scholarly journals Using self organising maps to explore ozone profile validation results – SCIAMACHY limb compared to ground-based lidar observations

2014 ◽  
Vol 7 (4) ◽  
pp. 4373-4406
Author(s):  
J. A. E. van Gijsel ◽  
R. Zurita-Milla ◽  
P. Stammes ◽  
S. Godin-Beekmann ◽  
T. Leblanc ◽  
...  
Keyword(s):  
Zenith Angle ◽  
Solar Zenith Angle ◽  
A Priori ◽  
Relative Difference ◽  
Full Time ◽  
Self Organizing Map ◽  
Ozone Profile ◽  
The Difference ◽  
Ground Based Lidar ◽  
Lidar Observations

Abstract. Traditional validation of atmospheric profiles is based on the intercomparison of two or more datasets in predefined ranges or classes of a given observational characteristic such as latitude or solar zenith angle. In this study we train a self organizing map (SOM) with a full time series of relative difference profiles of SCIAMACHY limb v5.02 and lidar ozone profiles from seven observation sites. Each individual observation characteristic is then mapped to the obtained SOM to investigate to which degree variation in this characteristic is explanatory for the variation seen in the SOM map. For the studied datasets, altitude-dependent relations for the global dataset were found between the difference profiles and studied variables. From the lowest altitude studied (18 km) ascending, the most influencing factors were found to be longitude, followed by solar zenith angle and latitude, sensor age and again solar zenith angle together with the day of the year at the highest altitudes studied here (up to 45 km). Clustering into three classes showed that there are also some local dependencies, with for instance one cluster having a much stronger correlation with the sensor age (days since launch) between 36 and 42 km. It was shown that the proposed approach provides a powerful tool for the exploring of differences between datasets without being limited to a-priori defined data subsets.

scholarly journals Using self-organising maps to explore ozone profile validation results – SCIAMACHY limb compared to ground-based lidar observations

2015 ◽  
Vol 8 (5) ◽  
pp. 1951-1963
Author(s):  
J. A. E. van Gijsel ◽  
R. Zurita-Milla ◽  
P. Stammes ◽  
S. Godin-Beekmann ◽  
T. Leblanc ◽  
...  
Keyword(s):  
Zenith Angle ◽  
Solar Zenith Angle ◽  
A Priori ◽  
Relative Difference ◽  
Data Sets ◽  
Full Time ◽  
Data Set ◽  
Partial Correlations ◽  
The Difference ◽  
Ground Based Lidar

Abstract. Traditional validation of atmospheric profiles is based on the intercomparison of two or more data sets in predefined ranges or classes of a given observational characteristic such as latitude or solar zenith angle. In this study we trained a self-organising map (SOM) with a full time series of relative difference profiles of SCIAMACHY limb v5.02 and lidar ozone profiles from seven observation sites. Each individual observation characteristic was then mapped to the obtained SOM to investigate to which degree variation in this characteristic is explanatory for the variation seen in the SOM map. For the studied data sets, altitude-dependent relations for the global data set were found between the difference profiles and studied variables. From the lowest altitude studied (18 km) ascending, the most influencing factors were found to be longitude, followed by solar zenith angle and latitude, sensor age and again solar zenith angle together with the day of the year at the highest altitudes studied here (up to 45 km). After accounting for both latitude and longitude, residual partial correlations with a reduced magnitude are seen for various factors. However, (partial) correlations cannot point out which (combination) of the factors drives the observed differences between the ground-based and satellite ozone profiles as most of the factors are inter-related. Clustering into three classes showed that there are also some local dependencies, with for instance one cluster having a much stronger correlation with the sensor age (days since launch) between 36 and 42 km. The proposed SOM-based approach provides a powerful tool for the exploration of differences between data sets without being limited to a priori defined data subsets.

