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This SI collects some papers regarding the retrieval, calibration, validation, analysis of data and uncertainties, as well as comparative studies on atmospheric gases and water vapor by remote sensing techniques, where different types of sensors, instruments, and algorithms are used or developed.<\/jats:p>","DOI":"10.3390\/rs12132074","type":"journal-article","created":{"date-parts":[[2020,6,29]],"date-time":"2020-06-29T11:17:17Z","timestamp":1593429437000},"page":"2074","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Editorial for the Special Issue \u201cRemote Sensing of Atmospheric Components and Water Vapor\u201d"],"prefix":"10.3390","volume":"12","author":[{"given":"Victoria E.","family":"Cachorro","sequence":"first","affiliation":[{"name":"Department of Experimental Sciences Teaching (feyts), \u201cAtmospheric Optics Group\u201d, University of Valladolid, Paseo de Bel\u00e9n, 7. Campus Miguel Delibes, 47011 Valladolid, Spain"}]},{"given":"Manuel","family":"Ant\u00f3n","sequence":"additional","affiliation":[{"name":"Department of Physics, University of Extremadura, Avenida de Elvas s\/n, 06006 Badajoz, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1343","DOI":"10.1088\/0034-4885\/68\/6\/R02","article-title":"Global warming","volume":"68","author":"Houghton","year":"2005","journal-title":"Rep. Prog. Phys."},{"key":"ref_2","unstructured":"(2020, May 26). AR5\/IPCC 2013\/2014. Available online: www.climatechange2013.org\/; https:\/\/www.ipcc.ch."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"741","DOI":"10.1007\/s00382-005-0017-4","article-title":"Trends and variability in column-integrated water vapour","volume":"247","author":"Threnberth","year":"2005","journal-title":"Clim. Dyn."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1175\/JHM600.1","article-title":"Estimates of the Global Water Budget and Its Annual Cycle Using Observational and Model Data","volume":"8","author":"Trenberth","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2119","DOI":"10.1126\/science.1064034","article-title":"Aerosol, climate, and the hidrologycal cycle","volume":"294","author":"Ramanathan","year":"2001","journal-title":"Science"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Karmakar, P.K. (2014). Ground-Based Microwave Radiometry and Remote Sensing: Methods and Applications, CRC Press, Taylor and Francis Group.","DOI":"10.1201\/b15494"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1935","DOI":"10.1002\/qj.2080","article-title":"The evaluation of the integrated water vapor annual cycle over the Iberian Peninsula from EOS-MODIS against different ground-based techniques","volume":"139","author":"Benounna","year":"2013","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_8","first-page":"214","article-title":"Validation of MODIS integrated water vapor product against reference GPS data at the Iberian Peninsula","volume":"63","author":"Cachorro","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"D07302","DOI":"10.1029\/2010JD014675","article-title":"The GOME-2 total column ozone product: Retrieval algorithm and ground-based validation","volume":"116","author":"Loyola","year":"2011","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1639","DOI":"10.1002\/2013JD020831","article-title":"Homogenized total ozone data records from the European sensors GOME\/ERS-2, SCIAMACHY\/Envisat, and GOME-2\/MetOp-A","volume":"119","author":"Lerot","year":"2014","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1927","DOI":"10.5194\/amt-10-1927-2017","article-title":"Validation of MOPITT carbon monoxide using ground-based Fourier transform infrared spectrometer data from NDACC","volume":"10","author":"Buchholz","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"104019","DOI":"10.1088\/1464-4258\/10\/10\/104019","article-title":"Monitoring of atmospheric trace gases, clouds, aerosols and surface properties from UV\/vis\/NIR satellite instruments","volume":"10","author":"Wagner","year":"2008","journal-title":"J. Opt. A Pure Appl. Opt."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1016\/j.rse.2017.09.028","article-title":"Inter-comparison of integrated water vapor from satellite instruments using reference GPS data at the Iberian Peninsula","volume":"204","author":"Cachorro","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"6269","DOI":"10.5194\/acp-19-6269-2019","article-title":"Trends and trend reversal detection in 2 decades of tropospheric NO2 satellite observations","volume":"19","author":"Georgoulias","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1109\/TGRS.2002.808236","article-title":"Retrieval of atmospheric and surface parameters from AIRS\/AMSU\/HSB data in the presence of clouds","volume":"41","author":"Susskind","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1007\/s12040-019-1325-0","article-title":"Trend analysis of atmospheric temperature, water vapour, ozone, methane and carbon-monoxide over few major cities of India using satellite data","volume":"129","author":"Jindal","year":"2020","journal-title":"J. Earth Syst. