scholarly journals Relative drifts and biases between six ozone limb satellite measurements from the last decade

2015 ◽  
Vol 8 (10) ◽  
pp. 4369-4381 ◽  
Author(s):  
N. Rahpoe ◽  
M. Weber ◽  
A. V. Rozanov ◽  
K. Weigel ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Third Party ◽  
Data Sets ◽  
Satellite Measurements ◽  
Data Set ◽  
Ozone Profile ◽  
Combining Data ◽  
High Vertical Resolution ◽  
Added Uncertainty ◽  
Long Term Trend

Abstract. As part of European Space Agency's (ESA) climate change initiative, high vertical resolution ozone profiles from three instruments all aboard ESA's Envisat (GOMOS, MIPAS, SCIAMACHY) and ESA's third party missions (OSIRIS, SMR, ACE-FTS) are to be combined in order to create an essential climate variable data record for the last decade. A prerequisite before combining data is the examination of differences and drifts between the data sets. In this paper, we present a detailed analysis of ozone profile differences based on pairwise collocated measurements, including the evolution of the differences with time. Such a diagnosis is helpful to identify strengths and weaknesses of each data set that may vary in time and introduce uncertainties in long-term trend estimates. The analysis reveals that the relative drift between the sensors is not statistically significant for most pairs of instruments. The relative drift values can be used to estimate the added uncertainty in physical trends. The added drift uncertainty is estimated at about 3 % decade−1 (1σ). Larger differences and variability in the differences are found in the lowermost stratosphere (below 20 km) and in the mesosphere.

scholarly journals Relative drifts and biases between six ozone limb satellite measurements from the last decade

2015 ◽  
Vol 8 (4) ◽  
pp. 3697-3728 ◽  
Author(s):  
N. Rahpoe ◽  
M. Weber ◽  
A. V. Rozanov ◽  
K. Weigel ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Relative Difference ◽  
Third Party ◽  
Satellite Measurements ◽  
Data Set ◽  
Middle Latitudes ◽  
Ozone Profile ◽  
Combining Data ◽  
High Vertical Resolution ◽  
Long Term Trend

Abstract. As part of ESA's climate change initiative high vertical resolution ozone profiles from three instruments all aboard ESA's Envisat (GOMOS, MIPAS, SCIAMACHY) in combination with ESA's third party missions (OSIRIS, SMR, ACE-FTS) are to be combined in order to create an essential climate variable data record for the last decade. A prerequisite before combining data is the examination of differences and drifts between the datasets. In this paper, we present a detailed analysis of ozone profile differences based on pairwise collocated measuerements, including the evolution of the differences with time. Such a diagnosis is helpful to identify strengths and weaknesses of each data set that may vary in time and introduce uncertainties in long-term trend estimates. Main results of this paper indicate that the 6 instruments perform well in the stratosphere particularly between 20 and 40 km with a mean relative difference of ±5% (middle latitudes) to ±10% (tropics). Larger differences and variability in the differences are found in the upper troposphere lower stratosphere region and in the mesosphere. The analysis reveals that the relative drift between the sensors is not statistically significant for most pairs of instruments.

scholarly journals ML-TOMCAT: machine-learning-based satellite-corrected global stratospheric ozone profile data set from a chemical transport model

2021 ◽  
Vol 13 (12) ◽  
pp. 5711-5729
Author(s):  
Sandip S. Dhomse ◽  
Carlo Arosio ◽  
Wuhu Feng ◽  
Alexei Rozanov ◽  
Mark Weber ◽  
...  
Keyword(s):  
Transport Model ◽  
Stratospheric Ozone ◽  
Chemical Transport ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Profile Data ◽  
Data Set ◽  
Ozone Profile ◽  
Satellite Instruments

