Articles | Volume 17, issue 2
https://doi.org/10.5194/amt-17-583-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-583-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Jan 2024
Research article |
| 26 Jan 2024
| 26 Jan 2024
Joint 1DVar retrievals of tropospheric temperature and water vapor from Global Navigation Satellite System radio occultation (GNSS-RO) and microwave radiometer observations
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, United States
Chi O. Ao
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, United States
Mary G. Morris
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, United States
George A. Hajj
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, United States
Marcin J. Kurowski
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, United States
Francis J. Turk
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, United States
Angelyn W. Moore
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, United States
Related authors
Jonas E. Katona, Manuel de la Torre Juárez, Terence L. Kubar, F. Joseph Turk, Kuo-Nung Wang, and Ramon Padullés
Atmos. Meas. Tech., 18, 953–970, https://doi.org/10.5194/amt-18-953-2025, https://doi.org/10.5194/amt-18-953-2025, 2025
Short summary
Short summary
Polarimetric radio occultations (PROs) use polarized radio signals from satellites to detect moisture and precipitation in Earth's atmosphere. By applying nonlinear regression and k-means cluster analysis to over 2 years of PRO and non-PRO data, this study shows how deviations from a refractivity model relate to vertical profiles of water vapor pressure (moisture) and that differences between components of PRO signals correlate directly with vertical profiles of water path (precipitation).
Sara Vannah, Stephen S. Leroy, Chi O. Ao, E. Robert Kursinski, Kevin J. Nelson, Kuo-Nung Wang, and Feiqin Xie
EGUsphere, https://doi.org/10.5194/egusphere-2024-4127, https://doi.org/10.5194/egusphere-2024-4127, 2025
Short summary
Short summary
Uncertainty estimation for GNSS radio occultation (RO) soundings in the planetary boundary layer (PBL) depends on the algorithms used to process the RO data. We compare the refractivity retrievals from three RO processing centers — each with their own retrieval algorithm — in the PBL, finding a strong underestimation of refractivity in regions with the strongest refractivity gradients, especially in JPL processing, as well as areas of weak overestimation of refractivity near the Poles.
Ramon Padullés, Estel Cardellach, Antía Paz, Santi Oliveras, Douglas C. Hunt, Sergey Sokolovskiy, Jan-Peter Weiss, Kuo-Nung Wang, F. Joe Turk, Chi O. Ao, and Manuel de la Torre Juárez
Earth Syst. Sci. Data, 16, 5643–5663, https://doi.org/10.5194/essd-16-5643-2024, https://doi.org/10.5194/essd-16-5643-2024, 2024
Short summary
Short summary
This dataset provides, for the first time, combined observations of clouds and precipitation with coincident retrievals of atmospheric thermodynamics obtained from the same space-based instrument. Furthermore, it provides the locations of the ray trajectories of the observations along various precipitation-related products interpolated into them with the aim of fostering the use of such dataset in scientific and operational applications.
Shunsuke Aoki, Takuji Kubota, and Francis Joseph Turk
EGUsphere, https://doi.org/10.5194/egusphere-2025-3596, https://doi.org/10.5194/egusphere-2025-3596, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
The EarthCARE/CPR provides the first spaceborne Doppler velocity measurements, while the GPM/DPR excels at observing rain and heavy snow, which are more attenuated in CPR. Using coincident observations from both radars, we examined vertical motions in stratiform and convective precipitation systems. The synergy between the radars enables a more comprehensive understanding of hydrometeor fall speeds and vertical air motions across different precipitation types.
Manisha Ganeshan, Dong L. Wu, Joseph A. Santanello, Jie Gong, Chi Ao, Panagiotis Vergados, and Kevin J. Nelson
Atmos. Meas. Tech., 18, 1389–1403, https://doi.org/10.5194/amt-18-1389-2025, https://doi.org/10.5194/amt-18-1389-2025, 2025
Short summary
Short summary
This study explores the potential of two newly launched commercial Global Navigation Satellite System (GNSS) radio occultation (RO) satellite missions for advancing Arctic lower-atmospheric studies. The products have a good sampling of the lower Arctic atmosphere and are useful to derive the planetary boundary layer (PBL) height during winter months. This research is a step towards closing the observation gap in polar regions due to the decomissioning of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC-1) GNSS RO mission and the lack of high-latitude coverage by its successor (COSMIC-2).
