scholarly journals Global Calibration and Error Estimation of Altimeter, Scatterometer, and Radiometer Wind Speed Using Triple Collocation

2020 ◽  
Vol 12 (12) ◽  
pp. 1997 ◽  
Author(s):  
Agustinus Ribal ◽  
Ian R. Young
Keyword(s):  
Wind Speed ◽  
Error Estimation ◽  
Major Axis ◽  
Statistical Parameters ◽  
Global Calibration ◽  
Error Standard Deviation ◽  
Standard Deviations ◽  
Reduced Major Axis ◽  
Buoy Data ◽  
Calibration Relations

The accuracy of wind speed measurements is important in many applications. In the present work, error standard deviations of wind speed measured by satellites and National Data Buoy Center (NDBC) buoys were estimated using triple collocation. The satellites included six altimeters, three scatterometers, and four radiometers. The six altimeters were TOPEX, ERS-2, JASON-1, ENVISAT, JASON-2, and CRYOSAT-2, whilst the three scatterometers were QUIKSCAT, METOP-A, and METOP-B and the four radiometers included SSMI-F15, AMSR-2, WINDSAT, and GMI. Hence, a total of 14 platform measurements, including NDBC buoy data, were used and the error standard deviations of each estimated. It was found that altimeters have the smallest error standard deviations for wind speed measurements followed by scatterometers and then radiometers. NDBC buoys have the largest error standard deviation. Since triple collocation can simultaneously perform error estimation as well as calibration for a given reference, this method enables us to perform intercalibration between platform measurements including NDBC buoy. In addition, the calibration relations obtained from triple collocation were compared with the calibrations obtained from the widely used reduced major axis (RMA) regression approach. This method, to some extent, can accommodate measurements in which both platforms contain errors. The results showed that calibration relations obtained from RMA and triple collocation are very similar, as indicated by statistical parameters such as RMSE, correlation coefficient, scatter index, and bias.

scholarly journals Calibration of scatterometer wind speed under hurricane conditions

2021 ◽  
Author(s):  
Agustinus Ribal ◽  
Ali Tamizi ◽  
Ian R. Young
Keyword(s):  
Wind Speed ◽  
Microwave Radiometer ◽  
Process Data ◽  
Calibration Process ◽  
Wind Speeds ◽  
Speed Range ◽  
Stepped Frequency ◽  
Spatio Temporal ◽  
Buoy Data ◽  
Calibration Relations

AbstractFour scatterometers, namely: METOP-A, METOP-B, ERS-2 and OCEANSAT-2 were re-calibrated against combined National Data Buoy Center (NDBC) data and aircraft Stepped Frequency Microwave Radiometer (SFMR) data from hurricanes. As a result, continuous calibration relations over the wind speed range 0 to 45 ms-1 were developed. The calibration process uses match-up criteria of 50 km and 30 min for the buoy data. However, due to the strong spatio-temporal wind speed gradients in hurricanes, a method which considers both scatterometer and SFMR data in a storm-centred translating frame of reference is adopted. The results show that although the scatterometer radar cross-section is degraded at high wind speeds, it is still possible to recover wind speed data using the re-calibration process. Data validation between the scatterometers shows that the calibration relations produce consistent results across all scatterometers and reduce the bias and root mean square error compared to previous calibrations. In addition, the results extend the useful range of scatterometer measurements to as high as 45 ms-1.

Estimation of response slopes in respiratory control

1984 ◽  
Vol 56 (2) ◽  
pp. 536-539 ◽  
Author(s):  
D. L. Sherrill ◽  
G. D. Swanson
Keyword(s):  
Statistical Approach ◽  
Ventilatory Response ◽  
Respiratory Control ◽  
Major Axis ◽  
Bivariate Normal Distribution ◽  
Directional Statistics ◽  
Control Behavior ◽  
Slope Estimate ◽  
Partial Pressure Of Co2 ◽  
Reduced Major Axis

