Atmospheric Observations of Weather and Climate

References

• Aberson, S., & Franklin, J. (1999). Impact on hurricane track and intensity forecasts of GPS dropwindsonde observations from the first-season flights of the NOAA gulfstream-IV Jet aircraft. Bulletin of the American Meteorological Society, 80(3), 421–427. https://doi.org/10.1175/1520-0477(1999)080<0421:IOHTAI>2.0.CO;2
   Web of Science ®Google Scholar
• Ackerman, S. A., Platnick, S., Bhartia, P. K., Duncan, B., L’Ecuyer, T., Heidinger, A., Skofronick-Jackson, G., Loeb, N., Schmit, T., & Smith, N. (2019). Satellites see the world’s atmosphere. Meteorological Monographs, 59, 4.1–4.53. https://doi.org/10.1175/AMSMONOGRAPHS-D-18-0009.1
   Google Scholar
• Adirosi, E., Baldini, L., & Tokay, A. (2020). Rainfall and DSD parameters comparison between Micro Rain Radar, two-dimensional video and Parsivel disdrometers, and S-band dual-polarization radar. Journal of Atmospheric and Oceanic Technology, 37(4), 621–640. https://doi.org/10.1175/JTECH-D-19-0085.1
   Web of Science ®Google Scholar
• Anagoustou, E. N., & Krajewski, W. F. (1999). Real-time radar rainfall estimation. Part I: Algorithm formulation. Journal of Atmospheric and Oceanic Technology, 16(2), 189–197. https://doi.org/10.1175/1520-0426(1999)016<0189:RTRREP>2.0.CO;2
   Web of Science ®Google Scholar
• Apke, J. M., Hilburn, K. A., Miller, S. D., & Peterson, D. A. (2020). Towards objective identification and tracking of convective outflow boundaries in next-generation geostationary satellite imagery. Atmospheric Measurement Techniques, 13(3), 1593–1608. https://doi.org/10.5194/amt-13-1593-2020
   Web of Science ®Google Scholar
• Apke, J. M., Mecikalski, J. R., & Jewett, C. P. (2016). Analysis of mesoscale atmospheric flows above mature deep convection using super rapid scan geostationary satellite data. Journal of Applied Meteorology and Climatology, 55(9), 1859–1887. https://doi.org/10.1175/JAMC-D-15-0253.1
   Web of Science ®Google Scholar
• Armijo, L. (1969). A theory for the determination of wind and precipitation velocities with Doppler radars. Journal of the Atmospheric Sciences, 26(3), 570–573. https://doi.org/10.1175/1520-0469(1969)026<0570:ATFTDO>2.0.CO;2
   Web of Science ®Google Scholar
• Austin, P. M. (1987). Relation between measured radar reflectivity and surface rainfall. Monthly Weather Review, 115(5), 1053–1070. https://doi.org/10.1175/1520-0493(1987)115<1053:RBMRRA>2.0.CO;2
   Web of Science ®Google Scholar
• Ayasse, A. K., Dennison, P. E., Foote, M., Thorpe, A. K., Joshi, S., Green, R. O., Duren, R. M., Thompson, D. R., & Roberts, D. A. (2019). Methane mapping with future satellite imaging spectrometers. Remote Sensing, 11(24), 3054. https://doi.org/10.3390/rs11243054
   Web of Science ®Google Scholar
• Balsley, B. B., & Gage, K. (1982). On the use of radars for operational wind profiling. Bulletin of the American Meteorological Society, 63(9), 1009–1018. https://doi.org/10.1175/1520-0477(1982)063<1009:OTUORF>2.0.CO;2
   Web of Science ®Google Scholar
• Banta, R. M. (1995). Sea breezes shallow and deep on the California coast. Monthly Weather Review, 123(12), 3614–3622. https://doi.org/10.1175/1520-0493(1995)123<3614:SBSADO>2.0.CO;2
   Web of Science ®Google Scholar
• Bartlett, B., Casey, J., Padula, F., Pearlman, A., Pogorzala, D., & Cao, C. (2018). Independent validation of the advanced baseline imager (ABI) on NOAA's GOES-16: Post-launch ABI airborne science field campaign results. Proceedings of the Society of Photo-optical Instrument Engineers, SPIE 10764, Earth Observing Systems XXIII, 107640H, 19-23 August, 2018. https://doi.org/10.1117/12.2323672
   Google Scholar
• Bauwens, M., Compernolle, S., Stavrakou, T., Müller, J.-F., Gent, J., Eskes, H., Levelt, P. F., Van der A, R., Veefkind, J. P., Vlietinck, J., Yu, H., & Zehner, C. (2020). Impact of coronavirus outbreak on NO2 Pollution assessed using TROPOMI and OMI observations. Geophysical Research Letters, 47(11), https://doi.org/10.1029/2020GL087978
   PubMed Web of Science ®Google Scholar
• Bedka, K. M., Murillo, E., Homeyer, C. R., Scarino, B., & Mersiovski, H. (2018). The above anvil cirrus plume: An important severe weather indicator in visible and infrared satellite imagery. Journal of Applied Meteorology, 33, 1159–1181. https://doi.org/10.1175/WAF-D-18-0040.1
   Google Scholar
• Bell, T. M., Greene, B. R., Klein, P. M., Carney, M., & Chilson, P. B. (2020). Confronting the boundary layer data gap: Evaluating new and existing methodologies of probing the lower atmosphere. Atmospheric Measurement Techniques, 13(7), 3855–3872. https://doi.org/10.5194/amt-13-3855-2020
   Web of Science ®Google Scholar
• Bilbro, J. W., Fichtl, G., Fitzjarrald, D. E., Krause, M., & Lee, R. W. (1984). Airborne Doppler lidar wind field measurements. Bulletin of the American Meteorological Society, 65(4), 348–359.  . https://doi.org/10.1175/1520-0477(1984)065<0348:ADLWFM>2.0.CO;2
   Web of Science ®Google Scholar
• Blakeslee, R. J., Lang, T. J., Koshak, W. J., Buechler, D., Gatlin, P., Mach, D. M., Stano, G. T., Virts, K. S., Walker, T. D., Cecil, D. J., Ellett, W., Goodman, S. J., Harrison, S., Hawkins, D. L., Heumesser, M., Lin, H., Maskey, M., Schultz, C. J., Stewart, M., Bateman, M., Chanrion, O., & Christian, H. (2020). Three years of the lightning imaging sensor onboard the International Space Station: Expanded global coverage and enhanced applications. Journal of Geophysical Research – Atmospheres, Earth and Space Science, 125, e2020JD032918. https://doi.org/10.1029/2020JD032918
   Web of Science ®Google Scholar
• Bluestein, H., Rauber, R. M., Burgess, D. W., Albrecht, B., Ellis, S. M., Richardson, Y. P., Jorgensen, D. P., Frasier, S. J., Chilson, P., Palmer, R. D., Yuter, S. E., Lee, W.-C., Dowell, D. C., Smith, P. L., Markowski, P. M., Friedrich, K., & Weckwerth, T. M. (2014). Radar in the atmospheric sciences and related research: Current systems, emerging technology, and future needs. Bulletin of the American Meteorological Society, 95(12), 1850–1861. https://doi.org/10.1175/BAMS-D-13-00079.1
   Web of Science ®Google Scholar
• Bluestein, H. B. (1992). Synoptic-dynamic meteorology in Midlatitudes, Vol. I: Principles of kinematics and dynamics. Oxford University Press.