Observing and Modelling the Surface Radiative Budget and Cloud Radiative Forcing at the Cabauw Experimental Site for Atmospheric Research (CESAR), the Netherlands, 2009–17

2019 ◽  
Vol 32 (21) ◽  
pp. 7209-7225
Author(s):  
Reinout Boers ◽  
Fred Bosveld ◽  
Henk Klein Baltink ◽  
Wouter Knap ◽  
Erik van Meijgaard ◽  
...  
Keyword(s):  
The Netherlands ◽  
Zenith Angle ◽  
Radiative Forcing ◽  
Solar Zenith Angle ◽  
Cold Bias ◽  
Experimental Site ◽  
Radiative Forcings ◽  
Atmospheric Research ◽  
Low Clouds ◽  
The Difference

Abstract A dataset of 9 years in duration (2009–17) of clouds and radiation was obtained at the Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands. Cloud radiative forcings (CRF) were derived from the dataset and related to cloud cover and temperature. Also, the data were compared with RCM output. Results indicate that there is a seasonal cycle (i.e., winter, spring, summer, and autumn) in longwave (CRF-LW: 48.3, 34.4, 30.8, and 38.7 W m−2) and shortwave (CRF-SW: −23.6, −60.9, −67.8, and −32.9 W m−2) forcings at CESAR. Total CRF is positive in winter and negative in summer. The RCM has a cold bias with respect to the observations, but the model CRF-LW corresponds well to the observed CRF-LW as a result of compensating errors in the difference function that makes up the CRF-LW. The absolute value of model CRF-SW is smaller than the observed CRF-SW in summer, mostly because of albedo differences. The majority of clouds from above 2 km are present at the same time as low clouds, so the higher clouds have only a small impact on CRF whereas low clouds dominate their values. CRF-LW is a function of fractional cloudiness. CRF-SW is also a function of fractional cloudiness, if the values are normalized by the cosine of solar zenith angle. Expressions for CRF-LW and CRF-SW were derived as functions of temperature, fractional cloudiness, and solar zenith angle, indicating that CRF is the largest when fractional cloudiness is the highest but is also large for low temperature and high sun angle.

scholarly journals HDO/H<sub>2</sub>O ratio retrievals from GOSAT

2013 ◽  
Vol 6 (3) ◽  
pp. 599-612 ◽  
Author(s):  
H. Boesch ◽  
N. M. Deutscher ◽  
T. Warneke ◽  
K. Byckling ◽  
A. J. Cogan ◽  
...  
Keyword(s):  
Zenith Angle ◽  
Solar Zenith Angle ◽  
A Priori ◽  
Regional Scale ◽  
Atmospheric Temperature ◽  
Total Carbon ◽  
Latitudinal Gradients ◽  
Random Errors ◽  
Synthetic Simulation ◽  
Shortwave Infrared

Abstract. We report a new shortwave infrared (SWIR) retrieval of the column-averaged HDO/H2O ratio from the Japanese Greenhouse Gases Observing Satellite (GOSAT). From synthetic simulation studies, we have estimated that the inferred δD values will typically have random errors between 20‰ (desert surface and 30° solar zenith angle) and 120‰ (conifer surface and 60° solar zenith angle). We find that the retrieval will have a small but significant sensitivity to the presence of cirrus clouds, the HDO a priori profile shape and atmospheric temperature, which has the potential of introducing some regional-scale biases in the retrieval. From comparisons to ground-based column observations from the Total Carbon Column Observing Network (TCCON), we find differences between δD from GOSAT and TCCON of around −30‰ for northern hemispheric sites which increase up to −70‰ for Australian sites. The bias for the Australian sites significantly reduces when decreasing the spatial co-location criteria, which shows that spatial averaging contributes to the observed differences over Australia. The GOSAT retrievals allow mapping the global distribution of δD and its variations with season, and we find in our global GOSAT retrievals the expected strong latitudinal gradients with significant enhancements over the tropics. The comparisons to the ground-based TCCON network and the results of the global retrieval are very encouraging, and they show that δD retrieved from GOSAT should be a useful product that can be used to complement datasets from thermal-infrared sounder and ground-based networks and to extend the δD dataset from SWIR retrievals established from the recently ended SCIAMACHY mission.

scholarly journals First validation of GOME-2/MetOp absorbing aerosol height using EARLINET lidar observations

2021 ◽  
Vol 21 (4) ◽  
pp. 3193-3213
Author(s):  
Konstantinos Michailidis ◽  
Maria-Elissavet Koukouli ◽  
Nikolaos Siomos ◽  
Dimitris Balis ◽  
Olaf Tuinder ◽  
...  
Keyword(s):  
Saharan Dust ◽  
Aerosol Layer ◽  
Pixel Size ◽  
Geometrical Features ◽  
Depth Analysis ◽  
Satellite Sensors ◽  
The Mean ◽  
The Difference ◽  
Ground Based Lidar ◽  
Lidar Observations