The ventilatory response to changes in alveolar (arterial) CO2 is widely used as an index of respiratory control behavior. Methods for estimating these response slopes should incorporate the possibility that there may be errors in both the independent (partial pressure of CO2) and dependent (ventilation) variables. In a recent paper Daubenspeck and Ogden (J. Appl. Physiol. Respirat. Environ. Exercise Physiol. 45:823–829, 1978) have suggested problems inherent in the traditional technique of reduced major axis and have suggested a more contemporary technique of directional statistics. We have previously analyzed both techniques and developed a method to overcome the problems of reduced major axis and problems inherent in the use of directional statistics. Under the assumption of a bivariate normal distribution, we demonstrate that our slope estimate is similar to the maximum likelihood estimate proposed by Mardia et al. (J. Appl. Physiol.: Respirat. Environ. Exercise Physiol. 54: 309–313, 1983) for this problem. In addition, we demonstrate a bootstrap statistical approach when the distributions are not normally distributed. These concepts are illustrated using O2-CO2 interaction data.

scholarly journals METABOLIC SCALING REGULARITY IN AQUATIC ECOSYSTEMS

2012 ◽  
Vol 27 (2) ◽  
pp. 13
Author(s):  
L. A. Salcido -Guevara ◽  
F. Arreguín -Sánchez ◽  
L. Palmeri ◽  
A. Barausse
Keyword(s):  
Aquatic Ecosystems ◽  
Major Axis ◽  
Ecosystem Metabolism ◽  
Power Scaling ◽  
Metabolic Scaling ◽  
Relevant Role ◽  
Geographic Differences ◽  
Reduced Major Axis ◽  
Distribución Geográfica ◽  
Trophic Models

We tested the hypothesis that ecosystem metabolism follows a quarter power scaling relation, analogous to organisms. Logarithm of Biomass/Production (B/P) to Trophic Level (TL) relationship was estimated to 98 trophic models of aquatic ecosystems. A normal distribution of the slopes gives a modal value of 0.64, which was significantly different of the theoretical value of 0.75 (p0.05). We also tested for error in both variables, Log (B/P) and TL, through a Reduced Major Axis regression with similar results, with a modal value of 0.756 (p>0.05). We also explored a geographic distribution showing no significant relation (p>0.05) to latitude and between different regions of the world. We conclude that: a) ecosystem metabolism follows the quarter-power scaling rule; b) transfer efficiency between TL plays a relevant role characterizing local attributes to ecosystem metabolism; and c) there is neither latitudinal nor geographic differences. These findings confirm the existence of a metabolic scaling regularity in aquatic ecosystems. Regularidad del escalamiento metabólico en ecosistemas acuáticos Se contrastó la hipótesis de que el metabolismo de un ecosistema sigue una relación de escalamiento análoga a la existente en los organismos. La relación entre el logaritmo de la razón Producción/Biomasa (B/P) y el nivel trófico (TL) se estimó para 98 modelos tróficos de los ecosistemas acuáticos. Una distribución normal de las pendientes de esta relación produjo un valor modal de 0.64 que es significativamente diferente del valor teórico de 0.75 (p0.05) similar al teórico esperado. También se contrastó la hipótesis de existencia de error en ambas variables, logaritmo (B/P) y TL, a través de la técnica de regresión denominada “Reduced Major Axis”, con resultados similares según el valor modal de 0.756, sin diferencia estadísticamente significativa (p>0.05) del valor teórico. Se exploró la existencia de algún patrón en la distribución geográfica, sin obtenerse relación significativa (p>0.05) con la latitud, o con diferentes regiones del mundo. Las conclusiones son: a) el metabolismo del ecosistema sigue la regla de escalamiento metabólico de 3/4; b) la eficiencia de la transferencia entre TL desempeña un papel relevante, representando los atributos locales del metabolismo del ecosistema; c) no hay una diferencias latitudinal o geográfica. Estos resultados confirman la existencia de una regularidad en el escalamiento metabólico en ecosistemas acuáticos.

Extreme Gust Loading for Wind Turbines during Operation

2001 ◽  
Vol 123 (4) ◽  
pp. 356-363 ◽  
Author(s):  
P. W. Cheng ◽  
W. A. A. M. Bierbooms
Keyword(s):  
Wind Speed ◽  
Theoretical Method ◽  
Rational Approach ◽  
Reliable Estimate ◽  
International Electrotechnical Commission ◽  
Response Distribution ◽  
Statistical Parameters ◽  
Extreme Load ◽  
Mean Wind Speed ◽  
Gust Response

