scholarly journals An empirical model to estimate ultraviolet erythemal transmissivity

2009 ◽  
Vol 27 (4) ◽  
pp. 1387-1398 ◽  
Author(s):  
M. Antón ◽  
A. Serrano ◽  
M. L. Cancillo ◽  
J. A. García
Keyword(s):  
Empirical Model ◽  
Weather Conditions ◽  
Bias Error ◽  
Clearness Index ◽  
Uv Index ◽  
The Public ◽  
Independent Variables ◽  
Absolute Bias ◽  
Western Spain ◽  
Ozone Column

Abstract. An empirical model to estimate the solar ultraviolet erythemal irradiance (UVER) for all-weather conditions is presented. This model proposes a power expression with the UV transmissivity as a dependent variable, and the slant ozone column and the clearness index as independent variables. The UVER were measured at three stations in South-Western Spain during a five year period (2001–2005). A dataset corresponding to the period 2001–2004 was used to develop the model and an independent dataset (year 2005) for validation purposes. For all three locations, the empirical model explains more than 95% of UV transmissivity variability due to changes in the two independent variables. In addition, the coefficients of the models show that when the slant ozone amount decreases 1%, UV transmissivity and, therefore, UVER values increase approximately 1.33%–1.35%. The coefficients also show that when the clearness index decreases 1%, UV transmissivity increase 0.75%–0.78%. The validation of the model provided satisfactory results, with low mean absolute bias error (MABE), about 7%–8% for all stations. Finally, a one-day ahead forecast of the UV Index for cloud-free cases is presented, assuming the persistence in the total ozone column. The percentage of days with differences between forecast and experimental UVI lower than ±0.5 unit and ±1 unit is within the range of 28% to 37%, and 60% to 75%, respectively. Therefore, the empirical model proposed in this work provides reliable forecast cloud-free UVI in order to inform the public about the possible harmful effects of UV radiation over-exposure.

scholarly journals Adaptation of an empirical model for erythemal ultraviolet irradiance

2007 ◽  
Vol 25 (7) ◽  
pp. 1499-1508 ◽  
Author(s):  
I. Foyo-Moreno ◽  
I. Alados ◽  
L. Alados-Arboledas
Keyword(s):  
Empirical Model ◽  
Independent Set ◽  
Mean Bias Error ◽  
Bias Error ◽  
Data Set ◽  
Uv Index ◽  
Ultraviolet Irradiance ◽  
Sky Conditions ◽  
Mean Square Errors ◽  
Radiation Measurements

Abstract. In this work we adapt an empirical model to estimate ultraviolet erythemal irradiance (UVER) using experimental measurements carried out at seven stations in Spain during four years (2000–2003). The measurements were taken in the framework of the Spanish UVB radiometric network operated and maintained by the Spanish Meteorological Institute. The UVER observations are recorded as half hour average values. The model is valid for all-sky conditions, estimating UVER from the ozone columnar content and parameters usually registered in radiometric networks, such as global broadband hemispherical transmittance and optical air mass. One data set was used to develop the model and another independent set was used to validate it. The model provides satisfactory results, with low mean bias error (MBE) for all stations. In fact, MBEs are less than 4% and root mean square errors (RMSE) are below 18% (except for one location). The model has also been evaluated to estimate the UV index. The percentage of cases with differences of 0 UVI units is in the range of 61.1% to 72.0%, while the percentage of cases with differences of ±1 UVI unit covers the range of 95.6% to 99.2%. This result confirms the applicability of the model to estimate UVER irradiance and the UV index at those locations in the Iberian Peninsula where there are no UV radiation measurements.

scholarly journals Influence of turbidity and clouds on satellite total ozone data over Madrid (Spain)

2010 ◽  
Vol 28 (7) ◽  
pp. 1441-1448
Author(s):  
J. L. Camacho ◽  
M. Antón ◽  
D. Loyola ◽  
E. Hernandez
Keyword(s):  
Total Ozone ◽  
Retrieval Algorithm ◽  
Bias Error ◽  
Ozone Monitoring Instrument ◽  
Ozone Data ◽  
Absolute Bias ◽  
Ozone Monitoring ◽  
Smooth Dependence ◽  
Aerosol Index ◽  
Ozone Column

