Abstract
Accurate estimation of the planetary boundary layer (PBL) top is essential for air quality prediction, weather forecast, and assessment of regional and global climate models. In this article, the long-term climatology of seasonal, global distribution of PBL is presented by using global positioning system radio occultation (GPSRO) based payloads such as Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), Communication/Navigation Outage Forecast System (C/NOFS), TerraSAR-X, and The Gravity Recovery and Climate Experiment (GRACE) from the year 2006–2015. We used Wavelet Covariance Transform (WCT) technique for precise PBL top identification. The derived PBL top from GPSRO data is rigorously evaluated with GPS radiosonde data over Gadanki. Significant seasonal variation is noticed in both radiosonde and GPSRO observations. Further, we compared the PBL obtained GPS RO with global radiosonde network and observed very good correlation. The number of occultations reaching down to 500 m and retrieval rate of PBL top from WCT method is very high in mid-latitudes compared to tropical latitudes. The global distribution of PBL top shows significant seasonal variation with higher during summer followed by spring, fall, and minimum in winter. In the vicinity of Inter Tropical Convergence Zone (ITCZ), the PBL top is high over eastern Pacific compared to other regions. The ERA-Interim reanalysis data underestimate the PBL top compared to GPS RO observations due to different measurement techniques. The seasonal variation of global averaged PBL top over land and ocean shows contrasting features at different latitude bands.
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References
Anthes RA, Ector D, Hunt DC, Kuo Y-H, Rocken C, Schreiner WS et al (2008) The COSMIC/FORMOSAT-3 mission early results. Bull Am Meteor Soc 89(3):313–333. https://doi.org/10.1175/BAMS-89-3-313
Ao C, Waliser B, Chan S, Li J-L, Tian B, Xie F, Mannucci A (2012) Planetary boundary layer heights from GPS radio occultation refractivity and humidity profiles. J Geophys Res Atmos 117:D16117. https://doi.org/10.1029/2012JD017598
Baars H, Ansmann A, Engelmann R, Althausen D (2008) Continuous monitoring of the boundary-layer top with lidar. Atmos Chem Phys 8:7281–7296. https://doi.org/10.5194/acp-8-7281-2008
Basha G, Ratnam MV (2009) Identification of atmospheric boundary layer height over a tropical station using high resolution radiosonde refractivity profiles: Comparison with GPS radio occultation measurements. J Geophys Res Atmos 114:D16101. https://doi.org/10.1029/2008JD011692
Basha G, Ratnam MV. Manjula G, Chandra Sekhar AV (2013) Anomalous wave propagation conditions observed over a tropical station using high-resolution GPS radiosonde observations. Radio Sci 48:42–49. https://doi.org/10.1002/rds.20012
Basha G, Kishore P, Ratnam MV, Ouarda TBMJ., Velicogna I, Sutterley T (2015) Vertical and latitudinal variation of the intertropical convergence zone derived using GPS radio occultation measurements. Remote Sens Environ 163:262–269
Batchvarova E, Gryning S-E (1991) Applied Model for the growth of the daytime mixed layer. Bound Layer Meteorol 56:261–274
Brooks IM (2003) Finding boundary layer top: application of a wavelet covariance transform to lidar backscatter profiles. J Atmos Ocean Technol 22:1092–1105
de la Beaujardiere O et al (2004) C/NOFS: A mission to forecast scintillation, J Atmos Solar Terr Phys 66: 1573, https://doi.org/10.1016/j.jastp.2004.07.030
Fetzer E, Teixeira J, Olsen E, Fishbein E (2004) Satellite remote sounding of atmospheric boundary layer temperature inversions over the subtropical eastern Pacific. Geophys Res Lett 31:L17102. https://doi.org/10.1029/2004GL020174
