scholarly journals Sampling Errors in the Measurement of Rainfall Parameters Using the Precipitation Occurrence Sensor System (POSS)

2007 ◽  
Vol 24 (2) ◽  
pp. 125-140 ◽  
Author(s):  
B. E. Sheppard
Keyword(s):  
Doppler Radar ◽  
Statistical Significance ◽  
Time Estimation ◽  
Sensor System ◽  
Parameter Estimates ◽  
Problem Analysis ◽  
Sampling Errors ◽  
Precipitation Occurrence ◽  
Occurrence Type ◽  
Raindrop Size

Abstract The Precipitation Occurrence Sensor System (POSS) is a small Doppler radar originally designed by the Meteorological Service of Canada (MSC) to report the occurrence, type, and intensity of precipitation in automated observing stations. It is also used for real-time estimation of raindrop size distributions (DSDs). From the DSD, various rainfall parameters can be calculated and relationships established, such as between the radar reflectivity factor (Z) and the rainfall rate (R). Earlier work presented first-order estimates of the sampling errors for some POSS rainfall parameter estimates. This work combines a Monte Carlo simulation and “inverse problem” analysis to better estimate errors due to the specific sampling problems of this disdrometer type. The uncertainties are necessary to determine the statistical significance of differences between DSD estimates by the POSS and other collocated disdrometers, or between POSS measurements in different climatologies. Additionally, confidence limits can be assigned to regression coefficients for rainfall parameter relationships determined from POSS estimates. An example is given of the uncertainties in the coefficients of measured Z–R relationships.

Standard Asymptotic Theory

2017 ◽  
Author(s):  
Russell Cheng
Keyword(s):  
Asymptotic Theory ◽  
Asymptotic Variance ◽  
Statistical Significance ◽  
Regularity Conditions ◽  
Parameter Estimates ◽  
Asymptotic Results ◽  
Ml Estimation ◽  
True Parameter ◽  
Log Likelihood ◽  
Ml Estimator

This book relies on maximum likelihood (ML) estimation of parameters. Asymptotic theory assumes regularity conditions hold when the ML estimator is consistent. Typically an additional third derivative condition is assumed to ensure that the ML estimator is also asymptotically normally distributed. Standard asymptotic results that then hold are summarized in this chapter; for example, the asymptotic variance of the ML estimator is then given by the Fisher information formula, and the log-likelihood ratio, the Wald and the score statistics for testing the statistical significance of parameter estimates are all asymptotically equivalent. Also, the useful profile log-likelihood then behaves exactly as a standard log-likelihood only in a parameter space of just one dimension. Further, the model can be reparametrized to make it locally orthogonal in the neighbourhood of the true parameter value. The large exponential family of models is briefly reviewed where a unified set of regular conditions can be obtained.

Frequency distribution of Wuchereria bancrofti microfilariae in human populations and its relationships with age and sex

Parasitology ◽  
1990 ◽  
Vol 101 (3) ◽  
pp. 429-434 ◽  
Author(s):  
P. K. Das ◽  
A. Manoharan ◽  
A. Srividya ◽  
B. T. Grenfell ◽  
D. A. P. Bundy ◽  
...  
Keyword(s):  
Frequency Distribution ◽  
Negative Binomial ◽  
Age Distribution ◽  
Indirect Evidence ◽  
Wuchereria Bancrofti ◽  
Parameter Estimates ◽  
Human Populations ◽  
Sampling Errors ◽  
Frequency Distributions ◽  
Age And Sex

SUMMARYThis paper examines the effects of host age and sex on the frequency distribution of Wuchereria bancrofti infections in the human host. Microfilarial counts from a large data base on the epidemiology of bancroftian filariasis in Pondicherry, South India are analysed. Frequency distributions of microfilarial counts divided by age are successfully described by zero-truncated negative binomial distributions, fitted by maximum likelihood. Parameter estimates from the fits indicate a significant trend of decreasing overdispersion with age in the distributions above age 10; this pattern provides indirect evidence for the operation of density-dependent constraints on microfilarial intensity. The analysis also provides estimates of the proportion of mf-positive individuals who are identified as negative due to sampling errors (around 5% of the total negatives). This allows the construction of corrected mf age–prevalence curves, which indicate that the observed prevalence may underestimate the true figures by between 25% and 100%. The age distribution of mf-negative individuals in the population is discussed in terms of current hypotheses about the interaction between disease and infection.