Abstract. The aim of this study is to investigate the potential of the Global Ozone Monitoring Experiment-2 (GOME-2) instruments, aboard the Meteorological Operational (MetOp)-A, MetOp-B and MetOp-C satellite programme platforms, to deliver accurate geometrical features of lofted aerosol layers. For this purpose, we use archived ground-based lidar data from stations available from the European Aerosol Research Lidar Network (EARLINET) database. The data are post-processed using the wavelet covariance transform (WCT) method in order to extract geometrical features such as the planetary boundary layer (PBL) height and the cloud boundaries. To obtain a significant number of collocated and coincident GOME-2 – EARLINET cases for the period between January 2007 and September 2019, 13 lidar stations, distributed over different European latitudes, contributed to this validation. For the 172 carefully screened collocations, the mean bias was found to be −0.18 ± 1.68 km, with a near-Gaussian distribution. On a station basis, and with a couple of exceptions where very few collocations were found, their mean biases fall in the ± 1 km range with an associated standard deviation between 0.5 and 1.5 km. Considering the differences, mainly due to the temporal collocation and the difference, between the satellite pixel size and the point view of the ground-based observations, these results can be quite promising and demonstrate that stable and extended aerosol layers as captured by the satellite sensors are verified by the ground-based data. We further present an in-depth analysis of a strong and long-lasting Saharan dust intrusion over the Iberian Peninsula. We show that, for this well-developed and spatially well-spread aerosol layer, most GOME-2 retrievals fall within 1 km of the exact temporally collocated lidar observation for the entire range of 0 to 150 km radii. This finding further testifies for the capabilities of the MetOp-borne instruments to sense the atmospheric aerosol layer heights.

scholarly journals Comparison of quiet-time ionospheric total electron content from the IRI-2016 model and from gridded and station-level GPS observations

2020 ◽  
Vol 38 (3) ◽  
pp. 725-748
Author(s):  
Gizaw Mengistu Tsidu ◽  
Mulugeta Melaku Zegeye
Keyword(s):  
Total Electron Content ◽  
Local Time ◽  
Zenith Angle ◽  
Solar Zenith Angle ◽  
Mean Absolute Error ◽  
Model Performance ◽  
Absolute Error ◽  
Electron Content ◽  
Total Electron ◽  
The Difference

Abstract. Earth's ionosphere is an important medium of radio wave propagation in modern times. However, the effective use of the ionosphere depends on the understanding of its spatiotemporal variability. Towards this end, a number of ground- and space-based monitoring facilities have been set up over the years. The information from these stations has also been complemented by model-based studies. However, assessment of the performance of ionospheric models in capturing observations needs to be conducted. In this work, the performance of the IRI-2016 model in simulating the total electron content (TEC) observed by a network of Global Positioning System (GPS) receivers is evaluated based on the RMSE, the bias, the mean absolute error (MAE) and skill score, the normalized mean bias factor (NMBF), the normalized mean absolute error factor (NMAEF), the correlation, and categorical metrics such as the quantile probability of detection (QPOD), the quantile categorical miss (QCM), and the quantile critical success index (QCSI). The IRI-2016 model simulations are evaluated against gridded International Global Navigation Satellite System (GNSS) Service (IGS) GPS-TEC and TEC observations at a network of GPS receiver stations during the solar minima in 2008 and solar maxima in 2013. The phases of modeled and simulated TEC time series agree strongly over most of the globe, as indicated by a high correlations during all solar activities with the exception of the polar regions. In addition, lower RMSE, MAE, and bias values are observed between the modeled and measured TEC values during the solar minima than during the solar maxima from both sets of observations. The model performance is also found to vary with season, longitude, solar zenith angle, and magnetic local time. These variations in the model skill arise from differences between seasons with respect to solar irradiance, the direction of neutral meridional winds, neutral composition, and the longitudinal dependence of tidally induced wave number four structures. Moreover, the variation in model performance as a function of solar zenith angle and magnetic local time might be linked to the accuracy of the ionospheric parameters used to characterize both the bottom- and topside ionospheres. However, when the NMBF and NMAEF are applied to the data sets from the two distinct solar activity periods, the difference in the skill of the model during the two periods decreases, suggesting that the traditional model evaluation metrics exaggerate the difference in model skill. Moreover, the performance of the model in capturing the highest ends of extreme values over the geomagnetic equator, midlatitudes, and high latitudes is poor, as noted from the decrease in the QPOD and QCSI as well as an increase in the QCM over most of the globe with an increase in the threshold percentile TEC values from 10 % to 90 % during both the solar minimum and the solar maximum periods. The performance of IRI-2016 in simulating observed low (as low as the 10th percentile) and high (higher than the 90th percentile) TEC correctly over equatorial ionization anomaly (EIA) crest regions is reasonably good given that IRI-2016 is a climatological model. However, it is worth noting that the performance of the IRI-2016 model is relatively poor in 2013 compared with 2008 at the highest ends of the TEC distribution. Therefore, this study reveals the strengths and weaknesses of the IRI-2016 model in simulating the observed TEC distribution correctly during all seasons and solar activities for the first time.

