Articles | Volume 16, issue 12
https://doi.org/10.5194/essd-16-5643-2024
© 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/essd-16-5643-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
10 Dec 2024
Data description paper |
| 10 Dec 2024
| 10 Dec 2024
The PAZ polarimetric radio occultation research dataset for scientific applications
Institut de Ciències de l'Espai, Consejo Superior de Investigaciones Científicas (ICE-CSIC), c/Can Margans, S/N, Campus UAB, 08193 Bellaterra, Spain
Institut d'Estudis Espacials de Catalunya (IEEC), Barcelona, Spain
Estel Cardellach
Institut de Ciències de l'Espai, Consejo Superior de Investigaciones Científicas (ICE-CSIC), c/Can Margans, S/N, Campus UAB, 08193 Bellaterra, Spain
Institut d'Estudis Espacials de Catalunya (IEEC), Barcelona, Spain
Antía Paz
Institut de Ciències de l'Espai, Consejo Superior de Investigaciones Científicas (ICE-CSIC), c/Can Margans, S/N, Campus UAB, 08193 Bellaterra, Spain
Institut d'Estudis Espacials de Catalunya (IEEC), Barcelona, Spain
Santi Oliveras
Institut de Ciències de l'Espai, Consejo Superior de Investigaciones Científicas (ICE-CSIC), c/Can Margans, S/N, Campus UAB, 08193 Bellaterra, Spain
Institut d'Estudis Espacials de Catalunya (IEEC), Barcelona, Spain
Douglas C. Hunt
University Corporation for Atmospheric Research (UCAR), Boulder, CO, USA
Sergey Sokolovskiy
University Corporation for Atmospheric Research (UCAR), Boulder, CO, USA
Jan-Peter Weiss
University Corporation for Atmospheric Research (UCAR), Boulder, CO, USA
Kuo-Nung Wang
Jet Propulsion Laboratory (JPL), California Institute of Technology, Pasadena, CA, USA
F. Joe Turk
Jet Propulsion Laboratory (JPL), California Institute of Technology, Pasadena, CA, USA
Chi O. Ao
Jet Propulsion Laboratory (JPL), California Institute of Technology, Pasadena, CA, USA
Manuel de la Torre Juárez
Jet Propulsion Laboratory (JPL), California Institute of Technology, Pasadena, CA, USA
Related authors
Antía Paz, Ramon Padullés, and Estel Cardellach
EGUsphere, https://doi.org/10.5194/egusphere-2025-1950, https://doi.org/10.5194/egusphere-2025-1950, 2025
Short summary
Short summary
This study explores how different assumptions in cloud microphysics affect the vertical distribution of hydrometeors during extreme precipitation events, such as atmospheric rivers. Using a combination of high-resolution weather simulations and radiative transfer modeling, we identify snow as the dominant contributor to the observed vertical signal. The analysis highlights the sensitivity of precipitation structure to particle properties, that could help refine atmospheric modeling approaches.
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).
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, 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.
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.
Antía Paz, Ramon Padullés, and Estel Cardellach
EGUsphere, https://doi.org/10.5194/egusphere-2025-1950, https://doi.org/10.5194/egusphere-2025-1950, 2025
Short summary
Short summary
This study explores how different assumptions in cloud microphysics affect the vertical distribution of hydrometeors during extreme precipitation events, such as atmospheric rivers. Using a combination of high-resolution weather simulations and radiative transfer modeling, we identify snow as the dominant contributor to the observed vertical signal. The analysis highlights the sensitivity of precipitation structure to particle properties, that could help refine atmospheric modeling approaches.
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).
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.
Kuo-Nung Wang, Chi O. Ao, Mary G. Morris, George A. Hajj, Marcin J. Kurowski, Francis J. Turk, and Angelyn W. Moore
Atmos. Meas. Tech., 17, 583–599, https://doi.org/10.5194/amt-17-583-2024, https://doi.org/10.5194/amt-17-583-2024, 2024
Short summary
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.
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.