scholarly journals Performance of the Precipitation Occurrence Sensor System as a Precipitation Gauge

2008 ◽  
Vol 25 (2) ◽  
pp. 196-212 ◽  
Author(s):  
B. E. Sheppard ◽  
P. I. Joe
Keyword(s):  
Interquartile Range ◽  
Sensor System ◽  
Precipitation Rate ◽  
Doppler Velocity ◽  
High Temporal Resolution ◽  
Velocity Spectrum ◽  
Ratio Distribution ◽  
Precipitation Occurrence ◽  
Solid Precipitation ◽  
Wide Range

Abstract The Precipitation Occurrence Sensor System (POSS) is a small X-band Doppler radar originally developed by the Meteorological Service of Canada for reporting the occurrence, type, and intensity of precipitation from Automated Weather Observing Stations. This study evaluates POSS as a gauge for measuring amounts of both liquid and solid precipitation. Different precipitation rate estimation algorithms are described. The effect of different solid precipitation types on the Doppler velocity spectrum is discussed. Lacking any accepted reference for high temporal resolution rates, the POSS precipitation rate measurements are integrated over time periods ranging from 6 h to one day and validated against international and Canadian reference gauges. Data from a wide range of sites across Canada and for periods of several years are used. The statistical performance of POSS is described in terms of the distribution of ratios of POSS to reference gauge amounts (catch ratios). In liquid precipitation the median of the catch ratio distribution is 82% and the interquartile range was between −12% and 19% about the median. In solid precipitation the median is 90% and the interquartile range is between −17% and 24% about the median. The underestimation in both liquid and solid precipitation is shown to be a function of precipitation rate and phase. The effects of radome wetting, raindrop splashing, wind, and the radar “brightband” effect on the estimation of precipitation rates are discussed.

Effect of sampling errors on efficiency of selection indices. 2. Use of information on associated traits for improvement of a single important trait

1976 ◽  
Vol 23 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Jill Sales ◽  
W. G. Hill
Keyword(s):  
Selection Index ◽  
Heritability Estimate ◽  
Parameter Estimates ◽  
Response To Selection ◽  
Sampling Errors ◽  
Estimation Of Parameters ◽  
Selection Indices ◽  
Important Trait ◽  
Selection For ◽  
Efficiency Of Selection

SUMMARYAn analysis is undertaken of the effect of errors in estimates of parameters on the response to selection for an economically important trait (trait 1) when one or more additional traits are added in a selection index. The detailed analysis is confined to one additional trait (trait 2) which contributes useful information unless the genetic and phenotypic regressions of trait 1 on trait 2 are equal.If there are errors in parameter estimates the extra response obtained by including trait 2 will usually be over-predicted. When trait 2 actually contributes no useful information the predicted benefit equals the real loss in efficiency from its inclusion.The loss in efficiency from poor estimation of parameters, whether or not the second trait makes a contribution, is roughly one-quarter of the squared coefficient of variation of a heritability estimate of trait 1 in the same experiment.

The Effects of Sampling Errors on the EnKF Assimilation of Inner-Core Hurricane Observations

2014 ◽  
Vol 142 (4) ◽  
pp. 1609-1630 ◽  
Author(s):  
Jonathan Poterjoy ◽  
Fuqing Zhang ◽  
Yonghui Weng
Keyword(s):  
Data Assimilation ◽  
Hurricane Katrina ◽  
Inner Core ◽  
Doppler Radar ◽  
Mesoscale Model ◽  
Outer Core ◽  
State Variables ◽  
Sampling Errors ◽  
Relaxation Coefficient ◽  
Airborne Doppler Radar

