[1] The cryogenic frost point hygrometer (CFH), currently built at the University of Colorado, is a new balloon borne hygrometer, which is capable of continuously measuring water vapor between the surface and the middle stratosphere. The design is loosely based on the old NOAA/CMDL frost point hygrometer, with improved accuracy and a number of significant new features that overcome some limitat...

ABSTRACT: NOAA images have been provided very useful environmental information from all over the world. In order to use NOAA images, they need to be transformed from image into map. This paper proposes a method that corrects the errors caused by this transformation. First, elevation errors are calculated and corrected based on elevation values, which are read from GTOPO30 database. These elevat...

The NOAA frost point hygrometer (FPH) is a balloon-borne instrument flown monthly at three sites to measure water vapor profiles up to 28 km. The FPH record from Boulder, Colorado, is the longest continuous stratospheric water vapor record. The instrument has an uncertainty in the stratosphere that is < 6 % and up to 12 % in the troposphere. A digital microcontroller version of the instrument i...

Glenn Research Center, Cleveland, Ohio Robert Anderson Glenn Research Center, Cleveland, Ohio Dulcinea Avouris Kent State University, Kent, Ohio Richard Becker University of Toledo, Toledo, Ohio James Churnside NOAA Earth System Research Lab, Boulder, Colorado Michael Cline University of Toledo, Toledo, Ohio James Demers Glenn Research Center, Cleveland, Ohio George Leshkevich NOAA Great Lakes ...

Two sources of H113 estimates were available at Platform Harvest; a NOAA buoy and CU depth sensor highrate data. H113 estimates from the NOAA buoy were based on twenty minutes of data every hour, CU pressure measurements were taken every 1.1 seconds. For purposes of this paper, H113 estimates from the (7U depth sensor were based on one hour of data, This paper compares H113 measurements from TO...

Glenn Research Center, Cleveland, Ohio Robert Anderson Glenn Research Center, Cleveland, Ohio Dulcinea Avouris Kent State University, Kent, Ohio Richard Becker University of Toledo, Toledo, Ohio James Churnside NOAA Earth System Research Lab, Boulder, Colorado Michael Cline University of Toledo, Toledo, Ohio James Demers Glenn Research Center, Cleveland, Ohio George Leshkevich NOAA Great Lakes ...

A neural network-based retrieval technique is developed to infer vapor, liquid. and ice columns using twoand threechannel microwave radiometers. Neural network-based inverse scattering methods are capable of merging various data streams in order to retrieve microphysical properties of clouds and precipitation. The method is calibrated using National Oceanic and Atmospheric Administration (NOAA)...

This study presents the results of a microwave-based algorithm which attempts to perform the retrieval of hydrometeor parameters in a profile form. The hydrometeors in question are both phases of the precipitating rain (liquid and frozen). The algorithm is called the Microwave Integrated Retrieval System (MiRS) which uses microwave radiances from AMSU and MHS sensors onboard NOAA-18, NOAA-19, M...

A surface-precipitation-rate retrieval algorithm for 13-channel Advanced Microwave Sounding Unit (AMSU) millimeter-wave spectral observations from 23 to 191 GHz is described. It was trained using cloudresolving fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) simulations over 106 global storms. The resulting retrievals from the U.S. N...

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