   Google Scholar
• Bohren, C. F., & Albrecht, B. A. (1998). Atmospheric thermodynamics. Oxford University Press. https://doi.org/10.1119/1.1313524
   Google Scholar
• Bouttier, F., & Kelly, G. (2001). Observing-system experiments in the ECMWF 4D-Var data assimilation system. Quarterly Journal of the Royal Meteorological Society, 127(574), 1469–1488. https://doi.org/10.1002/qj.49712757419
   Web of Science ®Google Scholar
• Brandes, E. A., Zhang, G., & Vivekanandan, J. (2003). An evaluation of a drop distribution-based polarimetric radar rainfall estimator. Journal of Applied Meteorology, 42(5), 652–660. https://doi.org/10.1175/1520-0450(2003)042<0652:AEOADD>2.0.CO;2
   Google Scholar
• Brewster, K. A., Bajij, A., Phillips, B. J., Pepyne, D. L., Lyons, E., & Carr, F. (2017). CASA Dallas-Fort Worth urban testbed observations: Networks of networks at work [Special Symposium on Meteorological Observations and Instruments]. 97th American Meteorological Society Annual Meeting, 22-26 January, Seattle, WA.
   Google Scholar
• Brock, F. V., & Richardson, S. J. (2001). Meteorological measurement systems. Oxford University Press. https://doi.org/10.1093/oso/9780195134513.001.0001
   Google Scholar
• Brotzge, J. A., Wang, J., Thorncroft, C. D., Joseph, E., Bain, N., Bassill, N., Farruggio, N., Freedman, J. M., Hemker, K., Johnston, D., Kane, E., McKim, S., Miller, S. D., Minder, J. R., Naple, P., Perez, S., Schwab, James J., Schwab, M. J., & Sicker, J. (2020). A technical overview of the New York State Mesonet standard network. Journal of Atmospheric and Oceanic Technology, 37(10), 1827–1845. https://doi.org/10.1175/JTECH-D-19-0220.1
   Web of Science ®Google Scholar
• Brown, R. A., Lemon, L. R., & Burgess, D. W. (1978). Tornado detection by pulsed Doppler radar. Monthly Weather Review, 106(1), 29–38. https://doi.org/10.1175/1520-0493(1978)106<0029:TDBPDR>2.0.CO;2
   Web of Science ®Google Scholar
• Browning, K. A., & Donaldson, R. J., Jr. (1963). Airflow and structure of a tornadic storm. Journal of the Atmospheric Sciences, 20(6), 533–545. https://doi.org/10.1175/1520-0469(1963)020<0533:AASOAT>2.0.CO;2
   Web of Science ®Google Scholar
• Bruneau, D., Quaglia, P., Flamant, C., & Pelon, J. (2001). Airborne lidar LEANDRE II for water-vapor profiling in the troposphere II first results. Applied Optics, 40(21), 3462–3475. https://doi.org/10.1364/AO.40.003462
   PubMed Web of Science ®Google Scholar
• Cardinali, C. (2018). Forecast sensitivity observation impact with an observation-only based objective function. Quarterly Journal of the Royal Meteorological Society, 144(716), 2089–2098. https://doi.org/10.1002/qj.3305
   Web of Science ®Google Scholar
• Chan, M.-Y., Zhang, F. Q., Chen, X. C., & Leung, L. R. (2020). Potential impacts of assimilating all-sky satellite infrared radiances on convection-permitting analysis and prediction of tropical convection. Monthly Weather Review, 148(8), 3203–3224. https://doi.org/10.1175/MWR-D-19-0343.1
   Web of Science ®Google Scholar
• Chance, K. V., Liu, X., Suleiman, R. M., Flittner, D. E., Al-Saadi, J., & Janz, S. J. (2013). Tropospheric emissions: Monitoring of pollution (TEMPO). Proceedings Society Photo-Optical Instrumentation Engineers (SPIE) 8866, Earth Observing Systems XVIII, ed. Butler, J. J., Xiong, X., & Gu, X., 88660D. https://doi.org/10.1117/12.2024479
   Google Scholar
• Chilson, P. B., Bell, T. M., Brewster, K. A., Britto Hupsel de Azevedo, G., Carr, F. H., Carson, K., Doyle, W., Fiebrich, C. A., Greene, B. R., Grimsley, J. L., Kanneganti, S. T., Martin, J., Moore, A., Palmer, R. D., Pillar-Little, E. A., Salazar-Cerreno, J. L., Segales, A. R., Weber, M. E., Yeary, M., & Droegemeier, K. K. (2019). Moving towards a network of autonomous UAS atmospheric profiling stations for observations in the Earth’s lower atmosphere: The 3D Mesonet concept. Sensors, 19(12), 2720. https://doi.org/10.3390/s19122720
   PubMed Web of Science ®Google Scholar
• Collard, A. D., & McNally, A. P. (2009). Infrared atmospheric sounding interferometer radiances at ECMWF. Quarterly Journal Royal Meteorological Society, 135(641), 1044–1058. https://doi.org/10.1002/qj.410
   Web of Science ®Google Scholar
• Cotton, J., & Eyre, J. (2019). Forecast sensitivity to observations impact (FSOI) by country or region. Met Office Forecasting Research Technical Report, No. 636.
   Google Scholar
• Crum, T. D., & Alberty, R. L. (1993). The WSR-88D and the WSR-88D operational support test facility. Bulletin of the American Meteorological Society, 74(9), 1669–1687. https://journals.ametsoc.org/view/journals/bams/74/9/1520-0477_1993_074_1669_twatwo_2_0_co_2.xml https://doi.org/10.1175/1520-0477(1993)074<1669:TWATWO>2.0.CO;2
   Web of Science ®Google Scholar
• Deepak, A. (1977). Inversion methods in atmospheric remote sensing. Academic Press. https://doi.org/10.1016/B978-0-122-08450-8.X5001-2
   Google Scholar
• Degelia, S. K., Wang, X., & Stensrud, D. J. (2019). An evaluation of the impact of assimilating AERI retrievals, kinematic profilers, rawinsondes, and surface observations on a forecast of a nocturnal convection initiation event during the PECAN field campaign. Monthly Weather Review, 147(8), 2739–2764. https://doi.org/10.1175/MWR-D-18-0423.1
   Web of Science ®Google Scholar
• Diniz, F. L. R., & Todling, R. (2020). Assessing the impact of observations in a multi-year reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(727), 724–747. https://doi.org/10.1002/qj.3705
   Web of Science ®Google Scholar
• Doviak, R. J., Bringi, V., Ryzhkov, A., Zahrai, A., & Zrnić, D. (2000). Considerations for polarimetric upgrades to operational WSR-88D radars. Journal of Atmospheric and Oceanic Technology, 17(3), 257–278. https://doi.org/10.1175/1520-0426(2000)017<0257:CFPUTO>2.0.CO;2
   Web of Science ®Google Scholar
• Doviak, R. J., & Zrnić, D. S. (2006). Doppler radar and weather observations (2nd ed.). Dover.