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
Anthes, R. A.: Exploring Earth's atmosphere with radio occultation: contributions to weather, climate and space weather, Atmos. Meas. Tech., 4, 1077–1103, https://doi.org/10.5194/amt-4-1077-2011, 2011. a
Ao, C. O., Waliser, D. E., Chan, S. K., Li, J. L., Tian, B., Xie, F., and Mannucci, A. J.: Planetary boundary layer heights from GPS radio occultation refractivity and humidity profiles, J. Geophys. Res.-Atmos., 117, 1–18, https://doi.org/10.1029/2012JD017598, 2012. a
Berg, W.: GPM SSMIS on F16 Common Calibrated Brightness Temperatures L1C 1.5 hours 12 km V07, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/SSMIS/F16/1C/07, 2021a. a
Berg, W.: GPM SSMIS on F17 Common Calibrated Brightness Temperatures L1C 1.5 hours 12 km V07, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/SSMIS/F17/1C/07, 2021b. a
Berg, W.: GPM SSMIS on F18 Common Calibrated Brightness Temperatures L1C 1.5 hours 12 km V07, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/SSMIS/F18/1C/07, 2021c. a
Berg, W.: GPM GMI Common Calibrated Brightness Temperatures Collocated L1C 1.5 hours 13 km V07, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/GMI/GPM/1C/07, 2022a. a
Berg, W.: GPM AMSR-2 on GCOM-W1 Common Calibrated Brightness Temperature L1C 1.5 hours 10 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/AMSR2/GCOMW1/1C/07, 2022b. a
Berg, W.: GPM ATMS on SUOMI-NPP Common Calibrated Brightness Temperature L1C 1.5 hours 16 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/ATMS/NPP/1C/07, 2022c. a
Berg, W.: GPM MHS on NOAA-19 Common Calibrated Brightness Temperatures L1C 1.5 hours 17 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/MHS/NOAA19/1C/07, 2022d. a
Berg, W.: GPM ATMS on NOAA-20 Common Calibrated Brightness Temperatures L1C 1.5 hours 17 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/ATMS/NOAA20/1C/07, 2022e. a
Berg, W.: GPM MHS on METOP-A Common Calibrated Brightness Temperature L1C 1.5 hours 17 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/MHS/METOPA/1C/07, 2022f. a
Berg, W.: GPM MHS on METOP-B Common Calibrated Brightness Temperature L1C 1.5 hours 17 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/MHS/METOPB/1C/07, 2022g. a
Berg, W.: GPM MHS on METOP-C Common Calibrated Brightness Temperature L1C 1.5 hours 17 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/MHS/METOPC/1C/07, 2022h. a
Berg, W.: GPM SAPHIR on MT1 Common Calibrated Brightness Temperature L1C 1.5 hours 10 km V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/SAPHIR/MT1/1C/07, 2022i. a
Beyerle, G., Grunwaldt, L., Heise, S., Köhler, W., König, R., Michalak, G., Rothacher, M., Schmidt, T., Wickert, J., Tapley, B. D., and Giesinger, B.: First results from the GPS atmosphere sounding experiment TOR aboard the TerraSAR-X satellite, Atmos. Chem. Phys., 11, 6687–6699, https://doi.org/10.5194/acp-11-6687-2011, 2011. a
Cardellach, E., Tomás, S., Oliveras, S., Padullés, R., Rius, A., de la Torre-Juárez, M., Turk, F. J., Ao, C. O., Kursinski, E. R., Schreiner, W. S., Ector, D., and Cucurull, L.: Sensitivity of PAZ LEO Polarimetric GNSS Radio-Occultation Experiment to Precipitation Events, IEEE T. Geosci. Remote, 53, 190–206, https://doi.org/10.1109/TGRS.2014.2320309, 2014. a, b, c, d
Cardellach, E., Padullés, R., Tomás, S., Turk, F. J., de la Torre-Juárez, M., and Ao, C. O.: Probability of intense precipitation from polarimetric GNSS radio occultation observations, Q. J. Roy. Meteor. Soc., 144, 206–220, https://doi.org/10.1002/qj.3161, 2017. a
Cardellach, E., Oliveras, S., Rius, A., Tomás, S., Ao, C. O., Franklin, G. W., Iijima, B. A., Kuang, D., Meehan, T. K., Padullés, R., de la Torre-Juárez, M., Turk, F. J., Hunt, D. C., Schreiner, W. S., Sokolovskiy, S. V., Van Hove, T., Weiss, J. P., Yoon, Y., Zeng, Z., Clapp, J., Xia-Serafino, W., and Cerezo, F.: Sensing heavy precipitation with GNSS polarimetric radio occultations, Geophys. Res. Lett., 46, 1024–1031, https://doi.org/10.1029/2018GL080412, 2019. 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
