scholarly journals Retrieval of Atmospheric and Cloud Property Anomalies and Their Trend from Temporally and Spatially Averaged Infrared Spectra Observed from Space

2014 ◽  
Vol 27 (12) ◽  
pp. 4403-4420 ◽  
Author(s):  
Seiji Kato ◽  
Fred G. Rose ◽  
Xu Liu ◽  
Bruce A. Wielicki ◽  
Martin G. Mlynczak
Keyword(s):  
Standard Deviation ◽  
Confidence Interval ◽  
Spectral Radiance ◽  
True Temperature ◽  
Retrieval Error ◽  
Cloud Property ◽  
Clear Sky ◽  
Temperature And Humidity ◽  
Sky Radiance ◽  
The Difference

Abstract A surface, atmospheric, and cloud (fraction, height, optical thickness, and particle size) property anomaly retrieval from highly averaged longwave spectral radiances is simulated using 28 years of reanalysis. Instantaneous nadir-view spectral radiances observed from an instrument on a 90° inclination polar orbit are computed. Spectral radiance changes caused by surface, atmospheric, and cloud property perturbations are also computed and used for the retrieval. This study’s objectives are 1) to investigate whether or not separating clear sky from cloudy sky reduces the retrieval error and 2) to estimate the error in a trend of retrieved properties. This simulation differs from earlier studies in that annual 10° latitude zonal cloud and atmospheric property anomalies defined as the deviation from 28-yr climatological means are retrieved instead of the difference of these properties from two time periods. The root-mean-square (RMS) difference of temperature and humidity anomalies retrieved from all-sky radiance anomalies is similar to the RMS difference derived from clear-sky radiance anomalies computed by removing clouds. This indicates that the cloud property anomaly retrieval error does not affect the retrieved temperature and humidity anomalies. When retrieval errors are nearly random, the error in the trend of retrieved properties is small. Approximately 30% of 10° latitude zones meet conditions that the true temperature and water vapor amount trends are within a 95% confidence interval of retrieved trends, and that the standard deviation of retrieved anomalies σret is within 20% of the standard deviation of true anomalies σn. If σret/σn − 1 is within ±0.2, 91% of the true trends fall within the 95% confidence interval of the corresponding retrieved trend.

scholarly journals Evaluating the Absolute Calibration Accuracy and Stability of AIRS Using the CMC SST

2020 ◽  
Vol 12 (17) ◽  
pp. 2743
Author(s):  
Hartmut H. Aumann ◽  
Steven E. Broberg ◽  
Evan M. Manning ◽  
Thomas S. Pagano ◽  
Robert C. Wilson
Keyword(s):  
Time Series ◽  
Standard Deviation ◽  
Absolute Calibration ◽  
Atmospheric Infrared Sounder ◽  
Clear Sky ◽  
Tropical Oceans ◽  
Atmospheric Window ◽  
Surface Skin Temperature ◽  
Calibration Accuracy ◽  
The Difference

We compare the daily mean and standard deviation of the difference between the sea surface skin temperature (SST) derived from clear sky Atmospheric InfraRed Sounder (AIRS) data from seven atmospheric window channels between 2002 and 2020 and collocated Canadian Meteorological Centre (CMC) SST data from the tropical oceans. After correcting the mean difference for cloud contamination and diurnal effects, the remaining bias relative to the CMC SST, is reasonably consistent with estimates of the AIRS absolute accuracy based on the uncertainty of the pre-launch calibration. The time series of the bias produces trends well below the 10 mK/yr level required for climate change evaluations. The trends are in the 2 mK/yr range for the five window channels between 790 and 1231 cm−1, and +5 mK/yr for the shortwave channels. Between 2002 and 2020, the time series of the standard deviation of the difference between the AIRS SST and the CMC SST dropped fairly steadily to below 0.4 K in several AIRS window channels, a level previously only seen in gridded SST products relative to the Argo buoys.

scholarly journals Variability of the Boundary Layer Over an Urban Continental Site Based on 10 Years of Active Remote Sensing Observations in Warsaw

2020 ◽  
Vol 12 (2) ◽  
pp. 340 ◽  
Author(s):  
Dongxiang Wang ◽  
Iwona S. Stachlewska ◽  
Xiaoquan Song ◽  
Birgit Heese ◽  
Anca Nemuc
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Standard Deviation ◽  
Diurnal Cycle ◽  
Log P ◽  
Transform Method ◽  
Boundary Layer Height ◽  
Clear Sky ◽  
The Difference ◽  
Good Agreement

