scholarly journals CO<sub>2</sub> column-averaged volume mixing ratio derived over Tsukuba from measurements by commercial airlines

2010 ◽  
Vol 10 (16) ◽  
pp. 7659-7667 ◽  
Author(s):  
M. Araki ◽  
I. Morino ◽  
T. Machida ◽  
Y. Sawa ◽  
H. Matsueda ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Standard Deviation ◽  
Ancillary Data ◽  
Climatological Data ◽  
Mixing Ratios ◽  
Clear Sky ◽  
Least Squares Fit ◽  
Small Uncertainty ◽  
Using Data ◽  
Co2 Profile

Abstract. Column-averaged volume mixing ratios of carbon dioxide (XCO2) during the period from January 2007 to May 2008 over Tsukuba, Japan, were derived using CO2 concentrations measured by Continuous CO2 Measuring Equipment (CME). The CMEs were installed on Japan Airlines Corporation (JAL) commercial airliners, which frequently fly to and from Narita Airport. It was assumed that CO2 profiles over Tsukuba and Narita are the same. CO2 profile data for 493 flights on clear-sky days were analyzed in order to calculate XCO2 with one of two ancillary datasets: "Tsukuba observational" data (rawinsonde and meteorological tower), or "global" forecast/reanalysis and climatological data (NCEP and CIRA-86). The amplitude of the seasonal variation of XCO2 using the ancillary data measured in Tsukuba (XCO2 (Tsukuba observational)) was determined by a least squares fit using a harmonic function to roughly evaluate the seasonal variation over Tsukuba. The highest and lowest values of the obtained fitted curve in 2007 for XCO2 (Tsukuba observational) were 386.4 ± 1.0 and 381.7 ± 1.0 ppm in May and September, respectively, where the errors represent 1 standard deviation of the fit residuals. The dependence of XCO2 on the type of ancillary dataset was evaluated. The average difference between XCO2 from global climatological data, XCO2 (global), and XCO2 (Tsukuba observational), i.e., the bias of XCO2 (global) based on XCO2 (Tsukuba observational), was found to be −0.621 ppm with a standard deviation of 0.682 ppm. The uncertainty of XCO2 (global) based on XCO2 (Tsukuba observational) was estimated to be 0.922 ppm. This small uncertainty relative to the GOSAT precision suggests that calculating XCO2 using data from airliners and global climatological data can be applied to the validation of GOSAT products for XCO2 over airports worldwide.

scholarly journals CO<sub>2</sub> column-averaged volume mixing ratio derived over Tsukuba from measurements by commercial airlines

2010 ◽  
Vol 10 (2) ◽  
pp. 3401-3421 ◽  
Author(s):  
M. Araki ◽  
I. Morino ◽  
T. Machida ◽  
Y. Sawa ◽  
H. Matsueda ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Observational Data ◽  
Meteorological Data ◽  
Co2 Concentration ◽  
Concentration Data ◽  
Climatological Data ◽  
Mixing Ratios ◽  
Least Squares Fit ◽  
Small Uncertainty ◽  
Using Data

Abstract. Column-averaged volume mixing ratios of carbon dioxide (XCO2) during the period from January 2007 to May 2008 over Tsukuba, Japan, were derived by using CO2 concentration data observed by Japan Airlines Corporation (JAL) commercial airliners, based on the assumption that CO2 profiles over Tsukuba and Narita were the same. CO2 profile data for 493 flights on clear-sky days were analysed in order to calculate XCO2 with an ancillary dataset: Tsukuba observational data (by rawinsonde and a meteorological tower) or global meteorological data (NCEP and CIRA-86). The amplitude of seasonal variation of XCO2 (Tsukuba observational) from the Tsukuba observational data was determined by least-squares fit using a harmonic function to roughly evaluate the seasonal variation over Tsukuba. The highest and lowest values of the obtained fitted curve in 2007 for XCO2 (Tsukuba observational) were 386.4 and 381.7 ppm in May and September, respectively. The dependence of XCO2 on the type of ancillary dataset was evaluated. The average difference between XCO2 (global) from global climatological data and XCO2 (Tsukuba observational), i.e., the bias of XCO2 (global) based on XCO2 (Tsukuba observational), was found to be -0.621 ppm with a standard deviation of 0.682 ppm. The uncertainty of XCO2 (global) based on XCO2 (Tsukuba observational) was estimated to be 0.922 ppm. This small uncertainty suggests that the present method of XCO2 calculation using data from airliners and global climatological data can be applied to the validation of GOSAT products for XCO2 over airports worldwide.

