scholarly journals Tropospheric ozone column retrieval at northern mid-latitudes from the Ozone Monitoring Instrument by means of a neural network algorithm

2011 ◽  
Vol 4 (11) ◽  
pp. 2375-2388 ◽  
Author(s):  
P. Sellitto ◽  
B. R. Bojkov ◽  
X. Liu ◽  
K. Chance ◽  
F. Del Frate
Keyword(s):  
Neural Network ◽  
Test Data ◽  
Tropospheric Ozone ◽  
Optimal Estimation ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Monitoring Instrument ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Ozone Monitoring

Abstract. Monitoring tropospheric ozone from space is of critical importance in order to gain more thorough knowledge on phenomena affecting air quality and the greenhouse effect. Deriving information on tropospheric ozone from UV/VIS nadir satellite spectrometers is difficult owing to the weak sensitivity of the measured radiance spectra to variations of ozone in the troposphere. Here we propose an alternative method of analysis to retrieve tropospheric ozone columns from Ozone Monitoring Instrument radiances by means of a neural network algorithm. An extended set of ozone sonde measurements at northern mid-latitudes for the years 2004–2008 has been considered as the training and test data set. The design of the algorithm is extensively discussed. Our retrievals are compared to both tropospheric ozone residuals and optimal estimation retrievals over a similar independent test data set. Results show that our algorithm has comparable accuracy with respect to both correlative methods and its performance is slightly better over a subset containing only European ozone sonde stations. Possible sources of errors are analyzed. Finally, the capabilities of our algorithm to derive information on boundary layer ozone are studied and the results critically discussed.

scholarly journals Tropospheric ozone column retrieval from the Ozone Monitoring Instrument by means of a neural network algorithm

2011 ◽  
Vol 4 (3) ◽  
pp. 2491-2524 ◽  
Author(s):  
P. Sellitto ◽  
B. R. Bojkov ◽  
X. Liu ◽  
K. Chance ◽  
F. Del Frate
Keyword(s):  
Neural Network ◽  
Test Data ◽  
Tropospheric Ozone ◽  
Optimal Estimation ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Monitoring Instrument ◽  
Neural Network Algorithm ◽  
Ozone Monitoring ◽  
Boundary Layer Ozone

Abstract. Monitoring tropospheric ozone from space is of critical importance in order to gain more thorough knowledge on phenomena affecting air quality and the greenhouse effect. Deriving information on tropospheric ozone from UV/VIS nadir satellite spectrometers is difficult owing to the weak sensitivity of the measured radiance spectra to variations of ozone in the troposphere. Here we propose an alternative method of analysis to retrieve tropospheric ozone columns from Ozone Monitoring Instrument radiances by means of a Neural Network algorithms. An extended set of ozone sonde measurements at northern mid-latitudes has been considered as the training and test data set. The design of the algorithm is extensively discussed. Our retrievals are compared to both tropospheric ozone residuals and optimal estimation retrievals over a similar independent test data set. Results show that our algorithm has comparable accuracy with respect to both correlative methods and its performance is slightly better over a subset containing only European ozone sonde stations. Possible sources of errors are analyzed. Finally, the capabilities of our algorithm to derive information on boundary layer ozone are studied and the results critically discussed.

scholarly journals Analysis Model of the Impact of Refined Intervention in Operating Room on Patients’ Recovery Quality and Complications after Thoracic Surgery Based on Deep Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jun He ◽  
Jing Wen
Keyword(s):  
Neural Network ◽  
Thoracic Surgery ◽  
Operating Room ◽  
Test Data ◽  
Deep Neural Network ◽  
Quality Of Recovery ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Room Nursing

To improve the nursing effect in patients after thoracic surgery, this paper proposes a refined intervention method in the operating room based on traditional operating room nursing and applies this method to the nursing of patients after thoracic surgery. Moreover, this paper improves the traditional neural network algorithm and uses the deep neural network algorithm to process test data. In addition, it includes patients accepted by the hospital as samples for test analysis and formulates detailed intervention methods for the operating room. Finally, this paper collects the corresponding test data by setting up test and control groups and visually displays the data using mathematical statistics. The statistical parameters of the experiment in this paper include the quality of recovery, complications, satisfaction score, and recovery effect. The comparative test shows that the refined intervention in the operating room based on the neural network proposed in this paper can achieve a certain effect in the postoperative nursing of thoracic surgery, effectively promote the quality of recovery, and reduce the possibility of complications.