   Google Scholar
• Dowell, D. C., Bluestein, H. B., & Jorgensen, D. P. (1997). Airborne Doppler radar analysis of supercells during COPS-91. Monthly Weather Review, 125(3), 365–383. https://doi.org/10.1175/1520-0493(1997)125<0365:ADRAOS>2.0.CO;2
   Web of Science ®Google Scholar
• Ecklund, W. L., Carter, D. A., & Balsley, B. B. (1988). A UHF wind profiler for the boundary layer: Brief description and initial results. Journal of Atmospheric and Oceanic Technology, 5(3), 432–441. https://doi.org/10.1175/1520-0426(1988)005<0432:AUWPFT>2.0.CO;2
   Google Scholar
• Emeis, S. (2010). Measurement methods in atmospheric sciences. Borntraeger Science Publishers. https://doi.org/10.1002/met.250
   Google Scholar
• Esmaili, R., Smith, N., Berndt, E. B., Dostalek, J. F., Kahn, B. H., White, K., Barnet, C. D., Sjoberg, W., & Goldberg, M. (2020). Adapting satellite soundings for operational forecasting within the hazardous weather testbed. Remote Sensing, 12(5), 886. https://doi.org/10.3390/rs12050886
   Web of Science ®Google Scholar
• Eyre, J. (1997). Variational assimilation of remotely-sensed observations of the atmosphere. Journal of the Meteorological Society of Japan, 75, 331–338. https://doi.org/10.2151/jmsj1965.75.1B_331
   Web of Science ®Google Scholar
• Fabry, F. (2015). Radar meteorology: Principles and practice. Cambridge University Press.
   Google Scholar
• Farrell, S. L., Duncan, K., Buckley, E. M., Richter-Menge, J., & Li, R. (2020). Mapping sea ice surface topography in high fidelity With ICESat-2. Geophysical Research Letters, 47(21), https://doi.org/10.1029/2020GL090708
   Web of Science ®Google Scholar
• Ferraro, R. R., Weng, F., Grody, N. C., Zhao, L., Meng, H., Kongoli, C., Pellegrino, P., Qiu, S., & Dean, C. (2005). NOAA operational hydrological products derived from the advanced microwave sounding unit. IEEE Transactions on Geoscience and Remote Sensing, 43(5), 1036–1049. https://ieeexplore.ieee.org/document/1424280. https://doi.org/10.1109/TGRS.2004.843249
   Web of Science ®Google Scholar
• Fiebrich, C. A., Brinson, K. R., Mahmood, R., Foster, S. A., Schargorodski, M., Edwards, N. L., Redmond, C. A., Atkins, J. R., Andresen, J. A., & Lin X. (2020). Toward the standardization of mesoscale meteorological networks. Journal of Atmospheric and Oceanic Technology, 37(11), 2033–2049. https://doi.org/10.1175/JTECH-D-20-0078.1
   Web of Science ®Google Scholar
• Fletcher, J. O., Swingle, D. M., Katz, I., Harney, P. J., Austin, P. M., Geotis, S. G., Metcalf, J. I., Glover, K. M., Kessler, E., Probert-Jones, J. R., Douglas, R. H., Kodaira, N., Aoyagi, J., Kulshrestha, S. M., Xu, Y.-M., Atlas, D., Ulbirch, C. W., Dennis, A. S., Hitschfeld, W. F., … Wilson, J. (1990). Radar in meteorology (D. Atlas, Ed.) American Meteorological Society.
   Google Scholar
• Foken, T. (2017). Micrometeorology (2nd ed.). Springer-Verlag GmbH. https://doi.org/10.1007/978-3-642-25440-6
   Google Scholar
• Foken, T. (Ed.). (2021). Springer handbook of atmospheric measurements. Springer. https://doi.org/10.1007/978-3-030-52171-4
   Google Scholar
• Gage, K. S., & Balsley, B. B. (1978). Doppler radar probing of the clear atmosphere. Bulletin of the American Meteorological Society, 59(9), 1074–1093. https://doi.org/10.1175/1520-0477(1978)059<1074:DRPOTC>2.0.CO;2
   Web of Science ®Google Scholar
• Geer, A. J., Baordo, F., Bormann, N., & English, S. (2014). All-sky assimilation of microwave humidity sounders, Technical Memo 741, ECMWF.
   Google Scholar
• Geer, A. J., Migliorini, S., & Matricardi, M. (2019). All-sky assimilation of infrared radiances sensitive to mid- and upper-tropospheric moisture and cloud. Atmospheric Measurement Techniques, 12(9), 4903–4929. https://doi.org/10.5194/amt-12-4903-2019
   Web of Science ®Google Scholar
• Gelaro, R., Langland, R. H., Pellerin, S., & Todling, R. (2010). The THORPEX observation impact intercomparison experiment. Monthly Weather Review, 138(11), 4009–4025. https://doi.org/10.1175/2010MWR3393.1
   Web of Science ®Google Scholar
• Gelaro, R., & Zhu, Y. (2009). Examination of observation impacts derived from observing system experiments (OSEs) and adjoint models. Tellus A: Dynamic Meteorology and Oceanography, 61(2), 179–193. https://doi.org/10.1111/j.1600-0870.2008.00388.x
   Web of Science ®Google Scholar
• Goldberg, M. D., Cikanek, H., Zhou, L., & Price, J. (2018). 1.04 -The joint polar satellite system. Comprehensive Remote Sensing, 1, 91–118. https://doi.org/10.1016/B978-0-12-409548-9.10314-8
   Google Scholar
• Goodman, S. J., Blakeslee, R. J., Koshak, W. J., Mach, D., Bailey, J., Buechler, D., Carey, L., Schultz, C., Bateman, M., McCaul, E., & Stano, G. (2013). The GOES-R geostationary lightning mapper (GLM). Atmospheric Research, 125-126, 34–49. https://doi.org/10.1016/j.atmosres.2013.01.006
   Web of Science ®Google Scholar
• Goodman, S. J., Schmit, T. J., Daniels, J., Denig, W., & Metcalf, K. (2018). GOES: Past, present and future. Comprehensive Remote Sensing, 1, 119–149. https://doi.org/10.1016/B978-0-12-409548-9.10315-X
   Google Scholar
• Goodman, S. J., Schmit, T. J., Daniels, J., & Redmon, R. (Eds.). (2019). The GOES-R series: A new generation of geostationary environmental satellites. Academic Press. Print and e-book, ISBN-13: 978-0128143278, ISBN-10: 0128143274.
   Google Scholar
• Graf, M., Chwala, C., Polz, J., & Kunstmann, H. (2020). Rainfall estimation from a German-wide commercial microwave link network: Optimized processing and validation for 1 year of data. Hydrology and Earth System Sciences, 24(6), 2931–2950. https://doi.org/10.5194/hess-24-2931-2020
   Web of Science ®Google Scholar
• Halley, E. (1686). An historical account of the trade winds, and monsoons, observable in the seas between and near the tropics, with an attempt to assign the physical cause of the said winds. Philosophical Transactions of the Royal Society of London, 16(183), 153–168. https://doi.org/10.1098/rstl.1686.0026
   Google Scholar
• Han, Y., van Delst, P., Liu, Q., Weng, F., Yan, B., Treadon, R., & Derber, J. (2006). JCSDA community radiative transfer model (CRTM)—Version 1. NOAA Tech. Rep. 122.