Luis F. Millán, Matthew D. Lebsock, and Marcin J. Kurowski
EGUsphere, https://doi.org/10.5194/egusphere-2025-322, https://doi.org/10.5194/egusphere-2025-322, 2025
Short summary
Short summary
This study explores the potential of a hypothetical spaceborne radar to observe water vapor within clouds.
Marcin J. Kurowski, Matthew D. Lebsock, and Kevin M. Smalley
EGUsphere, https://doi.org/10.5194/egusphere-2025-714, https://doi.org/10.5194/egusphere-2025-714, 2025
Short summary
Short summary
This study explores how clouds respond to pollution throughout the day using high-resolution simulations. Polluted clouds show stronger daily changes: thicker clouds at night and in the morning but faster thinning in the afternoon. Pollution reduces rainfall but enhances drying, deepening the cloud layer. While the pollution initially brightens clouds, the daily cycle of cloudiness slightly reduces this brightening effect.
Jonas E. Katona, Manuel de la Torre Juárez, Terence L. Kubar, F. Joseph Turk, Kuo-Nung Wang, and Ramon Padullés
Atmos. Meas. Tech., 18, 953–970, https://doi.org/10.5194/amt-18-953-2025, https://doi.org/10.5194/amt-18-953-2025, 2025
Short summary
Short summary
Polarimetric radio occultations (PROs) use polarized radio signals from satellites to detect moisture and precipitation in Earth's atmosphere. By applying nonlinear regression and k-means cluster analysis to over 2 years of PRO and non-PRO data, this study shows how deviations from a refractivity model relate to vertical profiles of water vapor pressure (moisture) and that differences between components of PRO signals correlate directly with vertical profiles of water path (precipitation).
Sara Vannah, Stephen S. Leroy, Chi O. Ao, E. Robert Kursinski, Kevin J. Nelson, Kuo-Nung Wang, and Feiqin Xie
EGUsphere, https://doi.org/10.5194/egusphere-2024-4127, https://doi.org/10.5194/egusphere-2024-4127, 2025
Short summary
Short summary
Uncertainty estimation for GNSS radio occultation (RO) soundings in the planetary boundary layer (PBL) depends on the algorithms used to process the RO data. We compare the refractivity retrievals from three RO processing centers — each with their own retrieval algorithm — in the PBL, finding a strong underestimation of refractivity in regions with the strongest refractivity gradients, especially in JPL processing, as well as areas of weak overestimation of refractivity near the Poles.
Terence L. Kubar, Manuel de la Torre Juarez, Jonas Katona, and F. Joseph Turk
EGUsphere, https://doi.org/10.5194/egusphere-2024-3898, https://doi.org/10.5194/egusphere-2024-3898, 2025
Short summary
Short summary
We analyze space-borne observations of simultaneous vertical profiles of precipitation, cloud layers, and temperatures, and find that about 80–90 % of cloud tops globally reach or are below the level of least stability. Since water vapor is limited at these low temperatures, this height may be a more important constraint on cloud top heights than the tropopause height below the level of maximum stability. Only the heaviest precipitating clouds vertically extend above this most unstable level.
Shu-Ya Chen, Ying-Hwa Kuo, Hsiu-Wen Li, Ramon Padullés, Estel Cardellach, and F. Joseph Turk
EGUsphere, https://doi.org/10.5194/egusphere-2024-3708, https://doi.org/10.5194/egusphere-2024-3708, 2025
Short summary
Short summary
This study used Polarimetric radio occultation (PRO) observations to evaluate simulations of cloud hydrometeors with five microphysics schemes for three typhoons from 2019 and 2021. The simulated cloud hydrometeors distributions varied significantly depending on model initial conditions, typhoon structures, and microphysics schemes. Results in this study demonstrate the potential for using PRO observation to evaluate the performance of different microphysics schemes in numerical models.