One of the extreme load cases treated in the wind turbine certification is the extreme gust loading during operation. In the certification codes, it is treated in a deterministic way. A method of generating stochastic extreme gusts that includes the turbulence properties of the wind is described in this paper. For the moment, only the horizontal along wind direction of the wind speed is considered. The stochastic gusts are used to determine the gust responses. The gust responses are processed together with the probability density of the gust amplitude and mean wind speed to obtain the gust response distribution. Different distribution types, namely Rayleigh, Weibull, and Gumbel distributions, are applied to fit the distribution of the extreme gust responses. The estimated distributions are analyzed with statistical methods to determine the required number of simulations to obtain a reliable estimate of the statistical parameters of the distribution. The resulting structural responses to the stochastic gusts are compared to the gust response to the extreme operating gust specified in the IEC (International Electrotechnical Commission) design standard. The results show that the extreme gust response can differ significantly depending on the control concept. The response of the deterministic gust proposed in the IEC design code can also deviate considerably from the response of the stochastic gust depending on the turbine configuration. The aim of this work is to provide a rational approach to determine the extreme gust response. This theoretical method has not yet been verified with extensive measurements.

scholarly journals On the Allometric Relationship Between Size and Composition of Avian Eggs: A Reassessment

The Condor ◽  
2007 ◽  
Vol 109 (3) ◽  
pp. 705-714 ◽  
Author(s):  
Todd W. Arnold ◽  
Andy J. Green
Keyword(s):  
Maternal Investment ◽  
Major Axis ◽  
Ordinary Least Squares ◽  
Egg Mass ◽  
Correlated Errors ◽  
Least Squares Regression ◽  
Inert Component ◽  
Female Component ◽  
Investment In Reproduction ◽  
Reduced Major Axis

AbstractAbstract. Numerous investigators have used allometric regression to characterize the relationship between proportional egg composition and egg size, which is a potentially important characterization for assessing maternal investment in reproduction. Herein, we document two important shortcomings of this approach. First, regressing log component mass against log egg mass involves regressing Y on itself, since each component (Y) is necessarily a part of the whole egg (X). This creates correlated errors, which leads to biased estimates of the regression slope. To circumvent this problem, we recommend regressing egg component masses on a relatively inert component like total water mass. Secondly, investigators routinely use ordinary least squares regression to estimate the slope of allometric relationships, which assumes that all error resides in Y. We demonstrate that this assumption is false, but so are the underlying error assumptions of commonly used alternatives such as reduced major axis and major axis regression. Because each egg is unique and determining composition involves destructive sampling, there is no obvious way to assess measurement error in Y versus X. As a solution, we recommend that investigators analyze multiple eggs per clutch whenever possible and fit a reduced major axis based on the among-female component of variability.

Calibration and Cross Validation of Global Ocean Wind Speed Based on Scatterometer Observations

2020 ◽  
Vol 37 (2) ◽  
pp. 279-297 ◽  
Author(s):  
Agustinus Ribal ◽  
Ian R. Young
Keyword(s):  
Wind Speed ◽  
Cross Validation ◽  
Regression Line ◽  
Total Duration ◽  
Global Ocean ◽  
High Wind ◽  
Wind Speeds ◽  
Buoy Data ◽  
Ocean Wind

AbstractGlobal ocean wind speed observed from seven different scatterometers, namely, ERS-1, ERS-2, QuikSCAT, MetOp-A, OceanSat-2, MetOp-B, and Rapid Scatterometer (RapidScat) were calibrated against National Data Buoy Center (NDBC) data to form a consistent long-term database of wind speed and direction. Each scatterometer was calibrated independently against NDBC buoy data and then cross validation between scatterometers was performed. The total duration of all scatterometer data is approximately 27 years, from 1992 until 2018. For calibration purposes, only buoys that are greater than 50 km offshore were used. Moreover, only scatterometer data within 50 km of the buoy and for which the overpass occurred within 30 min of the buoy recording data were considered as a “matchup.” To carry out the calibration, reduced major axis (RMA) regression has been applied where the regression minimizes the size of the triangle formed by the vertical and horizontal offsets of the data point from the regression line and the line itself. Differences between scatterometer and buoy data as a function of time were investigated for long-term stability. In addition, cross validation between scatterometers and independent altimeters was also performed for consistency. The performance of the scatterometers at high wind speeds was examined against buoy and platform measurements using quantile–quantile (Q–Q) plots. Where necessary, corrections were applied to ensure scatterometer data agreed with the in situ wind speed for high wind speeds. The resulting combined dataset is believed to be unique, representing the first long-duration multimission scatterometer dataset consistently calibrated, validated and quality controlled.