   Google Scholar
• Hardesty, R. M., Cupp, R. E., Post, M. J., Lawrence, T. R., Intrieri, J. M., & Neiman, P. J. (1988). A ground-based, injection-locked, pulsed TEA laser for atmospheric wind measurements. Society of Photo-optical Instrument Engineers (SPIE), 889, 23–28.
   Google Scholar
• Harrison, R. G. (2015). Meteorological measurements and instrumentation. John Wiley & Sons, Ltd. https://doi.org/10.1002/9781118745793
   Google Scholar
• Hildebrand, P. H., Lee, W.-C., Walther, C. A., Frush, C., Randall, M., Loew, E., Neitzel, R., Parsons, R., Testud, J., Baudin, F., & LeCornec, A. (1996). The ELDORA/ASTRAIA airborne Doppler weather radar: High resolution observations from TOGA COARE. Bulletin of the American Meteorological Society, 77(2), 213–232. https://doi.org/10.1175/1520-0477(1996)077<0213:TEADWR>2.0.CO;2
   Web of Science ®Google Scholar
• Hillger, D. W., Kopp, T., Lee, T., Lindsey, D., Seaman, C., Miller, S., Solbrig, J., Kidder, S., Bachmeier, S., Jasmin, T., & Rink, T. (2013). First-light imagery from Suomi NPP VIIRS. Bulletin of the American Meteorological Society, 94(7), 1019–1029. https://doi.org/10.1175/BAMS-D-12-00097.1
   Web of Science ®Google Scholar
• Hoffman, R. N., & Atlas, R. (2016). Future observing system simulation experiments. Bulletin of the American Meteorological Society, 97(9), 1601–1616. https://doi.org/10.1175/BAMS-D-15-00200.1
   Web of Science ®Google Scholar
• Holmlund, K., Grandell, J., Schmetz, J., Stuhlmann, R., Bojkov, B., Munro, R., Lekouara, M., Coppens, D., Viticchie, B., August, T., Theodore, B., Watts, P., Dobber, M., Fowler, G., Bojinski, S., Schmid, A., Salonen, K., Tjemkes, S., Aminou, D., Blythe, P. (2021). Meteosat third generation (MTG): Continuation and innovation of observations from geostationary orbit. Bulletin of the American Meteorological Society, 102(3), E990–E1015. https://doi.org/10.1175/BAMS-D-19-0304.1
   Google Scholar
• Homeyer, C. R. (2014). Formation of the enhanced-V infrared cloud-top feature from high-resolution three-dimensional radar observations. Journal of the Atmospheric Sciences, 71(1), 332–348. https://doi.org/10.1175/JAS-D-13-079.1
   Web of Science ®Google Scholar
• Horton, T., Bolt, M., Prather, C., Manobianco, J., & Adams, M. L. (2018). Airborne sensor network for atmospheric profiling. Wireless Sensor Network, 10((04|4)), 93–101. https://doi.org/10.4236/wsn.2018.104005
   Google Scholar
• Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K., Joyce, R., Kidd, C., Nelkin, E. J., Sorooshian, S., Tan, J., & Xie, P. (2018). NASA global precipitation measurement integrated multi-satellite retrievals for GPM (IMERG). Technical Report version 5.2. https://pmm.nasa.gov/sites/default/files/document_files/IMERG_ATBD_V5.2_0.pdf
   Google Scholar
• Illingworth, A. J., Cimini, D., Haefele, A., Haeffelin, M., Hervo, M., Kotthaus, S., Löhnert, U., Martinet, P., Mattis, I., O’Connor, E. J., & Potthast, R. (2019). How can existing ground-based profiling instruments improve European weather forecasts?. Bulletin of the American Meteorological Society, 100(4), 605–619. https://doi.org/10.1175/BAMS-D-17-0231.1
   Web of Science ®Google Scholar
• Illston, B., Basara, J. B., Fisher, D., Elliott, R., Fiebrich, C., Crawford, K., Humes, K., & Hunt, E. (2008). Mesoscale monitoring of soil moisture across a statewide network. Journal of Atmospheric and Oceanic Technology, 25(2), 167–182. https://doi.org/10.1175/2007JTECHA993.1
   Web of Science ®Google Scholar
• Im, E., Chandrasekar, V., Chen, S., Holland, G., Kakar, R., Lewis, W. E., Marks, F., Smith, E., Tanelli, S., & Tripoli, G. (2007). Workshop report on NEXRAD-in-Space – a geostationary satellite Doppler weather radar for hurricane studies, AGU Fall Meeting Abstracts.
   Google Scholar
• Ingleby, B., Rodwell, M., & Isaksen, L. (2016). Global radiosonde network under pressure. ECMWF Newsletter, No. 14.
   Google Scholar
• Isom, B., Palmer, R., Kelley, R., Meier, J., Bodine, D., Yeary, M., Cheong, B.-L., Zhang, Y., Yu, T.-Y., & Biggerstaff, M. I. (2013). The atmospheric imaging radar: Simultaneous volumetric observations using a phased-array weather radar. Journal of Atmospheric and Oceanic Technology, 30(4), 655–675. https://doi.org/10.1175/JTECH-D-12-00063.1
   Web of Science ®Google Scholar
• James, E. P., & Benjamin, S. G. (2017). Observation system experiments with the hourly updating rapid refresh model using GSI hybrid ensemble-variational data assimilation. Monthly Weather Review, 145(8), 2897–2918. https://doi.org/10.1175/MWR-D-16-0398.1
   Web of Science ®Google Scholar
• Janssen, M. A. (1993). Atmospheric remote sensing by microwave radiometry. John Wiley and Sons, Inc. http://hdl.handle.net/2014/34527
   Google Scholar
• Joo, S., Eyre, J., & Marriott, R. (2013). The impact of MetOp and other satellite data within the met office global NWP system using an adjoint-based sensitivity method. Monthly Weather Review, 141(10), 3331–3342. https://doi.org/10.1175/MWR-D-12-00232.1
   Web of Science ®Google Scholar
• Kaimal, J. C., & Finnigan, J. J. (1994). Atmospheric boundary layer flows: Their structure and measurement. Oxford University Press. https://doi.org/10.1002/qj.49712152512
   Google Scholar
• Kalnay, E., Ota, Y., Miyoshi, T., & Liu, J. (2012). A simpler formulation of forecast sensitivity to observations: Application to ensemble Kalman filters. Tellus A: Dynamic Meteorology and Oceanography, 64(1), 18462. https://doi.org/10.3402/tellusa.v64i0.18462
   Web of Science ®Google Scholar
• Key, J. R., Mahoney, R., Liu, Y., Romanov, P., Tschudi, M., Appel, I., Maslanik, J., Baldwin, D., Wang, X., & Meade, P. (2013). Snow and ice products from Suomi NPP VIIRS. Journal Geophysical Research Atmospheres, 118, doi:10.1002/2013JD020459
   Web of Science ®Google Scholar
• Key, J. R., Liu, Y., Wang, X., Letterly, A., & Painter, T. (2019). Chapter 14 – snow and ice products from ABI on the GOES-R series. In S. Goodman, T. Schmit, J. Daniels, & R. Redmond (Eds.), The GOES-R series: A new generation of geostationary environmental satellites. Elsevier. https://doi.org/10.1016/B978-0-12-814327-8.00014-7
   Google Scholar
• Kidder, S. Q., & Vonder Haar, T. H. (1995). Satellite meteorology: An introduction. Academic Press. ISBN 0-12-406430-2.