Abstract. This article focuses on the comparison of the total ozone column data from three satellite instruments; Total Ozone Mapping Spectrometers (TOMS) on board the Earth Probe (EP), Ozone Monitoring Instrument (OMI) on board AURA and Global Ozone Monitoring Experiment (GOME) on board ERS/2, with ground-based measurement recorded by a well calibrated Brewer spectrophotometer located in Madrid during the period 1996–2008. A cluster classification based on solar radiation (global, direct and diffuse), cloudiness and aerosol index allow selecting hazy, cloudy, very cloudy and clear days. Thus, the differences between Brewer and satellite total ozone data for each cluster have been analyzed. The accuracy of EP-TOMS total ozone data is affected by moderate cloudiness, showing a mean absolute bias error (MABE) of 2.0%. In addition, the turbidity also has a significant influence on EP-TOMS total ozone data with a MABE ~1.6%. Those data are in contrast with clear days with MABE ~1.2%. The total ozone data derived from the OMI instrument show clear bias at clear and hazy days with small uncertainties (~0.8%). Finally, the total ozone observations obtained with the GOME instrument show a very smooth dependence with respect to clouds and turbidity, showing a robust retrieval algorithm over these conditions.

Multiple regression analyses of midwinter fattening of the white-throated sparrow

1986 ◽  
Vol 64 (11) ◽  
pp. 2405-2411 ◽  
Author(s):  
Charles R. Blem ◽  
Michael H. Shelor
Keyword(s):  
Body Weight ◽  
Multiple Regression ◽  
Weather Conditions ◽  
Multiple Regression Model ◽  
Fine Tuning ◽  
Zonotrichia Albicollis ◽  
Independent Variables ◽  
Average Temperature ◽  
Extreme High Temperature

Midwinter lipid depots of the white-throated sparrow (Zonotrichia albicollis) at Richmond, Virginia, are correlated with a suite of environmental and morphological variables. Lipid reserves allow this species to survive even the most extreme winter conditions for several hours. Variables having the greatest individual correlations with lipid reserve are average temperature of the 20 days prior to capture, fat class, body weight, and long-term (32-year) average temperature of the date of capture. A comprehensive multiple regression model based on analyses of all possible independent variables accounts for 87% of the variation in lipid reserves. The most important independent variables in this model are body weight, mean temperature of the 20 days preceding collection, fat class, extreme high temperature of the day of capture, long-term average temperature, relative humidity, chill factor, wet-bulb temperatures of the day before and the day of capture, wing length, and precipitation. The "best" equation using only measurements of environment as independent variables included time of collection in hours after sunrise and hours before sunset, Eastern Standard Time, temperature of the 20 days prior to capture, and mean wind velocity of the day before capture. Models computed solely from temperature measurements included dry-bulb temperatures of the day of capture and the day before capture, low extreme temperatures of the day of capture, wet-bulb temperatures of the day before capture, and the 20-day average dry-bulb temperature of the period prior to collection. Fattening in response to weather conditions appears to be a form of "fine-tuning" of energy reserves superimposed on a more stable, intrinsic cycle of winter fattening.

Comparison of two gap-filling techniques for nitrous oxide fluxes from agricultural soil

2019 ◽  
Vol 99 (1) ◽  
pp. 12-24 ◽  
Author(s):  
Rezvan Taki ◽  
Claudia Wagner-Riddle ◽  
Gary Parkin ◽  
Rob Gordon ◽  
Andrew VanderZaag
Keyword(s):  
Missing Values ◽  
Interpolation Method ◽  
Weather Conditions ◽  
Linear Interpolation ◽  
Bias Error ◽  
Research Station ◽  
Ann Model ◽  
Gap Filling ◽  
Adverse Weather ◽  
The Impact

Micrometeorological methods are ideally suited for continuous measurements of N2O fluxes, but gaps in the time series occur due to low-turbulence conditions, power failures, and adverse weather conditions. Two gap-filling methods including linear interpolation and artificial neural networks (ANN) were utilized to reconstruct missing N2O flux data from a corn–soybean–wheat rotation and evaluate the impact on annual N2O emissions from 2001 to 2006 at the Elora Research Station, ON, Canada. The single-year ANN method is recommended because this method captured flux variability better than the linear interpolation method (average R2 of 0.41 vs. 0.34). Annual N2O emission and annual bias resulting from linear and single-year ANN were compatible with each other when there were few and short gaps (i.e., percentage of missing values <30%). However, with longer gaps (>20 d), the bias error in annual fluxes varied between 0.082 and 0.344 kg N2O-N ha−1 for linear and 0.069 and 0.109 kg N2O-N ha−1 for single-year ANN. Hence, the single-year ANN with lower annual bias and stable approach over various years is recommended, if the appropriate driving inputs (i.e., soil temperature, soil water content, precipitation, N mineral content, and snow depth) needed for the ANN model are available.

