{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T23:16:30Z","timestamp":1774480590790,"version":"3.50.1"},"reference-count":60,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T00:00:00Z","timestamp":1717027200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Civil Aerospace Technology Advance Research Project","award":["D040405"],"award-info":[{"award-number":["D040405"]}]},{"name":"Civil Aerospace Technology Advance Research Project","award":["42175082"],"award-info":[{"award-number":["42175082"]}]},{"name":"Civil Aerospace Technology Advance Research Project","award":["42075155"],"award-info":[{"award-number":["42075155"]}]},{"name":"Civil Aerospace Technology Advance Research Project","award":["2022AH020093"],"award-info":[{"award-number":["2022AH020093"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["D040405"],"award-info":[{"award-number":["D040405"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42175082"],"award-info":[{"award-number":["42175082"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42075155"],"award-info":[{"award-number":["42075155"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2022AH020093"],"award-info":[{"award-number":["2022AH020093"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Anhui Provincial Colleges Science Foundation for Distinguished Young Scholars","award":["D040405"],"award-info":[{"award-number":["D040405"]}]},{"name":"Anhui Provincial Colleges Science Foundation for Distinguished Young Scholars","award":["42175082"],"award-info":[{"award-number":["42175082"]}]},{"name":"Anhui Provincial Colleges Science Foundation for Distinguished Young Scholars","award":["42075155"],"award-info":[{"award-number":["42075155"]}]},{"name":"Anhui Provincial Colleges Science Foundation for Distinguished Young Scholars","award":["2022AH020093"],"award-info":[{"award-number":["2022AH020093"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In this study, a novel method for retrieving atmospheric temperature profiles with tree-structured Parzen estimator (TPE) and multilayer perceptron (MLP) algorithms was proposed, using FY-4A\/GIIRS (Geosynchronous Interferometric Infrared Sounder) and ERA5 data. Firstly, by adding solar altitude angle, satellite zenith angle, 2m temperature, and surface temperature to the input layer of MLP, there is an improvement in retrieval accuracy. Secondly, TPE is effective in optimizing the hyper-parameters of MLP, and a set of optimized hyper-parameters is obtained through iterative optimization. Thirdly, comparing the retrieved temperature profiles with ERA5 data, we found that retrieval accuracy is influenced by detector, signal-to-noise ratio, terrain, solar altitude angle, satellite zenith angle, and the horizontal temperature gradient. The mean biases of the two adjacent detectors show significant differences, and the retrieval accuracy of the center detectors is greater than that of the north and south sides. The retrieval accuracy is relatively poor in areas with high terrain and large satellite zenith angle. There is a monthly variation in the retrieval accuracy due to the horizontal temperature gradient and signal-to-noise ratio and a significant diurnal variation due to solar altitude angle and signal-to-noise ratio. Compared to in situ sounding data, the mean biases vary from \u22120.56 K to 0.60 K, and the standard deviations vary from 1.26 K to 2.17 K. The analysis of factors influencing retrieval accuracy provides important insights into improving the ability to retrieve atmospheric temperatures from geostationary hyperspectral IR sounder observations for near real-time (NRT) applications.<\/jats:p>","DOI":"10.3390\/rs16111976","type":"journal-article","created":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T10:42:34Z","timestamp":1717065754000},"page":"1976","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Retrieval of Atmospheric Temperature Profiles from FY-4A\/GIIRS Hyperspectral Data Based on TPE-MLP: Analysis of Retrieval Accuracy and Influencing Factors"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-9254-9894","authenticated-orcid":false,"given":"Xiaoze","family":"Xu","sequence":"first","affiliation":[{"name":"School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1966-446X","authenticated-orcid":false,"given":"Wei","family":"Han","sequence":"additional","affiliation":[{"name":"CMA Earth System Modeling