

TBE in Latvia

2019 ◽  
Author(s):  
Dace Zavadska ◽  
Zane Odzelevica
Keyword(s):  
Serological Testing ◽  
Aggregated Data

Aggregated data on TBE cases in Latvia are available from 1955, but serological testing for TBE began in the 1970’s.

RELIABILITY CRITERIA FOR SATURATION ANALYSIS OF STEROIDS BY COMPETITIVE PROTEIN BINDING

1970 ◽  
Vol 65 (1_Suppl) ◽  
pp. S61-S78 ◽  
Author(s):  
Billy D. Reeves ◽  
David W. Calhoun
Keyword(s):  
Protein Binding ◽  
Assay Method ◽  
Statistical Control ◽  
Protein Binding Assay ◽  
Competitive Protein Binding Assay ◽  
System 2 ◽  
Competitive Protein Binding ◽  
Single Method ◽  
Assay Design ◽  
Proper Perspective

ABSTRACT This communication is an attempt to delineate and define reliability criteria for saturation analysis of steroids by competitive protein binding assay. The discussion of these criteria evolved from three major considerations of assay method that help to place the ultimate criterion of accuracy in proper perspective. These major considerations are: 1) the measurement system, 2) the assay design and 3) the calculations and statistical control. Such an approach permits an evaluation, both relative and absolute, for a single method or for multiple methods.

Approximation in statistical sense to B -continuous functions by positive linear operators

2010 ◽  
Vol 47 (3) ◽  
pp. 289-298 ◽  
Author(s):  
Fadime Dirik ◽  
Oktay Duman ◽  
Kamil Demirci
Keyword(s):  
Compact Subset ◽  
Real Line ◽  
Statistical Convergence ◽  
Approximation Theorem ◽  
Continuous Functions ◽  
Linear Operators ◽  
Positive Linear Operators ◽  
Statistical Approximation ◽  
Classical Version ◽  
Statistical Sense

In the present work, using the concept of A -statistical convergence for double real sequences, we obtain a statistical approximation theorem for sequences of positive linear operators defined on the space of all real valued B -continuous functions on a compact subset of the real line. Furthermore, we display an application which shows that our new result is stronger than its classical version.

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