Ramon Padullés, Estel Cardellach, Antía Paz, Santi Oliveras, Douglas C. Hunt, Sergey Sokolovskiy, Jan-Peter Weiss, Kuo-Nung Wang, F. Joe Turk, Chi O. Ao, and Manuel de la Torre Juárez
Earth Syst. Sci. Data, 16, 5643–5663, https://doi.org/10.5194/essd-16-5643-2024, https://doi.org/10.5194/essd-16-5643-2024, 2024
Short summary
Short summary
This dataset provides, for the first time, combined observations of clouds and precipitation with coincident retrievals of atmospheric thermodynamics obtained from the same space-based instrument. Furthermore, it provides the locations of the ray trajectories of the observations along various precipitation-related products interpolated into them with the aim of fostering the use of such dataset in scientific and operational applications.
Maria J. Chinita, Mikael Witte, Marcin J. Kurowski, Joao Teixeira, Kay Suselj, Georgios Matheou, and Peter Bogenschutz
Geosci. Model Dev., 16, 1909–1924, https://doi.org/10.5194/gmd-16-1909-2023, https://doi.org/10.5194/gmd-16-1909-2023, 2023
Short summary
Short summary
Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
Ramon Padullés, Estel Cardellach, and F. Joseph Turk
Atmos. Chem. Phys., 23, 2199–2214, https://doi.org/10.5194/acp-23-2199-2023, https://doi.org/10.5194/acp-23-2199-2023, 2023
Short summary
Short summary
The results of comparing the polarimetric radio occultation observables and the ice water content retrieved from the CloudSat radar in a global and statistical way show a strong correlation between the geographical patterns of both quantities for a wide range of heights. This implies that horizontally oriented hydrometeors are systematically present through the whole globe and through all vertical levels, which could provide insights on the physical processes leading to precipitation.
Anthony J. Mannucci, Chi O. Ao, Byron A. Iijima, Thomas K. Meehan, Panagiotis Vergados, E. Robert Kursinski, and William S. Schreiner
Atmos. Meas. Tech., 15, 4971–4987, https://doi.org/10.5194/amt-15-4971-2022, https://doi.org/10.5194/amt-15-4971-2022, 2022
Short summary
Short summary
The Global Positioning System (GPS) radio occultation (RO) technique is a satellite-based method for producing highly accurate vertical profiles of atmospheric temperature and pressure. RO profiles are used to monitor global climate trends, particularly in that region of the atmosphere that includes the lower stratosphere. Two data sets spanning 1995–1997 that were produced from the first RO satellite are highly accurate and can be used to assess global atmospheric models.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 15, 117–129, https://doi.org/10.5194/amt-15-117-2022, https://doi.org/10.5194/amt-15-117-2022, 2022
Short summary
Short summary
Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that
smears2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is
towardsor
away fromthe Sun, so calculating
across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.
Richard J. Roy, Matthew Lebsock, and Marcin J. Kurowski
Atmos. Meas. Tech., 14, 6443–6468, https://doi.org/10.5194/amt-14-6443-2021, https://doi.org/10.5194/amt-14-6443-2021, 2021
Short summary
Short summary
This study describes the potential capabilities of a hypothetical spaceborne radar to observe water vapor within clouds.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021, https://doi.org/10.5194/amt-14-5555-2021, 2021
Short summary
Short summary
Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
Miguel Ricardo A. Hilario, Ewan Crosbie, Michael Shook, Jeffrey S. Reid, Maria Obiminda L. Cambaliza, James Bernard B. Simpas, Luke Ziemba, Joshua P. DiGangi, Glenn S. Diskin, Phu Nguyen, F. Joseph Turk, Edward Winstead, Claire E. Robinson, Jian Wang, Jiaoshi Zhang, Yang Wang, Subin Yoon, James Flynn, Sergio L. Alvarez, Ali Behrangi, and Armin Sorooshian
Atmos. Chem. Phys., 21, 3777–3802, https://doi.org/10.5194/acp-21-3777-2021, https://doi.org/10.5194/acp-21-3777-2021, 2021
Short summary
Short summary
This study characterizes long-range transport from major Asian pollution sources into the tropical northwest Pacific and the impact of scavenging on these air masses. We combined aircraft observations, HYSPLIT trajectories, reanalysis, and satellite retrievals to reveal distinct composition and size distribution profiles associated with specific emission sources and wet scavenging. The results of this work have implications for international policymaking related to climate and health.
