• Barros, A. P., M. Joshi, J. Putkonen, and D. W. Burbank, 2000: A study of the 1999 monsoon rainfall in a mountainous region in central Nepal using TRMM products and rain gauge observations. Geophys. Res. Lett., 27, 36833686, doi:10.1029/2000GL011827.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barros, A. P., and Coauthors, 2014: NASA GPM—Ground Validation Integrated Precipitation and Hydrology Experiment 2014 Science Plan. Tech. Rep., Duke University, 64 pp. [Available online at http://dukespace.lib.duke.edu/dspace/handle/10161/8991.]

    • Crossref
    • Export Citation
  • Chen, S., and Coauthors, 2013: Evaluation of spatial errors of precipitation rates and types from TRMM spaceborne radar over the southern CONUS. J. Hydrometeor., 14, 18841896, doi:10.1175/JHM-D-13-027.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Condom, T., P. Rau, and J. C. Espinoza, 2011: Correction of TRMM 3B43 monthly precipitation data over the mountainous area of Peru during the period 1998–2007. Hydrol. Processes, 25, 19241933, doi:10.1002/hyp.7949.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doswell, C., III, R. Davies-Jones, and D. Keller, 1990: On summary measures of skill in rare event forecasting based on contingency tables. Wea. Forecasting, 5, 576585, doi:10.1175/1520-0434(1990)005<0576:OSMOSI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Draper, D. W., D. A. Newell, F. J. Wentz, S. Krimchansky, and G. M. Skofronick-Jackson, 2015: The Global Precipitation Measurement (GPM) Microwave Imager (GMI): Instrument overview and early on-orbit performance. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 8, 34523462, doi:10.1109/JSTARS.2015.2403303.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duan, Y., A. Wilson, and A. Barros, 2015: Scoping a field experiment: Error diagnostics of TRMM Precipitation Radar estimates in complex terrain as a basis for IPHEx2014. Hydrol. Earth Syst. Sci., 19, 15011530, doi:10.5194/hess-19-1501-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Furukawa, K., T. Nio, T. Konishi, R. Oki, T. Masaki, T. Kubota, T. Iguchi, and H. Hanado, 2015: Current status of the Dual-Frequency Precipitation Radar on the Global Precipitation Measurement core spacecraft. Sensors, Systems, and Next-Generation Satellites XIX, R. Meynart, S. P. Neeck, and H. Shimoda, Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 9639), 96390G, doi:10.1117/12.2193868.

    • Crossref
    • Export Citation
  • Gabella, M., 2015: Checking absolute calibration of vertical and horizontal polarization weather radar receivers using the solar flux. J. Electr. Eng., 3, 163169.

    • Search Google Scholar
    • Export Citation
  • Gabella, M., J. Joss, G. Perona, and S. Maichaelides, 2006a: Range adjustment for ground-based radar, derived with the spaceborne TRMM Precipitation Radar. IEEE Trans. Geosci. Remote Sens., 44, 126133, doi:10.1109/TGRS.2005.858436.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gabella, M., S. Michaelides, P. Constantinides, and G. Perona, 2006b: Climatological validation of TRMM Precipitation Radar monthly rain products over Cyprus during the first 5 years (December 1997 to November 2002). Meteor. Z., 15, 559564, doi:10.1127/0941-2948/2006/0158.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gabella, M., E. Morin, and R. Notarpietro, 2011: Using TRMM spaceborne radar as a reference for compensating ground-based radar range degradation: Methodology verification based on rain gauges in Israel. J. Geophys. Res., 116, D02114, doi:10.1029/2010JD014496.

    • Search Google Scholar
    • Export Citation
  • Germann, U., and J. Joss, 2002: Mesobeta profiles to extrapolate radar precipitation measurements above the Alps to the ground level. J. Appl. Meteor., 41, 542557, doi:10.1175/1520-0450(2002)041<0542:MPTERP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Germann, U., and J. Joss, 2004: Operational measurement of precipitation in mountainous terrain. Weather Radar: Principles and Advanced Applications, P. Meischner, Ed., Springer, 52–77.

    • Crossref
    • Export Citation
  • Germann, U., G. Galli, M. Boscacci, and M. Bolliger, 2006: Radar precipitation measurement in a mountainous region. Quart. J. Roy. Meteor. Soc., 132, 16691692, doi:10.1256/qj.05.190.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Germann, U., M. Boscacci, M. Gabella, and M. Sartori, 2015: Peak performance: Radar design for precipitation in the Swiss Alps. Meteorological Technology International, April 2015, UKIP Media and Events, Surrey, United Kingdom, 42–45. [Available online at http://www.ukipme.com/pub-meteorological.php.]

  • Houze, R., Jr., 2012: Orographic effects on precipitating clouds. Rev. Geophys., 50, RG1001, doi:10.1029/2011RG000365.