scholarly journals Linearization of the effect of slit function changes for improving Ozone Monitoring Instrument ozone profile retrievals

2019 ◽  
Vol 12 (7) ◽  
pp. 3777-3788 ◽  
Author(s):  
Juseon Bak ◽  
Xiong Liu ◽  
Kang Sun ◽  
Kelly Chance ◽  
Jae-Hwan Kim
Keyword(s):  
Cross Sections ◽  
Shape Factor ◽  
Optimal Estimation ◽  
Ozone Monitoring Instrument ◽  
Thermally Induced ◽  
Monitoring Instrument ◽  
Spectral Fitting ◽  
Ozone Profile ◽  
Ozone Monitoring ◽  
Hartley Band

Abstract. We introduce a method that accounts for errors caused by the slit function in an optimal-estimation-based spectral fitting process to improve ozone profile retrievals from the Ozone Monitoring Instrument (OMI) ultraviolet measurements (270–330 nm). Previously, a slit function was parameterized as a standard Gaussian by fitting the full width at half maximum (FWHM) of the slit function from climatological OMI solar irradiances. This cannot account for the temporal variation in slit function in irradiance, the intra-orbit changes due to thermally induced change and scene inhomogeneity, and potential differences in the slit functions of irradiance and radiance measurements. As a result, radiance simulation errors may be induced due to convolving reference spectra with incorrect slit functions. To better represent the shape of the slit functions, we implement a more generic super Gaussian slit function with two free parameters (slit width and shape factor); it becomes standard Gaussian when the shape factor is fixed to be 2. The effects of errors in slit function parameters on radiance spectra, referred to as pseudo absorbers (PAs), are linearized by convolving high-resolution cross sections or simulated radiances with the partial derivatives of the slit function with respect to the slit parameters. The PAs are included in the spectral fitting scaled by fitting coefficients that are iteratively adjusted as elements of the state vector along with ozone and other fitting parameters. The fitting coefficients vary with cross-track and along-track pixels and show sensitivity to heterogeneous scenes. The PA spectrum is quite similar in the Hartley band below 310 nm for both standard and super Gaussians, but is more distinctly structured in the Huggins band above 310 nm with the use of super Gaussian slit functions. Finally, we demonstrate that some spikes of fitting residuals are slightly smoothed by accounting for the slit function errors. Comparisons with ozonesondes demonstrate noticeable improvements when using PAs for both standard and super Gaussians, especially for reducing the systematic biases in the tropics and midlatitudes (mean biases of tropospheric column ozone reduced from -1.4∼0.7 to 0.0∼0.4 DU) and reducing the standard deviations of tropospheric ozone column differences at high latitudes (by 1 DU for the super Gaussian). Including PAs also makes the retrievals consistent between standard and super Gaussians. This study corroborates the slit function differences between radiance and irradiance, demonstrating that it is important to account for such differences in the ozone profile retrievals.

scholarly journals Seasonality of the lower tropospheric ozone over China observed by the Ozone Monitoring Instrument

2018 ◽  
Vol 184 ◽  
pp. 244-253 ◽  
Author(s):  
Sachiko Hayashida ◽  
Mizuo Kajino ◽  
Makoto Deushi ◽  
Tsuyoshi Thomas Sekiyama ◽  
Xiong Liu
Keyword(s):  
Tropospheric Ozone ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Ozone Monitoring

scholarly journals Ozone profile retrievals from the Ozone Monitoring Instrument

2010 ◽  
Vol 10 (5) ◽  
pp. 2521-2537 ◽  
Author(s):  
X. Liu ◽  
P. K. Bhartia ◽  
K. Chance ◽  
R. J. D. Spurr ◽  
T. P. Kurosu
Keyword(s):  
Degrees Of Freedom ◽  
Optimal Estimation ◽  
Anthropogenic Pollution ◽  
Horizontal Resolution ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Ozone Profile ◽  
Ozone Monitoring ◽  
The Tropics ◽  
Middle Stratosphere