scholarly journals A Multispectral Technique for Detecting Low-Level Cloudiness near Sunrise

2007 ◽  
Vol 24 (10) ◽  
pp. 1800-1810 ◽  
Author(s):  
Anthony J. Schreiner ◽  
Steven A. Ackerman ◽  
Bryan A. Baum ◽  
Andrew K. Heidinger
Keyword(s):  
Zenith Angle ◽  
Solar Zenith Angle ◽  
Infrared Range ◽  
Difference Threshold ◽  
Low Clouds ◽  
Time Period ◽  
Dead Vegetation ◽  
The Difference ◽  
Simple Difference ◽  
Visible Reflectance

Abstract A technique using the Geostationary Operational Environmental Satellite (GOES) sounder radiance data has been developed to improve detection of low clouds and fog just after sunrise. The technique is based on a simple difference method using the shortwave (3.7 μm) and longwave (11.0 μm) window bands in the infrared range of the spectrum. The time period just after sunrise is noted for the difficulty in being able to correctly identify low clouds and fog over land. For the GOES sounder cloud product this difficulty is a result of the visible reflectance of the low clouds falling below the “cloud” threshold over land. By requiring the difference between the 3.7- and the 11.0-μm bands to be greater than 5.0 K, successful discrimination of low clouds and fog is found 85% of the time for 21 cases from 14 September 2005 to 6 March 2006 over the GOES-12 sounder domain. For these 21 clear and cloudy cases the solar zenith angle ranged from 87° to 77°; however, the range of solar zenith angles for cloudy cases was from 85° to 77°. The success rate further improved to 95% (20 out of 21 cases) by including a difference threshold of 5.0 K between the 3.7- and 4.0-μm bands, requiring that the 11.0-μm band be greater than 260 K, and limiting the test to fields of view where the surface elevation is below 999 m. These final three limitations were needed to more successfully deal with cases involving snow cover and dead vegetation. To ensure that only the time period immediately after sunrise is included the solar zenith angle threshold for application of these tests is between 89° and 70°.

TOPAS ozone profile retrieval from TROPOMI L1B version 2 dataset

2021 ◽  
Author(s):  
Nora Mettig ◽  
Mark Weber ◽  
Alexei Rozanov ◽  
Carlo Arosio ◽  
John P. Burrows ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Stratospheric Ozone ◽  
A Priori ◽  
Spectral Radiance ◽  
Absolute Calibration ◽  
Mean Deviation ◽  
Data Set ◽  
Ozone Profile ◽  
Ground Based Lidar ◽  
Mean Differences