Abstract. High-quality stratospheric ozone profile data sets are a key requirement for accurate quantification and attribution of long-term ozone changes. Satellite instruments provide stratospheric ozone profile measurements over typical mission durations of 5–15 years. Various methodologies have then been applied to merge and homogenise the different satellite data in order to create long-term observation-based ozone profile data sets with minimal data gaps. However, individual satellite instruments use different measurement methods, sampling patterns and retrieval algorithms which complicate the merging of these different data sets. In contrast, atmospheric chemical models can produce chemically consistent long-term ozone simulations based on specified changes in external forcings, but they are subject to the deficiencies associated with incomplete understanding of complex atmospheric processes and uncertain photochemical parameters. Here, we use chemically self-consistent output from the TOMCAT 3-D chemical transport model (CTM) and a random-forest (RF) ensemble learning method to create a merged 42-year (1979–2020) stratospheric ozone profile data set (ML-TOMCAT V1.0). The underlying CTM simulation was forced by meteorological reanalyses, specified trends in long-lived source gases, solar flux and aerosol variations. The RF is trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set over the time periods of the Microwave Limb Sounder (MLS) from the Upper Atmosphere Research Satellite (UARS) (1991–1998) and Aura (2005–2016) missions. We find that ML-TOMCAT shows excellent agreement with available independent satellite-based data sets which use pressure as a vertical coordinate (e.g. GOZCARDS, SWOOSH for non-MLS periods) but weaker agreement with the data sets which are altitude-based (e.g. SAGE-CCI-OMPS, SCIAMACHY-OMPS). We find that at almost all stratospheric levels ML-TOMCAT ozone concentrations are well within uncertainties of the observational data sets. The ML-TOMCAT (V1.0) data set is ideally suited for the evaluation of chemical model ozone profiles from the tropopause to 0.1 hPa and is freely available via https://doi.org/10.5281/zenodo.5651194 (Dhomse et al., 2021).

scholarly journals Past changes in the vertical distribution of ozone – Part 1: Measurement techniques, uncertainties and availability

2014 ◽  
Vol 7 (5) ◽  
pp. 1395-1427 ◽  
Author(s):  
B. Hassler ◽  
I. Petropavlovskikh ◽  
J. Staehelin ◽  
T. August ◽  
P. K. Bhartia ◽  
...  
Keyword(s):  
Stratospheric Ozone ◽  
Measurement Techniques ◽  
United Nations Environment Programme ◽  
Critical Examination ◽  
Profile Measurement ◽  
Data Sets ◽  
Data Set ◽  
Ozone Profile ◽  
Measurement Uncertainties

Abstract. Peak stratospheric chlorofluorocarbon (CFC) and other ozone depleting substance (ODS) concentrations were reached in the mid- to late 1990s. Detection and attribution of the expected recovery of the stratospheric ozone layer in an atmosphere with reduced ODSs as well as efforts to understand the evolution of stratospheric ozone in the presence of increasing greenhouse gases are key current research topics. These require a critical examination of the ozone changes with an accurate knowledge of the spatial (geographical and vertical) and temporal ozone response. For such an examination, it is vital that the quality of the measurements used be as high as possible and measurement uncertainties well quantified. In preparation for the 2014 United Nations Environment Programme (UNEP)/World Meteorological Organization (WMO) Scientific Assessment of Ozone Depletion, the SPARC/IO3C/IGACO-O3/NDACC (SI2N) Initiative was designed to study and document changes in the global ozone profile distribution. This requires assessing long-term ozone profile data sets in regards to measurement stability and uncertainty characteristics. The ultimate goal is to establish suitability for estimating long-term ozone trends to contribute to ozone recovery studies. Some of the data sets have been improved as part of this initiative with updated versions now available. This summary presents an overview of stratospheric ozone profile measurement data sets (ground and satellite based) available for ozone recovery studies. Here we document measurement techniques, spatial and temporal coverage, vertical resolution, native units and measurement uncertainties. In addition, the latest data versions are briefly described (including data version updates as well as detailing multiple retrievals when available for a given satellite instrument). Archive location information for each data set is also given.