scholarly journals Possible values of UV index in Serbia

2008 ◽  
Vol 136 (11-12) ◽  
pp. 640-643 ◽  
Author(s):  
Milorad Letic
Keyword(s):  
Uv Radiation ◽  
The Sun ◽  
Total Column Ozone ◽  
Uv Index ◽  
Clear Sky ◽  
Expected Values ◽  
June July ◽  
Column Ozone ◽  
Ozone Column

INTRODUCTION UV Index is an indicator of human exposure to solar ultraviolet (UV) rays. The numerical values of the UV Index range from 1-11 and above. There are three levels of protection against UV radiation; low values of the UV Index - protection is not required, medium values of the UV Index - protection is recommended and high values of the UV Index - protection is obligatory. The value of the UV Index primarily depends on the elevation of the sun and total ozone column. OBJECTIVE The aim of the study is to determine the intervals of possible maximal annual values of the UV Index in Serbia in order to determine the necessary level of protection in a simple manner. METHOD For maximal and minimal expected values of total column ozone and for maximal elevation of the sun, the value of the UV Index was determined for each month in the Northern and Southern parts of Serbia. These values were compared with the forecast of the UV Index. RESULTS Maximal clear sky values of the UV Index in Serbia for altitudes up to 500m in May, June, July and August can be 9 or even 10, and not less than 5 or 6. During November, December, January and February the UV Index can be 4 at most. During March, April, September and October the expected values of the UV Index are maximally 7 and not less than 3. The forecast of the UV Index is within these limits in 98% of comparisons. CONCLUSION The described method of determination of possible UV Index values showed a high agreement with forecasts. The obtained results can be used for general recommendations in the protection against UV radiation.

scholarly journals Weather Literacy in Times of Climate Change

2020 ◽  
Vol 12 (3) ◽  
pp. 435-452 ◽  
Author(s):  
Nadine Fleischhut ◽  
Stefan M. Herzog ◽  
Ralph Hertwig
Keyword(s):  
Climate Change ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
The Public ◽  
Weather Events ◽  
The Future ◽  
Nationally Representative ◽  
And Migration ◽  
Weather Risks

AbstractAs climate change unfolds, extreme weather events are on the rise worldwide. According to experts, extreme weather risks already outrank those of terrorism and migration in likelihood and impact. But how well does the public understand weather risks and forecast uncertainty and thus grasp the amplified weather risks that climate change poses for the future? In a nationally representative survey (N = 1004; Germany), we tested the public’s weather literacy and awareness of climate change using 62 factual questions. Many respondents misjudged important weather risks (e.g., they were unaware that UV radiation can be higher under patchy cloud cover than on a cloudless day) and struggled to connect weather conditions to their impacts (e.g., they overestimated the distance to a thunderstorm). Most misinterpreted a probabilistic forecast deterministically, yet they strongly underestimated the uncertainty of deterministic forecasts. Respondents with higher weather literacy obtained weather information more often and spent more time outside but were not more educated. Those better informed about climate change were only slightly more weather literate. Overall, the public does not seem well equipped to anticipate weather risks in the here and now and may thus also fail to fully grasp what climate change implies for the future. These deficits in weather literacy highlight the need for impact forecasts that translate what the weather may be into what the weather may do and for transparent communication of uncertainty to the public. Boosting weather literacy may help to improve the public’s understanding of weather and climate change risks, thereby fostering informed decisions and mitigation support.

scholarly journals The Acceptance of Government Resource Planning System Using UTAUT 2

2021 ◽  
Vol 17 (1) ◽  
pp. 1-19
Author(s):  
Muhardi Saputra ◽  
Berlian Maulidya Izzati ◽  
Jannatul Rahmadiani
Keyword(s):  
Information System ◽  
Business Processes ◽  
Resource Planning ◽  
Planning System ◽  
Primary Data ◽  
West Java ◽  
The Public ◽  
Independent Variables ◽  
Independent Variable ◽  
The Relationship