&lt;p&gt;The TOPAS (Tikhonov regularized Ozone Profile retrievAl with SCIATRAN) algorithm to retrieve vertical profiles of ozone from space-borne observations in nadir viewing geometry has been developed at the Institute of Environmental Physics (IUP) of the University of Bremen and applied to TROPOMI L1B spectral data version 2. The data set covers the period from June 2018 to October 2019. But it is not available continuously, but for only single weeks of all 3 months. TROPOMI spectral radiance from channel UV1 and UV2 between 270 nm and 331 nm are used for the retrieval. Since the ozone profiles are very sensitive to absolute calibration at short wavelengths, a re-calibration of the measured radiances is required using comparisons with simulated radiances with ozone limb profiles from collocated MLS/Aura used as input. The time-independent re-calibration bases on simulations for cloud-free pixels of four orbits distributed over the time period. Studies with synthetic spectra show that individual profiles in the stratosphere can be retrieved with the accuracy of about 10%. In the troposphere, the retrieval errors are larger depending on the a-priori profile used. The vertical resolution is between 6 and 10 km above 18 km altitude and 15 &amp;#8211; 25 km below. There are around 6 degree of freedom between 0 &amp;#8211; 60 km. The TOPAS ozone profiles retrieved from TROPOMI were validated using data from ozone sondes and stratospheric ozone lidars. Above 18 km, the comparison with sondes shows excellent agreement within less than &amp;#177; 5% for all latitudes. The standard deviation of mean differences is about 10%. Below 18 km, the relative mean deviation in the tropics and northern latitudes is still quite good remaining within &amp;#177; 20%. At southern latitudes larger differences of up to +40% occur between 10 and 15 km. Here the standard deviation is about 50% between 7 and 18 km and about 25% below 7 km. The validation of stratospheric ozone profiles with ground-based lidar measurements also shows very good agreement. The relative mean deviation is below &amp;#177; 5% in the 18 &amp;#8211; 45 km range with a standard deviation of 10%. A pilot application for one day of TROPOMI data with a comparison to MLS and OMPS confirmed the lidar validation results. The relative mean difference between TROPOMI and MLS or OMPS is largely below &amp;#177; 5% between 20 &amp;#8211; 50 km except for the very high latitudes where differences are getting larger.&lt;/p&gt;

scholarly journals First validation of GOME-2/MetOp Absorbing Aerosol Height using EARLINET lidar observations

2020 ◽  
Author(s):  
Konstantinos Michailidis ◽  
Maria-Elissavet Koukouli ◽  
Nikolaos Siomos ◽  
Dimitrios Balis ◽  
Olaf Tuinder ◽  
...  
Keyword(s):  
Saharan Dust ◽  
Aerosol Layer ◽  
Pixel Size ◽  
Geometrical Features ◽  
Depth Analysis ◽  
Satellite Sensors ◽  
The Mean ◽  
The Difference ◽  
Ground Based Lidar ◽  
Lidar Observations

Abstract. The aim of this study is to investigate the potential of GOME-2 instruments on board the MetOpA, MetOpB and MetOpC platforms, to deliver accurate geometrical features of lofted aerosol layers. For this purpose, we use archived ground-based lidar data from lidar stations available fromEuropean Aerosol Research Lidar Network (EARLINET) database. The data are post-processed with the wavelet covariance transform (WCT) method in order to extract geometrical features such as the Planetary Boundary Layer, PBL, height and the cloud boundaries. To obtain a significant number of collocated and coincident GOME-2 – EARLINET cases for the period between January 2007 and September 2019, fourteenlidar stations, distributed over different European latitudes, contributed to this validation. For the 172 carefully screened collocations, the mean bias was found to be −0.18 ± 1.68 km, with a near Gaussian distribution. On a station-basis, and with a couple of exceptions where very few collocations were found, their mean biases fall in the ± 1 km range with an associated standard deviation between 0.5 and 1.5 km. Considering the differences, mainly due to the temporal collocation and the difference between the satellite pixel size and the point view of the ground-based observations, these results are quite promising and demonstrating that stable and extended aerosol layers as captured by the satellite sensors, are verified by the ground-based data. We further present an in-depth analysis of a strong and long-lasting Saharan dust intrusion over the Iberian Peninsula. We show that for, this well-developed and spatially well-spread aerosol layer, most GOME-2 retrievals fall within 1 km of the exactly temporally collocated lidar observation for the entire range of 0 to 150 km radii. This finding further testifies to the capabilities of the MetOp-born instruments to sense the atmospheric aerosol layer height.

scholarly journals Ozone profile retrieval from nadir TROPOMI measurements in the UV range

2021 ◽  
Vol 14 (9) ◽  
pp. 6057-6082
Author(s):  
Nora Mettig ◽  
Mark Weber ◽  
Alexei Rozanov ◽  
Carlo Arosio ◽  
John P. Burrows ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Spectral Data ◽  
Stratospheric Ozone ◽  
A Priori ◽  
Mean Deviation ◽  
Vertical Resolution ◽  
Ozone Profile ◽  
Ground Based Lidar ◽  
Using Data ◽  
Mean Differences