  • Houze, R., Jr., K. L. Rasmussen, S. Medina, S. R. Brodzik, and U. Romatschke, 2011: Anomalous atmospheric events leading to the summer 2010 floods in Pakistan. Bull. Amer. Meteor. Soc., 92, 291298, doi:10.1175/2010BAMS3173.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houze, R., Jr., L. McMurdie, W. Petersen, and M. Schallwer, 2015: OLYMPEX ground validation experiment field operations plan (version 3). Tech. Rep., University of Washington, 57 pp. [Available online at http://olympex.atmos.washington.edu/docs/OLYMPEX_OpsPlan.pdf.]

  • Huaxing, L., 2008: Modelling terrain complexity. Advances in Digital Terrain Analysis, Q. Zhou, B. Lees, and G.-A. Tang, Eds., Springer, 159–176, doi:10.1007/978-3-540-77800-4_9.

    • Crossref
    • Export Citation
  • Iguchi, T., S. Seto, R. Meneghini, N. Yoshida, J. Awaka, M. Le, V. Chandrasekar, and T. Kubota, 2015: GPM/DPR Level-2 Algorithm Theoretical Basis Document. Tech. Rep., NASA/JAXA, 72 pp. [Available online at https://pmm.nasa.gov/sites/default/files/document_files/ATBD_GPM_DPR_n3_dec15.pdf.]

  • Isotta, F. A., and Coauthors, 2014: The climate of daily precipitation in the Alps: Development and analysis of a high-resolution grid dataset from pan-alpine rain-gauge data. Int. J. Climatol., 34, 16571675, doi:10.1002/joc.3794.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jarvis, A., H. Reuter, A. Nelson, and E. Guevara, 2008: Hole-filled SRTM for the globe version 4. SRTM 90m Database, CGIAR-CSI, accessed 1 April 2016. [Available online at http://srtm.csi.cgiar.org.]

  • Kubota, T., and Coauthors, 2014: Evaluation of precipitation estimates by at-launch codes of GPM/DPR algorithms using synthetic data from TRMM/PR observations. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 7, 39313944, doi:10.1109/JSTARS.2014.2320960.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kummerow, C., W. Barnes, T. Kozu, J. Shiue, and J. Simpson, 1998: The Tropical Rainfall Measuring Mission (TRMM) sensor package. J. Atmos. Oceanic Technol., 15, 809817, doi:10.1175/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mourre, L., T. Condom, C. Junquas, T. Lebel, J. Sicart, R. Figueroa, and A. Cochachin, 2016: Spatio-temporal assessment of WRF, TRMM and in situ precipitation data in a tropical mountain environment (Cordillera Blanca, Peru). Hydrol. Earth Syst. Sci., 20, 125141, doi:10.5194/hess-20-125-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • NASA/JAXA, 2015: Global Precipitation Measurement precipitation processing system: File specification 2ADPR. NASA/JAXA, 103 pp. [Available online at https://storm.pps.eosdis.nasa.gov/storm/data/docs/filespec.GPM.V1.2ADPR.pdf.]

  • Nastos, P., J. Kapsomenakis, and K. Philandras, 2016: Evaluation of the TRMM 3B43 gridded precipitation estimates over Greece. Atmos. Res., 169, 497514, doi:10.1016/j.atmosres.2015.08.008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neeck, S. P., R. K. Kakar, A. A. Azarbarzin, and A. Y. Hou, 2014: Global Precipitation Measurement (GPM) launch, commissioning, and early operations. Sensors, Systems, and Next-Generation Satellites XVIII, R. Meynart, S. P. Neeck, and H. Shimoda, Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 9241), 924104, doi:10.1117/12.2069868.

    • Crossref
    • Export Citation
  • Pellarin, T., G. Delrieu, G.-R. Saulnier, H. Andrieu, B. Vignal, and J.-D. Creutin, 2002: Hydrologic visibility of weather radar systems operating in mountainous regions: Case study for the Ardèche catchment (France). J. Hydrometeor., 3, 539555, doi:10.1175/1525-7541(2002)003<0539:HVOWRS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prasetia, R., A. Rahman As-syakur, and T. Osawa, 2013: Validation of TRMM Precipitation Radar satellite data over Indonesian region. Theor. Appl. Climatol., 112, 575587, doi:10.1007/s00704-012-0756-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Romatschke, U., S. Medina, and R. A. Houze Jr., 2010: Regional, seasonal, and diurnal variations of extreme convection in the South Asian region. J. Climate, 23, 419439, doi:10.1175/2009JCLI3140.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schaefer, J., 1990: The critical success index as an indicator of warning skill. Wea. Forecasting, 5, 570575, doi:10.1175/1520-0434(1990)005<0570:TCSIAA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schwaller, M. R., and K. R. Morris, 2011: A ground validation network for the Global Precipitation Measurement mission. J. Atmos. Oceanic Technol., 28, 301319, doi:10.1175/2010JTECHA1403.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sideris, I., M. Gabella, R. Erdin, and U. Germann, 2014: Real-time radar–rain-gauge merging using spatio-temporal co-kriging with external drift in the alpine terrain of Switzerland. Quart. J. Roy. Meteor. Soc., 140, 10971111, doi:10.1002/qj.2188.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Swiss Federal Office of Topography, 2005: DHM25: The digital height model of Switzerland. Federal Office of Topography, Wabern, Switzerland.