scholarly journals Modification of Summertime Arctic Cloud Characteristics between a Coastal and Inland Site

2006 ◽  
Vol 19 (13) ◽  
pp. 3207-3219 ◽  
Author(s):  
J. C. Doran ◽  
J. C. Barnard ◽  
W. J. Shaw
Keyword(s):  
Heat Fluxes ◽  
North Slope ◽  
Coastal Site ◽  
Mixing Ratios ◽  
Clear Sky ◽  
The North ◽  
Cloud Characteristics ◽  
North Slope Of Alaska ◽  
Using Data ◽  
Microwave Radiometers

Abstract Cloud characteristics at two sites on the North Slope of Alaska separated by ∼100 km have been examined for the warmer months of 2001–03 using data collected from microwave radiometers, ceilometers, rotating shadowband radiometers, and pyranometers. Clouds at the inland site, Atqasuk, were found to have approximately 26% greater optical depths than those at the coastal site, Barrow, and the ratio of measured irradiance to clear-sky irradiance was nearly 20% larger at Barrow under cloudy conditions. It is hypothesized that a significant factor contributing to these differences is the upward fluxes of heat and water vapor over the wet tundra and lakes. Support for this hypothesis is found from the behavior of the liquid water paths for low clouds, which tend to be higher at Atqasuk than at Barrow for onshore winds but not for offshore ones, from differences in sensible heat fluxes, which are small but significant over the tundra but are nearly zero over the ocean adjacent to Barrow, and from the mixing ratios, which are significantly higher at Atqasuk than at Barrow. Results from a simple model further indicate that latent heat fluxes over the tundra and lakes can account for a significant fraction of the differences in the estimated boundary layer water content between Barrow and Atqasuk.

On the sensibility of the Pairs Trading strategy: the case of the FTS stock market index

2020 ◽  
Vol 38 (3) ◽  
Author(s):  
Ainhoa Fernández-Pérez ◽  
María de las Nieves López-García ◽  
José Pedro Ramos Requena
Keyword(s):  
Standard Deviation ◽  
Stock Market ◽  
Trading Strategy ◽  
Stock Market Index ◽  
Pairs Trading ◽  
Empirical Application ◽  
Statistical Arbitrage ◽  
Market Index ◽  
Standard Deviations ◽  
Using Data

In this paper we present a non-conventional statistical arbitrage technique based in varying the number of standard deviations used to carry the trading strategy. We will show how values of 1 and 1,2 in the standard deviation provide better results that the classic strategy of Gatev et al (2006). An empirical application is performance using data of the FST100 index during the period 2010 to June 2019.

scholarly journals A Precise Benchmark for Cluster Scaling Relations: Fundamental Plane, Mass Plane and IMF in the Coma Cluster from Dynamical Models

2020 ◽  
Author(s):  
Shravan Shetty ◽  
Michele Cappellari ◽  
Richard M McDermid ◽  
Davor Krajnović ◽  
P T de Zeeuw ◽  
...  
Keyword(s):  
Galaxy Formation ◽  
Scaling Relations ◽  
Coma Cluster ◽  
Dynamical Models ◽  
Fundamental Plane ◽  
Cluster Galaxies ◽  
Dynamical Scaling ◽  
Small Uncertainty ◽  
Cluster Distance ◽  
Using Data

