Editorial for the Special Issue “Remote Sensing of Atmospheric Components and Water Vapor”
Abstract
:Author Contributions
Funding
Conflicts of Interest
References
- Houghton, J. Global warming. Rep. Prog. Phys. 2005, 68, 1343–1403. [Google Scholar] [CrossRef]
- AR5/IPCC 2013/2014. Available online: www.climatechange2013.org/; https://www.ipcc.ch (accessed on 26 May 2020).
- Threnberth, K.E.; Fasullo, J.; Smith, L. Trends and variability in column-integrated water vapour. Clim. Dyn. 2005, 247, 741–758. [Google Scholar] [CrossRef]
- Trenberth, K.E.; Smith, L.; Qian, T.; Dai, A.; Fasullo, J. Estimates of the Global Water Budget and Its Annual Cycle Using Observational and Model Data. J. Hydrometeorol. 2007, 8, 758–769. [Google Scholar] [CrossRef]
- Ramanathan, V.P.; Crutzen, J.; Kiehl, J.T.; Rosenfeld, D. Aerosol, climate, and the hidrologycal cycle. Science 2001, 294, 2119. [Google Scholar] [CrossRef] [Green Version]
- Karmakar, P.K. Ground-Based Microwave Radiometry and Remote Sensing: Methods and Applications; CRC Press, Taylor and Francis Group: Boca Raton, FL, USA, 2014. [Google Scholar]
- Benounna, Y.S.; Torres, B.; Cachorro, V.E.; Ortiz de Galisteo, J.P.; Toledano, C. The evaluation of the integrated water vapor annual cycle over the Iberian Peninsula from EOS-MODIS against different ground-based techniques. Q. J. R. Meteorol. Soc. 2013, 139, 1935–1956. [Google Scholar] [CrossRef]
- Vaquero-Martínez, J.; Antón, M.; de Galisteo, J.P.O.; Cachorro, V.E.; Costae, M.J.; Román, R.; Bennouna, Y.S. Validation of MODIS integrated water vapor product against reference GPS data at the Iberian Peninsula. Int. J. Appl. Earth Obs. Geoinf. 2017, 63, 214–221. [Google Scholar] [CrossRef] [Green Version]
- Loyola, D.G.; Koukouli, M.E.; Valks, P.; Balis, D.S.; Hao, N.; Van Roozendael, M.; Spurr, R.J.D.; Zimmer, W.; Kiemle, S.; Lerot, C.; et al. The GOME-2 total column ozone product: Retrieval algorithm and ground-based validation. J. Geophys. Res. Atmos. 2011, 116, D07302. [Google Scholar] [CrossRef]
- Lerot, C.; Van Roozendael, M.; Spurr, R.; Loyola, D.; Coldewey-Egbers, M.; Kochenova, S.; van Gent, J.; Koukouli, M.; Balis, D.; Lambert, J.-C.; et al. Homogenized total ozone data records from the European sensors GOME/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A. J. Geophys. Res. Atmos. 2014, 119, 1639–1662. [Google Scholar] [CrossRef]
- Buchholz, R.R.; Deeter, M.R.; Worden, H.M.; Gille, J.; Edwards, D.P.; Hannigan, J.W.; Jones, N.B.; Paton-Walsh, C.; Griffith, D.W.T.; Smale, S.; et al. Validation of MOPITT carbon monoxide using ground-based Fourier transform infrared spectrometer data from NDACC. Atmos. Meas. Tech. 2017, 10, 1927–1956. [Google Scholar] [CrossRef] [Green Version]
- Wagner, T.; Beirle, S.; Deutschmann, T.; Eigemeier, E.; Frankenberg, C.; Grzegorski, M.; Liu, C.; Marbach, T.; Platt, U.; de Vries, M.P. Monitoring of atmospheric trace gases, clouds, aerosols and surface properties from UV/vis/NIR satellite instruments. J. Opt. A Pure Appl. Opt. 2008, 10, 104019. [Google Scholar] [CrossRef]