Cited articles
Ao, C. O.: Effect of ducting on radio occultation measurements: an assessment based on high-resolution radiosonde soundings, Radio Sci., 42, RS2008, https://doi.org/10.1029/2006RS003485, 2007. a, b, c
Bao, Y., Xu, J., Powell Jr., A. M., Shao, M., Min, J., and Pan, Y.: Impacts of AMSU-A, MHS and IASI data assimilation on temperature and humidity forecasts with GSI–WRF over the western United States, Atmos. Meas. Tech., 8, 4231–4242, https://doi.org/10.5194/amt-8-4231-2015, 2015. a
Barnet, C. D.: Sounder SIPS: Suomi NPP CrIMSS Level 2 CLIMCAPS Normal Spectral Resolution: Atmosphere cloud and surface geophysical state V2, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), https://doi.org/10.5067/9HR0XHCH3IGS, 2019. a
Borbás, É., Menzel, W. P., Li, J., and Woolf, H. M.: Combining radio occultation refractivities and IR/MW radiances to derive temperature and moisture profiles: A simulation study plus early results using CHAMP and ATOVS, J. Geophys. Res., 108, 4676, https://doi.org/10.1029/2003JD003386, 2003. a
Bormann, N., Fouilloux, A., and Bell, W.: Evaluation and assimilation of ATMS data in the ECMWF system, J. Geophys. Res.-Atmos., 118, 12970–12980, https://doi.org/10.1002/2013JD020325, 2013. a
Boukabara, S.-A., Garrett, K. Chen, W., Iturbide-Sanchez, F., Grassotti, C., Kongoli, C., Chen, R. , Liu, Q., Yan, B., Weng, F., Ferraro, R., Kleespies, T. J., and Meng, H.: MiRS: An All-Weather 1DVAR Satellite Data Assimilation and Retrieval System, IEEE T. Geosci. Remote, 49, 9, 3249–3272, https://doi.org/10.1109/TGRS.2011.2158438, 2011. a
Burrows, C. P., Healy, S. B., and Culverwell, I. D.: Improving the bias characteristics of the ROPP refractivity and bending angle operators, Atmos. Meas. Tech., 7, 3445–3458, https://doi.org/10.5194/amt-7-3445-2014, 2014. a
Collard, A. D. and Healy, S. B.: The combined impact of future space-based atmospheric sounding instruments on numerical weather-prediction analysis fields: A simulation study, Q. J. Roy. Meteor. Soc., 129, 2741–2760, https://doi.org/10.1256/qj.02.124, 2003. a, b, c
Culverwell, I. D., Lewis, H. W., Offiler, D., Marquardt, C., and Burrows, C. P.: The Radio Occultation Processing Package, ROPP, Atmos. Meas. Tech., 8, 1887–1899, https://doi.org/10.5194/amt-8-1887-2015, 2015. a
Desroziers, G. and Ivanov, S.: Diagnosis and adaptive tuning of observation-error parameters in a variational assimilation, Q. J. Roy. Meteor. Soc., 127, 1433–1452, https://doi.org/10.1002/qj.49712757417, 2001. a
Errico, R. M., Bauer, P., and Mahfouf, J.: Issues Regarding the Assimilation of Cloud and Precipitation Data, J. Atmos. Sci., 64, 3785–3798, 2007. a
Fjeldbo, G., Kliore, A. J., and Eshleman, V. R.: The neutral atmosphere of Venus as studied with the Mariner V radio occultation experiments, Astron. J., 76, 123–140, 1971. a
Fujita, M. and Sato, T.: Observed behaviours of precipitable water vapour and precipitation intensity in response to upper air profiles estimated from surface air temperature, Sci. Rep., 7, 4233, https://doi.org/10.1038/s41598-017-04443-9, 2017. a
Gorbunov, M. E., Vorob'ev, V. V., and Lauritsen, K. B.: Fluctuations of refractivity as a systematic error source in radio occultations, Radio Sci., 50, 656–669, https://doi.org/10.1002/2014RS005639, 2015. a