   Google Scholar
• Klaes, K. D., Ackermann, J., Anderson, C., Andres, Y., August, T., Borde, R., Bojkov, B., Butenko, L., Cacciari, A., Coppens, D., Crapeau, M., Guedj, S., Hautecoeur, O., Hultberg, T., Lang, R., Linow, S., Marquardt, C., Munro, R., Pettirossi, C., … Vazquez-Navarro, M. (2021). The EUMETSAT polar system: 13+ successful years of global observations for operational weather prediction and climate monitoring. Bulletin of the American Meteorological Society, 102(3), E1224–E1238. https://doi.org/10.1175/BAMS-D-20-0082.1
   Google Scholar
• Kotsuki, S., Kurosawa, K., & Miyoshi, T. (2019). On the properties of ensemble forecast sensitivity to observations. Quarterly Journal of the Royal Meteorological Society, 145(722), 1897–1914. https://doi.org/10.1002/qj.3534
   Web of Science ®Google Scholar
• Kumjian, M. R., & Ryzhkov, A. V. (2008). Polarimetric signatures in supercell thunderstorms. Journal of Applied Meteorology and Climatology, 47(7), 1940–1961. https://doi.org/10.1175/2007JAMC1874.1
   Web of Science ®Google Scholar
• Kurdzo, J. M., Cheong, B. L., Palmer, R. D., Zhang, G., & Meier, J. B. (2014). A pulse compression waveform for improved-sensitivity weather radar observations. Journal of Atmospheric and Oceanic Technology, 31(12), 2713–2731. https://doi.org/10.1175/JTECH-D-13-00021.1
   Web of Science ®Google Scholar
• Lai, Y.-R., & Wang, L. (2021). Monthly surface elevation changes of the Greenland ice sheet from ICESat-1, CryoSat-2, and ICESat-2 altimetry missions. IEEE Geoscience and Remote Sensing Letters, https://doi.org/10.1109/LGRS.2021.3058956
   Web of Science ®Google Scholar
• Langland, R. H., & Baker, N. (2004). Estimation of observation impact using the NRL atmospheric variational data assimilation adjoint system. Tellus A: Dynamic Meteorology and Oceanography, 56A(3), 189–201. https://doi.org/10.3402/tellusa.v56i3.14413
   Google Scholar
• Lanicci, J. M., Carlson, T. B., & Warner, T. T. (1987). Sensitivity of the great plains severe-storm environment to soil-moisture distribution. Monthly Weather Review, 115(11), 2660–2673. https://doi.org/10.1175/1520-0493(1987)115<2660:SOTGPS>2.0.CO;2
   Web of Science ®Google Scholar
• Levizzani, V., Kidd, C., Kirschbaum, D. B., Kummerow, C. D., Nakamura, K., & Turk, J. (Eds.) (2020). Satellite precipitation measurement volume 1, advances in global change research. Springer. https://doi.org/10.1007/978-3-030-24568-9
   Google Scholar
• Lewis, J., Phillips, J. M., Menzel, W. P., Vonder Haar, T. H., Moosmüller, H., House, F. B., & Fearon, M. G. (2016). Verner Suomi: The life and work of the founder of satellite meteorology. American Meteorological Society. ISBN: 978-1-944970-22-2.
   Google Scholar
• Liang, S. (2017). Comprehensive remote sensing (1st ed.). Elsevier. ISBN-13: 978-0128032206.
   Google Scholar
• Liou, Y.-C., Bluestein, H. B., French, M. M., & Wienhoff, Z. B. (2018). Single-Doppler velocity retrieval of the wind field in a tornadic supercell using mobile, phased-array, Doppler radar data. Journal of Atmospheric and Oceanic Technology, 35(8), 1649–1663. https://doi.org/10.1175/JTECH-D-18-0004.1
   Web of Science ®Google Scholar
• Little, G. (1969). Acoustic methods for the remote probing of the lower atmosphere. Proceedings of the IEEE, 57(4), 571–578. https://doi.org/10.1109/PROC.1969.7010
   Web of Science ®Google Scholar
• Madaus, L. E., & Mass, C. F. (2017). Evaluating smartphone pressure observations for mesoscale analyses and forecasts. Weather and Forecasting, 32(2), 511–531. https://doi.org/10.1175/WAF-D-16-0135.1
   Web of Science ®Google Scholar
• Maier, M. W., Gallagher, F. W. III, St. Germain, K., Anthes, R., Zuffada, C., Menzies, R., Piepmeier, J., Di Pietro, D., Coakley, M. M., & Adams, E. (2021). Architecting the future of weather satellites. Bulletin of the American Meteorological Society, https://journals.ametsoc.org/view/journals/bams/102/3/BAMS-D-19-0258.1.xml. doi:10.1175/BAMS-D-19-0258.1
   Web of Science ®Google Scholar
• Markowski, P. M., Richardson, Y. P., Richardson, S. J., & Petersson, A. (2018). Aboveground thermodynamic observations in convective storms from balloonborne probes acting as pseudo-Lagrangian drifters. Bulletin of the American Meteorological Society, 99(4), 711–724. https://doi.org/10.1175/BAMS-D-17-0204.1
   Web of Science ®Google Scholar
• Marks, F. D., & Houze, R. A. (1984). Airborne Doppler radar observations of hurricane Debby. Bulletin of the American Meteorological Society, 65(6), 569–582. https://doi.org/10.1175/1520-0477(1984)065<0569:ADROIH>2.0.CO;2
   Web of Science ®Google Scholar
• McCaul, E. W., Jr., Bluestein, H. B., & Doviak, R. J. (1987). Airborne Doppler lidar observations of convective phenomena in Oklahoma. Journal of Atmospheric and Oceanic Technology, 4(3), 479–497. https://doi.org/10.1175/1520-0426(1987)004<0479:ADLOOC>2.0.CO;2
   Google Scholar
• McFarquhar, G. M., Smith, E., Pillar-Little, E. A., Brewster, K., Chilson, P. B., Lee, T. R., Waugh, S., Yussouf, N., Wang, X., Xue, M., de Boer, G., Gibbs, J. A., Fiebrich, C., Baker, B., Brotzge, J., Carr, F., Christophersen, H., Fengler, M., Hall, P., … Hawk, D. (2020). Current and future uses of UAS for improved forecasts/warnings and scientific studies. Bulletin of the American Meteorological Society, 101(8), E1322–E1328. https://doi.org/10.1175/BAMS-D-20-0015.1
   Web of Science ®Google Scholar
• McLaughlin, D., Pepyne, D., Chandrasekar, V., Philips, B., Kurose, J., Zink, M., Droegemeier, K., Cruz-Pol, S., Junyent, F., Brotzge, J., Westbrook, D., Bharadwaj, N., Wang, Y., Lyons, E., Hondl, K., Liu, Y., Knapp, E., Xue, M., Hopf, A., … Carr, F. (2009). Short-wavelength technology and the potential for distributed networks of small radar systems. Bulletin of the American Meteorological Society, 90(12), 1797–1818. https://doi.org/10.1175/2009BAMS2507.1
   Web of Science ®Google Scholar
