'Airs data' diaporamas de présentation

NASA Trace Gas Products for Air Quality Applications

NASA Trace Gas Products for Air Quality Applications. NASA Remote Sensing Training September 2014. ARSET A pplied R emote SE nsing T raining A project of NASA Applied Sciences.

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Status of the MOD07 atmospheric profile algorithm

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A Data Quality Screening Service for Remote Sensing Data

A Data Quality Screening Service for Remote Sensing Data. Christopher Lynnes, NASA/GSFC Edward Olsen, NASA/JPL Peter Fox, RPI Bruce Vollmer, NASA/GSFC Robert Wolfe, NASA/GSFC Shahin Samadi , NASA/GSFC.

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GIMPAP Annual Review

GIMPAP Annual Review. GSD Progress and Plans Dan Birkenheuer, Yuanfu Xi, Seth Gutman 11 August 2006. Main Goals. Better understand GOES-12 -10 and now GOES-11 error, improve data GSI Gradient assimilation, coordinate with JCSDA and GOES RRR No JCSDA funding this year. TAC Guidance.

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A Stategy for Predicting Climate Sensitivity Using Satellite Data Daniel B. Kirk-Davidoff

A Stategy for Predicting Climate Sensitivity Using Satellite Data Daniel B. Kirk-Davidoff University of Maryland Department of Meteorology dankd@atmos.umd.edu. Talk Structure Background on the Fluctuation Dissipation Theorem Experiments using a Toy Model Model Description Results

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Aqua Mission Review Atmospheric Infrared Sounder

Aqua Mission Review Atmospheric Infrared Sounder. Moustafa Chahine, AIRS Science Team Leader Hartmut G. Aumann, AIRS Project Scientist Bjorn Lambrigtsen, AMSU Instrument Scientist Steven Friedman, AIRS Project Manager (Acting) August 23, 2005 Jet Propulsion Laboratory

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The Use of AIRS Profiles in Short-term Weather Forecasts: A Case for Enhanced Quality Indicators

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McIDAS-Lite

McIDAS-Lite. Dave Santek Program Manager dave.santek@ssec.wisc.edu Space Science & Engineering Center University of Wisconsin-Madison 5 December 2002. Overview. Space Science & Engineering Center McIDAS McIDAS-Lite. SSEC: Data. National archive for GOES data

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McIDAS-Lite

McIDAS-Lite. Dave Santek Program Manager dave.santek@ssec.wisc.edu Space Science & Engineering Center University of Wisconsin-Madison 5 December 2002. Overview. Space Science & Engineering Center McIDAS McIDAS-Lite. SSEC: Data. National archive for GOES data

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Adaptive Use of AQUA Brightness Temperatures in Winter Storm Reconnaissance Case Studies

Adaptive Use of AQUA Brightness Temperatures in Winter Storm Reconnaissance Case Studies. Lacey Holland and Zoltan Toth Ackn.: Russ Treadon, Stephen Lord, Lars-Peter Riishojgaard. Motivation. Currently, computationally expensive to include all AIRS data in the GFS

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Evaluation of ATMS and CrIS data at ECMWF

Evaluation of ATMS and CrIS data at ECMWF. Niels Bormann, Tony McNally, Anne Fouilloux , William Bell, Mohamed Dahoui With help from Nigel Atkinson (Met Office), Steve Swadley (NRL) and others. Up-to-date monitoring statistics. Up-to-date monitoring statistics on the web:

293 views • 13 slides

Motivation

Identifying Modes of Temperature Variability Using AIRS Data Alexander Ruzmaikin, Hartmut H. Aumann and Yuk Yung Jet Propulsion Laboratory & California Institute of Technology. Motivation.

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Towards a Fundamental Global IR Radiance Decadal Data Record

Towards a Fundamental Global IR Radiance Decadal Data Record. Sponsor: Innovim Corp. PI M. Halem, PD. C.C. Wu Students: P. Nguyen, D. Chapman. Tracking Climate Changes from Satellite Radiances.

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1. FY08 GIMPAP Project Proposal Title Page

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Plans for Near-Real-Time AIRS L2 Profile Assimilation

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Numerical Weather Prediction Subcommittee Chairs: Ralph Petersen/Mark DeMaria

Numerical Weather Prediction Subcommittee Chairs: Ralph Petersen/Mark DeMaria. MEMBERS NESDIS/ORA : Bob Aune, Paul Menzel, Tim Schmit, Dan Tarpley NESDIS/OSD : Jim Gurka NOAA/FSL : Dan Birkenheuer, Steve Koch CIRA/CSU : Jim Purdom.

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Don Morton 1 , Kayla Harrison 1 , Brad Zavodsky 2 , Shih-Hung Chou 2 , Ming Hu 3

Assessment of data assimilation with the prototype High Resolution Rapid Refresh for Alaska (HRRRAK). Don Morton 1 , Kayla Harrison 1 , Brad Zavodsky 2 , Shih-Hung Chou 2 , Ming Hu 3 1 Arctic Region Supercomputing Center, University of Alaska Fairbanks, Fairbanks, Alaska USA

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Hurricane Intensity Estimation from GOES-R Hyperspectral Environmental Suite Eye Sounding

Lili 02 Oct 2002 07 UTC Lili 03 Oct 2002 08 UTC Isabel 13 Sep 2003 17 UTC. Isabel 14 Sep 2003 18 UTC Isabel 16 Sep 2003 18 UTC Isabel 17 Sep 2003 18 UTC. Figure 1. Enhanced GOES IR imagery of the 6 hurricane cases with AIRS/AMSU eye soundings.

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ABSTRACT

Preparing for GOES-R: old tools with new perspectives Bernadette Connell, CIRA CSU, Fort Collins, Colorado, USA connell@cira.colostate.edu. ABSTRACT

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