Grabowski, W. W., Bechtold, P., Cheng, A., Forbes, R., Halliwell, C., Khairoutdinov, M., Lang, S., Nasuno, T., Petch, J., Tao, W.-K., Wong, R., Wu, X., and Xu, K.-M.: Daytime convective development over land: A model intercomparison based on LBA observations, Q. J. Roy. Meteor. Soc., 132, 317–344, https://doi.org/10.1256/qj.04.147, 2006. a
Gustavo Gonçalves de Gonçalves, L., Borak, J. S., Costa, M. H., Saleska, S. R., Baker I., Restrepo-Coupe, N., Muza, M. N., Poulter, B., Verbeeck, H., Fisher, J. B., Arain, M. A., Arkin, P., Cestaro, B. P., Christoffersen, B., Galbraith, D., Guan, X., van den Hurk, B. J. J. M., Ichii, K., Acioli Imbuzeiro, H. M., Jain, A. K., Levine, N., Lu, C., Miguez-Macho, G., Roberti, D. R., Sahoo, A., Sakaguchi, K., Schaefer, K., Shi, M., Shuttleworth, W. J., Tian, H., Yang, Z., and Zeng, X.: Overview of the Large-Scale Biosphere–Atmosphere Experiment in Amazonia Data Model Intercomparison Project (LBA-DMIP) (2013), Agr. Forest Meteorol., 182–183, 111–127, 2013. a
Healy, S. B.: Smoothing radio occultation bending angles above 40 km, Ann. Geophys., 19, 459–468, https://doi.org/10.5194/angeo-19-459-2001, 2001. a, b
Ho, S., Kuo, Y., and Sokolovskiy S.: Improvement of the Temperature and Moisture Retrievals in the Lower Troposphere Using AIRS and GPS Radio Occultation Measurements, J. Atmos. Ocean. Tech., 24, 1726–1739, 2007. a
Holloway, C. E. and Neelin, J. D.: Moisture Vertical Structure, Column Water Vapor, and Tropical Deep Convection, J. Atmos. Sci., 66, 1665–1683, 2009. a
Kazumori, M., Liu, Q., Treadon, R., and Derber, J. C.: Impact Study of AMSR-E Radiances in the NCEP Global Data Assimilation System, Mon. Weather Rev., 136, 541–559, https://doi.org/10.1175/2007MWR2147.1, 2008. a
Keeler, E. and Burk, K.: Balloon-Borne Sounding System (SONDEWNPN), Atmospheric Radiation Measurement (ARM) User Facility, https://doi.org/10.5439/1595321, 2012. a
Kurowski, M. J., Teixeira, J., Ao, C. O., Brown, S., Davis, A., Forster, L., Wang, K.-N., Lebsock, M., Morris, M., Payne, V., Richardson, M., Roy, R., Thompson, D. R., and Wilson, R. C.: Synthetic Observations of the Planetary Boundary Layer from Space: A Retrieval Observing System Simulation Experiment Framework, B. Am. Meteorol. Soc., 104, E1999–E2022, https://doi.org/10.1175/BAMS-D-22-0129.1, 2023. a
Kursinski, E. R., Hajj, G. A., Schofield, J. T., Linfield, R. P., and Hardy, K. R.: Observing Earth's atmosphere with radio occultation measurements using the Global Positioning System, J. Geophys. Res., 102, 23429–23466, 1997. a
Lambrigtsen, B.: Suomi NPP ATMS Sounder Science Investigator-led Processing System (SIPS) Level 1B Brightness Temperature V2, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC), https://doi.org/10.5067/HFDD6A30MA10, 2018. a, b
Lewis, E. R.: Marine ARM GPCI Investigation of Clouds (MAGIC) Field Campaign Report, U.S. Department of Energy, https://doi.org/10.2172/1343577, 2016. a
Liebe, H. J., Hufford, G. A., and Cotton, M. G.: Propagation modeling of moist air and suspended water particles at frequencies below 1000 GHz, Proc. Conf. on Atmospheric Propagation Effects through Natural and Man-Made Obscurants for Visible to MM-Wave Radiation (AGARD-CP-542), 17–20 May 1993, Neuilly sur Seine, France, Advisory Group for Aerospace Research and Development (AGARD), 3-1–3-10, SEE N94-30495 08-32, 1993. a, b