Government Resource Planning (GRP) system is a solution for managing all the resources that exist in government, namely people, technology, and business processes in it. This study aims to analyses how the acceptance of the Service and Licensing Information System for the Public (SIMPATIK) in the Investment Board and Integrated Licensing (DPMPTSP) of West Java Province. This study uses UTAUT 2 model that consist of six independent variables and two dependant variables. The relationship between the independent variable and the dependent variable is moderated by age, gender, and experience variables. The data used are primary data obtained from distributing questionnaires online to 42 DPMPTSP employees that using SIMPATIK. The hypothesis was tested with the SmartPLS and SPSS applications. The results show from a total of 14 hypotheses there are 3 hypotheses that have a significant or acceptable effect, while 11 other hypotheses are not significant or cannot be accepted.

A Conceptual Model for the Measurement of E-Government 2.0 Adoption by Developing Countries

2015 ◽  
pp. 239-251
Author(s):  
Yfantis Vasileios ◽  
Abel Usoro ◽  
Tseles Dimitrios
Keyword(s):  
Information Technology ◽  
Developing Countries ◽  
Technology Acceptance ◽  
Conceptual Model ◽  
Empirical Model ◽  
Social Computing ◽  
Future Research ◽  
The Public ◽  
The Government ◽  
Acceptance Model

The current work explores the use of social computing as a tool to improve the interactions between the government and other parties. Social computing, which is known as Web 2.0, is applied in the public sector through the concept of e-Government 2.0. This chapter proposes a conceptual model that will measure e-Government 2.0 adoption by combining known information technology theories. The conceptual model is based on a combination of the Technology Acceptance Model, Theory of Planned Behavior and indexes from the United Nation's database. Future research should validate the empirical model. Meanwhile, the implications of the model are presented.

Appendix: A Brief Introduction to Analyzing Categorical Data and Finding More Data

2018 ◽  
pp. 302-326
Author(s):  
Quan Li
Keyword(s):  
Logistic Regression ◽  
Categorical Data ◽  
Public Domain ◽  
Statistical Independence ◽  
Discrete Variables ◽  
Short List ◽  
The Public ◽  
Independent Variables ◽  
Dichotomous Variable ◽  
Chi Squared

This chapter provides a brief introduction to two techniques often used with discrete data: testing statistical independence between two discrete variables with Chi-squared statistics, and testing the effects of some independent variables on the probability of a dependent variable taking on the value of one rather than zero with logistic regression. Both are illustrated by focusing on a dichotomous variable measuring self-reported happiness by survey respondents in World Value Surveys. In addition, the chapter also provides a short list of publicly available data resources that help to familiarize readers with the wealth of data in the public domain.

scholarly journals ANALISIS DETERMINAN EFEKTIVITAS AUDITOR INTERNAL PADA INSPEKTORAT PROVINSI DAERAH ISTIMEWA YOGYAKARTA

2016 ◽  
Vol 13 (2) ◽  
pp. 191
Author(s):  
Dea Nurfika Sari ◽  
Haryanto Haryanto
Keyword(s):  
Statistical Tests ◽  
Internal Audit ◽  
Primary Data ◽  
Internal Auditor ◽  
The Public ◽  
Independent Variables ◽  
External Auditor ◽  
Audit Activity ◽  
Audit Effectiveness ◽  
Special Region

The aims of this study is to examine factors that affect (determinants) internal audit effectiveness in the public sector, Inspectorate office at Province Special Region of Yogyakarta. This study is a replication of the research that has been done by Alzeban and Gwilliam in Saudi Arabia. There are 4 (four) independent variables that affect internal audit effectiveness as dependent variable. There are competence of internal auditor, the relationship between internal and external auditor, auditee support to internal audit activity, and independence of internal auditor. The population in this research is 51 internal auditor working in Inspectorate office at Province Special Region of Yogyakarta. This study uses primary data in the form of questionnaire. All of questionnaire can be processed. The datawere collected were processed using PLS analysis with SmartPLS 3 program. Statistical tests showed that three of four independent variables, there are the competence of the internal auditor, the auditee support and the independence of the internal auditor affect the effectiveness of the internal audit. while relationship between the internal auditor with the external auditor does not affect the internal audit effectiveness Keywords: Internal auditor effectiveness, competence of internal auditor, relationship between internal and external auditor, auditee support to internal audit activity, independence of internal auditor.

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