scholarly journals Round-robin evaluation of nadir ozone profile retrievals: methodology and application to MetOp-A GOME-2

2015 ◽  
Vol 8 (5) ◽  
pp. 2093-2120 ◽  
Author(s):  
A. Keppens ◽  
J.-C. Lambert ◽  
J. Granville ◽  
G. Miles ◽  
R. Siddans ◽  
...  
Keyword(s):  
Information Content ◽  
Global Climate ◽  
Optimal Estimation ◽  
Round Robin ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Profile Data ◽  
Satellite Measurements ◽  
Data Set ◽  
Ozone Profile

Abstract. A methodology for the round-robin evaluation and the geophysical validation of ozone profile data retrieved from nadir UV backscatter satellite measurements is detailed and discussed, consisting of data set content studies, information content studies, co-location studies, and comparisons with reference measurements. Within the European Space Agency's Climate Change Initiative on ozone (Ozone_cci project), the proposed round-robin procedure is applied to two nadir ozone profile data sets retrieved at the Royal Netherlands Meteorological Institute (KNMI) and the Rutherford Appleton Laboratory (RAL, United Kingdom), using their respective OPERA v1.26 and RAL v2.1 optimal estimation algorithms, from MetOp-A GOME-2 (i.e. the second generation Global Ozone Monitoring Experiment on the first Meteorological Operational Satellite) measurements taken in 2008. The ground-based comparisons use ozonesonde and lidar profiles as reference data, acquired by the Network for the Detection of Atmospheric Composition Change (NDACC), Southern Hemisphere Additional Ozonesonde programme (SHADOZ), and other stations of the World Meteorological Organisation's Global Atmosphere Watch (WMO GAW). This direct illustration highlights practical issues that inevitably emerge from discrepancies in e.g. profile representation and vertical smoothing, for which different recipes are investigated and discussed. Several approaches for information content quantification, vertical resolution estimation, and reference profile resampling are compared and applied as well. The paper concludes with compliance estimates of the two GOME-2 ozone profile data sets with user requirements from the Global Climate Observing System (GCOS) and from climate modellers.

scholarly journals SI<sup>2</sup>N overview paper: ozone profile measurements: techniques, uncertainties and availability

2013 ◽  
Vol 6 (6) ◽  
pp. 9857-9938 ◽  
Author(s):  
B. Hassler ◽  
I. Petropavlovskikh ◽  
J. Staehelin ◽  
T. August ◽  
P. K. Bhartia ◽  
...  
Keyword(s):  
Stratospheric Ozone ◽  
Measurement Techniques ◽  
United Nations Environment Programme ◽  
Critical Examination ◽  
Profile Measurement ◽  
Data Sets ◽  
Data Set ◽  
Ozone Profile ◽  
Measurement Uncertainties

Abstract. Peak stratospheric chlorofluorocarbon (CFC) and other ozone depleting substance (ODS) concentrations were reached in the mid to late 1990s. Detection and attribution of the expected recovery of the stratospheric ozone layer in an atmosphere with reduced ODSs as well as efforts to understand the evolution of stratospheric ozone in the presence of increasing greenhouse gases are key current research topics. These require a critical examination of the ozone changes with an accurate knowledge of the spatial (geographical and vertical) and temporal ozone response. For such an examination, it is vital that the quality of the measurements used be as high as possible and measurement uncertainties well quantified. In preparation for the 2014 United Nations Environment Programme (UNEP)/World Meteorological Organization (WMO) Scientific Assessment of Ozone Depletion, the SPARC/IO3C/IGACO-O3/NDACC (SI2N) initiative was designed to study and document changes in the global ozone profile distribution. This requires assessing long-term ozone profile data sets in regards to measurement stability and uncertainty characteristics. The ultimate goal is to establish suitability for estimating long-term ozone trends to contribute to ozone recovery studies. Some of the data sets have been improved as part of this initiative with updated versions now available. This summary presents an overview of stratospheric ozone profile measurement data sets (ground- and satellite-based) available for ozone recovery studies. Here we document measurement techniques, spatial and temporal coverage, vertical resolution, native units and measurement uncertainties. In addition, the latest data versions are briefly described (including data version updates as well as detailing multiple retrievals when available for a given satellite instrument). Archive location information is for each data set is also given.