• McPherson, R. A., Fiebrich, C. A., Crawford, K. C., Kilby, J. R., Grimsley, D. L., Martinez, J. E., Basara, J. B., Illston, B. G., Morris, D. A., Kloesel, K. A., Melvin, A. D., Shrivastava, H., Wolfinbarger, J. M., Bostic, J. P., Demko, D. B., Elliott, R. L., Stadler, S. J., Carlson, J. D., & Sutherland, A. J. (2007). Statewide monitoring of the mesoscale environment: A technical update on the Oklahoma Mesonet. Journal of Atmospheric and Oceanic Technology, 24(3), 301–321. https://doi.org/10.1175/JTECH1976.1
   Web of Science ®Google Scholar
• Meier, W. N., Stewart, J. S., Liu, Y., Key, J., & Miller, J. (2017). Operational implementation of sea ice concentration estimates from the AMSR2 sensor. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(9), 3904–3911. https://ieeexplore.ieee.org/document/7916905. https://doi.org/10.1109/JSTARS.2017.2693120
   Web of Science ®Google Scholar
• Meinig, C., Burger, Eugene F., Cohen, Nora, Cokelet, Edward D., Cronin, Meghan F., Cross, Jessica N., de Halleux, Sebastien, Jenkins, Richard, Jessup, Andrew T., Mordy, Calvin W., Lawrence-Slavas, Noah, Sutton, Adrienne J., Zhang, Dongxiao, & Zhang, C. (2019). Public–private partnerships to advance regional ocean-observing capabilities: A Saildrone and NOAA-PMEL case study and future considerations to expand to global scale observing. Frontiers in Marine Science, 6, 448. https://doi.org/10.3389/fmars.2019.00448
   Web of Science ®Google Scholar
• Menzel, W. P. (2019). History of geostationary satellites. In S. J. Goodman, T. J. Schmit, J. Daniels, & R. J. Redmon (Eds.), The GOES-R series: A new generation of geostationary environmental satellites. Academic Press. Print and e-book, ISBN-13: 978-0128143278, ISBN-10: 0128143274.
   Google Scholar
• Menzel, W. P., Schmit, T. J., Zhang, P., & Li, J. (2018). Satellite-based atmospheric infrared sounder development and applications. Bulletin of the American Meteorological Society, 99(3), 583–603. https://doi.org/10.1175/BAMS-D-16-0293.1
   Web of Science ®Google Scholar
• Middleton, W. E. K., & Spilhaus, A. F. (1953). Meteorological instruments (3rd ed.). Univ. of Toronto Press. https://doi.org/10.1002/qj.49708034532
   Google Scholar
• Miller, S. D., Lindsey, D. T., Seaman, C. J., & Solbrig, J. E. (2020). Geocolor: A blending technique for satellite imagery. Journal of Atmospheric and Oceanic Technology, 37(3), 429–448. https://doi.org/10.1175/JTECH-D-19-0134.1
   Web of Science ®Google Scholar
• Miller, S. D., Straka, W. C., Yue, J., Smith, S. M., Alexander, M. J., Hoffmann, L., Setvák, M., & Partain, P. T. (2015). Low-light satellite sees glowing atmospheric waves. Proceedings of the National Academy of Sciences, 112(49), E6728–E6735. https://www.pnas.org/doi/10. 1073/pnas.1508084112. https://doi.org/10.1073/pnas.1508084112
   PubMed Web of Science ®Google Scholar
• Morss, R. E., Emanuel, K. A., & Snyder, C. (2001). Idealized adaptive observation strategies for improving numerical weather prediction. Journal of the Atmospheric Sciences, 58(2), 210–232. https://doi.org/10.1175/1520-0469(2001)058<0210:IAOSFI>2.0.CO;2
   Web of Science ®Google Scholar
• Nag, A., Murphy, M. J., Schulz, W., & Cummins, K. L. (2015). Lightning locating systems: Insights on characteristics and validation techniques. Earth and Space Science, 2(4), 65–93. https://doi.org/10.1002/2014EA000051
   Web of Science ®Google Scholar
• National Research Council. (1999). Adequacy of climate observing systems. National Academies Press. https://doi.org/10.17226/6424
   Google Scholar
• National Research Council. (2002). Weather radar technology beyond NEXRAD. National Academies Press. https://doi.org/10.17226/10394
   Google Scholar
• National Research Council. (2009). Observing weather and climate from the ground up: A nationwide network of networks. National Academies Press. https://doi.org/10.17226/12540
   Google Scholar
• National Research Council. (2018). The future of atmospheric boundary layer observing, understanding, and modeling. National Academies Press. https://doi.org/10.17226/25138
   Google Scholar
• National Research Council. (2018). Thriving on our changing planet: A decadal strategy for earth observation from space. National Academies Press. https://doi.org/10.17226/24938
   Google Scholar
• National Research Council. (2021). Airborne platforms to advance NASA earth system science priorities. National Academies Press. https://doi.org/10.17226/26079
   Google Scholar
• NOAA, Climate Program Office. (2020). A value assessment of an atmospheric composition capability on the NOAA next-generation Geostationary and Extended Observations (GeoXO). NOAA Technical Report OAR CPO-8. https://doi.org/10.25923/1s4s=t405
   Google Scholar
• NOAA-NASA. (2019). GOES-R series data book, Revision A, May 2019, CDRL PM-14. https://www.goes-r.gov/downloads/resources/documents/GOES-RSeriesDataBook.pdf
   Google Scholar
• Nystuen, J. A. (1999). Relative performance of automatic rain gauges under different rainfall conditions. Journal of Atmospheric and Oceanic Technology, 16(8), 1025–1043. https://doi.org/10.1175/1520-0426(1999)016<1025:RPOARG>2.0.CO;2
   Web of Science ®Google Scholar
• Nystuen, J. A., Proni, J. R., Black, P. G., & Wilkerson, J. C. (1996). A comparison of automatic rain gauges. Journal of Atmospheric and Oceanic Technology, 13(1), 62–73. https://doi.org/10.1175/1520-0426(1996)013<0062:ACOARG>2.0.CO;2
   Web of Science ®Google Scholar
• Padula, F., Pearlman, A. J., Cao, C., & Goodman, S. (2016). Towards post-launch validation of GOES-R ABI SI traceability with high-altitude aircraft, small near surface UAS, and satellite reference measurements. Proceedings Society Photo-Optical Instrumentation Engineers (SPIE), 9972, Earth Observing Systems XXI, 99720V (19 September 2016). https://doi.org/10.1117/12.2238181
   Google Scholar
• Peterson, M. J., Lang, T. J., Bruning, E. C., Albrecht, R., Blakeslee, R. J., Lyons, W. A., Pédeboy, S., Rison, W., Zhang, Y., Brunet, M., & Cerveny, R. S. (2020). New WMO certified megaflash lightning extremes for flash distance (709 km) and duration (16.73 seconds) recorded from space. Geophysical Research Letters, https://agupubs.onlinelibrary.wiley.com/doi/10. 1029/2020GL088888
   Web of Science ®Google Scholar
• Rauber, R. J., & Nesbitt, S. W. (2018). Radar meteorology: A first course. Wiley.