Liu, Q., Cao, C., Grassotti, C., and Lee, Y.-K.: How Can Microwave Observations at 23.8 GHz Help in Acquiring Water Vapor in the Atmosphere over Land?, Remote Sens., 13, 489, https://doi.org/10.3390/rs13030489, 2021. a
Meissner, T. and Wentz, F. J.: The emissivity of the ocean surface between 6–90 GHz over a large range of wind speeds and Earth incidence angles, IEEE Trans. Geosci. Remote, 50, 3004–3026, 2012. a
Mülmenstädt, J., Salzmann, M., and Kay., J. E.: An underestimated negative cloud feedback from cloud lifetime changes Nat. Clim. Chang. 11, 508–513, https://doi.org/10.1038/s41558-021-01038-1, 2021. a
National Centers for Environmental Prediction (NCEP): Monthly Global Data Assimilation System (GDAS) Input Data Counts, https://www.nco.ncep.noaa.gov/pmb/nwprod/gdas/, last access: 20 October 2023. a
Rauber, R. M., Stevens, B., Ochs III, H. T., Knight, C., Albrecht, B. A., Blyth, A. M., Fairall, C. W., Jensen, J. B., Lasher-Trapp, S. G., Mayol-Bracero, O. L., Vali, G., Anderson, J. R., Baker, B. A., Bandy, A. R., Burnet, E., Brenguier, J.-L., Brewer, W. A., Brown, P. R. A., Chuang, R., Cotton, W. R., Di Girolamo, L., Geerts, B., Gerber, H., Göke, S., Gomes, L., Heikes, B. G., Hudson, J. G., Kollias, P., Lawson, R. R., Krueger, S. K., Lenschow, D. H., Nuijens, L., O'Sullivan, D. W., Rilling, R. A., Rogers, D. C., Siebesma, A. P., Snodgrass, E., Stith, J. L., Thornton, D. C., Tucker, S., Twohy, C. H., and Zuidema, P.: Rain in Shallow Cumulus Over the Ocean: The RICO Campaign, B. Am. Meteorol. Soc., 88, 1912–1928, 2007. a
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding – Theory and Practice, World Scientific Publishing Co. Pte. Ltd., ISBN 9789812813718, https://doi.org/10.1142/9789812813718, 2000. a
Rosenkranz P.: Water vapor microwave continuum absorption: A comparison of measurements and models, Radio Sci., 33, 919–928, https://doi.org/10.1029/98RS01182, 1998. a, b
Shao, X., Ho, S.-P., Zhang, B., Cao, C., and Chen, Y.: Consistency and Stability of SNPP ATMS Microwave Observations and COSMIC-2 Radio Occultation over Oceans, Remote Sens., 13, 3754, https://doi.org/10.3390/rs13183754, 2021. a
Sherwood, S. C., Roca, R., Weckwerth, T. M., and Andronova, N. G.: Tropospheric Water Vapor, Convection, and Climate, Rev. Geophys., 48, RG2001, https://doi.org/10.1029/2009RG000301, 2010. a
Smith, E. K. and Weintraub, S.: The constants in the equation for atmosphere refractive index at radio frequencies, P. IRE, 41, 1035–1037, 1953. a
Smith, N. and Barnet, C. D.: Uncertainty Characterization and Propagation in the Community Long-Term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS), Remote Sens., 11, 1227, https://doi.org/10.3390/rs11101227, 2019. a
Stevens, B., Lenschow, D. H., Vali, G., Gerber, H., Bandy, A., Blomquist, B., Brenguier, J.-L., Bretherton, C. S., Burnet, F., Campos, T., Chai, S., Faloona, I., Friesen, D., Haimov, S., Laursen, K., Lilly, D. K., Loehrer, S. M., Malinowski, S. P., Morley, B., Petters, M. D., Rogers, D. C., Russell, L., Savic-Jovcic, V., Snider, J. R., Straub, D., Szumowski, M. J., Takagi, H., Thornton, D. C., Tschudi, M., Twohy, C., Wetzel, M., and van Zanten, M. C.: Dynamics and Chemistry of Marine Stratocumulus – DYCOMS-II, B. Am. Meteorol. Soc., 84, 579–594, 2003. a