Gamage N, Hagelberg C (1993) Detection and analysis of microfronts and associated coherent events using localized transforms. J Atmos Sci 50:750–756
Garratt JR (1992) The atmospheric boundary layer. Cambridge atmospheric and space science series. Cambridge University Press, Cambridge, 316 pp
Gryning S-E, Batchvarova E (2002) Marine boundary layer and turbulent fluxes over the Baltic Sea. Measurements and modelling. Bound Layer Meteorol 103:29–47. https://doi.org/10.1023/A:1014514513936
Guo P, Kuo Y-H, Sokolovskiy SV, Lenschow DH (2011) Estimating atmospheric boundary layer depth using COSMIC radio occultation data. J Atmos Sci 68: 1703–1713. https://doi.org/10.1175/2011JAS3612.1
Ho S-P, Peng L, Anthes RA, Kuo Y-H, Lin H-C (2014) Marine boundary layer heights and their longitudinal, diurnal, and interseasonal variability in the Southeastern Pacific using COSMIC, CALIOP, and radiosonde data. J Clim 28:2856–2872
Johansson C, Bergstro H (2005) An auxiliary tool to determine the height of the boundary layer. Bound Layer Meteorol 115:423–432. https://doi.org/10.1007/s10546-004-1424-5
Kahle R, Schlepp B, Meissner F, Kirchner M, Kiehling M (2011) In: TerraSAR-X/TanDEM-X formation acquisition analysis and flight results 21st AAS/AISS Space Flight Mechanics Meeting, New Orleans
Karlsson J, Svensson G, Cardoso S, Teixeira J, Paradise S (2010) Subtropical cloud regime transitions: boundary layer depth and cloud-top height evolution in models and observations. J Appl Meteorol Climatol 49:1845–1858. https://doi.org/10.1175/2010JAMC2338.1
Kishore P, Ratnam MV, Namboothiri SP, Velicogna I, Basha G, Jiang JH et al (2011) Global (50S-50 N) distribution of water vapor observed by COSMIC GPS RO: Comparison with GPS radiosonde, NCEP, ERA-Interim, and JRA-25 reanalysis datasets. J Atmos Solar Terr Phys 73(13):1849–1860. https://doi.org/10.1016/j.jastp.2011.04.017
Kishore P et al (2016) Evaluating CMIP5 models using GPS radio occultation COSMIC temperature in UTLS region during 2006–2013: Twenty-first century projection and trends. Clim Dyn. https://doi.org/10.1007/s00382-016-3024-8
Krieger G, Moreira A, Fiedler H, Hajnsek I, Werner M, Younis M, Zink M (2007) Tan DEM-X: a satellite formation for high-resolution SAR interferometry. IEEE Trans Geosci Remote Sens 45:3317–3341
Luo T, Wang Z, Zhang D, Chen B (2016) Marine boundary layer structure as observed by A-train satellites. Atmos Chem Phys 16:5891–5903. https://doi.org/10.5194/acp-16-5891-2016
McGrath-Spangler EL, Denning AS (2013) Global seasonal variations of midday planetary boundary layer depth from CALIPSO space-borne LIDAR. J Geophys Res Atmos 118:1226–1233
Mehta SK, Ratnam MV, Sunilkumar SV, Rao DN, Krishna Murthy BV (2017) Diurnal variability of the atmospheric boundary layer height over a tropical station in the Indian monsoon region. Atmos Chem Phys 17:531–549. https://doi.org/10.5194/acp-17-531-2017
Norris JR (1998) Low cloud type over the ocean from surface observations. Part I: relationship to surface meteorology and the vertical distribution of temperature and moisture. J Clim 11:369–382. https://doi.org/10.1175/1520-0442(1998)011,0369:LCTOTO.2.0.CO;2
Rao DN, Ratnam MV, Mehta S, Nath D, Basha G, Jagannadha Rao VVM et al (2009) Validation of the COSMIC radio occultation data over gadanki (13. 48°N, 79.2°E): A tropical region. Terr J Atmos Ocean Sci 20:59–70. https://doi.org/10.3319/TAO.2008.01.23.01(F3C)
Ratnam MV, Basha G (2010) A robust method to determine global distribution of atmospheric boundary layer top from COSMIC GPS RO measurements. Atmos Sci Lett 11:216–222. https://doi.org/10.1002/asl.277
