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7 results for “SCIAMACHY”
Merged SCIAMACHY-OMPS limb ozone time series
<p>This data set contains the time series of merged monthly mean ozone profiles retrieved at the University of Bremen from SCIAMACHY and OMPS-LP limb observations. The merging is performed on deseasonalized anomalies, but the data set contains also the reconstructed number density time series. The data set is longitudinally resolved, with a 5° latitude and 20° longitude resolution, and a vertical grid with 3.3 km spacing. </p>
Nitric oxide (NO) data set (60--160 km) from SCIAMACHY mesosphere--lower thermosphere limb scans
<p><strong>Overview</strong><br> Contains the nitric oxide (NO) number densities (in cm<sup>-3</sup>) from 60 km to 160 km retrieved from SCIAMACHY mesosphere--lower thermosphere (MLT, 50--150 km) limb scans.</p> <p>SCIAMACHY is a UV-visible-near-infrared spectrometer which flies on ESA's Envisat and was operational from 08/2002 to 04/2012 (see Burrows et al., 1995 and Bovensmann et al., 1999 and references therein). The Mesosphere--Lower Thermosphere (MLT) measurement mode was carried out from 07/2008 until the end of the mission for one day every 15 days. This data set comprises 84 days of SCIAMACHY MLT NO measurements, each<br> containing about 15 orbits.</p> <p>The NO retrieval was carried out at the Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany, and is described in Bender et al., 2013. We used the SCIAMACHY geo-located atmospheric spectra (SCI_NL__1P) version 8.02 provided by ESA via their data browser at<br> https://earth.esa.int/web/guest/data-access/browse-data-products.<br> The spectra were calibrated with ESA's `SciaL1C` command line tool available for download at<br> https://earth.esa.int/web/guest/software-tools/content/-/article/scial1c-command-line-tool-4073.</p> <p>The SCIAMACHY NO data were compared to the results from ACE-FTS, MIPAS, and SMR in Bender et al., 2015, showing that all agree within the respective measurement uncertainties.</p> <p><strong>Acknowledgements</strong><br> The development of the retrieval was funded by the Helmholtz-society under the grant number VH-NG-624. The SCIAMACHY project, which was initiated by Professor Burrows in 1984, was funded by the German Aerospace Agency (DLR), the Netherlands Space Office NSO, formerly NIVR, and the Belgium ministry responsible for space. ESA funded the Envisat project. Professor Burrows of University of Bremen is the Principal Investigator. He and his research team comprising his colleagues in Bremen and international scientific collaborators led the scientific support and development of SCIAMACHY and the scientific exploitation of its data products.</p> <p>The SCIAMACHY instrument is developed by an industrial team headed by companies now known as Airbus SD on the German side and by Dutch Space on the Dutch side and included Belgium companies. The instrument and algorithm development is supported by the activities of the SCIAMACHY Science Advisory Group (SSAG), a team of scientists from various international institutions: University of Bremen (D), SRON (NL), SAO (USA), IASB (B), MPI Chemistry Mainz (D), KNMI (NL), University of Heidelberg (D), IMGA (I), CNRS-LPMA (F). Operational data processing is being performed by ESA and DLR-DFD within the ENVISAT ground segment. Support with respect to mission planning and operations is given by the SCIAMACHY Operations Support Team (SOST). The relevant work at the University of Bremen is funded by the University and State of Bremen.</p>
Nitric oxide (NO) data set (60--160 km) from SCIAMACHY nominal limb scans
<p><strong>Overview</strong><br> Contains the nitric oxide (NO) number densities (in cm<sup>-3</sup>) from 60 km to 160 km retrieved from SCIAMACHY nominal (~0--90 km) limb scans.</p> <p>SCIAMACHY is a UV-visible-near-infrared spectrometer which flies on ESA's Envisat and was operational from 08/2002 to 04/2012 (see Burrows et al., 1995 and Bovensmann et al., 1999 and references therein). The nominal limb mode was carried out daily (apart from outages and a few days dedicated to other measurement modes) from 08/2002 until the end of the mission. The limb scans were performed from ground to about 90 km tangent altitude, and the retrieval was performed on a 2.5° x 2 km latitude--altitude grid from 90°S--90°N and from 60 km--160 km. This data set comprises all SCIAMACHY nominal NO measurements sorted by date and year, each day comprised about 15 orbits. See the accompanying README for the dimension and variable descriptions.