Abstract Atmospheric data assimilation methods that estimate flow-dependent forecast statistics from ensembles are sensitive to sampling errors. This sensitivity is investigated in the context of vortex-scale hurricane data assimilation by cycling an ensemble Kalman filter to assimilate observations with a convection-permitting mesoscale model. In a set of numerical experiments, airborne Doppler radar observations are assimilated for Hurricane Katrina (2005) using an ensemble size that ranges from 30 to 300 members, and a varying degree of covariance inflation through relaxation to the prior. The range of ensemble sizes is shown to produce variations in posterior storm structure that persist for days in deterministic forecasts, with the most substantial differences appearing in the vortex outer-core wind and pressure fields. Ensembles with 60 or more members converge toward similar axisymmetric and asymmetric inner-core solutions by the end of the cycling, while producing qualitatively similar sample correlations between the state variables. Though covariance relaxation has little impact on model variables far from the observations, the structure of the inner-core vortex can benefit from a more optimal tuning of the relaxation coefficient. Results from this study provide insight into how sampling errors may affect the performance of an ensemble hurricane data assimilation system during cycling.

scholarly journals Agricultural Economists' Effectiveness in Reporting and Conveying Research Procedures and Results

2000 ◽  
Vol 29 (2) ◽  
pp. 173-182 ◽  
Author(s):  
Joe L. Parcell ◽  
Terry L. Kastens ◽  
Kevin C. Dhuyvetter ◽  
Ted C. Schroeder
Keyword(s):  
Regression Analysis ◽  
Degrees Of Freedom ◽  
Statistical Significance ◽  
Resource Economics ◽  
Economic Importance ◽  
Parameter Estimates ◽  
Summary Statistics ◽  
Economic Significance ◽  
Fourth Report

This study reviews articles using regression analysis published in the Journal of Agricultural and Resource Economics from 1994 to 1998 to determine agricultural economists’ effectiveness in reporting and conveying research procedures and results. Based on the authors’ experiences of surveying articles for this study, several suggestions for reporting of results and how to better separate statistical from economic significance are offered. First, clearly define the dependent variable—preferably in the results table as well as within the text. Second, report parameter estimates in an interpretable form either in the results table or in a subsequent table. Third, report summary statistics. Fourth, report degrees of freedom conspicuously in the results table. Fifth, report if statistically insignificant variables have been dropped. Lastly, weigh economic importance aside from statistical significance and use simulation to express economic significance where appropriate.

Investigating the Temporal Instability in Injury Severity Outcomes of Clear and Adverse Weather Crashes on Rural Mountainous Highways

2021 ◽  
pp. 036119812110570
Author(s):  
Irfan U. Ahmed ◽  
Mohamed M. Ahmed
Keyword(s):  
Monte Carlo ◽  
Injury Severity ◽  
Statistical Significance ◽  
Weather Conditions ◽  
Warning Signs ◽  
Parameter Estimates ◽  
Connected Vehicle ◽  
Temporal Instability ◽  
Short Period ◽  
Adverse Weather

Analysis of driver injury severity based on weather conditions on rural highways is limited in the literature. Such analyses provide insights useful to policymakers in optimizing the allocation of limited resources based on weather conditions. Furthermore, if there is a possibility of factors exhibiting temporal instability, then an aggregate analysis can lead to erroneous allocation of funds. In this study, separate models for clear and adverse weather conditions were developed for each of the years from 2015 to 2019 using crash data from a rural mountainous highway corridor. A random-intercept Bayesian logistic approach was used to analyze the dichotomous injury severity response and capture the between-crash variance. An efficient Markov chain Monte Carlo sampling technique known as the No-U-Turn Hamiltonian Monte Carlo was employed to sample the posterior distributions of parameter estimates. Likelihood ratio tests provided statistical significance of the temporal instability and also the differences in driver injury severities resulting from clear and adverse weather crashes. While most of the variables demonstrated temporal instability, some factors exhibited temporal stability over a short period of time and only during clear weather conditions. Findings from the separate models suggest that there are major differences in both the combination and magnitude of the significant contributing factors. Implementation of confirmatory warning signs, variable message signs, connected vehicle technology, strict enforcements during different times and locations, and driver awareness programs have been recommended as suitable countermeasures. The findings and recommendations could potentially help in guiding the respective agencies in formulating injury severity mitigation policies and strategies.