Atmospheric boundary layer height (ABLH) was observed by the CHM15k ceilometer (January 2008 to October 2013) and the PollyXT lidar (July 2013 to December 2018) over the European Aerosol Research LIdar NETwork to Establish an Aerosol Climatology (EARLINET) site at the Remote Sensing Laboratory (RS-Lab) in Warsaw, Poland. Out of a maximum number of 4017 observational days within this period, a subset of quasi-continuous measurements conducted with these instruments at the same wavelength (1064 nm) was carefully chosen. This provided a data sample of 1841 diurnal cycle ABLH observations. The ABLHs were derived from ceilometer and lidar signals using the wavelet covariance transform method (WCT), gradient method (GDT), and standard deviation method (STD). For comparisons, the rawinsondes of the World Meteorological Organization (WMO 12374 site in Legionowo, 25 km distance to the RS-Lab) were used. The ABLHs derived from rawinsondes by the skew-T-log-p method and the bulk Richardson (bulk-Ri) method had a linear correlation coefficient (R2) of 0.9 and standard deviation (SD) of 0.32 km. A comparison of the ABLHs obtained for different methods and instruments indicated a relatively good agreement. The ABLHs estimated from the rawinsondes with the bulk-Ri method had the highest correlations, R2 of 0.80 and 0.70 with the ABLHs determined using the WCT method on ceilometer and lidar signals, respectively. The three methods applied to the simultaneous, collocated lidar, and ceilometer observations (July to October 2013) showed good agreement, especially for the WCT method (R2 of 0.94, SD of 0.19 km). A scaling threshold-based algorithm was proposed to homogenize ceilometer and lidar datasets, which were applied on the lidar data, and significantly improved the coherence of the results (R2 of 0.98, SD of 0.11 km). The difference of ABLH between clear-sky and cloudy conditions was on average below 230 m for the ceilometer and below 70 m for the lidar retrievals. The statistical analysis of the long-term observations indicated that the monthly mean ABLHs varied throughout the year between 0.6 and 1.8 km. The seasonal mean ABLH was of 1.16 ± 0.16 km in spring, 1.34 ± 0.15 km in summer, 0.99 ± 0.11 km in autumn, and 0.73 ± 0.08 km in winter. In spring and summer, the daytime and nighttime ABLHs appeared mainly in a frequency distribution range of 0.6 to 1.0 km. In winter, the distribution was common between 0.2 and 0.6 km. In autumn, it was relatively balanced between 0.2 and 1.2 km. The annual mean ABLHs maintained between 0.77 and 1.16 km, whereby the mean heights of the well-mixed, residual, and nocturnal layer were 1.14 ± 0.11, 1.27 ± 0.09, and 0.71 ± 0.06 km, respectively (for clear-sky conditions). For the whole observation period, the ABLHs below 1 km constituted more than 60% of the retrievals. A strong seasonal change of the monthly mean ABLH diurnal cycle was evident; a mild weakly defined autumn diurnal cycle, followed by a somewhat flat winter diurnal cycle, then a sharp transition to a spring diurnal cycle, and a high bell-like summer diurnal cycle. A prolonged summertime was manifested by the September cycle being more similar to the summer than autumn cycles.

scholarly journals A new method for the absolute radiance calibration for UV–vis measurements of scattered sunlight

2015 ◽  
Vol 8 (10) ◽  
pp. 4265-4280 ◽  
Author(s):  
T. Wagner ◽  
S. Beirle ◽  
S. Dörner ◽  
M. Penning de Vries ◽  
J. Remmers ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Calibration Method ◽  
Spectral Radiance ◽  
Optical Absorption Spectroscopy ◽  
Light Sources ◽  
Clear Sky ◽  
Calibration Methods ◽  
Small Uncertainty ◽  
Sky Radiance ◽  
Spectrally Resolved