and Prediction Centre (CEMC), China Meteorological Administration, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8256-005X","authenticated-orcid":false,"given":"Zhiqiu","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5504-9627","authenticated-orcid":false,"given":"Jun","family":"Li","sequence":"additional","affiliation":[{"name":"CMA National Satellite Meteorological Centre (NSMC), China Meteorological Administration, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruoying","family":"Yin","sequence":"additional","affiliation":[{"name":"CMA Earth System Modeling and Prediction Centre (CEMC), China Meteorological Administration, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1002\/qj.4228","article-title":"Assimilation of Satellite Data in Numerical Weather Prediction. Part II: Recent Years","volume":"148","author":"Eyre","year":"2022","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1175\/BAMS-D-16-0293.1","article-title":"Satellite-Based Atmospheric Infrared Sounder Development and Applications","volume":"99","author":"Menzel","year":"2018","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_3","first-page":"602","article-title":"Research of the Infrared High Spectral (IASI) Satellite Remote Sensing Atmospheric Temperature and Humidity Profiles Based on the One-Dimensional Variational Algorithm","volume":"42","author":"Guan","year":"2019","journal-title":"Trans. Atmos. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Huang, P., Guo, Q., Han, C., Zhang, C., Yang, T., and Huang, S. (2021). An Improved Method Combining ANN and 1D-Var for the Retrieval of Atmospheric Temperature Profiles from FY-4A\/GIIRS Hyperspectral Data. Remote Sens., 13.","DOI":"10.3390\/rs13030481"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1175\/2009JTECHA1210.1","article-title":"Inferring Convective Weather Characteristics with Geostationary High Spectral Resolution IR Window Measurements: A Look into the Future","volume":"26","author":"Sieglaff","year":"2009","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1543","DOI":"10.1109\/JSTARS.2022.3142069","article-title":"Exploration of a Future NOAA Infrared Sounder in Geostationary Earth Orbit","volume":"15","author":"Wang","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1044","DOI":"10.1002\/qj.410","article-title":"The Assimilation of Infrared Atmospheric Sounding Interferometer Radiances at ECMWF","volume":"135","author":"Collard","year":"2009","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3177","DOI":"10.1002\/qj.3171","article-title":"The Assimilation of Cross-track Infrared Sounder Radiances at ECMWF","volume":"143","author":"Eresmaa","year":"2017","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1109\/TGRS.2002.808356","article-title":"AIRS\/AMSU\/HSB on the Aqua Mission: Design, Science Objectives, Data Products, and Processing Systems","volume":"41","author":"Aumann","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1117\/12.221368","article-title":"IASI: Instrument Overview","volume":"Volume 2553","author":"Cayla","year":"1995","journal-title":"Proceedings of the Infrared Spaceborne Remote Sensing III"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1117\/12.455124","article-title":"Development of the Crosstrack Infrared Sounder (CrIS) Sensor Design","volume":"Volume 4486","author":"Glumb","year":"2002","journal-title":"Proceedings of the Infrared Spaceborne Remote Sensing IX"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"E2733","DOI":"10.1175\/BAMS-D-21-0328.1","article-title":"Applications of Geostationary Hyperspectral Infrared Sounder Observations: Progress, Challenges, and Future Perspectives","volume":"103","author":"Li","year":"2022","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_13","first-page":"285","article-title":"Application of FY-4 Atmospheric Vertical Sounder in Weather Forecast","volume":"38","author":"Chen","year":"2019","journal-title":"J. Infrared Millim. Waves"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"e2021GL093794","DOI":"10.1029\/2021GL093794","article-title":"Four-Dimensional Wind Fields from Geostationary Hyperspectral Infrared Sounder Radiance Measurements with High Temporal Resolution","volume":"48","author":"Ma","year":"2021","journal-title":"Geophys. Res. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1175\/JTECH-D-21-0080.1","article-title":"Data Fusion of GEO FY-4A GIIRS and LEO Hyperspectral Infrared Sounders with Surface Observations: A Hong Kong Case Study","volume":"39","author":"Maier","year":"2022","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2273","DOI":"10.1175\/2009JTECHA1248.1","article-title":"High-Spectral- and High-Temporal-Resolution Infrared Measurements from Geostationary Orbit","volume":"26","author":"Schmit","year":"2009","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1562","DOI":"10.1002\/qj.3981","article-title":"Spectrum Calibration of the First Hyperspectral Infrared Measurements from a Geostationary Platform: Method and Preliminary Assessment","volume":"147","author":"Guo","year":"2021","journal-title":"Q. J. R. Meteorolog. Soc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1637","DOI":"10.1175\/BAMS-D-16-0065.1","article-title":"Introducing the New Generation of Chinese Geostationary Weather Satellites, Fengyun-4","volume":"98","author":"Yang","year":"2017","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1002\/qj.3746","article-title":"The Evaluation of FY4A \u2019s Geostationary Interferometric Infrared Sounder (GIIRS) Long-wave Temperature Sounding Channels Using the GRAPES Global 4D-Var","volume":"146","author":"Yin","year":"2020","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1175\/1520-0493(1970)098<0582:ARMFOR>2.3.CO;2","article-title":"A Regression Method for Obtaining Real-Time Temperature and Geopotential Height Profiles from Satellite Spectrometer Measurements and Its Application to Nimbus 3 \u201cSIRS\u201d Observations","volume":"98","author":"Smith","year":"1970","journal-title":"Mon. Weather Rev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1127","DOI":"10.1175\/1520-0469(1976)033<1127:TUOEOS>2.0.CO;2","article-title":"The Use of Eigenvectors of Statistical Covariance Matrices for Interpreting Satellite Sounding Radiometer Observations","volume":"33","author":"Smith","year":"1976","journal-title":"J. Atmos. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1175\/1520-0450(1985)024<0128:TIIIMA>2.0.CO;2","article-title":"The Improved Initialization Inversion Method: A High Resolution Physical Method for Temperature Retrievals from Satellites of the TIROS-N Series","volume":"24","author":"Chedin","year":"1985","journal-title":"J. Appl. Meteorol. Clim."},{"key":"ref_23","unstructured":"Smith, W., Woolf, H., Hayden, C., and Schreiner, A. (1985, January 18\u201322). The Simultaneous Export Retrieval Package. Proceedings of the Technical Proceedings of the Second International TOVS Study Conference, Iglis, Austria."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4677","DOI":"10.1029\/JD089iD03p04677","article-title":"Remote Sensing of Weather and Climate Parameters from HIRS2\/MSU on TIROS-N","volume":"89","author":"Susskind","year":"1984","journal-title":"J. Geophys. Res."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1414","DOI":"10.1002\/2015JD024008","article-title":"Neural Network Temperature and Moisture Retrieval Algorithm Validation for AIRS\/AMSU and CrIS\/ATMS","volume":"121","author":"Milstein","year":"2016","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Berndt, E., Smith, N., Burks, J., White, K., Esmaili, R., Kuciauskas, A., Duran, E., Allen, R., LaFontaine, F., and Szkodzinski, J. (2020). Gridded Satellite Sounding Retrievals in Operational Weather Forecasting: Product Description and Emerging Applications. Remote Sens., 12.","DOI":"10.3390\/rs12203311"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"e2022EA002725","DOI":"10.1029\/2022EA002725","article-title":"Integrating NASA Aqua AIRS in a Real-Time NUCAPS Science-to-Applications System to Support Severe Weather Forecasting","volume":"10","author":"Berndt","year":"2023","journal-title":"Earth Space Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.1175\/WAF-D-22-0204.1","article-title":"A Nowcasting Approach for Low-Earth-Orbiting Hyperspectral Infrared Soundings within the Convective Environment","volume":"38","author":"Kahn","year":"2023","journal-title":"Weather Forecast"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1175\/MWR-D-18-0055.1","article-title":"Trajectory-Enhanced AIRS Observations of Environmental Factors Driving Severe Convective Storms","volume":"147","author":"Kalmus","year":"2019","journal-title":"Mon. Weather Rev."