Gong, J. and Wu, D. L.: Microphysical properties of frozen particles inferred from Global Precipitation Measurement (GPM) Microwave Imager (GMI) polarimetric measurements, Atmos. Chem. Phys., 17, 2741–2757, https://doi.org/10.5194/acp-17-2741-2017, 2017. a, b, c
Hajj, G. A., Kursinski, E. R., Romans, L. J., Bertiger, W. I., and Leroy, S. S.: A Technical Description of Atmospheric Sounding By Gps occultation, J. Atmos. Solar-Terr. Phy., 64, 451–469, https://doi.org/10.1016/S1364-6826(01)00114-6, 2002. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D. P., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R. M., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hogan, R. J., Hólm, E. V., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D. P., and Thépaut, J.-N.: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2023. a, b
Huffman, G. J.: GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V05, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/IMERG/3B-HH/05, 2017. a
Huffman, G. J., Stocker, E. F., Bolvin, D. T., Nelkin, E. J., and Tan, J.: GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/IMERG/3B-HH/07, 2023. a
Janowiak, J., Joyce, B., and Xie, P.: NCEP/CPC L3 Half Hourly 4km Global (60S–60N) Merged IR V1, edited by: Savtchenko, A., Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/P4HZB9N27EKU, 2017. a, b
Kidd, C., Huffman, G. J., Maggioni, V., Chambon, P., and Oki, R.: The Global Satellite Precipitation Constellation. Current Status and Future Requirements, B. Am. Meteorol. Soc., 102, 1844–1861, https://doi.org/10.1175/BAMS-D-20-0299.1, 2021. a, b
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, 23429–23465, https://doi.org/10.1029/97JD01569, 1997. a, b
Li, Z., Tang, G., Kirstetter, P. E., Gao, S., Li, J. L., Wen, Y., and Hong, Y.: Evaluation of GPM IMERG and its constellations in extreme events over the conterminous united states, J. Hydrol., 606, 127357, https://doi.org/10.1016/j.jhydrol.2021.127357, 2022. a
Murphy, M. J., Haase, J. S., Padullés, R., Chen, S. H., and Morris, M. A.: The potential for discriminating microphysical processes in numerical weather forecasts using airborne polarimetric radio occultations, Remote Sens., 11, U2048–U2072, https://doi.org/10.3390/rs11192268, 2019. a
Padullés, R., Ao, C. O., Turk, F. J., de la Torre Juárez, M., Iijima, B., Wang, K. N., and Cardellach, E.: Calibration and validation of the Polarimetric Radio Occultation and Heavy Precipitation experiment aboard the PAZ satellite, Atmos. Meas. Tech., 13, 1299–1313, https://doi.org/10.5194/amt-13-1299-2020, 2020. a, b, c, d, e, f, g, h, i, j
Padullés, R., Cardellach, E., Turk, F. J., Ao, C. O., de la Torre-Juárez, M., Gong, J., and Wu, D. L.: Sensing Horizontally Oriented Frozen Particles With Polarimetric Radio Occultations Aboard PAZ: Validation Using GMI Coincident Observations and Cloudsat aPriori Information, IEEE T. Geosci. Remote, 60, 1–13, https://doi.org/10.1109/TGRS.2021.3065119, 2022. a, b, c, d
Padullés, R., Cardellach, E., and Turk, F. J.: On the global relationship between polarimetric radio occultation differential phase shift and ice water content, Atmos. Chem. Phys., 23, 2199–2214, https://doi.org/10.5194/acp-23-2199-2023, 2023. a, b, c
Padullés, R., Cardellach, E., and Oliveras, S.: resPrf, DIGITAL.CSIC [data set], https://doi.org/10.20350/DIGITALCSIC/16137, 2024. a, b
Paz, A., Padullés, R., and Cardellach, E.: Evaluating the Polarimetric Radio Occultation Technique Using NEXRAD Weather Radars, Remote Sens., 16, 1118, https://doi.org/10.3390/rs16071118, 2024. a
Peinó, E., Bech, J., and Udina, M.: Performance Assessment of GPM IMERG Products at Different Time Resolutions, Climatic Areas and Topographic Conditions in Catalonia, Remote Sens., 14, 5085, https://doi.org/10.3390/rs14205085, 2022. a
Ramadhan, R., Yusnaini, H., Marzuki, M., Muharsyah, R., Suryanto, W., Sholihun, S., Vonnisa, M., Harmadi, H., Ningsih, A. P., Battaglia, A., Hashiguchi, H., and Tokay, A.: Evaluation of GPM IMERG Performance Using Gauge Data over Indonesian Maritime Continent at Different Time Scales, Remote Sens., 14, 1–24, https://doi.org/10.3390/rs14051172, 2022. a