Abstract 16673: Framingham Risk Trajectories Predict Left Ventricular Dyssynchrony as a Measure of Subclinical Myocardial Dysfunction: The Coronary Artery Risk Development in Young Adults (CARDIA) Study

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Ravi Sharma ◽  
Satoru Kishi ◽  
Bharath Ambale-Venkatesh ◽  
Laura Colangelo ◽  
Jared Reis ◽  
...  
Keyword(s):  
Cardiovascular Risk ◽  
Myocardial Dysfunction ◽  
Statistical Significance ◽  
Cumulative Risk ◽  
Left Ventricular ◽  
Left Ventricular Dyssynchrony ◽  
Parameter Estimates ◽  
Reference Trajectory ◽  
Lv Dyssynchrony ◽  
Framingham Risk

Background: Left ventricular (LV) dyssynchrony is a measure of myocardial dysfunction in heart failure patients. However, its significance as a marker of incipient myocardial dysfunction in response to cumulative risk burden among asymptomatic individuals is not known. Our objective was to evaluate the extent of LV dyssynchrony in relationship to longitudinal changes in cardiovascular risk in otherwise healthy middle age individuals. Methods & Results: We defined five distinct Framingham risk score (FRS, D’Agostino Circulation 2008) (excluding age) trajectories in the CARDIA cohort (n=4634) to estimate the pattern of cumulative cardiovascular risk exposure over 25 year. Standard deviation of time to peak systolic circumferential strain (SD-TPS) among 6 mid-ventricular segments using 2-dimensional speckle-tracking echocardiography determined the extent of LV dyssynchrony in 2718 participant (54.3% women). Using multivariate linear regression after adjustment for demographics and LV ejection fraction, we found that among women in comparison to the low-stablegroup (reference trajectory), increased burden of cardiovascular risk was associated with progressively higher values of SD-TPS; B-coefficients were 3.50msec (95%CI, 0.23 - 6.77, p=0.04) for the moderate-stable, 7.32msec (2.56 - 12.09, p=0.003) for the elevated-stable, 8.79msec (3.49 - 14.10, p=0.001) for the moderate-increasing, and 9.54msec (0.09 - 18.99, p=0.048) for the elevated-increasing groups. There was attenuation of parameter estimates after further adjustment for cumulative body-mass-index (BMI) with loss of statistical significance. These associations were not statistically significant in men. Conclusions: Women had higher values of subclinical LV dyssynchrony in response to incremental cumulative cardiovascular risk burden over 25 years. Such relationships were absent in men. Cumulative BMI was the strongest predictor of LV dyssynchrony.

Clarifying remotely-retrieved precipitation of shallow marine clouds from the NSF/NCAR Gulfstream V

2021 ◽  
Author(s):  
Mampi Sarkar ◽  
Paquita Zuidema ◽  
Virendra Ghate
Keyword(s):  
Doppler Radar ◽  
Rain Attenuation ◽  
Doppler Velocity ◽  
Distribution Width ◽  
Raindrop Size Distribution ◽  
Remote Measurements ◽  
Raindrop Size ◽  
Rain Rates ◽  
The Impact

AbstractPrecipitation is a key process within the shallow cloud lifecycle. The Cloud System Evolution in the Trades (CSET) campaign included the first deployment of a 94 GHz Doppler radar and 532 nm lidar. Despite a larger sampling volume, initial mean radar/lidar retrieved rain rates (Schwartz et al. 2019) based on the upward-pointing remote sensor datasets are systematically less than those measured by in-situ precipitation probes in the cumulus regime. Subsequent retrieval improvements produce rainrates that compare better to in-situ values, but still underestimate. Retrieved shallow cumulus drop sizes can remain too small and too few, with an overestimated shape parameter narrowing the raindrop size distribution too much. Three potential causes for the discrepancy are explored: the gamma functional fit to the dropsize distribution, attenuation by rain and cloud water, and an underaccounting of Mie dampening of the reflectivity. A truncated exponential fit may represent the dropsizes below a showering cumulus cloud more realistically, although further work would be needed to fully evaluate the impact of a different dropsize representation upon the retrieval. The rain attenuation is within the measurement uncertainty of the radar. Mie dampening of the reflectivity is shown to be significant, in contrast to previous stratocumulus campaigns with lighter rain rates, and may be difficult to constrain well with the remote measurements. An alternative approach combines an a priori determination of the dropsize distribution width based on the in-situ data with the mean radar Doppler velocity and reflectivity. This can produce realistic retrievals, although a more comprehensive assessment is needed to better characterize the retrieval errors.

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