scholarly journals CONDUTIVIDADE ELÉTRICA DO EXTRATO DE SATURAÇÃO DO SOLO A PARTIR DE EXTRATOS 1:2 PELO MÉTODO DO EIXO PRINCIPAL REDUZIDO

Irriga ◽  
2005 ◽  
Vol 10 (4) ◽  
pp. 351-356
Author(s):  
Daniel Da Costa Dantas ◽  
José De Arimatea de Matos ◽  
José Francismar de Medeiros ◽  
Francisco De Queiroz Porto Filho ◽  
Neyton De Oliveira Miranda
Keyword(s):  
Electrical Conductivity ◽  
Linear Regression ◽  
Cucumis Melo ◽  
Major Axis ◽  
Soil Electrical Conductivity ◽  
Soil Extracts ◽  
Saturated Water ◽  
Different Depths ◽  
Reduced Major Axis ◽  
Soil And Water

CONDUTIVIDADE ELÉTRICA DO EXTRATO DE SATURAÇÃO DO SOLO A PARTIR DE EXTRATOS 1:2 PELO MÉTODO DO EIXO PRINCIPAL REDUZIDO  Daniel da Costa Dantas; José de Arimatea de Matos; José Francismar de Medeiros; Francisco de Queiroz Porto Filho; Neyton de Oliveira MirandaDepartamento de Ciências Ambientais, Universidade Federal Rural do Semi Árido, Mossoró, RN, [email protected]  1        RESUMO Com o objetivo de estimar a condutividade elétrica de extratos de saturação do solo (CEes) em função de extratos do solo 1:2 (CE1:2), procedeu-se o monitoramento da salinidade do solo em um experimento com melão irrigado com água de diferentes níveis de salinidade (S1 = 0,6; S2 = 1,9; S3 = 3,2 e S4 = 4,5 dS m-1), aplicada de forma incremental ao longo do ciclo. Coletaram-se amostras de solo para análise em três profundidades (0-15, 15-30 e 30-45 cm), durante dois ciclos de cultivo, aos 70 dias após a semeadura (DAS) no primeiro ciclo e aos 30 e 70 DAS no segundo. Determinou-se a CE1:2 e a CEes em amostras compostas, resultante de 15 tratamentos com três profundidades para cada tratamento. Os dados foram ajustados por profundidade e em conjunto, através de funções lineares de regressão e pelo método do eixo principal reduzido (EPR). A equação CEes = 8,094 CE1:2 + 0,0149 (R2 = 0,9112), desenvolvida através do eixo principal reduzido para todos os dados, apresentou nível de estimabilidade semelhante às equações obtidas para as diferentes profundidades e épocas e que a CE é inversamente proporcional a razão entre água:solo. UNITERMOS: Cucumis melo, salinidade.  DANTAS, D. da C.; MATOS, J. de. A. de; MEDEIROS, J. F. de; PORTO FILHO, F. de. Q.; MIRANDA, N. de. O.; ELECTRICAL CONDUCTIVITY OF SATURATED EXTRACTSDETERMINED BY THE REDUCED MAJOR AXIS METHOD USING MIXTURES OF SOIL AND WATER IN A 1:2 RATIO  2  ABSTRACT This experiment was carried out aiming to estimate electrical conductivity of saturated water soil extracts (CEes) using mixtures of soil and water in a 1:2 ratio (CE1:2). Soil salinity was monitored in a field where melon was irrigated with water which salinity level was increasing during the cycle (S1 = 0.6; S2 = 1.9; S3 = 3.2 and S4 = 4.5 dS m-¹). Samples were taken from two consecutive melon cycles at three depths (0-15, 15-30 and 30-45 cm). At 70 days after seeding (DAS) of the first cycle and at 30 and 70 DAS of the second CEes and CE1:2 were determined from compounded samples taken from 15 treatments with three depths each. Data were adjusted for all data and depth using linear regression and the reduced major axis method (RMA). The equation CEes = 8.094 CE1:2 + 0.0149 (R² = 0.9112) obtained using all data through RMA, showed a degree of predictability similar to the linear regression obtained for different depths and dates. Soil electrical conductivity was inversely correlated to the soil:water ratio. KEYWORDS: Cucumis melo, salinity

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