   Google Scholar
• Robock, A. (2002). The climatic aftermath. Science, 295(5558), 1242–1244. https://www.science.org/doi/full/10. 1126/science.1069903. https://doi.org/10.1126/science.1069903
   PubMed Web of Science ®Google Scholar
• Rudlosky, S., Goodman, S., Calhoun, K., Schultz, C., Back, A., Kuligowski, B., Stevenson, S., & Gravelle, C. (2020). Geostationary lightning mapper value assessment (NOAA Technical Report NESDIS 153). https://doi.org/10.25923/2616-3v73
   Google Scholar
• Rudlosky, S. D., & Virts, K. S. (2021). Dual geostationary lightning mapper observations. Monthly Weather Review, 149(4), 979–998. https://doi.org/10.1175/MWR-D-20-0242.1
   Web of Science ®Google Scholar
• Ryzhkov, A. V., Schuur, T. J., Burgess, D. W., & Zrnić, D. S. (2005). Polarimetric tornado detection. Journal of Applied Meteorology, 44(5), 557–570. https://doi.org/10.1175/JAM2235.1
   Google Scholar
• Sadeghi, S., Gao, L., Ebtehaj, A., Wigneron, J.-P., Crow, W. T., Reager, J. T., & Warrick, A. W. (2020). Retrieving global surface soil moisture from GRACE satellite gravity data. Journal of Hydrology, 584, 124717. https://doi.org/10.1016/j.jhydrol.2020.124717
   Web of Science ®Google Scholar
• Salazar, J. L., Yu, T.-Y., McCord, M., Diaz, J., Ortiz, J. A., Fulton, C., Yeary, M., Palmer, R., Cheong, B.-L., Bluestein, H., Kurdzo, J. M., & Isom, B. (2019). An ultra-fast scan C-band polarimetric atmospheric imaging radar (PAIR), Institute of Electrical and Electronics Engineers (IEEE), International Symposium on Phased Array Systems & Technology (PAS), 5 pp. https://doi.org/10.1109/PAST43306.2019.9021042
   Google Scholar
• Saunders, R. W., Matricardi, M., & Brunel, P. (1999). An improved fast radiative transfer model for assimilation of satellite radiance observations. Quarterly Journal of the Royal Meteorological Society, 125(556), 1407–1425. https://doi.org/10.1002/qj.1999.49712555615
   Web of Science ®Google Scholar
• Schmit, T. J., Griffith, P., Gunshor, M. M., Daniels, J. M., Goodman, S. J., & Lebair, W. J. (2017). A closer look at the ABI on the GOES-R series. Bulletin of the American Meteorological Society, 98(4), 681–698. https://doi.org/10.1175/BAMS-D-15-00230.1
   Web of Science ®Google Scholar
• Schmit, T. J., Lindstrom, S. S., Gerth, J. J., & Gunshor, M. M. (2018). Applications of the 16 spectral bands on the advanced baseline imager (ABI). Journal of Operational Meteorology, 6((04|4)), 33–46. https://doi.org/10.15191/nwajom.2018.0604
   Web of Science ®Google Scholar
• Schumann, G. J.-P. (2020). Grand challenges in microwave remote sensing. Frontiers Remote Sensing, https://www.frontiersin.org/articles/10. 3389/frsen.2020.603650/full
   Google Scholar
• Serafin, R. J., Carbone, R. E., Browning, K. A., Marks, F. D. Jr., Jorgensen, D. P., Weckwerth, T. M., Bluestein, H. B., Wakimoto, R. M., Gage, K. S., Gossard, E. E., Sun, J., Wilson, J. W., Fabry, F., Keeler, R. J., Chandrasekar, V., Meneghini, R., Zawadzki, I., Rosenfeld, D., Ulbrich, C. W., … Chandrasekar, V. (2003). Radar and atmospheric science: A collection of essays in Honor of David atlas (R. M. Wakimoto and R. C. Srivastava, Eds.) American Meteorological Society.
   Google Scholar
• Smith, W. L., Bishop, W. P., Dvorak, V. F., Hayden, C. M., McElroy, J. H., Mosher, F. R., Oliver, V. J., Purdom, J. F., & Wark, D. Q. (1986). The meteorological satellite: Overview of 25 years of operation. Science, 231(4737), 455–462. https://doi.org/10.1126/science.231.4737.455
   PubMed Web of Science ®Google Scholar
• Snyder, J. C., Bluestein, H. B., Zhang, G., & Frasier, S. J. (2010). Attenuation correction and hydrometeor classification of high-resolution, X-band, dual-polarized mobile radar measurements in severe convective storms. Journal of Atmospheric and Oceanic Technology, 27(12), 1979–2001. https://doi.org/10.1175/2010JTECHA1356.1
   Web of Science ®Google Scholar
• Spuler, S. M., Repasky, K. S., Morley, B., Moen, D., Hayman, M., & Nehrir, A. R. (2015). Field-deployable diode-laser-based differential absorption lidar (DIAL) for profiling water vapor. Atmospheric Measurement Techniques, 8(3), 1073–1087. https://doi.org/10.5194/amt-8-1073-2015
   Web of Science ®Google Scholar
• Stephens, G., Winker, David, Pelon, Jacques, Trepte, Charles, Vane, Deborah, Yuhas, Cheryl, L’Ecuyer, Tristan, & Lebsock M. (2018). Cloudsat and CALIPSO within the A-Train: Ten years of actively observing the Earth system. Bulletin of the American Meteorological Society, 99(3), 569–581. https://doi.org/10.1175/BAMS-D-16-0324.1
   Web of Science ®Google Scholar
• Stickler, A., Grant, A. N., Ewen, T., Ross, T. F., Vose, R. S., Comeaux, J., Bessemoulin, P., Jylhä, K., Adam, W. K., Jeannet, P., Nagurny, A., Sterin, A. M., Allan, R., Compo, G. P., Griesser, T., & Brönnimann, S. (2010). The comprehensive historical upper-air network. Bulletin of the American Meteorological Society, 91(6), 741–752. https://doi.org/10.1175/2009BAMS2852.1
   Web of Science ®Google Scholar
• Stith, J. L., Baumgardner, D., Haggerty, J., Hardesty, R. M., Lee, W., Lenschow, D., Pilewskie, P., Smith, P. L., Steiner, M., & Vömel, H. (2019). 100 years of progress in atmospheric observing systems. In G. McFarquhar (Ed.), Meteorological monographs, 59 (pp. 2.1–2.55). American Meteorlogical Society. https://doi.org/10.1175/AMSMONOGRAPHS-D-18-0006.1
   Google Scholar
• Teixeira, J., Piepmeier, R., Nehrir, A. R., Ao, C. O., Chen, S. S., Clayson, C. A., Fridlind, A. M., Lebsock, M., McCarty, W., Salmun, H., Santanello, J. A., Turner, D. D., Wang, Z., & Zeng, X. (2021). Toward a global planetary boundary layer observing system: The NASA PBL Incubation Study Team Report. NASA PBL Incubation Study Team.