Abstract We study a sample of 148 early-type galaxies in the Coma cluster using SDSS photometry and spectra, and calibrate our results using detailed dynamical models for a subset of these galaxies, to create a precise benchmark for dynamical scaling relations in high-density environments. For these galaxies, we successfully measured global galaxy properties, modeled stellar populations, and created dynamical models, and support the results using detailed dynamical models of 16 galaxies, including the two most massive cluster galaxies, using data taken with the SAURON IFU. By design, the study provides minimal scatter in derived scaling relations due to the small uncertainty in the relative distances of galaxies compared to the cluster distance. Our results demonstrate low (≤55% for 90th percentile) dark matter fractions in the inner 1Re of galaxies. Owing to the study design, we produce the tightest, to our knowledge, IMF-σe relation of galaxies, with a slope consistent with that seen in local galaxies. Leveraging our dynamical models, we transform the classical Fundamental Plane of the galaxies to the Mass Plane. We find that the coefficients of the mass plane are close to predictions from the virial theorem, and have significantly lower scatter compared to the Fundamental plane. We show that Coma galaxies occupy similar locations in the (M* - Re) and (M* - σe) relations as local field galaxies but are older. This, and the fact we find only three slow rotators in the cluster, is consistent with the scenario of hierarchical galaxy formation and expectations of the kinematic morphology-density relation.

scholarly journals MAX-DOAS observations of aerosols, formaldehyde and nitrogen dioxide in the Beijing area: comparison of two profile retrieval approaches

2015 ◽  
Vol 8 (2) ◽  
pp. 941-963 ◽  
Author(s):  
T. Vlemmix ◽  
F. Hendrick ◽  
G. Pinardi ◽  
I. De Smedt ◽  
C. Fayt ◽  
...  
Keyword(s):  
Standard Deviation ◽  
A Priori ◽  
Systematic Bias ◽  
Aerosol Extinction ◽  
Data Set ◽  
Near Surface ◽  
Beijing Area ◽  
Least Squares Fit ◽  
Relative Differences ◽  
Good Agreement

Abstract. A 4-year data set of MAX-DOAS observations in the Beijing area (2008–2012) is analysed with a focus on NO2, HCHO and aerosols. Two very different retrieval methods are applied. Method A describes the tropospheric profile with 13 layers and makes use of the optimal estimation method. Method B uses 2–4 parameters to describe the tropospheric profile and an inversion based on a least-squares fit. For each constituent (NO2, HCHO and aerosols) the retrieval outcomes are compared in terms of tropospheric column densities, surface concentrations and "characteristic profile heights" (i.e. the height below which 75% of the vertically integrated tropospheric column density resides). We find best agreement between the two methods for tropospheric NO2 column densities, with a standard deviation of relative differences below 10%, a correlation of 0.99 and a linear regression with a slope of 1.03. For tropospheric HCHO column densities we find a similar slope, but also a systematic bias of almost 10% which is likely related to differences in profile height. Aerosol optical depths (AODs) retrieved with method B are 20% high compared to method A. They are more in agreement with AERONET measurements, which are on average only 5% lower, however with considerable relative differences (standard deviation ~ 25%). With respect to near-surface volume mixing ratios and aerosol extinction we find considerably larger relative differences: 10 ± 30, −23 ± 28 and −8 ± 33% for aerosols, HCHO and NO2 respectively. The frequency distributions of these near-surface concentrations show however a quite good agreement, and this indicates that near-surface concentrations derived from MAX-DOAS are certainly useful in a climatological sense. A major difference between the two methods is the dynamic range of retrieved characteristic profile heights which is larger for method B than for method A. This effect is most pronounced for HCHO, where retrieved profile shapes with method A are very close to the a priori, and moderate for NO2 and aerosol extinction which on average show quite good agreement for characteristic profile heights below 1.5 km. One of the main advantages of method A is the stability, even under suboptimal conditions (e.g. in the presence of clouds). Method B is generally more unstable and this explains probably a substantial part of the quite large relative differences between the two methods. However, despite a relatively low precision for individual profile retrievals it appears as if seasonally averaged profile heights retrieved with method B are less biased towards a priori assumptions than those retrieved with method A. This gives confidence in the result obtained with method B, namely that aerosol extinction profiles tend on average to be higher than NO2 profiles in spring and summer, whereas they seem on average to be of the same height in winter, a result which is especially relevant in relation to the validation of satellite retrievals.

scholarly journals Comparison of Radiative Energy Flows in Observational Datasets and Climate Modeling