Trophic Level Relationships in Pelagic Food Webs: Comparisons Derived from Long-Term Data Sets for Oneida Lake, New York (USA), and Lake St. George, Ontario (Canada)

1992 ◽  
Vol 49 (8) ◽  
pp. 1588-1596 ◽  
Author(s):  
Donald J. McQueen ◽  
Edward L. Mills ◽  
John L. Forney ◽  
Mark R. S. Johannes ◽  
John R. Post
Keyword(s):  
New York ◽  
Total Phosphorus ◽  
Trophic Level ◽  
Data Sets ◽  
Phytoplankton Abundance ◽  
Data Set ◽  
Oneida Lake ◽  
Pelagic Food Webs ◽  
Term Data

We used standardized methods to analyze a 14-yr data set from Oneida Lake and a 10-yr data set from Lake St. George. We estimated mean summer concentrations of several trophic level indicators including piscivores, planktivores, zooplankton, phytoplankton, and total phosphorus, and we then investigated the relationships between these variables. Both data sets yielded similar long-term and short-term trends. The long-term mean annual trends were that (1) the relationships between concentrations of planktivores and zooplankton (including daphnids) were always negative, (2) the relationships between concentrations of zooplankton and various measures of phytoplankton abundance were unpredictable and never statistically significant, and (3) the relationships between total phosphorus and various measures of phytoplankton abundance were always positive. Over short periods, the data from both lakes showed periodic, strong top-down relationships between concentrations of zooplankton (especially large Daphnia) and chlorophyll a, but these events were unpredictable and were seldom related to piscivore abundance.

scholarly journals Intention, Principle, Outputs and Aims of the Experimental Pavilion Research of Building Envelopes Including Windows for Wooden Buildings

2017 ◽  
Vol 13 (1) ◽  
pp. 42-51 ◽  
Author(s):  
Daniela Štaffenová ◽  
Ján Rybárik ◽  
Miroslav Jakubčík
Keyword(s):  
Experimental Research ◽  
Climatic Conditions ◽  
Point Of View ◽  
Physical Parameters ◽  
Data Sets ◽  
Data Set ◽  
Building Envelopes ◽  
Climate Conditions ◽  
Time Period

AbstractThe aim of experimental research in the area of exterior walls and windows suitable for wooden buildings was to build special pavilion laboratories. These laboratories are ideally isolated from the surrounding environment, airtight and controlled by the constant internal climate. The principle of experimental research is measuring and recording of required physical parameters (e.g. temperature or relative humidity). This is done in layers of experimental fragment sections in the direction from exterior to interior, as well as in critical places by stable interior and real exterior climatic conditions. The outputs are evaluations of experimental structures behaviour during the specified time period, possibly during the whole year by stable interior and real exterior boundary conditions. The main aim of this experimental research is processing of long-term measurements of experimental structures and the subsequent analysis. The next part of the research consists of collecting measurements obtained with assistance of the experimental detached weather station, analysis, evaluation for later setting up of reference data set for the research locality, from the point of view of its comparison to the data sets from Slovak Hydrometeorological Institute (SHMU) and to localities with similar climate conditions. Later on, the data sets could lead to recommendations for design of wooden buildings.

scholarly journals Prediction of Progestin Affinity for the Human Progesterone Receptor Based on Corrected RBA Data

2018 ◽  
Vol 1 (4) ◽  
pp. e00080
Author(s):  
A.V. Mikurova ◽  
V.S. Skvortsov
Keyword(s):  
Progesterone Receptor ◽  
Prediction Equation ◽  
Binding Activity ◽  
Data Sets ◽  
Data Set ◽  
The Third ◽  
Relative Binding ◽  
Human Progesterone Receptor ◽  
Nuclear Progesterone Receptor