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1175\/2010JAMC2441.1","article-title":"Warning Information in a Preconvection Environment from the Geostationary Advanced Infrared Sounding System\u2014A Simulation Study Using the IHOP Case","volume":"50","author":"Li","year":"2011","journal-title":"J. Appl. Meteorol. Clim."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1175\/JAMC-D-11-0173.1","article-title":"Dual-Regression Retrieval Algorithm for Real-Time Processing of Satellite Ultraspectral Radiances","volume":"51","author":"Smith","year":"2012","journal-title":"J. Appl. Meteorol. Clim."},{"key":"ref_32","first-page":"214","article-title":"Infrared Remote Sensing of Clear Atmosphere and Related Inversion Problem. Part II: Experimental Study","volume":"21","author":"Li","year":"1997","journal-title":"Chin. J. Atmos. Sci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1007\/s00376-013-3094-z","article-title":"Ensemble Retrieval of Atmospheric Temperature Profiles from AIRS","volume":"31","author":"Zhang","year":"2014","journal-title":"Adv. Atmos. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1109\/TGRS.2010.2070508","article-title":"Improved Temperature Sounding and Quality Control Methodology Using AIRS\/AMSU Data: The AIRS Science Team Version 5 Retrieval Algorithm","volume":"49","author":"Susskind","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2005JD006272","DOI":"10.1029\/2005JD006272","article-title":"Accuracy of Geophysical Parameters Derived from Atmospheric Infrared Sounder\/Advanced Microwave Sounding Unit as a Function of Fractional Cloud Cover","volume":"111","author":"Susskind","year":"2006","journal-title":"J. Geophys. Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1007\/s00376-021-1032-z","article-title":"One-Dimensional Variational Retrieval of Temperature and Humidity Profiles from the FY4A GIIRS","volume":"39","author":"Xue","year":"2022","journal-title":"Adv. Atmos. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1016\/S0273-1177(97)00916-2","article-title":"Determination of Atmospheric and Surface Parameters from Simulated AIRS\/AMSU\/HSB Sounding Data: Retrieval and Cloud Clearing Methodology","volume":"21","author":"Susskind","year":"1998","journal-title":"Adv. Space Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"13,628","DOI":"10.1002\/2013JD020436","article-title":"Validation of Satellite Sounder Environmental Data Records: Application to the Cross-track Infrared Microwave Sounder Suite","volume":"118","author":"Nalli","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_39","first-page":"819","article-title":"Preliminary Study on the Capacity of High Spectral Resolution Infrared Atmospheric Sounding Instrument Using AIRS Measurements","volume":"26","author":"Jiang","year":"2010","journal-title":"J. Trop. Meteorol."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Cai, X., Bao, Y., Petropoulos, G.P., Lu, F., Lu, Q., Zhu, L., and Wu, Y. (2020). Temperature and Humidity Profile Retrieval from FY4-GIIRS Hyperspectral Data Using Artificial Neural Networks. Remote Sens., 12.","DOI":"10.3390\/rs12111872"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"577","DOI":"10.11834\/jrs.20210009","article-title":"Review of Temperature Profile Inversion of Satellite-Borne Infrared Hyperspectral Sensors","volume":"25","author":"Cao","year":"2021","journal-title":"Natl. Remote Sens. Bull."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1016\/j.atmosres.2018.06.025","article-title":"An Improved Retrieval Method of Atmospheric Parameter Profiles Based on the BP Neural Network","volume":"213","author":"Zhao","year":"2018","journal-title":"Atmos. Res."},{"key":"ref_43","unstructured":"Snoek, J., Larochelle, H., and Adams, R.P. (2012). Practical Bayesian Optimization of Machine Learning Algorithms. Adv. Neural Inf. Process. Syst., 25."},{"key":"ref_44","first-page":"28","article-title":"Preliminary Study on Atmospheric Temperature Profiles Retrieval from GIIRS Based on FY-4A Satelite","volume":"34","author":"Bao","year":"2017","journal-title":"Aerosp. Shanghai"},{"key":"ref_45","first-page":"281","article-title":"Random Search for Hyper-Parameter Optimization","volume":"13","author":"Bergstra","year":"2012","journal-title":"J. Mach. Learn. Res."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1324","DOI":"10.1016\/j.applthermaleng.2018.12.139","article-title":"Comparative Study of the Artificial Neural Network with Three Hyper-Parameter Optimization Methods for the Precise LP-EGR Estimation Using in-Cylinder Pressure in a Turbocharged GDI Engine","volume":"149","author":"Jo","year":"2019","journal-title":"Appl. Therm. Eng."