Abstract. Ozone profiles from the surface to about 60 km are retrieved from Ozone Monitoring Instrument (OMI) ultraviolet radiances using the optimal estimation technique. OMI provides daily ozone profiles for the entire sunlit portion of the earth at a horizontal resolution of 13 km×48 km for the nadir position. The retrieved profiles have sufficient accuracy in the troposphere to see ozone perturbations caused by convection, biomass burning and anthropogenic pollution, and to track their spatiotemporal transport. However, to achieve such accuracy it has been necessary to calibrate OMI radiances carefully (using two days of Aura/Microwave Limb Sounder data taken in the tropics). The retrieved profiles contain ~6–7 degrees of freedom for signal, with 5–7 in the stratosphere and 0–1.5 in the troposphere. Vertical resolution varies from 7–11 km in the stratosphere to 10–14 km in the troposphere. Retrieval precisions range from 1% in the middle stratosphere to 10% in the lower stratosphere and troposphere. Solution errors (i.e., root sum square of precisions and smoothing errors) vary from 1–6% in the middle stratosphere to 6–35% in the troposphere, and are dominated by smoothing errors. Total, stratospheric, and tropospheric ozone columns can be retrieved with solution errors typically in the few Dobson unit range at solar zenith angles less than 80°.

scholarly journals SELEKSI FITUR ALGORITMA NEURAL NETWORK MENGGUNAKAN PARTICLE SWARM OPTIMIZATION UNTUK MEMPREDIKSI KELAHIRAN PREMATUR

Kilat ◽  
2018 ◽  
Vol 6 (2) ◽  
pp. 106-111
Author(s):  
Redaksi Tim Jurnal
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Preterm Birth ◽  
Sensitivity And Specificity ◽  
Particle Swarm ◽  
Data Set ◽  
Swarm Optimization ◽  
Network Algorithm ◽  
The Neural Network ◽  
Neural Network Algorithm

Premature birth, defined as delivery in pregnant women with gestation age 20 - 36 weeks. Research related to preterm birth has been done by the researchers by using the neural network method. However such research only showcase about the results of the sensitivity and specificity. The results of research using the method of neural network in predicting preterm birth has a value of the resulting accuracy is still less accurate and only limited to presenting the results of the sensitivity and specificity. In this study produced a model of the neural network algorithm and model of neural network algorithm based on particle swarm optimization to get the architecture in predicting preterm birth and gives a more accurate value for accuracy on a data set of RSUPN Cipto Mangunkusumo , RS Sumber Waras and in its entirety. After you are done testing with two models of neural network algorithms and neural network algorithm based on particle swarm optimization and the results obtained are the neural network algorithm generates value accuracy of 94,60%, 96,40%, 91,33%, and AUC values of 0,973, 0,982, 0,953, however, after the addition of the neural network algorithm based on particle swarm optimization value accuracy of 95,20%, 96,80%, 92,40% and AUC values of 0,979 , 0,987, 0,965. So both of these methods has the distinction of accuracy which amounted to 0.60%, 0.40%, 1.07% and AUC value difference of 0.006, 0.005, 0.012.

scholarly journals Detection of non-linear effects in satellite UV/Vis reflectance spectra: Application to the Ozone Monitoring Instrument

2020 ◽  
Author(s):  
Nick Gorkavyi ◽  
Zachary Fasnacht ◽  
David Haffner ◽  
Sergey Marchenko ◽  
Joanna Joiner ◽  
...  
Keyword(s):  
Scattered Light ◽  
Cosmic Ray ◽  
Stray Light ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Monitoring Instrument ◽  
Non Linear ◽  
Linear Effects ◽  
Ozone Monitoring ◽  
Excessive Noise