The modeling of complexes of 3 sets of steroid and nonsteroidal progestins with the ligand-binding domain of the nuclear progesterone receptor was performed. Molecular docking procedure, long-term simulation of molecular dynamics and subsequent analysis by MM-PBSA (MM-GBSA) were used to model the complexes. Using the characteristics obtained by the MM-PBSA method two data sets of steroid compounds obtained in different scientific groups a prediction equation for the value of relative binding activity (RBA) was constructed. The RBA value was adjusted so that in all samples the actual activity was compared with the progesterone activity. The third data set of nonsteroidal compounds was used as a test. The resulted equation showed that the prediction results could be applied to both steroid molecules and nonsteroidal progestins.

Long-Term Rainfall Forecast Model Based on The TabNet and LightGbm Algorithm

2020 ◽  
Author(s):  
Tianyu Xu ◽  
Yongchuan Yu ◽  
Jianzhuo Yan ◽  
Hongxia Xu
Keyword(s):  
Prediction Model ◽  
Feature Fusion ◽  
Forecast Model ◽  
Data Sets ◽  
Good Prediction ◽  
Data Set ◽  
Rainfall Prediction ◽  
Improve Model ◽  
Probability Prediction

Abstract Due to the problems of unbalanced data sets and distribution differences in long-term rainfall prediction, the current rainfall prediction model had poor generalization performance and could not achieve good prediction results in real scenarios. This study uses multiple atmospheric parameters (such as temperature, humidity, atmospheric pressure, etc.) to establish a TabNet-LightGbm rainfall probability prediction model. This research uses feature engineering (such as generating descriptive statistical features, feature fusion) to improve model accuracy, Borderline Smote algorithm to improve data set imbalance, and confrontation verification to improve distribution differences. The experiment uses 5 years of precipitation data from 26 stations in the Beijing-Tianjin-Hebei region of China to verify the proposed rainfall prediction model. The test set is to predict the rainfall of each station in one month. The experimental results shows that the model has good performance with AUC larger than 92%. The method proposed in this study further improves the accuracy of rainfall prediction, and provides a reference for data mining tasks.

Long-term variations of the oxygen red 630 nm line nightglow intensity

2007 ◽  
Vol 85 (2) ◽  
pp. 189-198 ◽  
Author(s):  
N B Gudadze ◽  
G G Didebulidze ◽  
G Sh. Javakhishvili ◽  
M G Shepherd ◽  
M V Vardosanidze
Keyword(s):  
Line Intensity ◽  
Peak Height ◽  
Mean Value ◽  
Lower Atmosphere ◽  
Data Set ◽  
Term Trend ◽  
Long Term Trend ◽  
Long Term Variations ◽  
Red Line

The long-term data set of total nightglow intensity of the oxygen red 630.0~nm line observed at Abastumani (41.8°N, 42.8°E) between 1957–1993 is investigated. The long-term trend and characteristic variations in solar radiation during an 11 year cycle of the red-line intensity are different after astronomical twilight (premidnight) and at midnight. The amplitude of deviation of the red-line intensity from its mean value at solar maximum and (or) minimum phase is greatest after astronomical twilight and decreases toward midnight. The long-term trend of these variations changes from its value about 0.74 R/year premidnight to its minimum negative value of about –1.92 R/year at and after midnight. This behavior of the long-term trend is considered as a possible result of an increase in electron density below the peak height (hmF2) of the ionospheric F2 layer and lowering of the height hmF2 after midnight predicted by the TIME-GCM model on the assumption of an increase in density of greenhouse gases in the lower atmosphere. The third-order regression equation (with different solar activity indices) is considered to be convenient for describing long-term variations in the mean annual red-line intensity.PACS Nos.: 94.10.Rk, 94.20.Ji, 92.60.Vb

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