Ratnam MV, Basha G, Krishna Murthy BV, Jayaraman A (2013) Relative humidity distribution from SAPHIR experiment on board Megha-Tropiques satellite mission: comparison with global radiosonde and other satellite and reanalysis data sets. J Geophys Res Atmos 118:9622–9630. https://doi.org/10.1002/jgrd.50699
Seibert P, Beyrich F, Gryning S-E, Joffre S, Rasmussen A, Tercier P (2000) Review and intercomparison of operational methods for the determination of the mixing height. Atmos Environ 34:1001–1027
Sempreviva AM, Gryning S-E (2000) Mixing height over water and its role on the correlation between temperature and humidity fluctuations in the unstable surface layer. Bound Layer Meteorol 97:273–291. https://doi.org/10.1023/A:1002749729856
Sokolovski SV, Kuo Y-H, Rocken C, Schreiner WS, Hunt DR, Anthes A (2006) Monitoring the atmospheric boundary layer by GPS radio occultation signals recorded in the open-loop mode. Geophys Res Lett 33:L12813. https://doi.org/10.1029/2006GL025955
Strull RB (1988) An Introduction to Boundary Layer Meteorology. Kluwer Academic, Dordrecht
Tapley BD, Bettadpur S, Watkins M, Reigber C (2004) The gravity recovery and climate experiment: Mission overview and early results. Geophys Res Lett 31:L09607. https://doi.org/10.1029/2004GL019920
Teixeira J et al (2011) Tropical and sub-tropical cloud transitions in weather and climate prediction models: the GCSS/WGNE Pacific Crosssection Intercomparison (GPCI). J Clim 24(20):5223–5256. https://doi.org/10.1175/2011JCLI3672.1
Troen I, Mahrt M (1986) A simple model of the atmospheric boundary layer. Bound-Layer Meteorol 37:129–149
von Engeln A, Teixeira J (2013) A planetary boundary layer height climatology derived from ECMWF reanalysis data. J Clim 26:6575e6590
von Engeln A, Teixeira J, Wickert J, Buehler SA (2005) Using CHAMP radio occultation data to determine the top altitude of the planetary boundary layer. Geophys Res Lett 32:L06815. https://doi.org/10.1029/2004GL022168
Wickert J et al (2005) GPS radio occultation with CHAMP and GRACE: A first look at a new and promising satellite configuration for global atmospheric sounding. Ann Geophys 23:653–658
Wood R (2012) Stratocumulus clouds. Mon Weather Rev 140:2373–2423. https://doi.org/10.1175/MWR-D-11-00121.1
Xie F, Wu DL, Ao CO, Mannucci AJ, Kursinski ER(2012) Advances and limitations of atmospheric boundary layer observations with GPS occultation over southeast Pacific Ocean. Atmos Chem Phys 12:903–918, https://doi.org/10.5194/acp-12-903-2012
Acknowledgements
The authors acknowledge the CDAAC for provision of all the four GPSRO satellite datasets. Radiosonde data were obtained from the Integrated Global Radiosonde Archive (IGRA), National Climatic Data Center, National Oceanic and Atmospheric Administration. We would like to thank the ERA Interim for providing the PBL top information. Jonathan, and Chi O. Ao work at JPL, California Institute of Technology, was carried out under a contract with the National Aeronautics and Space Administration. Thanks to Ian M. Brooks for his help to make my code perfect. The authors are indebted to the Editor Jianping Li and two anonymous reviewers whose comments helped considerably improve the quality of the paper.
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Basha, G., Kishore, P., Ratnam, M.V. et al. Global climatology of planetary boundary layer top obtained from multi-satellite GPS RO observations. Clim Dyn 52, 2385–2398 (2019). https://doi.org/10.1007/s00382-018-4269-1
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DOI: https://doi.org/10.1007/s00382-018-4269-1