2016 ◽  
Vol 55 (1) ◽  
pp. 93-117 ◽  
Author(s):  
Ehrhard Raschke ◽  
Stefan Kinne ◽  
William B. Rossow ◽  
Paul W. Stackhouse ◽  
Martin Wild
Keyword(s):  
Climate Modeling ◽  
Radiative Flux ◽  
Radiative Energy ◽  
Trade Wind ◽  
Radiative Effects ◽  
Ancillary Data ◽  
Global Modeling ◽  
Lower Altitude ◽  
Clear Sky ◽  
Cloud Radiative Effects

AbstractThis study examines radiative flux distributions and local spread of values from three major observational datasets (CERES, ISCCP, and SRB) and compares them with results from climate modeling (CMIP3). Examinations of the spread and differences also differentiate among contributions from cloudy and clear-sky conditions. The spread among observational datasets is in large part caused by noncloud ancillary data. Average differences of at least 10 W m−2 each for clear-sky downward solar, upward solar, and upward infrared fluxes at the surface demonstrate via spatial difference patterns major differences in assumptions for atmospheric aerosol, solar surface albedo and surface temperature, and/or emittance in observational datasets. At the top of the atmosphere (TOA), observational datasets are less influenced by the ancillary data errors than at the surface. Comparisons of spatial radiative flux distributions at the TOA between observations and climate modeling indicate large deficiencies in the strength and distribution of model-simulated cloud radiative effects. Differences are largest for lower-altitude clouds over low-latitude oceans. Global modeling simulates stronger cloud radiative effects (CRE) by +30 W m−2 over trade wind cumulus regions, yet smaller CRE by about −30 W m−2 over (smaller in area) stratocumulus regions. At the surface, climate modeling simulates on average about 15 W m−2 smaller radiative net flux imbalances, as if climate modeling underestimates latent heat release (and precipitation). Relative to observational datasets, simulated surface net fluxes are particularly lower over oceanic trade wind regions (where global modeling tends to overestimate the radiative impact of clouds). Still, with the uncertainty in noncloud ancillary data, observational data do not establish a reliable reference.

scholarly journals An assessment of the quality indicators of operative and non-operative times in a public university hospital

2015 ◽  
Vol 13 (4) ◽  
pp. 594-599 ◽  
Author(s):  
Altair da Silva Costa Jr ◽  
Luiz Eduardo Villaça Leão ◽  
Maykon Anderson Pires de Novais ◽  
Paola Zucchi
Keyword(s):  
Standard Deviation ◽  
Operating Room ◽  
Operative Time ◽  
Patient Flow ◽  
Cross Sectional Study ◽  
Public University ◽  
Major Effect ◽  
University Hospital ◽  
Cross Sectional ◽  
Using Data

ABSTRACT Objective To assess the operative time indicators in a public university hospital. Methods A descriptive cross-sectional study was conducted using data from operating room database. The sample was obtained from January 2011 to January 2012. The operations performed in sequence in the same operating room, between 7:00 am and 5:00 pm, elective or emergency, were included. The procedures with incomplete data in the system were excluded, as well as the operations performed after 5:00 pm or on weekends or holidays. Results We measured the operative and non-operative time of 8,420 operations. The operative time (mean and standard deviation) of anesthesias and operations were 177.6±110 and 129.8±97.1 minutes, respectively. The total time of the patient in operative room (mean and standard deviation) was 196.8±113.2. The non-operative time, e.g., between the arrival of the patient and the onset of anesthesia was 14.3±17.3 minutes. The time to set the next patient in operating room was 119.8±79.6 minutes. Our total non-operative time was 155 minutes. Conclusion Delays frequently occurred in our operating room and had a major effect on patient flow and resource utilization. The non-operative time was longer than the operative time. It is possible to increase the operating room capacity by management and training of the professionals involved. The indicators provided a tool to improve operating room efficiency.

scholarly journals Seasonal variations of triple oxygen isotopic compositions of atmospheric sulfate, nitrate and ozone at Dumont d'Urville, coastal Antarctica

2016 ◽  
Author(s):  
Sakiko Ishino ◽  
Shohei Hattori ◽  
Joel Savarino ◽  
Bruno Jourdain ◽  
Susanne Preunkert ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Ice Cores ◽  
Oxidative Capacity ◽  
So2 Oxidation ◽  
Mixing Ratios ◽  
Isotopic Compositions ◽  
Oxygen Isotopic ◽  
Low Sensitivity ◽  
Complex Chemistry ◽  
Oxidation Chemistry