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/jgrd.50669","article-title":"Tropospheric ozone and nitrogen dioxide measurements in urban and rural regions as seen by IASI and GOME-2","volume":"118","author":"Safieddine","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4171","DOI":"10.5194\/amt-11-4171-2018","article-title":"The MUSICA IASI CH4 and N2O products and their comparison to HIPPO, GAW and NDACC FTIR","volume":"11","author":"Schneider","year":"2018","journal-title":"Atmos. Meas. Tech."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3921","DOI":"10.5194\/amt-9-3921-2016","article-title":"HDO and H2O total column retrievals from TROPOMI shortwave infrared measurements","volume":"9","author":"Scheepmaker","year":"2016","journal-title":"Atmos. Meas. Tech."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"119","DOI":"10.5194\/amt-10-119-2017","article-title":"Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 Precursor: Algorithm theoretical basis","volume":"10","author":"Theys","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"D21301","DOI":"10.1029\/2012JD018087","article-title":"Atmospheric carbon dioxide retrieved from the Greenhouse gases Observing SATellite (GOSAT): Comparison with ground-based TCCON observations and GEOS-Chem model calculations","volume":"117","author":"Cogan","year":"2012","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Fionda, E., Cadeddu, M., Mattioli, V., and Pacione, R. (2019). Intercomparison of Integrated Water Vapor Measurements at High Latitudes from Co-Located and Near-Located Instruments. Remote Sens., 11.","DOI":"10.3390\/rs11182130"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Carbajal Henken, C., Dirks, L., Steinke, S., Diedrich, H., August, T., and Crewell, S. (2020). Assessment of Sampling Effects on Various Satellite-Derived Integrated Water Vapor Datasets Using GPS Measurements in Germany as Reference. Remote Sens., 12.","DOI":"10.3390\/rs12071170"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Ngoc Trieu, T.T., Morino, I., Ohyama, H., Uchino, O., Sussmann, R., Warneke, T., Petri, C., Kivi, R., Hase, F., and Pollard, D.F. (2019). Evaluation of Bias Correction Methods for GOSAT SWIR XH2O Using TCCON data. Remote Sens., 11.","DOI":"10.3390\/rs11030290"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Jiang, X., Li, J., Li, Z., Xue, Y., Di, D., Wang, P., and Li, J. (2020). Evaluation of Environmental Moisture from NWP Models with Measurements from Advanced Geostationary Satellite Imager\u2014A Case Study. Remote Sens., 12.","DOI":"10.3390\/rs12040670"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Almansa, A.F., Cuevas, E., Barreto, A., Torres, B., Garc\u00eda, O.E., Garc\u00eda, R.D., Velasco-Merino, C., Cachorro, V.E., Berj\u00f3n, A., and Mallorqu\u00edn, M. (2020). Column integrated water vapour and aerosol load 2 characterization with the new ZEN-R52 radiometer. Remote Sens., 12.","DOI":"10.3390\/rs12091424"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Kulla, B.S., and Ritter, C. (2019). Water Vapor Calibration: Using a Raman Lidar and Radiosoundings to Obtain Highly Resolved Water Vapor Profiles. Remote Sens., 11.","DOI":"10.3390\/rs11060616"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Zhang, X., Liu, J., Han, H., Zhang, Y., Jiang, Z., Wang, H., Meng, L., Li, Y.C., and Liu, Y. (2020). Satellite-Observed Variations and Trends in Carbon Monoxide over Asia and Their Sensitivities to Biomass Burning. Remote Sens., 12.","DOI":"10.3390\/rs12050830"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Wang, W., Wang, Z., and Duan, Y. (2020). Preliminary Evaluation of the Error Budgets in the TALIS Measurements and Their Impact on the Retrievals. Remote Sens., 12.","DOI":"10.3390\/rs12030468"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Wang, Y., Tao, J., Cheng, L., Yu, C., Wang, Z., and Chen, L. (2019). An improved retrieval of glyoxal from OMI over China. Remote Sens., 11.","DOI":"10.3390\/rs11020137"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Mateos, D., and Ant\u00f3n, M. (2020). Worldwide Evaluation of Ozone Radiative Forcing in the UV-B Range between 1979 and 2014. Remote Sens., 12.","DOI":"10.3390\/rs12030436"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Vaquero-Mart\u00ednez, J., Ant\u00f3n, M., Sanchez-Lorenzo, A., and Cachorro, V.E. (2020). Evaluation of Water Vapor Radiative Effects Using GPS Data Series over Southwestern Europe. Remote Sens., 11.","DOI":"10.3390\/rs12081307"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/13\/2074\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:43:53Z","timestamp":1760175833000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/13\/2074"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,28]]},"references-count":32,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2020,7]]}},"alternative-id":["rs12132074"],"URL":"https:\/\/doi.org\/10.3390\/rs12132074","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2020,6,28]]}}}