</p> <p>The NO retrieval was carried out at the Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany, and is described in Bender et al., 2017. It is adapted from the MLT NO retrieval described in Bender et al., 2013. We used the SCIAMACHY geo-located atmospheric spectra (SCI_NL__1P) version 8.02 provided by ESA via their data browser at<br> https://earth.esa.int/web/guest/data-access/browse-data-products.<br> The spectra were calibrated with ESA's `SciaL1C` command line tool available for download at<br> https://earth.esa.int/web/guest/software-tools/content/-/article/scial1c-command-line-tool-4073.</p> <p>The SCIAMACHY MLT NO data were previously compared to the results from ACE-FTS, MIPAS, and SMR in Bender et al., 2015, showing that all agree within the respective measurement uncertainties. This nominal data set here was not yet validated with other measurements but compares well to the SCIAMACHY MLT NO measurements below 90 km.</p> <p><strong>Acknowledgements</strong><br> The development of the retrieval was funded by the Helmholtz-society under the grant number VH-NG-624. The SCIAMACHY project, which was initiated by Professor Burrows in 1984, was funded by the German Aerospace Agency (DLR), the Netherlands Space Office NSO, formerly NIVR, and the Belgium ministry responsible for space. ESA funded the Envisat project. Professor Burrows of University of Bremen is the Principal Investigator. He and his research team comprising his colleagues in Bremen and international scientific collaborators led the scientific support and development of SCIAMACHY and the scientific exploitation of its data products.</p> <p>The SCIAMACHY instrument is developed by an industrial team headed by companies now known as Airbus SD on the German side and by Dutch Space on the Dutch side and included Belgium companies. The instrument and algorithm development is supported by the activities of the SCIAMACHY Science Advisory Group (SSAG), a team of scientists from various international institutions: University of Bremen (D), SRON (NL), SAO (USA), IASB (B), MPI Chemistry Mainz (D), KNMI (NL), University of Heidelberg (D), IMGA (I), CNRS-LPMA (F). Operational data processing is being performed by ESA and DLR-DFD within the ENVISAT ground segment. Support with respect to mission planning and operations is given by the SCIAMACHY Operations Support Team (SOST). The relevant work at the University of Bremen is funded by the University and State of Bremen.</p>
SCIAMACHY NO regression fit MCMC samples
<p><strong>SCIAMACHY mesosphere NO data and regression model samples</strong></p> <p>SCIAMACHY mesosphere daily zonal mean NO data and Markov-Chain Monte-Carlo samples from the regression coefficient distributions, derived from and for use with the <a href="https://github.com/st-bender/sciapy"><code>sciapy</code></a> regression module.</p> <p>This data set contains the following files:</p> <ul> <li><code>NO_regress_output_pGM_Lya_ltcs_exp1dscan60d_km32_float32.nc</code>, <code>NO_regress_output_pGM_Lya_ltcs_exp1dscan60d_km32_float64.nc</code> - samples from the regression coefficient distributions (single and double precision)</li> <li><code>NO_regress_quantiles_pGM_Lya_ltcs_exp1dscan60d_km32.nc</code> - the 0.1, 2.5, 16, 50, 84, 97.5, and 99.9 percentiles of the sampled distributions</li> <li><code>scia_nom_dzmNO_2002-2012_v6.2.1_2.2_akm0.002_geomag10_nw.nc</code> - the SCIAMACHY daily zonal mean NO data</li> <li><code>sciapy_regress_tutorial.ipynb</code> - example ipython notebook</li> </ul> <p><strong>MCMC Samples</strong></p> <p>The files <code>NO_regress_output..._float32.nc</code> and <code>NO_regress_output..._float64.nc</code> contain MCMC samples of the model as single and double precision floats. The file <code>NO_regress_quantiles....nc</code> contains the 0.1, 2.5, 16, 50, 84, 97.5, and 99.9 percentiles of the sampled distributions and is provided for convenience. The files contain the following parameters:</p> <ul> <li><code>kernel:log_sigma</code>, <code>kernel:log_rho</code> - the "strength" and "lengthscale" of the Matérn-3/2 Gaussian Process kernel</li> <li><code>mean:offset:value</code> - the constant offset of the NO model in [<span class="math-tex">\(10^6\)</span> cm<span class="math-tex">\(^{-3}\)</span>]</li> <li><code>mean:Lya:amp</code> - the Lyman-<span class="math-tex">\(\alpha\)</span> coefficient of the mean model in [<span class="math-tex">\(10^6\)</span> cm<span class="math-tex">\(^{-3}\)</span> / Lyman-<span class="math-tex">\(\alpha\)</span>]</li> <li><code>mean:GM:amp</code> - the geomagnetic