   Google Scholar
• Tsai, Y.-L. S., Dietz, A., Oppelt, N., & Kuenzer, C. (2019). Remote sensing of snow cover using spaceborne SAR: A review. Remote Sensing, 11(12), 1456. https://www.mdpi.com/2072-4292/11/12/1456. https://doi.org/10.3390/rs11121456
   Web of Science ®Google Scholar
• Turner, D. D., & Goldsmith, J. E. M. (1999). Twenty-four-hour Raman lidar water vapor measurements during the Atmospheric Radiation Measurement program’s 1996 and 1997 water vapor intensive observation periods. Journal of Atmospheric and Oceanic Technology, 16(8), 1062–1076. https://doi.org/10.1175/1520-0426(1999)016<1062:TFHRLW>2.0.CO;2
   Web of Science ®Google Scholar
• Van Geffen, J., Boersma, K. F., Eskes, H., Sneep, M., ter Linden, M., Zara, M., & Veefkind, J. P. (2020). S5p TROPOMI NO2 slant column retrieval: Method, stability, uncertainties and comparisons with OMI. Atmospheric Measurement Techniques, 13(3), 1315–1335. https://doi.org/10.5194/amt-13-1315-2020
   Web of Science ®Google Scholar
• Vasiloff, S. V. (2001). Improving tornado warnings with the Federal Aviation Administration’s Terminal Doppler Weather Radar. Bulletin of the American Meteorological Society, 82(5), 861–874. https://doi.org/10.1175/1520-0477(2001)082<0861:ITWWTF>2.3.CO;2
   Web of Science ®Google Scholar
• VonderHaar, T. H., Dittberner, G., & Forsythe, J. (2020). History of science discoveries and weather forecasting advances from early weather satellites, an introduction. 16th Annual Symposium on New Generation Operational Environmental Satellite Systems, 2020 AMS Centennial Annual Meeting, American Meteorological Society.
   Google Scholar
• Wakimoto, R. M., Lee, W.-C., Bluestein, H. B., Liu, C.-H., & Hildebrand, P. H. (1996). ELDORA observations during VORTEX 95. Bulletin of the American Meteorological Society, 77(7), 1465–1481. https://doi.org/10.1175/1520-0477(1996)077<1465:EODV>2.0.CO;2
   Web of Science ®Google Scholar
• Weber, B. L., Wuertz, D. B., Strauch, R. G., Merritt, D. A., Moran, K. P., Law, D. C., van de Kamp, D., Chadwick, R. B., Ackley, M. H., Barth, M. F., Abshire, N. L., Miller, P. A., & Schlatter, T. W. (1990). Preliminary evaluation of the first NOAA demonstration network wind profiler. Journal of Atmospheric and Oceanic Technology, 7(6), 909–918. https://doi.org/10.1175/1520-0426(1990)007<0909:PEOTFN>2.0.CO;2
   Google Scholar
• Weckwerth, T. M., Weber, K. J., Turner, D. D., & Spuler, S. (2016). Validation of a water vapor micropulse differential absorption lidar (DIAL). Journal of Atmospheric and Oceanic Technology, 33(11), 2353–2372. https://doi.org/10.1175/JTECH-D-16-0119.1
   Web of Science ®Google Scholar
• Wielicki, B. A., Barkstrom, B. R., Harrison, E. F., Lee, R. B., III, Smith, G. L., & Cooper, J. E. (1996). Clouds and the Earth’s Radiant Energy System (CERES): An earth observing system experiment. Bulletin of the American Meteorological Society, 77(5), 853–868. https://doi.org/10.1175/1520-0477(1996)077<0853:CATERE>2.0.CO;2
   Web of Science ®Google Scholar
• Wilson, J. W., Weckwerth, T. M., Vivekanadan, J., Wakimoto, R. M., & Russell, R. W. (1994). Boundary layer clear-air radar echoes: Origin of echoes and accuracy of derived winds. Journal of Atmospheric and Oceanic Technology, 11(5), 1184–1206. https://doi.org/10.1175/1520-0426(1994)011<1184:BLCARE>2.0.CO;2
   Web of Science ®Google Scholar
• World Meteorological Organization. (2018). Guide to instruments and methods of observation, Volume III: Observing systems. https://library.wmo.int/doc_num.php?explnum_id=9872
   Google Scholar
• World Meteorological Organization. (2019). Vision for the WMO Integrated Global Observing System in 2040, WMO-1243, 47 pp., Annex 4 to draft Resolution 6.1(1).
   Google Scholar
• World Meteorological Organization Space Programme. (2020). https://public.wmo.int/en/programmes/wmo-space-programme
   Google Scholar
• Wulfmeyer, V., Hardesty, R. M., Turner, D. D., Behrendt, A., Cadeddu, M., Di Girolamo, P., Schluessel, P., van Baelen, J., & Zus, F. (2015). A review of the remote sensing of lower-tropospheric thermodynamic profiles and its indispensable role for the understanding and simulation of water and energy cycles. Reviews of Geophysics, 53(3), 819–895. https://doi.org/10.1002/2014RG000476
   Web of Science ®Google Scholar
• Wurman, J. (1994). Vector winds from a single-transmitter Bistatic dual-Doppler radar network. Bulletin of the American Meteorological Society, 75(6), 983–994. https://doi.org/10.1175/1520-0477(1994)075<0983:VWFAST>2.0.CO;2
   Web of Science ®Google Scholar
• Yang, J., Zhang, Z., Wei, C., Lu, F., & Guo, Q. (2017). Introducing the new generation of Chinese geostationary weather satellites, Fengyun-4. Bulletin of the American Meteorological Society, 98(8), 1637–1658. https://doi.org/10.1175/BAMS-D-16-0065.1
   Web of Science ®Google Scholar
• Zakhvatkina, N., Smirnov, V. R., & Bychkova, I. (2019). Satellite SAR data-based sea ice classification: An overview. Geosciences, 9(4), 152. https://doi.org/10.3390/geosciences9040152
   Web of Science ®Google Scholar
• Zeng, X., Atlas, R., Birk, R. J., Carr, F. H., Carrier, M. J., Cucurull, L., Hooke, W. H., Kalnay, E., Murtugudde, R., Posselt, D. J., Russell, J. L., Tyndall, D. P., Weller, R. A., & Zhang, F. (2020). Use of observing system simulation experiments in the United States. Bulletin of the American Meteorological Society, 101(8), E1427–E1438. https://doi.org/10.1175/BAMS-D-19-0155.1
   Web of Science ®Google Scholar
• Zhang, G. (2016). Weather radar polarimetry. CRC Press. https://doi.org/10.1201/9781315374666
   Google Scholar
• Zhang, J., Howard, K., Langston, C., Kaney, B., Qi, Y., Tang, L., Grams, H., Wang, Y., Cocks, S., Martinaitis, S., Arthur, A., Cooper, K., Brogden, J., & Kitzmiller, D. (2016). Multi-radar multi-sensor (MRMS) quantitative precipitation estimation: Initial operating capabilities. Bulletin of the American Meteorological Society, 97(4), 621–638. https://doi.org/10.1175/BAMS-D-14-00174.1
   Web of Science ®Google Scholar
• Zrnić, D. S., & Ryzhkov, A. V. (1999). Polarimetry for weather surveillance radars. Bulletin of the American Meteorological Society, 80(3), 389–406. https://doi.org/10.1175/1520-0477(1999)080<0389:PFWSR>2.0.CO;2
   Web of Science ®Google Scholar