Abstract. Reconstruction of the oxidative capacity of the atmosphere is of great importance to understanding climate change, because of its key role in determining the life times of trace gases. Triple oxygen isotopic compositions (Δ17O = δ17O − 0.52 × δ18O) of atmospheric sulfate (SO42−) and nitrate (NO3−) in the Antarctic ice cores have shown potential as stable proxies, because they reflect the oxidation chemistry involved in their formation processes. However, observations of Δ17O values of SO42−, NO3− and ozone in the present-day Antarctic atmosphere are very limited, and their complex chemistry is not fully understood in this region. We present the first simultaneous measurement of Δ17O values of atmospheric sulfate, nitrate, and ozone collected at Dumont d'Urville station (66°40' S, 140°01' E) throughout 2011. Δ17O values of sulfate and nitrate exhibited seasonal variation characterized by summer minima and winter maxima, within the ranges of 0.9–3.4 ‰ and 23.0–41.9 ‰, respectively. In contrast, Δ17O values of ozone showed no significant seasonal variation, with values of 26 ± 1 ‰ through the year. These contrasting seasonal trends suggest that Δ17O(O3) is not the major factor determining seasonal changes in Δ17O(SO42−) and Δ17O(NO3−) values. The summer/winter trends for Δ17O(SO42−) and Δ17O(NO3−) values are caused by sunlight-driven changes in O3/ROX ratios, which decrease in summer through ozone destruction and photo-oxidants production, resulting in co-variation between ozone mixing ratios and Δ17O(SO42−) and Δ17O(NO3−) values. However, despite similar ranges of ozone mixing ratios in spring (September to November) and fall (March to May), Δ17O(SO42−) values observed in spring were lower than in fall. The relatively low sensitivity of Δ17O(SO42−) values to the ozone mixing ratio in spring is possibly explained by (i) lower O3/ROX ratios caused by NOX emission from snowpack and/or (ii) SO2 oxidation by hypohalous acids (HOX = HOCl + HOBr) in the aqueous phase.

89. Seasonal Variation of the Percentage Butterfat Content of Milk. An Examination of the Results of Certain Individual Cow Tests

1935 ◽  
Vol 6 (1) ◽  
pp. 1-5 ◽  
Author(s):  
C. D. Oxley
Keyword(s):  
Seasonal Variation ◽  
Standard Deviation ◽  
Seasonal Variability ◽  
Milk Samples ◽  
Sources Of Error ◽  
The Mean ◽  
Morning Milk

Figures showing the means and the standard deviation of butterfat percentage of milk samples, at the afternoon and morning milkings res-pectively, during the four quarters of the year are presented.The probable sources of error due to the nature of the sample are discussed and the seasonal variability of mean and of standard deviation is considered.The likelihood of the mean of afternoon or of morning milk failing to reach certain specified minima during the respective seasons is calculated.

A Wind Wave Co-Cumulative Spectral Model

1970 ◽  
Vol 14 (04) ◽  
pp. 277-295
Author(s):  
Carl F. Kottler
Keyword(s):  
Standard Deviation ◽  
Least Squares ◽  
Wind Velocity ◽  
Wind Wave ◽  
Surface Wind ◽  
Systematic Investigation ◽  
Spectral Model ◽  
Least Squares Fit ◽  
Wind Sea ◽  
Cumulative Model

A systematic investigation was made of the parameters chosen to define the Pierson-Moskowitz wind sea spectral model. The model was generalized and the form was extended to give a better fit of the data. Using the same sets of data as those selected by Pierson and Moskowitz for building their model, a least-squares fit of each set of the co-cumulative data gave a corresponding optimum set of parameters. These unique optimum sets of parameters yielded an eightfold decrease in the standard deviation. From this family of parameter sets, a co-cumulative spectral model was. developed to fix some of the parameters and relate the others to surface wind velocity. This modification and extension show that at least a twofold improvement in accuracy over the associated Pierson-Moskowitz co-cumulative model can be achieved.

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