  • Tian, Y., and Coauthors., 2009: Component analysis of errors in satellite-based precipitation estimates. J. Geophys. Res., 114, D24101, doi:10.1029/2009JD011949.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Toyoshima, K., H. Masunaga, and F. A. Furuzawa, 2015: Early evaluation of Ku- and Ka-band sensitivities for the Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR). SOLA, 11, 1417, doi:10.2151/sola.2015-004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Viviroli, D., H. H. Dürr, B. Messerli, M. Meybeck, and R. Weingartner, 2007: Mountains of the world, water towers for humanity: Typology, mapping, and global significance. Water Resour. Res., 43, W07447, doi:10.1029/2006WR005653.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vollbracht, D., M. Sartori, and M. Gabella, 2014: Absolute dual-polarization radar calibration: Temperature dependence and stability with focus on antenna-mounted receivers and noise source–generated reference signal. 8th European Conf. on Radar in Meteorology and Hydrology, DWD-DLR, Garmisch-Partenkirchen, Germany, 111–122.

  • Wolfensberger, D., D. Scipion, and A. Berne, 2016: Detection and characterization of the melting layer based on polarimetric radar scans. Quart. J. Roy. Meteor. Soc., 142, 108124, doi:10.1002/qj.2672.

    • Crossref
    • Search Google Scholar
    • Export Citation
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A Comparison between the GPM Dual-Frequency Precipitation Radar and Ground-Based Radar Precipitation Rate Estimates in the Swiss Alps and Plateau

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  • 1 Environmental Remote Sensing Laboratory, School of Architecture, Civil and Environmental Engineering, École polytechnique fédérale de Lausanne, Lausanne, Switzerland
  • | 2 MeteoSwiss, Locarno-Monti, Switzerland
  • | 3 Environmental Remote Sensing Laboratory, School of Architecture, Civil and Environmental Engineering, École polytechnique fédérale de Lausanne, Lausanne, Switzerland
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Abstract

The Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar (DPR) provides a unique set of three-dimensional radar precipitation estimates across much of the globe. Both terrain and climatic conditions can have a strong influence on the reliability of these estimates. Switzerland provides an ideal testbed to evaluate the performance of the DPR in complex terrain: it consists of a mixture of very complex terrain (the Alps) and the far flatter Swiss Plateau. It is also well instrumented, covered with a dense gauge network as well as a network of four dual-polarization C-band weather radars, with the same instrument network used in both the Plateau and the Alps. Here an evaluation of the GPM DPR rainfall rate products against the MeteoSwiss radar rainfall rate product for the first two years of the GPM DPR’s operation is presented. Errors in both detection and estimation are considered, broken down by terrain complexity, season, precipitation phase, precipitation type, and precipitation rate. Errors are considered both integrated across the entire domain and spatially, and consistent underestimation of precipitation by GPM is found. This rises to −51% in complex terrain in the winter, primarily due to the predominance of DPR measurements wholly in the solid phase, where problems are caused by lower reflectivities. The smaller vertical extent of precipitation in winter is also likely a cause. Both detection and estimation performance are found to be significantly better in summer than in winter, in liquid than in solid precipitation, and in flatter terrain than in complex terrain.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Alexis Berne, alexis.berne@epfl.ch

Abstract

The Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar (DPR) provides a unique set of three-dimensional radar precipitation estimates across much of the globe. Both terrain and climatic conditions can have a strong influence on the reliability of these estimates. Switzerland provides an ideal testbed to evaluate the performance of the DPR in complex terrain: it consists of a mixture of very complex terrain (the Alps) and the far flatter Swiss Plateau. It is also well instrumented, covered with a dense gauge network as well as a network of four dual-polarization C-band weather radars, with the same instrument network used in both the Plateau and the Alps. Here an evaluation of the GPM DPR rainfall rate products against the MeteoSwiss radar rainfall rate product for the first two years of the GPM DPR’s operation is presented. Errors in both detection and estimation are considered, broken down by terrain complexity, season, precipitation phase, precipitation type, and precipitation rate. Errors are considered both integrated across the entire domain and spatially, and consistent underestimation of precipitation by GPM is found. This rises to −51% in complex terrain in the winter, primarily due to the predominance of DPR measurements wholly in the solid phase, where problems are caused by lower reflectivities. The smaller vertical extent of precipitation in winter is also likely a cause. Both detection and estimation performance are found to be significantly better in summer than in winter, in liquid than in solid precipitation, and in flatter terrain than in complex terrain.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Alexis Berne, alexis.berne@epfl.ch
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