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  • Influence
Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity
Abstract This paper addresses and documents a number of issues related to the implementation of an advanced land surface–hydrology model in the Penn State–NCAR fifth-generation Mesoscale Model (MM5).Expand
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AIRS/AMSU/HSB precipitation estimates
  • F. Chen, D. Staelin
  • Mathematics, Computer Science
  • IEEE Trans. Geosci. Remote. Sens.
  • 29 April 2003
Precipitation rates (mm per hour) with 15- and 50-km horizontal resolution are among the initial products of Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit/Humidity Sounder for BrazilExpand
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Precipitation observations near 54 and 183 GHz using the NOAA-15 satellite
  • D. Staelin, F. Chen
  • Computer Science, Mathematics
  • IEEE Trans. Geosci. Remote. Sens.
  • 1 September 2000
Promising agreement over land and sea has been obtained between NEXRAD 3-GHz radar observations of precipitation rate and retrievals based on simultaneous passive observations at 50-191 GHz from theExpand
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NPOESS Aircraft Sounder Testbed-Microwave (NAST-M): instrument description and initial flight results
The National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Aircraft Sounder Testbed (NAST) has been developed and deployed on the NASA ER-2 high-altitude aircraft. The testbedExpand
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Behavioral Responses to Epidemics in an Online Experiment: Using Virtual Diseases to Study Human Behavior
We report the results of a study we conducted using a simple multiplayer online game that simulates the spread of an infectious disease through a population composed of the players. We use ourExpand
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Neural Network Characterization of Geophysical Processes With Circular Dependencies
  • F. Chen
  • Computer Science
  • IEEE Transactions on Geoscience and Remote…
  • 1 July 2006
This paper describes a method for training neural networks to learn circular dependencies. Variables with circular structure (e.g., time of day, day of year, and Earth location) appear in manyExpand
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An identification scheme combining first principle knowledge, neural networks, and the likelihood function
An identification scheme is described for modeling uncertain systems. The method combines a physics-based model with a nonlinear mapping for capturing unmodeled physics and a statistical estimationExpand
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Neural network retrieval of atmospheric temperature and moisture profiles from AIRS/AMSU data in the presence of clouds
A nonlinear stochastic method for the retrieval of atmospheric temperature and moisture profiles has been developed and evaluated with sounding data from the Atmospheric InfraRed Sounder (AIRS) andExpand
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Recent progress in neural network estimation of atmospheric profiles using microwave and hyperspectral infrared sounding data in the presence of clouds
Recent work has demonstrated the feasibility of neural network estimation techniques for atmospheric profiling in partially cloudy atmospheres using combined microwave (MW) and hyperspectral infraredExpand
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Archiving and distribution of 2-D geophysical data using image formats with lossless compression
  • F. Chen
  • Computer Science
  • IEEE Geoscience and Remote Sensing Letters
  • 17 January 2005
Certain types of two-dimensional (2-D) numerical remote sensing data can be losslessly and compactly compressed for archiving and distribution using standardized image formats. One common method forExpand
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