Abstract. Non-linear effects, such as from saturation, stray light, or obstruction of light, negatively impact satellite measured ultraviolet and visible Earthshine radiance spectra and downstream retrievals of atmospheric and surface properties derived from these spectra. In addition, excessive noise such as from cosmic ray impacts, prevalent within the South Atlantic Anomaly, can also degrade satellite radiance measurements. Saturation specifically pertains to observations of very bright surfaces such as sun glint over water surfaces or thick clouds. Related residual electronic cross-talk or blooming effects may occur in spatial pixels adjacent to a saturated area. Obstruction of light can occur within the zones of solar eclipses as well as from material located outside of the satellite instrument. The latter may also produce unintended scattered light into a satellite instrument. When these effects cannot be corrected to an acceptable level for science quality retrievals, it is desirable to flag the affected pixels. Here, we introduce a new detection method that is based on the correlation, r, between the observed Earthshine radiance and solar irradiance spectra over a 10 nm-spectral range; our Decorrelation Index (DI for brevity) is simply defined as DI=1−r. DI increases with non-linear effects or excessive noise in either radiances (the most likely cause in OMI data) or irradiances. DI is relatively straight-forward to use and interpret and can be computed for different wavelength intervals. We developed a set of DIs for two spectral channels of the Ozone Monitoring Instrument (OMI), a hyperspectral pushbroom imaging spectrometer. For each OMI spatial measurement, we define 14 wavelength-dependent DIs within the OMI visible channel (350–498 nm) and 6 DIs in its ultraviolet 2 (UV2) channel (310–370 nm). As defined, DIs reflect a continuous range of deviations of observed spectra from the reference irradiance spectrum that are complementary to the binary Saturation Possibility Warning (SPW) flags currently provided for each individual spectral/spatial pixels in the OMI radiance data set. Smaller values of DI are also caused by a number of geophysical factors; this allows one to obtain interesting physical results on the global distribution of spectral variations.

Study on calculation and validation of tropospheric ozone by ozone monitoring instrument – microwave limb sounder over China

2020 ◽  
Vol 41 (23) ◽  
pp. 9101-9120
Author(s):  
Yueming Hu ◽  
Huanhuan Yan ◽  
Xingying Zhang ◽  
Yi Gao ◽  
Xiangdong Zheng ◽  
...  
Keyword(s):  
Tropospheric Ozone ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Ozone Monitoring

scholarly journals Retrievals of tropospheric ozone profiles from the synergism of AIRS and OMI: methodology and validation

2018 ◽  
Vol 11 (10) ◽  
pp. 5587-5605 ◽  
Author(s):  
Dejian Fu ◽  
Susan S. Kulawik ◽  
Kazuyuki Miyazaki ◽  
Kevin W. Bowman ◽  
John R. Worden ◽  
...  
Keyword(s):  
Measurement Error ◽  
Tropospheric Ozone ◽  
Retrieval Algorithm ◽  
Vertical Resolution ◽  
Ozone Monitoring Instrument ◽  
Atmospheric Infrared Sounder ◽  
Data Set ◽  
Global Coverage ◽  
Ozone Monitoring ◽  
Wide Swath

Abstract. The Tropospheric Emission Spectrometer (TES) on the A-Train Aura satellite was designed to profile tropospheric ozone and its precursors, taking measurements from 2004 to 2018. Starting in 2008, TES global sampling of tropospheric ozone was gradually reduced in latitude, with global coverage stopping in 2011. To extend the record of TES, this work presents a multispectral approach that will provide O3 data products with vertical resolution and measurement error similar to TES by combining the single-footprint thermal infrared (TIR) hyperspectral radiances from the Aqua Atmospheric Infrared Sounder (AIRS) instrument and the ultraviolet (UV) channels from the Aura Ozone Monitoring Instrument (OMI). The joint AIRS+OMI O3 retrievals are processed through the MUlti-SpEctra, MUlti-SpEcies, MUlti-SEnsors (MUSES) retrieval algorithm. Comparisons of collocated joint AIRS+OMI and TES to ozonesonde measurements show that both systems have similar errors, with mean and standard deviation of the differences well within the estimated measurement error. AIRS+OMI and TES have slightly different biases (within 5 parts per billion) vs. the sondes. Both AIRS and OMI have wide swath widths (∼1650 km for AIRS; ∼2600 km for OMI) across satellite ground tracks. Consequently, the joint AIRS+OMI measurements have the potential to maintain TES vertical sensitivity while increasing coverage by 2 orders of magnitude, thus providing an unprecedented new data set with which to quantify the evolution of tropospheric ozone.

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