},{"key":"ref_47","first-page":"2546","article-title":"Algorithms for Hyper-Parameter Optimization","volume":"24","author":"Bergstra","year":"2011","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s11430-012-4398-z","article-title":"A New Method for Retrieving Equivalent Cloud Base Height and Equivalent Emissivity by Using the Ground-Based Atmospheric Emitted Radiance Interferometer (AERI)","volume":"56","author":"Pan","year":"2013","journal-title":"Sci. China Earth Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1007\/s13351-017-6161-z","article-title":"Developing the Science Product Algorithm Testbed for Chinese Next-Generation Geostationary Meteorological Satellites: Fengyun-4 Series","volume":"31","author":"Min","year":"2017","journal-title":"J. Meteorol. Res."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1175\/1520-0426(1999)016<0828:ANRSFP>2.0.CO;2","article-title":"A New Radiosonde System for Profiling the Lower Troposphere","volume":"16","author":"Corner","year":"1999","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1197","DOI":"10.1002\/(SICI)1097-0088(199611)16:11<1197::AID-JOC89>3.0.CO;2-L","article-title":"Resistant, Robust and Non-Parametric Techniques for the Analysis of Climate Data: Theory and Examples, Including Applications to Historical Radiosonde Station Data","volume":"16","author":"Lanzante","year":"1996","journal-title":"Int. J. Climatol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2697","DOI":"10.1175\/1520-0469(2003)060<2697:SEIRB>2.0.CO;2","article-title":"Sampling Errors in Rawinsonde-Array Budgets","volume":"60","author":"Mapes","year":"2003","journal-title":"J. Atmos. Sci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1175\/1520-0426(2001)018<0135:CACORH>2.0.CO;2","article-title":"Characterization and Correction of Relative Humidity Measurements from Vaisala RS80-A Radiosondes at Cold Temperatures","volume":"18","author":"Miloshevich","year":"2001","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1109\/TGRS.2002.808236","article-title":"Retrieval of Atmospheric and Surface Parameters from AIRS\/AMSU\/HSB Data in the Presence of Clouds","volume":"41","author":"Susskind","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"D02112","DOI":"10.1029\/2005JD005846","article-title":"A Quality Control Procedure for GPS Radio Occultation Data","volume":"111","author":"Zou","year":"2006","journal-title":"J. Geophys. Res."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1145\/235815.235821","article-title":"The Quickhull Algorithm for Convex Hulls","volume":"22","author":"Barber","year":"1996","journal-title":"ACM Trans. Math. Softw."},{"key":"ref_57","unstructured":"Kingma, D.P., and Ba, J. (2017). Adam: A Method for Stochastic Optimization. arXiv."},{"key":"ref_58","first-page":"399","article-title":"Quality evaluation of FY-4A\/GIIRS atmospheric temperature profile","volume":"42","author":"Du","year":"2023","journal-title":"J. Infrared Millim. Waves"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"2300","DOI":"10.1175\/2008JAMC1687.1","article-title":"Deriving Atmospheric Temperature of the Tropopause Region\u2013Upper Troposphere by Combining Information from GPS Radio Occultation Refractivity and High-Spectral-Resolution Infrared Radiance Measurements","volume":"47","author":"Borbas","year":"2008","journal-title":"J. Appl. Meteorol. Clim."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2003JD003386","DOI":"10.1029\/2003JD003386","article-title":"Combining Radio Occultation Refractivities and IR\/MW Radiances to Derive Temperature and Moisture Profiles: A Simulation Study plus Early Results Using CHAMP and ATOVS","volume":"108","author":"Menzel","year":"2003","journal-title":"J. Geophys. Res."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/11\/1976\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:51:18Z","timestamp":1760107878000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/11\/1976"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,30]]},"references-count":60,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,6]]}},"alternative-id":["rs16111976"],"URL":"https:\/\/doi.org\/10.3390\/rs16111976","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,30]]}}}