coefficient (AE) in [<span class="math-tex">\(10^6\)</span> cm<span class="math-tex">\(^{-3}\)</span> / nT]</li> <li><code>mean:GM:tau0</code> - the constant lifetime of the geomagnetic lifetime in [d]</li> <li><code>mean:GM:taucos1</code>, <code>mean:GM:tausin1</code> - cosine and sine amplitudes of the yearly geomagnetic lifetime variation in [d]</li> </ul> <p><strong>Daily zonal mean NO data</strong></p> <p>The model was trained on the <a href="http://doi.org/10.5281/zenodo.1009078">SCIAMACHY mesosphere NO dataset</a>, binned into 10° geomagnetic latitude bins using the provided <code>gm_lat</code> variable and using the standard error of the mean as data uncertainties. The data are uploaded as <code>scia_nom_dzmNO_2002-2012_v6.2.1_2.2_akm0.002_geomag10_nw.nc</code> and were prepared by running (after installing <code><a href="https://github.com/st-bender/sciapy">sciapy</a>)</code>:</p> <pre><code class="language-bash">bash> scia_daily_zonal_mean.py -g -b'-90:90:10' -o <daily_zonal_mean_NO.nc> </path/to/SCIAMACHY_NO_NOM_orbits_20??_v6.2.1.nc></code></pre> <p><strong>Regression sampling</strong></p> <p>The samples were generated by running the following command:</p> <pre><code class="language-bash">bash> python -m sciapy.regress <daily_zonal_mean_NO.nc> --proxies Lya:<Lyman-alpha_file.dat>,GM:<AE_file.dat> -A <altitude> -L <geomag_latitude_bin> -w 14 -b 800 -p 1400 -F \"\" -I GM --fit_annlifetimes GM --positive_proxies GM --lifetime_scan=60 --lifetime_prior exp -k -K Mat32 -O0 -m "nom_pGM_Lya_ltcs_exp1dscan60d_km32" -P</code></pre> <p> </p>
Global High-Resolution Estimates of SIF from Fused SCIAMACHY and GOME-2, V2
This dataset provides global solar-induced chlorophyll fluorescence (SIF) estimates at a 0.05-degree resolution (approximately 5 km at the equator) for each month from January 2003 through December 2017. SIF data (740 nm) was retrieved from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) and Global Ozone Monitoring Experiment 2 (GOME-2) instruments onboard the MetOp-A satellite. The data were downscaled to 0.05 degrees using the Random Forest algorithm and predictors from Moderate Resolution Imaging Spectroradiometer (MODIS) and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis, and then harmonized with the cumulative distribution function (CDF) matching technique. The uncertainty of the harmonized SIF estimates was also quantified and provided. Validation of the harmonized product showed that it retained high spatial and temporal consistency with the original SCIAMACHY and GOME-2 SIF retrievals and had good correlations with independent airborne and ground-based SIF measurements. The dataset can inform on the synergy between satellite SIF and photosynthesis and research on drought, yield estimation, and land degradation evaluation. The data are provided in netCDF format.
L2 Solar-Induced Fluorescence (SIF) from SCIAMACHY, 2003-2012
This dataset provides Level 2 (L2) Solar-Induced Fluorescence (SIF) of chlorophyll estimates derived from the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) instrument on the European Space Agency's (ESA's) Environmental satellite (Envisat) with ~0.5 nm spectral resolution and wavelengths between 734 and 758 nm. SCIAMACHY covers global land between approximately 70 and -57 degrees latitude on an orbital basis at a resolution of approximately 30 km x 240 km. Data are provided for the period from 2003-01-01 to 2012-04-08. Each file contains daily raw and bias-adjusted solar-induced fluorescence along with quality control information and ancillary data.
Global 3-Year Running Mean Ground-Level Nitrogen Dioxide (NO2) Grids from GOME, SCIAMACHY and GOME-2
The Global 3-Year Running Mean Ground-Level Nitrogen Dioxide (NO2) Grids from GOME, SCIAMACHY and GOME-2 represent a series of three-year running mean grids (1996-2012) of ground level NO2 that were derived from Global Ozone Monitoring Experiment (GOME), SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) and Global Ozone Monitoring Experiment-2 (GOME-2) satellite retrievals. For each satellite-derived NO2 source, the relationship between satellite observations of tropospheric NO2 column densities and the NO2 concentrations at ground level relevant to human exposure is simulated, using the Goddard Earth Observing System chemical transport model (GEOS-Chem) to produce a mean NO2 concentration raster grid. The grid cell resolution is six arc-minutes (0.1 degree, or approximately 10 km at the equator) covering the global land surface.
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