- Vaquero-Martínez, J.; Antón, M.; de Galisteo, J.P.O.; Cachorro, V.E.; Álvarez-Zapatero, P.; Román, R.; Loyola, D.; Costa, M.J.; Wang, H.; Abad, G.G.; et al. Inter-comparison of integrated water vapor from satellite instruments using reference GPS data at the Iberian Peninsula. Remote Sens. Environ. 2018, 204, 729–740. [Google Scholar] [CrossRef]
- Georgoulias, A.K.; van der A, R.J.; Stammes, P.; Boersma, K.F.; Eskes, H.J. Trends and trend reversal detection in 2 decades of tropospheric NO2 satellite observations. Atmos. Chem. Phys. 2019, 19, 6269–6294. [Google Scholar] [CrossRef] [Green Version]
- Susskind, J.; Barnet, C.; Blaisdell, J. Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds. IEEE Trans. Geosci. Remote Sens. 2003, 41, 390–409. [Google Scholar] [CrossRef]
- Jindal, P.; Thapliyal Pradeep, K.; Shukla Munn, V.; Sharma, S.K.; Mitra, D. Trend analysis of atmospheric temperature, water vapour, ozone, methane and carbon-monoxide over few major cities of India using satellite data. J. Earth Syst. Sci. 2020, 129, 60. [Google Scholar] [CrossRef]
- Safieddine, S.; Clerbaux, C.; George, M.; Hadji-Lazaro, J.; Hurtmans, D.; Coheur, P.-F.; Wespes, C.; Loyola, D.; Valks, P.; Hao, N. Tropospheric ozone and nitrogen dioxide measurements in urban and rural regions as seen by IASI and GOME-2. J. Geophys. Res. Atmos. 2013, 118, 1–12. [Google Scholar] [CrossRef] [Green Version]
- García, O.E.; Schneider, M.; Ertl, B.; Sepúlveda, E.; Borger, C.; Diekmann, C.; Wiegele, A.; Hase, F.; Barthlott, S.; Blumenstock, T.; et al. The MUSICA IASI CH4 and N2O products and their comparison to HIPPO, GAW and NDACC FTIR. Atmos. Meas. Tech. 2018, 11, 4171–4215. [Google Scholar] [CrossRef] [Green Version]
- Scheepmaker, R.A.; aan de Brugh, J.; Hu, H.; Borsdorff, T.; Frankenberg, C.; Risi, C.; Hasekamp, O.; Aben, I.; Landgraf, J. HDO and H2O total column retrievals from TROPOMI shortwave infrared measurements. Atmos. Meas. Tech. 2016, 9, 3921–3937. [Google Scholar] [CrossRef] [Green Version]
- Theys, N.; De Smedt, I.; Yu, H.; Danckaert, T.; van Gent, J.; Hörmann, C.; Wagner, T.; Hedelt, P.; Bauer, H.; Romahn, F.; et al. Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 Precursor: Algorithm theoretical basis. Atmos. Meas. Tech. 2017, 10, 119–153. [Google Scholar] [CrossRef] [Green Version]
- Cogan, A.J.; Boesch, H.; Parker, R.J.; Feng, L.; Palmer, P.I.; Blavier, J.-F.L.; Deutscher, N.M.; Macatangay, R.; Notholt, J.; Roehl, C.; et al. Atmospheric carbon dioxide retrieved from the Greenhouse gases Observing SATellite (GOSAT): Comparison with ground-based TCCON observations and GEOS-Chem model calculations. J. Geophys. Res. Atmos. 2012, 117, D21301. [Google Scholar] [CrossRef] [Green Version]
- Fionda, E.; Cadeddu, M.; Mattioli, V.; Pacione, R. Intercomparison of Integrated Water Vapor Measurements at High Latitudes from Co-Located and Near-Located Instruments. Remote Sens. 2019, 11, 2130. [Google Scholar] [CrossRef] [Green Version]
- Carbajal Henken, C.; Dirks, L.; Steinke, S.; Diedrich, H.; August, T.; Crewell, S. Assessment of Sampling Effects on Various Satellite-Derived Integrated Water Vapor Datasets Using GPS Measurements in Germany as Reference. Remote Sens. 2020, 12, 1170. [Google Scholar] [CrossRef] [Green Version]