Stevens, B., Brogniez, H., Kiemle, C., Lacour, J.-L., Crevoisier, C., and Kiliani, J.: Structure and Dynamical Influence of Water Vapor in the Lower Tropical Troposphere, Surv. Geophys., 38, 1371–1397, https://doi.org/10.1007/s10712-017-9420-8, 2017. a
Todling, R., Semane, N., Anthes, R., and Healy, S.: The relationship between two methods for estimating uncertainties in data assimilation, Q. J. Roy. Meteor. Soc., 148, 2942–2954, https://doi.org/10.1002/qj.4343, 2022. a, b
Tretyakov, M. Y., Koshelev, M. A., Dorovskikh, V. V., Makarov, D. S., and Rosenkranz, P. W.: 60-GHz oxygen band: precise broadening and central frequencies of fine-structure lines, absolute absorption profile at atmospheric pressure, and revision of mixing coefficients, J. Mol. Spectrosc., 231, 1–14, https://doi.org/10.1016/j.jms.2004.11.011, 2005. a
von Engeln, A., Bühler, S., Kirchengast, G., and Künzi, K.: Temperature profile retrieval from surface to mesopause by combining GNSS Radio Occultation and Passive Microwave Limb Sounder Data, Geophys. Res. Lett., 28, 775–778, https://doi.org/10.1029/2000GL011718, 2001. a
von Engeln, A., Nedoluha, G., Kirchengast, G., and Buhler, S.:One-dimensional variational (1-D Var) retrieval of temperature, watervapor, and a reference pressure from radio occultation measurements:A sensitivity analysis, J. Geophys. Res., 108, 4337, https://doi.org/10.1029/2002JD002908, 2003. a, b
Wang, K.-N. and Ao, C. O.: GNSS-RO and MWR 1DVar joint retrieval software and dataset, Jet Propulsion Laboratory [data set], https://genesis.jpl.nasa.gov/ftp/publication_data/Wang_et_al_AMT/, last access: 15 January 2024. a
Wang, K.-N., Garrison, J. L., Acikoz, U., Haase, J. S., Murphy, B, J., Muradyan, P., and Lulich, T.: Open-Loop Tracking of Rising and Setting GPS Radio-Occultation Signals From an Airborne Platform: Signal Model and Error Analysis, IEEE T. Geosci. Remote, 54, 3967–3984, https://doi.org/10.1109/TGRS.2016.2532346, 2016. a
Wang, K.-N., de la Torre Juárez, M., Ao, C. O., and Xie, F.: Correcting negatively biased refractivity below ducts in GNSS radio occultation: an optimal estimation approach towards improving planetary boundary layer (PBL) characterization, Atmos. Meas. Tech., 10, 4761–4776, https://doi.org/10.5194/amt-10-4761-2017, 2017. a, b, c
Wang, K.-N., Ao, C. O., and de la Torre Juárez, M.: GNSS-RO Refractivity Bias Correction Under Ducting Layer Using Surface-Reflection Signal, Remote Sens., 12, 359, https://doi.org/10.3390/rs12030359, 2020. a, b
Zhou, C., Zelinka, M., and Klein, S.: Impact of decadal cloud variations on the Earth's energy budget, Nat. Geosci., 9, 871–874, https://doi.org/10.1038/ngeo2828, 2016. a
Short summary
In this article, we described a joint retrieval approach combining two techniques, RO and MWR, to obtain high vertical resolution and solve for temperature and moisture independently. The results show that the complicated structure in the lower troposphere can be better resolved with much smaller biases, and the RO+MWR combination is the most stable scenario in our sensitivity analysis. This approach is also applied to real data (COSMIC-2/Suomi-NPP) to show the promise of joint RO+MWR retrieval.
In this article, we described a joint retrieval approach combining two techniques, RO and MWR,...