Abstract. The TOPAS (Tikhonov regularised Ozone Profile retrievAl with SCIATRAN) algorithm to retrieve vertical profiles of ozone from space-borne observations in nadir-viewing geometry has been developed at the Institute of Environmental Physics (IUP) of the University of Bremen and applied to the TROPOspheric Monitoring Instrument (TROPOMI) L1B spectral data version 2. Spectral data between 270 and 329 nm are used for the retrieval. A recalibration of the measured radiances is done using ozone profiles from MLS/Aura. Studies with synthetic spectra show that individual profiles in the stratosphere can be retrieved with an uncertainty of about 10 %. In the troposphere, the retrieval errors are larger depending on the a priori profile used. The vertical resolution above 18 km is about 6–10 km, and it degrades to 15–25 km below. The vertical resolution in the troposphere is strongly dependent on the solar zenith angle (SZA). The ozone profiles retrieved from TROPOMI with the TOPAS algorithm were validated using data from ozonesondes and stratospheric ozone lidars. Above 18 km, the comparison with sondes shows excellent agreement within less than ±5 % for all latitudes. The standard deviation of mean differences is about 10 %. Below 18 km, the relative mean deviation in the tropics and northern latitudes is still quite good, remaining within ±20 %. At southern latitudes, larger differences of up to +40 % occur between 10 and 15 km. The standard deviation is about 50 % between 7–18 km and about 25 % below 7 km. The validation of stratospheric ozone profiles with ground-based lidar measurements also shows very good agreement. The relative mean deviation is below ±5 % between 18–45 km, with a standard deviation of 10 %. TOPAS retrieval results for 1 d of TROPOMI observations were compared to ozone profiles from the Microwave Limb Sounder (MLS) on the Aura satellite and the Ozone Mapping and Profiler Suite Limb Profiler (OMPS-LP). The relative mean difference was found to be largely below ±5 % between 20–50 km, except at very high latitudes.

scholarly journals HDO/H<sub>2</sub>O ratio retrievals from GOSAT

2012 ◽  
Vol 5 (5) ◽  
pp. 6643-6677 ◽  
Author(s):  
H. Boesch ◽  
N. M. Deutscher ◽  
T. Warneke ◽  
K. Byckling ◽  
A. J. Cogan ◽  
...  
Keyword(s):  
Zenith Angle ◽  
Solar Zenith Angle ◽  
A Priori ◽  
Regional Scale ◽  
Atmospheric Temperature ◽  
Total Carbon ◽  
Latitudinal Gradients ◽  
Random Errors ◽  
Synthetic Simulation ◽  
Shortwave Infrared

Abstract. We report a new shortwave infrared (SWIR) retrieval of the column-averaged HDO/H2O ratio from the Japanese Greenhouse Gases Observing SATellite (GOSAT). From synthetic simulation studies, we have estimated that the inferred δD values will typically have random errors between 20‰ (desert surface and 30° solar zenith angle) and 120‰ (conifer surface and 60° solar zenith angle). We find that the retrieval will have a small, but significant sensitivity to the presence of cirrus clouds, the HDO a priori profile shape and atmospheric temperature, which has the potential for introducing some regional-scale biases in the retrieval. From comparisons to ground-based column observations from the Total Carbon Column Observing Network (TCCON) we find differences between δD from GOSAT and TCCON of around −30‰ for northern-hemispheric sites which increase up to −70‰ for Australian sites. The bias for the Australian sites significantly reduces when decreasing the spatial co-location criteria, which shows that spatial averaging contributes to the observed differences over Australia. The GOSAT retrievals allow mapping the global distribution of δD and its variations with season and we find in our global GOSAT retrievals the expected strong latitudinal gradients with significant enhancements over the tropics. The comparisons to the ground-based TCCON network and the results of the global retrieval are very encouraging and they show that δD retrieved from GOSAT should be a useful product that can be used to complement datasets from thermal-infrared sounder and ground-based networks and to extend the δD dataset from SWIR retrievals established from the recently ended SCIAMACHY mission.

Sign in / Sign up

Export Citation Format

Share Document