- Ngoc Trieu, T.T.; Morino, I.; Ohyama, H.; Uchino, O.; Sussmann, R.; Warneke, T.; Petri, C.; Kivi, R.; Hase, F.; Pollard, D.F.; et al. Evaluation of Bias Correction Methods for GOSAT SWIR XH2O Using TCCON data. Remote Sens. 2019, 11, 290. [Google Scholar] [CrossRef] [Green Version]
- Jiang, X.; Li, J.; Li, Z.; Xue, Y.; Di, D.; Wang, P.; Li, J. Evaluation of Environmental Moisture from NWP Models with Measurements from Advanced Geostationary Satellite Imager—A Case Study. Remote Sens. 2020, 12, 670. [Google Scholar] [CrossRef] [Green Version]
- Almansa, A.F.; Cuevas, E.; Barreto, A.; Torres, B.; García, O.E.; García, R.D.; Velasco-Merino, C.; Cachorro, V.E.; Berjón, A.; Mallorquín, M.; et al. Column integrated water vapour and aerosol load 2 characterization with the new ZEN-R52 radiometer. Remote Sens. 2020, 12, 1424. [Google Scholar] [CrossRef]
- Kulla, B.S.; Ritter, C. Water Vapor Calibration: Using a Raman Lidar and Radiosoundings to Obtain Highly Resolved Water Vapor Profiles. Remote Sens. 2019, 11, 616. [Google Scholar] [CrossRef] [Green Version]
- Zhang, X.; Liu, J.; Han, H.; Zhang, Y.; Jiang, Z.; Wang, H.; Meng, L.; Li, Y.C.; Liu, Y. Satellite-Observed Variations and Trends in Carbon Monoxide over Asia and Their Sensitivities to Biomass Burning. Remote Sens. 2020, 12, 830. [Google Scholar] [CrossRef] [Green Version]
- Wang, W.; Wang, Z.; Duan, Y. Preliminary Evaluation of the Error Budgets in the TALIS Measurements and Their Impact on the Retrievals. Remote Sens. 2020, 12, 468. [Google Scholar] [CrossRef] [Green Version]
- Wang, Y.; Tao, J.; Cheng, L.; Yu, C.; Wang, Z.; Chen, L. An improved retrieval of glyoxal from OMI over China. Remote Sens. 2019, 11, 137. [Google Scholar] [CrossRef] [Green Version]
- Mateos, D.; Antón, M. Worldwide Evaluation of Ozone Radiative Forcing in the UV-B Range between 1979 and 2014. Remote Sens. 2020, 12, 436. [Google Scholar] [CrossRef] [Green Version]
- Vaquero-Martínez, J.; Antón, M.; Sanchez-Lorenzo, A.; Cachorro, V.E. Evaluation of Water Vapor Radiative Effects Using GPS Data Series over Southwestern Europe. Remote Sens. 2020, 11, 1307. [Google Scholar] [CrossRef] [Green Version]
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Cachorro, V.E.; Antón, M. Editorial for the Special Issue “Remote Sensing of Atmospheric Components and Water Vapor”. Remote Sens. 2020, 12, 2074. https://doi.org/10.3390/rs12132074
Cachorro VE, Antón M. Editorial for the Special Issue “Remote Sensing of Atmospheric Components and Water Vapor”. Remote Sensing. 2020; 12(13):2074. https://doi.org/10.3390/rs12132074
Chicago/Turabian StyleCachorro, Victoria E., and Manuel Antón. 2020. "Editorial for the Special Issue “Remote Sensing of Atmospheric Components and Water Vapor”" Remote Sensing 12, no. 13: 2074. https://doi.org/10.3390/rs12132074
APA StyleCachorro, V. E., & Antón, M. (2020). Editorial for the Special Issue “Remote Sensing of Atmospheric Components and Water Vapor”. Remote Sensing, 12(13), 2074. https://doi.org/10.3390/rs12132074