De: Jennifer HaaseDate: 6 mai 2005 17:15:26 GMT+02:00 Please let me know if you know of any graduate students finishing up or recently finished that would be interested in a postdoctoral position at Purdue University working on the following research projects. The position would start as soon as possible. Research investigating atmospheric properties using GPS signals recorded from an airborne platform. GPS navigation signals that pass near horizontally through the atmosphere from satellites that are setting behind the Earth are significantly delayed due to the varying index of refractivity of the atmosphere, which in turn depends on the atmospheric state ^Ö pressure, temperature, and humidity. We are developing a new airborne system for atmospheric remote sensing based on this concept to fly on the HIAPER aircraft (High performance Instrumented Airborne Platform for Environmental Research). The research requires a broad range of interests beyond atmospheric science, in particular electromagnetic wave propagation and theory of optics. The candidate should have a strong quantitative/mathematical background in atmospheric science, physics, geophysics, mathematics, or engineering and prior experience in programming in C or Fortran. Candidate should have an intimate working knowledge of precision GPS analysis software such as GIPSY, GAMIT, or BERNESE. Research using the new high resolution MODIS sensor on the Terra and Aqua Earth Observation Satellites. The MODIS sensor is able to image precipitable water vapor with an unprecedented resolution of 1 kilometer. The research project involves preparation of the data for assimilation into weather prediction models for improving the forecasts of events such as hurricane Lili in 2002. Hurricane Lili grew in intensity category 2 to category 4 in 24 hours, then decreased in intensity even more rapidly, from category 4 to category 1 in 13 hours, a phenomena that is still currently unexplained. The candidate will compare MODIS data with GPS precipitable water vapor data and develop algorithms for evaluating data quality, and will learn to use the NCL language for manipulating satellite data. The candidate should have a strong interest in atmospheric remote sensing, a relatively quantitative mathematical background and prior experience in programming. Candidate should have xperience with software such as NCL and ESRI. Experience with NWP modeling, particularly WRF, is a particular advantage. Potential candidates should send a curriculum vitae (including citizenship and/or visa status), statement of research interests, and the name of 3 references to: Jennifer Haase 550 Stadium Mall Dr. West Lafayette, IN, 47907-2051 jhaase@purdue.edu Fax: +1-765-496-1210 Tel: +1 765-494-1643 (electronic email applications will be accepted)