Sokolovskiy, S.: Improvements, modifications, and alternative approaches in the processing of GPS RO data, in: ECMWF/EUMETSAT ROM SAF Workshop, 16–18 June 2014, Reading, UK, https://cdaac-www.cosmic.ucar.edu/cdaac/doc/documents/Sokolovskiy_newroam.pdf (last access: 4 December 2024), 2014. a
Sokolovskiy, S. V., Kuo, Y.-H., Rocken, C., Schreiner, W. S., Hunt, D. C., and Anthes, R. A.: Monitoring the atmospheric boundary layer by GPS radio occultation signals recorded in the open-loop mode, Geophys. Res. Lett., 33, 12–15, https://doi.org/10.1029/2006GL025955, 2006. a
Turk, F. J., Padullés, R., Ao, C. O., de la Torre-Juárez, M., Wang, K.-N., Franklin, G. W., Lowe, S. T., Hristova-Veleva, S. M., Fetzer, E. J., Cardellach, E., Kuo, Y.-H., and Neelin, J. D.: Benefits of a closely-spaced satellite constellation of atmospheric polarimetric radio occultation measurements, Remote Sens., 11, 2399, https://doi.org/10.3390/rs11202399, 2019. a
Turk, F. J., Padullés, R., Cardellach, E., Ao, C. O., Wang, K.-N., Morabito, D. D., de la Torre-Juárez, M., Oyola, M., Hristova-Veleva, S. M., and Neelin, J. D.: Interpretation of the Precipitation Structure Contained in Polarimetric Radio Occultation Profiles Using Passive Microwave Satellite Observations, J. Atmos. Ocean. Tech., 38, 1727–1745, https://doi.org/10.1175/jtech-d-21-0044.1, 2021. a, b
Turk, F. J., Padullés, R., Morabito, D. D., Emmenegger, T., and Neelin, J. D.: Distinguishing Convective-Transition Moisture-Temperature Relationships with a Constellation of Polarimetric Radio Occultation Observations in and near Convection, Atmosphere, 13, 1–27, https://doi.org/10.3390/atmos13020259, 2022. a
Turk, F. J., Cardellach, E., de la Torre-Juárez, M., Padullés, R., Wang, K.-N., Ao, C. O., Kubar, T. L., Murphy, M. J., Neelin, J. D., Emmenegger, T., Wu, D. L., Nguyen, V., Kursinski, E. R., Masters, D., Kirstetter, P. E., Cucurull, L., and Lonitz, K.: Advances in the Use of Global Navigation Satellite System Polarimetric Radio Occultation Measurements for NWP and Weather Applications, B. Am. Meteorol. Soc., 105, E905–E914, https://doi.org/10.1175/BAMS-D-24-0050.1, 2024. a
UCAR-COSMIC-Program: PAZ RO Data Products, UCAR [data set], https://doi.org/10.5065/k9vg-t494, 2023a. a, b
UCAR-COSMIC-Program: TerraSar-X RO Data Products, UCAR [data set], https://doi.org/10.5065/fv7s-ax27, 2023b. a, b
Unidata: NetCDF data format Version 4, Unidata [data set], https://doi.org/10.5065/D6H70CW6, 2023. a
Wang, K.-N., Ao, C. O., Padullés, R., Turk, F. J., de la Torre-Juárez, M., and Cardellach, E.: The Effects of Heavy Precipitation on Polarimetric Radio Occultation (PRO) Bending Angle Observations, J. Atmos. Ocean. Tech., 39, 161–173, https://doi.org/10.1175/jtech-d-21-0032.1, 2021. a
Watters, D. C., Gatlin, P. N., Bolvin, D. T., Huffman, G. J., Joyce, R., Kirstetter, P., Nelkin, E. J., Ringerud, S., Tan, J., Wang, J., and Wolff, D.: Oceanic Validation of IMERG-GMI Version 6 Precipitation Using the GPM Validation Network, J. Hydrometeorol., 25, 125–142, https://doi.org/10.1175/jhm-d-23-0134.1, 2023. a
Wee, T. K., Anthes, R. A., Hunt, D. C., Schreiner, W. S., and Kuo, Y. H.: Atmospheric GNSS RO 1D-Var in Use at UCAR: Description and Validation, Remote Sens., 14, 5614, https://doi.org/10.3390/rs14215614, 2022. a
Weiss, J. P. and Hunt, D. C.: GNSS High Rate Binary Format (v2.1), Tech. rep., UCAR, https://cdaac-www.cosmic.ucar.edu/cdaac/fileFormats/GNSS_High_Rate_Binary_Format_v2.1.pdf (last access: 4 December 2024), 2022. a
Zeng, X., Skofronick-Jackson, G., Tian, L., Emory, A. E., Olson, W. S., and Kroodsma, R. A.: Analysis of the global microwave polarization data of clouds, J. Climate, 32, 3–13, https://doi.org/10.1175/JCLI-D-18-0293.1, 2019. a, b
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.
This dataset provides, for the first time, combined observations of clouds and precipitation...
Altmetrics
Final-revised paper
Preprint