Abstract. Absolute radiometric calibrations are important for measurements of the atmospheric spectral radiance. Such measurements can be used to determine actinic fluxes, the properties of aerosols and clouds, and the shortwave energy budget. Conventional calibration methods in the laboratory are based on calibrated light sources and reflectors and are expensive, time consuming and subject to relatively large uncertainties. Also, the calibrated instruments might change during transport from the laboratory to the measurement sites. Here we present a new calibration method for UV–vis instruments that measure the spectrally resolved sky radiance, for example zenith sky differential optical absorption spectroscopy (DOAS) instruments or multi-axis (MAX)-DOAS instruments. Our method is based on the comparison of the solar zenith angle dependence of the measured zenith sky radiance with radiative transfer simulations. For the application of our method, clear-sky measurements during periods with almost constant aerosol optical depth are needed. The radiative transfer simulations have to take polarisation into account. We show that the calibration results are almost independent from the knowledge of the aerosol optical properties and surface albedo, which causes a rather small uncertainty of about < 7 %. For wavelengths below about 330 nm it is essential that the ozone column density during the measurements be constant and known.

scholarly journals Understanding the Difference Between Standard Deviation and Standard Error of the Mean, and Knowing When to Use Which

2020 ◽  
Vol 42 (4) ◽  
pp. 409-410
Author(s):  
Chittaranjan Andrade
Keyword(s):  
Standard Deviation ◽  
Confidence Interval ◽  
Standard Error ◽  
Statistical Significance ◽  
Sample Mean ◽  
Population Mean ◽  
Sample Data ◽  
The Mean ◽  
The Difference

Many authors are unsure of whether to present the mean along with the standard deviation (SD) or along with the standard error of the mean (SEM). The SD is a descriptive statistic that estimates the scatter of values around the sample mean; hence, the SD describes the sample. In contrast, the SEM is an estimate of how close the sample mean is to the population mean; it is an intermediate term in the calculation of the 95% confidence interval around the mean, and (where applicable) statistical significance; the SEM does not describe the sample. Therefore, the mean should always be accompanied by the SD when describing the sample. There are many reasons why the SEM continues to be reported, and it is argued that none of these is justifiable. In fact, presentation of SEMs may mislead readers into believing that the sample data are more precise than they actually are. Given that the standard error is not presented for other parameters, such as difference between means or proportions, and difference between proportions, it is suggested that presentation of SEM values can be done away with, altogether.

Using Connectionist Modules for Decision Support

1990 ◽  
Vol 29 (03) ◽  
pp. 167-181 ◽  
Author(s):  
G. Hripcsak
Keyword(s):  
Decision Support ◽  
Standard Deviation ◽  
Confidence Interval ◽  
Posterior Probability ◽  
Back Propagation ◽  
Connectionist Model ◽  
Test Set ◽  
The Third ◽  
Independent Test ◽  
Better Than

AbstractA connectionist model for decision support was constructed out of several back-propagation modules. Manifestations serve as input to the model; they may be real-valued, and the confidence in their measurement may be specified. The model produces as its output the posterior probability of disease. The model was trained on 1,000 cases taken from a simulated underlying population with three conditionally independent manifestations. The first manifestation had a linear relationship between value and posterior probability of disease, the second had a stepped relationship, and the third was normally distributed. An independent test set of 30,000 cases showed that the model was better able to estimate the posterior probability of disease (the standard deviation of residuals was 0.046, with a 95% confidence interval of 0.046-0.047) than a model constructed using logistic regression (with a standard deviation of residuals of 0.062, with a 95% confidence interval of 0.062-0.063). The model fitted the normal and stepped manifestations better than the linear one. It accommodated intermediate levels of confidence well.

Brightness In The Photopic Range: Psychophysical Modelling With Blue-sensitive Retinal Signals

2020 ◽  
pp. 9-24
Author(s):  
Peter Bodrogi ◽  
Xue Guo ◽  
Tran Quoc Khanh
Keyword(s):  
Ganglion Cells ◽  
Light Stimulus ◽  
Spectral Radiance ◽  
Psychophysical Experiment ◽  
Retinal Ganglion ◽  
Reasonable Accuracy ◽  
Brightness Perception ◽  
Content Model ◽  
The Difference ◽  
Cone Signal

