@InProceedings{BlacuttLiuZips:2006:RaEsAl,
               author = "Blacutt, Luis and Liu, Chuntao and Zipser, Edward",
          affiliation = "{Dept. of Meteorology} and University of Utah, USA and {(valid for 
                         all authors)}",
                title = "Rainfall estimates on the Altiplano using radar and passive 
                         microwave data from TRMM",
            booktitle = "Proceedings...",
                 year = "2006",
               editor = "Vera, Carolina and Nobre, Carlos",
                pages = "977--980",
         organization = "International Conference on Southern Hemisphere Meteorology and 
                         Oceanography, 8. (ICSHMO).",
            publisher = "American Meteorological Society (AMS)",
              address = "45 Beacon Hill Road, Boston, MA, USA",
             keywords = "Altiplano, precipitation, remote sensing, radar.",
             abstract = "Rainfall estimates on the Altiplano using radar and passive 
                         microwave data from TRMM Luis Blacutt, Chuntao Liu, and Edward 
                         Zipser Dept. of Meteorology University of Utah, USA Accurate 
                         rainfall estimates over the Altiplano, and other high altitude 
                         regions of the world, present a special set of challenges. Rain 
                         gauge data are usually very sparse. Therefore, the ability for 
                         direct validation of remote sensing algorithms is very 
                         problematic. Further, most existing algorithms are designed and 
                         tested for lower altitude locations. Even the TRMM (Tropical Rain 
                         Measuring Mission) radar has special difficulties at high 
                         altitudes, because the lowest levels free from surface clutter 
                         contamination are near or above the O°C level, and accurate 
                         interpretation depends upon knowing whether radar backscatter 
                         comes from liquid or ice hydrometeors, or if there is a radar 
                         bright band near the melting level. Yet the TRMM radar data offer 
                         the best chance of learning more about the vertical structure of 
                         precipitation systems over high altitude terrain. The purpose of 
                         this paper is to combine the most relevant physical 
                         interpretations from the TRMM precipitation radar (PR) and TRMM 
                         Microwave Imager (TMI) data to improve upon current precipitation 
                         estimates over the Altiplano. More than 7 years of TRMM data over 
                         the Altiplano are used to compare rainfall estimates from 5 
                         independent estimates of seasonal rainfall data. Unfortunately, 
                         these estimates differ widely, sometimes by more than a factor of 
                         2. We explore reasons for these discrepancies, and propose an 
                         improved method that may be better suited for the high altitude 
                         regions. The most promising method, especially for summer 
                         convective rains, appears to be a direct estimate of ice water 
                         path (IWP) using the 85 GHz channels of the TMI. In contrast to 
                         current TMI estimates, it is proposed to relate the estimated IWP 
                         to surface precipitation directly.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "24-28 Apr. 2006",
             language = "en",
         organisation = "American Meteorological Society (AMS)",
                  ibi = "cptec.inpe.br/adm_conf/2005/10.11.23.14",
                  url = "http://urlib.net/ibi/cptec.inpe.br/adm_conf/2005/10.11.23.14",
           targetfile = "977-980.pdf",
                 type = "Monsoon systems and continental rainfall",
        urlaccessdate = "04 maio 2024"
}