The brightness perception of a large (41°) uniform visual field was investigated in a visual psychophysical experiment. Subjects assessed the brightness of 20 light source spectra of different chromaticities at two luminance levels, Lv=267.6 cd/m2 and Lv=24.8 cd/m2. The resulting mean subjective brightness scale values were modelled by a combination of the signals of retinal mechanisms: S-cones, rods, intrinsically photosensitive retinal ganglion cells (ipRGCs) and the difference of the L-cone signal and the M-cone signal. A new quantity, “relative spectral blue content”, was also considered for modelling. This quantity was defined as “the spectral radiance of the light stimulus integrated with the range (380–520) nm, relative to luminance”. The “relative spectral blue content” model could describe the subjective brightness perception of the observers with reasonable accuracy.

scholarly journals Significant Associations of lncRNA H19 Genotypes with Susceptibility to Childhood Leukemia in Taiwan

2021 ◽  
Vol 14 (3) ◽  
pp. 235
Author(s):  
Jen-Sheng Pei ◽  
Chao-Chun Chen ◽  
Wen-Shin Chang ◽  
Yun-Chi Wang ◽  
Jaw-Chyun Chen ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Childhood Leukemia ◽  
Healthy Controls ◽  
Nucleotide Polymorphisms ◽  
Wild Type ◽  
Single Nucleotide ◽  
Genotypic Distribution ◽  
Heterozygous Variant ◽  
Significant Difference ◽  
The Difference

The purpose of our study was to investigate whether genetic variations in lncRNA H19 were associated with susceptibility to childhood leukemia. Two hundred and sixty-six childhood leukemia patients and 266 healthy controls were enrolled in Taiwan, and two single nucleotide polymorphisms (SNPs), rs2839698 and rs217727, in H19 were genotyped and analyzed. There was a significant difference in the genotypic distribution of rs2839698 between patients and healthy controls (p = 0.0277). Compared to the wild-type CC genotype, the heterozygous variant CT and homozygous variant TT genotypes were associated with significantly increased risks of childhood leukemia with an adjusted odd ratio (OR) of 1.46 (95% confidence interval (CI), 1.08–2.14, p = 0.0429) and 1.94 (95%CI, 1.15–3.31, p = 0.0169), respectively (pfor tread = 0.0277). The difference in allelic frequencies between childhood leukemia patients and controls was also significant (T versus C, adjusted OR = 1.53, 95%CI, 1.13–1.79, p = 0.0077). There were no significant differences in the genotypic and allelic distributions of rs217727 between cases and controls. Interestingly, the average level of H19 rs2839698 was statistically significantly higher for patients with CT and TT genotypes than from those with the CC genotype (p < 0.0001). Our results indicate that H19 SNP rs2839698, but not rs217727, may serve as a novel susceptibility marker for childhood leukemia.

ZABOLOTSKA T.M., SHPYG V.M., TSILA A.YU. CIRCULATION INDEXES AND THE CLOUD COVER DURING OF THE GLOBAL WARMING PERIOD

2021 ◽  
pp. 76-91
Author(s):  
T.M. Zabolotska ◽  
V.M. Shpyg ◽  
A.Yu. Tsila
Keyword(s):  
Global Warming ◽  
North Atlantic ◽  
Relative Frequency ◽  
Cloud Cover ◽  
Annual Data ◽  
East Atlantic ◽  
Clear Sky ◽  
The Difference ◽  
Monthly Variations ◽  
Overcast Sky

The investigations of connection between the different meteorological processes, for example, the circulation indexes with the quantity of the total and lower cloudiness during 1961-2018 over Ukraine were made. The spatial distributions of the total and lower cloudiness were received for 73 years (1946-2018) at first. The quantity of cloudiness is diminished from west to east and with north to south. The declinations of the annual data of total and lower cloudiness from the historical (1961-1990) and the present (1981-2010) norms were calculated. The great variations were characterized for the lower cloudiness. The linear trends showed that the diminish of the lower cloudiness was on 90 % of the all territory, this changes were important on 70 % of the territory. The trends of the monthly variations were showed on the diminish of the lower cloudiness in during all year only on north, on other territory was the increasing in the separate months, frequently in January and September. The variations of the total cloudiness were insignificant, the increase or decrease were nearly in equal parts. North Atlantic Oscillation (NAO), Arctic Oscillation (AO), East-Atlantic Oscillation (EA), Scandinavian Oscillation (SCAND), Greenlandic Oscillation (GBI) and South Oscillation (El-Niño) were used for the investigation of relationship between the circulation indexes and cloud cover. It was shown that different circulation indexes have influence on climate of Northern Hemisphere and on Ukraine too. The relation with each other and their variations in period of global warming were showed. The quantity estimation of the total and lower cloudiness variations was made by the frequencies of clear, semi clear and overcast sky in the successive decades and by the relative variations of frequencies between decades (1961-1970 and 1971-1980; 1971-1980 and 1981-1990; 1981-1990 and 1991-2000; 1991-2000 and 2001-2010; 2001-2010 and 2011-2018). The parallel analyze of the variations of circulation was estimated in that time. The difference between the circulating processes during 1961-1970 and 1971-1980 contributed to a decrease in the relative frequency of the clear sky (on 5.4%) and a slight increase of the overcast sky (on 1.6%) by total cloud cover and a slight increase of the clear sky (on 0.8 %) and a decrease of the overcast sky (on 5.2%) by lower cloudiness. At the same time, the relative frequency of the semi-clear sky by lower cloudiness almost in three times increased in comparison to total cloudiness (on 10.2% and 3.8%, respectively). In the third decade of 1981-1990 the relative frequency of clear sky by lower cloudiness increased on 5.1% and did not change by total cloudiness (0%). During this decade the relative frequency of overcast sky decreased the most in the whole period under study: by total cloudiness on 6.4% and by lower cloudiness on 13.3%. At the same time, the relative frequency of semi-clear sky had largest increasing: on 22.4% for total cloudiness and 13% for lower cloudiness. Then, during 1991-2000, the frequency of clear sky decreased significantly both for total cloudiness (on 6.5%) and for lower cloudiness (on 3.1%). The frequency of overcast sky decreased also, but less significantly (on 1.3% and 2.3%, respectively), thereby the number of clouds of the middle and upper levels increased. From 2001 to 2010, the frequency of clear sky by total cloudiness and by lower cloudiness continued to decrease (on 5.3 and 3.2%, respectively), but the frequency of overcast sky increased (on 0.9 and 1.7%, respectively), thereby the number of clouds for all levels increased. During 2011-2018 the frequency of clear sky by total cloudiness increased (on 0.9%) and by lower cloudiness did not change. The frequency of overcast sky decreased on 3.6% (by total cloudiness) and on 0.7% (by lower cloudiness). The variations of the relative frequencies of the different state sky between the successive decades are agreed with the changes of the circulation indexes.

Quasi-periodic occurrence of earthquakes in the 1978-1986 Bishop-Mammoth Lakes sequence, eastern California

1987 ◽  
Vol 77 (4) ◽  
pp. 1347-1358
Author(s):  
J. C. Savage ◽  
Robert S. Cockerham
Keyword(s):  
Standard Deviation ◽  
Confidence Interval ◽  
Convincing Evidence ◽  
Data Selection ◽  
Individual Event ◽  
Physical Explanation ◽  
Interevent Interval ◽  
Prior Event ◽  
Important Activity ◽  
Mammoth Lakes

Abstract In December 1984, Ryall and Hill noted that the five principal events in the Bishop-Mammoth Lakes earthquake sequence occurred at intervals of about 1.5 yr with a standard deviation for an individual event of 0.25 yr. Some data selection was involved in identifying the principal events, although the choices seemed reasonable. The recent Chalfant Valley earthquake (ML = 6.4; 21 July 1986) followed the last prior principal event in the Bishop-Mammoth Lakes sequence by 1.65 yr, and no important activity intervened except one aftershock from the prior event. Thus, the Chalfant Valley earthquake could have been forecast from the observed periodicity. However, the precision of the forecast (±0.8 yr for the 95 per cent confidence interval) is not sufficient to furnish convincing evidence that the Bishop-Mammoth Lakes sequence is quasi-periodic. Extrapolation of the trend established by the six previous events suggests that the next event in the Bishop-Mammoth Lakes sequence would be expected in December 1987 ± 0.7 yr (95 per cent confidence interval). The regularity of the Bishop-Mammoth Lakes sequence is comparable to that of the Parkfield, California, sequence (average interevent interval 20.8 yr with a standard deviation for an individual interval of 6.2 yr). Both sequences consist of six events. There is a plausible physical explanation for the periodicity observed at Parkfield; such an explanation for the Bishop-Mammoth Lakes sequence is lacking.

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